Next Generation of B2C Retail Payment Systems

Next Generation of B2C Retail Payment Systems

 

Before advent of Web and Mobile based applications, people use the following for making payments for retail expenses.

  • Cash
  • Cheques
  • Money Orders
  • Credit and Debit Cards
  • ACH Transactions

 

After 1st generation of online commerce, payments, and banking websites, mobile solutions are leap frogging  the web apps particularly in developing countries to help people at bottom of the wealth pyramid who may not have computers but have smartphones.

 

Ist Gen:  e-commerce, e-payments, e-banking

  • Online commerce sites such as Amazon, eBay
  • Online payments such as Paypal
  • Online Banking at various Banks websites such as Wells Fargo
  • Magnetic Card readers and EMV Chip card readers

 

There are these networks around the globe for small value retail payments.  UnionPay in China and RuPay in India are now directly competing with other well established providers such as MasterCard and Visa.  The main motive is financial inclusion of unbanked people.

Debit Cards /Credit Cards (Small Value Retail Payment Systems) Networks

  • Mastercard
  • Visa
  • American Express
  • Discover
  • RuPay (India)
  • Union Pay (China)

 

2nd Gen: m-commerce, m-payments, m-banking, m-pos, m-transfer

USA and Other Countries (Excluding China and India)

m-payment Apps

  • Google Wallet
  • Apple Passbook
  • Android Pay
  • Samsung Pay
  • Apple Pay
  • Chase Pay
  • Citi Pay
  • Microsoft Wallet
  • Lemon Wallet
  • Square Wallet
  • Isis
  • Chirpify
  • Geode
  • Paypal Venmo

 

There are several solutions worth mentioning which do not yet fit in any broad categories.

Other solutions

  • Adyen (Amsterdam)
  • Tipalti
  • Razorpay (India/USA)
  • Boku
  • Poynt (USA)
  • Klarna (Stockholm)
  • Gocardless (London)

 

Chat/SMS based payment solutions are very popular in China and now being integrated in applications such as Facebook.

Chat based Payments

  • Tencent Wechat (China)
  • Facebook
  • Snapchat
  • Vodaphone M-PESA (SMS based)

 

There are newer Proximity based payments solutions using two technologies – BLE and NFC.  There are now several solutions based on each of these technologies.

Proximity Payments (No Contact)

A.  Payment solutions powered by iBeacon technology (Bluetooth Low Energy)

  • Powatag
  • Paij
  • PassMarket
  • TruBeacon
  • Labwerk

B.  NFC powered Payment Solutions

  • Apple Pay
  • Android Pay
  • Google Wallet
  • Moneto
  • Mastercard Paypass
  • Visa Pay Wave
  • ISIS
  • Quick Tap (UK)
  • Girogo (Germany)
  • Sure Tap (Canada)
  • Touch2Pay (New zealand)
  • CardMobile (Austria)
  • PayBox (Austria)
  • T-Money (South Korea)
  • Suica (Japan)
  • PASMO (Japan)
  • MTS (Russia)
  • Cep-T Cuzdan (Turkey)

 

m-POS apps using scanning hardware for reading of credit/debit cards of customers at businesses is a popular service provided.  Square leads the pack.

Mobile Card Readers (m-POS)

  • Square
  • Cartwheel Register
  • EMS+
  • Spark Pay
  • Flagship ROAMpay
  • Elavon
  • Creditcardprocessing.com
  • Moolah
  • Flint
  • Paypal Here
  • Chase Paymenttech
  • Yowza Merchant
  • Cayan
  • PayAnywhere
  • CDGCommerce
  • Quickbooks Gopayment

 

There are now several companies which offer money transfer service to accounts across the globe.

Overseas Money Transfer

  • Transferwise
  • Western Union
  • World Remit
  • Paypal Xoom
  • MoneyGram
  • Square Cash
  • Azimo Money Transfer

 

 

India

Mobile Payment applications have mushroomed in India.  India is on leading edge in providing real time mobile payment system available 24/7.  Some of the services providers have been given licensed to start Payment Banks dedicated to payment operations as opposed to Deposit Banks.

Mobile Payments

  • Paytm
  • PhonePe
  • Snapdeal Freecharge
  • MobiKwik
  • AirTel Money
  • BHIM
  • Oxigen
  • ICICI Easypay
  • Flipkart Money
  • DBS Rupizo
  • Micromax Udio
  • Payzapp
  • Citrus
  • ICICI Pockets
  • Bookmyshow
  • Ola Money
  • DBS Wallet
  • Jio money
  • Amazon Emvantage
  • PayUMoney
  • Vodaphone M Pesa
  • ItzCash
  • Trupay

 

There are many applications introduced by Banks who provide access to users accounts on a smartphone.  Some of them are listed below.

Mobile Banking

  • ICICI Bank imobile
  • State Bank of India Anywhere
  • HDFC Bank
  • Bank of Baroda mPassbook
  • PNB mBanking
  • Indian Bank Indpay
  • Kotak Mahindra Bank
  • Yes Bank
  • Axis Bank

 

In 2016, ICICI Bank introduced first NFC based mobile app in India.

NFC based m-payment solutions

  • ICICI Bank Pockets

 

 

There are several retailers who have introduced Mobile apps for payments.  Some of them are listed below.

 

Specialized Retail Payment Apps

  • Zomato (India)
  • Starbucks (USA)
  • Walmart Pay (USA)
  • Dunkin Donuts (USA)
  • Taco Bell (USA)
  • CVS Pay (USA)
  • Kohl Pay (USA)
  • Amazon Payment (USA)

 

Here is a list of Online Payment Solutions.

On-line Payment Solutions

  • 2CheckOut
  • Stripe
  • ACH Payments
  • WePay
  • Authorize.Net
  • Dwolla
  • Paypal

 

 

China

China has large population of smartphone users who do use m-payment apps such as Alipay regularly.  Many others are trying to get a foothold in this market with partnerships with Chinese UnionPay.

m-payment

  •  China UnionPay (CUP) Cloud Quick Pass
  • Alibaba Alipay
  • Tencent Wechat
  • Tencent TenPay
  • China Mobile
  • China Unicom
  • 99Bill
  • YeePay
  • Paypal
  • Lakala
  • LianlianPay
  • Ping An Pay
  • PayEase

 

NFC based m-payment

  • Apple Pay (CUP)
  • Samsung Pay (CUP)
  • Huawei
  • Xiaomi (CUP)
  • LG

 

 

Key Sources of Research:

 

Top 10 Trends in Payments in 2016

Capgemini

 

Click to access payments_trends_2016.pdf

 

 

Cashless Payment System in India- A Roadmap

Ashish Das, and Rakhi Agarwal

2010

 

Click to access PaymentCardAugust31.pdf

 

 

Fast Retail Payment Systems

Stephanie Bolt, David Emery and Paul Harrigan

2014

 

Click to access bu-1214-6.pdf

 

 

Report of the Key Advisory Group on the Payment Systems in India (KAG on PSI)

31st May, 2012

 

Click to access Report%20of%20KAG%20on%20PSI.pdf

 

 

NEFT, RTGS, UPI: What should you use to transfer money?

http://www.4-traders.com/DCB-BANK-LTD-9059622/news/NEFT-RTGS-UPI-What-should-you-use-to-transfer-money-23784479/

 

 

Meet the top 20 hottest payment companies

http://www.raconteur.net/technology/meet-the-hottest-payment-companies

 

Relational Turn in Economic Geography

Relational Turn in Economic Geography

This is an important topic.  Uneven development using orthodox economic and development theories has led researcher to look for alternative explanations.

  • How to properly integrate Global – Regional – National – Local perspectives?
  • How valuable is relational (network) perspective?
  • What is the role of power relations among Actors?
  • How does Institutional, Cultural, and Social embeddedness of Actors impact development and economy?
  • How does actions and interactions of Actors affect local economic environment?

 

From Toward a relational economic geography

During the 1990s, a controversial debate has emerged in economic geography and other social sciences, such as economics and sociology, focusing on the question of what research program, key focus and methodology a novel economic geography should embody (Perrons, 2001). This was, partially, a reaction to the work of Krugman (1991), Fujita et al. (2001), and others who claimed to have developed a new economic geography. This self-proclaimed new economic geography offers an interesting economic perspective on the conventional problems of spatial distribution and equilibrium, based on an analysis of increasing returns, transportation costs, and other traded interdependencies (Martin and Sunley, 1996; Bathelt, 2001). Yet it fails to develop a comprehensive research program as a basis for economic geography because ‘. . . the new economic geography ignores almost as much of the reality they study as old trade theory did’ (Krugman, 2000, p. 50).1 In following Martin and Sunley’s (1996) suggestion, this approach is better classified as geographical economics. While this literature brings economic geography closer to the core ideas of neoclassical economics, Amin and Thrift (2000) have recently suggested another fundamentally different direction for economic geography, capitalizing on concepts and theories from other social sciences. Amin and Thrift (2000, p. 4) provocatively claim that economic geography is no longer able to ‘fire the imagination’ of researchers. Therefore, they ask for a critical reflection and renewal of this field’s basic goals, concepts, and methods. The reactions to their contribution have stimulated a debate, parts of which have been published in a special issue of Antipode in 2001. This debate has unfortunately been dominated by discipline-political arguments, opinions, and claims. In essence, it focuses on the question of whether economic geography should be closely associated with economics or lean towards the social, political, and cultural sciences. In particular, Thrift (2000) has identified a growing interest in the cultural dimension of economic relations, as well as in economic issues of cultural studies. While Amin and Thrift (2000) propose a cultural turn away from neoclassical economics, their critics emphasize existing linkages with and the importance of economic theories as a foundation of economic geography (Martin and Sunley, 2001; Rodriguez- Pose, 2001). We agree with Martin and Sunley (2001) that this debate is partly based on false dualisms, such as economics vs. sociology and quantitative vs. qualitative methodology. In our view, this discussion is unclear because it mixes normative accounts of the discipline’s policy implications with epistemological and methodological arguments. The debate is also somewhat misdirected for it tries to separate those economic and social aspects that are inseparable. The decisive question cannot be whether economic geography should be economized or culturalized. Rather, the economic and the social are fundamentally intertwined. They are dimensions of the same empirical reality which should be studied in a dialogue of perspectives rather than in mutual exclusion and reductionist prioritization (Stark, 2000).

The second transition is characterized by a reformulation of the core concepts of economic geography. In the following sections, discontinuities between relational economic geography and regional science will be identified according to five dimensions of the research design. These dimensions include the conception of space, object of knowledge, conception of action, epistemological perspective, and research goal. From this, we develop a relational framework for analysis which systematically focuses on economic actors and their action and interaction. The basic propositions of this framework will be developed in the remainder of this section (Table 1).

4.1. Conception of space

A relational view of economic geography is based on a relationship between space and economy which is contrary to that of regional science.10 Specifically, regional science views space as a container which confines and determines economic action. It treats space as a separate entity which can be described and theorized independently from economic action. In contrast, a relational approach assumes that economic action transforms the localized material and institutional conditions of future economic action. Similar to Storper and Walker (1989), this approach emphasizes that the economic actors themselves produce their own regional environments. The way in which spatial categories and regional artifacts have an impact on economic action can only be understood if the particular economic and social context of that action is analysed (Bahrenberg, 1987). Spatial structures and processes have, however, been socially and economically underconceptualized in regional science. We contend that space can neither be used as an explanatory factor for economic action nor be treated as a separate research object in isolation from economic and social structures and relations. Consequently, as space is not an object of causal power to explain social or economic action it cannot be theorized (Sayer, 1985; Saunders, 1989; Hard, 1993).11 Of course, economic processes also have material outcomes (e.g. infrastructure) which are localized in certain places and territories and exist over longer time periods. Such structures clearly have an impact on economic action and interaction in these localities. Nonetheless, economic actors and their action and interaction should be at the core of a theoretical framework of economic geography and not space and spatial categories. Spatial scientists, such as Bunge (1973), treat spatiality as the object of knowledge in economic geography. They aim to detect those spatial laws which govern human action without looking at the actors themselves. Instead of treating space as a container, we suggest a conception of space as perspective (Glu¨ ckler, 1999). In other words, we use space as a basis for asking particular questions about economic phenomena but space is not our primary object of knowledge. It is this conception that we refer to as the geographical lens. As part of this, economic exchange becomes the focus of analysis and not space. Similarly, we do not seek to identify spatial laws but, instead, look for explanations of localized economic processes and their consequences.12 It is particularly through the application of a distinct perspective to the study of an object of knowledge that discipline-specific research problems can be formulated. The spatial perspective or geographical lens leads economic geographers to pose research questions about an economic phenomenon, different from those typically asked by economists or sociologists. We also suggest that the perspective applied helps mobilize a particular terminology and, over time, a set of tacit knowledge which entails an understanding of what it is that is being analysed and how this subject matter can be described and evaluated adequately.

relational2

 

From Rethinking relational economic geography

Since the mid-1990s, the softening of sub-disciplinary boundaries within human geography and the more general call for a ‘relational thinking’ in human geography (Massey et al . 1999; see also Allen et al. 1997; Sack 1997; Lee and Wills 1997) have stimulated the consolidation of what might be termed a ‘relational economic geography’. 1 In this ‘relational turn’, economic geographers tend to place their analytical focus on the complex nexus of relations among actors and structures that effect dynamic changes in the spatial organization of economic activities (see Amin 1998; Dicken and Malmberg 2001; Ettlinger 2001; Bathelt and Glückler 2003; Boggs and Rantisi 2003). This relational economic geography is concerned primarily with the ways in which socio-spatial relations of actors are intertwined with broader structures and processes of economic change at various geographical scales. Despite the claims of novelty among most economic geographers who have taken on such a relational thinking in their geographical analysis, it remains unclear whether this ‘relational turn’ represents merely a modest reworking of earlier work in economic geography that might not be explicitly relational in its conceptualization and analysis. After all, heated debates on the spatial divisions of labour, locality studies and flexible specialization dominated the heyday of economic geography during much of the 1980s and the early 1990s (Scott 2000). With hindsight, these debates have legitimized the analytical concern of economic geography with the social relations of production and the relations between the spatial and the social (Harvey 1982; Thrift 1983; Massey 1984; Smith 1984; Gregory and Urry 1985; Lee 1989). By sidestepping the pitfalls of an earlier brand of quantitative economic geography concerned with spatial geometries and locational analysis, the substantive foci on regions, localities and production processes in these debates have no doubt foregrounded the recent ‘relational turn’ in economic geography. While many recent geographic writings have addressed aspects tangential to the core theoretical categories deployed in a relational economic geography (e.g. Barnett 1998; Thrift 2000; Barnes 2001; Storper 2001), there is surprisingly a lack of systematic evaluation and integration of our knowledge of this growing field. In view of limited space, this paper develops a sympathetic critique and rethinking of the ‘relational turn’ in order to clarify the distinctive contributions of a relational economic geography and to rework some of its conceptual tools. In the next section, I critically examine the nature and emergence of the ‘relational turn’ in economic geography, by revisiting relational thought that existed as an undercurrent before the 1990s and situating the recent ‘relational turn’ in this earlier work in economic geography. Whilst the recent ‘relational turn’ has some of its intellectual antecedents in the earlier debates of the 1980s (particularly the social relations of production framework), its substantive content has been broadened to include social actors and their network relations at different spatial scales. Focusing on recent economicgeographical writings on regional development, embedded networks and geographical scales, I note that much of this large body of recent work is relational only in the thematic sense that relations among actors and structures are an important theme in contemporary economic-geographical enquiry. In particular, the causal nature of relationality and power relations are under-theorized and underspecified. If relational thinking in economic geography is to have a greater impact, we need to rework and deepen its theoretical constructs to go beyond simply a ‘thematic turn’ (Jessop 2001, 1214). The paper moves on to rework some of the most important theoretical insights in the ‘relational turn’ – relationality, power and actors. Dynamic and heterogeneous relations among actors and structures are conceptualized as causal mechanisms of socio-spatial change in economic landscapes. Here, I explore the notion of ‘relational geometries’ constituted through relationality and power . The concept of relational geometries refers to the spatial configurations of heterogeneous relations among actors and structures through which power and identities are played out and become efficacious. These relational geometries are neither actors (e.g. individuals and firms) nor structures (e.g. class, patriarchy and the state), but configurations of relations between and among them – connecting actors and structures through horizontal and vertical power relations. Relational geometries are also not networks per se because the latter refer mainly to horizontal and, mostly, static ties among actors only. Actors in these relational geometries are not static ‘things’ fixed in time and space. They are dynamic and evolving in such relational ways that their differential practices unleash multiple forms of emergent power in relational geometries. Building on the concept of different and emergent forms of causal power as positions in relational geometries and as practice through social action, this relational perspective allows us to avoid the two polarized frameworks in contemporary economic geography – actor networks and institutional structures. This effort to rework relational economic geography thus parallels the recently reinvigorated ‘relational sociology’ that ‘sees relations between terms or units as preeminently dynamic in nature, as unfolding, ongoing processes rather than as static ties among inert substances’ (Emirbayer 1997, 289). To substantiate the relevance of this reworking of conceptual categories, I show how relationality and multiple forms of power can offer vital insights into regional development that go beyond existing relational frameworks in economic geography.

related4relationality5

 

From Geographies of circulation and exchange: Constructions of markets

In the preceding sections we have discussed three heterodox alternatives to the orthodox free market logic.

For socioeconomists, markets are embedded in social structures and are a far cry from the virtual market model celebrated by orthodox economists. It is social relations that underwrite real markets, guaranteeing their functioning in the face of uncertainties. Work un- dertaken in this spirit puts emphasis on social relations and institutions, and analyses how non-economic institutions either enable or constrain efficient market exchange.

Political economists insist that, neoliberal claims to the contrary notwithstanding, capitalism cannot exist without “market imperfections”. In these accounts, the market model is nothing else than a fictitious ideological device to hide from view the underlying dynamics of capitalism. Accordingly, political economic scholars regard it as their task to remove the veil and to lay open the contradictory reality of concrete markets under capitalism.

Cultural economists apply the cultural theoretical concept of performativity towards the market. Rather than reproducing the classical distinction between the abstract market model and real-life markets, protagonists point to the role that the practice of economists widely understood plays in the self-realization of economic thought. It is argued that the model of the perfect market realizes itself in the world in the assembly of far-reaching socio-technical arrangements. Here, markets take on ambivalent form as relational effects of socio-technical networks engaging in the twin processes of framing and overflowing. The latter process includes the proliferation of new social relations, groups and communities which may articulate economic and non-economic alternatives.

In the discipline of economic geography heterodox approaches have managed to break the hegemony of the neoclassical orthodoxy. Unfortunately, the arguments in heterodox debates on the market and on alternative economic geographies more generally are very often taken from entrenched positions, authors apparently finding it very difficult to understand the train of thought followed by the “opposing” camp. While this is true for all positions introduced in this progress report, cultural economy has arguably had a particularly difficult time. With our representation of the performativity approach we hope to have been able to clarify some of the misunderstandings. The strength of the heterodox project lies precisely in the co-existence of competing positions, each challenging the still omnipresent logic of the perfect market in different ways. This is what a vibrant heterodox project should aspire to: A healthy competition of plurivalent and opposing ideas, a competition, however, which at the same time does not prevent conversation across different approaches and is pluralistic enough to gain from the application of different perspectives (see Barnes 2006).

 

 

From  Advancing evolutionary economic geography by engaged pluralism

relational

 

Please see my related post on Relational Sociology.

Boundaries and Relational Sociology

 

 

Key People:

  • Harrison White
  • Henry Wai-chung Yeung
  • H. Bathelt
  • J. Gluckler
  • Jeffrey S. Boggs
  • Norma M. Rantisi
  • Christian Berndt
  • Marc Boeckler
  • Robert Hassink
  • Claudia Klaerding

 

Related Schools of Thoughts:

  • Social Economics
  • Political Economy
  • Cultural Economy
  • Manchester School of Global Production Networks
  • German School of Relational approach

 

Key Terms:

  • Relational Geometries
  • Actor-Networks
  • Relationality
  • Actor-Structure
  • Global – Regional – National – Local
  • Social Embeddedness
  • Economic-Social-Political-Spatial
  • Cultural Economics
  • Critical Realism
  • Causal Relations
  • Boundaries
  • Institutional Economics
  • Political Economics
  • Spatial relations
  • Scale Structure
  • Regionalism
  • Power Relations

 

 

Key Sources of Research:

 

Geographies of circulation and exchange: Constructions of markets

Christian Berndt

Marc Boeckler

 

Click to access 3-BerndtBoeckler2009.pdf

 

 

Whither Global Production Networks in Economic Geography? Past, Present and Future

Martin Hess

Henry Wai-chung Yeung

 

Click to access 2006%20EPA_Hess_Yeung.pdf

 

 

Rethinking relational economic geography

Henry Wai-chung Yeung

2005

 

Click to access 2005_TIBG.pdf

 

 

Towards a Relational Economic Geography: Old Wine in New Bottles?

 

 

Toward a relational economic geography

Harald Bathelt and Johannes Glueckler

 

Journal of Economic Geography 3 (2003) pp. 117–144

Click to access 0c96052832bce3e2bf000000.pdf

 

 

Relational and evolutionary economic geography: competing or complementary paradigms?

Robert Hassink and Claudia Klaerding

2009

 

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.493.3838&rep=rep1&type=pdf

 

 

Towards an integrated Evolutionary and Relational Economic Geography approach

for analysing the evolution of destinations

 

Cinta Sanz‐Ibáñez,

Salvador Anton‐Clavé

 

Click to access SanzIbanez_AntonClave2014.pdf

Click to access 557194bb08ae7467f72ca317.pdf

 

 

Chains and networks, territories and scales: towards a relational framework for analysing the global economy

PETER DICKEN, PHILIP F. KELLY, KRIS OLDS and HENRY WAI-CHUNG YEUNG

 

Click to access DKOY_2001.pdf

 

 

What Really Goes on in Silicon Valley? Spatial Clustering and Dispersal in Modular Production Networks

Timothy J. Sturgeon

2003

 

Click to access 03-001.pdf

 

 

Theoretical advancement in economic geography by engaged pluralism

Robert Hassink, Claudia Klaerding

 

https://www.wigeo.uni-kiel.de/en/archiv/12peeg

 

 

EMBEDDEDNESS, ACTOR-NETWORKS AND THE ‘RELATIONAL TURN’ IN GEOGRAPHY

 

http://scholarbank.nus.edu.sg/bitstream/handle/10635/14512/chapter_3.PDF?sequence=5

 

 

The ‘relational turn’ in economic geography

Jeffrey S. Boggs  and Norma M. Rantisi

Click to access The-Relational-Turn-in-Economic-Geography.pdf

 

 

Manifesto for a Relational Sociology

Mustafa Emirbayer

 

Click to access Emirbayer%20Manifesto%20for%20a%20Relational%20Sociology.pdf

 

 

Relational Economic Geography: A Partial Understanding
or a New Paradigm?

Peter Sunley

 

Click to access 552fb80c0cf2f2a588a8f6c7.pdf

 

 

The Relational Economy : Geographies of Knowing and Learning

Harald Bathelt and Johannes Gluckler

2011

Oxford

 

 

Can we learn anything from economic geography proper?

Yes, we can!

Robert Hassink, Huiwen Gong, Fabian Faller

Click to access peeg1622.pdf

 

 

GEOGRAPHIES OF FINANCE: CENTERS, FLOWS, AND RELATIONS

BONGMAN SEO

Accepted March 2011

 

 

Geographies of Production I:
Relationality revisited and the ‘practice shift’ in economic geography

 

Andrew Jones

2013

Click to access SR%20PiHG%20Geographies%20of%20Production%20Report%201%2024%20Jul13%20FINAL.pdf

 

 

Advancing evolutionary economic geography by engaged pluralism

 

Robert Hassink, Claudia Klaerding, Pedro Marque

2014

Click to access 54200ea90cf241a65a1afcd4.pdf

 

 

Geographies of Production: Growth Regimes in Spatial Perspective 3 – Toward a Relational View of Economic Action and Policy

Harald Bathelt

2006

Click to access 43_Bathelt%202006_PIHG.pdf

 

Economics of Trade Finance

Economics of Trade Finance

 

Matrix of trade finance instruments

  • Raising working capital for exports: Debt financing; Asset-based financing; Export factoring; and Leasing
  • Facilitating payments: Cash-in-advance; Letter of Credit(L/C); Documentary collection; and Open accounts
  • Mitigating risks: Export credit guarantee; Export credit insurance; Forfeiting; and Hedging.

 

Trade Finance is the lubricant in Global Trade.  The concentration of banks providing Trade Finance is very high.  So are the risks if a bank fails or withdraws credit due to regulations.

Questions:

  • How many Banks provide Trade Finance?
  • What happens when Banks withdraw credit due to Financial Crisis?
  • What other alternatives are there for Trade Finance ?  GTLP?
  • What is the role of increased regulations on Trade Finance? BASEL III

 

From Trade finance around the world

tradefin2tradefin3

 

Decline in Trade Finance as a cause of Global Trade Collapse

  • Concentration of Banks providing Trade Finance
  • De-risking by EU Banks to EMEs due to BASEL III requirement
  • Backlash against Trade

 

From DE-RISKING BY BANKS IN EMERGING MARKETS – EFFECTS AND RESPONSES FOR TRADE / IFC EMCOMPASS

Emerging evidence suggests that de-risking is a reality. Increased capital requirements, coupled with rising Know-Your-Customer, Anti-Money-Laundering, and Combating-the-Financing-of-Terrorism compliance costs have resulted in the exit of several global banks from cross-border relationships with many emerging market clients and markets, particularly in the correspondent banking business. A subset of this business, trade finance, is also at risk, with potential consequences for segments of emerging market trade. The emerging market trade finance gap was significant before the crisis and has since likely expanded. Those involved in addressing the de-risking challenge must focus on compliance consistency and effective adaptation of technological innovations.

 

From ADB 2016 Trade Finance Gaps, Growth, and Jobs Survey

  • The estimated global trade finance gap is $1.6 trillion.
  • $692 billion of the gap is in developing Asia (including India and the People’s Republic of China).
  • 56% of SME trade finance proposals are rejected, while large corporates face rejection rates of 34% and multinational corporations are rejected only 10% of the time.
  • Firms report that 25% more trade finance would enable them to hire 20% more people.
  • Woman-owned firms face higher than average rejection rates.
  • 70% of surveyed firms are unfamiliar with digital finance, uptake rates highest in peer-to-peer lending.

 

From ADDRESSING THE GLOBAL SHORTAGE OF TRADE FINANCE

The International Chamber of Commerce (ICC) 2016 Global Survey on Trade Finance reveals that 61 percent of respondents cited a global shortage of trade finance—a figure that is particularly concerning as we continue to observe a period of prolonged sluggishness when it comes to global trade growth. But hope is not lost. Doina Buruiana, Project Manager at ICC Banking Commission, explains the various ways that the trade-finance gap can be filled.

For the fifth consecutive year, trade growth has been reported at below 3 percent and has not recovered to pre-crisis levels—with a global trade-finance shortage estimated to have reached US$1.6 trillion in 2016, according to the Asian Development Bank (ADB). Such figures certainly make for grim reading. And what’s more, the findings from the International Chamber of Commerce’s (ICC) 2016 Global Survey on Trade Finance—an annual report reflecting the issues and trends on the trade-finance landscape—are also providing cause for concern. Sixty-one percent of respondents—national, regional and global banks providing trade finance—reported a global shortage of trade finance.

There are various reasons for this. Ninety percent cited the cost or complexity of compliance requirements relating to anti-money laundering (AML), know your customer (KYC) and sanctions as a chief barrier to the provision of trade finance. Furthermore, 77 percent of respondents to the Global Survey cited Basel III regulatory requirements as a significant impediment to trade finance. Many global banks are withdrawing from several emerging-market regions dependent on trade and trade finance, partly due to pressures to favour domestic clients following some banks’ bailouts by taxpayers.

And the fallout can be severe. A shortage of trade finance impacts the growth of businesses worldwide. In particular, small to medium-sized enterprises (SMEs) are being affected by the shortage of bank liquidity. According to the Global Survey, 58 percent of rejected trade-finance proposals were SME applications, despite the sector submitting 44 percent of all trade-finance proposals.

Yet hope is not lost. There are various ways in which the industry can adapt to not only bridge the gap in unmet demand for finance and help revive global growth, but also to evolve the industry, to drive healthy competition and to remove the focus from being global-bank dependent.

Backlash against trade

Improving understanding and attitudes toward trade, and awareness around trade finance, would be a good place to start. Across the world, many have attacked trade and globalisation for threatening jobs and benefitting only big businesses—sentiments that have been evident across the European Union (EU) during Transatlantic Trade and Investment Partnership (TTIP) negotiations, and also during the recent US presidential election campaigns.

Indeed, we’ve seen a clear rise in protectionist and populist policies—a recent World Trade Organization (WTO) report cited that between mid-October 2015 and mid-May 2016, G20 economies had introduced new protectionist trade measures at the fastest pace since 2008. To address this, we need to first make the case for trade itself in order to highlight the importance of trade finance. It is therefore crucial that businesses and trade-finance industry stakeholders reinvigorate the narrative around global trade, relaying its significance to the public and ensuring that trade is on the agenda of policymakers worldwide.

Understanding trade finance.

Next, enhancing awareness around trade finance should also remain a top priority. While there has already been significant progress in the dialogue between trade-finance practitioners and regulators, and a noticeable shift towards a more suitable risk-aligned treatment of trade finance, it is crucial that we continue to emphasise the low risk nature of trade-finance instruments.

Indeed, ICC’s 2015 Trade Register report highlights the low risk nature of trade-finance products—with favourable credit and default-risk experience. For instance, the Trade Register shows that there is a low default rate across all short-term trade-finance products, with the average expected loss for short-term trade finance lower than typical corporate exposures. In particular, traditional documentary trade-finance products such as letters of credit (LC) are low risk. Remarkably, the transaction default rate for export LCs between 2008 and 2014 was 0.01 percent. Medium- to long-term products also fare well, with a low loss nature due to the export credit agency’s (ECA) guarantee—normally with investment-grade ratings and backed by high-income Organisation for Economic Co-operation and Development (OECD) governments.

The need for increased awareness around trade finance extends well beyond traditional trade finance and also includes newer techniques and instruments under the supply-chain finance umbrella. We also need to raise industry understanding around compliance measures—differentiating between client KYC and non-client KYC, for instance, in order to ease processes. In addition, enhanced awareness and understanding in relatively unsettled areas in trade finance, such as trade-based money laundering, would help direct compliance measures. Despite common belief, for instance, only a small proportion of trade-based money laundering actually occurs in trade-finance transactions.

Collaboration

Yet while progress has certainly been made with regulation and compliance proposals, the Global Survey suggests that the costs associated with such measures are still, and will perhaps continue to be, prohibitive. As such, if we want to close the trade-finance gap, we need to move slightly away from a global bank-dominated financial landscape and embrace collaboration.

Financial-technology firms (fintechs) are increasingly shaping the future of trade finance, and make an obvious banking partner, with both parties bringing strengths and expertise to such arrangements. Indeed, many fintechs are looking to partner with—rather than compete with—banks due to balance-sheet requirements, the regulatory framework to navigate, and the industry expertise required to bring new concepts to fruition. Certainly, partnerships between the two players could drive additional efficiencies and the capacity of banks to conduct business—perhaps eventually reducing the trade-finance shortage.

Fintechs aren’t the only players that could potentially collaborate with banks—or even fill the trade-finance gap independently. The Global Survey found that export credit agencies (ECAs) are increasingly supporting export finance, with alternative liquidity flowing into the ECA space. Thirty-seven percent of respondents reported that they had successfully concluded business with institutional investors in ECA finance, up from 30 percent in the previous survey in 2015, reflective of the growing role of alternative investors.

The Global Survey also highlighted the important role of multilateral development banks (MDBs), with 75 percent of respondents agreeing that MDBs (and ECAs) help reduce trade-finance gaps. In particular, MDBs provide financial assistance to emerging markets for investment projects and policy-based loans. This can prove crucial for enabling access to trade finance in general, and for SMEs.

The ADB’s Trade Finance Program (TFP), for instance, fills market gaps for trade finance by providing guarantees and loans through more than 200 banks. The TFP has supported more than 12,000 transactions across Asia, valued at over US$23.1 billion—of which more than 7,700 involved SMEs. What’s more, the TFP focuses on markets in which the private sector has less capacity to provide trade finance, and where there are large trade-finance gaps.

However, the Global Survey also indicated that MDB and ECA support varies by region—with respondents deeming it most effective in advanced Asia, Russia and sub-Saharan Africa, and less effective in Commonwealth of Independent States (CIS) countries, India and Central America and the Caribbean. Clearly, an increase in the envelope and effectiveness of MDB trade-finance provision in these regions will help further reduce the gap. In order to counter geographical disparities, the next step for MDBs is to consider any structural limitations in existing trade-finance programmes—or contextual difficulties in particular markets.

Finally, non-bank capital provides another useful source of trade finance, particularly from private-sector sources of finance—such as specialist financiers or alternative-finance providers. Since the financial crisis, these players have played an increasingly crucial role in meeting unmet demand, and have experienced considerable growth. What’s more, specialist financing is growing increasingly popular among companies in emerging markets, in which trade-finance demand is most acute.

Revamping trade finance.

Of course, one way to possibly boost the provision of trade finance is to make it more efficient and attractive. Certainly, the digitisation of trade finance holds huge potential. Automating trade finance can make overall processes more effective and reliable, increasing capacity for banks, corporates and other stakeholders along the supply chain. For instance, eDocs (paperless documents) streamline processes, with the ability for multiple parties to access, review and collaborate at any one time. The resulting operational improvements in turn reduce errors, maintain data integrity and accelerate the completion of agreements.

Despite the clear benefits, the Global Survey shows that there has been a slow uptake of digitisation. In fact, one-fifth of respondents reported that there is no evident digitisation at all, two-thirds saw very little impact of technology on trade finance, and just over 7 percent saw digitisation as being widespread. The slow uptake is likely due to the challenges of digitising trade—including the considerable scale and complexity of the task at hand, for instance. Banks should play a key role in advocating the benefits of digitisation and help their corporate clients adapt to new systems.

We cannot let the trade-finance gap incapacitate trade. Clearly, there are steps that the trade-finance industry can take to help meet unmet demand. Looking ahead, improving attitudes and raising understanding, encouraging collaboration and making progress towards innovation in the industry will support the growth of businesses of all sizes—and the economy—worldwide.

 

From Global Trade Liquidity Program /IFC

The Global Trade Liquidity Program (GTLP) is a unique, coordinated global initiative that brings together governments, development finance institutions (DFIs), and private sector banks to support trade in developing markets and address the shortage of trade finance resulting from the global financial crisis.

With targeted commitments of $4 billion from public sector sources, the program has supported nearly $20 billion of trade since its inception. It raises funds from international finance and development institutions, governments, and banks, and it works through global and regional banks to extend trade finance to importers and exporters in developing countries. IFC’s commitment to the program is $1 billion.

GTLP began its operations in May 2009, channeling much-needed funds to back trade in developing countries. Phase 2 was launched in January 2010 with an unfunded solution, based on the existing GTLP platform, to support trade finance directed at the food and agribusiness sectors. The program was extended in January 2012 to continue to stabilize and foster trade and commodity finance to emerging markets.

Since its launch, GTLP has been acknowledged in the financial industry as an innovative structure to help infuse much needed liquidity into the trade finance market, thereby catalyzing global trade growth. The solution also represents a win-win proposition: for the banks it provides an opportunity to continue supporting clients through these difficult times; for IFC and its partners, it affords the ability to channel liquidity and credit into markets to help revitalize trade flows by leveraging on the banks’ vast networks across emerging markets in Asia, Africa, Middle East, Europe, and Latin America.

The program is already benefiting thousands of importers and exporters and small- and medium-sized enterprises.

 

From ADB Trade Finance Program

ADB’s Trade Finance Program (TFP) fills market gaps for trade finance by providing guarantees and loans to banks to support trade.

Backed by its AAA credit rating, ADB’s TFP works with over 200 partner banks to provide companies with the financial support they need to engage in import and export activities in Asia’s most challenging markets. With dedicated trade finance specialists and a response time of 24 hours, the TFP has established itself as a key player in the international trade community, providing fast, reliable, and responsive trade finance support to fill market gaps.

A substantial portion of TFP’s portfolio supports small and medium-sized enterprises (SMEs), and many transactions occur either intra-regionally or between ADB’s developing member countries. The program supports a wide range of transactions, from commodities and capital goods to medical supplies and consumer goods.

The TFP continues to grow, supporting billions of dollars of trade throughout the region, which in turn helps create sustainable jobs and economic growth in Asia’s developing countries.

 

 

Key Terms:

  • IFC GTFP (Global Trade Finance Program)
  • IFC GTLP (Global Trade Liquidity Program)
  • IFC GTSF (Global Trade Supplier Finance)
  • IFC GWFP (Global Warehouse Finance Program)
  • SME ( Small and Medium Enterprises)
  • LC (Letter of Credit)
  • DC (Documentary Collections)
  • IFC ( International Finance Corporation)
  • WTO (World Trade Organization)
  • ADB (Asian Development Bank)
  • WB (World Bank)
  • MDB ( Multilateral Development Banks)
  • ECA (Export Credit Agency)
  • Structured Trade
  • Aid for Trade
  • SWIFT
  • BRICS NDB (New Development Bank)
  • ADB TFP (Trade Finance Program)

 

 

Key Sources of Research:

 

Global Trade Liquidity Program

IFC

http://www.ifc.org/wps/wcm/connect/Industry_EXT_Content/IFC_External_Corporate_Site/Industries/Financial+Markets/Trade+and+Supply+Chain/GTLP/

 

 

Trade Finance Program

ADB

https://www.adb.org/site/trade-finance-program

 

 

EXPORTS AND FINANCIAL SHOCKS

Mary Amiti David E. Weinstein

Click to access amiti.pdf

 

 

Why Boosting the Availability of Trade Finance Became a Priority during the 2008–09 Crisis

Jean-Jacques Hallaert

 

Click to access TradeFinancech14.pdf

 

 

International Trade, Risk, and the Role of Banks

Friederike Niepmann Tim Schmidt-Eisenlohr

September 2013

Revised November 2014

 

Click to access sr633.pdf

 

 

International Trade Risk and the Role of Banks

Niepmann, Friederike and Tim Schmidt-Eisenlohr

2015

Click to access ifdp1151.pdf

 

 

 

Trade finance: developments and issues

Report submitted by a Study Group established by the Committee on the Global Financial System

The Group was chaired by John J Clark, Federal Reserve Bank of New York

January 2014

 

Click to access cgfs50.pdf

 

 

Trade finance and SMEs

WTO

 

Click to access tradefinsme_e.pdf

 

 

Improving the Availability of Trade Finance during Financial Crises

Marc Auboin

Moritz Meier-Ewert

2003

Click to access dis02_e.pdf

 

 

Trade Finance in Financial Crises: Assessment of Key Issues

December 9, 2003

 

Click to access 120903.pdf

 

 

US Trade Finance Guide 2008

Click to access tfg2008.pdf

 

 

ADDRESSING THE GLOBAL SHORTAGE OF TRADE FINANCE

Doina Buruiana, Project Manager at ICC Banking Commission

December 15, 2016

https://internationalbanker.com/finance/addressing-global-shortage-trade-finance/

 

 

Trade finance around the world

Friederike Niepmann, Tim Schmidt-Eisenlohr

11 June 2016

http://voxeu.org/article/trade-finance-around-world

 

 

The challenges of trade financing

Marc Auboin

28 January 2009

http://voxeu.org/article/challenges-trade-financing

 

 

The role of trade credit financing in international trade

Katharina Eck, Martina Engemann, Monika Schnitzer

20 April 2015

http://voxeu.org/article/role-trade-credit-financing-international-trade

 

 

The global financial crisis: A wake-up call for trade finance capacity building in emerging Asia

Wei Liu, Yann Duval

19 June 2009

http://voxeu.org/article/trade-finance-emerging-asian-economies

 

 

The role of bank guarantees in international trade

Tim Schmidt-Eisenlohr, Friederike Niepmann

26 November 2014

http://voxeu.org/article/role-bank-guarantees-international-trade

 

 

Why does finance matter for trade? Evidence from new data

Marc Auboin, Martina Engemann

03 December 2012

http://voxeu.org/article/why-does-finance-matter-trade-evidence-new-data

 

 

Trade and Trade Finance in the 2008-09 Financial Crisis

Prepared by Irena Asmundson, Thomas Dorsey, Armine Khachatryan, Ioana Niculcea,

and Mika Saito

January 2011

Click to access 07364.pdf

Click to access wp1116.pdf

 

 

 

Enhanced Attention for Trade Finance

Andrew Cornford

 

Click to access Trade_Finance.pdf

 

 

Trade finance: The landscape is changing— are you?

Accenture

Click to access Accenture-Trade-Finance.pdf

 

 

RETHINKING TRADE & FINANCE 2016

ICC Global Survey on Trade Finance

 

Click to access ICC_Global_Trade_and_Finance_Survey_2016.pdf

 

 

2016 TRaDE FINaNCE GaPS, GROwTh, aND JObS SURvEY

 

alisa Di Caprio Ying Yao Steven beck Fahad Khan

ADB

 

Click to access trade-finance-gaps.pdf

 

 

Articles on Trade Finance

The Banker.com

http://www.thebanker.com/Transactions-Technology/Trade-Finance

 

 

2016 State of Supply Chain Finance Industry

 

Click to access 2016-State-of-SCF-April-15.pdf

 

 

ICC Global Survey on Trade Finance

 

http://www.iccwbo.org/Products-and-Services/Trade-facilitation/ICC-Global-Survey-on-Trade-Finance/

 

 

 

 

TRADE AND DEVELOPMENT REPORT, 2016

UNCTAD

 

Click to access tdr2016_en.pdf

 

 

No Guarantees, No Trade: How Banks Affect Export Patterns

Friederike Niepmann Tim Schmidt-Eisenlohr

2016

 

Click to access ifdp1158.pdf

 

 

Understanding Trade Finance: Theory and Evidence from Transaction-level Data

Jae Bin Ahn

International Monetary Fund

August, 2015

 

 

Off the Cliff and Back? Credit Conditions and International Trade during the Global Financial Crisis

Davin Chor Kalina Manova

2010

Click to access manova_presentation.pdf

Click to access w16174.pdf

 

 

Trade Finance during the Great Trade Collapse

Jean-Pierre Chauffour and Mariem Malouche

2011

 

Click to access Trade-Finance-finalpdf.pdf

 

 

Why Trade Finance matters for Trade

WTO/IFC

 

Click to access ifcwks3.pdf

 

 

TRADE FINANCE IN PERIODS OF CRISIS: WHAT HAVE WE LEARNED IN RECENT YEARS?

Marc Auboin and Martina Engemann

2013

Click to access ersd201301_e.pdf

 

 

Global Finance Names The World’s Best Trade Finance Providers 2016

https://www.gfmag.com/media/press-releases/global-finance-names-worlds-best-trade-finance-providers-2016

https://www.gfmag.com/magazine/february-2016/worlds-best-trade-finance-providers-2016-table-contents

 

 

The Trade Finance Business of U.S. Banks

Friederike Niepmann and Tim Schmidt-Eisenlohr

MAY 19, 2014

http://libertystreeteconomics.newyorkfed.org/2014/05/the-trade-finance-business-of-us-banks.html

 

 

Why U.S. Exporters Use Letters of Credit

Friederike Niepmann and Tim Schmidt-Eisenlohr

2014

http://libertystreeteconomics.newyorkfed.org/2014/05/why-us-exporters-use-letters-of-credit.html

 

 

WHAT DRIVES BANK-INTERMEDIATED TRADE FINANCE? EVIDENCE FROM CROSS-COUNTRY ANALYSIS 

José María Serena Garralda

Garima Vasishtha

2015

Click to access dt1524e.pdf

 

 

The impact of Basel III on trade finance

Author: Bc. Jana Malešová

Masters Thesis

 

 

 

The Withdrawal of Correspondent Banking Relationships: A Case for Policy Action

Prepared by Michaela Erbenová, Yan Liu, Nadim Kyriakos-Saad, Alejandro López-Mejía, Giancarlo Gasha, Emmanuel Mathias, Mohamed Norat, Francisca Fernando, and Yasmin Almeida1

2016

 

Click to access sdn1606.pdf

 

 

Leveraging Supply Chain Finance for Development

Alexander R. Malaket

September 2015

 

Click to access E15-Finance-Malaket-final.pdf

 

 

 

Trade Finance: A Catalyst for Asian Growth

Claude Lopez

2015

 

Click to access MPRA_paper_66250.pdf

 

 

 

Trade Flows in Developing Countries: What is the Role of Trade Finance?

 

Clara Brandi Birgit Schmitz

 

Click to access DP_13.2015.pdf

 

 

Financing Global Development: The Potential of Trade Finance

Click to access 13_BP_10.2015.pdf

Understanding Global Value Chains – G20/OECD/WB Initiative

Understanding Global Value Chains – G20/OECD/WB Initiative

 

There is lot of opacity in understanding of GVCs.  Efforts are underway since last few years to get better analytical and statistical tools to understand International Trade and Global Value Chains.

Globalization in Trade and Finance encouraged by International organizations such as IMF/WB/OECD/WTO/UNCTAD/UNIDO and others has changed the landscape of Trade.

There is still a long way to go to make better sense of issues and concerns for policy makers.

OECD/WB/WTO along with G20 Trade Ministers have initiated efforts since 2012.

 

From Global Value Chains 

Introduction to GVCs

International production, trade and investments are increasingly organised within so-called global value chains (GVCs) where the different stages of the production process are located across different countries. Globalisation motivates companies to restructure their operations internationally through outsourcing and offshoring of activities.

Firms try to optimise their production processes by locating the various stages across different sites. The past decades have witnessed a strong trend towards the international dispersion of value chain activities such as design, production, marketing, distribution, etc.

This emergence of GVCs challenges conventional wisdom on how we look at economic globalisation and in particular, the policies that we develop around it.

 

Trade in Value Added

The goods and services we buy are composed of inputs from various countries around the world. However, the flows of goods and services within these global production chains are not always reflected in conventional measures of international trade. The joint OECD – WTO Trade in Value-Added (TiVA) initiative addresses this issue by considering the value added by each country in the production of goods and services that are consumed worldwide. TiVA indicators are designed to better inform policy makers by providing new insights into the commercial relations between nations.

 

GVCs and Trade Policy

Global value chains (GVCs) have become a dominant feature of world trade, encompassing developing, emerging, and developed economies. The whole process of producing goods, from raw materials to finished products, is increasingly carried out wherever the necessary skills and materials are available at competitive cost and quality. Similarly, trade in services is essential for the efficient functioning of GVCs, not only because services link activities across countries but also because they help companies to increase the value of their products. This fragmentation highlights the importance of an ambitious complementary policy agenda to leverage engagement in GVCs into more inclusive growth and employment and the OECD is currently undertaking comprehensive statistical and analytical work that aims to shed light on the scale, nature and consequences of international production sharing.

 

From Global Value Chains/Global Production Networks: Organizing the Global Economy

The key organizational feature of the global economy?

  • “Global Value Chains are defined by fragmented supply chains, with internationally dispersed tasks and activities coordinated by a lead firm (a TNC)” (UNCTAD, 2013, p.125; original italics).
  • Data gathering exercises:UNCTAD,OECD,WTO,JETRO…
  • Now firmly on the agenda among leading international economic organizations
  • The international division of labour:imperial/colonialsystems and exchanges of raw materials and finished goods
  • The new international division of labour(NIDL):establishment of overseas production bases of core country TNCs
  • The global division of labour:much more complex global networks lying behind the production of different goods and services

The phenomenon

  • About 60% of global trade, which today amounts to more than $20 trillion, consists of trade in intermediate goods and services that are incorporated at various stages in the production process of goods and services for final consumption” (UNCTAD, 2013, p. 122)
  • Not new, but since 2000 trade and FDI have increased exponentially, and ahead of GDP growth, highlighting a growth in TNC coordinated global value chains
  • Double counting – approx. 25-30% of value of world trade, e.g. the iPhone example. Not just trade from China to US, but incorporates high value components from Japan, South Korea etc.
  • Beyond national economies and basic trade data, and beyond TNCs and FDI, to more complex organizational structures involving intra-firm trade, arm’s length trade and non-equity modes e.g. subcontracting

 

 

From GLOBAL VALUE CHAIN ANALYSIS: A PRIMER

gvc5

 

From Global Capitalism and Commodity Chains: Looking Back, Going Forward

gvc4

 

From Global Value Chains/Global Production Networks: Organizing the Global Economy

gvc1gvc-2gvc3

 

Key Terms

  • Global Commodities Chains (GCCs)
  • Global Production Networks (GPNs)
  • Global Value Chains (GVCs)
  • Strategic Coupling
  • Economic Deepening
  • Trans National Corporation (TNC)
  • Multi National Corporation (MNC)
  • Multi National Enterprises (MNE)
  • SMILE curve
  • Economic Clusters
  • UNIDO (United Nations Industrial Development Organization)
  • OECD (Organization for Economic Cooperation and Development)
  • WTO (World Trade Organization)
  • WB (World Bank)
  • UNESCAP (Economic and Social Commission for Asia and Pacific)
  • UNCTAD ( United Nations Commission for Trade and Development)
  • ILO ( International Labor Organization)
  • G20 ( Group of 20 Nations)
  • TIVA ( Trade in Value Added)
  • On shoring
  • Off shoring
  • Outsourcing

 

 

Key People

  • Gary Gereffi
  • Neil M Coe
  • Jennifer Bair
  • Henry Wai-chung Yeung
  • Timothy Sturgeon

 

 

Key Sources of Research:

 

Measuring Trade in Value Added: An OECD-WTO joint initiative

https://www.oecd.org/tad/measuringtradeinvalue-addedanoecd-wtojointinitiative.htm

 

 

Global Value Chains

https://www.oecd.org/about/g20-oecd-global-value-chains.htm

https://www.oecd.org/sti/ind/global-value-chains.htm

 

 

OECD Stocktaking Seminar on Global Value Chains 2014

https://www.oecd.org/g20/topics/trade-and-investment/g20-oecd-global-value-chains-2014.htm

 

 

IMPLICATIONS OF GLOBAL VALUE CHAINS
FOR TRADE, INVESTMENT, DEVELOPMENT AND JOBS

OECD, WTO, UNCTAD 6 August 2013

Prepared for the
G-20 Leaders Summit
Saint Petersburg (Russian Federation) September 2013

 

Click to access G20-Global-Value-Chains-2013.pdf

 

 

Inclusive Global Value Chains

Policy options in trade and complementary areas for GVC Integration by small and medium enterprises and low-income developing countries

OECD and World Bank Group

Report prepared for submission to G20 Trade Ministers Meeting Istanbul, Turkey, 6 October 2015

 

Click to access Participation-Developing-Countries-GVCs-Summary-Paper-April-2015.pdf

 

 

GLOBAL VALUE CHAINS: CHALLENGES, OPPORTUNITIES, AND IMPLICATIONS FOR POLICY

OECD, WTO and World Bank Group

Report prepared for submission to the G20 Trade Ministers Meeting Sydney, Australia, 19 July 2014

 

Click to access gvc_report_g20_july_2014.pdf

 

 

Making Global Value Chains (GVCs) Accessible to All

Progress Report
Meeting of the Council at Ministerial Level

6-7 May 2014

 

Click to access MCM-GVC-Progress-Report-May-2014.pdf

 

 

Inclusive Global Value Chains

Policy Options for Small and Medium Enterprises and Low-Income Countries

Ana Paula Cusolito, Raed Safadi, and Daria Taglioni

2016

Click to access 9781464808425.pdf

 

 

Global value chains in a changing world

Edited by Deborah K. Elms and Patrick Low

2013

 

Click to access aid4tradeglobalvalue13_e.pdf

 

 

The rise of global value chains

WORLD TRADE REPORT 2014

 

Click to access wtr14-2c_e.pdf

 

 

Who Captures the Value in the Global Value Chain? High Level Implications for the World Trade Organization

Peter Draper and Andreas Freytag

July 2014

 

Click to access E15-Global-Value-Chains-DraperFreytag-FINAL.pdf

 

 

Joining, Upgrading and Being Competitive in Global Value Chains: 

A Strategic Framework

 

O. Cattaneo G. Gereffi S. Miroudot D. Taglioni

 

Click to access 2013-04_WorldBank_wps6406_Cattaneo_Gereffi_Miroudot_Taglioni_Competitiveness_GVCs.pdf

 

 

Global value chains, development and emerging economies

Gary Gereffi

2015

Click to access WP_18.pdf

 

 

GLOBAL VALUE CHAINS IN A POSTCRISIS WORLD A DEVELOPMENT PERSPECTIVE

Olivier Cattaneo, Gary Gereffi, and Cornelia Staritz

2010

Click to access Gereffi_GVCs_in_the_Postcrisis_World_Book.pdf

 

 

 

Global value chains and global production networks in the changing international political economy: An introduction

Jeffrey Neilson1, Bill Pritchard1 and Henry Wai-chung Yeung

2014

http://www.tandfonline.com/doi/pdf/10.1080/09692290.2013.873369

 

 

Combining the Global Value Chain and global I-O approaches

 

 

 

Global value chains and world trade : Prospects and challenges for Latin America

René A. Hernández
Jorge Mario Martínez-Piva Nanno Mulder

 

http://repositorio.cepal.org/bitstream/handle/11362/37176/S2014061_en.pdf?sequence=1

 

 

 

Global value chains in a post-Washington Consensus world

Gary Gereffi

2014

 

https://dukespace.lib.duke.edu/dspace/bitstream/handle/10161/10696/2014%20Feb_RIPE_Gereffi,%20Gary_GVCs%20in%20a%20post-Washington%20Consensus%20world.pdf?sequence=1

 

 

GLOBAL VALUE CHAINS AND DEVELOPMENT: Governance, Upgrading & Emerging Economies

Gary Gereffi

Director, Duke CGGC Duke University

2016

Click to access 697_10587.pdf

 

 

 

MaPPing gLoBaL VaLUe CHainS

Koen De Backer and Sébastien Miroudot

2014

Click to access ecbwp1677.pdf

 

 

 

Global Value Chains/Global Production Networks: Organizing the Global Economy

Neil M. Coe

2013

Click to access DrCoe.pdf

 

 

 

GLOBAL VALUE CHAIN ANALYSIS: A PRIMER

Gary Gereffi
Karina Fernandez-Stark

July 2016

 

http://dukespace.lib.duke.edu/dspace/bitstream/handle/10161/12488/2016-07-28_GVC%20Primer%202016_2nd%20edition.pdf?sequence=1

 

 

 

WHY THE WORLD SUDDENLY CARES ABOUT GLOBAL SUPPLY CHAINS

GARY GEREFFI AND JOONKOO LEE

Duke University

http://dukespace.lib.duke.edu/dspace/bitstream/handle/10161/10699/2012-07_JSCM_Gereffi%20&%20Lee_Why%20the%20world%20suddenly%20cares%20about%20global%20supply%20chains.pdf?sequence=1

 

 

 

The Economic Crisis: A Global Value Chain Perspective

 

Gary Gereffi

 

Click to access a-global-value-chain-perspective.pdf

 

 

The governance of global value chains

Gary Gereffi John Humphrey Timothy Sturgeon

2005

 

Click to access sturgeon2005.pdf

 

 

Global production networks and the analysis of economic development

Jeffrey Henderson, Peter Dicken, Martin Hess, Neil Coe and Henry Wai-Chung Yeung

2002

Click to access 2002_RIPE.pdf

 

 

GLOBAL VALUE CHAINS: INVESTMENT AND TRADE FOR DEVELOPMENT

UNCTAD 2013

Click to access wir2013_en.pdf

 

 

Asia and Global Production Networks

Implications for Trade, Incomes and Economic Vulnerability

Benno Ferrarini David Hummels

2014

Click to access asia-and-global-production-networks.pdf

 

 

 

Global Production Networks: Theorizing Economic Development in an Interconnected World

By Neil M. Coe, Henry Wai-Chung Yeung

2015

 

 

Toward a Dynamic Theory of Global Production Networks

Henry Wai-chung Yeung

Neil M. Coe

 

Click to access 2015_GPN_theory_paper_EG%20Vol91(1)_29-58.pdf

 

 

Global Value Chains and deVelopment

unido’s support towards inclusive and sustainable industrial development

2015

Click to access GVC_REPORT_FINAL.PDF

 

 

Global Value Chains: The New Reality of International Trade

Sherry Stephenson

December 2013

Click to access E15_GVCs_BP_Stephenson_FINAL.pdf

 

 

GLOBAL VALUE CHAINS SURVEYING DRIVERS AND MEASURES

João Amador and Sónia Cabral

2014

Click to access ecbwp1739.en.pdf

 

 

GLOBAL VALUE CHAINS AND INTERCONNECTEDNESS OF ASIA-PACIFIC ECONOMIES

Asia Pacific Trade and Investment Report

2015

 

Click to access Chapter%207%20-%20GVCs%20in%20the%20Asia-Pacific.pdf

Click to access Full%20Report%20%20-%20APTIR%202015.pdf

 

 

Global Capitalism and Commodity Chains: Looking Back, Going Forward

JENNIFER BAIR

2005

COMPETITION & CHANGE, Vol. 9, No. 2, June 2005 153–180

 

 

Global Value Chains: Development Challenges and Policy Options

Proposals and Analysis

December 2013

Click to access E15-Global-Value-Chains-Compliation-Report-FINAL.pdf

 

 

Globalizing’ regional development: a global production networks perspective

Neil M Coe, Martin Hess, Henry Wai-chung Yeung, Peter Dicken and Jeffrey Henderson

Click to access 2004_TIBG.pdf

 

 

Multilateral approaches to Global Supply Chains

 

International Labour Office

2014

 

Click to access wcms_485351.pdf

The Collapse of Global Trade during Global Financial Crisis of 2008-2009

The Collapse of Global Trade during Global Financial Crisis of 2008-2009

There are three broad categories of global Trade.

  • Trade in Commodities
  • Trade in Manufactured Goods
  • Trade in Services

During the Financial Crisis, Trade in commodities declined due to increase in Prices.

Trade in Services were largely unaffected.

Trade in Manufactured goods declined sharply for variety of reasons not yet entirely clear.

 

Potential Causes for decline

  • Fall in Aggregate Demand of goods
  • Constrained Trade Finance
  • Increase in Trade Barriers
  • Impact of Global Value Chains

 

From GLOBAL VALUE CHAINS IN A POSTCRISIS WORLD A DEVELOPMENT PERSPECTIVE

The global economic crisis of 2008–09 has revealed the interdependence of the world economy. The financial crisis originated in the United States, but the resulting economic downturn quickly spread to the rest of the world. Trade, along with finance, was one of the main vectors of transmission of the crisis. In 2009, there was a massive contraction in global trade—minus 13 percent. The contraction was largely a reflection of a drop in demand, especially for durable goods. The fact that the shock was transmitted very rapidly reflects the increasing reliance by businesses on so-called global value chains (GVCs)—the process of ever-finer specialization and geographic fragmentation of production, with the more labor-intensive parts of the production process transferred to developing countries. In a world where GVCs are the prevalent business model for multinational corporations, a reduction in demand for final products by global buyers implies that demand shocks are immediately transmitted “upstream” to subcontractors in developing countries.

 

From Resilient to the crisis? Global supply chains and trade flows

According to the most recent IMF estimates (IMF 2009), the ongoing recovery will drive a wedge between output and trade. Output is supposed to shrink by ‘only’ 1.1% at the end of 2009 (-3.4% in advanced economies), but world trade is forecast to still experience a drop of -11.9%. While other estimates put the latter figure at –9% (WTO, World Bank), it is indisputable that during 2009 official figures recording trade flows will fall much more than GDP.

Apart from its magnitude, the fall in trade in 2009 has also been quite homogeneous across all countries (more than 90% of OECD countries have exhibited simultaneously a decline in exports and imports exceeding 10%, as noted by Araujo and Olivera Martins 2009). This fall has also been very fast, with trade virtually grinding to a halt in the last month of 2008.1 These facts led Baldwin and Evenett (2009) to qualify the drop in trade during the crisis as “severe, sudden and synchronised”.

A number of transmission mechanisms have recently been proposed to account for these three attributes of the contraction of trade flows, many of which impinge upon the role that global supply chains might have played in exacerbating the drop in global demand.

The basic argument is that in a world characterised increasingly by vertical specialisation, goods are produced sequentially in stages across different countries – so-called international supply chains. The constituent parts and components of a final good crosses borders several times before the final product reaches the consumer; at each border crossing, the full value of the partially assembled good is recorded as trade. As a result, for a given reduction in world income, trade should decline “not only by the value of the finished product, but also by the value of all the intermediate trade flows that went into creating it”.

This implies that the extensive presence of supply chains does not automatically explain why world trade overshot the world GDP drop; other explanatory factors are needed. These may include:

  • The collapse in internal demand and production, affecting current and future level of (tradable) inventories worldwide;
  • Fiscal stimulus plans with a relatively stronger support of non-tradable sectors, like construction and infrastructures (Bénassy-Quéré et al. 2009);
  • The rise of ‘murky’ protectionism; and
  • The problems of trade finance with financial spreads still well-above ‘normal’ (i.e. pre-crisis) market rates (Auboin, 2009).

Do the above arguments mean that global supply chains are totally neutral as a transmission mechanism of the crisis from GDP to trade? Of course not. In all likelihood, however, the channels are much more complex than originally thought, and entail important compositional effects.

For the sake of argument, let us take the following story based on the idea that a relatively large part of the overreaction of trade has been caused by the sudden drying up of liquidity in trade finance. Auboin (2009) notes that, in the second part of 2008, spreads on short-term trade credit facilities suddenly soared to between 300 to 600 basis points above LIBOR, compared to 10 to 20 basis points in normal times, leading to a virtual freeze of important trade deals throughout the globe, with supply chain operations being disrupted by lack of financing, especially for developing country suppliers.

Under this assumption we would have a scenario in which the liquidity channel has led trade to overshoot the fall in demand, with the effect being larger within supply chains, as the trade financing of these operations is typically managed by large international financial institutions, particularly hit by the crisis.3

In this scenario, we would still obtain a severe, sudden and synchronised drop in trade flows, with the effects correlated with (but not caused by) the behaviour of global supply chains.

Moreover, under the same scenario, we would also observe that, during the crisis,trade falls more along the intensive margin (i.e. value per trade) than the extensive margins (i.e. number of traders). The reason being that, if the overreaction of trade was caused relatively more by liquidity constraints than by a disruption of supply chains, the above effects would lead to a reduction in the volume of trade, but not necessarily to a similar reduction in the number of traders worldwide.

This is exactly what Bricongne et al. (2009) find in a paper analysing the behaviour of French exporters during the crisis. Relying on monthly data for individual French exporters observed until April 2009, the authors find that the drop in French exports is mainly due to the intensive margin of large exporters, with small and large firms evenly affected once sectoral and geographical specialisation are controlled for. Interestingly, they also find that firms (small and large) in sectors more dependent on external finance are the most affected by the crisis.

While any conclusion must wait for more data to become available, there are good reasons to believe that the rise of global supply chains has not necessarily been the main cause of the recent “severe, sudden and synchronised” fall in global trade flows. Based on the available evidence, one may even be tempted to conclude that, under certain circumstances, international networks of production may also display some degree of ‘resilience’ to adverse shocks like the current crisis: supply-chain-related trade flows may react later (rather than sooner) to an adverse shock. Their fall may be smaller and, eventually, their recovery may happen faster relative to overall trade flows.

The observed resilience of supply chains may arise from some intrinsic attribute of production chains, as argued above. Alternatively, it may be the outcome of the political economy. Fearing that a collapse of supply chains would set off a sudden process of de-globalisation and implosion of international trade, governments may intervene in favour of supply chains. For example, the massive bail-outs of large financial institutions have helped their best customers, among them the big players within supply chains. Finally, of course, this indirect support of supply chains may have also been an unintended consequence of financial bailouts implemented for very different reasons.

 

From UNCTAD Global Value Chains: Investment and Trade for Development

gvc

 

Key Terms

  • BLS ( Bureau of Labor Statistics)
  • UNCTAD ( United Nations Conference on Trade and Development)
  • NIPAs ( National Income and Product Accounts)
  • OECD ( Organization for Economic Cooperation and Development)
  • EBRD (European Bank for Reconstruction and Development)
  • WTO (world Trade Organization)
  • GATT (General Agreement on Trade and Tariffs)
  • ILO (International Labor Organization)
  • ADB (Asian Development Bank)
  • UNIDO ( United Nations Industrial Development Organization)
  • BEA ( Bureau of Economic Analysis)
  • Production Networks
  • Vertical Specialization
  • Production Fragmentation
  • Intermediate Goods
  • Network Linkages
  • Global Supply Chains
  • Global Value Chains (GVCs)
  • Production Sharing
  • Inter Industry Input Output Tables
  • Inter Country Input Output Tables
  • Global Networks
  • Multi National Companies ( MNCs)
  • Regional Economic Integration
  • Trade Globalization
  • Trade in Goods and Services
  • Trade in Value Added (TIVA)
  • World Input Output Database (WIOD)
  • OECD-WTO TIVA Database
  • UNCTAD-EORA GVC Database
  • Global Trade Analysis Project (GTAP) Database
  • Institute of Developing Economies (IDE-JETRO) Asian IO Tables
  • World Input Output Network (WION)
  • Global Multi Regional Input Output (GMRIO) Framework
  • EXIOBASE/EXIOPOL EXIOBASE is a global, detailed Multi-regional Environmentally Extended Supply and Use / Input Output (MR EE SUT/IOT) database.

 

 

Key Sources of Research:

 

The Global Trade Slowdown: Cyclical or Structural?

Cristina Constantinescu, Aaditya Mattoo, and Michele Ruta

2015

Click to access wp1506.pdf

 

 

The future of global trade: Where are we heading and should we be concerned?

Gaaitzen de Vries
Bart Los
Robert Stehrer
Marcel Timmer

2016

https://www.weforum.org/agenda/2016/11/the-future-of-global-trade-where-are-we-heading

 

 

Demand Spillovers and the Collapse of Trade in the Global Recession

Rudolfs Bems Robert C. Johnson

Kei-Mu Yi

2010

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.186.7680&rep=rep1&type=pdf

 

 

Vertical Linkages and the Collapse of Global Trade

Rudolfs Bems
Robert C. Johnson
Kei-Mu Yi

AMERICAN ECONOMIC REVIEW
VOL. 101, NO. 3, MAY 2011

Click to access 600661c5f17781a38ca3168026b8663b8ebb.pdf

 

 

The Role of Vertical Linkages in the Propagation of the Global Downturn of 2008

Rudolfs Bems Robert C. Johnson

Kei-Mu Yi

2010

 

Click to access 0e43be03f9da1c48a385b94fbcc4904a3fb0.pdf

 

 

The Great Trade Collapse

Rudolfs Bems, Robert C. Johnson and Kei-Mu Yi

Annual Review of Economics
Vol.5:1-549 (Volume publication date August 2013)

 

 

GLOBAL VALUE CHAINS DURING THE GREAT TRADE COLLAPSE

A BULLWHIP EFFECT?

by Carlo Altomonte, Filippo Di Mauro, Gianmarco Ottaviano, Armando Rungi and Vincent Vicard

2012

 

Click to access 169822.pdf

 

 

The bullwhip effect and the Great Trade Collapse

Veronika Zavacka

 

Click to access wp0148.pdf

 

 

Trade Finance and the Great Trade Collapse

By JaeBin Ahn, Mary Amiti, and David E. Weinstein

2011

 

Click to access Ahn-Amiti-WeinsteinAERPP.pdf

 

 

Economic Crisis and Global Supply Chains 

Agnès Bénassy-Quéré, Yvan Decreux, Lionel Fontagné & David Khoudour-Casteras

Click to access wp2009-15.pdf

 

 

 

The Financial Crisis and Global Supply Chains

 

Robert N. Mefford, University of San Francisco, USA

http://repository.usfca.edu/cgi/viewcontent.cgi?article=1010&context=fe

 

 

International Supply Chains and Trade Elasticity in Times of Global Crisis

Click to access ersd201008_e.pdf

 

 

GLOBAL SUPPLY CHAINS: TRADE AND ECONOMIC POLICIES FOR DEVELOPING COUNTRIES

Alessandro Nicita Victor Ognivtsev Miho Shirotori

 

Click to access itcdtab56_en.pdf

 

 

The Great Trade Collapse: Shock Amplifiers and Absorbers in Global Value Chains

Zhengqi Pan

June 2016

 

Click to access Zhengqi%20Pan_GPN2016_008.pdf

 

 

The Age of Global Value Chains: Maps and Policy Issues

 

Click to access JACB201530.pdf

 

 

Asia and Global Production Networks Implications for Trade, Incomes and Economic Vulnerability

 

Click to access asia-and-global-production-networks.pdf

 

 

Mapping globaL Value Chains

Koen De Backer and Sébastien Miroudot

2014

Click to access ecbwp1677.pdf

 

 

Mapping Global Value Chains:

Intermediate Goods Trade and Structural Change in the World Economy

Timothy J. Sturgeon

Olga Memedovic

2011

 

Click to access WP%2005%20Mapping%20Glocal%20Value%20Chains.pdf

 

 

 

World Investment Report 2013:

Global Value Chains: Investment and Trade for Development

2013

 

Click to access wir2013_en.pdf

 

 

Trade finance: developments and issues

Report submitted by a Study Group established by the Committee on the Global Financial System

The Group was chaired by John J Clark, Federal Reserve Bank of New York

January 2014

 

Click to access cgfs50.pdf

 

 

East Asian Value Chains and the Global Financial Crisis

Genet Zinabou

2010

Click to access FR4-14-8-2010-eng.pdf

 

 

The collapse of global trade, murky protectionism, Recommendations for the G20

and the crisis

 

Edited by: Richard Baldwin and Simon Evenett

2009

Click to access 2009-03-murky-protectionism.pdf

 

 

Production Sharing in East Asia: Who Does What for Whom and Why?

 

Francis Ng and Alexander Yeats

1999

 

Click to access multi-page.pdf

 

 

PRODUCTION SHARING IN EAST ASIA: CHINA’S POSITION, TRADE PATTERN AND TECHNOLOGY UPGRADING

Laike Yang

 

Click to access gdsmdp20152yang_en.pdf

 

 

GLOBAL VALUE CHAINS SURVEYING DRIVERS AND MEASURES

João Amador and Sónia Cabral

2014

 

Click to access ecbwp1739.en.pdf

 

 

A New Measurement for International Fragmentation of the Production Process: An International Input-Output Approach

Satoshi Inomata

October 2008

 

Click to access 175.pdf

 

 

GLOBAL VALUE CHAINS IN A POSTCRISIS WORLD

A DEVELOPMENT PERSPECTIVE

Olivier Cattaneo, Gary Gereffi, and Cornelia Staritz Editors

 

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.364.8729&rep=rep1&type=pdf#page=97

 

 

THE NATURE AND GROWTH OF VERTICAL SPECIALIZATION IN WORLD TRADE

David Hummels Jun Ishii Kei-Mu Yi

March 1999

 

Click to access sr72.pdf

 

 

TRADE INTEGRATION IN EAST ASIA:
THE ROLE OF CHINA AND PRODUCTION NETWORKS

MONA HADDAD

2007

Click to access wps4160.pdf

 

 

Production Networks and Trade Patterns in East Asia: Regionalization or Globalization?

Prema-chandra Athukorala

No. 56 | August 2010

Click to access wp56-trade-patterns-east-asia.pdf

 

 

Trade Integration and Production Network in East Asia

Pornnapa Leelapornchai

August 2007

 

Click to access Pornnapa.pdf

 

 

Trade patterns and global value chains in East Asia:
From trade in goods to trade in tasks

 

Click to access stat_tradepat_globvalchains_e.pdf

 

 

Global production sharing and trade patterns in East Asia

Prema-chandra Athukorala

June 2013

Click to access TU_VIROT,%20Ali_Reading2_Global%20Production%20Sharing%20and%20Trade%20Patterns%20in%20East%20Asia.pdf

 

 

Global Production Networks in Electronics and Intra-Asian Trade

Byron Gangnes

Ari Van Assche

2010

 

Click to access WP_2010-4.pdf

 

 

The Role of China, Japan, and Korea in Machinery Production Networks

Ayako OBASHI†

Fukunari KIMURA

March 2016

 

Click to access ERIA-DP-2016-10.pdf

 

 

China’s evolving role in global production networks: the decoupling debate revisited

Prema-chandra Athukorala

John Ravenhill

 

Click to access 2016-12_athukorala_ravenhill_wp_june_2016.pdf

 

 

International Production Networks And Changing Trade Patterns In East Asia: The Case Of The Electronics Industry

Dieter Ernst & Paolo Guerrieri

May 1997

Click to access 19970007.pdf

 

 

UNDERSTANDING THE WORLD TRADE COLLAPSE

Calista Cheung and Stéphanie Guichard

2009

http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?doclanguage=en&cote=eco/wkp(2009)70

 

 

GLOBAL TRADE: WHAT’S BEHIND THE SLOWDOWN?

IMF World Economic Outlook Report October 2016

 

Click to access c2.pdf

 

 

A Theory of Domestic and International Trade Finance

JaeBin Ahn

2011

Click to access 0c96052274d4abea86000000.pdf

 

 

The Great Trade Collapse: Causes, Consequences and Prospects

 

Edited by Richard Baldwin

2009

 

Click to access great_trade_collapse.pdf

 

 

Understanding the Weakness in World Trade

2015

 

Click to access eb201503_article01.en.pdf

 

 

The mystery of the missing world trade growth after the global financial crisis

Hanna armelius, Carl-JoHan Belfrage and Hanna stenBaCka

2014

 

Click to access rap_pov_artikel_1_141121_eng.pdf

 

 

Resilient to the crisis? Global supply chains and trade flows

Carlo Altomonte, Gianmarco Ottaviano

27 November 2009

http://voxeu.org/article/resilient-crisis-global-supply-chains-and-trade-flows

 

 

The great trade collapse: What caused it and what does it mean?

Richard Baldwin

27 November 2009

 

 

The Collapse of International Trade During the 2008-2009 Crisis: In Search of the Smoking Gun

Andrei A. Levchenko

Logan T. Lewis

Linda L. Tesar

2009

 

 

Off the Clif  and Back? Credit Conditions and International Trade during the Global Financial Crisis

Davin Chory

Kalina Manova

This version: December 2009

 

 

WHY THE WORLD SUDDENLY CARES ABOUT GLOBAL SUPPLY CHAINS

GARY GEREFFI AND JOONKOO LEE

2012

 

 

China’s Slowdown: The First Stage of the Bullwhip Effect

Yossi Sheffi

September 09, 2015

 

 

Financial Crisis and Supply-Chain Financing

Leora Klapper and Douglas Randall

 

 

The mystery of the missing world trade growth after the global financial crisis

Hanna Armelius, Carl-Johan Belfrage and Hanna Stenbacka

2014

 

 

Trade Collapse, Trade Relapse and Global Production Networks: Supply Chains in the Great Recession

Escaith, Hubert

OECD, DEFI, WTO

28. October 2009

 

 

SPIDERS AND SNAKES: OFFSHORING AND AGGLOMERATION IN THE GLOBAL ECONOMY

Richard Baldwin Anthony Venables

Working Paper 16611

2010

 

 

 

GLOBAL VALUE CHAINS IN A POSTCRISIS WORLD A DEVELOPMENT PERSPECTIVE

Olivier Cattaneo, Gary Gereffi, and Cornelia Staritz

2010

 

 

Accounting relations in bilateral value added trade

Robert Stehrer

2013

 

Click to access wiod14.pdf

 

 

NETWORKS OF VALUE ADDED TRADE

Working Papers 2015

João Amador | Sónia Cabral

 

 

Trade patterns and global value chains in East Asia: From trade in goods to trade in tasks

WTO Report

 

 

Counting borders in global value chains

Kirill Muradov:

May 2016

 

 

Using Average Propagation Lengths to Identify Production Chains in the Andalusian Economy

ERIK DIETZENBACHER*, ISIDORO ROMERO LUNA** AND NIELS S. BOSMA

2005

https://idus.us.es/xmlui/bitstream/handle/11441/17372/file_1.pdf?sequence=1

 

 

Trade in Value Added: An East Asian Perspective

Satoshi Inomata

No. 451 December 2013

 

Click to access adbi-wp451.pdf

 

 

TRADE INTERCONNECTEDNESS: THE WORLD WITH GLOBAL VALUE CHAINS

2013

 

 

The globalisation of inflation: the growing importance of global value chains

by Raphael Auer, Claudio Borio and Andrew Filardo

 

 

 

 

GLOBAL MULTIREGIONAL INPUT–OUTPUT FRAMEWORKS: AN INTRODUCTION AND OUTLOOK

Arnold Tukker a b & Erik Dietzenbacher

2013

Click to access UNSD%20-%20Tukker%20-%20Overview%20on%20International%20IO%20Tables%20-%202013.pdf

 

Oscillations and Amplifications in Demand-Supply Network Chains

Oscillations and Amplifications in Demand-Supply Network Chains

 

From Modeling and Measuring the Bullwhip Effect

Demand variability and uncertainty is a driver of supply chain inventory. Managing supply chains can be a challenge when demand variability and uncertainty is high. For a company in a supply chain consisting of multiple stages, each of which is run by a separate organization (or company), the variability of demand faced by this company can be much higher than the variability faced by downstream stages (where “downstream stages” refers to the stages closer to the final consumption of the product). The bullwhip effect refers to the phenomenon where demand variability amplifies as one moves upstream in a supply chain (Lee et al, 1997a, or LPW). LPW described this as a form of demand information distortion. Lee et al (1997b) further discussed the managerial and practical aspects of the bullwhip effect, giving more industry examples. The bullwhip effect phenomenon is closely related to studies in systems dynamics (Forrester, 1961; Sterman, 1989; Senge, 1990). Sterman (1989) observed a systematic pattern of demand variation amplification in the Beer Game, and attributed it to behavioral causes (i.e., misperceptions of feedback). Macroeconomists have also studied the phenomenon (Holt et al, 1968; Blinder, 1981; Blanchard, 1983).

 

From Operational and Behavioral Causes of Supply Chain Instability

 

Supply chain instability is often described as the bullwhip effect, the tendency for variability to increase at each level of a supply chain as one moves from customer sales to production (Lee et al. 1997, Chen et al. 2000). While amplification from stage to stage is important, supply chain instability is a richer and more subtle phenomenon. The economy, and the networks of supply chains embedded within it, is a complex dynamic system and generates multiple modes of behavior. These include business cycles (oscillation), amplification of orders and production from consumption to raw materials (the bullwhip), and phase lag (shifts in the timing of the cycles from consumption to materials). High product returns and spoilage are common in industries from consumer electronics to hybrid seed corn (Gonçalves 2003). Many firms experience pronounced hockey-stick patterns in which orders and output rise sharply just prior to the end of a month or quarter as the sales force and managers rush to hit revenue goals. Boom and bust dynamics in supply chains are often worsened by phantom orders—orders customers place in response to perceived shortages in an attempt to gain a greater share of a shrinking pie (T. Mitchell 1923, Sterman 2000, ch. 18.3, Gonçalves 2002, Gonçalves and Sterman 2005).

What are the causes of supply chain instability? Why does supply chain instability persist, despite the lean revolution and tremendous innovations in technology? What can be done to stabilize supply chains and improve their efficiency?

Here I describe the origins of supply chain instability from a complex systems perspective. The dynamics of supply chain networks arise endogenously from their structure. That structure includes both operational and behavioral elements.

 

From Operational and Behavioral Causes of Supply Chain Instability

Oscillation, Amplification, and Phase Lag

Exhibit 1 shows industrial production in the US. The data exhibit several modes of behavior. First, the long-run growth rate of manufacturing output is about 3.4%/year. Second, as seen in the bottom panel, production fluctuates significantly around the growth trend. The dominant periodicity is the business cycle, a cycle of prosperity and recession of about 3–5 years in duration, but exhibiting considerable variability.

The amplitude of business cycle fluctuations in materials production is significantly greater than that in consumer goods production (exhibit 2). The peaks and troughs of the cycle in materials production also tend to lag behind those in production of consumer goods. Typically, the amplitude of fluctuations increases as they propagate from the customer to the supplier, with each upstream stage tending to lag behind its customer. These three features, oscillation, amplification, and phase lag, are pervasive in supply chains.

 

From Booms, Busts, and Beer: Understanding the Dynamics of Supply Chains

A central question in operations management is whether the oscillations, amplification and phase lag observed in supply chains arise as the result of operational or behavioral causes.

Operational theories assume that decision makers are rational agents who make optimal decisions given their local incentives and information.  Supply chain instability must then result from the interaction of rational actors with the physical and institutional structure of the system.

  • Physical structure includes the network linking customers and suppliers and the placement of inventories and buffers within it, along with capacity constraints and time delays in production, order fulfillment, transportation, and so on.
  • Institutional structure includes the degree of horizontal and vertical coordination and competition among firms, the availability of information to decision makers in each organization, and the incentives faced by each decision maker.

Behavioral explanations also capture the physical and institutional structure of supply chains, but view decision makers as boundedly rational actors with imperfect mental models, actors who use heuristics to make ordering, production, capacity acquisition, pricing and other decisions (Morecroft 1985, Sterman 2000, Boudreau et al. 2003, Gino & Pisano 2008, Bendoly et al. 2010, Croson et al. 2013).

Amplifications and Phase Lag

Amplification and phase lag arise from the presence of basic physical structures including stocks of inventory and delays in adjusting production or deliveries to changes in incoming orders.

Oscillations

Oscillations, however, are not inevitable. They arise from boundedly rational, behavioral decision processes

The difference matters: if supply chain instability arises from operational factors and rational behavior, then policies must be directed at changing the physical and institutional structure of the system, including incentives.

If, however, instability arises from bounded rationality and emotional arousal such policies may not be sufficient.

 

Key People:

  • Jay W Forrester
  • John Sterman
  • Rogelio Oliva
  • Hau L Lee

 

Key Terms:

  • Bullwhip Effect
  • Oscillations
  • Amplifications
  • Negative Feedback Loop
  • Positive Feedback Loop
  • Phase Lag
  • Supply Chain Networks
  • Inventory Management
  • Production Smoothening
  • Beer Distribution Game
  • Industrial Dynamics
  • Operational and Institutional Structures
  • Behavioral causes
  • Instability
  • Variability
  • Uncertainty

 

Key Sources of Research:

 

Behavioral Causes of Demand Amplification in Supply Chains: “Satisficing” Policies with Limited Information Cues

Rogelio Oliva

Paulo Gonçalves

 

Click to access 1889_087eb4f1-0532-4a7d-a206-3d565efc02af_2005-OLIVA133.pdf

 

 

REDUCING THE IMPACT OF DEMAND PROCESS VARIABILITY WITHIN A MULTI-ECHELON SUPPLY CHAIN

Francisco Campuzano Bolarín1,Lorenzo Ros Mcdonnell1, Juan Martín García

2008

 

Click to access CAMPU215.pdf

 

 

The impact of order variance amplification/dampening on supply chain performance

 

Robert N. Boute, Stephen M. Disney, Marc R. Lambrecht and Benny Van Houdt

 

Click to access KBI_0603.pdf

 

 

Coping with Uncertainty: Reducing ”Bullwhip” Behaviour in Global Supply Chains

 

Rachel Mason-Jones, and Denis R. Towill

Click to access 24557527da7aa9da7de238fe7f4a463b2af6.pdf

 

 

Bullwhip in Supply Chains ~ Past, Present and Future

Steve Geary Stephen M Disney and Denis R Towill

 

Click to access 492a6e6ae1d0f186fe2570b7477428e8e467.pdf

 

 

Shrinking the Supply Chain Uncertainty Circle

R Mason-Jones

Click to access 19980901d.pdf

 

 

THE BULLWHIP EFFECT IN SUPPLY CHAIN Reflections after a Decade

Gürdal Ertek, Emre Eryılmaz

 

Click to access ertek_eryilmaz_cels2008.pdf

 

 

Information distortion in a supply chain: The bullwhip effect

Hau L Lee; V Padmanabhan; Seugjin Whang

Management Science; Apr 1997; 43, 4;

Click to access f26117d56ab96aabe2d6cee4c390ab20ee18.pdf

 

 

 

THE SUPPLY CHAIN COMPLEXITY TRIANGE: UNCERTAINTY GENERATION IN THE SUPPLY CHAIN

 

Click to access 140687.pdf

 

 

The Bullwhip Effect in Supply Chains

Hau L. Lee, V. Padmanabhan and Seungjin Whang

1997

http://sloanreview.mit.edu/article/the-bullwhip-effect-in-supply-chains/

 

 

The Bullwhip Effect: Analysis of the Causes and Remedies

 

Jonathan Moll

Rene Bekker

 

Click to access werkstuk-moll_tcm243-354834.pdf

 

 

‘BULLWHIP’ AND ‘BACKLASH’ IN SUPPLY PIPELINES

Vinaya Shukla, Mohamed M Naim, Ehab A Yaseen

 

https://hal.archives-ouvertes.fr/hal-00525857/document

 

 

How human behaviour amplifies the bullwhip effect – a study based on the beer distribution game online

Joerg Nienhaus, Arne Ziegenbein*, Christoph Duijts

 

Click to access Bullwhip_Effect_Article.pdf

 

 

The Bullwhip Effect in Different Manufacturing Paradigm: An Analysis

Shamila Nabi KHAN1 Mohammad Ajmal KHAN2 Ramsha SOHAIL

 

Click to access 11.pdf.pdf

 

 

On replenishment rules, forecasting and the bullwhip effect in supply chains

Stephen M. Disney1 and Marc R. Lambrecht

 

Click to access Disney%20-%20On%20replenishment%20rules%20forecasting%20and%20the%20bullwhip%20effect%20in%20supply%20chains%20pre%20print.pdf

 

 

Causes and Remedies of Bullwhip Effect in Supply Chain

Sivakumar Balasubramanian Larry Whitman Kartik Ramachandran Ravindra Sheelavant

 

Click to access 2001IERCBullwhip.pdf

 

 

Booms, Busts, and Beer: Understanding the Dynamics of Supply Chains

John Sterman

 

Click to access Sterman%20Beh%20Ops%20Handbook%20Chapter%20140210.pdf

 

 

Modeling and Measuring the Bullwhip Effect

Li Chen and Hau L. Lee

2015

Click to access Chen_Lee_Bullwhip_2015.pdf

 

 

Operational and Behavioral Causes of Supply Chain Instability

John D. Sterman

Click to access 2a3118c5c7d2bd475335549b0b943009d66c.pdf

 

 

Order Stability in Supply Chains: Coordination Risk and the Role of Coordination Stock

Rachel Croson, Karen Donohue, Elena Katok, and John Sterman

Click to access Order%20Stability%20in%20SCs050212.pdf

Click to access Order_Stability_070505.pdf

 

 

SUPPLY CHAIN DYNAMICS, THE “BEER DISTRIBUTION GAME” AND MISPERCEPTIONS IN DYNAMIC DECISION MAKING

John D. Sterman

Click to access E6-63-01-02.pdf

 

 

When Do Minor Shortages Inflate To Great Bubbles?

Paulo Gonçalves

2002

 

Click to access Gonca1.pdf

 

 

A new technology paradigm for collaboration in the supply chain

Branko Pecar and Barry Davies

Click to access c522d454d1dc036a22db29b2dee005dbc44e.pdf

 

 

MANAGERIAL INSIGHTS ON THE IMPACT OF FORECASTING AND INFORMATION ON VARIABILITY IN A SUPPLY CHAIN

Frank Chent, Zvi Drezner2 , Jennifer K. Ryan3 and David Simchi-Levi

 

Click to access 4%20chen.pdf

 

 

Supply and Production Networks: From the Bullwhip Effect to Business Cycles

Dirk Helbing Stefan Laemmer

2004

 

Click to access 04-12-033.pdf

 

 

Inventory dynamics and the bullwhip effect : studies in supply chain performance

Udenio, M.

2014

 

Click to access 776508.pdf

 

 

RECENT WORK ON BUSINES CYCLES IN HISTORICAL PERSPECTIVE: REVIEW OF THEORIES AND EVIDENCE

VictorZarnowitz

1984

 

Click to access w1503.pdf

 

 

THEORY AND HISTORY BEHIND BUSINESS CYCLES:ARE THE 1990S

THE ONSET OF A GOLDEN AGE?

 

Victor Zarnowitz

WorkingPaper7010 htp:/w.nber.org/papers/w7010

1999

 

Click to access w7010.pdf

 

 

The Beginning of System Dynamics

Jay W. Forrester

 

Click to access D-4165-1.pdf

 

 

Profiles in Operations Research: Jay Wright Forrester

David C. Lane John D. Sterman

 

Click to access jwf-profile-in-op.pdf

 

 

SYSTEM DYNAMICS MODELLING IN SUPPLY CHAIN MANAGEMENT: RESEARCH REVIEW

2000

 

Click to access 54fe11ea0aaa47f4c8e08959be2ef52d50a6.pdf

 

 

INDUSTRIAL DYNAMICS-AFTER THE FIRST DECADE

JAY W. FORRESTER

 

Click to access Forrester68.pdf

 

 

Industrial Dynamics

Jay W Forrester

1961

 

 

Business Dynamics

John Sterman

2000

 

Financial Stability and Systemically Important Countries -IMF-FSAP

Financial Stability and Systemically Important Countries -IMF-FSAP

 

IMF – FSAP

Assess financial stability and development

From The Financial Sector Assessment Program (FSAP)

The goal of FSAP assessments is twofold: to gauge the stability and soundness of the financial sector, and to assess its potential contribution to growth and development.

To assess the stability of the financial sector, FSAP teams examine the resilience of the banking and other non bank financial sectors; conduct stress tests and analyze systemic risks including linkages among banks and nonbanks and domestic and cross border spillovers; examine microprudential and macroprudential frameworks; review the quality of bank and non bank supervision, and financial market infrastructure oversight against accepted international standards; and evaluate the ability of central banks, regulators and supervisors, policymakers, and backstops and financial safety nets to respond effectively in case of systemic stress. While FSAPs do not evaluate the health of individual financial institutions and cannot predict or prevent financial crises, they identify the main vulnerabilities that could trigger one.

To assess the development aspects of the financial sector, FSAPs examine the development needs in terms of institutions, markets, infrastructure, and inclusiveness; quality of the legal framework and of payments and settlements system; identify obstacles to the competitiveness and efficiency of the sector; topics relating to financial inclusion and retail payments; and examine its contribution to economic growth and development. Issues related to development of domestic capital markets are particularly important in developing and low-income countries. While focusing on development issues, FSAPs also keep in view financial stability dimensions .

Since 1999 the IMF has monitored countries’ financial sectors on a voluntary basis through the Financial Sector Assessment Program. In developing and emerging market countries, the World Bank participates in these assessments, focusing on long-term financial development issues.

In the context of these financial sector assessments, the IMF examines three key components in all countries:

• the soundness of banks and other financial institutions, including stress tests;

• the quality of financial market oversight in banking and, if appropriate, insurance and securities; and

• the ability of supervisors, policymakers, and financial safety nets to respond effectively in case of a crisis.

One size does not fit all in these assessments. The IMF tailors its focus in each of these areas to a country’s individual circumstances, and takes into account the potential sources that might make the country in question vulnerable.

The objective is to assess countries’ crisis prevention and management frameworks, with the goal of supporting both national and global financial stability.

 

Based on 2010 IMF-FSAP, these are the counties having the systemically important Financial Sectors:

  • Australia
  • Austria
  • Belgium
  • Brazil
  • Canada
  • China
  • France
  • Germany
  • Hong Kong SAR
  • Italy
  • Japan
  • India
  • Ireland
  • Luxembourg
  • Mexico
  • the Netherlands
  • Russia
  • Singapore
  • South Korea
  • Spain
  • Sweden
  • Switzerland
  • Turkey
  • the United Kingdom
  • the United States

 

In 2014, Four new countries were added to the list based on expanded criteria for financial stability:

  • Finland,
  • Poland,
  • Denmark,
  • Norway

Expanded criteria emphasize connections between financial sectors, institutions

More emphasis on how problems in one country affect others

 

From Press Release: IMF Expanding Surveillance to Require Mandatory Financial Stability Assessments of Countries with Systemically Important Financial Sectors

September 27, 2010

Press Release No. 10/357
September 27, 2010

The Executive Board of the International Monetary Fund (IMF) has approved making financial stability assessments under the Financial Sector Assessment Program (FSAP) a regular and mandatory part of the Fund’s surveillance for members with systemically important financial sectors. While participation in the FSAP program has been voluntary for all Fund members, the Executive Board’s decision will make financial stability assessments mandatory for members with systemically important financial sectors under Article IV of the Fund’s Articles of Agreement.

The decision adopted on September 21, 2010 to raise the profile of financial stability assessments under the FSAP for members with systemically important financial sectors is a recognition of the central role of financial systems in the domestic economy of its members, as well as in the overall stability of the global economy. It is a major step toward enhancing the Fund’s economic surveillance to take into account the lessons from the recent crisis, which originated in financial imbalances in large and globally interconnected countries.

The FSAP provides the framework for comprehensive and in-depth assessments of a country’s financial sector, and was established in 1999, in the aftermath of the Asian crisis. FSAP assessments are conducted by joint IMF-World Bank teams in developing and emerging market countries, and by the Fund alone in advanced economies. FSAPs have two components, which may also be conducted in separate modules: a financial stability assessment, which is the responsibility of the IMF and, in developing and emerging market countries, a financial development assessment, the responsibility of the World Bank.

These mandatory financial stability assessments will comprise three elements: 1) An evaluation of the source, probability, and potential impact of the main risks to macro-financial stability in the near term, based on an analysis of the structure and soundness of the financial system and its interlinkages with the rest of the economy; 2) An assessment of each countries’ financial stability policy framework, involving an evaluation of the effectiveness of financial sector supervision against international standards; and 3) An assessment of the authorities’ capacity to manage and resolve a financial crisis should the risks materialize, looking at the country’s liquidity management framework, financial safety nets, crisis preparedness and crisis resolution frameworks.

“The FSAP program has been a key tool for analyzing the strengths and weaknesses of the financial systems of IMF member countries. This is why more than three-quarters of the Fund’s members have volunteered for these assessments, some more than once. However, the recent crisis has made clear the need for mandatory and regular assessments of financial stability for countries with large and interconnected financial systems. The Board’s decision represents an important part of the international community’s response to the recent crisis and will buttress our ability to exercise surveillance over a key aspect of the global economic machinery – the financial system,” said John Lipsky, First Deputy Managing Director of the IMF.

A total of 25 jurisdictions were identified as having systemically important financial sectors, based on a methodology that combines the size and interconnectedness of each country’s financial sector.

They are in alphabetical order: Australia, Austria, Belgium, Brazil, Canada, China, France, Germany, Hong Kong SAR, Italy, Japan, India, Ireland, Luxembourg, Mexico, the Netherlands, Russia, Singapore, South Korea, Spain, Sweden, Switzerland, Turkey, the United Kingdom, and the United States.

This group of countries covers almost 90 percent of the global financial system and 80 percent of global economic activity. It includes 15 of the Group of 20 member countries, and a majority of members of the Financial Stability Board, which has been working with the IMF on monitoring compliance with international banking regulations and standards. Each country on this list will have a mandatory financial stability assessment every five years. Countries may undergo more frequent assessments, if appropriate, on a voluntary basis. The methodology and list of jurisdictions will be reviewed periodically to make sure it continues to capture the countries with the most systemically important financial sectors that need to be covered by regular, in-depth, mandatory financial stability assessments.

“Going forward, regular stability assessments of systemically important financial sectors should contribute to a deeper the public understanding of the risks to economic stability arising from the financial sector. Financial instability can have a major impact on economic activity and job creation.” Mr. Lipsky said. “At the same time, we are committed—with the World Bank—to ensuring that this new mandate does not crowd out FSAP assessments in other countries.”

 

From IMF Survey : IMF Broadens Financial Surveillance

New methods for new risks

In the wake of the crisis, the IMF has strengthened the framework for surveillance of countries’ financial systems.

In 2010, the IMF made financial sector assessments mandatory for the countries with most important financial sectors in the global system, initially 25 and now 29.

The IMF is also focusing on how problems in one country can affect others, and on the connections between financial institutions. The IMF, among others, has developed what are known as network models to try and understand how events in one financial institution, market, or country will impact others.

Given the growing reach of global banks, the IMF also closely examines cross-border supervisory cooperation arrangements. In countries where foreign-owned banks are systemically important, it is essential that the host country supervisor has enough tools and good communications with the parent banks’ regulators.

Last December, the IMF Board reviewed the methodology that determines whether a country’s financial sector is systemically important. In light of the experience since the crisis, it agreed to place even more emphasis on the connections between financial sectors and institutions, expand the coverage of cross-border linkages to cover not only banking but also equity and debt exposures, and capture the potential for pure price contagion. Based on these revamped criteria, the IMF added the four countries to the original 25.

 

From Systemic Risk: From measurement to the New Financial Stability Agenda

interinter-2inter-3

 

Broad coverage of possible cross-border transmission channels for shocks:

  1. Banking claims (BIS Locational Statistics)
  2. Debt portfolio holdings (IMF CPIS Data)
  3. Equity portfolio holdings  (IMF CPIS Data)
  4. Price effects (“contagion”) (MSCI Price Indices)

 

Key Terms:

  •  FSAP – Financial Sector Assessment Program
  • IMF – International Monetary Fund
  • FSB – Financial Stability Board
  • BIS – Bank for International Settlements
  • FSSA – Financial Sector Stability Assessment

 

 

Key Sources of Research :

 

The Financial Sector Assessment Program (FSAP)

http://www.imf.org/About/Factsheets/Sheets/2016/08/01/16/14/Financial-Sector-Assessment-Program?pdf=1

 

 

MANDATORY FINANCIAL STABILITY ASSESSMENTS UNDER THE FINANCIAL SECTOR ASSESSMENT PROGRAM: UPDATE

2013

Click to access 111513.pdf

 

 

IMF Survey: Top 25 Financial Sectors to Get Mandatory IMF Check-Up

2010

http://www.imf.org/external/pubs/ft/survey/so/2010/NEW092710A.htm

 

 

The Financial Sector Assessment Program (FSAP)

http://www.imf.org/external/np/exr/facts/fsap.htm

 

 

Press Release: IMF Executive Board Reviews Mandatory Financial Stability Assessments Under the Financial Sector Assessment Program

2014

http://www.imf.org/external/np/sec/pr/2014/pr1408.htm

 

 

IMF Survey : IMF Broadens Financial Surveillance

 

2015

http://www.imf.org/en/News/Articles/2015/09/28/04/53/sopol011314a

 

 

Strengthening Surveillance—Lessons from the Financial Crisis

 

http://www.imf.org/external/np/pp/eng/2010/082710.pdfhttp://www.imf.org/external/np/exr/facts/refsurv.htm

 

 

External Sector Report

 

Click to access 062614.pdf

 

 

Identifying Global Systemically Important Financial Institutions

Mustafa Yuksel

 

Click to access bu-1214-8.pdf

 

 

A Comparison of U.S. and International Global Systemically Important Banks

by Paul Glasserman and Bert Loudis

 

Click to access OFRbr-2015-07_A-Comparison-of-US-and-International-Global-Systemically-Important-Banks.pdf

 

 

Integrating Stability Assessments Under the Financial Sector Assessment Program into Article IV Surveillance: Background Material

Prepared by the Monetary and Capital Markets Department Approved by José Viñals

August 27, 2010

 

Click to access 082710a.pdf

 

 

Integrating Stability Assessments Under the Financial Sector Assessment Program into Article IV Surveillance

Prepared by the Monetary and Capital Markets, Legal, and Strategy, Policy, and Review Departments

Approved by José Viñals, Reza Moghadam, and Sean Hagan August 27, 2010

 

Click to access 082710.pdf

 

 

The geographical composition of national external balance sheets: 1980–2005

Chris Kubelec and Filipa Sá

March 2010

Click to access wp384.pdf

 

 

The role of external balance sheets in the financial crisis

Yaser Al-Saffar, Wolfgang Ridinger and Simon Whitaker

Click to access fs_paper24.pdf

 

 

Evidence on Financial Globalization and Crisis: Geographic/Bilateral External Balance Sheets

Filipa Sá

August 3, 2010

Click to access cwpe1038.pdf

 

 

Bilateral Financial Linkages and Global Imbalances: a View on The Eve of the Financial Crisis

Gian Maria Milesi-Ferretti, Francesco Strobbe, and Natalia Tamirisa

2010

 

Click to access wp10257.pdf

 

 

International banking centres: a network perspective

Goetz von Peter

2007

 

Click to access r_qt0712e.pdf

 

 

Financial Sector Assessment Program: an Update

Presented by Mario Guadamillas and Christine Sampic

October 18-22, 2010

 

Click to access Guadamillas_Sampic_FSAP.pdf

 

 

 

Systemic Risk: From measurement to the New Financial Stability Agenda

Jorge A. Chan-Lau

April 4, 2014

 

Click to access Chan_lau_4avril2014.pdf

 

 

Changing Perceptions of Systemic Risk in Financial Regulation

Caroline Bradley

 

Click to access riskparadigmshift.0061.pdf

Balance Sheets, Financial Interconnectedness, and Financial Stability – G20 Data Gaps Initiative

Balance Sheets, Financial Interconnectedness, and Financial Stability – G20 Data Gaps Initiative

 

From G-20 Data Gaps Initiative II: Meeting the Policy Challenge

In 2009, the G-20 Finance Ministers and Central Bank Governors (FMCBG) endorsed 20 recommendations to address data gaps revealed by the global financial crisis. The initiative, aimed at supporting enhanced policy analysis, is led by the Financial Stability Board (FSB) and the International Monetary Fund (IMF). The Inter-Agency Group on Economic and Financial Statistics (IAG)1 plays the global facilitator role to coordinate and monitor the implementation of the DGI recommendations.

The financial crisis which started in 2007 with problems in the U.S. subprime market, spread to the rest of the world becoming the most severe global crisis since the Great Depression. One difference between the global financial crisis and earlier post-war crises was that the crisis struck at the heart of the global financial system spreading throughout the global economy. This required global efforts for recovery. As one element of the global response, in October 2009, the G-20 Finance Ministers and Central Bank Governors (FMCBG) endorsed a DGI led by the Financial Stability Board (FSB) Secretariat and the IMF Staff. DGI was launched as an overarching initiative of 20 recommendations to address information gaps revealed by the global financial crisis.

Following the global financial crisis, in 2008, the G-20 leaders, at their meeting in Washington,9 committed to implement a fundamental reform of the global financial system to strengthen financial markets and regulatory regimes so as to avoid future crises.10 As part of the reform agenda, the FSB was established in April 2009 as the successor to the Financial Stability Forum (FSF) and started working as the central locus of coordination to take forward the financial reform program as developed by the relevant bodies. The obligations of members of the FSB were set to include agreeing to undergo periodic peer reviews, using among other inputs IMF/World Bank Financial Sector Assessment Program (FSAP) reports. The G-20 leaders noted the importance of global efforts in implementing the global regulatory reform so as to protect against adverse cross-border, regional and global developments affecting international financial stability.

The components of the G-20 regulatory reform agenda complement each other with an ultimate goal of strengthening the international financial system. The DGI has been an important element of this agenda as the regulatory reform agenda items mostly require better data. The collection of data on Global Systemically Important Banks’ (G-SIBs) exposures and funding dependencies is among the steps towards addressing the “too-big-to-fail” issue by reducing the probability and impact of G-SIBs’ failing. The FSB work on developing standards and processes for global data collection and aggregation on securities financing transactions aims to improve transparency in securitization towards the main goal of reducing risks related to the shadow banking system. Over-the-counter (OTC) derivatives markets including Credit Default Swap (CDS) were brought under greater scrutiny towards the main goal of making derivatives markets safer following the global crisis. DGI supported this goal by improving information in CDS markets. A number of other G-20 initiatives have strong links with the DGI project including the FSB work on strengthening the oversight and regulation of the shadow banking system; and on the work on global legal entity identifiers (LEI)11 which contribute to the robustness of the data frameworks with a more micro focus. The changing global regulatory reforms particularly the implementation of Basel III was also taken into consideration in the development of the DGI.

Surveillance Agenda

The importance of closing the data gaps hampering the surveillance of financial systems was also highlighted as part of the IMF’s 2014 Triennial Surveillance Review (TSR).12 The 2014 TSR emphasized that due to growing interconnectedness across borders, financial market shocks will continue to have significant spillovers via both capital flows and shifts in risk positions. Also, new dimensions to interconnectedness will continue to emerge such as through the potential short-run adverse spillovers generated by the financial regulatory reforms. To this end, the TSR recommended improving information on balance-sheets and enriching flow-of funds data. The IMF has overhauled its surveillance to make it more risk-based. To this end, the IMF Managing Director’s Action Plan for Strengthening Surveillance following the 2014 TSR13 underlined that the IMF will revive and adapt the Balance Sheet Approach (BSA) to facilitate a more in-depth analysis of the impact of shocks and their transmission across sectors, and possibly initiate the global flow of funds to better reflect global interconnections (Box 1). This work requires data from the DGI as it will help support the IMF’s macro-financial work including in the key exercises and reports (i.e., Early Warning Exercise, FSAP, and GFSR).

Global Flow of Funds

Through the use of internationally-agreed statistical standards, data on cross-border financial exposures (IBS, CPIS, and Coordinated Direct Investment Survey (CDIS)) can be linked with the domestic sectoral accounts data to build up a comprehensive picture of financial interconnections domestically and across borders, with a link back to the real economy through the sectoral accounts. This work is known as the “Global Flow of Funds (GFF).”14 The GFF project is mainly aimed at constructing a matrix that identifies interlinkages among domestic sectors and with counterpart countries (and possibly counterpart country sectors) to build up a picture of bilateral financial exposures and support analysis of potential sources of contagion. The concept of the GFF was first outlined in the Second Progress Report on the G-20 Data Gaps Initiative and initiated in 2013 as part of a broader IMF initiative aimed at strengthening the analysis of interconnectedness across borders, global liquidity flows and global financial interdependencies. In the longer term, the GFF matrix is intended to support regular monitoring of bilateral cross-border financial positions through a framework that highlight risks to national and international financial stability. IMF Staff is working towards developing a GFF matrix starting with the largest global economies.

 

How Does the DGI Address the Surveillance Agenda?

As noted above, in the wake of the 2014 TSR the IMF Managing Director published an Action Plan for Strengthening Surveillance. Among the actions to be taken was that “The Fund will revive and adapt the balance sheet approach to facilitate a more in-depth analysis of the impact of shocks and their transmission across sectors.” This responded to a call from outside experts David Li and Paul Tucker in their external study for the 2014 TSR on risks and spillovers.37

Sectoral Analysis

Even though the 2007/2008 crisis emerged in the financial sector, given its intermediary role, the problems in the financial sector also affected other sectors of an economy. To this end, analysis of balance sheet exposures is essential given the increasingly interconnected global economy. As it is pointed out in the IMF TSR 2014, the use of balance sheets to identify sources of vulnerability and the transmission of shocks, could have helped detect risks associated with European banks’ reliance on U.S. wholesale funding to finance structured products. In June 2015, the IMF set out the way forward in a paper for the IMF Executive Board on Balance Sheet Analysis in Surveillance. 38 Sectoral accounts and balance sheet data are essential, including from-whom to-whom data, in providing the context for an assessment of the links between the real economy and financial sectors. The sectoral balance sheets of the SNA is seen as the overarching framework for balance sheet analysis as the IMF Executive Board paper makes clear. Further, the paper sets out a data framework for such analysis.39 Putting the sectoral balance sheets of the SNA in a policy context, the IMF has developed a BSA, which compiles all the main balance sheets in an economy using aggregate data by sector. The BSA is based on the same conceptual principles as the sectoral accounts, providing information on a from-whom-to-whom basis with an additional focus on vulnerabilities arising from maturity and, currency mismatches as well as the capital structure of economic sectors.

While currently not that many economies compile from-whom-to-whom balance sheet data, BSA data can be compiled from the IMF’s Standardized Report Forms, IIP, and government balance sheet data—a more limited set of data than needed to compile the sectoral accounts. The DGI-2 recommendations address key data gaps that act as a constraint on a full-fledged balance sheet analysis. The DGI recommends addressing such gaps through improving G-20 economies’ dissemination of sectoral accounts and balance sheets building on 2008 SNA, including for the non-financial corporate and household sectors. (Annex 1, Recommendation II.8) Given the multifaceted character of the datasets, implementation of this recommendation is challenging and progress has been slow. However, all G-20 economies agree on the importance of having such information and have plans in place to make it happen.

Understanding Cross-border Financial Interconnections

The crisis emphasized the fact that it is not possible to isolate the problems in a single financial system as shocks propagate rapidly across the financial systems. Indeed, the IMF, since 2010, has been identifying jurisdictions with systemically important financial sectors based on a set of relevant and transparent criteria including size and interconnectedness. Within this identification framework, cross-border interconnectedness is considered an important complementary measure to the size of the economy: it captures the systemic risk that can arise through direct and indirect interlinkages among financial sectors in the global financial system (i.e., the risk that failure or malfunction of a national financial system may have severe repercussions on other countries or on overall systemic stability.48 The 2014 TSR summed up the issue succinctly in its Executive Summary: “Risks and spillovers remain first-order issues for the world economy and should be central to Fund surveillance. Recent reforms have made surveillance more risk-based, helping to better capture global interconnections. Experience so far also points to the need to build a deeper understanding of how risks map across countries, and how spillovers can quickly spread across sectors to expose domestic vulnerabilities.”49 Four existing datasets that include key information on cross-country financial linkages are the IIP, BIS IBS, IMF CPIS and IMF CDIS. Together these datasets provide a comprehensive picture of cross-border financial interconnections. This picture is especially relevant for policy makers as financial connections strengthen across border and domestic conditions are affected by financial developments in other economies to whom they are closely linked financially. DGI-2 focuses on improving the availability and cross-country comparability of these datasets (Annex1, Recommendations II.10, 11, 12 and 13). The well-known IIP is a key data source to understanding the linkages between the domestic economy and the rest of the world by providing information on both external assets and liabilities of the economy with a detailed instrument breakdown. However, the crisis revealed the need for currency and more detailed sector breakdowns, particularly for the other financial corporations (OFCs) sector. Consequently, as part of the DGI, the IIP was enhanced to support these policy needs. Significant progress has also been made in ensuring regular reporting of IIP along with the increase in frequency of reporting from annual to quarterly. By end-2015 virtually all G-20 economies reported quarterly IIP data. The IBS have been a key source of data for many decades providing information on aggregate assets and liabilities of internationally active banking systems on a quarterly frequency. The CPIS data, while on an annual frequency, provided significant insights into portfolio investment assets. That said, both datasets had limitations in terms of country coverage and granularity. CPIS also needed to be improved in terms of frequency and timeliness. To this end, the DGI supported the enhancements in these datasets.

 

Key Terms:

  • G-20 Data Gaps Initiative (DGI)
  • Financial Stability Board (FSB)
  • The Inter-Agency Group on Economic and Financial Statistics (IAG)
  • Finance Ministers and Central Bank Governors (FMCBG)
  • Financial Stability Forum (FSF)
  • Global Systemically Important Banks (G-SIBs)
  • Over-the-counter (OTC)
  • Credit Default Swap (CDS)
  • Global legal entity identifiers (LEI)
  • IMF Triennial Surveillance Review (TSR)
  • IMF Balance Sheet Approach (BSA)
  • IMF Global Flow of Funds (GFF)
  • IMF IIP (International Investment Positions)
  • BIS IBS (International Banking Statistics)
  • IMF CPIS (Coordinated Portfolio Investment Survey)
  • IMF CDIS (Coordinated Direct Investment Survey)
  • IMF GFSR ( Global Financial Stability Report)

 

Other Related Terms:

  • Global Systemically Important Financial Institutions (G-SIFIs )
  • GLOBAL SYSTEMICALLY IMPORTANT INSURERS (G-SIIS)
  • Systemically Important Financial Market Utilities (G-FMUs)
  • Nonbank Financial Companies (G-SINFC)
  • Financial Stability Oversight Council (FSOC)

     

The IAG members are

  • BIS (Bank of International Settlements)
  • G20 (Group of 20 Nations)
  • IMF (International Monetary Fund)
  • OECD (Organisation for Economic Co-operation and Development)
  • ECB (European Central Bank)
  • World Bank
  • Eurostat (European Statistics/Directorate-General of the European Commission)
  • UN (United Nations)

 

From G-20 Data Gaps Initiative II: Meeting the Policy Challenge

balancesheets

From G-20 Data Gaps Initiative II: Meeting the Policy Challenge

dgi

 

Progress of DGI ((DGI-I and DGI-II)

From G-20 Data Gaps Initiative II: Meeting the Policy Challenge

The first phase of the DGI was successfully concluded in September 2015 and the second phase of the initiative (DGI-2) was endorsed by the G-20 FMCBG. The key objective of the DGI-2 is to implement the regular collection and dissemination of comparable, timely, integrated, high quality, and standardized statistics for policy use. DGI-2 encompasses 20 new or revised recommendations, focused on datasets that support: (i) monitoring of risk in the financial sector; and (ii) analysis of vulnerabilities, interconnections and spillovers, not least cross-border.

Following the significant progress in closing some of the information gaps identified during the global financial crisis of 2007/08, the G-20 FMCBG endorsed, in September 2015, the closing of DGI-1. During the six-year implementation of DGI-1, significant achievements were obtained, particularly regarding the development of conceptual frameworks, as well as enhancements in some statistical collection and reporting. Regarding the latter, more work is needed for the implementation of some recommendations, especially in seven high-priority areas across G-20 economies, notably in government finance statistics and sectoral accounts and balance sheets.

In September 2015, the G-20 FMCBG also endorsed the launch of the second phase of the DGI. The main objective of DGI-2 is to implement the regular collection and dissemination of reliable and timely statistics for policy use. Its twenty recommendations are clustered under three main headings: (1) monitoring risk in the financial sector, (2) vulnerabilities, interconnections and spillovers, and (3) data sharing and communication of official statistics. The DGI-2 maintains the continuity with the DGI-1 recommendations while setting more specific objectives with the intention for the G-20 economies to compile and disseminate minimum common datasets for these recommendations. The DGI-2 also includes new recommendations to reflect the evolving users’ needs. Furthermore, the DGI-2 aims at strengthening the synergies with other relevant global initiatives.

The DGI-2 facilitates closing data gaps that are policy-relevant. By achieving its main objective, the DGI-2 will be instrumental in closing gaps in policy-relevant data. Most of the datasets covered by the DGI-2 are particularly relevant for meeting the emerging macro- financial policy needs, including the analysis of international positions, global liquidity, foreign currency exposures, and capital flows volatility.

The DGI-2 introduces action plans that set out specific “targets” for the implementation of its twenty recommendations through the five-year horizon of the initiative. The action plans acknowledge that countries may be at different stages of statistical development and take into account national priorities and resource constraints. The DGI-2 intends to bring the G-20 economies at higher common statistical standards through a coordinated effort; however, flexibility will be considered in terms of intermediate steps to achieve the targets based on national priorities, resource constraints, emerging data needs, and other considerations.

 

 

 

Key Sources of Research:

 

Second Phase of the G-20 Data Gaps Initiative (DGI-2) Second Progress Report

 

Prepared by the Staff of the IMF and the FSB Secretariat September 2017

Click to access 092117.pdf

http://www.imf.org/external/ns/cs.aspx?id=290

 

 

 

Second Phase of the G-20 Data Gaps Initiative (DGI-2) First Progress Report

 

Prepared by the Staff of the IMF and the FSB Secretariat September 2016

 

Click to access 090216.pdf

 

 

Sixth Progress Report on the Implementation of the G-20 Data Gaps Initiative

 

Prepared by the Staff of the IMF and the FSB Secretariat September 2015

 

Click to access The-Financial-Crisis-and-Information-Gaps.pdf

 

 

Fifth Progress Report on the Implementation of the G-20 Data Gaps Initiative

 

Prepared by the Staff of the IMF and the FSB Secretariat September 2014

Click to access 5thprogressrep.pdf

 

 

Fourth Progress Report on the Implementation of the G-20 Data Gaps Initiative

 

Prepared by the Staff of the IMF and the FSB Secretariat September 2013

 

Click to access 093013.pdf

 

 

 

Progress Report on the G-20 Data Gaps Initiative: Status, Action Plans, and Timetables

 

Prepared by the Staff of the IMF and the FSB Secretariat September 2012

Click to access 093012.pdf

 

 

 

Implementation Progress Report

 

Prepared by the IMF Staff and the FSB Secretariat June 2011

Click to access 063011.pdf

 

 

 

Progress Report Action Plans and Timetables

 

Prepared by the IMF Staff and the FSB Secretariat May 2010

 

Click to access 053110.pdf

 

 

 

Report to the
G-20 Finance Ministers and Central Bank Governors

 

Prepared by the IMF Staff and the FSB Secretariat October 29, 2009

 

Click to access 102909.pdf

 

 

 

G-20 Data Gaps Initiative II: Meeting the Policy Challenge

by Robert Heath and Evrim Bese Goksu

2016

Click to access wp1643.pdf

 

 

 

Why are the G-20 Data Gaps Initiative and the SDDS Plus Relevant for Financial Stability Analysis?

Robert Heath

Click to access wp1306.pdf

 

 

 

Toward the Development of Sectoral Financial Positions and Flows in a From-Whom-to-Whom Framework

Manik Shrestha

 

Click to access c12835.pdf

 

 

An Integrated Framework for Financial Positions and Flows on a From-Whom-to- Whom Basis: Concepts, Status, and Prospects

Manik Shrestha, Reimund Mink, and Segismundo Fassler

 

Click to access wp1257.pdf

 

 

Financial investment and financing in a from-whom-to-whom framework

Mink, Reimund

Click to access 2011_dublin_61_01_mink.pdf

 

 

Users Conference on the Financial Crisis and Information Gaps

Conference co-hosted by The International Monetary Fund and The Financial Stability Board

2009

http://www.imf.org/external/np/seminars/eng/2009/usersconf/index.htm

 

 

A Status on the Availability of Sectoral Balance Sheets and Accumulation Accounts in Advanced Economies not Represented by Membership in the G-20

2011

 

Click to access g20a.pdf

 

 

A Status on the Availability of Sectoral Balance Sheets and Accumulation Accounts in G-20 Economies

2011

 

Click to access g20b.pdf

 

 

AN UPDATE ON THE IMF-OECD CONFERENCE ON STRENGTHENING SECTORAL POSITION AND FLOW DATA IN THE MACROECONOMIC ACCOUNTS

FEBRUARY 28 – MARCH 2, 2011

 

http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=COM/STD/DAF(2010)21&docLanguage=En

 

 

The Balance Sheet Approach:
Data Needs, Data at Hand, and Data Gaps (August 2009)

 

Alfredo Leone, Statistics Department, International Monetary Fund

 

Click to access leone_paper.pdf

 

 

Development of financial sectoral accounts

New opportunities and challenges for supporting financial stability analysis

by Bruno Tissot

2016

 

Click to access ifcwork15.pdf

 

 

A Flow-of-Funds Perspective on the Financial Crisis Volume I: Money, Credit

edited by B. Winkler, A. van Riet, P. Bull, Ad van Riet

 

 

A Flow-of-Funds Perspective on the Financial Crisis Volume II: Macroeconomic

edited by B. Winkler, A. van Riet, P. Bull

 

 

Financial investment and financing in a from-whom-to-whom framework

Mink, Reimund

2011

Click to access 650287.pdf

 

 

Expanding the Integrated Macroeconomic Accounts’ Financial Sector

By Robert J. Kornfeld, Lisa Lynn, and Takashi Yamashita

2016

Click to access 0116_expanding_the_integrated_macroeconomic_accounts_financial_sector.pdf

 

 

Using the Balance Sheet Approach in Surveillance: Framework, Data Sources, and Data Availability

Johan Mathisen and Anthony Pellechio

2006

Click to access wp06100.pdf

 

 

Balance Sheet Analysis: A New Approach to Financial Stability

Surveillance

By Jean Christine A. Armas

2016

 

Click to access EN16-01.pdf

 

 

USING THE BALNCE SHEET APPROACH IN FINANCIAL STABILITY SURVEILLANCE:
Analyzing the Israeli economy’s resilience to exchange rate risk

 

Click to access JFS2007_HaimLevy_pres.pdf

Click to access dp0701e.pdf

 

 

 

A Balance Sheet Approach to Financial Crisis

Mark Allen, Christoph Rosenberg, Christian Keller, Brad Setser, and Nouriel Roubini

2002

Click to access wp02210.pdf

 

 

THE BALANCE SHEET APPROACH TO FINANCIAL CRISES IN EMERGING MARKETS

Giovanni Cozzi and
Jan Toporowski

2006

Click to access wp_485.pdf

 

 

Balance-sheets. A financial/liability approach

Bo Bergman

2015

 

Click to access bergman_paper.pdf

 

 

Understanding Financial Crisis Through Accounting Models

Dirk J Bezemer

2009

Click to access Bezemer_-_No_one_show_this_comming.pdf

 

 

 

Schumpeter Might Be Right Again: The Functional Differentiation of Credit

Dirk J. Bezemer
University of Groningen

Click to access the_functional_differentiation_of_credit.pdf

 

 

Causes of Financial Instability: Don’t Forget Finance

Dirk J. Bezemer

April 2011

 

Click to access wp_665.pdf

 

 

THE ECONOMY AS A COMPLEX SYSTEM: THE BALANCE SHEET DIMENSION

DIRK J BEZEMER

2012

Click to access ACS_1250047_1st_Prf.pdf

 

 

Did Credit Decouple from Output in the Great Moderation?

Maria Grydaki and Dirk Bezemer

June 2013

Click to access MPRA_paper_47424.pdf

 

 

 

Towards an ‘accounting view’ on money, banking and the macroeconomy: history, empirics, theory

Dirk J. Bezemer

2016

Click to access Camb._J._Econ.-2016-Bezemer-1275-95.pdf

 

 

Modelling systemic financial sector and sovereign risk

Dale F. Gray anD anDreas a. Jobst

2011

 

Click to access Gray_2.pdf

 

 

BALANCE SHEET ANALYSIS IN FUND SURVEILLANCE

2015

Click to access 061215.pdf

Click to access 071315.pdf

 

 

The role of external balance sheets in the financial crisis

Yaser Al-Saffar, Wolfgang Ridinger and Simon Whitaker

2013

 

Click to access fs_paper24.pdf

 

 

Global Conferences on DGI

June 2, 2016

http://www.imf.org/external/np/seminars/eng/dgi/

 

 

CAPITAL FLOWS AND GLOBAL LIQUIDITY

IMF Note for G20 IFA WG

February 2016

 

Click to access P020160811536051676178.pdf

 

 

Introduction to Balance of Payments and International Investment Position Manual, 6th Edition and BPM6 Compilation Guide

Click to access Link3_766_105.pdf

 

 

Introduction: ‘cranks’ and ‘brave heretics’: rethinking money and banking after the Great Financial Crisis

Geoffrey Ingham Ken Coutts Sue Konzelmann

Camb J Econ (2016) 40 (5): 1247-1257.

 

 

Network Analysis of Sectoral Accounts: Identifying Sectoral Interlinkages in G-4 Economies

by Luiza Antoun de Almeida

2016

Click to access wp15111.pdf

 

 

2014 TRIENNIAL SURVEILLANCE REVIEW—EXTERNAL STUDY—RISKS AND SPILLOVERS

Prepared By David Daokui Li and Paul Tucker

 

Click to access 073014e.pdf

Click to access 14-10.pdf

 

 

 

2014 TRIENNIAL SURVEILLANCE REVIEW—OVERVIEW PAPER

 

Click to access 073014.pdf

http://www.imf.org/external/np/spr/triennial/2014/

 

 

Measuring Global Flow of Funds and Integrating Real and Financial Accounts: Concepts, Data Sources and Approaches

Nan Zhang (Stanford University)

2015

Click to access zhang.pdf

 

 

Cross-border financial linkages: Identifying and measuring vulnerabilities

 

Philip R. Lane

2014

 

Click to access PolicyInsight77.pdf

 

 

Global Flow of Funds: Mapping Bilateral Geographic Flows

Authors1: Luca Errico, Richard Walton, Alicia Hierro, Hanan AbuShanab, Goran Amidzic

 

2013

Click to access STS083-P1-S.pdf

 

Global-Flow-of-Funds Analysis in a Theoretical Model -What Happened in China’s External Flow of Funds –

 

Nan Zhang

 

Click to access 08GFOF.pdf

 

 

Mapping the Shadow Banking System through a Global Flow of Funds Analysis

Hyun Song Shin

Princeton University

Click to access Hyun-Song-Shin2.pdf

 

 

The Composition of the Global Flow of Funds in East Asia

 

Nan Zhang

 

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.534.757&rep=rep1&type=pdf

 

 

What Has Capital Flow Liberalization Meant for Economic and Financial Statistics?

Robert Heath

2015

Click to access 41aac8864e53b6176f7b3b7df22aba05ac0e.pdf

 

 

Global flows in a digital age: How trade, finance, people, and data connect the world economy

McKinsey & Company Report

2014

 

 

Managing global finance as a system

Speech given by

Andrew G Haldane, Chief Economist, Bank of England

At the Maxwell Fry Annual Global Finance Lecture, Birmingham University 29 October 2014

Click to access speech772.pdf

A Brief History of Macro-Economic Modeling, Forecasting, and Policy Analysis

A Brief History of Macro-Economic Modeling, Forecasting, and Policy Analysis

 

From A History of Macroeconomics from Keynes to Lucas and Beyond

history-of-macro

 

From Modern Macroeconomic Models as Tools for Economic Policy

I believe that during the last financial crisis, macroeconomists (and I include myself among them) failed the country, and indeed the world. In September 2008, central bankers were in desperate need of a playbook that offered a systematic plan of attack to deal with fast- evolving circumstances. Macroeconomics should have been able to provide that playbook. It could not. Of course, from a longer view, macroeconomists let policymakers down much earlier, because they did not provide policymakers with rules to avoid the circumstances that led to the global financial meltdown.

Because of this failure, macroeconomics and its practitioners have received a great deal of pointed criticism both during and after the crisis. Some of this criticism has come from policymakers and the media, but much has come from other economists. Of course, macroeconomists have responded with considerable vigor, but the overall debate inevitably leads the general public to wonder: What is the value and applicability of macroeconomics as currently practiced?

 

There have been several criticisms of Main stream Economic Modeling from economists such as

  • Paul Romer
  • Willem H Buiter
  • Paul Krugman
  • R Cabellero
  • William White
  • Dirk Bezemer
  • Steve Keen
  • Jay Forrester
  • Lavoie and Godley

 

Issues with Neo Classical Models

  • No role of Money, Credit  and Finance
  • Lack of Interaction between Real and Financial sectors
  • Lack of Aggregate Demand
  • Rational Expectations and others.

 

Orthodox and Heterodox Modeling

  • Input Output Equations Models – Inter Industry Analysis
  • Structural Models
  • CGE and DSGE Models
  • VAR ( Vector Auto Regression ) Models
  • Stock flow Consistent Models
  • System Dynamics models

 

Neoclassical Models

  • Structural
  • VAR after Lucas Critique
  • DSGE (Dynamic Stochastic General Equilibrium Models)
  • DSGE – VAR

 

From HISTORY OF MACROECONOMETRIC MODELLING: LESSONS FROM PAST EXPERIENCE

The origin of macroeconometric modelling dates back to after World War II when Marschak organised a special team at the Cowles Commission by inviting luminaries such as Tjalling Koopmans, Kenneth Arrow, Trygve Haavelmo, T.W. Anderson, Lawrence Klein, G. Debreu, Leonid Hurwitz, Harry Markowitz, and Franco Modigliani (Diebold, 1998).

An interesting feature of macro modelling in this group was that there were three divisions to undertake the modelling procedures: first, economic theory or model specification; second, statistical inference (including model estimation, diagnostic tests and applications); and third, model construction which was dealing with data preparation and computations. The use of a team approach in macroeconometric modelling has been regarded as both cause and effect of large scale macroeconometric modelling (Intriligator, Bodkin and Hsiao, 1996).

Klein joined this team and conducted his first attempt in the mid 1940s to build a MEM for the US economy. See Klein (1983), Bodkin, Klein and Marwah (1991) and Intriligator, Bodkin and Hsiao (1996) for discussions of the MEMs which have been constructed for developed countries such as

  • the Klein interwar model,
  • the Klein-Goldberger model,
  • the Wharton model,
  • the DRI (Data Resources. Inc.) model,
  • the CANDIDE model,
  • the Brooking model etc.

 

 

History of Early Models

A. Klein Interwar Model

  • MODEL I
  • MODEL II
  • MODEL III
  • Developed in late 1940s

B. Klein -Goldberger Model

  • Developed at University of Michigan in 1950s.  Annual forecasts

C. BEA Model

  • Developed by L Klein.  Quarterly.  Operational in 1961. Transferred to BEA.  Eventually became BEA model.

D. Wharton Model

  • WHAR – III, with Anticipations
  • WHAR – MARK III
  • WHAR -ANNUAL
  • WEFA,  Project LINK
  • Wharton models were constantly operated until 2001.  DRI and WEFA merged to form Global Insight, Inc.

E. DRI Model

  • Built in 1969.  by Data Resources inc.  by Eckstein, Fromm, and Duessenbury.

F. Brookings Model

  • Developed by L Klein and J.S. Duessenberry. .  Quarterly.

G. MPS Model

  • FRB-MIT Model

H. The Hickman – Coen Model

  • Developed by Hickman and Coen for long term forecasting

I. FAIR model

  • Developed by Ray Fair at Princeton.  Now at Yale.  Available for free.

J. The St. Louis Model

  • Developed by FRB/ST.Louis

K. Michigan MQEM Model

  • Quarterly. DHL III

L. The Liu-HWA Model

  • Developed in 1970s.  Monthly.

M. WEFA -DRI/ Global Insight Model

  • Developed after merger of WEFA and DRI in 2001

N. Michigan MQEM /RSQE Model

  • Developed and extended in 1990s.  Replaced by Hymans RSQE model.

O. Current Quarterly Model

  • L Klein and Global Insight collaboration. L Klein died in 2013.

P. CANDIDE Model

  • Model developed for Canada

 

 

From Economic Theory, Model Size, and Model Purpose

models-7

 

 

From HISTORY OF MACROECONOMETRIC MODELLING: LESSONS FROM PAST EXPERIENCE

A Macro Econometric Model (MEM) is a set of behavioural equations, as well as institutional and definitional relationships representing the main behaviours of economic agents and the operations of an economy. The equations, or behavioural relations, can be empirically validated to capture the structure of a macroeconomy, and can then be used to simulate the effects of policy changes.

Macroeconometric modelling is multi- dimensional and both a science and an art. Bautista (1988) and Capros, Karadeloglou and Mentzas (1990) have classified macroeconomic models into broad groups: MEMS and CGE (computable general equilibrium) models.

Further, according to Challen and Hagger (1983, pp.2-22) there are five varieties of MEMs in the literature:

  • the KK (Keynes- Klein) model,
  • the PB (Phillips-Bergstrom) model,
  • the WJ (Walras-Johansen) model,
  • the WL (Walras-Leontief) model,
  • the MS (Muth-Sargent) model.

The KK model is mainly used by model builders in developing countries to explain the Keynesian demand-oriented model of macroeconomic fluctuations. They deal with the problems of short-run instability of output and employment using mainly stabilisation policies. The basic Keynesian model has been criticised as it does not consider the supply side and the incorporation of production relations. Furthermore, this modelling approach does not adequately capture the role of the money market, relative prices and expectations. As a response to the shortcomings associated with the KK model, the St Louis model was constructed by the monetarist critics (Anderson and Carlson, 1970) in order to highlight the undeniable impacts of money on the real variables in the economy.

The second type of MEM, the PB, emerged in the literature when Phillips (1954, 1957) used both the Keynesian and the Neoclassical theories within a dynamic and continuous time model to analyse stabilisation policy. Although the PB model is also a demand-oriented model, differential or difference equations are used to estimate its stochastic structural parameters. In essence, the steady state and asymptotic properties of models are thus examined in a continuous time framework. One should note that this modelling method in practice becomes onerous to implement especially for large scale models.

The third type of MEM, the WJ, can be referred to as a multi-sector model in which the economy is disaggregated into various interdependent markets, each reaching an equilibrium state by the profit maximising behaviour of producers and utility maximising actions of consumers in competitive markets. Similar to an input-output (IO) approach, different sectors in the WJ model are linked together via their purchases and sales from, and to, each other. However, it is different from an IO model as it is highly non-linear and uses logarithmic differentiation.

The fourth type of MEMs, known as the WL model, has been widely considered as the more relevant MEM for developing countries (Challen and Hagger, 1983). The WL model incorporates an IO table into the Walrasian general equilibrium system, enabling analysts to obtain the sectoral output, value added or employment given the values of the sectoral or aggregate final demand components.

Finally, the foundations of the MS model are based on the evolution of the theory of rational expectations. The MS model is similar to the KK model in that they both are dynamic, non-linear, stochastic and discrete. But in this model the formation of expectations is no longer a function of previous values of dependent variables. The forward looking expectation variables can be obtained only through solving the complete model. The New Classical School demonstrated the role of the supply side and expectations in a MEM with the aim of highlighting the inadequacy of demand management policies. To this end, Sargent (1976) formulated forward-looking variants of this model which suggest no trade-off between inflation and unemployment in the short term, which is in sharp contrast to both the Keynesian and Monetarist modelling perspectives.

It is noteworthy that the subsequent advances in the WJ and WL models led to the formulation of CGE modelling, which is categorised here as the second type of macroeconomic model. The Neoclassical CGE models are based on the optimising behaviour of economic agents. The main objectives of CGE models are to conduct policy analysis on resource economics, international trade, efficient sectoral production and income distribution (Capros, Karadeloglou and Mentzas, 1990).

The 1960s witnessed the flowering of the large scale macroeconometric modelling. This decade saw the construction of the Brookings model, in which an input-output table was incorporated into the model. Adopting the team approach in modelling procedure in the 1970s, the majority of model builders aimed at the commercialisation of the comprehensive macro models, such as DRI, Wharton and Chase, by providing information to private enterprises. Modellers designed their models on the basis of quarterly or monthly data with the goal of keeping the models up-to-date, for commercial gain. As a consequence of taking such measures, model-builders became commercially successful (Fair, 1987). It is believed that in this era, the full-grown models “would contribute substantively to enlarging our understanding of economic processes and to solving real- world economic problems” (Sowey and Hargreaves, 1991: 600).

During the last three decades, MEMs have been internationalised via Project LINK which was first operated at the University of Pennsylvania. In 1987 according to Bodkin (1988b) Project LINK consisted of 79 MEMs of individual countries or aggregations. In Project LINK the world is treated as a closed system of approximately 20,000 equations which “allow trade, capita flows, and possible exchange rate and other repercussions to influence systematically the individual national economies” (Bodkin, 1988b: 222).

 

From STRUCTURAL ECONOMETRIC MODELLING: METHODOLOGY AND TOOLS WITH APPLICATIONS UNDER EVIEWS

Since an early date in the twentieth century, economists have tried to produce mathematical tools which, applied to a given practical problem, formalized a given economic theory to produce a reliable numerical picture. The most natural application is of course to forecast the future, and indeed this goal was present from the first. But one can also consider learning the consequences of an unforeseen event, or measuring the efficiency of a change in the present policy, or even improving the understanding of a set of mechanisms too complex to be grasped by the human mind.

In the last decades, three kinds of tools of this type have emerged, which share the present modelling market.

  •   The “VAR” models. They try to give the most reliable image of the near future, using a complex estimated structure of lagged elements, based essentially on the statistical quality, although economic theory can be introduced, mostly through constraints on the specifications. The main use of this tool is to produce short term assessments.
  •   The Computable General Equilibrium models. They use a detailed structure with a priori formulations and calibrated coefficients to solve a generally local problem, through the application of one or several optimizing behaviors. The issues typically addressed are optimizing resource allocations, or describing the consequences of trade agreements. The mechanisms described contain generally little dynamics.

This is no longer true for the Dynamic Stochastic General Equilibrium models, which dominate the current field. They include dynamic behaviors and take into account the uncertainty in economic evolutions. Compared to the traditional models (see later) they formalize explicitly the optimizing equilibria, based on the aggregated behavior of individual agents. This means that they allow agents to adapt their behavior to changes is the rules governing the behaviors of others, including the State, in principle escaping the Lucas critique. As the model does not rely on traditional estimated equations, calibration is required for most parameters.

  •  The “structural” models. They start from a given economic framework, defining the behaviors of the individual agents according to some globally consistent economic theory. They use the available data to associate to these behaviors reliable formulas, which are linked by identities guaranteeing the consistency of the whole set. These models can be placed halfway between the two above categories: they do rely on statistics, and also on theory. To accept a formula, it must respect both types of criteria.

The use of this last kind of models, which occupied the whole field at the beginning, is now restricted to policy analysis and medium term forecasting. For the latter, they show huge advantages: the full theoretical formulations provide a clear and understandable picture, including the measurement of individual influences. They allow also to introduce stability constraints leading to identified long term equilibriums, and to separate this equilibrium from the dynamic fluctuations which lead to it.

Compared to CGEs and DSGEs, optimization behaviors are present (as we shall see later) and introduced in the estimated equations. But they are frozen there, in a state associated with a period, and the behavior of other agents at the time. If these conditions do not change, the statistical validation is an important advantage. But sensitivity to shocks is flawed, in a way which is difficult to measure.

 

From Macroeconomic Modeling in the Policy Process: A Review of Tools Used at the Federal Reserve Board and Their Relation to Ongoing Research

models-1models-2models-3

 

From Macroeconomic Modeling in the Policy Process: A Review of Tools Used at the Federal Reserve Board and Their Relation to Ongoing Research

models-4

 

USA Central Bank Models

A. FRB Models (Neo Classical)

  • MPS ( MIT-PENN-FRB)
  • FRB/US (since 1996)
  • FRB/MCM
  • FRB/WORLD
  • FRB/EDO
  • SIGMA
  • VAR Models
  • Accelerator Models

B.  FRB/NY DSGE Model

C.  FRB/Chicago DSGE Model

D. FRB/Philadelphia DSGE Model – PRISM

 

 

Newer Central Bank Models

From Macroeconomic Models for Monetary Policies: A Critical Review from a Finance Perspective

There has been a remarkable evolution of macroeconomic models used for monetary policy at major central banks around the world, in aspects such as model formulation, solution methods, estimation approaches, and importantly, communication of results between central banks. Central banks have developed many different classes and variants of macroeconomic models in the hopes of producing a reliable and comprehensive analysis of monetary policy. Early types of models included quantitative macroeconomic models1, reduced-form statistical models, structural vector autore- gressive models, and large-scale macroeconometric models, a hybrid form combining the long-run structural relationships implied by a partial equilibrium treatment of theory (e.g., the decision rule for aggregate consumption) and reduced-form short-run relationships employing error-correcting equations.

Over the past 20 years in particular, there have been significant advances in the specification and estimation for New Keynesian Dynamic Stochastic General Equilibrium (New Keynesian DSGE) models. Significant progress has been made to advance policymaking models from the older static and qualitative New Keynesian style of modeling to the New Keynesian DSGE paradigm. The New Keynesian DSGE model is designed to capture real world data within a tightly structured and self-consistent macroeconomic model. The New Keynesian DSGE model has explicitly theoretical foundations, allowing it to circumvent the Sims Critique (see Sims, 1980) and the Lucas Critique (see Lucas, 1976), and therefore it can provide more reliable monetary policy analysis than earlier models. A consensus baseline New Keynesian DSGE model has emerged, one that is heavily influenced by estimated impulse response functions based on Structural Vector Autoregression (SVAR) models. In particular, a baseline New Keynesian DSGE model has recently been shown by Christiano et al. (2005) to successfully account for the effects of a monetary policy shock with nominal and real rigidities. Similarly, Smets and Wouters (2003, 2007) show that a baseline New Keynesian DSGE model can track and forecast time series as well as, if not better than, a Bayesian vector autoregressive (BVAR) model. New Keynesian DSGE models have been developed at many central banks, becoming a crucial part of many of their core models.2 Sbordone et al. (2010) have emphasized that an advantage of New Keynesian DSGE models is that they share core assumptions about the behavior of agents, making them scalable to relevant details to address the policy question at hand. For example, Smets and Wouters (2007) introduced wage stickiness and investment frictions into their model, Gertler et al. (2008) incorporated labor market search and wage bargaining, and Bernanke et al. (1999), Chari et al. (1995) and Christiano et al. (2008) studied the interaction between the financial sector and macroeconomic activity.

The devastating aftermath of the financial crisis and the Great Recession has prompted a rethink of monetary policy and central banking. Central bank monetary policy models face new challenges. Many macroeconomists (and in fact, many of the world’s leading thinkers) have called for a new generation of DSGE models. The first and foremost critique of the current state of the art of New Keynesian DSGE models is that these models lack an appropriate financial sector with a realistic interbank market, and as a result, the models fail to fully account for an important source of aggregate fluctuations, such as systemic risk. Second, the linkage between the endogenous risk premium and macroeconomic activity is crucial for policymakers to understand the transmission mechanism of monetary policy, especially in financially stressed periods. In models that lack a coherent endogenous risk premium, policy experiments become unreliable in stressed periods, and the model cannot provide a consistent framework for conducting experimental stress tests regarding financial stability or macroprudential policy. Third, heterogeneity among the players in the economy is essential to our understanding of inefficient allocations and flows between agents. These inefficiencies have an extremely important effect on the equilibrium state of the economy. Without reasonable heterogeneity among agents in models, there is no way to infer the distributional effects of monetary policy.

Finally, and perhaps most importantly in terms of government policy, a new generation of models is in strong demand to provide policymakers a unified and coherent framework for both conventional and unconventional monetary policies. For example, at the onset of the financial crisis, the zero lower bound went from a remote possibility to reality with frightening speed. This led central banks to quickly develop unconventional measures to provide stimulus, including credit easing, quantitative easing and extraordinary forward guidance. These unconventional measures demanded a proper platform to be analyzed. Furthermore, these unconventional monetary policies have blurred the boundary between monetary policy and fiscal policy. Through these policies, central banks gave preference to some debtors over others (e.g. industrial companies, mortgage banks, governments), and some sectors over others (e.g. export versus domestic). In turn, the distributional effects of monetary policy were much stronger than in normal times. As a result, these measures are sometimes referred to as quasi-fiscal policy. As Sims emphasized, a reliable monetary policy experiment cannot ignore the effect of ongoing fiscal policy. In order to implement unconventional measures during the crisis, central banks put much more risk onto government balance sheets than ever before, which had the potential to lead to substantial losses. Thus the government balance sheets in these models should be forward-looking, and its risk characteristics are crucial to the success of the model. 

 

 

Other Central Banks Models

From Macro-Econometric System Modelling @75

A fourth generation of models has arisen in the early 2000s. Representatives are TOTEM (Bank of Canada, Murchinson and Rennison, 2006), MAS (the Modelling and Simulation model of the Bank of Chile, Medina and Soto, 2005), GEM (the Global Economic Model of the IMF, Laxton and Pesenti, 2003), BEQM (Bank of England Quarterly Model, Harrison et al, 2004), NEMO (Norwegian Economic Model at the Bank of Norway, Brubakk et al, 2006), The New Area Wide Model at the European Central Bank, Kai et al, 2008), the RAMSES model at the Riksbank (Adolfson et al, 2007), AINO at the Bank of Finland (Kuismanen et al, 2003), SIGMA (Erceg et al, 2006) at the U.S. Federal Reserve, and KITT (Kiwi Inflation Targeting Technology) at the Reserve Bank of New Zealand, Beneˇs et al, 2009.

From Macroeconomic Models for Monetary Policies: A Critical Review from a Finance Perspective

  • the Bank of Canada (QPM, ToTEM),
  • the Bank of England (MTMM, BEQM),
  • the Central Bank of Chile (MAS),
  • the Central Reserve Bank of Peru (MEGA-D),
  • the European Central Bank (NAWM, CMR),
  • the Norges Bank (NEMO),
  • the Sveriges Riksbank (RAMSES),
  • the US Federal Reserve (SIGMA, EDO),
  • the Central Bank of Brazil,
  • the Central Bank of Spain,
  • the Reserve Bank of New Zealand,
  • the Bank of Finland,
  • and IMF (GEM, GFM and GIMF).

In particular, the Bank of Canada, the Bank of England, the Central Bank of Chile, the Central European Bank, the Norges Bank, the Sveriges Rikbank, and the U.S. Federal Reserve have incorporated New Keynesian DSGE models into their core models.

 

 

Other Institutions Models

  • USA CBO (Congressional Budget Office)
  • USA OMB ( Office of Management and Budget)
  • USA Department of Energy – EIA Models
  • USA Bureau of Economic Analysis (BEA) Model
  • University of Michigan RSQE Model
  • World Bank
  • UN
  • IMF
  • OECD
  • FAIR US and MC Model at Yale University

 

Other Governmental Agencies Models

  • PITM Model
  • MATH Model
  • KGB Model
  • TRIM Model
  • Claremont Model

 

Private Sector Forecasting Models

  • The Conference Board
  • Wells Fargo
  • JP Morgan
  • Citi
  • Oxford Economics
  • Moody’s Analytics
  • IHS Inc./Global Insight

 

Old Non Governmental Models

  • DRI (Data Resources Inc.)
  • Chase Econometrics
  • Wharton Econometrics

They all merged into an entity IHS, Inc.

In 1987 Wharton Econometric Forecasting Associates (WEFA) merged with Chase Econometrics, a competitor to DRI and WEFA,[13] and in 2001 DRI merged with WEFA to form Global Insight.[14][15] In 2008 Global Insight was bought by IHS Inc., thus inheriting 50 years of experience and more than 200 full-time economists, country risk analysts, and consultants. [16]

 

The following book is a good resource for Lists of Models used in various countries.

  • Macroeconometric Models By Władysław Welfe

 

 

Heterodox Models

 

  • System Dynamics Models
  • Stock Flow Consistent Models
  • Flow of Funds Models
  • Agent based Computational Models
  • Network Economics Approaches

 

From Can Disequilibrium Macroeconomic Models Be Used to Anticipate Financial Instability? A Case Study

Two other approaches to modeling the macroeconomy are flow-of-funds models and stock-flow consistent models, and a fourth is agent-based models. All trace unfolding processes rather than equilibrium snapshots, and are so evolutionary. SFC models also differ from DSGE models in that they aim to be financially complete (but obviously stylized) representations of the economy.

 

Please see my other posts on Heterodox Modeling.

Increasing Returns, Path Dependence, Circular and Cumulative Causation in Economics

Jay W. Forrester and System Dynamics

Micro Motives, Macro Behavior: Agent Based Modeling in Economics

Stock-Flow Consistent Modeling

Foundations of Balance Sheet Economics

Contagion in Financial (Balance sheets) Networks

 

 

Key People:

  • Jan Tinbergen
  • Lawrance Klein
  • Wassily Leontief
  • Tjalling Koopmans
  • Franco Modigliani
  • Kenneth Arrow
  • Trygve Haavelmo
  • T.W. Anderson
  • G. Debreu
  • Leonid Hurwitz
  • Harry Markowitz
Key Sources of Research:

 

 

Macroeconomic Models, Forecasting, and Policymaking

Andrea Pescatori and Saeed Zaman

Click to access 0_New_14947.pdf

 

 

The Evolution of Macro Models at the Federal Reserve Board

􏰃Flint Brayton, Andrew Levin, Ralph Tryon, and John C. Williams

Revised: February 7, 1997

Click to access 199729pap.pdf

 

 

A Guide to FRB/US

A Macroeconomic Model of the United States

Macroeconomic and Quantitative Studies 􏰂 Division of Research and Statistics Federal Reserve Board Washington, D.C. 20551

version 1.0, October 1996

Click to access 199642pap.pdf

 

 

The FRB/US Model: A Tool for Macroeconomic Policy Analysis

Flint Brayton, Thomas Laubach, and David Reifschneider

2014

https://www.federalreserve.gov/econresdata/notes/feds-notes/2014/a-tool-for-macroeconomic-policy-analysis.html

https://www.federalreserve.gov/econresdata/frbus/us-models-package.htm

https://www.federalreserve.gov/econresdata/frbus/us-documentation-papers.htm

https://www.federalreserve.gov/econresdata/frbus/us-technical-qas.htm

https://www.federalreserve.gov/econresdata/notes/feds-notes/2014/november-2014-update-of-the-frbus-model-20141121.html

 

 

Estimated Dynamic Optimization (EDO) Model

https://www.federalreserve.gov/econresdata/edo/edo-models-about.htm

https://www.federalreserve.gov/econresdata/edo/edo-model-package.htm

https://www.federalreserve.gov/econresdata/edo/edo-documentation-papers.htm

 

 

The FRBNY DSGE Model

Marco Del Negro Stefano Eusepi Marc Giannoni Argia Sbordone Andrea Tambalotti Matthew Cocci Raiden Hasegawa M. Henry Linder

 

2013

Click to access sr647.pdf

 

 

Can Disequilibrium Macroeconomic Models Be Used to Anticipate Financial Instability?

A Case Study

Dirk J. Bezemer

 

Click to access a6d8daa2716892ed0984f8aa0882c6dccefc.pdf

 

 

Central Bank Models:Lessons from the Past and Ideas for the Future

John B. Taylor

November 2016

Click to access Text_Keynote_BoC_Workshop_Taylor-2016.pdf

 

 

DSGE models and central banks

by Camilo E Tovar

2008

Click to access work258.pdf

 

 

Macro-Finance Models of Interest Rates and the Economy

Glenn D. Rudebusch∗
Federal Reserve Bank of San Francisco

Click to access 3c8c75a3daa52749dd4ade71f9ae1642f9aa.pdf

 

 

Panel Discussion on Uses of Models at Central Banks

ECB Workshop on DSGE Models and Forecasting September 23, 2016

John Roberts

 

Click to access Roberts_Panel_discussion.pdf

 

 

The Chicago Fed DSGE Model

Scott A. Brave Jerey R. Campbell  Jonas D.M. Fisher  Alejandro Justiniano

August 16, 2012

https://www.chicagofed.org/publications/working-papers/2012/wp-02

 

 

Macroeconomics and consumption: Why central bank models failed and how to repair them

John Muellbauer

21 December 2016

http://voxeu.org/article/why-central-bank-models-failed-and-how-repair-them

 

 

Model Comparison and Robustness: A Proposal for Policy Analysis after the Financial Crisis

Volker Wieland

1st Version: November 28, 2010 This Version: March 21, 2011

 

Click to access Wieland_CournotConf_110321.pdf

 

 

TOBIN LIVES: INTEGRATING EVOLVING CREDIT MARKET ARCHITECTURE INTO FLOW OF FUNDS BASED MACRO- MODELS

John Duca and John Muellbauer

September 2012

 

Click to access paper622.pdf

 

 

FRB/US Equations Documentation

Click to access frbus_equation_documentation.pdf

 

 

Challenges for Central Banks’ Macro Models

Jesper Lindé, Frank Smets and Rafael Wouters

2016

 

Click to access rap_wp323_160512.pdf

 

 

Central Bank Models: Lessons from the Past and Ideas for the Future

John B. Taylor

2016

 

Click to access central-bank-models-lessons-past.pdf

 

 

Lawrence R. Klein: Macroeconomics, econometrics and economic policy􏰑

Ignazio Visco

2014

 

Click to access Visco_Klein_2014.pdf

 

 

Macro-Econometric System Modelling @75

Tony Hall  Jan Jacobs Adrian Pagan

Click to access WP95.pdf

 

 

The Econometrics of Macroeconomic Modelling

Gunnar Ba ̊rdsenØyvind Eitrheim Eilev S. Jansen Ragnar Nymoen

Click to access master210104.pdf

 

 

The Macroeconomist as Scientist and Engineer

N. Gregory Mankiw

May 2006

 

http://scholar.harvard.edu/files/mankiw/files/macroeconomist_as_scientist.pdf?m=1360042085

 

 

 Macroeconometric Models

By Władysław Welfe

 

 

HISTORY OF MACROECONOMETRIC MODELLING: LESSONS FROM PAST EXPERIENCE

Abbas Valadkhani

 

Click to access Valadkhani_131.pdf

 

 

ECONOMETRICS: AN HISTORICAL GUIDE FOR THE UNINITIATED

by D.S.G. Pollock

University of Leicester

Click to access dp14-05.pdf

 

 

RBI-MSE Joint Initiative on Modeling the Indian Economy for Forecasting and Policy Simulations

N R Bhanumurthy NIPFP, New Delhi, India

 

Click to access Model-1.pdf

 

 

ECONOMIC MODELS

 

Click to access chap1.pdf

 

 

MACROECONOMIC MODELLING OF MONETARY POLICY

BY MATT KLAEFFLING

SEPTEMBER 2003

https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp257.pdf?62a2706261fcf6fb02a681c780f3408f

 

 

Macroeconomic Modeling in India

N R Bhanumurthy NIPFP, New Delhi, India

 

Click to access India-Macroeconomic%20modeling%20in%20India.pdf

 

 

Macroeconomic Modeling in the Policy Process: A Review of Tools Used at the Federal Reserve Board and Their Relation to Ongoing Research

 

Michael Kiley

 

Click to access Apresentação%20Michael%20Kiley.pdf

 

 

Policy Analysis Using DSGE Models: An Introduction

Argia M. Sbordone, Andrea Tambalotti, Krishna Rao, and Kieran Walsh

2010

 

Click to access 1010sbor.pdf

 

 

DSGE Model-Based Forecasting

Marco Del Negro Frank Schorfheide

Staff Report No. 554 March 2012

 

Click to access 2761a45dbc2a4b57990d250adb8ae846129f.pdf

 

 

The Use of (DSGE) Models in Central Bank Forecasting: The FRBNY Experience

Marco Del Negro

 

Click to access DelNegro_DSGE_forecasting_panel.pdf

 

 

Modern Macroeconomic Models as Tools for Economic Policy

Narayana Kocherlakota

 

Click to access 2009_mplsfed_annualreport_essay.pdf

 

 

STRUCTURAL ECONOMETRIC MODELLING: METHODOLOGY AND TOOLS WITH APPLICATIONS UNDER EVIEWS

 

Click to access structmodel.pdf

 

 

Macroeconomic Models for Monetary Policies: A Critical Review from a Finance Perspective∗

Winston W. Dou †, Andrew W. Lo‡, and Ameya Muley

This Draft: March 12, 2015

Click to access MacroFinanceReview_v11_DLM.pdf

 

 

Lawrence R. Klein 1920-2013: Notes on the early years

Olav Bjerkholt, University of Oslo

 

 

A History of Macroeconomics from Keynes to Lucas and Beyond

 

By Michel De Vroey

2016

 

 

Economic Theory, Model Size, and Model Purpose

John B Taylor

Chapter in a Book Large Scale Macroe conomtric Models

1981