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

 

Feedback Thought in Economics and Finance

Feedback Thought in Economics and Finance

  • Negative Feedbacks
  • Positive Feedbacks
  • Stocks and Flows
  • Limiting Factors

 

Key People:

  • Jay Forrester
  • George Richardson
  • John Sterman
  • Michael Radzicki
  • Mikhail Oet
  • Oleg Pavlov
  • Eric D. Beinhocker
  • Stuart A. Umpleby
  • Khalid Saeed
  • Kaoru Yamaguchi

 

Reflexivity and Second order economics are closely related concepts.

 

From System Dynamics and Its Contribution to Economics and Economic Modeling

 

System dynamics is a computer simulation modeling methodology that is used to analyze complex nonlinear dynamic feedback systems for the purposes of generating insight and designing policies that will improve system performance. It was originally created in 1957 by Jay W. Forrester of the Massachusetts Institute of Technology as a methodology for building computer simulation models of problematic behavior within corporations. The models were used to design and test policies aimed at altering a corporation’s structure so that its behavior would improve and become more robust.

Today, system dynamics is applied to a large variety of problems in a multitude of academic disciplines, including economics. System dynamics models are created by identifying and linking the relevant pieces of a system’s structure and simulating the behavior generated by that structure. Through an iterative process of structure identification, mapping, and simulation a model emerges that can explain (mimic) a system’s problematic behavior and serve as a vehicle for policy design and testing. From a system dynamics perspective a system’s structure consists of stocks, flows, feedback loops, and limiting factors.

Stocks can be thought of as bathtubs that accumulate/de-cumulate a system’s flows over time. Flow can be thought of as pipe and faucet assemblies that fill or drain the stocks. Mathematically, the process of flows accumulating/de-cumulating in stocks is called integration. The integration process creates all dynamic behavior in the world be it in a physical system, a biological system, or a socioeconomic system. Examples of stocks and flows in economic systems include a stock of inventory and its inflow of production and its outflow of sales, a stock of the book value of a firm’s capital and its inflow of investment  spending and its outflow of depreciation, and a stock of employed labor and its inflow of hiring and its outflow of labor separations.

Feedback is the transmission and return of information about the amount of information or material that has accumulated in a system’s stocks. Information travels from a stock back to its flow(s) either directly or indirectly, and this movement of information causes the system’s faucets to open more, close a bit, close all the way, or stay in the same place. Every feedback loop has to contain at least one stock so that a simultaneous equation situation can be avoided and a model’s behavior can be revealed recursively. Loops with a single stock are termed minor, while loops containing more than one stock are termed major. 

Two types of feedback loops exist in system dynamics modeling: positive loops and negative loops. Generally speaking, positive loops generate self-reinforcing behavior and are responsible for the growth or decline of a system. Any relationship that can be termed a virtuous or vicious circle is thus a positive feedback loop. Examples of positive loops in economic systems include path dependent processes, increasing returns, speculative bubbles, learning by-doing, and many of the relationships found in macroeconomic growth theory. Forrester [12], Radzicki and Sterman [46],Moxnes [32], Sterman (Chap. 10 in [55]), Radzicki [44], Ryzhenkov [49], and Weber [58] describe system dynamics models of economic systems that possess dominant positive feedback processes.

Negative feedback loops generate goal-seeking behavior and are responsible for both stabilizing systems and causing them to oscillate. When a negative loop detects a gap between a stock and its goal it initiates corrective action aimed at closing the gap. When this is accomplished without a significant time delay, a system will adjust smoothly to its goal. On the other hand, if there are significant time lags in the corrective actions of a negative loop, it can overshoot or undershoot its goal and cause the system to oscillate. Examples of negative feedback processes in economic systems include equilibrating mechanisms (“auto-pilots”) such as simple supply and demand relationships, stock adjustment models for invetory control, any purposeful behavior, and many of the relationships found in macroeconomic business cycle theory. Meadows [27], Mass [26], Low [23], Forrester [12], and Sterman [54] provide examples of system dynamics models that generate cyclical behavior at the macro-economic and micro-economic levels.

From a system dynamics point of view, positive and negative feedback loops fight for control of a system’s behavior. The loops that are dominant at any given time determine a system’s time path and, if the system is nonlinear, the dominance of the loops can change over time as the system’s stocks fill and drain. From this perspective, the dynamic behavior of any economy that is, the interactions between the trend and the cycle in an economy over time can be explained as a fight for dominance between the economy’s most significant positive and negative feedback loops.

 

Key Sources of Research:

 

Systemic Financial Feedbacks – Conceptual Framework and Modeling Implications

Dieter Gramlich1 and Mikhail V. Oet

Click to access 54992d5c0cf2519f5a1df20b.pdf

 

 

FEEDBACK MECHANISMS IN THE FINANCIAL SYSTEM: A MODERN VIEW

Mikhail V. Oet

Oleg V. Pavlov

Click to access P1441.pdf

 

 

Mr. Hamilton, Mr. Forrester, and a Foundation for Evolutionary Economics

Michael J. Radzicki

 

Click to access 0a85e52e41951a468c000000.pdf

 

European Contributions to Evolutionary Institutional Economics: The Cases of ‘Cumulative Circular Causation’ (CCC) and ‘Open Systems Approach’ (OSA).
Some Methodological and Policy Implications

 

Sebastian Berger and Wolfram Elsner

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.519.7169&rep=rep1&type=pdf

 

System Dynamicsand Its Contribution to Economics and Economic Modeling

MICHAEL J. RADZICKI

 

Click to access 02e7e53331fe5f394b000000.pdf

 

 

Institutional Economics, Post Keynesian Economics, and System Dynamics: Three Strands of a Heterodox Economics Braid

Michael J. Radzicki, Ph.D.

Click to access 02e7e53331eeea388c000000.pdf

 

 

Was Alfred Eichner a System Dynamicist?

by

Michael J. Radzicki

Click to access 0f317536d3f41a13fb000000.pdf

 

Second-Order Economics as an Example of Second-Order Cybernetics

Stuart A. Umpleby

 

Click to access 890.pdf

 

Reflexivity, complexity, and the nature of social science

Eric D. Beinhocker

 

Click to access Beinhocker%20(JEM%202013).pdf

 

Path dependence, its critics and the quest for ‘historical economics’

By

Paul A. David

Click to access 0deec53b482217c114000000.pdf

 

Endogenous Feedback Perspective on Money in a Stock-Flow Consistent Model

I. David Wheat
University of Bergen

 

Click to access Wheat%20Endogenous%20Feedback%20Perspective%20on%20Money%20WP.pdf

 

Classical Economics on Limits to Growth

Khalid Saeed

 

Click to access Classical%20Economics%20on%20Limits%20to%20Growth.pdf

 

 

Misperceptions of Feedback in Dynamic Decisionmaking

John D. Sterman

 

Click to access 54359e4e0cf2bf1f1f2b3520.pdf

 

Learning in and about complex systems

John D. Sterman

 

Click to access sterman-learning-in-and-about-complex-systems.pdf

 

Micro-worlds and Evolutionary Economics

Michael J. Radzicki

Click to access radzi533.pdf

 

Feedback Thought in Social Science and Systems Theory

George Richardson

Pegasus Communications, Inc. ©1999
ISBN:1883823463

 

The Feedback concept in American Social Sciences 

George Richardson

1983

Click to access richa001.pdf

 

Evolutionary Economics and System Dynamics

Radzicki and Sterman

 

Effects of Feedback Complexity on Dynamic Decision Making
Ernst Diehl, John D. Sterman

Organizational Behavior and Human Decision Processes

Volume 62, Issue 2, May 1995, Pages 198-215

 

Old Wine in a New Bottle:
Towards a Common Language for Post-Keynesian Macroeconomics Model

Ginanjar Utama

2014

Click to access P1307.pdf

 

On Component Based Modeling Approach using System Dynamics for The Financial System (With a Case Study of Keen-Minsky Model)

Ginanjar Utama

2013

Click to access P1209.pdf

 

On the Monetary and Financial Stability under A Public Money System

– Modeling the American Monetary Act Simplified –

Kaoru Yamaguchi

 

Click to access P1065.pdf

 

Integration of Real and Monetary Sectors with Labor Market
– SD Macroeconomic Modeling (3) –

Kaoru Yamaguchi

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.436.1085&rep=rep1&type=pdf

 

Balance of Payments and Foreign Exchange Dynamics

– SD Macroeconomic Modeling (4) –

Kaoru Yamaguchi, Ph.D

2007

Click to access YAMAG211.pdf

 

 

Money and Macroeconomic Dynamics

Accounting System Dynamics Approach

Kaoru Yamaguchi, Ph.D

 

Click to access Macro%20Dynamics.pdf

 

Does Money Matter on the Formation of Business Cycles and Economic Recessions ?
– SD Simulations of A Monetary Goodwin Model –

 

Kaoru Yamaguchi

Click to access DBS12-01.pdf

 

Head and Tail of Money Creation and its System Design Failures

– Toward the Alternative System Design –

JFRC Working Paper No. 01-2016

Kaoru Yamaguchi, Ph.D.

Yokei Yamaguchi

Click to access Head-and-Tail-2016_WP__-_Japan_Futures_Research_Center.pdf

 

Modelling the Great Transition

 

Emanuele Campiglio

New Economics Foundation

Click to access Emanuel-SD-conference-9-2-12.pdf

 

The role of System Dynamics modelling to understand food chain complexity and address challenges for sustainability policies

Irene Monasterolo1, Roberto Pasqualino, Edoardo Mollona

 

Click to access CFP3-06_Full_Paper.pdf

 

Dynamic regional economic modeling: a systems approach

I. David Wheat

2014

 

Click to access 1.17_wheat_pawluczuk.pdf

 

Expectation Formation and Parameter Estimation in Uncertain Dynamical Systems: The System Dynamics Approach to Post Keynesian-Institutional Economics

Introduction

 

Michael J. Radzicki

 

Click to access 0deec536d3da974962000000.pdf

 

The Circular and Cumulative Structure of Administered Pricing

Mark Nichols, Oleg Pavlov, and Michael J. Radzicki

2006

Click to access 02e7e5282d33c933df000000.pdf

 

A System Dynamics Approach to the Bhaduri‐Marglin Model

Klaus D. John

Click to access P1306.pdf

 

An Institutional Dynamics Model of the Euro zone crisis: Greece as an Illustrative Example

Domen Zavrl

Miroljub Kljajić

Click to access P1144.pdf

 

Is system dynamics modelling of relevance to neoclassical economists? 

Douglas J. Crookes Martin P. De Wit

Click to access 00b7d53861d6b14d9f000000.pdf

 

System dynamics modelling and simulating the effects of intellectual capital on economic growth

Ivona Milić Beran

http://hrcak.srce.hr/ojs/index.php/crorr/article/viewFile/2803/2121