Short term Thinking in Investment Decisions of Businesses and Financial Markets

Short term Thinking in Investment Decisions of Businesses and Financial Markets

 

When companies buyback shares and pay dividends rather than investing in new capacity, it leads to low economic growth and low aggregate demand.

Central Banks respond by cutting interest rates.  Yet Businesses do not invest in new capacity.

Many studies attribute this to short term thinking dominant in corporate investment decisions.  Pressures from shareholders push corporate managers to be short term oriented.

Many economists and thinkers have criticized this recently as advanced economies are suffering from anemic growth.

Larry Summers has invoked Secular Stagnation.  He says one of the reason for Secular Stagnation is short term thinking.

Andy Haldane of Bank of England has criticized short term thinking as it prevents investments and causes low economic growth.

Key Terms:

  • Quarterly Capitalism
  • Secular Stagnation
  • Short Term Thinking
  • Low Economic Growth
  • Business Investments
  • Real Interest Rates
  • Monetary Policy
  • Income and Wealth Inequality
  • Aggregate Demand
  • Productive Capacity
  • Productivity growth
  • Long Term Investments
  • Share Buybacks
  • Dividends
  • Corporate Cash Pools

 

Capitalism for the Long Term

The near meltdown of the financial system and the ensuing Great Recession have been, and will remain, the defining issue for the current generation of executives. Now that the worst seems to be behind us, it’s tempting to feel deep relief—and a strong desire to return to the comfort of business as usual. But that is simply not an option. In the past three years we’ve already seen a dramatic acceleration in the shifting balance of power between the developed West and the emerging East, a rise in populist politics and social stresses in a number of countries, and significant strains on global governance systems. As the fallout from the crisis continues, we’re likely to see increased geopolitical rivalries, new international security challenges, and rising tensions from trade, migration, and resource competition. For business leaders, however, the most consequential outcome of the crisis is the challenge to capitalism itself.

That challenge did not just arise in the wake of the Great Recession. Recall that trust in business hit historically low levels more than a decade ago. But the crisis and the surge in public antagonism it unleashed have exacerbated the friction between business and society. On top of anxiety about persistent problems such as rising income inequality, we now confront understandable anger over high unemployment, spiraling budget deficits, and a host of other issues. Governments feel pressure to reach ever deeper inside businesses to exert control and prevent another system-shattering event.

My goal here is not to offer yet another assessment of the actions policymakers have taken or will take as they try to help restart global growth. The audience I want to engage is my fellow business leaders. After all, much of what went awry before and after the crisis stemmed from failures of governance, decision making, and leadership within companies. These are failures we can and should address ourselves.

In an ongoing effort that started 18 months ago, I’ve met with more than 400 business and government leaders across the globe. Those conversations have reinforced my strong sense that, despite a certain amount of frustration on each side, the two groups share the belief that capitalism has been and can continue to be the greatest engine of prosperity ever devised—and that we will need it to be at the top of its job-creating, wealth-generating game in the years to come. At the same time, there is growing concern that if the fundamental issues revealed in the crisis remain unaddressed and the system fails again, the social contract between the capitalist system and the citizenry may truly rupture, with unpredictable but severely damaging results.

Most important, the dialogue has clarified for me the nature of the deep reform that I believe business must lead—nothing less than a shift from what I call quarterly capitalism to what might be referred to as long-term capitalism. (For a rough definition of “long term,” think of the time required to invest in and build a profitable new business, which McKinsey research suggests is at least five to seven years.) This shift is not just about persistently thinking and acting with a next-generation view—although that’s a key part of it. It’s about rewiring the fundamental ways we govern, manage, and lead corporations. It’s also about changing how we view business’s value and its role in society.

There are three essential elements of the shift. First, business and finance must jettison their short-term orientation and revamp incentives and structures in order to focus their organizations on the long term. Second, executives must infuse their organizations with the perspective that serving the interests of all major stakeholders—employees, suppliers, customers, creditors, communities, the environment—is not at odds with the goal of maximizing corporate value; on the contrary, it’s essential to achieving that goal. Third, public companies must cure the ills stemming from dispersed and disengaged ownership by bolstering boards’ ability to govern like owners.

When making major decisions, Asians typically think in terms of at least 10 to 15 years. In the U.S. and Europe, nearsightedness is the norm.

None of these ideas, or the specific proposals that follow, are new. What is new is the urgency of the challenge. Business leaders today face a choice: We can reform capitalism, or we can let capitalism be reformed for us, through political measures and the pressures of an angry public. The good news is that the reforms will not only increase trust in the system; they will also strengthen the system itself. They will unleash the innovation needed to tackle the world’s grand challenges, pave the way for a new era of shared prosperity, and restore public faith in business.

1. Fight the Tyranny of Short-Termism

As a Canadian who for 25 years has counseled business, public sector, and nonprofit leaders across the globe (I’ve lived in Toronto, Sydney, Seoul, Shanghai, and now London), I’ve had a privileged glimpse into different societies’ values and how leaders in various cultures think. In my view, the most striking difference between East and West is the time frame leaders consider when making major decisions. Asians typically think in terms of at least 10 to 15 years. For example, in my discussions with the South Korean president Lee Myung-bak shortly after his election in 2008, he asked us to help come up with a 60-year view of his country’s future (though we settled for producing a study called National Vision 2020.) In the U.S. and Europe, nearsightedness is the norm. I believe that having a long-term perspective is the competitive advantage of many Asian economies and businesses today.

Myopia plagues Western institutions in every sector. In business, the mania over quarterly earnings consumes extraordinary amounts of senior time and attention. Average CEO tenure has dropped from 10 to six years since 1995, even as the complexity and scale of firms have grown. In politics, democracies lurch from election to election, with candidates proffering dubious short-term panaceas while letting long-term woes in areas such as economic competitiveness, health, and education fester. Even philanthropy often exhibits a fetish for the short term and the new, with grantees expected to become self-sustaining in just a few years.

Lost in the frenzy is the notion that long-term thinking is essential for long-term success. Consider Toyota, whose journey to world-class manufacturing excellence was years in the making. Throughout the 1950s and 1960s it endured low to nonexistent sales in the U.S.—and it even stopped exporting altogether for one bleak four-year period—before finally emerging in the following decades as a global leader. Think of Hyundai, which experienced quality problems in the late 1990s but made a comeback by reengineering its cars for long-term value—a strategy exemplified by its unprecedented introduction, in 1999, of a 10-year car warranty. That radical move, viewed by some observers as a formula for disaster, helped Hyundai quadruple U.S. sales in three years and paved the way for its surprising entry into the luxury market.

To be sure, long-term perspectives can be found in the West as well. For example, in 1985, in the face of fierce Japanese competition, Intel famously decided to abandon its core business, memory chips, and focus on the then-emerging business of microprocessors. This “wrenching” decision was “nearly inconceivable” at the time, says Andy Grove, who was then the company’s president. Yet by making it, Intel emerged in a few years on top of a new multi-billion-dollar industry. Apple represents another case in point. The iPod, released in 2001, sold just 400,000 units in its first year, during which Apple’s share price fell by roughly 25%. But the board took the long view. By late 2009 the company had sold 220 million iPods—and revolutionized the music business.

It’s fair to say, however, that such stories are countercultural. In the 1970s the average holding period for U.S. equities was about seven years; now it’s more like seven months. According to a recent paper by Andrew Haldane, of the Bank of England, such churning has made markets far more volatile and produced yawning gaps between corporations’ market price and their actual value. Then there are the “hyperspeed” traders (some of whom hold stocks for only a few seconds), who now account for 70% of all U.S. equities trading, by one estimate. In response to these trends, executives must do a better job of filtering input, and should give more weight to the views of investors with a longer-term, buy-and-hold orientation.

If they don’t, short-term capital will beget short-term management through a natural chain of incentives and influence. If CEOs miss their quarterly earnings targets, some big investors agitate for their removal. As a result, CEOs and their top teams work overtime to meet those targets. The unintended upshot is that they manage for only a small portion of their firm’s value. When McKinsey’s finance experts deconstruct the value expectations embedded in share prices, we typically find that 70% to 90% of a company’s value is related to cash flows expected three or more years out. If the vast majority of most firms’ value depends on results more than three years from now, but management is preoccupied with what’s reportable three months from now, then capitalism has a problem.

Roughly 70% of all U.S. equities trading is now done by “hyperspeed” traders—some of whom hold stocks for only a few seconds.

Some rightly resist playing this game. Unilever, Coca-Cola, and Ford, to name just a few, have stopped issuing earnings guidance altogether. Google never did. IBM has created five-year road maps to encourage investors to focus more on whether it will reach its long-term earnings targets than on whether it exceeds or misses this quarter’s target by a few pennies. “I can easily make my numbers by cutting SG&A or R&D, but then we wouldn’t get the innovations we need,” IBM’s CEO, Sam Palmisano, told us recently. Mark Wiseman, executive vice president at the Canada Pension Plan Investment Board, advocates investing “for the next quarter century,” not the next quarter. And Warren Buffett has quipped that his ideal holding period is “forever.” Still, these remain admirable exceptions.

To break free of the tyranny of short-termism, we must start with those who provide capital. Taken together, pension funds, insurance companies, mutual funds, and sovereign wealth funds hold $65 trillion, or roughly 35% of the world’s financial assets. If these players focus too much attention on the short term, capitalism as a whole will, too.

In theory they shouldn’t, because the beneficiaries of these funds have an obvious interest in long-term value creation. But although today’s standard practices arose from the desire to have a defensible, measurable approach to portfolio management, they have ended up encouraging shortsightedness. Fund trustees, often advised by investment consultants, assess their money managers’ performance relative to benchmark indices and offer only short-term contracts. Those managers’ compensation is linked to the amount of assets they manage, which typically rises when short-term performance is strong. Not surprisingly, then, money managers focus on such performance—and pass this emphasis along to the companies in which they invest. And so it goes, on down the line.

Only 45% of those surveyed in the U.S. and the UK expressed trust in business. This stands in stark contrast to developing countries: For example, the figure is 61% in China, 70% in India, and 81% in Brazil.

As the stewardship advocate Simon Wong points out, under the current system pension funds deem an asset manager who returns 10% to have underperformed if the relevant benchmark index rises by 12%. Would it be unthinkable for institutional investors instead to live with absolute gains on the (perfectly healthy) order of 10%—especially if they like the approach that delivered those gains—and review performance every three or five years, instead of dropping the 10-percenter? Might these big funds set targets for the number of holdings and rates of turnover, at least within the “fundamental investing” portion of their portfolios, and more aggressively monitor those targets? More radically, might they end the practice of holding thousands of stocks and achieve the benefits of diversification with fewer than a hundred—thereby increasing their capacity to effectively engage with the businesses they own and improve long-term performance? Finally, could institutional investors beef up their internal skills and staff to better execute such an agenda? These are the kinds of questions we need to address if we want to align capital’s interests more closely with capitalism’s.

2. Serve Stakeholders, Enrich Shareholders

The second imperative for renewing capitalism is disseminating the idea that serving stakeholders is essential to maximizing corporate value. Too often these aims are presented as being in tension: You’re either a champion of shareholder value or you’re a fan of the stakeholders. This is a false choice.

The inspiration for shareholder-value maximization, an idea that took hold in the 1970s and 1980s, was reasonable: Without some overarching financial goal with which to guide and gauge a firm’s performance, critics feared, managers could divert corporate resources to serve their own interests rather than the owners’. In fact, in the absence of concrete targets, management might become an exercise in politics and stakeholder engagement an excuse for inefficiency. Although this thinking was quickly caricatured in popular culture as the doctrine of “greed is good,” and was further tarnished by some companies’ destructive practices in its name, in truth there was never any inherent tension between creating value and serving the interests of employees, suppliers, customers, creditors, communities, and the environment. Indeed, thoughtful advocates of value maximization have always insisted that it is long-term value that has to be maximized.

Capitalism’s founding philosopher voiced an even bolder aspiration. “All the members of human society stand in need of each others assistance, and are likewise exposed to mutual injuries,” Adam Smith wrote in his 1759 work, The Theory of Moral Sentiments. “The wise and virtuous man,” he added, “is at all times willing that his own private interest should be sacrificed to the public interest,” should circumstances so demand.

Smith’s insight into the profound interdependence between business and society, and how that interdependence relates to long-term value creation, still reverberates. In 2008 and again in 2010, McKinsey surveyed nearly 2,000 executives and investors; more than 75% said that environmental, social, and governance (ESG) initiatives create corporate value in the long term. Companies that bring a real stakeholder perspective into corporate strategy can generate tangible value even sooner. (See the sidebar “Who’s Getting It Right?”)

Creating direct business value, however, is not the only or even the strongest argument for taking a societal perspective. Capitalism depends on public trust for its legitimacy and its very survival. According to the Edelman public relations agency’s just-released 2011 Trust Barometer, trust in business in the U.S. and the UK (although up from mid-crisis record lows) is only in the vicinity of 45%. This stands in stark contrast to developing countries: For example, the figure is 61% in China, 70% in India, and 81% in Brazil. The picture is equally bleak for individual corporations in the Anglo-American world, “which saw their trust rankings drop again last year to near-crisis lows,” says Richard Edelman.

How can business leaders restore the public’s trust? Many Western executives find that nothing in their careers has prepared them for this new challenge. Lee Scott, Walmart’s former CEO, has been refreshingly candid about arriving in the top job with a serious blind spot. He was plenty busy minding the store, he says, and had little feel for the need to engage as a statesman with groups that expected something more from the world’s largest company. Fortunately, Scott was a fast learner, and Walmart has become a leader in environmental and health care issues.

Tomorrow’s CEOs will have to be, in Joseph Nye’s apt phrase, “tri-sector athletes”: able and experienced in business, government, and the social sector. But the pervading mind-set gets in the way of building those leadership and management muscles. “Analysts and investors are focused on the short term,” one executive told me recently. “They believe social initiatives don’t create value in the near term.” In other words, although a large majority of executives believe that social initiatives create value in the long term, they don’t act on this belief, out of fear that financial markets might frown. Getting capital more aligned with capitalism should help businesses enrich shareholders by better serving stakeholders.

3. Act Like You Own the Place

As the financial sector’s troubles vividly exposed, when ownership is broadly fragmented, no one acts like he’s in charge. Boards, as they currently operate, don’t begin to serve as a sufficient proxy. All the Devils Are Here, by Bethany McLean and Joe Nocera, describes how little awareness Merrill Lynch’s board had of the firm’s soaring exposure to subprime mortgage instruments until it was too late. “I actually don’t think risk management failed,” Larry Fink, the CEO of the investment firm BlackRock, said during a 2009 debate about the future of capitalism, sponsored by the Financial Times. “I think corporate governance failed, because…the boards didn’t ask the right questions.”

What McKinsey has learned from studying successful family-owned companies suggests a way forward: The most effective ownership structure tends to combine some exposure in the public markets (for the discipline and capital access that exposure helps provide) with a significant, committed, long-term owner. Most large public companies, however, have extremely dispersed ownership, and boards rarely perform the single-owner-proxy role. As a result, CEOs too often listen to the investors (and members of the media) who make the most noise. Unfortunately, those parties tend to be the most nearsighted ones. And so the tyranny of the short term is reinforced.

The answer is to renew corporate governance by rooting it in committed owners and by giving those owners effective mechanisms with which to influence management. We call this ownership-based governance, and it requires three things:

Just 43% of the nonexecutive directors of public companies believe they significantly influence strategy. For this to change, board members must devote much more time to their roles.

More-effective boards.

In the absence of a dominant shareholder (and many times when there is one), the board must represent a firm’s owners and serve as the agent of long-term value creation. Even among family firms, the executives of the top-performing companies wield their influence through the board. But only 43% of the nonexecutive directors of public companies believe they significantly influence strategy. For this to change, board members must devote much more time to their roles. A government-commissioned review of the governance of British banks last year recommended an enormous increase in the time required of nonexecutive directors of banks—from the current average, between 12 and 20 days annually, to between 30 and 36 days annually. What’s especially needed is an increase in the informal time board members spend with investors and executives. The nonexecutive board directors of companies owned by private equity firms spend 54 days a year, on average, attending to the company’s business, and 70% of that time consists of informal meetings and conversations. Four to five days a month obviously give a board member much greater understanding and impact than the three days a quarter (of which two may be spent in transit) devoted by the typical board member of a public company.

Boards also need much more relevant experience. Industry knowledge—which four of five nonexecutive directors of big companies lack—helps boards identify immediate opportunities and reduce risk. Contextual knowledge about the development path of an industry—for example, whether the industry is facing consolidation, disruption from new technologies, or increased regulation—is highly valuable, too. Such insight is often obtained from experience with other industries that have undergone a similar evolution.

In addition, boards need more-effective committee structures—obtainable through, for example, the establishment of a strategy committee or of dedicated committees for large business units. Directors also need the resources to allow them to form independent views on strategy, risk, and performance (perhaps by having a small analytical staff that reports only to them). This agenda implies a certain professionalization of nonexecutive directorships and a more meaningful strategic partnership between boards and top management. It may not please some executive teams accustomed to boards they can easily “manage.” But given the failures of governance to date, it is a necessary change.

More-sensible CEO pay.

An important task of governance is setting executive compensation. Although 70% of board directors say that pay should be tied more closely to performance, CEO pay is too often structured to reward a leader simply for having made it to the top, not for what he or she does once there. Meanwhile, polls show that the disconnect between pay and performance is contributing to the decline in public esteem for business.

Companies should create real risk for executives.Some experts privately suggest mandating that new executives invest a year’s salary in the company.

CEOs and other executives should be paid to act like owners. Once upon a time we thought that stock options would achieve this result, but stock-option- based compensation schemes have largely incentivized the wrong behavior. When short-dated, options lead to a focus on meeting quarterly earnings estimates; even when long-dated (those that vest after three years or more), they can reward managers for simply surfing industry- or economy-wide trends (although reviewing performance against an appropriate peer index can help minimize free rides). Moreover, few compensation schemes carry consequences for failure—something that became clear during the financial crisis, when many of the leaders of failed institutions retired as wealthy people.

There will never be a one-size-fits-all solution to this complex issue, but companies should push for change in three key areas:

• They should link compensation to the fundamental drivers of long-term value, such as innovation and efficiency, not just to share price.

• They should extend the time frame for executive evaluations—for example, using rolling three-year performance evaluations, or requiring five-year plans and tracking performance relative to plan. This would, of course, require an effective board that is engaged in strategy formation.

• They should create real downside risk for executives, perhaps by requiring them to put some skin in the game. Some experts we’ve surveyed have privately suggested mandating that new executives invest a year’s salary in the company.

Redefined shareholder “democracy.”

The huge increase in equity churn in recent decades has spawned an anomaly of governance: At any annual meeting, a large number of those voting may soon no longer be shareholders. The advent of high-frequency trading will only worsen this trend. High churn rates, short holding periods, and vote-buying practices may mean the demise of the “one share, one vote” principle of governance, at least in some circumstances. Indeed, many large, top-performing companies, such as Google, have never adhered to it. Maybe it’s time for new rules that would give greater weight to long-term owners, like the rule in some French companies that gives two votes to shares held longer than a year. Or maybe it would make sense to assign voting rights based on the average turnover of an investor’s portfolio. If we want capitalism to focus on the long term, updating our notions of shareholder democracy in such ways will soon seem less like heresy and more like common sense.

While I remain convinced that capitalism is the economic system best suited to advancing the human condition, I’m equally persuaded that it must be renewed, both to deal with the stresses and volatility ahead and to restore business’s standing as a force for good, worthy of the public’s trust. The deficiencies of the quarterly capitalism of the past few decades were not deficiencies in capitalism itself—just in that particular variant. By rebuilding capitalism for the long term, we can make it stronger, more resilient, more equitable, and better able to deliver the sustainable growth the world needs. The three imperatives outlined above can be a start along this path and, I hope, a way to launch the conversation; others will have their own ideas to add.

The kind of deep-seated, systemic changes I’m calling for can be achieved only if boards, business executives, and investors around the world take responsibility for bettering the system they lead. Such changes will not be easy; they are bound to encounter resistance, and business leaders today have more than enough to do just to keep their companies running well. We must make the effort regardless. If capitalism emerges from the crisis vibrant and renewed, future generations will thank us. But if we merely paper over the cracks and return to our precrisis views, we will not want to read what the historians of the future will write. The time to reflect—and to act—is now.

 

Please see my other related posts.

Business Investments and Low Interest Rates

Mergers and Acquisitions – Long Term Trends and Waves

 

 

Key sources of Research:

Secular stagnation and low investment: Breaking the vicious cycle—a discussion paper

McKinsey

http://www.mckinsey.com/global-themes/europe/secular-stagnation-and-low-investment-breaking-the-vicious-cycle

Case Still Out on Whether Corporate Short-Termism Is a Problem

Larry Summers

http://larrysummers.com/2017/02/09/case-still-out-on-whether-corporate-short-termism-is-a-problem/

Where companies with a long-term view outperform their peers

McKinsey

http://www.mckinsey.com/global-themes/long-term-capitalism/where-companies-with-a-long-term-view-outperform-their-peers

How short-term thinking hampers long-term economic growth

FT

https://www.ft.com/content/8c868a98-b821-11e4-b6a5-00144feab7de

Anthony Hilton: Short-term thinking hits nations as a whole, not just big business

http://www.standard.co.uk/comment/comment/anthony-hilton-short-term-thinking-hits-nations-as-a-whole-not-just-big-business-10427294.html

Short-termism in business: causes, mechanisms and consequences

EY Poland Report

http://www.ey.com/Publication/vwLUAssets/EY_Poland_Report/$FILE/Short-termism_raport_EY.pdf

Overcoming the Barriers to Long-term Thinking in Financial Markets

Ruth Curran and Alice Chapple
Forum for the Future

https://www.forumforthefuture.org/sites/default/files/project/downloads/long-term-thinking-fpf-report-july-11.pdf

Understanding Short-Termism: Questions and Consequences

http://rooseveltinstitute.org/wp-content/uploads/2015/11/Understanding-Short-Termism.pdf

Ending Short-Termism : An Investment Agenda for Growth

http://rooseveltinstitute.org/wp-content/uploads/2015/11/Ending-Short-Termism.pdf

The Short Long

Speech by
Andrew G Haldane, Executive Director, Financial Stability, and Richard Davies

Brussels May 2011

http://www.bankofengland.co.uk/archive/Documents/historicpubs/speeches/2011/speech495.pdf

Capitalism for the Long Term

Dominic Barton

From the March 2011 Issue

https://hbr.org/2011/03/capitalism-for-the-long-term

Quarterly capitalism: The pervasive effects of short-termism and austerity

https://currentlyunderdevelopment.wordpress.com/2016/05/10/quarterly-capitalism-the-pervasive-effects-of-short-termism-and-austerity/

Is Short-Term Behavior Jeopardizing the Future Prosperity of Business?

http://www.wlrk.com/docs/IsShortTermBehaviorJeopardizingTheFutureProsperityOfBusiness_CEOStrategicimplications.pdf

Andrew G Haldane: The short long

Speech by Mr Andrew Haldane, Executive Director, Financial Stability, and Mr Richard
Davies, Economist, Financial Institutions Division, Bank of England,
at the 29th Société
Universitaire Européene de Recherches Financières Colloquium,
Brussels, 11 May 2011

http://www.bis.org/review/r110511e.pdf

THE UNEASY CASE FOR FAVORING LONG-TERM SHAREHOLDERS

Jesse M. Fried

https://dash.harvard.edu/bitstream/handle/1/17985223/Fried_795.pdf?sequence=1

The fringe economic theory that might get traction in the 2016 campaign

https://www.washingtonpost.com/news/wonk/wp/2015/03/02/the-fringe-economic-theory-that-might-get-traction-in-the-2016-campaign/?utm_term=.932bc0b97758

FCLT Global:  Focusing Capital on the Long Term

Publications

http://www.fcltglobal.org/insights/publications

Finally, Evidence That Managing for the Long Term Pays Off

Dominic Barton

James Manyika

Sarah Keohane Williamson

February 07, 2017 UPDATED February 09, 2017

https://hbr.org/2017/02/finally-proof-that-managing-for-the-long-term-pays-off

Focusing Capital on the Long Term

Dominic Barton

Mark Wiseman

From the January–February 2014 Issue

Is Corporate Short-Termism Really a Problem? The Jury’s Still Out

Lawrence H. Summers

February 16, 2017

Yes, Short-Termism Really Is a Problem

Roger L. Martin

October 09, 2015

Long-Termism or Lemons

The Role of Public Policy in Promoting Long-Term Investments

By Marc Jarsulic, Brendan V. Duke, and Michael Madowitz October 2015

Center for American Progress

https://cdn.americanprogress.org/wp-content/uploads/2015/10/21060054/LongTermism-reportB.pdf

 

Overcoming Short-termism: A Call for A More Responsible Approach to Investment and Business Management

https://corpgov.law.harvard.edu/2009/09/11/overcoming-short-termism-a-call-for-a-more-responsible-approach-to-investment-and-business-management/

 

 

Focusing capital on the Long Term

Jean-Hugues Monier – Senior Parter – McKinsey & Company

Princeton University – November 2016

http://jrc.princeton.edu/sites/jrc/files/jean-hugues_j._monier_slides_final.pdf

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

 

https://www.uni-frankfurt.de/46314372/3-BerndtBoeckler2009.pdf

 

 

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

Martin Hess

Henry Wai-chung Yeung

 

https://courses.nus.edu.sg/course/geoywc/publication/2006%20EPA_Hess_Yeung.pdf

 

 

Rethinking relational economic geography

Henry Wai-chung Yeung

2005

 

https://courses.nus.edu.sg/course/geoywc/publication/2005_TIBG.pdf

 

 

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

 

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

https://www.researchgate.net/profile/Johannes_Glueckler/publication/5213254_Toward_a_Relational_Economic_Geography/links/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

 

http://www.globaltur.org/files/Conferences/SanzIbanez_AntonClave2014.pdf

https://www.researchgate.net/profile/Cinta_Sanz-Ibanez/publication/262688026_The_evolution_of_destinations_towards_an_evolutionary_and_relational_economic_geography_approach/links/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

 

https://courses.nus.edu.sg/course/geoywc/publication/DKOY_2001.pdf

 

 

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

Timothy J. Sturgeon

2003

 

https://ipc.mit.edu/sites/default/files/documents/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

https://www.researchgate.net/profile/Norma_Rantisi/publication/5213253_The_%27Relational_Turn%27_in_Economic_Geography/links/02e7e528f5e7bd37a5000000/The-Relational-Turn-in-Economic-Geography.pdf

 

 

Manifesto for a Relational Sociology

Mustafa Emirbayer

 

https://edisciplinas.usp.br/pluginfile.php/88938/mod_resource/content/1/Emirbayer%20Manifesto%20for%20a%20Relational%20Sociology.pdf

 

 

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

Peter Sunley

 

https://www.researchgate.net/profile/Peter_Sunley/publication/249475732_Relational_Economic_Geography_A_Partial_Understanding_or_a_New_Paradigm/links/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

http://econ.geo.uu.nl/peeg/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

http://openaccess.city.ac.uk/2603/1/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

https://www.researchgate.net/profile/Robert_Hassink/publication/261070844_Advancing_Evolutionary_Economic_Geography_by_Engaged_Pluralism/links/54200ea90cf241a65a1afcd4.pdf

 

 

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

Harald Bathelt

2006

https://tspace.library.utoronto.ca/bitstream/1807/71378/1/43_Bathelt%202006_PIHG.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) First Progress Report

 

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

 

http://www.imf.org/external/np/g20/pdf/2016/090216.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

 

http://www.fsb.org/wp-content/uploads/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

http://www.imf.org/external/np/g20/pdf/2014/5thprogressrep.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

 

http://www.imf.org/external/np/G20/pdf/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

http://www.imf.org/external/np/g20/pdf/093012.pdf

 

 

 

Implementation Progress Report

 

Prepared by the IMF Staff and the FSB Secretariat June 2011

http://www.imf.org/external/np/g20/pdf/063011.pdf

 

 

 

Progress Report Action Plans and Timetables

 

Prepared by the IMF Staff and the FSB Secretariat May 2010

 

http://www.imf.org/external/np/g20/pdf/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

 

http://www.imf.org/external/np/g20/pdf/102909.pdf

 

 

 

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

by Robert Heath and Evrim Bese Goksu

2016

https://www.imf.org/external/pubs/ft/wp/2016/wp1643.pdf

 

 

 

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

Robert Heath

http://www.imf.org/external/pubs/ft/wp/2013/wp1306.pdf

 

 

 

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

Manik Shrestha

 

http://www.nber.org/chapters/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

 

https://www.imf.org/external/pubs/ft/wp/2012/wp1257.pdf

 

 

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

Mink, Reimund

https://www.bis.org/ifc/events/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

 

https://www.imf.org/external/np/seminars/eng/2011/sta/pdf/g20a.pdf

 

 

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

2011

 

https://www.imf.org/external/np/seminars/eng/2011/sta/pdf/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

 

https://www.czso.cz/staticke/conference2009/proceedings/data/quaterly_accounts/leone_paper.pdf

 

 

Development of financial sectoral accounts

New opportunities and challenges for supporting financial stability analysis

by Bruno Tissot

2016

 

http://www.bis.org/ifc/publ/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

http://2011.isiproceedings.org/papers/650287.pdf

 

 

Expanding the Integrated Macroeconomic Accounts’ Financial Sector

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

2016

https://www.bea.gov/scb/pdf/2016/01%20January/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

http://www.imf.org/external/pubs/ft/wp/2006/wp06100.pdf

 

 

Balance Sheet Analysis: A New Approach to Financial Stability

Surveillance

By Jean Christine A. Armas

2016

 

http://www.bsp.gov.ph/downloads/EcoNews/EN16-01.pdf

 

 

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

 

http://www.suomenpankki.fi/en/tutkimus/konferenssit/konferenssit_tyopajat/Documents/JFS2007/JFS2007_HaimLevy_pres.pdf

http://www.boi.org.il/deptdata/stability/papers/dp0701e.pdf

 

 

 

A Balance Sheet Approach to Financial Crisis

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

2002

https://www.imf.org/external/pubs/ft/wp/2002/wp02210.pdf

 

 

THE BALANCE SHEET APPROACH TO FINANCIAL CRISES IN EMERGING MARKETS

Giovanni Cozzi and
Jan Toporowski

2006

http://www.levyinstitute.org/pubs/wp_485.pdf

 

 

Balance-sheets. A financial/liability approach

Bo Bergman

2015

 

http://iariw.org/papers/2015/bergman_paper.pdf

 

 

Understanding Financial Crisis Through Accounting Models

Dirk J Bezemer

2009

http://www.uclm.es/actividades/2009/workshopESHET-UCLM/Bezemer_-_No_one_show_this_comming.pdf

 

 

 

Schumpeter Might Be Right Again: The Functional Differentiation of Credit

Dirk J. Bezemer
University of Groningen

https://www.rug.nl/staff/d.j.bezemer/the_functional_differentiation_of_credit.pdf

 

 

Causes of Financial Instability: Don’t Forget Finance

Dirk J. Bezemer

April 2011

 

http://www.levyinstitute.org/pubs/wp_665.pdf

 

 

THE ECONOMY AS A COMPLEX SYSTEM: THE BALANCE SHEET DIMENSION

DIRK J BEZEMER

2012

http://www.economicsofcreditanddebt.org/media/research/ACS_1250047_1st_Prf.pdf

 

 

Did Credit Decouple from Output in the Great Moderation?

Maria Grydaki and Dirk Bezemer

June 2013

https://mpra.ub.uni-muenchen.de/47424/1/MPRA_paper_47424.pdf

 

 

 

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

Dirk J. Bezemer

2016

http://www.economicsofcreditanddebt.org/media/research/Camb._J._Econ.-2016-Bezemer-1275-95.pdf

 

 

Modelling systemic financial sector and sovereign risk

Dale F. Gray anD anDreas a. Jobst

2011

 

http://www3.tcmb.gov.tr/konferanslar/fsr/Gray_2.pdf

 

 

BALANCE SHEET ANALYSIS IN FUND SURVEILLANCE

2015

https://www.imf.org/external/np/pp/eng/2015/061215.pdf

https://www.imf.org/external/np/pp/eng/2015/071315.pdf

 

 

The role of external balance sheets in the financial crisis

Yaser Al-Saffar, Wolfgang Ridinger and Simon Whitaker

2013

 

http://www.bankofengland.co.uk/financialstability/Documents/fpc/fspapers/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

 

http://g20chn.org/English/Documents/Current/201608/P020160811536051676178.pdf

 

 

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

http://www.imfmetac.org/Upload/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

https://www.imf.org/external/pubs/ft/wp/2015/wp15111.pdf

 

 

2014 TRIENNIAL SURVEILLANCE REVIEW—EXTERNAL STUDY—RISKS AND SPILLOVERS

Prepared By David Daokui Li and Paul Tucker

 

https://www.imf.org/external/np/pp/eng/2014/073014e.pdf

https://www.imf.org/external/pubs/ft/bop/2014/pdf/14-10.pdf

 

 

 

2014 TRIENNIAL SURVEILLANCE REVIEW—OVERVIEW PAPER

 

http://www.imf.org/external/np/pp/eng/2014/073014.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

http://iariw.org/papers/2015/zhang.pdf

 

 

Cross-border financial linkages: Identifying and measuring vulnerabilities

 

Philip R. Lane

2014

 

http://cepr.org/sites/default/files/policy_insights/PolicyInsight77.pdf

 

 

Global Flow of Funds: Mapping Bilateral Geographic Flows

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

 

2013

http://2013.isiproceedings.org/Files/STS083-P1-S.pdf

 

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

 

Nan Zhang

 

http://ns1.shudo-u.ac.jp/~zhang/08GFOF.pdf

 

 

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

Hyun Song Shin

Princeton University

https://www.imf.org/external/np/seminars/eng/2013/sta/forum/pdf/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

https://pdfs.semanticscholar.org/48dd/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

http://www.bankofengland.co.uk/publications/Documents/speeches/2014/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

http://www.relooney.com/NS3040/0_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

https://www.federalreserve.gov/pubs/feds/1997/199729/199729pap.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

https://www.federalreserve.gov/pubs/feds/1996/199642/199642pap.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

https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr647.pdf

 

 

Can Disequilibrium Macroeconomic Models Be Used to Anticipate Financial Instability?

A Case Study

Dirk J. Bezemer

 

https://pdfs.semanticscholar.org/224f/a6d8daa2716892ed0984f8aa0882c6dccefc.pdf

 

 

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

John B. Taylor

November 2016

http://web.stanford.edu/~johntayl/2016_pdfs/Text_Keynote_BoC_Workshop_Taylor-2016.pdf

 

 

DSGE models and central banks

by Camilo E Tovar

2008

http://www.bis.org/publ/work258.pdf

 

 

Macro-Finance Models of Interest Rates and the Economy

Glenn D. Rudebusch∗
Federal Reserve Bank of San Francisco

https://pdfs.semanticscholar.org/6b60/3c8c75a3daa52749dd4ade71f9ae1642f9aa.pdf

 

 

Panel Discussion on Uses of Models at Central Banks

ECB Workshop on DSGE Models and Forecasting September 23, 2016

John Roberts

 

https://www.ecb.europa.eu/pub/conferences/shared/pdf/20160922_dsge/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

 

http://www.macromodelbase.com/fileadmin/user_upload/documents/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

 

http://www.economics.ox.ac.uk/materials/papers/12225/paper622.pdf

 

 

FRB/US Equations Documentation

http://www.petertulip.com/frbus_equation_documentation.pdf

 

 

Challenges for Central Banks’ Macro Models

Jesper Lindé, Frank Smets and Rafael Wouters

2016

 

http://www.riksbank.se/Documents/Rapporter/Working_papers/2016/rap_wp323_160512.pdf

 

 

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

John B. Taylor

2016

 

http://www.bankofcanada.ca/wp-content/uploads/2016/12/central-bank-models-lessons-past.pdf

 

 

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

Ignazio Visco

2014

 

http://economics.sas.upenn.edu/sites/economics.sas.upenn.edu/files/u4/Visco_Klein_2014.pdf

 

 

Macro-Econometric System Modelling @75

Tony Hall  Jan Jacobs Adrian Pagan

http://www.ncer.edu.au/papers/documents/WP95.pdf

 

 

The Econometrics of Macroeconomic Modelling

Gunnar Ba ̊rdsenØyvind Eitrheim Eilev S. Jansen Ragnar Nymoen

http://folk.uio.no/rnymoen/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

 

http://eprints.qut.edu.au/385/1/Valadkhani_131.pdf

 

 

ECONOMETRICS: AN HISTORICAL GUIDE FOR THE UNINITIATED

by D.S.G. Pollock

University of Leicester

http://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp14-05.pdf

 

 

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

N R Bhanumurthy NIPFP, New Delhi, India

 

http://www.mse.ac.in/wp-content/uploads/2016/09/Model-1.pdf

 

 

ECONOMIC MODELS

 

http://pages.hmc.edu/evans/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

 

http://www.unescap.org/sites/default/files/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

 

http://www.bcb.gov.br/secre/apres/Apresentação%20Michael%20Kiley.pdf

 

 

Policy Analysis Using DSGE Models: An Introduction

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

2010

 

https://www.newyorkfed.org/medialibrary/media/research/epr/10v16n2/1010sbor.pdf

 

 

DSGE Model-Based Forecasting

Marco Del Negro Frank Schorfheide

Staff Report No. 554 March 2012

 

https://pdfs.semanticscholar.org/7597/2761a45dbc2a4b57990d250adb8ae846129f.pdf

 

 

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

Marco Del Negro

 

https://www.ecb.europa.eu/pub/conferences/shared/pdf/20160922_dsge/DelNegro_DSGE_forecasting_panel.pdf

 

 

Modern Macroeconomic Models as Tools for Economic Policy

Narayana Kocherlakota

 

https://www.minneapolisfed.org/~/media/files/pubs/region/10-05/2009_mplsfed_annualreport_essay.pdf

 

 

STRUCTURAL ECONOMETRIC MODELLING: METHODOLOGY AND TOOLS WITH APPLICATIONS UNDER EVIEWS

 

http://www.eviews.com/StructModel/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

https://bfi.uchicago.edu/sites/default/files/research/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

 

Jay W. Forrester and System Dynamics

Jay W. Forrester and System Dynamics

 

 

Jay Forrester passed away at the age of 98 on November 16, 2016

The link below will take you to JWF memorial webpage.

Jay W Forrester Memorial Web Page at the System Dynamics Society

I admire Jay W Forrester greatly.  I was introduced to Operational Research and System dynamics back in early 1980s after I graduated from IIT Roorkee Engineering undergraduate degree in India.  I had bought a book on Operations Research at a road side book seller in Dariya Ganj, Old Delhi, India.

I met Jay on three occasions.  I attended Business Dynamics Executive Education program at MIT Sloan School of Management back in 2002.  Jay was one of the Instructor.  Then I again met Jay at 2003 SDS International Conference at New York City.  Last time I met Jay was in Washington DC at the Club of Rome Symposium celebrating 40 yrs anniversary of publication of The Limits to Growth book.

Jay will be missed greatly.

– Mayank Chaturvedi

 

Jay Forrester’s vision of future of Economics and System Dynamics.

Traditional mainstream academic economics, by trying to be a science, has failed to answer major questions about real- life economic behavior. Economics should become a systems profession, such as management, engineering, and medicine. By closely observing the structures and policies in business and government, simulation models can be constructed to answer questions about business cycles, causes of major depressions, inflation, monetary policy, and the validity of descriptive economic theories. A system dynamics model, as a general theory of economic behavior, now endogenously generates business cycles, Kuznets cycles, the economic long wave, and growth. A model is a theory of the behavior that it generates. The economic model provides the theory, thus far missing from economics, for the Great Depression of the 1930s and how such episodes can recur 50–70 years apart. Simpler system dynamics models can become the vehicle for a relevant and exciting pre-college economics education.

 

From PHD thesis of I David Wheat

Within the interdisciplinary system dynamics (SD) community, the motivation to improve understanding of economic systems came nearly fifty years ago with Jay W. Forrester’s seminal call for a new kind of economics education, a call that he has renewed in the K-12 education setting in recent years. John Sterman’s encyclopedic Business Dynamics is a symbol not only of the breadth of his own economic policy and management research and teaching but also the range of work done by others in this field.

Teaching the economics of resource management with system dynamics tools has been the devotion of Andrew Ford and Erling Moxnes. James Lyneis took his management consultant’s expertise into the university classroom and developed an SD-based microeconomics course. Economists Michael Radzicki and Kaoru Yamaguchi have developed complete graduate-level economics courses on a system dynamics foundation. An informal survey produced this list of others who have used SD as a teaching tool in economics courses: Glen Atkinson, Scott Fullwiler, John Harvey, Steve Keen, Ali Mashayekhi, Jairo Parada, Oleg Pavlov, Khalid Saeed, Jim Sturgeon, Linwood Tauheed, Pavlina Tcherneva, Scott Trees, Eric Tymoigne, Lars Weber, and Agnieszka Ziomek, and that is surely just a fraction.

 

Key Sources of Research:

 

Economic theory for the new millennium

Jay W. Forrester

2003

 

System Dynamics Review vol 29, No 1 (January-March 2013): 26–41

 

 

 

Three slices of Jay Forrester’s general theory of economic behavior: An interpretation

 

Khalid Saeed

Worcester Polytechnic Institute Worcester, MA, USA

February 13, 2013

 

http://www.systemdynamics.org/conferences/2013/proceed/papers/P1018.pdf

 

 

System Dynamics: A disruptive science

A conversation with Jay W. Forrester, founder of the field

Khalid Saeed Worcester Polytechnic Institute Sept. 2013

 

http://static.clexchange.org/ftp/ISDC2013_forresterchat.pdf

http://digitalcommons.wpi.edu/cgi/viewcontent.cgi?article=1000&context=ssps-papers&sei-redir=1&referer=https%3A%2F%2Fscholar.google.com%2Fscholar%3Fstart%3D40%26q%3Djay%2Bw%2Bforrester%2Bsystem%2Bdynamics%26hl%3Den%26as_sdt%3D0%2C47%26as_ylo%3D2013#search=%22jay%20w%20forrester%20system%20dynamics%22

 

 

Unintended Consequences

Jay Forrester

http://simgua.com/documents/SB_Forrester.pdf

 

 

A dynamic synthesis of basic macroeconomic theory : implications for stabilization policy analysis

Nathan Forrester

PHD THESIS

https://dspace.mit.edu/handle/1721.1/15739

 

 

SYSTEM DYNAMICS: PORTRAYING BOUNDED RATIONALITY

 

John D.W. Morecroft

1982

 

https://dspace.mit.edu/bitstream/handle/1721.1/49181/systemdynamicspo00more.pdf?sequence=1

 

 

THE SYSTEM DYNAMICS NATIONAL MODEL:  MACRO BEHAVIOR FROM MICRO STRUCTURE

JAY W FORRESTER

 

http://systemsmodelbook.org/uploadedfile/1470_0a924c5b-b909-42fa-be9b-932588278f36_forre004.pdf

 

 

1976 Economic Forecast Report including studies by Jay W Forrester and Nathial Mass

US congress Joint Economic Review of US Economy

http://njlaw.rutgers.edu/collections/gdoc/hearings/7/76603310f/76603310f_1.pdf

 

 

Backround Material for a Meeting on Long Waves, Depression and Innovation –

IMPLICATIONS FOR NATIONAL AND REGIONAL ECONOMIC POLICY

Jay W. Forrester, Alan K.Oraham, Peter M.Senge, John D Sterman

 

Siena/Florence, October 26-29, 1983

Bianchi, G., Bruckmann, G. and Vasko, T.

 

http://pure.iiasa.ac.at/2338/1/CP-83-044.pdf

 

 

 

Industrial Dynamics-After the First Decade

Author(s): Jay W. Forrester

Management Science, Vol. 14, No. 7, Theory Series (Mar., 1968), pp. 398-415

 

http://www.sfu.ca/~vdabbagh/Forrester68.pdf

 

 

Systems Analysis as a Tool for Urban Planning

JAY W. FORRESTER, FELLOW, IEEE

1970

 

http://web.boun.edu.tr/ali.saysel/ESc59M/forrester.pdf

 

 

IS ECONOMETRIC MODELING OBSOLETE?

AUTHOR: Mr. Oakley E. Van Slyke

 

https://www.casact.org/pubs/dpp/dpp80/80dpp650.pdf

 

 

Money and Macroeconomic Dynamics : Accounting System Dynamics Approach

 

Kaoru Yamaguchi

Ph.D. Japan Futures Research Center

Awaji Island, Japan

November 11, 2016

 

http://muratopia.org/Yamaguchi/macrodynamics/Macro%20Dynamics.pdf

 

 

The Feedback Method : A System Dynamics Approach to Teaching Macroeconomics

I. David Wheat, Jr.

Dissertation for the degree philosophiae doctor (PhD)

System Dynamics Group, Social Science Faculty University of Bergen

 

http://bora.uib.no/bitstream/handle/1956/2239/Introduction_David_Wheat.pdf?sequence=46

 

 

Disequilibrium Systems Representation of Growth Models—Harrod-Domar, Solow, Leontief, Minsky, and Why the U.S. Fed Opened the Discount Window to Money-Market Funds

Frederick Betz

2015

 

http://file.scirp.org/pdf/ME_2015120814432915.pdf

 

 

Cyclical dynamics of airline industry earnings

Kawika Piersona and John D. Sterman

System Dynamics Review vol 29, No 3 (July-September 2013): 129–156

https://www.researchgate.net/profile/John_Sterman2/publication/259542762_Cyclical_dynamics_of_airline_industry_earnings/links/5550ead108ae739bdb9202a9.pdf

 

 

 

Modeling Financial Instability

Steve Keen

http://www.debtdeflation.com/blogs/wp-content/uploads/2014/02/Keen2014ModelingFinancialInstability.pdf

 

 

Harvey, J.T.,

2013.

Keynes’s trade cycle: a system dynamics model.

Journal of Post Keynesian Economics, 36(1), pp.105-130.

 

 

ECONOMICS, TECHNOLOGY, AND THE ENVIRONMENT

Jay Forrester

 

https://dspace.mit.edu/bitstream/handle/1721.1/2197/SWP-1983-18213738.pdf?sequence=1

 

 

Forrester, J. W. (1968). Market Growth as Influenced by Capital Investment. Industrial Management Review (now Sloan Management Review), 9(2), 83-105.

 

 

Forrester, J. W 1971). Counterintuitive Behavior of Social Systems. Collected Papers of J.W. Forrester. Cambridge, MA: Wright-Allen Press.

 

 

Forrester, J. W (1976). Business Structure, Economic Cycles, and National Policy. Futures, June.

 

 

Forrester, J. W (1979). An Alternative Approach to Economic Policy: Macrobehavior from Microstructure. In Kamrany & Day (Eds.), Economic Issues of the Eighties. Baltimore: The Johns Hopkins University Press.

 

 

Forrester, J. W., Mass, N. J., & Ryan, C. (1980). The System Dynamics National Model: Understanding Socio-economic Behavior and Policy Alternatives. Technology Forecasting and Social Change, 9, 51-68.

 

 

Forrester, N. B. (1982). A Dynamic Synthesis of Basic Macroeconomic Theory: Implications for Stabilization Policy Analysis. Unpublished PhD dissertation, Massachusetts Institute of Technology, Cambridge, MA.

 

 

Low, G. (1980). The Multiplier-Accelerator Model of Business Cycles Interpreted from a System Dynamics Perspective. In J. Randers (Ed.), Elements of the System Dynamics Method. Cambridge, MA: MIT Press.

 

 

Mass, N. J. (1975). Economic Cycles: An Analysis of Underlying Causes. Cambridge, MA: Wright-Allen Press, Inc.

 

 

Mass, N. J.(1980). Stock and Flow Variables and the Dynamics of Supply and Demand. In J. Randers (Ed.), Elements of the System Dynamics Method. (pp. 95-112). Cambridge, MA: MIT Press.

 

 

Meadows, D. L., Behrens III, W. W., Meadows, D. H., Naill, R. F., & Zahn, E. (1974). Dynamics of Growth in a Finite World. Cambridge, MA: Wright-Allen Press.

 

 

Morecroft, J. D. W. & Sterman, J. D. (Eds.). (1994). Modeling for Learning Organizations. Portland, OR: Productivity Press.

 

 

Radzicki, M. (1993). A System Dynamics Approach to Macroeconomics (Guest lecture at the Department of Information Science, University of Bergen.).

 

 

Richardson, G. P. (1991). Feedback Thought in Social Science and Systems Theory. Waltham, MA: Pegasus Communications, Inc.

 

 

Senge, P. M. (1990). The Fifth Discipline: The Art and Practice of the Learning Organization. New York: Doubleday.

 

 

Sterman, J. D. (1985). A Behavioral Model of the Economic Long Wave. Journal of Economic Behavior and Organization, 6, 17-53.

 

 

Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston, MA: McGraw-Hill Companies.

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

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

 

Increasing Returns is another term for Positive Feedback loop.

Path Dependence is also known as Lock-In

Circular and Cumulative Causation is another name for Positive Feedback Loop.

 

Vicious Circle – Bad gets to worse, Failure leads to more failure

Virtuous Circle – Success breeds Success, Wealth gets more wealth

 

See this Document – Book Foreward by Geoffrey Hodgson

Geoffrey Hodgson foreward in a book The Foundations of Non Equilibrium Economics.

 

Key Economists :

  • Allyn Young
  • Gunnar Myrdal
  • Karl William Kapp
  • Kaldor
  • Veblen
  • Paul Romer
  • Knut Wicksell
  • W. Brian Arthur
  • Paul David
  • Steven Durlauf
  • Nicholas Georgescu-Roegen

 

Various Increasing Returns, Circular and Cumulative Causations Theories

  • CCC Theory of Allyn Young
  • CCC Theory of N Kaldor
  • CCC Theory of Gunnar Myrdal
  • CCC Theory of T Veblen
  • CCC Theory of Paul Romer
  • CCC Theory of Paul Krugman
  • CCC Theory of W. Brain Arthur

 

Circular Causation in Kaldor Theory

kaldor

 

 

Key Sources of Research:

 

A A Young

Increasing Returns and Technical Progress

The Economic Journal

1928

https://periferiaactiva.files.wordpress.com/2015/08/young28.pdf

 

 

Kaldor, N. (1966)

Causes of the Slow Rate of Economic Growth of the United Kingdom,

Cambridge: Cambridge University Press.

 

 

Kaldor, N. (1970)

“The case for regional policies,”

Scottish Journal of Political Economy, 17, pp. 337-348.

 

 

Kaldor, N. (1985)

Economics Without Equilibrium,

Cardiff, University College Cardiff Press.

 

 

Kaldor, N. (1996)

Causes of Growth and Stagnation in the World Economy,

Cambridge, Cambridge University Press

 

 

 

Kaldor, N., 1981.

The role of increasing returns, technical progress and cumulative causation in the theory of international trade and economic growth.

Economie appliquée, 34(4), pp.593-617.

 

 

Nicholas Kaldor on Endogenous Money and Increasing Returns

Guglielmo Forges Davanzati

2013

 

http://www.siecon.org/online/wp-content/uploads/2015/10/Forges.pdf

 

 

Fujita, Nanako.

“Myrdal’s theory of cumulative causation.”

Evolutionary and Institutional Economics Review 3, no. 2 (2007): 275-284.

 

 

Gunnar Myrdal’s Theory of Cumulative Causation Revisited

Nanako Fujita

 

http://ir.nul.nagoya-u.ac.jp/jspui/bitstream/2237/11958/3/paper147.pdf

 

 

Circular Cumulative Causation (CCC) à la Myrdal and Kapp — Political Institutionalism for Minimizing Social Costs

Sebastian Berger

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.587.5765&rep=rep1&type=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://www.lim.uni-bremen.de/files/elsner/publikationen/European_Institutionalism_Berger_Elsner_JEI_No_2_07_5_07.pdf

 

 

Dutt, Amitava Krishna.

“Path dependence, equilibrium and economic growth.”

In Path Dependency and Macroeconomics, pp. 119-161. Palgrave Macmillan UK, 2009.

 

 

Setterfield, Mark.

“Notes and comments. Cumulative causation, interrelatedness and the theory of economic growth: a reply to Argyrous and Toner.”

Cambridge Journal of Economics 25, no. 1 (2001): 107-112.

 

 

Setterfield, Mark.

“‘History versus equilibrium’and the theory of economic growth.”

Cambridge Journal of Economics 21, no. 3 (1997): 365-378.

 

 

Setterfield, M. (2009)

“Path dependency, hysteresis and macrodynamics,”

in P. Arestis and M. Sawyer (eds) Path Dependency and Macroeconomics (International Papers in Political Economy 2009), London, Palgrave Macmillan, 37-79

 

 

Setterfield, M.

(1997a)

Rapid Growth and Relative Decline: Modelling Macroeconomic Dynamics with Hysteresis,

London: Macmillan.

 

 

 

Kaldor’s 1970 Regional Growth Model Revisited

A.P.Thirlwall

ftp://ftp.ukc.ac.uk/pub/ejr/RePEc/ukc/ukcedp/1311.pdf

 

 

Argyrous, George.

“Setterfield on cumulative causation and interrelatedness: a comment.”

Cambridge Journal of Economics 25, no. 1 (2001): 103-106.

 

 

Endogenous Growth: A Kaldorian Approach

Mark Setterfield

2010

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.163.8257&rep=rep1&type=pdf

 

 

Increasing Returns and Long Run Growth

Paul Romer

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.589.3348&rep=rep1&type=pdf

 

 

O’Hara, P.A., 2008.

Principle of circular and cumulative causation: Fusing Myrdalian and Kaldorian growth and development dynamics.

Journal of Economic Issues, 42(2), pp.375-387.

 

 

Path Dependency and Macroeconomics

edited by P. Arestis, Malcolm Sawyer

 

 

Main Currents in Cumulative Causation: The Dynamics of Growth and Development
Phillip Toner
Palgrave Macmillan UK, May 12, 1999 – Business & Economics – 228 pages

 

 

 

Why is Economics not an Evolutionary Science?

Thorstein Veblen

(with an introduction by Jean Boulton)

 

https://emergentpublications.com/ECO/ECO_other/Issue_12_2_6_CP.pdf?AspxAutoDetectCookieSupport=1

 

 

 

On the evolution of Thorstein Veblen’s evolutionary economics

Geoffrey M. Hodgson

 

http://www.geoffrey-hodgson.info/user/image/evveblenec.pdf

 

 

 

“Different epistemologies beneath similar methods: The case of causal loop thinkers.”

Maruyama, Magoroh.

Human Systems Management 9, no. 3 (1990): 195-198.

http://content.iospress.com/download/human-systems-management/hsm9-3-07?id=human-systems-management%2Fhsm9-3-07

 

 

The feedback concept in American social science, with implications for system dynamics.

Richardson, G.

(1983, July).

http://www.systemdynamics.org/conferences/1983/proceed/plenary/richa001.pdf

 

 

Path Dependence in Aggregate Output

STEVEN N. DURLAUF

 

https://pdfs.semanticscholar.org/30c8/9870fa9010ed42d897dae442a3316d5cf805.pdf

 

 

Nonergodic Economic Growth

STEVEN N. DURLAUF

 

http://ssc.wisc.edu/~sdurlauf//includes/pdf/Nonergodic%20Economic%20Growth.pdf

 

 

Evolution and Path Dependence in Economic Ideas: Past and Present

edited by Pierre Garrouste, Stavros Ioannides,

European Association for Evolutionary Political Economy

 

 

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

Paul A. David

http://www-siepr.stanford.edu/workp/swp00011.pdf

 

 

Positive Feedbacks and Research Productivity in Science: Reopening Another Black Box

Paul A. David

 

http://www.aidaf-ey.unibocconi.it/wps/allegatiCTP/David(1994)_PositiveFeedbacks_Marstrand3_re-release%5B1%5D.20070702.120531.pdf

 

 

Increasing Returns and Path Dependence in the Economy

By W. Brian Arthur

University of Michigan Press, 1994 – Business & Economics – 201 pages

 

 

Positive Feedbacks in the Economy

W. Brian Arthur

26 November 1989

 

https://files.itslearning.com/data/ntnu/open/co35568/1558085.pdf?

 

 

Complexity economics: a different framework for economic thought

W. Brian Arthur

March 12, 2013

 

http://tuvalu.santafe.edu/~wbarthur/Papers/Comp.Econ.SFI.pdf

 

 

A webpage for resources on Path dependence in Economics

http://www2.econ.iastate.edu/tesfatsi/apathdep.htm

 

 

The Foundations of Non-Equilibrium Economics: The Principle of Circular and Cumulative Causation

edited by Sebastian Berger

 

 

The New Approach to Regional Economics Dynamics: Path Dependence and Spatial Self-Reinforcing Mechanisms

Domenico Marino and Raffaele Trapasso

 

http://ebooks.narotama.ac.id/files/Growth%20and%20Innovation%20of%20Competitive%20Regions;%20The%20Role%20of%20Internal%20and%20External%20Connections/Chapter%2015%20The%20New%20Approach%20to%20Regional%20Economics%20Dynamics;%20Path%20Dependence%20and%20Spatial%20Self-Reinforcing%20Mechanisms.pdf

 

Positive Feedback Mechanisms in. Economic Development: A Review of Recent Contributions

A RODRFGUEZ-CLARE

http://eml.berkeley.edu/~arodeml/Papers/Positive%20Feedback%20Mechanisms%20in%20Economic%20Development.pdf

 

 

Increasing Returns and Economic Geography

Paul Krugman

JPE,1991

March 4, 2010

 

http://dave-donaldson.com/wp-content/uploads/2015/12/krugman91.pdf