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


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

Larry Summers

Where companies with a long-term view outperform their peers


How short-term thinking hampers long-term economic growth


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

Short-termism in business: causes, mechanisms and consequences

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

Understanding Short-Termism: Questions and Consequences

Ending Short-Termism : An Investment Agenda for Growth

The Short Long

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

Brussels May 2011

Capitalism for the Long Term

Dominic Barton

From the March 2011 Issue

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

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

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


Jesse M. Fried

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

FCLT Global:  Focusing Capital on the Long Term


Finally, Evidence That Managing for the Long Term Pays Off

Dominic Barton

James Manyika

Sarah Keohane Williamson

February 07, 2017 UPDATED February 09, 2017

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


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

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



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



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

  • 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
  • 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.


  • Model developed for Canada



From Economic Theory, Model Size, and Model Purpose





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).



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



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



USA Central Bank Models

A. FRB Models (Neo Classical)

  • FRB/US (since 1996)
  • VAR Models
  • Accelerator Models


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



The Evolution of Macro Models at the Federal Reserve Board

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

Revised: February 7, 1997



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



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

Flint Brayton, Thomas Laubach, and David Reifschneider




Estimated Dynamic Optimization (EDO) Model




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





Can Disequilibrium Macroeconomic Models Be Used to Anticipate Financial Instability?

A Case Study

Dirk J. Bezemer



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

John B. Taylor

November 2016



DSGE models and central banks

by Camilo E Tovar




Macro-Finance Models of Interest Rates and the Economy

Glenn D. Rudebusch∗
Federal Reserve Bank of San Francisco



Panel Discussion on Uses of Models at Central Banks

ECB Workshop on DSGE Models and Forecasting September 23, 2016

John Roberts



The Chicago Fed DSGE Model

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

August 16, 2012



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

John Muellbauer

21 December 2016



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




John Duca and John Muellbauer

September 2012



FRB/US Equations Documentation



Challenges for Central Banks’ Macro Models

Jesper Lindé, Frank Smets and Rafael Wouters




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

John B. Taylor




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

Ignazio Visco




Macro-Econometric System Modelling @75

Tony Hall  Jan Jacobs Adrian Pagan



The Econometrics of Macroeconomic Modelling

Gunnar Ba ̊rdsenØyvind Eitrheim Eilev S. Jansen Ragnar Nymoen



The Macroeconomist as Scientist and Engineer

N. Gregory Mankiw

May 2006



 Macroeconometric Models

By Władysław Welfe




Abbas Valadkhani




by D.S.G. Pollock

University of Leicester



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

N R Bhanumurthy NIPFP, New Delhi, India











Macroeconomic Modeling in India

N R Bhanumurthy NIPFP, New Delhi, India



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


Michael Kileyção%20Michael%20Kiley.pdf



Policy Analysis Using DSGE Models: An Introduction

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




DSGE Model-Based Forecasting

Marco Del Negro Frank Schorfheide

Staff Report No. 554 March 2012



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

Marco Del Negro



Modern Macroeconomic Models as Tools for Economic Policy

Narayana Kocherlakota






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



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




Economic Theory, Model Size, and Model Purpose

John B Taylor

Chapter in a Book Large Scale Macroe conomtric Models



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



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



System Dynamics: A disruptive science

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

Khalid Saeed Worcester Polytechnic Institute Sept. 2013



Unintended Consequences

Jay Forrester



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

Nathan Forrester






John D.W. Morecroft








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

US congress Joint Economic Review of US Economy



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


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.




Industrial Dynamics-After the First Decade

Author(s): Jay W. Forrester

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



Systems Analysis as a Tool for Urban Planning






AUTHOR: Mr. Oakley E. Van Slyke



Money and Macroeconomic Dynamics : Accounting System Dynamics Approach


Kaoru Yamaguchi

Ph.D. Japan Futures Research Center

Awaji Island, Japan

November 11, 2016



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



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




Cyclical dynamics of airline industry earnings

Kawika Piersona and John D. Sterman

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




Modeling Financial Instability

Steve Keen



Harvey, J.T.,


Keynes’s trade cycle: a system dynamics model.

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




Jay Forrester



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




Key Sources of Research:


A A Young

Increasing Returns and Technical Progress

The Economic Journal




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




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



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

Sebastian Berger



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



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.


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

London: Macmillan.




Kaldor’s 1970 Regional Growth Model Revisited




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




Increasing Returns and Long Run Growth

Paul Romer



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)




On the evolution of Thorstein Veblen’s evolutionary economics

Geoffrey M. Hodgson




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

Maruyama, Magoroh.

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



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

Richardson, G.

(1983, July).



Path Dependence in Aggregate Output




Nonergodic Economic Growth




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



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

Paul A. David



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



Complexity economics: a different framework for economic thought

W. Brian Arthur

March 12, 2013



A webpage for resources on Path dependence in Economics



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;%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




Increasing Returns and Economic Geography

Paul Krugman


March 4, 2010

Classical roots of Interdependence in Economics


When did economists start thinking systematically?

Where do we find it now in Economics?

  • Systems Thinking
  • Interdependence
  • Interconnectedness


From  Structural Interdependence in Monetary Economics: Theoretical Assessment and Policy Implications


Acknowledgment of the existence of structural interconnections in a sufficiently developed country is not a novelty in the literature of economics. It has been present since its very beginning, in Quesnay’s Tableau Économique and Petty’s and Cantillon’s descriptions of production and consumption as a circular flow. Significant evidence of structural interdependence is provided by Walras’s general equilibrium model, by Marx’s reproduction schemes and by his circuit of capital, by Keynes’s dismissal of the ‘classical’ assumption of a dichotomic economic system, by Leontief’s inter-industry input-output analysis, and by other analytical approaches (von Neumann and Morgenstern strategic game theory, Copeland’s flow-of-funds tables, Koopmans’s activity analysis of production and allocation).


Relevant contributions to the literature on structural interdependence in economics have been made by Tobin, Davidson, Meade and Stone, Godley and Cripps, Lavoie, Lance Taylor and others, with reference to specific institutional frameworks. In the last decades this branch of research has attracted increasing attention. Sectoral flows of funds connecting balance sheets have been analyzed. Some controversial issues, however, regarding the integration of money and finance in the theory of value and the structural relations between stock and flow variables, are still partially unsettled.


From ‘Classical’ Roots of Input-Output Analysis: A Short Account of its Long Prehistory


According to Wassily Leontief, ‘Input-output analysis is a practical extension of the classical theory of general interdependence which views the whole economy of a region, a country and even of the entire world as a single system and sets out to describe and to interpret its operation in terms of directly observable basic structural relationships’ (Leontief, 1987, p. 860).


The key terms in this characterisation are ‘classical theory’, ‘general interdependence’ and ‘directly observable basic structural relationships’. In this overview of contributions that can be said to have prepared the ground for input-output analysis proper, ‘classical theory’ will be interpreted to refer to the contributions of the early classical economists from William Petty to David Ricardo; further elaborated by authors such as Karl Marx, Vladimir K. Dmitriev, Ladislaus von Bortkiewicz and Georg von Charasoff; and culminating in the works of John von Neumann and Piero Sraffa. ‘General interdependence’ will be taken to involve two intimately intertwined problems, which, in a first step of the analysis, may however be treated separately. First, there is the problem of quantity for which a structure of the levels of operation of processes of production is needed in order to guarantee the reproduction of the means of production used up in the course of production and the satisfaction of some ‘final demand’, that is, the needs and wants of the different groups (or ‘classes’) of society, perhaps making allowance for the growth of the system. Secondly, there is the problem of price for which a structure of exchange values of the different products or commodities is needed in order to guarantee a distribution of income between the different classes of income recipients consistent with the repetition of the productive process on a given (or increasing) level. It is a characteristic feature of input-output analysis that both the independent and the dependent variables are to be ‘directly observable’, at least in principle. The practical importance of this requirement is obvious, but there is also a theoretical motivation for it: the good of an economic analysis based on magnitudes that cannot be observed, counted and measured is necessarily uncertain.


From ‘Classical’ Roots of Input-Output Analysis: A Short Account of its Long Prehistory

We shall see that input-output analysis can indeed look back at a formidable history prior to its own proper inception, which is often dated from the early writings of Wassily Leontief. These include his 1928 paper ‘Die Wirtschaft als Kreislauf’ (The economy as a circular flow) (Leontief, 1928) and his 1936 paper on ‘Quantitative input-output relations in the economic system of the United States’ (Leontief, 1936); because of its applied character, the latter is occasionally considered ‘the beginning of what has become a major branch of quantitative economics’ (Rose and Miernyk, 1989, p. 229). The account of the prehistory of input- output analysis may also throw light on wider issues which played an important role in the past, but are commonly set aside in many, but not all modern contributions to input- output analysis. This concerns first and foremost the subject of value and distribution. While in earlier authors and also in Leontief (1928) that issue figured prominently, in modern contributions it is frequently set aside or dealt with in a cavalier way. This raises a problem, because production, distribution and relative prices are intimately intertwined and cannot, in principle, be tackled independently of one another. Scrutinizing the earlier literature shows why.


Key Sources of Research:


‘Classical’ Roots of Input-Output Analysis: A Short Account of its Long Prehistory

By Heinz D. Kurz and Neri Salvadori



Who is Going to Kiss Sleeping Beauty? On the ‘Classical’ Analytical Origins and Perspectives of Input–Output Analysis

HEINZ D. KURZ‘Classical’_Analytical_Origins_and_Perspectives_of_Input-Output_Analysis__in_Review_of_Political_Economy_.pdf


Wassily Leontief: In appreciation

William J. Baumol and Thijs ten Raa


Wassily Leontief and L ́eon Walras: the Production as a Circular Flow

Akhabbar, Amanar and Lallement, J ́eroˆme Lausanne University, Centre Walras-Pareto, Centre d’Economie de la Sorbonne


Input–Output Analysis from a Wider Perspective: a Comparison of the Early Works of Leontief and Sraffa

HEINZ D. KURZ􏰀 & NERI SALVADORI􏰀􏰀–Output_Analysis_from_a_Wider_Perspective__in_Economic_Systems_Research_.pdf



Impact Studies without Multipliers: Lessons from Quesnay’s Tableau Economique

Albert E. Steenge and Richard van den Berg



Causality and interdependence in Pasinetti’s works and in the modern classical approach

by Enrico Bellino  and Sebastiano Nerozzi


Three centuries of macro-economic statistics

Frits Bos


The Circularity of the Production Process


Modeling the Economy as a Whole: An Integrative Approach



Structural Interdependence in Monetary Economics: Theoretical Assessment and Policy Implications

Duccio Cavalieri



The agents of production are the commodities themselves On the classical theory of production, distribution and value

Heinz D. Kurz




Ángel Luis Ruiz Pedro F. Pellet