Low Interest Rates and Business Investments : Update August 2017

Low Interest Rates and Business Investments : Update August 2017

 

From  Explaining Low Investment Spending

USINVEST

globalinvest

 

Please see my earlier posts.

Business Investments and Low Interest Rates

Mergers and Acquisitions – Long Term Trends and Waves

The Decline in Long Term Real Interest Rates

Short term Thinking in Investment Decisions of Businesses and Financial Markets

Low Interest Rates and Monetary Policy Effectiveness

Low Interest Rates and Banks’ Profitability : Update July 2017

Low Interest Rates and Banks Profitability: Update – December 2016

 

Since my earlier posts on this subject there has been several new studies published highlighting weakness in business investments as one of the cause of slower economic growth and lower interest rates.

Other significant factors impacting interest rates are demographic changes, and slower economic growth.

I argue that there is mutual (circular) causality in weak business investment, slower economic growth, and lower interest rates which reinforce each other.

 

Decreased competition, increased concentration, corporate savings glut, share buybacks, paying dividends are also identified as factors.

Number of public companies have decreased significantly in USA since 1996 due to M&A activity.   See the data below.

Increased Mergers/Acquisitions, Increased Concentration, Decreased Competition, Decreased Number of Public Companies, Share buybacks, and Dividend Payouts are multiple perspectives of same problem.

 

From The Incredible Shrinking Universe of Stocks

The Causes and Consequences of Fewer U.S. Equities

USNUMUSSTAT

 

Key sources of Research:

The Low Level of Global Real Interest Rates

Remarks by
Stanley Fischer
Vice Chairman
Board of Governors of the Federal Reserve System

at the
Conference to Celebrate Arminio Fraga’s 60 Years
Casa das Garcas, Rio de Janeiro, Brazil

July 31, 2017

The Low Level of Global Real Interest Rates

 

 

INVESTMENT-LESS GROWTH: AN EMPIRICAL INVESTIGATION

German Gutierrez Thomas Philippon

Working Paper 22897

NATIONAL BUREAU OF ECONOMIC RESEARCH

1050 Massachusetts Avenue
Cambridge, MA 02138

December 2016

 

INVESTMENT-LESS GROWTH: AN EMPIRICAL INVESTIGATION

 

 

Explaining Low Investment Spending

The NBER Digest
NATIONAL BUREAU OF ECONOMIC RESEARCH

February 2017

Explaining Low Investment Spending

 

 

The Secular Stagnation of Investment?

Callum Jones and Thomas Philippon

December 2016

 

The Secular Stagnation of Investment?

 

 

Is there an investment gap in advanced economies? If so, why?

By Robin Dottling, German Gutierrez and Thomas Philippon

 

Is there an investment gap in advanced economies? If so, why?

 

 

The Disappointing Recovery of Output after 2009

JOHN G. FERNALD ROBERT E. HALL

JAMES H. STOCK MARK W. WATSON

May 2, 2017

The Disappointing Recovery of Output after 2009

 

 

Declining Competition and Investment in the U.S.

German Gutierrez and Thomas Philippon

NATIONAL BUREAU OF ECONOMIC RESEARCH

July 2017

 

Declining Competition and Investment in the U.S

 

 

Real Interest Rates Over the Long Run : Decline and convergence since the 1980s

Kei-Mu Yi   Jing Zhang

ECONOMIC POLICY PAPER 16-10 SEPTEMBER 2016

FEDERAL RESERVE BANK of MINNEAPOLIS

Real Interest Rates over the Long Run Decline and convergence since the 1980s, due significantly to factors causing lower investment demand

 

 

Understanding global trends in long-run real interest rates

Kei-Mu Yi and Jing Zhang

Economic Perspectives, Vol. 41, No. 2, 2017
Chicago Fed Reserve Bank

 

Understanding Global Trends in Long-run Real Interest Rates

 

 

Weakness in Investment Growth: Causes, Implications and Policy Responses

CAMA Working Paper 19/2017 March 2017

M. Ayhan Kose

Franziska Ohnsorge

Lei Sandy Ye

Ergys Islamaj

 

Weakness in Investment Growth: Causes, Implications and Policy Responses

 

 

Are US Industries Becoming More Concentrated?

Gustavo Grullon, Yelena Larkin and Roni Michaely

October 2016

 

Are US Industries Becoming More Concentrated?

 

 

Why Is Global Business Investment So Weak? Some Insights from Advanced Economies

 

Robert Fay, Justin-Damien Guénette, Martin Leduc and Louis Morel,

International Economic Analysis Department

Bank of Canada Review Spring 2017

 

Why Is Global Business Investment So Weak? Some Insights from Advanced Economies

 

 

What Is Behind the Weakness in Global Investment?

by Maxime Leboeuf and Bob Fay

2016

Bank of Canada

 

What Is Behind the Weakness in Global Investment?

 A Structural Interpretation of the Recent Weakness in Business Investment

by Russell Barnett and Rhys Mendes

 The Corporate Saving Glut in the Aftermath of the Global Financial Crisis

 

Gruber, Joseph W., and Steven B. Kamin

International Finance Discussion Papers
Board of Governors of the Federal Reserve System
Number 1150 October 2015

 

The Corporate Saving Glut in the Aftermath of the Global Financial Crisis

 

 

The Incredible Shrinking Universe of Stocks

The Causes and Consequences of Fewer U.S. Equities

March 22, 2017

GLOBAL FINANCIAL STRATEGIES

http://www.credit-suisse.com

 

The Incredible Shrinking Universe of Stocks The Causes and Consequences of Fewer U.S. Equities

 

 

They Just Get Bigger: How Corporate Mergers Strangle the Economy

Jordan Brennan

2017 February 19

They Just Get Bigger: How Corporate Mergers Strangle the Economy

 

 

Rising Corporate Concentration, Declining Trade Union Power, and the Growing Income Gap: American Prosperity in Historical Perspective

Jordan Brennan

March 2016

 

Rising Corporate Concentration, Declining Trade Union Power, and the Growing Income Gap: American Prosperity in Historical Perspective

Low Interest Rates and Monetary Policy Effectiveness

Low Interest Rates and Monetary Policy Effectiveness

 

World economy is stuck in low interest rates environment.   Euro area, japan have even negative interest rates.  US Fed Reserve since December 2016 has started raising interest rates.

Attempts by Central Banks have not been effective in increasing economic growth.  Many Economists now are presenting counter intuitive reasons for low growth.

 

Please see my earlier related posts.

Business Investments and Low Interest Rates

Mergers and Acquisitions – Long Term Trends and Waves

 

Since 2016, there are several new studies published exploring effectiveness of monetary policy in low interest rates environment.

 

Is monetary policy less effective when interest rates are persistently low?

by Claudio Borio and Boris Hofmann

April 2017

Is Monetary Policy Less Effective When Interest Rates are Persistently Low?

 

In March 2017, Brookings Institution published the following study by the economists of the US Federal Reserve.

Monetary policy in a low interest rate world

 

Fed Reserve of Chicago published speech given by Charles Evans in 2016.

Monetary Policy in a Lower Interest Rate Environment

 

Lecture by Vítor Constâncio, Vice-President of the ECB, Macroeconomics Symposium at Utrecht School of Economics, 15 June 2016

The challenge of low real interest rates for monetary policy

 

Journal of Policy Modeling published a paper by Ken Rogoff.  Paper was presented at American Economic Association, 2017.

Monetary policy in a low interest rate world

 

Eight BIS CCA Research Conference on “Low interest rates, monetary policy and international spillovers”, hosted by the Board of Governors of the Federal Reserve System, Washington DC, 25-26 May 2017

Low interest rates, monetary policy and international spillovers

 

Economist Magazine published an article on views of Bill Gross and others.

November 2015

Do ultra-low interest rates really damage growth?

 

Bloomberg Business Week published an article describing views of Charles Calomiris and others.

June 2017

Is the World Overdoing Low Interest Rates?

 

Claudio Borio and Boris Hofmann

The Paper was prepared for the Reserve Bank of Australia conference
“Monetary Policy and Financial Stability in a World of Low Interest Rates”,

16-17 March 2017, Sydney

Is monetary policy less effective when interest rates are persistently low?

 

Monetary policy and bank lending in a low interest rate environment: diminishing effectiveness?

Claudio Borio and Leonardo Gambacorta

February 2017

Monetary policy and bank lending in a low interest rate environment: diminishing effectiveness?

 

Negative Interest Rate Policy (NIRP):
Implications for Monetary Transmission and Bank Profitability in the Euro Area

Prepared by Andreas (Andy) Jobst and Huidan Lin

IMF

August 2016

Negative Interest Rate Policy (NIRP): Implications for Monetary Transmission and Bank Profitability in the Euro Area

 

James Bullard, President and CEO of Federal Reserve Bank of St. Louis

March 24, 2009

The Henry Thornton Lecture, Cass Business School, London

Effective Monetary Policy in a Low Interest Rate Environment

 

Federal Reserve Bank of New York

Monetary Policy, Financial Conditions, and Financial Stability

Tobias Adrian
Nellie Liang

Monetary Policy, Financial Conditions, and Financial Stability

 

Monetary policy, the financial cycle and ultra-low interest rates

Mikael Juselius of Bank of Finland

DNB Workshop on “Estimating and Interpreting Financial Cycles”

Amsterdam, 2 September 2016

Monetary policy, the financial cycle and ultra-low interest rates

BIS Paper

Monetary policy, the financial cycle and ultra-low interest rates

 

The dynamics of real interest rates, monetary policy and its limits

Philippe d’Arvisenet

May 2016

The dynamics of real interest rates, monetary policy and its limits

 

Output Gaps and Monetary Policy at Low Interest Rates

By Roberto M. Billi

Output Gaps and Monetary Policy at Low Interest Rates

 

The insensitivity of investment to interest rates: Evidence from a survey of CFOs

Steve A. Sharpe and Gustavo A. Suarez

2014-02

The insensitivity of investment to interest rates: Evidence from a survey of CFOs

 

Does Prolonged Monetary Policy Easing Increase Financial Vulnerability?

Prepared by Stephen Cecchetti, Tommaso Mancini-Griffoli, and Machiko Narita

February 2017

Does Prolonged Monetary Policy Easing Increase Financial Vulnerability?

 

The Microeconomic Perils of Monetary Policy Experiments

Charles W. Calomiris

Cato Institute

The Microeconomic Perils of Monetary Policy Experiments

 

Why Have the Fed’s Policies Failed to Stimulate the Economy?

Mickey D. Levy

Cato Institute

Why Have the Fed’s Policies Failed to Stimulate the Economy?

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

Economics of Digital Globalization and Information Data Flows

Economics of Digital Globalization and Information Data Flows

 

Please see this link below for changes in global data flows between 2005 and 2014.

Source: McKinsey & Company.

McKinsey Global Flows of Data

 

digitalglobal

 

 

People and Businesses are using internet and other data and communications technologies in variety of ways.  Some are listed below.

  • e-commerce
  • Social networking
  • Digital media
  • Blogging
  • Online eduction
  • Online entertainment
  • Business Communications
  • Online Capital
  • Online Organizing
  • Online Markets (Amazon, Ebay, Alibaba)

 

Governments and Trade organizations are catching up to these trends. Several research reports have been published recently.  Trade agreements are being negotiated which include means to reduce barriers to digital trade.

 

From DIGITAL GLOBALIZATION: THE NEW ERA OF GLOBAL FLOWS

Conventional wisdom says that globalization has stalled. But although the global goods trade has flattened and cross-border capital flows have declined sharply since 2008, globalization is not heading into reverse. Rather, it is entering a new phase defined by soaring flows of data and information.

Remarkably, digital flows—which were practically nonexistent just 15 years ago—now exert a larger impact on GDP growth than the centuries-old trade in goods, according to a new McKinsey Global Institute (MGI) report, Digital globalization: The new era of global flows. And although this shift makes it possible for companies to reach international markets with less capital-intensive business models, it poses new risks and policy challenges as well.

The world is more connected than ever, but the nature of its connections has changed in a fundamental way. The amount of cross-border bandwidth that is used has grown 45 times larger since 2005. It is projected to increase by an additional nine times over the next five years as flows of information, searches, communication, video, transactions, and intracompany traffic continue to surge. In addition to transmitting valuable streams of information and ideas in their own right, data flows enable the movement of goods, services, finance, and people. Virtually every type of cross-border transaction now has a digital component.

Trade was once largely confined to advanced economies and their large multinational companies. Today, a more digital form of globalization has opened the door to developing countries, to small companies and start-ups, and to billions of individuals. Tens of millions of small and midsize enterprises worldwide have turned themselves into exporters by joining e-commerce marketplaces such as Alibaba, Amazon, eBay, Flipkart, and Rakuten. Approximately 12 percent of the global goods trade is conducted via international e-commerce. Even the smallest enterprises can be born global: 86 percent of tech-based start-ups surveyed by MGI report some type of cross-border activity. Today, even the smallest firms can compete with the largest multinationals.

Individuals are using global digital platforms to learn, find work, showcase their talent, and build personal networks. Some 900 million people have international connections on social media, and 360 million take part in cross-border e-commerce. Digital platforms for both traditional employment and freelance assignments are beginning to create a more global labor market.

In this increasingly digital era of globalization, large companies can manage their international operations in a leaner, more efficient ways. Using digital platforms and tools, they can sell in fast-growing markets while keeping virtual teams connected in real time. This is a moment for companies to rethink their organizational structures, products, assets, and competitors.

Global flows of all types support growth by raising productivity, and data flows are amplifying this effect by broadening participation and creating more efficient markets. MGI’s analysis finds that over a decade, all types of flows acting together have raised world GDP by 10.1 percent over what would have resulted in a world without any cross-border flows. This value amounted to some $7.8 trillion in 2014 alone, and data flows account for $2.8 trillion of this impact. Both inflows and outflows matter for growth, as they expose economies to ideas, research, technologies, talent, and best practices from around the world.

Although there is substantial value at stake, not all countries are making the most of this potential. The latest MGI Connectedness Index—which ranks 139 countries on inflows and outflows of goods, services, finance, people, and data—finds large gaps between a handful of leading countries and the rest of the world. Singapore tops the latest rankings, followed by the Netherlands, the United States, and Germany. China has grown more connected, reaching number seven, but advanced economies in general remain more connected than developing countries. In fact, each type of flow is concentrated among a small set of highly connected countries.

Lagging countries are closing the gaps with the leaders at a very slow pace, and their limited participation has had a real cost to the world economy. If the rest of the world had increased its participation in global flows at the same rate as the top quartile over the past decade, world GDP would be $10 trillion, or 13 percent, higher today. For countries that have been slow to participate, the opportunities for catch-up growth are too substantial to ignore.

 

 

From Why globalization isn’t it in retreat, it’s gone digital

A hand is silhouetted in front of a computer screen in this picture illustration taken in Berlin May 21, 2013. The Financial Times’ website and Twitter feeds were hacked May 17, 2013, renewing questions about whether the popular social media service has done enough to tighten security as cyber-attacks on the news media intensify. The attack is the latest in which hackers commandeered the Twitter account of a prominent news organization to push their agenda. Twitter’s 200 million users worldwide send out more than 400 million tweets a day, making it a potent distributor of news.

Around the world, countries are rethinking the terms of engagement in global trade. This is not all bad; in fact, acknowledgement of globalization’s disruptive effects on millions of advanced-economy workers is long overdue. But new trade policies must be based on a clear-eyed understanding of how globalization is evolving, not on a backward-looking vision based on the last 30 years.

Globalization has done the world a lot of good. Research from the McKinsey Global Institute shows that, thanks to global flows of goods, services, finance, data, and people, world GDP is more than 10% higher – some $7.8 trillion in 2014 alone – than it would have been had economies remained closed.

More interconnected countries capture the largest share of this added value. For example, the United States, which ranks third among 195 countries on MGI’s Connectedness Index, has done rather well. Emerging-market economies have also reaped major gains, using export-oriented industrialization as a springboard for rapid growth.

Yet, even as globalization has narrowed inequality among countries, it has aggravated income inequality within them. From 1998 to 2008, the middle class in advanced economies experienced no income growth, while incomes soared by nearly 70% for those at the top of the global income distribution. Top earners in the US, accounting for half of the global top 1%, reaped a significant share of globalization’s benefits.

To be sure, this isn’t all, or even mostly, a result of globalization. The main culprit is technological change that automates routine manual and cognitive tasks, while increasing demand (and wages) for highly skilled workers. But import competition and labor arbitrage from emerging economies have also played a role. Perhaps more important, they have proved more salient targets of voters’ fear and resentment.

Indeed, in the industries and regions hit hardest by import competition, years of simmering discontent have now boiled over, fueling support for populists promising to roll back globalization. But, as the advanced economies reformulate trade policy, it is critical that they understand that globalization was already undergoing a major structural transformation.

Since the global financial crisis, cross-border capital flows have plummeted, with banks pulling back in response to new regulation. From 1990 to 2007, global trade grew twice as fast as global GDP; since 2010, GDP growth has outpaced that of trade.

Both cyclical and secular forces are behind the trade slowdown. Investment has been anemic for years. China’s growth has slowed – a secular trend that is unlikely to be reversed. And the expansion of global supply chains seems to have reached the frontier of efficiency. In short, slower global trade is likely to be the new normal.

None of this is to say that globalization is in retreat. Rather, it is becoming a more digital phenomenon. Just 15 years ago, cross-border digital flows were almost non-existent; today, they have a larger impact on global economic growth than traditional flows of traded goods.

The volume of cross-border data flows has soared 45-fold since 2005, and is expected to grow another nine-fold over the next five years. Users worldwide can stream Beyoncé’s latest single immediately upon its release. A manufacturer in South Carolina can use the e-commerce platform Alibaba to buy components from a Chinese supplier. A young girl in Kenya can learn math through Khan Academy. Eighty percent of students taking Coursera’s online courses live outside the US.

This new form of digital globalization is more knowledge-intensive than capital- or labor-intensive. It requires broadband connections, rather than shipping lanes. It reduces barriers to entry, strengthens competition, and changes the rules governing how business is done.

Consider export activities, which once seemed out of reach for small businesses lacking the resources to scout out international prospects or navigate cross-border paperwork. Now, digital platforms like Alibaba and Amazon enable even small-scale entrepreneurs to connect directly with customers and suppliers around the world, transforming themselves into “micro multinationals.” Facebook estimates that 50 million small businesses are on its platform, up from 25 million in 2013; 30% of these companies’ Facebook fans, on average, are from other countries.

While digital technologies open the door for small companies and individuals to participate in the global economy, there is no guarantee that sufficient numbers will walk through it. That will require policies that help them take advantage of new global market opportunities.

The US has pulled out of the Trans-Pacific Partnership (TPP) deal, but many of the issues it addressed still require global rules. Data localization requirements and protectionism are on the rise, and data privacy and cyber-security are pressing concerns. In the absence of the TPP, it will be critical to find some other vehicle for establishing new principles for digital trade in the twenty-first century, with a greater emphasis on intellectual property protection, cross-border data flows, and trade in services.

At the same time, advanced economies must help workers acquire the skills needed to fill high-quality jobs in the digital economy. Lifelong learning cannot just be a slogan; it must become a reality. Mid-career retraining must be made available not only to those who have lost their jobs to foreign competition, but also to those facing disruption from the continuing march of automation. Training programs should be able to impart new skills in a matter of months, not years, and they should be complemented by programs that support workers’ incomes during retraining, and that help them relocate for more productive work.

Most of the advanced economies, including the US, have not adequately responded to the needs of the communities and individuals left behind by globalization. Addressing these needs is now of paramount importance. Effective responses will require policies that help people adapt to the present and take advantage of future opportunities in the next phase of digital globalization.

 

From The ascendancy of international data flows

We compiled data for more than 150 countries for 20 years regarding six types of cross-border flows: physical flows of goods and services, FDI flows, financial flows, labour migration flows, and data flows measured in bits. As flows are most likely correlated to each other, we first resorted to a principal component analysis of flows and found that the largest factor accounted for up to 60% of the variance among flows, with all flows being positively correlated to the factor. Among the factors, this primary factor was also the only one to be statistically (and, as expected, positively) associated with a country’s economic growth.

Estimating a pooled cross-section, time series co-integration model of country GDP growth, we find that, together, global flows of goods, services, finance, people, and data have raised world GDP by at least 10% in the past decade, adding US$8 trillion of GDP by 2015. More crucially, and in part driven by the material growth in cross-border data bits internationally, the value of data flows has nearly matched the value of global trade in physical goods. By 2014, cross-border data flows accounted for $2.3 trillion of this value, or roughly 3.5% of total world GDP.

This estimate is only a first benchmark which will require further verification. But it underscores the importance of global data flows for economies at large. It also highlights new elements of consideration for economists, for policymakers, and for business. Given the significant contribution to GDP, governments must address pending issues such as free flows of data, cybersecurity, and privacy. They must also harness flows better through international standardisation of single payment systems, standardisation of internet of things protocols, coordination of tax issues, and integrated logistics. On the business side, the world’s biggest digital platforms – from e-commerce marketplaces to social media network – have become global in a matter of a few years, but though their concentration may be a concern, they have also amassed hundreds of millions of companies that can benefit from improved export opportunities and achieve major productivity gains.

Furthermore, the international flow of information facilitated by these digital technologies is a powerful driver of new performance for global firms, for example in optimising distributed R&D and innovation. Ultimately, everyone will need to go with the flow.

 

Key Terms:

 

  • GATS (General Agreement on Trade in Services)
  • ICT (information and communications technology)
  • IPR (intellectual property rights)
  • ITA (International Technology Agreement)
  • NTIA (National Telecommunications and Information Administration)
  • OECD (Organization for Economic Co-operation and Development)
  • TPP (Trans-Pacific Partnership)
  • TTIP (Transatlantic Trade and Investment Partnership)
  • TiSA (Trade in Services Agreement)
  • USITC (United States International Trade Commission)
  • USTR (United States Trade Representative)
  • WTO (World Trade Organization)
  • Digital Trade

 

 

Key Sources of Research:

 

DIGITAL GLOBALIZATION: THE NEW ERA OF GLOBAL FLOWS

2016

MGI

http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/digital-globalization-the-new-era-of-global-flows

 

 

Global flows in a digital age

How trade, finance, people, and data connect the world economy

By James Manyika, Jacques Bughin, Susan Lund, Olivia Nottebohm, David Poulter, Sebastian Jauch, and Sree Ramaswamy

McKinsey 2014

http://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/global-flows-in-a-digital-age

 

 

Harnessing the power of shifting global flows

By Jacques Bughin, Susan Lund, and James Manyika

McKinsey

2015

http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/harnessing-the-power-of-shifting-global-flows

 

 

Internet matters: The Net’s sweeping impact on growth, jobs, and prosperity

By Matthieu Pélissié du Rausas, James Manyika, Eric Hazan, Jacques Bughin, Michael Chui, Rémi Said

McKinsey 2011

http://www.mckinsey.com/industries/high-tech/our-insights/internet-matters

 

 

Online and Upcoming:  Internet’s Impact on India

McKinsey 2012

http://lateralpraxis.com/download/Internets%20impact%20on%20India.pdf

 

 

Online and upcoming: The Internet’s impact on aspiring countries

January 2012

Olivia Nottebohm James Manyika Jacques Bughin Michael Chui Abdur-Rahim Syed

http://www.innovacion.cl/wp-content/uploads/2012/05/Internet.pdf

 

 

The Importance of The Internet and Transatlantic data flows for U.S. and EU Trade and Investment

Joshua p. meltzer

2014

Brookings

https://www.brookings.edu/wp-content/uploads/2016/06/internet-transatlantic-data-flows-version-2.pdf

 

 

ASEF OUTLOOK REPORT 2016/2017

 

Asia Europe Foundation

http://www.asef.org/images/docs/1.%20Measuring%20Connectivity.pdf

http://www.asef.org/images/docs/ASEF%20Outlook%20Report%202016-2017%20Vol2.pdf

http://asef.org/images/docs/ASEF%20Outlook%20Report%202016-2017%20Vol1.pdf

 

 

Mega-trends 2015 Making sense of a world in motion

EY

http://www.ey.com/Publication/vwLUAssets/ey-megatrends-report-2015/$FILE/ey-megatrends-report-2015.pdf

http://www.ey.com/Publication/vwLUAssets/ey-making-sense-of-a-world-in-motion/$FILE/ey-making-sense-of-a-world-in-motion.pdf

 

 

Cross-Border Data Flows, Digital Innovation, and Economic Growth

Robert Pepper John Garrity Connie LaSalle

2016

WEF

 

http://www3.weforum.org/docs/GITR2016/WEF_GITR_Chapter1.2_2016.pdf

http://www.aciem.org/home/images/Prensa/Newsletter/PDF_Notas_Prensa_Int_Gen_07_Jul_2016.pdf

 

 

Business Without Borders: The Importance of Cross-Border Data Transfers to Global Prosperity

US Chamber of Commerce

2014

https://www.hunton.com/files/Publication/d28675b8-5d7b-4f43-a1f1-dda852294ba6/Presentation/PublicationAttachment/2d735aec-6ce8-48c3-b736-e2e4baf8dbf5/Business_without_Borders.pdf

https://www.uschamber.com/sites/default/files/021384_BusinessWOBorders_final.pdf

 

 

The Digital Revolution in Banking

Gail Kelly

Group of Thirty

 

http://www.centerforfinancialstability.org/research/OP89.pdf

 

 

Digital Trade and U.S. Trade Policy

Rachel F. Fefer

Shayerah Ilias Akhtar

Wayne M. Morrison

US Congress Research

January 13, 2017

https://fas.org/sgp/crs/misc/R44565.pdf

 

 

Measuring the Value of Cross-Border Data Flows

US Deptt of Commerce

2016

https://www.ntia.doc.gov/files/ntia/publications/measuring_cross_border_data_flows.pdf

 

Transatlantic Digital Economy and Data Protection: State-of-Play and Future Implications for the EU’s External Policies

EU Parliament

 

http://www.europarl.europa.eu/RegData/etudes/STUD/2016/535006/EXPO_STU(2016)535006_EN.pdf

 

 

Why globalization isn’t it in retreat, it’s gone digital

WEF

https://www.weforum.org/agenda/2017/02/why-globalization-isnt-it-in-retreat-its-gone-digital

 

 

The ascendancy of international data flows

Jacques Bughin, Susan Lund

09 January 2017

http://voxeu.org/article/ascendancy-international-data-flows

 

 

DIGITAL TRADE AND THE TPP HOW ASIA-PACIFIC BENEFITS

 

https://static1.squarespace.com/static/5393d501e4b0643446abd228/t/57fc86501b631ba46c243265/1476167250211/digital+trade+and+the+TPP_v2_DIGITAL.pdf

 

 

The Digital Trade Imbalance and Its Implications for Internet Governance

Susan Ariel Aaronson

2016

 

https://www.cigionline.org/sites/default/files/gcig_no25_web_0.pdf

https://www2.gwu.edu/~iiep/assets/docs/papers/2016WP/AaronsonIIEPWP2016-7.pdf

 

 

Solutions to the digital trade imbalance

Susan Ariel Aaronson

07 March 2016

http://voxeu.org/article/solutions-digital-trade-imbalance

http://www.worldcommercereview.com/publications/article_pdf/1049

 

 

Digital Trade in the U.S. and Global Economies, Part 2

USITC

2014

 

https://www.usitc.gov/publications/332/pub4485.pdf

 

 

Digital Trade in the U.S. and Global Economies, Part 1

USITC

2013

https://www.usitc.gov/publications/332/pub4415.pdf

 

 

Enter the Data Economy : EU Policies for a Thriving Data Ecosystem

European Commission

2017

 

https://ec.europa.eu/epsc/sites/epsc/files/strategic_note_issue_21.pdf

 

 

Data, Trade and Growth

BY DR. MICHAEL MANDEL

2014

http://www.progressivepolicy.org/wp-content/uploads/2014/04/2014.04-Mandel_Data-Trade-and-Growth.pdf

 

 

Bridging the Data Gap How Digital Innovation Can Drive Growth and Create Jobs

By Paul Hofheinz and Michael Mandel

2014

 

http://www.progressivepolicy.org/wp-content/uploads/2014/04/LISBON_COUNCIL_PPI_Bridging_the_Data_Gap2.pdf

 

 

Measuring the Economic Value of Cross-Border Data Flows

April 22, 2016

Jessica R. Nicholson

UNCTAD

 

http://unctad.org/meetings/en/Presentation/dtl_eweek2016_JNicholson_en.pdf

 

 

Trends in Digitally-Enabled Trade in Services

by Maria Borga and Jennifer Koncz-Bruner

 

https://www.bea.gov/international/pdf/trends_in_digitally_enabled_services.pdf

 

 

Digital Economy and Cross-Border Trade: The Value of Digitally-Deliverable Services

Jessica R. Nicholson and Ryan Noonan

2014

U.S. Department of Commerce / Economics and Statistics Administration

 

http://www.esa.doc.gov/sites/default/files/digitaleconomyandtrade2014-1-27final.pdf

 

 

World Development Report 2016: Digital Dividends

World Bank 2016

http://www.worldbank.org/en/publication/wdr2016

 

 

Cross-Border Data Flows Enable Growth in All Industries

BY DANIEL CASTRO AND ALAN MCQUINN

| FEBRUARY 2015

 

http://www2.itif.org/2015-cross-border-data-flows.pdf?_ga=1.64526831.1959464330.1454009762

 

 

Addressing Barriers to Digital Trade

Usman Ahmed and Grant Aldonas

WEF

E15 Initiative

December 2015

http://e15initiative.org/publications/addressing-barriers-to-digital-trade/

 

 

The Internet Economy in the G-20

The $4.2 Trillion Growth Opportunity

 

https://www.bcg.com/documents/file100409.pdf

Understanding Global Value Chains – G20/OECD/WB Initiative

Understanding Global Value Chains – G20/OECD/WB Initiative

 

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

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

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

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

 

From Global Value Chains 

Introduction to GVCs

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

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

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

 

Trade in Value Added

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

 

GVCs and Trade Policy

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

 

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

The key organizational feature of the global economy?

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

The phenomenon

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

 

 

From GLOBAL VALUE CHAIN ANALYSIS: A PRIMER

gvc5

 

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

gvc4

 

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

gvc1gvc-2gvc3

 

Key Terms

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

 

 

Key People

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

 

 

Key Sources of Research:

 

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

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

 

 

Global Value Chains

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

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

 

 

OECD Stocktaking Seminar on Global Value Chains 2014

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

 

 

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

OECD, WTO, UNCTAD 6 August 2013

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

 

https://www.oecd.org/trade/G20-Global-Value-Chains-2013.pdf

 

 

Inclusive Global Value Chains

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

OECD and World Bank Group

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

 

https://www.oecd.org/tad/tradedev/Participation-Developing-Countries-GVCs-Summary-Paper-April-2015.pdf

 

 

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

OECD, WTO and World Bank Group

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

 

https://www.oecd.org/tad/gvc_report_g20_july_2014.pdf

 

 

Making Global Value Chains (GVCs) Accessible to All

Progress Report
Meeting of the Council at Ministerial Level

6-7 May 2014

 

https://www.oecd.org/mcm/MCM-GVC-Progress-Report-May-2014.pdf

 

 

Inclusive Global Value Chains

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

Ana Paula Cusolito, Raed Safadi, and Daria Taglioni

2016

https://openknowledge.worldbank.org/bitstream/handle/10986/24910/9781464808425.pdf

 

 

Global value chains in a changing world

Edited by Deborah K. Elms and Patrick Low

2013

 

https://www.wto.org/english/res_e/booksp_e/aid4tradeglobalvalue13_e.pdf

 

 

The rise of global value chains

WORLD TRADE REPORT 2014

 

https://www.wto.org/english/res_e/booksp_e/wtr14-2c_e.pdf

 

 

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

Peter Draper and Andreas Freytag

July 2014

 

http://e15initiative.org/wp-content/uploads/2015/09/E15-Global-Value-Chains-DraperFreytag-FINAL.pdf

 

 

Joining, Upgrading and Being Competitive in Global Value Chains: 

A Strategic Framework

 

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

 

http://www.cggc.duke.edu/pdfs/2013-04_WorldBank_wps6406_Cattaneo_Gereffi_Miroudot_Taglioni_Competitiveness_GVCs.pdf

 

 

Global value chains, development and emerging economies

Gary Gereffi

2015

http://www.unido.org/fileadmin/user_media/Research_and_Statistics/WPs_2010/WP_18.pdf

 

 

GLOBAL VALUE CHAINS IN A POSTCRISIS WORLD A DEVELOPMENT PERSPECTIVE

Olivier Cattaneo, Gary Gereffi, and Cornelia Staritz

2010

http://www.cggc.duke.edu/pdfs/Gereffi_GVCs_in_the_Postcrisis_World_Book.pdf

 

 

 

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

Jeffrey Neilson1, Bill Pritchard1 and Henry Wai-chung Yeung

2014

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

 

 

Combining the Global Value Chain and global I-O approaches

 

 

 

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

René A. Hernández
Jorge Mario Martínez-Piva Nanno Mulder

 

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

 

 

 

Global value chains in a post-Washington Consensus world

Gary Gereffi

2014

 

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

 

 

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

Gary Gereffi

Director, Duke CGGC Duke University

2016

http://host.uniroma3.it/facolta/economia/db/materiali/insegnamenti/697_10587.pdf

 

 

 

MaPPing gLoBaL VaLUe CHainS

Koen De Backer and Sébastien Miroudot

2014

https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1677.pdf

 

 

 

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

Neil M. Coe

2013

https://www.mier.org.my/presentations/archives/pdf-restore/presentations/archives/pdf/DrCoe.pdf

 

 

 

GLOBAL VALUE CHAIN ANALYSIS: A PRIMER

Gary Gereffi
Karina Fernandez-Stark

July 2016

 

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

 

 

 

WHY THE WORLD SUDDENLY CARES ABOUT GLOBAL SUPPLY CHAINS

GARY GEREFFI AND JOONKOO LEE

Duke University

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

 

 

 

The Economic Crisis: A Global Value Chain Perspective

 

Gary Gereffi

 

http://www.ictsd.org/downloads/2010/08/a-global-value-chain-perspective.pdf

 

 

The governance of global value chains

Gary Gereffi John Humphrey Timothy Sturgeon

2005

 

https://rrojasdatabank.info/sturgeon2005.pdf

 

 

Global production networks and the analysis of economic development

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

2002

https://courses.nus.edu.sg/course/geoywc/publication/2002_RIPE.pdf

 

 

GLOBAL VALUE CHAINS: INVESTMENT AND TRADE FOR DEVELOPMENT

UNCTAD 2013

http://unctad.org/en/PublicationsLibrary/wir2013_en.pdf

 

 

Asia and Global Production Networks

Implications for Trade, Incomes and Economic Vulnerability

 

 

 

Global Production Networks: Theorizing Economic Development in an Interconnected World

By Neil M. Coe, Henry Wai-Chung Yeung

2015

 

 

Toward a Dynamic Theory of Global Production Networks

Henry Wai-chung Yeung

Neil M. Coe

 

http://gpn.nus.edu.sg/file/2015_GPN_theory_paper_EG%20Vol91(1)_29-58.pdf

 

 

Global Value Chains and deVelopment

unido’s support towards inclusive and sustainable industrial development

2015

https://www.unido.org/fileadmin/user_media/Research_and_Statistics/GVC_REPORT_FINAL.PDF

 

 

Global Value Chains: The New Reality of International Trade

Sherry Stephenson

December 2013

http://e15initiative.org/wp-content/uploads/2015/01/E15_GVCs_BP_Stephenson_FINAL.pdf

 

 

GLOBAL VALUE CHAINS SURVEYING DRIVERS AND MEASURES

João Amador and Sónia Cabral

2014

https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1739.en.pdf

 

 

GLOBAL VALUE CHAINS AND INTERCONNECTEDNESS OF ASIA-PACIFIC ECONOMIES

Asia Pacific Trade and Investment Report

2015

 

http://www.unescap.org/sites/default/files/Chapter%207%20-%20GVCs%20in%20the%20Asia-Pacific.pdf

http://www.unescap.org/sites/default/files/Full%20Report%20%20-%20APTIR%202015.pdf

 

 

Global Capitalism and Commodity Chains: Looking Back, Going Forward

JENNIFER BAIR

2005

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

 

 

Global Value Chains: Development Challenges and Policy Options

Proposals and Analysis

December 2013

http://e15initiative.org/wp-content/uploads/2015/09/E15-Global-Value-Chains-Compliation-Report-FINAL.pdf

 

 

Globalizing’ regional development: a global production networks perspective

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

https://courses.nus.edu.sg/course/geoywc/publication/2004_TIBG.pdf

 

 

Multilateral approaches to Global Supply Chains

 

International Labour Office

2014

 

http://www.ilo.org/wcmsp5/groups/public/—dgreports/—integration/documents/publication/wcms_485351.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