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January 18, 2008

Economist's View - 5 new articles

Fed Watch: Odds Still Favor a 50bp Cut

Tim Duy says the Fed is likely to cut rates a half point:

Odds Still Favor a 50bp Cut, by Tim Duy: I am inclined to believe that Bernanke & Co. intend to cut rates 50bp on Jan. 31. Bernanke's move to a more blunt communication strategy, however, has shifted market expectations to a debate between 50bp and 75bp. While I think a 75bp rate cut will be in play at the upcoming FOMC meeting, I think the odds still favor the 50bp rate cut.

I am trying to maintain a baseline assumption about Federal Reserve policy objectives –fundamentally, the Fed wants to make their medium term forecast meaningful and relevant from a policy perspective. Returning to Fed Governor Frederic Mishkin's speech last week:

I think there is too much focus on what decision will be made about the federal funds rate target at the next FOMC meeting (Mishkin, 2007e). What is important for pricing most financial assets is the path of monetary policy, not the particular action taken at a single meeting. For these reasons, I hope the recent enhancements to the Federal Reserve's communication strategy--especially the greater prominence of the macroeconomic projections of FOMC participants--will help shift attention toward our medium-term objectives and our approach in meeting these objectives.

I have already argued my position that the Fed's medium and long run forecasts imply a neutral Fed Funds rate in the range of 4.0 to 4.5%, and that the Fed would like to anchor expectations around that range. They do not want to continue the policy see-saw of the last decade.

My next assumption is that the flow of economic data will tend toward weakness for the first part of this year and that the Fed will find it virtually impossible to resist responding to that weakness. That argues for continued rate cuts for at least the next four meetings, barring some miraculous turnaround in the data. The Fed simply cannot sit back and do nothing.

My final assumption is obvious – no amount of rate cutting now will have any affect on the flow of data in the near term. Fed Chairman Ben Bernanke knows this; hence his support for immediate fiscal stimulus. The next 100bp of cutting is about what the economy looks like in January 2009, not now.

If the Fed pulls the trigger on 75bp at the end of next week, they will be on the path to a minimum of 150bp in the first half of this year – 75bp in January and 25bp in the each of the next three FOMC meetings (I think 100bp is more consistent with the Fed's supposed policy objectives). This would go along way to meeting the Goldman Sachs call of 2.5%, or a full 200bp below the Fed's estimate of neutral and 275bp below the last peak. The see-saw continues and any efforts to tie policy to their supposed medium and long term objectives are essentially meaningless.

Of course, the Fed could reverse course rapidly in the latter half of this year, unwinding the excess stimulus. Personally, I have virtually no faith in the Fed's willingness to reverse rate cuts – regardless of the rate or direction of inflation – during a period of economic weakness.

Moreover, while the negative tone of recent data continues relatively unabated, it is not quite as dismal as the business press would lead us to believe. Not that I see roses where others see weeds. Instead, I sense that tenor of the data speaks more to 50bp than 75bp even if the Fed intends to front load additional policy. The industrial production report was not yet consistent with the ever increasing recession calls (although the Philly Fed report was decidedly weak). Nor was the most recent read on initial unemployment claims, which should be accelerating if we are actually in recession.

I had a similar reaction to the retail sales report as Jim Hamilton. Wasn't great by any means, but not the end of the world either. But I wasn't excited by the November strength in retail sales in the first place, and the December numbers are largely just matching my expectation that consumer spending looks finally to be ratcheting down. Indeed, January's rise in consumer confidence is consistent with year-over-year growth of real consumer spending somewhere around the 2% rate I keep expecting to see and is inconsistent with economic freefall. Finally, the drop in the inventory to sales ratio in November is very inconsistent with the recession story.

Then there is housing. I have no need to comment on the state of the housing market itself – the numbers speak for themselves and are a significant part of the reason that the Fed will be induced to continue cutting interest rates.

Not to say that there is no argument for 75bp. In the grand scope of things, what's another 25bp, especially if you expect to cut rates at least that much anyway? And while in December the Fed was sufficiently confident of their outlook to disappoint market participants looking for the more aggressive of the rate cut options at the time, they may not feel the same liberty given the renewed market instability we have seen this week.

Bottom Line: I think odds still favor 50bp – it would be more consistent with the Fed's medium term objectives, and help maintain policy flexibility over the first half of the year. Moreover, this cut will do nothing to support the current environment, and the Fed needs to be looking at what it means for 2009. The case for 75bp relies largely on meeting market expectations, expectations that may be driven by an excessive level of fear.

Paul Krugman: Don't Cry for Me, America

How did we end up with problems usually associated with third-world economies?:

Don't Cry for Me, America, by Paul Krugman, Commentary, NY Times: Mexico. Brazil. Argentina. Mexico, again. Thailand. Indonesia. Argentina, again. And now, the United States.

The story has played itself out time and time again... Global investors, disappointed with the returns they're getting, search for alternatives. They think they've found what they're looking for in some country or other, and money rushes in.

But eventually it becomes clear that the investment opportunity wasn't all it seemed to be, and the money rushes out again, with nasty consequences... That's the story of multiple financial crises in Latin America and Asia. And it's also the story of the U.S. combined housing and credit bubble. These days, we're playing the role usually assigned to third-world economies. ...

The global origins of our current mess were ... laid out by ... Ben Bernanke ... in 2005... Mr. Bernanke asked a good question: "Why is the United States, with the world's largest economy, borrowing heavily on international capital markets — rather than lending, as would seem more natural?"

His answer was that ... third world economies ... were shaken by a series of financial crises beginning in 1997. As a result,... their governments began accumulating huge precautionary hoards of overseas assets.

The result, said Mr. Bernanke, was a "global saving glut"... In the end, most of that money went to the United States. Why? Because, said Mr. Bernanke, of the "depth and sophistication of the country's financial markets."

All of this was right, except for one thing: U.S. financial markets ... were ... not, in fact, uniquely well-suited to make use of the world's surplus funds. It was, instead, a place where large sums could be and were invested very badly. Directly or indirectly, capital flowing into America ... ended up financing a housing-and-credit bubble that has now burst, with painful consequences. ...

[T]hese consequences probably won't be as bad as the devastating recessions that racked third-world victims.... The saving grace ... is that our foreign debts are in our own currency. This means that we won't have the kind of financial death spiral Argentina experienced, in which a falling peso caused the country's debts, which were in dollars, to balloon in value...

But even without those currency effects, the next year or two could be quite unpleasant.

What should have been done differently? Some critics say that the Fed helped inflate the housing bubble with low interest rates. But those rates were low for a good reason: although the last recession officially ended in November 2001, it was another two years before the U.S. economy began delivering convincing job growth, and the Fed was rightly concerned about the possibility of Japanese-style prolonged economic stagnation.

The real sin, both of the Fed and of the Bush administration, was the failure to exercise adult supervision over markets running wild.

It wasn't just Alan Greenspan's unwillingness to admit that there was anything more than a bit of "froth" in housing markets, or his refusal to do anything about subprime abuses. The fact is that as America's financial system has grown ever more complex, it has also outgrown the framework of banking regulations that used to protect us — yet instead of an attempt to update that framework, all we got were paeans to the wonders of free markets.

Right now, Mr. Bernanke is in crisis-management mode, trying to deal with the mess his predecessor left behind. ... I suspect that it's already too late to prevent a recession.

But let's hope that when the dust settles a bit, Mr. Bernanke takes the lead in talking about what needs to be done to fix a financial system gone very, very wrong.

Inequality and Growth: Challenges to the Old Orthodoxy

Erwan Quintin and Jason L. Saving of the Dallas Fed review the evidence on inequality and growth and note "new theories that provide explanations for why inequality might hinder economic growth":

Inequality and Growth: Challenges to the Old Orthodoxy by Erwan Quintin and Jason L. Saving, FRB Dallas: Discussions of how best to alleviate poverty often center on the relative merits of policies that boost growth and those that promote redistribution. If greater inequality allows economies to expand faster, or if it's an inevitable consequence of pro-growth measures, the two principles seem incompatible. Under such a scenario, societies seeking rapid growth rates have to forgo redistribution from rich to poor. Conversely, choosing a high degree of redistribution implies the decision to accept lower growth rates.

If, on the other hand, inequality impedes growth, these principles aren't only compatible but may, in fact, reinforce one another. François Bourguignon, the former World Bank chief economist, wrote: "If one interprets literally the potentially negative relationship between inequality and growth, then redistribution [from rich to poor] would enhance growth. It would then be sufficient to have at one's disposal policy instruments to guarantee that growth is pro-poor—i.e. that it reduces inequality—for a virtuous circle to start and lead progressively to faster growth, declining inequality, and accelerated poverty reduction."[1]

The question of whether inequality impedes or fosters economic growth once seemed largely settled, with traditional economic theory focusing on inequality's beneficial effects on saving, investment and incentives. In the past two decades, however, research has identified new channels between inequality and growth, suggesting a more subtle relationship than the one advanced by earlier theorists.

The new work doesn't refute many of the important insights of classical economics, but it points out that inequality can have disruptive effects on resource allocation in economies where markets function poorly. Inequality, therefore, is more likely to be harmful in countries with weak institutions for the exchange of goods, services and money. This confirms the idea that improved market institutions are a key condition for economic success.

Trade-offs between inequality and growth aren't merely theoretical matters. They're crucially important not only for policymakers who shape their countries' safety nets but also for monetary authorities seeking to understand potential growth rates and make more informed policy decisions.

Classical Views Until recently, a broad set of ideas led much of the economic profession to opine that inequality was, if anything, favorable to—or at least a necessary by-product of—economic growth.[2]

In classical models, economic growth depends chiefly on the rate at which nations accumulate productive resources, a factor that traces to aggregate savings rates. In this context, distributional considerations matter for growth only if households' propensity to save varies systematically with wealth. If the rich save at a high rate, a view closely associated with prominent economist Nicholas Kaldor, unequal societies can actually build up their productive infrastructure faster than equal ones, achieving higher growth rates.

Inequality could also foster growth because new industries typically require large initial investments. If credit markets function poorly, a society's savings may not be efficiently transferred to investments. In this environment, a high concentration of wealth may allow some investors to overcome these impediments and stimulate growth by bringing capital-intensive industries into being.

In the early work, income or wealth redistribution policies are overwhelmingly viewed as detrimental to growth based on at least two arguments. First, redistribution via such instruments as progressive taxation distorts incentives to save, which reduces resource accumulation. Second, some variation in economic rewards helps provide incentives to invest and work.

The classical view long dominated economic thought and emphasized that policies designed to reduce inequality would entail adverse consequences for economic growth.

Recent Challenges Over the past two decades, these conventional notions have been challenged both on empirical and theoretical grounds. In cross-country comparisons, for example, researchers have generally found a negative relationship between income inequality and subsequent economic growth. These empirical findings, taken at face value, suggest that more equality could, in fact, foster growth.[3]

We illustrate the empirical argument by plotting income inequality in 1960 against average growth rates over the next four decades for all countries with available data. The results suggest, albeit weakly, that nations with more initial income inequality have tended to fare worse in the long run than countries with greater equality (Chart 1). In this example, inequality alone accounts for a fairly small fraction of the variance in growth across countries.

Chart 1: Income inequality and economic growth by nation

Even so, a growing body of empirical work finds that inequality remains significantly correlated with future growth even after controlling for other important factors, such as nations' initial level of development. Furthermore, the correlation between inequality and growth seems particularly strong among certain subgroups of nations—for example, those in which private credit is scarce.

Several caveats are in order. First, the empirical exercises don't imply that causation runs from inequality to growth. Second, most studies rely on measures of inequality of income rather than wealth. Because the theoretical work focuses on the distribution of productive resources, wealth inequality would be preferable, but little data exist on it. Finally, changing estimation techniques and time periods yields different results.[4]

Although cross-country studies have produced mixed results, they do suggest that inequality may not be conducive to growth. The statistical associations, however, reveal little about why. A historical example can shed some light on the mechanism through which inequality might impede economic growth.

If we look at the Western Hemisphere, we see that the United States and Canada have emerged as its strongest economies (Chart 2), with per capita GDP five to six times the South American average.[5]

Chart 2: North and south: economic divergence

It was not always this way. In the century before the U.S. was founded, Caribbean islands such as Barbados and Cuba produced 50 to 70 percent more output per person than did colonial America. Large swaths of South America, including Brazil, were also ahead of the U.S. and Canada. Contemporary observers routinely predicted that fortune could be found in these nations, rather than the U.S. or Canada, a belief borne out by migration patterns that show most Atlantic crossers headed to the Caribbean and South America.

What gave the United States and Canada their eventual edge over other apparently better-positioned nations? To answer this question, it's important to look at past structural differences between Western Hemisphere economies.

Caribbean and certain South American nations relied primarily on such high-value agricultural crops as sugar, which entail substantial economies of scale in production. These societies developed with large numbers of laborers working for relatively few landowners. The results were a vastly unequal distribution of income and little prospect that citizens could escape their station through upward mobility.

Much of Canada and the U.S., on the other hand, offered land in abundance but lacked the physical conditions conducive to large-scale farming in the colonial era. This led to societies in which newcomers with few assets could compete on relatively level playing fields with longer-term residents. The results were a relatively equal distribution of income and a relatively large amount of movement between income classes.

These fundamental economic realities led the rest of the hemisphere to develop institutions that were very different from the U.S. and Canada. When income and power are in the hands of a few, institutions tend to reinforce that concentration and perpetuate a high degree of income inequality. It was difficult for poor workers in many Caribbean and South American nations to acquire land, start corporations, secure patents or do any of the other things that generally go along with entrepreneurial success.

A more equal distribution of income and power makes it more difficult to create institutions that concentrate influence in the hands of a few. In the U.S and Canada, economically disadvantaged groups had a greater say in policy and more incentive to use their influence because they could hope to become prosperous themselves.

Comparing suffrage across countries provides some support for these notions. It's well known that the U.S. initially restricted voting to white males of privilege, which led to participation rates that would be regarded as pitiful by today's standards. In the 1850s, for example, 13 percent of American citizens voted in presidential elections, and participation rose to a still-low 18 percent in 1900. Yet, voting rates at the dawn of the 20th century were far lower in other Western Hemisphere nations—1.8 percent in Argentina, 2.4 percent in Brazil, 4.4 percent in Chile.

While the U.S. and Canada moved far more slowly toward universal suffrage than many would have liked, their polities were far more participatory than those of their Western Hemisphere counterparts. And empirical evidence supports the notion that expanded suffrage tends to produce governments whose programs are more likely to be directed toward the interests of the broad populace, not a small elite.[6]

The provision of public education in the Americas provides at least some evidence of a correlation between inequality and suffrage. If highly skewed income distributions produce highly skewed institutions that reinforce the status quo, we would expect relatively equal societies to provide universal schooling to their children, and relatively unequal societies to be less likely to do so.

This is indeed what we've seen in the Western Hemisphere over the past two centuries. The U.S. and Canada achieved literacy rates in excess of 80 percent by the 1870s, even if we include newly freed U.S. slaves (Chart 3). Institutions—usually state and local governments—understood and embraced the notion that education would help bring prosperity to the citizenry.

Other nations in the hemisphere with more unequal distributions of income and power were far below the U.S. and Canada in literacy in 1870. With the exception of tiny Barbados, no other Western Hemisphere nation had achieved 80 percent literacy rates half a century later. At least some have argued that this dearth of educational opportunity is due to suboptimal institutions' focus on protecting the few rather than enriching the many.[7]

New Theories These empirical arguments have prompted the development of new theories that provide explanations for why inequality might hinder economic growth. A lot of this work focuses on situations in which market mechanisms falter, whereas the classical theorists often assumed properly functioning markets.

The new work points out, for instance, that dispersion in factor endowments implies different rates of return when resource owners are unable to trade with one another—at least under the standard assumption that returns to factors are diminishing. In other words, high-return uses of resources coexist with much lower-return ones. Redirecting resources toward the more productive enterprises should bolster growth and make income more equal.[8] However, market impediments short-circuit this process, leading to more inequality and slower growth.

Another strand of recent work starts with the assumption that borrowers exert more effort when their stakes in projects are higher. Under that premise, it's possible to envision an environment where a more even distribution of resources gives more participants a significant interest, leading to a higher average level of effort and greater output.[9] We get similar results under the simple assumption that insufficient collateral leads some borrowers to forgo high-return projects.[10]

Another branch of inquiry focuses on political-economy questions and finds that greater inequality increases public support for redistribution, which leads to higher tax rates on capital accumulation and slower growth of the overall economy.[11]

These models show links between equality and growth, but they don't generally account for movements up and down the income distribution ladder. In some countries, it's difficult for people to leave the economic strata into which they were born. Other nations exhibit a great deal of upward mobility, often because of better education systems and well-functioning markets.

A fair amount of empirical work suggests that market-oriented economies such as the U.S. facilitate income mobility.[12] When citizens believe greater wealth may be in their future, they may vote as if they were "richer" than they actually are—a phenomenon that suggests a relatively equal distribution of opportunity may be a more important determinant of growth than a relatively equal distribution of income.[13]

These theoretical constructs provide a possible explanation for the observed negative relationship between inequality and growth and, in some cases, a potential rationale for redistribution. But it should be noted that these theories emphasize imperfections—be they barriers to trade or financial market access—that may be difficult to overcome through standard income-redistribution programs.

Moreover, the classical notion that redistribution distorts incentives to save and work can't be dismissed, creating trade-offs between redistribution's potential economic gains and its adverse consequences. Models typically find a hill-shaped relationship, where redistribution adds to growth for a while but eventually reaches a point where it becomes a drag on the economy.[14]

Institutional Links One of the distinguishing features of developing nations is the inefficiency of their basic economic institutions, such as property rights enforcement and the ability of ordinary people to undertake market transactions. Among many negative consequences, these imperfections limit access to financial markets throughout the developing world. Less credit stifles growth, leading to lower per capita incomes (Chart 4).

Chart 4: Economic and financial development by nation

Understanding the links between inequality and institutional development requires that we explain how better institutions help markets operate more effectively and devise a method for distributing the burden of institution building across taxpayers.[15] Setting aside political constraints, this framework predicts that economies with more inequality should be more willing to develop institutions conducive to trade among their citizens because greater inequality means potentially higher returns from exchange between the relatively rich and relatively poor.

This prediction seems puzzling in light of the historical evidence for the Western Hemisphere. In that case, nations with the most unequal distributions of wealth and income developed the least market-friendly institutions, while nations with more equal distributions developed the strongest institutions.

This outcome becomes more reasonable once we take a broader perspective. The link from the distribution of investment returns to growth and institution building depends in sometimes counterintuitive ways on the distribution of resources across individuals.

In Latin America, for instance, the concentration of productive resources has historically been high not only with respect to physical capital and land but also education and other forms of human capital. To the extent that physical and human resources are complementary in production, inequality may in fact be associated with very little dispersion in marginal products. Institutions conducive to trading physical resources may not have much effect on growth rates unless resource-poor individuals acquire more human capital. Redistribution schemes that target physical resources may be ineffective for similar reasons.

This suggests that educational investments via, for instance, public education can play an important role in successful institutional development. And as our case study illustrates, Latin America has historically lagged far behind the U.S. and Canada in educational achievement.

If anything, the new theories are strongly consistent with the hypothesis that persistent inequality generally hinders institutional development and thereby slows growth, even before taking into account strategic political considerations. Just as important, they suggest that inequality should have limited impact on growth when effective institutions are in place.

The empirical literature has, indeed, found that the impact of inequality on growth is stronger in nations where markets function poorly. [16] We can illustrate this by taking a second look at the relationship between income inequality in 1960 and growth over the next four decades. This time, we divide the sample into three groups based on the effectiveness of their market institutions, reflected by each country's score on the Fraser Institute's rankings for regulation of credit, labor and business.[17] These scores include factors such as price controls, mandatory hiring costs and the availability of capital to the private sector.

Among the third of countries with the weakest market institutions, we see a negative relationship between inequality and growth, echoing our earlier results (Chart 5A). When we isolate the third of countries with the strongest institutions, however, inequality has a barely discernible impact on economic growth (Chart 5B).

Chart 5: Inequality and growth by nation

We don't have data on whether countries did have effective market institutions in the past, which helps explain why our findings in these charts are fairly weak. Despite the data constraints, differences are present, suggesting that the quality of market-related institutions matters to the relationship between inequality and growth.

Obstacles to Development While recent work has enhanced our understanding of the interplay between inequality and growth, much remains to be done before we can confidently describe the policy mix that will give nations the best chance to grow and reduce poverty.

To date, little effort has been made to carefully quantify the importance of the channels emphasized by the new theories on inequality. Once devised, these models should enable us to better weigh the consequences of redistribution.

On a more basic level, a wide gap remains between the variables these theories highlight and the available data. Most obviously, data on wealth inequality remain scarce, even for industrialized nations, let alone developing nations. We also need a deeper understanding of the link between available measures of inequality and the dispersion of returns to competing uses of resources.

Finally, we have chosen to concentrate on the impact of inequality on growth, but it's clear that growth, in turn, affects inequality. A large literature studies this direction of causality. The famous Kuznets hypothesis—that growth initially increases inequality but eventually reduces it—has been challenged by the recent increase in earnings inequality in much of the industrialized world. Satisfactory theories of the relationship between growth and inequality will have to account for these recent patterns.

Even at this early stage, however, strong themes are emerging from studies of inequality. One seems particularly important: To the extent inequality is detrimental to growth, the impact rises with the severity of market imperfections. This suggests that dealing with these deficiencies—for example, by better protecting property rights and removing obstacles to financial development—is a key step toward economic development and poverty reduction.


  1. See "The Poverty-Growth-Inequality Triangle," by François Bourguignon, unpublished paper, World Bank, March 2004.
  2. This article draws heavily from various survey papers, particularly "Inequality and Economic Growth: The Perspective from New Growth Theories," by Philippe Aghion, Eve Caroli and Cecilia García-Peñalos, Journal of Economic Literature, vol. 37, December 1999, pp. 1615– 60, and "Inequality and Growth," by Roland Benabou, NBER Macroeconomics Annual, 1996.
  3. See, for example, "Political Equilibrium, Income Distribution, and Growth," by Roberto Perotti, Review of Economic Studies, vol. 60, October 1993, pp. 755–76; "Redistributive Policies and Economic Growth," by Alberto Alesina and Dani Rodrick, Quarterly Journal of Economics, vol. 109, May 1994, pp. 465–90; and "Is Inequality Harmful for Growth?" by Thorsten Persson and Guido Tabellini, American Economic Review, vol. 84, June 1994, pp. 600–21.
  4. For instance, using panel evidence rather than cross-sectional evidence leads to very different conclusions. See "A Reassessment of the Relationship Between Inequality and Growth," by Kristin Forbes, American Economic Review, vol. 90, September 2000, pp. 869–87. This is interpreted as evidence that the negative relationship between inequality and growth holds in the long run but may not hold over shorter horizons.
  5. This section draws heavily from "History Lessons: Institutions, Factor Endowments, and Paths of Development in the New World," by Kenneth Sokoloff and Stanley Engerman, Journal of Economic Perspectives, vol. 14, Summer 2000, pp. 217–32.
  6. See "The Effect of the Expansion of the Voting Franchise on the Size of Government," by Thomas Husted and Lawrence Kenny, Journal of Political Economy, vol. 105, February 1997, pp. 54–82.
  7. For more on this subject, see "Why Isn't the Whole World Developed?" by Richard Easterlin, Journal of Economic History, vol. 41, March 1981, pp. 1–19.
  8. This argument is formalized in Aghion, Caroli and García-Peñalos and Benabou (note 2).
  9. See "A Theory of Trickle-Down Growth and Development," by Philippe Aghion and Patrick Bolton, Review of Economic Studies, vol. 64, April 1997, pp. 151–72.
  10. See, for instance, "Imperfect Capital Markets and the Persistence of Initial Wealth Inequalities," by Thomas Piketty, London School of Economics Working Paper no. TE/92/255, 1992.
  11. See Alesina and Rodrick and Persson and Tabellini (note 3).
  12. For further information on income mobility in the United States, see Myths of Rich and Poor, by W. Michael Cox and Richard Alm, New York: Basic Books, 1999.
  13. See "Preferences for Redistribution in the Land of Opportunities," by Alberto Alesina and Eliana La Ferrera, Journal of Public Economics, vol. 89, June 2005, pp. 897–931, and "Social Mobility and the Demand for Redistribution," by Roland Benabou and Efe Ok, Quarterly Journal of Economics, vol. 116, May 2001, pp. 447–87.
  14. See Benabou (note 2).
  15. For such a framework, see "Inequality and Growth: The Institutional Link," by Thorsen Koeppl, Cyril Monnet and Erwan Quintin, Federal Reserve Bank of Dallas, unpublished paper, 2007.
  16. See Benabou (note 2) for a detailed discussion.
  17. Data are from Economic Freedom of the World: 2007 Annual Report, by James D. Gwartney and Robert A. Lawson, Fraser Institute, 2007, EFW2007BOOK2.pdf.

"Can we Predict Exchange Rates? Economic Evidence against the Random Walk Model"

According to this research, the forward premium, the difference between the forward exchange rate and the spot exchange rate, can help to predict short-run exchange rates and "investors who ignore it and use random walk models may be leaving money on the table":

Can we predict exchange rates? Economic evidence against the random walk model, by Pasquale Della Corte, Lucio Sarno, and Ilias Tsiakas, Vox EU: Exchange rates are important to innumerable economic activities. Tourists care about the value of their home currency abroad. Investors care about the effect of exchange rate fluctuations on their international portfolios. Central banks care about the value of their international reserves and open positions in foreign currency as well as about the impact of exchange rate fluctuations on their inflation objectives. Governments care about the prices of exports and imports and the domestic currency value of debt payments. Markets care both directly - the market for foreign exchange is by far the largest market in the world – and indirectly, since exchange-rate shifts can affect all sorts of other asset prices.

No surprise then that forecasting exchange rates has long been at the top of the research agenda in international finance. Still, most of this literature is characterised by empirical failure. Starting with the seminal contribution of Meese and Rogoff (1983), a vast body of empirical research finds that models which are based on economic fundamentals cannot outperform a naive random walk model (i.e. the exchange rate is, at any moment of time, as likely to rise as it is to fall). Therefore, the prevailing view in the international finance profession – shared in academic and policy circles as well as in a large fraction of the practitioner community – is that exchange rates are not predictable, especially at short horizons. In academic jargon, exchange rates are thought to follow a random walk.

A Random Walk?

At first glance, the random walk model makes a lot of sense. The person on the street knows that movements in exchange rates are often hard to explain and is reluctant to believe that fundamental forces are at play. Exchange rates often swing wildly on a daily basis for reasons that apparently have little connection to economic and financial variables. Even worse, they often move in the opposite direction of differences in short-term interest rates across countries. Despite its simplicity, therefore, the random walk model remains appealing because it leads to smaller forecasting errors than most other exchange rate models.

The horse race

This conclusion is based on a 'horse race' between the random walk and theory-based predictions. In this race, the random walk always wins. Our recent research argues that this is not the end of the story, but explaining our point requires something of a detour – an explanation of the 'horse' that classic exchange rate theory says should be winning the race every time.

The cornerstone condition for efficiency in the foreign exchange market is 'uncovered interest parity', i.e. the exchange rate jumps to the point where risk-neutral investors are indifferent between holding any two currencies. As a matter of accounting, the difference between the rates of return on the two currencies is the interest rate gap plus the expected appreciation; if the 12-month dollar interest rate is 5% while the 12-month yen interest rate is 1%, then, according to the theory, markets must expect the yen to appreciate 4%. If this isn't true, why would investors hold yen?

As logical as this seems, the relationship does not hold in the data, as the famous "Fama regression" (Fama, 1984) showed. One relationship that does hold in the data is the so-called covered interest parity, which states that the interest rate gap equals the premium on forward contracts. That is to say, if the dollar-yen interest rate gap is 4% as in the example, the forward contract for dollar-yen will imply a 4% premium over today's exchange rate for yen. Indeed, that is basically how banks set forward rates. The Fama regressions put together the uncovered and covered interest parities to check whether the actual exchange rate follows the forward premium. In the example, the question would be whether the actual appreciation of the yen over the next 12 months was 4% (plus or minus some white noise randomness due to unforeseeable events). Decades of research on masses of data by dozens of scholars show that the actual appreciation does not follow the forward rate. Indeed, it is the currency with the high interest rate that tends to appreciate, not the one with the low interest rate.[1]

This is stylised fact that is so well known that it has a name, the "forward bias puzzle," namely high-interest currencies tend to appreciate when uncovered parity predicts depreciation. While troublesome for economic theory, this puzzling behaviour may be valuable to investors.[2]

As mentioned, the horse race between pure randomness and uncovered interest parity always goes to randomness. But what happens if we let a new horse enter the race? What happens if we assume that investors ignore the pure theory and instead work off the empirical fact, i.e. the forward bias?

Valuable Predictions

In recent research, we examine whether exchange rate predictability could translate into economic gains for investors using an asset allocation strategy that exploits this predictability (Della Corte, Sarno and Tsiakas, 2007). In particular, we assess the economic value of the predictive ability of empirical exchange rate models that condition on the forward premium in the context of dynamic asset allocation strategies.[3]

We focus on predicting short-horizon exchange rate returns when conditioning on the lagged forward premium. But statistical evidence of exchange rate predictability in itself does not guarantee that an investor can profit by exploiting this predictability. We therefore evaluate the impact of predictable changes in the conditional FX returns and volatility on the performance of dynamic allocation strategies. Ultimately, we measure how much a risk-averse investor is willing to pay for switching from a dynamic portfolio strategy based on the random walk model to one which conditions on monetary fundamentals, the forward premium or a broader set of variables, including the money supply and income differentials across countries.

Our work suggests that these exchange rate predictions are valuable. There is strong economic evidence against the naïve random walk benchmark with constant variance innovations. In particular, the predictive ability of forward exchange rate premia has substantial economic value in a dynamic allocation strategy. In addition, conditioning on a forecast of future volatility given current information, rather than assuming that volatility in the foreign exchange market is constant, further enhances the predictability of exchange rates and increases risk-adjusted profits.


There's money to be made in the world's biggest market. Our evidence suggests that investors using sophisticated models could make informative exchange rate predictions and considerably outperform the random walk benchmark. Those trading currencies may find it worthwhile investing in a model using the forward premium and dynamic volatility. Policy makers can also find some comfort in these results since predictability in the exchange rate would allow them to better gauge the value of their international reserves, their debt positions, and their competitiveness in international goods markets.


Della Corte, P., L. Sarno, and I. Tsiakas (2007). "An Economic Evaluation of Empirical Exchange Rate Models," CEPR Discussion Paper 6598. Forthcoming in Review of Financial Studies.

Fama, E.F. (1984) "Forward and Spot Exchange Rates," Journal of Monetary Economics 14, 319-338.

Meese, R.A., and K. Rogoff (1983). "Empirical Exchange Rate Models of the Seventies: Do They Fit Out of Sample?" Journal of International Economics 14, 3-24.


1 More technically, the future k-period change in the exchange rate is regressed on the current k-period forward premium. If the market is efficient, the intercept of this regression should be zero, the slope (beta) in this regression should be 1, so that the forward premium today is an optimal predictor of the future exchange rate change. Also, the error term should be white noise, i.e. uncorrelated with information available today or in the past.

2 This fact is what drives much of the so-called carry trade where funds borrow in low-interest rate currencies to invest in higher-return assets in other currencies. Due to the forward premium puzzle, they can, on average, buy enough of the original currency to pay off the loan and still pocket a bundle.

3 This means a portfolio whose shares shift according to current information, especially the forward rate

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