Ray Fair Research Articles

Horizons of Understanding: A Review of Ray Fair's Estimating How the Macroeconomy Works

Ray Fair's Estimating How the Macroeconomy Works is the latest in a series of books by Fair that build, estimate, and apply his macroeconometric model to study the U.S. economy. In this book, Fair updates the model to incorporate the most recent data and uses it to analyze several important empirical questions, such as whether the U.S. economy moved into a new age of high productivity in the last half of the 1990s and the dynamics of prices, output, and unemployment. This review places his work in the context of the historical evolution of aggregate econometric models, compares it with the current developments in the estimation of dynamic stochastic general equilibrium models, and discusses some salient aspects of Fair's contributions.

Review of: Predicting Presidential Elections and Other Things

Ray Fair is one of my favorite econometricians. He has an excellent website, fairmodel.econ.yale.edu, where he freely shares his models. He writes clearly and his methods are reported in detail. He is concerned with the proper use of econometric methods. For example, he has long been opposed to the common practice of making ex post subjective adjustments to forecasts from econometric models. A review of empirical evidence supports his position (Armstrong and Collopy 1998).

US presidential election forecasting: An introduction

The modern era of election forecasting is now almost thirty years old. Like many significant developments in science, it began as separate streams of work occurring at around the same time: the investigations of Lee Sigelman (1979), Michael Lewis-Beck and Tom Rice (1982), Richard Brody and Sigelman (1983) on the relationship between presidential approval ratings and the vote; economist Ray Fair's (1978) work on the predictive strength of the economy and presidential incumbency for the vote; Steven Rosenstone's (1983) construction of a forecasting model for the presidential vote in the States; the identification by geophysicist Vladimir Keilis-Borok and historian Allan Lichtman (1981) of thirteen general indicators or “keys” for foretelling the outcome of presidential elections. Soon thereafter, Michael Lewis-Beck and Tom Rice (1984) combined the presidential approval ratings with an indicator of economic conditions to create a core forecasting equation based on retrospective voting theory. Alan Abramowitz (1988) later added to this core idea his “time for a change” consideration of the number of consecutive terms that the president's political

Predicting presidential election results

The 2004 US presidential election proved again how difficult it is to predict vote shares on the basis of polls. Midday media exit polls suggested that Senator Kerry would become the 44th President. Political scientists and econometricians, led by Ray Fair, have promulgated theoretical arguments and empirical results to predict US presidential elections, using macro-economic data and political factors. Respecifying Fair's war variable to include Korea and Vietnam and removing serial correlation improves his election forecasting without public opinion poll variables. This generalized Fair model predicts President Bush's two-party vote share would be 52.3 percent, well below predictions by Fair and prestigious political scientists.

Deconstructing the 2004 Presidential Election Forecasts: The Fiscal Model and the Campbell Collection Compared

In this paper we compare the August 1st forecast of the 2004 presidential election generated with the fiscal model with those made with the seven models of what we call the “Campbell Collection,” after James E. Campbell, the editor or co-editor of several forecasting symposia that have appeared in the American Politics Quarterly (October, 1996) and in successive issues of PS: Political Science and Politics (October, 2004 and January, 2005). For reasons that will become evident, Ray Fair's “presidential vote equation” (Fair 2002a, 2002b) is also included in the comparison. First, given space constraints, we present only a brief summary of the theoretical model. (For a more extended discussion, interested readers are encouraged to pursue the relevant references.) Then, as we did pursuant to issuing a forecast for the 2004 election, we estimate the model over the 22 elections held between 1916 and 2000, showing the out-of-sample results. Finally, we evaluate the model relative to the Campbell Collection on operational and substantive criteria.

Near-Rational Wage and Price Setting and the Long-Run Phillips Curve

OVER THIRTY YEARS ago, in his presidential address to the American Economic Association, Milton Friedman asserted that in the long run the Phillips curve was vertical at a natural rate of unemployment that could be identified by the behavior of inflation.(1) Unemployment below the natural rate would generate accelerating inflation, and unemployment above it, accelerating deflation. Five years later the New Classical economists posed a further challenge to the stabilization orthodoxy of the day. In their models with rational expectations, not only was monetary policy unable to alter the long-term level of unemployment, it could not even contribute to stabilization around the natural rate.(2) The New Keynesian economics has shown that, even with rational expectations, small amounts of wage and price stickiness permit a stabilizing monetary policy.(3) But the idea of a natural unemployment rate that is invariant to inflation still characterizes macroeconomic modeling and informs policymaking. The familiar empirical counterpart to the theoretical natural rate is the nonaccelerating-inflation rate of unemployment, or NAIRU. Phillips curves embodying a NAIRU are estimated using lagged inflation as a proxy for inflationary expectations. NAIRU models appear in most textbooks, and estimates of the NAIRU--which is assumed to be relatively constant--are widely used by economic forecasters, policy analysts, and policymakers. However, the inadequacy of such models has been demonstrated forcefully in recent years, as low and stable rates of inflation have coexisted with a wide range of unemployment rates. If there were a single, relatively constant natural rate, we should have seen inflation slowing significantly when unemployment was above that rate, and rising when it was below. Instead, the inflation rate has remained fairly steady, with annual inflation as measured by the urban consumer price index (CPI-U) ranging from 1.6 to 3.0 percent since 1992, while the unemployment rate has ranged from 6.8 to 3.9 percent. In this paper we present a model that can accommodate relatively constant inflation over a wide range of unemployment rates. Another motivation is a recent finding by William Brainard and George Perry.(4) Estimating a Phillips curve in which all the parameters are allowed to vary over time, they find that the coefficient on the proxy for expected inflation in the Phillips curve has changed considerably, while other parameters of that model have been relatively constant. In particular, Brainard and Perry found that the coefficient on expected inflation was initially low in the 1950s and 1960s, grew in the 1970s, and has fallen since then. The model we present can explain both why the coefficient on expected inflation might be expected to change over time and, to some extent, the time pattern of changes observed by Brainard and Perry. Our paper also allows an interpretation of the findings of Robert King arm Mark Watson and of Ray Fair.(5) Both find a long-run trade-off between inflation and unemployment. In addition, King and Watson find that the amount of inflation that must be tolerated to obtain a given reduction of unemployment rose considerably after 1970. Our model allows a trade-off, but only at low rates of inflation such as those that prevailed in the 1950s, 1960s, and 1990s. At higher rates of inflation, the trade-off is reduced, and at high enough rates of inflation, it disappears. Much of the empirical controversy surrounding the relationship between inflation and unemployment has focused on how people form expectations. This may be neither the most important theoretical nor the most important empirical issue. Instead, this paper suggests that it is not how people form expectations but how they use them--and even whether they use them at all--that is the issue. Economists typically assume that economic agents make the best possible use of the information available to them. But psychologists who study how people make decisions have a different view. …

The NAIRU and Wages in Local Labor Markets

Unemployment in the United States has been below its presumed NAIRU ( nonaccelerating-inflation rate of unemployment) of 6 percent for more than four years. The doctrine or dogma of the NAIRU led to the expectation that an unemployment rate below the NAIRU would make accelerating inflation inevitable; but by all measures inflation has, if anything, declined and shows no signs of increasing. The NAIRU doctrine has had a major role in macroeconomic theory and monetary policy for several decades. For example, the seven hikes in interest rates by the Fed in 1994–1995 seem to have been motivated not by concerns about existing inflation (CPI-U inflation was steady and below 3 percent) , but by fears that an unemployment rate falling toward the 6-percent level, and then below 6 percent in September 1994, would foster future inflation. Theoretical and statistical criticisms of the NAIRU have been growing (see e.g., Robert Solow, 1986; James Tobin, 1993; Eisner, 1994; Rod Cross, 1995 [ essays by Cross, Frank Hahn and Tobin ] ; Ray Fair, 1996; Olivier Blanchard and Lawrence Katz, 1997;

Irving Fisher's Debt–Deflation Theory of Great Depressions

eminent Yale monetary and capital theorist Fisher is best known in the economics profession for the equation of exchange, the distinction between real and nominal interest rates, and an early analysis of intertemporal allocation. fact, his contributions as an early macroeconomist were extensive, and his debt-deflation theory of depression both deserves and implicitly gets consideration currently. It is Fisher's misfortune, as well as that of the profession, that his analysis of the debt-deflation process, one of his most insightful contributions to macroeconomics, received little notice from his contemporaries. Fisher has acquired lasting and unenviable fame for his predictions in September 1929 that prices have reached what looks like permanently high plateau (Barber, 1985, p. 77) and for the consequences to Fisher of his predictive error. As John Kenneth Galbraith (1977, p. 192) remarked, In the late nineteen-twenties Fisher went heavily into the stock market and in the Crash lost between eight and ten million dollars. This was sizable sum, even for an economics professor. Fisher was known for this even to those, such as Robert Sobel (1968, pp. 97, 132), whose direct knowledge of Fisher and his work was vague enough to identify him as Irving Fisher of Harvard. Kathryn Dominguez, Ray Fair, and Matthew Shapiro (1988) have now shown that even using modern statistical techniques and adding some retrospectively compiled time series to those available to Fisher and to the Harvard Economic Society, it would not have been possible to predict the onset, length or depth of the Great Depression by time-series analysis. Dominguez, Fair, and Shapiro have done much to redeem Fisher's reputation as forecaster relative to that of, for example, Roger Babson, whose successful prediction of break in stock prices in the fall of 1929 must be balanced against his prediction of stock price boom in 1930. If one views the bull market of the 1920s as speculative bubble, all that could be predicted is that the bubble would eventually burst, not when. Indeed, Fisher's formal statistical forecasting method, as distinct from his more subjective statements about future stock prices, held up quite well. series of journal articles, Fisher (1923, 1925, 1926) sought empirical verification of his monetary theory of economic fluctuations by correlating output and unemployment with distributed lag of past changes in the price level (see Dimand, 1992). He was an innovator in the use of correlation analysis and distributed lags, and constructed his own price indices. His 1926 article was republished in 1973 as I Discovered the Phillips Curve. Fisher (1925) found correlation of .941 between trend-adjusted measure of the volume of trade and distributed lag of monthly inflation rates for the 114 months ending January 1923. Scott Sumner (1990) has found that, using the lag weights from Fisher's 1925 paper, Fisher's equation yielded correlation of .851 for the period from January 1923 to July 1933, close out-of-sample fit. stable relationship between output and inflation collapsed only with the economic policy regime change after Franklin Roosevelt's inauguration when the United States left the fixed gold value of the dollar for what Maynard Keynes termed a gold standard on the booze and U.S. output recovered sharply. Thus updating Fisher's model to the 1923-35 period, Sumner found that The correlation between the predicted and the actual output series was only .256 because of the structural change in 1933 (1990, p. 721). Fisher's Audience Apart from the regrettable impact on his personal finances, the stock market crash and subsequent depression had two important consequences for Fisher as theorist of economic fluctuations. Fisher's attention was focused on gap in his analysis in the 1920s of the business cycle as a dance of the dollar: the need to explain why sometimes deep and lasting depression occurred. …

The Significance of the 1992 Election

The 1992 election was influenced by a number of factors. The personalities, or characteristics, of the candidates clearly played a role, as did the kind of campaign they ran. Economic conditions were particularly important. However, it is interesting to note that statistical models by economists predicting election results, which emphasize economic trends, were less successful in 1992 than in previous years. Political scientists were more successful.Models and PerceptionsFour years ago, Ray Fair, an economist at Yale, was hailed for an incredibly accurate prediction. Applying a model that did not include data more recent than six months before the election, he anticipated the outcome of the 1988 contest within .3 of 1%. This model did not include Willie Horton or even Dukakis. It simply analyzed the way in which parameter data anticipated support for the incumbent and the opposition. Other economically based models were also quite accurate.Successfully applying such models is enough to make journalists and politicians ill, as it suggests that everything they do or write about is useless—that the outcome of elections is determined by pre-existing structural factors, not by candidates, campaign tactics, or ideology. This time Fair was wrong! He predicted that Bush was going to win, since the economy was really not that bad. The 1991-92 downturn was more moderate than the Reagan 1981-82 recession, or the Carter 1977 decline, while the misery index—unemployment plus the inflation rate—was much worse in 1979-80. But Bush was never able to get this message across.

The Significance of the 1992 Election

The 1992 election was influenced by a number of factors. The personalities, or characteristics, of the candidates clearly played a role, as did the kind of campaign they ran. Economic conditions were particularly important. However, it is interesting to note that statistical models by economists predicting election results, which emphasize economic trends, were less successful in 1992 than in previous years. Political scientists were more successful.Models and PerceptionsFour years ago, Ray Fair, an economist at Yale, was hailed for an incredibly accurate prediction. Applying a model that did not include data more recent than six months before the election, he anticipated the outcome of the 1988 contest within .3 of 1%. This model did not include Willie Horton or even Dukakis. It simply analyzed the way in which parameter data anticipated support for the incumbent and the opposition. Other economically based models were also quite accurate.Successfully applying such models is enough to make journalists and politicians ill, as it suggests that everything they do or write about is useless—that the outcome of elections is determined by pre-existing structural factors, not by candidates, campaign tactics, or ideology. This time Fair was wrong! He predicted that Bush was going to win, since the economy was really not that bad. The 1991-92 downturn was more moderate than the Reagan 1981-82 recession, or the Carter 1977 decline, while the misery index—unemployment plus the inflation rate—was much worse in 1979-80. But Bush was never able to get this message across.

Economic determinants of presidential elections: The fair model

Ray Fair has constructed a model explaining the incumbent share of the two-party presidential popular vote for the elections of 1916-1984. The economic measures of the growth rate of real per capita GNP and the absolute value of the rate of inflation are singled out as important. In addition, a time trend favoring Democrats and whether an incumbent is seeking reelection are included. I argue that the Fair model is misspecified. Including the rate of growth in the Dow Jones Industrial Averages significantly improves the fit of the model, eliminates the trend as significant, reduces the income parameter, and strengthens the inflation parameter. In addition, the model remains stable when including the 1908 and 1912 elections, and up-dating to include the 1988 election strengthens the results. The explanatory power of the model is impressive with only one missed election outcome (1976) between 1908 and 1988, and this miss is easily explained by the impact of Watergate on the Republican candidate, President Ford.

Comparative performance of U.S. econometric models

Lawrence Klein won the Nobel Prize in Economics for his original work in developing models One of the most important, and visible, things economists do is to forecast what will happen in the economy in the future. Each year a number of different groups in the US use their own econometric models to forecast what will happen to the economy in the coming year. Some forecasts are more accurate than others. This book consists of chapters by distinguished economists comparing the different models now being used. It is organized topically rather than by model. The contributors include: Roger Brimmer, Ray Fair, Bert Hickman, F. Gerard Adams, and Albert Ando. Lawrence Klein provides an introduction to the volume. Available in OSO:

Modelling Anticipated and Temporary Fiscal Policy Shocks in a Macro-Econometric Model of Canada

Following the work of Ray Fair (1979), expectations terms in the FOCUS model are generated using predicted values from the model itself. Expectations are therefore consistent with the model struct ured. Government expenditure multipliers are compared for the standar d model and the CE version. Three further examples show the power of the technique as applied to the analysis of fiscal policy shocks. T he first considers a temporary versus a permanent income tax surcharg e. The second considers the possibility of an anticipatory recession when preannounced fiscal stimulus is combined with monetary restrai nt. The third examines the planned restructuring of the Canadian corp orate tax system.

Specification, Estimation, and Analysis of Macroeconomic Models

This book gives a practical, applications-oriented account of the latest techniques for estimating and analyzing large, nonlinear macroeconomic models. Ray Fair demonstrates the application of these techniques in a detailed presentation of several actual models, including his United States model, his multicountry model, Sargent's classical macroeconomic model, autoregressive and vector autoregressive models, and a small (twelve equation) linear structural model. He devotes a good deal of attention to the difficult and often neglected problem of moving from theoretical to econometric models. In addition, he provides an extensive discussion of optimal control techniques and methods for estimating and analyzing rational expectations models.A computer program that handles all the techniques in the book is available from the author, making it possible to use the techniques with little additional programming. The book presents the logic of this program. A smaller program for personal microcomputers for analysis of Fair's United States model is available from Urban Systems Research & Engineering, Inc. Anyone wanting to learn how to use large macroeconomic models, including researchers, graduate students, economic forecasters, and people in business and government both in the United States and abroad, will find this an essential guidebook.

Presidential Popularity and Macroeconomic Performance: Are Voters Really so Naive?

F OLLOWING the pioneering work of Kramer (1971), numerous studies have analyzed the relationships between the macroeconomic performance of political administrations and their popularity or vote-getting ability. Kramer's work showed that the aggregate congressional vote for an incumbent party can be explained rather well by variables indicating recent economic performance. Subsequent works have extended Kramer's research by explaining presidential vote or Gallup Poll popularity data with similar models.' On one point almost all of these studies agree:2 votes and popularity can be explained well by models which suppose that voters judge policymakers on the basis of retrospective evaluation of past macroeconomic outcomes. Most authors interpret their results as being supportive of the hypothesis of rational voters, since the evidence indicates that voting decisions are not based purely upon personalities, party affiliation, or chance. Kramer argued that if voters regard past macroeconomic performance of an administration to be indicative of future performance, then a concern with past performance indicates a concern for future performance. Voters who simply extrapolate from the past to predict the future are rather naive, however. A voter, who has an understanding of the important intertemporal constraints embodied in the structure of the economy, would be able to forecast future consequences of current policy choices more accurately than one who simply extrapolates. If votes and popularity are simply functions of past outcomes, then voters must either be ignorant of the basic structure of the economy, or unconcerned with the future. The supposition that voters are so might run counter to the intuition of most economists, who generally assume individual rationality as a central behavioral postulate. Nevertheless, the empirical results noted above have been accepted by many as evidence that voters do misperceive their own long-run interest. The implications of the voter hypothesis for macroeconomic policymaking are disturbing. Nordhaus (1975) has developed a model which shows that voter naivete can encourage vote maximizing politicians to induce political business cycles and an inflationary bias. There is some, but not unanimous, empirical support for the existence of politically motivated business cycles, and casual empiricism also suggests that politicians themselves believe in the voter.3 While studies show that empirical evidence is consistent with the notion that voters are concerned with the recent past, the results do not reject a voter hypothesis. None of the aforementioned studies has tested a model consistent with a sophisticated voter hypothesis, i.e., a model in which voters understand what outcomes are feasible in the long and short runs, and are concerned with future as well as current and past economic performance. In this paper we develop such a model and estimate it using Gallup Poll data on presidential popularity. Results of this model are compared to results from a naive voter model similar to those employed in previous research. Received for publication February 4, 1982. Revision accepted for publication July 30, 1982. University of South Carolina. I am grateful for helpful comments provided by Ray Fair, Douglas Hibbs, William Keech, Daniel Richards, Abel L. Da Costa Fernandes, and an anonymous referee. I also wish to thank William Keech for providing me with the Gallup Poll data on presidential approval rates. Aurel Schubert provided excellent research assistance. ' Fair (1978a), Bloom and Price (1975), Arcelus and Meltzer (1975), and Pollard (1981 a, 1981 b) have all estimated models to explain voting, while Frey and Schneider (1978) and Hibbs (I 982a, 1982b) have developed models to explain presidential popularity. 2 An exception is provided by Arcelus and Meltzer (1975). 3Nordhaus (1975) and Tufte (1978) have provided evidence of political business cycles for a number of Western democracies, and Frey and Schneider (1978) and Maloney and Smirlock (1981) have estimated policy reaction functions suggesting that the timing of elections affects policymaking. See Tufte for a discussion of casual empirical evidence indicating that politicians believe that current economic conditions affect electoral outcomes.

THE STRATEGIC USE OF REGULATORY INVESTMENT BY INDUSTRY SUB-GROUPS

Economic InquiryVolume 20, Issue 4 p. 604-618 THE STRATEGIC USE OF REGULATORY INVESTMENT BY INDUSTRY SUB-GROUPS SHARON OSTER, SHARON OSTER *Yale University. The research on which this work is based was funded by the Federal Trade Commission and the Small Business Administration; however, the ideas expressed herein are the author's and in no way are intended to express the views of the Federal Trade Commission. I would like to thank Ray Fair, Richard Levin, Richard Nelson and Michael Spence for helpful comments.Search for more papers by this author SHARON OSTER, SHARON OSTER *Yale University. The research on which this work is based was funded by the Federal Trade Commission and the Small Business Administration; however, the ideas expressed herein are the author's and in no way are intended to express the views of the Federal Trade Commission. I would like to thank Ray Fair, Richard Levin, Richard Nelson and Michael Spence for helpful comments.Search for more papers by this author First published: October 1982 https://doi.org/10.1111/j.1465-7295.1982.tb00369.xCitations: 38AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume20, Issue4October 1982Pages 604-618 RelatedInformation