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Time Series Representations of Economic Variables

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Time Series Representations of Economic Variables and Alternative Models of theLabour MarketOrley Ashenfelter; David CardThe Review of Economic Studies, Vol. 49, No. 5, Special Issue on Unemployment. (1982), pp.761-781.Stable URL:http://links.jstor.org/sici?sici=0034-6527%281982%2949%3A5%3C761%3ATSROEV%3E2.0.CO%3B2-9The Review of Economic Studies is currently published by The Review of Economic Studies Ltd..Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available athttp://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtainedprior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content inthe JSTOR archive only for your personal, non-commercial use.Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained athttp://www.jstor.org/journals/resl.html.Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printedpage of such transmission.The JSTOR Archive is a trusted digital repository providing for long-term preservation and access to leading academicjournals and scholarly literature from around the world. The Archive is supported by libraries, scholarly societies, publishers,and foundations. It is an initiative of JSTOR, a not-for-profit organization with a mission to help the scholarly community takeadvantage of advances in technology. For more information regarding JSTOR, please contact [email protected]://www.jstor.orgFri Jun 29 15:51:40 2007Review of Economic Studies (1982) XLIX, 761-782 @ 1982 The Society for Economic Analysis Limited Time Series Representations of Economic Variables and Alternative Models of the Labour Market ORLEY ASHENFELTER Princeton University and DAVID CARD University of Chicago Accepting the hypothesis that the time-series "facts" of the aggregate labour market may be summarized by the linear autoregressive and moving average representations of wages, prices, unemployment, and interest rates implies that a useful theory ought to lead to predictions about these representations. Following this approach, this paper first catalogues many of the time-series facts about the aggregate labour market and then compares them against alternative models of the labour market based on the intertemporal substitution and staggered contract hypotheses. INTRODUCTION The inability of the empirical models of wage inflation built in the 1960s to predict the simultaneous high inflation and high unemployment of the 1970s led to their virtual demise and to a subsequent rebirth of interest in the theoretical foundations of these models. Both the empirical failure and the spate of theoretical work leave the impression with many economists that virtually any theory is likely to be consistent with the "facts" of the aggregate labour market, and that there simply are not enough facts to discriminate among leading candidates. At the same time, having learned the hard way from the poor performance of many models in the 1970s, econometric practice has changed so as to emphasize the importance of the dynamic structure of most time series data. In this new view parsimonious descriptions of the data are the autoregressive and moving average (ARMA) characteris- tics of the various time series that represent the data history of particular markets.' Since most of the cyclical characteristics of movements in labour market variables seem to be satisfactorily represented by relatively low order ARMA models, these representa- tions are then taken to be the "facts".' If the ARMA representations of labour market variables are an adequate description of the data, then it seems that a useful theory is one that likewise delivers a linear ARMA representation of the data. Tests of the theory then involve straightforward comparisons of the observed and predicted ARMA representations of the data.3 In this paper we employ this research strategy by first summarizing the time series "facts" about the aggregate labour market with which a useful theory must be consistent.REVIEW OF ECONOMIC STUDIES Our empirical strategy is to first set out the unrestricted reduced forms from a vector autoregression that contains nominal wages, consumer prices, nominal interest rates, and unemployment. From there we are able to test and catalogue the "exclusion restrictions" that are consistent with the quarterly U.S. time series data. We then compare the facts against the predictions of several elegant and straightforward models due to Lucas (1973), Fischer (1977), and Taylor (1980~) and others that satisfy our methodologi- cal criterion for a useful theory. These are also models of considerable practical significance, since the continuing debate over the effectiveness of monetary policy in stabilizing aggregate employment and output has been conducted around them. Much to our surprise, the facts are not only sufficient to discriminate among these models, they are also sufficient to demonstrate serious problems with at least the simplest specifications of all of them. 1. THE TIME SERIES DATA Table I(a) provides one elementary description of the basic U.S. quarterly time series on the logarithm of the nominal wage (W), the logarithm of the consumer price index (P),the logarithm of the unemployment rate (U),and the 90 day Treasury Bill rate (R). In this study we have used average hourly straight time earnings in manufacturing as an index of aggregate wages. Precise data definitions and sources are contained in the Appendix. For each of these time series we present in Table I(a) the fourth order univariate autoregressions (AR4) obtained by least squares fit over the period indicated. In all cases here, and in subsequent tables, we have included seasonal dummy variables and linear and quadratic trend terms. Even the simple data analysis in Table I(a) is revealing because it suggests that these four time series have quite different properties. On the one hand, the nominal wage TABLE I(a) Univariate AR 4 representations Dependent variablea (Estimated standard errors in parentheses) Regressors W P U R Standard error 0.0046 0.0034 0.0688 0.0054 BP~ 2.79 7.22 7.58 5.55 (significance) (0.514) (0.125) (0.109) (0.234)


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