ARE INVESTMENT EXPECTATIONS RATIONAL, ADAPTIVE OR REGRESSIVE?

I. INTRODUCTION Tests of the rational expectations hypothesis (REH) outside the experimental laboratory typically utilize two types of data: quantitative measures of expectations about publicly observed variables such as inflation, usually elicited from small samples of professional forecasters; and qualitative measures of expectations about privately observed variables such as personal income, elicited from large samples of households. Analyses of both types of data have produced varying levels of support for the REH. For example, Keane and Runkle (1990, 1998) find evidence in favor of the REH using the first type of data, while Bonham and Cohen (2001) in part overturn their results after accounting for the nature of cross-correlations inherent in a group of individuals forecasting the same publicly observed integrated time series. Next, using household survey data, Das and van Soest (1997, 1999) and Das et al. (1999) find evidence against the REH. In contrast, Benitez-Silva et al. (2008) furthered the econometric analysis of such data and presented evidence in favor of the REH. In employing publicly available professional forecaster data several concerns related to pooling, data revisions, and the possibility of signaling on the part of forecasters have been raised. (1) Further, Pesaran and Weale (2006) review a large and growing literature on survey expectations of households and the attendant econometric and substantive issues in analyzing qualitative response expectations data from such surveys. They conclude for myriad reasons that "it remains the case that the analysis of individual responses to such surveys, and in particular to those who collect only qualitative information, is underdeveloped." These issues can be addressed in part by data on quantitative expectations about privately observed variables; this paper employs data from two new survey sources that provide such information. The resulting panel of 775 firms in Canada contains quantitative information on expectations about purchases of new machinery and equipment ("investment"), as well as realized levels of investment, over 7 yr. The data are particularly useful because they avoid some of the issues raised for previous studies and their analysis helps to contribute, on the firm side, to the agenda laid out by Manski (2004) who sees a "critical need for basic research on expectations formation." [FIGURE 1 OMITTED] Estimation results suggest that investment expectations are not rational if the assumed underlying loss function is assumed to be symmetric. That is, the usual unbiasedness and efficiency requirements for rational expectations, clearly elucidated for instance by Lovell (1986), do not hold for the collected data. Further, hypothesis tests on statistical models implied by conventional adaptive expectations do not suggest the prevalence of such behavior in the data. However, a particular version of such extrapolative expectations, namely, regressive expectations formation, does find support in the data. The paper is structured as follows. Section II discusses the data on 775 manufacturing plants over 7 yr that was compiled by merging two national surveys in Canada. In Section III, the statistical models (and attendant hypothesis tests) as implied by various expectations formation assumptions are described followed by their estimation results. Section V concludes. II. THE DATA Data were compiled from two confidential, proprietary surveys conducted by Statistics Canada: the Capital Expenditures Survey (CES) and the Annual Survey of Manufactures (ASM) over 7 yr (1986-1992). (2) The CES contains data on one-step ahead expected ([Expect.sub.it]) and realized (Actualit) capital expenditures on machinery and equipment (i.e., "investment"), and the ASM on shipments ([Shipment.sub.sit]). (3) Owing to the lumpy and long-term nature of construction expenditures, this variable was excluded. Finally, only manufacturing sector records were selected for both surveys. …