Tests of risk premia in linear factor models

Frank Kleibergen

Journal of Econometrics, 2009, vol. 149, issue 2, 149-173

Abstract: We show that statistical inference on the risk premia in linear factor models that is based on the Fama-MacBeth (FM) and generalized least squares (GLS) two-pass risk premia estimators is misleading when the [beta]'s are small and/or the number of assets is large. We propose novel statistics, that are based on the maximum likelihood estimator of Gibbons [Gibbons, M., 1982. Multivariate tests of financial models: A new approach. Journal of Financial Economics 10, 3-27], which remain trustworthy in these cases. The inadequacy of the FM and GLS two-pass t/Wald statistics is highlighted in a power and size comparison using quarterly portfolio returns from Lettau and Ludvigson [Lettau, M., Ludvigson, S., 2001. Resurrecting the (C)CAPM: A cross-sectional test when risk premia are time-varying. Journal of Political Economy 109, 1238-1287]. The power and size comparison shows that the FM and GLS two-pass t/Wald statistics can be severely size distorted. The 95% confidence sets for the risk premia in the above-cited work that result from the novel statistics differ substantially from those that result from the FM and GLS two-pass t-statistics. They show support for the human capital asset pricing model although the 95% confidence set for the risk premia on labor income growth is unbounded. The 95% confidence sets show no support for the (scaled) consumption asset pricing model, since the 95% confidence set of the risk premia on the scaled consumption growth consists of the whole real line, but do not reject it either.

Keywords: Small; [beta]'s; Size; distortion; of; test; statistics; Consumption; capital; asset; pricing; model (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (65)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:149:y:2009:i:2:p:149-173

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