Kenneth D. West’s research while affiliated with University of Wisconsin–Madison and other places

The authors develop regression-based tests of hypotheses about out of sample prediction errors. Representative tests include ones for zero mean and zero correlation between a prediction error and a vector of predictors. The relevant environments are ones in which predictions depend on estimated parameters. The authors show that standard regression statistics generally fail to account for errors introduced by estimation of these parameters. They propose computationally convenient test statistics that properly account for such errors. Simulations indicate that the procedures can work well in samples of size typically available, although there sometimes are substantial size distortions. Copyright 1998 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

I modify the uniform-price auction rules in allowing the seller to ration bidders. This allows me to provide a strategic foundation for underpricing when the seller has an interest in ownership dispersion. Moreover, many of the so-called "collusive-seeming" equilibria disappear.

To analyze business fixed investment in Japan, which has been unusually volatile in recent years, we develop and apply a loglinear flexible accelerator model. We find that movements in business fixed investment are consistent with movements in output and the tax- adjusted cost of capital, both on average during our entire 1961-94 sample and during the recent 1986-94 business cycle.

I study the dynamics of oil futures prices in the NYMEX using a large panel dataset that includes global macroeconomic indicators, financial market indices, quantities and prices of energy products. I extract common factors from the panel data series and estimate a Factor-Augmented Vector Autoregression for the maturity structure of oil futures prices. I find that latent factors generate information that, once combined with that of the yields, improves the forecasting performance for oil prices. Furthermore, I show that a factor correlated to purely financial developments contributes to the model performance, in addition to factors related to energy quantities and prices.

Using a dynamic linear equation that has a conditionally homoskedastic moving average disturbance, the authors compare two parameterizations of a commonly used instrumental variables estimator (Hansen (1982)) to one that is asymptotically optimal in a class of estimators that includes the conventional one (Hansen (1985)). They find that for some plausible data generating processes, the optimal one is distinctly more efficient asymptotically. Simulations indicate that, in samples of size typically available, asymptotic theory describes the distribution of the parameter estimates reasonably well but that test statistics sometimes are poorly sized.

This paper develops procedures for inference about the moments of smooth functions of out-of-sample predictions and prediction errors when there is a long time series of predictions and realizations. The aim is to provide tools for analysis of predictive accuracy and efficiency and, more generally, of predictive ability. The paper allows for nonnested and nonlinear models as well as for possible dependence of predictions and prediction errors on estimated regression parameters. Simulations indicate that the procedures can work well in samples of size typically available. Copyright 1996 by The Econometric Society.

Using a dynamic linear equation that has a conditionally homoskedastic moving average disturbance, we compare two parameterizations of a commonly used instrumental variables estimator (Hansen (1982)) to one that is asymptotically optimal in a class of estimators that includes the conventional one (Hansen (1985)). We find that for some plausible data generating processes, the optimal one is distinctly more efficient asymptotically. Simulations indicate that in samples of size typically available, asymptotic theory describes the distribution of the parameter estimates reasonably well, but that test statistics sometimes are poorly sized.

We summarize some recent work of ours on estimation and hypothesis testing on the parameters of the linear-quadratic inventory model. For some data-generating processes calibrated to estimates from some existing studies, this work uses (1) asymptotic theory to compare alternative estimators on the basis of the asymptotic efficiency of parameter estimates, (2) asymptotic theory and simulations to consider how likely one will be to get sharp estimates of the parameters of the model, and (3) simulations to see how accurately sized are hypothesis tests about the parameters of the model.

An aggregate demand - aggregate supply framework is used to analyze the effects of Japanese monetary policy, 1973:1-1990:8. It is found that money supply shocks contribute relatively little to output variability over the sample as a whole. Nor do these shocks seem to be particularly marked during business cycle contractions. The effects of monetary policy on prices and output appear to be quite similar to those of a constant money growth rule.