Search Results
Working Paper
Variable selection and model comparison in regression
In the specification of linear regression models it is common to indicate a list of candidate variables from which a subset enters the model with nonzero coefficients. This paper interprets this specification as a mixed continuous-discrete prior distribution for coefficient values. It then utilizes a Gibbs sampler to construct posterior moments. It is shown how this method can incorporate sign constraints and provide posterior probabilities for all possible subsets of regressors. The methods are illustrated using some standard data sets.
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Pricing the term structure with linear regressions
We estimate the time series and cross section of bond returns by way of three-stage ordinary least squares, which we label dynamic Fama-MacBeth regressions. Our approach allows for estimation of models with a large number of pricing factors. Even though we do not impose yield cross-equation restrictions in the estimation, we show that our bond return regressions generate a term structure of interest rates with small yield errors when compared with commonly reported specifications. We uncover specifications that give rise to lower pricing errors than do commonly advocated specifications, both ...
Working Paper
A note on the estimation of linear regression models with Heteroskedastic measurement errors
I consider the estimation of linear regression models when the independent variables are measured with errors whose variances differ across observations, a situation that arises, for example, when the explanatory variables in a regression model are estimates of population parameters based on samples of varying sizes. Replacing the error variance that is assumed common to all observations in the standard errors-in-variables estimator by the mean measurement error variance yields a consistent estimator in the case of measurement error heteroskedasticity. However, another estimator, which I call ...
Working Paper
Exhuming Q: market power capital market imperfections
Evidence of the statistical significance of profits in Q regressions remains one of the principal findings in the empirical investment literature. This result is frequently taken to support the view that capital market imperfections are an important element for understanding investment. This paper challenges that conclusion. We argue that allowing the profit function at the firm level to be strictly concave, reflecting, for example, market power, is sufficient to replicate the Q theory based regression results in which profits are a significant factor determining investment. To be clear, our ...
Working Paper
Superneutrality in postwar economies
A structural vector autoregression is employed to estimate the real output level response to permanent inflation shocks. We identify the model by assuming that in the long run, inflation is a monetary phenomenon. Well-known economic theory is used to establish this identification restriction. The model is estimated for a sample of 16 countries from the larger pool based on data quality, existence of long uninterrupted series on output and inflation, and evidence that the country experienced permanent shocks to inflation and output. The VAR is estimated for each country separately. We find ...
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Model selection criteria for factor-augmented regressions
In a factor-augmented regression, the forecast of a variable depends on a few factors estimated from a large number of predictors. But how does one determine the appropriate number of factors relevant for such a regression? Existing work has focused on criteria that can consistently estimate the appropriate number of factors in a large-dimensional panel of explanatory variables. However, not all of these factors are necessarily relevant for modeling a specific dependent variable within a factor-augmented regression. This paper develops a number of theoretical conditions that selection ...
Working Paper
Terms-of-trade uncertainty and economic growth: are risk indicators significant in growth regressions?
This paper examines a neoclassical stochastic endogenous growth model in which terms-of-trade uncertainty affects savings and consumption growth. The model explains the positive link between growth and the average rate of change of terms of trade found in recent empirical studies. In addition, terms-of-trade variability, as an indicator of risk, is found to be a key determinant of growth. This implies that welfare costs of uncertainty are much larger than conventional measures of costs of consumption instability. The model's key predictions are strongly supported by results of panel ...
Discussion Paper
Understanding hedge fund alpha using improved replication methodologies
In this paper, we estimate alpha for major hedge fund indexes. To set the stage, we examine several alternative methods for replicating Hedge Fund Research Inc. hedge fund indexes. The replication methods include stepwise regression, variations of the lasso shrinkage method, principal component regression, partial least squares regression, and dynamic linear regression. We find that the lasso methods and dynamic regression are superior for generating hedge fund replications and that the performance of the replications corresponds closely to that of the respective actual indexes. Using these ...
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Commodity prices, commodity currencies, and global economic developments
In this paper, we seek to produce forecasts of commodity price movements that can systematically improve on naive statistical benchmarks. We revisit how well changes in commodity currencies perform as potential efficient predictors of commodity prices, a view emphasized in the recent literature. In addition, we consider different types of factor-augmented models that use information from a large data set containing a variety of indicators of supply and demand conditions across major developed and developing countries. These factor-augmented models use either standard principal components or ...