Search Results
Working Paper
Interpreting long-horizon estimates in predictive regressions
This paper analyzes the asymptotic properties of long-horizon estimators under both the null hypothesis and an alternative of predictability. Asymptotically, under the null of no predictability, the long-run estimator is an increasing deterministic function of the short-run estimate and the forecasting horizon. Under the alternative of predictability, the conditional distribution of the long-run estimator, given the short-run estimate, is no longer degenerate and the expected pattern of coefficient estimates across horizons differs from that under the null. Importantly, however, under the ...
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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
The Role of Selective High Schools in Equalizing Educational Outcomes: Heterogeneous Effects by Neighborhood Socioeconomic Status
We investigate whether elite Chicago public high schools can help close the achievement gap between high-achieving students from more and less affluent neighborhoods. Seats are allocated based on prior achievement with 70 percent reserved for high-achieving applicants from four neighborhood socioeconomic status (SES) categories. Using regression discontinuity design, we find no effect on test scores or college attendance for students from high- or low-SES neighborhoods and positive effects on student reports of their experiences. For students from low-SES neighborhoods, we estimate ...
Working Paper
A note on the coefficient of determination in models with infinite variance variables
Since the seminal work of Mandelbrot (1963), alpha-stable distributions with infinite variance have been regarded as a more realistic distributional assumption than the normal distribution for some economic variables, especially financial data. After providing a brief survey of theoretical results on estimation and hypothesis testing in regression models with infinite-variance variables, we examine the statistical properties of the coefficient of determination in models with alpha-stable variables. If the regressor and error term share the same index of stability alpha
Working Paper
Estimation of panel data regression models with two-sided censoring or truncation
This paper constructs estimators for panel data regression models with individual specific heterogeneity and two-sided censoring and truncation. Following Powell (1986) the estimation strategy is based on moment conditions constructed from re-censored or re-truncated residuals. While these moment conditions do not identify the parameter of interest, they can be used to motivate objective functions that do. We apply one of the estimators to study the effect of a Danish tax reform on household portfolio choice. The idea behind the estimators can also be used in a cross sectional setting.
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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Consistent covariance matrix estimation in probit models with autocorrelated errors
Some recent time-series applications use probit models to measure the forecasting power of a set of variables. Correct inferences about the significance of the variables requires a consistent estimator of the covariance matrix of the estimated model coefficients. A potential source of inconsistency in maximum likelihood standard errors is serial correlation in the underlying disturbances, which may arise, for example, from overlapping forecasts. We discuss several practical methods for constructing probit autocorrelation-consistent standard errors, drawing on the generalized method of moments ...
Working Paper
Confidence intervals for long-horizon predictive regressions via reverse regressions
Long-horizon predictive regressions in finance pose formidable econometric problems when estimated using the sample sizes that are typically available. A remedy that has been proposed by Hodrick (1992) is to run a reverse regression in which short-horizon returns are projected onto a long-run mean of some predictor. By covariance stationarity, the slope coefficient is zero in the reverse regression if and only if it is zero in the original regression, but testing the hypothesis in the reverse regression avoids small sample problems. Unfortunately this only allows us to test the null of no ...