This paper provides estimators of discrete choice models, including binary, ordered, and multinomial response (choice) models. The estimators closely resemble ordinary and two stage least squares. The distribution of the model's latent variable error is unknown and may be related to the...

We re-examine Sephton and Larsen's (1991) conclusion that cointegration-based tests for market efficiency suffer from temporal instability. We improve upon their research by i) including a drift term in the vector error correction model (VECM) in the Johansen procedure, ii) correcting the...

This paper considers identification and estimation of the marginal effect of a mismeasured binary regressor in a nonparametric regression, or the conditional average effect of a binary treatment or policy on some outcome where treatment may be misclassified. Misclassification probabilities and...

We consider estimation of means of functions that are scaled by an unknown density, or equivalently, integrals of conditional expectations. The "ordered data" estimator we provide is root n consistent, asymptotically normal, and is numerically extremely simple, involving little more than...

We employ a nonlinear, nonparametric method to model the stochastic behavior of changes in several short and long term U.S. interest rates. We apply a nonlinear autoregression to the series using the locally weighted regression (LWR) estimation method, a nearest-neighbor method, and evaluate the...

Several studies have tested for long-range dependence in macroeconomic and financial time series but very few have assessed the usefulness of long-memory models as forecast generating mechanisms. This study tests for fractional differencing in the U.S. monetary indices (simple sum and divisia)...

Significant departures from log normality are observed in income data, in violation of Gibrat's law. We identify a new empirical regularity, which is that the distribution of consumption expenditures across households is, within cohorts, closer to log normal than the distribution of income. We...

This paper investigates the presence of fractal dynamics in stock returns. We improve upon existing literature in two ways: i) instead of rescaled-range analysis, we use the more efficient semi- nonparametric procedure suggested by Geweke and Porter-Hudak (GPH, 1983), and ii) to ensure...

Relative prices are nonstationary and standard root-T inference is invalid for demand systems. But demand systems are nonlinear functions of relative prices, and standard methods for dealing with nonstationarity in linear models cannot be used. Demand system residuals are also frequently found...

For vectors z and w and scalar v, let r(v,z,w) be a function that can be nonparametrically estimated consistently and asymptotically normally, such as a distribution, density, or conditional mean regression function. We provide consistent, asymptotically normal nonparametric estimators for the...