This study develops practical methods for Bayesian nonparametric inference in regression models. The emphasis is on extending a nonparametric treatment of the regression function to the full conditional distribution. It applies these methods to the relationship of earnings of men in the United States to their age and education over the period 1967 through 1996. Principal findings include increa...

Preamble These lecture notes were written for a 2nd-year Ph.D. course in econometrics of panel data and limited-dependent-variable-models. The primary goal of the course is to introduce tools necessary to understand and implement empirical studies in economics focusing on other than time-series issues. The main emphasis of the course is twofold: (i) to extend regression models in the context of...

The present study aims at proving the existence of long memory (or long-range dependence) in earthquake process through analysis time series induced seismicity. Specifically, we apply alternative statistical techniques borrowed from econometrics to seismic catalog Geysers geothermal field (California), world’s largest field. choice area is essentially guided by completeness smaller magnitudes (...

The previous researches on the prediction of accidents frequently assumed the independence among the error terms, from the standpoint of traditional statistics. However, as spatial data including information about geographical spaces, data collected in each traffic analysis zones are not randomly distributed in space and have the spatial correlation each other. That violates the basic assumptio...

Goodness of fit tests based on sup-norm statistics of empirical processes have nonstandard limiting distributions when the null hypothesis is composite — that is, when parameters of the null model are estimated. Several solutions to this problem have been suggested, including the calculation of adjusted critical values for these nonstandard distributions and the transformation of the empirical ...