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Understanding spot and forward exchange rate regressions (replication data)
Using the Kalman filter, we obtain maximum likelihood estimates of a permanent-transitory components model for log spot and forward dollar prices of the pound, the franc, and... -
Stochastic trends, deterministic trends, and business cycle turning points (r...
This study examines the relationship between specifications for long-run output patterns and specifications for business cycle dynamics. In an application to US GDP, it is found... -
Is there a unit root in the inflation rate? Evidence from sequential break an...
Using sequential trend break and panel data models, we investigate the unit root hypothesis for the inflation rates of thirteen OECD countries. With individual country tests, we... -
HETEROGENEITY, EXCESS ZEROS, AND THE STRUCTURE OF COUNT DATA MODELS (replicat...
This paper demonstrates that the unobserved heterogeneity commonly assumed to be the source of overdispersion in count data models has predictable implications for the... -
SEMI-PARAMETRIC ESTIMATION OF HURDLE REGRESSION MODELS WITH AN APPLICATION TO...
This paper develops a semi-parametric estimation method for hurdle (two-part) count regression models. The approach in each stage is based on Laguerre series expansion for the... -
COUNT DATA REGRESSION USING SERIES EXPANSIONS: WITH APPLICATIONS (replication...
A new class of parametric regression models for both under? and overdispersed count data is proposed. These models are based on squared polynomial expansions around a Poisson... -
STATISTICAL INFERENCE VIA BOOTSTRAPPING FOR MEASURES OF INEQUALITY (replicati...
In this paper we consider the use of bootstrap methods to compute interval estimates and perform hypothesis tests for decomposable measures of economic inequality. Two... -
A PREDICTIVE APPROACH TO MODEL SELECTION AND MULTICOLLINEARITY (replication d...
We argue for the adoption of a predictive approach to model specification. Specifically, we derive the difference between means and the ratio of determinants of covariance...
