We compare the finite sample performance of a number of Bayesian and Classical procedures for limited information simultaneous equations models with weak instruments by a Monte Carlo study. We consider recent Bayesian approaches developed by Ch ao and Phillips (1998, CP), Geweke (1996),...

We compare the finite sample performance of a number of Bayesian and classical procedures for limited information simultaneous equations models with weak instruments by a Monte Carlo study. We consider recent Bayesian approaches developed by Chao and Phillips (1998, CP), Geweke (1996),...

We have estimated a 4-step sequential probit model with and without sample separation information to characterize SSA's disability determination process. Under the program provisions, different criteria dictate the outcomes at different steps of the process. We used data on health, activity...

Dwivedi and Srivastava (1984, DS) studied the exact finite sample properties of Nagar’s (1962) double k-class estimator as continuous functions of its two characterizing scalars k1 and k2, and provided guidelines for their choice in empirical work. In this note we show that the empirical...

We have estimated a 4-step sequential probit model with and without sample separation information to characterize SSA's disability determination process. Under the program provisions, different criteria dictate the outcomes at different steps o f the process. We used data on health, activity...

This paper examines the determinants of inflation forecast uncertainty using a panel of density forecasts from the Survey of Professional Forecasters (SPF). Based on a dynamic heterogeneous panel data model, we find that the persistence in forecast uncertainty is much less than what the...

The authors compare the estimated after-tax ex ante real interest rates and the inflation forecasts generated by two alternative approaches: (1) the rational expectations model in which the real rate is assumed to have an autoregressive structure, and (2) by utilizing the Livingston survey data...