This paper is concerned with Bayesian reduced rank regression when instruments are weak. There have been a number of studies on weak identification problem with the application of reduced rank regression combined with singular value decomposition (SVD) method in the Bayesian framework, see...

This paper examines the determinants of inflation forecast uncertainty using a panel of density forecasts from the Survey of Professional Forecasters (SPF). We show that previous studies based on aggregate data are biased due to heterogeneity of individual forecasts. Instead, we estimate a...

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 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...