This paper proposes a couple of new methods to compute the news impact curve for stochastic volatility (SV) models. The new methods incorporate the joint movement of return and volatility, which has been ignored by the extant literature. The first method employs the Bayesian Markov chain Monte...

We propose to model endogeneity bias using prior distributions of moment conditions. The estimator can be obtained both as a method-of-moments estimator and in a Ridge penalized regression framework. We show the estimator’s relation to a Bayesian estimator.

In this paper we propose new estimation techniques in connection with regression models whose errors have distributions which are members of the celebrated Pearson’s system. Efficient MCMC procedures are proposed in the context of likelihood—based inference. The new techniques are applied to...

The expected value of the log of a Bayesian’s posterior assessment of the true state of nature, computed under the probability law of the true state, is always at least as large as the log of the prior.

There is a long and detailed history of attempts to understand what causes crime. One of the most prominent strands of this literature has sought to better understand the relationship between economic conditions and crime. An economic argument is that in an attempt to maintain consumption in the...

In this note, we provide the application of HCCME-type refinements to nonlinear GMM models with Bayesian interpretations.

Using GARCH models for density prediction of stock index returns, a comparison is provided between frequentist and Bayesian estimation. No significant difference is found between qualities of whole density forecasts, whereas the Bayesian approach exhibits significantly better left-tail forecast...

There have been numerous applications of partial observability bivariate probit models. These models identify determinants of individual discrete outcomes when all that is observed are collective outcomes and individual characteristics. Numerical difficulties with their likelihood functions are...

Exchange rate arrangements and trade are inherently connected. Exchange rate volatility has a significant impact on trade volumes, and trading partners thus could affect each other’s exchange rate regime choice. This spatial effect among trading partners has been overlooked in empirical...

A trade-off exists between the Gelfand and Dey (1994) and Chib (1995) methods to calculate the marginal likelihood in Bayesian estimation. Using the Markov Chain Monte Carlo method, we demonstrate that the performance of the two methods is fairly close.