With 23 core econometrics journals now in operation, this study fills a gap in the literature by cataloguing the editorial specifications of each journal, and, more importantly, assessing their impact based on citations to research published in each over the 15-year period beginning in 2001 and...

Most econometric multi-equation models estimated are assumed to be linear in both the variables and the parameters. One reason is that, in general, methods of linear algebra cannot be applied to nonlinear systems. In this paper a certain class of nonlinear models is defined, however, the members...

This paper addresses how to enhance the role of data in structural model design by utilizing structural breaks and superfluous information as auxiliary tools of exact identification. To illustrate the procedure and to study the simultaneous interplay between financial variables and the real side...

We find empirical evidence of a financial accelerator using a data based procedure of Structural Model Design. Credit to firms, asset prices and aggregate economic activity interact over the business cycle in our empirical model of a dynamic economy. Furthermore, the interdependence between...

This paper establishes nonparametric identification of individual treatment effects in a nonseparable model with a binary endogenous regressor. The outcome variable may be continuous, discrete, or a mixture of both, while the instrumental variable can take binary values. First, we study the case...

The generalized autoregressive conditional heteroscedastic model (GARCH) is used to estimate volatility for Nifty Index futures on day trades. The purpose is to find out if a contemporaneous or causal relation exists between volatility volume and open interest for Nifty Index futures traded on...

This paper examines the rise of the VAR approach from a historical perspective. It shows that the VAR approach arises as a systematic solution to the issue of 'model choice' bypassed by Cowles Commission (CC) researchers, and that the approach essentially inherits and enhances the CC legacy...

The generalized method of moments estimator may be substantially biased in finite samples, especially so when there are large numbers of unconditional moment conditions. This paper develops a class of first order equivalent semi-parametric efficient estimators and tests for conditional moment...

The principal purpose of this paper is to adapt to the conditional moment context the GEL unconditional moment methods described in Smith(1997, 2001) and Newey and Smith(2004). In particular we develop GEL estimators which achieve the semiparametric efficiency lower bound. The requisite GEL...