We propose a test for the evaluation of statistical acceptability of a functional constraint which is imposed on parameters in the mixed data sampling regressions. The asymptotic behavior of the test statistic is characterized and a few other extensions are discussed.

In this note, we argue that tests of overidentifying restrictions give little information on the validity of the moment conditions implied by the underlying economic model, and therefore are mute about the possibility of identifying the parameters of interest.

In the aftermath of the financial crisis, this study investigates which underlying determinants cause bank rating transitions. We develop survival analysis models to explain credit transition hazards using macroeconomic factors and the rating history. We find that there exists a significant...

This article tests the linearity assumption underlying the popular heterogeneous autoregressive model for realized volatility (HAR-RV). We implement a consistent model specification test that is robust to both distributional and model misspecification. We find that, using a nonparametric HAR-RV...

Recently, there has been increasing interest in model averaging within frequentist paradigm. In the existing literature, for proving consistency of model averaging estimators, local mis-specification is assumed. In this paper, we show that under general fixed parameter setup, the model averaging...

We highlight a subtle identification problem that afflicts models for non-negative data in which the conditional expectation is specified as the product of a logit and an exponential function. The results are illustrated with an empirical model for medical expenditures.

In this paper, we build on Ryan and Wales (1998), Moschini (1999), and Serletis and Shahmoradi (2007) and impose curvature conditions locally on the quadratic Almost Ideal Demand System (AIDS) model of Banks et al. (1997), an extension of the simple AIDS model of Deaton and Muellbauer (1980)...

Estimation of the non-linear Constant Elasticity of Scale (CES) function is generally considered problematic due to convergence problems and unstable and/or meaningless results. These problems often arise from a non-smooth objective function with large flat areas, the discontinuity of the CES...

We provide an alternative way to model sequential decision processes, which is consistent with the random utility maximization hypothesis and the existence of a representative agent. Our result is stated on terms of a direct utility representation, and it does not depend on parametric assumptions.

This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.