Monte Carlo evidence has made it clear that asymptotic tests based on generalized method of moments (GMM) estimation have disappointing size. The problem is exacerbated when the moment conditions are serially correlated. Several block bootstrap techniques have been proposed to correct the...

Jagannathan and Wang [Jagannthan, R., and Wang, Z., "The conditional CAPM and the cross-section of expected returns." Journal of Finance, 51 (1996), 3-53] derive the asymptotic distribution of the Hansen-Jagannathan distance (HJ-distance) proposed by Hansen and Jagannathan [Hansen, L.P., and...

This paper analyzes the higher-order properties of the estimators based on the nested pseudo-likelihood (NPL) algorithm and the practical implementation of such estimators for parametric discrete Markov decision models. We derive the rate at which the NPL algorithm converges to the MLE and...

Jagannathan and Wang (1996) derive the asymptotic distribution of the Hansen-Jagannathan distance (HJ-distance) proposed by Hansen and Jagannathan (1997), and develop a specification test of asset pricing models based on the HJ-distance. While the HJ-distance has several desirable properties,...

Purchasing power parity (PPP) is one of the most important, but empirically controversial theories in international macroeconomics. Although many researchers believe that some variant of PPP holds in the long run, there are diverse empirical results regarding the PPP hypothesis. We examine the...

We propose to extend the cointegration rank determination procedure of Robinson and Yajima (2002) to accommodate both (asymptotically) stationary and nonstationary fractionally integrated processes as the common stochastic trends and cointegrating errors by applying the exact local Whittle...

As Canada increasingly structures itself towards a "knowledge based economy", the supply of high-skilled professionals such as engineers and other science graduates acquires more importance. Following the theoretical framework developed by Ryoo and Rosen(2004), we develop and estimate a dynamic...

We study nonparametric identifiability of finite mixture models of k-variate data with M subpopulations, in which the components of the data vector are independent conditional on belonging to a subpopulation. We provide a sufficient condition for nonparametrically identifying M subpopulations...

This paper proposes two simple tests that are based on certain time domain properties of I(d) processes. First, if a time series follows an I(d) process, then each subsample of the time series also follows an I(d) process with the same value of d. Second, if a time series follows an I(d)...

This paper analyzes the higher-order properties of nested pseudo-likelihood (NPL) estimators and their practical implementation for parametric discrete Markov decision models in which the probability distribution is defined as a fixed point. We propose a new NPL estimator that can achieve...