Two-step estimation with large panel data sets generally involves estimating vectors of individual-specific coefficients in a first-stage. In a second-stage estimation a vector of estimated coefficients is used as the dependent variable. Potential problems of heteroskedasticity in the second...

The Nelson–Olsen covariance estimator of the simultaneous least squares-probit model is adjusted to accommodate probability based stratified surveys. A simultaneous model of body mass and the propensity to exercise provides an empirical example using stratified survey data.

In this paper, we study the Jarque–Bera (JB) and cusum tests for the normality of innovations and parameter change in BCTT-GARCH models. In order to demonstrate the validity of JB normality and cusum parameter change tests, we derive their limiting null distributions under mild conditions.

We make an extensive simulation analysis in order to investigate the consequences of ignoring the potentially complex and data dependent effects of allocative inefficiency on the estimation of stochastic frontier panel data models. Generally system estimators perform worse than single equation...

A Wald type test of the joint null hypothesis of linearity and nonstationarity within a threshold autoregressive process of order one with deterministic components is developed. Its limiting distribution is derived and its local power and finite sample properties investigated.

Many promising efforts in the social sciences aim to measure future outcomes (such as wages or health outcomes) given some base level of human capital or ability. They typically fail to recognize the proxies for human capital are all measured with error, creating bias in regression analysis....

I provide the nonparametric identification of nonlinear dynamic panel data models. I relax the assumption of covariate evolution in Shiu and Hu (2013) by the results of Hu and Shum (2012). The assumptions include first-order Markov assumptions and a restriction on the evolution of the covariate.

This article provides a procedure for the estimation of parametric homogeneous stochastic volatility (SV) pricing formulae based on option data. Our estimator has the advantage of being (i) based on option data, (ii) easy to implement in practice, (iii) with clear statistic properties and (iv)...

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...

A simple example is provided that shows that one test can strictly dominate another test in both local power and its robustness to asymptotic size distortion under local model misspecification, with both tests having asymptotic size equal to nominal size under correct model specification....