Minimizing Bias in Selection on Observables Estimators When Unconfoundness Fails We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using simulated data, as wel...

This paper uses MSA level data and a panel VAR model to analyze the dynamic determination and impact of the volatility of single-family home value appreciation. We find that the volatility can be magnified by an exogenous increase in the home appreciation rate, responds to changes in the population growth rate, and is serially correlated. Moreover, an exogenous increase in the volatility increa...

This paper employs Hamilton’s (1989) original Markov-switching model and time-varying Markov-switching model developed by Filardo (1994), respectively, to investigate the business cycle and evaluate the usefulness of the coincident and leading indexes in dating the business cycle and in predicting future GDP in Taiwan. The empirical results do suggest that these two indexes help date the busine...

Currently available asymptotic results in the literature suggest that matching estimators have higher variance than reweighting estimators. The extant literature comparing the finite sample properties of matching to specific reweighting estimators, however, has concluded that reweighting performs far worse than even the simplest matching estimator. We resolve these puzzling conclusions. Specifi...

There has been serious suspicion of a spurious rejection of the unit roots in panel studies of PPP due to the failure to control for cross-sectional dependence. This article presents evidence of mean-reversion in industrial country real exchange rates in a set up that accounts naturally for cross-sectional dependence, is invariant to the benchmark currency and capable of detecting against regim...

In this paper, we use the adaptive lasso estimator to choose the relevant instruments and eliminate the irrelevant instruments. The limit theory of Zou (2006) is extended from univariate iid case to heteroskedastic and non Gaussian data. Then we use the selected instruments in generalized empirical likelihood estimators (GEL). In this sense, these are called hybrid GEL. It is also shown that th...

In Markov-switching regression models, we use Kullback–Leibler (KL) divergence between the true and candidate models to select the number of states and variables simultaneously. Specifically, we derive a new information criterion, Markov switching criterion (MSC), which is an estimate of KL divergence. MSC imposes an appropriate penalty to mitigate the overretention of states in the Markov chai...

In this paper Efficient Importance Sampling (EIS) is used to perform a classical and Bayesian analysis of univariate and multivariate Stochastic Volatility (SV) models for financial return series. EIS provides a highly generic and very accurate procedure for the Monte Carlo (MC) evaluation of high-dimensional interdependent integrals. It can be used to carry out ML-estimation of SV models as we...

Following Lancaster (2002), we propose a strategy to solve the incidental parameter problem. The method is demonstrated under a simple panel Poisson count model. We also extend the strategy to accomodate cases when information orthogonality is unavailable, such as the linear AR(p) panel model. For the AR(p) model, there exists a correction function to fix the incidental parameter problem when t...

This paper explores the ability of some popular income distributions to model observed skewness and kurtosis. We present the generalized beta type 1 (GB1) and type 2 (GB2) distributions’ skewnesskurtosis spaces and clarify and expand on previously known results on other distributions’ skewnesskurtosis spaces. Data from the Luxembourg Income Study are used to estimate sample moments and explore ...