Showing papers in "Journal of Econometrics in 2005"

TL;DR: The authors showed that the extra variation due to the presence of these estimated parameters in the weight matrix accounts for much of the difference between the finite sample and the usual asymptotic variance of the two-step generalized method of moments estimator, when the moment conditions used are linear in the parameters.

TL;DR: The authors applied cross-sectional and longitudinal propensity score matching estimators to data from the National Supported Work (NSW) Demonstration that have been previously analyzed by LaLonde (1986) and Dehejia and Wahba (1999, 2002).

TL;DR: This paper examines several extensions of the stochastic frontier that account for unmeasured heterogeneity as well as firm inefficiency, and considers a special case of the random parameters model that produces a random effects model that preserves the central feature of the Stochastic frontier model and accommodates heterogeneity.

TL;DR: In this article, the authors use a quadratic directional output distance function to measure the technical efficiency of 209 electric utilities that produce electricity and a polluting byproduct, SO 2 before (1993) and after (1997) implementation of Phase I regulations of the acid rain program.

TL;DR: The adaptive quadrature approach is extended to general random coefficient models with limited and discrete dependent variables, which can include several nested random effects representing unobserved heterogeneity at different levels of a hierarchical dataset.

TL;DR: In this article, the authors discuss propensity score matching in the context of Smith and Todd's (does matching overcome Lalonde's critique of nonexperimental estimators, J. Am. Statist., 2002, forthcoming).

TL;DR: In this paper, the authors show that the sum of the estimated autoregressive parameters of the conditional variance converges to one for all common estimators of the GARCH model.

TL;DR: In this paper, the leverage effect in stochastic volatility (SV) models is modeled using a Gaussian nonlinear state space form with uncorrelated measurement and transition errors.

TL;DR: This article found that the equivalent of an academic year of community college schooling raises the long-term earnings of displaced workers by an average of about 9 percent for men and about 13 percent for women.

TL;DR: In this paper, a Bayesian approach is used to impose constraints on the parameters of a translog output distance function, leading to significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed.

TL;DR: The authors analyzed the impact of interventions on discrete outcomes when responses to treatment vary among observationally identical persons using a latent variable model motivated by economics, and applied the model to study the Norwegian Vocational Rehabilitation training program.

TL;DR: In this article, the authors developed a theoretical framework for the analysis of small-sample properties of forecasts from general autoregressive models under structural breaks, both conditionally and unconditionally, and numerical results for different types of break specifications are presented.

TL;DR: A set of new Markov chain Monte Carlo algorithms for Bayesian analysis of the multinomial probit model are introduced, which are as quick to converge as the fastest methods but with a more attractive prior.

TL;DR: In this paper, the main aim of this volume is to present key recent developments in the fields of modeling structural breaks and the analysis of long-term memory and stock market volatility.

TL;DR: This article analyzed the consistency, rate of convergence and limiting distributions of parameter estimates in models where the trend function exhibits a slope change at some unknown date and the errors can be either stationary or have a unit root.

TL;DR: In this article, the authors quantify the U.S. agricultural sector by measuring scale economies and output and input contributions and jointness, and find that both scope and scale economies have important economic performance implications, and that an inputoriented framework including off-farm income best characterizes agricultural production.

TL;DR: A computationally attractive instrumental variables estimator that is consistent under a relatively weak set of conditions is proposed and a Monte Carlo study indicates that this estimator may work well in practice.

TL;DR: In this paper, the authors report the results of the only field test of which they are aware that uses randomized trials to measure whether stricter enforcement and verification of work search behavior alone decreases unemployment claims and benefits paid in the U.S. unemployment insurance (UI) program.

TL;DR: In this paper, the authors argue for thinking of program evaluation as a decision problem, where a counselor determines which program (treatment or control) each individual joins, based for example on maximizing the probability of employment or expected earnings.

TL;DR: In this paper, the authors investigate the problem of predicting the average effect of a new training program using experiences with previous implementations, and find that adjusting for pre-training earnings and individual characteristics removes many of the differences between control units that have some previous employment experience.

TL;DR: In this paper, a control function estimator is proposed to adjust for endogeneity in the triangular simultaneous equations model where there are no available exclusion restrictions to generate suitable instruments, but the form of the error dependence on the exogenous variables is not parametrically specified.

TL;DR: In this article, the authors derived the asymptotic distribution of a new class of quasi-maximum likelihood estimators (QMLE) based on a tick-exponential family of densities.

TL;DR: Using the bus strike as an instrument for prenatal care in birth outcome equations, it is found that two-stage least-squares estimates of the impact of prenatal care on birth weight, gestation and maternal weight gain are similar to single-equation estimates.

TL;DR: Simulation-based Bayesian inference procedures in a cost system that includes the cost function and the cost share equations augmented to accommodate technical and allocative inefficiency are proposed and implemented.

TL;DR: In this article, the authors use the Generalized Method of Moments (GMM) estimator to estimate shadow prices, technical efficiency, and productivity change for a panel of electric utilities, yielding results that differ substantially from those obtained using standard GMM.

TL;DR: In this paper, a two-step estimator is proposed where the first step constitutes non-parametric estimation of the instrument and the second step is a nonparametric version of two-stage least squares.

TL;DR: In this article, the effects of structural breaks on tests for equal forecast accuracy and encompassing were investigated. And they showed that predictive content is harder to find with some tests than others: in power, F-type tests often dominate t-type alternatives, which may explain why researchers often find evidence of in-sample but not out-of-sample, predictive content.

TL;DR: In this article, the authors discuss inference in self-exciting threshold autoregressive (SETAR) models and show that valid inference can be drawn by the use of the subsampling method.

TL;DR: In this paper, a modification to Shibata's (Ann. Statist. 8 (1980) 147) final prediction error criterion was proposed to jointly choose the VAR lag order and one of two predictors: the maximum likelihood estimator plug-in predictor or the loss function estimator predictor.

TL;DR: In this paper, the authors deal with the testing of autoregressive conditional duration (ACD) models by gauging the distance between the parametric density and hazard rate functions implied by the duration process and their non-parametric estimates.