Showing papers in "Journal of Econometrics in 2002"

TL;DR: In this article, the authors consider pooling cross-section time series data for testing the unit root hypothesis, and they show that the power of the panel-based unit root test is dramatically higher, compared to performing a separate unit-root test for each individual time series.

TL;DR: In this paper, a nonparametric estimator based on the concept of expected minimum input function (or expected maximal output function) is proposed, which is related to the FDH estimator but will not envelop all the data.

TL;DR: In this article, the authors examined a two-regime vector error-correction model with a single cointegrating vector and a threshold effect in the errorcorrection term, and proposed a relatively simple algorithm to obtain maximum likelihood estimation of the complete threshold cointegration model for the bivariate case.

TL;DR: In this article, a Markov chain Monte Carlo (MCMCMC) algorithm is proposed to estimate the likelihood function of a generalized model of stochastic volatility, defined by heavy-tailed Student-t distributions.

TL;DR: In this article, the authors examined the panel data estimation of dynamic models for count data that include correlated fixed effects and predetermined variables, and used a linear feedback model to obtain a consistent estimator for the parameters in the dynamic model.

TL;DR: In this article, a generalization of the variance ratio statistic is suggested, which can be used to test the cointegration rank in the spirit of Johansen (J. Econ. Dyn. Econom. 15 (1992) 159) but assumes nonstationarity under the null hypothesis.

TL;DR: In this paper, a transformed likelihood approach is suggested to estimate fixed effects dynamic panel data models and conditions on the data generating process of the exogenous variables are given to get around the issue of "incidental parameters".

TL;DR: In this article, a unit root test for panels with cross-sectional dependency is proposed, which is based on nonlinear IV estimation of the usual augmented Dickey-Fuller type regression.

TL;DR: In this article, the structural properties of a family of GARCH processes are investigated, and necessary and sufficient conditions for the existence of the moments are derived, where α∈(0, 1] and δ>0.

TL;DR: This paper developed a class of Poisson-Gaussian models of the Fed Funds rate to capture surprise effects, and showed that these models offer a good statistical description of short rate behavior, and are useful in understanding many empirical phenomena.

TL;DR: In this article, the authors exploit the distributional information contained in high-frequency intraday data in constructing a simple conditional moment estimator for stochastic volatility diffusions.

TL;DR: In this article, the authors examined the predictability of stock market returns by employing a new metric entropy measure of dependence with several desirable properties, including the ability to detect nonlinear dependence within the returns series, and the ability of detecting nonlinear "affinity" between the returns and their predictions obtained from various models.

TL;DR: Simple matrix algebra techniques are developed that simplify and unify much of the previous literature on estimating error components models (ECMs) and are useful for analyzing a very broad set of models with complex error structures.

TL;DR: This paper evaluates the properties of a joint and sequential estimation procedure for estimating the parameters of single and multiple threshold models via the introduction of a model selection based procedure that allows the estimation of both the unknown parameters and their number to be performed jointly.

TL;DR: In this article, the existence and extent of cointegration in fractionally integrated systems is investigated in the setting of stationary series, with some discussion of extension to nonstationarity.

TL;DR: In this article, a unified framework for testing the adequacy of an estimated GARCH model is presented, where Parametric Lagrange multiplier (LM) or LM type tests of no ARCH in standardized errors, linearity, and parameter constancy are proposed.

TL;DR: In this article, the use of the bootstrap for the most commonly applied procedures in inequality, mobility and poverty measurement is proposed, and Monte Carlo evidence suggests that the simplest possible bootstrap procedure should be the preferred method in practice, as it achieves the same accuracy as the δ-method and takes into account the stochastic dependencies in the data without explicitly having to deal with its covariance structure.

TL;DR: In this article, a structural labour supply model that can be used to analyse all sorts of (non-linear) tax and benefits reforms is presented, where the direct utility function is approximated with a series expansion.

TL;DR: In this article, the authors investigate a test for the null hypothesis of trend stationarity with a structural change against a unit root, and derive the limiting distribution of an Lagrange Multiplier (LM) test statistic and its characteristic function under a sequence of local alternatives.

TL;DR: The authors proposed an integrated conditional moment type predictive accuracy test that is similar in spirit to that developed by Bierens and Ploberger (Econometrica 65 (1997) 1129).

TL;DR: In this article, the first four moments are given, and the skewness-kurtosis domain for which densities are defined is found to be much larger than for Hermite or Edgeworth expansions.

TL;DR: This paper derives a limited information likelihood (LIL) under some moment-based limited information available in GMM based on entropy theory of I-projection theory and investigates an interesting relation between the Bayesian and the classical distribution theories.

TL;DR: In this article, it was shown that an abrupt change in the innovation variance of an integrated process can generate spurious rejections of the unit root null hypothesis in routine applications of Dickey-Fuller tests.

TL;DR: A new time series model is put forward that describes the data rather well and that it outperforms related competitive models on various measures of fit.

TL;DR: In this article, a dual characterization of the shadow cost system and the shadow distance system is presented, where the first-order conditions from the cost minimization problem are used to obtain direct estimates of input inefficiency with the former and indirect estimates with the latter.

TL;DR: In this paper, a nonparametric estimation of the conditional density of the latent variables given the measurements using the identification results at the first stage, and at the second stage, a semiparametric nonlinear least-squares estimator is proposed.

TL;DR: In this paper, the authors proposed a score test for univariate time series with a limiting normal distribution, which is similar to the Dickey-Fuller test for multivariate cointegration tests.

TL;DR: In this paper, a general semiparametric Bayesian model is developed which contains potential outcomes and subject level outcome-specific random effects, and the model is subjected to a fully Bayesian analysis based on Markov chain Monte Carlo simulation methods.

TL;DR: Amos Golan Department of Economics, American University, Roper 200, 4400 Massachusetts Ave., NW, Washington, DC 20016, USA as mentioned in this paper has published a paper on the Golan Decision Process.

TL;DR: In this paper, the authors consider methods of deriving sufficient conditions for the central limit and functional central limit theorem to hold in a broad class of time series processes, including nonlinear processes and semiparametric linear processes.