Journal of Econometrics
Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models [статья]
Опубликовано на портале: 06-04-2004Robert F. Engle, Mark W. Watson Journal of Econometrics. 1983. Vol. 23. No. 3. P. 385-400.
This paper provides a general approach to the formulation and estimation of dynamic unobserved component models. After introducing the general model, two methods for estimating the unknown parameters are presented. Both are algorithms for maximizing the likelihood function. The first is based on the method of Scoring. The second is the EM algorithm, a derivative-free method. Each iteration of EM requires a Kalman filter and smoother followed by straightforward regression calculations. The paper suggests using the EM methods to quickly locate a neighborhood of the maximum. Scoring can then be used to pinpoint the maximum and calculate the information matrix.
Опубликовано на портале: 07-04-2004Harry H. Kelejian Journal of Econometrics. 1982. Vol. 20. No. 2. P. 325-333.
The Glejser (1969) test for heteroskedasticity concerning the disturbance terms of a regression model is widely referenced - see, e.g., Goldfeld and Quandt (1972), Johnston (1972), Theil (1971) and Maddala (1978) among others. As originally proposed, Glejser suggested estimating the model’s disturbance terms via least squares, and then regressing their absolute values on certain known functions of the regressors; the suggested test for heteroskedasticity then relates to the significance of the ‘slope’ coefficients. Obvious modifications of this procedure, such as using squared estimated disturbance terms, have been suggested - see Goldfeld and Quandt (1972), and Kelejian and Oates (1974); still others have suggested modifications of the procedure which involve iterations - see Maddala (1978). Glejser noted that there may be shortcomings in the procedure which arise due to the use of the estimated disturbances in the second-stage regression. Goldfeld and Quandt (1972), among others, also noted shortcomings in the procedure but recognized that conditions may exist under which these shortcomings are of no consequence in the relevant asymptotic distribution; they went on to note, however, that at the time, a demonstration of such conditions was not available. In recent papers Amemiya (1977) and White (1980) gave results which justify the large sample version of the Glejser test based on squared estimated disturbances. However, their results assumed the absence of lagged dependent variables, and were given in the single-equation context. The purpose of this paper is to extend the Amemiya (1977) and White (1980) results to the case of a simultaneous equation framework, which may or may not contain lagged endogenous variables. We consider two cases. The first is the one in which the researcher suspects that heteroskedasticity may exist in only one of the system’s equations. This extension is not trivial due to, among other things, feedbacks involving the endogenous regressors. Nevertheless, it turns out that if the least-squares procedure in the first stage is replaced by virtually any consistent procedure, such as two-stage least- squares - henceforth 2SLS, no additional complexities arise. The importance of this result is that under typical modelling specifications, a computationally simple large sample test for heteroskedasticity, which is associated with one equation of a system, can be carried out in the context of that system. This test should be especially useful in those cases in which the exact specification of the ‘suspected’ heteroskedasticity is not known1 The second case we consider is the one in which the researcher suspects that heteroskedasticity may be associated with more than one equation of the system. As expected, the resulting test is computationally more ‘demanding’. The model is specified in section 2, and the basic results are given in section 3. Suggestions for further work are given in section 4; technical details are relegated to the appendix.
Опубликовано на портале: 13-04-2004Tim Bollerslev, Ray Y. Chou, Kenneth F. Kroner Journal of Econometrics. 1992. Vol. 52. No. 1-2. P. 5-59.
Although volatility clustering has a long history as a salient empirical regularity characterizing high-frequency speculative prices, it was not until recently that applied researchers in finance have recognized the importance of explicitly modeling time-varying second-order moments. Instrumental in most of these empirical studies has been the Autoregressive Conditional Heteroskedasticity (ARCH) model introduced by Engle (1982). This paper contains an overview of some of the developments in the formulation of ARCH models and a survey of the numerous empirical applications using financial data. Several suggestions for future research, including the implementation and tests of competing asset pricing theories, market microstructure models, information transmission mechanisms, dynamic hedging strategies, and the pricing of derivative assets, are also discussed.
Опубликовано на портале: 13-04-2004Donald Wilfrid Kao Andrews Journal of Econometrics. 1988. Vol. 37. No. 1. P. 135-157.
The Pearson chi-square testing method is extended to nondynamic parametric econometric models, particularly models with covariates. A chi-square test is developed that is applicable in a variety of cross-sectional models including panel data methods. It can be employed to test the null hypothesis that the specified parametric model is correct, i.e., the classical goodness-of-fit hypothesis. It also can be employed to test more specific aspects of a parametric model. The tests are applicable in models with covariates that are discrete, continuous, or mixed. The cells may be chosen by using the data, may have flexible shapes, and may partition the product space of the response variable and covariate spaces. The estimator employed to calculate the conditionally expected number of outcomes in each cell can be chosen quite generally. Furthermore, any regular, asymptotically normal estimator can be used. Abstract2: This paper and its sequel, Andrews, extend the Pearson chi-square testing method to non-dynamic parametric econometric models, in particular, models with covariates. The present paper introduced the test and discusses a wide variety of applications. Andrews establishes the asymptotic properties of the test, by extending recent probabilistic results for the weak convergence of empirical processes indexed by sets. The chi-square test that is introduced can be used to test goodness-of-fit of a parametric model, as well as to test particular aspects of the parametric model that are of interest. In the event of rejection of the null hypothesis of correct specification, the test provides information concerning the direction of departure from the null. The results allow for estimation of the parameters of the model by quite general methods. The cells used to construct the test statistic my be random and can be specified in a general form.
Опубликовано на портале: 05-02-2007Ronald G. Ehrenberg Journal of Econometrics. 2004. Vol. 121. No. 1. P. 19-37 .
This paper surveys the various strands of the literature on the econometrics of higher education that have developed during the last 40 years and indicates how the papers in the special issue of the Journal of Econometrics fit into this literature. It discusses in turn the estimation of rates of return to higher education, studies of the academic labor market, studies relating to institutional behavior and studies relating to higher education as an industry. It concludes by suggesting a number of important areas for future research.
Generalised residuals [статья]
Опубликовано на портале: 05-01-2003Christian Gourieroux, Alain Monfort, Alain Trognon, Eric Renault Journal of Econometrics. 1987. Vol. 34. No. 1-2. P. 5-32.
This paper proposes a definition of generalised residuals for a large class of non-linear econometric models. These residuals are shown to have properties similar to those of the familiar residuals in the linear model and to be useful in many hypothesis testing problems.
Опубликовано на портале: 13-04-2004Tim Bollerslev Journal of Econometrics. 1986. Vol. 31. No. 3. P. 307-327.
A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in Engle (1982) to allow for past conditional variances in the current conditional variance equation is proposed. Stationarity conditions and autocorrelation structure for this new class of parametric models are derived. Maximum likelihood estimation and testing are also considered. Finally an empirical example relating to the uncertainty of the inflation rate is presented.
Опубликовано на портале: 26-09-2007William A. Brock, Steven N. Durlauf, Kenneth D. West Journal of Econometrics. 2007. Vol. 136. No. 2. P. 629-664.
This paper explores ways to integrate model uncertainty into policy evaluation. We first describe a general framework for the incorporation of model uncertainty into standard econometric calculations. This framework employs Bayesian model averaging methods that have begun to appear in a range of economic studies. Second, we illustrate these general ideas in the context of assessment of simple monetary policy rules for some standard New Keynesian specifications. The specifications vary in their treatment of expectations as well as in the dynamics of output and inflation. We conclude that the Taylor rule has good robustness properties, but may reasonably be challenged in overall quality with respect to stabilization by alternative simple rules that also condition on lagged interest rates, even though these rules employ parameters that are set without accounting for model uncertainty
Опубликовано на портале: 06-04-2004A. Colin Cameron, Pravin K. Trivedi Journal of Econometrics. 1990. Vol. 46. No. 3. P. 347-364.
A property of the Poisson regression model is mean-variance equality, conditional on explanatory variables. "Regression-based" tests for this property are proposed in a very general setting. Unlike classical statistical tests, these tests require specification of only the mean-variance relationship under the alternative, rather than the complete distribution whose choice is usually arbitrary. The optimal regression-based test is easily computed as the t-test from an auxiliary regression. If a distribution under the alternative hypothesis is in fact specified and is in the Katz system of distributions or is Cox's local approximation to the Poisson, the score test for the Poisson distribution is equivalent to the optimal regression-based test.
Опубликовано на портале: 06-04-2004Andrew Chesher, Margaret Irish Journal of Econometrics. 1987. Vol. 34. No. 1-2. P. 33-62.
Graphical and numerical analysis of residual can be informative about model misspecification even when data are censored or grouped. This paper provides simple procedures for calculating diagnostic statistics to detect model misspecification when grouped or censored data are analysed using a normal linear model. Graphs can reveal the nature of the correlations that these statistics pick up but when grouping or censoring is severe they can be difficult to interpret. We discuss the processing of graphs so that they are more easily interpreted and provide examples based on artificial data and on grouped data relating to unemployment durations.
Опубликовано на портале: 01-07-2004Andrew Chesher Journal of Econometrics. 1985. Vol. 28. No. 3. P. 291-305.
Efficient estimation of normal linear simultaneous equations systems is frequently easier when error covariances are zero. The score test is examined for the hypothesis that an error covariance is zero in a 2-equation recursive normal linear simultaneous equations system where endogenous variates may be completely observed, censored, or grouped. The model contains the seemingly unrelated regression equation model and its analogues for grouped and censored data as special cases. The score test for the hypothesis explores the sample covariance of suitably defined residuals and is closely related to the Information Matrix test calculated for the restricted model in which the error covariance is zero. These results are obtained by viewing a non-zero error covariance as emerging from correlated random variation in intercept parameters that can be detected through the use of Chesher's (1984) test for neglected heterogeneity
Опубликовано на портале: 25-10-2007Svend Hylleberg, Robert F. Engle, Clive W. J. Granger, Byung Sam Yoo Journal of Econometrics. 1990. Vol. 44. No. 1. P. 215-238.
This paper develops tests for roots in linear time series which have a modulus of one but which correspond to seasonal frequencies. Critical values for the tests are generated by Monte Carlo methods or are shown to be available from Dickey-Fuller or Dickey-Hasza-Fuller critical values. Representations for multivariate processes with combinations of seasonal and zero-frequency unit roots are developed leading to a variety of autoregressive and error-correction representations. The techniques are used to examine cointegration at different frequencies between consumption and income in the U.K.
Опубликовано на портале: 06-04-2004John Kennan Journal of Econometrics. 1985. Vol. 28. No. 1. P. 5-28.
This paper develops new evidence on the hazard function for strike duration, and on cyclical changes in this function, using data on contract strikes in U.S. manufacturing industries. A flexible duration model is estimated, and it is found that the hazard rate is generally a U-shaped function of strike age. The level of industrial production is found to have a significant positive effect on the hazard rate: strike duration is countercyclical. A convenient parametric model of heterogeneity and duration dependence is introduced, in which the logit of the hazard rate is a polynomial function of strike age, up to a random individual effect drawn from a beta distribution. Estimates of this `beta-logit' model indicate that it is difficult to detect the influence of unobserved heterogeneity on the aggregate hazard function for strike duration.