Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics68:53-78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L-F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables, Cambridge: Cambridge University Press, pp. 199-225] are extended to higher-order dynamic panel data models with general covariance structure. The focus is on estimation of both short- and long-run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M1, M2 and M3 are estimated for the EU area as a whole for the period 1991: I-1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long-run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross-correlation patterns between countries are sometimes considerable.     

Markov chain Monte Carlo methods for high dimensional inversion in remote sensing

Summary.  We discuss the inversion of the gas profiles (ozone, NO₃, NO₂, aerosols and neutral density) in the upper atmosphere from the spectral occultation measurements. The data are produced by the 'Global ozone monitoring of occultation of stars' instrument on board the Envisat satellite that was launched in March 2002. The instrument measures the attenuation of light spectra at various horizontal paths from about 100 km down to 10–20 km. The new feature is that these data allow the inversion of the gas concentration height profiles. A short introduction is given to the present operational data management procedure with examples of the first real data inversion. Several solution options for a more comprehensive statistical inversion are presented. A direct inversion leads to a non-linear model with hundreds of parameters to be estimated. The problem is solved with an adaptive single-step Markov chain Monte Carlo algorithm. Another approach is to divide the problem into several non-linear smaller dimensional problems, to run parallel adaptive Markov chain Monte Carlo chains for them and to solve the gas profiles in repetitive linear steps. The effect of grid size is discussed, and we present how the prior regularization takes the grid size into account in a way that effectively leads to a grid-independent inversion.     

Interactionism,Social Organization,and Social Processes: Looking Back and Moving Ahead

With its roots in American pragmatism, symbolic interactionism has created a distinctive perspective and produced numerous important contributions and now offers significant prospects for the future. In this article, I review my intellectual journey with this perspective over forty years. This journey was initiated within the American society, sociology, and symbolic interaction of circa 1960. I note many of the contributions made by interactionists since that time, with particular focus on those who have contributed to the study of social organization and social process. I offer an agenda for the future based on currently underdeveloped areas that have potential. These are inequality orders, institutional analysis, collective action across space and time, and the integration of temporal and spatial orders. The article concludes with calls for further efforts at cross‐perspective dialogues, more attention to feminist scholars, and an elaborated critical pragmatism.     

领导权理论与后现代思潮

英国著名教授E·拉克劳以其拓展马克思主义的革命理论而闻名,并成为西方“后马克思主义”的著名代表人物之一。在其代表作《领导权与社会主义策略》(“Hegemony”一词,曾有“文化霸权”等译法;但本文译者认为,在拉克劳的著作中,他主要是在“国家、革命、阶级和革命的领导者”等意义上来谈论这一范畴的,所以在这里把“hegemony”译为“领导权”)一书中,拉克劳把马克思主义的领导权理论与后结构主义等当代“时髦”理论相结合的尝试引人注目,但也备受争议。为此,他在另一本著作《我们时代革命的新反思》一书中,系统地回答了《领导权与社会主义策略》一书中的有关问题。这些问题涉及其领导权理论与社会主义革命在当今社会现实中所面临的理论困境,包括革命的主体、阶级的构成、阶级斗争、对立和认同等等。此外,领导权理论还涉及其与现代西方哲学思潮的内在逻辑联系,如胡塞尔的现象学、维特根斯坦的后分析哲学、德里达的解构主义以及其他的后现代主义理论等。针对这些理论和现实问题,拉克劳一一进行了认真的回答和阐述。英国《新左派评论》编委会的部分成员罗宾(Robin Blackburn)、彼德(Peter Dews)和安娜(Anna-Marie Smith)于1988年5月策划专访拉克劳。以下访谈是从拉克劳《我们时代革命的新反思》一书中选译     

Facilitative Aspects of Field Research with Deviant Street Populations*

The authors examine facilitative aspects of field research with deviant street populations. Based on the authors' research with the homeless and with male street prostitutes, the facilitative aspects include access to settings, social relationships, acquisition of information, and the maintenance of researcher interest. The authors argue that in each of these aspects street deviants may in some ways be easier to study than other populations. The paper concludes with suggestions for maximizing the efficiency and quality of fieldwork with specific deviant populations.     

A Quasi-Experimental Evaluation of the Premarital Assessment Program for Premarital Counselling

The Premarital Assessment Program for premarital counselling (Buckner & Salts, 1985) was implemented to evaluate its potential for enhancing positive growth with premarital individuals. Twenty-one engaged couples were assigned to one of three groups, an experimental group that received the Premarital Assessment Program (PAP), an experimental group that received segments of the Couples Communication Program combined with a modified Premarital Assessment Program (CCPAP), or to a control group that received no treatment. Prior to the treatment period all individuals were administered a pretest which contained demographic questions, the Marital Communication Inventory (MCI), and the Dyadic Adjustment Scale (DAS). Following the treatment, all individuals were administered a post-test containing the MCI, DAS, and an open-ended question pertaining to their treatment experience. Both treatment groups showed improvement on the DAS total score and one of its subscales compared to the control group, although this change only reached statistical significance between the CCPAP group and the control groups. Further assessment is needed of the value of communication training in premarital counselling.     

Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances

We study the properties of the quasi-maximum likelihood estimator (QMLE) and related test statistics in dynamic models that jointly parameterize conditional means and conditional covariances, when a normal log-likelihood os maximized but the assumption of normality is violated. Because the score of the normal log-likelihood has the martingale difference property when the forst two conditional moments are correctly specified, the QMLE is generally Consistent and has a limiting normal destribution. We provide easily computable formulas for asymptotic standard errors that are valid under nonnormality. Further, we show how robust LM tests for the adequacy of the jointly parameterized mean and variance can be computed from simple auxiliary regressions. An appealing feature of these robyst inference procedures is that only first derivatives of the conditional mean and variance functions are needed. A monte Carlo study indicates that the asymptotic results carry over to finite samples. Estimation of several AR and AR-GARCH time series models reveals that in most sotuations the robust test statistics compare favorably to the two standard (nonrobust) formulations of the Wald and IM tests. Also, for the GARCH models and the sample sizes analyzed here, the bias in the QMLE appears to be relatively small. An empirical application to stock return volatility illustrates the potential imprtance of computing robust statistics in practice.