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Panel Data Models (panel + data_models)
Selected AbstractsSemiparametric Bayesian Inference in Autoregressive Panel Data ModelsECONOMETRICA, Issue 2 2002Keisuke Hirano First page of article [source] Bounds on Parameters in Panel Dynamic Discrete Choice ModelsECONOMETRICA, Issue 3 2006Bo E. Honoré Identification of dynamic nonlinear panel data models is an important and delicate problem in econometrics. In this paper we provide insights that shed light on the identification of parameters of some commonly used models. Using these insights, we are able to show through simple calculations that point identification often fails in these models. On the other hand, these calculations also suggest that the model restricts the parameter to lie in a region that is very small in many cases, and the failure of point identification may, therefore, be of little practical importance in those cases. Although the emphasis is on identification, our techniques are constructive in that they can easily form the basis for consistent estimates of the identified sets. [source] How Did the Elimination of the US Earnings Test above the Normal Retirement Age Affect Labour Supply Expectations?,FISCAL STUDIES, Issue 2 2008Pierre-Carl Michaud H55; J22 Abstract We look at the effect of the 2000 repeal of the earnings test above the normal retirement age (NRA) on the self-reported probabilities of working full-time after ages 65 and 62 of male workers in the US Health and Retirement Study (HRS). Using administrative records on social security benefit entitlements linked to the HRS survey data, we can distinguish groups of respondents according to the predicted effect of the earnings test before its repeal on their marginal wage rate after the NRA. We use panel data models with fixed and random effects to investigate the effect of the repeal. We find that male workers whose predicted marginal wage rate increased because the earnings test was repealed had the largest increase in the subjective probability of working full-time after age 65. We find no significant effects of the repeal on the subjective probability of working full-time past age 62. [source] Dynamic treatment effect analysis of TV effects on child cognitive developmentJOURNAL OF APPLIED ECONOMETRICS, Issue 3 2010Fali Huang We investigate whether TV watching at ages 6,7 and 8,9 affects cognitive development measured by math and reading scores at ages 8,9, using a rich childhood longitudinal sample from NLSY79. Dynamic panel data models are estimated to handle the unobserved child-specific factor, endogeneity of TV watching, and dynamic nature of the causal relation. A special emphasis is placed on the last aspect, where TV watching affects cognitive development, which in turn affects future TV watching. When this feedback occurs, it is not straightforward to identify and estimate the TV effect. We develop a two-stage estimation method which can deal with the feedback feature; we also apply the ,standard' econometric panel data approaches. Overall, for math score at ages 8,9, we find that watching TV during ages 6,7 and 8,9 has a negative total effect, mostly due to a large negative effect of TV watching at the younger ages 6,7. For reading score, there is evidence that watching no more than 2 hours of TV per day has a positive effect, whereas the effect is negative outside this range. In both cases, however, the effect magnitudes are economically small. Copyright © 2010 John Wiley & Sons, Ltd. [source] Semiparametric Bayesian inference for dynamic Tobit panel data models with unobserved heterogeneityJOURNAL OF APPLIED ECONOMETRICS, Issue 6 2008Tong Li This paper develops semiparametric Bayesian methods for inference of dynamic Tobit panel data models. Our approach requires that the conditional mean dependence of the unobserved heterogeneity on the initial conditions and the strictly exogenous variables be specified. Important quantities of economic interest such as the average partial effect and average transition probabilities can be readily obtained as a by-product of the Markov chain Monte Carlo run. We apply our method to study female labor supply using a panel data set from the National Longitudinal Survey of Youth 1979. Copyright © 2008 John Wiley & Sons, Ltd. [source] Heterogeneity and cross section dependence in panel data models: theory and applications introductionJOURNAL OF APPLIED ECONOMETRICS, Issue 2 2007Badi H. Baltagi The papers included in this special issue are primarily concerned with the problem of cross section dependence and heterogeneity in the analysis of panel data models and their relevance in applied econometric research. Cross section dependence can arise due to spatial or spill over effects, or could be due to unobserved (or unobservable) common factors. Much of the recent research on non-stationary panel data have focussed on this problem. It was clear that the first generation panel unit root and cointegration tests developed in the 1990's, which assumed cross-sectional independence, are inadequate and could lead to significant size distortions in the presence of neglected cross-section dependence. Second generation panel unit root and cointegration tests that take account of possible cross-section dependence in the data have been developed, see the recent surveys by Choi (2006) and Breitung and Pesaran (2007). The papers by Baltagi, Bresson and Pirotte, Choi and Chue, Kapetanios, and Pesaran in this special issue are further contributions to this literature. The papers by Fachin, and Moon and Perron are empirical studies in this area. Controlling for heterogeneity has also been an important concern for empirical researchers with panel data methods promising better handle on heterogeneity than cross-section data methods. The papers by Hsiao, Shen, Wang and Weeks, Pedroni and Serlenga and Shin are empirical contributions to this area. Copyright © 2007 John Wiley & Sons, Ltd. [source] Forecasting with panel data,JOURNAL OF FORECASTING, Issue 2 2008Badi H. Baltagi Abstract This paper gives a brief survey of forecasting with panel data. It begins with a simple error component regression model and surveys the best linear unbiased prediction under various assumptions of the disturbance term. This includes various ARMA models as well as spatial autoregressive models. The paper also surveys how these forecasts have been used in panel data applications, running horse races between heterogeneous and homogeneous panel data models using out-of-sample forecasts. Copyright © 2008 John Wiley & Sons, Ltd. [source] Consistent estimation of binary-choice panel data models with heterogeneous linear trendsTHE ECONOMETRICS JOURNAL, Issue 2 2006Alban Thomas Summary, This paper presents an extension of fixed effects binary choice models for panel data, to the case of heterogeneous linear trends. Two estimators are proposed: a Logit estimator based on double conditioning and a semiparametric, smoothed maximum score estimator based on double differences. We investigate small-sample properties of these estimators with a Monte Carlo simulation experiment, and compare their statistical properties with standard fixed effects procedures. An empirical application to land renting decisions of Russian households between 1996 and 2002 is proposed. [source] Dynamic or Static Capabilities?THE JOURNAL OF PRODUCT INNOVATION MANAGEMENT, Issue 5 2009Process Management Practices, Response to Technological Change Whether and how organizations adapt to changes in their environments has been a prominent theme in organization and strategy research. Within this research, there is controversy about whether organizational routines hamper or facilitate adaptation. Organizational routines give rise to inertia but are also the vehicles for change in recent work on dynamic capabilities. This rising interest in routines in research coincides with an increase in management practices focused on organizational routines and processes. This study explores how the increasing use of process management practices affected organizational response to a major technological change through new product developments. The empirical setting is the photography industry over a decade, during the shift from silver-halide chemistry to digital technology. The advent and rise of practices associated with the new ISO 9000 certification program in the 1990s coincided with increasing technological substitution in photography, allowing for assessing how increasing attention to routines through ISO 9000 practices over time affected ongoing responsiveness to the technological change. The study further compares the effects for the incumbent firms in the existing technology with nonincumbent firms entering from elsewhere. Relying on longitudinal panel data models as well as hazard models, findings show that greater process management practices dampened response to new generations of digital technology, but this effect differed for incumbents and nonincumbents. Increasing use of process management practices over time had a greater negative effect on incumbents' response to the rapid technological change. The study contributes to research in technological change by highlighting specific management practices that may create disconnects between firms' capabilities and changing environments and disadvantage incumbents in the face of radical technological change. This research also contributes to literature on organizational routines and capabilities. Studying the effects of increasing ISO 9000 practices undertaken in firms provides an opportunity to gauge the effects of systematic routinization of organizational activities and their effects on adaptation. This research also contributes to management practice. The promise of process management is to help firms adapt to changing environments, and, as such, managers facing technological change may adopt process management practices as a response to uncertainty and change. But managers must more fully understand the potential benefits and risks of process management to ensure these practices are used in the appropriate contexts. 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