Generalized dynamic panel data models with random effects for cross-section and time

Mesters, Geert; Koopman, Siem Jan

doi:10.1016/j.jeconom.2014.03.004

Cited by 13 publications

(17 citation statements)

References 59 publications

(43 reference statements)

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“…Section 3. The methodology is discussed for a more general panel data model in Mesters and Koopman (2014). The parameters are summarized in the vector ψ.…”

Section: Discussionmentioning

confidence: 99%

“…More efficiency can be obtained by sampling sequences for µ from an appropriate importance density (Ripley, 1987). For the construction of an adequate importance density we follow Jungbacker and Koopman (2007) and Mesters and Koopman (2014). where samples µ (s) are drawn independently from importance density g(µ|Y ).…”

Section: Discussionmentioning

confidence: 99%

“…The parameters are estimated by using the Monte Carlo maximum likelihood methods developed in Jungbacker and Koopman (2007) and Mesters and Koopman (2014). A detailed discussion for the methods is provided in Appendix A.…”

Section: Statistical Modelmentioning

confidence: 99%

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Crime, Employment and Social Welfare: An Individual-Level Study on Disadvantaged Males

2015

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. We test economic and sociological theories for the relationship between employment and crime, where social welfare is used as an identifying mechanism. Methods: We consider a sample of disadvantaged males from The Netherlands who are observed between ages 18 and 32 on a monthly time scale. We simultaneously model the offending, employment and social welfare variables using a dynamic discrete choice model, where we allow for state dependence, reciprocal effects and time-varying unobserved heterogeneity. Results: We find significant negative bi-directional structural effects between employment and property crime. Robustness checks show that only regular employment is able to significantly reduce the offending probability. Further, a significant uni-directional effect is found for the public assistance category of social welfare on property offending. Terms of use: Documents in Conclusions:The results highlight the importance of economic incentives for explaining the relationship between employment and crime for disadvantaged individuals. For these individuals the crime reducing effects from the public assistance category of social welfare equivalent to those from employment, which suggests the importance of financial gains. Further, the results suggest that stigmatizing effects from offending reduce the future employment probability.

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“…Section 3. The methodology is discussed for a more general panel data model in Mesters and Koopman (2014). The parameters are summarized in the vector ψ.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Crime, Employment and Social Welfare: An Individual-Level Study on Disadvantaged Males

2015

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“…All parameters of the model can be summarized in the vector ψ. The estimation of the model parameters is performed by the Monte Carlo maximum likelihood methods that are developed in [41].…”

Section: Analytic Strategymentioning

confidence: 99%

The Employment-Crime Association for Individuals Convicted of a Sexual Offense in their Youth

Berg

Mesters

2017

J Dev Life Course Criminology

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Objective We study the bi-directional relationship between employment and crime for individuals convicted for a sexual offense in their youth (JSO) and investigate the moderating influences of age and employment duration. Method A bi-variate dynamic binary choice model is developed to allow for interactions between employment and crime. The model takes into account statistical aspects such as state dependence and unobserved heterogeneity. Results For a sample of N = 493 JSO, who are observed in early adulthood, age 18 until 28, we find significant negative predictive effects for employment on property offending and vice versa. For other types of offenses, the model indicates that the negative correlation with employment is due to spurious effects. This holds for all ages, but the negative effect of employment on property offending becomes stronger for the older cohorts, while the effect of property offending on employment decreases in magnitude. Employment duration is found to be a mild moderating factor. Conclusion The evidence in favor of bidirectional negative relationships among offending and employment that increase in magnitude with age suggests the importance of theories that emphasize cumulative (dis)advantage, such as social control theory.

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“…For cross-section models with non-Gaussian and nonlinear features, importance sampling methods have been developed by Hajivassiliou (1990), Geweke (1991), Keane (1994), and Hajivassiliou et al (1996). The simultaneous treatment of both cross-section and time series dimensions by importance sampling methods has been treated by Liesenfeld and Richard (2010) and Mesters and Koopman (2014). Our method is closely linked with this branch of literature, but we adopt and modify these simulation-based methods in the novel context of network blockmodels combined with dynamic factor structures.…”

Section: Introductionmentioning

confidence: 99%

The Dynamic Factor Network Model with an Application to Global Credit-Risk

Bräuning

Koopman

2016

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract We introduce a dynamic network model with probabilistic link functions that depend on stochastically time-varying parameters. We adopt the widely used blockmodel framework and allow the high-dimensional vector of link probabilities to be a function of a low-dimensional set of dynamic factors. The resulting dynamic factor network model is straightforward and transparent by nature. However, parameter estimation, signal extraction of the dynamic factors, and the econometric analysis generally are intricate tasks for which simulation-based methods are needed. We provide feasible and practical solutions to these challenging tasks, based on a computationally e cient importance sampling procedure to evaluate the likelihood function. A Monte Carlo study is carried out to provide evidence of how well the methods work. In an empirical study, we use the novel framework to analyze a database of significance-flags of Granger causality tests for pair-wise credit default swap spreads of 61 di erent banks from the United States and Europe. Based on our model, we recover two groups that we characterize as "local" and "international" banks. The credit-risk spillovers take place between banks, from the same and from di erent groups, but the intensities change over time as we have witnessed during the financial crisis and the sovereign debt crisis. Terms of use: Documents in

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Generalized dynamic panel data models with random effects for cross-section and time

Cited by 13 publications

References 59 publications

Crime, Employment and Social Welfare: An Individual-Level Study on Disadvantaged Males

Crime, Employment and Social Welfare: An Individual-Level Study on Disadvantaged Males

The Employment-Crime Association for Individuals Convicted of a Sexual Offense in their Youth

The Dynamic Factor Network Model with an Application to Global Credit-Risk

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