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848 records from EconBiz based on author Name
1. A pretest estimator for the two-way error component model
abstractFor a panel data linear regression model with both individual and time effects, empirical studies select the two-way random-effects (TWRE) estimator if the Hausman test based on the contrast between the two-way fixed-effects (TWFE) estimator and the TWRE estimator is not rejected. Alternatively, they select the TWFE estimator in cases where this Hausman test rejects the null hypothesis. Not all the regressors may be correlated with these individual and time effects. The one-way Hausman-Taylor model has been generalized to the two-way error component model and allow some but not all regressors to be correlated with these individual and time effects. This paper proposes a pretest estimator for this two-way error component panel data regression model based on two Hausman tests. The first Hausman test is based upon the contrast between the TWFE and the TWRE estimators. The second Hausman test is based on the contrast between the two-way Hausman and Taylor (TWHT) estimator and the TWFE estimator. The Monte Carlo results show that this pretest estimator is always second best in MSE performance compared to the efficient estimator, whether the model is random-effects, fixed-effects or Hausman and Taylor. This paper generalizes the one-way pretest estimator to the two-way error component model.
Baltagi, Badi H.; Bresson, Georges; Etienne, Jean-Michel;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
2. The multidimensional Mundlak estimator
Baltagi, Badi H.;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability:
Link 3. Testing for spatial correlation under a complete bipartite network
Baltagi, Badi H.; Liu, Long;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability:
Link 4. Consistent estimation of panel data sample selection models
abstractThe properties of classical panel data estimators including fixed effect, first-differences, random effects, and generalized method of moments-instrumental variables estimators in both static as well as dynamic panel data models are investigated under sample selection. The correlation of the unobserved errors is shown not to be sufficient for the inconsistency of these estimators. A necessary condition for this to arise is the presence of common (and/or non-independent) non-deterministic covariates in the selection and outcome equations. When both equations do not have covariates in common and independent of each other, the fixed effects, and random effects estimators in static models with exogenous covariates are consistent. Furthermore, the first-differenced generalized method of moments estimator uncorrected for sample selection as well as the instrumental variables estimator uncorrected for sample selection are both consistent for autoregressive models even with endogenous covariates. The same results hold when both equations have no covariates in common but are correlated once we account for such correlation. Under the same circumstances, the system generalized method of moments estimator adding more moments from the levels equation has moderate bias. Alternatively, when both equations have common covariates the appropriate correction method is suggested. Serial correlation of the errors being a key determinant for that choice. The finite sample properties of the proposed estimators are evaluated using a Monte Carlo study. Two empirical illustrations are provided.
Baltagi, Badi H.; Jiménez-Martín, Sergi; Labeaga, José M.; Sadoon, Majid M. al-;2023
Type: Graue Literatur; Non-commercial literature; Arbeitspapier; Working Paper;
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Link Link 5. Robust dynamic space-time panel data models using [epsilon]-contamination : an application to crop yields and climate change
Baltagi, Badi H.; Bresson, Georges; Chaturvedi, Anoop; Lacroix, Guy;2023
Type: Graue Literatur; Non-commercial literature; Arbeitspapier; Working Paper;
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Link Link 6. Spatial wage curves for formal and informal workers in Turkey
abstractThis paper estimates spatial wage curves for formal and informal workers in Turkey using individual level data from the Turkish Household Labor Force Survey (THLFS) provided by TURKSTAT for the period 2008-2014. Unlike previous studies on wage curves for formal and informal workers, we extend the analysis to allow for spatial effects. We also consider household characteristics that would affect the selection into formal employment, informal employment, and non-employment. We find that the spatial wage curve relation holds both for formal and informal workers in Turkey for a variety of specifications. In general, the wages of informal workers are more sensitive to the unemployment rates of the same region and other regions than formal workers. We find that accounting for the selection into formal and informal employment affects the magnitudes but not the significance of the spatial wage curves for the formal and informal workers with the latter always being larger in absolute value than that for formal workers.
Baltagi, Badi H.; Başkaya, Yusuf Soner;2022
Type: Graue Literatur; Non-commercial literature; Arbeitspapier; Working Paper;
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Link Link 7. Bayesian estimation of multivariate panel probits with higher-order network interdependence and an application to firms' global market participation in Guangdong
abstractThis paper proposes a Bayesian estimation framework for panel-data sets with binary dependent variables where a large number of cross-sectional units is observed over a short period of time, and cross-sectional units are interdependent in more than a single network domain. The latter provides for a substantial degree of flexibility towards modelling the decay function in network neighbourliness (e.g., by disentangling the importance of rings of neighbors) or towards allowing for several channels of interdependence whose relative importance is unknown ex ante. Besides the flexible parameterization of cross-sectional dependence, the approach allows for simultaneity of the equations. These features should make the approach interesting for applications in a host of contexts involving structural and reduced-form models of multivariate choice problems at micro-, meso-, and macroeconomic levels. The paper outlines the estimation approach, illustrates its suitability by simulation examples, and provides an application to study exporting and foreign ownership among potentially interdependent firms in the specialized and transport machinery sector in the province of Guangdong.
Baltagi, Badi H.; Egger, Peter; Kesina, Michaela;2022
Type: Graue Literatur; Non-commercial literature; Arbeitspapier; Working Paper;
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Link Link 8. Robust dynamic space-time panel data models using ε-contamination : an application to crop yields and climate change
abstractThis paper extends the Baltagi et al. (2018, 2021) static and dynamic ε-contamination papers to dynamic space-time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach departs from the standard Bayesian framework in two ways. First, we consider the ε-contamination class of prior distributions for the model parameters as well as for the individual effects. Second, both the base elicited priors and the ε-contamination priors use Zellner (1986)’s g-priors for the variance-covariance matrices. We propose a general “toolbox” for a wide range of specifications which includes the dynamic space- time panel model with random effects, with cross-correlated effects à la Chamberlain, for the Hausman-Taylor world and for dynamic panel data models with homogeneous/ heterogeneous slopes and cross-sectional dependence. Using an extensive Monte Carlo simulation study, we compare the finite sample properties of our proposed estimator to those of standard classical estimators. We illustrate our robust Bayesian estimator using the same data as in Keane and Neal (2020). We obtain short run as well as long run effects of climate change on corn producers in the United States.
Baltagi, Badi H.; Bresson, Georges; Chaturvedi, Anoop; Lacroix, Guy;2022
Type: Graue Literatur; Non-commercial literature; Arbeitspapier; Working Paper;
Availability:
Link Link 9. Bayesian estimation of multivariate panel probits with higher-order network interdependence and an application to firms' global market participation in Guangdong
Baltagi, Badi H.; Egger, Peter; Kesina, Michaela;2022
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
Research Data:
10. Cities in a pandemic : evidence from China
abstractThis paper studies the impact of urban density, city government efficiency, and medical resources on COVID-19 infection and death outcomes in China. We adopt a simultaneous spatial dynamic panel data model to account for (i) the simultaneity of infection and death outcomes, (ii) the spatial pattern of the transmission, (iii) the inter-temporal dynamics of the disease, and (iv) the unobserved city- and time-specific effects. We find that, while population density increases the level of infections, government efficiency significantly mitigates the negative impact of urban density. We also find that the availability of medical resources improves public health outcomes conditional on lagged infections. Moreover, there exists significant heterogeneity at different phases of the epidemiological cycle.
Baltagi, Badi H.; Deng, Ying; Li, Jing; Yang, Zhenlin;2022
Type: Graue Literatur; Non-commercial literature; Arbeitspapier; Working Paper;
Availability:
Link Link