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Social and Behavioral Sciences Commons™
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Articles 1 - 7 of 7
Full-Text Articles in Social and Behavioral Sciences
The Identification And Estimation Of A Large Factor Model With Structural Instability, Badi H. Baltagi, Chihwa Kao, Fa Wang
The Identification And Estimation Of A Large Factor Model With Structural Instability, Badi H. Baltagi, Chihwa Kao, Fa Wang
Center for Policy Research
This paper tackles the identification and estimation of a high dimensional factor model with unknown number of latent factors and a single break in the number of factors and/or factor loadings occurring at unknown common date. First, we propose a least squares estimator of the change point based on the second moments of estimated pseudo factors and show that the estimation error of the proposed estimator is Op(1). We also show that the proposed estimator has some degree of robustness to misspecification of the number of pseudo factors. With the estimated change point plugged in, consistency of the estimated number …
The Academic Effects Of Chronic Exposure To Neighborhood Violence, Amy Ellen Schwartz, Agustina Laurito, Johanna Lacoe, Patrick Sharkey, Ingrid Gould Ellen
The Academic Effects Of Chronic Exposure To Neighborhood Violence, Amy Ellen Schwartz, Agustina Laurito, Johanna Lacoe, Patrick Sharkey, Ingrid Gould Ellen
Center for Policy Research
We estimate the causal effect of repeated exposure to violent crime on test scores in New York City. We use two distinct empirical strategies; value-added models linking student performance on standardized exams to violent crimes on a student’s residential block, and a regression discontinuity approach that identifies the acute effect of an additional crime exposure within a one-week window. Exposure to violent crime reduces academic performance. Value added models suggest the average effect is very small; approximately -0.01 standard deviations in English Language Arts (ELA) and mathematics. RD models suggest a larger effect, particularly among children previously exposed. The marginal …
Stationary Points For Parametric Stochastic Frontier Models, William C. Horrace, Ian A. Wright
Stationary Points For Parametric Stochastic Frontier Models, William C. Horrace, Ian A. Wright
Center for Policy Research
The results of Waldman (1982) on the Normal-Half Normal stochastic frontier model are generalized using the theory of the Dirac delta (Dirac, 1930), and distribution-free conditions are established to ensure a stationary point in the likelihood as the variance of the inefficiency distribution goes to zero. Stability of the stationary point and "wrong skew" results are derived or simulated for common parametric assumptions on the model. Identification is discussed.
New York Camp Econometrics Xi Program, Center For Policy Research
New York Camp Econometrics Xi Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
Asymptotic Power Of The Sphericity Test Under Weak And Strong Factors In A Fixed Effects Panel Data Model, Badi H. Baltagi, Chihwa Kao, Fa Wang
Asymptotic Power Of The Sphericity Test Under Weak And Strong Factors In A Fixed Effects Panel Data Model, Badi H. Baltagi, Chihwa Kao, Fa Wang
Center for Policy Research
This paper studies the asymptotic power for the sphericity test in a fixed effect panel data model proposed by Baltagi, Feng and Kao (2011), (JBFK). This is done under the alternative hypotheses of weak and strong factors. By weak factors, we mean that the Euclidean norm of the vector of the factor loadings is O(1). By strong factors, we mean that the Euclidean norm of the vector of factor loadings is O(pn), where n is the number of individuals in the panel. To derive the limiting distribution of JBFK under the alternative, we first derive the limiting distribution of its …
Prediction In A Generalized Spatial Panel Data Model With Serial Correlation, Badi H. Baltagi, Long Liu
Prediction In A Generalized Spatial Panel Data Model With Serial Correlation, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper considers the generalized spatial panel data model with serial correlation proposed by Lee and Yu (2012) which encompasses a lot of the spatial panel data models considered in the literature, and derives the best linear unbiased predictor (BLUP) for that model. This in turn provides valuable BLUP for several spatial panel models as special cases.
Bayesian Spatial Bivariate Panel Probit Estimation, Badi Baltagi, Peter H. Egger, Michaela Kesina
Bayesian Spatial Bivariate Panel Probit Estimation, Badi Baltagi, Peter H. Egger, Michaela Kesina
Center for Policy Research
This paper formulates and analyzes Bayesian model variants for the analysis of systems of spatial panel data with binary dependent variables. The paper focuses on cases where latent variables of cross-sectional units in an equation of the system contemporaneously depend on the values of the same and, eventually, other latent variables of other cross-sectional units. Moreover, the paper discusses cases where time-invariant effects are exogenous versus endogenous. Such models may have numerous applications in industrial economics, public economics, or international economics. The paper illustrates that the performance of Bayesian estimation methods for such models is supportive of their use with …