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Articles 1 - 30 of 54
Full-Text Articles in Econometrics
New York Camp Econometrics Xvii Program, Center For Policy Research
New York Camp Econometrics Xvii Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
New York Camp Econometrics Xvi Program, Center For Policy Research
New York Camp Econometrics Xvi Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
Is Offense Worth More Than Defense In The National Basketball Association?, Justin Ehrlich, Joel Potter
Is Offense Worth More Than Defense In The National Basketball Association?, Justin Ehrlich, Joel Potter
Sport Management - All Scholarship
Motivated by the popular sports saying, “Offense sells tickets, defense wins championships,” we use Forbes revenue data to quantify whether offense really does sell more ‘tickets’ than defense in the National Basketball Association (NBA). Employing team offensive and defensive win shares as measures of offensive and defensive proficiency, we find offensively oriented teams generate the same amount of revenue as do defensively oriented teams, other things equal. Our results suggest that both profit-maximizing and win-maximizing teams should value offensively and defensively players equivalently (per unit). Thus, in an efficient free agent market, we would expect equilibrium player salaries for offensive …
New York Camp Econometrics Xv Program, Center For Policy Research
New York Camp Econometrics Xv Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
The Effect Of Attendance On Home Field Advantage In The National Football League: A Natural Experiment, Justin Ehrlich, Joel Potter, Shane Sanders
The Effect Of Attendance On Home Field Advantage In The National Football League: A Natural Experiment, Justin Ehrlich, Joel Potter, Shane Sanders
Sport Management - All Scholarship
While economists have previously noted that home field advantage is affected by crowd density, isolating this effect is difficult since crowd size is likely endogenous with team ability and game matchup. The COVID-19 pandemic has presented a unique natural experiment since local governments have introduced safety protocols that varies widely across the United States. These safety protocols have limited attendance in varying ways for live sporting events, including National Football League games. Given the differential (and exogenous) attendance restrictions, we were able to isolate three broad categories of attendance: 1) games without attendance restrictions (seasons 2016-2019), 2) games with limited …
New York Camp Econometrics Xiv Program, Center For Policy Research
New York Camp Econometrics Xiv Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
New York Camp Econometrics Xiii Program, Center For Policy Research
New York Camp Econometrics Xiii Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
Determinants Of Firm-Level Domestic Sales And Exports With Spillovers: Evidence From China, Badi H. Baltagi, Peter H. Egger, Michaela Kesina
Determinants Of Firm-Level Domestic Sales And Exports With Spillovers: Evidence From China, Badi H. Baltagi, Peter H. Egger, Michaela Kesina
Center for Policy Research
This paper studies the determinants of firm-level revenues, as a measure of the performance of firms in China's domestic and export markets. The analysis of the determinants of the aforementioned outcomes calls for a mixed linear-nonlinear econometric approach. The paper proposes specifying a system of equations, which is inspired by Basmann's work and recent theoretical work in international economics and conducts comparative static analyses regarding the role of exogenous shocks to the system to flesh out the relative importance of transmissions across outcomes.
Robust Linear Static Panel Data Models Using Ε-Contamination, Badi H. Baltagi, Georges Bresson, Anoop Chaturvedi, Guy Lacroix
Robust Linear Static Panel Data Models Using Ε-Contamination, Badi H. Baltagi, Georges Bresson, Anoop Chaturvedi, Guy Lacroix
Center for Policy Research
The paper develops a general Bayesian framework for robust linear static panel data models using ε-contamination. A two-step approach is employed to derive the conditional type-II maximum likelihood (ML-II) posterior distribution of the coefficients and individual effects. The ML-II posterior means are weighted averages of the Bayes estimator under a base prior and the data-dependent empirical Bayes estimator. Two-stage and three stage hierarchy estimators are developed and their finite sample performance is investigated through a series of Monte Carlo experiments. These include standard random effects as well as Mundlak-type, Chamberlain-type and Hausman-Taylor-type models. The simulation results underscore the relatively good …
New York Camp Econometrics Xii Program, Center For Policy Research
New York Camp Econometrics Xii Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
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 …
Testing For Spatial Lag And Spatial Error Dependence In A Fixed Effects Panel Data Model Using Double Length Artificial Regressions, Badi H. Baltagi, Long Liu
Testing For Spatial Lag And Spatial Error Dependence In A Fixed Effects Panel Data Model Using Double Length Artificial Regressions, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper revisits the joint and conditional Lagrange Multiplier tests derived by Debarsy and Ertur (2010) for a fixed effects spatial lag regression model with spatial auto-regressive error, and derives these tests using artificial Double Length Regressions (DLR). These DLR tests and their corresponding LM tests are compared using an empirical example and a Monte Carlo simulation.
Averaged Instrumental Variables Estimators, Yoonseok Lee, Yu Zhou
Averaged Instrumental Variables Estimators, Yoonseok Lee, Yu Zhou
Center for Policy Research
We develop averaged instrumental variables estimators as a way to deal with many weak instruments. We propose a weighted average of the preliminary k-class estimators, where each estimator is obtained using different subsets of the available instrumental variables. The averaged estimators are shown to be consistent and to satisfy asymptotic normality. Furthermore, its approximate mean squared error reveals that using a small number of instruments for each preliminary k-class estimator reduces the finite sample bias, while averaging prevents the variance from inflating. Monte Carlo simulations find that the averaged estimators compare favorably with alternative instrumental-variable-selection approaches when the strength levels …
New York Camp Econometrics X Program, Center For Policy Research
New York Camp Econometrics X Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
Estimation Of Heterogeneous Panels With Structural Breaks, Badi Baltagi
Estimation Of Heterogeneous Panels With Structural Breaks, Badi Baltagi
Center for Policy Research
This paper extends Pesaran's (2006) work on common correlated effects (CCE) estimators for large heterogeneous panels with a general multifactor error structure by allowing for unknown common structural breaks. Structural breaks due to new policy implementation or major technological shocks, are more likely to occur over a longer time span. Consequently, ignoring structural breaks may lead to inconsistent estimation and invalid inference. We propose a general framework that includes heterogeneous panel data models and structural break models as special cases. The least squares method proposed by Bai (1997a, 2010) is applied to estimate the common change points, and the consistency …
Adaptive Elastic Net Gmm Estimation With Many Invalid Moment Conditions: Simultaneous Model And Moment Selection, Mehmet Caner, Xu Han, Yoonseok Lee
Adaptive Elastic Net Gmm Estimation With Many Invalid Moment Conditions: Simultaneous Model And Moment Selection, Mehmet Caner, Xu Han, Yoonseok Lee
Center for Policy Research
This paper develops the adaptive elastic net GMM estimator in large dimensional models with many possibly invalid moment conditions, where both the number of structural parameters and the number of moment conditions may increase with the sample size. The basic idea is to conduct the standard GMM estimation combined with two penalty terms: the quadratic regularization and the adaptively weighted lasso shrinkage. The new estimation procedure consistently selects both the nonzero structural parameters and the valid moment conditions. At the same time, it uses information only from the valid moment conditions to estimate the selected structural parameters and thus achieves …
Estimation And Identification Of Change Points In Panel Models With Nonstationary Or Stationary Regressors And Error Term, Badi H. Baltagi, Chihwa Kao, Long Liu
Estimation And Identification Of Change Points In Panel Models With Nonstationary Or Stationary Regressors And Error Term, Badi H. Baltagi, Chihwa Kao, Long Liu
Center for Policy Research
This paper studies the estimation of change point in panel models. We extend Bai (2010) and Feng, Kao and Lazarová (2009) to the case of stationary or nonstationary regressors and error term, and whether the change point is present or not. We prove consistency and derive the asymptotic distributions of the Ordinary Least Squares (OLS) and First Difference (FD) estimators. We find that the FD estimator is robust for all cases considered.
Sources Of Productivity Spillovers: Panel Data Evidence From China, Badi H. Baltagi, Peter H. Egger, Michaela Kesina
Sources Of Productivity Spillovers: Panel Data Evidence From China, Badi H. Baltagi, Peter H. Egger, Michaela Kesina
Center for Policy Research
This paper assesses sources of productivity spillovers in China's electric and electronic manufacturing industry using a rich panel data-set of 25,360 firms observed over the period 2004-2007. This industry is characterized by its important reliance on technology. In particular, the paper focuses on the role of other firms' productivity as well as productivity shifters in affecting own firm-level total factor productivity. In addition, this paper examines the possible difference between spillovers from foreign-owned units and from units which participate at global markets through exporting in comparison to domestically-owned and non-exporting units. We find evidence of stronger spillovers from exporting firms …
Firm-Level Productivity Spillovers In China’S Chemical Industry: A Spatial Hausman-Taylor Approach, Peter H. Egger, Badi H. Baltagi, Michaela Kesina
Firm-Level Productivity Spillovers In China’S Chemical Industry: A Spatial Hausman-Taylor Approach, Peter H. Egger, Badi H. Baltagi, Michaela Kesina
Center for Policy Research
This paper assesses the role of intra-sectoral spillovers in total factor productivity across Chinese producers in the chemical industry. We use a rich panel data-set of 12,552 firms observed over the period 2004-2006 and model output by the firm as a function of skilled and unskilled labor, capital, materials, and total factor productivity, which is broadly defined. The latter is a composite of observable factors such as export market participation, foreign as well as public ownership, the extent of accumulated intangible assets, and unobservable total factor productivity. Despite the richness of our data-set, it suffers from the lack of time …
Random Effects, Fixed Effects And Hausman’S Test For The Generalized Mixed Regressive Spatial Autoregressive Panel, Badi Baltagi, Long Liu
Random Effects, Fixed Effects And Hausman’S Test For The Generalized Mixed Regressive Spatial Autoregressive Panel, Badi Baltagi, Long Liu
Center for Policy Research
This paper suggests random and fixed effects spatial two-stage least squares estimators for the generalized mixed regressive spatial autoregressive panel data model. This extends the generalized spatial panel model of Baltagi, Egger and Pfaffermayr (2013) by the inclusion of a spatial lag dependent variable. The estimation method utilizes the Generalized Moments method suggested by Kapoor, Kelejian, and Prucha (2007) for a spatial autoregressive panel data model. We derive the asymptotic distributions of these estimators and suggest a Hausman test a la Mutl and Pfaffermayr (2011) based on the difference between these estimators. Monte Carlo experiments are performed to investigate the …
Test Of Hypotheses In A Time Trend Panel Data Model With Serially Correlated Error Component Disturbances, Chihwa Kao, Badi H. Baltagi, Long Liu
Test Of Hypotheses In A Time Trend Panel Data Model With Serially Correlated Error Component Disturbances, Chihwa Kao, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper studies test of hypotheses for the slope parameter in a linear time trend panel data model with serially correlated error component disturbances. We propose a test statistic that uses a bias corrected estimator of the serial correlation parameter. The proposed test statistic which is based on the corresponding fixed effects feasible generalized least squares (FE-FGLS) estimator of the slope parameter has the standard normal limiting distribution which is valid whether the remainder error is I(0) or I(1). This performs well in Monte Carlo experiments and is recommended.
Endogenous Network Production Functions With Selectivity, William C. Horrace, Xiaodong Liu, Eleonora Patacchini
Endogenous Network Production Functions With Selectivity, William C. Horrace, Xiaodong Liu, Eleonora Patacchini
Center for Policy Research
We consider a production function model that transforms worker inputs into outputs through peer effect networks. The distinguishing features of this production model are that the network is formal and observable through worker scheduling, and selection into the network is done by a manager. We discuss identification and suggest a variety of estimation techniques. In particular, we tackle endogeneity issues arising from selection into groups and exposure to common group factors by employing a polychotomous Heckman-type selection correction. We illustrate our method using data from the Syracuse University Men’s Basketball team, where at any point in time the coach selects …
New York Camp Econometrics Ix Program, Center For Policy Research
New York Camp Econometrics Ix Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
New York Camp Econometrics Viii Program, Center For Policy Research
New York Camp Econometrics Viii Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.