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Articles 1 - 30 of 70
Full-Text Articles in Econometrics
The Mundlak Estimator In A Panel Data Model With Serially Correlated Error Component Disturbances, Badi H. Baltagi, Long Liu
The Mundlak Estimator In A Panel Data Model With Serially Correlated Error Component Disturbances, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper shows that the classic Mundlak (1978) result where the random effects estimator reduces to the fixed effects estimator when the regressors are all correlated with the individual effects, may not hold if the remainder disturbances have a general serial correlation variance-covariance matrix. This includes the popular AR(1), MA(1) and ARMA(p, q) processes for serial correlation. This is illustrated with an empirical example for the AR(1) case.
Identifying Common Trend Determinants In Panel Data, Yoonseok Lee, Peter C. Phillips, Suyong Song, Donggyu Sul
Identifying Common Trend Determinants In Panel Data, Yoonseok Lee, Peter C. Phillips, Suyong Song, Donggyu Sul
Center for Policy Research
This paper develops a novel method for identifying observable determinants of latent common trends in nonstationary panel data, which are typically removed or controlled in two-way fixed effects regressions. By examining cross sectional dispersion processes, we assess whether panel series exhibit distributional convergence toward specific observed time series, revealing them as long run determinants of the underlying latent trend. The approach also offers a new perspective on cointegration between time series and panel data, focusing on the relative variation of the panel data with respect to the cointegration error. Applying this method to U.S. state-level crime rates demonstrates that the …
Time Invariant Variables In The Mundlak And Hausman-Taylor Panel Data Models, Badi H. Baltagi, Long Liu
Time Invariant Variables In The Mundlak And Hausman-Taylor Panel Data Models, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper shows that the classic augmented Mundlak (1978) regression yields the between estimator for time-invariant variables. It is well known that the estimates of the time varying variables yield the fixed effects estimates. While the latter are consistent for this correlated random effects model, the between estimates are not. The between estimator is consistent only when the Hausman (1978) test does not reject the null based on between versus fixed effects. An alternative modified Hausman and Taylor (1981) estimator is proposed. Monte Carlo experiments are performed to compare various estimators under a correlated random effects as well as a …
Two Special Spatial Weight Matrices And Their Effects On Estimation And Testing In Spatial Regressions, Badi H. Baltagi, Long Liu
Two Special Spatial Weight Matrices And Their Effects On Estimation And Testing In Spatial Regressions, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper collects in one place some of the consequences of using two special spatial weight matrices in the spatial econometrics literature. The two weight matrices considered are the equal weight spatial matrix and the complete bipartite network. In particular, we summarize the effects of these special weight matrices on the statistical properties of commonly used spatial estimators as well as commonly used tests for spatial dependence.
The Basics Of The Mundlak And Chamberlain Projections, Badi H. Baltagi, Tom Wansbeek
The Basics Of The Mundlak And Chamberlain Projections, Badi H. Baltagi, Tom Wansbeek
Center for Policy Research
One of the best-known results in panel data econometrics, due to Mundlak (1978), is the equality of the random-effects and fixed-effects estimators when the individual effects are correlated with the means over time of the regressors. Chamberlain (1980) showed that the same result holds when the individual effects are correlated with the regressors for all moments in time separately. In this chapter, we review basic elements of the Mundlak and Chamberlain projections. We emphasize the simplicity that is often obtained when the model is transformed into the within and between-model, following Arellano (1993). Topics that we discuss include the augmented …
Estimation Of Serially Correlated Error Components Models Using Whittle’S Approximate Maximum Likelihood Method, Badi H. Baltagi, Georges Bresson, Jean-Michel Etienne
Estimation Of Serially Correlated Error Components Models Using Whittle’S Approximate Maximum Likelihood Method, Badi H. Baltagi, Georges Bresson, Jean-Michel Etienne
Center for Policy Research
This chapter studies the estimation of error components models with serial correlation of the 𝐴𝑅𝑀𝐴(𝑝, 𝑞) type using Whittle’s (Whittle, 1953) approximate maximum likelihood method. This is done for the one-way and two-way error components panel data model. Monte Carlo simulations are performed that investigate the small sample performance of this method.
Nba Player Types And Salaries: Assessing The Disparities In Pay, Nick Riccardi, Rodney J. Paul
Nba Player Types And Salaries: Assessing The Disparities In Pay, Nick Riccardi, Rodney J. Paul
Sport Management - All Scholarship
The purpose of this study was to identify player types that exist in the modern National Basketball Association (NBA), test whether player types are paid differently controlling for performance and other factors and construct successful rosters with cheaper payrolls.
We collected performance statistics and salary data for players and teams across five seasons (2018-19 to 2022-23). Cluster analysis is leveraged to group together player-seasons to identify the player types that exist in the NBA. Linear regression models are run to test for differences in pay by cluster membership while controlling for performance, age, and contractual details. Linear programming simulation models …
Family Ties: Nba Draft Position And Player Performance, Nick Riccardi, Rodney J. Paul
Family Ties: Nba Draft Position And Player Performance, Nick Riccardi, Rodney J. Paul
Sport Management - All Scholarship
This study aims to investigate the role, if any, that nepotism plays in the careers of players in the National Basketball Association (NBA). Career performance is compared between the 780 players drafted from 2007-2019 with familial relationships considered. Ordinary Least Squares and logistic regression models are specified to estimate the effect of having a relative on the success of an NBA player’s career. We find that siblings of NBA players earn more and reach minimum games played thresholds more often, while sons of NBA players earn more, but generally do not reach games played thresholds more often than similarly-drafted peers.
Estimation And Testing In A Fixed Effects Panel Data Model With Serially Correlated Error Component Disturbances, Badi H. Baltagi, Long Liu
Estimation And Testing In A Fixed Effects Panel Data Model With Serially Correlated Error Component Disturbances, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper revisits the fixed effects panel data model with AR(1) remainder disturbances and provides a bias corrected estimator for the serial correlation coefficient based on first differencing the panel regression to get rid of the fixed effects. This bias corrected estimator builds upon the estimator proposed by Han and Phillips (2010). Asymptotic properties as well as Monte Carlo results are provided that show the better performance of this new proposed bias corrected estimator. This is extended to the unbalanced panel data case and also illustrated using the empirical application in Donohue and Levitt (2001).
New York Camp Econometrics Xix Program, Center For Policy Research
New York Camp Econometrics Xix Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
Two-Stage Least Squares Estimation In A Spatial Lag Model Under A Complete Bipartite Network, Badi H. Baltagi, Long Liu
Two-Stage Least Squares Estimation In A Spatial Lag Model Under A Complete Bipartite Network, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper considers a spatial lag model with a complete bipartite network weighting matrix which is important in network theory. We show that two-stage least squares is equivalent to ordinary least squares and both estimators are inconsistent for the cross-section data case. This result has also been derived for the spatial lag model with an equal weight matrix by Kelejian and Prucha (2002). We also show that the fixed effects two-stage least squares estimator is consistent in case we have panel data and the spatial lag model includes time fixed effects. This is different from the result for an equal …
Nonstationary Heterogeneous Panels With Multiple Structural Changes, Badi H. Baltagi, Qu Feng, Wei Wang
Nonstationary Heterogeneous Panels With Multiple Structural Changes, Badi H. Baltagi, Qu Feng, Wei Wang
Center for Policy Research
Nonstationary panels have been widely used in empirical studies in macroeconomics and finance. This paper considers multiple structural changes in nonstationary heterogeneous panels with common factors. Kapetanios, Pesaran, Yamagata (2011) showed that unobserved nonstationary factors can be proxied by cross-sectional averages of observable data. This means that unobserved error factors can be treated as additional regressors, and different break points in slopes and error factor loadings can be considered as multiple breaks in linear regression models with panel data. We generalize the least squares approach by Bai and Perron (1998) to nonstationary panels and show that the break points in …
New York Camp Econometrics Xviii Program, Center For Policy Research
New York Camp Econometrics Xviii Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
Optimizing Nba Roster Construction, Nick R. Riccardi
Optimizing Nba Roster Construction, Nick R. Riccardi
Sport Management - All Scholarship
This study aims to quantify the effect that complementary player types have on team success in the National Basketball Association. Using cluster analysis, player-seasons are redefined from their traditional basketball positions to better encompass the roles that players play. For the 10 seasons of data, the best player for each of the 30 teams in the league is determined and teams are grouped based on the cluster of their best player. Ordinary Least Squares regressions are performed to test what player types fit together best. The results of this study show the importance of complementary workers to a firm’s success.
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.
Canadian Hockey Leagues Game-To-Game Performance, Nick R. Riccardi
Canadian Hockey Leagues Game-To-Game Performance, Nick R. Riccardi
Sport Management - All Scholarship
This study examines game-to-game performance of players across the three Canadian Hockey Leagues (Western Hockey League, Ontario Hockey League, and Quebec Major Junior Hockey League) for the 2017-2018 season. It tests the importance of factors such as rest, travel, weather conditions, and more. Data for this study were collected from each of the three CHL websites and from www.weatherunderground.com. The null hypotheses of different factors affecting performance were tested through regression models using Ordinary Least Squares. The dependent variables, used across different specifications, were on-ice performance variables such as points, goals, and penalty minutes on a per-game basis.
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 …