Social and Behavioral Sciences Commons^™

Hospital Treatment Rates And Spill-Over Effects: Does Ownership Matter?, Badi H. Baltagi, Yin -Fang Yen

Center for Policy Research

This paper studies the effect of hospital ownership on treatment rates allowing for spatial correlation among hospitals. Competition among hospitals and knowledge spillovers generate significant externalities which we try to capture using the spatial Durbin model. Using a panel of 2342 hospitals in the 48 continental states observed over the period 2005 to 2008, we find significant spatial correlation of medical service treatment rates among hospitals. We also get mixed results on the effect of hospital ownership on treatment rates that depends upon the market structure where the hospital is located and which varies by treatment type.

A Robust Hausman-Taylor Estimator, Badi Baltagi, Georges Bresson

Center for Policy Research

This paper suggests a robust Hausman and Taylor (1981) estimator, here-after HT that deals with the possible presence of outliers. This entails two modifications of the classical HT estimator. The first modification uses the Bramati and Croux (2007) robust Within MS estimator instead of the Within estimator in the first stage of the HT estimator. The second modification uses the robust Wagenvoort and Waldmann (2002) two stage generalized MS estimator instead of the 2SLS estimator in the second step of the HT estimator. Monte Carlo simulations show that, in the presence of vertical outliers or bad leverage points, the robust …

Essays On Testing Hypotheses When Non-Stationarity Exists In Panel Data Models, Sang Gon Na

Economics - Dissertations

This dissertation consists of two essays on testing hypotheses in panel data models when non-stationarity exists in the model. This is done under the high-dimensional framework where both n (cross-section dimension) and T (time series dimension) are large. In the first essay, I discuss the limiting distribution of the t-statistic; using different panel data estimators and propose using the t-statistic based on Feasible GLS estimator. In the second essay, I develop the bootstrap F-statistic for cross-sectional independence in a panel data model with factor structure.

The first essay considers the problem of hypotheses testing in a simple panel data regression …

The Value Of A Statistical Life: Evidence From Panel Data, Thomas J. Kniesner, W. Kip Viscusi, Christopher Woock

Center for Policy Research

Our research addresses fundamental long-standing concerns in the compensating wage differentials literature and its public policy implications: the econometric properties of estimates of the value of statistical life (VSL) and the wide range of such estimates from about $0 to almost $30 million. Here we address most of the prominent econometric issues by applying panel data, a new and more accurate fatality risk measure, and systematic application of panel data estimators. Controlling for measurement error, endogeneity, latent individual heterogeneity that may be correlated with the regressors, state dependence, and sample composition yields an estimated value of a statistical life of …

Panel Data Inference Under Spatial Dependence, Badi H. Baltagi, Alain Pirotte

Center for Policy Research

This paper focuses on inference based on the usual panel data estimators of a one-way error component regression model when the true specification is a spatial error component model. Among the estimators considered, are pooled OLS, random and fixed effects, maximum likelihood under normality, etc. The spatial effects capture the cross-section dependence, and the usual panel data estimators ignore this dependence. Two popular forms of spatial autocorrelation are considered, namely, spatial auto-regressive random effects (SAR-RE) and spatial moving average random effects (SMA-RE). We show that when the spatial coefficients are large, test of hypothesis based on the usual panel data …

A Generalized Spatial Panel Data Model With Random Effects, Badi H. Baltagi, Peter Egger, Michael Pfaffermayr

Center for Policy Research

This paper proposes a generalized panel data model with random effects and first-order spatially auto correlated residuals that encompasses two previously suggested specifications. The first one is described in Anselin's (1988) book and the second one by Kapoor, Kelejian, and Prucha (2007). Our encompassing specification allows us to test for these models as restricted specifications. In particular, we derive three LM and LR tests that restrict out generalized model to obtain (i) the Anselin model, (ii) the Kapoor, Kelejian, and Prucha model, and (iii) the simple random effects model that ignores the spatial correlation in the residuals. For two of …

Fixed-Effect Estimation Of Highly-Mobile Production Technologies, William C. Horrace, Kurt E. Schnier

Center for Policy Research

We consider fixed-effect estimation of a production function where inputs and outputs vary over time, space, and cross-sectional unit. Variability in the spatial dimension allows for time-varying individual effects, without parametric assumptions on the effects. Asymptotics along the spatial dimension provide consistency and normality of the marginal products. A finite-sample example is provided: a production function for bottom-trawler fishing vessels in the flatfish fisheries of the Bering Sea. We find significant spatial variability of output (catch) which we exploit in estimation of a harvesting function.

Testing For Heteroskedasticity And Spatial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Seuck Heun Song, Jae Hyeok Kwon

Center for Policy Research

A panel data regression model with heteroskedastic as well as spatially correlated disturbance is considered, and a joint LM test for homoskedasticity and no spatial correlation is derived. In addition, a conditional LM test for no spatial correlation given heteroskedasticity, as well as a conditional LM test for homoskedasticity given spatial correlation, are also derived. These LM tests are compared with marginal LM tests that ignore heteroskedasticity in testing for spatial correlation, or spatial correlation in testing for homoskedasticity. Monte Carlo results show that these LM tests as well as their LR counterparts perform well even for small N and …

Testing For Random Effects And Spatial Lag Dependence In Panel Data Models, Badi H. Baltagi, Long Liu

Center for Policy Research

This paper derives a joint Lagrande Multiplier (LM) test which simultaneously tests for the absence of spatial lag dependence and random individual effects in a panel data regression model. It turns out that this LM statistic is the sum of two standard LM statistics. The first one tests for the absence of spatial lag dependence ignoring the random individual effects, and the second one tests for the absence of random individual effects ignoring the spatial lag dependence. This paper also derives two conditional LM tests. The first one tests for the absence of random individual effects without ignoring the possible …

New Evidence On The Dynamic Wage Curve For Western Germany: 1980-2004, Badi H. Baltagi, Uwe Blien, Katja Wolf

Center for Policy Research

Blanchflower and Oswald (1994) reported that they have found an 'empirical law of economics'--the Wage Curve. Our paper reconsiders the western German Wage Curve using disaggregated regional data and is based on almost one million employees drawn from the Federal Employment Services of Germany over the period 1980-2004. We find that the wage equation is highly autoregressive but far from unit root. The unemployment elasticity is significant but relatively small: only between -0.02 and -0.04. We also check the sensitivity of this elasticity for different population groups (young versus old, men versus women, less educated versus highly educated, German native …

Testing For Heteroskedasticity And Serial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Byoung Cheol Jung, Seuck Heun Song

Center for Policy Research

This paper considers a panel data regression model with heteroskedastic as well as serially correlated disturbances, and derives a joint LM test for homoskedasticity and no first order serial correlation. The restricted model is the standard random individual error component model. It also derives a conditional LM test for homoskedasticity given serial correlation, as well as a conditional LM test for no first order serial correlation given heteroskedasticity, all in the context of a random effects panel data model. Monte Carlo results show that these tests, along with their likelihood ratio alternatives, have good size and power under various forms …

A Monte Carlo Study For Pure And Pretest Estimators Of A Panel Data Model With Spatially Auto Correlated Disturbances, Badi H. Baltagi, Peter Egger, Michael Pfaffermayr

Center for Policy Research

This paper examines the consequences of model misspecification using a panel data model with spatially auto correlated disturbances. The performance of several maximum likelihood estimators assuming different specifications for this model are compared using Monte Carlo experiments. These include (i) MLE of a random effects model that ignore the spatial correlation; (ii) MLE described in Anselin (1988) which assumes that the individual effects are not spatially auto correlated; (iii) MLE described in Kapoor et al. (2006) which assumes that both the individual effects and the remainder error are governed by the same spatial autocorrelation; (iv) MLE described in Baltagi et …

Copula-Based Tests For Cross-Sectional Independence In Panel Models, Chihwa Kao, Giovanni Urga

Center for Policy Research

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Pinning Down The Value Of Statistical Life, Thomas J. Kniesner, W. Kip Viscusi, Christopher Woock, James P. Ziliak

Center for Policy Research

Our research addresses fundamental long-standing concerns in the compensating wage differentials literature and its public policy implications: the econometric properties of estimates of the value of statistical life (VSL) and the wide range of such estimates from about $0.5 million to about $21 million. We address most of the prominent econometric issues by applying panel data, a new and more accurate fatality risk measure, and systematic selection of panel estimator in our research. Controlling for measurement error, endogeneity, individual heterogeneity, and state dependence yields both a reasonable average level and narrow range for the estimated value of a statistical life …

Rational Alcohol Addiction: Evidence From The Russian Longitudinal Monitoring Survey, Badi H. Baltagi, Ingo Geishecker

Center for Policy Research

Alcohol consumption in Russia is legendary and has been reported to be the third leading cause of death in the former Soviet Union after heart disease and cancer. Are Russian alcohol consumers rational addicts? This paper uses eight rounds of a nationally representative Russian survey spanning the period 1994-2003 to estimate a rational addiction (RA) model for alcohol consumption. This is done in a panel data setting as well as on a wave by wave basis. The profile of the Russian drinker finds a huge difference between males and females and the model is estimated by gender. We do not …

Panel Unit Root Tests And Spatial Dependence, Badi H. Baltagi, Georges Bresson, Alain Pirotte

Center for Policy Research

This paper studies the performance of panel unit root tests when spatial effects are present that account for cross-section correlation. Monte Carlo simulations show that there can be considerable size distortions in panel unit root tests when the true specification exhibits spatial error correlation. These tests are applied to a panel data set on net real income from the 1000 largest French communes observed over the period 1985-1998.

Taxes, Deadweight Loss And Intertemporal Female Labor Supply: Evidence From Panel Data, Anil Kumar

Center for Policy Research

Very few existing studies have estimated female labor supply elasticities using a U.S. panel data set, although cross-sectional studies abound. Also, most existing studies have done so in a static framework. I make an attempt to fill the gap in this literature by estimating a lifecycle-consistent specification with taxes, in a limited dependent variable framework, on a panel of married females from the PSID. Both parametric random effects and semi parametric fixed effects methods are applied. I find evidence of larger substitution effects than found in female labor supply literature with taxes, suggesting considerable distortionary effects from income taxation. The …

Entrepreneurship And Economic Growth: The Proof Is In The Productivity, Douglas Holtz-Eakin, Chihwa Kao

Center for Policy Research

Popular and policy discussions have focused extensively on "entrepreneurship." While entrepreneurship is often viewed from the perspective of the individual's benefits--an increase in standard of living, flexibility in hours, and so forth--much of the policy interest derives from the presumption that entrepreneurs provide economy-wide benefits in the form of new products, lower prices, innovations, and increased productivity. How large are these effects? Using a rich panel of state-level data, we quantify the relationship between productivity growth--by state and by industry--and entrepreneurship. Specifically, we use state-of-the-art econometric techniques for panel data to determine whether variations in the birth rate and death …

Microdata Panel Data And Public Policy: National And Cross-National Perspectives, Richard V. Burkhauser

Center for Policy Research

This paper focuses on the movement of data-based social policy analysis from a single-country cross-section frame to a multi-country panel frame. It provides examples of policy insights this movement to panel data has permitted, both with respect to economic well-being and behavior--using data from the Panel Study of Income Dynamics (PSID), the British Household Panel Study (BHPS), the German Socio-Economic Panel (GSOEP), and the Health and Retirement Study (HRS). It also suggests fruitful areas for future panel data-based policy research.

Testing The Stability Of A Production Function With Urbanization As A Shift Factor: An Application Of Non-Stationary Panel Data Techniques, Suzanne Mccoskey, Chihwa Kao

Center for Policy Research

Urban economists have long sought to explain the relationship between urbanization levels and output. In this paper we revisit this question and test the long-run stability of a production function with urbanization using non-stationary panel data techniques. Our results show that a long-run relationship between urbanization output per worker and capital per worker cannot be rejected for either our sample of 30 developing countries or our sample of 22 developed countries. In addition, we estimate the long-run average effects on GDPW of urbanization and capital. These results offer newer insights and potential for dynamic urban models than the simple cross-section …