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Full-Text Articles in Social and Behavioral Sciences
Fixed-Effect Estimation Of Highly-Mobile Production Technologies, William C. Horrace, Kurt E. Schnier
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 Random Effects And Spatial Lag Dependence In Panel Data Models, Badi H. Baltagi, Long Liu
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
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
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 …
Testing For Heteroskedasticity And Spatial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Seuck Heun Song, Jae Hyeok Kwon
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 …