Panel data analysis of U.S. coal productivity

Abstract

We analyze labor productivity in coal mining in the United States using indices of productivity change associated with the concepts of panel data modeling. This approach is valuable when there is extensive heterogeneity in production units, as with coal mines. We¯nd substantial returns to scale for coal mining in all geographical regions, and¯nd that smooth technical progress is exhibited by estimates of the¯xed e®ects for coal mining. We carry out a variety of diagnostic analyses of our basic model and primary modeling assumptions, using recently proposed methods for addressing`errors-in-variables' and`weak instrument bias' problems, as well a new method for studying errors-in-variables in nonlinear contexts.

A look upstream: Market restructuring, risk, procurement contracts and efficiency

“…Ellerman and Montero, 1998;Ellerman, Joskow, Schmalensee, Montero, and Bailey, 2000). On the other hand, Stoker, Berndt, Ellerman, and Schennach (2005) emphasize the large productivity advantage of Western coal mines over the remaining ones, as well as the differential trends in productivity growth among the two groups. To make sure that our empirical analysis is not biased by these two aspects, we re-estimate the evolution of labor productivity for treated mines relative to control ones excluding Western mines from our sample.…”

Internationalization and Performance of Vietnamese Manufacturing Firms: Does Organizational Slack Matter?

“…Then, the repeated manufacturing firms were filtered and appended to form a panel data for a six-year period from 2007 to 2012. Stoker et al (2005) described that panel data contains the cross-sectional indicators of the same individual or entity, such as country, region, firm, consumer, etc., which are observed repeatedly over time. The panel data may be balanced-each repeated individual or entity has the same periods of time-or unbalanced, each repeated individual or entity has different periods of time.…”

“…Fixed effect model assumes that there are the possible correlations between time-invariant differences across entities and the explanatory variables. According to Greene (2003) and Stoker et al (2005), fixed effect model (FEM) can control and separate the effects of these differences from the predictors to help us estimate the net effects on the explanatory variables on dependent variable. However, FEM also reveals the limitation as it cannot measure time-invariant factors, such as gender, race, etc., as it absorbs the dummies variables on the intercept.…”

Comparative analysis of regional labor cost variations in China’s construction industry: Panel data modeling and analysis

“…Panel data is an econometric approach for analyzing dynamic relationship due to its capability of coping with missing data and individual heterogeneity, and can automatically diminish the negative impacts of collinearity within various data sets that time series modeling and other regression techniques have no capabilities to avoid these aspects [24] . It has been widely applied in econometric analysis at firm [25] , regional [26] , or sectoral [27] levels within different time periods. Panel data consists of not only time series data but also cross section data, the introduction of cross section data increases the degrees of freedom and the reliability of statistics tests.…”