No abstract

Markov chain theory, which has frequently been applied to analyze income convergence, imposes restrictive assumptions on the data-generating process. In most empirical studies, it is taken for granted that per capita income follows a stationary first-order Markov process. To examine the reliability of estimated Markov transition matrices, the authors propose Pearson X2 and likelihood ratio tests of the Markov property, spatial independence, and homogeneity over time and space. As an illustration, it is shown that per capita income in the forty-eight contiguous U.S. states did clearly not follow a common stationary first-order Markov process from 1929 to 2000.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Night lights could be a valuable proxy of economic activity at the subnational level when GDP data are lacking or of poor quality. Supplementing Henderson et al.'s (2012) analysis at the national level, we assess the stability of the elasticity of GDP with regard to night lights across regions in Brazil, India, the United States, and Western Europe. The relationship between regional GDP and night lights proves to be unstable, not only where regional GDP data may be unreliable but also where such data are of high quality. This suggests that night lights tend to be a poor proxy of regional economic activity. Terms of use: Documents in EconStor may

This paper extends the methodological toolbox of measures of regional concentration of industries and industrial specialization of regions. It first defines disproportionality measures of concentration and specialization, and proposes a taxonomy of these measures. This taxonomy is based on three characteristic features of any disproportionality measure. It helps researchers define the measure that fits their research purpose and data best. The paper then generalizes this taxonomy to cover disproportionality measures of economic localization thatevaluate specialization and concentration simultaneously, and spatial disproportionality measures that deal with the checkerboard problem and the modifiable areal unit problem.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Spatial Effects of Foreign Direct Investment in US StatesEckhardt Bode, Peter Nunnenkamp, Andreas WaldkirchAbstract: This paper estimates the aggregate productivity effects of Marshallian externalities generated by foreign direct investments (FDI) in the US. In contrast to earlier work, this paper puts special emphasis on controlling for Marshallian externalities and other intra-and inter-regional spillovers generated by domestic firms. The productivity effects of these externalities may, if not accounted for appropriately, be falsely attributed to FDI. This paper also deals with the potential endogeneity of FDI and the presence of spatial lags by employing a system generalized method of moments (GMM) estimator. We use a regional production function framework that models Marshallian externalities and other intraand inter-regional spillovers explicitly as determinants of total factor productivity, and tests several empirical specifications of this model, using data for US states from 1977-2003. The results indicate that FDI does, in fact, generate positive externalities, while those from domestic firms are negative.