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...

We test a New Economic Geography (NEG) model for U.S. counties, employing a new strategy that allows us to bring the full NEG model to the data, and to assess selected elements of this model separately. We find no empirical support for the full NEG model. Regional wages in the U.S. do not...

This paper estimates annual data on educational attainment for 3,076 mainland U.S. counties 1991-2005. Being estimated without resorting to ancillary information, this data is suited particular well for panel regression analyses. Several plausibility checks indicate that the data is fairly...

This paper investigates the effects of inward FDI on per-capita income and growth of the US states since the mid-1970s. Using a Markov chain approach, it shows that both quantitative and qualitative characteristics of FDI affect per-capita income and growth. Employment-intensive FDI,...

We test a New Economic Geography (NEG) model for U.S. counties, employing a new strategy that allows us to bring the full NEG model to the data, and to assess selected elements of this model separately. We find no empirical support for the full NEG model. Regional wages in the U.S. do not...

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...

This paper substantiates the debate following Richard Florida’s suggestion to measure regional human capital by creative occupations rather than education. Consistent with Florida’s notion of creativity, it suggests a microfoundation that relates creativity to workers’ cognitive and...