Date of Award

8-2016

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Agricultural Economics

First Advisor

Raymond J. Florax

Committee Chair

Raymond J. Florax

Committee Member 1

Jason Henderson

Committee Member 2

Brigitte S. Waldorf

Abstract

This thesis deals with firm formation and location choice of firms in the manufacturing (and commercial service) sector in the United States after 1990. The topics of firm formation and location choice are part of a wider field that is usually referred to as "firm demography.'' We start off with a description of the size structure of firms by looking at the evolution of the average size of manufacturing firms in counties in the USA between 1990 and 2011. We hypothesize that the size of manufacturing firms depends on the firm sizes in proximate regions as well as on the region's own average firm size in previous years. Three Markov chain models are proposed to test this hypothesis, a first-order process, a second-order process and a spatially lagged Markov chain models. By means of Likelihood Ratio tests, we show that the first-order Markov chain does not suffice to describe average firm size. We recommend the use of more elaborate space-time modeling to explain the distribution of firm sizes across counties in the US. Exploratory space-time regressions confirm the relevance of spatio-temporal processes in the evolution of the average size of manufacturing firms in the US.

The analysis of the second topic is concerned with the location choice of firms, in particular of new firms (or start-ups). We address the question whether the location choice of start-ups over their life cycle follows a theoretical framework that is known as the “nursery city hypothesis.” This hypothesis suggests that firms are initially best located in highly diversified cities, because in their process of innovation towards finding their ideal product specification they benefit substantially from externalities associated with diversity in the city's production structure. Once start-ups have determined what their ideal product is, one can expect moves or the establishment of subsidiary firms in highly specialized areas to be beneficial. These benefits accrue from localization economies. Using information about firm migration between (and the establishment of subsidiary firms in) different counties in the US, two models are proposed to see whether firms draw benefits from diverse areas in the beginning of their product-life-cycle and from specialized regions after migration (or branching out). We use statistical tests based on a theoretical spatial equilibrium model to identify whether the nursery strategy hypothesis holds. First, we use an unbalanced panel with several types of fixed effects (for time, space, sector, and/or establishment) to look at differences in sales between start-ups that moved and did not move between US counties. Hence, a firm's sales are used as a proxy for profitability. The second model uses a location preference modeling strategy to test for location choice preferences among firms that migrated versus those that did not.

The empirical results show that the nursery city hypothesis should be rejected on the basis of the sales model. In the location choice model, the nursery city hypothesis only fails to be rejected under specific conditions. Sales proved to be a weak proxy for profit maximization, as only the firm's own employment explained most of the variation in firm sales. Neither specialization nor diversity for movers or non-movers had an impact on sales. The location model confirms the nursery city pattern if we do not allow for heterogeneity across counties through fixed effects. Once county fixed effects are introduced, they strip the advantages of being in a diverse location out of the model for both movers as well as non-mover start-up firms. In sum, we conclude that firm location behavior according to the nursery city hypothesis pattern cannot be detected after accounting for all possible factors explaining heterogeneity across space, time and sectors.

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