@article{Carpenter_Dudensing_Van Sandt_2022, place={Vienna, Austria}, title={Estimating Determinants of Transportation and Warehousing Establishment Locations Using U.S. Administrative Data}, volume={9}, url={https://openjournals.wu-wien.ac.at/ojs/index.php/region/article/view/366}, DOI={10.18335/region.v9i1.366}, abstractNote={<p>Interactions between transportation and warehousing and other industry clusters are not widely explored and the determinants of logistics locational determinants is limited in the U.S. context. These gaps in the literature, along with the U.S. transportation and warehousing sector’s decentralization from urban areas and concentration in regions, highlight the importance of understanding the effects of place-based factors and inter-industry clusters on the locations and employment of transportation and warehousing industries. The analysis uses restricted-access U.S. Census Bureau data aggregated to the county level, along with secondary data sources, to estimate the locational determinants of transportation and warehousing (TW) industries based on transportation infrastructure as well as sociodemographic and institutional variables. The analysis takes a cross-sectional (non-causal) approach to focus on time-invariant location factors while testing and implementing zero-inflated count data distributions to model the data generation processes more accurately. Results indicate that subsectors are affected differently by infrastructure, sociodemographic, and institutional variables. Additionally, different factors are associated with industry presence versus size. Finally, we show that data using aggregated industries obscures locational factors’ importance for individual sub-sectors and, further, that industrial aggregation obscures TW sectors’ relationships to other clusters.</p>}, number={1}, journal={REGION}, author={Carpenter, Craig and Dudensing, Rebekka and Van Sandt, Anders}, year={2022}, month={Jan.}, pages={1–27} }