Citation

Ravulaparthy SK, Selby B, Kuppam A, Jeon K, Nippani S, Livshits V. Transp. Res. Rec. 2017; 2671: 59-70.

Copyright

(Copyright © 2017, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.3141/2671-07

PMID

unavailable

Abstract

Integrated land use and transportation models address regional issues related to congestion, mobility, and economic competitiveness. Essential to this is freight transport in the form of economic vitality, along with distribution and complex interactions between various stakeholders. Within this context, it is critical to capture and describe accurately the behavioral dynamics of these stakeholders (or firms) in the region, including modeling firm demographic events of birth, death, growth-decline, and migration patterns. This study presents a framework for modeling firm demographics with a microsimulation approach as applicable to the Phoenix and Tucson, Arizona, megaregion. The spatial firm demographic microsimulator makes use of the National Establishment Time Series database of business establishments and thereby evolves them over time and space from 2007 to 2012. A series of econometric models is estimated to simulate the firm events that consider determinants such as firm internal attributes (size, age, and growth) and external attributes. Empirical results from the simulation suggest that events of death and relocation are driven primarily by changes in firm internal attributes such as employment size or growth rates. Additionally, locational impacts such as agglomeration economies and access to transportation infrastructure trigger these events. The simulation results presented in this study are validated further with observed firm demographic trends along with microlevel zonal employment estimated with various goodness-of-fit measures. The firm demographic microsimulator model presented in this study is unique, as this is one of the first large-scale implementations for a megaregion in the United States within the context of simulating demand for commercial transportation.

Language: en