Modeling and analysis of the link between accessibility and employment growth

Various accessibility measures, differing in terms of their definitions and formulations, have been proposed over the past 40years and been applied to a wide range of problems. This paper extends previous research by developing a new functional form to represent accessibility using real transportation data from the New York/New Jersey metropolitan area. The accessibility function is used as an input to develop an employment function in terms of several socioeconomic variables. Two main hypotheses are tested: (1) that improved accessibility, with all other factors remaining the same, will positively affect individuals' tendency to enter the labor market; and (2) that this effect will vary across employment types and industries. Both functions are estimated simultaneously with county-level data for the year 2000 using two-stage and three-stage least squares analysis (2SLS and 3SLS). Because the results of 3SLS were statistically more robust than 2SLS while the parameter estimates remained similar in magnitude and sign, the proposed model mainly used the 3SLS estimation results. Main results show that the changes in accessibility have a noticeable effect on employment in the studied area. Depending on skill requirements, offered wage rates, household's income, and children of specific age groups, participation in the employment sectors considered were proved to be responsive to accessibility improvements.