Econometric Analysis of the Determinants of Household Geographical Migration in the US (original) (raw)

For several decades, the United States has witnessed a great rate of household mobility. Analysis of migration patterns by Brookings show that during the post-WWII period, the years 2008/2009 saw the lowest rate of mobility in the United States (Frey 2009). Data from Annual Social and Economic Supplement shows that 35.9 million Americans changed residence between the year 2012 and 2013 (Ihrke 2014). Taking into account the mobility rate of renters and homeowners, surveys demonstrate that renters are the most mobile compared to the homeowners. Similarly, findings from empirical studies shows all else fixed, home owners are 41.73 percent more likely to move compared to home-renters for the period 1993 to 2001 (Boehm and Schlottmann 2006). Geographical mobility is an important factor in economics. In theory, migration occurs from areas with lower benefits to areas with higher benefits. Since mobility is costly, an individual will consider moving when the present value of benefits exceeds the present value of costs, both monetary and physic. In a recent survey by the U.S. Census Bureau, when asked about their reasons of moving, about 45 percent gave housing related reasons, 30 percent gave family related reasons, and 20 percent gave job related reasons (Ihrke 2014). With the current developments in communication and transportation technology, geographical mobility is expected to take several turns and shifts. Individuals and households will give diverse reasons on their decisions to change residence. This is because when transportation market is efficient and reliable there is increased access to opportunities. Technological advancement has a big influence on the everyday life of individuals. At the aggregate level, technological advancement in transportation industry reduces the cost of travelling to seek jobs, reduces congestion in residential areas and increases the geographical access in terms of opportunities available to movers (Green 2002; Cowan et al. 2012). This calls for a review of current literature to ascertain whether the determinants of mobility change over time or have remained constant. Using data from 2000, 2005 and 2010, this study examines whether the determinants of mobility have evolved over time. In particular, the focus is on the role played by location specific amenities and fiscal amenities, based on the current residence of the population. Specifically, separate regressions will be estimated for each year of data, and tests will be conducted to see if coefficients across models are statistically significantly different. This paper will also estimate regressions separately for those who move across states and those who move within states. By comparing the estimated coefficients from these models, it is possible to determine if the determinants of in-state moves are similar to the determinants of out-of-state moves. Lastly, the study looks to explore the rate of mobility of women who are household heads. Mobility decisions of women has been tough to ascertain because of their role in the society as they are classified as secondary earners in the household. Women are traditionally tied movers and move because their husband's place of employment is changing. Therefore, by comparing female household heads to their male counterparts, we can see if the determinants of mobility are the same. If they are different, then that means that there remains gender differences concerning migration decisions. Comparing the results from the three years (2000, 2005 and 2010), the findings show that most determinants of household mobility vary across the three time-periods, except Gender, education level, annual income and property crime rate. In the estimation for the difference in the determinants of interstate and intrastate mobility decisions, number of bedrooms, age of household head and property tax rate are statistically the same for intrastate and interstate migration. In the regressions for male and female household heads, the results show that the coefficients for the variables home ownership, Hispanic, Black, annual income and average temperatures are statistically the same. The coefficients for the variable property tax rate had unexpected sign all through the regression results. The remaining part of this paper is planned as follows: Section 2 is the discussion of the existing literature for geographic mobility. In Section 3, the empirical model used for this study is outlined and analyzed. Data and results are outlined and discussed in Section 4 and lastly, Section 5 is the conclusion of the paper.