An Empirical Analysis of Determinants of Interstate Living-Cost Differentials, 2005 (original) (raw)

An Empirical Note on Determinants of Geographic Living-Cost Differentials for Counties in the State of Florida, 2003

Review of Regional Studies

This study empirically seeks to identify determinants of geographic living-cost differentials among counties in the state of Florida for the year 2003. The heteroskedasticity-corrected ordinary least squares estimates reveal that the cost of living in those counties is an increasing function of population size, per capita income or the percentage of households with an annual income in excess of $100,000, coastal location, and the square of the population density while being unaffected by the unemployment rate.

On the determinants of inter-regional living-cost differentials in the United States, 1970 and 1975

Regional Science and Urban Economics, 1983

The criticism takes issue with our recent study [Cebula and Smith (19Sl)] on three matters. We believe that the criticism is correct in charging that we fail '. .. to allow for the effects of fuel-price differentials and differences in climate among metropolitan areas.. .'. In addition, the argument for using the 'per capita property tax' variable seems most reasonable. The criticism of our right-to-work variable would also seem to have merit. It certainly can be argued that the variable Ui, defined as 'the percentage of the civilian labor force that is unionized', is appropriate to use as a measure of union power. However, Ui does not indicate precisely the same labor market characteristics that the right-to-work variable (Wi) does. Both Ui and Wi are attempting to measure 'union power'. But union power depends, among other things, upon union membership and the legality of the 'union shop'. Unions in an area where the degree of union membership is very high but where right-to-work laws exist might well have the same power as unions in an area where the degree of union membership is low but the union shop is legal. Ideally, the variables Ui and K should be included in the analysis simultaneously; this is not statistically workable, however, due to the severe degree of collinearity between these two variables. Given that we accept the arguments regarding both utility prices and property taxes but that we reject the 'union-power' variable (U,), the following regression is estimated for the year 1970: Ci= a, + a,Di + a,Pi + a3 Yi + a,Wi + U,Ai + a,Xi + p, where a0 = constant term, Ci =average annual cost of living for a four-person family living on an intermediate budget, in SMSAi, 1970,

Measuring Regional Cost of Living

Journal of Business & Economic Statistics, 2000

The American Chamber of Commerce Research Association (ACCRA) produces the only source of publicly available regional cost of living data which, this paper suggests, may provide misleading information. An evaluation of the quality of the ACCRA indexesconcludes that they contain substantial errors and biases, predominantly from the estimated prices, although error also is introduced by the choice of index formula. To evaluate the ACCRA index, this paper uses category indexes produced by BLS researchers, Kokoski, Cardiff and Moulton (KCM 1994) to produce new regional cost-of-living indexes which substantially reduce the errors and biases found in the ACCRA indexes. 'The authors thank Mary Daly and other participants at the Federal Reserve System Committee on Regional Analysis, Mary Kokoski, Brent Moulton, W olf Weber, Kim Zieschang and Mark Wynne for valuable insights. Jeff Osborne and John Benedetto provided valuable research assistance. This paper does not represent the official views o f the Federal Reserve Bank o f Dallas or the Federal Reserve System. 2Money, July 1996

Economic Wellbeing and Where We Live: Accounting for Geographical Cost-of-living Differences in the US

Urban Studies, 2006

Regional cost-of-living differences affect the quality of life that individuals and families experience in different metropolitan areas. Yet, lack of metropolitan cost-of-living indexes has left analysts without the ability to make accurate cost-of-living adjustments to measures of economic wellbeing. This paper evaluates alternative approaches to cost-of-living measurement and then applies the ACCRA cost-of-living index to various US metropolitan area datasets, including median household income, the number of people living in poverty, and family eligibility for the Free and Reduced Price School Lunch and Head Start programmes to illustrate some of the policy impacts of adjusting economic indicators of wellbeing for geographical cost-of-living differentials.

The impact of living costs on geographic mobility

The Quarterly Review of Economics and Finance

During recent years, a small number of studies have generated indices of geographically comparable living costs for states. The first of these was by W. McMahon and C. Melton [6], who generated an index for 1977. G. Fournier and D. Rasmussen [ 31 then generated an index for 1980. The most recent, and by far the most sophisticated analysis and index construction, is by W. McMahon [5]. The purpose of this paper is to use the W.McMahon [5] data to investigate the impact of geographic livingcost differentials upon geographic mobility in the United States. In this study, we focus primarily (although not exclusively) upon the elderly. The reason for this focus is simple. First, the migration decision calculus for the elderly is likely to be somewhat simpler than it is for younger segments of the population. This largely reflects the fact that the labor force participation rate among the elderly is markedly lower than for younger age groups; as a result of this fact, labor market considerations per se are likely 012 average to not be of major significance in the elderly migration decision. Consequently, by essentially being able to ignore the labor market, we are able to more

Expenditure-based Interarea Cost of Living Index

2004

The main difficulty in comparing the cost-of-living among metropolitan areas is that, at this level, prices of most goods and services are not available. Even when the prices are available, constructing aggregate prices for groups of goods and services comparable across areas, is a difficult task. In this paper we attempt to construct a costof-living index for metropolitan areas, using only data on metropolitan-level expenditures. While our method circumvents the two problems mentioned above, it requires two assumptions regarding the level of utility attained across areas, and the effect of demand elasticity on the relationship priceexpenditure.

Quality of Life, Transportation Costs, and Federal Housing Assistance: Leveling the Playing Field

Housing Policy Debate, 2016

Federal housing subsidies are allocated without regard to spatial differences in the cost of living or quality of life. In this article, we calculate housing subsidy payments for participants in the Housing Choice Voucher (HCV) program and demonstrate that these subsidies are significantly related to metropolitan quality-of-life differentials. We then estimate amenityadjusted subsidies and compare these estimates with data from the U.S. Department of Housing and Urban Development's Location Affordability Portal. Our analysis yields three insights regarding the relationship between federal housing assistance payments (HAP), metropolitan quality-of-life differentials, and transportation cost burdens. First, HCV HAP show a strong inverse correlation with household transportation expenditures, and this is particularly pronounced for low-income households. Thus, HAP do not address location affordability because those living in high-transportation cost metropolitan areas receive the lowest housing subsidies. Second, we present evidence that HAP are positively related to metropolitan qualityof-life differentials. This suggests that high-amenity metropolitan areas also tend to be the most affordable from a transportation cost perspective. Third, our proposed amenity-adjusted HAP strongly reduce the inverse relationship between HAP and transportation cost burdens. Like most transfer payments, U.S. federal housing subsidies are designed to achieve redistributive goals. Unlike other forms of income redistribution such as the Earned Income Tax Credit, federal housing subsidies explicitly target housing consumption, reducing housing cost burdens for low-income households by equalizing the share of income spent on housing to 30% of an eligible low-income household's budget. Many scholars have criticized the arbitrariness of the 30% threshold formula, which is based largely on convention rather than a sound economic rationale (see, e.g., Green & Malpezzi, 2003). Some advocate for a more expansive definition of housing affordability that considers both the housing costs in a particular location and the transportation costs of reaching destinations from that location (Center for Neighborhood Technology, 2010). This latter critique is often characterized as the location efficiency argument, based on the rationale that when the housing and transportation costs of a given residential location are considered, the total cost of living in many otherwise affordable locations is much higher when transportation costs are considered. This article reexamines the transportation cost location efficiency argument as a corollary to a more general objection: The U.S. federal housing subsidy approach ignores the influence of a wide range ARTICLE HISTORY

Determinants of Interstate Differentials in the Real Median Price of Single-Family Homes, 2005

2007

This empirical study investigates determinants of interstate real median home price differentials for the year 2005. While the literature on geographic cost-of-living differentials is well developed, the literature on geographic housing price differentials is much less so. Given the relatively large impact of housing prices on overall living costs, this research seeks to address this issue and shed light on specific factors influencing the real median price of housing across states. The OLS results imply that the real median price of a single-family home in a state is positively a function of the state's population growth rate, its per capita income, and its relative amount of shoreline on major bodies of water, and negatively a function of toxic waste releases in the state, the state's geographic area, and the presence of right-to-work laws in the state.