Measuring Regional Cost of Living

Koo, Jahyeong; Phillips, Keith R.; Sigalla, Fiona

doi:10.1080/07350015.2000.10524853

Cited by 49 publications

(31 citation statements)

References 8 publications

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“…The only regional cost-of- Unfortunately, the sample is voluntary, and the number of MSAs covered each quarter varies. Moreover, numerous studies have found the ACCRA index to be unreliable (Dumond et al, 1999,) and subject to significant bias from various sources, including sampling error, sampling bias, and aggregation bias (Koo, 2000). It also does not include a number of key metropolitan areas (Fosu, 1999).…”

Section: Data Source and Methodologymentioning

confidence: 99%

Housing costs and the geography of family migration outcomes

Withers

Clark

2006

Population Space and Place

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This paper takes a geographic approach towards assessing the 'returns' to family migration by addressing explicitly the impacts of differences in the cost of housing between the place of origin and place of destination for family migrants. While numerous studies have examined differences in labor-force participation and wages subsequent to migration, particularly on the part of wives, few studies have considered the local geographic context of these events. This study examines the "adjusted" outcomes from migration for husbands, wives, and families in the United States in the context of local housing costs. Our findings challenge the assumption of simple economic gains and instead indicate that who gains and who loses from family migration is quite complex.The geography of family migration is critical in determining gains and losses and is interrelated with moves in and out of the labor market on the part of wives. Our research indicates that wives who leave the labor market after a move are very likely to have moved to a more affordable housing market. Conversely, wives enter the labor market when the move is to a more expensive housing market. For this group, wives earnings go a long way towards minimizing the impact on overall family earnings. This paper provides an important contribution to understanding family migration by positioning the analysis of migration outcomes within the context of labor markets and local housing market costs.

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Section: Data Source and Methodologymentioning

confidence: 99%

Housing costs and the geography of family migration outcomes

Withers

Clark

2006

Population Space and Place

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“…12. A further weakness of ACCRA data, identified by Koo et al (2000), is that, because participation in the survey varies each quarter, the base (100) value in each period is just the average of the cities included, not a fixed concept. Therefore, ACCRA data cannot be used for time-series measures of COL. 13.…”

Section: Resultsmentioning

confidence: 99%

“…Koo et al (2000) identify several potential biases in market basket measures such as ACCRA. First, because baseline indices count all cities equally rather than by population weighting them, the overall baseline (i.e.…”

Section: Summary and Evaluation Of Approachesmentioning

confidence: 99%

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

et al. 2006

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Summary. 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.

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“…In contrast, the SCOL reflects how much more expenditure an individual needs in region b, to maintain his same level of utility as in region a given the migration of the consumer from a to b. By keeping the utility constant, an estimation of the SCOL facilitates the comparison of the differences in the cost of living across cities (Koo et al, 2000). In summary, the SCOL provides a different perspective than the RPI, for interregional comparisons.…”

Section: Introductionmentioning

confidence: 98%

A spatial cost of living index for Colombia using a microeconomic approach and censored data

Atuesta

Paredes

2012

Applied Economics Letters

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SUMMARYThis paper describes a methodology to calculate a spatial cost of living index using Colombian data for 2006 that takes into consideration the microeconomic behavior of households. Using the Almost Ideal Demand System and recovering the expenditure functions for the 23 main Colombian cities, the index proposed is compared to the traditional methodologies used to calculate the regional basket of goods in the country and to an alternative methodology proposed by Romero (2005). This comparison suggests that when the substitution effects are not considered, and the same basket of goods is evaluated in every city, the index is biased, and this bias increases when the difference between cities increases. For reducing the bias, we use a microeconomic approach that keeps the households' level of utility constant and allows substitution among different baskets of goods. According to our calculations, Bogota is still the most expensive city in the country followed by Armenia, Cali, Bucaramanga and Ibague.

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Measuring Regional Cost of Living

Cited by 49 publications

References 8 publications

Housing costs and the geography of family migration outcomes

Housing costs and the geography of family migration outcomes

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

A spatial cost of living index for Colombia using a microeconomic approach and censored data

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