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Erschienen in: The Annals of Regional Science 2/2016

02.02.2016 | Original Paper

The Texas economic model, miracle or mirage? A spatial hedonic analysis

verfasst von: Hongbo Wang

Erschienen in: The Annals of Regional Science | Ausgabe 2/2016

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Abstract

As a state without a personal income tax that has experienced strong employment and population growth in the past, Texas was held up as the economic policy model for Kansas and Oklahoma to follow in recently cutting their personal income tax rates. Using microlevel data, this paper examines whether Texas has benefitted from its mix of public policies by examining the geographic patterns of estimated quality-adjusted wages and housing costs across the USA. The overall finding is the absence of significantly positive capitalized effects from the policies of Texas. The only significant capitalized policy effect found was lower quality of life in Texas nonmetropolitan areas relative to those in Oklahoma.

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Fußnoten
1
For discussion of other recent studies of state fiscal policies and growth, see Rickman (2013).
 
2
Oklahoma also reduced its top marginal personal income tax rate from 6.75 % in 2000 to 5.5 % in 2010, though this remained in stark contrast to the absence of a state income tax rate in Texas.
 
3
According to 2003 definition by Office of Management and Budget, metropolitan areas include all counties containing one or more urbanized areas: high-density urban areas containing 50,000 people or more; metropolitan areas also include outlying counties that are economically tied to the central counties, as measured by the share of workers commuting on a daily basis to the central counties. Nonmetropolitan counties are outside the boundaries of metropolitan areas and have no cities with 50,000 residents or more. Source: http://​www.​whitehouse.​gov/​omb/​inforeg_​statpolicy#ms.
 
4
IPUMS-USA Web site is https://​usa.​ipums.​org/​usa/​ (Ruggles et al. 2010).
 
5
Under the Fair Labor Standards Act the federal minimum wage rate was raised from $5.15 to $7.25 an hour for all covered nonexempt workers effective July 24, 2009 (http://​www.​dol.​gov/​whd/​minwage/​coverage.​htm.). So, $2768 in 2000 is obtained by $5.15 times 20 h times 26 weeks and $3770 is obtained by $7.25 times 20 h times 26 weeks.
 
6
According to the description of IPUMA-USA database, counties are unavailable in public-use microdata from 1950 onwards.
 
7
Although the boundaries and PUMA codes generally are the same for the 2000 Census and the 2006–2011 ACS samples, population displacement following Hurricane Katrina caused one notable exception in Louisiana. Three PUMA’s (01801, 01802, and 01905) are combined into code 77777 for the 2006-onward ACS and for all cases in the 2005–2007 ACS 3-year file.
 
8
Source: Economic Research Service of the United States Department of Agriculture website: http://​www.​ers.​usda.​gov/​. Some CONSPUMAs contain both metropolitan and nonmetropolitan counties. In these cases, the population-weighted ERS rural–urban continuum code is used to classify the area. When metropolitan counties are removed in constructing the nonmetropolitan sample, some mixed areas previously classified as metropolitan areas become nonmetropolitan areas.
 
9
In the sensitivity analysis, I also calculated characteristic-adjusted wages without industry and occupation controls.
 
10
In sensitivity analysis, I also use only rents to measure housing costs because housing prices can reflect both consumption and investment motives (Winters 2009). See footnote 14 for discussion of the results.
 
11
According to USDA, the codes from one to nine denote whether a county is: (1) in a metropolitan area with population of 1 million or more; (2) in a metropolitan area of 250,000 to 1 million people; (3) in a metropolitan area with population fewer than 250,000; (4) a nonmetropolitan county with urban population of 20,000 or more, and adjacent to a metropolitan area; (5) a nonmetropolitan county with urban population of 20,000 or more, but not adjacent to a metropolitan area; (6) a nonmetropolitan county with urban population of 2500–19,999, adjacent to a metropolitan area; (7) a nonmetropolitan county with urban population of 2500–19,999, not adjacent to a metropolitan area; (8) a nonmetropolitan county completely rural or \(<\)2500 urban population, adjacent to metropolitan area; or (9) a nonmetropolitan county completely rural or \(<\)2500 urban population, not adjacent to metropolitan area.
 
12
Because there are too few observations in category [8, 9], I merge the categories [8, 9] and [7, 8) to create the category that the rank is greater than or equal to 7.
 
13
Gyourko et al. (2008) ranks Texas as having the 30th most restrictive local and state regulatory environment for housing supply, while Oklahoma is ranked 38th, suggesting it is less restrictive than Texas. Kansas is ranked as the least restrictive state.
 
14
Examination of statistical differences in the coefficients was performed using LINCOM for the wage and housing cost regressions together in STATA (www.​stata.​com/​manuals13/​rlincom.​pd).
 
15
Using only housing rents to calculate housing costs, because housing prices may reflect both consumption and investment motives (Winters 2009), does not much affect the results. For all areas, there are no significant differences in amenity attractiveness or productivity between Texas and either Kansas or Oklahoma. For nonmetropolitan areas, Texas is both significantly more household unattractive and more productive than those in Oklahoma in 2000, where both differences become insignificant in 2010; the changes from 2000 to 2010 are statistically insignificant. No significant differences exist between the nonmetropolitan areas of Texas and Kansas.
 
16
The wages residuals are included in the wage equations; whereas the housing cost residuals are included in the housing cost equations. In the results not shown, the wage residuals variable is significant in both growth and 2010 levels equations; whereas, the housing cost residuals variable is only significant in the 2010 levels equation.
 
17
Following the Eqs. (4) to (5), the three variables are aggregated into the CONSPUMA level. In results not shown, the variable born-in-state is insignificant in the year 2000 regressions, and negative and significant in the year 2010 regressions. The variable, movedin, is negative and significant in all regressions, except for the 2010 housing cost regression where it is insignificant. Home ownership is positive and significant in the wage regressions and insignificant in the housing cost regressions.
 
18
According to IPUMS, the movedin variable was scaled from 1 to 8; whereas in 2000 5 % sample 1 represents moved in at survey year or the year prior the survey year; 2 represent individual moved in 2–5 years ago; 5 represents 6–10 years ago; 6 represents 11–20 years ago, 7 represents 21–30 years ago; 8 represents moved in current reside unit over 31 years ago; while in 2010 5-year ACS survey, 1 represents 12 months or less; 2 represents 13–23 months ago; 3 represents 2–4 years ago; 4 represents 5–9 years ago; 5 represents 10–19 years ago; 6 represents 20–29 years ago; 7 represents more than 30 years ago. In results not shown, while excluding the movedin variable, the born-in-state is statistically and negatively related to both wages and housing costs in both 2000 and 2010. As before (see footnote 17), home ownership is statistically significant and positive in the wage regressions but insignificant in the housing cost regressions.
 
19
Because the observations of Maine, New Hampshire, Vermont, Wyoming, New Mexico and North Dakoda are too few, I combined Maine, New Hampshire and Vermont for one group while combineing Wyoming, New Mexico and North Dakota for another group for the fixed effects model.
 
20
In results not shown, the coefficients of these three states’ dummy variables are mostly all statistically significant. The exceptions are that New York is not statistically significant in the wage growth equation and Illinois is not statistically significant in the housing cost growth equation.
 
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Metadaten
Titel
The Texas economic model, miracle or mirage? A spatial hedonic analysis
verfasst von
Hongbo Wang
Publikationsdatum
02.02.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
The Annals of Regional Science / Ausgabe 2/2016
Print ISSN: 0570-1864
Elektronische ISSN: 1432-0592
DOI
https://doi.org/10.1007/s00168-016-0744-y

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