[논문]미국 대도시 지역 청년 1-2인가구의 주거 특성 및 주거비 부담 영향 요인

최병숙; 이현정

doi:10.6107/jkha.2014.25.1.051

미국 대도시 지역 청년 1-2인가구의 주거 특성 및 주거비 부담 영향 요인
Housing Characteristics and Determinants of Housing Cost Burden of Young Single- or Two-person Households in the U.S. Metropolitan Areas 원문보기

한국주거학회 논문집 = Journal of the Korean Housing Association, v.25 no.1, 2014년, pp.51 - 61

Abstract ▼ AI-Helper

The purpose of this study was to explore housing characteristics of young single- or two-person households in the U.S. metropolitan urban areas and determinants of their housing cost burden. Total 764 single-person households, 744 two-person households and 424 households with three or more persons were selected from the 2011 American Housing Survey public-use microdata for the study based on specific sampling criteria. The major findings are as follows: (1) In comparisons with larger households, single- or two-person households were characterized to be headed by younger householders, to have less income, and to have a greater proportion of households living in central cities of metropolitan areas, renting housing units, living in smaller size units or multifamily structures; (3) housing cost of single- or two-person households were significantly less than a larger households while housing costs per unit square footage (SQFT) of single- or two-person households was significantly greater; (4) regardless of the household size, there are many household headed by young college graduates paying too much of their income for housing, and single-person households were found to have the greatest housing cost burden; and (5) a linear combination of low-income status, monthly housing costs per unit SQFT, annual household income, and unit SQFT per person was found to be most efficient to predict single- or two-person households with housing cost burden.

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문제 정의

This was a part of study series to explore housing and housing cost burden situation of young professionals in Korea and the United States. The purpose of this study was to explore housing characteristics of young single- or two-person households in the U.S. metropolitan urban areas and determinants of their housing cost burden using the 2011 American Housing Survey (AHS) public-use microdata. Especially, this study focused on single- or two-person households headed by college graduates and who have recently moved for job-related reasons.
This study utilized public-use microdata of the AHS, a national survey. Some of the greatest advantages to use national survey data are a vast sample size and representativeness of the sample examined and guaranteed, which individual researchers are extremely difficult to achieve with limited resource and manpower.
This study was conducted to explore housing characteristics of young single- or two-person households headed by young college graduates in the U.S. metropolitan urban areas and determinants of their housing cost burden. This study used the 2011 AHS public-use microdata as secondary data.
This was a part of study series to explore housing and housing cost burden situation of young professionals in Korea and the United States. The purpose of this study was to explore housing characteristics of young single- or two-person households in the U.

제안 방법

As stated earlier in this manuscript, this study follows methodology of a previous study by Lee (2012c) which was a similar study utilizing a public-use microdata of the 2009 AHS. After review of other studies on housing issues of young households and housing cost burdens, however, sampling criteria and variables were modified in this study.
In the first stage, household and housing characteristics of single- or two-person households were compared with households with three or more household members using a series of chi-square tests of independence and one-way analyses of variance (ANOVA). In the second stage of the data analysis, determinants of housing cost burden of single- or two-person households were explored utilizing a series of discriminant analyses. For the entire data analyses, IBM SPSS Statistics 21.
The independent variables used in the discriminant analyses were household and housing characteristics used in the first stage of data analysis excluding housing cost burden: Age, gender, race and Spanish origin of householder, annual household income, low-income status, location in metropolitan area, tenure type, structure type, unit size (unit SQFT, number of bedrooms), unit density (persons/bedroom, unit SQFT/person), housing adequacy, self-ratings of the unit and neighborhood as a place to live, and housing cost (monthly housing cost, monthly housing costs/unit SQFT). In addition, household size (1 person, 2 persons) were added to the independent variables.
Dependent variable is housing cost burden (burdened, not burdened). The model is based on discriminant analysis with all one- to two-person households.
The second stage of the data analysis was to explore determinants of housing cost burden of single- or twoperson households. A series of discriminant analyses were utilized to examine influences of linear combination of household and housing characteristics on housing cost burden of single- or two-person households.
This study follows major sampling criteria and data analysis procedure of the previous study by Lee (2012c) and sampling criteria and variables were modified to for a better diagnose of young households’ housing cost burdens.

대상 데이터

metropolitan urban areas and determinants of their housing cost burden. This study used the 2011 AHS public-use microdata as secondary data. Major findings are summarized as follows:

데이터처리

Data analysis of this study consists of two major stages. In the first stage, household and housing characteristics of single- or two-person households were compared with households with three or more household members using a series of chi-square tests of independence and one-way analyses of variance (ANOVA). In the second stage of the data analysis, determinants of housing cost burden of single- or two-person households were explored utilizing a series of discriminant analyses.

이론/모형

Actual housing cost burden (burdened, not burdened) and predicted discriminant membership of housing cost burden resulted from the new discriminant model were compared using cross-tabulations. As results, it was found that the new discriminant model with only four most influential variables were abel to predict 84.
For variable entry in discriminant models, a stepwise method using Wilk’s lambda was adopted.

성능/효과

(6) a linear combination of low-income status, monthly housing costs per unit SQFT, annual household income, and unit SQFT per person was found to be most efficient to predict single- or two-person households with housing cost burden.
Among the independent variable included in the final stepwise models of discriminant analyses by household size, low-income status, monthly housing costs per unit SQFT, annual household income, and unit SQFT per person were found to have the strongest influences on prediction of households with housing cost burden regardless of the household size. It was examined to see if a singular discriminant model using these four most influential variables has the accuracy level to predict households with housing cost burden regardless of the household size similar to previous stepwise discriminant models with more variables as presented in Table 10.
Actual housing cost burden (burdened, not burdened) and predicted discriminant membership of housing cost burden resulted from the new discriminant model were compared using cross-tabulations. As results, it was found that the new discriminant model with only four most influential variables were abel to predict 84.1 percent of single-person households with housing cost burden, and 77.8 percent of two-person households with housing cost burden correctly [Table 12].
As results, significant differences were found in tenure type, home structure types, housing unit size (number of bedrooms, unit SQFT), unit density (unit SQFT per person, persons per bedroom), housing adequacy, housing cost (monthly housing costs, monthly housing costs per unit SQFT) and whether or not the household had housing cost burden [Table 6, 7 & 8].
For the ANCOVA, household annual income was a dependent variable, household size (1 person, 2 persons, 3 or more persons) was an independent variable, and the number of household members who had wage and salary income was a covariate. As results, significant income differences were found by household size even after controlling the effect of the number of household members with wage and salary income (F=38.883, p=.000).
5% of one- to two-person households with housing cost burden correctly. Final stepwise models of discriminant analysis by household size were found to predict 84.l percent of single-person households with housing cost burden and 79.9 percent of two-person households with housing cost burden correctly.
There are a couple of implications to make based on the study findings. First, although single- or two-person households were found to live in smaller units than households with three or more persons, they were found to pay a greater housing costs per unit SQFT. Also, the housing costs per unit SQFT was one of the crucial predictors of households with housing cost burden.
Household characteristics of single- or two-person households were compared with those of households with three or more persons. Households characteristics compared in the study was demographic characteristics of householders including age, gender, race, and whether or not from Spanish origin; and household characteristics including annual household income, low-income household status and location in MSA. A low-income household in this study refers to a household whose annual income was below 80 percent of the area median income (AMI).
Housing characteristics of single- or two-person households were compared with those of households with three or more persons. Housing characteristics compared were tenure type, home structure type, unit size (number of bedrooms⁵⁾, unit square footage (SQFT)), unit density (unit SQFT/person, persons/bedroom), housing adequacy, self-rating of the unit or neighborhood as a place to live (1 being worst, to 10 being best), housing costs (monthly housing costs, monthly housing costs/unit SQFT), housing cost burden (annual housing costs/ annual household income, whether or not the household had housing cost burden). In addition to the housing variables used in the previous study by Lee (2012c), more diverse variables including unit size, unit density, and housing costs per unit SQFT were added for a better examination of housing situation and housing cost burden of the young households.
To see that the group centriod of households with housing cost burden was greater than that of households without housing cost burden, households headed by Asian, with less income, being low-income households, living in units with more bedrooms and a smaller SQFT per person, and paying more housing costs per unit SQFT tended to have a greater chance to have housing cost burden. The final discriminant model was found to be able to predict 81.5% of one- to two-person households with housing cost burden correctly. Final stepwise models of discriminant analysis by household size were found to predict 84.
7 percent⁶⁾ of the variance in housing cost burden of one- to two-person households. To see that the group centriod of households with housing cost burden was greater than that of households without housing cost burden, households headed by Asian, with less income, being low-income households, living in units with more bedrooms and a smaller SQFT per person, and paying more housing costs per unit SQFT tended to have a greater chance to have housing cost burden. The final discriminant model was found to be able to predict 81.
Refer to [Table 11] for a new discriminant model with four most influential variables using all 1- to 2-person households. To see the squared canonical correlation, the new model was found to explain 48.1 percent of the variance in housing cost burden of one- to two-person households.

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