Estimation of housing needs amid population growth and change

Myers, Dowell; Pitkin, John; Park, Julie

doi:10.1080/10511482.2002.9521455

Cited by 25 publications

(17 citation statements)

References 12 publications

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“…A number of studies have analyzed links between demographic characteristics and housing (Masnick, 2002;Myers, Pitkin, & Park, 2002;Myers & Ryu, 2008;Nelson, 2006). Several have focused specifically on the housing needs of disabled residents (Imrie, 2003(Imrie, , 2004Milner & Madigan, 2004).…”

Section: Implications For the Housing Industry And Housing Policy In mentioning

confidence: 99%

Aging and Disability: Implications for the Housing Industry and Housing Policy in the United States

Smith¹,

Rayer²,

Smith³

2008

Journal of the American Planning Association

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Section: Implications For the Housing Industry And Housing Policy In mentioning

confidence: 99%

Aging and Disability: Implications for the Housing Industry and Housing Policy in the United States

Smith¹,

Rayer²,

Smith³

2008

Journal of the American Planning Association

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“…Even if one uses the changing headship rates based on regression or another trend extrapolation method to correctly project numbers of households, it is still possible that the headship rates may result in biased projections of household consumption demands, which largely depend on household size (Myers et al 2002) because the headship-rate method excludes household size. To test this hypothesis, we conducted another assessment in which the changing headship rates are assumed to produce the same numbers of households as those observed in the 2000 census in each of the 50 states and Washington, DC (for details, see Online Resource 1, Sections C3–C4).…”

Section: Empirical Assessmentsmentioning

confidence: 99%

“…There is a growing demand for projections of the distribution of household types, sizes, and living arrangements for socioeconomic planning, environment, development, business and market research, and policy and scholarly analysis (Keilman 2003; Liu et al 2003; Lutz and Prinz 1994; Mackellar et al 1995; Moffitt 2000; Myers et al 2002). For example, past research has established that household status and living arrangements are two of the major determinants of the amount and type of long-term care for the elderly (e.g., FIFARS 2004; Freedman 1996; Soldo et al 1990).…”

Section: Introductionmentioning

confidence: 99%

Household and Living Arrangement Projections at the Subnational Level: An Extended Cohort-Component Approach

et al. 2012

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This article presents the core methodological ideas, empirical assessments, and applications of an extended cohort-component approach (known as the “ProFamy model”) to simultaneously project household composition, living arrangements, and population sizes at the subnational level in the United States. Comparisons of projections from 1990 to 2000 using this approach with census counts in 2000 for each of the 50 states and Washington, DC show that 68.0 %, 17.0 %, 11.2 %, and 3.8 % of the absolute percentage errors are <3.0 %, 3.0 % to 4.99 %, 5.0 % to 9.99 %, and ≥10.0 %, respectively. Another analysis compares average forecast errors between the extended cohort-component approach and the still widely used classic headship-rate method, by projecting number-of-bedrooms–specific housing demands from 1990 to 2000 and then comparing those projections with census counts in 2000 for each of the 50 states and Washington, DC. The results demonstrate that, compared with the extended cohort-component approach, the headship-rate method produces substantially more serious forecast errors because it cannot project households by size while the extended cohort-component approach projects detailed household sizes. We also present illustrative household and living arrangement projections for the five decades from 2000 to 2050, with medium-, small-, and large-family scenarios for each of the 50 states; Washington, DC; six counties of southern California, and the Minneapolis–St. Paul metropolitan area. Among many interesting numerical outcomes of household and living arrangement projections with medium, low, and high bounds, the aging of American households over the next few decades across all states/areas is particularly striking. Finally, the limitations of the present study and potential future lines of research are discussed.

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“…We also performed household projections from 1990 to 2000 for 25 randomly selected counties and 25 randomly selected cities (each state has one 9 The numerical projections reported in this paper were calculated with the ProFamy computer software program; this program incorporates the ECC projection method and contains a demographic database of the U.S. age-specific schedules of demographic rates (see footnote 7) to assist users in making projections. A free trial version of the ProFamy software for household forecasting can be downloaded from the Website http://www.profamy.com/ 10 The marriage/union history data from the following four national surveys are pooled to estimate the race-sex-age-specific model standard schedules: (a) National Survey of Family Households (NSFH) conducted in 1987-1988, 1992-1994, and 2002; (b) National Survey of Family Growth (NSFG) conducted in 1983, and 2002(c) Current Population Surveys (CPS) conducted in 1980, 1990(d) Survey of Income and Program Participation (SIPP) conducted in 1996 (see Zeng, Morgan et al 2010 for discussions on justifications of pooling data from the four surveys). randomly selected county or city), based on the observed/projected household distributions of their parental states in 1990/2000 and the constant-share ratio method.…”

Section: An Empirical Assessmentmentioning

confidence: 99%

“…Moffitt (2000) argues that better projections of demographic and household trends could provide valuable intelligence to guide planning and should be a major policy goal. Extant research has well established that demands for energy use (e.g., gas and electricity), automobiles, housing, water, durable goods and other home-related products and services are largely determined by changes in households (e.g., Foncel & Ivaldi 1999;Myers et al, 2002;Davis 2003;Keilman, 2003;Liu et al 2003;Prskawetz et al 2004;Wang et al 2005; Dalton et al, 2008). Past research has also established that household and living arrangements are the major determinant of the amount and type of long-term care for the elderly (e.g., Doty, 1986;Chappell 1991;Morris et al 1998;Soldo et al 1990;FIFARS 2004).…”

Section: Introductionmentioning

confidence: 99%

Household and population projections at sub-national levels: an extended cohort-component approach

Zeng¹,

Land²,

Wang³

et al. 2010

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This paper describes the core methodological ideas, the required input data, and estimation issues of the extended cohort-component approach to simultaneously project household composition and population distributions at sub-national levels. We assess the projection accuracy of this approach by calculating projections from 1990 to 2000 and comparing projected with the census-observed counts in 2000 for the 50 states and the District of Columbia and for sets of randomly selected 25 counties and 25 cities which are more or less evenly distributed across the United States. The comparisons show that most absolute percent errors of the main indices of household and population projections and the corresponding census observations are small -less than three percent -and almost all errors are less than ten percent. We then report illustrative household projections from 2000 to 2050 for the 50 states and the District of Columbia, and household/housing projections for the small town of Chapel Hill, North Carolina up to 2015 in order to demonstrate the practical capabilities of the new approach. Among many interesting numerical outcomes, the aging of American households over the next few decades across all states and the aging of the housing market in Chapel Hill are particularly striking trends in the projections. Key words: household projections, cohort-component approach, sub-national household projections, household projections at the state level, sub-state area household projections, aging of households, aging of housing markets.

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Estimation of housing needs amid population growth and change

Cited by 25 publications

References 12 publications

Aging and Disability: Implications for the Housing Industry and Housing Policy in the United States

Aging and Disability: Implications for the Housing Industry and Housing Policy in the United States

Household and Living Arrangement Projections at the Subnational Level: An Extended Cohort-Component Approach

Household and population projections at sub-national levels: an extended cohort-component approach

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