Abstract
Chapter 15 presented households and housing demand projections in rural and urban areas of Hebei, a province with 72 million residents and a median level of socioeconomic development in China, using the most recent census and other data and the ProFamy extended cohort-component model. The results showed that, due to changes in household and population structure, demand for both owned housing and rental housing for elders aged 65+ will grow dramatically, but housing demand will decline for young people aged less than 35. One-person households will have the largest growth in demand for 1–2 room owned-housing; one-couple households will have the largest growth in demand for 3–4 room owned-housing. Demand for larger housing units for three-generation households will go down. Based on our analysis, we discussed some relevant policy considerations such as “dual-apartment” housing for elderly parents neighboring directly with their children, which may result in a win-win outcome for both generations in facing the serious challenges of population and household aging.
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Notes
- 1.
The micro-data for the 2010 China census, which are needed for the household housing demand projections, are currently not available for scholars and the public to use; thus, we are not able to conduct household housing demand projections for China as a whole at present time.
- 2.
Our estimated under-reporting rate of 7.6 % was an average for ages 0–9. However, the underreporting rate of new births is much higher than other childhood ages, especially ages 6–9, when most of the under-reported children were registered for school. Our estimate of the TFR as 1.7 in 2010 in Hebei province implies an under-reporting rate of new births of 24.1 %.
- 3.
We did not include income in our estimates of homeownership rates and home-rental rates for three reasons. First, based on many others’ and our own research, we do not trust the accuracy of self-reported income in the Chinese census data. Second, even assuming we might obtain reasonably accurate estimates of income categories, it would be extremely hard to forecast future changes in income for various rural and urban household types/sizes and age groups. The accuracy of the forecasts relies heavily on the validity of assumptions regarding future time paths of the covariates and parameters included in the forecasting model. Erroneous assumptions about very uncertain future years’ covariates and parameters included in the model can quickly lead to forecasts that are far off the mark (e.g., Lee and Tuljapurkar 2001). Third, we have included in our projection the rural/urban dimension, which captures the income level to a considerable extent, and meets our needs in the present study.
- 4.
We investigate housing demand trends of private households in this chapter; housing demand for institutionalized persons is out of the scope of this chapter and therefore excluded from the present study.
- 5.
Unlike the U.S. census, which collects data on the number of bedrooms in housing units, the Chinese census collects data on the number of rooms in the housing units without distinguishing between bedrooms, living room, dining room, or storage rooms.
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Zeng, Y., Land, K.C., Gu, D., Wang, Z. (2014). Household Housing Demand Projections for Hebei Province of China. In: Household and Living Arrangement Projections. The Springer Series on Demographic Methods and Population Analysis, vol 36. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8906-9_15
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