Population Aging, Mobility, and Real Estate Price: Evidence from Cities in China
Abstract
:1. Introduction
2. Literature Review
3. Empirical Model and Data Description
3.1. Empirical Model
3.2. Hypotheses
3.3. Data Description
4. Empirical Findings
5. Stationary Test
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Variable | Variable Name | Proxy Variable | Data Source | |
---|---|---|---|---|
Dependent variable | Housing price | Ln HP | The logarithm of housing price | China statistical yearbook for regional economy |
Independent variables | Age structure | CDR | The children dependency ratio | Provincial Statistical Yearbook |
EDR | The elderly dependency ratio | |||
Population mobility | Urbanization | The percentage of non-agricultural population | ||
Inter-regional Migration | The percentage of inter-regional migrants | The sixth population census in 2010 and the provincial population sampling survey in 2015 | ||
Control variables | Population scale | Ln POP | The logarithm of the number of permanent population | |
Income | Ln INC | The logarithm of per capita disposable income | China statistical yearbook for regional economy | |
Housing supply | Ln HS | The logarithm of floor space of buildings completed in construction | ||
Economic development | Ln PGDP | The logarithm of per capita gross domestic product | ||
City category | DUMMYF | First tier cities (Yes = 1, No = 0) | China’s city tier system | |
DUMMYS | Second tier cities (Yes = 1, No = 0) | |||
DUMMYT | Third tier cities (Yes = 1, No = 0) |
Variable | Observations | Mean | Maximum | Minimum | St. Deviation |
---|---|---|---|---|---|
Housing Price | 588 | 4976 | 33,426 | 1167 | 3493 |
Children dependency ratio | 588 | 0.203 | 0.390 | 0.090 | 0.058 |
Elderly dependency ratio | 588 | 0.175 | 0.393 | 0.033 | 0.051 |
Inter-regional migration | 588 | 0.175 | 0.871 | 0.012 | 0.123 |
Urbanization | 588 | 0.450 | 1.000 | 0.090 | 0.191 |
Population scale | 588 | 434.5 | 3017 | 19.51 | 335.8 |
Income | 588 | 22,670 | 52,962 | 10,317 | 7910 |
Per capita GDP | 588 | 41,810 | 280,117 | 3816 | 29,451 |
Housing supply | 588 | 828.8 | 13,575 | 2.566 | 1295 |
Estimation 1 | Estimation 2 | Estimation 3 | Estimation 4 | |
---|---|---|---|---|
CDR | −0.453 * (−1.689) | −0.091 (−0.711) | −0.062 (−0.852) | −0.042 (−0.936) |
EDR | 1.824 *** (6.025) | 0.323 ** (1.871) | 0.323 ** (1.910) | 0.308 ** (1.824) |
Migration | 2.282 *** (13.717) | 1.077 *** (6.628) | 1.149 *** (6.922) | 0.748 *** (4.416) |
Urbanization | 0.657 *** (6.035) | 0.461 *** (4.687) | 0.471 *** (4.843) | 0.408 *** (4.214) |
Ln INC | 0.826 *** (13.098) | 0.804 *** (8.285) | ||
Ln POP | 0.071 *** (4.132) | 0.029 (1.420) | ||
Ln HS | 0.016 ** (2.316) | 0.016 ** (2.248) | ||
Ln PGDP | 0.092 *** (2.624) | 0.092 ** (2.448) | ||
DUMMYF | 1.016 *** (8.227) | 0.673 *** (5.378) | ||
DUMMYS | 0.349 *** (7.019) | 0.171 *** (3.166) | ||
DUMMYT | 0.128 *** (4.548) | 0.022 (0.711) | ||
YEAR | 0.374 *** (12.074) | 0.041 (0.895) | ||
Constant | 7.304 *** (90.709) | 0.145 (0.295) | 7.622 *** (10.2.28) | 0.605 (0.783) |
Num | 588 | 588 | 588 | 588 |
R2 | 0.538 | 0.697 | 0.684 | 0.733 |
Adjust R2 | 0.534 | 0.695 | 0.681 | 0.732 |
F stat. of Chow tests | 9.320 | 6.305 | 7.718 | 6.793 |
Estimation 5 | Estimation 6 | Estimation 7 | Estimation 8 | |
---|---|---|---|---|
CDR | −0.121 (−0.527) | −0.086 (−0.412) | −0.139 (−0.602) | −0.093 (−0.442) |
EDR | 0.805 *** (2.858) | 0.586 ** (2.216) | 0.632 ** (2.247) | 0.414 *** (3.607) |
Migration | 0.919 *** (5.498) | 0.264 *** (2.503) | 0.855 *** (4.185) | 0.456 *** (2.818) |
Urbanization | 0.437 *** (4.712) | 0.283 *** (3.051) | 0.449 *** (4.778) | 0.301 ** (3.241) |
PPL*EDR | −0.695 ** (−2.835) | −0.802 ** (−2.522) | ||
PPL*MIG | −0.402 ** (−2.612) | −0.184 ** (−2.119) | ||
PPL | Controlled | Controlled | Controlled | Controlled |
Control variables | No | Yes | No | Yes |
Constant | 7.589 *** (105.62) | 2.019 *** (2.659) | 7.622 *** (105.37) | 2.145 ** (2.816) |
Num | 588 | 588 | 588 | 588 |
R2 | 0.679 | 0.743 | 0.677 | 0.741 |
Adjust R2 | 0.676 | 0.739 | 0.673 | 0.737 |
ST 1 | ST 2 | ST 3 | ST 4 | |
---|---|---|---|---|
CDR | −0.530 ** (−1.971) | −0.015 (−0.702) | −0.498 * (−1.880) | −0.017 (−0.808) |
EDR | 1.833 *** (6.088) | 0.286 ** (1.905) | 1.890 *** (6.336) | 0.288 ** (1.792) |
Migration | 2.224 *** (13.331) | 0.751 *** (4.380) | 2.078 *** (12.214) | 0.749 *** (4.411) |
Urbanization | 0.612 *** (5.587) | 0.414 *** (4.268) | 0.653 *** (6.092) | 0.415 *** (4.293) |
Control variables | No | Yes | No | Yes |
Num | 588 | 588 | 588 | 588 |
R2 | 0.543 | 0.726 | 0.552 | 0.745 |
Adjust R2 | 0.539 | 0.724 | 0.548 | 0.741 |
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Wang, X.; Hui, E.C.-M.; Sun, J. Population Aging, Mobility, and Real Estate Price: Evidence from Cities in China. Sustainability 2018, 10, 3140. https://doi.org/10.3390/su10093140
Wang X, Hui EC-M, Sun J. Population Aging, Mobility, and Real Estate Price: Evidence from Cities in China. Sustainability. 2018; 10(9):3140. https://doi.org/10.3390/su10093140
Chicago/Turabian StyleWang, Xinrui, Eddie Chi-Man Hui, and Jiuxia Sun. 2018. "Population Aging, Mobility, and Real Estate Price: Evidence from Cities in China" Sustainability 10, no. 9: 3140. https://doi.org/10.3390/su10093140