Study on the Effect of Job Accessibility and Residential Location on Housing Occupancy Rate: A Case Study of Xiamen, China
Abstract
:1. Introduction
2. Literature Review
2.1. Job–Housing Distance and Population Distribution in the City
2.2. Industry-and-City Integration and Population Aggregation
2.3. Job–Housing Balance and Residential Location Choice
3. Theoretical Hypotheses
3.1. Concentric Zone Model and Occupancy Rate
3.2. Sector Model and Occupancy Rate
3.3. Multiple Nuclei Model and Occupancy Rate
4. Empirical Framework and Data
4.1. Econometric Model
4.2. Variables
4.3. Overview of the Study Area and Data
5. Results
5.1. Results of the Baseline Model
5.2. Instrumental Evidence
5.3. Robustness Test
5.4. Heterogeneity Analysis
6. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variables | Descriptions | Min | Max | Mean | Std |
---|---|---|---|---|---|
Y | Occupancy rate: the number of households divided by the number of housing units | 0.000 | 1.000 | 0.743 | 0.281 |
A | Job accessibility via ELMO | −2.029 | 2.153 | 0.000 | 1.000 |
M | 1/distance to nearest metro station | −1.200 | 7.757 | 0.000 | 1.000 |
R | 1/distance from residential block to trunk road | −0.257 | 15.456 | 0.000 | 1.000 |
D | Population density within 3 km | −2.648 | 2.177 | 0.000 | 1.000 |
P | log(housing price) | 9.123 | 11.366 | 10.235 | 0.334 |
DX | 1/distance to Xiamen North Railway Station | 0.097 | 1.751 | 0.164 | 0.137 |
YX | Year of house delivery before 2000 | 0.000 | 1.000 | 0.453 | 0.451 |
Year of house delivery 2001–2010 | 0.000 | 1.000 | 0.165 | 0.372 | |
Year of house delivery 2011–2012 | 0.000 | 1.000 | 0.111 | 0.315 | |
Year of house delivery 2013–2014 | 0.000 | 1.000 | 0.111 | 0.315 | |
Year of house delivery After 2015 | 0.000 | 1.000 | 0.160 | 0.367 | |
Edu | Mean of education years in residential block | 2.536 | 24.285 | 9.462 | 1.342 |
Labor | Proportion of labor force in residential block | 0.250 | 0.983 | 0.645 | 0.084 |
IR | Industrial land ratio | 0.000 | 0.656 | 0.151 | 0.205 |
RR | Residential land ratio | 0.063 | 0.818 | 0.287 | 0.134 |
Variables | Model 1 | Model 2 | ||
---|---|---|---|---|
Coefficient | Standard Errors | Coefficient | Standard Errors | |
A | 0.069 *** | 0.024 | 0.021 | 0.017 |
M | −0.048 *** | 0.015 | −0.035 ** | 0.015 |
M × A | 0.008 | 0.048 | ||
R | −0.022 | 0.015 | −0.009 | 0.014 |
R × A | 0.084 * | 0.054 | ||
D | 0.004 | 0.016 | 0.024 * | 0.015 |
D × A | −0.099 *** | 0.018 | ||
P | −0.146 *** | 0.051 | −0.132 ** | 0.052 |
DX | −273.008 ** | 110.565 | −186.025 * | 113.971 |
YX | ||||
2001–2010 | −0.007 | 0.039 | −0.042 | 0.040 |
2011–2012 | 0.000 | 0.054 | −0.058 | 0.055 |
2013–2014 | 0.073 * | 0.053 | 0.096 * | 0.055 |
After 2015 | −0.132 ** | 0.045 | −0.185 *** | 0.046 |
Edu | 0.004 | 0.011 | 0.015 | 0.011 |
Labor | 0.420 ** | 0.179 | 0.120 | 0.175 |
Constant | 1.992 *** | 0.548 | 1.940 *** | 0.558 |
R2 | 0.203 | 0.128 | ||
N | 367 |
Variables | Model 3 | Model 4 | ||
---|---|---|---|---|
Coefficient | Standard Errors | Coefficient | Standard Errors | |
IR (industrial land ratio) | −1.549 *** | 0.220 | ||
RR (residential land ratio) | −2.235 *** | 0.262 | ||
A | 0.168 *** | 0.058 | ||
M | −0.159 *** | 0.031 | −0.043 *** | 0.0161 |
M × A | −1.173 *** | 0.075 | 0.151 * | 0.085 |
R | 0.046 | 0.030 | −0.026 * | 0.015 |
R × A | −0.493 *** | 0.107 | 0.130 ** | 0.058 |
D | 0.011 | 0.036 | 0.011 | 0.016 |
D × A | 0.332 *** | 0.035 | −0.138 *** | 0.025 |
P | 0.143 | 0.107 | −0.214 *** | 0.063 |
DX | 0.413 * | 0.220 | −0.357 *** | 0.119 |
YX | ||||
2001–2010 | −0.311 *** | 0.078 | 0.136** | 0.065 |
2011–2012 | −0.334 *** | 0.108 | 0.057 | 0.070 |
2013–2014 | 0.022 | 0.106 | 0.103 | 0.071 |
After 2015 | −0.267 ** | 0.089 | −0.077 | 0.062 |
Edu | 0.069 *** | 0.021 | −0.002 | 0.011 |
Labor | −1.235 *** | 0.356 | 0.493 *** | 0.188 |
Constant | −0.389 | 1.170 | 2.693 *** | 0.679 |
Chi-sq(3) | −0.793 | |||
Kleibergen-Paap rk LM | 54.574 | |||
Chi-sq(2) p-value | 0.0000 | |||
Cragg-Donald Wald F | 40.163 | |||
Kleibergen-Paap rk Wald F | 42.328 | |||
Stock-Yogo 10% maximal IV size | 19.93 | |||
Hansen J | 0.873 | |||
Chi-sq(1) p-value | 0.350 |
Decay Function (Search Radius) | Model 5 | Model 6 | Model 7 | Model 8 | Model 9 | Model 10 | |
---|---|---|---|---|---|---|---|
Variables | Gaussian (5 km) | Gaussian (7 km) | Gaussian (11 km) | No Decay (9 km) | Kernel Density (9 km) | Gravity (9 km) | |
A | 0.006 | 0.030 * | 0.046 * | −0.032 | 0.071 *** | −0.057 *** | |
M | −0.036 ** | −0.044 *** | −0.049 *** | −0.043 *** | −0.047 *** | −0.004 | |
M × A | −0.055 *** | −0.047 | −0.040 | 0.050 * | 0.033 | −0.046 *** | |
R | −0.021 | −0.020 | −0.020 | −0.014 | −0.023 | −0.008 | |
R × A | 0.101 ** | 0.088 * | 0.090 ** | −0.303 ** | 0.083 | 0.007 | |
D | 0.012 | 0.010 | −0.004 | 0.023 | 0.005 | 0.021 | |
D × A | −0.065 *** | −0.083 *** | −00.96 *** | 0.020 | −0.098 *** | 0.017 | |
constant | 1.510 *** | 1.626 *** | 2.152 *** | 1.644 *** | 2.055 *** | 1.623 ** | |
R2 | 0.191 | 0.191 | 0.196 | 0.152 | 0.203 | 0.197 |
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Ren, F.; Zhang, J.; Yang, X. Study on the Effect of Job Accessibility and Residential Location on Housing Occupancy Rate: A Case Study of Xiamen, China. Land 2023, 12, 912. https://doi.org/10.3390/land12040912
Ren F, Zhang J, Yang X. Study on the Effect of Job Accessibility and Residential Location on Housing Occupancy Rate: A Case Study of Xiamen, China. Land. 2023; 12(4):912. https://doi.org/10.3390/land12040912
Chicago/Turabian StyleRen, Feng, Jinbo Zhang, and Xiuyun Yang. 2023. "Study on the Effect of Job Accessibility and Residential Location on Housing Occupancy Rate: A Case Study of Xiamen, China" Land 12, no. 4: 912. https://doi.org/10.3390/land12040912
APA StyleRen, F., Zhang, J., & Yang, X. (2023). Study on the Effect of Job Accessibility and Residential Location on Housing Occupancy Rate: A Case Study of Xiamen, China. Land, 12(4), 912. https://doi.org/10.3390/land12040912