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Columns (1)–(4) of Table 1 show the regression results of the logarithms of the change in land supply—total and by type (residential, commercial, or industrial)—on the above-mentioned standard urban economic explanations of land-demand increases. In all the regressions in this paper, we control for year fixed effects and cluster standard errors at the province level. In the regression in Table 1, we do not include prefecture fixed effects because we want to investigate the effect of population growth. However, since our population data are either interpolated or extrapolated, the logarithms of population increments become constant over time. As industrial structures may affect the breakdown of land supply and potentially affect the total land supply as well, we use the ratio of tertiary industries to secondary industries (in GDP terms) to proxy industrial structure. Columns (5)–(8) show results when we control for this ratio.

Table 1. 
Standard Urban-Economic Predictions: First Look
 ln(increase in land supply)
TotalResidentialCommercialIndustrialTotalResidentialCommercialIndustrial
Variables(1)(2)(3)(4)(5)(6)(7)(8)
ln(population increase) 0.437*** 0.423*** 0.478*** 0.444*** 0.449*** 0.429*** 0.470*** 0.479*** 
 (0.054) (0.067) (0.059) (0.058) (0.057) (0.069) (0.059) (0.063) 
ln(increase in GDP per capita) 0.0578*** 0.0402*** 0.0706*** 0.0557*** 0.0576*** 0.0401*** 0.0708*** 0.0556*** 
 (0.011) (0.014) (0.013) (0.014) (0.011) (0.014) (0.013) (0.014) 
ratio of GDPs (tertiary to secondary)     −0.217** −0.105 0.138 −0.590*** 
     (0.104) (0.123) (0.133) (0.187) 
Constant 5.734*** 4.317*** −1.196*** 3.384*** 5.893*** 4.395*** −1.298*** 3.815*** 
 (0.167) (0.211) (0.187) (0.206) (0.182) (0.230) (0.212) (0.262) 
Year FE Yes Yes Yes Yes Yes Yes Yes Yes 
Observations 1,438 1,437 1,441 1,429 1,438 1,437 1,441 1,429 
R2 0.499 0.389 0.329 0.431 0.504 0.390 0.331 0.458 
 ln(increase in land supply)
TotalResidentialCommercialIndustrialTotalResidentialCommercialIndustrial
Variables(1)(2)(3)(4)(5)(6)(7)(8)
ln(population increase) 0.437*** 0.423*** 0.478*** 0.444*** 0.449*** 0.429*** 0.470*** 0.479*** 
 (0.054) (0.067) (0.059) (0.058) (0.057) (0.069) (0.059) (0.063) 
ln(increase in GDP per capita) 0.0578*** 0.0402*** 0.0706*** 0.0557*** 0.0576*** 0.0401*** 0.0708*** 0.0556*** 
 (0.011) (0.014) (0.013) (0.014) (0.011) (0.014) (0.013) (0.014) 
ratio of GDPs (tertiary to secondary)     −0.217** −0.105 0.138 −0.590*** 
     (0.104) (0.123) (0.133) (0.187) 
Constant 5.734*** 4.317*** −1.196*** 3.384*** 5.893*** 4.395*** −1.298*** 3.815*** 
 (0.167) (0.211) (0.187) (0.206) (0.182) (0.230) (0.212) (0.262) 
Year FE Yes Yes Yes Yes Yes Yes Yes Yes 
Observations 1,438 1,437 1,441 1,429 1,438 1,437 1,441 1,429 
R2 0.499 0.389 0.329 0.431 0.504 0.390 0.331 0.458 

FE = fixed effects, GDP = gross domestic product.

Notes: Population data are from population census data in 2000 and 2010, and authors' calculation. GDP data are from City Statistics Yearbook. Land data are from the website of the Ministry of Land and Resources. Standard errors are clustered at the province level and shown in parentheses. The difference between Columns (1)–(4) and Columns (5)–(8) is whether the ratio of tertiary to secondary GDP is included as a control. *** = p < .01, ** = p < .05, * = p < 0.1.

Source: Authors’ calculations.

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