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The main difference between Hypotheses 2 and 3 is the different psychological reactions to not being promoted in later years. Based on the results on corruption, it is safe to say that a prefectural leader may increase land sales for more pocket money. Thus, if Hypothesis 3 is true and a prefectural leader gives up in later years, then the rising pattern in the years-in-office effect on land sales implies that these prefectural leaders become more corrupt over time. To check this, we examine the effect of interacting corruption with years in office in the regressions in Tables 3 and 4. As seen in Table 2, corruption exerts more influence on land sales quantity than land sales revenue for the reasons explained in section III.B; we examine the regressions with the change in land supply as the dependent variable. The results are shown in Panel 1 of Table 5. Here we focus on the effect of party secretaries as the rising trend is most pronounced for them. For total, residential, and commercial land, the coefficients on the interaction terms imply that the effect of corruption on the increase of land supply is smaller the greater the number of years in office.15 If a prefectural leader gives up in later years and becomes more corrupt, he or she should sell more land instead of less. Hence, the results here suggest that Hypothesis 3 is not supported. An alternative way to examine this is to run a regression of corruption on years in office and the same set of other regressors in Table 3. Here again we focus on party secretaries. The results are shown in Panel 2 of Table 5. We see that conditioned on other factors that may potentially affect corruption, the correlation between years in office and corruption is negative for residential land, positive for commercial land, and insignificant for industrial land. Overall, there is a negative but insignificant correlation. We can conclude that the empirical results do not support Hypothesis 3.

Table 5. 
Corruption, Years in Office, and Change in Land Supply
 Panel 1: Years in Office and Land SupplyPanel 2: Corruption and Years in Office
ln(increase in land supply)Corruption (fraction of two-stage auction)
TotalResidentialCommercialIndustrial
Variables(1)(2)(3)(4)(1)(2)(3)(4)
years in office 1.137*** 1.029*** 1.671*** 0.355 −0.0130 −0.0867*** 0.105* 0.00625 
 (0.345) (0.237) (0.352) (0.386) (0.0202) (0.0330) (0.0551) (0.0127) 
(years in office)2 −0.0692* −0.0359* −0.112*** 0.0227 0.000500 0.00114 0.000425 −9.23e–05 
 (0.0377) (0.0187) (0.0343) (0.0425) (0.00118) (0.00209) (0.00288) (0.000842) 
ln(GDP increase) −0.00298 −0.0603 −0.00450 0.0274 0.00227 −0.00731 −0.000432 0.00914 
 (0.0383) (0.0618) (0.0749) (0.0602) (0.00597) (0.0113) (0.0139) (0.00820) 
ratio of GDPs (tertiary to secondary) −0.180 0.0410 −0.665* −0.675 −0.000269 0.118* −0.166 −0.0188 
 (0.286) (0.434) (0.374) (0.647) (0.0428) (0.0667) (0.126) (0.0226) 
fraction of 2-stage (total) 1.457*    0.0159 −0.0469 0.125 0.0761 
 (0.778)    (0.712) (0.712) (0.769) (0.768) 
fraction of 2-stage (total)*(years in office) −0.658*        
 (0.356)        
fraction of 2-stage (total)*(years in office)2 0.0724*        
 (0.0408)        
fraction of 2-stage (residential)  1.204***       
  (0.383)       
fraction of 2-stage (residential)*(years in office)  −0.426**       
  (0.192)       
fraction of 2-stage (residential)*(years in office)2  0.0440*       
  (0.0224)       
fraction of 2-stage (commercial)   2.280***      
   (0.619)      
fraction of 2-stage (commercial)*(years in office)   −0.981***      
   (0.337)      
fraction of 2-stage (commercial)*(years in office)2   0.112***      
   (0.0384)      
fraction of 2-stage (industrial)    0.872     
    (0.800)     
fraction of 2-stage (industrial)*(years in office)    0.0918     
    (0.424)     
fraction of 2-stage (industrial)*(years in office)2    −0.0320     
    (0.0484)     
Constant 4.263*** 2.321*** −2.056*** 4.851** 0.902*** 0.701*** 0.669*** 0.946*** 
 (0.841) (0.755) (0.789) (2.317) (0.0601) (0.0801) (0.161) (0.0595) 
Prefecture-(Party-Secretary) FE Yes Yes Yes Yes Yes Yes Yes Yes 
Year FE Yes Yes Yes Yes Yes Yes Yes Yes 
Observations 1,343 1,344 1,341 1,340 1,348 1,346 1,341 1,341 
R2 0.894 0.868 0.817 0.827 0.801 0.845 0.637 0.702 
 Panel 1: Years in Office and Land SupplyPanel 2: Corruption and Years in Office
ln(increase in land supply)Corruption (fraction of two-stage auction)
TotalResidentialCommercialIndustrial
Variables(1)(2)(3)(4)(1)(2)(3)(4)
years in office 1.137*** 1.029*** 1.671*** 0.355 −0.0130 −0.0867*** 0.105* 0.00625 
 (0.345) (0.237) (0.352) (0.386) (0.0202) (0.0330) (0.0551) (0.0127) 
(years in office)2 −0.0692* −0.0359* −0.112*** 0.0227 0.000500 0.00114 0.000425 −9.23e–05 
 (0.0377) (0.0187) (0.0343) (0.0425) (0.00118) (0.00209) (0.00288) (0.000842) 
ln(GDP increase) −0.00298 −0.0603 −0.00450 0.0274 0.00227 −0.00731 −0.000432 0.00914 
 (0.0383) (0.0618) (0.0749) (0.0602) (0.00597) (0.0113) (0.0139) (0.00820) 
ratio of GDPs (tertiary to secondary) −0.180 0.0410 −0.665* −0.675 −0.000269 0.118* −0.166 −0.0188 
 (0.286) (0.434) (0.374) (0.647) (0.0428) (0.0667) (0.126) (0.0226) 
fraction of 2-stage (total) 1.457*    0.0159 −0.0469 0.125 0.0761 
 (0.778)    (0.712) (0.712) (0.769) (0.768) 
fraction of 2-stage (total)*(years in office) −0.658*        
 (0.356)        
fraction of 2-stage (total)*(years in office)2 0.0724*        
 (0.0408)        
fraction of 2-stage (residential)  1.204***       
  (0.383)       
fraction of 2-stage (residential)*(years in office)  −0.426**       
  (0.192)       
fraction of 2-stage (residential)*(years in office)2  0.0440*       
  (0.0224)       
fraction of 2-stage (commercial)   2.280***      
   (0.619)      
fraction of 2-stage (commercial)*(years in office)   −0.981***      
   (0.337)      
fraction of 2-stage (commercial)*(years in office)2   0.112***      
   (0.0384)      
fraction of 2-stage (industrial)    0.872     
    (0.800)     
fraction of 2-stage (industrial)*(years in office)    0.0918     
    (0.424)     
fraction of 2-stage (industrial)*(years in office)2    −0.0320     
    (0.0484)     
Constant 4.263*** 2.321*** −2.056*** 4.851** 0.902*** 0.701*** 0.669*** 0.946*** 
 (0.841) (0.755) (0.789) (2.317) (0.0601) (0.0801) (0.161) (0.0595) 
Prefecture-(Party-Secretary) FE Yes Yes Yes Yes Yes Yes Yes Yes 
Year FE Yes Yes Yes Yes Yes Yes Yes Yes 
Observations 1,343 1,344 1,341 1,340 1,348 1,346 1,341 1,341 
R2 0.894 0.868 0.817 0.827 0.801 0.845 0.637 0.702 

FE = fixed effects, GDP = gross domestic product.

Notes: Data on the length of terms for prefectural party secretaries and mayors are from authors' collection. 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. All the regressions in this table are for party secretaries. *** = p < .01, ** = p < .05, * = p < 0.1.

Source: Authors’ calculations.

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