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Table 2 Estimated effects of protected areas on poverty in Chile. The main explanatory variable is a binary variable equal to 1 if the unit has at least a fraction of its area protected

From: The impact of protected areas on poverty: evidence from Chile

  Outcome of interest: poverty index
  Main model Alternative model specifications
  (1) (2) (3) (4)
Binary variable = 1 if at least 17% is protected -0.216* (0.127)    -0.050 (0.138)
Binary variable = 1 if at least 10% is protected   -0.229* (0.118)   
Binary variable = 1 if at least 30% is protected    -0.220 (0.131)  
\({D}_{it}\) * Patagonia, where \({D}_{it}\) is a binary variable = 1 if at least 17% is protected     -0.580** (0.205)
\(log(population)\) 0.265 (0.194) 0.261 (0.194) 0.263 (0.194) 0.263 (0.192)
Constant -3.474 (2.311) -3.470 (2.275) -3.491 (2.282) -3.488 (2.255)
Unit-fixed effect Yes Yes Yes Yes
Year-fixed effect Yes Yes Yes Yes
No. of observations 534 534 534 534
\({R}^{2}\) 0.914 0.914 0.914 0.916
  1. Robust standard errors clustered at the unit level are reported in parentheses. The levels of significance are *10%, and **1%