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 |