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On February 12, 2022 at 3:03:59 AM UTC, Gravatar Zhichao He:
  • Updated description of Causal effect of LUP from

    Title: Does zoning contain built-up land expansion? Causal evidence from Zhangzhou City, China. Research objective: Built-up land zoning is an imporatant policy measure of land use planning (LUP) to contain built-up land expansion in China. We used a difference-indifference model with propensity score matching to estimate the average and annual effect of built-up land zoning on built-up land expansion in Zhangzhou City, China between 2010 and 2020. Data: Data.dbf contains the varibles of 1662 villages in Zhangzhou Cities in 1995, 2000, 2005, 2010, 2013, 2015, 2018, and 2020. XZQDM2 is villages' unique administrative ID. Area is the land area of village i Dis2water is the Euclidean distance from village i to the nearest waterbody. Dis2coastl is the Euclidean distance from village i to the nearest coastline. Dis2city is the the Euclidean distance from village i to the city center Dis2county is the the Euclidean distance from village i to the nearest county center Elevation is the the average elevation within village i Dis2road is the the Euclidean distance from village i to the nearest road Nei_Built_ is the the area of built-up land (Nei Built.upit) in the neighboring villages of village i in year t Treated is a binary variable, Treated = 1 to the villages that were partially or entirely located inside the development-permitted zones, and Treated = 0 to the villages that were entirely located outside the development-permitted zones Intensity is the percentage of land that was assigned to the development-permitted zones in village i Year represent the year in 1995, 2000, 2005, 2010, 2013, 2015, 2018, and 2020 BuLE is the dependent variable, representing built-up land expansion in village i in year t . Town is town' unique administrative ID. Method: First, we employed propensity score matching to overcome the selection bias and satisfy the parallel trend assumption. Second, we built four Difference-in-Difference models to estimate the average and annual effect
    to
    Title: Does zoning contain built-up land expansion? Causal evidence from Zhangzhou City, China. Research objective: Built-up land zoning is an imporatant policy measure of land use planning (LUP) to contain built-up land expansion in China. We used a difference-indifference model with propensity score matching to estimate the average and annual effect of built-up land zoning on built-up land expansion in Zhangzhou City, China between 2010 and 2020. Data: Data.dbf contains the varibles of 1662 villages in Zhangzhou Cities in 1995, 2000, 2005, 2010, 2013, 2015, 2018, and 2020. XZQDM2 is villages' unique administrative ID; Area is the land area of village i; Dis2water is the Euclidean distance from village i to the nearest waterbody; Dis2coastl is the Euclidean distance from village i to the nearest coastline; Dis2city is the the Euclidean distance from village i to the city center; Dis2county is the the Euclidean distance from village i to the nearest county center; Elevation is the the average elevation within village i; Dis2road is the the Euclidean distance from village i to the nearest road; Nei_Built_ is the the area of built-up land (Nei Built.upit) in the neighboring villages of village i in year t; Treated is a binary variable, Treated = 1 to the villages that were partially or entirely located inside the development-permitted zones, and Treated = 0 to the villages that were entirely located outside the development-permitted zones; Intensity is the percentage of land that was assigned to the development-permitted zones in village i; Year represent the year in 1995, 2000, 2005, 2010, 2013, 2015, 2018, and 2020; BuLE is the dependent variable, representing built-up land expansion in village i in year t; Town is town' unique administrative ID. Method: First, we employed propensity score matching to overcome the selection bias and satisfy the parallel trend assumption. Second, we built four Difference-in-Difference models to estimate the average and annual effect.