In an interesting paper, Beland (AEJ: Applied Economics, 2015), estimates causal impacts of the party allegiance...

 

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In an interesting paper, Beland (AEJ: Applied Economics, 2015), estimates causal impacts of the party allegiance (Republican or Democratic) of US governors on labor- market outcomes of different groups in society; specifically, Black and White adults in each state. He matches gubernatorial elections information in each of the 50 states with March Current Population Survey (CPS) data with labor market information (e.g., labor force participation, employment, hours worked, earnings) of a representative sample of Black and White individuals for the years 1977 to 2008. The goal of this exercise is to implement the RDD in Beland (2015) to estimate these causal effects for states in which a Democrat gubernatorial candidate barely won an election relative to those in which a Republican candidate barely won. Dataset You should use the Stata dataset posted on the course website to do this, following the suggestions below. The dataset available for the assignment is a version of the one used by Beland (2015) where we have taken the mean of each variable per state and year, for each group of white and black individuals. Below is a description of each variable in the dataset before collapsing to the state-year- ethnic group cell means. obs: vars: 3,107 32 2 Nov 2021 12:36 1 The individual-level data may be too large for the versions of Stata used by some students in the course. variable name storage display value type format label variable label year2 float %9.0g state2 float %9.0g black2 byte employed float %9.0g %9.0g age float % 8.0g age2 float %9.0g Year State ID Black individual (1/0) Employment status (1/0) Individual's age (years) (mean) age2 age3 float %9.0g (mean) age3 age4 float %9.0g (mean) age4 female float %9.0g Gender F=1/M=0 separated float %9.0g divorced float %9.0g widowed nevermaried elementary float %9.0g float %9.0g float %9.0g somecol float %9.0g coll float %9.0g moreba float %9.0g demwon float %9.0g blackdemwon float %9.0g marginvvv float %9.0g marginvictory2 float %9.0g marginvictory3 float %9.0g dMVv dMV2v dMV3v float %9.0g float %9.0g float %9.0g blackMVV float %9.0g blackMV2v blackMV3v blackdMVv blackdMV2v blackdMV3v marginggg float %9.0g float %9.0g float %9.0g float %9.0g float %9.0g float %9.0g Separated (1/0) Divorced (1/0) Widowed (1/0) Never married (1/0) High school dropout (1/0) Some college (1/0) College graduate (1/0) More than college degree (1/0) Democrat candidate won (1/0) Black ind x Democrat won (1/0) Margin of victory (votes) (Margin of victory)^2 (Margin of victory) ^3 demwon x Margin of victory demwon x (Margin of victory)^2 demwon x (Margin of victory) ^3 Black ind. x Margin of victory Black ind. x (Margin of victory)^2 Black ind. x (Margin of victory) ^3 Black ind. x demwon x Margin of victory Black ind. x demwon x (Margin of victory)^2 Black ind. x demwon x (Margin of victory)^3 Margin of victory grouping cells Sorted by: state2 year2 In an interesting paper, Beland (AEJ: Applied Economics, 2015), estimates causal impacts of the party allegiance (Republican or Democratic) of US governors on labor- market outcomes of different groups in society; specifically, Black and White adults in each state. He matches gubernatorial elections information in each of the 50 states with March Current Population Survey (CPS) data with labor market information (e.g., labor force participation, employment, hours worked, earnings) of a representative sample of Black and White individuals for the years 1977 to 2008. The goal of this exercise is to implement the RDD in Beland (2015) to estimate these causal effects for states in which a Democrat gubernatorial candidate barely won an election relative to those in which a Republican candidate barely won. Dataset You should use the Stata dataset posted on the course website to do this, following the suggestions below. The dataset available for the assignment is a version of the one used by Beland (2015) where we have taken the mean of each variable per state and year, for each group of white and black individuals. Below is a description of each variable in the dataset before collapsing to the state-year- ethnic group cell means. obs: vars: 3,107 32 2 Nov 2021 12:36 1 The individual-level data may be too large for the versions of Stata used by some students in the course. variable name storage display value type format label variable label year2 float %9.0g state2 float %9.0g black2 byte employed float %9.0g %9.0g age float % 8.0g age2 float %9.0g Year State ID Black individual (1/0) Employment status (1/0) Individual's age (years) (mean) age2 age3 float %9.0g (mean) age3 age4 float %9.0g (mean) age4 female float %9.0g Gender F=1/M=0 separated float %9.0g divorced float %9.0g widowed nevermaried elementary float %9.0g float %9.0g float %9.0g somecol float %9.0g coll float %9.0g moreba float %9.0g demwon float %9.0g blackdemwon float %9.0g marginvvv float %9.0g marginvictory2 float %9.0g marginvictory3 float %9.0g dMVv dMV2v dMV3v float %9.0g float %9.0g float %9.0g blackMVV float %9.0g blackMV2v blackMV3v blackdMVv blackdMV2v blackdMV3v marginggg float %9.0g float %9.0g float %9.0g float %9.0g float %9.0g float %9.0g Separated (1/0) Divorced (1/0) Widowed (1/0) Never married (1/0) High school dropout (1/0) Some college (1/0) College graduate (1/0) More than college degree (1/0) Democrat candidate won (1/0) Black ind x Democrat won (1/0) Margin of victory (votes) (Margin of victory)^2 (Margin of victory) ^3 demwon x Margin of victory demwon x (Margin of victory)^2 demwon x (Margin of victory) ^3 Black ind. x Margin of victory Black ind. x (Margin of victory)^2 Black ind. x (Margin of victory) ^3 Black ind. x demwon x Margin of victory Black ind. x demwon x (Margin of victory)^2 Black ind. x demwon x (Margin of victory)^3 Margin of victory grouping cells Sorted by: state2 year2