mixtape/R/castle_1.R at master · scunning1975/mixtape · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
library(bacondecomp)
library(tidyverse)
library(haven)
library(lfe)

read_data <- function(df)
{
  full_path <- paste("https://github.com/scunning1975/mixtape/raw/master/",
                     df, sep = "")
  df <- read_dta(full_path)
  return(df)
}

castle <- read_data("castle.dta")

#--- global variables
crime1 <- c("jhcitizen_c", "jhpolice_c",
            "murder", "homicide",
            "robbery", "assault", "burglary",
            "larceny", "motor", "robbery_gun_r")

demo <- c("emo", "blackm_15_24", "whitem_15_24",
          "blackm_25_44", "whitem_25_44")

# variables dropped to prevent colinearity
dropped_vars <- c("r20004", "r20014",
                  "r20024", "r20034",
                  "r20044", "r20054",
                  "r20064", "r20074",
                  "r20084", "r20094",
                  "r20101", "r20102", "r20103",
                  "r20104", "trend_9", "trend_46",
                  "trend_49", "trend_50", "trend_51"
)

lintrend <- castle %>%
    select(starts_with("trend")) %>%
  colnames %>%
  # remove due to colinearity
  subset(.,! . %in% dropped_vars)

region <- castle %>%
  select(starts_with("r20")) %>%
  colnames %>%
  # remove due to colinearity
  subset(.,! . %in% dropped_vars)


exocrime <- c("l_lacerny", "l_motor")
spending <- c("l_exp_subsidy", "l_exp_pubwelfare")


xvar <- c(
  "blackm_15_24", "whitem_15_24", "blackm_25_44", "whitem_25_44",
  "l_exp_subsidy", "l_exp_pubwelfare",
  "l_police", "unemployrt", "poverty",
  "l_income", "l_prisoner", "l_lagprisoner"
)

law <- c("cdl")

dd_formula <- as.formula(
  paste("l_homicide ~ ",
        paste(
          paste(xvar, collapse = " + "),
          paste(region, collapse = " + "),
          paste(lintrend, collapse = " + "),
          paste("post", collapse = " + "), sep = " + "),
        "| year + sid | 0 | sid"
  )
)

#Fixed effect regression using post as treatment variable
dd_reg <- felm(dd_formula, weights = castle$popwt, data = castle)
summary(dd_reg)