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  1. 109/paper.pdf +3 -0
  2. 109/replication_package/CJLR_Replication_ReadMe.pdf +3 -0
  3. 109/replication_package/Data Files/city_gb_wbbd.dta +3 -0
  4. 109/replication_package/Data Files/county_gb_correlates_1940.dta +3 -0
  5. 109/replication_package/Data Files/county_gb_hotels.dta +3 -0
  6. 109/replication_package/Data Files/county_gb_hotels_panel.dta +3 -0
  7. 109/replication_package/Data Files/county_gb_main.dta +3 -0
  8. 109/replication_package/Data Files/county_gb_retail.dta +3 -0
  9. 109/replication_package/Data Files/county_gb_retail_panel.dta +3 -0
  10. 109/replication_package/Data Files/national_gb_freq_ind.dta +3 -0
  11. 109/replication_package/Data Files/national_gb_ind_year.dta +3 -0
  12. 109/replication_package/Data Files/national_gb_region_year.dta +3 -0
  13. 109/replication_package/Data Files/state_gb_cob.dta +3 -0
  14. 109/replication_package/Data Files/state_gb_paulimurray.dta +3 -0
  15. 109/replication_package/Data Files/state_gb_wbbd.dta +3 -0
  16. 109/replication_package/Do Files/CJLR_GreenBooks_QJE_Rep.do +1842 -0
  17. 109/replication_package/List of Tabs and FIgs.xlsx +3 -0
  18. 109/replication_package/Output/Figures/a_killed_w__gbtot_by_excluded_ptiles.pdf +3 -0
  19. 109/replication_package/Output/Figures/a_killed_white_event_gbtot.pdf +3 -0
  20. 109/replication_package/Output/Figures/count_all_est_over_time_usa_allindustries_novacay.pdf +3 -0
  21. 109/replication_package/Output/Figures/count_all_est_over_time_usa_byregion_novacay.pdf +3 -0
  22. 109/replication_package/Output/Figures/covariate_balance_std.pdf +3 -0
  23. 109/replication_package/Output/Figures/formalGB_vs_blackCOB_45deg_novacay.pdf +3 -0
  24. 109/replication_package/Output/Figures/formalGB_vs_blackWBD_45deg_novacay.pdf +3 -0
  25. 109/replication_package/Output/Figures/formalGB_vs_blackWBD_45deg_novacay_citylevel_weighted.pdf +3 -0
  26. 109/replication_package/Output/Figures/formalGB_vs_othersources.pdf +3 -0
  27. 109/replication_package/Output/Figures/freq_by_type_novacay.pdf +3 -0
  28. 109/replication_package/Output/Figures/gbpc_all_est_over_time_usa_byregion_novacay.pdf +3 -0
  29. 109/replication_package/Output/Figures/gbpc_correlates_Main.pdf +3 -0
  30. 109/replication_package/Output/Figures/num_est_by_existing_GB_novacay.pdf +3 -0
  31. 109/replication_package/Output/Figures/pauli_murray_residual_gb_vs_antidisc_noOutlier_novacay.pdf +3 -0
  32. 109/replication_package/Output/Figures/pauli_murray_residual_gb_vs_antidisc_novacay.pdf +3 -0
  33. 109/replication_package/Output/Figures/pauli_murray_residual_gb_vs_disc_noOutlier_novacay.pdf +3 -0
  34. 109/replication_package/Output/Figures/pauli_murray_residual_gb_vs_disc_novacay.pdf +3 -0
  35. 109/replication_package/Output/Figures/pauli_murray_residuals_noOutlier_novacay.pdf +3 -0
  36. 109/replication_package/Output/Figures/pauli_murray_residuals_novacay.pdf +3 -0
  37. 109/replication_package/Output/Figures/shareGBeating_correlates_Retail.pdf +3 -0
  38. 109/replication_package/Output/Figures/shareGBgas_correlates_Retail.pdf +3 -0
  39. 109/replication_package/Output/Figures/shareGBhotel_correlates_Hotels.pdf +3 -0
  40. 109/replication_package/Output/Figures/share_counties_w_gb_novacay.pdf +3 -0
  41. 109/replication_package/Output/Figures/share_eating_pc_byregion_novacay.pdf +3 -0
  42. 109/replication_package/Output/Figures/share_gas_pc_byregion_novacay.pdf +3 -0
  43. 109/replication_package/Output/Figures/share_hotel_byregion_novacay.pdf +3 -0
  44. 109/replication_package/Output/Tables/a_killed_draft_white_did_by_industry.tex +20 -0
  45. 109/replication_package/Output/Tables/a_killed_draft_white_did_gbtot.tex +18 -0
  46. 109/replication_package/Output/Tables/a_killed_draft_white_did_shares.tex +20 -0
  47. 109/replication_package/Output/Tables/a_killed_white_did_by_industry.tex +20 -0
  48. 109/replication_package/Output/Tables/a_killed_white_did_gbtot.tex +18 -0
  49. 109/replication_package/Output/Tables/a_killed_white_did_shares.tex +20 -0
  50. 109/replication_package/Output/Tables/iv_robust_eatingdrinking.tex +52 -0
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1
+ ********************************************************************************
2
+ *---------------------- REPLICATION CODE: PRELIM INFO ------------------------*
3
+ ********************************************************************************
4
+
5
+ /*
6
+ Purpose:
7
+ This do file replicates the empirical analysis in:
8
+ Cook, Jones, Logan, Rosé (2022)
9
+ "The Evolution of Access to Public Accommodations in the United States"
10
+
11
+ Packages:
12
+ ssc (grstyle lvr2plot2 palettes colrspace parmest ivreg2 ranktest)
13
+
14
+ Replicates all tables and figures except:
15
+ Fig 1
16
+ Fig 8
17
+ Tab 1
18
+ */
19
+
20
+ notes: Last updated Aug 1, 2022
21
+
22
+ ********************************************************************************
23
+ *------------------------- STANDARD PRELIM CODE ------------------------------*
24
+ ********************************************************************************
25
+
26
+ clear all
27
+ set more off
28
+ capture log close
29
+ set matsize 10000
30
+
31
+ // Nicer quality graphs -> need to install LMRoman10-Regular font package, or comment out
32
+ graph set window fontface "LMRoman10-Regular"
33
+ graph set window fontfacemono "LMRoman10-Regular"
34
+ graph set window fontfacesans "LMRoman10-Regular"
35
+ graph set window fontfaceserif "LMRoman10-Regular"
36
+ graph set window fontfacesymbol "LMRoman10-Regular"
37
+
38
+ // Need the grstyle package for this graph command to work, or comment out
39
+ grstyle init
40
+ grstyle set mesh, horizontal compact minor
41
+ grstyle set legend 6, nobox stack
42
+ grstyle linewidth plineplot 0.7
43
+ grstyle set color hue, n(4)
44
+
45
+ ********************************************************************************
46
+ *------------------------- SET WORKING DIRECTORIES ----------------------------*
47
+ ********************************************************************************
48
+
49
+
50
+ // SET FOLDER FILE PATH HERE:
51
+
52
+ global wd "/Users/maggiejones/Dropbox/Research/Green Books/Green Books/Do Files/QJE Empirics/QJE Replication Package/"
53
+ //global wd "C:/Users/darose/Dropbox/Research/Discrimination/Do Files/QJE Empirics/QJE Replication Package"
54
+
55
+ global qjedata "$wd/Data Files/"
56
+ global tables "$wd/Output/Tables/"
57
+ global figures "$wd/Output/Figures/"
58
+
59
+
60
+ ********************************************************************************
61
+
62
+ ********************************************************************************
63
+ ********************************************************************************
64
+ *************************** SECTION 1: MAIN PAPER ******************************
65
+ ********************************************************************************
66
+ ********************************************************************************
67
+
68
+
69
+ ********************************************************************************
70
+ *-------------- FIG 2: Green Books vs. CoB and WBBD ---------------*
71
+ ********************************************************************************
72
+
73
+ capture graph drop *
74
+
75
+ ***
76
+ // gb vs. wbbd
77
+ use "$qjedata/state_gb_wbbd.dta", clear
78
+
79
+ #delimit ;
80
+ twoway (scatter num_est_hotel formal_wb, sort mlabel(state_abv)
81
+ mlabcolor(black) mcolor(black%50) mlcolor(black%50) msize(tiny))
82
+ (line num_est_hotel num_est_hotel2, sort lcolor(black) lwidth(medthin) lpattern(dash)),
83
+ xtitle("Number in Wisconsin Black Business Directory", margin(medium))
84
+ ytitle("Number in Green Books")
85
+ legend(off) text(36 41 "45-degree line", place(e) size(.3cm))
86
+ xlabel(0(20)60, grid) ylabel(0(20)60, grid) name(formal_WBD);
87
+ graph export "$figures/formalGB_vs_blackWBD_45deg_novacay.pdf", replace ;
88
+ #delimit cr
89
+
90
+ ***
91
+ // gb vs. cob
92
+ use "$qjedata/state_gb_cob.dta", clear
93
+
94
+ #delimit ;
95
+ twoway (scatter num_est_hotel hotels_BlackCOB , sort mlabel(state_abv)
96
+ mlabcolor(black) mcolor(black%50) mlcolor(black%50) msize(tiny))
97
+ (line num_est_hotel num_est_hotel2, sort lcolor(black) lwidth(medthin) lpattern(dash)),
98
+ xtitle("Number of Black-Owned in Census of Business", margin(medium)) ytitle(Number in Green Book)
99
+ legend(off) text(36 41 "45-degree line", place(e) size(.3cm))
100
+ xlabel(0(20)70, grid) ylabel(0(20)70, grid) name(formal_COB);
101
+ graph export "$figures/formalGB_vs_blackCOB_45deg_novacay.pdf", replace;
102
+ #delimit cr
103
+
104
+ graph combine formal_WBD formal_COB, ycommon xcommon
105
+
106
+ graph export "$figures/formalGB_vs_othersources.pdf", replace
107
+
108
+ graph drop formal_WBD formal_COB
109
+
110
+ ********************************************************************************
111
+ *------------ FIG 3: Geographic coverage & GB listings -----------*
112
+ ********************************************************************************
113
+
114
+ capture graph drop *
115
+
116
+ ***
117
+ use "$qjedata/county_gb_main.dta", clear
118
+
119
+ sort ICPSRST ICPSRCTY year
120
+
121
+ gen new_growth = gb_tot if gb_tot[_n-1]==0 & county_code[_n] == county_code[_n-1] // n est in counties that already have at least one gb est
122
+ gen existing_growth = gb_tot if gb_tot[_n-1]!=0 & county_code[_n] == county_code[_n-1] // n est in counties that don't have any gb est
123
+
124
+ count if year == 1940
125
+ scalar nobs = r(N)
126
+
127
+ collapse (sum) gb_tot gb_est new_growth existing_growth, by(year)
128
+
129
+
130
+ // Panel (a) Share with at least 1 Greeb Book establishment
131
+ gen sh_w_gb = gb_est/nobs
132
+ gen no_gb_est = (gb_est == 0)
133
+ gen sh_wout_gb= no_gb_est/nobs
134
+
135
+ tsset year
136
+ tsfill
137
+
138
+
139
+ #delimit
140
+ twoway (line sh_w_gb year if sh_w_gb > 0, sort lcolor(black) lpattern(solid) lwidth(medium) cmissing(n))
141
+ (line sh_w_gb year if sh_w_gb > 0, sort lcolor(black) lpattern(dot) lwidth(medium) cmissing(y))
142
+ (scatter sh_w_gb year if sh_w_gb > 0, sort mcolor(black) msymbol(triangle) msize(medium)),
143
+ ylabel(0.10(0.02)0.18,grid) xtitle("Year") ytitle("Share of Counties (0 to 1)")
144
+ legend(off);
145
+ graph export "$figures/share_counties_w_gb_novacay.pdf", replace ;
146
+ #delimit cr
147
+
148
+ ***
149
+ //Panel (b): Growth in new counties (i.e. those without an existing GB) vs. existing counties (i.e. those with at least 1 GB)
150
+ #delimit ;
151
+ twoway (line gb_tot year, sort lcolor(black) lpattern(solid) lwidth(medium) cmissing(n))
152
+ (line gb_tot year, sort lcolor(black) lpattern(dot) lwidth(medium) cmissing(y))
153
+ (scatter gb_tot year, sort mcolor(black) msymbol(triangle) msize(medium))
154
+
155
+ (line new_growth year, sort lcolor(black) lpattern(dash) lwidth(medium) cmissing(n))
156
+ (line new_growth year, sort lcolor(black) lpattern(dot) lwidth(medium) cmissing(y))
157
+ (scatter new_growth year, sort mcolor(black) msymbol(circle) msize(medium))
158
+
159
+ (line existing_growth year, sort lcolor(black) lpattern(longdash) lwidth(thick) cmissing(n))
160
+ (line existing_growth year, sort lcolor(black) lpattern(dot) lwidth(medium) cmissing(y))
161
+ (scatter existing_growth year, sort mcolor(black) msymbol(X) msize(large)) ,
162
+ ylabel(,grid) xtitle("Year") ytitle("Number of Establishments")
163
+ legend(label(3 "Total No. of Establishments") label(6 "No. Est. in New Counties")
164
+ label(9 "N. Est. in Existing Counties") order(3 6 9) rows(1)) ;
165
+ graph export "$figures/num_est_by_existing_GB_novacay.pdf", replace ;
166
+ #delimit cr
167
+
168
+
169
+ ********************************************************************************
170
+ *-------------- FIG 4: Green Books vs. Seg/Anti-Seg laws ---------------*
171
+ ********************************************************************************
172
+
173
+ capture graph drop *
174
+
175
+ use "$qjedata/state_gb_paulimurray.dta", replace
176
+
177
+ qui reg gb_tot pop_b_1950
178
+ predict double resid_gb, residuals
179
+
180
+ qui reg numdisc pop_b_1950
181
+ predict double resid_disc, residuals
182
+
183
+ qui reg numantidisc pop_b_1950
184
+ predict double resid_antidisc, residuals
185
+
186
+ #delimit ;
187
+ // Discrimination Laws
188
+ twoway (scatter resid_gb resid_disc if year == 1950, sort mlabel(state_abv)
189
+ mlabcolor(black) mcolor(black%50) mlcolor(black%50) msize(tiny))
190
+ (lfit resid_gb resid_disc if year == 1950 , sort lcolor(black) lwidth(medthin)),
191
+ xtitle("Residualized Number of Discrimination Laws", margin(medium)) ytitle("Residualized Number of Green Book Estabs.")
192
+ legend(off) name(disc) ;
193
+ graph export "$figures/pauli_murray_residual_gb_vs_disc_novacay.pdf", replace ;
194
+
195
+ // Anti-Discrimination Laws
196
+ twoway (scatter resid_gb resid_antidisc if year == 1950, sort mlabel(state_abv)
197
+ mlabcolor(black) mcolor(black%50) mlcolor(black%50) msize(tiny))
198
+ (lfit resid_gb resid_antidisc if year == 1950 , sort lcolor(black) lwidth(medthin)),
199
+ xtitle("Residualized Number of Anti-Discrimination Laws", margin(medium)) ytitle("Residualized Number of Green Book Estabs.")
200
+ name(antidisc) legend(off) ;
201
+ graph export "$figures/pauli_murray_residual_gb_vs_antidisc_novacay.pdf", replace ;
202
+ #delimit cr
203
+
204
+ graph combine disc antidisc, scheme(s1color) ycommon xcommon
205
+
206
+ graph export "$figures/pauli_murray_residuals_novacay.pdf", replace
207
+
208
+ ********************************************************************************
209
+ *-------------- FIG 5: Green Books by Industry/Region ---------------*
210
+ ********************************************************************************
211
+
212
+ // by industry
213
+ use "$qjedata/national_gb_ind_year.dta", clear
214
+
215
+ #delimit ;
216
+ twoway (line gb_tot year if ind_stub== "barber" , sort lcolor(black) lpattern(solid) lwidth(medium) yaxis(1) cmissing(n))
217
+ (line gb_tot year if ind_stub== "barber", sort lcolor(black) lpattern(dash_dot) lwidth(medium) yaxis(1))
218
+ (scatter gb_tot year if ind_stub== "barber" , sort mcolor(black) msymbol(O) yaxis(1))
219
+
220
+ (line gb_tot year if ind_stub== "eating" , sort lcolor(black) lpattern(solid) lwidth(medium) yaxis(1) cmissing(n))
221
+ (line gb_tot year if ind_stub== "eating" , sort lcolor(black) lpattern(dash_dot) lwidth(medium) yaxis(1))
222
+ (scatter gb_tot year if ind_stub== "eating" , sort mcolor(black) msymbol(triangle) yaxis(1))
223
+
224
+ (line gb_tot year if ind_stub== "formal" , sort lcolor(black) lpattern(solid) lwidth(medium) yaxis(1) cmissing(n))
225
+ (line gb_tot year if ind_stub== "formal" , sort lcolor(black) lpattern(dash_dot) lwidth(medium) yaxis(1))
226
+ (scatter gb_tot year if ind_stub== "formal" , sort mcolor(black) msymbol(diamond) yaxis(1))
227
+
228
+ (line gb_tot year if ind_stub== "gasoline" , sort lcolor(black) lpattern(solid) lwidth(medium) yaxis(1) cmissing(n))
229
+ (line gb_tot year if ind_stub== "gasoline" , sort lcolor(black) lpattern(dash_dot) lwidth(medium) yaxis(1))
230
+ (scatter gb_tot year if ind_stub== "gasoline" , sort mcolor(black) msize(*2) msymbol(+) yaxis(1))
231
+
232
+ (line gb_tot year if ind_stub== "informal" , sort lcolor(black) lpattern(solid) lwidth(medium) yaxis(1) cmissing(n))
233
+ (line gb_tot year if ind_stub== "informal" , sort lcolor(black) lpattern(dash_dot) lwidth(medium) yaxis(1))
234
+ (scatter gb_tot year if ind_stub== "informal" , sort mcolor(black) msize(*2) msymbol(X) yaxis(1)) ,
235
+ ylabel(,grid) ytitle("Number of Establishments") xtitle("Year")
236
+ legend(order(3 "Barber & Beauty" 6 "Eating & Drinking" 9 "Hotels & Motels"
237
+ 12 "Gas Stations" 15 "Informal Accomod." ) rows(2)) xsize(6) ysize(3) ;
238
+ graph export "$figures/count_all_est_over_time_usa_allindustries_novacay.pdf", replace ;
239
+ #delimit cr
240
+
241
+ // by region
242
+ use "$qjedata/national_gb_region_year.dta", clear
243
+
244
+ #delimit ;
245
+ twoway (line gb_tot year if region_dataset == "Midwest-Main", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
246
+ (line gb_tot year if region_dataset == "Midwest-Main", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
247
+ (scatter gb_tot year if region_dataset == "Midwest-Main", sort cmissing(n) mcolor(black) msymbol(circle) msize(med))
248
+
249
+ (line gb_tot year if region_dataset == "Northeast-Main", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
250
+ (line gb_tot year if region_dataset == "Northeast-Main", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
251
+ (scatter gb_tot year if region_dataset == "Northeast-Main", sort cmissing(n) mcolor(black) msymbol(diamond) msize(med))
252
+
253
+ (line gb_tot year if region_dataset == "South-Main", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
254
+ (line gb_tot year if region_dataset == "South-Main", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
255
+ (scatter gb_tot year if region_dataset == "South-Main", sort cmissing(n) mcolor(black) msymbol(X) msize(large))
256
+
257
+ (line gb_tot year if region_dataset == "West-Main", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
258
+ (line gb_tot year if region_dataset == "West-Main", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
259
+ (scatter gb_tot year if region_dataset == "West-Main", sort cmissing(n) mcolor(black) msymbol(triangle) msize(med)),
260
+ legend(label(3 "Midwest") label(6 "Northeast") label(9 "South") label(12 "West") order(3 6 9 12) rows(1))
261
+ ytitle("Number of Establishments") xtitle("Year", margin(medium)) xsize(6) ysize(3);
262
+
263
+ graph export "$figures/count_all_est_over_time_usa_byregion_novacay.pdf", replace ;
264
+ #delimit cr
265
+
266
+
267
+ // by region pc
268
+ use "$qjedata/national_gb_region_year.dta", clear
269
+
270
+ #delimit ;
271
+ twoway (line gb_tot_PC year if region_dataset == "Midwest-Main", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
272
+ (line gb_tot_PC year if region_dataset == "Midwest-Main", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
273
+ (scatter gb_tot_PC year if region_dataset == "Midwest-Main", sort cmissing(n) mcolor(black) msymbol(circle) msize(med))
274
+
275
+ (line gb_tot_PC year if region_dataset == "Northeast-Main", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
276
+ (line gb_tot_PC year if region_dataset == "Northeast-Main", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
277
+ (scatter gb_tot_PC year if region_dataset == "Northeast-Main", sort cmissing(n) mcolor(black) msymbol(diamond) msize(med))
278
+
279
+ (line gb_tot_PC year if region_dataset == "South-Main", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
280
+ (line gb_tot_PC year if region_dataset == "South-Main", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
281
+ (scatter gb_tot_PC year if region_dataset == "South-Main", sort cmissing(n) mcolor(black) msymbol(X) msize(large))
282
+
283
+ (line gb_tot_PC year if region_dataset == "West-Main", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
284
+ (line gb_tot_PC year if region_dataset == "West-Main", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
285
+ (scatter gb_tot_PC year if region_dataset == "West-Main", sort cmissing(n) mcolor(black) msymbol(triangle) msize(med)),
286
+ legend(label(3 "Midwest") label(6 "Northeast") label(9 "South") label(12 "West") order(3 6 9 12) rows(1))
287
+ ytitle("# Est. Per 1,000 Black Pop") xtitle("Year", margin(medium)) xsize(6) ysize(3);
288
+
289
+ graph export "$figures/gbpc_all_est_over_time_usa_byregion_novacay.pdf", replace ;
290
+ #delimit cr
291
+
292
+
293
+ ********************************************************************************
294
+ *-------------- FIG 6: Share Est by Region ---------------*
295
+ ********************************************************************************
296
+ capture graph drop *
297
+
298
+ use "$qjedata/national_gb_region_year.dta", clear
299
+
300
+ // Panel (a) - Formal Accommodations
301
+ #delimit ;
302
+ twoway (line shareGBhotel year if region_dataset == "Midwest-Hotels", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
303
+ (line shareGBhotel year if region_dataset == "Midwest-Hotels", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
304
+ (scatter shareGBhotel year if region_dataset == "Midwest-Hotels", sort cmissing(n) mcolor(black) msymbol(circle) msize(med))
305
+
306
+ (line shareGBhotel year if region_dataset == "Northeast-Hotels", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
307
+ (line shareGBhotel year if region_dataset == "Northeast-Hotels", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
308
+ (scatter shareGBhotel year if region_dataset == "Northeast-Hotels", sort cmissing(n) mcolor(black) msymbol(diamond) msize(med))
309
+
310
+ (line shareGBhotel year if region_dataset == "South-Hotels", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
311
+ (line shareGBhotel year if region_dataset == "South-Hotels", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
312
+ (scatter shareGBhotel year if region_dataset == "South-Hotels", sort cmissing(n) mcolor(black) msymbol(X) msize(large))
313
+
314
+ (line shareGBhotel year if region_dataset == "West-Hotels", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
315
+ (line shareGBhotel year if region_dataset == "West-Hotels", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
316
+ (scatter shareGBhotel year if region_dataset == "West-Hotels", sort cmissing(n) mcolor(black) msymbol(triangle) msize(med)),
317
+ legend(label(3 "Midwest") label(6 "Northeast") label(9 "South") label(12 "West") order(3 6 9 12) rows(1))
318
+ ytitle("Share of Formal Accommodations") xtitle("Year", margin(medium)) name(hotelshr) xsize(6) ysize(3);
319
+ #delimit cr
320
+
321
+ graph export "$figures/share_hotel_byregion_novacay.pdf", replace
322
+
323
+
324
+ // Panel (b) - Eating and Drinking Places
325
+ #delimit ;
326
+ twoway (line shareGBeat year if region_dataset == "Midwest-Retail", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
327
+ (line shareGBeat year if region_dataset == "Midwest-Retail", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
328
+ (scatter shareGBeat year if region_dataset == "Midwest-Retail", sort cmissing(n) mcolor(black) msymbol(circle) msize(med))
329
+
330
+ (line shareGBeat year if region_dataset == "Northeast-Retail", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
331
+ (line shareGBeat year if region_dataset == "Northeast-Retail", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
332
+ (scatter shareGBeat year if region_dataset == "Northeast-Retail", sort cmissing(n) mcolor(black) msymbol(diamond) msize(med))
333
+
334
+ (line shareGBeat year if region_dataset == "South-Retail", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
335
+ (line shareGBeat year if region_dataset == "South-Retail", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
336
+ (scatter shareGBeat year if region_dataset == "South-Retail", sort cmissing(n) mcolor(black) msymbol(X) msize(large))
337
+
338
+ (line shareGBeat year if region_dataset == "West-Retail", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
339
+ (line shareGBeat year if region_dataset == "West-Retail", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
340
+ (scatter shareGBeat year if region_dataset == "West-Retail", sort cmissing(n) mcolor(black) msymbol(triangle) msize(med)),
341
+ legend(label(3 "Midwest") label(6 "Northeast") label(9 "South") label(12 "West") order(3 6 9 12) rows(1))
342
+ ytitle("Share of Eating/Drinking") xtitle("Year", margin(medium)) name(eatingshr) xsize(6) ysize(3) ;
343
+ #delimit cr
344
+
345
+ graph export "$figures/share_eating_byregion_novacay.pdf", replace
346
+
347
+ // Panel (c) - Gas stations
348
+ #delimit ;
349
+ twoway (line shareGBgas year if region_dataset == "Midwest-Retail", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
350
+ (line shareGBgas year if region_dataset == "Midwest-Retail", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
351
+ (scatter shareGBgas year if region_dataset == "Midwest-Retail", sort cmissing(n) mcolor(black) msymbol(circle) msize(med))
352
+
353
+ (line shareGBgas year if region_dataset == "Northeast-Retail", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
354
+ (line shareGBgas year if region_dataset == "Northeast-Retail", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
355
+ (scatter shareGBgas year if region_dataset == "Northeast-Retail", sort cmissing(n) mcolor(black) msymbol(diamond) msize(med))
356
+
357
+ (line shareGBgas year if region_dataset == "South-Retail", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
358
+ (line shareGBgas year if region_dataset == "South-Retail", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
359
+ (scatter shareGBgas year if region_dataset == "South-Retail", sort cmissing(n) mcolor(black) msymbol(X) msize(large))
360
+
361
+ (line shareGBgas year if region_dataset == "West-Retail", sort cmissing(n) lpattern(solid) lcolor(black) lwidth(thin))
362
+ (line shareGBgas year if region_dataset == "West-Retail", sort cmissing(y) lpattern(dash) lcolor(black) lwidth(thin))
363
+ (scatter shareGBgas year if region_dataset == "West-Retail", sort cmissing(n) mcolor(black) msymbol(triangle) msize(med)),
364
+ legend(label(3 "Midwest") label(6 "Northeast") label(9 "South") label(12 "West") order(3 6 9 12) rows(1))
365
+ ytitle("Share of Gas Stations") xtitle("Year", margin(medium)) name(gasshr) xsize(6) ysize(3);
366
+ #delimit cr
367
+
368
+ graph export "$figures/share_gas_byregion_novacay.pdf", replace
369
+
370
+
371
+ ********************************************************************************
372
+ *-------------- FIG 7: Correlates of GB Per Cap ---------------*
373
+ ********************************************************************************
374
+
375
+ use "$qjedata/county_gb_correlates_1940.dta", clear
376
+
377
+ keep if dataset == "Main"
378
+
379
+ local varstostd gbpc fracblack postal_b mig_bw_state_b mig_wi_state_b confed_symbol_N lynch_black naacp_chptrs1941 dissimilarity_po isolation_po alpha_po none_b none_w hotel_own_w eating_own_w hotel_own_b eating_own_b lforce_w incwage_w lforce_b incwage_b own_w_1940 own_b_1940 man_estab_1940 pop_b_1940
380
+
381
+ foreach i of local varstostd {
382
+ egen std_`i' = std(`i'), mean(0) std(1)
383
+ }
384
+
385
+ tempfile t1
386
+
387
+ parmby "reg std_gbpc std_pop_b_1940, r", lab saving(`"`t1'"',replace) idn(1) ids(total) level(95)
388
+
389
+ local varlist fracblack postal_b mig_bw_state_b mig_wi_state_b confed_symbol_N lynch_black naacp_chptrs1941 dissimilarity_po isolation_po alpha_po none_b none_w hotel_own_w eating_own_w hotel_own_b eating_own_b lforce_w incwage_w lforce_b incwage_b own_w_1940 own_b_1940 man_estab_1940
390
+
391
+ local j = 1
392
+ foreach v of local varlist {
393
+ local j = `j' + 1
394
+ tempfile t`j'
395
+ parmby "reg std_gbpc std_`v' std_pop_b_1940, r", lab saving(`"`t`j''"',replace) idn(`j') ids(total) level(95)
396
+ }
397
+
398
+ drop _all
399
+
400
+ forvalues i=1(1)24 {
401
+ append using `"`t`i''"'
402
+ }
403
+
404
+ drop if parm == "_cons"
405
+ drop if parm == "std_pop_b_1940" & idn != 1
406
+
407
+ gen ordervar = .
408
+
409
+ // baseline corr bw black pop and gbpc
410
+ replace ordervar = 31 if parm == "std_fracblack"
411
+ replace ordervar = 30 if parm == "std_pop_b_1940"
412
+
413
+ // mail and migration
414
+ replace ordervar = 28 if parm == "std_postal_b"
415
+ replace ordervar = 27 if parm == "std_mig_bw_state_b"
416
+ replace ordervar = 26 if parm == "std_mig_wi_state_b"
417
+
418
+ // other discriminatory indices
419
+ replace ordervar = 24 if parm == "std_confed_symbol_N"
420
+ replace ordervar = 23 if parm == "std_lynch_black"
421
+ replace ordervar = 22 if parm == "std_naacp_chptrs1941"
422
+
423
+ // other segregation
424
+ replace ordervar = 20 if parm == "std_dissimilarity_po"
425
+ replace ordervar = 19 if parm == "std_isolation_po"
426
+ replace ordervar = 18 if parm == "std_alpha_po"
427
+
428
+ // education (black and white)
429
+ replace ordervar = 16 if parm == "std_none_b"
430
+ replace ordervar = 15 if parm == "std_none_w"
431
+
432
+ // hotel owners and restaurant owners
433
+ replace ordervar = 13 if parm == "std_hotel_own_w"
434
+ replace ordervar = 12 if parm == "std_hotel_own_b"
435
+ replace ordervar = 11 if parm == "std_eating_own_w"
436
+ replace ordervar = 10 if parm == "std_eating_own_b"
437
+
438
+ // affluence
439
+ replace ordervar = 8 if parm == "std_lforce_w"
440
+ replace ordervar = 7 if parm == "std_incwage_w"
441
+ replace ordervar = 6 if parm == "std_own_w_1940"
442
+ replace ordervar = 5 if parm == "std_lforce_b"
443
+ replace ordervar = 4 if parm == "std_incwage_b"
444
+ replace ordervar = 3 if parm == "std_own_b_1940"
445
+
446
+ // manufacturing
447
+ replace ordervar = 1 if parm == "std_man_estab_1940"
448
+
449
+
450
+ #delimit ;
451
+ label define coefnames
452
+ 31 `"Share Black"'
453
+ 30 `"Black Population"'
454
+ 29 `" "'
455
+ 28 `"# Black Postal Workers"'
456
+ 27 `"% Black Migrants Between States"'
457
+ 26 `"% Black Migrants Within States"'
458
+ 25 `" "'
459
+ 24 `"# Confederate Symbols"'
460
+ 23 `"# Black Lynchings"'
461
+ 22 `"# NAACP Chapters (1941)"'
462
+ 21 `" "'
463
+ 20 `"Dissimilarity Index"'
464
+ 19 `"Isolation Index"'
465
+ 18 `"Logan-Parman Index"'
466
+ 17 `" "'
467
+ 16 `"% Black With No Education"'
468
+ 15 `"% White With No Education"'
469
+ 14 `" "'
470
+ 13 `"# White Hotel Owners"'
471
+ 12 `"# White Restaurant Owners"'
472
+ 11 `"# Black Hotel Owners"'
473
+ 10 `"# Black Restaurant Owners"'
474
+ 9 `" "'
475
+ 8 `"% White in Labor Force"'
476
+ 7 `"White Wage/Salary Income"'
477
+ 6 `"% White Homeowners"'
478
+ 5 `"% Black in Labor Force"'
479
+ 4 `"Black Wage/Salary Income"'
480
+ 3 `"% Black Homeowners"'
481
+ 2 `" "'
482
+ 1 `"Manufacturing Establishments"'
483
+ 0 `" "'
484
+ ;
485
+ #delimit cr
486
+
487
+ label values ordervar coefnames
488
+
489
+ gen altmin95 = min95
490
+ gen altmax95 = max95
491
+
492
+ #delimit ;
493
+ twoway (scatter ordervar estimate, sort msymbol(square) mcolor(black) msize(small))
494
+ (rcap altmin95 altmax95 ordervar, sort lcolor(black) horizontal),
495
+ graphregion(color(white)) xline(0)
496
+ legend(off)
497
+ xlabel(-.2(.1).2)
498
+ ylabel(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,valuelabel labsize(vsmall) angle(0) grid)
499
+ ytitle("") xtitle("Estimate", margin(medium) size(small))
500
+ yline(0, lcolor(gs8) lpattern(dash))
501
+ yline(2, lcolor(gs8) lpattern(dash))
502
+ yline(9, lcolor(gs8) lpattern(dash))
503
+ yline(14, lcolor(gs8) lpattern(dash))
504
+ yline(17, lcolor(gs8) lpattern(dash))
505
+ yline(21, lcolor(gs8) lpattern(dash))
506
+ yline(25, lcolor(gs8) lpattern(dash))
507
+ yline(29, lcolor(gs8) lpattern(dash))
508
+ yline(32, lcolor(gs8) lpattern(dash))
509
+ xsize(8) ysize(8);
510
+ #delimit cr
511
+
512
+ graph export "$figures/gbpc_correlates_Main.pdf", replace
513
+
514
+ ********************************************************************************
515
+ *-------------- FIG 9: Event Study ---------------*
516
+ ********************************************************************************
517
+
518
+ use "$qjedata/county_gb_main.dta", clear
519
+
520
+ tempfile t1
521
+
522
+ areg a_gb_tot taumin3_a_killed_w taumin2_a_killed_w taupos1_a_killed_w taupos2_a_killed_w taupos3_a_killed_w taupos4_a_killed_w taupos5_a_killed_w taupos6_a_killed_w taupos7_a_killed_w taupos8_a_killed_w taupos9_a_killed_w i.year , absorb(county_code) cluster(county_code)
523
+ parmest, label list(parm label estimate min* max* p) saving(`"`t1'"', replace)
524
+
525
+ use `t1', clear
526
+
527
+ gen year = 1939 if parm == "taumin3_a_killed_w"
528
+ replace year = 1940 if parm == "taumin2_a_killed_w"
529
+ replace year = 1947 if parm == "taupos1_a_killed_w"
530
+ replace year = 1948 if parm == "taupos2_a_killed_w"
531
+ replace year = 1949 if parm == "taupos3_a_killed_w"
532
+ replace year = 1950 if parm == "taupos4_a_killed_w"
533
+ replace year = 1951 if parm == "taupos5_a_killed_w"
534
+ replace year = 1952 if parm == "taupos6_a_killed_w"
535
+ replace year = 1953 if parm == "taupos7_a_killed_w"
536
+ replace year = 1954 if parm == "taupos8_a_killed_w"
537
+ replace year = 1955 if parm == "taupos9_a_killed_w"
538
+
539
+ keep if year != .
540
+
541
+ set obs 12
542
+ replace year = 1941 in 12
543
+ replace estimate = 0 in 12
544
+
545
+ #delimit ;
546
+ twoway (scatter estimate year, sort mcolor(black) msymbol(square) msize(small))
547
+ (rcap min95 max95 year, sort lcolor(black)),
548
+ yline(0) xline(1941) xline(1942 1943 1944 1945 1946, lwidth(9) lc(gs12))
549
+ legend(off) ytitle("Estimate") xtitle("Year");
550
+
551
+ graph export "$figures/a_killed_white_event_gbtot.pdf", replace ;
552
+ #delimit cr
553
+
554
+ ********************************************************************************
555
+ *-------------- FIG 10: Trim Casualties ---------------*
556
+ ********************************************************************************
557
+
558
+ use "$qjedata/county_gb_main.dta", clear
559
+
560
+ // Not reported in paper, also robust to using qreg at median
561
+ areg a_killed_w_after i.year, absorb(county_code)
562
+ predict a_killed_w_after_resid, resid
563
+ areg a_gb_tot i.year, absorb(county_code)
564
+ predict a_gbtot_resid, resid
565
+ qreg a_gbtot_resid a_killed_w_after_resid, q(50)
566
+
567
+ xtile ww2dec = a_killed_w if year == 1940, nq(100)
568
+ bysort county_code: egen a_killed_w_decile = max(ww2dec)
569
+
570
+ forvalues i = 0(1)48 {
571
+ tempfile t`i'
572
+ }
573
+
574
+ parmby "areg a_gb_tot a_killed_w_after i.year, absorb(county_code) cluster(county_code)", lab saving(`"`t0'"',replace) idn(0) ids(A) level(95)
575
+
576
+ forvalues i = 1(1)48 {
577
+ local j = 101-`i'
578
+ parmby "areg a_gb_tot a_killed_w_after i.year if a_killed_w_decile > `i' & a_killed_w_decile < `j', absorb(county_code) cluster(county_code)", lab saving(`"`t`i''"',replace) idn(`i') ids(A) level(95)
579
+ }
580
+
581
+ use `t0', clear
582
+ forvalues i=1(1)48 {
583
+ append using `"`t`i''"'
584
+ }
585
+
586
+ keep if parm == "a_killed_w_after"
587
+
588
+ #delimit ;
589
+ twoway (scatter estimate idnum if idnum == 0, sort mcolor(red) msymbol(square))
590
+ (rcap min95 max95 idnum if idnum == 0, sort lcolor(red))
591
+ (scatter estimate idnum if idnum > 0 & idnum <= 25, sort mcolor(black) msymbol(square))
592
+ (rcap min95 max95 idnum if idnum > 0 & idnum <= 25, sort lcolor(black)),
593
+ yline(0) ytitle("Estimate")
594
+ xtitle("Excluded Top and Bottom Percentiles", margin(medium)) legend(off) ;
595
+
596
+ graph export "$figures/a_killed_w__gbtot_by_excluded_ptiles.pdf", replace ;
597
+ #delimit cr
598
+
599
+
600
+ ********************************************************************************
601
+ *-------------- TAB 2: Baseline Descriptives ---------------*
602
+ ********************************************************************************
603
+
604
+ use "$qjedata/county_gb_main.dta", clear
605
+
606
+ global gbs gb_tot num_est_other num_est_informal num_est_hotel num_est_gas num_est_eating num_est_barber
607
+ global sumstats killed_b enlist_b pop_b_1940 killed_w enlist_w pop_w_1940 shr_farmland postal_b mig_bw_state_b mig_wi_state_b confed_symbol_N lynch_black naacp_chptrs1941 dissimilarity_po isolation_po alpha_po none_b educ_lo_1940_b educ_hs_1940_b none_w educ_lo_1940_w educ_hs_1940_w lforce_b incwage_b own_b_1940 lforce_w incwage_w own_w_1940
608
+
609
+ estpost sum $gbs $sumstats if gb_est == 1 & year ==1940, det
610
+ est store A
611
+
612
+ estpost sum $gbs $sumstats if gb_est == 0 & year ==1940, det
613
+ est store B
614
+
615
+ #delimit ;
616
+ esttab A B using "$tables/sumstat_noGBvsGB.tex", replace cells("mean(fmt(%9.2g)) sd(fmt(%9.2g))")label
617
+ substitute(% \%)
618
+ fragment nonumber noobs
619
+ stats(N , fmt(%9.0fc) label("Observations")) star(* .1 ** .05 *** .01)
620
+ keep(
621
+ gb_tot num_est_other num_est_informal num_est_hotel num_est_gas num_est_eating num_est_barber
622
+ killed_b enlist_b pop_b_1940 killed_w enlist_w pop_w_1940
623
+ shr_farmland postal_b mig_bw_state_b mig_wi_state_b
624
+ confed_symbol_N lynch_black naacp_chptrs1941 dissimilarity_po isolation_po alpha_po
625
+ none_b educ_lo_1940_b educ_hs_1940_b none_w educ_lo_1940_w educ_hs_1940_w
626
+ lforce_b incwage_b own_b_1940 lforce_w incwage_w own_w_1940
627
+ )
628
+ order(
629
+ gb_tot num_est_informal num_est_hotel num_est_gas num_est_eating num_est_barber num_est_other
630
+ killed_b enlist_b pop_b_1940 killed_w enlist_w pop_w_1940
631
+ shr_farmland postal_b mig_bw_state_b mig_wi_state_b
632
+ confed_symbol_N lynch_black naacp_chptrs1941 dissimilarity_po isolation_po alpha_po
633
+ none_b educ_lo_1940_b educ_hs_1940_b none_w educ_lo_1940_w educ_hs_1940_w
634
+ lforce_b incwage_b own_b_1940 lforce_w incwage_w own_w_1940
635
+ )
636
+ mtitle("Listed" "Never Listed")
637
+ refcat(gb_tot "\midrule \textbf{\emph{Green Book Listings}}"
638
+ killed_b "\midrule \textbf{\emph{World War II}}"
639
+ none_b "\midrule \textbf{\emph{Education, Employment, and Income}}"
640
+ confed_symbol_N "\midrule \textbf{\emph{Residential Segregation \& Discrimination}}"
641
+ shr_farmland "\midrule \textbf{\emph{Other Demographics}}", nolabel) ;
642
+ #delimit cr
643
+
644
+ estimates clear
645
+
646
+
647
+ ********************************************************************************
648
+ *-------------- TAB 3: Diff in Diff Results ---------------*
649
+ ********************************************************************************
650
+
651
+ use "$qjedata/county_gb_main.dta", clear
652
+
653
+ #delimit ;
654
+ global countycontrols
655
+
656
+ shr_farmland
657
+
658
+ pop_b_1940
659
+ pop_w_1940
660
+
661
+ postal_b
662
+ mig_bw_state_b
663
+ mig_wi_state_b
664
+
665
+ confed_symbol_N
666
+ lynch_black
667
+ naacp_chptrs1941
668
+
669
+ dissimilarity_po
670
+ isolation_po
671
+ alpha_po
672
+
673
+ none_b
674
+ educ_lo_1940_b
675
+ educ_hs_1940_b
676
+ none_w
677
+ educ_lo_1940_w
678
+ educ_hs_1940_w
679
+
680
+ hotel_own_w
681
+ hotel_own_b
682
+ eating_own_w
683
+ eating_own_b
684
+
685
+ lforce_w
686
+ lforce_b
687
+ incwage_w
688
+ incwage_b
689
+ own_w_1940
690
+ own_b_1940
691
+
692
+ man_estab_1940
693
+ man_worker_1940
694
+ man_wages_1940
695
+ man_output_1940
696
+ man_vadd_1940
697
+
698
+ warsup_com_1940
699
+ warsup_oth_1940
700
+ warfac_ind_1940
701
+ warfac_mil_1940
702
+ war_total_1940;
703
+
704
+ #delimit cr
705
+
706
+ #delimit ;
707
+ global countycontrolsmissing
708
+
709
+ shr_farmland_miss
710
+
711
+ pop_b_1940_miss
712
+ pop_w_1940_miss
713
+
714
+ mig_bw_state_b_miss
715
+ mig_wi_state_b_miss
716
+
717
+ confed_symbol_N_miss
718
+ lynch_black_miss
719
+
720
+ dissimilarity_po_miss
721
+ isolation_po_miss
722
+ alpha_po_miss
723
+
724
+ none_b_miss
725
+ educ_lo_1940_b_miss
726
+ educ_hs_1940_b_miss
727
+ none_w_miss
728
+ educ_lo_1940_w_miss
729
+ educ_hs_1940_w_miss
730
+
731
+ own_w_1940_miss
732
+ own_b_1940_miss
733
+
734
+ man_estab_1940_miss
735
+ man_worker_1940_miss
736
+ man_wages_1940_miss
737
+ man_output_1940_miss
738
+ man_vadd_1940_miss
739
+
740
+ war_total_1940_miss
741
+ warsup_com_1940_miss
742
+ warsup_oth_1940_miss
743
+ warfac_ind_1940_miss
744
+ warfac_mil_1940_miss;
745
+ #delimit cr
746
+
747
+ foreach a of global countycontrols {
748
+ gen asinh_`a' = asinh(`a')
749
+ }
750
+
751
+ foreach a of global countycontrols {
752
+ gen postint_`a' = asinh_`a'*after
753
+ }
754
+
755
+ foreach a of global countycontrolsmissing {
756
+ gen mis_`a' = `a'*after
757
+ }
758
+
759
+ gen misscontrols = 0
760
+ foreach a of global countycontrolsmissing {
761
+ replace misscontrols = 1 if `a' == 1
762
+ }
763
+
764
+ // PANEL A: FULL SAMPLE
765
+ estimates clear
766
+ *col 1 reg: diff in diff no fe
767
+ qui: eststo: xi: reg a_gb_tot a_killed_w a_killed_w_after after , cluster(county_code)
768
+ *col 2 reg: state FE
769
+ qui: eststo: xi: reg a_gb_tot a_killed_w a_killed_w_after after i.stateid , cluster(county_code)
770
+ *col 3 reg: county controls, year FE
771
+ qui: eststo: xi: reg a_gb_tot a_killed_w a_killed_w_after postint_* mis_* asinh_* $countycontrolsmissing i.year i.stateid , cluster(county_code)
772
+ *col 4: reg: county FE, year FE
773
+ qui: eststo: xi: areg a_gb_tot a_killed_w_after i.year , absorb(county_code) cluster(county_code)
774
+ *col 5: reg: stateXyear FE, county FE
775
+ qui: eststo: xi: areg a_gb_tot a_killed_w_after i.stateid*i.year , absorb(county_code) cluster(county_code)
776
+ *col 6 reg: county-level linear time trends, county FE, year FE
777
+ // qui: eststo: xi: areg a_gb_tot a_killed_w_after i.year c.year##i.county_code , absorb(county_code) cluster(county_code)
778
+
779
+ #delimit ;
780
+ esttab using "$tables/a_killed_white_did_gbtot.tex", replace label title("Effects of White Casualties on Number of Establishments")
781
+ star(* 0.10 ** 0.05 *** 0.01) se ar2 b(a3) se(3)
782
+ scalar("N_clust \# clusters") nomtitles keep(a_killed_w_after)
783
+ varlabel(a_killed_w_after "Asinh(\# White Deaths) $\times$ Post-WW2") ;
784
+ estimates clear ;
785
+ #delimit cr
786
+
787
+ // PANEL B: BY INDUSTRY
788
+ estimates clear
789
+ *col 1 reg: Barber\beauty parlors: year FE and county FE
790
+ eststo barber: areg a_num_est_barber a_killed_w_after i.year , absorb(county_code) cluster(county_code)
791
+ *col 2 reg: Eating and drinking: year FE and county FE
792
+ eststo eating: areg a_num_est_eating a_killed_w_after i.year , absorb(county_code) cluster(county_code)
793
+ *col 3 reg: Service stations: year FE and county FE
794
+ eststo gas: areg a_num_est_gas a_killed_w_after i.year , absorb(county_code) cluster(county_code)
795
+ *col 4 reg: Formal accommodations: year FE and county FE
796
+ eststo hotel: areg a_num_est_hotel a_killed_w_after i.year , absorb(county_code) cluster(county_code)
797
+ *col 5 reg: Informal accommodations: year FE and county FE
798
+ eststo informal: areg a_num_est_informal a_killed_w_after i.year , absorb(county_code) cluster(county_code)
799
+ *col 6 reg: Other establishments: year FE and county FE
800
+ eststo other: areg a_num_est_other a_killed_w_after i.year , absorb(county_code) cluster(county_code)
801
+
802
+ #delimit ;
803
+ esttab using "$tables/a_killed_white_did_by_industry.tex", replace label title("Effects of White Casualties on Number of Establishments")
804
+ star(* 0.10 ** 0.05 *** 0.01) se ar2 b(a3) se(3) scalar(N_clust)
805
+ addnotes("Standard errors clustered by county in parentheses.
806
+ Casualties are measured in units of 100.
807
+ All columns include county and year fixed effects.")
808
+ mtitles keep(a_killed_w_after)
809
+ varlabel(a_killed_w_after
810
+ "Treatment") ;
811
+ estimates clear ;
812
+ #delimit cr
813
+
814
+ // PANEL C: SHARES
815
+ use "$qjedata/county_gb_hotels_panel.dta", clear
816
+
817
+ eststo: areg a_shareGBhotel_i2 a_killed_w_after i.year, absorb(county_code) cluster(county_code)
818
+ eststo: xi: areg a_shareGBhotel_i2 a_killed_w_after i.stateid*i.year, absorb(county_code) cluster(county_code)
819
+
820
+ use "$qjedata/county_gb_retail_panel.dta", clear
821
+
822
+ eststo: areg a_shareGBeat_i2 a_killed_w_after i.year, absorb(county_code) cluster(county_code)
823
+ eststo: xi: areg a_shareGBeat_i2 a_killed_w_after i.stateid*i.year, absorb(county_code) cluster(county_code)
824
+
825
+ eststo: areg a_shareGBgas_i2 a_killed_w_after i.year, absorb(county_code) cluster(county_code)
826
+ eststo: xi: areg a_shareGBgas_i2 a_killed_w_after i.stateid*i.year, absorb(county_code) cluster(county_code)
827
+
828
+ #delimit ;
829
+ esttab using "$tables/a_killed_white_did_shares.tex", replace label title("Effects of White Casualties on Share of GB Establishments")
830
+ star(* 0.10 ** 0.05 *** 0.01) se ar2 b(a3) se(3) scalar(N_clust)
831
+ addnotes("Standard errors clustered by county in parentheses.
832
+ Casualties are measured in units of 100.
833
+ All columns include county and year fixed effects.")
834
+ mtitles keep(a_killed_w_after)
835
+ varlabel(a_killed_w_after
836
+ "Treatment") ;
837
+ estimates clear ;
838
+ #delimit cr
839
+
840
+
841
+ ********************************************************************************
842
+ *-------------- TAB 4: IV Results ---------------*
843
+ ********************************************************************************
844
+
845
+ estimates clear
846
+
847
+ use "$qjedata/county_gb_hotels.dta", clear
848
+
849
+ gen d_gbhotel4050 = (gbhotel1950 - gbhotel1940)/numCOBhotel1940
850
+ gen d_blackshr4050 = (pop_b_1950-pop_b_1940)/pop1940
851
+
852
+ foreach v in d_gbhotel4050 d_blackshr4050 killed_w bartikshock4050 {
853
+ gen a_`v' = asinh(`v')
854
+ }
855
+
856
+ // HOTELS
857
+
858
+ ***
859
+
860
+ // ols
861
+ eststo main_ols_hotel_wwii: reg a_d_gbhotel4050 a_d_blackshr4050 i.stateid if num_hotel_CoBab1935 != ., first
862
+ eststo main_ols_hotel_bartik: reg a_d_gbhotel4050 a_d_blackshr4050 i.stateid if num_hotel_CoBab1935 != . & us_region != "South", first
863
+
864
+ // iv
865
+ eststo main_iv_hotel_wwii: ivreg2 a_d_gbhotel4050 (a_d_blackshr4050 = a_killed_w) i.stateid if num_hotel_CoBab1935 != ., first
866
+ eststo main_iv_hotel_bartik: ivreg2 a_d_gbhotel4050 (a_d_blackshr4050 = a_bartikshock4050) i.stateid if num_hotel_CoBab1935 != . & us_region != "South", first
867
+
868
+ // reduced form
869
+ eststo rf_ols_hotel_wwii: reg a_d_gbhotel4050 a_killed_w i.stateid if num_hotel_CoBab1935 != ., first
870
+ eststo rf_ols_hotel_bartik: reg a_d_gbhotel4050 a_bartikshock4050 i.stateid if num_hotel_CoBab1935 != . & us_region != "South", first
871
+
872
+ // first stage
873
+ eststo fs_ols_hotel_wwii: reg a_d_blackshr4050 a_killed_w i.stateid if num_hotel_CoBab1935 != . & a_d_gbhotel4050 != ., first
874
+ eststo fs_ols_hotel_bartik: reg a_d_blackshr4050 a_bartikshock4050 i.stateid if num_hotel_CoBab1935 != . & us_region != "South" & a_d_gbhotel4050 != ., first
875
+
876
+ ***
877
+
878
+ use "$qjedata/county_gb_retail.dta", clear
879
+
880
+ gen d_gbeat4050 = (gbeat1950 - gbeat1940)/numCOBeat1940
881
+ gen d_gbgas4050 = (gbgas1950 - gbgas1940)/numCOBgas1940
882
+ gen d_blackshr4050 = (pop_b_1950-pop_b_1940)/pop1940
883
+
884
+ foreach v in d_gbeat4050 d_gbgas4050 d_blackshr4050 killed_w bartikshock4050 {
885
+ gen a_`v' = asinh(`v')
886
+ }
887
+
888
+ ***
889
+
890
+ // EATING AND DRINKING
891
+
892
+ //ols
893
+ eststo main_ols_eat_wwii: reg a_d_gbeat4050 a_d_blackshr4050 i.stateid if num_eat_CoB1935 != ., first
894
+ eststo main_ols_eat_bartik: reg a_d_gbeat4050 a_d_blackshr4050 i.stateid if num_eat_CoB1935 != . & us_region != "South", first
895
+
896
+ // iv
897
+ eststo main_iv_eat_wwii: ivreg2 a_d_gbeat4050 (a_d_blackshr4050 = a_killed_w) i.stateid if num_eat_CoB1935 != ., first
898
+ eststo main_iv_eat_bartik: ivreg2 a_d_gbeat4050 (a_d_blackshr4050 = a_bartikshock4050) i.stateid if num_eat_CoB1935 != . & us_region != "South", first
899
+
900
+ // reduced form
901
+ eststo rf_ols_eat_wwii: reg a_d_gbeat4050 a_killed_w i.stateid if num_eat_CoB1935 != ., first
902
+ eststo rf_ols_eat_bartik: reg a_d_gbeat4050 a_bartikshock4050 i.stateid if num_eat_CoB1935 != . & us_region != "South", first
903
+
904
+ // first stage
905
+ eststo fs_ols_eat_wwii: reg a_d_blackshr4050 a_killed_w i.stateid if num_eat_CoB1935 != . & a_d_gbeat4050 != ., first
906
+ eststo fs_ols_eat_bartik: reg a_d_blackshr4050 a_bartikshock4050 i.stateid if num_eat_CoB1935 != . & us_region != "South" & a_d_gbeat4050 != ., first
907
+
908
+ ***
909
+
910
+ // GAS STATIONS
911
+
912
+ // ols
913
+ eststo main_ols_gas_wwii: reg a_d_gbgas4050 a_d_blackshr4050 i.stateid if num_gas_CoB1935 != ., first
914
+ eststo main_ols_gas_bartik: reg a_d_gbgas4050 a_d_blackshr4050 i.stateid if num_gas_CoB1935 != . & us_region != "South", first
915
+
916
+ // iv
917
+ eststo main_iv_gas_wwii: ivreg2 a_d_gbgas4050 (a_d_blackshr4050 = a_killed_w) i.stateid if num_gas_CoB1935 != ., first
918
+ eststo main_iv_gas_bartik: ivreg2 a_d_gbgas4050 (a_d_blackshr4050 = a_bartikshock4050) i.stateid if num_gas_CoB1935 != . & us_region != "South", first
919
+
920
+ // reduced form
921
+ eststo rf_ols_gas_wwii: reg a_d_gbgas4050 a_killed_w i.stateid if num_gas_CoB1935 != ., first
922
+ eststo rf_ols_gas_bartik: reg a_d_gbgas4050 a_bartikshock4050 i.stateid if num_gas_CoB1935 != . & us_region != "South", first
923
+
924
+ // first stage
925
+ eststo fs_ols_gas_wwii: reg a_d_blackshr4050 a_killed_w i.stateid if num_gas_CoB1935 != . & a_d_gbgas4050 != .,first
926
+ eststo fs_ols_gas_bartik: reg a_d_blackshr4050 a_bartikshock4050 i.stateid if num_gas_CoB1935 != . & us_region != "South" & a_d_gbgas4050 != ., first
927
+
928
+ ***
929
+
930
+ // MAIN IV TABLE
931
+
932
+ #delimit ;
933
+ esttab main_ols_hotel_wwii main_ols_eat_wwii main_ols_gas_wwii main_ols_hotel_bartik main_ols_eat_bartik main_ols_gas_bartik using "$tables/iv_statefe_full.tex", replace label title("OLS results for the change in the share of non-discriminatory hotels")
934
+ star(* 0.10 ** 0.05 *** 0.01) scalars(widstat) se ar2 b(a3) se(3) addnotes("Standard errors in parentheses clustered by state.")
935
+ keep(a_d_blackshr*);
936
+
937
+ esttab fs_ols_hotel_wwii fs_ols_eat_wwii fs_ols_gas_wwii fs_ols_hotel_bartik fs_ols_eat_bartik fs_ols_gas_bartik using "$tables/iv_statefe_full.tex", append label title("First Stage results for the change in the share of non-discriminatory hotels")
938
+ star(* 0.10 ** 0.05 *** 0.01) scalars(widstat) se ar2 b(a3) se(3) addnotes("Standard errors in parentheses clustered by state.")
939
+ keep(a_killed_w a_bartikshock4050);
940
+
941
+ esttab rf_ols_hotel_wwii rf_ols_eat_wwii rf_ols_gas_wwii rf_ols_hotel_bartik rf_ols_eat_bartik rf_ols_gas_bartik using "$tables/iv_statefe_full.tex", append label title("Reduced Form results for the change in the share of non-discriminatory hotels")
942
+ star(* 0.10 ** 0.05 *** 0.01) scalars(widstat) se ar2 b(a3) se(3) addnotes("Standard errors in parentheses clustered by state.")
943
+ keep(a_killed_w a_bartikshock4050);
944
+
945
+ esttab main_iv_hotel_wwii main_iv_eat_wwii main_iv_gas_wwii main_iv_hotel_bartik main_iv_eat_bartik main_iv_gas_bartik using "$tables/iv_statefe_full.tex", append label title("IV results for the change in the share of non-discriminatory hotels")
946
+ star(* 0.10 ** 0.05 *** 0.01) scalars(widstat) se ar2 b(a3) se(3) addnotes("Standard errors in parentheses clustered by state.")
947
+ keep(a_d_blackshr*);
948
+ #delimit cr
949
+
950
+
951
+ ********************************************************************************
952
+
953
+
954
+
955
+
956
+ ********************************************************************************
957
+ ********************************************************************************
958
+ **************************** SECTION 2: APPENDIX *******************************
959
+ ********************************************************************************
960
+ ********************************************************************************
961
+
962
+
963
+ ********************************************************************************
964
+ *-------------- FIG 1: Frequency by Industry ---------------*
965
+ ********************************************************************************
966
+
967
+ use "$qjedata/national_gb_freq_ind.dta", clear
968
+
969
+ #delimit ;
970
+ graph hbar (sum) num_est, over(industry, sort(ordervar)) ytitle("")
971
+ intensity(*0.5)
972
+ bar(1, color(midblue))
973
+ bar(2, color(midblue))
974
+ bar(3, color(midblue))
975
+ bar(4, color(midblue))
976
+ bar(5, color(midblue));
977
+ #delimit cr
978
+
979
+ graph export "$figures/freq_by_type_novacay.pdf", replace
980
+
981
+
982
+ ********************************************************************************
983
+ *-------------- FIG 2: Green Books vs. WBBD (City-level) ---------------*
984
+ ********************************************************************************
985
+
986
+ capture graph drop *
987
+
988
+ ***
989
+ // gb vs. wbbd
990
+ use "$qjedata/city_gb_wbbd.dta", clear
991
+
992
+ #delimit ;
993
+ twoway (scatter num_gb formal_wb [aweight = invweightsize], sort
994
+ mcolor(black%20) mlcolor(black%100) msize(small))
995
+ (scatter num_gb formal_wb, sort
996
+ mcolor(black) msize(tiny))
997
+ (line num_gb num_gb2, sort lcolor(black) lwidth(medthin) lpattern(dash)),
998
+ xtitle("Number in Wisconsin Black Business Directory", margin(medium)) ytitle("Number in Green Books")
999
+ legend(off) text(28 32 "45-degree line", place(e) size(.3cm)) ;
1000
+
1001
+ graph export "$figures/formalGB_vs_blackWBD_45deg_novacay_citylevel_weighted.pdf", replace ;
1002
+ #delimit cr
1003
+
1004
+
1005
+ ********************************************************************************
1006
+ *----------- FIG 3: Green Books vs. Seg/Anti-Seg laws (no outliers) -----------*
1007
+ ********************************************************************************
1008
+
1009
+ capture graph drop *
1010
+
1011
+ use "$qjedata/state_gb_paulimurray.dta", clear
1012
+
1013
+ qui reg gb_tot pop_b_1950
1014
+ predict double resid_gb, residuals
1015
+
1016
+ qui reg numdisc pop_b_1950
1017
+ predict double resid_disc, residuals
1018
+
1019
+ qui reg numantidisc pop_b_1950
1020
+ predict double resid_antidisc, residuals
1021
+
1022
+ // Use leverage versus squared residual plot to identify outliers
1023
+ qui reg resid_gb resid_disc
1024
+ // lvr2plot, mlabel(state_abv)
1025
+ qui reg resid_gb resid_antidisc
1026
+ // lvr2plot, mlabel(state_abv)
1027
+
1028
+ #delimit ;
1029
+ // APPENDIX: Discrimination Laws excl HighLev (NY, VA, OK)
1030
+ twoway (scatter resid_gb resid_disc if year == 1950 & !inlist(state_abv, "NY", "VA", "OK"), sort mlabel(state_abv)
1031
+ mlabcolor(black) mcolor(black%50) mlcolor(black%50) msize(tiny))
1032
+ (lfit resid_gb resid_disc if year == 1950 & !inlist(state_abv, "NY", "VA", "OK"), sort lcolor(black) lwidth(medthin)),
1033
+ xtitle("Residualized Number of Discrimination Laws", margin(medium)) ytitle("Residualized Number of Green Book Estabs.")
1034
+ name(discnoOut) legend(off) ;
1035
+
1036
+ graph export "$figures/pauli_murray_residual_gb_vs_disc_noOutlier_novacay.pdf", replace ;
1037
+
1038
+ // APPENDIX: Anti-Discrimination Laws excl HighLev (NY, IL, NJ)
1039
+ twoway (scatter resid_gb resid_antidisc if year == 1950 & !inlist(state_abv, "NY" , "IL", "NJ"), sort mlabel(state_abv)
1040
+ mlabcolor(black) mcolor(black%50) mlcolor(black%50) msize(tiny))
1041
+ (lfit resid_gb resid_antidisc if year == 1950 & !inlist(state_abv, "NY", "IL", "NJ"), sort lcolor(black) lwidth(medthin)),
1042
+ xtitle("Residualized Number of Anti-Discrimination Laws", margin(medium)) ytitle("Residualized Number of Green Book Estabs.")
1043
+ name(antidiscnoOut) legend(off) ;
1044
+
1045
+ graph export "$figures/pauli_murray_residual_gb_vs_antidisc_noOutlier_novacay.pdf", replace ;
1046
+ #delimit cr
1047
+
1048
+ graph combine discnoOut antidiscnoOut, scheme(s1color) ycommon xcommon
1049
+
1050
+ graph export "$figures/pauli_murray_residuals_noOutlier_novacay.pdf", replace
1051
+
1052
+ ********************************************************************************
1053
+ *-------------- FIG 4: Correlates of Est Shares for Hotels ---------------*
1054
+ ********************************************************************************
1055
+
1056
+ use "$qjedata/county_gb_correlates_1940.dta", clear
1057
+
1058
+ keep if dataset == "Hotels" // Only counties in CoB - accounts for counties jointly reported
1059
+
1060
+ local varstostd fracblack postal_b mig_bw_state_b mig_wi_state_b confed_symbol_N lynch_black naacp_chptrs1941 dissimilarity_po isolation_po alpha_po none_b none_w hotel_own_w eating_own_w hotel_own_b eating_own_b lforce_w incwage_w lforce_b incwage_b own_w_1940 own_b_1940 man_estab_1940 shareGBhotel pop_b_1940
1061
+
1062
+
1063
+ foreach i of local varstostd {
1064
+ egen std_`i' = std(`i'), mean(0) std(1)
1065
+ }
1066
+
1067
+ tempfile t1
1068
+
1069
+ parmby "reg std_shareGBhotel std_pop_b_1940, r", lab saving(`"`t1'"',replace) idn(1) ids(total) level(95)
1070
+
1071
+ local varlist fracblack postal_b mig_bw_state mig_wi_state confed_symbol lynch_black naacp_chptrs1941 dissimilarity isolation alpha none_b none_w hotel_own_w eating_own_w hotel_own_b eating_own_b lforce_w incwage_w lforce_b incwage_b own_w_1940 own_b_1940 man_estab_1940
1072
+
1073
+ local j = 1
1074
+ foreach v of local varlist {
1075
+ local j = `j' + 1
1076
+ tempfile t`j'
1077
+ parmby "reg std_shareGBhotel std_`v' std_pop_b_1940, r", lab saving(`"`t`j''"',replace) idn(`j') ids(total) level(95)
1078
+ }
1079
+
1080
+ drop _all
1081
+
1082
+ forvalues i=1(1)24 {
1083
+ append using `"`t`i''"'
1084
+ }
1085
+
1086
+ drop if parm == "_cons"
1087
+ drop if parm == "std_pop_b_1940" & idn != 1
1088
+
1089
+ gen ordervar = .
1090
+
1091
+ // baseline corr bw black pop and gbpc
1092
+ replace ordervar = 31 if parm == "std_fracblack"
1093
+ replace ordervar = 30 if parm == "std_pop_b_1940"
1094
+
1095
+ // mail and migration
1096
+ replace ordervar = 28 if parm == "std_postal_b"
1097
+ replace ordervar = 27 if parm == "std_mig_bw_state_b"
1098
+ replace ordervar = 26 if parm == "std_mig_wi_state_b"
1099
+
1100
+ // other discriminatory indices
1101
+ replace ordervar = 24 if parm == "std_confed_symbol_N"
1102
+ replace ordervar = 23 if parm == "std_lynch_black"
1103
+ replace ordervar = 22 if parm == "std_naacp_chptrs1941"
1104
+
1105
+ // other segregation
1106
+ replace ordervar = 20 if parm == "std_dissimilarity_po"
1107
+ replace ordervar = 19 if parm == "std_isolation_po"
1108
+ replace ordervar = 18 if parm == "std_alpha_po"
1109
+
1110
+ // education (black and white)
1111
+ replace ordervar = 16 if parm == "std_none_b"
1112
+ replace ordervar = 15 if parm == "std_none_w"
1113
+
1114
+ // hotel owners and restaurant owners
1115
+ replace ordervar = 13 if parm == "std_hotel_own_w"
1116
+ replace ordervar = 12 if parm == "std_hotel_own_b"
1117
+ replace ordervar = 11 if parm == "std_eating_own_w"
1118
+ replace ordervar = 10 if parm == "std_eating_own_b"
1119
+
1120
+ // affluence
1121
+ replace ordervar = 8 if parm == "std_lforce_w"
1122
+ replace ordervar = 7 if parm == "std_incwage_w"
1123
+ replace ordervar = 6 if parm == "std_own_w_1940"
1124
+ replace ordervar = 5 if parm == "std_lforce_b"
1125
+ replace ordervar = 4 if parm == "std_incwage_b"
1126
+ replace ordervar = 3 if parm == "std_own_b_1940"
1127
+
1128
+ // manufacturing
1129
+ replace ordervar = 1 if parm == "std_man_estab_1940"
1130
+
1131
+
1132
+ #delimit ;
1133
+ label define coefnames
1134
+ 31 `"Share Black"'
1135
+ 30 `"Black Population"'
1136
+ 29 `" "'
1137
+ 28 `"# Black Postal Workers"'
1138
+ 27 `"% Black Migrants Between States"'
1139
+ 26 `"% Black Migrants Within States"'
1140
+ 25 `" "'
1141
+ 24 `"# Confederate Symbols"'
1142
+ 23 `"# Black Lynchings"'
1143
+ 22 `"# NAACP Chapters (1941)"'
1144
+ 21 `" "'
1145
+ 20 `"Dissimilarity Index"'
1146
+ 19 `"Isolation Index"'
1147
+ 18 `"Logan-Parman Index"'
1148
+ 17 `" "'
1149
+ 16 `"% Black With No Education"'
1150
+ 15 `"% White With No Education"'
1151
+ 14 `" "'
1152
+ 13 `"# White Hotel Owners"'
1153
+ 12 `"# White Restaurant Owners"'
1154
+ 11 `"# Black Hotel Owners"'
1155
+ 10 `"# Black Restaurant Owners"'
1156
+ 9 `" "'
1157
+ 8 `"% White in Labor Force"'
1158
+ 7 `"White Wage/Salary Income"'
1159
+ 6 `"% White Homeowners"'
1160
+ 5 `"% Black in Labor Force"'
1161
+ 4 `"Black Wage/Salary Income"'
1162
+ 3 `"% Black Homeowners"'
1163
+ 2 `" "'
1164
+ 1 `"Manufacturing Establishments"'
1165
+ 0 `" "'
1166
+ ;
1167
+ #delimit cr
1168
+
1169
+ label values ordervar coefnames
1170
+
1171
+ gen altmin95 = min95
1172
+ gen altmax95 = max95
1173
+
1174
+ #delimit ;
1175
+ twoway (scatter ordervar estimate, sort msymbol(square) mcolor(black) msize(small))
1176
+ (rcap altmin95 altmax95 ordervar, sort lcolor(black) horizontal),
1177
+ graphregion(color(white)) xline(0)
1178
+ legend(off)
1179
+ ylabel(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,valuelabel labsize(vsmall) angle(0) grid)
1180
+ ytitle("") xtitle("Estimate", margin(medium) size(small))
1181
+ yline(0, lcolor(gs8) lpattern(dash))
1182
+ yline(2, lcolor(gs8) lpattern(dash))
1183
+ yline(9, lcolor(gs8) lpattern(dash))
1184
+ yline(14, lcolor(gs8) lpattern(dash))
1185
+ yline(17, lcolor(gs8) lpattern(dash))
1186
+ yline(21, lcolor(gs8) lpattern(dash))
1187
+ yline(25, lcolor(gs8) lpattern(dash))
1188
+ yline(29, lcolor(gs8) lpattern(dash))
1189
+ yline(32, lcolor(gs8) lpattern(dash))
1190
+ xsize(8) ysize(8);
1191
+ #delimit cr
1192
+
1193
+ graph export "$figures/shareGBhotel_correlates_Hotels.pdf", replace
1194
+
1195
+ ********************************************************************************
1196
+ *-------------- FIG 5-6: Correlates of Est Shares for Retail ---------------*
1197
+ ********************************************************************************
1198
+
1199
+ use "$qjedata/county_gb_correlates_1940.dta", clear
1200
+
1201
+ keep if dataset == "Retail"
1202
+
1203
+ local varstostd fracblack postal_b mig_bw_state_b mig_wi_state_b confed_symbol_N lynch_black naacp_chptrs1941 dissimilarity_po isolation_po alpha_po none_b none_w hotel_own_w eating_own_w hotel_own_b eating_own_b lforce_w incwage_w lforce_b incwage_b own_w_1940 own_b_1940 man_estab_1940 pop_b_1940 shareGBhotel shareGBeating shareGBgas
1204
+
1205
+
1206
+ foreach i of local varstostd {
1207
+ egen std_`i' = std(`i'), mean(0) std(1)
1208
+ }
1209
+
1210
+ tempfile tFile
1211
+ save `tFile'
1212
+
1213
+ local outcomes shareGBeating shareGBgas
1214
+
1215
+ foreach k of local outcomes {
1216
+
1217
+ use `tFile', clear
1218
+ tempfile t1
1219
+
1220
+ parmby "reg std_`k' std_pop_b_1940, r", lab saving(`"`t1'"',replace) idn(1) ids(total) level(95)
1221
+
1222
+ local varlist fracblack postal_b mig_bw_state mig_wi_state confed_symbol lynch_black naacp_chptrs1941 dissimilarity isolation alpha none_b none_w hotel_own_w eating_own_w hotel_own_b eating_own_b lforce_w incwage_w lforce_b incwage_b own_w_1940 own_b_1940 man_estab_1940
1223
+
1224
+ local j = 1
1225
+ foreach v of local varlist {
1226
+ local j = `j' + 1
1227
+ tempfile t`j'
1228
+ parmby "reg std_`k' std_`v' std_pop_b_1940, r", lab saving(`"`t`j''"',replace) idn(`j') ids(total) level(95)
1229
+ }
1230
+
1231
+ drop _all
1232
+
1233
+ forvalues i=1(1)24 {
1234
+ append using `"`t`i''"'
1235
+ }
1236
+
1237
+ drop if parm == "_cons"
1238
+ drop if parm == "std_pop_b_1940" & idn != 1
1239
+
1240
+ gen ordervar = .
1241
+
1242
+ // baseline corr bw black pop and gbpc
1243
+ replace ordervar = 31 if parm == "std_fracblack"
1244
+ replace ordervar = 30 if parm == "std_pop_b_1940"
1245
+
1246
+ // mail and migration
1247
+ replace ordervar = 28 if parm == "std_postal_b"
1248
+ replace ordervar = 27 if parm == "std_mig_bw_state_b"
1249
+ replace ordervar = 26 if parm == "std_mig_wi_state_b"
1250
+
1251
+ // other discriminatory indices
1252
+ replace ordervar = 24 if parm == "std_confed_symbol_N"
1253
+ replace ordervar = 23 if parm == "std_lynch_black"
1254
+ replace ordervar = 22 if parm == "std_naacp_chptrs1941"
1255
+
1256
+ // other segregation
1257
+ replace ordervar = 20 if parm == "std_dissimilarity_po"
1258
+ replace ordervar = 19 if parm == "std_isolation_po"
1259
+ replace ordervar = 18 if parm == "std_alpha_po"
1260
+
1261
+ // education (black and white)
1262
+ replace ordervar = 16 if parm == "std_none_b"
1263
+ replace ordervar = 15 if parm == "std_none_w"
1264
+
1265
+ // hotel owners and restaurant owners
1266
+ replace ordervar = 13 if parm == "std_hotel_own_w"
1267
+ replace ordervar = 12 if parm == "std_hotel_own_b"
1268
+ replace ordervar = 11 if parm == "std_eating_own_w"
1269
+ replace ordervar = 10 if parm == "std_eating_own_b"
1270
+
1271
+ // affluence
1272
+ replace ordervar = 8 if parm == "std_lforce_w"
1273
+ replace ordervar = 7 if parm == "std_incwage_w"
1274
+ replace ordervar = 6 if parm == "std_own_w_1940"
1275
+ replace ordervar = 5 if parm == "std_lforce_b"
1276
+ replace ordervar = 4 if parm == "std_incwage_b"
1277
+ replace ordervar = 3 if parm == "std_own_b_1940"
1278
+
1279
+ // manufacturing
1280
+ replace ordervar = 1 if parm == "std_man_estab_1940"
1281
+
1282
+
1283
+ #delimit ;
1284
+ label define coefnames
1285
+ 31 `"Share Black"'
1286
+ 30 `"Black Population"'
1287
+ 29 `" "'
1288
+ 28 `"# Black Postal Workers"'
1289
+ 27 `"% Black Migrants Between States"'
1290
+ 26 `"% Black Migrants Within States"'
1291
+ 25 `" "'
1292
+ 24 `"# Confederate Symbols"'
1293
+ 23 `"# Black Lynchings"'
1294
+ 22 `"# NAACP Chapters (1941)"'
1295
+ 21 `" "'
1296
+ 20 `"Dissimilarity Index"'
1297
+ 19 `"Isolation Index"'
1298
+ 18 `"Logan-Parman Index"'
1299
+ 17 `" "'
1300
+ 16 `"% Black With No Education"'
1301
+ 15 `"% White With No Education"'
1302
+ 14 `" "'
1303
+ 13 `"# White Hotel Owners"'
1304
+ 12 `"# White Restaurant Owners"'
1305
+ 11 `"# Black Hotel Owners"'
1306
+ 10 `"# Black Restaurant Owners"'
1307
+ 9 `" "'
1308
+ 8 `"% White in Labor Force"'
1309
+ 7 `"White Wage/Salary Income"'
1310
+ 6 `"% White Homeowners"'
1311
+ 5 `"% Black in Labor Force"'
1312
+ 4 `"Black Wage/Salary Income"'
1313
+ 3 `"% Black Homeowners"'
1314
+ 2 `" "'
1315
+ 1 `"Manufacturing Establishments"'
1316
+ 0 `" "'
1317
+ ;
1318
+ #delimit cr
1319
+
1320
+ label values ordervar coefnames
1321
+
1322
+
1323
+ gen altmin95 = min95
1324
+ gen altmax95 = max95
1325
+
1326
+ #delimit ;
1327
+ twoway (scatter ordervar estimate, sort msymbol(square) mcolor(black) msize(small))
1328
+ (rcap altmin95 altmax95 ordervar, sort lcolor(black) horizontal),
1329
+ graphregion(color(white)) xline(0)
1330
+ legend(off)
1331
+ ylabel(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,valuelabel labsize(vsmall) angle(0) grid)
1332
+ ytitle("") xtitle("Estimate", margin(medium) size(small))
1333
+ yline(0, lcolor(gs8) lpattern(dash))
1334
+ yline(2, lcolor(gs8) lpattern(dash))
1335
+ yline(9, lcolor(gs8) lpattern(dash))
1336
+ yline(14, lcolor(gs8) lpattern(dash))
1337
+ yline(17, lcolor(gs8) lpattern(dash))
1338
+ yline(21, lcolor(gs8) lpattern(dash))
1339
+ yline(25, lcolor(gs8) lpattern(dash))
1340
+ yline(29, lcolor(gs8) lpattern(dash))
1341
+ yline(32, lcolor(gs8) lpattern(dash))
1342
+ xsize(8) ysize(8);
1343
+ #delimit cr
1344
+
1345
+ graph export "$figures/`k'_correlates_Retail.pdf", replace
1346
+
1347
+ }
1348
+
1349
+
1350
+ ********************************************************************************
1351
+ *-------------- FIG 7: Balance of Covariates ---------------*
1352
+ ********************************************************************************
1353
+
1354
+ /*
1355
+ // WE NEED TO UPDATE THIS IN THE TEXT
1356
+ tempfile t1
1357
+
1358
+ use "/Users/maggiejones/Dropbox/Research/Green Books/Green Books/Data/Raw/Census County Data (Haines)/1940_pt1/ICPSR_02896/data/Census_1940pt1.dta", clear
1359
+
1360
+ keep county state areaac acfarms
1361
+
1362
+ rename (county state) (ICPSRCTY ICPSRST)
1363
+
1364
+ save `t1'
1365
+
1366
+ use "$qjedata/county_gb_main.dta", clear // NEW MAIN GB COUNTY LEVEL DATA
1367
+
1368
+ merge m:1 ICPSRST ICPSRCTY using `t1'
1369
+
1370
+ drop shr_farmland shr_farmland_miss
1371
+
1372
+ gen shr_farmland = acfarms/areaac
1373
+ gen shr_farmland_miss = (shr_farmland == .)
1374
+ replace shr_farmland = 0 if shr_farmland == .
1375
+ */
1376
+
1377
+ use "$qjedata/county_gb_main.dta", clear // NEW MAIN GB COUNTY LEVEL DATA
1378
+
1379
+ #delimit ;
1380
+ global countycontrols
1381
+
1382
+ shr_farmland
1383
+
1384
+ pop_b_1940
1385
+ pop_w_1940
1386
+
1387
+ postal_b
1388
+ mig_bw_state_b
1389
+ mig_wi_state_b
1390
+
1391
+ confed_symbol_N
1392
+ lynch_black
1393
+ naacp_chptrs1941
1394
+
1395
+ dissimilarity_po
1396
+ isolation_po
1397
+ alpha_po
1398
+
1399
+ none_b
1400
+ educ_lo_1940_b
1401
+ educ_hs_1940_b
1402
+ none_w
1403
+ educ_lo_1940_w
1404
+ educ_hs_1940_w
1405
+
1406
+ hotel_own_w
1407
+ hotel_own_b
1408
+ eating_own_w
1409
+ eating_own_b
1410
+
1411
+ lforce_w
1412
+ lforce_b
1413
+ incwage_w
1414
+ incwage_b
1415
+ own_w_1940
1416
+ own_b_1940
1417
+
1418
+ man_estab_1940
1419
+ man_worker_1940
1420
+ man_wages_1940
1421
+ man_output_1940
1422
+ man_vadd_1940
1423
+
1424
+ warsup_com_1940
1425
+ warsup_oth_1940
1426
+ warfac_ind_1940
1427
+ warfac_mil_1940
1428
+ war_total_1940;
1429
+ #delimit cr
1430
+
1431
+ egen std_killed_w = std(killed_w), mean(0) std(1)
1432
+
1433
+ local j = 0
1434
+
1435
+ foreach i of global countycontrols {
1436
+ capture gen `i'_miss = (`i' == .)
1437
+ egen std_`i' = std(`i'), mean(0) std(1)
1438
+ local j = `j' + 1
1439
+ tempfile t`j'
1440
+ parmby "reg std_killed_w std_`i' `i'_miss i.stateid pop1940 if year == 1940, r", lab saving(`"`t`j''"',replace) idn(`j') ids(Unadjusted)
1441
+ }
1442
+
1443
+ use `t1', clear
1444
+
1445
+ forvalues k = 2(1)`j' {
1446
+ append using `t`k''
1447
+ }
1448
+
1449
+ gen missingvars = strpos(parm, "miss")
1450
+ drop if missingvars != 0
1451
+
1452
+ gen statevars = strpos(parm, "stateid")
1453
+ drop if statevars != 0
1454
+
1455
+ drop if parm == "_cons"
1456
+ drop if parm == "pop1940"
1457
+
1458
+ gen estimate_sig = .
1459
+ replace estimate_sig = estimate if min95 > 0 & max95 > 0
1460
+ replace estimate_sig = estimate if min95 < 0 & max95 < 0
1461
+
1462
+ #delimit ;
1463
+ label define varnames
1464
+ 1 `"Share Farmland"'
1465
+ 2 `"Black Pop"'
1466
+ 3 `"White Pop"'
1467
+ 4 `"Black Postal Workers"'
1468
+ 5 `"# Black Migrants b/w"'
1469
+ 6 `"# Black Migrants w/i"'
1470
+ 7 `"# Confederate Symbols"'
1471
+ 8 `"# Black Lynchings"'
1472
+ 9 `"# NAACP Chapters"'
1473
+ 10 `"Dissimilarity Index"'
1474
+ 11 `"Isolation Index"'
1475
+ 12 `"Logan-Parman Index"'
1476
+ 13 `"% Black No School"'
1477
+ 14 `"% Black >= 5 Years School"'
1478
+ 15 `"% Black >= 10 Years School"'
1479
+ 16 `"% White No School"'
1480
+ 17 `"% White >= 5 Years School"'
1481
+ 18 `"% White >= 10 Years School"'
1482
+ 19 `"# White Hotel Owners"'
1483
+ 20 `"# Black Hotel Owners"'
1484
+ 21 `"# White Restaurant Owners"'
1485
+ 22 `"# Black Restaurant Owners"'
1486
+ 23 `"% White in LF"'
1487
+ 24 `"% Black in LF"'
1488
+ 25 `"White Avg Income"'
1489
+ 26 `"Black Avg Income"'
1490
+ 27 `"# White Home Owners"'
1491
+ 28 `"# Black Home Owners"'
1492
+ 29 `"# Manufacturing Establishments"'
1493
+ 30 `"# Manufacturing Workers"'
1494
+ 31 `"Manufacturing Wages"'
1495
+ 32 `"Manufacturing Output"'
1496
+ 33 `"Manufacturing Value Added"'
1497
+ 34 `"War Supply Contracts"'
1498
+ 35 `"War Supply Other"'
1499
+ 36 `"War Supply Industry"'
1500
+ 37 `"War Supply Military"'
1501
+ 38 `"War Supply Total"' ;
1502
+ #delimit cr
1503
+
1504
+ label values idnum varnames
1505
+
1506
+ #delimit ;
1507
+ twoway (scatter idnum estimate , sort mcolor(black) msymbol(square) msize(small))
1508
+ (rcap min95 max95 idnum, horizontal sort lcolor(black)),
1509
+ legend(off) xline(0) ysize(7) xsize(3)
1510
+ ylabel(1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
1511
+ 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38,valuelabel)
1512
+ xtitle(Estimate, margin(medium)) ytitle("");
1513
+ graph export "$figures/covariate_balance_std.pdf", replace ;
1514
+ #delimit cr
1515
+
1516
+
1517
+
1518
+ ********************************************************************************
1519
+ *-------------- TAB 1: Diff in Diff using Draftee Mortality ---------------*
1520
+ ********************************************************************************
1521
+
1522
+ use "$qjedata/county_gb_main.dta", clear
1523
+
1524
+ #delimit ;
1525
+ global countycontrols
1526
+
1527
+ shr_farmland
1528
+
1529
+ pop_b_1940
1530
+ pop_w_1940
1531
+
1532
+ postal_b
1533
+ mig_bw_state_b
1534
+ mig_wi_state_b
1535
+
1536
+ confed_symbol_N
1537
+ lynch_black
1538
+ naacp_chptrs1941
1539
+
1540
+ dissimilarity_po
1541
+ isolation_po
1542
+ alpha_po
1543
+
1544
+ none_b
1545
+ educ_lo_1940_b
1546
+ educ_hs_1940_b
1547
+ none_w
1548
+ educ_lo_1940_w
1549
+ educ_hs_1940_w
1550
+
1551
+ hotel_own_w
1552
+ hotel_own_b
1553
+ eating_own_w
1554
+ eating_own_b
1555
+
1556
+ lforce_w
1557
+ lforce_b
1558
+ incwage_w
1559
+ incwage_b
1560
+ own_w_1940
1561
+ own_b_1940
1562
+
1563
+ man_estab_1940
1564
+ man_worker_1940
1565
+ man_wages_1940
1566
+ man_output_1940
1567
+ man_vadd_1940
1568
+
1569
+ warsup_com_1940
1570
+ warsup_oth_1940
1571
+ warfac_ind_1940
1572
+ warfac_mil_1940
1573
+ war_total_1940;
1574
+
1575
+ #delimit cr
1576
+
1577
+ #delimit ;
1578
+ global countycontrolsmissing
1579
+
1580
+ shr_farmland_miss
1581
+
1582
+ pop_b_1940_miss
1583
+ pop_w_1940_miss
1584
+
1585
+ mig_bw_state_b_miss
1586
+ mig_wi_state_b_miss
1587
+
1588
+ confed_symbol_N_miss
1589
+ lynch_black_miss
1590
+
1591
+ dissimilarity_po_miss
1592
+ isolation_po_miss
1593
+ alpha_po_miss
1594
+
1595
+ none_b_miss
1596
+ educ_lo_1940_b_miss
1597
+ educ_hs_1940_b_miss
1598
+ none_w_miss
1599
+ educ_lo_1940_w_miss
1600
+ educ_hs_1940_w_miss
1601
+
1602
+ own_w_1940_miss
1603
+ own_b_1940_miss
1604
+
1605
+ man_estab_1940_miss
1606
+ man_worker_1940_miss
1607
+ man_wages_1940_miss
1608
+ man_output_1940_miss
1609
+ man_vadd_1940_miss
1610
+
1611
+ war_total_1940_miss
1612
+ warsup_com_1940_miss
1613
+ warsup_oth_1940_miss
1614
+ warfac_ind_1940_miss
1615
+ warfac_mil_1940_miss;
1616
+ #delimit cr
1617
+
1618
+ foreach a of global countycontrols {
1619
+ gen asinh_`a' = asinh(`a')
1620
+ }
1621
+
1622
+ foreach a of global countycontrols {
1623
+ gen postint_`a' = asinh_`a'*after
1624
+ }
1625
+
1626
+ foreach a of global countycontrolsmissing {
1627
+ gen mis_`a' = `a'*after
1628
+ }
1629
+
1630
+ gen misscontrols = 0
1631
+ foreach a of global countycontrolsmissing {
1632
+ replace misscontrols = 1 if `a' == 1
1633
+ }
1634
+
1635
+ estimates clear
1636
+ // PANEL A: FULL SAMPLE
1637
+ *col 1 reg: diff in diff no fe
1638
+ qui: eststo: xi: reg a_gb_tot a_killed_draft_w a_killed_draft_w_after after, cluster(county_code)
1639
+ *col 2 reg: state FE
1640
+ qui: eststo: xi: reg a_gb_tot a_killed_draft_w a_killed_draft_w_after after i.stateid , cluster(county_code)
1641
+ *col 3 reg: county controls, year FE
1642
+ qui: eststo: xi: reg a_gb_tot a_killed_draft_w a_killed_draft_w_after postint_* mis_* asinh_* $countycontrolsmissing i.year i.stateid , cluster(county_code)
1643
+ *col 4: reg: county FE, year FE
1644
+ qui: eststo: xi: areg a_gb_tot a_killed_draft_w_after i.year , absorb(county_code) cluster(county_code)
1645
+ *col 5: reg: stateXyear FE, county FE
1646
+ qui: eststo: xi: areg a_gb_tot a_killed_draft_w_after i.stateid*i.year , absorb(county_code) cluster(county_code)
1647
+ *col 6 reg: county-level linear time trends, county FE, year FE
1648
+ //qui: eststo: xi: areg a_gb_tot a_killed_draft_w_after i.year c.year##i.county_code , absorb(county_code) cluster(county_code)
1649
+
1650
+ #delimit ;
1651
+ esttab using "$tables/a_killed_draft_white_did_gbtot.tex", replace label title("Effects of White Draftee Casualties on Number of Establishments")
1652
+ star(* 0.10 ** 0.05 *** 0.01) se ar2 b(a3) se(3)
1653
+ scalar("N_clust \# clusters") nomtitles keep(a_killed_draft_w_after)
1654
+ varlabel(a_killed_draft_w_after "Asinh(\# White Deaths) $\times$ Post-WW2") ;
1655
+ estimates clear ;
1656
+ #delimit cr
1657
+
1658
+ // PANEL B: BY INDUSTRY
1659
+ *col 1 reg: Barber\beauty parlors: year FE and county FE
1660
+ qui: eststo barber: areg a_num_est_barber a_killed_draft_w_after i.year , absorb(county_code) cluster(county_code)
1661
+ *col 2 reg: Eating and drinking: year FE and county FE
1662
+ qui: eststo eating: areg a_num_est_eating a_killed_draft_w_after i.year , absorb(county_code) cluster(county_code)
1663
+ *col 3 reg: Service stations: year FE and county FE
1664
+ qui: eststo gas: areg a_num_est_gas a_killed_draft_w_after i.year , absorb(county_code) cluster(county_code)
1665
+ *col 4 reg: Formal accommodations: year FE and county FE
1666
+ qui: eststo hotel: areg a_num_est_hotel a_killed_draft_w_after i.year , absorb(county_code) cluster(county_code)
1667
+ *col 5 reg: Informal accommodations: year FE and county FE
1668
+ qui: eststo informal: areg a_num_est_informal a_killed_draft_w_after i.year , absorb(county_code) cluster(county_code)
1669
+ *col 6 reg: Other establishments: year FE and county FE
1670
+ qui: eststo other: areg a_num_est_other a_killed_draft_w_after i.year , absorb(county_code) cluster(county_code)
1671
+
1672
+ #delimit ;
1673
+ esttab using "$tables/a_killed_draft_white_did_by_industry.tex", replace label title("Effects of White Casualties on Number of Establishments")
1674
+ star(* 0.10 ** 0.05 *** 0.01) se ar2 b(a3) se(3) scalar(N_clust)
1675
+ addnotes("Standard errors clustered by county in parentheses.
1676
+ Casualties are measured in units of 100.
1677
+ All columns include county and year fixed effects.")
1678
+ mtitles keep(a_killed_draft_w_after)
1679
+ varlabel(a_killed_draft_w_after
1680
+ "Treatment") ;
1681
+ estimates clear ;
1682
+ #delimit cr
1683
+
1684
+
1685
+ // PANEL C: SHARES
1686
+ use "$qjedata/county_gb_hotels_panel.dta", clear
1687
+
1688
+ estimates clear
1689
+ eststo: areg a_shareGBhotel_i2 a_killed_draft_w_after i.year, absorb(county_code) cluster(county_code)
1690
+ eststo: xi: areg a_shareGBhotel_i2 a_killed_draft_w_after i.stateid*i.year , absorb(county_code) cluster(county_code)
1691
+
1692
+ use "$qjedata/county_gb_retail_panel.dta", clear
1693
+
1694
+ eststo: areg a_shareGBeat_i2 a_killed_draft_w_after i.year , absorb(county_code) cluster(county_code)
1695
+ eststo: xi: areg a_shareGBeat_i2 a_killed_draft_w_after i.stateid*i.year , absorb(county_code) cluster(county_code)
1696
+
1697
+ eststo: areg a_shareGBgas_i2 a_killed_draft_w_after i.year , absorb(county_code) cluster(county_code)
1698
+ eststo: xi: areg a_shareGBgas_i2 a_killed_draft_w_after i.stateid*i.year , absorb(county_code) cluster(county_code)
1699
+
1700
+ #delimit ;
1701
+ esttab using "$tables/a_killed_draft_white_did_shares.tex", replace label title("Effects of White Casualties on Share of GB Establishments")
1702
+ star(* 0.10 ** 0.05 *** 0.01) se ar2 b(a3) se(3) scalar(N_clust)
1703
+ addnotes("Standard errors clustered by county in parentheses.
1704
+ Casualties are measured in units of 100.
1705
+ All columns include county and year fixed effects.")
1706
+ mtitles keep(a_killed_draft_w_after)
1707
+ varlabel(a_killed_draft_w_after
1708
+ "Treatment") ;
1709
+ estimates clear ;
1710
+ #delimit cr
1711
+
1712
+
1713
+ ********************************************************************************
1714
+ *-------------- TAB 2-4: IV Functional Form by Industry ---------------*
1715
+ ********************************************************************************
1716
+
1717
+ estimates clear
1718
+
1719
+ // HOTELS
1720
+ use "$qjedata/county_gb_hotels.dta", clear
1721
+
1722
+ gen d_gbhotel4050 = (gbhotel1950 - gbhotel1940)/numCOBhotel1940
1723
+ gen d_gbhotel5060 = (gbhotel1960 - gbhotel1950)/numCOBhotel1950
1724
+
1725
+ gen d_blackshr4050 = (pop_b_1950-pop_b_1940)/pop1940
1726
+ gen d_blackshr5060 = (pop_b_1960-pop_b_1950)/pop1950
1727
+
1728
+
1729
+ foreach v in d_gbhotel4050 d_gbhotel5060 d_blackshr4050 d_blackshr5060 killed_w bartikshock4050 bartikshock5060 {
1730
+ gen a_`v' = asinh(`v')
1731
+ }
1732
+
1733
+ gen a_delta_shrhotel = asinh((gbhotel1950/numCOBhotel1950) - (gbhotel1940/numCOBhotel1940))
1734
+ gen a_delta_shrblack = asinh((pop_b_1950/pop1950) - (pop_b_1940/pop1940))
1735
+
1736
+ gen a_pct_d_shrblack = asinh(((pop_b_1950/pop1950) - (pop_b_1940/pop1940))/(pop_b_1940/pop1940))
1737
+ gen a_pct_d_shrhotel= asinh(((gbhotel1950/numCOBhotel1950) - (gbhotel1940/numCOBhotel1940))/(gbhotel1940/numCOBhotel1940))
1738
+ gen a_dhotels = asinh((numCOBhotel1950-numCOBhotel1940)/numCOBhotel1940)
1739
+
1740
+ ***
1741
+ //ols
1742
+ eststo rob_ols_5060_hotel: reg a_d_gbhotel5060 a_d_blackshr5060 i.stateid if num_hotel_CoBab1948 != . & us_region != "South"
1743
+ eststo rob_ols_delta_hotel: reg a_delta_shrhotel a_delta_shrblack i.stateid if num_hotel_CoBab1935 != .
1744
+ eststo rob_ols_pct_hotel: reg a_pct_d_shrhotel a_pct_d_shrblack i.stateid if num_hotel_CoBab1935 != .
1745
+ eststo rob_ols_chgest_hotel: reg a_d_gbhotel4050 a_d_blackshr4050 a_dhotel i.stateid if num_hotel_CoBab1935 != .
1746
+
1747
+ //iv
1748
+ eststo rob_iv_5060_hotel: ivreg2 a_d_gbhotel5060 (a_d_blackshr5060 = a_bartikshock5060) i.stateid if num_hotel_CoBab1948 != . & us_region != "South", partial(i.stateid) first
1749
+ eststo rob_iv_delta_hotel: ivreg2 a_delta_shrhotel (a_delta_shrblack = a_killed_w) i.stateid if num_hotel_CoBab1935 != ., partial(i.stateid) first
1750
+ eststo rob_iv_pct_hotel: ivreg2 a_pct_d_shrhotel (a_pct_d_shrblack = a_killed_w) i.stateid if num_hotel_CoBab1935 != .,partial(i.stateid) first
1751
+ eststo rob_iv_chgest_hotel: ivreg2 a_d_gbhotel4050 (a_d_blackshr4050 = a_killed_w) a_dhotel i.stateid if num_hotel_CoBab1935 != ., partial(i.stateid) first
1752
+
1753
+ ***
1754
+
1755
+ // EATING & DRINKING / GASOLINE STATIONS
1756
+ use "$qjedata/county_gb_retail.dta", clear
1757
+
1758
+ gen d_gbeat4050 = (gbeat1950 - gbeat1940)/numCOBeat1940
1759
+ gen d_gbgas4050 = (gbgas1950 - gbgas1940)/numCOBgas1940
1760
+ gen d_blackshr4050 = (pop_b_1950-pop_b_1940)/pop1940
1761
+
1762
+ foreach v in d_gbeat4050 d_gbgas4050 d_blackshr4050 killed_w bartikshock4050 {
1763
+ gen a_`v' = asinh(`v')
1764
+ }
1765
+
1766
+
1767
+ gen a_delta_shreat = asinh((gbeat1950/numCOBeat1950) - (gbeat1940/numCOBeat1940))
1768
+ gen a_delta_shrgas = asinh((gbgas1950/numCOBgas1950) - (gbgas1940/numCOBgas1940))
1769
+
1770
+ gen a_delta_shrblack = asinh((pop_b_1950/pop1950) - (pop_b_1940/pop1940))
1771
+
1772
+ gen a_pct_d_shrblack = asinh(((pop_b_1950/pop1950) - (pop_b_1940/pop1940))/(pop_b_1940/pop1940))
1773
+ gen a_pct_d_shreat= asinh(((gbeat1950/numCOBeat1950) - (gbeat1940/numCOBeat1940))/(gbeat1940/numCOBeat1940))
1774
+ gen a_pct_d_shrgas= asinh(((gbgas1950/numCOBgas1950) - (gbgas1940/numCOBgas1940))/(gbgas1940/numCOBgas1940))
1775
+
1776
+ gen a_deat = asinh((numCOBeat1950-numCOBeat1940)/numCOBeat1940)
1777
+ gen a_dgas = asinh((numCOBgas1950-numCOBgas1940)/numCOBgas1940)
1778
+
1779
+ ***
1780
+
1781
+ // EATING AND DRINKING
1782
+
1783
+
1784
+ // ols
1785
+ eststo rob_ols_delta_eat: reg a_delta_shreat a_delta_shrblack i.stateid if num_eat_CoB1935 != .
1786
+ eststo rob_ols_pct_eat: reg a_pct_d_shreat a_pct_d_shrblack i.stateid if num_eat_CoB1935 != .
1787
+ eststo rob_ols_chgest_eat: reg a_d_gbeat4050 a_d_blackshr4050 a_deat i.stateid if num_eat_CoB1935 != .
1788
+
1789
+ // iv
1790
+ eststo rob_iv_delta_eat: ivreg2 a_delta_shreat (a_delta_shrblack = a_killed_w) i.stateid if num_eat_CoB1935 != ., partial(i.stateid) first
1791
+ eststo rob_iv_pct_eat: ivreg2 a_pct_d_shreat (a_pct_d_shrblack = a_killed_w) i.stateid if num_eat_CoB1935 != ., partial(i.stateid) first
1792
+ eststo rob_iv_chgest_eat: ivreg2 a_d_gbeat4050 (a_d_blackshr4050 = a_killed_w) a_deat i.stateid if num_eat_CoB1935 != ., partial(i.stateid) first
1793
+
1794
+ ***
1795
+
1796
+ // GAS STATIONS
1797
+
1798
+
1799
+ // ols
1800
+
1801
+ eststo rob_ols_delta_gas: reg a_delta_shrgas a_delta_shrblack i.stateid if num_gas_CoB1935 != .
1802
+ eststo rob_ols_pct_gas: reg a_pct_d_shrgas a_pct_d_shrblack i.stateid if num_gas_CoB1935 != .
1803
+ eststo rob_ols_chgest_gas: reg a_d_gbgas4050 a_d_blackshr4050 a_dgas i.stateid if num_gas_CoB1935 != .
1804
+
1805
+ // iv
1806
+ eststo rob_iv_delta_gas: ivreg2 a_delta_shrgas (a_delta_shrblack = a_killed_w) i.stateid if num_gas_CoB1935 != ., partial(i.stateid) first
1807
+ eststo rob_iv_pct_gas: ivreg2 a_pct_d_shrgas (a_pct_d_shrblack = a_killed_w) i.stateid if num_gas_CoB1935 != ., partial(i.stateid) first
1808
+ eststo rob_iv_chgest_gas: ivreg2 a_d_gbgas4050 (a_d_blackshr4050 = a_killed_w) a_dgas i.stateid if num_gas_CoB1935 != ., partial(i.stateid) first
1809
+
1810
+ ***
1811
+
1812
+ // TABLE RESULTS
1813
+
1814
+ #delimit ;
1815
+ esttab rob_ols_5060_hotel rob_ols_delta_hotel rob_ols_pct_hotel rob_ols_chgest_hotel using "$tables/iv_robust_hotels.tex", replace label title("OLS results for the change in the share of non-discriminatory hotels")
1816
+ star(* 0.10 ** 0.05 *** 0.01) scalars(widstat) se ar2 b(a3) se(3) addnotes("Standard errors in parentheses.")
1817
+ keep(a_d_blackshr5060 a_delta_shrblack a_pct_d_shrblack a_d_blackshr4050);
1818
+
1819
+ esttab rob_iv_5060_hotel rob_iv_delta_hotel rob_iv_pct_hotel rob_iv_chgest_hotel using "$tables/iv_robust_hotels.tex", append label title("IV results for the change in the share of non-discriminatory hotels")
1820
+ star(* 0.10 ** 0.05 *** 0.01) scalars(widstat) se ar2 b(a3) se(3) addnotes("Standard errors in parentheses.")
1821
+ keep(a_d_blackshr5060 a_delta_shrblack a_pct_d_shrblack a_d_blackshr4050);
1822
+
1823
+ esttab rob_ols_delta_eat rob_ols_pct_eat rob_ols_chgest_eat using "$tables/iv_robust_eatingdrinking.tex", replace label title("OLS results for the change in the share of non-discriminatory eating and drinking establishments")
1824
+ star(* 0.10 ** 0.05 *** 0.01) scalars(widstat) se ar2 b(a3) se(3) addnotes("Standard errors in parentheses.")
1825
+ keep(a_delta_shrblack a_pct_d_shrblack a_d_blackshr4050);
1826
+
1827
+ esttab rob_iv_delta_eat rob_iv_pct_eat rob_iv_chgest_eat using "$tables/iv_robust_eatingdrinking.tex", append label title("IV results for the change in the share of non-discriminatory eating and drinking establishments")
1828
+ star(* 0.10 ** 0.05 *** 0.01) scalars(widstat) se ar2 b(a3) se(3) addnotes("Standard errors in parentheses.")
1829
+ keep(a_delta_shrblack a_pct_d_shrblack a_d_blackshr4050);
1830
+
1831
+ esttab rob_ols_delta_gas rob_ols_pct_gas rob_ols_chgest_gas using "$tables/iv_robust_gas.tex", replace label title("OLS results for the change in the share of non-discriminatory gasoline stations")
1832
+ star(* 0.10 ** 0.05 *** 0.01) scalars(widstat) se ar2 b(a3) se(3) addnotes("Standard errors in parentheses.")
1833
+ keep(a_delta_shrblack a_pct_d_shrblack a_d_blackshr4050);
1834
+
1835
+ esttab rob_iv_delta_gas rob_iv_pct_gas rob_iv_chgest_gas using "$tables/iv_robust_gas.tex", append label title("IV results for the change in the share of non-discriminatory gasoline stations")
1836
+ star(* 0.10 ** 0.05 *** 0.01) scalars(widstat) se ar2 b(a3) se(3) addnotes("Standard errors in parentheses.")
1837
+ keep(a_delta_shrblack a_pct_d_shrblack a_d_blackshr4050);
1838
+ #delimit cr
1839
+
1840
+
1841
+
1842
+
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109/replication_package/Output/Tables/a_killed_draft_white_did_by_industry.tex ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \begin{table}[htbp]\centering
2
+ \def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
3
+ \caption{Effects of White Casualties on Number of Establishments}
4
+ \begin{tabular}{l*{6}{c}}
5
+ \hline\hline
6
+ &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}&\multicolumn{1}{c}{(4)}&\multicolumn{1}{c}{(5)}&\multicolumn{1}{c}{(6)}\\
7
+ &\multicolumn{1}{c}{barber}&\multicolumn{1}{c}{eating}&\multicolumn{1}{c}{gas}&\multicolumn{1}{c}{hotel}&\multicolumn{1}{c}{informal}&\multicolumn{1}{c}{other}\\
8
+ \hline
9
+ Treatment & 0.0515\sym{***}& 0.0686\sym{***}& 0.0242\sym{***}& 0.0179\sym{***}& 0.00493 & 0.0552\sym{***}\\
10
+ & (0.008) & (0.009) & (0.005) & (0.005) & (0.005) & (0.008) \\
11
+ \hline
12
+ Observations & 37248 & 37248 & 37248 & 37248 & 37248 & 37248 \\
13
+ Adjusted \(R^{2}\) & 0.817 & 0.844 & 0.766 & 0.865 & 0.878 & 0.787 \\
14
+ N\_clust & 3104 & 3104 & 3104 & 3104 & 3104 & 3104 \\
15
+ \hline\hline
16
+ \multicolumn{7}{l}{\footnotesize Standard errors in parentheses}\\
17
+ \multicolumn{7}{l}{\footnotesize Standard errors clustered by county in parentheses. Casualties are measured in units of 100. All columns include county and year fixed effects.}\\
18
+ \multicolumn{7}{l}{\footnotesize \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\)}\\
19
+ \end{tabular}
20
+ \end{table}
109/replication_package/Output/Tables/a_killed_draft_white_did_gbtot.tex ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \begin{table}[htbp]\centering
2
+ \def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
3
+ \caption{Effects of White Draftee Casualties on Number of Establishments}
4
+ \begin{tabular}{l*{5}{c}}
5
+ \hline\hline
6
+ &\multicolumn{1}{c}{(1)} &\multicolumn{1}{c}{(2)} &\multicolumn{1}{c}{(3)} &\multicolumn{1}{c}{(4)} &\multicolumn{1}{c}{(5)} \\
7
+ \hline
8
+ Asinh(\# White Deaths) $\times$ Post-WW2& 0.0605\sym{***}& 0.0605\sym{***}& 0.0191\sym{*} & 0.0605\sym{***}& 0.0880\sym{***}\\
9
+ & (0.008) & (0.008) & (0.011) & (0.009) & (0.012) \\
10
+ \hline
11
+ Observations & 37248 & 37248 & 37248 & 37248 & 37248 \\
12
+ Adjusted \(R^{2}\) & 0.170 & 0.248 & 0.624 & 0.906 & 0.909 \\
13
+ \# clusters & 3104 & 3104 & 3104 & 3104 & 3104 \\
14
+ \hline\hline
15
+ \multicolumn{6}{l}{\footnotesize Standard errors in parentheses}\\
16
+ \multicolumn{6}{l}{\footnotesize \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\)}\\
17
+ \end{tabular}
18
+ \end{table}
109/replication_package/Output/Tables/a_killed_draft_white_did_shares.tex ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \begin{table}[htbp]\centering
2
+ \def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
3
+ \caption{Effects of White Casualties on Share of GB Establishments}
4
+ \begin{tabular}{l*{6}{c}}
5
+ \hline\hline
6
+ &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}&\multicolumn{1}{c}{(4)}&\multicolumn{1}{c}{(5)}&\multicolumn{1}{c}{(6)}\\
7
+ &\multicolumn{1}{c}{est1}&\multicolumn{1}{c}{est2}&\multicolumn{1}{c}{est3}&\multicolumn{1}{c}{est4}&\multicolumn{1}{c}{est5}&\multicolumn{1}{c}{est6}\\
8
+ \hline
9
+ Treatment & 0.000389 & 0.00147\sym{*} & 0.000229\sym{***}& 0.000401\sym{***}& -0.0000583 & 0.000104 \\
10
+ & (0.001) & (0.001) & (0.000) & (0.000) & (0.000) & (0.000) \\
11
+ \hline
12
+ Observations & 23953 & 23953 & 36620 & 36620 & 36684 & 36684 \\
13
+ Adjusted \(R^{2}\) & 0.668 & 0.677 & 0.744 & 0.744 & 0.638 & 0.637 \\
14
+ N\_clust & 2957 & 2957 & 3071 & 3071 & 3070 & 3070 \\
15
+ \hline\hline
16
+ \multicolumn{7}{l}{\footnotesize Standard errors in parentheses}\\
17
+ \multicolumn{7}{l}{\footnotesize Standard errors clustered by county in parentheses. Casualties are measured in units of 100. All columns include county and year fixed effects.}\\
18
+ \multicolumn{7}{l}{\footnotesize \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\)}\\
19
+ \end{tabular}
20
+ \end{table}
109/replication_package/Output/Tables/a_killed_white_did_by_industry.tex ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \begin{table}[htbp]\centering
2
+ \def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
3
+ \caption{Effects of White Casualties on Number of Establishments}
4
+ \begin{tabular}{l*{6}{c}}
5
+ \hline\hline
6
+ &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}&\multicolumn{1}{c}{(4)}&\multicolumn{1}{c}{(5)}&\multicolumn{1}{c}{(6)}\\
7
+ &\multicolumn{1}{c}{barber}&\multicolumn{1}{c}{eating}&\multicolumn{1}{c}{gas}&\multicolumn{1}{c}{hotel}&\multicolumn{1}{c}{informal}&\multicolumn{1}{c}{other}\\
8
+ \hline
9
+ Treatment & 0.0550\sym{***}& 0.0740\sym{***}& 0.0263\sym{***}& 0.0192\sym{***}& 0.00488 & 0.0602\sym{***}\\
10
+ & (0.008) & (0.010) & (0.005) & (0.005) & (0.005) & (0.009) \\
11
+ \hline
12
+ Observations & 37248 & 37248 & 37248 & 37248 & 37248 & 37248 \\
13
+ Adjusted \(R^{2}\) & 0.818 & 0.844 & 0.766 & 0.865 & 0.878 & 0.788 \\
14
+ N\_clust & 3104 & 3104 & 3104 & 3104 & 3104 & 3104 \\
15
+ \hline\hline
16
+ \multicolumn{7}{l}{\footnotesize Standard errors in parentheses}\\
17
+ \multicolumn{7}{l}{\footnotesize Standard errors clustered by county in parentheses. Casualties are measured in units of 100. All columns include county and year fixed effects.}\\
18
+ \multicolumn{7}{l}{\footnotesize \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\)}\\
19
+ \end{tabular}
20
+ \end{table}
109/replication_package/Output/Tables/a_killed_white_did_gbtot.tex ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \begin{table}[htbp]\centering
2
+ \def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
3
+ \caption{Effects of White Casualties on Number of Establishments}
4
+ \begin{tabular}{l*{5}{c}}
5
+ \hline\hline
6
+ &\multicolumn{1}{c}{(1)} &\multicolumn{1}{c}{(2)} &\multicolumn{1}{c}{(3)} &\multicolumn{1}{c}{(4)} &\multicolumn{1}{c}{(5)} \\
7
+ \hline
8
+ Asinh(\# White Deaths) $\times$ Post-WW2& 0.0650\sym{***}& 0.0650\sym{***}& 0.0263\sym{*} & 0.0650\sym{***}& 0.0884\sym{***}\\
9
+ & (0.009) & (0.009) & (0.014) & (0.009) & (0.012) \\
10
+ \hline
11
+ Observations & 37248 & 37248 & 37248 & 37248 & 37248 \\
12
+ Adjusted \(R^{2}\) & 0.179 & 0.257 & 0.624 & 0.906 & 0.909 \\
13
+ \# clusters & 3104 & 3104 & 3104 & 3104 & 3104 \\
14
+ \hline\hline
15
+ \multicolumn{6}{l}{\footnotesize Standard errors in parentheses}\\
16
+ \multicolumn{6}{l}{\footnotesize \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\)}\\
17
+ \end{tabular}
18
+ \end{table}
109/replication_package/Output/Tables/a_killed_white_did_shares.tex ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \begin{table}[htbp]\centering
2
+ \def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
3
+ \caption{Effects of White Casualties on Share of GB Establishments}
4
+ \begin{tabular}{l*{6}{c}}
5
+ \hline\hline
6
+ &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}&\multicolumn{1}{c}{(4)}&\multicolumn{1}{c}{(5)}&\multicolumn{1}{c}{(6)}\\
7
+ &\multicolumn{1}{c}{est1}&\multicolumn{1}{c}{est2}&\multicolumn{1}{c}{est3}&\multicolumn{1}{c}{est4}&\multicolumn{1}{c}{est5}&\multicolumn{1}{c}{est6}\\
8
+ \hline
9
+ Treatment & 0.000474 & 0.00137 & 0.000234\sym{**} & 0.000399\sym{***}& -0.0000661 & 0.0000762 \\
10
+ & (0.001) & (0.001) & (0.000) & (0.000) & (0.000) & (0.000) \\
11
+ \hline
12
+ Observations & 23953 & 23953 & 36620 & 36620 & 36684 & 36684 \\
13
+ Adjusted \(R^{2}\) & 0.668 & 0.677 & 0.744 & 0.744 & 0.638 & 0.637 \\
14
+ N\_clust & 2957 & 2957 & 3071 & 3071 & 3070 & 3070 \\
15
+ \hline\hline
16
+ \multicolumn{7}{l}{\footnotesize Standard errors in parentheses}\\
17
+ \multicolumn{7}{l}{\footnotesize Standard errors clustered by county in parentheses. Casualties are measured in units of 100. All columns include county and year fixed effects.}\\
18
+ \multicolumn{7}{l}{\footnotesize \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\)}\\
19
+ \end{tabular}
20
+ \end{table}
109/replication_package/Output/Tables/iv_robust_eatingdrinking.tex ADDED
@@ -0,0 +1,52 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \begin{table}[htbp]\centering
2
+ \def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
3
+ \caption{OLS results for the change in the share of non-discriminatory eating and drinking establishments}
4
+ \begin{tabular}{l*{3}{c}}
5
+ \hline\hline
6
+ &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}\\
7
+ &\multicolumn{1}{c}{a\_delta\_shreat}&\multicolumn{1}{c}{a\_pct\_d\_shreat}&\multicolumn{1}{c}{a\_d\_gbeat4050}\\
8
+ \hline
9
+ a\_delta\_shrblack & 0.0166\sym{**} & & \\
10
+ & (0.008) & & \\
11
+ [1em]
12
+ a\_pct\_d\_shrblack & & 0.535 & \\
13
+ & & (0.350) & \\
14
+ [1em]
15
+ a\_d\_blackshr4050 & & & 0.0230\sym{***}\\
16
+ & & & (0.005) \\
17
+ \hline
18
+ Observations & 3050 & 125 & 3050 \\
19
+ Adjusted \(R^{2}\) & 0.002 & -0.050 & 0.010 \\
20
+ widstat & & & \\
21
+ \hline\hline
22
+ \multicolumn{4}{l}{\footnotesize Standard errors in parentheses}\\
23
+ \multicolumn{4}{l}{\footnotesize Standard errors in parentheses.}\\
24
+ \multicolumn{4}{l}{\footnotesize \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\)}\\
25
+ \end{tabular}
26
+ \end{table}
27
+ \begin{table}[htbp]\centering
28
+ \def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
29
+ \caption{IV results for the change in the share of non-discriminatory eating and drinking establishments}
30
+ \begin{tabular}{l*{3}{c}}
31
+ \hline\hline
32
+ &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}\\
33
+ &\multicolumn{1}{c}{a\_delta\_shreat}&\multicolumn{1}{c}{a\_pct\_d\_shreat}&\multicolumn{1}{c}{a\_d\_gbeat4050}\\
34
+ \hline
35
+ a\_delta\_shrblack & 1.273 & & \\
36
+ & (1.302) & & \\
37
+ [1em]
38
+ a\_pct\_d\_shrblack & & 4.574\sym{*} & \\
39
+ & & (2.418) & \\
40
+ [1em]
41
+ a\_d\_blackshr4050 & & & 0.0578\sym{**} \\
42
+ & & & (0.024) \\
43
+ \hline
44
+ Observations & 3050 & 125 & 3050 \\
45
+ Adjusted \(R^{2}\) & -8.199 & -2.193 & -0.026 \\
46
+ widstat & 1.030 & 3.661 & 135.7 \\
47
+ \hline\hline
48
+ \multicolumn{4}{l}{\footnotesize Standard errors in parentheses}\\
49
+ \multicolumn{4}{l}{\footnotesize Standard errors in parentheses.}\\
50
+ \multicolumn{4}{l}{\footnotesize \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\)}\\
51
+ \end{tabular}
52
+ \end{table}