Adjust prices to 2014 prices
library(jsonlite)
##
## Attaching package: 'jsonlite'
## The following object is masked from 'package:purrr':
##
## flatten
library(priceR)
country <- "United States"
countries_dataframe <- show_countries()
Generating URL to request all 299 results
inflation_dataframe <- retrieve_inflation_data(country, countries_dataframe)
Retrieving inflation data for US Generating URL to request all 61 results
# Provide a World Bank API URL and `url_all_results` will convert it into one with all results for that indicator
original_url <- "http://api.worldbank.org/v2/country"
# "http://api.worldbank.org/v2/country?format=json&per_page=304"
url_all_results(original_url)
Generating URL to request all 299 results [1] “http://api.worldbank.org/v2/country?format=json&per_page=299”
my_df$budget_2014_const <- adjust_for_inflation(my_df$pd_budget,
my_df$year,
country,
to_date = 2014,
inflation_dataframe = inflation_dataframe,
countries_dataframe = countries_dataframe)
my_df$budget_pc_2014_const <- adjust_for_inflation(my_df$pd_budget_pc,
my_df$year,
country,
to_date = 2014,
inflation_dataframe = inflation_dataframe,
countries_dataframe = countries_dataframe)
my_df %<>%
group_by(year) %>%
mutate(total_budget = sum(pd_budget, na.rm = TRUE)) %>%
ungroup() %>%
group_by(cow_code, year) %>%
mutate(budget_proportion = pd_budget / total_budget ) %>%
mutate(budget_percent = budget_proportion*100) %>%
ungroup()
Full
my_df %<>%
mutate(total_trade = us_exports + us_imports) %>%
mutate(us_trade_dep = (total_trade / gdp_current)*100)
stargazer(full_model <- plm(lead(log(budget_pc_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
un_agreement_score +
polity_index +
log(us_exports),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year")), type = "html", style = "apsr")
|
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lead(log(budget_pc_2014_const))
|
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log(gdp_pc)
|
0.111***
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|
(0.036)
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|
log(pop)
|
-0.455***
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|
(0.026)
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|
percent_muslim
|
0.004***
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|
|
(0.001)
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|
un_agreement_score
|
0.097
|
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|
(0.231)
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|
polity_index
|
0.015***
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|
(0.005)
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log(us_exports)
|
0.021
|
|
|
(0.021)
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|
N
|
1,066
|
|
R2
|
0.477
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|
Adjusted R2
|
0.471
|
|
F Statistic
|
160.259*** (df = 6; 1053)
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p < .1; p < .05; p < .01
|
stargazer(full_model <- plm(lead(log(budget_pc_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
un_agreement_score +
polity_index +
log(us_exports),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year")), type = "html", style = "asr")
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lead(log(budget_pc_2014_const))
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log(gdp_pc)
|
0.111**
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|
log(pop)
|
-0.455***
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|
percent_muslim
|
0.004***
|
|
un_agreement_score
|
0.097
|
|
polity_index
|
0.015**
|
|
log(us_exports)
|
0.021
|
|
N
|
1,066
|
|
R2
|
0.477
|
|
Adjusted R2
|
0.471
|
|
F Statistic
|
160.259*** (df = 6; 1053)
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p < .05; p < .01; p < .001
|
stargazer(full_model <- plm(lead(log(budget_pc_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
un_agreement_score +
polity_index +
log(us_exports),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year")), type = "html", style = "aer")
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lead(log(budget_pc_2014_const))
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log(gdp_pc)
|
0.111***
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|
(0.036)
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|
log(pop)
|
-0.455***
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|
(0.026)
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|
|
|
|
percent_muslim
|
0.004***
|
|
|
(0.001)
|
|
|
|
|
un_agreement_score
|
0.097
|
|
|
(0.231)
|
|
|
|
|
polity_index
|
0.015***
|
|
|
(0.005)
|
|
|
|
|
log(us_exports)
|
0.021
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|
(0.021)
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Observations
|
1,066
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|
R2
|
0.477
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|
Adjusted R2
|
0.471
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|
F Statistic
|
160.259*** (df = 6; 1053)
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Notes:
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***Significant at the 1 percent level.
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**Significant at the 5 percent level.
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*Significant at the 10 percent level.
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stargazer(full_model <- plm(lead(log(budget_pc_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
un_agreement_score +
polity_index +
log(us_exports),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year")), type = "html", style = "io")
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lead(log(budget_pc_2014_const))
|
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LOG(GDP_PC)
|
0.111***
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|
(0.036)
|
|
LOG(POP)
|
-0.455***
|
|
|
(0.026)
|
|
PERCENT_MUSLIM
|
0.004***
|
|
|
(0.001)
|
|
UN_AGREEMENT_SCORE
|
0.097
|
|
|
(0.231)
|
|
POLITY_INDEX
|
0.015***
|
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|
(0.005)
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LOG(US_EXPORTS)
|
0.021
|
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|
(0.021)
|
|
Observations
|
1,066
|
|
R-squared
|
0.477
|
|
Adjusted R-squared
|
0.471
|
|
F statistic
|
160.259*** (df = 6; 1053)
|
|
|
|
Notes:
|
p < .01; p < .05; p < .1
|
stargazer(full_model <- plm(lead(log(budget_pc_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
un_agreement_score +
polity_index +
log(us_exports),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year")), type = "html", style = "qje")
|
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|
lead(log(budget_pc_2014_const))
|
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|
|
log(gdp_pc)
|
0.111***
|
|
|
(0.036)
|
|
|
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|
log(pop)
|
-0.455***
|
|
|
(0.026)
|
|
|
|
|
percent_muslim
|
0.004***
|
|
|
(0.001)
|
|
|
|
|
un_agreement_score
|
0.097
|
|
|
(0.231)
|
|
|
|
|
polity_index
|
0.015***
|
|
|
(0.005)
|
|
|
|
|
log(us_exports)
|
0.021
|
|
|
(0.021)
|
|
|
|
|
N
|
1,066
|
|
R2
|
0.477
|
|
Adjusted R2
|
0.471
|
|
F Statistic
|
160.259*** (df = 6; 1053)
|
|
|
|
Notes:
|
***Significant at the 1 percent level.
|
|
|
**Significant at the 5 percent level.
|
|
|
*Significant at the 10 percent level.
|
stargazer(full_model <- plm(lead(log(budget_pc_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
un_agreement_score +
polity_index +
log(us_exports),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year")), type = "html", style = "ajs")
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LEAD(LOG(BUDGET_PC_2014_CONST))
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log(gdp_pc)
|
.111**
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|
(.036)
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|
log(pop)
|
-.455***
|
|
|
(.026)
|
|
|
|
|
percent_muslim
|
.004***
|
|
|
(.001)
|
|
|
|
|
un_agreement_score
|
.097
|
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|
(.231)
|
|
|
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polity_index
|
.015**
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|
(.005)
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|
log(us_exports)
|
.021
|
|
|
(.021)
|
|
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Observations
|
1,066
|
|
R2
|
.477
|
|
Adjusted R2
|
.471
|
|
F Statistic
|
160.259*** (df = 6; 1053)
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Notes:
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*P < .05
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**P < .01
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***P < .001
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Including Plots
library(rnaturalearth)
map <- ne_countries(scale = "medium", returnclass = "sf")
my_df %<>%
dplyr::mutate(political_geo = ifelse(geo_region == 1, "Post Soviet",
ifelse(geo_region == 2, "Latin",
ifelse(geo_region == 10, "Latin",
ifelse(geo_region == 9, "Latin",
ifelse(geo_region == 3, "MENA",
ifelse(geo_region == 4, "Africa",
ifelse(geo_region == 5, "West",
ifelse(geo_region == 6, "Asia",
ifelse(geo_region == 7, "Asia",
ifelse(geo_region == 8, "Asia", geo_region)))))))))))
my_df19 <- my_df[which(my_df$year == 2019),]
map$COWcode <- countrycode(map$sov_a3, "iso3c", "cown")
map19 <- merge(map, my_df19, by.x = "COWcode", by.y = "cow_code", all.x = TRUE)
map19 %>%
group_by(country_name.x) %>%
fill(geo_region, .direction = "updown") -> map2
ggplot(data = map19) +
geom_sf(aes(fill = as.factor(political_geo)),
position = "identity") +
labs(fill='Freedom of Association Index') + ggthemes::theme_map() + theme(legend.position = "blank")
soviet_model <- plm(lead(log(budget_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
# polity_index +
civ_lib_fh +
pol_right_fh +
log(us_exports + 1) +
log(us_imports + 1),
data = post_sov_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
latin_model <- plm(lead(log(budget_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
# polity_index +
civ_lib_fh +
pol_right_fh +
log(us_exports + 1) +
log(us_imports + 1),
data = latin_am_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
mena_model <- plm(lead(log(budget_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
civ_lib_fh +
pol_right_fh +
# polity_index +
log(us_exports + 1) +
log(us_imports + 1),
data = mena_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
west_model <- plm(lead(log(budget_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
civ_lib_fh +
pol_right_fh +
# polity_index +
log(us_exports + 1) +
log(us_imports + 1),
data = west_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
asia_model <- plm(lead(log(budget_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
civ_lib_fh +
pol_right_fh +
# as.factor(president) +
# polity_index +
log(us_exports + 1) +
log(us_imports + 1),
data = asia_df,
model = "within", effects = "time",
index = c("cow_code", "year"))
africa_model <- plm(lead(log(budget_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
civ_lib_fh +
pol_right_fh +
as.factor(president) +
# polity_index +
log(us_exports + 1) +
log(us_imports + 1),
data = africa_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
full_model <- plm(lead(log(budget_2014_const)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
# polity_index +
civ_lib_fh +
pol_right_fh +
log(us_exports + 1) +
log(us_imports + 1),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
stargazer(africa_model, west_model, mena_model, latin_model, soviet_model, asia_model,
column.labels = c("Africa", "West", "MENA", "Latin", "Soviet", "Asia"), type = "html", style = "io")
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lead(log(budget_2014_const))
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Africa
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West
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MENA
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Latin
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Soviet
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Asia
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(1)
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(2)
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(3)
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(4)
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(5)
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(6)
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LOG(GDP_PC)
|
0.180*
|
0.167
|
-0.310*
|
-0.025
|
-0.325**
|
1.631**
|
|
|
(0.097)
|
(0.154)
|
(0.181)
|
(0.109)
|
(0.146)
|
(0.706)
|
|
LOG(POP)
|
0.498***
|
0.554***
|
0.163
|
0.451***
|
0.289***
|
0.318
|
|
|
(0.066)
|
(0.096)
|
(0.139)
|
(0.059)
|
(0.104)
|
(2.449)
|
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PERCENT_MUSLIM
|
0.002*
|
-0.004
|
0.001
|
0.004
|
-0.001
|
0.001
|
|
|
(0.001)
|
(0.002)
|
(0.002)
|
(0.003)
|
(0.002)
|
(0.002)
|
|
LOG(US_TROOPS + 1)
|
0.056
|
-0.006
|
0.117***
|
0.008
|
-0.048
|
0.272**
|
|
|
(0.044)
|
(0.029)
|
(0.035)
|
(0.049)
|
(0.042)
|
(0.105)
|
|
UN_AGREEMENT_SCORE
|
-0.490
|
0.984
|
0.407
|
-0.729
|
1.327**
|
-0.748
|
|
|
(0.802)
|
(0.910)
|
(0.544)
|
(0.911)
|
(0.627)
|
(0.650)
|
|
CIV_LIB_FH
|
-0.162**
|
-0.307
|
-0.078
|
-0.241**
|
0.009
|
0.382
|
|
|
(0.075)
|
(0.245)
|
(0.133)
|
(0.099)
|
(0.104)
|
(0.246)
|
|
POL_RIGHT_FH
|
0.015
|
0.408
|
-0.065
|
0.021
|
0.102
|
-0.220
|
|
|
(0.062)
|
(0.282)
|
(0.092)
|
(0.083)
|
(0.083)
|
(0.150)
|
|
LOG(US_EXPORTS + 1)
|
-0.005
|
-0.002
|
0.105
|
0.096
|
-0.001
|
-0.177
|
|
|
(0.060)
|
(0.084)
|
(0.118)
|
(0.103)
|
(0.070)
|
(0.275)
|
|
LOG(US_IMPORTS + 1)
|
0.023
|
-0.129*
|
0.136**
|
-0.040
|
0.046
|
-0.065
|
|
|
(0.038)
|
(0.077)
|
(0.056)
|
(0.049)
|
(0.072)
|
(0.168)
|
|
Observations
|
257
|
149
|
118
|
167
|
178
|
127
|
|
R-squared
|
0.432
|
0.622
|
0.489
|
0.666
|
0.427
|
0.174
|
|
Adjusted R-squared
|
0.397
|
0.580
|
0.414
|
0.633
|
0.374
|
-0.051
|
|
F statistic
|
20.371*** (df = 9; 241)
|
24.362*** (df = 9; 133)
|
10.842*** (df = 9; 102)
|
33.452*** (df = 9; 151)
|
13.426*** (df = 9; 162)
|
2.318** (df = 9; 99)
|
|
|
|
Notes:
|
p < .01; p < .05; p < .1
|
pd_budget <- plm(lead(log(pd_budget)) ~ log(gdp_pc) +
log(pop) +
as.factor(war_terror)*log(us_troops + 1) +
percent_muslim +
un_agreement_score +
as.factor(president) +
# civ_lib_fh +
# pol_right_fh +
polity_index +
us_imports,
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
stargazer(pd_budget, type = "html")
|
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|
Dependent variable:
|
|
|
|
|
|
lead(log(pd_budget))
|
|
|
|
log(gdp_pc)
|
0.134***
|
|
|
(0.023)
|
|
|
|
|
log(pop)
|
0.415***
|
|
|
(0.019)
|
|
|
|
|
as.factor(war_terror)1
|
1.162**
|
|
|
(0.535)
|
|
|
|
|
log(us_troops + 1)
|
0.017
|
|
|
(0.013)
|
|
|
|
|
percent_muslim
|
0.002***
|
|
|
(0.001)
|
|
|
|
|
un_agreement_score
|
0.085
|
|
|
(0.213)
|
|
|
|
|
polity_index
|
0.008
|
|
|
(0.005)
|
|
|
|
|
us_imports
|
-0.00000*
|
|
|
(0.00000)
|
|
|
|
|
as.factor(war_terror)1:log(us_troops + 1)
|
0.114
|
|
|
(0.070)
|
|
|
|
|
|
|
Observations
|
1,010
|
|
R2
|
0.496
|
|
Adjusted R2
|
0.488
|
|
F Statistic
|
108.629*** (df = 9; 994)
|
|
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|
peace_corps_model <- plm(lead(log(sum_peace_corps + 1)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
# civ_lib_fh +
# pol_right_fh +
polity_index +
log(us_exports + 1) +
log(us_imports + 1),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
disaster_model <- plm(lead(log(sum_disaster_assist + 1)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
# civ_lib_fh +
# pol_right_fh +
polity_index +
log(us_exports + 1) +
log(us_imports + 1),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
food_aid_model <- plm(lead(log(sum_food_assist + 1)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
# civ_lib_fh +
# pol_right_fh +
polity_index +
log(us_exports + 1) +
log(us_imports + 1) ,
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
econ_aid_model <- plm(lead(log(sum_econ + 1)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
# civ_lib_fh +
# pol_right_fh +
polity_index +
log(us_exports + 1) +
log(us_imports + 1),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
military_aid_model <- plm(lead(log(sum_military + 1)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
# civ_lib_fh +
# pol_right_fh +
polity_index +
log(us_exports + 1) +
log(us_imports + 1),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
ned_model <- plm(lead(log(sum_ned + 1)) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
as.factor(president) +
# civ_lib_fh +
# pol_right_fh +
polity_index +
log(us_exports + 1) +
log(us_imports + 1),
data = my_df,
model = "within", effect = "time",
index = c("cow_code", "year"))
stargazer(pd_budget, ned_model, peace_corps_model, military_aid_model, disaster_model, econ_aid_model, food_aid_model,
dep.var.labels.include = FALSE,
column.labels = c("Public Diplomacy", "Endowment Democracy", "Peace Corps", "Military Aid", "Disaster Aid", "Economic Aid", "Food Aid"), type = "html")
|
|
|
|
Dependent variable:
|
|
|
|
|
|
Public Diplomacy
|
Endowment Democracy
|
Peace Corps
|
Military Aid
|
Disaster Aid
|
Economic Aid
|
Food Aid
|
|
|
(1)
|
(2)
|
(3)
|
(4)
|
(5)
|
(6)
|
(7)
|
|
|
|
log(gdp_pc)
|
0.134***
|
-1.753***
|
-3.541***
|
-2.672***
|
-4.486***
|
-2.243***
|
-3.455***
|
|
|
(0.023)
|
(0.281)
|
(0.332)
|
(0.250)
|
(0.318)
|
(0.163)
|
(0.293)
|
|
|
|
|
|
|
|
|
|
|
log(pop)
|
0.415***
|
1.054***
|
-1.512***
|
-1.038***
|
-0.190
|
0.007
|
0.174
|
|
|
(0.019)
|
(0.208)
|
(0.246)
|
(0.185)
|
(0.236)
|
(0.120)
|
(0.217)
|
|
|
|
|
|
|
|
|
|
|
as.factor(war_terror)1
|
1.162**
|
|
|
|
|
|
|
|
|
(0.535)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
log(us_troops + 1)
|
0.017
|
-0.141
|
-0.288**
|
0.137
|
0.179
|
-0.006
|
0.468***
|
|
|
(0.013)
|
(0.104)
|
(0.123)
|
(0.093)
|
(0.118)
|
(0.060)
|
(0.109)
|
|
|
|
|
|
|
|
|
|
|
percent_muslim
|
0.002***
|
0.009
|
-0.012*
|
0.024***
|
0.009
|
0.007**
|
-0.006
|
|
|
(0.001)
|
(0.006)
|
(0.007)
|
(0.005)
|
(0.006)
|
(0.003)
|
(0.006)
|
|
|
|
|
|
|
|
|
|
|
un_agreement_score
|
0.085
|
-3.564**
|
-2.559
|
3.801***
|
-2.026
|
-2.495***
|
1.534
|
|
|
(0.213)
|
(1.653)
|
(1.950)
|
(1.471)
|
(1.871)
|
(0.957)
|
(1.726)
|
|
|
|
|
|
|
|
|
|
|
polity_index
|
0.008
|
-0.167***
|
0.203***
|
0.070**
|
0.079*
|
-0.029
|
0.040
|
|
|
(0.005)
|
(0.037)
|
(0.044)
|
(0.033)
|
(0.042)
|
(0.022)
|
(0.039)
|
|
|
|
|
|
|
|
|
|
|
us_imports
|
-0.00000*
|
|
|
|
|
|
|
|
|
(0.00000)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
as.factor(war_terror)1:log(us_troops + 1)
|
0.114
|
|
|
|
|
|
|
|
|
(0.070)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
log(us_exports + 1)
|
|
0.296
|
1.410***
|
0.484***
|
0.696***
|
0.343***
|
0.139
|
|
|
|
(0.196)
|
(0.231)
|
(0.174)
|
(0.222)
|
(0.113)
|
(0.204)
|
|
|
|
|
|
|
|
|
|
|
log(us_imports + 1)
|
|
-0.284*
|
-0.041
|
0.486***
|
0.541***
|
0.180**
|
-0.142
|
|
|
|
(0.146)
|
(0.172)
|
(0.130)
|
(0.165)
|
(0.084)
|
(0.152)
|
|
|
|
|
|
|
|
|
|
|
|
|
Observations
|
1,010
|
900
|
900
|
900
|
900
|
900
|
900
|
|
R2
|
0.496
|
0.361
|
0.240
|
0.152
|
0.387
|
0.453
|
0.400
|
|
Adjusted R2
|
0.488
|
0.351
|
0.228
|
0.139
|
0.377
|
0.444
|
0.391
|
|
F Statistic
|
108.629*** (df = 9; 994)
|
62.603*** (df = 8; 885)
|
34.886*** (df = 8; 885)
|
19.865*** (df = 8; 885)
|
69.832*** (df = 8; 885)
|
91.535*** (df = 8; 885)
|
73.808*** (df = 8; 885)
|
|
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|
# stargazer( pd_budget, ned_model, peace_corps_model, food_aid_model,
# dep.var.labels.include = FALSE,
# column.labels = c("Public Diplomacy2", "Endowment Democracy", "Peace Corps", "Food Aid"), type = "html")
Examine only 2019
full <- lm(log(pd_budget) ~ log(gdp_pc) +
log(pop) +
percent_muslim +
log(us_troops + 1) +
un_agreement_score +
# polity_index +
civ_lib_fh +
pol_right_fh,
# as.factor(contig_china) +
# as.factor(contig_russia),
data = my_df19)
stargazer(full, type = "html")
|
|
|
|
Dependent variable:
|
|
|
|
|
|
log(pd_budget)
|
|
|
|
log(gdp_pc)
|
0.175***
|
|
|
(0.066)
|
|
|
|
|
log(pop)
|
0.416***
|
|
|
(0.047)
|
|
|
|
|
percent_muslim
|
-0.001
|
|
|
(0.002)
|
|
|
|
|
log(us_troops + 1)
|
0.080*
|
|
|
(0.042)
|
|
|
|
|
un_agreement_score
|
0.767
|
|
|
(0.529)
|
|
|
|
|
civ_lib_fh
|
0.240**
|
|
|
(0.106)
|
|
|
|
|
pol_right_fh
|
-0.137
|
|
|
(0.083)
|
|
|
|
|
Constant
|
4.971***
|
|
|
(1.030)
|
|
|
|
|
|
|
Observations
|
140
|
|
R2
|
0.549
|
|
Adjusted R2
|
0.525
|
|
Residual Std. Error
|
0.719 (df = 132)
|
|
F Statistic
|
22.977*** (df = 7; 132)
|
|
|
|
Note:
|
p<0.1; p<0.05; p<0.01
|