Bazzi, Fiszbein and Gebresilasse (2020) "Frontier Culture" replication data

A subset of the data from Bazzi, Fiszbein and Gebresilasse (2020) used in the Diegert-Masten-Poirier (2026) sensitivity analysis vignette. Each row is a county; each column is a covariate used in the DMP empirical application.

Usage

bfg2020

Format

A data.frame with 2036 rows and 14 columns:

lat, lon

Latitude and longitude.

statea

State indicator (numeric).

avgrep2000to2016

Outcome: average Republican vote share, 2000-2016.

temp_mean, rain_mean, elev_mean

Climate / topography.

d_coa, d_riv, d_lak

Distance to coast / river / lake.

ave_gyi

Average GYI.

tye_tfe890_500kNI_100_l6

Treatment: years of frontier exposure.

log_area_2010

Log area, 2010.

km_grid_cel_code

Grid cell code used for clustering.

Source

Bazzi, Fiszbein and Gebresilasse (2020), "Frontier Culture: The Roots and Persistence of 'Rugged Individualism' in the United States", Econometrica doi:10.3982/ECTA16484. A 14-variable, 2036-row subset of their public replication data, used here to demonstrate the package.

Examples

data(bfg2020)
str(bfg2020)
#> 'data.frame':	2036 obs. of  14 variables:
#>  $ lat                     : num  32.5 30.7 31.9 33 34 ...
#>   ..- attr(*, "label")= chr "latitude"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ lon                     : num  -86.6 -87.7 -85.4 -87.1 -86.6 ...
#>   ..- attr(*, "label")= chr "longitude"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ statea                  : num  1 1 1 1 1 1 1 1 1 1 ...
#>   ..- attr(*, "label")= chr "state code"
#>   ..- attr(*, "format.stata")= chr "%8.0g"
#>  $ avgrep2000to2016        : num  72.8 75.6 50.9 70.8 82.2 ...
#>   ..- attr(*, "label")= chr "average Republican Presidential vote share, 2000 to 2016"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ temp_mean               : num  17.8 19.1 18.1 17.3 15.5 ...
#>   ..- attr(*, "label")= chr "mean temperature"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ rain_mean               : num  1415 1627 1361 1425 1450 ...
#>   ..- attr(*, "label")= chr "mean rainfall"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ elev_mean               : num  119.8 39.1 115.9 132.7 244.4 ...
#>   ..- attr(*, "label")= chr "mean elevation"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ d_coa                   : num  217686 22562 169688 265655 378500 ...
#>   ..- attr(*, "label")= chr "distance to the coast"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ d_riv                   : num  13971 24708 36964 56269 46732 ...
#>   ..- attr(*, "label")= chr "distance to rivers"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ d_lak                   : num  34995 255740 21274 55554 53897 ...
#>   ..- attr(*, "label")= chr "distance to lakes"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ ave_gyi                 : num  0.609 0.584 0.658 0.608 0.622 ...
#>   ..- attr(*, "label")= chr "potential agricultural productivity"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ tye_tfe890_500kNI_100_l6: num  0.3 2.5 1.6 0.8 2.2 ...
#>   ..- attr(*, "label")= chr "TFE: 100 km, $\\leq 6$/mi$^2$, no inner island lines (baseline)"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ log_area_2010           : num  6.4 7.4 6.81 6.44 6.48 ...
#>   ..- attr(*, "label")= chr "log county area"
#>   ..- attr(*, "format.stata")= chr "%9.0g"
#>  $ km_grid_cel_code        : num  713 512 615 713 913 614 613 814 714 914 ...
#>   ..- attr(*, "label")= chr "arbitrary 60km grid cells for clustering"
#>   ..- attr(*, "format.stata")= chr "%9.0g"