再生这些2SLS导致R
我正在完成一项任务，我必须重现这些结果：
From this paper。我打算在Stata中这样做，但是为了节省几百美元并使用开源软件等等，我使用R。
我尝试过使用aer软件包，从中我可以得到系数和标准误差，但我不确定如何获得Hausman测试或Sargan测试值，以及回归第二阶段的F stat。这就是我所拥有的
> library("AER")
> stage1 <- lm(ln_export_area ~ atlantic_distance_minimum +
+ indian_distance_minimum + saharan_distance_minimum + red_sea_distance_minimum,
+ data=nunn)
> reg1 <- ivreg(ln_maddison_pcgdp2000 ~ ln_export_area | atlantic_distance_minimum +
+ indian_distance_minimum + saharan_distance_minimum +
+ red_sea_distance_minimum, data=nunn)
> summary(stage1)
Call:
lm(formula = ln_export_area ~ atlantic_distance_minimum + indian_distance_minimum +
saharan_distance_minimum + red_sea_distance_minimum, data = nunn)
Residuals:
Min 1Q Median 3Q Max
-6.3574 -2.4772 0.2513 2.8323 5.9544
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 29.10969 6.95941 4.183 0.000125 ***
atlantic_distance_minimum -1.31399 0.35678 -3.683 0.000594 ***
indian_distance_minimum -1.09543 0.37978 -2.884 0.005901 **
saharan_distance_minimum -2.43487 0.82305 -2.958 0.004830 **
red_sea_distance_minimum -0.00186 0.71041 -0.003 0.997922
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 3.445 on 47 degrees of freedom
Multiple R-squared: 0.2789, Adjusted R-squared: 0.2176
F-statistic: 4.545 on 4 and 47 DF, p-value: 0.003472
> summary(reg1)
Call:
ivreg(formula = ln_maddison_pcgdp2000 ~ ln_export_area | atlantic_distance_minimum +
indian_distance_minimum + saharan_distance_minimum + red_sea_distance_minimum,
data = nunn)
Residuals:
Min 1Q Median 3Q Max
-1.9254 -0.4602 0.1429 0.4917 1.4163
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.81135 0.20375 38.337 < 2e-16 ***
ln_export_area -0.20794 0.05301 -3.923 0.000267 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.7787 on 50 degrees of freedom
Multiple R-Squared: 0.1273, Adjusted R-squared: 0.1098
Wald test: 15.39 on 1 and 50 DF, p-value: 0.0002674
这些应该与第1列匹配。有谁知道如何
- 我可以从第二阶段回归得到置信区间吗？
- 我可以从第二阶段回归得到F stat吗？
- 我可以在第一阶段回归中进行Hausman检验和Sargan检验吗？
以下是您想要玩的数据
> dput(nunn)
structure(list(isocode = structure(1:52, .Label = c("AGO", "BDI",
"BEN", "BFA", "BWA", "CAF", "CIV", "CMR", "COG", "COM", "CPV",
"DJI", "DZA", "EGY", "ETH", "GAB", "GHA", "GIN", "GMB", "GNB",
"GNQ", "KEN", "LBR", "LBY", "LSO", "MAR", "MDG", "MLI", "MOZ",
"MRT", "MUS", "MWI", "NAM", "NER", "NGA", "RWA", "SDN", "SEN",
"SLE", "SOM", "STP", "SWZ", "SYC", "TCD", "TGO", "TUN", "TZA",
"UGA", "ZAF", "ZAR", "ZMB", "ZWE"), class = "factor"), country = structure(c(2L,
6L, 3L, 5L, 4L, 9L, 23L, 7L, 12L, 11L, 8L, 14L, 1L, 15L, 17L,
18L, 20L, 21L, 19L, 22L, 16L, 24L, 26L, 27L, 25L, 33L, 28L, 30L,
34L, 31L, 32L, 29L, 35L, 36L, 37L, 38L, 45L, 40L, 42L, 43L, 39L,
46L, 41L, 10L, 48L, 49L, 47L, 50L, 44L, 13L, 51L, 52L), .Label = c("Algeria",
"Angola", "Benin", "Botswana", "Burkina Faso", "Burundi", "Cameroon",
"Cape Verde Islands", "Central African Republic", "Chad", "Comoros",
"Congo", "Democratic Republic of Congo", "Djibouti", "Egypt",
"Equatorial Guinea", "Ethiopia", "Gabon", "Gambia", "Ghana",
"Guinea", "Guinea-Bissau", "Ivory Coast", "Kenya", "Lesotho",
"Liberia", "Libya", "Madagascar", "Malawi", "Mali", "Mauritania",
"Mauritius", "Morocco", "Mozambique", "Namibia", "Niger", "Nigeria",
"Rwanda", "Sao Tome & Principe", "Senegal", "Seychelles", "Sierra Leone",
"Somalia", "South Africa", "Sudan", "Swaziland", "Tanzania",
"Togo", "Tunisia", "Uganda", "Zambia", "Zimbabwe"), class = "factor"),
ln_maddison_pcgdp2000 = c(6.670766, 6.35437, 7.187657, 6.74876,
8.377471, 6.472346, 7.189922, 7.01661, 7.702556, 6.364751,
7.482682, 7.005789, 7.934514, 7.979339, 6.436151, 8.265393,
7.154615, 6.349139, 6.796824, 6.523562, 8.981682, 6.927558,
6.741701, 7.750184, 7.405496, 7.885329, 6.559615, 6.73578,
7.266828, 6.924613, 9.273503, 6.520621, 8.24144, 6.22059,
7.052721, 6.721426, 6.898715, 7.267525, 5.937536, 6.760415,
7.111512, 7.865572, 8.75684, 6.049734, 6.35437, 8.420241,
6.261492, 6.669498, 8.32821, 5.384495, 6.50129, 7.154615),
ln_export_area = c(7.967494, 1.140843, 8.304137, 6.413822,
-2.302585, 1.171314, 5.096793, 4.944928, 5.623267, -2.302585,
-2.302585, -1.661718, 3.257355, 0.3999169, 7.078711, 4.62739,
8.818254, 7.26078, 7.561687, 8.518584, -0.9844123, 4.99911,
4.113622, 1.61487, -2.302585, -2.302585, 5.363239, 6.520308,
6.659775, 5.072949, -2.302585, 6.968824, -1.465302, 2.752292,
7.690816, -2.302585, 5.841245, 7.561687, 6.878126, 3.923764,
-2.302585, -2.302585, -2.302585, 6.023867, 8.536835, -2.302585,
6.338511, 2.959842, 0.5095113, 5.787438, 3.614361, 1.023552
), ln_export_pop = c(14.39925, 4.451658, 13.30897, 11.72429,
3.912023, 8.052058, 10.8437, 10.33106, 12.39107, 3.912023,
3.912023, 4.703024, 9.961392, 5.477251, 12.99278, 11.69496,
13.69867, 12.8232, 12.20487, 13.78166, 4.560218, 10.44663,
10.01004, 9.503454, 3.912023, 3.912023, 11.35552, 13.05647,
12.70125, 12.87464, 3.912023, 12.33135, 7.080479, 9.695232,
12.08837, 3.912023, 11.95632, 12.91682, 11.47905, 10.37327,
3.912023, 3.912023, 3.912023, 12.87262, 13.28513, 3.912023,
12.10194, 7.543646, 7.011269, 11.76894, 10.893, 7.925018),
colony0 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), colony1 = c(0L,
0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L,
1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L,
1L, 1L, 1L, 0L, 1L, 1L), colony2 = c(0L, 0L, 1L, 1L, 0L,
1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L,
0L, 0L), colony3 = c(1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), colony4 = c(0L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 1L, 0L, 0L), colony5 = c(0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L), colony6 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), colony7 = c(0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L), abs_latitude = c(8, 16, 6, 12, 24,
4, 6, 4, 4, 11, 15, 11, 36, 28, 12, 0.2, 7, 10, 13, 12, 3,
2, 6, 32, 29, 33, 19, 14, 23, 18, 20, 15, 24, 13, 9, 2, 12,
14, 8, 5, 0.2, 26, 4, 12, 6, 36, 4, 0.2, 30, 7, 20, 19),
longitude = c(17.54142, 29.88722, 2.34264, -1.74292, 23.82042,
20.48058, -5.55555, 12.74132, 15.2263, 43.49777, -24.04431,
42.57752, 2.63691, 29.87953, 39.61983, 11.79747, -1.20736,
-10.93922, -15.38402, -14.96533, 10.34204, 37.85755, -9.3071,
18.04934, 28.2439, -6.35425, 46.72618, -3.54519, 35.58901,
-10.34285, 57.79387, 34.30362, 17.21072, 9.3731, 8.10141,
29.91774, 30.04159, -14.46586, -11.79189, 45.93132, 6.68778,
31.49749, 55.37541, 18.66029, 0.97634, 9.56295, 34.81658,
32.38633, 25.14831, 23.65134, 27.81663, 29.87154), rain_min = c(0L,
5L, 13L, 0L, 0L, 5L, 41L, 23L, 0L, 69L, 0L, 0L, 0L, 0L, 5L,
3L, 15L, 3L, 0L, 0L, 5L, 15L, 31L, 0L, 8L, 0L, 8L, 0L, 13L,
0L, 0L, 0L, 0L, 0L, 25L, 7L, 0L, 0L, 3L, 0L, 0L, 20L, 69L,
0L, 15L, 3L, 0L, 46L, 8L, 3L, 0L, 0L), humid_max = c(78L,
82L, 78L, 67L, 74L, 72L, 82L, 75L, 71L, 78L, 73L, 74L, 66L,
41L, 73L, 79L, 77L, 87L, 78L, 74L, 95L, 62L, 95L, 72L, 42L,
72L, 71L, 73L, 67L, 69L, 74L, 66L, 35L, 68L, 80L, 83L, 41L,
74L, 82L, 80L, 79L, 81L, 78L, 72L, 77L, 64L, 56L, 72L, 67L,
73L, 71L, 57L), low_temp = c(14L, 17L, 18L, 9L, -4L, 14L,
15L, 14L, 12L, 19L, 13L, 17L, 0L, 1L, 0L, 17L, 15L, 17L,
7L, 13L, 17L, 5L, 13L, 1L, -9L, 0L, 1L, 8L, 7L, 7L, 10L,
-1L, -4L, 8L, 16L, 12L, 5L, 12L, 19L, 15L, 13L, -5L, 19L,
8L, 15L, -1L, 8L, 12L, -2L, 14L, 4L, 0L), ln_coastline_area = c(0.2468601,
-4.60517, 0.0684028, -4.60517, -4.60517, -4.60517, 0.4696153,
-0.1668627, -0.7049121, 5.054218, 5.478362, 2.65835, -0.7015861,
0.8960881, 4.529333, 1.194601, 0.813252, 0.3411072, 1.957224,
2.026835, 2.35459, -0.084053, 1.651772, 0.0056658, -4.60517,
1.414962, 2.107577, -4.60517, 1.124865, -0.3119217, 4.555573,
-4.60517, 0.5923609, -4.60517, -0.0799525, -4.60517, -1.079278,
0.9966474, 1.723961, 1.55798, 5.383156, -4.60517, 6.983902,
-4.60517, -0.0141846, 1.947651, 0.4072272, -4.60517, 0.8589395,
-4.151253, -4.60517, -4.60517), island_dum = c(0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L), islam = c(0, 1, 13, 42, 0, 8, 20, 22, 1,
99, 0, 94, 99, 88, 32, 0.8, 16, 80, 94, 34, 0.5, 6, 14, 97,
0, 99, 3, 89, 13, 99, 13, 16, 0, 90, 45, 9, 73, 91, 39, 100,
0, 0, 0, 43, 12, 99, 33, 7, 1, 1, 0.3, 0), legor_fr = c(1L,
1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
0L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L,
0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 1L,
0L, 0L, 0L, 1L, 0L, 0L), legor_uk = c(0L, 0L, 0L, 0L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L,
0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L,
0L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L,
1L, 1L), region_n = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L), region_s = c(0L,
0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L,
1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L,
0L, 0L, 1L, 0L, 1L, 1L), region_w = c(0L, 0L, 1L, 1L, 0L,
0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L,
0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L,
0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L,
0L, 0L), region_e = c(0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L,
1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L), region_c = c(1L,
0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 1L, 0L, 0L), ln_avg_gold_pop = c(-6.614335, -2.633923,
-13.81551, -2.164328, -3.70509, -3.316046, -2.972711, -4.296489,
-3.967561, -13.81551, -13.81551, -13.81551, -13.81551, -13.81551,
-3.805913, -1.654193, 0.6532509, -0.8973768, -13.81551, -13.81551,
-13.81551, -5.279897, -1.717547, -13.81551, -13.81551, -5.472521,
-7.501954, -0.8741745, -5.648631, -1.444776, -13.81551, -13.81551,
-0.6370343, -5.203685, -11.85755, -3.503525, -3.181087, -13.81551,
-3.553395, -13.81551, -13.81551, -13.81551, -13.81551, -13.81551,
-13.81551, -13.81551, -3.161444, -2.876623, 3.084304, -2.295242,
-3.235008, 0.6928481), ln_avg_oil_pop = c(0.643126, -9.21034,
-3.531555, -9.21034, -9.21034, -9.21034, -3.270892, -0.8711616,
1.000878, -9.21034, -9.21034, -9.21034, 0.9135318, -0.3610424,
-9.21034, 2.650107, -5.899707, -9.21034, -9.21034, -9.21034,
0.3627662, -9.21034, -9.21034, 3.235896, -9.21034, -7.77914,
-9.21034, -9.21034, -9.21034, -9.21034, -9.21034, -9.21034,
-9.21034, -9.21034, 0.1340378, -9.21034, -4.488462, -9.21034,
-9.21034, -9.21034, -9.21034, -9.21034, -9.21034, -9.21034,
-9.21034, -0.3781253, -9.21034, -9.21034, -5.725029, -3.441503,
-9.21034, -9.21034), ln_avg_all_diamonds_pop = c(-1.701396,
-6.907755, -6.907755, -6.907755, 2.186849, -1.849576, -4.228216,
-6.907755, -6.907755, -6.907755, -6.907755, -6.907755, -6.907755,
-6.907755, -6.907755, -2.165953, -2.239469, -3.673854, -6.907755,
-6.907755, -6.907755, -6.907755, -2.123542, -6.907755, -3.637529,
-6.907755, -6.907755, -6.907755, -6.907755, -6.907755, -6.907755,
-6.907755, 0.2363898, -6.907755, -6.907755, -6.907755, -6.907755,
-6.907755, -1.536141, -6.907755, -6.907755, -4.457984, -6.907755,
-6.907755, -6.907755, -6.907755, -4.186928, -6.907755, -1.201608,
-0.68398, -6.907755, -5.543311), ln_pop_dens_1400 = c(-0.024917,
3.036856, 1.214196, 0.9085654, -2.075029, -0.4739045, 0.4721229,
1.020704, -0.3609614, -2.302585, -2.302585, -0.1698741, -0.404099,
1.430923, 0.3556669, -0.6607257, 1.338615, 0.6566054, 1.575844,
0.9559578, 0.8622092, 0.8193114, 0.3226074, -1.258461, -0.1520654,
1.268198, -0.074497, -0.1801779, -0.020148, -1.445708, -2.302585,
0.9706659, -2.121291, -0.586962, 1.821479, 2.945036, 0.4084752,
0.8638997, 1.618101, 0.0606283, -2.302585, -0.6176535, -2.302585,
-0.4927752, 1.470734, 1.629374, 0.4596342, 1.723667, -0.9186776,
0.4253423, -1.048586, -0.2810889), atlantic_distance_minimum = c(5.66876,
10.62621, 5.120652, 4.774938, 5.686335, 5.642056, 4.185696,
5.642056, 5.527229, 10.13065, 3.646842, 14.40755, 6.559232,
16.39266, 12.58899, 5.531399, 4.772588, 3.719985, 3.888797,
3.795674, 5.577306, 11.08334, 3.776146, 8.422357, 7.202152,
5.793966, 9.686486, 3.897489, 9.264256, 4.42371, 10.3101,
9.266991, 5.682842, 5.158515, 5.224331, 10.7538, 15.25287,
3.897721, 3.705474, 12.05779, 5.196697, 8.290959, 11.45741,
5.581032, 4.92623, 7.479859, 10.59497, 10.99569, 6.765942,
5.712497, 9.027167, 9.027167), indian_distance_minimum = c(6.980571,
2.570375, 9.233961, 9.299419, 5.764575, 8.772295, 9.457085,
8.772295, 7.923528, 1.754229, 11.59978, 2.682206, 14.91231,
4.667312, 2.705884, 8.366795, 9.299526, 10.26924, 10.79257,
10.63111, 8.556146, 2.704583, 9.777017, 16.77543, 3.035,
13.67561, 0.9039161, 10.79005, 2.185373, 11.9143, 0.0319096,
2.183153, 5.792154, 9.223114, 9.150605, 2.622741, 3.527528,
10.79068, 10.18761, 2.358296, 8.474005, 2.622083, 1.742192,
8.875547, 9.258235, 15.83294, 2.558215, 2.699154, 3.457205,
7.643048, 2.388914, 2.388914), saharan_distance_minimum = c(4.925892,
3.718742, 2.834785, 2.763519, 5.856533, 2.840084, 3.353074,
3.002548, 3.697363, 4.845693, 3.481602, 2.350743, 0.9850905,
0.4303847, 2.543248, 3.70284, 3.174178, 3.245414, 3.171976,
3.284617, 3.462215, 3.358859, 3.594752, 0.6098508, 6.637325,
1.022596, 5.731615, 2.262917, 5.267768, 2.255257, 6.273852,
4.820801, 5.980785, 1.768215, 2.641684, 3.567813, 1.827123,
3.034838, 3.473508, 3.090304, 3.6702, 6.294675, 4.635344,
1.879364, 3.009106, 0.3097339, 4.05628, 3.203552, 6.583775,
3.747742, 4.848526, 5.453967), red_sea_distance_minimum = c(3.872354,
2.215324, 3.901736, 4.239375, 4.2996, 2.293167, 4.793966,
3.051031, 3.227007, 2.609506, 6.465437, 0.0643895, 3.654165,
1.112658, 0.5100758, 3.528861, 4.332308, 5.258811, 5.637868,
5.633392, 3.515037, 1.36133, 5.2275, 2.151154, 4.845831,
4.570611, 3.453547, 4.310751, 3.298301, 4.973302, 3.883714,
2.922141, 4.685066, 2.953876, 3.314152, 2.101732, 0.983083,
5.518319, 5.409636, 0.6954757, 3.932184, 4.422592, 2.252856,
2.026491, 4.084906, 3.20461, 2.18672, 1.649949, 4.89507,
2.686999, 3.253377, 3.695537), ethnic_fractionalization = c(0.7867,
0.2951, 0.7872, 0.7377, 0.4102, 0.8295, 0.8204, 0.8635, 0.8747,
0, 0.4174, 0.7962, 0.3394, 0.1836, 0.7235, 0.769, 0.6733,
0.7389, 0.7864, 0.8082, 0.3467, 0.8588, 0.9084, 0.792, 0.255,
0.4841, 0.8791, 0.6906, 0.6932, 0.615, 0.4634, 0.6744, 0.6329,
0.6518, 0.8505, 0.3238, 0.7147, 0.6939, 0.8191, 0.8117, NA,
0.0582, 0.2025, 0.862, 0.7099, 0.0394, 0.7353, 0.9302, 0.7517,
0.8747, 0.7808, 0.3874), state_dev = c(0.635, 0.995, 0.695,
0.338, 0.893, 0.144, 0.082, 0.316, 0.536, 1, NA, 0.133, 0.99,
0.99, 0.843, 0.011, 0.651, 0.406, 0.426, 0.214, 0.211, 0.172,
0, 0.94, 1, 0.81, 0.505, 0.115, 0.844, 0.858, NA, 0.861,
0.664, 0.582, 0.478, 0.982, 0.576, 0.694, 0.008, 0.034, NA,
1, NA, 0.384, 0.622, 0.98, 0.669, 0.634, NA, 0.649, 0.743,
0.965), land_area = c(1.25, 0.0278, 0.113, 0.274, 0.6, 0.623,
0.322, 0.475, 0.342, 0.00217, 0.00403, 0.022, 2.38, 1, 1.22,
0.268, 0.239, 0.246, 0.0113, 0.0361, 0.0281, 0.583, 0.111,
1.76, 0.0304, 0.447, 0.587, 1.24, 0.802, 1.03, 0.00186, 0.118,
0.824, 1.27, 0.924, 0.0263, 2.51, 0.196, 0.0717, 0.638, 0.00096,
0.0174, 0.000455, 1.28, 0.0568, 0.164, 0.945, 0.236, 1.22,
2.35, 0.753, 0.391), stage1 = c(2.01310178962912, 3.27246381305353,
5.35639168025068, 5.91184836065855, 1.05526739235966, 5.16708434318269,
5.07687379044942, 4.77009597973404, 4.15863470510818, 2.07294773749099,
3.12168352262372, 1.51620481461539, 1.7500720543329, 1.40710379910631,
3.41028983224398, 3.65368793863828, 4.91474434088887, 5.06042577393594,
4.44344092292367, 4.46841489797154, 3.97186132841912, 3.40263869963118,
4.67529406834981, -1.82253414812983, 0.151421774947407, 4.01732607566164,
1.4293632764156, 6.65069002995716, 1.71011443496853, 4.74511489084807,
0.244087584882236, 2.79795925529004, 0.726391664388915, 7.91724568619572,
5.78273806073103, 3.41515174873482, 0.752703025744719, 4.76792093974516,
4.61325345534811, 3.15668762557839, 4.05476681343383, 0.00815576315910405,
0.855615157261806, 7.47388924450179, 5.16048051732826, 1.17712597142371,
2.5050250342168, 3.90137319769041, 0.39239658701787, 4.10077923691789,
2.81956584642736, 1.34457256371601)), .Names = c("isocode",
"country", "ln_maddison_pcgdp2000", "ln_export_area", "ln_export_pop",
"colony0", "colony1", "colony2", "colony3", "colony4", "colony5",
"colony6", "colony7", "abs_latitude", "longitude", "rain_min",
"humid_max", "low_temp", "ln_coastline_area", "island_dum", "islam",
"legor_fr", "legor_uk", "region_n", "region_s", "region_w", "region_e",
"region_c", "ln_avg_gold_pop", "ln_avg_oil_pop", "ln_avg_all_diamonds_pop",
"ln_pop_dens_1400", "atlantic_distance_minimum", "indian_distance_minimum",
"saharan_distance_minimum", "red_sea_distance_minimum", "ethnic_fractionalization",
"state_dev", "land_area", "stage1"), row.names = c(NA, -52L), class = "data.frame")
0 个答案:
没有答案
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