SUPPORTING INFORMATION
Online Appendix for
Dictators and Death: Casualty Sensitivity of Autocracies in Militarized Interstate Disputes
Cigdem V. Sirin
Michael T. Koch
Contents
Table A1. Descriptive Statistics
Table A2. Sensitivity Analyses with the Minimum and Maximum MID Casualty Values
Table A3. Replicating the Analyses with Casualty Rate and Casualty Per Capita Measures
Table A4. Heckman Two-Stage Selection Models - Full Table with All Covariates
Table A5. Variance Inflation Factors
Table A6. Sensitivity Analyses with Lagged Measures
Table A7. The Number of Casualties Sustained in Militarized Interstate Disputes - Lai and
Slater’s Typology
Table A8. Replicating the Analyses with Alternative Casualty Codings - Lai and Slater’s
Typology
Table A9. Replicating the Analyses with Casualty Rate and Casualty Per Capita Measures - Lai
and Slater’s Typology
Table A10. Heckman Two-Stage Selection Models - Lai and Slater’s Typology
Table A11. Sensitivity Analyses with Lagged Measures - Lai and Slater’s Typology
Table A12. Replicating the Analyses with an Alternative Autocracy Measure “Dictator”
Table A13. Sensitivity Analyses with Hybrid Regimes and Monarchies
Table A14. Sensitivity Analyses with Authoritarian Regimes’ (1) Winning Coalition Size and
(2) Ratio of the Winning Coalition Size to the Selectorate
Table A15. Sensitivity Analyses with Authoritarian Regimes’ (1) Repression, (2) Number of
Veto Players, and (3) Political Constraints
Table A16. Sensitivity Analyses with Authoritarian Regimes’ (1) Competitiveness, (2)
Contestation, and (3) Inclusiveness
Table A17. Sensitivity Analyses with Additional Controls
Table A18. Sensitivity Analyses with Panel Corrected Standard Errors (PSCEs)
Additional Notes
Variables
Casualties
Personalist regimes
Single-party regimes
Military regimes
Relative capabilities (ln)
Population (ln)
Military personnel size (ln)
Democratic adversary
Alliance
Contiguity
Initiation
Duration
Economic development (ln)
TABLE A1. Descriptive Statistics
Mean
Standard Deviation
2293.29 33205.38
0.26
0.44
0.34
0.47
0.08
0.27
-0.93
1.20
10.13
1.69
5.35
1.76
0.90
0.31
0.20
0.40
0.11
0.32
0.75
0.43
343.88
679.99
9.94
3.11
2
Minimum
0.00
0.00
0.00
0.00
-9.55
2.94
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Maximum
500000.00
1.00
1.00
1.00
0.00
14.06
9.43
1.00
1.00
1.00
1.00
4058.00
15.48
TABLE A2. Sensitivity Analyses with the Minimum and Maximum MID Casualty Values
MID Casualties - Minimum
MID Casualties - Maximum
Model 1
Model 2
Single-party regimes
-14878.84***
-14884.18***
(4345.87)
(4344.38)
Military regimes
-32288.13***
-32277.45***
(5606.06)
(5604.12)
Relative capabilities (ln)
-2740.70
-2742.99
(1782.15)
(1781.53)
Population (ln)
-6508.46**
-6503.47**
(2108.16)
(2107.43)
Military personnel size (ln)
5132.49**
5126.07**
(1832.92)
(1832.28)
Democratic adversary
-2423.69
-2425.55
(4115.92)
(4114.50)
Alliance
-4695.01
-4703.94
(5233.87)
(5232.07)
Contiguity
7797.56†
7803.84†
(4183.04)
(4181.59)
Initiation
8323.13†
8325.73†
(4967.56)
(4965.85)
Duration
43.04***
43.08***
(3.34)
(3.34)
Economic development (ln)
1603.90
1604.92
(1018.07)
(1017.72)
Constant
17543.89
17516.20
(16392.67)
(16387.02)
Wald χ2
267.05***
267.67***
Observations
723
723
(Notes. “Personalist regimes” is the reference category. GLS random-effects linear regression. ***p <
.001; **p < .01; *p < .05; †p < .10. Two-tailed tests.)
3
TABLE A3. Replicating the Analyses with Casualty Rate and Casualty Per Capita Measures
Casualty Rate
Casualty Per Capita
Model 3
Model 4
Single-party regimes
-384.07 (113.45)***
-1.115 (0.29)***
Military regimes
-557.87 (138.26)***
-2.318 (0.38)***
Relative capabilities (ln)
-36.36 (46.12)
-0.245 (0.12)*
Population (ln)
-132.31 (53.91)**
Military personnel size (ln)
177.70 (45.88)***
0.139 (0.11)
Democratic adversary
-116.64 (107.87)
-0.240 (0.28)
Alliance
123.19 (130.35)
-0.182 (0.35)
Contiguity
152.87 (113.60)
0.374 (0.28)
Initiation
163.47 (108.20)
0.620 (0.34)†
Duration
0.41 (0.07)***
0.003 (0.00)***
Economic development (ln) 11.56 (25.80)
0.041 (0.07)
Constant
314.39 (418.97)
-1.466 (0.69)*
Wald χ2
86.61***
252.60***
Observations
485
723
(Notes. “Personalist regimes” is the reference category. GLS random-effects linear regression. ***p <
.001; **p < .01; *p < .05; †p < .10. Two-tailed tests.)
4
TABLE A4. Heckman Two-Stage Selection Models - Full Table with All Covariates
Model 5
Stage 1: Conflict initiation
Single-party regimes
-0.297 (0.14)**
Military regimes
0.248 (0.20)
New/unstable regime
-0.133 (0.14)
Military capabilities, Side A
29.646 (7.53)***
Military capabilities, Side B
6.819 (2.41)**
Side A’s prop. of dyadic cap.
0.378 (0.19)*
Trade dependency
272.258 (115.25)*
Majmaj
-4.564 (0.94)***
Minmaj
-0.756 (0.31)*
Majmin
-3.888 (0.83)***
Democratic adversary
0.445 (0.16)**
Contiguity
0.013 (0.43)
Distance (ln)
0.065 (0.07)
Alliance portfolio similarity
-0.183 (0.27)
Alli. port. sim. with the US_1
-0.171 (0.35)
Alli. port. sim. with the US_2
-0.788 (0.29)**
Peace years
0.024 (0.01)***
Constant
0.477 (0.58)
Stage 2: # of casualties suffered
Single-party regimes
-12687.35 (4647.58)**
Military regimes
-33510.18 (5828.13)***
Relative capabilities (ln)
-2570.57 (1847.02)
Population (ln)
-6109.67 (2227.18)**
Military personnel size (ln)
4787.67 (1928.86)**
Democratic adversary
-4826.01 (4671.63)
Alliance
-3734.31 (5568.19)
Contiguity
8207.05 (4325.53)†
Duration
41.09 (3.01)***
Economic development (ln)
1297.36 (1096.42)
Constant
29426.50 (16638.19)†
Wald χ2
263.61***
Observations
833
(Notes. “Personalist regimes” is the reference category. ***p < .001; **p < .01; *p < .05; †p < .10. Twotailed tests.)
5
TABLE A5. Variance Inflation Factors
Variables
VIF
1/VIF
Population (ln)
3.28
0.31
Military personnel size (ln)
3.25
0.31
Economic development (ln)
2.52
0.40
Single-party regimes
1.5
0.67
Duration
1.48
0.68
Initiation
1.32
0.76
Democratic adversary
1.31
0.76
Military regimes
1.3
0.77
Relative capabilities (ln)
1.29
0.78
Contiguity
1.23
0.81
Alliance
1.21
0.82
Mean VIF
1.79
6
TABLE A6. Sensitivity Analyses with Lagged Measures
Model 6
Single-party regimes
-15948.74***
(4753.93)
Military regimes
-31252.49***
(6099.56)
Relative capabilities (ln)
-3059.51
(1926.10)
Population (ln)
-6658.75**
(2277.46)**
Military personnel size (ln)
5521.34
(1997.26)
Democratic adversary
-2988.77
(4454.88)
Alliance
-6753.54
(5800.20)
Contiguity
8792.74*
(4573.63)
Initiation
3142.86
(5280.03)
Duration
36.46***
(3.55)
Economic development (ln)
1641.84
(1123.70)
Constant
21988.11
(17780.81)
Wald χ2
195.92***
Observations
691
(Notes. Dependent variable is the number of casualties sustained by an autocracy in a militarized dispute.
“Personalist regimes” is the reference category. GLS random-effects linear regression. ***p < .001; **p
< .01; *p < .05; †p < .10. Two-tailed tests.)
7
TABLE A7. The Number of Casualties Sustained in Militarized Interstate Disputes
Lai and Slater’s Typology
Model 7
Model 8
Personalist (unconstrained) regimes
13271.62 (3799.46)***
Strongman
-9757.25 (4932.18)*
Machine
-11503.39 (5007.81)*
Junta
-24654.91 (5833.31)***
Relative capabilities (ln)
-1177.66 (1825.92)
-1060.81 (1820.82)
Population (ln)
-5673.56 (2063.13)**
-4914.60 (2082.85)*
Military personnel size (ln)
3202.94 (1929.15)†
2144.60 (1963.38)
Democratic adversary
-2749.43 (3912.04)
-2570.43 (3914.26)
Alliance
-1728.16 (5013.14)
-1260.25 (5014.86)
Contiguity
6403.60 (4433.94)*
7270.46 (4549.12)
Initiation
11543.06 (4791.87)*
11763.21 (4779.32)*
Duration
39.37 (3.23)***
40.02 (3.31)***
Economic development (ln)
2277.13 (1136.70)*
1454.94 (1179.06)
Constant
-9629.11 (17269.54)
12568.83 (16641.79)
Wald χ2
216.95***
225.49***
Observations
761
761
(Notes. “Bossism” is the reference category in Model 8. GLS random-effects linear regression. ***p <
.001; **p < .01; *p < .05; †p < .10. Two-tailed tests.)
8
TABLE A8. Replicating the Analyses with Alternative Casualty Codings
Lai and Slater’s Typology
Casualty vs. no-casualty
High vs. low- or nodisputes
casualty disputes
Model 9
Model 10
Model 11
Model 12
Personalist (unconstrained) regimes 0.837***
0.811†
(0.231)
(0.469)
Strongman
0.384
0.612
(0.273)
(0.592)
Machine
-0.811**
0.791
(0.325)
(0.574)
Junta
-0.447
-4.425***
(0.366)
(1.283)
Relative capabilities (ln)
-0.392***
-0.413***
0.413
0.441
(0.109)
(0.111)
(0.322)
(0.328)
Population (ln)
0.400***
0.392**
-0.296
0.123
(0.124)
(0.126)
(0.265)
(0.315)
Military personnel size (ln)
-0.210†
-0.174
0.405†
0.148
(0.113)
(0.116)
(0.238)
(0.259)
Democratic adversary
-0.798***
-0.827***
-0.444
-0.588
(0.228)
(0.230)
(0.460)
(0.489)
Alliance
-0.956**
-0.932**
-0.739
-0.942
(0.310)
(0.308)
(0.700)
(0.754)
Contiguity
1.501***
1.444***
2.168*
1.615
(0.318)
(0.325)
(1.052)
(1.061)
Initiation
-0.271
-0.248
-0.601
-0.336
(0.263)
(0.264)
(0.441)
(0.467)
Duration
0.003***
0.003***
0.001***
0.002***
(0.000)
(0.000)
(0.000)
(0.000)
Economic development (ln)
-0.153*
-0.133*
-0.220†
-0.350**
(0.062)
(0.066)
(0.121)
(0.139)
Constant
-4.767***
-4.424
-2.287
-3.530
(1.053)
(1.081)
(2.315)
(2.518)
LR χ2
293.61***
296.00***
62.64***
84.29***
Observations
761
761
761
761
(Notes. “Bossism” is the reference category for Models 10 and 12. Binary Logistic Regression. ***p <
.001; **p < .01; *p < .05; †p < .10. Two-tailed tests.)
9
TABLE A9. Replicating the Analyses with Casualty Rate and Casualty Per Capita Measures
Lai and Slater’s Typology
Casualty Rate
Casualty Per Capita
Model 13
Model 14
Model 15
Model 16
Personalist (unconstrained) regimes 205.06*
0.960***
(88.06)
(0.26)
Strongman
-198.13†
-0.689*
(114.59)
(0.33)
Machine
-220.82†
-0.777*
(117.73)
(0.34)
Junta
-371.04**
-1.818***
(135.85)
(0.39)
Relative capabilities (ln)
-1.97
-0.10
-0.172
-0.149
(44.00)
(43.96)
(0.12)
(0.12)
Population (ln)
-112.70*
-102.50*
(49.68)
(50.42)
Military personnel size (ln)
124.23**
109.25*
0.038
-0.016
(45.16)
(45.93)
(0.12)
(0.12)
Democratic adversary
-114.96
-104.12
-0.216
-0.201
(92.62)
(92.90)
(0.26)
(0.26)
Alliance
177.84
176.07
-0.003
0.018
(116.54)
(117.01)
(0.34)
(0.33)
Contiguity
128.75
165.25
0.340
0.406
(112.10)
(115.47)
(0.30)
(0.30)
Initiation
164.41†
166.03†
0.796**
0.818**
(98.47)
(98.38)
(0.32)
(0.32)
Duration
0.39***
0.39***
0.003***
0.003***
(0.07)
(0.07)
(0.00)
(0.00)
Economic development (ln)
11.20
-0.89
0.088
0.035
(27.24)
(28.29)
(0.07)
(0.07)
Constant
-16.15
334.49
-3.025***
-1.058
(419.66)
(405.53)
(0.78)
(0.77)
2
Wald χ
67.24***
71.09***
206.06***
216.98***
Observations
553
553
761
761
(Notes. “Bossism” is the reference category in Models 14 and 16. GLS random-effects linear regression.
***p < .001; **p < .01; *p < .05; †p < .10. Two-tailed tests.)
10
TABLE A10. Heckman Two-Stage Selection Models
Lai and Slater’s Typology
Model 17
Model 18
Stage 1: Conflict initiation
Personalist (unconstrained) regimes
-0.011 (0.13)
Strongman
0.176 (0.15)
Machine
-0.286 (0.16)†
Junta
0.839 (0.24)***
New/unstable regime
0.238 (0.16)
0.164 (0.17)
Military capabilities, Side A
19.909 (5.21)***
23.508 (5.32)***
Military capabilities, Side B
3.647 (2.34)
3.728 (2.37)
Side A’s prop. of dyadic cap.
0.076 (0.19)
0.051 (0.20)
Trade dependency
280.620 (126.50)*
257.116 (116.57)*
Majmaj
-3.566 (0.74)***
-3.832 (0.75)***
Minmaj
-0.614 (0.34)†
-0.637 (0.34)†
Majmin
-2.934 (0.64)***
-3.163 (0.65)***
Democratic adversary
0.030 (0.13)
-0.023 (0.13)
Contiguity
0.341 (0.46)
0.278 (0.45)
Distance (ln)
0.112 (0.06)†
0.106 (0.06)†
Alliance portfolio similarity
-0.802 (0.25)***
-0.856 (0.25)***
Alli. port. sim. with the US_1
-0.407 (0.33)
-0.405 (0.34)
Alli. port. sim. with the US_2
-0.276 (0.27)
-0.236 (0.27)
Peace years
0.016 (0.01)*
0.015 (0.01)*
Constant
0.623 (0.59)
0.634 (0.57)
Stage 2: # of casualties suffered
Personalist (unconstrained) regimes
14094.09 (4026.98)***
Strongman
-11130.98 (5205.15)*
Machine
-11821.59 (5175.29)*
Junta
-27744.14 (6938.49)***
Relative capabilities (ln)
-1181.21 (1884.89)
-1073.16 (1874.24)
Population (ln)
-4693.97 (2266.01)*
-4094.42 (2239.97)†
Military personnel size (ln)
2653.73 (2059.64)
1539.50 (2104.68)
Democratic adversary
-4013.84 (4195.25)
-3602.29 (4157.88)
Alliance
-441.09 (5328.11)
-75.11 (5313.48)
Contiguity
6659.17 (4715.91)
7496.41 (4814.88)
Duration
36.09 (2.86)***
36.52 (2.94)***
Economic development (ln)
2160.86 (1204.27)†
1330.96 (1256.33)
Constant
-1895.41 (17454.93)
23246.54 (16974.88)
Wald χ2
210.08***
216.73***
Observations
873
873
(Notes. “Bossism” is the reference category in Model 18. ***p < .001; **p < .01; *p < .05; †p < .10.
Two-tailed tests.)
11
TABLE A11. Sensitivity Analyses with Lagged Measures
Lai and Slater’s Typology
Model 19
Model 20
Personalist (unconstrained) regimes
13008.92***
(4072.46)
Strongman
-10792.31*
(5332.46)
Machine
-13097.49*
(5362.17)
Junta
-23291.90***
(6364.34)
Relative capabilities (ln)
-1246.51
-1216.21
(1972.32)
(1968.77)
Population (ln)
-5790.56**
-5088.62*
(2198.50)
(2226.70)
Military personnel size (ln)
3121.64
2037.31
(2091.88)
(2137.72)
Democratic adversary
-3461.60
-3012.96
(4162.44)
(4169.86)
Alliance
-3535.85
-2860.52
(5507.09)
(5532.93)
Contiguity
6392.92
7925.54†
(4778.33)
(4929.33)
Initiation
5854.88
5941.85
(5040.84)
(5033.96)
Duration
31.56***
31.73***
(3.33)
(3.43)
Economic development (ln)
2385.55*
1702.64
(1238.11)
(1283.58)
Constant
-1898.91
19497.19
(18601.07)
(17832.97)
Wald χ2
149.07***
155.33***
Observations
735
735
(Notes. Dependent variable is the number of casualties sustained by an autocracy in a militarized dispute.
“Bossism” is the reference category for Model 20. GLS random-effects linear regression. ***p < .001;
**p < .01; *p < .05; †p < .10. Two-tailed tests.)
12
TABLE A12. Replicating the Analyses with an Alternative Autocracy Measure “Dictator” Adopted from the Institutions and Elections Project (IAEP)
Model 21
Dictator
11206.44*
(4714.32)
Relative capabilities (ln)
-2775.82
(2507.30)
Population (ln)
-7601.48**
(3016.41)
Military personnel size (ln)
4829.92*
(2302.40)
Democratic adversary
-7326.65
(5243.69)
Alliance
-7436.44
(5710.44)
Contiguity
1665.24
(5322.43)
Initiation
6716.35
(6154.69)
Duration
42.41*
(3.67)
Economic development (ln)
2616.79
(1859.58)
Constant
10325.03
(23171.33)
2
Wald χ
209.89***
Observations
612
(Notes. Dependent variable is the number of casualties sustained by an autocracy in a militarized dispute.
GLS random-effects linear regression. ***p < .001; **p < .01; *p < .05; †p < .10. Two-tailed tests.)
13
TABLE A13. Sensitivity Analyses with Hybrid Regimes and Monarchies
Model 22
Single-party regimes
-14930.11*
(7848.38)
Military regimes
-30852.76†
(21255.45)
Monarchies
-13811.44*
(7862.42)
Single-party/military regimes
-6912.66†
(4766.58)
Single-party/personalist regimes
-30743.00†
(19061.09)
Military/personalist regimes
-10154.75*
(6055.54)
Single-party/military/personalist regimes
-15689.46*
(8691.33)
Relative capabilities (ln)
-2115.63
(2329.00)
Population (ln)
-4844.28*
(2846.38)
Military personnel size (ln)
3689.90†
(2594.16)
Democratic adversary
-3831.48
(3886.86)
Alliance
-3614.75
(3356.81)
Contiguity
6065.18
(6346.18)
Initiation
9247.78
(9088.95)
Duration
38.87
(35.95)
Economic development (ln)
1363.03
(1282.27)
Constant
13066.84
(20472.28)
2
Wald χ
15.72
Observations
981
(Notes. Dependent variable is the number of casualties sustained by an autocracy in a militarized dispute.
“Personalist regimes” is the reference category. GLS random-effects linear regression. ***p < .001; **p
< .01; *p < .05; †p < .10. One-tailed tests.)
14
TABLE A14. Sensitivity Analyses with Authoritarian Regimes’
(1) Winning Coalition Size and (2) Ratio of the Winning Coalition Size to the Selectorate
Model 23
Model 24
Winning coalition size
-39232.60***
(8822.03)
Winning coalition/Selectorate
-40400.10***
(8830.33)
Relative capabilities (ln)
-1776.72
-1872.79
(1815.78)
(1844.15)
Population (ln)
-7351.87***
-7035.92***
(2185.27)
(2214.43)
Military personnel size (ln)
5591.12**
5523.21**
(1872.65)
(1891.84)
Democratic adversary
-2968.66
-2831.51
(4240.251)
(4293.70)
Alliance
-5978.43
-6046.28
(5320.49)
(5392.99)
Contiguity
6029.85
6238.82
(4287.99)
(4354.00)
Initiation
7448.55
7284.44
(5118.94)
(5156.09)
Duration
41.45***
41.80***
(3.31)
(3.33)
Economic development (ln)
2484.38*
2470.14**
(1028.79)
(1042.81)
Constant
23484.38
21423.11
(16790.62)
(16931.91)
2
Wald χ
243.38***
243.55***
Observations
709
700
(Notes. Dependent variable is the number of casualties sustained by an autocracy in a militarized dispute.
GLS random-effects linear regression. ***p < .001; **p < .01; *p < .05; †p < .10. Two-tailed tests
15
TABLE A15. Sensitivity Analyses with Authoritarian Regimes’ (1) Repression, (2) Number of Veto Players, and (3) Political Constraints
Model 25
Model 26
Model 27
Model 28
Model 29
Model 30
Repression
5554.91***
-4224.86*
(1510.90)
(1812.11)
Number of veto players
-8598.04***
-20644.73***
(2206.43)
(3793.58)
Political constraints
-37048.90***
-48423.04***
(9037.84)
(12419.37)
Single-party regimes
-27117.22**
-23978.29***
-10732.21†
(9056.59)
(7310.72)
(5607.53)
Military regimes
-68880.83***
-54000.41***
-37600.41***
(13848.87)
(10459.00)
(7185.51)
Relative capabilities (ln)
-4300.37
-10167.18*
-1612.23
-8905.65**
-1509.63
-6783.18**
(3494.43)
(4189.31)
(2732.58)
(3527.01)
(1613.22)
(2346.76)
Population (ln)
-10625.43**
-6885.81
-9089.12**
-10602.85**
-7009.45***
-10315.86***
(4116.37)
(6030.33)
(3102.86)
(4290.78)
(1976.76)
(2875.21)
Military personnel size (ln)
4476.45
6759.99†
4553.64†
5235.82
3988.04*
7167.69**
(3184.79)
(4136.31)
(2503.47)
(3283.86)
(1651.34)
(2359.76)
Democratic adversary
-8230.83
-9967.52
-3309.66
-11636.20
-5400.05
-7191.67
(6748.57)
(8555.66)
(5535.94)
(7307.74)
(3566.97)
(5253.75)
Alliance
-6186.57
-10218.80
-3773.40
-6017.40
-2192.26
-5025.56
(7770.64)
(10482.44)
(6091.99)
(8521.43)
(4234.99)
(6410.50)
Contiguity
8049.99
19293.80*
3553.03
10872.64
4094.37
12387.21*
(6911.32)
(8528.43)
(5704.81)
(7195.04)
(3797.62)
(5223.98)
Initiation
7217.13
-4042.97
10252.08
7281.91
9131.43*
8386.20
(8301.03)
(10111.51)
(6632.58)
(8180.24)
(4451.72)
(6188.14)
Duration
55.60***
62.08***
49.45***
62.70***
40.16***
47.95***
(5.01)
(5.90)
(4.08)
(4.99)
(2.99)
(3.84)
Economic development (ln)
4733.91†
7026.72
3827.76†
6620.38*
1959.03*
3169.81*
(2842.19)
(4369.01)
(2182.14)
(3218.23)
(898.79)
(1408.90)
Constant
29940.12
-27422.09
24893.09
34216.78
19094.97
26857.89
(29823.15)
(41528.80)
(23313.62)
(32245.47)
(15244.33)
(22215.55)
Wald χ2
214.55***
245.33***
221.08***
281.93***
256.53***
264.71***
Observations
419
316
566
405
850
576
(Notes. Dependent variable is the number of casualties sustained by an autocracy in a militarized dispute. “Personalist regimes” is the reference category for
Models 26, 28, and 30. GLS random-effects linear regression. ***p < .001; **p < .01; *p < .05; †p < .10. Two-tailed tests.)
16
TABLE A16. Sensitivity Analyses with Authoritarian Regimes’ (1) Competitiveness, (2) Contestation, and (3) Inclusiveness
Model 31
Model 32
Model 33
Model 34
Model 35
Model 36
Competitiveness
-3882.06**
-5799.49***
(1248.02)
(1775.34)
Contestation
-6243.56**
-13369.22***
(2272.37)
(3885.68)
Inclusiveness
-625.76
-1806.59
(1313.45)
(2106.52)
Single-party regimes
-25561.95***
-11203.75*
-14277.13**
(7536.67)
(4712.21)
(4717.00)
Military regimes
-63562.87***
-28880.96***
-34559.55***
(10467.26)
(5966.76)
(6018.77)
Relative capabilities (ln)
-1667.66
-9326.62**
-723.92
-3081.45†
-757.25
-3000.98
(2763.26)
(3634.48)
(1292.93)
(1841.71)
(1297.80)
(1858.52)
Population (ln)
-9865.15**
-11400.77**
-4662.00**
-7086.05**
-4991.25*
-6563.81**
(3123.82)
(4422.62)
(1618.63)
(2245.12)
(1621.46)
(2260.47)
Military personnel size (ln)
4791.34†
4925.99
2331.75†
3966.07*
3208.29
5524.56**
(2559.34)
(3516.78)
(1389.88)
(1960.63)
(1371.71)
(1951.76)
Democratic adversary
-4167.09
-11077.66
-3668.05
-2461.88
-3602.35
-2020.01
(5581.49)
(7526.09)
(2944.50)
(4273.72)
(2955.57)
(4306.70)
Alliance
-4707.99
-2385.91
-922.88
-4090.44
-1846.52
-4116.16
(6135.09)
(8800.25)
(3621.11)
(5578.54)
(3621.03)
(5630.77)
Contiguity
5965.96
14010.34†
980.96
7524.26†
1275.23
7914.12†
(5828.75)
(7457.20)
(3209.49)
(4367.33)
(3219.66)
(4401.66)
Initiation
6873.89
4300.59
9389.32**
8952.02†
8814.32*
8881.78†
(6627.44)
(8329.50)
(3708.35)
(5209.98)
(3715.59)
(5253.87)
Duration
43.78***
53.76***
37.15****
45.36***
36.43***
43.77***
(3.87)
(4.81)
(2.65)
(3.47)
(2.65)
(3.47)
Economic development (ln)
3621.03†
8940.73**
1612.18*
2430.51*
1249.11†
1652.71
(2202.21)
(3386.02)
(704.73)
(1088.72)
(698.99)
(1072.04)
Constant
36945.82
14270.48
3039.99
9315.06
9610.01
14267.04
(23423.35)
(32689.07)
(12813.44)
(17359.32)
(12663.88)
(17454.08)
Wald χ2
201.53***
240.31***
265.45***
274.04***
256.28***
258.71***
Observations
569
407
1026
691
1026
691
(Notes. Dependent variable is the number of casualties sustained by an autocracy in a militarized dispute. “Personalist regimes” is the reference category for
Models 32, 34, and 36. GLS random-effects linear regression. ***p < .001; **p < .01; *p < .05; †p < .10. Two-tailed tests.)
17
TABLE A17. Sensitivity Analyses with Additional Controls
Model 37
Model 38
Single-party regimes
-19218.48 (5303.96)***
Military regimes
-38869.43 (6973.97)***
Personalist (unconstrained) regimes
16539.09 (4293.38)***
Strongman
Machine
Junta
Conscription
-9813.93 (6797.24)
6.21 (6148.18)
Peace years
62.43 (140.44)
103.26 (191.84)
Adversary’s aims
-5227.71 (6125.40)
-17380.53 (5293.18)***
Reciprocation
-741.45 (4630.68)
-3345.31 (4502.09)
Dispute outcome
-4232.50 (10915.50)
-4015.43 (10169.23)
Relative capabilities (ln)
-2549.55 (2285.76)
1574.42 (2205.17)
Population (ln)
-5630.75 (2712.07)*
-5816.55 (2481.44)*
Military personnel size (ln)
4225.69 (2418.87)†
5174.06 (2563.16)*
Democratic adversary
-1841.16 (4618.57)
-5989.47 (4394.61)
Alliance
-6114.33 (6092.80)
-2009.60 (5584.62)
Contiguity
11606.61 (4936.07)*
12930.10 (5239.50)*
Initiation
6538.19 (5593.57)
8442.97 (5199.47)†
Duration
43.28 (3.70)***
39.93 (3.46)***
Economic development (ln)
1513.14 (1212.93)
1713.62 (1269.68)
Constant
18410.06 (18993.96)
-13116.64 (19437.48)
2
Wald χ
252.11***
219.68***
Observations
652
697
Model 39
-13377.08 (5521.25)*
-16938.06 (5708.35)**
-28489.16 (6699.28)***
2.62 (6141.20)
89.16 (191.54)
-17857.32 (5469.72)***
-2350.40 (4516.42)
-7068.02 (10268.61)
-1080.62 (2210.67)
-4932.00 (2508.35)*
3675.84 (2626.95)
-5219.26 (4388.43)
-1646.22 (5570.40)
15140.06 (5408.12)**
8694.16 (5183.22)†
40.00 (3.57)****
921.41 (1317.98)
13707.58 (18612.35)
228.75***
697
(Notes. Dependent variable is the number of casualties sustained by an autocracy in a militarized dispute. “Personalist regimes” is the reference
category for Model 37. “Bossism” is the reference category for Model 39. GLS random-effects linear regression. ***p < .001; **p < .01; *p <
.05; †p < .10. Two-tailed tests.)
18
Additional Notes
*As Clark and Linzer (forthcoming) suggest, compared to fixed effects (FE) models, random
effects (RE) models are likely to produce better estimates of β when there are few observations
per unit. This is the case for our dataset in which many autocracies engage in few militarized
interstate disputes within the given time period. Furthermore, by removing the higher-level
variance, the FE models result in the loss of a large amount of critical information (Bell and
Jones 2015). Specifically, FE would lead to the absorption of the effects of our time-invariant
variables (such as contiguity—an important factor in estimating casualties) by the intercept.
Even for “almost” time-invariant variables—variables that are not fully constant but rarely
change over time (such as a dyad’s state of peace)—the effects of such variables are largely
filtered out in the FE model (Bell and Jones 2015; see also Beck and Katz 2001; Plümper and
Troeger 2007). This would be particularly problematic for our analyses since the specific regime
type of many autocracies rarely changes during the time period under study. Accordingly, the
RE (rather than FE) model is a more suitable methodological approach for our purpose here.
BECK, NATHANIEL, AND JONATHAN N. KATZ. (2001) Throwing out the Baby with the Bath
Water: A Comment on Green, Kim, and Yoon. International Organization 55: 487-495.
BELL, ANDREW, AND KELVYN JONES. (2015) Explaining Fixed Effects: Random Effects
Modeling of Time-Series Cross-Sectional and Panel Data. Political Science Research and
Methods 3: 133-153.
CLARK, TOM S., AND DREW A. LINZER. Should I Use Fixed or Random Effects? Political Science
Research and Methods (forthcoming).
PLÜMPER, THOMAS, AND VERA E. TROEGER. (2007) Efficient Estimation of Time-Invariant and
Rarely Changing Variables in Finite Sample Panel Analyses with Unit Fixed
Effects. Political Analysis 15:124-139.
*As part of our robustness checks, we also control for the severity of the dispute since the level
of casualties is likely to rise with the escalation of the dispute. However, including a control for
the severity of conflict (using the MID hostility level measure) leads to high multicollinearity
because the hostility level variable is highly correlated with the ordinal fatality scale. Given this
issue, we exclude this control from our models.
*As alternative economic indicators, we use GDP per capita and trade openness measures for
robustness purposes. While the results are consistent with our main analyses, our sample size is
substantively reduced due to a large amount of missing data (particularly for earlier periods) for
these indicators. As such, we retain energy consumption as our main measure of economic
development.
*With time-series cross-section data, it is desirable to use panel-corrected standard errors
(PCSEs) as Beck and Katz (1995:644-5) suggest. However, the nature of our dataset precludes
the efficient use of PCSE. Because the observations in the dataset consist of autocracies that
engaged in a militarized dispute in a given year, there exist gaps in time periods for various
countries who did not engage in a dispute within that period, resulting in computations for rho
restarted at each time gap. Such data structure also produces uncommon time periods between
panels. Dropping panel units with very small number of observations (to resolve the issue of
19
uncommon time periods) would lead to a significant decline in the overall number of
observations and thus reduce the statistical power of our analyses. Despite these concerns,
however, running PSCE models using pairwise covariances between panel units generates results
consistent with those we obtain using GLS random-effects models (see Table A18 below).
BECK, NATHANIEL, AND JONATHAN N. KATZ. (1995) What to Do (and Not to Do) with TimeSeries Cross-Section Data. American Political Science Review 89: 634-647.
TABLE A18. Sensitivity Analyses with Panel Corrected Standard Errors (PSCEs)
Model 40
Model 41
Model 42
Single-party regimes
-9703.21*
(5059.16)
Military regimes
-19502.28**
(6255.28)
Personalist (unconstrained) regimes
8843.92**
(3359.26)
Strongman
-5631.40
(4477.42)
Machine
-7030.38†
(3884.32)
Junta
-16581.89**
(5416.43)
Relative capabilities (ln)
-1467.68
-1906.70†
-1858.20†
(977.38)
(1070.04)
(1099.09)
Population (ln)
-4354.08*
-3334.25
-2946.65
(2278.64)
(2207.16)
(2171.64)
Military personnel size (ln)
3468.37†
2306.43
1603.61
(2095.14)
(1697.74)
(1574.21)
Democratic adversary
-1005.23
-936.03
-924.30
(2657.08)
(2569.88)
(2606.43)
Alliance
-1172.35
2111.58
2233.61
(3681.47)
(3426.50)
(3502.07)
Contiguity
3101.38
2659.29
2758.87
(2607.17)
(2965.73)
(3001.33)
Initiation
6399.51**
5662.28*
5778.22*
(2600.51)
(2329.31
(2399.77)
Duration
41.81***
37.71***
37.96***
(4.77)
(4.00)
(4.09)
Economic development (ln)
984.83
1414.33†
1033.04
(652.27)
(839.69)
(815.49)
Constant
11164.07
-11767.25
2717.98
(15032.68)
(13570.20)
(16368.25)
Wald χ2
95.07***
110.00***
115.92***
Observations
723
761
761
(Notes. Dependent variable is the number of casualties sustained by an autocracy in a militarized dispute.
“Personalist regimes” is the reference category for Model 40. “Bossism” is the reference category for
Model 42. Prais-Winsten Regression. ***p < .001; **p < .01; *p < .05; †p < .10. Two-tailed tests.)
20
*One should note that controlling for dispute duration does not directly address how the temporal
rate of casualties (such as suffering a high number of casualties in a short amount of time) may
affect a state’s willingness to continue a militarized dispute. Answering this question would
require the use of an alternative research design such as hazard analysis, in which the dependent
variable might be the “decision to surrender,” whereas the rate of casualties (or casualty density)
might be employed as an independent variable and interacted with each regime type. This would
allow one to further capture casualty sensitivity with respect to the concentration of fighting and
discern between a conflict that was short and costly versus one that was relatively low in cost but
lasted so long that the total number of casualties gradually accumulated over time.
Unfortunately, the directed militarized dispute dataset does not provide information on the
temporal rate of casualties. See Morey (2011:267-9) for a discussion of high- versus lowconcentration conflicts.
MOREY, DANIEL. (2011) When War Brings Peace: A Dynamic Model of the Rivalry Process.
American Journal of Political Science 55: 263-275.
*To control for adversary’s aim, we create a dummy variable that receives a value of “1” if the
adversary’s goal is primarily territorial conquest or government/regime change and “0” for all
other issues at stake.
*The MID dataset codes dispute outcome within a nine-category scheme: (1) victory for side A,
(2) victory for side B, (3) yield by side A, (4) yield by side B, (5) stalemate, (6) compromise, (7)
released, (8) unclear, and (9) joins ongoing war. Based on these categorizations, we identify
whether the dispute resulted in a win (either a “victory for Side A” or a “yield by Side B”), a
defeat (either a “victory for Side B” or a “yield by Side A”), or a draw (either a “stalemate” or
“compromise”) for the autocratic state. We exclude the outcomes “released” (i.e., seized
material or personnel of the other side is released), “joins ongoing war,” and “unclear” since
these categories do not clearly indicate a win, draw, or defeat (Hensel 1996; Partell 1997).
HENSEL, PAUL R. (1996) Charting a Course to Conflict: Territorial Issues and Interstate Conflict,
1816-1992. Conflict Management and Peace Science 15: 43-73.
PARTELL, PETER J. (1997) Executive Constraints and Success in International Crises. Political
Research Quarterly 50: 503-528.
*A militarized interstate dispute may involve high civilian casualties yet low military fatalities in
a country where the military exclusively comprises the winning coalition and effectively
represses its citizens as the selectorate. The regime’s sensitivity evoked in such dispute may be
different from the one where almost all human costs are military personnel and the general
public is part of the winning coalition (such as the U.S. experience in World War II). While
COW/MID data (which focus on combatant fatalities) would code the former as a low-casualty
dispute and the latter as a high-casualty one, it would be ideal to be able to further distinguish
between these disputes based on the level of civilian costs.
21