Online Appendix:
Institutional characteristics and regime survival: Why
are semi-democracies less durable than autocracies and
democracies?
September 22, 2014
A
Online Appendix
This online appendix consists of four sections. The first presents analysis and discusses
whether there are structural changes, over time, in the durability of autocracies, democracies and semi-democracies. The second section presents metrics and discussions on the
performance of the different models presented in the paper. The third contains a number of
models mentioned in the paper – but which are not reported in tables – and a selection of the
many robustness tests that we have performed. The fourth section contains a table listing
all the regimes that either logically could not liberalize or could not de-liberalize according
to the main regime change definition applied in the paper.
A.1
Identifying structural breaks in the durability of regime types:
Change point models
In the paper, we briefly discussed the possibility that the relationships between regime-type
characteristics and regime durability may have changed over time. Although it is beyond the
scope of the paper, or this appendix, to analyze what may cause such changes – changes in
the international context and changes in the institutional structures of the “typical” democracy, semi-democracy and autocracy are two plausible types of explanatory factors – the
descriptive statistics represented in Figure 1 provided strong suggestions that the expected
durability of different regimes are time-contingent. Below, we briefly analyze whether such
time-contingencies exist and, if yes, when changes likely occurred by investigating whether
there are identifiable structural breaks in the time series of regime survival for democracies, autocracies and semi-democracies. As in the paper, we use the data from Gates et al.
(2006); the sample runs from 1800–2000. Further, we employ the Bayesian change point
i
model developed by Park (2013).1 This is a simple linear model, and the posterior likelihood
we sample from is
0
yt = xt βi + I(st = i)εt , i = 1, ..., k
(1)
where k is the number of states, or change points, I(st = i) is an indicator function that
equals 1 in state t and 0 otherwise, xt βi is the set of independent variables, and εt is the
error. The model is estimated using vague priors, and the results are represented in Figures
A.1 (democracies and autocracies) and A.2 (semi-democracies).
Figure A.1: Change points in democratic (left) and autocratic (right) regime duration
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
●
●
Posterior Regime Probability
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●● ●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
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1.0
1.0
Posterior Regime Probability
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Pr(St= k |Yt)
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Pr(St= k |Yt)
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1850
1900
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● ●
0.0
0.0
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1800
●
0.2
0.2
●
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1950
1800
Time
1850
1900
1950
2000
Time
Bayesian change point model. Probability of change (y-axis) across years (x-axis). Data source: Gates et al.
(2006)
The left panel in Figure A.1 shows the result for democracies and the right panel for
autocracies. The x-axes represent the temporal dimension, and the y-axes show the probability of the relationship with regime survival holding a particular value. Hence, the declines
and increases of the different lines identify where we observe structural breaks for the different regime types. Three change points are located for both democracies and autocracies,
1
Most often, political scientists assume that the relationship between a set of variables is constant over
time. When taking the possibility of variation in relationships across time into consideration, this is most
often modeled by using a standard regression framework and including a set of dummy variables (and
interactions between these dummies and the relevant independent variable) marking points in time in which
the relationship is expected to have changed. Change point models, in contrast, explicitly look for variation
in the relationship between variables, and can be used to estimate both whether structural breaks in the
time series have occurred and, if yes, how many and when these breaks are temporally located (Western and
Kleykamp 2004).
ii
indicating that the 200 years can appropriately be divided into four time periods.2 For
democracies the first period ended in 1830, and an intermittent period stretches from then
to around 1890. These are periods with a small sample of democracies, and resulting large
fluctuations in average regime duration (as a result of particular democracies entering or
exiting the sample). The third period runs from 1890 to 1940, and observes, at first, a sharp
decrease followed by an increase in mean duration. In parts of this period, mean longevity of
democracies is the same as for semi-democracies. Finally, the fourth period starts around the
time of the Second World War and continues throughout the remainder of the dataset’s time
series. This is a period of democratic consolidation, with a steady increase in the longevity
of democracies. In this period, democracies are also by far more durable than the other
regime types. Hence, consistent with the argument made by Svolik (2013), we observe the
strongest correlation between having a democratic regime-type and long regime duration in
the post-war period characterized by steady economic growth. The robust finding from both
this paper and the literature at large, namely that democracy is the most stable regime type,
is mainly driven by the strong relationship in this period. In this regard, it is notable that
the size of the democracy time ratio is higher in the Gates et al replication model run on the
sample starting in 1972 (Model B1, Table 3) than in replication models employing longer
time series.
The right panel in Figure A.1 shows the result for autocracies. For these regimes, our
model places the change points just before 1850, during the First World War, and in the
1950s. The period up until 1850 is one of consistent increase in autocratic durability. This
trend ends, however, in 1850; from then until the First World War the average duration
of autocracies is fairly constant. Following the First World War, the average survival time
for autocracies falls sharply, before it levels of in the fourth and final period starting in the
1950s. The moderately high survival time of autocracies reported in our paper is basically a
result of a weighted average over these four periods, but with earlier periods weighing heavier
than for democracies as autocracies used to be more numerous. Interestingly, the size of the
autocracy time ratio is lower in the Gates et al replication model run on the shorter sample
starting in 1972 than when including more extensive time series, and the difference between
the democracy and autocracy time ratios is much larger in this shorter sample.
Figure A.2 shows the result of the change point model for semi-democracies. In contrast
to what was the case for democracies and autocracies, the model only identifies two change
points for semi-democracies. These change points are placed around 1870 and just before
1940. The period up until 1870 contains a considerable amount of fluctuation in the average
duration of semi-democracies, with the period between 1870 and 1940 being much more
stable. Starting around 1940 the average duration of semi-democracies drops by around 50
percent and then levels of and remains at a very low level throughout the time period covered
by the dataset.
Finally, we should note that the change in estimated covariates is much greater for autoc2
The bayesian change point model recovers the full posterior, meaning that the uncertainty around the
exact location of the change points also is available. For all three regime types, however, the high probability
density intervals around the estimated change points are so narrow that, for the present discussion, we ignore
the uncertainty.
iii
Figure A.2: Change points in semi-democratic regime duration
1.0
Posterior Regime Probability
●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●
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0.8
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0.6
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0.4
Pr(St= k |Yt)
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0.2
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0.0
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1800
1850
1900
1950
2000
Time
Bayesian change point model. Probability of change (y-axis) across years (x-axis). Data source: Gates et al.
(2006)
racies and democracies, indicating that pooling all country-years together and not accounting for structural breaks is less problematic for semi-democracies, and more problematic
for democracies and autocracies. One consequence of the above-discussed temporal heterogeneity is that models estimated on the full time series, and that do not properly for the
period-specificity of effects, may either under- or overestimate the longevity of democracies
and autocracies. This is further evidenced by looking at the predictive performance of the
different models presented in the paper, to which we now turn.
iv
A.2
Evaluating model performance
In this section, we evaluate the relative performance of the various models presented in
the paper in terms of explaining regime duration (see Ward, Greenhill and Bakke 2010).
More precisely, we examine the predicted survival times for democracies, autocracies and
semi-democracies from the different models, and evaluate how they correspond with actual
survival times. To this end, the centre column of Table A.1 reports the observed median
duration time of semi-democracies, autocracies, and democracies as defined by Gates et al.
(2006) for the relevant samples of the different models. The left column reports the predicted
median survival times for the three regime types for all the models discussed, starting with
the Gates et al. (2006) replication. A well performing model makes predictions about median
survival time that match, as closely as possible, the observed median survival time of the
different regime types.
Table A.1 also reports the Root Mean Squared Error (MSE; third column) of each model.
The root MSE is the square root of the mean of the squared difference between the predicted
and observed survival time for all regime types. This statistic is reported in years, indicating,
for instance, that the average error in predicted survival time from the Gates et al. (2006)
replication model (from Table 1) is 7 years. This column then does not show how well a
model performs in explaining the duration of, respectively, semi-democracies, autocracies or
democracies, but how well the model explains regime duration in general.
Interestingly, the root MSE is the lowest in models incorporating the Geddes (1999) (7
years) and Hadenius and Teorell (2007) (9 years) regime dummies. These models do not
perform particularly well for what they are intended to – explaining autocratic survival, as
we discuss below – but they do very well in explaining regime survival in general. At this
aggregated regime level, several of the models have more or less overlapping explanatory
power, with most models falling within ± 5 of the median model (Coup d’Etats). This
implies that at this level of aggregation the different models do not add much to each other.
When disaggregating to independently consider semi-democracies, autocracies, democracies,
however, the differences are starker.
What is immediately clear from Table A.1 is that every model exaggerates the survival
time of democracies. The average observed duration for democracies varies between 23 and
27 years (because of different samples), yet the predicted survival times range from 41 to
70 years in the models estimated on all types of regime breakdowns (i.e. not distinguishing
liberalizing- and de-liberalizing changes, which makes comparison with observed average survival problematic). In the paper we focused on explaining the instability of semi-democracies,
so it might not be too surprising that the models fail to account properly for what makes
democracies endure or not. Nevertheless, since we are interested in the relative longevity of
semi-democracies compared to democracies and autocracies, it is somewhat worrisome that
none of the models produce reasonable expectations of democracies’ duration. There is a
large literature investigating the determinants of democratization or the breakdown of authoritarian regimes. The literature investigating what factors make democracies endure is,
however, much scarcer – with notable exceptions such as Przeworski et al. (2000)’s finding
that high levels of economic development stabilizes democracies (see also Boix and Stokes
v
Table A.1: Predicted Survival Time
Median predicted
survival (years)
Gates et al Replication (Mod.2, Tab.1)
Semi-democracy
6
Autocracy
9
Democracy
46
Recent Instability – Riots (Mod.3, Tab.1)
Semi-democracy
5
Autocracy
9
Democracy
41
Recent Instability – Coup d’Etats (Mod.4, Tab.1)
Semi-democracy
5
Autocracy
10
Democracy
49
Ruling Coalitions (Mod.5, Tab.1)
Semi-democracy
9
Autocracy
20
Democracy
70
Regime Types, Geddes et al. (Mod.4, Tab.4)
Semi-democracy
5
Autocracy
9
Democracy
45
Regime Types, Hadenius and Teorell (Mod.3, Tab.4)
Semi-democracy
7
Autocracy
15
Democracy
50
Floor and Ceiling – Liberalization (Mod.2, Tab.6)
Semi-democracy
8
Autocracy
11
Democracy
62
Floor and Ceiling – De-liberaliz. (Mod.3, Tab.6)
Semi-democracy
20
Autocracy
65
Democracy
175
Floor and Ceiling – Dummy controls (Mod.4, Tab.6)
Semi-democracy
5
Autocracy
8
Democracy
59
Observed
survival
Root MSE
(model)
6
13
24
7
5
13
24
11
5
21
25
9
7
15
26
15
4
15
24
7
5
17
27
9
6
13
23
15
6
13
24
16
6
13
24
13
2003; Svolik 2008), and Houle (2009)’s result that low income inequality enhances democratic
survival. One possible implication of the results from Table A.1 is that future research should
pay more attention to studying and modeling the determinants of democratic survival.
Furthermore, the models above – except for the ruling coalition model – underestimate
the longevity of authoritarian regimes. Most models predict authoritarian regimes to live
around 10 years – compared to observed median survival times around 15 years. As noted,
the exception is the model in Table 1 including a measure of the duration of a regime’s
vi
ruling coalition. This model actually overestimates the median duration of autocracies by 5
years. Again, though, this model grossly overestimates the longevity of democracies (by 44
years). Perhaps more surprisingly, the model incorporating the non-democratic regime type
dummies from Geddes, Wright and Frantz (2014) does a poor job in predicting authoritarian
survival times. This model underestimate the median survival time by 6 years, whereas the
replication model misses by 4 years. In contrast, the model including regime dummies from
Hadenius and Teorell (2007) improves on the explanatory power of the Gates et al. (2006)
model in this respect, under-predicting the median duration of authoritarian regimes only
by 2 years.
In contrast to what is the case for autocracies and particularly democracies, most models
do an excellent job in predicting median survival times for semi-democracies. The exception,
quite naturally, is the model that only investigates regime changes in an autocratic direction.
Among the models investigating regime changes in “both directions”, all except two are off
by one year or less. The two remaining models – the ruling coalition and Hadenius and
Teorell models – over-predict the median survival time of semi-democracies by (only) two
years. Independent of specification, the models employed in the paper are seemingly very
good at predicting the duration of semi-democratic regimes.
vii
A.3
Alternative model specifications and selected robustness tests
Table A.2: A selection of robustness tests for Model A3, Table 1; different estimation techniques and regime measures
Autocracy
Democracy
Cox model
Baseline
Instability
∗∗∗
0.540
0.551∗∗∗
(-5.95)
(-5.75)
∗∗∗
0.252
0.248∗∗∗
(-8.97)
(-8.98)
Polity
Polity2
Polity
Baseline
Instability
1.029∗∗∗
(6.32)
1.011∗∗∗
(4.75)
1.030∗∗∗
(6.53)
1.011∗∗∗
(4.97)
SIP
SIP2
SIP
Baseline
Instability
0.00200∗∗∗
(-8.06)
1266.4∗∗∗
(9.31)
0.00209∗∗∗
(-8.18)
1257.2∗∗∗
(9.57)
1.261∗∗∗
(4.77)
1.170∗∗∗
(4.86)
1.014
(1.64)
0.384∗∗
(-3.28)
1.404
(1.59)
1424.2
-701.1
0.651
5426
587
431
0.546
(-1.46)
1.620
(1.78)
0.654∗∗
(-3.29)
1.274∗∗∗
(5.06)
1.167∗∗∗
(4.84)
1.012
(1.43)
0.420∗∗
(-2.99)
1.514∗
(1.98)
1412.3
-692.2
0.641
5426
587
431
logit(SIP)
logit(SIP2 )
Pressure to Democratize
0.792∗∗∗
(-4.90)
0.890∗∗∗
(-4.43)
0.978∗∗∗
(-3.40)
3.082∗∗∗
(4.73)
0.697∗
(-2.37)
5417.4
-2699.7
2.039
(1.64)
0.575∗
(-2.10)
1.410∗∗
(3.03)
0.781∗∗∗
(-5.04)
0.884∗∗∗
(-4.63)
0.979∗∗
(-3.15)
2.869∗∗∗
(4.40)
0.661∗∗
(-2.74)
5408.7
-2692.3
6520
687
516
6520
687
516
SIP change
Past instability
GDP p.c.
GDP p.c. squared
GDP p.c. growth
Neighboring regimes
First polity
AIC
ll
Gamma
N
Polities
Failures
1.226∗∗∗
(3.60)
1.190∗∗∗
(4.76)
1.021∗
(2.18)
0.263∗∗∗
(-4.87)
1.672∗
(2.43)
1568.8
-773.4
0.650
6340
666
495
0.513
(-1.79)
1.462
(1.69)
0.645∗∗∗
(-3.41)
1.248∗∗∗
(3.99)
1.188∗∗∗
(4.82)
1.018∗
(1.99)
0.287∗∗∗
(-4.63)
1.838∗∗
(3.07)
1556.6
-764.3
0.635
6340
666
495
∗
p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
t statistics in parentheses. Time-period dummies are omitted from table
viii
logit(SIP)
Baseline
Instability
1.239∗∗∗
(5.66)
1.107∗∗∗
(5.29)
1.236∗∗∗
(3.96)
1.176∗∗∗
(4.78)
1.015
(1.61)
0.311∗∗∗
(-3.67)
1.425
(1.53)
1448.0
-713.0
0.672
5426
587
431
1.247∗∗∗
(5.98)
1.107∗∗∗
(5.21)
0.520
(-1.57)
1.611
(1.72)
0.657∗∗
(-3.13)
1.247∗∗∗
(4.21)
1.174∗∗∗
(4.80)
1.013
(1.42)
0.337∗∗∗
(-3.47)
1.548
(1.88)
1437.1
-704.6
0.661
5426
587
431
Table A.3: A selection of robustness tests for Model A3, Table 1; different sets of control
variables
Autocracy
Democracy
Standard
Baseline
1.847∗∗∗
(5.83)
3.806∗∗∗
(8.84)
1.290∗∗∗
(5.47)
1.179∗∗∗
(5.64)
1.017∗
(2.01)
0.348∗∗∗
(-4.06)
1.676∗∗
(2.58)
controls
Instability
1.850∗∗∗
(5.94)
3.856∗∗∗
(9.19)
0.561
(-1.61)
1.572
(1.85)
0.659∗∗∗
(-3.59)
1.309∗∗∗
(5.86)
1.178∗∗∗
(5.67)
1.015
(1.82)
0.381∗∗∗
(-3.80)
1.792∗∗
(3.04)
1.018∗
(2.22)
0.256∗∗∗
(-5.15)
1.695∗
(2.54)
1.016∗
(2.04)
0.279∗∗∗
(-4.96)
1.818∗∗
(3.04)
1687.9
-833.0
0.645
6520
687
516
1674.5
-823.3
0.631
6520
687
516
1715.1
-847.5
0.664
6520
687
516
1702.6
-838.3
0.651
6520
687
516
Pressure to Democratize
SIP change
Past instability
GDP p.c.
GDP p.c. squared
GDP p.c. growth
Neighboring regimes
First polity
Drop squared GDP
Baseline
Instability
1.851∗∗∗
1.866∗∗∗
(5.70)
(5.85)
4.224∗∗∗
4.307∗∗∗
(9.21)
(9.71)
0.557
(-1.67)
1.610∗
(2.05)
0.663∗∗∗
(-3.39)
1.173∗∗
1.196∗∗∗
(3.26)
(3.72)
Drop neighboring regimes
Baseline
Instability
2.023∗∗∗
2.013∗∗∗
(6.70)
(6.79)
3.775∗∗∗
3.847∗∗∗
(8.55)
(8.92)
0.563
(-1.60)
1.574
(1.87)
0.641∗∗∗
(-3.83)
1.307∗∗∗
1.325∗∗∗
(5.61)
(5.99)
1.211∗∗∗
1.206∗∗∗
(6.71)
(6.70)
1.016
1.014
(1.87)
(1.69)
1.696∗
(2.57)
1.816∗∗
(2.99)
1702.0
-841.0
0.653
6520
687
516
1686.7
-830.3
0.638
6520
687
516
Latin America
W. Eur., N. Am., Oceania
Eastern Europe
M.East and N. Afr.
Western Africa
Eastern and Central Africa
Southern Africa
South and Central Asia
AIC
ll
Gamma
N
Polities
Failures
Add region dummies
Baseline
Instability
1.844∗∗∗
1.865∗∗∗
(5.85)
(6.06)
3.901∗∗∗
3.969∗∗∗
(8.27)
(8.66)
0.562
(-1.65)
1.563
(1.94)
0.672∗∗
(-3.24)
1.343∗∗∗
1.349∗∗∗
(4.70)
(4.86)
1.178∗∗∗
1.173∗∗∗
(5.25)
(5.21)
1.018∗
1.016
(2.12)
(1.95)
∗∗∗
0.400
0.423∗∗∗
(-3.50)
(-3.37)
∗
1.575
1.697∗∗
(2.25)
(2.70)
1.636∗
1.442
(2.16)
(1.60)
1.065
0.965
(0.31)
(-0.18)
0.961
0.918
(-0.14)
(-0.30)
1.159
1.175
(0.53)
(0.60)
1.180
1.096
(0.66)
(0.38)
1.052
0.918
(0.21)
(-0.37)
∗∗
1.901
1.661∗
(2.76)
(2.20)
0.945
0.997
(-0.22)
(-0.01)
1688.0
1677.0
-825.0
-816.5
0.636
0.624
6520
6520
687
687
516
516
∗
p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
Exponentiated coefficients; t statistics in parentheses. Time dummies are omitted from table.
Reference category for region dummies is Eastern and South-East Asia.
ix
Table A.4: Models employing continuous SIP and including various regime categories –
Regime Survival 1975–2005
SIP
SIP squared
G Monarchy
G Single-party
G Personalist
G Military
(1)
Geddes Regime type
0.00397∗∗∗
(-9.42)
1006.9∗∗∗
(10.61)
1.553
(1.23)
1.615∗∗
(2.94)
1.317
(1.48)
0.951
(-0.26)
(2)
H.T. Regime type
0.00829∗∗∗
(-5.63)
489.0∗∗∗
(6.42)
3.172∗∗
(2.58)
0.722
(-1.16)
2.248∗
(2.14)
0.879
(-0.52)
0.742
(-0.65)
HT Monarchy
HT Military
HT One-party
HT Multiparty
HT No-party
Hegemonic
Competitive
GDP p.c.
GDP p.c. squared
GDP p.c. growth
Neighboring regimes
First polity
AIC
ll
Gamma
N
Polities
Failures
(3)
Competitive author.
0.0107∗∗∗
(-5.71)
391.0∗∗∗
(6.66)
1.288∗∗∗
(5.39)
1.137∗∗∗
(4.35)
1.019∗
(2.19)
0.335∗∗∗
(-4.14)
1.443∗
(1.99)
1582.2
-777.1
0.649
5997
629
474
1.159∗
(2.52)
1.130∗∗∗
(3.53)
1.034∗∗∗
(3.43)
0.294∗∗∗
(-3.87)
1.760∗∗
(3.01)
1008.2
-490.1
0.621
4070
470
317
∗
1.381
(1.46)
1.156
(0.76)
1.266∗∗∗
(4.36)
1.168∗∗∗
(4.40)
1.030∗∗
(2.84)
0.293∗∗∗
(-3.62)
2.006∗∗∗
(3.31)
962.4
-470.2
0.658
3708
445
292
p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
Time ratios and t statistics (in parentheses) are reported.
Time dummies are omitted from table.
Hadenius and Teorell No-party and Other regimes are collapsed.
x
Table A.5: Testing first alternative explanation when disaggregating regime dimensions; only
polities with open and competitive executive recruitment
Participation
Executive Constraints
Participation*Constraints
(1)
Gates et al.
1900–2000
1.246∗
(1.98)
0.884
(-1.47)
1.235∗∗∗
(4.27)
(2)
Gates et al.
1919–2000
1.265∗
(1.96)
0.925
(-0.93)
1.232∗∗∗
(4.22)
Past instability
Pressure to Democratize
SIP change
(3)
Instability
(4)
Coups
(5)
Ruling Coalition
(6)
Transitions
(7)
Shared frailty
1.249
(1.91)
0.953
(-0.58)
1.220∗∗∗
(3.96)
0.595∗
(-2.29)
0.708
(-0.79)
1.027
(0.10)
1.307∗∗
(2.91)
0.983
(-0.22)
1.187∗∗∗
(3.66)
1.140∗
(2.23)
1.024
(0.51)
1.062∗
(2.09)
1.275∗
(2.04)
0.967
(-0.41)
1.204∗∗∗
(3.82)
1.265∗
(2.17)
0.921
(-1.01)
1.231∗∗∗
(4.69)
0.0636∗∗∗
(-6.45)
1.363∗∗∗
(3.45)
1.154∗∗
(2.67)
1.010
(0.43)
0.432
(-1.73)
1.215
(0.45)
444.6
-211.3
0.620
2775
207
128
1.349∗∗∗
(3.50)
1.177∗∗
(2.89)
1.015
(0.93)
0.473
(-1.53)
1.110
(0.29)
466.9
-222.5
0.636
2775
207
128
Coups last 10 years
0.846∗∗∗
(-3.52)
Ruling Coal. Duration
1.719∗∗∗
(6.73)
Polity transition (-88)
GDP p.c.
GDP p.c. squared
GDP p.c. growth
Neighboring regimes
First polity
AIC
ll
Gamma
N
Polities
Failures
∗∗
1.308
(3.13)
1.160∗∗
(2.93)
1.016
(0.67)
0.459
(-1.63)
1.071
(0.20)
516.0
-248.0
0.646
3031
218
144
∗∗∗
1.343
(3.31)
1.177∗∗
(3.02)
1.015
(0.62)
0.477
(-1.50)
1.122
(0.28)
465.1
-222.6
0.646
2775
207
128
∗∗∗
1.379
(3.69)
1.176∗∗
(3.03)
1.010
(0.46)
0.490
(-1.52)
1.187
(0.42)
462.8
-218.4
0.625
2775
207
128
1.411
(4.05)
1.136∗
(2.48)
1.004
(0.12)
0.479
(-1.60)
0.995
(-0.02)
410.1
-194.1
0.620
2440
186
113
∗
p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
Time ratios and t statistics (in parentheses) are reported.
xi
∗∗∗
∗∗
1.147
(2.65)
1.058∗
(2.27)
1.012
(1.14)
0.597∗
(-2.25)
1.080
(0.53)
461.3
-219.7
0.379
2874
207
135
Table A.6: Testing first alternative explanation when disaggregating regime dimensions; only
polities with closed executive recruitment
Participation
Executive Constraints
Dual executive
Participation*Constraints
Dual*Participation
(1)
Gates et al.
1900–2000
0.879
(-1.94)
0.938
(-1.39)
0.845
(-0.96)
1.058∗
(2.01)
1.247∗
(1.99)
(2)
Gates et al.
1919–2000
0.925
(-1.08)
0.897∗
(-2.08)
0.864
(-0.72)
1.080∗
(2.50)
1.205
(1.49)
Past instability
Pressure to Democratize
SIP change
(3)
Instability
(4)
Coups
(5)
Ruling Coalition
(6)
Transitions
(7)
Shared frailty
0.902
(-1.51)
0.904∗
(-2.11)
0.872
(-0.69)
1.078∗∗
(2.64)
1.245
(1.81)
0.674∗∗
(-2.78)
0.707
(-0.75)
1.814∗
(2.22)
0.906
(-1.38)
0.880∗∗
(-2.60)
0.863
(-0.78)
1.070∗
(2.25)
1.210
(1.65)
0.881∗
(-2.58)
0.987
(-0.39)
0.855
(-1.16)
1.039
(1.87)
1.191∗
(1.99)
0.881
(-1.75)
0.889∗
(-2.39)
0.791
(-1.17)
1.077∗
(2.40)
1.256
(1.77)
0.926
(-1.16)
0.896∗
(-2.33)
0.865
(-0.83)
1.080∗∗
(2.68)
1.204
(1.66)
0.0722∗∗∗
(-7.33)
1.228∗∗
(3.02)
1.117∗∗
(2.72)
1.021∗
(2.29)
0.374∗∗
(-3.01)
1.642∗
(2.35)
1091.1
-532.6
0.605
3643
459
369
1.174∗
(2.49)
1.118∗∗
(2.77)
1.017∗
(2.28)
0.447∗
(-2.41)
1.816∗∗
(2.61)
1162.8
-568.4
0.620
3643
459
369
Coups last 10 years
0.925∗
(-2.09)
Ruling Coal. Duration
1.293∗
(2.52)
Polity transition (-88)
GDP p.c.
GDP p.c. squared
GDP p.c. growth
Neighboring regimes
First polity
AIC
ll
Gamma
N
Polities
Failures
∗
1.136
(2.32)
1.086∗
(2.31)
1.019∗
(2.32)
0.520∗
(-2.27)
2.042∗∗∗
(3.63)
1281.9
-628.9
0.619
4216
642
412
∗
1.174
(2.52)
1.118∗∗
(2.84)
1.017
(1.96)
0.449∗∗
(-2.60)
1.816∗∗
(2.77)
1160.8
-568.4
0.622
3643
459
369
∗∗
1.183
(2.78)
1.111∗∗
(2.79)
1.016
(1.90)
0.496∗
(-2.33)
1.994∗∗∗
(3.43)
1153.3
-561.7
0.606
3643
459
369
1.121
(1.90)
1.093∗
(2.43)
1.023∗
(2.49)
0.450∗∗
(-2.64)
1.890∗∗
(3.08)
1122.4
-548.2
0.619
3509
432
352
∗
p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
Time ratios and t statistics (in parentheses) are reported.
xii
∗
1.090
(2.00)
1.052
(1.77)
1.016∗
(2.45)
0.582∗
(-2.56)
1.682∗∗∗
(3.36)
1091.9
-532.9
0.475
3736
512
394
Table A.7: Dimensions of Authority by Regime Type
Executive
Average Proportion
constraints participation
dual
Geddes et al. Regime Categories
Single-Party
2.75
.83 (1.22)
.10
Personalist
1.90
.87 (1.33)
.06
Military
2.17
.70 (1.30)
.09
Monarchy
1.95
.20 (.52)
.52
Hadenius and Teorell Regime Categories
Monarchy
1.76
.17 (.47)
.68
Military
1.75
.44 (.99)
.06
Multiparty
3.67
.11 (.37)
.01
One-Party
2.21
2.42(1.24)
.30
No-Party
2.11
.40 (1.02)
.03
Gates et. al.
Semi-Democracies
4.50
1.47 (1.30)
.50
Autocracies
1.70
.14 (.40)
.03
Democracies
6.73
3.51 (.45)
0
Note: The time series is 1946–2010 for the Geddes et al. categories and 1972–
2010 for the Hadeniues and Teorell categories. Standard deviation in parenthesis for participation.
xiii
Figure A.3: Regime types in the year 2000
Geddes et al. classification, 2000
Regime
type
Monarchy
Military
Party
Personal
Democracy
Hadenius and Teorell classification, 2000
Regime
type
Monarchy
Military
One−Party
Multi−party
Other
Democracy
Map produced using CShapes (Weidmann,
Dorussen and Gleditsch 2010).
xiv
Table A.8: Testing second alternative explanation when disaggregating regime dimensions;
only polities with open executive recruitment
Participation
Executive Constraints.
Participation*Constraints
(1)
Gates et al
1.372∗
(2.19)
1.074
(0.61)
1.163∗
(2.16)
G Single-party
G Personalist
G Military
(2)
Geddes regimes
1.384∗∗
(2.60)
1.028
(0.23)
1.174∗
(2.49)
1.190
(0.36)
0.393∗
(-1.96)
2.796∗
(2.31)
HT Military
HT Multiparty
HT No-party
(3)
H.T. regimes
1.414∗
(2.29)
0.996
(-0.03)
1.084
(0.94)
0.0735∗∗∗
(-4.85)
0.352∗
(-2.30)
0.195∗∗
(-3.24)
(4)
Geddes full sample
1.342∗∗
(2.79)
0.931
(-0.91)
1.228∗∗∗
(4.36)
1.446
(1.07)
0.497
(-1.92)
1.230
(0.65)
Hegemonic
Competitive
GDP p.c.
GDP p.c. squared
GDP p.c. growth
Neighboring regimes
First polity
AIC
ll
Gamma
N
Polities
Failures
1.555∗∗∗
(3.55)
1.213∗
(2.53)
1.020
(0.82)
0.484
(-1.10)
1.993
(1.67)
248.6
-114.3
0.657
1611
133
60
1.456∗∗
(2.73)
1.263∗∗
(2.96)
1.021
(0.78)
0.493
(-1.03)
2.152∗
(2.20)
246.1
-110.1
0.630
1611
133
60
1.350∗
(2.17)
1.196∗∗
(2.67)
1.020
(0.81)
0.973
(-0.04)
1.732
(1.44)
213.5
-93.74
0.580
1611
133
60
∗
1.347∗∗
(3.13)
1.176∗∗
(3.13)
1.004
(0.14)
0.412
(-1.69)
1.118
(0.37)
437.3
-205.6
0.652
2523
190
117
(5)
Competitive author.
1.362
(1.57)
0.932
(-0.47)
1.184
(1.84)
1.476
(0.47)
0.549
(-1.41)
1.501∗∗
(3.02)
1.219∗
(2.56)
1.019
(0.71)
0.579
(-0.78)
1.771
(1.42)
237.2
-106.6
0.657
1497
128
55
p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
Time ratios and t statistics (in parentheses) are reported.
Hadenius and Teorell No-party regimes and Other regimes are collapsed.
G Monarchy and H.T. Monarchy and One-party dummies are dropped (perfect colin./no obs.).
xv
Table A.9: Testing second alternative explanation when disaggregating regime dimensions;
only polities with closed executive recruitment
Participation
Executive Constraints
Dual executive
Participation*Constraints
Dual*Participation
(1)
Gates et al
0.917
(-0.98)
0.897
(-1.81)
0.819
(-0.77)
1.029
(0.83)
1.318
(1.92)
G Monarchy
G Single-party
G Personalist
G Military
(2)
Geddes regimes
0.903
(-1.10)
0.946
(-0.67)
0.686
(-1.37)
1.032
(0.80)
1.444∗
(2.34)
3.137∗
(2.31)
1.404
(1.17)
1.366
(0.97)
1.280
(0.75)
(3)
H.T. regimes
0.907
(-1.07)
1.014
(0.22)
0.583
(-1.93)
1.020
(0.54)
1.621∗∗
(3.03)
19.35∗∗∗
(4.86)
3.227∗∗
(3.23)
7.615∗∗∗
(4.69)
2.453∗∗
(2.68)
3.129∗
(2.10)
HT Monarchy
HT Military
HT One-party
HT Multiparty
HT No-party/Other
(4)
Geddes full sample
0.906
(-1.35)
0.895∗
(-2.04)
0.901
(-0.52)
1.089∗∗
(2.72)
1.227
(1.64)
1.672
(1.44)
1.618∗
(2.45)
1.428
(1.65)
0.988
(-0.05)
Hegemonic
Competitive
GDP p.c.
GDP p.c. squared
GDP p.c. growth
Neighboring regimes
First polity
AIC
ll
Gamma
N
Polities
Failures
1.114
(1.39)
1.086
(1.94)
1.033∗∗
(3.17)
0.298∗∗
(-3.14)
2.503∗∗∗
(4.30)
767.3
-371.7
0.606
2459
337
257
1.068
(0.79)
1.051
(1.12)
1.034∗∗
(3.23)
0.301∗∗
(-3.10)
2.479∗∗∗
(4.07)
768.0
-368.0
0.595
2459
337
257
1.024
(0.32)
1.044
(1.01)
1.038∗∗∗
(3.77)
0.458∗
(-2.11)
1.956∗∗
(3.17)
726.7
-346.4
0.571
2459
337
257
∗
1.132
(1.96)
1.078∗
(2.00)
1.022∗
(2.45)
0.496∗
(-2.23)
1.898∗∗
(3.15)
1132.4
-550.2
0.612
3686
583
358
p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
Time ratios and t statistics (in parentheses) are reported.
Hadenius and Teorell No-party regimes and Other regimes are collapsed.
xvi
(5)
Competitive author.
0.965
(-0.36)
0.870∗
(-2.25)
0.892
(-0.42)
1.036
(0.94)
1.273
(1.56)
1.188
(0.73)
1.026
(0.12)
1.125
(1.40)
1.101∗
(2.10)
1.032∗∗
(2.74)
0.276∗∗
(-3.17)
2.513∗∗∗
(4.21)
722.3
-347.2
0.623
2211
317
237
Table A.10: Testing third alternative explanation when disaggregating regime dimensions;
polities with open and competitive executive recruitment (4 leftmost models) and polities
with closed executive recruitment (4 rightmost models)
Polities w. open and comp. exec. recr.
Participation
Executive Constr.
Particip.*Constr.
Baseline
1.246∗
(1.98)
0.884
(-1.47)
1.235∗∗∗
(4.27)
Lib. only
1.701∗∗∗
(3.69)
0.765∗∗
(-2.71)
1.305∗∗∗
(4.08)
Delib. only
0.978
(-0.15)
1.063
(0.46)
1.140
(1.77)
Floor-Ceiling
1.250∗
(2.03)
0.889
(-1.39)
1.226∗∗∗
(4.09)
1.943∗∗∗
(5.52)
1.286∗∗
(3.12)
1.015
(0.48)
0.236∗∗
(-2.68)
1.372
(0.78)
378.1
-179.1
0.710
3031
218
81
2.350
(1.10)
–
–
1.281∗∗
(2.68)
1.148∗
(2.48)
1.016
(0.67)
0.472
(-1.52)
1.037
(0.10)
516.0
-247.0
0.654
3031
218
144
Dual executive
Dual*Particip.
Ceiling dummy
Floor dummy
GDP p.c.
GDP p.c. sq.
GDP p.c. gr.
Neighb. regimes
First polity
AIC
ll
Gamma
N
Polities
Failures
1.308∗∗
(3.13)
1.160∗∗
(2.93)
1.016
(0.67)
0.459
(-1.63)
1.071
(0.20)
516.0
-248.0
0.646
3031
218
144
0.882
(-0.78)
1.071
(0.85)
1.026
(1.23)
1.000
(-0.00)
0.658
(-0.83)
301.9
-141.0
0.711
3031
218
63
∗
p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
Time ratios and t statistics (in parentheses) are reported.
xvii
Polities w. closed exec. recr.
Baseline
0.879
(-1.94)
0.938
(-1.39)
1.058∗
(2.01)
0.845
(-0.96)
1.247∗
(1.99)
Lib. only
1.085
(0.91)
0.973
(-0.51)
1.032
(0.92)
0.874
(-0.64)
1.065
(0.43)
Delib. only
0.550∗∗∗
(-6.01)
0.794∗∗
(-3.13)
1.214∗∗∗
(4.35)
0.664
(-1.49)
1.644∗∗
(2.68)
1.136∗
(2.32)
1.086∗
(2.31)
1.019∗
(2.32)
0.520∗
(-2.27)
2.042∗∗∗
(3.63)
1281.9
-628.9
0.619
4216
642
412
1.011
(0.16)
1.075
(1.77)
1.031∗∗
(3.12)
0.446∗
(-2.35)
3.338∗∗∗
(5.98)
1056.5
-516.3
0.664
4216
642
287
1.394∗∗
(2.91)
1.066
(1.00)
1.002
(0.13)
1.438
(0.58)
0.777
(-0.77)
621.6
-298.8
0.760
4216
642
118
Floor-Ceiling
0.867∗
(-2.13)
0.913
(-1.82)
1.075∗
(2.41)
0.835
(-1.04)
1.256∗
(2.06)
–
–
0.726
(-1.79)
1.121∗
(2.04)
1.088∗
(2.43)
1.018∗
(2.24)
0.532∗
(-2.20)
1.916∗∗∗
(3.29)
1280.9
-627.4
0.615
4216
642
412
Table A.11: Estimated median survival times for different polities in models with/without
past instability controls
Open and competitive executive recruitment
Share of population
Executive constraints
participating elections 1 (weak)
2-3
4-5
6-7
≤ 1%
8.2/6.5
4.4/4.1
1.6/1.4
0.6/0.8
5%
5.0/4.0
3.6/3.3
2.8/1.6
2.8/2.8
10%
2.6/2.0
3.7/3.4
6.0/6.0
23.6/32.1
50%
1.9/1.8
6.1/6.2 16.5/17.2
74.2/100.5
Designated or ascribed executive
Share of population
Executive constraints
participating elections 1 (weak)
2-3
4-5
6-7
≤ 1%
10.3/11.5 7.9/7.9
4.0/3.2
2.6/2.3
5%
7.2/7.6
5.9/6.0
4.0/3.2
3.5/2.5
10%
3.6/3.7
4.0/4.3
4.5/4.7
6.1/6.6
50%
2.6/2.7
4.5/5.1
4.7/5.2
8.7/10.8
All covariates at means. Estimates are for: Baseline model/Model controlling
for Pressure to Democratize, Past instability and SIP-change; see Appendix
Tables A.5, A.6.
xviii
A.4
List of regime-observations that cannot register liberalizing
or de-liberalizing regime changes
Table A.12: List of regimes that cannot liberalize (Ceiling) or de-liberalize (Floor)
Country
Cuba
Haiti
Haiti
Haiti
Mexico
Mexico
Mexico
Guatemala
Guatemala
Guatemala
Guatemala
Guatemala
Guatemala
Nicaragua
Panama
Ecuador
Peru
Peru
Peru
Peru
Peru
Peru
Brazil
Brazil
Bolivia
Bolivia
Bolivia
Bolivia
Bolivia
Paraguay
Chile
Argentina
Uruguay
Uruguay
Ceiling Floor Start year Last year
0
1
1961
2000
0
1
1810
1915
0
1
1988
1989
0
1
1991
1994
0
1
1835
1846
0
1
1848
1863
0
1
1864
1867
0
1
1839
1847
0
1
1854
1871
0
1
1897
1898
0
1
1954
1958
0
1
1963
1966
0
1
1982
1985
0
1
1981
1984
0
1
1968
1978
0
1
1972
1979
0
1
1821
1822
0
1
1835
1836
0
1
1836
1839
0
1
1879
1881
0
1
1882
1886
0
1
1968
1978
0
1
1889
1894
0
1
1934
1945
0
1
1836
1839
0
1
1864
1871
0
1
1876
1879
0
1
1964
1966
0
1
1969
1982
0
1
1936
1937
0
1
1973
1989
1
0
1983
2000
0
1
1828
1856
0
1
1860
1873
Continued on next page
xix
Table A.12 – continued from previous page
Country
Ceiling Floor Start year Last year
Uruguay
0
1
1875
1890
Uruguay
0
1
1898
1903
Uruguay
1
0
1989
2000
Belgium
1
0
1949
2000
Luxembourg
1
0
1945
2000
Spain
0
1
1923
1930
Spain
0
1
1939
1975
Spain
1
0
1978
2000
Portugal
0
1
1823
1833
Portugal
1
0
1976
2000
Germany
1
0
1949
2000
Hungary
0
1
1919
1920
Czechoslovakia
1
0
1946
1947
Czechoslovakia
1
0
1990
1992
Czech Republic
1
0
1993
2000
Slovakia
1
0
1993
2000
Italy
1
0
1948
2000
Yugoslavia
0
1
1830
1838
Slovenia
1
0
1991
2000
Greece
0
1
1833
1844
Greece
0
1
1967
1974
Greece
1
0
1986
2000
Bulgaria
1
0
1990
2000
Rumania
0
1
1864
1866
Rumania
0
1
1941
1944
Rumania
1
0
1996
2000
Lithuania
1
0
1991
2000
Finland
1
0
1978
2000
Sweden
1
0
1968
2000
Denmark
1
0
1945
2000
Equatorial Guinea
0
1
1969
2000
Gambia
0
1
1994
1996
Mali
0
1
1968
1991
Benin
0
1
1965
1967
Benin
0
1
1972
1990
Niger
0
1
1974
1987
Niger
0
1
1996
1996
Guinea
0
1
1984
1993
Burkina Faso
0
1
1966
1977
Burkina Faso
0
1
1980
1991
Continued on next page
xx
Table A.12 – continued from previous page
Country
Ceiling Floor Start year Last year
Liberia
0
1
1980
1985
Sierra Leone
0
1
1967
1968
Sierra Leone
0
1
1992
1996
Ghana
0
1
1966
1969
Ghana
0
1
1972
1978
Ghana
0
1
1981
1991
Togo
0
1
1967
1991
Togo
0
1
1993
1994
Nigeria
0
1
1966
1978
Nigeria
0
1
1983
1998
Cent. Af. Rep.
0
1
1960
1986
Cent. Af. Rep.
0
1
1986
1993
Chad
0
1
1975
1978
Chad
0
1
1985
1996
Congo
0
1
1997
2000
Zaire
0
1
1997
2000
Uganda
0
1
1971
1979
Uganda
0
1
1986
1993
Burundi
0
1
1966
1991
Burundi
0
1
1996
2000
Rwanda
0
1
1973
1991
Rwanda
0
1
1995
2000
Somalia
0
1
1969
1991
Ethiopia
0
1
1930
1935
Ethiopia
0
1
1942
1946
Lesotho
0
1
1986
1993
Comoros
0
1
1985
1990
Comoros
0
1
1999
2000
Algeria
0
1
1992
1995
Libya
0
1
1969
2000
Sudan
0
1
1958
1964
Sudan
0
1
1989
1996
Iraq
0
1
1936
1941
Iraq
0
1
1958
1979
Syria
0
1
1951
1954
Afghanistan
0
1
1973
1979
Afghanistan
0
1
1996
2000
South Korea
0
1
1961
1963
South Korea
1
0
1988
2000
Pakistan
0
1
1958
1962
Continued on next page
xxi
Table A.12 – continued from previous page
Country
Ceiling Floor Start year Last
Pakistan
0
1
1977
Pakistan
0
1
1999
Bangladesh
0
1
1975
Bangladesh
0
1
1982
Bangladesh
0
1
1990
Myanmar
0
1
1962
Nepal
0
1
1846
Thailand
0
1
1958
Thailand
0
1
1971
Cambodia
0
1
1976
Cambodia
0
1
1997
Republic of Vietnam
0
1
1963
Indonesia
1
0
1999
xxii
year
1985
2000
1978
1986
1991
1980
1951
1968
1973
1979
1998
1967
2000
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