Supplementary Appendix for "Dealing with Dictators: Negotiated Democratization and the
Fate of Outgoing Autocrats"
Table of Contents:
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Section One: Constructing State Antiquity Index, Region Dummies, and Structural Inequality
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Section Two: Constructing Autocratic Regime Types at Leader-year Level
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Section Three: Constructing De Facto Party Legacy
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SECTION ONE: CONSTRUCTING STATE ANTIQUITY INDEX AND REGION DUMMIES
1. State Antiquity Index
We follow Bockstette et al. (2002) and measure state capacity as the State Antiquity Index, a proxy
for the longevity of a state’s infrastructure and bureaucratic culture. Bockstette et al. (2002) discount
the influence of the past for each half-century at various rates. We employ, as recommended by
them, the 5% discount rate. We also use the version of the index normalized to run from 0 to 1,
where the sum of the discounted series is divided by the maximum possible value the series could
take given the same discount rate. We follow Putterman and Weil (2010) and adjust the State
Antiquity index by migration patterns. Specifically, to address the fact that during the colonization of
the Americas, Sub-Saharan Africa, and Asia, European settlers and non-European indentured
servants and slaves migrated in different numbers, displaced indigenous populations to different
degrees, and imported their home institutions with varying measures of success, we weight this ratio
by Putterman and Weil’s World Migration Matrix. This matrix allows researchers to adjust crosscountry indicators to reflect the history of a population’s ancestors, rather than the history of the
place they live today. Specifically, the matrix discloses the different shares of a country’s population
in 2000 that are descended from people in different source countries in the year 1500. For example,
Mexico’s Antiquity Index is multiplied by Mexicans’ share of ancestors of Aztec descent and
adjusted by Spain’s State Antiquity Index multiplied by Mexicans’ share of ancestors of Spanish
descent. This allows us to capture both the state capacity accumulated by the Aztecs during the PreColombian period and the legacy of Spanish state capacity as introduced by the Conquistadores
during the 16th Century.
See Putterman, Louis, and David Weil. 2010. “Post-1500 Population Flows and the Long-Run
Determinants of Economic Growth and Inequality.” The Quarterly Journal of Economics 125: 16271682.
2. Region Dummies
In the regressions where we include region fixed effects, we have constructed the region dummies
following Hadenius & Teorell (2005), “Assessing Alternative Indices of Democracy, C&M Working
Papers 6, IPSA” (available at: http://www.conceptsmethods.org/working_papers/20050812_16_PC%206%20Hadenius%20&%20Teorell.pdf), who
divide the world into ten politico-geographic regions. It is based on both geographical proximity and
demarcation by area specialists who have contributed to a regional understanding of
democratization. The ten regions are: 1) Eastern Europe and post Soviet Union (including Central
Asia); 2) Latin America (including Cuba, Haiti & Dominican Republic); 3) North Africa & Middle
East (including Israel, Turkey and Cyprus); 4) Sub-saharan Africa; 5) Western Europe & North
America (including Australia & New Zealand); 6) East Asia (Including Japan & Mongolia); 7)
Southeast Asia; 8) South Asia; 9; The Pacific (excluding Australia & New Zealand); 10) The
Caribbean.
We make some minor adjustments to the Hadenius and Teorell classications, as follows. We
allocate Haiti and Suriname to the Caribbean. We do so on the following basis: neither is Spanish
speaking. Moreover, Guyana is in this category, so it makes little sense that neighboring Suriname is
not. We also allocate Mongolia to Eastern Europe and the Post Soviet Union because it was in the
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Soviet Union’s sphere of influence during the Cold War. Historically it also has more in common
with Central Asia (which is in Hadenius and Teorell’s category for Eastern Europe and the PostSoviet Union) than it does with the Pacific or Southeast Asia. We allocate Cyprus and Israel to
Western Europe, because the populations of both are of European origin and their political
institutions have been clearly shaped by their orientation toward Europe.
3. Structural Inequality
We follow Easterly (2007) and control for persistent structural inequality as the log(%Land Suitable for
Wheat to %Land Suitable for Sugar Cane) in Table 5. Because there are some countries where the land
suitable for either/both of these crops is zero, we compute the ratio as: log((1+% land suitable for
wheat)/(1+% land suitable for sugar)). Unlike Easterly, we use the arable land suitable for these
crops within 100 miles of the country’s largest city to address the possibility that country averages
mask a considerable degree of heterogeneity and may be biased by areas that are not populated. In
order to calculate the arable land suitable for each crop, we use data from the Food and Agriculture
Organization (FAO) GAEZ (2002) dataset. The FAO computes, based on measures of soil
characteristics, such as moisture, temperature, chemical composition, depth, texture, and organic
matter, a suitability index for a large number of crops. That suitability index (SI) is scaled from 0
(completely unsuitable for that crop) to 100 (the highest possible yield for that crop under rainfed
conditions). This is done crop by crop, by parcel, on a global scale. Each of these parcels roughly
corresponds to 36 mile by 36 mile squares. We then used the parcel SIs to compute, via
triangulation, the average SI for each crop 100 miles in radius from the largest city.
See Easterly, William. 2007. "Inequality does Cause Underdevelopment: Insights from a New
Instrument." Journal of Development Economics 84: 755-776.
SECTION TWO: CONSTRUCTING AUTOCRATIC REGIME TYPES AT LEADERYEAR LEVEL
Several of the regressions in Tables 3-4 of the manuscript include autocratic regime types as control
variables. Table 5 includes controls for autocratic regime legacies. To construct these variables, we
coded the Wright (2008) data on autocratic regime types from 1875 to the present at the leader-year
level for the outgoing autocrats in our sample. This is because we are looking at the individual fates
of former dictators after they relinquish power. We did this following Geddes’s (2003) coding
scheme of autocratic regime types. To code these variables we consulted, among other sources, her
original coding manual, which has the original questions and score sheets used to code autocratic
regime types. We include variables for whether the regime evidences a single party, military, or
personalist component, though the results are also robust to using pure regime types. Following
Geddes (2003), this allows a leader, such as Suharto in Indonesia (observed from 1966 to 1998), to
be coded as a hybrid possessing multiple regime type components.
There are several autocratic regimes coded by Boix and Rosato/Cheibub et al. that do not well fit
within the Geddes/Wright autocratic regime typology. In particular, most of the pre-WWII
European cases (such as the UK prior to 1885 or the Netherlands prior to 1897) have multiparty
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competition among civilian politicians with suffrage restricted to less than 50% of the male
population and which hold regular elections. There are also several post-WWII cases in which
leaders rose to power via regular means and resumed regular elections (such as when an autocrat
flees or steps down and a legislative body or other institution appoints an individual to complete
their term, as with Sanya in Thailand in 1973). These cases do not correspond well to single party,
military, or personalist regimes, but instead represent “partial democracies” or “oligarchies.” We
therefore coded these cases in a separate category called Oligarchy. Importantly, however, recoding
these leaders as heading either personalist or single party regimes – the most plausible alternatives –
does not alter the results.
To construct these variables, we consulted Geddes (2003), Wright (2008), Henisz (2000), Vanhanen
(2003), Goemans et al. (2009), Boix and Rosato (2001), and various secondary sources.
We have included our coding decisions for each non-transitional dictator (less than 1 year) in the
Appendix Table 1.
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Table 1. Coding Regime Types
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Table 1 (cont).
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SECTION THREE: CONSTRUCTING DE FACTO PARTY LEGACY
Several of the Table 5 regressions include the number of de facto parties under the previous
autocratic regime as a control variable. This variable was built from the “defacto” variable in
Cheibub et al. (2009). This variable codes the legacy value of “defacto” for the last full year of
dictatorship – in other words, all country-years of a democratic regime episode will be coded with
the value of “defacto” that was observed just prior to democratization.
The Cheibub et al. (2009) data span the period from 1946 to the present. There were, however,
several cases (such as Argentina, Italy, and Peru) that transitioned to democracy in 1946. Because
these cases were missing the legacy values from 1945, we filled in the missing values using Henisz
(2000) and secondary sources.
The main version of this variable, which is used in the regressions reported in Table 5 of the
manuscript, codes the regime episodes in countries that gain independence under democracy as a
“0”; that is, they are recorded as having no autocratic party legacy. It also codes pre-1946
democracies that follow an “oligarchy” as a “0” since conceptually these were not autocratic political
parties per se, but parties contesting actual elections, albeit restricted ones, under a quasi democratic
system. We nonetheless probed the robustness of the results presented in the paper to relaxing each
of these coding rules.
First, we recoded regime episodes in countries with no legacy of autocracy separately from those
with a legacy of autocracy but without single or several parties under autocracy. For example,
countries such as Australia, Switzerland, or Canada were all democratic upon independence, and
have experienced uninterrupted democracy since independence. We therefore omit these and similar
cases without any autocratic legacy in a set of robustness tests. The results are similar across the
range of dependent variables in Table 5. The results also hold if, instead of dropping these
observations, we treat the variable as an unordered nominal variable and code countries that were
democratic at inception as a separate category that indicates that they never had an autocratic legacy.
This implies that those democracies that follow multiparty autocracies are coded as one category;
democracies that follow single party autocracies are coded as a separate category; democracies that
follow autocracies with no parties are coded as a separate category; and democracies that were
democratic at inception are coded as a separate category.
Second, we recoded democracies that follow oligarchies as having a legacy of multiparty elections
under autocracy. For instance, countries such as the UK prior to 1885, Denmark prior to 1901, and
Sweden prior to 1911, have multiparty competition among civilian politicians with suffrage restricted
to less than 50% of the male population and which hold regular elections. Recoding these and
similar cases as having a legacy of multiparty elections does not substantially change any of the Table
5 results. The results also hold if we drop these cases from the regressions.
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