Examining and forecasting political outcomes such as interstate peace, intrastate conflict, and economic development is one of the primary goals of political science researchers and practitioners. Assessing these outcomes requires data that characterizes the institutions, regimes, and behaviors that lead to these outcomes. Therein lies one of the core debates of political science. How does one best characterize political institutions? How do you quantitatively measure levels of democracy and autocracy across the global spectrum? Datasets designed to answer these questions generally fall into 2 categories: 1) a mix of composite indices and measures of institutional behaviors and outcomes coded by teams of local experts, and 2) de jure measurements of directly observable institutional characteristics.

Datasets offered by Polity¹ and Freedom House² generally fall into the former, while direct assessments of constitutional and electoral structure like the Institutions and Elections Project³ and the Comparative Constitutions Project⁴ make up the latter. Other datasets like the Varieties of Democracy⁵ present an interesting blend of both. Neither are better than the other; they both have their merits depending on the use case. Relying on composite indices derived by long time experts can spare you weeks of exploratory analysis and derived variable construction, while using highly disaggregated metrics or de jure measures of institutional capability may better serve narrowly focused research questions.

One of the first attempts at broad-scale characterization of global political institutions was the Database of Political Institutions [⁶; DPI]. The DPI has a historical record dating to 1975, spans 178 nation-states, and includes 129 variables in the 2020 report.⁷ In contrast to the Institutions and Elections Project and the Comparative Constitutions Project, the DPI has a greater focus on election outcomes as opposed to the formal rules and mechanisms that drive those outcomes. Variables of this nature in the DPI include the percentage of vote received by the executive, the Herfindahl Index for parties across all branches of government, and composition of the executive opposition party within the legislature.

Sample data from Comparative Constitutions Project’s Characteristics of National Constitutions V2.0. depicting annual proportion of global countries with compulsory citizen voting.

The Comparative Constitutions Project’s Characteristics of National Constitutions (CNC) is one of the 3 primary datasets presenting structural characteristics of national constitutions. The central goal of the Comparative Constitutions Project is to provide data to legal scholars assisting in the drafting of constitutions.⁸ In doing so, they created a rich resource for political scientists and environment-security researchers looking to examine the causal relationships between institutional structure and political outcomes. In contrast to Freedom House and Polity V, CNP does not utilize abstract constructs of institutions and civil liberties; most of the included variables are clear and leave little room for interpretation.

The Institutions and Elections Project (IAEP) is another very popular dataset designed to capture several aspects of historical national electoral procedures, electoral events, institutional provisions, and constitutional stability for 170 countries between 1960-2012. Variables include binary flags for the presence of a formal constitution, whether or not the constitution was in effect, the age of the current constitution, years since it was last amended, and several additional variables describing the country’s electoral process. These are direct measures of constitutional and electoral institutions that permit less ambiguous causal inference between institutional structure and political behaviors and outcomes. Version 2.0 of IAEP added additional variables that describe the age of the current constitution and the number of years the current constitution has been in effect. These variables would be helpful for assessing constitutional or regime stability, but in my experience they suffer from severe coding inconsistencies that render them unusable.

The CNP and IAEP datasets have a lot of overlap, but differ in some ways. First, the CNC contains a longer historical record than IAEP (1789 vs. 1960). While the CNC is almost entirely focused on constitutional structure, the IAEP contains variables that also characterize rules dictating participation in elections, candidate nomination procedures, and provisions concerning the central bank. On the other hand, the Comparative Constitutions Project provides 2 complimentary datasets to the CNC: 1) Constitute;⁹ verbatim text transcriptions of national constitutions, and 2) the Chronology of Constitutional Events;¹⁰ a narrowly focused country-year dataset tracking changes to national constitutions. Lastly, both datasets receive only intermittent updates (2-3 over 15 years of existence). Therefore, they are more applicable for static research interest, because infrequent updates limits the ability to create production pipelines or annual forecasts using the data as it becomes more dated. In these instances, DPI may be a better dataset, because it receives updates every 2-4 years.