The primary source for this information is Shugart and Carey (1992, ch. 8). Altogether, we end up with 39 parliamentary democracies, indicated by solid on the map, and 25 presidential democracies, indicated by striped on the map. Many, but not all, presidential democracies are found in Latin America. A complete and detailed data set of our regime types, electoral rules and other data is under preparation and will be made available soon.
As noted in the Introduction, government size is measured as total expenditures of central government in percent of GDP, averaged over the period 1988-92. The primary data source is IMF’s Government Financial Statistics, but we have also collected data from other sources. We rely on data for central government, rather than general government, since they are available for a larger number of countries. Such data admittedly do not take variation in decentralization to local governments into account, a problem we try to remedy by including measures of centralization among our control variables. Anyway, the theory assumes decisions to be under centralized political control, which better fits central (rather than general) government expenditures. Data on public goods expenditure are not directly available. We create such measures by aggregating data on expenditure categories which, a priori, should have a high public-good content. Thus, our measure of public goods is the sum of expenditures on transportation, education and order and safety, also in percent of GDP. We also experiment with broader measures of spending on public goods.
Finally, we use a number of socio-economic control variables, found in previous empirical studies to be correlated with the size of government. When explaining the size of government, our most parsimonious list of controls, denoted XB in the Tables below, includes the following variables:
(i) the log of per capita income, as the level of development could influence the voters preferences for private versus public consumption, as well as the availability of tax bases, as conjectured by the so called “Wagner’s law” (cf. Mueller (1989));
(ii) the log of openness, measured as the log of the sum of exports plus imports in % of GDP, as suggested by the earlier empirical work by Cameron (1978) and Rodrik (1998) and also to capture the greater availability of tax bases in less developed open economies (cf. Goode (1984));
(iii) the share of the population above 65, which determines spending on pensions and health (see, e.g., the empirical findings in Lindert (1996); (iv) a measure of ethno-linguistic fractionalization, to capture the idea that political interaction is more difficult in more fractionalized countries which could affect public policy decisions (see, in particular, the empirical work by Alesina, Easterly and Baqir (1997) and by Easterly and Levine (1997)).
When explaining public good provision, the list of parsimonious controls, now denoted ZB, is defined as XB above, except that the index of fractionalization is replaced by: (iv) centralization of government spending (measured as expenditures of central government divided by expenditures of general government), as the assignment of tasks to various levels of governments could differ across countries (Panizza (1997) also used this variable). Below, we comment on what happens when these sets of regressors are expanded to include other variables.