Government finance in IFs sits within a broader social accounting matrix (SAM) structure that accounts for, and in the process balances, all domestic and international financial exchanges among firms, households, and governments. The IFs system is unique, not only in the representation of flows within and across so many countries of the world, but also in maintaining, insofar as the sparse data allow, stocks (accumulations of net flows, such as government debt and assets of firms) that provide signals for equilibration processes that require changes in flows (like revenues and expenditures) over time. Like the goods and services markets of the economic model, the government finance representation in IFs (its representation of revenues and expenditures) does not seek an exact equilibrium in every time point, but rather chases equilibrium over time. The variables computed (see the links) are GOVREV, GOVEXP (with direct government consumption or GOVCON as a subset), and GOVBAL. This approach is both more realistic and more computationally efficient.
The desired IFs treatment of government is of consolidated or general government. Beyond our use of the OECD's general government expenditure data for its members, however, our main data source for finance is the World Bank's World Development Indicators (Kaufmann, Kraay, and Mastruzzi 2010), which appear to provide mostly data for central government. In fact, for most countries there are quite incomplete and inconsistent systems of national accounts on which to build social accounting matrices generally, or a full mapping of government finance more specifically. Thus the "preprocessor" in IFs plays a big role in creating a consistent and complete initial image of government finance.
With respect to government finance and the SAM more generally, the preprocessor both fills holes for missing data series of many countries, using cross-sectionally estimated functions or algorithms, and otherwise cleans and balances the SAM data. The preprocessor first builds on data to estimate total governmental revenues and expenditures for the model's base year and then uses available data on the breakdown of revenues and expenditures to calculate initial values of those streams consistent with the totals. Those who wish to understand the entire social accounting system, both initialization and forecast, should look to Hughes and Hossain (2003). More generally, the IFs preprocessor's computational rules assist in the initialization of all models within the IFs system and the connections among them, including reconciliation of physical systems such as energy and agriculture with financial ones.
We make simplifying assumptions to move from limited data to initial values for total general government expenditures and revenues of all countries as a percentage of GDP. For OECD countries we have general government expenditure data (from the OECD), and we assume that the general government revenue share of GDP differs from the expenditures share by the same percentage as central government expenditure and revenue shares differ in WDI data; the implicit assumption is that local government expenditures and revenues are in balance For non-OECD countries we have only central government expenditures and revenues, and we estimate a size for local government revenues and expenditures that rises progressively from 2 percent for the lowest income countries to 14 percent for high-income countries—the latter being the contemporary average of OECD countries, and both the former and the rise being apparent in the data and discussion of North, Wallis, and Weingast (2009: 10).
In the forecasting itself, there is similar attention to revenues and expenditures, but also attention to the cumulative imbalance between them and how that imbalance affects their dynamics over time. The model represents five revenue streams from taxes on household and firm income: household income taxes, household social security/welfare taxes, firm income taxes, firm social security/welfare taxes, and indirect taxes. In the absence of cross-country data on other revenue streams such as property taxes, the preprocessor allocates them in the base year to household taxes, a category for which data are especially weak. Total domestic government revenue is computed from the five streams. Foreign assistance augments domestic revenue in computing the fiscal balance with expenditures.
Government expenditures (GOVEXP) combine direct consumption expenditures (GOVCON) and transfer payments, especially to households (GOVHHTRN). Direct government consumption as a portion of GDP is computed from functions linking GDP per capita (PPP) to key elements of spending such as military, health, and education; total government consumption generally rises with GDP per capita. An additional optional term in the equation is a Wagner term (set to zero in the Base Case), after the discoverer of the long-term behavioral tendency for government consumption to rise as a share of GDP. The final division of government consumption into target destination categories, namely military, education, health, research and development, infrastructure (two subcategories) and an "other" or residual category, depends on a combination of functions and broader algorithmic and modeling elements specific to each spending category (including, for instance, demand for expenditures from the education and infrastructure models). The model normalizes across spending categories to assure that they equal total government consumption.
As a general rule, transfer payments grow with GDP per capita more rapidly than does direct government consumption. And within the category of transfer payments, pension payments grow especially rapidly in many countries, particularly in more economically developed ones. Computation of government transfers involves integrating two different behavioral logics, a top-down one depending on general relationships to income and a bottom-up one. The bottom-up logic is especially important in the analysis of pensions, because it is responsive to the changing size of the elderly population.
With completed computations of revenues and expenditures, it is possible to compute the government fiscal balance, an annual flow variable. That allows the update of cumulative government financial assets or debt and a calculation of their magnitude relative to GDP. IFs uses this cumulative total as a percentage of GDP in its equilibrating dynamics for annual government revenues and expenditures.