Production system and representation of economic sectors - IFs
The economic model produces GDP at market exchange rates and at purchasing power parity. It also produces supply, demand, and trade in each of six economic sectors: agriculture, primary energy, raw materials, manufactures, services, and information/communications technology. It further provides a calculation of income distribution in the form of a Gini index, thereby facilitating also its calculation of poverty rates at multiple per-capita income (or household consumption) levels.
The model draws upon data from many sources including the World Bank and IMF (and the OECD for higher-income countries). It also uses ongoing updates from the Global Trade and Analysis Project (GTAP); GTAP 11 data were being used as of this writing and IFs version 8.35, but new releases lead to regular IFs updates. The IFs pre-processor (integrated software that reads raw data and prepares the initial base year for all models) collapses the large number of GTAP sectors into the six IFs sectors and theoretically could collapse them into a different aggregated subset.
Two features of the economic model are especially notable. First, it is embedded in a full social accounting matrix (SAM) structure. It assures consistency of financial flows among firms, households, and government and determines transfer payments and direct expenditures in categories including health, education, and infrastructure, thereby affecting dynamics of those models. Second, the production function that calculates value added and sums that across sectors for GDP, fundamentally important to long-term dynamics, includes endogenous representation of multifactor productivity, driving it by changes in human, social, and physical capital from other models in the IFs system, as well as knowledge advance. Both the SAM (as simplified in Figure 5) and the production function are therefore pivot points for the interaction of dynamics across the range of models in the integrated IFs system and for policy analysis.
On the demand side, the six sectors of IFs, the division of households into skilled and unskilled (with differential use of income for consumption versus savings and consumption patterns across sectors that vary with income), and an extensive representation of government revenues and expenditures are all part of that SAM elaboration. For instance, the government finance elaboration represents revenues from domestic taxes, tariffs, and foreign assistance when received and represents expenditures as transfer payments (which affect poverty levels) and direct expenditures in military, health, education, research and development, infrastructure types represented in the IFs infrastructure model, other infrastructure, and other spending (including administration) categories. Model dynamics limit growth in government debt.
On the supply side the model user can use the interface to fully override the growth of GDP with values that have been operationalized by other models in their representations of the Shared Socio-economic Pathways (SSPs) and put into the IFs database, just as the user can similarly override population growth patterns and many other SSP variables in IFs. In default mode, however, the Cobb-Douglas production function determines value added, summed across sectors to compute GDP. Two principal production factors are capital and labor. Capital stock is changed over time with depreciation and investment, the latter responsive to inventory stocks as elaborated below; investment rates by sector are flexible and existing capital stocks are fixed by sector (a putty-clay representation). Labor is responsive not just to population size and structure, but to the labor participation rate, including the changing role of women in the work force. A labor submodel calculates labor demand that is equilibrated over time with supply, recognizing initial unemployment rates but moving those to standard (scenario-affected) targets over the long run. Immediate energy shortages/shocks can also affect value added. In addition, capacity utilization (CAPUT) of capital and labor is responsive over time to inventories.
The "disembodied" (or Solow residual) technological factor in the production function is often called multifactor productivity (MFP) or total-factor productivity (TFP). In IFs the variable name is TEFF. The basic value of the technology term for each country/geopolitical region (r) is a sum of a global productivity growth rate driven by the economically advanced or leading country/region (by default the United States), a technological convergence factor dependent on GDP per capita, and an exogenous or scenario factor. In addition, however, other factors affect productivity growth over time. These include a wide range of variables across human (MFPHC), social (MFPSC), physical (MFPPC), and knowledge (MFPKN) capital categories that are computed using variables from other models of the hard-linked IFs system. For instance, years of adult education attainment and the level of economic freedom, respectively are among the variables that affect change in MFP associated with human and social capital. The production function thus constitutes an important linkage across the models in the IFs system.
Input-output matrices, which are tied to GTAP data but change endogenously with the level of development (GDP per capita), allow the computation from value added of gross production. The calculation of gross production (ZS) in value terms within the economic model is overridden by calculations of physical production converted to value in the agricultural and energy models when respective switches (AGON and ENON) are thrown as in the default of the IFs Base Case scenario. After satisfaction of intersectoral flows, the remainder of gross production is available to meet final demand, both domestic and in other countries via trade.