Macro-economy - IFs: Difference between revisions
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The economic model represents supply, demand, and trade in each of six economic sectors: agriculture, primary energy, raw materials, manufactures, services, and information/communications technology. The model draws upon data from many sources including the Global Trade and Analysis Project (GTAP) with 57 sectors as of GTAP 8; the IFs pre-processor (integrated software that reads raw data and prepares the initial base year for all models) collapses those into the six IFs sectors and theoretically could collapse them into a different aggregated subset. | |||
On the supply side, a Cobb-Douglas production function determines value added. Thus two principal factors are capital and labor. 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, but allows unemployment rate changes. Accumulated growth in the level of technology or multifactor productivity (MFP), in a "disembodied" representation (TEFF), modifies these factors. Immediate energy shortages/shocks can also affect value added. | |||
The technological factor in the production function is often called multifactor productivity (MFP). The basic value of MFP is a sum of a global productivity growth rate driven by the economically advanced or leading country/region, 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, social, physical, and knowledge capital categories. 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. | |||
Input-output matrices, which are tied to GTAP data but specified dependent on 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 for meeting final demand, both domestic and in other countries via trade. | |||
On the demand side, most of household income supports consumption, which is directed to sectors via a linear expenditure system. It is the balance of this production for final demand with actual final demand that determines whether inventories grow or decline. | |||
Inventories (or stocks) are the key equilibrating variable in four negative or equilibrating feedback loops. As inventories rise, prices fall, increasing final demand (one loop), decreasing production (a second loop), and thereby in total decreasing inventories in the pursuit over time of a target value and equilibrium. Similarly, as inventories rise, capacity utilization falls, decreasing production, and restraining inventories. Finally, relative prices affect the levels of trade among countries. | |||
In the longer run, investment and capital stocks are the key driving variables in an important positive feedback loop. As capital rises, it increases value added and GDP, increasing final demand and further increasing investment. Capital stock is a function of investment and depreciation rates. Endogenously determined investment can be influenced exogenously by a multiplier and the lifetime of capital can be changed. Similarly, government social investment can increase productivity, production and inventories in another positive feedback loop. | |||
Latest revision as of 19:40, 10 August 2018
Note: The documentation of IFs is 'under review' and is not yet 'published'!| Corresponding documentation | |
|---|---|
| Previous versions | |
| Model information | |
| Model link | |
| Institution | Frederick S. Pardee Center for International Futures, University of Denver (Pardee Center), Colorado, USA, https://pardee.du.edu/. |
| Solution concept | |
| Solution method | Dynamic recursive with annual time steps through 2100. |
| Anticipation | Myopic |
The economic model represents supply, demand, and trade in each of six economic sectors: agriculture, primary energy, raw materials, manufactures, services, and information/communications technology. The model draws upon data from many sources including the Global Trade and Analysis Project (GTAP) with 57 sectors as of GTAP 8; the IFs pre-processor (integrated software that reads raw data and prepares the initial base year for all models) collapses those into the six IFs sectors and theoretically could collapse them into a different aggregated subset. On the supply side, a Cobb-Douglas production function determines value added. Thus two principal factors are capital and labor. 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, but allows unemployment rate changes. Accumulated growth in the level of technology or multifactor productivity (MFP), in a "disembodied" representation (TEFF), modifies these factors. Immediate energy shortages/shocks can also affect value added.
The technological factor in the production function is often called multifactor productivity (MFP). The basic value of MFP is a sum of a global productivity growth rate driven by the economically advanced or leading country/region, 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, social, physical, and knowledge capital categories. 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.
Input-output matrices, which are tied to GTAP data but specified dependent on 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 for meeting final demand, both domestic and in other countries via trade.
On the demand side, most of household income supports consumption, which is directed to sectors via a linear expenditure system. It is the balance of this production for final demand with actual final demand that determines whether inventories grow or decline. Inventories (or stocks) are the key equilibrating variable in four negative or equilibrating feedback loops. As inventories rise, prices fall, increasing final demand (one loop), decreasing production (a second loop), and thereby in total decreasing inventories in the pursuit over time of a target value and equilibrium. Similarly, as inventories rise, capacity utilization falls, decreasing production, and restraining inventories. Finally, relative prices affect the levels of trade among countries.
In the longer run, investment and capital stocks are the key driving variables in an important positive feedback loop. As capital rises, it increases value added and GDP, increasing final demand and further increasing investment. Capital stock is a function of investment and depreciation rates. Endogenously determined investment can be influenced exogenously by a multiplier and the lifetime of capital can be changed. Similarly, government social investment can increase productivity, production and inventories in another positive feedback loop.