Services Sector

Purpose and Perspective

The Services sector employs an extended Cobb-Douglas (CD) production function to represent services production in the private sector. Production factors include capital and labor. Factor productivity depends on several other drivers, including: education (average years of schooling used as proxy); health (life expectancy used as proxy); infrastructure (including roads and irrigation infrastructure); access to electricity; level of governance; macroeconomic stability (inflation rate used as proxy); and openness to trade. Value added from the production of non-marketed public services is calculated based on salaries and wages paid in the public sector, while services produced by public enterprises are treated as output from the private sector.

In the production function described above, growth in production is driven by the increase in availability of the necessary production factors or by the increase in their productivity. This implies that demand factors are not considered in the calculation of production, that the quantities produced are fully consumed, and prices are exogenous to the model. Such production function can adequately represent the long-term pattern of production growth, and is therefore well suited to calculate production in iSDG. On the other hand, the production functions used is not suitable to represent short-term fluctuations in production caused by the accumulation of inventories of finished goods. Since iSDG is geared toward the analysis of long-term trends and not short-term fluctuations, these limitations do not affect the validity of the model.

Model Structure and Major Assumptions

Exogenous Input Variables


Initialization Variables

  • Initial services capital output ratio – Units: Year

  • Initial generic services production – Units: Rlcu/Year

Modeling Details

In iSDG the production factors are used in unit-consistent form, using the values for capital, labor, and land relative to their initial values, or normalized. A similar approach is used to normalize the drivers of productivity. Thanks to such normalization, the effects of production factors and drivers of productivity are effectively and consistently combined. More specifically all such effects are combined in a multiplicative form, assuming Hicks-neutral technological change.

Footnotes and References

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[3] Intergovernmental Panal on Climate Change (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change [Field, C.B., Barros, V., Stocker, T.F., Qin, D., Dokken, D.F., Ebi, K.L., Mastrandrea, M.D. et al.(Eds.)]. Cambridge, UK, and New York, NY: Cambridge University Press.

[4] Calderón, C. & Servén, L. (2004). The Effects of Infrastructure Development on Growth and Income Distribution. World Bank Working Paper, (WPS3400). Washington, DC: World Bank.

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[6] Bloom, D.E., Canning, D. et al. (2001). The Effect of Health on Economic Growth: Theory and Evidence. NBER Working Paper Series, (WP8587). Cambridge, MA: National Bureau of Economic Research.

Howitt, P., (2005). Health, Human Capital and Economic Growth: A Schumpeterian Perspective. In López-Casanovas, G., Rivera, B., & Currais, L. (Eds.) Health and Economic Growth: Findings and Policy Implications. Cambridge, MA: MIT Press.

López-Casasnovas, G., B. Rivera, et al., (2005). Introduction: The Role Health Plays in Economic Growth. In López-Casanovas, G., Rivera, B., & Currais, L. (Eds.) Health and Economic Growth: Findings and Policy Implications. Cambridge, MA: MIT Press.

[7] Kaufmann, D., Kraay, A. et al. (2002). Governance Matters II, Updated Indicators for 2000/01. Policy Research Working Paper, (2772). Washington, DC: World Bank.

[8] Calderón, C. & Servén, L. (2004). The Effects of Infrastructure Development on Growth and Income Distribution. World Bank Working Paper, (WPS3400). Washington, DC: World Bank.

[9] Bruno, M., Easterly, W. (1998). Inflation crises and long-run growth. Journal of Monetary Economics 41: 3-26.

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[10] Boileau L., Diouf, M.A. (2009). Revisiting the Determinants of Productivity Growth: What’s New? IMF working paper WP/09/225. Washington, DC: International Monetary Fund.

Cuberes, D., & Teignier, M. (2012). Gender gaps in the labor market and aggregate productivity, Sheffield Economic Research Paper Series. Sheffield, UK: University of Sheffield.

[11] Edwards, S. (1998). Openness, productivity and growth: What do we really know? The Economic Journal, 108(447): 383-398.

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[12] Burke, M., Hsiang, S.M., & Miguel, E. (2015). Global non-linear effect of temperature on economic production. Nature, 527: 235-239.

[13] Arezki, R., Blanchard, O. (2014). Seven Questions about the Recent Oil Price Slump. IMFdirect - The IMF Blog, December 22, 2014.

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Peersman, G. & Van Robays, I. (2012). Cross-country differences in the effects of oil shocks. Energy Economics, 34(5):* 1532-1547.

[14] Bloem, A.M., Dippelsman, R.J., & Maehle, N.O. (2001). Quarterly National Accounts Manual—Concepts, Data Sources, and Compilation. International Monetary Fund