Barro, Robert J., 1998, “Notes on Growth Accounting,” NBER Working Paper No. 6654 (Cambridge,Massachusetts: National Bureau of Economic Research).
Blanchard, Olivier J., and Michael Kremer, 1997, “Disorganization,” Quarterly Journal of Economics, Vol. 112, (November), pp. 1091–126.
De Broeck, Mark, and Vincent Koen, 2000, “The Great Contractions in Russia, the Baltics and the Other Countries of the Former Soviet Union: A View from the Supply Side,” IMF Working Paper 00/32 (Washington: International Monetary Fund).
Dobozi, I., 1995, “Electricity Consumption and Output Decline: An Update,” Transition Newslette, World Bank,Vol. 6, Nos. 9–10 pp. 19–20.
Dobozi, I., G. Pohl, 1995, “Real Output Decline in Transition Economies: Forget GDP, Try Power Consumption Data!” Transition Newsletter, World Bank,Vol.6, Nos. 1–2, pp. 17–18.
Easterly, William R., and Stanley Fischer, 1994, “The Soviet Economic Decline: Historical and Republican Data,” NBER Working Paper No. 4735 (Cambridge, Massachusetts: National Bureau of Economic Research).
Eatwell, John L., 1997, “Effective Demand and Disguised Unemployment” in Employment and Economic Performance, ed. by Jonathan Michie and John Grieve Smith (Oxford and New York: Oxford University Press).
Gavrilenkov, Evgeny, and Vincent Koen, 1994, “How Large Was the Output Collapse in Russia? Alternative Estimates and Welfare Implications,” IMF Working Paper 94/154 (Washington: International Monetary Fund).
Goskomstat Rossii, 1999, Rossiiskii Statisticheskii Ezhegodnik, (Moscow: State Committee for Statistics of the Russian Federation).
Hernández–Catá, Ernesto, 1997, “Liberalization and the Behavior of Output during the Transition from Plan to Market,” Staff Papers, International Monetary Fund, Vol. 44 (December), pp. 405–29.
International Monetary Fund, 2000, World Economic Outlook, October 2000: A Survey by the Staff of the International Monetary Fund, World Economic and Financial Surveys (Washington).
Kaufmann, Daniel, and Aleksander Kaliber 1996, “Integrating the Unofficial Economy into the Dynamics of Post– Socialist Economies: A Framework of Analysis and Evidence” World Bank Policy Research Working Paper No. 1691 (Washington: World Bank).
Solow, Robert, 1956, “A Contribution to the Theory of Economic Growth” Quarterly Journal of Economics, No. 70, (February), pp. 65–94.
Irina Dolinskaya is an Economist in the European Division of the IMF Institute. The author is grateful to Richard Barth, Stanley Black, Eric Clifton, Oleh Havrylyshyn, Mohsin Khan, Vincent Koen, Caryl McNeilly, Mark Schaffer, Ratna Sahay, Abdelhak Senhadji, Sunil Sharma, an anonymous referee, participants in the CEPR (Center for Economic Policy Research) Transition Economics Workshop in Budapest in May 1999, and especially to Willem Buiter for valuable comments.
Based on the recession immediately following the launch of reforms and not including the effects of the Russian crisis of 1998.
Note that the log approximation may not be appropriate in this case, since it requires that the growth rates in question be sufficiently small, which is not always the case in Russian data.
Note that in this case the real wage and the real rental rate of capital reflect not only marginal factor products but also respective utilization rates.
Besides differences across economic sectors, the transition process causes differences within sectors, most importantly between state, privatized, and newly created private enterprises. Owing to data limitations, however, these phenomena are harder to capture empirically, so the present work focuses exclusively on sectoral variations.
The services sector data are taken as a residual and therefore include all economic activity except industry, agriculture, and construction.
The actual length of shortened working days has varied greatly across enterprises, so while the halfday assumption is admittedly arbitrary, it is hard to improve on it given the data at hand. It is also unclear whether there has been a discernible trend in the number of working hours per day or working days per week. The results, however, appear robust to perturbations of this condition.
In Russian capital accounting (Poletayev, 1997), the rate of growth of the gross fixed capital stock in constant prices equals the difference between “the coefficient of renewal” (the ratio of the value of new facilities created during the year to the capital stock) and “the coefficient of depletion” (the ratio of fixed assets that are depleted during the year to the capital stock). The coefficient of renewal is reported as a share of capital at the end of the year, while the coefficient of depletion is reported as a share of capital at the beginning of the year. These coefficients therefore need to be recalculated uniformly as shares of the capital stock at the end of the previous year.
Some justification for this assumption is provided by econometric estimates (not reported here) on a cross–section dataset of Russia’ subnational regions. The factor shares were estimated from the Cobb– Douglas production function under the constant–returns–to–scale restriction. While admittedly crude, the exercise yielded the shares of 0.7 for labor and 0.3 for capital.
In other words, the share of capital in sectoral output is fixed, while the share of capital in total output is proportional to the sectoral output share. A more accurate accounting for differences in capital shares by sector is not feasible owing to the lack of information.
These results are very similar to those obtained by De Broeck and Koen (2000), who found that the TFP drop accounted for 80 percent of the output decline in Russia between 1991 and 1997.
It may be argued that, in fact—at least at most state and former state enterprises, which still comprise the most significant part of the economy—returns to scale are likely to be decreasing, and while returns are probably increasing in the newly emerging private sector, it still constitutes the smaller part of the economy.
The 90 percent confidence interval for the regression coefficient in the capital–utilization equation (7) is 0.75 1.94 x 0.26, or [0.25; 1.25].
This paradox was also obtained by De Broeck and Koen (2000). Note, however, that this result may be sensitive to the assumptions on factor shares by sector.
The 90 percent confidence interval for the regression coefficient in the labor–utilization equation (6) is 0.12 1.94 x 0.04, or [0.05; 0.20]. Note that capital utilization in industry was given, while all the other sectoral utilization rates were estimated from equation (6) for labor and from equation (7) for capital.