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1 2 3 4 5 Republic of Khakassia 15.25 13.09 23.54 22.61 18.Rostov oblast 17.52 19.68 26.44 32.21 21.Ryazan oblast 15.50 15.84 28.15 18.08 19.Samara oblast 0.19 0.54 3.93 5.23 3.Saratov oblast 14.21 14.08 21.18 23.72 18.Sakhalin oblast 33.35 34.12 32.97 31.22 33.Sverdlovsk oblast 3.63 1.54 6.27 6.37 4.Smolensk oblast 11.72 27.39 18.64 21.93 18.Stavropol krai 18.02 26.78 30.52 40.10 30.Taymyr (Dolgan-Nenetsky) 26.46 13.01 24.97 35.10 30.autonomous okrug Tambov oblast 24.23 31.18 44.14 45.74 30.Tver oblast 15.26 32.27 30.34 25.78 23.omsk oblast 8.88 10.16 12.40 19.77 16.Tula oblast 10.95 17.05 22.13 20.61 19.Tyumen oblast 5.88 0.33 3.82 4.73 10.Udmurt Republic 11.40 7.01 12.04 18.30 18.Ulyanovsk oblast 10.00 8.56 29.12 32.94 19.Ust-Ordynsky Buryatsky 76.36 81.42 82.82 84.08 99.autonomous okrug Khabarovsk krai 22.56 19.62 23.43 23.50 26.Khanty-Mansy autonomous 0.00 0.00 0.64 1.78 1.okrug Chelyabinsk oblast 2.53 3.55 9.54 13.51 9.Chita oblast 41.45 41.03 45.36 47.69 36.Chuvash Republic 21.24 18.91 39.45 42.34 23.Chukotka autonomous 64.31 68.04 51.80 40.04 63.okrug Evenk autonomous okrug 79.13 87.30 50.76 30.64 69.Yamal-Nenetsky autono0.01 0.43 2.91 3.88 1.mous okrug Yaroslavl oblast 3.46 2.36 7.35 7.66 9.Table A1Investment in Capital Assets Funded at the Expense of Budget Resources to GRP over 19951998, as % 1995 1996 1997 1 2 3 4 Aginsky Buryatsky autono0.00 0.00 0.00 2.mous okrug Altay krai 0.00 0.00 0.00 3.Amur oblast 0.00 0.00 0.00 4.Arkhangel oblast 2.14 2.17 1.58 0.Astarkhan oblast 3.20 2.37 2.41 2.Belgorod oblast 4.02 3.61 4.56 3.Bryansk oblast 6.30 3.66 2.53 1.Vladimir oblast 1.39 1.40 1.14 1.Volgograd oblast 2.80 2.70 3.17 2.Vologda oblast 1.74 1.73 1.98 1.Voronezh oblast 2.11 3.36 2.38 2.City of Moscow 8.05 7.36 6.53 4.Saint Petesrburg 3.57 3.48 2.59 2.Jewish Autonomous oblast 0.00 0.00 0.00 12.Ivanovo oblast 1.68 2.30 2.01 7.Irkutsk oblast 0.00 0.00 0.00 2.Kabardino-Balkar Republic 6.50 8.73 9.20 10.Kaliningrad oblast 0.00 0.00 0.00 1.Kaluga oblast 3.08 2.78 3.76 2.Kamchatka oblast 0.00 0.00 0.00 2.Karachay-Cherkess Republic 1.63 2.96 4.60 6.Kemerovo oblast 0.00 0.00 0.00 3.Kirov oblast 1.50 1.86 1.65 1.Komi-Permyak autonomous 2.09 1.42 0.91 2.okrug Koryak autonomous okrug 0.00 0.00 0.00 0.Kostroma oblast 2.71 1.58 2.28 1.Krasnodar krai 1.96 1.91 1.66 2.Krasnoyarsky krai 0.00 0.00 0.00 1.Kurgan oblast 2.88 3.05 3.06 1. 1 2 3 4 Kursk oblast 2.12 2.08 2.67 1.Leningrad oblast 1.83 1.99 2.93 3.Lipetsk oblast 2.14 4.17 4.44 4.Magadan oblast 0.00 0.00 0.00 2.Moscow oblast 5.46 3.77 4.00 3.Murmansk oblast 2.33 1.88 1.47 1.Nenetsky autonomous okrug 1.94 2.89 3.08 4.N. Novgorod oblast 2.48 2.69 3.14 2.Novgorod oblast 2.10 1.15 2.54 0.Novossibirsk oblast 0.00 0.00 0.00 2.Omsk oblast 0.00 0.00 0.00 3.Orenburg oblast 2.27 2.22 2.61 2.Orel oblast 2.34 6.32 4.75 6.Penza oblast 3.03 2.58 2.81 5.Perm oblast 1.07 1.55 2.17 1.Primorye krai 0.00 0.00 0.00 2.Pskov oblast 3.36 3.83 2.69 3.Republic Of Adygeya 3.77 5.53 3.36 3.Altay Republic 0.00 0.00 0.00 3.Republic of Bashkortostan 4.05 3.26 2.44 3.Republic of Buryatia 0.00 0.00 0.00 3.Republic of Dagestan 12.55 10.29 8.32 11.Ingoush Republic 56.14 36.80 50.29 36.Kalmyk Republic 8.27 9.17 10.92 22.Republic of Karelia 1.81 2.35 2.80 1.Republic Komi 2.46 6.37 4.30 1.Republic of Mary El 3.03 3.68 3.14 3.Republic of Mordovia 2.01 4.38 4.40 4.Republic of Sakha (Yakutia) 0.00 0.00 0.00 3.Republic of North Ossetia 7.98 10.34 9.27 8.(Alania) Republic of Tatarstan 3.26 3.43 3.06 1.Republic of Tyva 0.00 0.00 0.00 8.Republic of Khakassia 0.00 0.00 0.00 3.Rostov oblast 2.46 3.74 3.34 3.1 2 3 4 Ryazan oblast 1.81 1.59 2.72 1.Samara oblast 1.94 1.51 1.38 1.Saratov oblast 1.68 4.63 6.52 5.Sakhalin oblast 0.00 0.00 0.00 3.Sverdlovsk oblast 2.37 2.80 3.52 2.Smolensk oblast 1.78 1.44 2.09 1.Stavropol krai 4.85 3.38 3.34 3.Taymyr (Dolgan-Nenetsky) 0.00 0.00 0.00 3.autonomous okrug Tambov oblast 2.83 3.01 2.51 1.Tver oblast 2.22 3.58 2.56 2.omsk oblast 0.00 0.00 0.00 2.Tula oblast 2.99 5.15 2.80 2.Tyumen oblast 0.00 0.00 0.00 0.Udmurt Republic 3.03 3.02 2.09 1.Ulyanovsk oblast 2.19 1.74 2.03 4.Ust-Ordynsky Buryatsky 0.00 0.00 0.00 4.autonomous okrug Khabarovsk krai 0.00 0.00 0.00 2.Khanty-Mansy autonomous 0.00 0.00 0.00 2.okrug Chelyabinsk oblast 2.91 4.41 4.52 3.Chita oblast 0.00 0.00 0.00 2.Chuvash Republic 4.31 3.90 5.15 5.Chukotka autonomous okrug 0.00 0.00 0.00 5.Evenk autonomous okrug 0.00 0.00 0.00 11.Yamal-Nenetsky autonomous 0.00 0.00 0.00 7.okrug Yaroslavl oblast 2.23 1.22 1.75 2. Table A1Investment in Capital Assets Funded at the Expense of Budget Resources to GRP over 19992002, as % 1999 2000 2001 2002 inv1 2 3 4 5 Aginsky Buryatsky 5.93 7.95 9.63 11.97 4.autonomous okrug Altay krai 3.73 4.57 2.65 2.53 2.Amur oblast 3.76 4.01 4.49 7.18 2.Arkhangel oblast 0.90 0.85 1.41 0.51 1.Astarkhan oblast 1.98 2.68 2.61 3.20 2.Belgorod oblast 2.84 2.93 2.12 2.24 3.Bryansk oblast 1.78 2.24 2.13 2.28 2.Vladimir oblast 1.40 2.92 2.47 2.24 1.Volgograd oblast 1.77 2.19 1.26 1.32 2.Vologda oblast 1.69 2.03 1.82 1.34 1.Voronezh oblast 2.63 3.29 2.44 2.35 2.City of Moscow 2.13 5.98 4.49 4.48 5.Saint Petesrburg 3.62 3.20 5.50 3.85 3.Jewish Autonomous 8.41 3.96 3.22 5.01 4.oblast Ivanovo oblast 1.08 1.53 3.68 3.61 2.Irkutsk oblast 2.39 2.73 1.81 1.60 1.Kabardino-Balkar Re6.21 9.13 7.28 7.83 8.public Kaliningrad oblast 1.91 2.88 2.84 2.65 1.Kaluga oblast 3.54 5.12 4.02 3.15 3.Kamchatka oblast 1.46 4.98 5.14 4.64 2.Karachay-Cherkess 3.90 5.16 6.24 6.14 4.Republic Kemerovo oblast 2.88 3.67 2.20 1.58 1.Kirov oblast 1.97 1.96 1.98 1.89 1.Komi-Permyak autono1.11 2.26 5.68 11.13 3.mous okrug Koryak autonomous 0.65 2.37 4.89 8.96 2.okrug Kostroma oblast 1.95 2.95 4.40 3.27 2.Krasnodar krai 2.43 3.72 2.27 2.32 2.Krasnoyarsky krai 1.30 1.02 2.06 1.33 0.1 2 3 4 5 Kurgan oblast 2.38 2.63 1.92 2.46 2.Kursk oblast 1.98 2.36 2.21 2.05 2.Leningrad oblast 3.48 3.83 3.21 3.15 3.Lipetsk oblast 2.47 2.73 1.81 0.90 2.Magadan oblast 3.49 4.70 3.81 3.71 2.Moscow oblast 6.13 4.84 3.81 2.01 4.Murmansk oblast 1.16 1.09 1.47 2.05 1.Nenetsky autonomous 1.95 2.47 3.05 2.45 2.okrug N.

Novgorod oblast 1.77 2.50 1.58 1.85 2.Novgorod oblast 1.25 1.38 0.86 0.85 1.Novossibirsk oblast 1.78 2.90 2.60 2.47 1.Omsk oblast 2.11 1.98 1.96 1.63 1.Orenburg oblast 1.16 1.13 2.45 1.39 1.Orel oblast 5.02 2.80 3.17 1.48 4.Penza oblast 3.48 4.20 6.24 4.69 4.Perm oblast 1.27 1.64 1.58 2.49 1.Primorye krai 1.77 1.84 1.86 2.01 1.Pskov oblast 3.97 5.77 5.03 3.61 4.Republic Of Adygeya 4.06 4.75 12.16 10.02 5.Altay Republic 2.46 3.43 14.57 13.55 4.Republic of Bashkor3.43 6.90 7.09 6.26 4.tostan Republic of Buryatia 1.79 3.05 3.14 3.46 1.Republic of Dagestan 7.36 8.76 10.72 7.53 9.Ingoush Republic 29.23 8.73 20.97 15.04 31.Kalmyk Republic 13.38 3.15 3.24 4.23 9.Republic of Karelia 2.36 3.57 3.37 3.04 2.Republic Komi 1.19 1.85 0.00 1.27 2.Republic of Mary El 4.15 4.81 3.64 3.76 3.Republic of Mordovia 4.66 3.98 8.78 8.90 5.Republic of Sakha 4.69 5.74 5.18 3.37 2.(Yakutia) Republic of North 7.53 11.32 9.40 8.87 9.Ossetia (Alania) Republic of Tatarstan 1.01 3.41 5.40 2.74 2.Republic of Tyva 7.56 5.94 11.17 8.59 5. 1 2 3 4 5 Republic of Khakassia 1.76 2.09 1.56 1.41 1.Rostov oblast 2.81 3.65 3.46 3.26 3.Ryazan oblast 1.25 1.98 1.23 2.59 1.Samara oblast 0.78 0.91 2.74 1.74 1.Saratov oblast 3.14 1.58 1.86 3.28 3.Sakhalin oblast 3.05 3.76 2.37 1.76 1.Sverdlovsk oblast 1.20 3.09 2.45 2.54 2.Smolensk oblast 1.05 1.26 1.48 1.90 1.Stavropol krai 3.97 3.64 2.92 2.26 3.Taymyr (DolganNenetsky) autonomous 3.78 4.32 7.99 5.07 3.okrug Tambov oblast 1.67 1.81 1.96 2.61 2.Tver oblast 3.47 3.33 2.49 2.52 2.omsk oblast 1.82 0.97 1.78 1.03 0.Tula oblast 3.54 10.87 4.45 2.68 4.Tyumen oblast 0.27 2.39 2.21 0.17 0.Udmurt Republic 1.91 2.36 2.63 2.01 2.Ulyanovsk oblast 3.68 4.33 3.59 2.83 3.Ust-rdynsky Buryatsky 3.00 5.48 5.64 5.88 3.autonomous okrug Khabarovsk krai 3.09 2.14 4.72 3.51 2.Khanty-Mansy autono3.04 3.10 4.13 2.79 2.mous okrug Chelyabinsk oblast 3.26 4.28 3.80 2.88 3.Chita oblast 1.99 1.82 2.82 4.23 1.Chuvash Republic 4.98 6.91 6.25 6.02 5.Chukotka autonomous 4.72 5.41 8.97 7.70 3.okrug Evenk autonomous 11.73 5.87 11.30 26.97 8.okrug Yamal-Nenetsky 6.88 5.02 1.98 2.78 2.autonomous okrug Yaroslavl oblast 2.77 2.09 1.39 1.45 1.3. Decomposition of Economic Growth in Russias Regions As shown in the previous chapter, Russian regions have demonstrated a great deal of diversity in terms of pace of their development. More specifically, it can be argued that, overall, those regions that at the starting moment had been poorer than others demonstrated a greater pace of growth over the whole period of observations, however the differentiation between the extreme regions continued to increase.

Decomposition of growth by factors can form the first step towards explanation of the inter-regional differentiation of economic growth rates. This particular procedure also forms the first step to identification of driving forces behind economic growth. The main purpose of the decomposition is to identify sources of growth and its division into extensive and intensive components. Intensive component is usually singled out in the form of an assessment of total factor productivity (TFP) or technical progress embodied in factors of growth (labor and capital).

In earlier IETs papers (Entov, Lugovoy at al. (2003)), their authors conducted decomposition of economic growth by factors on the sectoral and general economy levels. The research demonstrated that during the transition period a considerable rate of the dynamics of output in the industrial sector was determined by the loading rate of then existing capacities and intensity of the use of labor (see Table A2-1 and Fig. A2-1 in the Annex2). Meanwhile, the contribution rate of TFP to the growth of output in the industrial sector accounted for 2050%.

At the level of GDP, economic growth unexplained by the basic factors (labor and capital) accounted for a far greater value some 3070% (see Table A2-2 and Fig. A2-2 in the Annex 2). This particular level of unexplained economic growth is typical of the earliest computations of decomposition of growth (see, for example, Solow (1957), Kuznets (1996)), while consequent research demonstrated that the value of the remainder can be diminished considerably or even reduced to zero by means of a more accurate measure of growth factors25.

It should be noted that a greater accuracy of measuring requires a greater data detalization (disaggregation), which is not always possible, given the state of the national statistics in Russia. However, in the circumstances even fairly rough assessments may prove to be useful from the perspective of understanding of the ongoing processes and political decision making.

The earlier IETs research demonstrated that the dynamics of TFP advanced those of output. The productivity series had experienced a turn of the trend from the transformational decline to growth in 13 years earlier than output did.

The present paper constitutes an attempt to decompose economic growth of Subjects of the Russian Federation basing on the officially published statistical information.

3.1. Methodology and Data The problem of decomposition of growth by factors, alias growth accounting, found itself among the most debated issues of the second half of the 20th century. Despite the seemingly simple In their paper, Griliches and Jorgenson (1967) were the first to put forward a hypothesis on the possibility for total factor productivity being reduced to zero by means of a more accurate measuring of the factors. However the hypotheses suggests that technical progress is embodied in capital and labor. The discussion with Dennison allowed a demonstration of the fact that even under a more accurate measure of indicators of growth of output and factors the unexplained remainder remains substantial, anyway, albeit accounting for a considerably smaller value.

task setting that is, identification of a contribution of factors (labor, capital, among others) to the growth in output and thus singling out an unexplained by the factors remainder (usually interpreted as TFP), the main discussion centered on the problem of measuring the factors.

However, the research community has recently succeeded in mobilizing consensus on a number of key issues, albeit many of them still remain open for discussion. The main approaches and issues of decomposition still under discussion have been highlighted to a greatest possible extent in two OECD methodological papers (2001a and 2001b) and a NBER monography (2004). The aforementioned IET paper on analysis of factors of Russian economic growth (Entov, Lugovoy at al. (2003)) provides a review of main issues of decomposition of growth.

Given the narrowness of the available statistical base, the present paper considers the possibility for employment of various methods of decomposition (direct and dual) and measuring the employed indicators (output, labor and capital).

All the computations were conducted using the official information on socioeconomic state of Subjects of the Russian Federation published by Rosstat. Naturally, not all the information needed for the purpose of the analysis has become available the problem was remedied by introduction of various estimates or affected the employed methodology and interpretation of results. All the methodology and work with the data, as well as interpretation of the findings are given below.

3.2. The Main Approach to Decomposition of Growth Underlying the method of decomposition of growth is the assumption of the existence of a macroeconomic production function that determines a correlation between the maximum possible vol ume of output and production factors available, under a given level of technology:

Y = f (K, L, A), where Y output, L labor input, K capital input, technology.

Analogously to the national level, the production function can be computed for every region. Then the decomposition of growth in every regions output is made proceeding from the differential form of the production function:

& & & Y FK K K FL L L = gTFP + +, (3.1) Y Y K Y L where:

FK and FL marginal products of capital and labor production factors, respectively, gTFP growth rate determined by technical progress:

& FA A A gTFP (in the case of the neutral technical pro Y A & A gress ).

gTFP A The pace of growth of technical progress is computed as a remainder:

& & & Y FK K K FL L L gTFP = - -. (3.2) Y Y K Y L Thus received growth rates of technical progress are usually defined as assessment of growth of total factor productivity26.

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