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So, the theoretical assessments of fixed assets should represent an aggregate indicator that considers changes in the quality of individual production units associated both with their ageing and depreciation, and the change of the technological level. The building of such an assessment necessitates information of assets being placed into operation, their productivity in comparison with already existing ones, their operational term, maintenance and repair costs, and numerous other factors (see (3.7)(3.8)).

The statistics of the national wealth is one of the weakest spots of Russian statistics. At the conference Assessment and Management of the National Wealth in Russia (Ivanov, Khomenko (2003)), its participants noted that the absence of the respective information base and the mismatch between the principles of Russian accounting system and those of the National Accounting System posed the critical problem in this area. In Russian accounting system, fixed assets are often assessed basing on their initial price, rather than on prices in existence as of the moment of compiling reports; the detailed information of the structure of fixed assets is lacked as well. In addition, revaluations of fixed assets that have become compulsory since 1997 also introduce considerable biases.

The currently existing drawbacks of the national wealth statistics, as well as of the statistics of fixed assets of the Soviet period that form the starting point for computations of their dynamics seriously complicate the task of assessing actual changes in volumes of production capacities. According to the official statistical data, the physical volume of fixed assets grew by 5.99% between and 2001; according to some estimates (Khanin (2005)), fixed production assets fell by 30% over the period concerned, while their active part contracted by 5060%; according to the IET experts (Entov, Lugovoy at al. (2003)) Russias fixed assets shrank by 12% on average, while effective ones 2.9 times on average.

At the regional level, the statistical data on fixed assets appeared yet poorer. The practically available regional indicator that regional government statistical bodies provide is the total book value of fixed assets, which, due to fixed assets revaluations, poorly mirrors actual processes of formation of enterprises production capacities in a given region. For example, the dynamics of FA indices (computed on the basis of FA value given in constant prices on the basis of the GDP deflator averaged as of the start and end of a given pe riod) across the federal okrugs (Fig. 3.8) demonstrates a drastic rise in 1997 and a dramatic decline afterwards.

1996 1997 1998 1999 2000 Russian Federation Far-Eastern Volga North-Western Siberian Ural Central Southern Fig. 3.8. The Dynamics of Fixed Assets Indices of Across the Federal Okrugs (1996 = 100%) The existing investment statistics do not seriously improve the situation, as it is hard to bring the data to a comparable form (there is no reliable deflator on hand), while the building of the indicator on the basis of the constant inventory methods requires fairly long series.

The dynamics of fixed assets presented in Fig. 3.8 appear poorly correspondent to the fixed assets renovation and replacement statistics. According to the official data, during the period in question, the commissioning of fixed assets into operation by the economy as whole did not exceed 1.5% of their volume as of end-year, while their replacement rate did not exceed 1.3% of their volume as of the beginning of the year. The dynamics of the coefficients witness that the volume of fixed assets had remained practically constant prior to 1999, after which there arose a trend to their insignificant growth (with the renovation coefficients advancing the replacement ones). Underlying such discrepancies is likely to be the ongoing re valuations of fixed assets.

Due to the absence of the necessary information on the regional level, it appears impossible to directly employ the approach that is based on the renovation and replacement coefficients (the IET expert team (Entov, Lugovoy at al. (2003)) used this particular approach to decompose growth on the sectoral level).

That is why the index of the physical volume of fixed assets of i region was built basing on the data on investments. In the course of conduct of the assessment it is assumed that the regional structure of investment coincides with the regional structure of fixed assets commissioning, while their replacement rate is equal across all the regions:

FAi (t) = FAi (t -1) + Rni (t) - Rpi (t), (3.9) where FAi (t) volume of fixed assets of i region as of the end of period t;

Rni (t) commissioning fixed assets of i region in period t, computed on the basis of the data on investment and the fixed assets renovation rate across Russia as a whole ktRn :

i I (t) Rni (t) = ktRn FA(t), I(t) FA(t) volume of fixed assets across Russia as a whole as of end period t, i I (t) investments of i region in period t, I(t) investments across Russia as a whole in period t, Rpi (t) withdrawal of fixed assets of i region in period t, computed on the basis of the fixed assets replacement rate across Russia as a whole ktRp : Rpi (t) = ktRp FAi (t -1).

Thus built index of the physical volume of fixed assets demonstrates loose positive dynamics for most of the federal okrugs between 1997 and 2002 (see Fig. 3.9), except for the Siberian and Far-Eastern ones. As concerns the Siberian okrug, the trend of its index is strictly negative.

In any case, the range of the change of assets accumulated over the six years in question was found to be within 5%.

1996 1997 1998 1999 2000 2001 Russian Federation Far-Eastern Volga North-Western Siberian Ural Central Southern Fig. 3.9. The Index of the Physical Volume of Fixed Assets by Federal Okrugs (1996 = 100%) Let us once again note that the index of the physical volume of FA received on the basis of the renovation and replacement rates forms rather a rough approximation of the dynamics of the physical volume of capital. It does not consider changes in the productive capacities efficiency due to their age, physical depreciation and moral ageing. This leads to an additional error of measure of the contribution capital services make to economic growth, thus increasing an unexplained by production factors remainder (TFP).

The theoretical assessment of capital input (in the assumption that technical progress is not embodied in capital) is built on the basis of the weighted sum of production means of different age (see (3.7)).

In addition, the FA replacement rate does not mirror the latent replacement of the production equipment due to a change in a given product range, decay and depreciation of production capacities that continue to remain on enterprises balance-sheets. The nationwide FA depreciation rate grew on average from 41.9% in up to 47.9% in 2002. An analogous situation is noted for most regions (see Annex 2, Table A2-7). The most substantial rise in the depreciation rate was noted in Kostroma oblast (from 37.4 to 55.3%), Republic of Tyva (from 35.5 to 48.5%), city of Moscow (37.7 to 50.1%), Khabarovsk krai (32.7 to 44.7%), Penza oblast (42.2 to 53.7%). In 2002, the level of depreciation of FA in Kirov and Yroslavl oblasts exceeded 57%. The depreciation of FA in 19992002 fell only in 12 regions: republics of Ingoushetia, kalmykia, Altay, Chuvashia, North Ossetia-Alania, Dagestan, Karachaevo-Cherkessia, Krasnodar krai, Tomsk, Astrakhan, Arkhangelsk and Tyumen oblasts, and for most of them the fall was insignificant.

As it noted in the case of labor input, the dynamics of the index of the physical volume of FA likewise display no visible similarity to the dynamics of the GRP index (see Fig. 3.1). A considerable fall in GRP index is accompanied by almost constant value of the index of the physical volume of FA.

This can be attributed to the fact that the volume of production means does not fully mirror the capital formation process, as it overvalues the assessment of their part that is actually involved in production. Plus, the given series imply the constancy of output depending on the age of the equipment and improvement of means of production, which increases their net contribution to output.

A more accurate assessment of capital necessitates the account of a change in the volume of production capacities as well as intensity of their use. In the present paper, the intensity of the use of FA is computed basing on the data on the level of electricity consumption (such a method was employed by Griliches, Jorgenson (1967);

Costello (1993)32), whose dynamics across the federal okrugs are given in Fig. 3.10.

Whilst employing the electricity consumption indicator as an indicator of the capacity loading rate, one needs to conduct an adjustment at the change of the average capacity of the production equipment involved in the production process. There are no necessary statistical data to make the respective assessments by regions.

However, as during the period in question FA renovation rate by the economy as a whole has not exceeded 1.5% of their volume as of endyear, it appears possible not to adjust the indicators.

The product of the multiplication of the index of the physical volume of FA by the capacity loading level index is regarded as the capital index (Fig. 3.11).

According to Denison, the employment of the electricity consumption indicator as the one of production capacity loading is incorrect, primarily because there are no adjustments made to the economic cycle. Second, an accurate assessment necessitates the use of kilowatt-hours consumed by means of production for which electricity forms a major source of power.

1996 1997 1998 1999 2000 2001 Russian Federation Far-Eastern Volga North-Western Siberian Ural Central Southern Fig. 3.10. Capacity Loading Rate Index by the Federal Okrugs (1996 = 100%) 1996 1997 1998 1999 2000 2001 Russian Federation Far-Eastern Volga North-Western Siberian Ural Central Southern Fig. 3.11. Capital Index by the Federal Okrugs (1996 = 100%) Table 3.Results of Assessment of the Output Growth rates and Contribution of Components of Capital Input by the Federal Okrugs Growth rates As % of the GRP growth rates Effect from Effect from Effect from Effect from Federal okrug the change of the change of the change in Effect from the change in Effect from the level of GRP the level of the volume of capital input the volume of capital input capacity capacity FA FA loading loading 1997Far-Eastern 0.09 1.52 1.61 4.80 1.83 31.66 33.Volga 0.13 1.56 1.43 2.63 5.05 59.34 54.North-Western 0.10 0.34 0.44 3.22 3.14 10.68 13.Siberian 0.26 2.03 2.29 6.69 3.82 30.40 34.Ural 0.27 0.54 0.27 2.92 9.17 18.44 9.Central 0.08 0.32 0.25 0.12 62.46 265.28 202.Southern 0.06 2.48 2.42 3.66 1.52 67.66 66.1999Far-Eastern 0.05 0.17 0.22 4.60 0.98 3.71 4.Volga 0.28 0.64 0.92 5.52 5.11 11.54 16.North-Western 0.17 0.96 1.13 7.46 2.29 12.89 15.Siberian 0.19 1.35 1.16 5.60 3.39 24.20 20.Ural 0.53 1.13 1.66 6.22 8.53 18.19 26.Central 0.35 1.45 1.80 7.72 4.54 18.78 23.Southern 0.40 0.50 0.90 8.17 4.90 6.14 11.1997Far-Eastern 0.00 0.40 0.40 1.37 0.06 28.99 28.Volga 0.23 0.10 0.13 2.73 8.50 3.65 4.North-Western 0.08 0.52 0.60 3.77 2.13 13.89 16.Siberian 0.21 0.21 0.00 1.33 15.93 15.92 0.Ural 0.44 0.57 1.01 3.08 14.36 18.56 32.Central 0.26 0.86 1.11 5.13 5.05 16.70 21.Southern 0.29 0.50 0.22 4.07 7.00 12.30 5.The computations (see Table 3.4) testify that for most regions capital input form a more significant growth factor than labor input (see Table 3.3 and Table 3.4), which becomes especially notable in the period of growth of 19992002. Given the above, as it was noted in the case of labor input, the impact of capital inputon the output growth rate likewise appeared more substantial at the stage of decline (19971998) than at the stage of growth in output (19992002).

The percentage of the output growth rates explained by the change in capital input Fig. 3.12. Bar Chart of the Output Growth Rate Explained by Changes in Capital Input Across Regions (the Period between 1997 and 2002) As it noted for the case of labor input, the percentage of output growth rates explained by changes in capital inputlikewise varies across regions. There exist a number of them for which the direction of changes in the output growth rates appears opposite to the one of changes in the capital inputgrowth rates (negative values in the Bar Chart). For most regions, changes in the volume of fixed assets in a region with account of their loading level explain 040% Number of Regions ) ) ) ) ) ) ) ) ) ) ;

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( r e ( ( ( ( v e ( ( ( ( o d n ( u of their GRP growth rates (see Fig. 3.12). Similar to the case of labor input, negative values of the proportion of the output growth rates explained by changes in capital input are largely explained by the selection of the initial and final points of a given time interval.

In sub-periods (see Annex 2, Fig. A2-5 and A2-6), the indicator value for most of regions finds itself within 020%. In 19971998, only 14% of regions saw changes in their output coupled by an opposite change in capital input, wile the proportion of such regions grew up to 36% in 19992002.

3.2.4. Assessing Weight Coefficients to Integrate Inputs As noted above, decomposition requires the presence of marginal factor products and their proportion in the output on hand to have a possibility for computing weight coefficients L and K (see (3.2)(3.4)) to integrate factor costs.

There exist two main methods to assess the coefficients: (1) econometric and (2) basing on proportions of factors in the output (in the assumption of the equality between marginal products of factors and prices for them). Econometric method entails some complexities33 and cannot be employed in the absence of a sufficient mass of data. That is why in this paper we employed the other, widespread method.

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