1. Approaches to increase efficiency of the IO tool in the system of scenario forecasting Strizshkova L.A.(reporter) Kuranov A.G. Zhuravskiy V.P. Tishina L.I. Slobodyanik S.N. 1

2. IO models have a set of unique characteristics which determine their important role in scenario forecasting IO models’ characteristics Consideration of system (i. a. intersectoral) links and compliance with balance identity Consideration of demand multipliers Consideration of price multipliers Role of IO models in scenario forecasting Identifying imbalances between forecast figures estimated exogenously Coordination of forecast figures within the system of IO models Scenario calculations “What happens if …” 2

3. IO models require a specific information support, primarily – time series of statistical data which include the system of IO tables Since 2003 economists don’t have official statistical estimations of IO tables. Time series for many others indicators are broken and consequently short. Should we deal with the IO analysis under the circumstances? Should we try to feel information gaps by expert estimations? Our answer is “YES”. This allows: To maintain traditions in IO researches To maintain Russian economy history To reveal economic relations for purposes of further forecasting To apply the IO tool in scenario forecasting and to receive additional estimated referents points 3

4. Our institute – FBNU IMEI – applies the IO model (IOM) and other models as well in scenario forecasting by order of the Ministry of Economic Development. Calculations are performed several times a year in accordance with the chart of the Ministry’s projects which include forecasts of Russian socio-economic development. Our institute IOM takes into account all the parameters of scenario conditions and reference points developed by the Ministry. On the one hand, it is very convenient, but on the other hand, the IOM requires a large amount of exogenous information. IOM The model complex “FORECAST” is developed in IMEI. This increases efficiency of the IOM use. The IOM as a part of the complex (and the complex itself) can work with minimum of input data if necessary. “FORECAST” 4

5. A set of control parameters for the model complex "FORECAST“ Scenario conditions Parameters of non- government policy external conditions demographic conditions Parameters of government policy investment policy social policy price policy tax policy Energy conditions for Russia extraction volumes export of energy resources other 5

6. The scheme of the model complex "FORECAST" Scenario conditions and models of macroeconomic targets Export/Import models Model of the labor market Model of financial balance of institutional sectors and balance of payments Model of consumer demand IOM with production and price blocks The balance of labor funds - analysis of innovation processes, evaluation of links and hypothesis Investment - fixed assets model Output information 1.Supply and Use tables of goods and services (indices of real dynamics and prices, outputs, GDP, import, export, etc.) 2. Financial indicators (investments, profit, taxes, custom duties, etc.) 3. Financial balances of institutional sectors, public finances and monetary sphere (GDI, DI, net lending/borrowing, M2X, etc.) 4. Quality characteristics of economic growth 6

7. The model complex “FORECAST” ensures consistency of forecast figures Consistency in time - «past determines future» t→t+1 Consistency in statics «resources – production» «demand – supply» «prices – income – demand» This can be achieved by - selection of models included in the complex - the principle of modeling - information databases Important question – how to organize the first iteration in conditions of minimum of forecast information? 7

8. Solution to the question – assessment of the initial values of key macroeconomic indicators which are used as exogenous parameters in IOM GDP final consumption investments in fixed assets exportimportexchange rate consumer price indices producer price indices other 8

9. The difficulty of the question is determined by small amount of initial data necessity to harmonize initial macroeconomic reference points with each other and with given scenario conditions 9

10. To resolve the question “step by step” calculation scheme can be applied The essence of the “step by step” scheme evaluation of each following indicator is based on previous estimates of other indicators and background information on scenario conditions To realize the “step by step” scheme – system of macroeconomic econometric functions is developed – number of consistent relations between indicators is identified – sequence of application of functions and relations is developed, what allows sequentially estimate initial macroeconomic parameters for IOM 10

11. Informational base of the IMEI’s IOM Block 1. The system of IOTs (expert estimations ) Sub-block 1.1. Analytics Sub-block 1.2. III quadrant – detalization Use tables for domestic production at basic prices Use tables for import production at basic prices Tables of trade and transport margins Table of net taxes on products (including excises, customs import and export duties, VAT and subsidies on products) Block 2. Import-Export Time series on export and import (based on customs statistics and the balance of payments) at current and constant prices and arranged with the IOM positions Block 2. Energy Time series of Energy balances (in physical units) with detailed characteristics of use (international standard) Block 3. Investments – fixed assets – capacity utilization Time series with data at current and constant prices arranged with the IOM positions Other information blocks with official statistical data (SNA statistics, statistics of production, prices, incomes, taxes, etc.). Sub-block 2.1. Analytics Sub-block 3.1. Analytics Sub-block 4.1. Analytics Sub-blocks with analytics 11

12. The structure of the IMEI’s IOM Production block Forecast estimates of the system of IOTs in the year t at constant prices of the year (t-1) considering: - production constraints -scenario conditions Price block Forecast estimates of the system of IOTs in the year t at prices of the year t considering: -scenario conditions - validation criteria Investment – fixed assets block Benchmarks for sectors’ productive capacities considering: - investments in fixed assets - forecast of the fixed assets balance - level of production capacity utilization 12

13. Control parameter and scenario conditions are benchmarks for production block of the IOM Parameters of dynamics of direct technological coefficients matrix Real dynamics indices of: - GDP - retail turnover - paid consumer services - investments in fixed assets - export and import of goods (11 product groups according with HS-codes) - budget spending for education, health, science ( % of GDP) Energy balances (physical units) Production constraints on energy Production block of the IOM 1. Sub-block of II quadrant estimations at purchasers’ prices 2. Sub-block of moving to II quadrant estimations at basic prices 3. Sub-block of output and margin tables calculation 1a. Sub-block of export and import vectors estimation 2 a. Sub-block of import matrix estimation Test on production constraints Balanced: → moving to price block Benchmarks from investment – fixed assets block Imbalanced: → correction of II quadrant 3a. Sub-block of stock changes restrictions 13

14. Control parameter and scenario conditions are benchmarks for price block of the IOM Indices of: - consumer prices - domestic prices for production of natural monopolies - domestic exchange rate - producers’ prices by sectors Indices of: - world prices for oil, gas, refined oil products - prices for export and import goods ( for 11 product groups according with HS-codes) Parameters of tax policy Households’ incomes; Policy parameters on social transfers and wages in the public sector Price block of the IOM 1. Sub-block of output and product use estimation at current basic prices 1a. Sub-block of export vector estimation at current basic prices and trade margin on export 2. Sub-block of moving to indicators of use at purchasers’ prices and evaluation of deflator indices Test on criteria for consistency -particular (by gross production profit) - macroeconomic (by aggregate macroeconomic indicators 2a. Sub-block of GVA elements estimation 3. Sub-block of independent estimation of producers’ price indices (econometrics) Imbalanced: → correction of domestic price indices Balanced: moving to next year estimation Benchmarks from investment – fixed assets block 14

15. Price indices in econometric block IOM (with close link which sustainable over time) Oil price index (Urals) Refined oil products world price index Electricity price index Indices of producers’ prices by sectors Oil and gas extraction Crude oil extraction DJ CB Metal ores Iron ore DG DM Coal Agriculture products DA DN CPI nonfood commodity CPI CPI food commodity DE Wood DI F F DD DF Price index for group D 15

16. IOM information database and special calculation schemes allow to conduct qualitative analysis of the economy 1. Investigation of income’s influence on the development and structure of the final demand 2. Factor analysis of industries using the total requirements matrix method of decomposition of intermediate consumption expenditures by elements of the final product 3. Research of competitiveness 3.1. Shifts in import consumption and import intensity in consumer market investment market domestic production 3.2. Shifts in structure of export and export-orientation of national production 3.3. Shifts in the structure of value formation 4. Analysis of the cost structure of the final product and the final output of the economy using method of decomposition of GVA by elements of the final product method of measuring the total import intensity by elements of final output 5. Investigation on influence of different factors (prices, taxes and other) on dynamics of inflation and industry prices 16

17. Summary Ways to improve the efficiency of IOM (to upgrade its analytical and predictive properties) Improving the statistical support for the IOM and other models of the complex «FORECAST” Improving the systemic linkages of IOM with other models of the complex "FORECAST" Improving the calculated blocks of IOM, including methods of evaluation of direct requirements matrix. 17

18. Thank you for your attention! 18