The econometric model of diagnosis and prognosis of sectors of the economy of Ufa

ПОДЕЛИТЬСЯ С ДРУЗЬЯМИ
Authors


graduate student
Russia, Republic of Bashkortostan, the Bashkir State University
k.t.a.1991.1991@mail.ru


Head of Department of Mathematical Methods in Economics, Doctor of Economics, professor
Russia, Republic of Bashkortostan, the Bashkir State University

Abstract

The article presents the results of a model of diagnosis and prediction of economic activities of Ufa. This research is an analytical support for the creation of the economic development strategy of the metropolis. The vector autoregression model was chosen as a tool for the diagnosis of the economy, which allowed to take into account the relationship between the main macroeconomic indicators.

Keywords

development of industries, econometric modeling, vector autoregression model

Рекомендуемая ссылка

Belova Tat'jana Aleksandrovna , Bahitova Railya Hurmatovna
The econometric model of diagnosis and prognosis of sectors of the economy of Ufa// Современные технологии управления. ISSN 2226-9339. – #9 (69). Номер статьи: 6902. Дата публикации: . Режим доступа: http://sovman.ru/en/article/6902/

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References

  1. Strategic planning in the cities and regions of Russia [Strategicheskoe planirovanie v gorodah i regionah Rossii]. Official site of the Resource Centre for Strategic Planning (RTSSP) under Leontief Centre. URL: http://www.city-strategy.ru/regions/?rt=1 (reference date: 01.11.2014).
  2. The territorial body of the Federal Service for State Statistics RB [Territorial’nyj organ Federal’noj sluzhby gosudarstvennoj statistiki po RB]. official website. URL: http://bashstat.gks.ru/wps/wcm/connect/rosstat_ts/bashstat/ru/ (reference date: 20.09.2014).
  3. Suhanova E.I., Shirnaeva S.Ju. Forecasting performance stabilization of the Russian economy-based process models VAR [Prognozirovanie pokazatelej stabilizacionnyh processov jekonomiki Rossii na osnove modelej vektornoj avtoregressii].Economics. Basic research. Economic Sciences. Fundamental research. 2014.№9. P. 1590-1595.
  4. Derjugina E., Ponomarenko A. Large Bayesian vector autoregression model for the Russian housekeeper [Bol’shaja bajesovskaja vektornaja avtoregressionnaja model’ dlja rossijskoj jekonomki]. A series of reports on economic research. The Bank of Russia. March 2015. №1
  5. Central Bank [Central’nyj bank RF]. URL: http://cbr.ru/ (reference date: 20/03/2015)
  6. Dickey D.A., Fuller W.A. Distribution of the Estimators for Autoregressive Time Series with a Unit Root J. of the American Statistical Association.1977. №74. P. 427-431.
  7. Green W.H. Econometric Analysis (Fifth edition). Prentice Hall International, Inc. 2003. P. 1056.
  8. Grandger C.W.J. Investigating Causal Relations by Econometric Models and Cross – spectral Methods // Econometrica. V. 37. №3. P. 424-438.
  9. Dubrovin S. Investigation of causality if the stock market operations [Issledovanie prichinno-sledstvennyh svjazej pri operacijah na fondovom rynke]. Izvestiya of the Tula State University. Natural Sciences. 2009. Issue 2 P.167-173.
  10. Bannikov V.A. Vector autoregression model and correction of the regression residuals (EViews) [Vektornye modeli avtoregressii i korrekcii regressionnyh ostatkov (EViews)]. Journal of Applied Econometrics. 2006. № 3. P. 96-129.
  11. White Halbert. A Heteroskedasticity-Consistent Covariance Matrix and a Direct Test for Heteroskedasticity. 1980. №48. P. 817-838.
  12. Kelejian H. H. An Extension of a Standard Test for Heteroskedasticity to a Systems Framework . Journal of Econometrics. 1982. №20. P. 325-333.
  13. Lutkepohl Helmut. Introduction to Multiple Time Series Analysis. New York. Springer-Verlag. 1991.
  14. Abakumova Ju.G. The use of vector autoregression models for the study of the interest rate channel of transmission of monetary policy of the Republic of Belarus mechanism [Primenenie modelej vektornyh avtoregressij dlja issledovanija procentnogo kanala transmissionnogo mehanizma monetarnoj politiki Respubliki Belarus’]. Economy and Management. 2011. №2
  15. Kantorovich G.G. Lectures and tutorials. Time series analysis [Lekcionnye i metodicheskie materialy. Analiz vremennyh rjadov]. VSHE.2002 Economic Journal. №4 P. 498-523
  16. Speranskaja L.L. Improving monetary policy with Russia, taking into account the differences in the reactions of the regional economy [Sovershenstvovanie denezhno-kreditnoj politiki Rossii s uchetom razlichij v reakcijah regional’nyh jekonomiki]. Management of economic systems. 2015.
  17. Asteriou, Dimitrios; Hall, Stephen G. (2011). “Vector Autoregressive (VAR) Models and Causality Tests”. Applied Econometrics (Seconded.). London. Palgrave MacMillan. P. 319-333.
  18. Enders, Walter (2010). Applied Econometric Time Series (Thirded.). New York: John Wiley & Sons. P. 272-355. ISBN 978-0-470-50539-7.