IDENTIFICATION OF THE UNOBSERVABLE COMPONENTS IN THE OUTPUT TRAJECTORY: POTENTIAL LEVEL AND GAPS

He authors systematize the most well-known concepts and definitions of potential output and gaps according to the various economic schools approaches. The article also provides a typology of basic econometric methods for estimating potential level and output gap in the national gross product dynamics. The authors give a brief description of various econometric methods of statistical decomposition of the Gross Value Added dynamics for long -term potential level and short-term deviation - from simple statistical filtering to complex dynamic stochastic general equilibrium models. In particular, they describe properties of one -dimensional filters, which are based on statistical evaluation of interrelations only in the output dynamics, with decomposing long-term level by probabilistic methods without taking into account any settings of economic theory. Also, authors examine advantages and disadvantages of multi-dimensional and structural methods for estimating potential levels and output gaps, which allow considering the economic interrelations through inclusion of additional relevant variables. These include multidimensional Hodrick-Prescott filter, multivariate models with unobserved components, structural vector autoregression models, and stochastic dynamic general equilibrium model. The analysis of decomposition methods and numerous studies devoted to this problem lead to conclusion that decomposition of time series for long-term and cyclical components is not a trivial task, which may have a unique solution. Many of decomposition methods are sensitive to input data, including presence of additional parameters in the model, therefore more complex algorithms may show poorer results than algorithms based on statistical analysis, without taking into account an economic nature of investigated series. The results of the research substantiated the assumption that finding the best decomposition method in various countries is possible only through empirical studies.

конъюнктурный мониторинг, бизнес-циклы, потенциальный выпуск, разрыв ВВП, business tendencies monitoring, business cycles, potential output, output gap

1. Brunner K., Meltzer A.H. Stabilization policies and labor markets // Carnegie-Rochester Conference Series on Public Policy. 1988. Vol. 28. P. 1-8.

2. Romer D. Advanced macroeconomics. The McGraw-Hill Companies, Inc. 1996.

3. Razin A. Aggregate supply and potential output. NBER Working Paper No. 10294. 2004. URL: http://www. nber.org/papers/w10294.pdf.

4. Hauptmeier S., Heipertz M. and Schuknecht L. Expenditure reform in industrialised countries: A case study approach. ECB Working Paper No. 634. 2006.

5. Beveridge S., Nelson Ch.R. A new approach to the decomposition of economic time series into permanent and transitory components with particular attention to measurement of the business cycle // Journal of Monetary Economics. 1981. No. 7. Р. 151-174. URL: http ://www.uh.edu/~cmurray/courses/econ_7395/ Beveridge%20Nelson.pdf.

6. Baxter M., R.G. King. Measuring business cycles: approximate band-pass filters for economic time series // Review of Economic and Statistics. 1999. Vol. 81. No. 4. P. 575-593.

7. Christiano L.J., Fitzgerald T.J. The band pass filter. NBER Working Paper No. 7257. 1999.

8. Hodrick R., Prescott E., Postwar U.S. Business cycles: an empirical investigation // Journal of money, credit and banking. 1997. Vol. 29. No. 1. Р 1-16.

9. Cotis J.P., Elmeskov J., Mourougane A. Estimates of potential output: Benefits and pitfalls from a policy perspective / Reichlin L. (ed.). The Euro area business cycle: stylized facts and measurement issues. London. 2004. P. 35-60.

10. Vetlov I., Hledic T., Jonsson M., Kucsera H., Pisani M. Potential output in DSGE models. ECB Working Paper No. 1351. 2011.

11. Blanchard O.J., Quah D. The dynamic effects of aggregate demand and supply disturbances // The American Economic Review. 1989. Vol. 79. No. 4. Р 655-673. URL: http://www.jstor.org/stable/pdfplus/1827924.pdf.

12. Nilsson R., Gyomai G. Cycle extraction: a comparison of the PAT method, the Hodrick-Prescott and Christiano-Fitzgerald filters. OECD. 2011. URL: http://www.oecd. org/std/leading-indicators/41520591.pdf.

13. Китрар Л.А., Остапкович Г.В. Особенности и направления использования индикаторного подхода в циклическом мониторинге экономической динамики // Вопросы статистики. 2013. № 8. С. 42-50.

14. Китрар Л.А., Остапкович Г.В. Интегрированный подход к построению композитных индикаторов со встроенным алгоритмом оценки цикличности в динамике результатов конъюнктурного мониторинга // Вопросы статистики. 2013. № 12. С. 23-34.

15. Maravall A., del Rho A. Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter // Computational Statistics & Data Analysis. 2007. Vol. 52. No. 2. Р 975-998.

16. Kalman R.E. A new approach to linear filtering and prediction problems // Transactions of the ASME -Journal of Basic Engineering. 1960. Vol. 82 (Series D). P 35-45. URL: www.cs.unc.edu/~welch/kalman/media/ pdf/Kalman1960.pdf.

17. Zhang X., Conn L. Estimating the cyclical component from annual time series. ABS Research Paper No. 1352.0.55.085. Australian Bureau of Statistics, Canberra. 2007.

18. Dias M.-H.A., Dias J., Evans Ch.L. Estimation of the cyclical component of economic time series. National Council for Scientific and Technological Development (CNPq), Brazil and Research Department of the Federal Reserve Bank of Chicago, USA. 2004.

19. Chagny O., Döpke J. Measures of the output gap in the Euro-Zone: an empirical assessment of selected methods. Kiel Working Paper No. 1053. 2001.

20. McMorrow K., Roeger W. Potential output: measurement methods, «new» economy influences and scenarios for 2001-2010 - a comparison of the EU15 and the US. European Commission Economic Papers No. 150. 2001.

21. Canova F. Detrending and business cycles facts // Journal of Monetary Economics. 1998. Vol. 41. Iss. 3. Р. 475-512.

22. Kuttner K.N. Estimating potential output as a latent variable // Journal of Business and Economic Statistics. 1994. Vol. 12. Iss. 3. Р. 361-368.

23. Kichian M. Measuring potential output with a state space framework. Bank of Canada Working Paper 99-9. 1999.

24. Rünstler G. The information content of real-time output gap estimates: an application to the Euro area. ECB Working Paper No. 182. 2002.

25. De Brouwer G. Estimating output gaps. Reserve Bank of Australia Research Discussion Paper 9809. 1998. URL: http://www.rba.gov.au/publications/rdp/1998/9809.html.