voprecotestВопросы экономикиVoprosy Ekonomiki0042-8736Voprosy Ekonomiki, NP10.32609/0042-8736-2016-6-45-75voprecotest-205Research ArticleИНСТРУМЕНТЫ МАКРОЭКОНОМИЧЕСКОЙ ПОЛИТИКИINSTRUMENTS OF MACROECONOMIC POLICYОбзор методов макроэкономического прогнозирования: в поисках перспективных направлений для РоссииA survey of methods for macroeconomic forecasting:looking for perspective directions in russiaПестоваА. А.PestovaA.

к. э. н., ведущий эксперт Центра макроэкономического анализа и краткосрочного прогнозирования (ЦМАКП), научный сотрудник Института народнохозяйственного прогнозирования РАН (ИНП РАН), старший научный сотрудник НИУ ВШЭ (Москва)

annapestova@gmail.comМамоновМ. Е.MamonovM.

к. э. н., ведущий эксперт ЦМАКП, научный сотрудник ИНП РАН, старший научный сотрудник НИУ ВШЭ (Москва)

mmamonov@forecast.ruЦентр макроэкономического анализа и краткосрочного прогнозирования (ЦМАКП); Институт народнохозяйственного прогнозирования РАН (ИНП РАН); НИУ ВШЭРоссияCenter for Macroeconomic Analysis and Short-Term Forecasting; Institute of Economic Forecasting, RAS; National Research University Higher School of EconomicsRussian FederationЦентр макроэкономического анализа и краткосрочного прогнозирования (ЦМАКП); Институт народнохозяйственного прогнозирования РАН (ИНП РАН); НИУ ВШЭРоссияCenter for Macroeconomic Analysis and Short-Term Forecasting, Institute of Economic Forecasting, RAS; National Research University Higher School of EconomicsRussian Federation201620062016064575Copyright © Voprosy Ekonomiki, NP, 20162016Voprosy Ekonomiki, NPVoprosy Ekonomiki, NPhttps://www.vopreco.ru/jour/about/submissions#copyrightNoticehttps://www.vopreco.ru/jour/article/view/205

В работе описана эволюция макроэкономических теорий в XX в. и развитие эмпирических моделей, предназначенных для прикладного макроэкономического прогнозирования. Сравниваются его современные структурные и неструктурные методы. Рассмотрена практика прогнозирования в России, выявлены ее недостатки и возможности улучшения.

The paper describes the evolution of macroeconomic theory in the XX century and the development of empirical models for applied macroeconomic forecasting. A comparison of modern structural and non-structural methods for macroeconomic forecasting is made. We consider the experience of macroeconomic forecasting in Russia and reveal its weaknesses and prospects for improvement.

макроэкономическое прогнозированиебольшие макроэконометрические моделибайесовская векторная авторегрессияDSGE-моделированиеmacroeconomic forecastinglarge macroeconometric modelsDSGE-modelingBayesian vector autoregressionReferencesОсновные направления единой государственной денежно-кредитной политики на 2015 год и период 2016 и 2017 годов; ФЗ РФ «О федеральном бюджете на 2015 год и на плановый период 2016 и 2017 годов» от 1 декабря 2014 гAstafieva E., Turuntseva M. (2014). Forecasting using large data sets. Part 2. Moscow: RANEPA. (In Russian).Астафьева Е., Турунцева М. (2014). Прогнозирование с использованием больших массивов данных. Ч. 2. М.: РАНХиГСAyvazyan S. A., Brodsky B. E., Sandoyan E. M., Voskanyan M. A., Manukyan D. E. (2013). Macroeconometric modeling of the economies of Russia and Armenia. II: Aggregated macroeconometric models of the national economies of Russia and Armenia. Prikladnaya Ekonometrika, Vol. 31, No. 3, pp. 7—31. (In Russian).Айвазян С. А., Бродский Б. Е., Сандоян Э. М., Восканян М. А., Манукян Д. Э. (2013). Макроэконометрическое моделирование экономик России и Армении. II: Агрегированные макроэконометрические модели национальных экономик России и Армении // Прикладная эконометрика. Т. 31, № 3. С. 7-31Borodin A., Gorbova E., Plotnikov S., Plushchevskaya Yu. (2008). Estimating potential output and other unobserved variables in a transmission mechanism model (The case of Russia). Proceedings of the II International scientific and practical conference, Minsk, May 19—20. Minsk: The National Bank of the Republic of Belarus, pp. 119—143. (In Russian).Бородин А., Горбова Е., Плотников С., Плущевская Ю. (2008). Оценка потенциального выпуска и других ненаблюдаемых переменных в рамках модели трансмиссионного механизма монетарной политики (на примере России) // Сборник докладов II международной научно-практической конференции, Минск, 19-20 мая. Минск: Национальный Банк Республики Беларусь. С. 119-143Demidenko M., Karatchoun O., Korshunov D., Lipin A., Hrebichek G. (2016). System for analysis and macroeconomic forecasting of the Eurasian Economic Union. Moscow; St. Petersburg: Eurasian Economic Commission; Eurasian Development Bank. (In Russian).Демиденко М., Карачун О., Коршунов Д., Липин А., Хребичек Г. (2016). Система анализа и макроэкономического прогнозирования Евразийского экономического союза. М.; СПб.: Евразийская экономическая комиссия; Евразийский банк развитияDeryugina E., Ponomarenko A. (2015). A large Bayesian vector autoregression model for Russia. Bank of Russia Working Paper Series, No. 1. (In Russian).Дерюгина Е., Пономаренко А. (2015). Большая байесовская векторная авторегрессионная модель для российской экономики // Банк России. Серия докладов об экономических исследованиях. № 1Zamulin O., Styrin K. (2012). How to distinguish cause and effect? (2011 Nobel memorial prize in economics). Voprosy Ekonomiki, No. 1, pp. 4—20. (In Russian).Замулин О., Стырин К. (2012). Как различать причину и следствие? Нобелевская премия по экономике 2011 года // Вопросы экономики. № 1. С. 4-20Ivashchenko S. M. (2013). Dynamic stochastic general equilibrium model with the banking sector and endogenous firm defaults. Zhurnal Novoy Ekonomicheskoy Assotsiatsii, Vol. 3, No. 19, pp. 27—50. (In Russian).Иващенко С. М. (2013). Динамическая стохастическая модель общего экономического равновесия с банковским сектором и эндогенными дефолтами фирм // Журнал Новой экономической ассоциации. Т. 3, № 19. С. 27-50Malakhovskaya O. A., Minabutdinov A. R. (2013). Dynamic stochastic general equilibrium model for the export-oriented economy (Preprint No. WP12/2013/04). Moscow: HSE. (In Russian).Малаховская О. А., Минабутдинов А. Р. (2013). Динамическая стохастическая модель общего равновесия для экспортоориентированной экономики (Препринт WP12/2013/04). М.: НИУ ВШЭ.Mikusheva A. (2014). Estimation of dynamic stochastic general equilibrium models. Kvantil, No. 12, pp. 1—21. (In Russian).А. Пестова, М. Мамонов / Вопросы экономики. 2016. № 6. С. 45-76 Микушева А. (2014). Оценивание динамических стохастических моделей общего равновесия // Квантиль. № 12. С. 1-21Mikhaylenko K. V. (2005). Economic and mathematical support for scenario forecasts of socio-economic development of Russia in the medium term. Abstract of the thesis. Moscow: IEF RAS. (In Russian).Михайленко К. В. (2005). Экономико-математическое обеспечение сценарных прогнозов социально-экономического развития России на среднесрочную перспективу. Автореф. дис. ... канд. экон. наук. М.: ИНП РАНPolbin A. V. (2014). The econometric estimation of the structural macroeconomic model of the Russian economy. Prikladnaya Ekonometrika, Vol. 33, No. 1, pp. 3—29. (In Russian).Полбин А. В. (2014). Эконометрическая оценка структурной макроэкономической модели российской экономики // Прикладная эконометрика. Т. 33, № 1. С. 3-29. [Porshakov A., Deryugina E., Ponomarenko A., Sinyakov A. (2015). Nowcasting and short-term forecasting of Russian GDP with a dynamic factor model. Bank of Russia Working Paper Series, No. 2. (In Russian).Поршаков А., Дерюгина Е., Пономаренко А., Синяков А. (2015). Краткосрочное оценивание и прогнозирование ВВП России с помощью динамической факторной модели // Банк России. Серия докладов об экономических исследованиях. № 2Skrobotov A., Turuntseva M. (2015). Forecasting properties of VAR models: Application to the Russian data. Nauchnyi Vestnik IEP im. Gaydara, No. 8, pp. 39—43. (In Russian).Скроботов А., Турунцева М. (2015). Прогнозные свойства VAR моделей: приложение к российским данным // Научный вестник ИЭП им. Гайдара. № 8. С. 39-43Styrin K., Potapova V. (2009). GDP leading indicator of RenCap-NES: Better and earlier. Moscow: NES, Renaissance Capital. (In Russian).Стырин К., Потапова В. (2009). Опережающий индикатор ВВП РенКап-РЭШ: лучше и раньше. М.: РЭШ, Ренессанс-КапиталTuruntseva M. (2011). Forecasting in Russia: Overview of the main models. Ekonomicheskaya Politika, No. 1, pp. 193—202. (In Russian).Турунцева М. (2011). Прогнозирование в России: обзор основных моделей // Экономическая политика. № 1. С. 193-202Turuntseva M., Astafieva E., Baeva M., Bozhechkova A., Buzaev A., Kiblitskaya T., Ponomarev Yu., Skrobotov A. (2015). Model short-term forecasts of socio-economic indicators of the Russian Federation. Nauchnyi Vestnik IEP im. Gaydara, No. 8, pp. 3—33. (In Russian).Турунцева М., Астафьева Е., Баева М., Божечкова А., Бузаев А., Киблицкая Т., Пономарев Ю., Скроботов А. (2015). Модельные расчеты краткосрочных прогнозов социально-экономических показателей РФ // Научный вестник ИЭП им. Гайдара. № 8. С. 3-33Turuntseva M., Yudin A., Drobyshevskiy S., Kadochnikov P., Ponomarenko S. (2005). Some approaches to forecasting economic indicators (Scientific Papers No. 89). Moscow: Gaidar Institute for Economic Policy. (In Russian).Турунцева М., Юдин А., Дробышевский С., Кадочников П., Пономаренко С. (2005). Некоторые подходы к прогнозированию экономических показателей (Научные труды № 89). М.: ИЭППUzyakov M. N., Brusentseva A. R., Govtvan O. J., Gusev M. S., Kaminova S. V., Mironova E. S., Savchishina K. E., Uzyakov R. M., Shirov A. A. (2009). Forecast of macroeconomic indicators of the Russian economy for 2009—2012. Problemy Prognozirovaniya, No. 4, pp. 3—25. (In Russian).Узяков М. Н., Брусенцева А. Р., Говтвань О. Дж., Гусев М. С., Каминова С. В., Миронова Е. С., Савчишина К. Е., Узяков Р. М., Широв А. А. (2009). Прогноз макропоказателей экономики России на 2009-2012 гг. // Проблемы прогнозирования. № 4. С. 3-25Shulgin A. G. (2014). Bayesian estimation of DSGE model with two monetary policy rules for Russia (Preprint No. WP12/2014/01). Moscow: HSE. (In Russian).Шульгин А. Г. (2014). Байесовская оценка DSGE-модели с двумя правилами монетарной политики для России (Препринт No. WP12/2014/01). М.: НИУ ВШЭBanbura M., Giannone D., Reichlin L. (2010). Large Bayesian vector autoregressions. Journal of Applied Econometrics, Vol. 25, No. 1, pp. 71-92.А. Пестова, М. Мамонов / Вопросы экономики. 2016. № 6. С. 45-76 Bai J. (2004). Estimating cross-section common stochastic trends in nonstationary panel data. Journal of Econometrics, Vol. 177, pp. 137-183.Banbura M., Giannone D., Lenza M. (2015). Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections. International Journal of Forecasting, Vol. 31, No. 3, pp. 739-756.Banbura M., Giannone D., Reichlin L. (2010). Large Bayesian vector autoregressions. Journal of Applied Econometrics, Vol. 25, No. 1, pp. 71-92.Banerjee A., Marcellino M., Masten I. (2008). Forecasting macroeconomic variables using diffusion indexes in short samples with structural change. In: D. Rapach, M. Wohar (eds.). Forecasting in the presence of structural breaks and model uncertainty. Bingley, UK: Emerald Group.Banbura M., Giannone D., Lenza M. (2015). Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections. International Journal of Forecasting, Vol. 31, No. 3, pp. 739-756.Barhoumi K., Darne O., Ferrara L. (2013). Dynamic factor models: A review of the literature. OECD Journal: Journal of Business Cycle Measurement and Analysis, Vol. 2013, No. 2, pp. 73-107.Banerjee A., Marcellino M., Masten I. (2008). Forecasting macroeconomic variables using diffusion indexes in short samples with structural change. In: D. Rapach, M. Wohar (eds.). Forecasting in the presence of structural breaks and model uncertainty. Bingley, UK: Emerald Group.Baumeister C., Liu P., Mumtaz H. (2010). Changes in the transmission of monetary policy: Evidence from a time-varying factor-augmented VAR. Bank of England Working Papers, No. 401.Barhoumi K., Darne O., Ferrara L. (2013). Dynamic factor models: A review of the literature. OECD Journal: Journal of Business Cycle Measurement and Analysis, Vol. 2013, No. 2, pp. 73-107.Bernanke B. S., Boivin J., Eliasz P. (2005). Measuring the effects of monetary policy: A factor-augmented vector autoregressive (FAVAR) approach. Quarterly Journal of Economics, Vol. 120, No. 1, pp. 387-422.Baumeister C., Liu P., Mumtaz H. (2010). Changes in the transmission of monetary policy: Evidence from a time-varying factor-augmented VAR. Bank of England Working Papers, No. 401.Blake A., Mumtaz H. (2012). Applied Bayesian econometrics for central bankers. CCBS Technical Handbook, No. 4. London: Centre for Central Banking Studies, Bank of England.Bernanke B. S., Boivin J., Eliasz P. (2005). Measuring the effects of monetary policy: A factor-augmented vector autoregressive (FAVAR) approach. Quarterly Journal of Economics, Vol. 120, No. 1, pp. 387-422.Box G. E. P., Jenkins G. M. (1970). Time series analysis, forecasting and control. San Francisco, CA: Holden-Day.Blake A., Mumtaz H. (2012). Applied Bayesian econometrics for central bankers. CCBS Technical Handbook, No. 4. London: Centre for Central Banking Studies, Bank of England.Brayton F., Tinsley P. (eds.) (1996). A guide to FRB/US. A macroeconomic model of the United States. Federal Reserve Board. Washington, DC.Box G. E. P., Jenkins G. M. (1970). Time series analysis, forecasting and control. San Francisco, CA: Holden-Day.Brayton F., Levin A., Lyon R., Williams J. C. (1997). The evolution of macro models at the Federal Reserve Board. Carnegie-Rochester Conference Series on Public Policy, No. 47, pp. 43-81.Brayton F., Tinsley P. (eds.) (1996). A guide to FRB/US. A macroeconomic model of the United States. Federal Reserve Board. Washington, DC.Brillinger D. R. (1981). Time series: Data analysis and theory. San Francisco, CA: Holden-Day.Brayton F., Levin A., Lyon R., Williams J. C. (1997). The evolution of macro models at the Federal Reserve Board. Carnegie-Rochester Conference Series on Public Policy, No. 47, pp. 43-81.Chamberlain G., Rothschild M. (1983). Arbitrage, factor structure and mean-variance analysis in large asset markets. Econometrica, Vol. 51, No. 5, pp. 1305-1324.Brillinger D. R. (1981). Time series: Data analysis and theory. San Francisco, CA: Holden-Day.Chari V. V., Kehoe P. J., McGrattan E. R. (2009). New Keynesian models: Not yet useful for policy analysis. American Economic Journal: Macroeconomics, Vol. 1, No. 1, pp. 242-266.Chamberlain G., Rothschild M. (1983). Arbitrage, factor structure and mean-variance analysis in large asset markets. Econometrica, Vol. 51, No. 5, pp. 1305-1324.Chauvet M., Potter S. (2013). Forecasting output. In: A. Timmermann, G. Elliott (eds.). Handbook of Economic Forecasting, Vol. 2A. Amsterdam: Elsevier, pp. 141-194.Chari V. V., Kehoe P. J., McGrattan E. R. (2009). New Keynesian models: Not yet useful for policy analysis. American Economic Journal: Macroeconomics, Vol. 1, No. 1, pp. 242-266.Christiano L., Eichenbaum M., Evans C. (2005). Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy, Vol. 113, No. 1, pp. 1-45.Chauvet M., Potter S. (2013). Forecasting output. In: A. Timmermann, G. Elliott (eds.). Handbook of Economic Forecasting, Vol. 2A. Amsterdam: Elsevier, pp. 141-194.De Vroey M., Malgrange P. (2010). From the Keynesian revolution to the Klein-Goldberger model: Klein and the dynamization of Keynesian theory (Discussion paper No. 2010019). Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).Christiano L., Eichenbaum M., Evans C. (2005). Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy, Vol. 113, No. 1, pp. 1-45.De Vroey M., Malgrange P. (2011). The history of macroeconomics from Keynes’s general theory to the present (Discussion paper No. 2011028). Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).De Vroey M., Malgrange P. (2010). From the Keynesian revolution to the Klein-Goldberger model: Klein and the dynamization of Keynesian theory (Discussion paper No. 2010019). Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).Del Negro M., Otrok C. (2008). Dynamic factor models with time-varying parameters: Measuring changes in international business cycles (Staff Report No. 326). Federal Reserve Bank of New York.De Vroey M., Malgrange P. (2011). The history of macroeconomics from Keynes’s general theory to the present (Discussion paper No. 2011028). Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).Del Negro M., Schorfheide F., Smets F., Wouters R. (2007). On the fit of new-Keynesian models. Journal of Business & Economics Statistics, Vol. 25, No. 2, pp. 123-149.Del Negro M., Otrok C. (2008). Dynamic factor models with time-varying parameters: Measuring changes in international business cycles (Staff Report No. 326). Federal Reserve Bank of New York.Demeshev B., Malakhovskaya O. (2015). Forecasting Russian macroeconomic indicators with BVAR (Working paper No. 105). Moscow: HSE.Del Negro M., Schorfheide F., Smets F., Wouters R. (2007). On the fit of new-Keynesian models. Journal of Business & Economics Statistics, Vol. 25, No. 2, pp. 123-149.Del Negro M., Otrok C. (2008). Dynamic factor models with time-varying parameters: Measuring changes in international business cycles (Staff Report No. 326). Federal Reserve Bank of New York.Demeshev B., Malakhovskaya O. (2015). Forecasting Russian macroeconomic indicators with BVAR (Working paper No. 105). Moscow: HSE.Del Negro M., Schorfheide F., Smets F., Wouters R. (2007). On the fit of new-Keynesian models. Journal of Business & Economics Statistics, Vol. 25, No. 2, pp. 123-149.Del Negro M., Otrok C. (2008). Dynamic factor models with time-varying parameters: Measuring changes in international business cycles (Staff Report No. 326). Federal Reserve Bank of New York.Demeshev B., Malakhovskaya O. (2015). Forecasting Russian macroeconomic indicators with BVAR (Working paper No. 105). Moscow: HSE.Del Negro M., Schorfheide F., Smets F., Wouters R. (2007). On the fit of new-Keynesian models. Journal of Business & Economics Statistics, Vol. 25, No. 2, pp. 123-149.Diamond P. (1982). Aggregate demand management in search equilibrium. Journal of Political Economy, Vol. 90, No. 5, pp. 881-894.Demeshev B., Malakhovskaya O. (2015). Forecasting Russian macroeconomic indicators with BVAR (Working paper No. 105). Moscow: HSE.Diebold F. X. (1998). The past, present, and future of macroeconomic forecasting. Journal of Economic Perspectives, Vol. 12, No. 2, pp. 175-192.Diamond P. (1982). Aggregate demand management in search equilibrium. Journal of Political Economy, Vol. 90, No. 5, pp. 881-894.Diebold F. X., Rudebusch G. D. (1996). Measuring business cycles: A modern perspective. The Review of Economics and Statistics, Vol. 78, No. 1, pp. 67-77.Diebold F. X. (1998). The past, present, and future of macroeconomic forecasting. Journal of Economic Perspectives, Vol. 12, No. 2, pp. 175-192.Doan T., Litterman R., Sims C. A. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, Vol. 3, No. 1, pp. 1-100.Diebold F. X., Rudebusch G. D. (1996). Measuring business cycles: A modern perspective. The Review of Economics and Statistics, Vol. 78, No. 1, pp. 67-77.Doz C., Giannone D., Reichlin L. (2011). A two-step estimator for large approximate dynamic factor models based on Kalman filtering. Journal of Econometrics, Vol. 164, No. 1, pp. 188-205.Doan T., Litterman R., Sims C. A. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, Vol. 3, No. 1, pp. 1-100.Edge R. M., Kiley M. T., Laforte J. P. (2010). A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model. Journal of Applied Econometrics, Vol. 25, No. 4, pp. 720-754.Doz C., Giannone D., Reichlin L. (2011). A two-step estimator for large approximate dynamic factor models based on Kalman filtering. Journal of Econometrics, Vol. 164, No. 1, pp. 188-205.Eickmeier S., Lemke W., Marcellino M. (2011). Classical time-varying FAVAR models - Estimation, forecasting and structural analysis. CEPR Discussion Papers, No. 8321.Edge R. M., Kiley M. T., Laforte J. P. (2010). A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model. Journal of Applied Econometrics, Vol. 25, No. 4, pp. 720-754.Engle R. F., Granger C. W. J. (1987). Cointegration and error correction: Representation, estimation and testing. Econometrica, Vol. 55, No. 2, pp. 251-276.Eickmeier S., Lemke W., Marcellino M. (2011). Classical time-varying FAVAR models - Estimation, forecasting and structural analysis. CEPR Discussion Papers, No. 8321.Fernández-Villaverde J. (2008). Horizons of understanding: A review of Ray Fair’s estimating how the macroeconomy works. Journal of Economic Literature, Vol. 46, No. 3, pp. 685-703.Engle R. F., Granger C. W. J. (1987). Cointegration and error correction: Representation, estimation and testing. Econometrica, Vol. 55, No. 2, pp. 251-276.Forni M., Hallin M., Lippi M., Reichlin L. (2000). The generalized dynamic-factor model: Identification and estimation. Review of Economics and Statistics, Vol. 82, No. 4, pp. 540-554.Fernández-Villaverde J. (2008). Horizons of understanding: A review of Ray Fair’s estimating how the macroeconomy works. Journal of Economic Literature, Vol. 46, No. 3, pp. 685-703.Friedman M. (1968). The role of monetary policy. American Economic Review, Vol. 58, No. 1, pp. 1-17.Forni M., Hallin M., Lippi M., Reichlin L. (2000). The generalized dynamic-factor model: Identification and estimation. Review of Economics and Statistics, Vol. 82, No. 4, pp. 540-554.Geweke J. (1977). The dynamic factor analysis of economic time series. In: D. J. Aigner, A. S. Goldberger (eds.). Latent variables in socio-economic models. Amsterdam: North-Holland.Friedman M. (1968). The role of monetary policy. American Economic Review, Vol. 58, No. 1, pp. 1-17.Geweke J., Whiteman C. (2006). Bayesian forecasting. In: G. Elliott, C. W. J. Granger, A. Timmermann (eds.). Handbook of economic forecasting, Vol. 1. Amsterdam: Elsevier, pp. 3-80.Geweke J. (1977). The dynamic factor analysis of economic time series. In: D. J. Aigner, A. S. Goldberger (eds.). Latent variables in socio-economic models. Amsterdam: North-Holland.Ghysels E., Sinko A., Valkanov R. (2006). MIDAS regressions: Further results and new directions. Econometric Reviews, Vol. 26, No. 1, pp. 53-90.Geweke J., Whiteman C. (2006). Bayesian forecasting. In: G. Elliott, C. W. J. Granger, A. Timmermann (eds.). Handbook of economic forecasting, Vol. 1. Amsterdam: Elsevier, pp. 3-80.Giacomini R. (2015). Economic theory and forecasting: Lessons from the literature. Econometrics Journal, Vol. 18, No. 2, pp. C22-C41.Ghysels E., Sinko A., Valkanov R. (2006). MIDAS regressions: Further results and new directions. Econometric Reviews, Vol. 26, No. 1, pp. 53-90.Giannone D., Lenza M., Primiceri G. E. (2015). Prior selection for vector autoregressions. The Review of Economics and Statistics, Vol. 97, No. 2, pp. 436-451.Giacomini R. (2015). Economic theory and forecasting: Lessons from the literature. Econometrics Journal, Vol. 18, No. 2, pp. C22-C41.Goodfriend M., King R. (1997). The new neo-classical synthesis and the role of monetary policy. NBER Macroeconomics Annual, pp. 231-283.Giannone D., Lenza M., Primiceri G. E. (2015). Prior selection for vector autoregressions. The Review of Economics and Statistics, Vol. 97, No. 2, pp. 436-451.Granger C. W. J. (1969). Investigating causal relations by econometric models and cross- spectral methods. Econometrica, Vol. 37, No. 3, pp. 424-438.Goodfriend M., King R. (1997). The new neo-classical synthesis and the role of monetary policy. NBER Macroeconomics Annual, pp. 231-283.Granger C. W. J. (1981). Some properties of time series data and their use in econometric model specification. Journal of Econometrics, Vol. 16, No. 1, pp. 121-130.Granger C. W. J. (1969). Investigating causal relations by econometric models and cross- spectral methods. Econometrica, Vol. 37, No. 3, pp. 424-438.Griliches Z. (1968). The Brookings model volume: A review article. Review of Economics and Statistics, Vol. 50, No. 2, pp. 215-234.Granger C. W. J. (1981). Some properties of time series data and their use in econometric model specification. Journal of Econometrics, Vol. 16, No. 1, pp. 121-130.Hamilton J. D. (1989). A new approach to the economic analysis of nonstationary time-series and the business cycle. Econometrica, Vol. 57, No. 2, pp. 357-384.Griliches Z. (1968). The Brookings model volume: A review article. Review of Economics and Statistics, Vol. 50, No. 2, pp. 215-234.Hamilton J. D. (1994). Time series analysis. Princeton, NJ: Princeton University Press.Hamilton J. D. (1989). A new approach to the economic analysis of nonstationary time-series and the business cycle. Econometrica, Vol. 57, No. 2, pp. 357-384.Hicks J. R. (1937). Mr. Keynes and the classics. Econometrica, Vol. 5, No. 2, pp. 147-159.Hamilton J. D. (1994). Time series analysis. Princeton, NJ: Princeton University Press.Kadiyala K. R., Karlsson S. (1993). Forecasting with generalized Bayesian vector autoregressions. Journal of Forecasting, Vol. 12, No. 3-4, pp. 365-378.Hicks J. R. (1937). Mr. Keynes and the classics. Econometrica, Vol. 5, No. 2, pp. 147-159.Kadiyala K. R., Karlsson S. (1997). Numerical methods for estimation and inference in Bayesian VAR models. Journal of Applied Econometrics, Vol. 12, No. 2, pp. 99-132.Kadiyala K. R., Karlsson S. (1993). Forecasting with generalized Bayesian vector autoregressions. Journal of Forecasting, Vol. 12, No. 3-4, pp. 365-378.Keynes J. M. (1936). The general theory of employment, interest, and money. London: Macmillan.Kadiyala K. R., Karlsson S. (1997). Numerical methods for estimation and inference in Bayesian VAR models. Journal of Applied Econometrics, Vol. 12, No. 2, pp. 99-132.Klein L. R. (1950). Economic fluctuations in the United States, 1921-1941. N. Y.: John Wiley.Keynes J. M. (1936). The general theory of employment, interest, and money. London: Macmillan.Klein L. R., Goldberger A. S. (1955). An econometric model of the United States, 1929-52. Amsterdam: North-Holland.Klein L. R. (1950). Economic fluctuations in the United States, 1921-1941. N. Y.: John Wiley.Knoop T. (2009). Recessions and depressions: Understanding business cycles. 2nd ed. Westport, CT: Praeger.Klein L. R., Goldberger A. S. (1955). An econometric model of the United States, 1929-52. Amsterdam: North-Holland.Krolzig H. (1997). Markov-switching vector autoregressions: Modelling, statistical inference, and application to business cycle analysis. Berlin: Springer.Knoop T. (2009). Recessions and depressions: Understanding business cycles. 2nd ed. Westport, CT: Praeger.Kydland F., Prescott E. (1977). Rules rather than discretion: The inconsistency of optimal plans. Journal of Political Economy, Vol. 85, No. 3, pp. 473-491.Krolzig H. (1997). Markov-switching vector autoregressions: Modelling, statistical inference, and application to business cycle analysis. Berlin: Springer.Kydland F., Prescott E. (1982). Time to build and aggregate fluctuations. Econometrica, Vol. 50, No. 6, pp. 1345-1370.Kydland F., Prescott E. (1977). Rules rather than discretion: The inconsistency of optimal plans. Journal of Political Economy, Vol. 85, No. 3, pp. 473-491.Lawley D. N., Maxwell A. E. (1971). Factor analysis in a statistical method. London: Butterworth.Kydland F., Prescott E. (1982). Time to build and aggregate fluctuations. Econometrica, Vol. 50, No. 6, pp. 1345-1370.Litterman R. B. (1979). Techniques of forecasting using vector autoregressions. (Working Paper, No. 115). Federal Reserve Bank of Minneapolis.Lawley D. N., Maxwell A. E. (1971). Factor analysis in a statistical method. London: Butterworth.Litterman R. B. (1986). Forecasting with Bayesian vector autoregressions - 5 years of experience. Journal of Business and Economic Statistics, Vol. 4, No. 1, pp. 25-38.Litterman R. B. (1979). Techniques of forecasting using vector autoregressions. (Working Paper, No. 115). Federal Reserve Bank of Minneapolis.Lucas R. E. (1972). Expectations and the neutrality of money. Journal of Economic Theory, Vol. 4, No. 2, pp. 103-124.Litterman R. B. (1986). Forecasting with Bayesian vector autoregressions - 5 years of experience. Journal of Business and Economic Statistics, Vol. 4, No. 1, pp. 25-38.Lucas R. E. (1976). Econometric policy evaluation: A critique. In: K. Brunner, A. Meltzer (eds.). The Phillips curve and the labor market. Carnegie-Rochester Conference Series on Public Policy, Vol. 1. Amsterdam: North-Holland, pp. 19-46.Lucas R. E. (1972). Expectations and the neutrality of money. Journal of Economic Theory, Vol. 4, No. 2, pp. 103-124.Lutkepohl H. (2005). New introduction to multiple time series analysis. Berlin: Springer.Lucas R. E. (1976). Econometric policy evaluation: A critique. In: K. Brunner, A. Meltzer (eds.). The Phillips curve and the labor market. Carnegie-Rochester Conference Series on Public Policy, Vol. 1. Amsterdam: North-Holland, pp. 19-46.Mankiw N. (1985). Small menu costs and large business cycles: A macroeconomic modeling of monopoly. Quarterly Journal of Economics, Vol. 100, No. 2, pp. 529-538.Lutkepohl H. (2005). New introduction to multiple time series analysis. Berlin: Springer.Mariano R. S., Murasawa Y. (2003). A new coincident index of business cycles based on monthly and quarterly series. Journal of Applied Econometrics, Vol. 18, No. 4, pp. 427-443.Mankiw N. (1985). Small menu costs and large business cycles: A macroeconomic modeling of monopoly. Quarterly Journal of Economics, Vol. 100, No. 2, pp. 529-538.Nelson C. R. (1972). The prediction performance of the FRB-MIT-PENN model of the US economy. American Economic Review, Vol. 62, No. 5, pp. 902-917.Mariano R. S., Murasawa Y. (2003). A new coincident index of business cycles based on monthly and quarterly series. Journal of Applied Econometrics, Vol. 18, No. 4, pp. 427-443.Nelson C. R., Plosser C. I. (1982). Trends and random walks in macroeconomic time series: Some evidence and implications. Journal of Monetary Economics, Vol. 10, No. 2, pp. 139-162.Nelson C. R. (1972). The prediction performance of the FRB-MIT-PENN model of the US economy. American Economic Review, Vol. 62, No. 5, pp. 902-917.Phelps E., Taylor J. (1977). Stabilizing powers of monetary policy under rational expectations. Journal of Political Economy, Vol. 85, No. 1, pp. 163-190.Nelson C. R., Plosser C. I. (1982). Trends and random walks in macroeconomic time series: Some evidence and implications. Journal of Monetary Economics, Vol. 10, No. 2, pp. 139-162.Phillips W. (1958). The relationship between unemployment and the rate of change of money wages in the United Kingdom, 1861-1957. Economica, Vol. 25, No. 100, pp. 283-299.Phelps E., Taylor J. (1977). Stabilizing powers of monetary policy under rational expectations. Journal of Political Economy, Vol. 85, No. 1, pp. 163-190.Qin D. (2011). Rise of VAR modelling approach. Journal of Economic Surveys, Vol. 25, No. 1, pp. 156-174.Phillips W. (1958). The relationship between unemployment and the rate of change of money wages in the United Kingdom, 1861-1957. Economica, Vol. 25, No. 100, pp. 283-299.Ramey V. (2016). Macroeconomic shocks and their propagation. NBER Working Papers, No. 21978.Qin D. (2011). Rise of VAR modelling approach. Journal of Economic Surveys, Vol. 25, No. 1, pp. 156-174.Rotemberg J., Woodford M. (1997). An optimization-based econometric framework for the evaluation of monetary policy. In: B. S. Bernanke, J. Rotemberg (eds.). NBER Macroeconomics Annual 1997. Cambridge, MA: MIT Press, pp. 297-346.Ramey V. (2016). Macroeconomic shocks and their propagation. NBER Working Papers, No. 21978.Sargent T. J., Sims C. A. (1977). Business cycle modelling without pretending to have too much a priori economic theory. In: New methods in business cycle research: Proceedings from a conference. Minneapolis, MN: Federal Reserve Bank of Minneapolis, pp. 45-109.Rotemberg J., Woodford M. (1997). An optimization-based econometric framework for the evaluation of monetary policy. In: B. S. Bernanke, J. Rotemberg (eds.). NBER Macroeconomics Annual 1997. Cambridge, MA: MIT Press, pp. 297-346.Sсhorfheide F. (2011). Estimation and evaluation of DSGE models: Progress and challenges (Working paper, No. 11-7). Federal Reserve Bank of Philadelphia.Sargent T. J., Sims C. A. (1977). Business cycle modelling without pretending to have too much a priori economic theory. In: New methods in business cycle research: Proceedings from a conference. Minneapolis, MN: Federal Reserve Bank of Minneapolis, pp. 45-109.Shapiro C., Stiglitz J. E. (1984). Equilibrium unemployment as worker discipline device. American Economic Review, Vol. 74, No. 3, pp. 433-444.Sсhorfheide F. (2011). Estimation and evaluation of DSGE models: Progress and challenges (Working paper, No. 11-7). Federal Reserve Bank of Philadelphia.Sims C. A. (1980). Macroeconomics and reality. Econometrica, Vol. 48 , No. 1, pp. 1-48.Shapiro C., Stiglitz J. E. (1984). Equilibrium unemployment as worker discipline device. American Economic Review, Vol. 74, No. 3, pp. 433-444.Sims C. A. (1981). An autoregressive index model for the U.S. 1948-1975. In: J. Kmenta, J. B. Ramsey (eds.). Large-scale macro-econometric models. Amsterdam: North-Holland, pp. 283-327.Sims C. A. (1980). Macroeconomics and reality. Econometrica, Vol. 48 , No. 1, pp. 1-48.Smets F., Wouters R. (2003). An estimated dynamic stochastic general equilibrium of the Euro Area. Journal of the European Economic Association, Vol. 1, No. 5, pp. 1123-1175.Sims C. A. (1981). An autoregressive index model for the U.S. 1948-1975. In: J. Kmenta, J. B. Ramsey (eds.). Large-scale macro-econometric models. Amsterdam: North-Holland, pp. 283-327.Smets F., Wouters R. (2007). Shocks and frictions in US business cycles: A Bayesian DSGE approach. American Economic Review, Vol. 97, No. 3, pp. 586-606.Smets F., Wouters R. (2003). An estimated dynamic stochastic general equilibrium of the Euro Area. Journal of the European Economic Association, Vol. 1, No. 5, pp. 1123-1175.Stock J. H., Watson M. W. (2002). Macroeconomic forecasting using diffusion indexes. Journal of Business and Economic Statistics, Vol. 20, No. 2, pp. 147-162.Smets F., Wouters R. (2007). Shocks and frictions in US business cycles: A Bayesian DSGE approach. American Economic Review, Vol. 97, No. 3, pp. 586-606.Stock J. H., Watson M. W. (2016). Factor models and structural vector autoregressions in macroeconomics. In: J. B. Taylor, H. Uhlig (eds.). Handbook of Macroeconomics, Vol. 2 (forthcoming).Stock J. H., Watson M. W. (2002). Macroeconomic forecasting using diffusion indexes. Journal of Business and Economic Statistics, Vol. 20, No. 2, pp. 147-162.Tinbergen J. (1939). Statistical testing of business-cycle theories. Business cycles in the United States of America, 1919-1932. Vol. 2. Geneva: League of Nations.Stock J. H., Watson M. W. (2016). Factor models and structural vector autoregressions in macroeconomics. In: J. B. Taylor, H. Uhlig (eds.). Handbook of Macroeconomics, Vol. 2 (forthcoming).Tovar C. E. (2009). DSGE models and central banks. Economics: The Open-Access, Open-Assessment E-Journal, Vol. 3, pp. 1-31.Tinbergen J. (1939). Statistical testing of business-cycle theories. Business cycles in the United States of America, 1919-1932. Vol. 2. Geneva: League of Nations.Uhlig H. (2005). What are the effects of monetary policy on output? Results from an agnostic identification procedure. Journal of Monetary Economics, Vol. 52, No. 2, pp. 381-419.Tovar C. E. (2009). DSGE models and central banks. Economics: The Open-Access, Open-Assessment E-Journal, Vol. 3, pp. 1-31.Wang M. C. (2009). Comparing the DSGE model with the factor model: An out-of- sample forecasting experiment. Journal of Forecasting, Vol. 28, No. 2, pp. 167-182.Uhlig H. (2005). What are the effects of monetary policy on output? Results from an agnostic identification procedure. Journal of Monetary Economics, Vol. 52, No. 2, pp. 381-419.Wolters M. H. (2015). Evaluating point and density forecasts of DSGE models. Journal of Applied Econometrics, Vol. 30, No. 1, pp. 74-96.Wang M. C. (2009). Comparing the DSGE model with the factor model: An out-of- sample forecasting experiment. Journal of Forecasting, Vol. 28, No. 2, pp. 167-182.Woodford M. (2009). Convergence in macroeconomics: Elements of the new synthesis. American Economic Journal: Macroeconomics, Vol. 1, No. 1, pp. 267-279.Wolters M. H. (2015). Evaluating point and density forecasts of DSGE models. Journal of Applied Econometrics, Vol. 30, No. 1, pp. 74-96.Zellner A. (1971). An introduction to Bayesian inference in econometrics. New York: Wiley.Woodford M. (2009). Convergence in macroeconomics: Elements of the new synthesis. American Economic Journal: Macroeconomics, Vol. 1, No. 1, pp. 267-279.Woodford M. (2009). Convergence in macroeconomics: Elements of the new synthesis. American Economic Journal: Macroeconomics, Vol. 1, No. 1, pp. 267-279.Zellner A. (1971). An introduction to Bayesian inference in econometrics. New York: Wiley.Zellner A. (1971). An introduction to Bayesian inference in econometrics. New York: Wiley.

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