Литература

Литература

Литература к разделу 1

Андерсон Т. (1976). Статистический анализ временных рядов. М.: Мир.

Бокс Дж., Дженкинс Г. (1974). Анализ временных рядов. Прогноз и управление. М.: Мир. Вып. 1, 2. (Русский перевод издания: Box G.E.P., Jenkins G.M. (1970) Time series analysis: Forecasting and control, San Francisco: Holden-Day.)

Носко В.П., Бузаев A.B., Кадочников П.А., Пономаренко С.С. (2003). Анализ прогнозных свойств структурных моделей и моделей с включением результатов опросов предприятий, сравнение с прогнозами по моделям временных рядов. Научные труды № 64. М.: ИЭПП.

Энтов P.M., Носко В.П., Юдин А.Д., Кадочников П.А., Пономаренко С.С. (2002). Проблемы прогнозирования некоторых макроэкономических показателей. М.: ИЭПП.

Box G.E.P., Jenkins G.M., Reinsel G.C. (2008). Time Series Analysis: Forecasting and Control. 4th Edition. Wiley.

Beveridge S., Nelson C. (1981). A new approach to decomposition of economic times series into permanent and transitory components with particular attention to the measurement of the business cycle // Journal of Monetary Economics. Vol. 7. P. 151 —174.

Campbell J. J., Perron P. (1991). Pitfalls and Opportunities: What Macroeconomists should know about Unit Roots // Macroeconomics Annual. 1991. NBER. P. 141—201.

Clements M.P., Hendry D.F. (1996). Multi-step estimation for forecasting // Oxford Bulletin of Economics and Statistics. Vol. 58. № 4. P. 657—684.

Clements Michael P., Hendry D.F. (1998a). Forecasting Economic Processes // International Journal of Forecasting. Vol. 14. № 1. P. Ill —131.

Clements M.P., Hendry D.F. (1998b). Forecasting Economic Time Series. Cambridge: Cambridge University Press. (The Marshall Lectures on Economic Forecasting.)

Clements M.P., Hendry D.F. (2000). Forecasting with difference-stationary and trend-stationary models. Discussion Paper Series, Number 5. Department of Economics, University of Oxford.

Clements M.P., Hendry D.F. (2001). Forecasting Non-stationary Economic Time Series. Cambridge, Massachusetts: The MIT Press.

Dickey D.A., Bell W.R., Miller R.B. (1986). Unit Roots in Time Series Models: Tests and Implications // American Statistica. Vol. 40. P. 12—26.

Diebold F.X. (1998). The Past, Present and Future of Macroeconomic Forecasting // Journal of Economic Perspectives. Vol. 12. № 2. P. 175—192.

Diebold F.X., Kilian L. (2000). Unit-Root Tests Are Useful for Selecting Forecasting Models // Journal of Business and Economic Statistics. Vol. 18. № 3. P. 265—273.

Diebold F.X., Mariano R.S. (1995). Comparing Predictive Accuracy // Journal of Business & Economic Statistics. Vol. 13. № 3. P. 253—63.

Enders W. (1995). Applied Econometric Time Series. New York: Wiley.

Granger C.W.J., Newbold P. (1986). Forecasting Economic Time Series. Second Edition. New York: Academic Press.

Gregory A.W., Smith G.W., Yetman J. (2001). Testing for Forecast Consensus // Journal of Business and Economic Statistics. Vol. 19. № 1. P. 34—43.

Hamilton J.D. (1994). Time Series Analysis. Princeton. Princeton University Press.

Harvey D.I., Leybourne S.J., Newbold P. (1998). Tests for Forecast Encompassing // Journal of Business and Economic Statistics. Vol. 16. № 2. P. 254.

Kumar K, Gill D.S. (2000) On Forecasting Economic Time Series Data: A Comparative Study // Indian Journal of Economics. Vol. 81. P. 265—273.

Snyder R.D., OrdJ.K, Koehler A.B. (2001) Prediction Intervals for ARIMA Models // Journal of Business and Economic Statistics. Vol. 19. № 2. P. 217—225.

Stock J.H. (1996). VAR, Error Correction and Pretest Forecasts at Long Horizons // Oxford Bulletin of Economics and Statistics. Vol. 58. № 4. P. 685—701.

Stock J.H., Watson M.W. (1996). A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series // Journal of Business and Economic Statistics. Vol. 14. № 1. P. 11—30.

Swanson NR., White H. (1997). Forecasting Economic Time Series Using Flexible versus Fixed Specification and Linear versus Nonlinear Econometric Models // International Journal of Forecasting. Vol. 13. № 4. P. 439—461.

Wallis K.F., Whitley J.D. (1991). Sources of Error in Forecasts and Expectations: UK economic models 1984-8 // Journal of Forecasting. Vol. 10. P. 231—253.

West K.D. (2001). Tests for Forecast Encompassing When Forecasts Depend on Estimated Regression // Journal of Business and Economic Statistics. Vol. 19. № 1. P. 29—33.

Литература к разделу 2

Bernanke B.S., Blinder A.S. (1992). The Federal Funds Rate and the Channels of Monetary Transmission // American Economic Review. Vol. 82. P. 901—921.

Blanchard O., Quah D. (1989). The Dynamic Effects of Aggregate Demand and Supply Disturbances // The American Economic Review. Vol. 79 (4). P. 655—673.

Campbell J.Y, Perron P. (1991). Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots // NBER Macroeconomics Annual 1991. Vol. 6 / eds. O.J. Blanchard, S. Fischer. Cambridge: MIT Press. January 1992.

Christiano L.J., Eichenbaum M., Evans C. (1998). Monetary Policy Shocks: What Have We Learned and to What End? // NBER Working Paper, 6400/1998.

Clements M.P., Hendry D.F. (1999). Forecasting Non-stationary Economic Time series // MIT Press. Cambridge; Massachusetts; London, 1999.

Diebold FX., Kilian L. (2000). Unit-root tests are useful for selecting forecasting models // Journal of Business and Economic Statistics. Vol. 18. 265—273.

Eichenbaum M. (1992). Comment on Interpreting the Macroeconomic Time Series Facts: The Effects of Monetary Policy // European Economic Review. Vol. 10. P. 1001 —1011.

Favero С A. (2001). Applied macroeconometrics // Oxford University Press. Oxford: xi + 282 pp.

9. Favero С, GiavazziF., SpaventaL. (1997). High Yelds: the Spread on German Interest Rates // Economic Journal. Vol. 107. P. 956— 986.

GaliJ. (1992). Variability of Durable and Nondurable Consumption: Evidence for Six O.E.C.D. Countries // Review of Economics & Statistics. Vol. 75 (3). P. 418—28.

Hamilton J.D. (1994). Time Series Analysis // Princeton University Press. Princeton.

Lucas R.E. Jr. (1978). Macro-economic Policy Evaluation: A Critique // Carnegi-Rochester Conference Series on Public Policy. Vol. 1. P. 19—46.

Lee J., Shin B.S., In C. (1996). Causality between Advertising and Sales: New Evidence from Cointegration // Applied Economic Letters. Vol. 3. P. 299—301.

Leeper E.M., Sims СЛ., Zha T. (1996). What Does Monetary Policy Do? // Brookings Papers on Economic Activity. 1996. Issue 2. P. 1—63.

MarcetA. (2001). Overdifferencing VAR's is Ok // Working Paper. UPF (Universitat Pompeu Fabra, Barcelona).

McCallum (1983). A Reconsideration of Sims' Evidence Regarding Monetarism // Economics Letters. Vol. 13. 167—171.

Mehra Y.P. (1978). Is Money Exogenous in Money-Demand Equations // Journal of Political Economy. Vol. 86. № 2. Part 1. P. 211—228.

Mellander E., VredinA., Warne A. (1993). Stochastic Trends and Economic Fluctuations in a Small Open Economy // Journal of Applied Econometrics. Vol. 7. Issue 4. P. 369—94.

Phillips (1995). Impulse Response and Forecast Error Variance Asymptotics in Nonsta-tionary VAR's // Cowles Foundation Discussion Paper 1102.

Shapiro M., Watson M. (1988). The sources of business cycle fluctuations: NBER Chapters // NBER Macroeconomics Annual. 1988. Vol. 3. P. 111 — 156. National Bureau of Economic Research, Inc.

Sims С (1972). Money, Income, and Causality // American Economic Review. Vol. 62. P. 540—552.

Sims С A. (1980). Comparison on Interwar and Postwar Cycles: Monetarism Revisited // American Economic Review. 1980. May. P. 250—257.

Sims С A. (1980). Macroeconomics and reality // Econometrica. Vol. 48 (1). P. 1—48.

Sims C.A. (1992). Interpreting the Macroeconomic Time Series Facts: the Effects of Monetary Policy // European Economic Review. Vol. 36. P. 975—1011.

Sims C.A., Zha T.A. (1998). Does monetary policy generate recessions? // Working Paper 98-12. Federal Reserve Bank of Atlanta.

Toda H.Y., Phillips P.C.B. (1994). Vector autoregression and causality: A theoretical overview and simulation study // Econometric Reviews. Vol. 13. P. 259—285.

Toda H.Y., Yamamoto T. (1995). Statistical inferences in vector autoregressions with possibly integrated processes // Journal of Econometrics. Vol. 66. 225—50.

Литература к разделу З

Carrion-i-Silvestre J.L., Sanso-i-Rossello A.S. (2004). Testing the Null Hypothesis of Cointegration with Structural Breaks // Unpublished Manuscript. Department d'Econometria. Estadistica і Economia Espanyola. Universitat de Barcelona.

Corradi V. (1995). Nonlinear transformations of integrated time series: a reconsideration // Journal of Time Series Analysis. Vol. 16. 1995. P. 539—549.

Engle R.F., Granger C.W.J. (1987). Co-integration and Error Correction: Representation, Estimation and Testing // Econometrica. Vol. 55. № 2. P. 251—276.

Ermini L., Granger С W.J. (1993). Some Generalizations on the Algebra of 1(1) Processes // Journal of Econometrics. Vol. 58. P. 369—384.

Granger C.W.J., Hallmann J. (1988). The algebra of 1(1) // Finance and Economics Discussion Series. Vol. 45. Board of Governors of the Federal Reserve System (U.S.).

Granger C.W.J., Hallmann J. (1991). Nonlinear transformations of integrated time series // Journal of Time Series Analysis. Vol. 12. P. 207—224.

Kramer W., Davies L. (2002). Testing for unit roots in the context of misspecified logarithmic random walks // Economics Letters. Vol. 74. P. 313—319.

Phillips P.C.B. (1987). Time Series Regression with a Unit Root // Econometrica. Vol. 55. P. 277—301.

Phillips P.C.B., Hansen B.E. (1990). Statistical Inference in Instrumental Variables Regression with 1(1) Processes // Review of Economic Studies. Vol. 57(1). P. 99—125.

Phillips P.C.B., Loretan M. (1991). Estimating long-run economic equilibria // Review of Economic Studies. Vol. 58. P. 407—436.

Saikkonen P. (1991). Asymptotically effcient estimation of cointegration regressions // Econometric Theory. Vol. 7. P. 1—21.

Stock J.H., Watson M. W. (1993). A simple estimator of cointegrating vectors in higher order integrated systems // Econometrica. Vol. 61. P. 783—820.

Литература к разделу 4

Aigner D.J., Chu S.F. (1968). On estimating the industry production function // American Economic Review. Vol. 58. P. 826—839.

Aigner D., Lovell K, Schmidt P. (1977). Formulation and Estimation of Stochastic Frontier Function Models // Journal of Econometrics. Vol. 6. P. 21—37.

Alfirman L. (2003). Estimating Stochastic Frontier Tax Potential: Can Indonesian Local Governments Increase Tax Revenues Under Decentralization? // Working Paper No. 03—19. Center for Economic Analysis, Department of Economics, University of Colorado.

Battese G.E., Coelli T.J. (1992). Frontier Production Function, technical efficiency and panel data: with application to Paddy Farmers in India // Journal of Productivity Analysis. P. 153—169.

BroeckJ. van den, Fersund F.R., Hjalmarsson L., Meeusen W. (1980). On the estimation of deterministic and stochastic frontier production functions // Journal of Econometrics. Vol. 13. P. 117—138.

Dugger R. (1974). An application of bounded nonparametric estimating functions to the analysis of bank cost and production functions. Unpublished Ph.D. dissertation (University of North Carolina. Chapel Hill, NC).

Farrell M.J. (1957). The measurement of productive efficiency // Journal of the Royal Statistical Society (Series A, general). Vol. 120. № 3. P. 253—281.

Schmidt P. (1976). On the statistical estimation of parametric frontier production functions // Review of Economics and Statistics. Vol. 58. P. 238—239.

Timmer CP. (1971). Using a probabilistic frontier production function to measure technical efficiency // Journal of Political Economy. Vol. 79. P. 776—794.

10. Головань СВ., Карминский A.M., Пересецкий A.A. (2007). Факторы, влияющие на эффективность российских банков // Модернизация экономики и государство / отв. ред. Е.Г. Ясин; Гос. ун-т — Высшая школа экономики. В 3 кн. Кн. 2. М.: Изд. дом ГУ—ВШЭ. С. 188—206.