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Citations for "Macroeconomic forecasting and structural change"

by Antonello D'Agostino & Luca Gambetti & Domenico Giannone

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  1. Joshua C.C. Chan, 2015. "The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling," CAMA Working Papers 2015-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  2. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working Papers 201230, University of Pretoria, Department of Economics.
  3. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox," CREATES Research Papers 2013-09, Department of Economics and Business Economics, Aarhus University.
  4. Neil Shephard, 2013. "Martingale unobserved component models," Economics Series Working Papers 644, University of Oxford, Department of Economics.
  5. Dimitris Korobilis, 2010. "VAR Forecasting Using Bayesian Variable Selection," Working Paper Series 51_10, The Rimini Centre for Economic Analysis, revised Apr 2011.
  6. Gary Koop & Dimitris Korobilis, . "A new index of financial conditions," Working Papers 2013_06, Business School - Economics, University of Glasgow.
  7. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.
  8. Bermingham, Colin & D’Agostino, Antonello, 2011. "Understanding and forecasting aggregate and disaggregate price dynamics," Working Paper Series 1365, European Central Bank.
  9. Bekiros, Stelios & Gupta, Rangan & Paccagnini, Alessia, 2015. "Oil price forecastability and economic uncertainty," Economics Letters, Elsevier, vol. 132(C), pages 125-128.
  10. Jaromir Baxa & Miroslav Plasil & Borek Vasicek, 2012. "Changes in Inflation Dynamics under Inflation Targeting? Evidence from Central European Countries," Working Papers 2012/04, Czech National Bank, Research Department.
  11. Li, Jiahan & Chen, Weiye, 2014. "Forecasting macroeconomic time series: LASSO-based approaches and their forecast combinations with dynamic factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 996-1015.
  12. Michele Campolieti & Deborah Gefang & Gary Koop, 2011. "Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada," Working Papers 1138, University of Strathclyde Business School, Department of Economics.
  13. Wollmershäuser, Timo & Hristov, Nikolay & Hülsewig, Oliver & Siemsen, Thomas, 2014. "Smells Like Fiscal Policy? Assessing the Potential Effectiveness of the ECB s OMT Program," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100280, Verein für Socialpolitik / German Economic Association.
  14. Miguel A.G. Belmonte & Gary Koop & Dimitris Korobilis, 2014. "Hierarchical Shrinkage in Time‐Varying Parameter Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 80-94, 01.
  15. Punzi, Maria Teresa, 2016. "Financial cycles and co-movements between the real economy, finance and asset price dynamics in large-scale crises," FinMaP-Working Papers 61, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
  16. Berg, Tim Oliver & Henzel, Steffen, 2013. "Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79783, Verein für Socialpolitik / German Economic Association.
  17. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2012. "Forecasting UK GDP growth, inflation and interest rates under structural change: a comparison of models with time-varying parameters," Bank of England working papers 450, Bank of England.
  18. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Paper 1227, Federal Reserve Bank of Cleveland.
  19. Koop, Gary & Potter, Simon M., 2011. "Time varying VARs with inequality restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 35(7), pages 1126-1138, July.
  20. Christiane Baumeister & Lutz Kilian, 2014. "What Central Bankers Need To Know About Forecasting Oil Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55, pages 869-889, 08.
  21. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland, Institute for Economies in Transition.
  22. Krueger, Fabian & Clark, Todd E. & Ravazzolo, Francesco, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Paper 1439, Federal Reserve Bank of Cleveland.
  23. Eric Eisenstat & Rodney W. Strachan, 2014. "Modelling Inflation Volatility," CAMA Working Papers 2014-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  24. Joshua Chan & Gary Koop & Roberto Leon-Gonzalez & Rodney Strachan, 2011. "Time Varying Dimension Models," Working Papers 1116, University of Strathclyde Business School, Department of Economics.
  25. Ikram Jebabli & Mohamed Arouri & Frédéric Teulon, 2014. "On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVPVAR models with stochastic volatility," Working Papers 2014-209, Department of Research, Ipag Business School.
  26. Ching-Wai Chiu & Haroon Mumtaz & Gabor Pinter, 2016. "VAR Models with Non-Gaussian Shocks," Discussion Papers 1609, Centre for Macroeconomics (CFM).
  27. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
  28. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, Elsevier.
  29. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, Elsevier.
  30. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
  31. Cimadomo, Jacopo & D'Agostino, Antonello, 2015. "Combining time-variation and mixed-frequencies: an analysis of government spending multipliers in Italy," Working Paper Series 1856, European Central Bank.
  32. D'Agostino, Antonello & Ehrmann, Michael, 2013. "The pricing of G7 sovereign bond spreads: the times, they are a-changin," Working Paper Series 1520, European Central Bank.
  33. Markus Kirchner & Jacopo Cimadomo & Sebastian Hauptmeier, 2010. "Transmission of Government Spending Shocks in the Euro Area: Time Variation and Driving Forces," Tinbergen Institute Discussion Papers 10-021/2, Tinbergen Institute.
  34. Benkovskis, Konstantins & Caivano, Michele & D’Agostino, Antonello & Dieppe, Alistair & Hurtado, Samuel & Karlsson, Tohmas & Ortega, Eva & Várnai, Tímea, 2011. "Assessing the sensitivity of inflation to economic activity," Working Paper Series 1357, European Central Bank.
  35. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  36. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270, CPB Netherlands Bureau for Economic Policy Analysis.
  37. Nakajima, Jouchi & Kasuya, Munehisa & Watanabe, Toshiaki, 2011. "Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 225-245, September.
  38. Gambetti, Luca & Musso, Alberto, 2012. "Loan supply shocks and the business cycle," Working Paper Series 1469, European Central Bank.
  39. Guido Ascari & Efrem Castelnuovo & Lorenza Rossi, 2010. "Calvo vs. Rotemberg in a Trend Inflation World: An Empirical Investigation," Quaderni di Dipartimento 108, University of Pavia, Department of Economics and Quantitative Methods.
  40. Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2016. "Dynamic Factor model with infinite dimensional factor space: forecasting," Center for Economic Research (RECent) 120, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
  41. Andrea Stella & James H. Stock, 2012. "A state-dependent model for inflation forecasting," International Finance Discussion Papers 1062, Board of Governors of the Federal Reserve System (U.S.).
  42. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2011. "A Comparison of Forecasting Procedures for Macroeconomic Series: the Contribution of Structural Break Models," Cahiers de recherche 1104, CIRPEE.
  43. repec:hhs:bofitp:2015_012 is not listed on IDEAS
  44. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Large Vector Autoregressions with Asymmetric Priors," Working Papers 759, Queen Mary University of London, School of Economics and Finance.
  45. Mirriam Chitalu Chama-Chiliba & Rangan Gupta & Nonophile Nkambule & Naomi Tlotlego, 2011. "Forecasting Key Macroeconomic Variables of the South African Economy Using Bayesian Variable Selection," Working Papers 201132, University of Pretoria, Department of Economics.
  46. D'Agostino, Antonello & Surico, Paolo, 2011. "A Century of Inflation Forecasts," CEPR Discussion Papers 8292, C.E.P.R. Discussion Papers.
  47. Carriero, Andrea & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2015. "Macroeconomic information, structural change, and the prediction of fiscal aggregates," International Journal of Forecasting, Elsevier, vol. 31(2), pages 325-348.
  48. Koop, Gary & Tole, Lise, 2013. "Modeling the relationship between European carbon permits and certified emission reductions," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 166-181.
  49. Korobilis, Dimitris, 2014. "Data-based priors for vector autoregressions with drifting coefficients," MPRA Paper 53772, University Library of Munich, Germany.
  50. Amir-Ahmadi, Pooyan & Matthes, Christian & Wang, Mu-Chun, 2015. "Measurement Errors and Monetary Policy: Then and Now," Working Paper 15-13, Federal Reserve Bank of Richmond.
  51. D'Agostino, Antonello & Mendicino, Caterina, 2015. "Expectation-driven cycles: time-varying effects," Working Paper Series 1776, European Central Bank.
  52. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.
  53. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
  54. Michael H. Breitner & Christian Dunis & Hans-Jörg Mettenheim & Christopher Neely & Georgios Sermpinis & Georgios Sermpinis & Charalampos Stasinakis & Konstantinos Theofilatos & Andreas Karathanasopoul, 2014. "Inflation and Unemployment Forecasting with Genetic Support Vector Regression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(6), pages 471-487, 09.
  55. Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2014. "Have standard VARs remained stable since the crisis?," Working Paper 2014/13, Norges Bank.
  56. Zeyyad Mandalinci, 2015. "Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models," CReMFi Discussion Papers 3, CReMFi, School of Economics and Finance, QMUL.
  57. Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2013. "Time-varying combinations of predictive densities using nonlinear filtering," Journal of Econometrics, Elsevier, vol. 177(2), pages 213-232.
  58. Eric Ghysels & Andros Kourtellos & Elena Andreou, 2012. "Should macroeconomic forecasters use daily financial data and how?," 2012 Meeting Papers 1196, Society for Economic Dynamics.
  59. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
  60. Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARs," Working Papers ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
  61. Joshua C.C. Chan, 2015. "Large Bayesian VARs: A flexible Kronecker error covariance structure," CAMA Working Papers 2015-41, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  62. repec:bof:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
  63. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2015. "Was the recent downturn in US real GDP predictable?," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2985-3007, June.
  64. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in nonstationary environments: What works and what doesn't in reduced-form and structural models," Economics Working Papers 1476, Department of Economics and Business, Universitat Pompeu Fabra.
  65. Domenico Giannone, 2010. "Comment on "Can Parameter Instability Explain the Meese-Rogoff Puzzle?"," NBER Chapters, in: NBER International Seminar on Macroeconomics 2009, pages 180-190 National Bureau of Economic Research, Inc.
  66. Fabio Busetti & Michele Caivano & Lisa Rodano, 2015. "On the conditional distribution of euro area inflation forecast," Temi di discussione (Economic working papers) 1027, Bank of Italy, Economic Research and International Relations Area.
  67. Marco Del Negro & Giorgio E. Primiceri, 2013. "Time-varying structural vector autoregressions and monetary policy: a corrigendum," Staff Reports 619, Federal Reserve Bank of New York.
  68. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," IMES Discussion Paper Series 11-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
  69. Miguel, Belmonte & Gary, Koop, 2013. "Model Switching and Model Averaging in Time- Varying Parameter Regression Models," SIRE Discussion Papers 2013-34, Scottish Institute for Research in Economics (SIRE).
  70. Andreas Karatahansopoulos & Georgios Sermpinis & Jason Laws & Christian Dunis, 2014. "Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(8), pages 596-610, December.
  71. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
  72. Nicoletti, Giulio & Passaro, Raffaele, 2012. "Sometimes it helps: the evolving predictive power of spreads on GDP dynamics," Working Paper Series 1447, European Central Bank.
  73. Joshua C.C. Chan & Eric Eisenstat, 2015. "Bayesian model comparison for time-varying parameter VARs with stochastic volatility," CAMA Working Papers 2015-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  74. Linlin Niu & Xiu Xu & Ying Chen, 2015. "An Adaptive Approach to Forecasting Three Key Macroeconomic Variables for Transitional China," SFB 649 Discussion Papers SFB649DP2015-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  75. D'Agostino, Antonello & Mendicino, Caterina, 2014. "Expectation-Driven Cycles: Time-varying Effects," MPRA Paper 53607, University Library of Munich, Germany.
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