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Citations for "Macroeconomic forecasting and structural change"

by Antonello D'Agostino & Luca Gambetti & Domenico Giannone

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  1. 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.
  2. Korobilis, Dimitris, 2014. "Data-based priors for vector autoregressions with drifting coefficients," MPRA Paper 53772, University Library of Munich, Germany.
  3. Ascari, Guido & Castelnuovo, Efrem & Rossi, Lorenza, 2011. "Calvo vs. Rotemberg in a trend inflation world: An empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 35(11), pages 1852-1867.
  4. Chan, Joshua C C & Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W, 2010. "Time Varying Dimension Models," SIRE Discussion Papers 2012-33, Scottish Institute for Research in Economics (SIRE).
  5. 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.
  6. 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.
  7. Bauwens, Luc & Korobilis, Dimitris & Koop, Gary & Rombouts, Jeroen V.K., 2011. "A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models," SIRE Discussion Papers 2011-25, Scottish Institute for Research in Economics (SIRE).
  8. Dimitris Korobilis, 2013. "Var Forecasting Using Bayesian Variable Selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 204-230, 03.
  9. 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.
  10. Petrella, Ivan & Delle Monache, Davide, 2016. "Adaptive models and heavy tails," Bank of England working papers 577, Bank of England.
  11. Raffaella Giacomini & Barbara Rossi, 2015. "Forecasting in Nonstationary Environments: What Works and What Doesn’t in Reduced-Form and Structural Models," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 207-229, 08.
  12. Gary Koop & Dimitris Korobilis, 2012. "Large Time-Varying Parameter VARs," Working Paper Series 11_12, The Rimini Centre for Economic Analysis.
  13. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, Elsevier.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. Carriero, Andrea & Clark, Todd & Marcellino, Massimiliano, 2013. "Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility," CEPR Discussion Papers 9312, C.E.P.R. Discussion Papers.
  21. Nikolay Hristov & Oliver Hülsewig & Thomas Siemsen & Timo Wollmershäuser, 2014. "Smells Like Fiscal Policy? Assessing the Potential Effectiveness of the ECB's OMT Program," CESifo Working Paper Series 4628, CESifo Group Munich.
  22. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Parallel Sequential Monte Carlo for Efficient Density Combination: The DeCo Matlab Toolbox," Working Papers 2013:08, Department of Economics, University of Venice "Ca' Foscari".
  23. Bekiros, Stelios & Gupta, Rangan & Paccagnini, Alessia, 2015. "Oil price forecastability and economic uncertainty," Economics Letters, Elsevier, vol. 132(C), pages 125-128.
  24. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.
  25. Colin Bermingham & Antonello D’Agostino, 2014. "Understanding and forecasting aggregate and disaggregate price dynamics," Empirical Economics, Springer, vol. 46(2), pages 765-788, March.
  26. 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.
  27. 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.
  28. Jouchi Nakajima & Munehisa Kasuya & Toshiaki Watanabe, 2009. "Bayesian Analysis of Time-Varying Parameter Vector Autoregressive Model for the Japanese Economy and Monetary Policy," IMES Discussion Paper Series 09-E-13, Institute for Monetary and Economic Studies, Bank of Japan.
  29. Baxa, Jaromír & Plašil, Miroslav & Vašíček, Bořek, 2015. "Changes in inflation dynamics under inflation targeting? Evidence from Central European countries," Economic Modelling, Elsevier, vol. 44(C), pages 116-130.
  30. 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.
  31. 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.
  32. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
  33. 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.
  34. 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.
  35. Neil Shephard, 2013. "Martingale unobserved component models," Economics Papers 2013-W01, Economics Group, Nuffield College, University of Oxford.
  36. 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.
  37. Kirchner, Markus & Cimadomo, Jacopo & Hauptmeier, Sebastian, 2010. "Transmission of government spending shocks in the euro area: Time variation and driving forces," Working Paper Series 1219, European Central Bank.
  38. 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.
  39. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working papers 2012-38, University of Connecticut, Department of Economics, revised Dec 2013.
  40. 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.
  41. 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.
  42. 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.
  43. D’Agostino, Antonello & Ehrmann, Michael, 2014. "The pricing of G7 sovereign bond spreads – The times, they are a-changin," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 155-176.
  44. 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.
  45. Baumeister, Christiane & Kilian, Lutz, 2012. "What Central Bankers Need to Know about Forecasting Oil Prices," CEPR Discussion Papers 9118, C.E.P.R. Discussion Papers.
  46. 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.
  47. 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.
  48. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2013. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 240-251, April.
  49. 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.
  50. Miguel Belmonte & Gary Koop, 2013. "Model Switching and Model Averaging in Time-Varying Parameter Regression Models," Working Papers 1302, University of Strathclyde Business School, Department of Economics.
  51. Gary Koop & Dimitris Korobilis, . "A new index of financial conditions," Working Papers 2013_06, Business School - Economics, University of Glasgow.
  52. Tim Oliver Berg & Steffen Henzel, 2014. "Point and Density Forecasts for the Euro Area Using Bayesian VARs," CESifo Working Paper Series 4711, CESifo Group Munich.
  53. 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.
  54. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
  55. D'Agostino, Antonello & Mendicino, Caterina, 2015. "Expectation-driven cycles: time-varying effects," Working Paper Series 1776, European Central 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. 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.
  58. 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.
  59. 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.
  60. D'Agostino, Antonello & Mendicino, Caterina, 2014. "Expectation-Driven Cycles: Time-varying Effects," MPRA Paper 53607, University Library of Munich, Germany.
  61. 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.
  62. D'Agostino, Antonello & Surico, Paolo, 2011. "A Century of Inflation Forecasts," CEPR Discussion Papers 8292, C.E.P.R. Discussion Papers.
  63. Gambetti, Luca & Musso, Alberto, 2012. "Loan supply shocks and the business cycle," Working Paper Series 1469, European Central Bank.
  64. 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.).
  65. Nicoletti, Giulio & Passaro, Raffaele, 2012. "Sometimes it helps: the evolving predictive power of spreads on GDP dynamics," Working Paper Series 1447, European Central Bank.
  66. 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.
  67. 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.
  68. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270, CPB Netherlands Bureau for Economic Policy Analysis.
  69. 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.
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