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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 & Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2012. "Time Varying Dimension Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 358-367, January.
  2. Gary Koop & Dimitris Korobilis, . "A new index of financial conditions," Working Papers 2013_06, Business School - Economics, University of Glasgow.
  3. 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.
  4. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 1218, Federal Reserve Bank of Cleveland.
  5. Stelios Bekiros & Rangan Gupta & Alessia Paccagnini, 2015. "Oil Price Forecastability and Economic Uncertainty," Working Papers 201518, University of Pretoria, Department of Economics.
  6. 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, School of Economics and Management, University of Aarhus.
  7. 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.
  8. Jebabli, Ikram & Arouri, Mohamed & Teulon, Frédéric, 2014. "On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVP-VAR models with stochastic volatility," Energy Economics, Elsevier, vol. 45(C), pages 66-98.
  9. Dimitris Korobilis, 2013. "Var Forecasting Using Bayesian Variable Selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 204-230, 03.
  10. Joris de Wind & Luca Gambetti, 2014. "Reduced-rank time-varying vector autoregressions," CPB Discussion Paper 270, CPB Netherlands Bureau for Economic Policy Analysis.
  11. Bermingham, Colin & D’Agostino, Antonello, 2011. "Understanding and forecasting aggregate and disaggregate price dynamics," Working Paper Series 1365, European Central Bank.
  12. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
  13. Korobilis, Dimitris, 2014. "Data-based priors for vector autoregressions with drifting coefficients," MPRA Paper 53772, University Library of Munich, Germany.
  14. 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.
  15. 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.
  16. Koop, Gary & Korobilis, Dimitris, 2012. "Large time-varying parameter VARs," MPRA Paper 38591, University Library of Munich, Germany.
  17. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Birkbeck Working Papers in Economics and Finance 1409, Birkbeck, Department of Economics, Mathematics & Statistics.
  18. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
  19. 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.
  20. 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.
  21. Antonello D'Agostino & Paolo Surico, 2012. "A Century of Inflation Forecasts," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1097-1106, November.
  22. 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.
  23. Miguel, Belmonte & Gary, Koop & Dimitris, Korobilis, 2011. "Hierarchical shrinkage in time-varying parameter models," MPRA Paper 31827, University Library of Munich, Germany.
  24. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working Papers 1210, University of Nevada, Las Vegas , Department of Economics.
  25. 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.
  26. Marco Del Negro & Giorgio Primiceri, 2013. "Time-varying structural vector autoregressions and monetary policy: a corrigendum," Staff Reports 619, Federal Reserve Bank of New York.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
  33. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
  34. 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.
  35. Koop, Gary & Gefang, Deborah & Campolieti, Michele, 2012. "Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada," SIRE Discussion Papers 2012-69, Scottish Institute for Research in Economics (SIRE).
  36. Aastveit, Knut Are & Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2014. "Have Standard VARs Remained Stable since the Crisis?," Working Paper 1411, Federal Reserve Bank of Cleveland.
  37. 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).
  38. 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.
  39. 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.).
  40. Eric Eisenstat & Rodney Strachan, 2014. "Modelling Inflation Volatility," Working Paper Series 43_14, The Rimini Centre for Economic Analysis.
  41. 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.
  42. Nicoletti, Giulio & Passaro, Raffaele, 2012. "Sometimes it helps: the evolving predictive power of spreads on GDP dynamics," Working Paper Series 1447, European Central Bank.
  43. Neil Shephard, 2013. "Martingale unobserved component models," Economics Series Working Papers 644, University of Oxford, Department of Economics.
  44. 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.
  45. 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.
  46. 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.
  47. 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.
  48. D'Agostino, Antonello & Mendicino, Caterina, 2014. "Expectation-Driven Cycles: Time-varying Effects," MPRA Paper 53607, University Library of Munich, Germany.
  49. 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.
  50. Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in Nonstationary Environments: What Works and What Doesn’t in Reduced-Form and Structural Models," Working Papers 819, Barcelona Graduate School of Economics.
  51. 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.
  52. 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.
  53. 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.
  54. Clark, Todd E. & Doh, Taeyoung, 2014. "Evaluating alternative models of trend inflation," International Journal of Forecasting, Elsevier, vol. 30(3), pages 426-448.
  55. repec:ecb:ecbwps:20151776 is not listed on IDEAS
  56. 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.
  57. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.
  58. Gambetti, Luca & Musso, Alberto, 2012. "Loan supply shocks and the business cycle," Working Paper Series 1469, European Central Bank.
  59. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox," Tinbergen Institute Discussion Papers 13-055/III, Tinbergen Institute, revised 16 Jan 2015.
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