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Alessia Paccagnini

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.

    Mentioned in:

    1. Dealing with Misspecification in DSGE Models: A Survey
      by Christian Zimmermann in NEP-DGE blog on 2018-02-10 04:25:16
  2. Stelios D. Bekiros & Alessia Paccagnini, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Open Access publications 10197/7322, School of Economics, University College Dublin.

    Mentioned in:

    1. Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models
      by Christian Zimmermann in NEP-DGE blog on 2015-12-31 21:28:19

Working papers

  1. Alessia Paccagnini & Fabio Parla, 2021. "Identifying high-frequency shocks with Bayesian mixed-frequency VARs," CAMA Working Papers 2021-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Alain Hecq & Marie Ternes & Ines Wilms, 2023. "Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions," Papers 2301.10592, arXiv.org, revised Nov 2024.
    2. Piergiorgio Alessandri & Andrea Gazzani & Alejandro Vicondoa, 2023. "Are the Effects of Uncertainty Shocks Big or Small?," Working Papers 244, Red Nacional de Investigadores en Economía (RedNIE).

  2. Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2021. "Testing the predictive accuracy of COVID-19 forecasts," CAMA Working Papers 2021-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Medeiros, Marcelo C. & Street, Alexandre & Valladão, Davi & Vasconcelos, Gabriel & Zilberman, Eduardo, 2022. "Short-term Covid-19 forecast for latecomers," International Journal of Forecasting, Elsevier, vol. 38(2), pages 467-488.
    2. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2024. "Predictive ability tests with possibly overlapping models," Journal of Econometrics, Elsevier, vol. 241(1).

  3. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

    Cited by:

    1. Janczura, Joanna & Wójcik, Edyta, 2022. "Dynamic short-term risk management strategies for the choice of electricity market based on probabilistic forecasts of profit and risk measures. The German and the Polish market case study," Energy Economics, Elsevier, vol. 110(C).
    2. Heymann, Fabian & Milojevic, Tatjana & Covatariu, Andrei & Verma, Piyush, 2023. "Digitalization in decarbonizing electricity systems – Phenomena, regional aspects, stakeholders, use cases, challenges and policy options," Energy, Elsevier, vol. 262(PB).
    3. Nie, Yan & Zhang, Guoxing & Zhong, Luhao & Su, Bin & Xi, Xi, 2024. "Urban‒rural disparities in household energy and electricity consumption under the influence of electricity price reform policies," Energy Policy, Elsevier, vol. 184(C).
    4. Spiliotis, Evangelos & Petropoulos, Fotios, 2024. "On the update frequency of univariate forecasting models," European Journal of Operational Research, Elsevier, vol. 314(1), pages 111-121.
    5. Ramos, Paulo Vitor B. & Villela, Saulo Moraes & Silva, Walquiria N. & Dias, Bruno H., 2023. "Residential energy consumption forecasting using deep learning models," Applied Energy, Elsevier, vol. 350(C).
    6. Said Rosli & Sulaimi Mardhiati & Majid Rohayu Ab & Aini Ainoriza Mohd & Olanrele Olusegun Olaopin & Akinsomi Omokolade, 2024. "Evaluating Market Attributes and Housing Affordability: Gaining Perspective on Future Value Trends," Real Estate Management and Valuation, Sciendo, vol. 32(3), pages 87-100.
    7. Ghelasi, Paul & Ziel, Florian, 2024. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," International Journal of Forecasting, Elsevier, vol. 40(2), pages 581-596.
    8. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    9. Raja, Aitazaz Ali & Pinson, Pierre & Kazempour, Jalal & Grammatico, Sergio, 2024. "A market for trading forecasts: A wagering mechanism," International Journal of Forecasting, Elsevier, vol. 40(1), pages 142-159.
    10. Simon Hirsch & Jonathan Berrisch & Florian Ziel, 2024. "Online Distributional Regression," Papers 2407.08750, arXiv.org, revised Aug 2024.
    11. Katarzyna Maciejowska & Weronika Nitka, 2024. "Multiple split approach -- multidimensional probabilistic forecasting of electricity markets," Papers 2407.07795, arXiv.org.
    12. Amjad Almusaed & Ibrahim Yitmen & Asaad Almssad, 2023. "Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review," Energies, MDPI, vol. 16(6), pages 1-23, March.
    13. Jozef Barunik & Lubos Hanus, 2023. "Learning Probability Distributions of Day-Ahead Electricity Prices," Papers 2310.02867, arXiv.org, revised Oct 2023.
    14. Xiaoqian Wang & Yanfei Kang & Rob J Hyndman & Feng Li, 2020. "Distributed ARIMA Models for Ultra-long Time Series," Monash Econometrics and Business Statistics Working Papers 29/20, Monash University, Department of Econometrics and Business Statistics.
    15. Bergsteinsson, Hjörleifur G. & Sørensen, Mikkel Lindstrøm & Møller, Jan Kloppenborg & Madsen, Henrik, 2023. "Heat load forecasting using adaptive spatial hierarchies," Applied Energy, Elsevier, vol. 350(C).
    16. Nghia Chu & Binh Dao & Nga Pham & Huy Nguyen & Hien Tran, 2022. "Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques," Papers 2209.09649, arXiv.org, revised Jul 2023.
    17. Mutele, Litshedzani & Carranza, Emmanuel John M., 2024. "Statistical analysis of gold production in South Africa using ARIMA, VAR and ARNN modelling techniques: Extrapolating future gold production, Resources–Reserves depletion, and Implication on South Afr," Resources Policy, Elsevier, vol. 93(C).
    18. Takahashi, Carlos Kazunari & Figueiredo, Júlio César Bastos de & Scornavacca, Eusebio, 2024. "Investigating the diffusion of innovation: A comprehensive study of successive diffusion processes through analysis of search trends, patent records, and academic publications," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    19. Li, Xishu & Zuidwijk, Rob & de Koster, M.B.M, 2023. "Optimal competitive capacity strategies: Evidence from the container shipping market," Omega, Elsevier, vol. 115(C).
    20. Richard Bean, 2023. "Forecasting the Monash Microgrid for the IEEE-CIS Technical Challenge," Energies, MDPI, vol. 16(3), pages 1-23, January.
    21. Emmanuel Senyo Fianu, 2022. "Analyzing and Forecasting Multi-Commodity Prices Using Variants of Mode Decomposition-Based Extreme Learning Machine Hybridization Approach," Forecasting, MDPI, vol. 4(2), pages 1-27, June.
    22. Ca’ Zorzi, Michele & Rubaszek, Michał, 2023. "How many fundamentals should we include in the behavioral equilibrium exchange rate model?," Economic Modelling, Elsevier, vol. 118(C).
    23. Racek, Daniel & Thurner, Paul W. & Davidson, Brittany I. & Zhu, Xiao Xiang & Kauermann, Göran, 2024. "Conflict forecasting using remote sensing data: An application to the Syrian civil war," International Journal of Forecasting, Elsevier, vol. 40(1), pages 373-391.
    24. Huang, Congzhi & Yang, Mengyuan, 2023. "Memory long and short term time series network for ultra-short-term photovoltaic power forecasting," Energy, Elsevier, vol. 279(C).
    25. Joanna Janczura & Andrzej Puć, 2023. "ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation," Energies, MDPI, vol. 16(2), pages 1-28, January.
    26. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    27. Wesley Marcos Almeida & Claudimar Pereira Veiga, 2023. "Does demand forecasting matter to retailing?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 219-232, June.
    28. Elalem, Yara Kayyali & Maier, Sebastian & Seifert, Ralf W., 2023. "A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1874-1894.
    29. Anna Sznajderska & Alfred A. Haug, 2023. "Bayesian VARs of the U.S. economy before and during the pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 211-236, June.
    30. Michael Pedersen, 2024. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," Papers 2404.04105, arXiv.org.
    31. Jun Meng & Jingfang Fan & Uma S. Bhatt & Jürgen Kurths, 2023. "Arctic weather variability and connectivity," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    32. Marek Kwas & Alessia Paccagnini & Michal Rubaszek, 2020. "Common factors and the dynamics of cereal prices. A forecasting perspective," CAMA Working Papers 2020-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    33. Aitazaz Ali Raja & Pierre Pinson & Jalal Kazempour & Sergio Grammatico, 2022. "A Market for Trading Forecasts: A Wagering Mechanism," Papers 2205.02668, arXiv.org, revised Oct 2022.
    34. Grzegorz Marcjasz & Micha{l} Narajewski & Rafa{l} Weron & Florian Ziel, 2022. "Distributional neural networks for electricity price forecasting," Papers 2207.02832, arXiv.org, revised Dec 2022.
    35. Bernhard Tröster & Ulrich Gunter, 2023. "The Financialization of Coffee, Cocoa and Cotton Value Chains: The Role of Physical Actors," Development and Change, International Institute of Social Studies, vol. 54(6), pages 1550-1574, November.
    36. Tetiana Zatonatska & Olena Liashenko & Yana Fareniuk & Oleksandr Dluhopolskyi & Artur Dmowski & Marzena Cichorzewska, 2022. "The Migration Influence on the Forecasting of Health Care Budget Expenditures in the Direction of Sustainability: Case of Ukraine," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    37. Jeroen Rombouts & Marie Ternes & Ines Wilms, 2024. "Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning," Papers 2402.09033, arXiv.org, revised May 2024.
    38. Jonathan Berrisch & Florian Ziel, 2022. "Distributional modeling and forecasting of natural gas prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1065-1086, September.
    39. Oscar Espinosa & Valeria Bejarano & Jeferson Ramos & Boris Martínez, 2023. "Statistical actuarial estimation of the Capitation Payment Unit from copula functions and deep learning: historical comparability analysis for the Colombian health system, 2015–2021," Health Economics Review, Springer, vol. 13(1), pages 1-20, December.
    40. Niklas Valentin Lehmann, 2023. "Forecasting skill of a crowd-prediction platform: A comparison of exchange rate forecasts," Papers 2312.09081, arXiv.org.
    41. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.
    42. Fałdziński, Marcin & Fiszeder, Piotr & Molnár, Peter, 2024. "Improving volatility forecasts: Evidence from range-based models," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
    43. Alroomi, Azzam & Karamatzanis, Georgios & Nikolopoulos, Konstantinos & Tilba, Anna & Xiao, Shujun, 2022. "Fathoming empirical forecasting competitions’ winners," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1519-1525.
    44. Qi, Lingzhi & Li, Xixi & Wang, Qiang & Jia, Suling, 2023. "fETSmcs: Feature-based ETS model component selection," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1303-1317.
    45. Guo, Su & Zheng, Kun & He, Yi & Kurban, Aynur, 2023. "The artificial intelligence-assisted short-term optimal scheduling of a cascade hydro-photovoltaic complementary system with hybrid time steps," Renewable Energy, Elsevier, vol. 202(C), pages 1169-1189.
    46. Rai, Amit & Shrivastava, Ashish & Jana, Kartick C., 2023. "Differential attention net: Multi-directed differential attention based hybrid deep learning model for solar power forecasting," Energy, Elsevier, vol. 263(PC).
    47. Swaminathan, Kritika & Venkitasubramony, Rakesh, 2024. "Demand forecasting for fashion products: A systematic review," International Journal of Forecasting, Elsevier, vol. 40(1), pages 247-267.
    48. Anita M. Bunea & Mariangela Guidolin & Piero Manfredi & Pompeo Della Posta, 2022. "Diffusion of Solar PV Energy in the UK: A Comparison of Sectoral Patterns," Forecasting, MDPI, vol. 4(2), pages 1-21, April.
    49. Andrea Savio & Luigi De Giovanni & Mariangela Guidolin, 2022. "Modelling Energy Transition in Germany: An Analysis through Ordinary Differential Equations and System Dynamics," Forecasting, MDPI, vol. 4(2), pages 1-18, April.
    50. Zheng, Zhuang & Shafique, Muhammad & Luo, Xiaowei & Wang, Shengwei, 2024. "A systematic review towards integrative energy management of smart grids and urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    51. Fernández, Joaquín Delgado & Menci, Sergio Potenciano & Lee, Chul Min & Rieger, Alexander & Fridgen, Gilbert, 2022. "Privacy-preserving federated learning for residential short-term load forecasting," Applied Energy, Elsevier, vol. 326(C).
    52. Radovan Šomplák & Veronika Smejkalová & Martin Rosecký & Lenka Szásziová & Vlastimír Nevrlý & Dušan Hrabec & Martin Pavlas, 2023. "Comprehensive Review on Waste Generation Modeling," Sustainability, MDPI, vol. 15(4), pages 1-29, February.
    53. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    54. Paul Ghelasi & Florian Ziel, 2023. "Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions," Papers 2305.16255, arXiv.org.
    55. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
    56. Allen, Sam & Koh, Jonathan & Segers, Johan & Ziegel, Johanna, 2024. "Tail calibration of probabilistic forecasts," LIDAM Discussion Papers ISBA 2024018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  4. Valentina Colombo & Alessia Paccagnini, 2020. "The asymmetric effects of uncertainty shocks," CAMA Working Papers 2020-72, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Min Fang, 2021. "Lumpy Investment, Fluctuations in Volatility and Monetary Policy," Working Papers 002001, University of Florida, Department of Economics.
    2. Giovanni Pellegrino & Federico Ravenna & Gabriel Züllig, 2021. "The Impact of Pessimistic Expectations on the Effects of COVID‐19‐Induced Uncertainty in the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 841-869, August.
    3. Valentin Jouvanceau, 2023. "Consumer price rigidity in periods of low and high inflation: the case of Lithuania," Bank of Lithuania Discussion Paper Series 34, Bank of Lithuania.

  5. V. Colombo & A. Paccagnini, 2020. "Has the credit supply shock asymmetric effects on macroeconomic variables?," Working Papers wp1140, Dipartimento Scienze Economiche, Universita' di Bologna.

    Cited by:

    1. David Finck & Paul Rudel, 2020. "Do Credit Supply Shocks Have Asymmetric Effects?," MAGKS Papers on Economics 202026, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    2. Philipp Meinen & Ana Cristina Soares, 2022. "Markups and Financial Shocks," The Economic Journal, Royal Economic Society, vol. 132(647), pages 2471-2499.
    3. Ozili, Peterson K & Oladipo, Olajide & Iorember, Paul, 2023. "Effect of abnormal increase in credit supply on economic growth in Nigeria," MPRA Paper 115988, University Library of Munich, Germany.

  6. Marek Kwas & Alessia Paccagnini & Michal Rubaszek, 2020. "Common factors and the dynamics of cereal prices. A forecasting perspective," CAMA Working Papers 2020-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Massimiliano Caporin & C. Vladimir Rodríguez-Caballero & Esther Ruiz, 2024. "The factor structure of exchange rates volatility: global and intermittent factors," Empirical Economics, Springer, vol. 67(1), pages 31-45, July.
    2. Marek Kwas & Michał Rubaszek, 2021. "Forecasting Commodity Prices: Looking for a Benchmark," Forecasting, MDPI, vol. 3(2), pages 1-13, June.

  7. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.

    Cited by:

    1. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Erlan Konebayev, 2022. "Forecasting a commodity-exporting small open developing economy using DSGE and DSGE-BVAR," NAC Analytica Working Paper 24, NAC Analytica, Nazarbayev University, revised May 2022.
    3. Concetta Rondinelli & Roberta Zizza, 2020. "Spend today or spend tomorrow? The role of inflation expectations in consumer behaviour," Temi di discussione (Economic working papers) 1276, Bank of Italy, Economic Research and International Relations Area.
    4. Rangan Gupta & Xiaojin Sun, 2022. "Time-Varying Parameter Four-Equation DSGE Model," Working Papers 202234, University of Pretoria, Department of Economics.

  8. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2018. "Limited Asset Market Participation and the Euro Area Crisis. An Empirical DSGE Model," Working Papers 391, University of Milano-Bicocca, Department of Economics, revised Nov 2018.

    Cited by:

    1. Tervala, Juha & Watson, Timothy, 2022. "Hysteresis and fiscal stimulus in a recession," Journal of International Money and Finance, Elsevier, vol. 124(C).
    2. Alice Albonico & Guido Ascari & Qazi Haque, 2024. "Monetary Policy in the Euro Area: Active or Passive?," Working Papers 535, University of Milano-Bicocca, Department of Economics.
    3. Emilio Colombo & Davide Furceri & Pietro Pizzuto & Patrizio Tirelli, 2022. "Fiscal Multipliers and Informality," IMF Working Papers 2022/082, International Monetary Fund.
    4. Bartocci, Anna & Cantelmo, Alessandro & Cova, Pietro & Notarpietro, Alessandro & Pisani, Massimiliano, 2024. "Monetary and fiscal policy responses to fossil fuel price shocks," Energy Economics, Elsevier, vol. 136(C).
    5. Giovanni Melina & Stefania Villa, 2023. "Drivers of large recessions and monetary policy responses," Temi di discussione (Economic working papers) 1425, Bank of Italy, Economic Research and International Relations Area.
    6. Ricciutelli, Francesco, 2024. "Energy Inflation and Consumption Inequality," MPRA Paper 120899, University Library of Munich, Germany.
    7. Germaschewski, Yin & Wang, Shu-Ling, 2022. "Fiscal stabilization in high-debt economies without monetary independence," Journal of Macroeconomics, Elsevier, vol. 72(C).
    8. Alice Albonico & Guido Ascari & Qazi Haque, 2020. "The (Ir)Relevance of Rule-of-Thumb Consumers for U.S. Business Cycle Fluctuations," Working Papers 453, University of Milano-Bicocca, Department of Economics, revised Oct 2022.
    9. Marco Lorusso & Luca Pieroni, 2019. "Disentangling Civilian and Military Spending Shocks: A Bayesian DSGE Approach for the US Economy," JRFM, MDPI, vol. 12(3), pages 1-41, September.
    10. Charalampidis, Nikolaos, 2020. "On unemployment cycles in the Euro Area, 1999–2018," European Economic Review, Elsevier, vol. 121(C).

  9. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2017. "PIIGS in the Euro area: An empirical DSGE model," Discussion Papers in Economics economics:201710, Griffith University, Department of Accounting, Finance and Economics.

    Cited by:

    1. Tatiana Kirsanova & Celsa Machado & Ana Paula Ribeiro, 2018. "Should the ECB Coordinate EMU Fiscal Policies?," International Journal of Central Banking, International Journal of Central Banking, vol. 14(3), pages 237-280, June.
    2. Himmels, Christoph & Kirsanova, Tatiana, 2018. "Discretionary policy in a small open economy: Exchange rate regimes and multiple equilibria," Journal of Macroeconomics, Elsevier, vol. 56(C), pages 53-64.

  10. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.

    Cited by:

    1. Marcin Kolasa & Michał Rubaszek, 2018. "Does the foreign sector help forecast domestic variables in DSGE models?," NBP Working Papers 282, Narodowy Bank Polski.
    2. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Den Haan, Wouter & Drechsel, Thomas, 2018. "Agnostic Structural Disturbances (ASDs): Detecting and Reducing Misspecification in Empirical Macroeconomic Models," CEPR Discussion Papers 13145, C.E.P.R. Discussion Papers.

  11. Alessia Paccagnini, 2017. "Forecasting with FAVAR: macroeconomic versus financial factors," NBP Working Papers 256, Narodowy Bank Polski.

    Cited by:

    1. Behera, Harendra & Gunadi, Iman & Rath, Badri Narayan, 2023. "COVID-19 uncertainty, financial markets and monetary policy effects in case of two emerging Asian countries," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 173-189.
    2. Szydlo, Jan, 2023. "Forecasting Credit Dynamics : VAR, VECM or modern Factor-Augmented VAR approach?," Warwick-Monash Economics Student Papers 63, Warwick Monash Economics Student Papers.

  12. Stelios D. Bekiros & Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2016. "Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a predictability analysis versus TVP-VARs," Open Access publications 10197/7323, School of Economics, University College Dublin.

    Cited by:

    1. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    2. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Caraiani, Petre & Luik, Marc-André & Wesselbaum, Dennis, 2020. "Credit policy and asset price bubbles," Journal of Macroeconomics, Elsevier, vol. 65(C).
    4. Bekiros, Stelios & Nilavongse, Rachatar & Uddin, Gazi Salah, 2020. "Expectation-driven house prices and debt defaults: The effectiveness of monetary and macroprudential policies," Journal of Financial Stability, Elsevier, vol. 49(C).
    5. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    6. Jang, Tae-Seok & Sacht, Stephen, 2021. "Forecast heuristics, consumer expectations, and New-Keynesian macroeconomics: A Horse race," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 493-511.
    7. Liu, Guangling & Molise, Thabang, 2019. "Housing and credit market shocks: Exploring the role of rule-based Basel III counter-cyclical capital requirements," Economic Modelling, Elsevier, vol. 82(C), pages 264-279.
    8. Lenhle Dlamini & Harold Ngalawa, 2022. "Macroprudential policy and house prices in an estimated Dynamic Stochastic General Equilibrium model for South Africa," Australian Economic Papers, Wiley Blackwell, vol. 61(2), pages 304-336, June.
    9. Abdi, N. & Aminikhah, H. & Sheikhani, A.H. Refahi, 2022. "High-order compact finite difference schemes for the time-fractional Black-Scholes model governing European options," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    10. Eric Jondeau & Michael Rockinger, 2019. "Predicting Long‐Term Financial Returns: VAR versus DSGE Model—A Horse Race," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(8), pages 2239-2291, December.

  13. Alice, Albonico & Alessia, Paccagnini & Patrizio, Tirelli, 2016. "In search of the Euro Area Fiscal Stance," Working Papers 324, University of Milano-Bicocca, Department of Economics, revised 24 Feb 2016.

    Cited by:

    1. Babecký, Jan & Franta, Michal & Ryšánek, Jakub, 2018. "Fiscal policy within the DSGE-VAR framework," Economic Modelling, Elsevier, vol. 75(C), pages 23-37.
    2. Piotr Krajewski & Agata Szymanska, 2019. "The effectiveness of fiscal policy within business cycle-Ricardians vs. non-Ricardians approach," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 19(2), pages 195-215.
    3. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    4. Albonico, Alice & Paccagnini, Alessia & Tirelli, Patrizio, 2017. "Great recession, slow recovery and muted fiscal policies in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 81(C), pages 140-161.
    5. Mathilde Le Moigne & Francesco Saraceno & Sébastien Villemot, 2016. "Probably Too Little, Certainly Too Late. An Assessment of the Juncker Investment Plan," PSE Working Papers hal-03459360, HAL.
    6. Albonico, Alice & Tirelli, Patrizio, 2020. "Financial crises and sudden stops: Was the European monetary union crisis different?," Economic Modelling, Elsevier, vol. 93(C), pages 13-26.
    7. Alice, Albonico & Roberta, Cardani & Patrizio, Tirelli, 2017. "Debunking the Myth of Southern Profligacy. A DSGE Analysis of Business Cycles in the EMU’s Big Four," Working Papers 373, University of Milano-Bicocca, Department of Economics, revised Jan 2018.
    8. Germaschewski, Yin & Wang, Shu-Ling, 2022. "Fiscal stabilization in high-debt economies without monetary independence," Journal of Macroeconomics, Elsevier, vol. 72(C).
    9. Francisco de Castro & Francisco Martí & Antonio Montesinos & Javier J. Pérez & Antonio Jesús Sánchez Fuentes, 2018. "A Quarterly Fiscal Database Fit for Macroeconomic Analysis," Hacienda Pública Española / Review of Public Economics, IEF, vol. 224(1), pages 139-155, March.
    10. Alice, Albonico & Lorenza, Rossi, 2017. "Inflation bias and markup shocks in a LAMP model with strategic interaction of monetary and fiscal policy," Working Papers 362, University of Milano-Bicocca, Department of Economics, revised 14 Feb 2017.
    11. Drygalla, Andrej & Holtemöller, Oliver & Kiesel, Konstantin, 2020. "The Effects Of Fiscal Policy In An Estimated Dsge Model—The Case Of The German Stimulus Packages During The Great Recession," Macroeconomic Dynamics, Cambridge University Press, vol. 24(6), pages 1315-1345, September.
    12. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2017. "PIIGS in the Euro area: An empirical DSGE model," Discussion Papers in Economics economics:201710, Griffith University, Department of Accounting, Finance and Economics.
    13. Nicoletta Batini & Alessandro Cantelmo & Giovanni Melina & Stefania Villa, 2020. "How Loose, how tight? A measure of monetary and fiscal stance for the euro area," Temi di discussione (Economic working papers) 1295, Bank of Italy, Economic Research and International Relations Area.
    14. Beqiraj Elton & Di Bartolomeo Giovanni & Di Pietro Marco, 2016. "Financial crises, limited asset market participation, and banks balance sheet constraints," wp.comunite 00127, Department of Communication, University of Teramo.
    15. Patrizio Tirelli & Maria Ferrara, 2020. "Disinflation, Inequality, And Welfare In A Tank Model," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1297-1313, July.
    16. Ageliki Anagnostou & Piotr Krajewski & Katarzyna Pilat, 2020. "Regional Specific Idiosyncrasies and Fiscal Policy: Evidence from 47 Regions of the Central and Eastern European Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 936-954.
    17. Christos Avdoulas & Stelios Bekiros, 2018. "Nonlinear Forecasting of Euro Area Industrial Production Using Evolutionary Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 521-530, August.

  14. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2016. "Great Recession, Slow Recovery and Muted Fiscal Policies in the US," Working Papers 201602, School of Economics, University College Dublin.

    Cited by:

    1. Babecký, Jan & Franta, Michal & Ryšánek, Jakub, 2018. "Fiscal policy within the DSGE-VAR framework," Economic Modelling, Elsevier, vol. 75(C), pages 23-37.
    2. Sergey Ivashchenko, 2022. "Dynamic Stochastic General Equilibrium Model with Multiple Trends and Structural Breaks," Russian Journal of Money and Finance, Bank of Russia, vol. 81(1), pages 46-72, March.
    3. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    4. Emilio Colombo & Davide Furceri & Pietro Pizzuto & Patrizio Tirelli, 2022. "Fiscal Multipliers and Informality," IMF Working Papers 2022/082, International Monetary Fund.
    5. Acocella, Nicola & Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco & Felici, Francesco, 2020. "An evaluation of alternative fiscal adjustment plans: The case of Italy," Journal of Policy Modeling, Elsevier, vol. 42(3), pages 699-711.
    6. Funashima, Yoshito, 2020. "Monetary policy, financial uncertainty, and secular stagnation," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    7. Alice, Albonico & Lorenza, Rossi, 2017. "Inflation bias and markup shocks in a LAMP model with strategic interaction of monetary and fiscal policy," Working Papers 362, University of Milano-Bicocca, Department of Economics, revised 14 Feb 2017.
    8. Nicoletta Batini & Alessandro Cantelmo & Giovanni Melina & Stefania Villa, 2020. "How Loose, how tight? A measure of monetary and fiscal stance for the euro area," Temi di discussione (Economic working papers) 1295, Bank of Italy, Economic Research and International Relations Area.
    9. Acocella, Nicola & Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco & Felici, Francesco & Alleva, Giorgio & Di Dio, Fabio & Liseo, Brunero, 2020. "A stochastic estimated version of the Italian dynamic General Equilibrium Model," Economic Modelling, Elsevier, vol. 92(C), pages 339-357.
    10. Marco Lorusso & Luca Pieroni, 2019. "Disentangling Civilian and Military Spending Shocks: A Bayesian DSGE Approach for the US Economy," JRFM, MDPI, vol. 12(3), pages 1-41, September.
    11. Acocella, Nicola & Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco & Felici, Francesco, 2019. "An evaluation of alternative fiscal adjustment plans," EconStor Preprints 209707, ZBW - Leibniz Information Centre for Economics.
    12. Patrizio Tirelli & Maria Ferrara, 2020. "Disinflation, Inequality, And Welfare In A Tank Model," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1297-1313, July.
    13. Zhang, Wen, 2019. "Deciphering the causes for the post-1990 slow output recoveries," Economics Letters, Elsevier, vol. 176(C), pages 28-34.
    14. Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco & Serpieri, Carolina, 2018. "Comparing Central Europe and the Baltic macro-economies: A Bayesian approach," EconStor Preprints 175242, ZBW - Leibniz Information Centre for Economics.

  15. Stelios Bekiros & Rangan Gupta & Alessia Paccagnini, 2015. "Oil Price Forecastability and Economic Uncertainty," Working Papers 298, University of Milano-Bicocca, Department of Economics, revised Apr 2015.

    Cited by:

    1. Wen, Jun & Khalid, Samia & Mahmood, Hamid & Zakaria, Muhammad, 2021. "Symmetric and asymmetric impact of economic policy uncertainty on food prices in China: A new evidence," Resources Policy, Elsevier, vol. 74(C).
    2. Jihoon Lee & Hong Chong Cho, 2021. "Impact of Structural Oil Price Shock Factors on the Gasoline Market and Macroeconomy in South Korea," Sustainability, MDPI, vol. 13(4), pages 1-23, February.
    3. Kang, Wensheng & Ratti, Ronald. A. & Vespignani, Joaquin, 2017. "Oil price shocks and policy uncertainty: New evidence on the effects of US and non-US oil production," Working Papers 2017-02, University of Tasmania, Tasmanian School of Business and Economics.
    4. Drachal, Krzysztof, 2021. "Forecasting selected energy commodities prices with Bayesian dynamic finite mixtures," Energy Economics, Elsevier, vol. 99(C).
    5. Xu, Yan & Wang, Xinyu & Liu, Hening, 2021. "Quantile-based GARCH-MIDAS: Estimating value-at-risk using mixed-frequency information," Finance Research Letters, Elsevier, vol. 43(C).
    6. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    7. Chatziantoniou, Ioannis & Degiannakis, Stavros & Delis, Panagiotis & Filis, George, 2021. "Forecasting oil price volatility using spillover effects from uncertainty indices," Finance Research Letters, Elsevier, vol. 42(C).
    8. Dutta, Anupam & Bouri, Elie & Saeed, Tareq, 2021. "News-based equity market uncertainty and crude oil volatility," Energy, Elsevier, vol. 222(C).
    9. F. Dilvin Taşkin & Efe Çağlar Çağlı & Umut Halaç, 2016. "The impact of oil price shocks on the volatility of the Turkish stock market," International Journal of Accounting and Finance, Inderscience Enterprises Ltd, vol. 6(1), pages 1-23.
    10. Chatziantoniou, Ioannis & Degiannakis, Stavros & Delis, Panagiotis & Filis, George, 2019. "Can spillover effects provide forecasting gains? The case of oil price volatility," MPRA Paper 96266, University Library of Munich, Germany.
    11. Yang, Lu, 2019. "Connectedness of economic policy uncertainty and oil price shocks in a time domain perspective," Energy Economics, Elsevier, vol. 80(C), pages 219-233.
    12. Yang, Lu & Hamori, Shigeyuki, 2021. "Systemic risk and economic policy uncertainty: International evidence from the crude oil market," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 142-158.
    13. Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2015. "The Role of News-Based Uncertainty Indices in Predicting Oil Markets: A Hybrid Nonparametric Quantile Causality Method," Working Papers 201522, University of Pretoria, Department of Economics.
    14. Hosseini, Seyed Hossein & Shakouri G., Hamed & Kazemi, Aliyeh, 2021. "Oil price future regarding unconventional oil production and its near-term deployment: A system dynamics approach," Energy, Elsevier, vol. 222(C).
    15. Shi, Chunpei & Wei, Yu & Li, Xiafei & Liu, Yuntong, 2023. "Combination forecasts of China's oil futures returns based on multiple uncertainties and their connectedness with oil," Energy Economics, Elsevier, vol. 126(C).
    16. Lin, Boqiang & Bai, Rui, 2021. "Oil prices and economic policy uncertainty: Evidence from global, oil importers, and exporters’ perspective," Research in International Business and Finance, Elsevier, vol. 56(C).
    17. Gu, Xin & Zhu, Zixiang & Yu, Minli, 2021. "The macro effects of GPR and EPU indexes over the global oil market—Are the two types of uncertainty shock alike?," Energy Economics, Elsevier, vol. 100(C).
    18. Krzysztof Drachal, 2018. "Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework," Energies, MDPI, vol. 11(5), pages 1-24, May.
    19. Das, Debojyoti & Kannadhasan, M., 2020. "The asymmetric oil price and policy uncertainty shock exposure of emerging market sectoral equity returns: A quantile regression approach," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 563-581.
    20. Yong Jiang & Yi-Shuai Ren & Chao-Qun Ma & Jiang-Long Liu & Basil Sharp, 2018. "Does the price of strategic commodities respond to U.S. Partisan Conflict?," Papers 1810.08396, arXiv.org, revised Feb 2020.
    21. Bos, Martijn & Demirer, Riza & Gupta, Rangan & Tiwari, Aviral Kumar, 2018. "Oil returns and volatility: The role of mergers and acquisitions," Energy Economics, Elsevier, vol. 71(C), pages 62-69.
    22. Medel, Carlos A., 2015. "Geopolitical Tensions, OPEC News, and Oil Price: A Granger Causality Analysis," MPRA Paper 65667, University Library of Munich, Germany.
    23. Yi‐Ting Peng & Tsangyao Chang & Omid Ranjbar, 2022. "Analyzing the degree of persistence of economic policy uncertainty using linear and non‐linear fourier quantile unit root tests," Manchester School, University of Manchester, vol. 90(4), pages 453-471, July.
    24. Uddin, Gazi Salah & Bekiros, Stelios & Ahmed, Ali, 2018. "The nexus between geopolitical uncertainty and crude oil markets: An entropy-based wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 30-39.
    25. Gaoke Liao & Zhenghui Li & Ziqing Du & Yue Liu, 2019. "The Heterogeneous Interconnections between Supply or Demand Side and Oil Risks," Energies, MDPI, vol. 12(11), pages 1-17, June.
    26. Giovanni Bonaccolto & Massimiliano Caporin & Rangan Gupta, 2015. "The Dynamic Impact of Uncertainty in Causing and Forecasting the Distribution of Oil Returns and Risk," Working Papers 201564, University of Pretoria, Department of Economics.
    27. Rehman, Mobeen Ur & Kang, Sang Hoon, 2021. "A time–frequency comovement and causality relationship between Bitcoin hashrate and energy commodity markets," Global Finance Journal, Elsevier, vol. 49(C).
    28. Dong, Minyi & Chang, Chun-Ping & Gong, Qiang & Chu, Yin, 2019. "Revisiting global economic activity and crude oil prices: A wavelet analysis," Economic Modelling, Elsevier, vol. 78(C), pages 134-149.
    29. Ender Demir & Giray Gozgor, 2016. "The Impact Of Economic Policy Uncertainty On The Vehicle Miles Traveled (Vmt) In The U.S," Eurasian Journal of Business and Management, Eurasian Publications, vol. 4(3), pages 39-48.
    30. César Castro & Rebeca Jiménez-Rodríguez & Pilar Poncela & Eva Senra, 2017. "A new look at oil price pass-through into inflation: evidence from disaggregated European data," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 34(1), pages 55-82, April.
    31. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    32. Wei, Yu & Liu, Jing & Lai, Xiaodong & Hu, Yang, 2017. "Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 141-150.
    33. Gong, Mengqi & You, Zhe & Wang, Longle & Ruan, Dapeng, 2024. "Research of the non-linear dynamic relationship between global economic policy uncertainty and crude oil prices," Journal of Asian Economics, Elsevier, vol. 90(C).
    34. Ying Chen & Xiaoqian Shen & Li Wang, 2021. "The Heterogeneity Research of the Impact of EPU on Environmental Pollution: Empirical Evidence Based on 15 Countries," Sustainability, MDPI, vol. 13(8), pages 1-13, April.
    35. Ruixin Su & Jianguo Du & Fakhar Shahzad & Xingle Long, 2020. "Unveiling the Effect of Mean and Volatility Spillover between the United States Economic Policy Uncertainty and WTI Crude Oil Price," Sustainability, MDPI, vol. 12(16), pages 1-12, August.
    36. Apergis, Nicholas & Hayat, Tasawar & Saeed, Tareq, 2021. "US partisan conflict uncertainty and oil prices," Energy Policy, Elsevier, vol. 150(C).
    37. Qadan, Mahmoud & Idilbi-Bayaa, Yasmeen, 2020. "Risk appetite and oil prices," Energy Economics, Elsevier, vol. 85(C).
    38. Mohsen Bahmani-Oskooee & Hanafiah Harvey & Farhang Niroomand, 2018. "On the Impact of Policy Uncertainty on Oil Prices: An Asymmetry Analysis," IJFS, MDPI, vol. 6(1), pages 1-11, January.
    39. Degiannakis, Stavros & Filis, George & Panagiotakopoulou, Sofia, 2018. "Oil price shocks and uncertainty: How stable is their relationship over time?," Economic Modelling, Elsevier, vol. 72(C), pages 42-53.
    40. Huabin Bian & Renhai Hua & Qingfu Liu & Ping Zhang, 2022. "Petroleum market volatility tracker in China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2022-2040, November.
    41. Gizem Uzuner & Sudeshna Ghosh, 2021. "Do pandemics have an asymmetric effect on tourism in Italy?," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1561-1579, October.
    42. Lucey, Brian & Ren, Boru, 2021. "Does news tone help forecast oil?," Economic Modelling, Elsevier, vol. 104(C).
    43. Xinwei Zhao & Xinsong Yang & Geng Peng & Shengjie Yue, 2023. "International Trade and Carbon Emissions: Evaluating the Role of Trade Rule Uncertainty," Sustainability, MDPI, vol. 15(15), pages 1-19, July.
    44. Alola, Andrew A. & Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2022. "Outlook of oil prices and volatility from 1970 to 2040 through global energy mix-security from production to reserves: A nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 79(C).
    45. Kang, Wensheng & Perez de Gracia, Fernando & Ratti, Ronald A., 2017. "Oil price shocks, policy uncertainty, and stock returns of oil and gas corporations," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 344-359.
    46. Yanhong Feng & Dilong Xu & Pierre Failler & Tinghui Li, 2020. "Research on the Time-Varying Impact of Economic Policy Uncertainty on Crude Oil Price Fluctuation," Sustainability, MDPI, vol. 12(16), pages 1-24, August.
    47. Yu, Mengyan & Umair, Muhammad & Oskenbayev, Yessengali & Karabayeva, Zhаnsaya, 2023. "Exploring the nexus between monetary uncertainty and volatility in global crude oil: A contemporary approach of regime-switching," Resources Policy, Elsevier, vol. 85(PB).
    48. Krzysztof Drachal & Michał Pawłowski, 2024. "Forecasting Selected Commodities’ Prices with the Bayesian Symbolic Regression," IJFS, MDPI, vol. 12(2), pages 1-56, March.
    49. Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    50. Kang, Wensheng & de Gracia, Fernando Perez & Ratti, Ronald A., 2019. "The asymmetric response of gasoline prices to oil price shocks and policy uncertainty," Energy Economics, Elsevier, vol. 77(C), pages 66-79.
    51. Beatrice D. Simo-Kengne & Kofi Agyarko Ababio & Jules Mba & Ur Koumba & Makgale Molepo, 2018. "Risk, Uncertainty and Exchange Rate Behavior in South Africa," Journal of African Business, Taylor & Francis Journals, vol. 19(2), pages 262-278, April.
    52. Wang, Yuejing & Ye, Wuyi & Jiang, Ying & Liu, Xiaoquan, 2024. "Volatility prediction for the energy sector with economic determinants: Evidence from a hybrid model," International Review of Financial Analysis, Elsevier, vol. 92(C).
    53. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    54. Nonejad, Nima, 2021. "Predicting the return on the spot price of crude oil out-of-sample by conditioning on news-based uncertainty measures: Some new empirical results," Energy Economics, Elsevier, vol. 104(C).
    55. Fan, Liwei & Pan, Sijia & Li, Zimin & Li, Huiping, 2016. "An ICA-based support vector regression scheme for forecasting crude oil prices," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 245-253.
    56. Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.
    57. Dutta, Anupam & Soytas, Ugur & Das, Debojyoti & Bhattacharyya, Asit, 2022. "In search of time-varying jumps during the turmoil periods: Evidence from crude oil futures markets," Energy Economics, Elsevier, vol. 114(C).

  16. Stelios D. Bekiros & Alessia Paccagnini, 2015. "Macroprudential policy and forecasting using Hybrid DSGE models with financial frictions and State space Markov-Switching TVP-VARs," Open Access publications 10197/7333, School of Economics, University College Dublin.

    Cited by:

    1. Stelios D. Bekiros & Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2016. "Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a predictability analysis versus TVP-VARs," Open Access publications 10197/7323, School of Economics, University College Dublin.
    2. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    3. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    4. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017. "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 109-121, March.
    5. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2018. "Limited Asset Market Participation and the Euro Area Crisis. An Empirical DSGE Model," Working Papers 391, University of Milano-Bicocca, Department of Economics, revised Nov 2018.
    6. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    7. Villa, Stefania, 2016. "Financial Frictions In The Euro Area And The United States: A Bayesian Assessment," Macroeconomic Dynamics, Cambridge University Press, vol. 20(5), pages 1313-1340, July.
    8. Franz Ramsauer & Aleksey Min & Michael Lingauer, 2019. "Estimation of FAVAR Models for Incomplete Data with a Kalman Filter for Factors with Observable Components," Econometrics, MDPI, vol. 7(3), pages 1-43, July.
    9. Bekiros, Stelios & Gupta, Rangan & Paccagnini, Alessia, 2015. "Oil price forecastability and economic uncertainty," Economics Letters, Elsevier, vol. 132(C), pages 125-128.
    10. Jang, Tae-Seok & Sacht, Stephen, 2021. "Forecast heuristics, consumer expectations, and New-Keynesian macroeconomics: A Horse race," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 493-511.
    11. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2014. "Estimating a DSGE model with Limited Asset Market Participation for the Euro Area," Working Papers 286, University of Milano-Bicocca, Department of Economics, revised Nov 2014.

  17. Rangan Gupta & Patrick T. Kanda & Mampho P. Modise & Alessia Paccagnini, 2015. "DSGE model-based forecasting of modelled and nonmodelled inflation variables in South Africa," Open Access publications 10197/7351, School of Economics, University College Dublin.

    Cited by:

    1. Gupta, Rangan & Kotzé, Kevin, 2017. "The role of oil prices in the forecasts of South African interest rates: A Bayesian approach," Energy Economics, Elsevier, vol. 61(C), pages 270-278.
    2. Franz Ruch & Mehmet Balcilar Author-Name-First Mehmet & Mampho P. Modise & Rangan Gupta, 2015. "Forecasting Core Inflation: The Case of South Africa," Working Papers 15-08, Eastern Mediterranean University, Department of Economics.
    3. Byron J. Idrovo-Aguirre & Javier E. Contreras-Reyes, 2019. "Backcasting cement production and characterizing cement’s economic cycles for Chile 1991–2015," Empirical Economics, Springer, vol. 57(5), pages 1829-1852, November.
    4. Idrovo Aguirre, Byron & Contreras, Javier, 2015. "Back-splicing of cement production and characterization of its economic cycle: The case of Chile (1991-2015)," MPRA Paper 67387, University Library of Munich, Germany, revised 20 Sep 2015.

  18. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2015. "Forecasting in a DSGE Model with Banking Intermediation: Evidence from the US," Working Papers 292, University of Milano-Bicocca, Department of Economics, revised Feb 2015.

    Cited by:

    1. Stelios D. Bekiros & Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2016. "Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a predictability analysis versus TVP-VARs," Open Access publications 10197/7323, School of Economics, University College Dublin.
    2. Galvão, Ana Beatriz & Giraitis, Liudas & Kapetanios, George & Petrova, Katerina, 2016. "A time varying DSGE model with financial frictions," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 690-716.
    3. Bekiros, Stelios D.; Cardani, Roberta; Paccagnini, Alessia; Villa, Stefania, 2015. "Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a forecastability analysis versus TVP-VARs," Economics Working Papers ECO2015/04, European University Institute.
    4. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    6. Stefan Gebauer, 2017. "The Use of Financial Market Variables in Forecasting," DIW Roundup: Politik im Fokus 115, DIW Berlin, German Institute for Economic Research.

  19. Riccardo M. Masolo & Alessia Paccagnini, 2015. "Identifying Noise Shocks: a VAR with Data Revisions," Discussion Papers 1510, Centre for Macroeconomics (CFM).

    Cited by:

    1. Dées, Stephane & Zimic, Srečko, 2019. "Animal spirits, fundamental factors and business cycle fluctuations," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    2. Kenza Benhima & Céline Poilly, 2017. "Do Misperceptions about Demand Matter? Theory and Evidence," Working Papers halshs-01518467, HAL.
    3. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.

  20. Stelios D. Bekiros & Alessia Paccagnini, 2014. "Policy-oriented macroeconomic forecasting with hybrid DGSE and time-varying parameter VAR models," Working Papers 2014-426, Department of Research, Ipag Business School.

    Cited by:

    1. Roberta Cardani & Alessia Paccagnini & Stelios D. Bekiros, 2017. "The Effectiveness of Forward Guidance in an Estimated DSGE Model for the Euro Area: the Role of Expectations," Working Papers 201701, School of Economics, University College Dublin.
    2. Tsai, I-Chun & Chen, Han-Bo & Lin, Che-Chun, 2024. "The ability of energy commodities to hedge the dynamic risk of epidemic black swans," Resources Policy, Elsevier, vol. 89(C).
    3. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. César Castro & Rebeca Jiménez-Rodríguez & Pilar Poncela & Eva Senra, 2017. "A new look at oil price pass-through into inflation: evidence from disaggregated European data," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 34(1), pages 55-82, April.
    5. Lai, Hung-Cheng & Wang, Kuan-Min, 2014. "Relationship between the trading behavior of three institutional investors and Taiwan Stock Index futures returns," Economic Modelling, Elsevier, vol. 41(C), pages 156-165.

  21. Stelios D. Bekiros & Alessia Paccagnini, 2014. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Open Access publications 10197/7588, School of Economics, University College Dublin.

    Cited by:

    1. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    2. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    4. Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.

  22. Stelios D. Bekiros & Alessia Paccagnini, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Open Access publications 10197/7322, School of Economics, University College Dublin.

    Cited by:

    1. Emmanuel C. Mamatzakis & Mike G. Tsionas, 2020. "Revealing forecaster's preferences: A Bayesian multivariate loss function approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 412-437, April.
    2. Babecký, Jan & Franta, Michal & Ryšánek, Jakub, 2018. "Fiscal policy within the DSGE-VAR framework," Economic Modelling, Elsevier, vol. 75(C), pages 23-37.
    3. Roberta Cardani & Alessia Paccagnini & Stelios D. Bekiros, 2017. "The Effectiveness of Forward Guidance in an Estimated DSGE Model for the Euro Area: the Role of Expectations," Working Papers 201701, School of Economics, University College Dublin.
    4. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    5. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    6. Sofiane Aboura & Julien Chevallier, 2015. "Cross-market volatility index with Factor-DCC," Post-Print halshs-01348723, HAL.
    7. Chin, Kuo-Hsuan & Li, Xue, 2019. "Bayesian forecast combination in VAR-DSGE models," Journal of Macroeconomics, Elsevier, vol. 59(C), pages 278-298.
    8. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2018. "Limited Asset Market Participation and the Euro Area Crisis. An Empirical DSGE Model," Working Papers 391, University of Milano-Bicocca, Department of Economics, revised Nov 2018.
    9. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    10. Villa, Stefania, 2016. "Financial Frictions In The Euro Area And The United States: A Bayesian Assessment," Macroeconomic Dynamics, Cambridge University Press, vol. 20(5), pages 1313-1340, July.
    11. Franz Ramsauer & Aleksey Min & Michael Lingauer, 2019. "Estimation of FAVAR Models for Incomplete Data with a Kalman Filter for Factors with Observable Components," Econometrics, MDPI, vol. 7(3), pages 1-43, July.
    12. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.
    13. Jang, Tae-Seok & Sacht, Stephen, 2021. "Forecast heuristics, consumer expectations, and New-Keynesian macroeconomics: A Horse race," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 493-511.
    14. Marco Lorusso & Luca Pieroni, 2019. "Disentangling Civilian and Military Spending Shocks: A Bayesian DSGE Approach for the US Economy," JRFM, MDPI, vol. 12(3), pages 1-41, September.
    15. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2014. "Estimating a DSGE model with Limited Asset Market Participation for the Euro Area," Working Papers 286, University of Milano-Bicocca, Department of Economics, revised Nov 2014.

  23. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2014. "Estimating a DSGE model with Limited Asset Market Participation for the Euro Area," Working Papers 286, University of Milano-Bicocca, Department of Economics, revised Nov 2014.

    Cited by:

    1. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2016. "In search of the Euro area fiscal stance," Working Papers 201612, School of Economics, University College Dublin.
    2. Albonico, Alice & Paccagnini, Alessia & Tirelli, Patrizio, 2017. "Great recession, slow recovery and muted fiscal policies in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 81(C), pages 140-161.
    3. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2018. "Limited Asset Market Participation and the Euro Area Crisis. An Empirical DSGE Model," Working Papers 391, University of Milano-Bicocca, Department of Economics, revised Nov 2018.
    4. Roman Horvath & Lorant Kaszab & Ales Marsal, 2020. "Equity Premium and Monetary Policy in a Model with Limited Asset Market Participation," MNB Working Papers 2020/3, Magyar Nemzeti Bank (Central Bank of Hungary).
    5. Alice, Albonico & Roberta, Cardani & Patrizio, Tirelli, 2017. "Debunking the Myth of Southern Profligacy. A DSGE Analysis of Business Cycles in the EMU’s Big Four," Working Papers 373, University of Milano-Bicocca, Department of Economics, revised Jan 2018.
    6. Alice, Albonico & Lorenza, Rossi, 2017. "Inflation bias and markup shocks in a LAMP model with strategic interaction of monetary and fiscal policy," Working Papers 362, University of Milano-Bicocca, Department of Economics, revised 14 Feb 2017.
    7. Ferrara, Maria & Tirelli, Patrizio, 2017. "Equitable fiscal consolidations," Economic Modelling, Elsevier, vol. 61(C), pages 207-223.
    8. Piergallini, Alessandro, 2017. "Fiscal policy and liquidity traps with heterogeneous agents," Economics Letters, Elsevier, vol. 157(C), pages 103-106.

  24. Alessia Paccagnini, 2014. "The Macroeconomic Determinants of the US Term-Structure during the Great Moderation," Working Papers 274, University of Milano-Bicocca, Department of Economics, revised Jun 2014.

    Cited by:

    1. Almeida, Thiago Ramos, 2024. "Estimating time-varying factors’ variance in the string-term structure model with stochastic volatility," Research in International Business and Finance, Elsevier, vol. 70(PA).
    2. Moreno, Manuel & Novales, Alfonso & Platania, Federico, 2018. "A term structure model under cyclical fluctuations in interest rates," Economic Modelling, Elsevier, vol. 72(C), pages 140-150.
    3. Akram, Tanweer & Li, Huiqing, 2017. "What keeps long-term U.S. interest rates so low?," Economic Modelling, Elsevier, vol. 60(C), pages 380-390.
    4. Shang, Yuhuang & Zheng, Tingguo, 2018. "Fitting and forecasting yield curves with a mixed-frequency affine model: Evidence from China," Economic Modelling, Elsevier, vol. 68(C), pages 145-154.
    5. Tanweer Akram & Huiqing Li, 2020. "The Empirics of UK Gilts' Yields," Economics Working Paper Archive wp_969, Levy Economics Institute.
    6. Oguzhan Cepni & Ibrahim Ethem Guney & Doruk Kucuksarac & Muhammed Hasan Yilmaz, 2020. "Do Local and Global Factors Impact the Emerging Markets’s Sovereign Yield Curves? Evidence from a Data-Rich Environment," Working Papers 2004, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    7. Anupam Das & Tanweer Akram, 2020. "A Keynesian analysis of Canadian government securities yields," PSL Quarterly Review, Economia civile, vol. 73(294), pages 241-260.
    8. Tanweer Akram & Huiqing Li, 2018. "The Dynamics of Japanese Government Bonds' Nominal Yields," Economics Working Paper Archive wp_906, Levy Economics Institute.
    9. Tanweer Akram & Huiqing Li, 2020. "Some Empirical Models of Japanese Government Bond Yields Using Daily Data," Economics Working Paper Archive wp_962, Levy Economics Institute.
    10. Polat, Onur & Ozkan, Ibrahim, 2019. "Transmission mechanisms of financial stress into economic activity in Turkey," Journal of Policy Modeling, Elsevier, vol. 41(2), pages 395-415.

  25. Stelios Bekiros & Alessia Paccagnini, 2014. "Forecasting the US Economy with a Factor-Augmented Vector Autoregressive DSGE model," Working Papers 2014-183, Department of Research, Ipag Business School.

    Cited by:

  26. Stelios D. Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Open Access publications 10197/7326, School of Economics, University College Dublin.

    Cited by:

    1. Stelios D. Bekiros & Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2016. "Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a predictability analysis versus TVP-VARs," Open Access publications 10197/7323, School of Economics, University College Dublin.
    2. 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.
    3. Babecký, Jan & Franta, Michal & Ryšánek, Jakub, 2018. "Fiscal policy within the DSGE-VAR framework," Economic Modelling, Elsevier, vol. 75(C), pages 23-37.
    4. Balcilar, Mehmet & Gupta, Rangan & Segnon, Mawuli, 2016. "The role of economic policy uncertainty in predicting U.S. recessions: A mixed-frequency Markov-switching vector autoregressive approach," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-20.
    5. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    6. Bekiros, Stelios D. & Paccagnini, Alessia, 2015. "Macroprudential Policy And Forecasting Using Hybrid Dsge Models With Financial Frictions And State Space Markov-Switching Tvp-Vars," Macroeconomic Dynamics, Cambridge University Press, vol. 19(7), pages 1565-1592, October.
    7. Maddalena Cavicchioli, 2020. "Invertibility and VAR Representations of Time-Varying Dynamic Stochastic General Equilibrium Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 61-86, January.
    8. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    9. Alessia Paccagnini, 2012. "Comparing Hybrid DSGE Models," Working Papers 228, University of Milano-Bicocca, Department of Economics, revised Dec 2012.
    10. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017. "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 109-121, March.
    11. Xiuying Ma & Yongjing Wang & Haiyan Song & Han Liu, 2020. "Time-varying mechanisms between foreign direct investment and tourism development under the new normal in China," Tourism Economics, , vol. 26(2), pages 324-343, March.
    12. David Hudgins & Patrick M. Crowley, 2019. "Stress-Testing U.S. Macroeconomic Policy: A Computational Approach Using Stochastic and Robust Designs in a Wavelet-Based Optimal Control Framework," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1509-1546, April.
    13. 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.
    14. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    15. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2015. "Forecasting in a DSGE Model with Banking Intermediation: Evidence from the US," Working Papers 292, University of Milano-Bicocca, Department of Economics, revised Feb 2015.

  27. Rangan Gupta & Patrick Kanda & Mampho Modise & Alessia Paccagnini, 2013. "DGSE Model-Based Forecasting of Modeled and Non-Modeled Inflation Variables in South Africa," Working Papers 259, University of Milano-Bicocca, Department of Economics, revised Nov 2013.

    Cited by:

    1. Gupta, Rangan & Kotzé, Kevin, 2017. "The role of oil prices in the forecasts of South African interest rates: A Bayesian approach," Energy Economics, Elsevier, vol. 61(C), pages 270-278.
    2. Franz Ruch & Mehmet Balcilar Author-Name-First Mehmet & Mampho P. Modise & Rangan Gupta, 2015. "Forecasting Core Inflation: The Case of South Africa," Working Papers 15-08, Eastern Mediterranean University, Department of Economics.
    3. Byron J. Idrovo-Aguirre & Javier E. Contreras-Reyes, 2019. "Backcasting cement production and characterizing cement’s economic cycles for Chile 1991–2015," Empirical Economics, Springer, vol. 57(5), pages 1829-1852, November.
    4. Idrovo Aguirre, Byron & Contreras, Javier, 2015. "Back-splicing of cement production and characterization of its economic cycle: The case of Chile (1991-2015)," MPRA Paper 67387, University Library of Munich, Germany, revised 20 Sep 2015.

  28. Marcella Nicolini & Alessia Paccagnini, 2011. "Does Trade Foster Institutions?," Open Access publications 10197/7587, School of Economics, University College Dublin.

    Cited by:

    1. Krenz, Astrid & Abeliansky, Ana, 2016. "Democracy and International Trade: Differential Effects from a Panel Quantile Regression Framework," VfS Annual Conference 2016 (Augsburg): Demographic Change 145788, Verein für Socialpolitik / German Economic Association.
    2. Ion MUȘCHEI, 2022. "The Causal Relationship Between Institution And Trade. Evidence From The Republic Of Moldova - The European Union," EURINT, Centre for European Studies, Alexandru Ioan Cuza University, vol. 9, pages 182-201, December.
    3. Yanjun Ma & Churen Sun, 2023. "Trade liberalization, institutional quality, and social trust of Chinese residents," Empirical Economics, Springer, vol. 65(3), pages 1453-1486, September.
    4. Gandjon Fankem, Gislain Stéphane & Feyom, Cédric, 2024. "Does trade openness improve or worsen public governance in sub-Saharan Africa?," International Economics, Elsevier, vol. 178(C).
    5. Krenz, Astrid, 2016. "Do political institutions influence international trade? Measurement of institutions and the Long-Run effects," University of Göttingen Working Papers in Economics 276, University of Goettingen, Department of Economics.
    6. Bergh, Andreas & Mirkina, Irina & Nilsson, Therese, 2013. "More Open – Better Governed? Evidence from High- and Low-income Countries," Working Paper Series 997, Research Institute of Industrial Economics.
    7. Law, Siong Hook & Lim, Thong Cheen & Ismail, Normaz Wana, 2013. "Institutions and economic development: A Granger causality analysis of panel data evidence," Economic Systems, Elsevier, vol. 37(4), pages 610-624.
    8. Khalid, Usman, 2015. "Why Trading with Dictators May Nevertheless Help the People: On the Interplay between Trade, Political Regimes and Economic Institutions," Working Papers 2015:15, Lund University, Department of Economics, revised 23 Jul 2015.
    9. Moon Jung Choi & Kee Hoon Chung, 2022. "Trade patterns and institutional change in East Asia," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 30(3), pages 567-595, July.
    10. Marcella Nicolini & Alessia Paccagnini, 2011. "Does Trade Foster Institutions? An Empirical Assessment," Open Access publications 10197/7585, School of Economics, University College Dublin.
    11. Astrid Krenz & Ana Abeliansky, 2015. "Democracy and Trade—Evidence along the Distribution of Trading Activity," EcoMod2015 8750, EcoMod.
    12. Saad, Ayhab F., 2021. "Institutional change in the global economy: How trade reform can be detrimental to welfare," Economic Modelling, Elsevier, vol. 95(C), pages 97-110.

  29. Marcella Nicolini & Alessia Paccagnini, 2011. "Does Trade Foster Institutions? An Empirical Assessment," Open Access publications 10197/7585, School of Economics, University College Dublin.

    Cited by:

    1. Krenz, Astrid & Abeliansky, Ana, 2016. "Democracy and International Trade: Differential Effects from a Panel Quantile Regression Framework," VfS Annual Conference 2016 (Augsburg): Demographic Change 145788, Verein für Socialpolitik / German Economic Association.
    2. Yanjun Ma & Churen Sun, 2023. "Trade liberalization, institutional quality, and social trust of Chinese residents," Empirical Economics, Springer, vol. 65(3), pages 1453-1486, September.
    3. Gandjon Fankem, Gislain Stéphane & Feyom, Cédric, 2024. "Does trade openness improve or worsen public governance in sub-Saharan Africa?," International Economics, Elsevier, vol. 178(C).
    4. Krenz, Astrid, 2016. "Do political institutions influence international trade? Measurement of institutions and the Long-Run effects," University of Göttingen Working Papers in Economics 276, University of Goettingen, Department of Economics.
    5. Law, Siong Hook & Lim, Thong Cheen & Ismail, Normaz Wana, 2013. "Institutions and economic development: A Granger causality analysis of panel data evidence," Economic Systems, Elsevier, vol. 37(4), pages 610-624.
    6. Khalid, Usman, 2015. "Why Trading with Dictators May Nevertheless Help the People: On the Interplay between Trade, Political Regimes and Economic Institutions," Working Papers 2015:15, Lund University, Department of Economics, revised 23 Jul 2015.
    7. Moon Jung Choi & Kee Hoon Chung, 2022. "Trade patterns and institutional change in East Asia," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 30(3), pages 567-595, July.
    8. Astrid Krenz & Ana Abeliansky, 2015. "Democracy and Trade—Evidence along the Distribution of Trading Activity," EcoMod2015 8750, EcoMod.
    9. Saad, Ayhab F., 2021. "Institutional change in the global economy: How trade reform can be detrimental to welfare," Economic Modelling, Elsevier, vol. 95(C), pages 97-110.

  30. Paccagnini, Alessia, 2010. "DSGE Model Validation in a Bayesian Framework: an Assessment," MPRA Paper 24509, University Library of Munich, Germany.

    Cited by:

    1. Roberta Cardani & Alessia Paccagnini & Stelios D. Bekiros, 2017. "The Effectiveness of Forward Guidance in an Estimated DSGE Model for the Euro Area: the Role of Expectations," Working Papers 201701, School of Economics, University College Dublin.
    2. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2019. "Validation of Agent-Based Models in Economics and Finance," Post-Print halshs-02375423, HAL.

  31. Favero, Carlo A. & Consolo, Agostino & Paccagnini, Alessia, 2009. "On the Statistical Identification of DSGE Models," CEPR Discussion Papers 7176, C.E.P.R. Discussion Papers.

    Cited by:

    1. Evren Caglar & Jagjit S. Chadha & Katsuyuki Shibayama, 2011. "Bayesian Estimation of DSGE models: Is the Workhorse Model Identified?," Studies in Economics 1125, School of Economics, University of Kent.
    2. Giovanni Angelini & Luca Fanelli Fanelli, 2015. "Misspecification and Expectations Correction in New Keynesian DSGE Models," Quaderni di Dipartimento 1, Department of Statistics, University of Bologna.
    3. Stelios D. Bekiros & Alessia Paccagnini, 2014. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Open Access publications 10197/7588, School of Economics, University College Dublin.
    4. 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.
    5. Carlo A. Favero, 2007. "The Econometrics of Monetary Policy: an Overview," Working Papers 329, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    6. Dufour, Jean-Marie & Khalaf, Lynda & Kichian, Maral, 2010. "On the precision of Calvo parameter estimates in structural NKPC models," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1582-1595, September.
    7. Rangan Gupta & Patrick T. Kanda & Mampho P. Modise & Alessia Paccagnini, 2015. "DSGE model-based forecasting of modelled and nonmodelled inflation variables in South Africa," Applied Economics, Taylor & Francis Journals, vol. 47(3), pages 207-221, January.
    8. Bekiros, Stelios D. & Paccagnini, Alessia, 2015. "Macroprudential Policy And Forecasting Using Hybrid Dsge Models With Financial Frictions And State Space Markov-Switching Tvp-Vars," Macroeconomic Dynamics, Cambridge University Press, vol. 19(7), pages 1565-1592, October.
    9. Zhijian Wang & Bin Xu, 2014. "Cycling in stochastic general equilibrium," Papers 1410.8432, arXiv.org.
    10. Maddalena Cavicchioli, 2020. "Invertibility and VAR Representations of Time-Varying Dynamic Stochastic General Equilibrium Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 61-86, January.
    11. Van Nguyen, Phuong, 2020. "Evaluating the forecasting accuracy of the closed- and open economy New Keynesian DSGE models," Dynare Working Papers 59, CEPREMAP.
    12. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Ratto, Marco, 2018. "Identification Versus Misspecification in New Keynesian Monetary Policy Models," Working Paper Series 362, Sveriges Riksbank (Central Bank of Sweden).
    13. Alessia Paccagnini, 2012. "Comparing Hybrid DSGE Models," Working Papers 228, University of Milano-Bicocca, Department of Economics, revised Dec 2012.
    14. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2018. "Limited Asset Market Participation and the Euro Area Crisis. An Empirical DSGE Model," Working Papers 391, University of Milano-Bicocca, Department of Economics, revised Nov 2018.
    15. Stelios Bekiros & Alessia Paccagnini, 2013. "Policy-oriented macroeconomic forecasting with hybrid DGSE and time-varying parameter VAR models," Working Papers 236, University of Milano-Bicocca, Department of Economics, revised Feb 2013.
    16. Dufour, Jean-Marie & Khalaf, Lynda & Kichian, Maral, 2013. "Identification-robust analysis of DSGE and structural macroeconomic models," Journal of Monetary Economics, Elsevier, vol. 60(3), pages 340-350.
    17. Reicher, Christopher Phillip, 2013. "A note on the identification of dynamic economic models with generalized shock processes," Kiel Working Papers 1821, Kiel Institute for the World Economy (IfW Kiel).
    18. Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Post-Print hal-02332090, HAL.
    19. Marcellino, Massimiliano & Kapetanios, George & Khalaf, Lynda, 2015. "Factor based identification-robust inference in IV regressions," CEPR Discussion Papers 10390, C.E.P.R. Discussion Papers.
    20. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    21. Angelini, Giovanni, 2020. "Bootstrap lag selection in DSGE models with expectations correction," Econometrics and Statistics, Elsevier, vol. 14(C), pages 38-48.
    22. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers CWP21/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Rangan Gupta & Patrick Kanda & Mampho Modise & Alessia Paccagnini, 2013. "DGSE Model-Based Forecasting of Modeled and Non-Modeled Inflation Variables in South Africa," Working Papers 259, University of Milano-Bicocca, Department of Economics, revised Nov 2013.
    24. 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.
    25. Muhammad Ali Nasir & Milton Yago & Alaa M. Soliman & Junjie Wu, 2016. "Financial stability, wealth effects and optimal macroeconomic policy combination in the United Kingdom: A new-Keynesian dynamic stochastic general equilibrium framework," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1136098-113, December.
    26. Stelios Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Empirical Economics, Springer, vol. 45(1), pages 635-664, August.
    27. Stelios D. Bekiros & Alessia Paccagnini, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Open Access publications 10197/7322, School of Economics, University College Dublin.
    28. Chunyeung Kwok, 2022. "Estimating Structural Shocks with the GVAR-DSGE Model: Pre- and Post-Pandemic," Mathematics, MDPI, vol. 10(10), pages 1-32, May.
    29. Muhammad Ali Nasir & Junjie Wu & Milton Yago & Alaa M. Soliman, 2016. "Macroeconomic policy interaction: State dependency and implications for financial stability in UK: A systemic review," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1154283-115, December.
    30. Paccagnini, Alessia, 2010. "DSGE Model Validation in a Bayesian Framework: an Assessment," MPRA Paper 24509, University Library of Munich, Germany.
    31. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
    32. Zhongjun Qu & Denis Tkachenko, 2010. "Identification and Frequency Domain QML Estimation of Linearized DSGE Models," Boston University - Department of Economics - Working Papers Series WP2010-053, Boston University - Department of Economics.
    33. Claire A. Reicher, 2016. "A Note on the Identification of Dynamic Economic Models with Generalized Shock Processes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(3), pages 412-423, June.
    34. Iiboshi, Hirokuni, 2016. "A multiple DSGE-VAR approach: Priors from a combination of DSGE models and evidence from Japan," Japan and the World Economy, Elsevier, vol. 40(C), pages 1-8.

Articles

  1. Coroneo, Laura & Iacone, Fabrizio & Paccagnini, Alessia & Santos Monteiro, Paulo, 2023. "Testing the predictive accuracy of COVID-19 forecasts," International Journal of Forecasting, Elsevier, vol. 39(2), pages 606-622.
    See citations under working paper version above.
  2. Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2022. "Common factors and the dynamics of cereal prices. A forecasting perspective," Journal of Commodity Markets, Elsevier, vol. 28(C).
    See citations under working paper version above.
  3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    See citations under working paper version above.
  4. Kwas, Marek & Paccagnini, Alessia & Rubaszek, Michał, 2021. "Common factors and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 74(C).

    Cited by:

    1. Arabinda Basistha & Richard Startz, 2023. "Measuring Persistent Global Economic Factors with Output, Commodity Price, and Commodity Currency Data," Working Papers 23-05, Department of Economics, West Virginia University.
    2. Henriques, Irene & Sadorsky, Perry, 2023. "Forecasting rare earth stock prices with machine learning," Resources Policy, Elsevier, vol. 86(PA).
    3. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
    4. Choi, Insu & Kim, Woo Chang, 2024. "Practical forecasting of risk boundaries for industrial metals and critical minerals via statistical machine learning techniques," International Review of Financial Analysis, Elsevier, vol. 94(C).
    5. He, Zhichao & Huang, Jianhua, 2023. "A novel non-ferrous metal price hybrid forecasting model based on data preprocessing and error correction," Resources Policy, Elsevier, vol. 86(PB).
    6. Luo, Hongyuan & Wang, Deyun & Cheng, Jinhua & Wu, Qiaosheng, 2022. "Multi-step-ahead copper price forecasting using a two-phase architecture based on an improved LSTM with novel input strategy and error correction," Resources Policy, Elsevier, vol. 79(C).
    7. Liu, Yanqiong & Guo, Yaoqi & Wei, Qing, 2024. "Time-varying and multi-scale analysis of copper price influencing factors based on LASSO and EMD methods," Journal of Commodity Markets, Elsevier, vol. 34(C).

  5. Colombo, Valentina & Paccagnini, Alessia, 2020. "Does the credit supply shock have asymmetric effects on macroeconomic variables?," Economics Letters, Elsevier, vol. 188(C).

    Cited by:

    1. Feng Min & Fenghua Wen & Jiayu Xu & Nan Wu, 2023. "Credit supply, house prices, and financial stability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2088-2108, April.
    2. David Finck & Paul Rudel, 2020. "Do Credit Supply Shocks Have Asymmetric Effects?," MAGKS Papers on Economics 202026, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. David Finck & Paul Rudel, 2023. "Do credit supply shocks have asymmetric effects?," Empirical Economics, Springer, vol. 64(4), pages 1559-1597, April.
    4. Philipp Meinen & Ana Cristina Soares, 2022. "Markups and Financial Shocks," The Economic Journal, Royal Economic Society, vol. 132(647), pages 2471-2499.
    5. Ozili, Peterson K & Oladipo, Olajide & Iorember, Paul, 2023. "Effect of abnormal increase in credit supply on economic growth in Nigeria," MPRA Paper 115988, University Library of Munich, Germany.
    6. Helmut Herwartz & Christian Ochsner & Hannes Rohloff, 2021. "Global Credit Shocks and Real Economies," MAGKS Papers on Economics 202116, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    7. Puch González, Luis Antonio & Ruiz, Jesús, 2024. "The asymmetry puzzle: the supply chain disruptions news shocks effects on oil prices and inflation," UC3M Working papers. Economics 43758, Universidad Carlos III de Madrid. Departamento de Economía.

  6. Riccardo M. Masolo & Alessia Paccagnini, 2019. "Identifying Noise Shocks: A VAR with Data Revisions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(8), pages 2145-2172, December.
    See citations under working paper version above.
  7. Cardani, Roberta & Paccagnini, Alessia & Villa, Stefania, 2019. "Forecasting with instabilities: An application to DSGE models with financial frictions," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    See citations under working paper version above.
  8. Alice Albonico & Alessia Paccagnini & Patrizio Tirelli, 2019. "Limited Asset Market Participation And The Euro Area Crisis: An Empirical Dsge Model," Economic Inquiry, Western Economic Association International, vol. 57(3), pages 1302-1323, July.
    See citations under working paper version above.
  9. Paccagnini, Alessia, 2019. "Did financial factors matter during the Great Recession?," Economics Letters, Elsevier, vol. 174(C), pages 26-30.

    Cited by:

    1. Donato Ceci & Andrea Silvestrini, 2023. "Nowcasting the state of the Italian economy: The role of financial markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1569-1593, November.
    2. Bas Scheer, 2022. "Addressing Unemployment Rate Forecast Errors in Relation to the Business Cycle," CPB Discussion Paper 434, CPB Netherlands Bureau for Economic Policy Analysis.
    3. Claire Giordano & Marco Marinucci & Andrea Silvestrini, 2022. "Assessing the usefulness of survey‐based data in forecasting firms' capital formation: Evidence from Italy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 491-513, April.
    4. Claire Giordano & Marco Marinucci & Andrea Silvestrini, 2021. "Forecasting corporate capital accumulation in Italy: the role of survey-based information," Questioni di Economia e Finanza (Occasional Papers) 596, Bank of Italy, Economic Research and International Relations Area.
    5. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    6. Kumar, Ankit & Dash, Pradyumna, 2020. "Changing transmission of monetary policy on disaggregate inflation in India," Economic Modelling, Elsevier, vol. 92(C), pages 109-125.

  10. Albonico, Alice & Paccagnini, Alessia & Tirelli, Patrizio, 2017. "Great recession, slow recovery and muted fiscal policies in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 81(C), pages 140-161.
    See citations under working paper version above.
  11. Stelios D. Bekiros & Alessia Paccagnini, 2016. "Policy‐Oriented Macroeconomic Forecasting with Hybrid DGSE and Time‐Varying Parameter VAR Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(7), pages 613-632, November.
    See citations under working paper version above.
  12. Bekiros, Stelios & Cardani, Roberta & Paccagnini, Alessia & Villa, Stefania, 2016. "Dealing with financial instability under a DSGE modeling approach with banking intermediation: A predictability analysis versus TVP-VARs," Journal of Financial Stability, Elsevier, vol. 26(C), pages 216-227.
    See citations under working paper version above.
  13. Paccagnini, Alessia, 2016. "The macroeconomic determinants of the US term structure during the Great Moderation," Economic Modelling, Elsevier, vol. 52(PA), pages 216-225.
    See citations under working paper version above.
  14. Albonico, Alice & Paccagnini, Alessia & Tirelli, Patrizio, 2016. "In search of the Euro area fiscal stance," Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 254-264.
    See citations under working paper version above.
  15. Bekiros, Stelios & Gupta, Rangan & Paccagnini, Alessia, 2015. "Oil price forecastability and economic uncertainty," Economics Letters, Elsevier, vol. 132(C), pages 125-128.
    See citations under working paper version above.
  16. Bekiros Stelios & Paccagnini Alessia, 2015. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 107-136, April.
    See citations under working paper version above.
  17. Rangan Gupta & Patrick T. Kanda & Mampho P. Modise & Alessia Paccagnini, 2015. "DSGE model-based forecasting of modelled and nonmodelled inflation variables in South Africa," Applied Economics, Taylor & Francis Journals, vol. 47(3), pages 207-221, January.
    See citations under working paper version above.
  18. Bekiros, Stelios D. & Paccagnini, Alessia, 2015. "Macroprudential Policy And Forecasting Using Hybrid Dsge Models With Financial Frictions And State Space Markov-Switching Tvp-Vars," Macroeconomic Dynamics, Cambridge University Press, vol. 19(7), pages 1565-1592, October.
    See citations under working paper version above.
  19. Bekiros, Stelios D. & Paccagnini, Alessia, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 298-323.
    See citations under working paper version above.
  20. Stelios Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Empirical Economics, Springer, vol. 45(1), pages 635-664, August.
    See citations under working paper version above.
  21. Marcella Nicolini & Alessia Paccagnini, 2011. "Does Trade Foster Institutions? An Empirical Assessment," Review of Economics and Institutions, Università di Perugia, vol. 2(2).
    See citations under working paper version above.
  22. Consolo, Agostino & Favero, Carlo A. & Paccagnini, Alessia, 2009. "On the statistical identification of DSGE models," Journal of Econometrics, Elsevier, vol. 150(1), pages 99-115, May.
    See citations under working paper version above.
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