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António Rua
(Antonio Rua)

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.

Working papers

  1. António Rua & Hossein Hassani, 2019. "Monthly Forecasting of GDP with Mixed Frequency Multivariate Singular Spectrum Analysis," Working Papers w201913, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Galdi, Giulio & Casarin, Roberto & Ferrari, Davide & Fezzi, Carlo & Ravazzolo, Francesco, 2023. "Nowcasting industrial production using linear and non-linear models of electricity demand," Energy Economics, Elsevier, vol. 126(C).
    2. Mohammad Reza Yeganegi & Hossein Hassani & Rangan Gupta, 2023. "The ENSO cycle and forecastability of global inflation and output growth: Evidence from standard and mixed‐frequency multivariate singular spectrum analyses," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1690-1707, November.
    3. Bai, Yun & Deng, Shuyun & Pu, Ziqiang & Li, Chuan, 2024. "Carbon price forecasting using leaky integrator echo state networks with the framework of decomposition-reconstruction-integration," Energy, Elsevier, vol. 305(C).
    4. Mahdi Kalantari & Hossein Hassani, 2019. "Automatic Grouping in Singular Spectrum Analysis," Forecasting, MDPI, vol. 1(1), pages 1-16, October.
    5. Qifa Xu & Zezhou Wang & Cuixia Jiang & Yezheng Liu, 2023. "Deep learning on mixed frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2099-2120, December.
    6. Hossein Hassani & Mohammad Reza Yeganegi & Xu Huang, 2021. "Fusing Nature with Computational Science for Optimal Signal Extraction," Stats, MDPI, vol. 4(1), pages 1-15, January.
    7. Yang, Wendong & Zang, Xinyi & Wu, Chunying & Hao, Yan, 2024. "A new multi-objective ensemble wind speed forecasting system: Mixed-frequency interval-valued modeling paradigm," Energy, Elsevier, vol. 304(C).
    8. Kalantari, Mahdi, 2021. "Forecasting COVID-19 pandemic using optimal singular spectrum analysis," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).

  2. António Rua, 2019. "Modelling the Demand for Euro Banknotes," Working Papers w201905, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Hans-Eggert Reimers & Friedrich Schneider & Franz Seitz, 2020. "Payment Innovations, the Shadow Economy and Cash Demand of Households in Euro Area Countries," CESifo Working Paper Series 8574, CESifo.

  3. Paulo Soares Esteves & Miguel Portela & António Rua, 2018. "Does domestic demand matter for firms’ exports?," NIPE Working Papers 18/2018, NIPE - Universidade do Minho.

    Cited by:

    1. João Vasco Coelho, 2022. "Non‐linear internationalization processes in Portugal: Evidence across retail, construction and software development industries," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(3), pages 539-559, June.
    2. Karsten Staehr, 2020. "Export performance and capacity pressures in Central and Eastern Europe," Bank of Estonia Working Papers wp2020-4, Bank of Estonia, revised 13 Aug 2020.
    3. Tracy Wilcox & Michelle Greenwood & Alison Pullen & Anne O’Leary Kelly & Deborah Jones, 2021. "Interfaces of domestic violence and organization: Gendered violence and inequality," Gender, Work and Organization, Wiley Blackwell, vol. 28(2), pages 701-721, March.

  4. António Rua, 2017. "Modelling currency demand in a small open economy within a monetary union," Working Papers w201710, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Franz Seitz & Lucas Devigne & Raymond de Pastor, 2022. "Different Motives for Holding Cash in France: an Analysis of the Net Cash Issues of the Banque de France," Working papers 888, Banque de France.
    2. António Rua, 2019. "Modelling the Demand for Euro Banknotes," Working Papers w201905, Banco de Portugal, Economics and Research Department.
    3. Luca Baldo & Elisa Bonifacio & Marco Brandi & Michelina Lo Russo & Gianluca Maddaloni & Andrea Nobili & Giorgia Rocco & Gabriele Sene & Massimo Valentini, 2021. "Inside the black box: tools for understanding cash circulation," Mercati, infrastrutture, sistemi di pagamento (Markets, Infrastructures, Payment Systems) 7, Bank of Italy, Directorate General for Markets and Payment System.
    4. Bo Yang & Minhaj Ali & Shujahat Haider Hashmi & Mohsin Shabir, 2020. "Income Inequality and CO 2 Emissions in Developing Countries: The Moderating Role of Financial Instability," Sustainability, MDPI, vol. 12(17), pages 1-24, August.
    5. Franz Seitz & Hans-Eggert Reimers & Friedrich Schneider, 2018. "Cash in Circulation and the Shadow Economy: An Empirical Investigation for Euro Area Countries and Beyond," CESifo Working Paper Series 7143, CESifo.
    6. Brian Micallef & Tiziana Gauci, "undated". "Excess demand for banknotes in Malta," CBM Policy Papers PP/02/2022, Central Bank of Malta.
    7. André Cardoso Dias, 2019. "Estimating a country’s currency circulation within a monetary union," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
    8. Hans-Eggert Reimers & Friedrich Schneider & Franz Seitz, 2020. "Payment Innovations, the Shadow Economy and Cash Demand of Households in Euro Area Countries," CESifo Working Paper Series 8574, CESifo.
    9. Vicente Ríos & Antonio Gómez & Pedro Pascual, 2021. "Raising the Accuracy of Shadow Economy Measurements," Hacienda Pública Española / Review of Public Economics, IEF, vol. 239(4), pages 71-125, November.
    10. Lalouette, Laure & Zamora-Pérez, Alejandro & Rusu, Codruta & Bartzsch, Nikolaus & Politronacci, Emmanuelle & Delmas, Martial & Rua, António & Brandi, Marco & Naksi, Martti, 2021. "Foreign demand for euro banknotes," Occasional Paper Series 253, European Central Bank.

  5. António Rua & Paulo M.M. Rodrigues & João Pedro Pereira, 2016. "Market integration and the persistence of electricity prices," Working Papers w201609, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Martin-Valmayor, Miguel A. & Gil-Alana, Luis A. & Infante, Juan, 2023. "Energy prices in Europe. Evidence of persistence across markets," Resources Policy, Elsevier, vol. 82(C).
    2. Chai, Shanglei & Li, Qiang & Abedin, Mohammad Zoynul & Lucey, Brian M., 2024. "Forecasting electricity prices from the state-of-the-art modeling technology and the price determinant perspectives," Research in International Business and Finance, Elsevier, vol. 67(PA).
    3. Macedo, Daniela Pereira & Marques, António Cardoso & Damette, Olivier, 2022. "The role of electricity flows and renewable electricity production in the behaviour of electricity prices in Spain," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 885-900.

  6. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Jens J. Krüger, 2021. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 293-319, December.
    2. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    3. Dejan Živkov & Slavica Manić & Jelena Kovačević & Željana Trbović, 2022. "Assessing volatility transmission between Brent and stocks in the major global oil producers and consumers – the multiscale robust quantile regression," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 21(1), pages 67-93, January.
    4. Martin Mandler & Michael Scharnagl, 2022. "Financial Cycles in Euro Area Economies: A Cross‐Country Perspective Using Wavelet Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 569-593, June.
    5. Stein, Tobias, 2024. "Forecasting the equity premium with frequency-decomposed technical indicators," International Journal of Forecasting, Elsevier, vol. 40(1), pages 6-28.
    6. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
    7. Risse, Marian, 2019. "Combining wavelet decomposition with machine learning to forecast gold returns," International Journal of Forecasting, Elsevier, vol. 35(2), pages 601-615.
    8. Joanna Bruzda, 2020. "The wavelet scaling approach to forecasting: Verification on a large set of Noisy data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 353-367, April.
    9. Faria, Gonçalo & Verona, Fabio, 2018. "The equity risk premium and the low frequency of the term spread," Bank of Finland Research Discussion Papers 7/2018, Bank of Finland.
    10. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.

  7. Cláudia Duarte, 2016. "A Mixed Frequency Approach to Forecast Private Consumption with ATM/POS Data," Working Papers w201601, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Gurgul Henryk & Suder Marcin, 2016. "Calendar and Seasonal Effects on the Size of Withdrawals from Atms Managed By Euronet," Statistics in Transition New Series, Statistics Poland, vol. 17(4), pages 691-722, December.
    2. Cláudia Duarte & Sónia Cabral, . "Nowcasting Portuguese tourism exports," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.

  8. Rua, António & Soares Esteves, Paulo & Staehr, Karsten & Bobeica, Elena, 2015. "Exports and domestic demand pressure: a dynamic panel data model for the euro area countries," Working Paper Series 1777, European Central Bank.

    Cited by:

    1. João Vasco Coelho, 2022. "Non‐linear internationalization processes in Portugal: Evidence across retail, construction and software development industries," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(3), pages 539-559, June.
    2. Karsten Staehr, 2020. "Export performance and capacity pressures in Central and Eastern Europe," Bank of Estonia Working Papers wp2020-4, Bank of Estonia, revised 13 Aug 2020.
    3. Matteo Bugamelli & Silvia Fabiani & Stefano Federico & Alberto Felettigh & Claire Giordano & Andrea Linarello, 2018. "Back on Track? A micro-macro Narrative of Italian Exports," Working Papers 1, Department of the Treasury, Ministry of the Economy and of Finance.
    4. Duncan van Limbergen & Robert Vermeulen, 2020. "The importance of value chains for euro area trade: a time series perspective," Working Papers 672, DNB.
    5. Beissinger, Thomas & Hellier, Joël & Marczak, Martyna, 2020. "Divergence in Labour Force Growth: Should Wages and Prices Grow Faster in Germany?," IZA Discussion Papers 13538, Institute of Labor Economics (IZA).
    6. Soares Esteves, Paulo & Prades, Elvira, 2016. "On domestic demand and export performance in the euro area countries: does export concentration matter?," Working Paper Series 1909, European Central Bank.
    7. Juan Laborda & Sonia Ruano & Ignacio Zamanillo, 2023. "Multi-Country and Multi-Horizon GDP Forecasting Using Temporal Fusion Transformers," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
    8. Saša Jakšić & Nataša Erjavec & Boris Cota, 2019. "The role of foreign direct investment and labor productivity in explaining croatian regional export dynamics," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(3), pages 835-849, September.
    9. Paulo Soares Esteves & Miguel Portela & António Rua, 2022. "Does Domestic Demand Matter for Firms’ Exports?," Open Economies Review, Springer, vol. 33(2), pages 311-332, April.
    10. Nazlı Karamollaoğlu & Cihan Yalçın, 2017. "Exports of manufacturing firms, exchange rates, and foreign currency exposure: firm level evidence from Turkey," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Uses of central balance sheet data offices' information, volume 45, Bank for International Settlements.
    11. Elena Bobeica & Olegs Tkacevs & Styliani Christodoulopoulou, 2016. "The role of price and cost competitiveness for intra- and extra-euro area trade of euro area countries," Working Papers 2016/04, Latvijas Banka.
    12. Esteves, Paulo Soares & Prades, Elvira, 2018. "Does export concentration matter in economic adjustment programs? Evidence from the euro-area," Journal of Policy Modeling, Elsevier, vol. 40(2), pages 225-241.
    13. Juan Laborda & Vicente Salas & Cristina Suárez, 2020. "Manufacturing firms’ export activity: Business and financial cycles overlaps!," International Economics, CEPII research center, issue 162, pages 1-14.
    14. Niels Gilbert & Sebastiaan Pool, 2020. "Sectoral allocation and macroeconomic imbalances in EMU," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 156(4), pages 945-984, November.
    15. Nazlı Karamollaoğlu & Cihan Yalçin, 2020. "Exports, real exchange rates and dollarization: empirical evidence from Turkish manufacturing firms," Empirical Economics, Springer, vol. 59(5), pages 2527-2557, November.
    16. Habanabakize Thomas & Muzindutsi Paul-Francois, 2018. "Analysis of the Keynesian Theory of Employment and Sectoral Job Creation: The Case of the South African Manufacturing Sector," Folia Oeconomica Stetinensia, Sciendo, vol. 18(1), pages 123-143, June.
    17. Serhiy Moroz & Khabibullo Pirmatov & Elena Horska & Ludmila Nagyova & Zuzana Polakova, 2017. "The Effect of Selected Economic Indicators on Export of Goods of Regions of Ukraine," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 13(2), pages 141-150.

  9. António Rua & Miguel de Carvalho, 2014. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," Working Papers w201416, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Bógalo, Juan & Poncela, Pilar & Senra, Eva, 2017. "Automatic Signal Extraction for Stationary and Non-Stationary Time Series by Circulant SSA," MPRA Paper 76023, University Library of Munich, Germany.
    2. Marcelo C. Medeiros & Henrique F. Pires, 2021. "The Proper Use of Google Trends in Forecasting Models," Papers 2104.03065, arXiv.org, revised Apr 2021.
    3. Paulo Canas Rodrigues & Olushina Olawale Awe & Jonatha Sousa Pimentel & Rahim Mahmoudvand, 2020. "Modelling the Behaviour of Currency Exchange Rates with Singular Spectrum Analysis and Artificial Neural Networks," Stats, MDPI, vol. 3(2), pages 1-21, June.
    4. Jiang, Ping & Liu, Zhenkun & Niu, Xinsong & Zhang, Lifang, 2021. "A combined forecasting system based on statistical method, artificial neural networks, and deep learning methods for short-term wind speed forecasting," Energy, Elsevier, vol. 217(C).
    5. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    6. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    7. de Carvalho, Miguel & Martos, Gabriel, 2020. "Brexit: Tracking and disentangling the sentiment towards leaving the EU," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1128-1137.
    8. Juan B'ogalo & Pilar Poncela & Eva Senra, 2020. "Understanding fluctuations through Multivariate Circulant Singular Spectrum Analysis," Papers 2007.07561, arXiv.org, revised Aug 2023.
    9. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.

  10. Rua, António & Soares Esteves, Paulo, 2013. "Is there a role for domestic demand pressure on export performance?," Working Paper Series 1594, European Central Bank.

    Cited by:

    1. João Vasco Coelho, 2022. "Non‐linear internationalization processes in Portugal: Evidence across retail, construction and software development industries," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(3), pages 539-559, June.
    2. Rua, António & Soares Esteves, Paulo & Staehr, Karsten & Bobeica, Elena, 2015. "Exports and domestic demand pressure: a dynamic panel data model for the euro area countries," Working Paper Series 1777, European Central Bank.
    3. Ruling Hong & Mengxun Liu & Haoming Yang & Qianqian Zhang, 2023. "What Drives China’s Exports: Evidence from a Domestic Consumption Expansion Policy," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
    4. Karsten Staehr, 2020. "Export performance and capacity pressures in Central and Eastern Europe," Bank of Estonia Working Papers wp2020-4, Bank of Estonia, revised 13 Aug 2020.
    5. Matteo Bugamelli & Silvia Fabiani & Stefano Federico & Alberto Felettigh & Claire Giordano & Andrea Linarello, 2018. "Back on Track? A micro-macro Narrative of Italian Exports," Working Papers 1, Department of the Treasury, Ministry of the Economy and of Finance.
    6. Pami Dua & Ritu Suri, 2023. "India’s Bilateral Export Growth and Exchange Rate Volatility: A Panel GMM Approach," Springer Books, in: Pami Dua (ed.), Macroeconometric Methods, chapter 0, pages 123-148, Springer.
    7. Wang, Hua & Liao, Lingtao & Wu, Ji (George), 2023. "Robot adoption and firm's capacity utilization: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    8. Gkypali, Areti & Love, James H. & Roper, Stephen, 2021. "Export status and SME productivity: Learning-to-export versus learning-by-exporting," Journal of Business Research, Elsevier, vol. 128(C), pages 486-498.
    9. Željko Bogdan Boris Cota Nataša Erjavec, 2017. "Current Account Balance and Export Performances: Evidence Based on New EU Countries," Zagreb International Review of Economics and Business, Faculty of Economics and Business, University of Zagreb, vol. 20(2), pages 33-48, November.
    10. Gnimassoun, Blaise, 2015. "The importance of the exchange rate regime in limiting current account imbalances in sub-Saharan African countries," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 36-74.
    11. Alexander F. McQuoid & JaeBin Ahn, 2015. "Capacity Constrained Exporters: Identifying Increasing Marginal Cost," Departmental Working Papers 49, United States Naval Academy Department of Economics.
    12. Duncan van Limbergen & Robert Vermeulen, 2020. "The importance of value chains for euro area trade: a time series perspective," Working Papers 672, DNB.
    13. Soares Esteves, Paulo & Prades, Elvira, 2016. "On domestic demand and export performance in the euro area countries: does export concentration matter?," Working Paper Series 1909, European Central Bank.
    14. Bugamelli, Matteo & Gaiotti, Eugenio & Viviano, Eliana, 2015. "Domestic and foreign sales: Complements or substitutes?," Economics Letters, Elsevier, vol. 135(C), pages 46-51.
    15. Roseline Misati & Kethi Ngoka, 2021. "Constraints on the performance and competitiveness of Tanzania's manufacturing exports," WIDER Working Paper Series wp-2021-35, World Institute for Development Economic Research (UNU-WIDER).
    16. Belke, Ansgar & Oeking, Anne & Setzer, Ralph, 2015. "Domestic demand, capacity constraints and exporting dynamics: Empirical evidence for vulnerable euro area countries," Economic Modelling, Elsevier, vol. 48(C), pages 315-325.
    17. Blanchard, Olivier & Portugal, Pedro, 2017. "Boom, Slump, Sudden stops, Recovery, and Policy Options. Portugal and the Euro," CEPR Discussion Papers 12118, C.E.P.R. Discussion Papers.
    18. Juan Laborda & Sonia Ruano & Ignacio Zamanillo, 2023. "Multi-Country and Multi-Horizon GDP Forecasting Using Temporal Fusion Transformers," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
    19. Tkačevs, Olegs & Christodoulopoulou, Styliani, 2014. "Measuring the effectiveness of cost and price competitiveness in external rebalancing of euro area countries: What do alternative HCIs tell us?," Working Paper Series 1736, European Central Bank.
    20. Paulo Soares Esteves & Miguel Portela & António Rua, 2022. "Does Domestic Demand Matter for Firms’ Exports?," Open Economies Review, Springer, vol. 33(2), pages 311-332, April.
    21. Dai, Xiaoyong & Zhao, Zhiqi, 2021. "Can exporting resolve overcapacity? Evidence from Chinese steel companies," Economic Modelling, Elsevier, vol. 102(C).
    22. Radovan Kovačević, 2019. "The Export Performance Of The Euro Area: A Panel Quantile Regression Approach," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 64(222), pages 7-62, July – Se.
    23. Ansgar Belke & Anne Oeking & Ralph Setzer, 2014. "Domestic demand pressure and export dynamics – An empirical threshold model analysis for six euro area countries," EcoMod2014 6780, EcoMod.
    24. Helena Engemann & Yaghoob Jafari & Thomas Heckelei, 2023. "Institutional quality and the duration of agri‐food trade flows," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(1), pages 135-154, February.
    25. Ansgar Belke & Anne Oeking & Ralph Setzer, 2015. "Exports and Capacity Constraints: Evidence for Several Euro Area Countries," CESifo Working Paper Series 5455, CESifo.
    26. Jean Pisani-Ferry & André Sapir & Guntram B. Wolff, . "EU-IMF assistance to euro area countries- an early assessment," Blueprints, Bruegel, number 779.
    27. Christoph Fischer & Oliver Hossfeld & Karin Radeck, 2018. "On the Suitability of Alternative Competitiveness Indicators for Explaining Real Exports of Advanced Economies," Open Economies Review, Springer, vol. 29(1), pages 119-139, February.
    28. Belke, Ansgar & Oeking, Anne & Setzer, Ralph, 2014. "Exports and Capacity Constraints: A smooth transition regression model for six euro-area countries," CEPS Papers 9228, Centre for European Policy Studies.
    29. José Bardaji & Jean‐Charles Bricongne & Benoît Campagne & Guillaume Gaulier, 2019. "Domestic and export performances of French firms," The World Economy, Wiley Blackwell, vol. 42(3), pages 785-817, March.
    30. Srhoj, Stjepan & Walde, Janette, 2020. "Getting ready for EU Single Market: The effect of export-oriented grant schemes on firm performance," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 279-293.
    31. Ansgar Belke & Jan Wagemester, 2017. "Export Hysteresis, Capacity Constraints and Uncertainty: A Smooth-Transition Analysis for Euro Area Member Countries," CESifo Working Paper Series 6634, CESifo.
    32. Elena Bobeica & Olegs Tkacevs & Styliani Christodoulopoulou, 2016. "The role of price and cost competitiveness for intra- and extra-euro area trade of euro area countries," Working Papers 2016/04, Latvijas Banka.
    33. Jiang, Xiandeng & Shi, Yanlin, 2020. "Does US partisan conflict affect US–China bilateral trade?," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 1117-1131.
    34. Ayhab F. Saad, 2017. "Trade and technology adoption," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 26(1), pages 1-24, January.
    35. Ansgar Belke & Daniel Gros & Alcidi Cinzia & Leonor Coutinho & Alessandro Giovannini, 2014. "Exit State-of-play in Implementing Macroeconomic Adjustment Programmes in the Euro Area," ROME Working Papers 201405, ROME Network.
    36. Esteves, Paulo Soares & Prades, Elvira, 2018. "Does export concentration matter in economic adjustment programs? Evidence from the euro-area," Journal of Policy Modeling, Elsevier, vol. 40(2), pages 225-241.
    37. Juan Laborda & Vicente Salas & Cristina Suárez, 2020. "Manufacturing firms’ export activity: Business and financial cycles overlaps!," International Economics, CEPII research center, issue 162, pages 1-14.
    38. Krichene, H. & Geiger, T. & Frieler, K. & Willner, S.N. & Sauer, I. & Otto, C., 2021. "Long-term impacts of tropical cyclones and fluvial floods on economic growth – Empirical evidence on transmission channels at different levels of development," World Development, Elsevier, vol. 144(C).
    39. Serhiy Moroz & Khabibullo Pirmatov & Elena Horska & Ludmila Nagyova & Zuzana Polakova, 2017. "The Effect of Selected Economic Indicators on Export of Goods of Regions of Ukraine," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 13(2), pages 141-150.
    40. Gros, Daniel & Alcidi, Cinzia & Belke, Ansgar & Coutinho, Leonor & Giovannini, Alessandro, 2014. "State-of-play in implementing macroeconomic adjustment programmes in the euro area," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100407, Verein für Socialpolitik / German Economic Association.

  11. António Rua & Artur Silva Lopes, 2012. "Cohesion within the euro area and the U. S.: a wavelet-based view," Working Papers w201204, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Hanus, Lubos & Vacha, Lukas, 2015. "Business cycle synchronization of the Visegrad Four and the European Union," FinMaP-Working Papers 42, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. Lubos Hanus & Lukas Vacha, 2015. "Business cycle synchronization within the European Union: A wavelet cohesion approach," Papers 1506.03106, arXiv.org, revised Feb 2016.
    3. Martin Mandler & Michael Scharnagl, 2022. "Financial Cycles in Euro Area Economies: A Cross‐Country Perspective Using Wavelet Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 569-593, June.
    4. Aguiar-Conraria Luís & Brinca Pedro & Guðjónsson Haukur Viðar & Soares Maria Joana, 2017. "Business cycle synchronization across U.S. states," The B.E. Journal of Macroeconomics, De Gruyter, vol. 17(1), pages 1-15, January.
    5. Syed Jawad Hussain Shahzad & Jose Arreola‐Hernandez & Md Lutfur Rahman & Gazi Salah Uddin & Muhammad Yahya, 2021. "Asymmetric interdependence between currency markets' volatilities across frequencies and time scales," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2436-2457, April.
    6. Kurowski, Łukasz & Rogowicz, Karol, 2018. "Are business and credit cycles synchronised internally or externally?," Economic Modelling, Elsevier, vol. 74(C), pages 124-141.
    7. Naeem, Muhammad Abubakr & Peng, Zhe & Bouri, Elie & Hussain Shahzad, Syed Jawad & Karim, Sitara, 2022. "Examining the asymmetries between equity and commodity ETFs during COVID-19," Resources Policy, Elsevier, vol. 79(C).
    8. Mandler, Martin & Scharnagl, Michael, 2022. "Financial cycles across G7 economies: A view from wavelet analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    9. Rünstler, Gerhard & Balfoussia, Hiona & Burlon, Lorenzo & Buss, Ginters & Comunale, Mariarosaria & De Backer, Bruno & Dewachter, Hans & Guarda, Paolo & Haavio, Markus & Hindrayanto, Irma & Iskrev, Nik, 2018. "Real and financial cycles in EU countries - Stylised facts and modelling implications," Occasional Paper Series 205, European Central Bank.
    10. Chaker Aloui & Rania Jammazi & Hela Ben Hamida, 2018. "Multivariate Co-movement Between Islamic Stock and Bond Markets Among the GCC: A Wavelet-Based View," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 603-626, August.
    11. Luboš Hanus & Lukáš Vácha, 2020. "Growth cycle synchronization of the Visegrad Four and the European Union," Empirical Economics, Springer, vol. 58(4), pages 1779-1795, April.
    12. João Martins, 2022. "Bond Yields Movement Similarities and Synchronization in the G7: A Time–Frequency Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 189-214, July.
    13. Davor Kunovac & Martin Mandler & Michael Scharnagl, 2018. "Financial cycles in euro area economies: a cross-country perspective," Working Papers 55, The Croatian National Bank, Croatia.
    14. Aguiar-Conraria, Luis & Brinca, Pedro & Gudjonsson, Haukur & Soares, Joana, 2015. "Optimal currency area and business cycle synchronization across U.S. states," MPRA Paper 62125, University Library of Munich, Germany.
    15. Patrick M. Crowley & Andrew Hughes Hallett, 2021. "The Evolution of US and UK Real GDP Components in the Time-Frequency Domain: A Continuous Wavelet Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 233-261, December.
    16. Scharnagl Michael & Mandler Martin, 2019. "Real and Financial Cycles in Euro Area Economies: Results from Wavelet Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(5-6), pages 895-916, October.
    17. Vácha, Lukáš & Šmolík, Filip & Baxa, Jaromír, 2019. "Comovement and disintegration of EU sovereign bond markets during the crisis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 541-556.

  12. António Rua & Luís Catela Nunes, 2012. "A wavelet-based assessment of market risk: The emerging markets case," Working Papers w201203, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. George Tzagkarakis & Frantz Maurer, 2020. "An energy-based measure for long-run horizon risk quantification," Annals of Operations Research, Springer, vol. 289(2), pages 363-390, June.
    2. Oguzhan Cepni & Yavuz Selim Hacihasanoglu & Muhammed Hasan Yilmaz, 2020. "Credit decomposition and economic activity in Turkey: A wavelet-based approach," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 20(3), pages 109-131.
    3. Gazi Salah Uddin & Mohamed Arouri & Aviral Kumar Tiwari, 2014. "Co-movements between Germany and International Stock Markets: Some New Evidence from DCC-GARCH and Wavelet Approaches," Working Papers 2014-143, Department of Research, Ipag Business School.
    4. Özmen, M. Utku & Yılmaz, Erdal, 2017. "Co-movement of exchange rates with interest rate differential, risk premium and FED policy in “fragile economies”," Emerging Markets Review, Elsevier, vol. 33(C), pages 173-188.
    5. Manuel Monge & Luis A. Gil-Alana, 2020. "The Lithium Industry and Analysis of the Beta Term Structure of Oil Companies," Risks, MDPI, vol. 8(4), pages 1-17, December.
    6. Aasif Shah & Arif Tali & Qaiser Farooq, 2018. "Beta through the prism of wavelets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-17, December.
    7. Rahul Deora & Duc Khuong Nguyen, 2014. "Time-scale comovement between the Indian and world stock markets," Working Papers 2014-242, Department of Research, Ipag Business School.
    8. William A. Barnett & Fredj Jawadi & Zied Ftiti, 2020. "Causal Relationships Between Inflation and Inflation Uncertainty," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202010, University of Kansas, Department of Economics, revised Jul 2020.
    9. George Tzagkarakis & Frantz Maurer, 2023. "Horizon-Adaptive Extreme Risk Quantification for Cryptocurrency Assets," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1251-1286, October.
    10. Uddin, Gazi Salah & Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2018. "Time-varying evidence of efficiency, decoupling, and diversification of conventional and Islamic stocks," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 167-180.
    11. Chakrabarty, Anindya & De, Anupam & Gunasekaran, Angappa & Dubey, Rameshwar, 2015. "Investment horizon heterogeneity and wavelet: Overview and further research directions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 45-61.
    12. Aloui, Chaker & Hkiri, Besma & Lau, Marco Chi Keung & Yarovaya, Larisa, 2018. "Information transmission across stock indices and stock index futures: International evidence using wavelet framework," Research in International Business and Finance, Elsevier, vol. 44(C), pages 411-421.
    13. Sang Hoon Kang & Salim Lahmiri & Gazi Salah Uddin & Jose Arreola Hernandez & Seong-Min Yoon, 2020. "Inflation cycle synchronization in ASEAN countries," Post-Print hal-02779489, HAL.
    14. Akoum, Ibrahim & Graham, Michael & Kivihaho, Jarno & Nikkinen, Jussi & Omran, Mohammed, 2012. "Co-movement of oil and stock prices in the GCC region: A wavelet analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(4), pages 385-394.
    15. Anindya Chakrabarty & Anupam De & Gautam Bandyopadhyay, 2016. "Horizon heterogeneity, institutional constraint and managerial myopia: a multi-frequency perspective on ELSS," International Journal of Business Excellence, Inderscience Enterprises Ltd, vol. 9(1), pages 18-47.
    16. Meng, Xiangcai & Huang, Chia-Hsing, 2019. "The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 131-148.
    17. Bruzda, Joanna, 2019. "Complex analytic wavelets in the measurement of macroeconomic risks," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    18. Power, Gabriel J. & Eaves, James & Turvey, Calum & Vedenov, Dmitry, 2017. "Catching the curl: Wavelet thresholding improves forward curve modelling," Economic Modelling, Elsevier, vol. 64(C), pages 312-321.
    19. M. Utku Ozmen & Erdal Yilmaz, 2016. "Co-movement of Exchange Rates with Interest Rate Differential, Risk Premium and FED Policy in �Fragile Economies�," Working Papers 1621, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    20. Vuong, Giang Thi Huong & Nguyen, Phuc Van & Barky, Walid & Nguyen, Manh Huu, 2024. "Stock return volatility and financial distress: Moderating roles of ownership structure, managerial ability, and financial constraints," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 634-652.
    21. Antonios K. Alexandridis & Mohammad S. Hasan, 2020. "Global financial crisis and multiscale systematic risk: Evidence from selected European stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 518-546, October.
    22. McNevin, Bruce D. & Nix, Joan, 2018. "The beta heuristic from a time/frequency perspective: A wavelet analysis of the market risk of sectors," Economic Modelling, Elsevier, vol. 68(C), pages 570-585.
    23. Ijaz Younis & Cheng Longsheng & Muhammad Farhan Basheer & Ahmed Shafique Joyo, 2020. "Stock market comovements among Asian emerging economies: A wavelet-based approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-23, October.
    24. Olaolu Richard Olayeni, 2016. "Causality in Continuous Wavelet Transform Without Spectral Matrix Factorization: Theory and Application," Computational Economics, Springer;Society for Computational Economics, vol. 47(3), pages 321-340, March.
    25. Berdiev, Aziz N. & Chang, Chun-Ping, 2015. "Business cycle synchronization in Asia-Pacific: New evidence from wavelet analysis," Journal of Asian Economics, Elsevier, vol. 37(C), pages 20-33.
    26. Jiang, Zhuhua & Yoon, Seong-Min, 2020. "Dynamic co-movement between oil and stock markets in oil-importing and oil-exporting countries: Two types of wavelet analysis," Energy Economics, Elsevier, vol. 90(C).
    27. Ryuta Sakemoto, 2022. "Multi‐scale inter‐temporal capital asset pricing model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4298-4317, October.
    28. Funashima Yoshito, 2021. "Time–Frequency Regression," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 21-32, January.
    29. Xiaojie Xu, 2018. "Causal structure among US corn futures and regional cash prices in the time and frequency domain," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(13), pages 2455-2480, October.
    30. Bruno Milani & Paulo Sérgio Ceretta, 2014. "A multiscale approach to emerging market pricing," Economics Bulletin, AccessEcon, vol. 34(2), pages 784-792.
    31. Rababa’a, Abdel Razzaq Al & Alomari, Mohammad & Rehman, Mobeen Ur & McMillan, David & Hendawi, Raed, 2022. "Multiscale relationship between economic policy uncertainty and sectoral returns: Implications for portfolio management," Research in International Business and Finance, Elsevier, vol. 61(C).
    32. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    33. Kregždė Arvydas & Kišonaitė Karolina, 2018. "Co-movements of Lithuanian and Central European Stock Markets Across Different Time Horizons: A Wavelet Approach," Ekonomika (Economics), Sciendo, vol. 97(2), pages 55-69, December.
    34. Naseri, Marjan & Masih, Mansur, 2014. "Integration and Comovement of Developed and Emerging Islamic Stock Markets: A Case Study of Malaysia," MPRA Paper 58799, University Library of Munich, Germany.
    35. Erdost Torun & Afife Duygu Ayhan Akdeniz & Erhan Demireli & Simon Grima, 2022. "Long-Term US Economic Growth and the Carbon Dioxide Emissions Nexus: A Wavelet-Based Approach," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
    36. Shovon Sengupta & Tanujit Chakraborty & Sunny Kumar Singh, 2023. "Forecasting CPI inflation under economic policy and geopolitical uncertainties," Papers 2401.00249, arXiv.org, revised Jul 2024.
    37. Al Rababa’a, Abdel Razzaq & Alomari, Mohammad & McMillan, David, 2021. "Multiscale stock-bond correlation: Implications for risk management," Research in International Business and Finance, Elsevier, vol. 58(C).

  13. António Rua & João Pedro Pereira, 2012. "Asset pricing with a bank risk factor," Working Papers w201202, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Saad Alsunbul & Basim Alzugaiby & Sajid Chaudhry & Rhada Boujlil, 2024. "The fatter the tail, the shorter the sail," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 331-380, March.

  14. António Rua, 2011. "Money growth and inflation in the euro area: a time-frequency view," Working Papers w201122, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Khalfaoui, Rabeh & Padhan, Hemachandra & Tiwari, Aviral Kumar & Hammoudeh, Shawkat, 2020. "Understanding the time-frequency dynamics of money demand, oil prices and macroeconomic variables: The case of India," Resources Policy, Elsevier, vol. 68(C).
    2. Jun‐Hyung Ko & Yoshito Funashima, 2019. "On the Sources of the Feldstein–Horioka Puzzle across Time and Frequencies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 889-910, August.
    3. Tursoy, Turgut & Mar'i, Muhammad, 2020. "Lead-lag and relationship between money growth and inflation in Turkey: New evidence from a wavelet analysis," MPRA Paper 99595, University Library of Munich, Germany.
    4. Aviral Tiwari & Niyati Bhanja & Arif Dar & Faridul Islam, 2015. "Time–frequency relationship between share prices and exchange rates in India: Evidence from continuous wavelets," Empirical Economics, Springer, vol. 48(2), pages 699-714, March.
    5. Verona, Fabio, 2016. "Time-frequency characterization of the U.S. financial cycle," Bank of Finland Research Discussion Papers 14/2016, Bank of Finland.
    6. Crowley, Patrick M. & Hallett, Andrew Hughes, 2018. "What causes business cycles to elongate, or recessions to intensify?," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 338-349.
    7. Patrick M. Crowley & David Hudgins, 2022. "Monetary policy objectives and economic outcomes: What can we learn from a wavelet‐based optimal control approach?," Manchester School, University of Manchester, vol. 90(2), pages 144-170, March.
    8. Yingying XU & Zhixin LIU & Jaime ORTIZ, 2018. "Actual and Expected Inflation in the U.S.: A Time-Frequency View," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 42-62, December.
    9. Rita Sousa & Luís Aguiar-Conraria & Maria Joana Soares, 2014. "Carbon Financial Markets: a time-frequency analysis of CO2 price drivers," NIPE Working Papers 03/2014, NIPE - Universidade do Minho.
    10. Villa-Loaiza, Carlos & Taype-Huaman, Irvin & Benavides-Franco, Julián & Buenaventura-Vera, Guillermo & Carabalí-Mosquera, Jaime, 2023. "Does climate impact the relationship between the energy price and the stock market? The Colombian case," Applied Energy, Elsevier, vol. 336(C).
    11. Jiang, Chun & Chang, Tsangyao & Li, Xiao-Lin, 2015. "Money growth and inflation in China: New evidence from a wavelet analysis," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 249-261.
    12. Funashima, Yoshito, 2015. "The Fed-Induced Political Business Cycle," MPRA Paper 63654, University Library of Munich, Germany.
    13. Fathi Abid & Bilel Kaffel, 2018. "The extent of virgin olive-oil prices’ distribution revealing the behavior of market speculators," Review of Quantitative Finance and Accounting, Springer, vol. 50(2), pages 561-590, February.
    14. Yoshito Funashima, 2018. "Macroeconomic policy coordination between Japanese central and local governments," Empirical Economics, Springer, vol. 54(4), pages 1631-1651, June.
    15. Funashima, Yoshito, 2017. "Time-varying leads and lags across frequencies using a continuous wavelet transform approach," Economic Modelling, Elsevier, vol. 60(C), pages 24-28.
    16. Thomas Conlon & Brian M. Lucey & Gazi Salah Uddin, 2018. "Is gold a hedge against inflation? A wavelet time-scale perspective," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 317-345, August.
    17. Funashima, Yoshito, 2014. "Macroeconomic policy coordination between Japanese central and local governments," MPRA Paper 59821, University Library of Munich, Germany.
    18. Funashima, Yoshito, 2016. "The Fed-induced political business cycle: Empirical evidence from a time–frequency view," Economic Modelling, Elsevier, vol. 54(C), pages 402-411.
    19. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
    20. Xu, Yingying, 2020. "Will energy transitions impact financial systems?," Energy, Elsevier, vol. 194(C).
    21. Luís Aguiar-Conraria & Pedro Magalhães & Maria Soares, 2013. "The nationalization of electoral cycles in the United States: a wavelet analysis," Public Choice, Springer, vol. 156(3), pages 387-408, September.
    22. Maciej Ryczkowski, 2021. "Money and inflation in inflation-targeting regimes – new evidence from time–frequency analysis," Journal of Applied Economics, Taylor & Francis Journals, vol. 24(1), pages 17-44, January.
    23. Robert Czudaj, 2019. "Crude oil futures trading and uncertainty," Chemnitz Economic Papers 027, Department of Economics, Chemnitz University of Technology, revised Jan 2019.
    24. Maciej Ryczkowski, 2020. "Money and credit during normal times and house price booms: evidence from time-frequency analysis," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(4), pages 835-861, November.
    25. Lin, Fu-Lai & Chen, Yu-Fen & Yang, Sheng-Yung, 2016. "Does the value of US dollar matter with the price of oil and gold? A dynamic analysis from time–frequency space," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 59-71.
    26. Caraiani, Petre, 2015. "Estimating DSGE models across time and frequency," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 33-49.
    27. Portugal, Pedro & Rua, António, 2020. "How the ins and outs shape differently the U.S. unemployment over time and across frequencies," European Economic Review, Elsevier, vol. 121(C).
    28. Berdiev, Aziz N. & Chang, Chun-Ping, 2015. "Business cycle synchronization in Asia-Pacific: New evidence from wavelet analysis," Journal of Asian Economics, Elsevier, vol. 37(C), pages 20-33.
    29. Funashima, Yoshito, 2015. "Automatic stabilizers in the Japanese tax system," Journal of Asian Economics, Elsevier, vol. 39(C), pages 86-93.
    30. Funashima Yoshito, 2021. "Time–Frequency Regression," Journal of Econometric Methods, De Gruyter, vol. 10(1), pages 21-32, January.
    31. Su, Chi-Wei & Khan, Khalid & Tao, Ran & Nicoleta-Claudia, Moldovan, 2019. "Does geopolitical risk strengthen or depress oil prices and financial liquidity? Evidence from Saudi Arabia," Energy, Elsevier, vol. 187(C).
    32. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    33. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
    34. Kregždė Arvydas & Kišonaitė Karolina, 2018. "Co-movements of Lithuanian and Central European Stock Markets Across Different Time Horizons: A Wavelet Approach," Ekonomika (Economics), Sciendo, vol. 97(2), pages 55-69, December.
    35. Abid, Fathi & Kaffel, Bilel, 2018. "Time–frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1028-1045.
    36. Gallegati, Marco & Ramsey, James B. & Semmler, Willi, 2014. "Interest rate spreads and output: A time scale decomposition analysis using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 283-290.
    37. Funashima, Yoshito, 2016. "Governmentally amplified output volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 469-478.
    38. Erdost Torun & Afife Duygu Ayhan Akdeniz & Erhan Demireli & Simon Grima, 2022. "Long-Term US Economic Growth and the Carbon Dioxide Emissions Nexus: A Wavelet-Based Approach," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
    39. Yingying Xu & Zhixin Liu & Jichang Zhao & Chiwei Su, 2017. "Weibo sentiments and stock return: A time-frequency view," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-21, July.
    40. Al Rababa’a, Abdel Razzaq & Alomari, Mohammad & McMillan, David, 2021. "Multiscale stock-bond correlation: Implications for risk management," Research in International Business and Finance, Elsevier, vol. 58(C).
    41. Patrick M. Crowley & Andrew Hughes Hallett, 2021. "The Evolution of US and UK Real GDP Components in the Time-Frequency Domain: A Continuous Wavelet Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 233-261, December.
    42. Funashima, Yoshito, 2015. "Wagner's law versus displacement effect," MPRA Paper 68390, University Library of Munich, Germany.
    43. Cheng-Feng Wu & Fangjhy Li & Hsin-Pei Hsueh & Chien-Ming Wang & Meng-Chen Lin & Tsangyao Chang, 2020. "A Dynamic Relationship between Environmental Degradation, Healthcare Expenditure and Economic Growth in Wavelet Analysis: Empirical Evidence from Taiwan," IJERPH, MDPI, vol. 17(4), pages 1-17, February.

  15. António Rua & Miguel de Carvalho, 2010. "Extremal Dependence in International Output Growth: Tales from the Tails," Working Papers w201008, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. de Carvalho, Miguel & Rua, António, 2017. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.

  16. António Rua, 2010. "A Wavelet Approach for Factor-Augmented Forecasting," Working Papers w201007, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    2. Manuel M. F. Martins & Fabio Verona, 2020. "Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters," CEF.UP Working Papers 2001, Universidade do Porto, Faculdade de Economia do Porto.
    3. Kilponen, Juha & Verona, Fabio, 2016. "Testing the Q theory of investment in the frequency domain," Bank of Finland Research Discussion Papers 32/2016, Bank of Finland.
    4. Martins, Manuel Mota Freitas & Verona, Fabio, 2021. "Inflation dynamics and forecast: Frequency matters," Bank of Finland Research Discussion Papers 8/2021, Bank of Finland.
    5. Özmen, M. Utku & Yılmaz, Erdal, 2017. "Co-movement of exchange rates with interest rate differential, risk premium and FED policy in “fragile economies”," Emerging Markets Review, Elsevier, vol. 33(C), pages 173-188.
    6. Ramazan Gencay & Ege Yazgan, 2017. "When Are Wavelets Useful Forecasters?," Working Papers 1704, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    7. Stein, Tobias, 2024. "Forecasting the equity premium with frequency-decomposed technical indicators," International Journal of Forecasting, Elsevier, vol. 40(1), pages 6-28.
    8. Fosten, Jack, 2019. "CO2 emissions and economic activity: A short-to-medium run perspective," Energy Economics, Elsevier, vol. 83(C), pages 415-429.
    9. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
    10. Voutilainen, Ville, 2017. "Wavelet decomposition of the financial cycle: An early warning system for financial tsunamis," Bank of Finland Research Discussion Papers 11/2017, Bank of Finland.
    11. Risse, Marian, 2019. "Combining wavelet decomposition with machine learning to forecast gold returns," International Journal of Forecasting, Elsevier, vol. 35(2), pages 601-615.
    12. M. Utku Ozmen & Erdal Yilmaz, 2016. "Co-movement of Exchange Rates with Interest Rate Differential, Risk Premium and FED Policy in �Fragile Economies�," Working Papers 1621, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    13. He, Kaijian & Xu, Yang & Zou, Yingchao & Tang, Ling, 2015. "Electricity price forecasts using a Curvelet denoising based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 425(C), pages 1-9.
    14. Joanna Bruzda, 2020. "The wavelet scaling approach to forecasting: Verification on a large set of Noisy data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 353-367, April.
    15. Su, Chi-Wei & Khan, Khalid & Tao, Ran & Nicoleta-Claudia, Moldovan, 2019. "Does geopolitical risk strengthen or depress oil prices and financial liquidity? Evidence from Saudi Arabia," Energy, Elsevier, vol. 187(C).
    16. Xiaojie Xu, 2018. "Causal structure among US corn futures and regional cash prices in the time and frequency domain," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(13), pages 2455-2480, October.
    17. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    18. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    19. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
    20. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    21. Caraiani, Petre, 2017. "Evaluating exchange rate forecasts along time and frequency," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 60-81.
    22. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
    23. Chiara Perricone, 2018. "Wavelet analysis for temporal disaggregation," CEIS Research Paper 444, Tor Vergata University, CEIS, revised 29 Oct 2018.
    24. Gallegati, Marco & Ramsey, James B. & Semmler, Willi, 2014. "Interest rate spreads and output: A time scale decomposition analysis using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 283-290.
    25. Sevda Kuşkaya & Nurhan Toğuç & Faik Bilgili, 2022. "Wavelet coherence analysis and exchange rate movements," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4675-4692, December.
    26. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Emmanuel Kwesi Arthur & Luis Alberiko Gil-Alana, 2023. "The influence of economic policy uncertainty shocks on art market," Applied Economics, Taylor & Francis Journals, vol. 55(29), pages 3404-3421, June.
    27. Sinem Celik Girgin & Thanasis Karlis & Hong-Oanh Nguyen, 2018. "A Critical Review of the Literature on Firm-Level Theories on Ship Investment," IJFS, MDPI, vol. 6(1), pages 1-19, January.

  17. António Rua, 2010. "Measuring comovement in the time-frequency space," Working Papers w201001, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Hanus, Lubos & Vacha, Lukas, 2015. "Business cycle synchronization of the Visegrad Four and the European Union," FinMaP-Working Papers 42, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. Jens J. Krüger, 2021. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 293-319, December.
    3. Jun‐Hyung Ko & Yoshito Funashima, 2019. "On the Sources of the Feldstein–Horioka Puzzle across Time and Frequencies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 889-910, August.
    4. Svatopluk KAPOUNEK & Jitka POMĚNKOVÁ, 2013. "The endogeneity of optimum currency area criteria in the context of financial crisis: Evidence from the time-frequency domain analysis," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 59(9), pages 389-395.
    5. Mustafa Gülerce & Gazanfer Ünal, 2017. "Forecasting Of Oil And Agricultural Commodity Prices: Varma Versus Arma," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(03), pages 1-30, September.
    6. Der-Yuan Yang & Chen-Hsun Lee, 2016. "The solar and lunar divide and the impact on Taiwan’s stock returns," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1177153-117, December.
    7. Lubos Hanus & Lukas Vacha, 2015. "Business cycle synchronization within the European Union: A wavelet cohesion approach," Papers 1506.03106, arXiv.org, revised Feb 2016.
    8. Dejan Živkov & Slavica Manić & Jelena Kovačević & Željana Trbović, 2022. "Assessing volatility transmission between Brent and stocks in the major global oil producers and consumers – the multiscale robust quantile regression," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 21(1), pages 67-93, January.
    9. Gazi Salah Uddin & Mohamed Arouri & Aviral Kumar Tiwari, 2014. "Co-movements between Germany and International Stock Markets: Some New Evidence from DCC-GARCH and Wavelet Approaches," Working Papers 2014-143, Department of Research, Ipag Business School.
    10. Zied Ftiti & Aviral Tiwari & Amél Belanès & Khaled Guesmi, 2014. "Tests of Financial Market Contagion: Evolutionary Cospectral Analysis V.S. Wavelet Analysis," Working Papers 2014-577, Department of Research, Ipag Business School.
    11. Svatopluk Kapounek & Zuzana Kucerova, 2018. "Historical Decoupling in the EU: Evidence from Time-Frequency Analysis," MENDELU Working Papers in Business and Economics 2018-75, Mendel University in Brno, Faculty of Business and Economics.
    12. Zied Ftiti & Aviral Tiwari & Amél Belanès & Khaled Guesmi, 2015. "Tests of Financial Market Contagion: Evolutionary Cospectral Analysis Versus Wavelet Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 575-611, December.
    13. Angus, A. & Casado, M. Rivas & Fitzsimons, D., 2012. "Exploring the usefulness of a simple linear regression model for understanding price movements of selected recycled materials in the UK," Resources, Conservation & Recycling, Elsevier, vol. 60(C), pages 10-19.
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    16. Tiwari, Aviral Kumar & Mutascu, Mihai Ioan & Albulescu, Claudiu Tiberiu & Kyophilavong, Phouphet, 2015. "Frequency domain causality analysis of stock market and economic activity in India," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 224-238.
    17. Mihai Mutascu & Alexandre Sokic, 2023. "Air transportation under COVID-19 pandemic restrictions: A wavelet analysis," Post-Print hal-04273878, HAL.
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    46. Samia Nasreen & Syed Asif Ali Naqvi & Aviral Kumar Tiwari & Shawkat Hammoudeh & Syed Ale Raza Shah, 2020. "A Wavelet-Based Analysis of the Co-Movement between Sukuk Bonds and Shariah Stock Indices in the GCC Region: Implications for Risk Diversification," JRFM, MDPI, vol. 13(4), pages 1-21, March.
    47. Sang Hoon Kang & Salim Lahmiri & Gazi Salah Uddin & Jose Arreola Hernandez & Seong-Min Yoon, 2020. "Inflation cycle synchronization in ASEAN countries," Post-Print hal-02779489, HAL.
    48. Akoum, Ibrahim & Graham, Michael & Kivihaho, Jarno & Nikkinen, Jussi & Omran, Mohammed, 2012. "Co-movement of oil and stock prices in the GCC region: A wavelet analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(4), pages 385-394.
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    51. Sadullah Çelik & Deniz Şatıroğlu, 2015. "A Reality Check on the Relationship between Poverty and Income Inequality for Turkey," EY International Congress on Economics II (EYC2015), November 5-6, 2015, Ankara, Turkey 229, Ekonomik Yaklasim Association.
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    54. Muhammad Zakaria & Seemab Tanveer & Bashir Ahmad Fida & Muhammad Iftikhar ul Husnain, 2023. "Inflation Differential Pass-Through to Exchange Rate: Some Evidence From Pakistan," SAGE Open, , vol. 13(4), pages 21582440231, December.
    55. Chaker Aloui & Rania Jammazi & Hela Ben Hamida, 2018. "Multivariate Co-movement Between Islamic Stock and Bond Markets Among the GCC: A Wavelet-Based View," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 603-626, August.
    56. Wen-Yi CHEN & Yu-Hui LIN, 2016. "Co-Movement of Healthcare Financing in OECD Countries: Evidence from Discrete Wavelet Analyses," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 40-56, September.
    57. Claudiu Tiberiu Albulescu & Mihai Ioan Mutascu, 2021. "Fuel price co-movements among France, Germany and Italy: A time-frequency investigation," Post-Print hal-03529585, HAL.
    58. Kristoufek, Ladislav, 2017. "Has global warming modified the relationship between sunspot numbers and global temperatures?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 351-358.
    59. Luboš Hanus & Lukáš Vácha, 2020. "Growth cycle synchronization of the Visegrad Four and the European Union," Empirical Economics, Springer, vol. 58(4), pages 1779-1795, April.
    60. Mihai Mutascu & Alexandre Sokic, 2022. "Revisiting the oil price and expected inflation in the U.S. - a wavelet approach," Economics Bulletin, AccessEcon, vol. 42(2), pages 959-964.
    61. Aloui, Chaker & Hkiri, Besma & Nguyen, Duc Khuong, 2016. "Real growth co-movements and business cycle synchronization in the GCC countries: Evidence from time-frequency analysis," Economic Modelling, Elsevier, vol. 52(PB), pages 322-331.
    62. Lin, Fu-Lai & Chen, Yu-Fen & Yang, Sheng-Yung, 2016. "Does the value of US dollar matter with the price of oil and gold? A dynamic analysis from time–frequency space," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 59-71.
    63. Caraiani, Petre, 2015. "Estimating DSGE models across time and frequency," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 33-49.
    64. Gozgor, Giray & Tiwari, Aviral Kumar & Demir, Ender & Akron, Sagi, 2019. "The relationship between Bitcoin returns and trade policy uncertainty," Finance Research Letters, Elsevier, vol. 29(C), pages 75-82.
    65. Portugal, Pedro & Rua, António, 2020. "How the ins and outs shape differently the U.S. unemployment over time and across frequencies," European Economic Review, Elsevier, vol. 121(C).
    66. Berdiev, Aziz N. & Chang, Chun-Ping, 2015. "Business cycle synchronization in Asia-Pacific: New evidence from wavelet analysis," Journal of Asian Economics, Elsevier, vol. 37(C), pages 20-33.
    67. Croux, Christophe & Reusens, Peter, 2013. "Do stock prices contain predictive power for the future economic activity? A Granger causality analysis in the frequency domain," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 93-103.
    68. Miljkovic, Dragan & Vatsa, Puneet, 2023. "On the linkages between energy and agricultural commodity prices: A dynamic time warping analysis," International Review of Financial Analysis, Elsevier, vol. 90(C).
    69. Dimic, Nebojsa & Kiviaho, Jarno & Piljak, Vanja & Äijö, Janne, 2016. "Impact of financial market uncertainty and macroeconomic factors on stock–bond correlation in emerging markets," Research in International Business and Finance, Elsevier, vol. 36(C), pages 41-51.
    70. Martín-Barragán, Belén & Ramos, Sofía B. & Veiga, Helena, 2013. "Correlations between oil and stock markets : a wavelet-based approach," DES - Working Papers. Statistics and Econometrics. WS ws130504, Universidad Carlos III de Madrid. Departamento de Estadística.
    71. Su-Ling TSAI & Tsangyao CHANG, 2018. "The Comovment between Money and Economic Growth in 15 Asia-Pacific Countries: Wavelet Coherency Analysis in Time-Frequency Domain," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 63-79, December.
    72. Su, Chi-Wei & Khan, Khalid & Tao, Ran & Nicoleta-Claudia, Moldovan, 2019. "Does geopolitical risk strengthen or depress oil prices and financial liquidity? Evidence from Saudi Arabia," Energy, Elsevier, vol. 187(C).
    73. Chun-Ping Chang & Chien-Chiang Lee & GenFu Feng & Shao-Lin Ning, 2016. "Does higher government debt link to higher social expenditure? New method, new evidence," Applied Economics, Taylor & Francis Journals, vol. 48(16), pages 1429-1451, April.
    74. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    75. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
    76. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    77. Svatopluk Kapounek & Jitka Poměnková, 2012. "Liquidity supply and money velocity co-movements in the Eurozone - Time-Frequency Domain Approach," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 60(2), pages 109-116.
    78. Qureshi, Saba & Rehman, Ijaz Ur & Qureshi, Fiza, 2018. "Does gold act as a safe haven against exchange rate fluctuations? The case of Pakistan rupee," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 685-708.
    79. Su, Chi-Wei & Khan, Khalid & Tao, Ran & Umar, Muhammad, 2020. "A review of resource curse burden on inflation in Venezuela," Energy, Elsevier, vol. 204(C).
    80. Lin, Fu-Lai & Yang, Sheng-Yung & Marsh, Terry & Chen, Yu-Fen, 2018. "Stock and bond return relations and stock market uncertainty: Evidence from wavelet analysis," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 285-294.
    81. Zuzana Kucerova & Jitka Pomenkova, 2014. "Financial and Trade Integration of Selected EU Regions: Dynamic Correlation and Wavelet Approach," MENDELU Working Papers in Business and Economics 2014-45, Mendel University in Brno, Faculty of Business and Economics.
    82. Bruno Scalzo & Alvaro Arroyo & Ljubisa Stankovic & Danilo P. Mandic, 2021. "Nonstationary Portfolios: Diversification in the Spectral Domain," Papers 2102.00477, arXiv.org.
    83. Fan, Ying & Yang, Zan & Yavas, Abdullah, 2019. "Understanding real estate price dynamics: The case of housing prices in five major cities of China✰," Journal of Housing Economics, Elsevier, vol. 43(C), pages 37-55.
    84. Funashima, Yoshito, 2016. "Governmentally amplified output volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 469-478.
    85. Yung-hsiang Ying & Koyin Chang & Ginny ju-ann Yang & Chen-hsun Lee, 2014. "Measuring co-movement of globalization and democratization in the time–frequency space," Economics Bulletin, AccessEcon, vol. 34(1), pages 206-219.
    86. Caraiani, Petre, 2012. "Stylized facts of business cycles in a transition economy in time and frequency," Economic Modelling, Elsevier, vol. 29(6), pages 2163-2173.
    87. Ladislav Kristoufek & Karel Janda & David Zilberman, 2015. "Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA," CAMA Working Papers 2015-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    88. Luís Francisco Aguiar & Maria Joana Soares, 2010. "Business Cycle Synchronization and the Euro: a Wavelet Analysis," NIPE Working Papers 36/2010, NIPE - Universidade do Minho.
    89. Erdost Torun & Afife Duygu Ayhan Akdeniz & Erhan Demireli & Simon Grima, 2022. "Long-Term US Economic Growth and the Carbon Dioxide Emissions Nexus: A Wavelet-Based Approach," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
    90. Peterson Owusu Junior & Anokye M. Adam & George Tweneboah, 2017. "Co-movement of real exchange rates in the West African Monetary Zone," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1351807-135, January.
    91. Aguiar-Conraria, Luis & Brinca, Pedro & Gudjonsson, Haukur & Soares, Joana, 2015. "Optimal currency area and business cycle synchronization across U.S. states," MPRA Paper 62125, University Library of Munich, Germany.
    92. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2011. "Synchronization of Economic Sentiment Cycles in the Euro Area: a time-frequency analysis," CEF.UP Working Papers 1105, Universidade do Porto, Faculdade de Economia do Porto.
    93. Jena, Sangram Keshari & Tiwari, Aviral Kumar & Roubaud, David, 2018. "Comovements of gold futures markets and the spot market: A wavelet analysis," Finance Research Letters, Elsevier, vol. 24(C), pages 19-24.
    94. Lindman, Sebastian & Tuvhag, Tom & Jayasekera, Ranadeva & Uddin, Gazi Salah & Troster, Victor, 2020. "Market Impact on financial market integration: Cross-quantilogram analysis of the global impact of the euro," Journal of Empirical Finance, Elsevier, vol. 56(C), pages 42-73.
    95. Habimana, Olivier, 2016. "Oil price, exchange rate and consumer price co-movement: A continuous-wavelet analysis," MPRA Paper 71886, University Library of Munich, Germany.
    96. Scharnagl Michael & Mandler Martin, 2019. "Real and Financial Cycles in Euro Area Economies: Results from Wavelet Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(5-6), pages 895-916, October.
    97. Krüger, Jens J., 2024. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 149438, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    98. Mensi, Walid & Hammoudeh, Shawkat & Tiwari, Aviral Kumar, 2016. "New evidence on hedges and safe havens for Gulf stock markets using the wavelet-based quantile," Emerging Markets Review, Elsevier, vol. 28(C), pages 155-183.
    99. Vácha, Lukáš & Šmolík, Filip & Baxa, Jaromír, 2019. "Comovement and disintegration of EU sovereign bond markets during the crisis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 541-556.
    100. Ftiti, Zied & Fatnassi, Ibrahim & Tiwari, Aviral Kumar, 2016. "Neoclassical finance, behavioral finance and noise traders: Assessment of gold–oil markets," Finance Research Letters, Elsevier, vol. 17(C), pages 33-40.

  18. António Rua & Miguel de Carvalho, 2010. "Tracking the US Business Cycle With a Singular Spectrum Analysis," Working Papers w201009, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Miguel de Carvalho & Gabriel Martos, 2022. "Modeling interval trendlines: Symbolic singular spectrum analysis for interval time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 167-180, January.
    2. Svatopluk KAPOUNEK & Jitka POMĚNKOVÁ, 2013. "The endogeneity of optimum currency area criteria in the context of financial crisis: Evidence from the time-frequency domain analysis," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 59(9), pages 389-395.
    3. Groth, Andreas & Ghil, Michael & Hallegatte, Stephane & Dumas, Patrice, 2012. "The Role of Oscillatory Modes in U.S. Business Cycles," Economy and Society 127421, Fondazione Eni Enrico Mattei (FEEM).
    4. Bógalo, Juan & Poncela, Pilar & Senra, Eva, 2017. "Automatic Signal Extraction for Stationary and Non-Stationary Time Series by Circulant SSA," MPRA Paper 76023, University Library of Munich, Germany.
    5. de Carvalho, Miguel & Rua, António, 2017. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.
    6. Lisa Sella & Gianna Vivaldo & Andreas Groth & Michael Ghil, 2016. "Economic Cycles and Their Synchronization: A Comparison of Cyclic Modes in Three European Countries," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 25-48, September.
    7. Paulo Canas Rodrigues & Olushina Olawale Awe & Jonatha Sousa Pimentel & Rahim Mahmoudvand, 2020. "Modelling the Behaviour of Currency Exchange Rates with Singular Spectrum Analysis and Artificial Neural Networks," Stats, MDPI, vol. 3(2), pages 1-21, June.
    8. Josu Arteche & Javier García‐Enríquez, 2022. "Singular spectrum analysis for value at risk in stochastic volatility models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 3-16, January.
    9. Lisa Sella & Gianna Vivaldo & Andreas Groth & Michael Ghil, 2016. "Economic Cycles and Their Synchronization: A Comparison of Cyclic Modes in Three European Countries," Post-Print hal-01701122, HAL.
    10. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    11. Hua, Jia-Chen & Roy, Sukesh & McCauley, Joseph L. & Gunaratne, Gemunu H., 2016. "Using dynamic mode decomposition to extract cyclic behavior in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 172-180.
    12. Juan Bógalo & Pilar Poncela & Eva Senra, 2021. "Circulant Singular Spectrum Analysis to Monitor the State of the Economy in Real Time," Mathematics, MDPI, vol. 9(11), pages 1-17, May.
    13. Roman Marsalek & Jitka Pomenkova & Svatopluk Kapounek, 2014. "A Wavelet-Based Approach to Filter Out Symmetric Macroeconomic Shocks," Computational Economics, Springer;Society for Computational Economics, vol. 44(4), pages 477-488, December.
    14. Rocco S, Claudio M., 2013. "Singular spectrum analysis and forecasting of failure time series," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 126-136.
    15. Hicham M. Hachem, 2017. "How Moderate was the Great Moderation and how Destabilizing is Secular Stagnation? Fiscal and monetary policy implications based on åvidence from US macro data," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 2, pages 226-236, June.
    16. Papailias, Fotis & Thomakos, Dimitrios, 2017. "EXSSA: SSA-based reconstruction of time series via exponential smoothing of covariance eigenvalues," International Journal of Forecasting, Elsevier, vol. 33(1), pages 214-229.
    17. Coussin, Maximilien, 2022. "Singular spectrum analysis for real-time financial cycles measurement," Journal of International Money and Finance, Elsevier, vol. 120(C).

  19. António Rua & Maximiano Pinheiro, 2009. "Dynamic factor models with jagged edge panel data: Taking on board the dynamics of the idiosyncratic components," Working Papers w200913, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Francisco Corona & Pilar Poncela & Esther Ruiz, 2017. "Determining the number of factors after stationary univariate transformations," Empirical Economics, Springer, vol. 53(1), pages 351-372, August.
    2. Jin, Sainan & Miao, Ke & Su, Liangjun, 2021. "On factor models with random missing: EM estimation, inference, and cross validation," Journal of Econometrics, Elsevier, vol. 222(1), pages 745-777.
    3. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    4. Poncela, Pilar, 2015. "Small versus big-data factor extraction in Dynamic Factor Models: An empirical assessment," DES - Working Papers. Statistics and Econometrics. WS ws1502, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. António Rua & Francisco Dias, 2020. "A non-hierarchical dynamic factor model for three-way data," Working Papers w202007, Banco de Portugal, Economics and Research Department.
    6. Dias, Francisco & Pinheiro, Maximiano & Rua, António, 2015. "Forecasting Portuguese GDP with factor models: Pre- and post-crisis evidence," Economic Modelling, Elsevier, vol. 44(C), pages 266-272.
    7. Poncela, Pilar, 2021. "Dynamic factor models: does the specification matter?," DES - Working Papers. Statistics and Econometrics. WS 32210, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    9. Alvarez, Rocio & Camacho, Maximo & Perez-Quiros, Gabriel, 2016. "Aggregate versus disaggregate information in dynamic factor models," International Journal of Forecasting, Elsevier, vol. 32(3), pages 680-694.

  20. António Rua & Luís Catela Nunes, 2009. "International comovement of stock market returns: a wavelet analysis," Working Papers w200904, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Bossman, Ahmed & Gubareva, Mariya & Agyei, Samuel Kwaku & Vo, Xuan Vinh, 2024. "Time-frequency comovements between environmental cryptocurrency sentiment and faith-based sectoral stocks," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 699-719.
    2. Marfatia, Hardik A., 2017. "A fresh look at integration of risks in the international stock markets: A wavelet approach," Review of Financial Economics, Elsevier, vol. 34(C), pages 33-49.
    3. Jens J. Krüger, 2021. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 293-319, December.
    4. Khalfaoui, Rabeh & Padhan, Hemachandra & Tiwari, Aviral Kumar & Hammoudeh, Shawkat, 2020. "Understanding the time-frequency dynamics of money demand, oil prices and macroeconomic variables: The case of India," Resources Policy, Elsevier, vol. 68(C).
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  21. António Rua & Cláudia Duarte & Francisco Craveiro Dias, 2008. "Inflation expectations in the euro area: Are consumers rational?," Working Papers w200823, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Konstantin Makrelov & Channing Arndt & Rob Davies & Laurence Harris, 2018. "Stock-and-flow-consistent macroeconomic model for South Africa," WIDER Working Paper Series wp-2018-7, World Institute for Development Economic Research (UNU-WIDER).
    2. Makrelov, Konstantin & Arndt, Channing & Davies, Rob & Harris, Laurence, 2020. "Balance sheet changes and the impact of financial sector risk-taking on fiscal multipliers," Economic Modelling, Elsevier, vol. 87(C), pages 322-343.
    3. Péter Gábriel, 2010. "Household inflation expectations and inflation dynamics," MNB Working Papers 2010/12, Magyar Nemzeti Bank (Central Bank of Hungary).
    4. Magdalena Szyszko, 2017. "Central Banks Inflation Forecast and Expectations. A Comparative Analysis," Prague Economic Papers, Prague University of Economics and Business, vol. 2017(3), pages 286-299.
    5. Martina Vránková, 2012. "Inflation Targeting and Behavioural Economics: Introduction," Proceedings of FIKUSZ '12, in: Pál Michelberger (ed.),Proceedings of FIKUSZ '12, pages 91-100, Óbuda University, Keleti Faculty of Business and Management.
    6. Gabriele Galati & Peter Heemeijer & Richhild Moessner, 2011. "How do inflation expectations form? New insights from a high-frequency survey," BIS Working Papers 349, Bank for International Settlements.
    7. Puah, Chin-Hong & Wong, Shirly Siew-Ling & Habibullah, Muzafar Shah, 2012. "Rationality of business operational forecasts: evidence from Malaysian distributive trade sector," MPRA Paper 37599, University Library of Munich, Germany.
    8. Piotr Białowolski, 2016. "The influence of negative response style on survey-based household inflation expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(2), pages 509-528, March.
    9. Chin-Hong Puah & Shirly Siew-Ling Wong & Venus Khim-Sen Liew, 2013. "Testing rational expectations hypothesis in the manufacturing sector in Malaysia," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 14(2), pages 303-316, April.
    10. Ornela SHALARI & Fejzi KOLANECI, 2014. "Statistical analysis of the inflation in the case of Albania," EuroEconomica, Danubius University of Galati, issue 2(33), pages 67-77, November.
    11. Wong, Shirly Siew-Ling & Puah, Chin-Hong & Shazali, Abu Mansor, 2011. "Survey Evidence on the Rationality of Business Expectations: Implications from the Malaysian Agricultural Sector," MPRA Paper 36661, University Library of Munich, Germany.
    12. Peter, Eckley, 2015. "(Non)rationality of consumer inflation perceptions," MPRA Paper 77082, University Library of Munich, Germany.
    13. Carin van der Cruijsen & Anna Samarina, 2021. "Trust in the ECB in turbulent times," Working Papers 722, DNB.

  22. G. Rünstler & K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze, 2008. "Short-Term Forecasting of GDP Using Large Monthly Datasets: A Pseudo Real-Time Forecast Evaluation Exercise," Bank of Lithuania Working Paper Series 1, Bank of Lithuania.

    Cited by:

    1. Marie Bessec, 2013. "Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 500-511, September.
    2. Dorrucci, Ettore & Meyer-Cirkel, Alexis & Santabárbara, Daniel, 2009. "Domestic financial development in emerging economies: evidence and implications," Occasional Paper Series 102, European Central Bank.
    3. Sturm, Michael & Adolf, Petra & Peschel, Dominik & Stráský, Jan, 2008. "The Gulf Cooperation Council countries: economic structures, recent developments and role in the global economy," Occasional Paper Series 92, European Central Bank.
    4. Audrone Jakaitiene & Stephane Dees, 2012. "Forecasting the World Economy in the Short Term," The World Economy, Wiley Blackwell, vol. 35(3), pages 331-350, March.
    5. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    6. Ard Reijer, 2013. "Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets," Empirical Economics, Springer, vol. 44(2), pages 435-453, April.
    7. Taglioni, Daria & Straub, Roland & Bussière, Matthieu & Pérez-Barreiro, Emilia, 2010. "Protectionist responses to the crisis – global trends and implications," Occasional Paper Series 110, European Central Bank.
    8. Deicy J. Cristiano & Manuel D. Hernández & José David Pulido, 2012. "Pronósticos de corto plazo en tiempo real para la actividad económica colombiana," Borradores de Economia 9827, Banco de la Republica.
    9. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    10. Francisco Dias & Cláudia Duarte & António Rua, 2010. "Inflation expectations in the euro area: are consumers rational?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 146(3), pages 591-607, September.
    11. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
    12. Hubrich, Kirstin & Karlsson, Tohmas, 2010. "Trade consistency in the context of the Eurosystem projection exercises - an overview," Occasional Paper Series 108, European Central Bank.
    13. Laurent Ferrara & Dominique Guegan & Patrick Rakotomarolahy, 2010. "GDP nowcasting with ragged-edge data: a semi-parametric modeling," Post-Print halshs-00460461, HAL.
    14. Siliverstovs Boriss & Kholodilin Konstantin A., 2012. "Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(4), pages 429-444, August.
    15. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    16. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
    17. Julius Stakenas, 2012. "Generating short-term forecasts of the Lithuanian GDP using factor models," Bank of Lithuania Working Paper Series 13, Bank of Lithuania.
    18. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
    19. Filippo Di Mauro & Katrin Forster, "undated". "Globalisation and the competitiveness of the Euro area," Working Papers 5, Department of the Treasury, Ministry of the Economy and of Finance.
    20. Roland Beck & Michael Fidora, 2008. "The impact of sovereign wealth funds on global financial markets," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 43(6), pages 349-358, November.
    21. Sturm, Michael & Gurtner, François & González Alegre, Juan, 2009. "Fiscal policy challenges in oil-exporting countries: a review of key issues," Occasional Paper Series 104, European Central Bank.
    22. Le Breton, Gwenaël & Be Duc, Louis, 2009. "Flow-of-funds analysis at the ECB: framework and applications," Occasional Paper Series 105, European Central Bank.
    23. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72.
    24. Winkler, Adalbert & Schokker, Hubert & Cocozza, Emidio & Herzberg, Valerie & Móré, Csaba & de Lannoy, Anthony & Gardó, Sándor & Chmielewski, Tomasz & Polgár, Éva Katalin & Habib, Maurizio Michael & Br, 2008. "Financial stability challenges in candidate countries managing the transition to deeper and more market-oriented financial systems," Occasional Paper Series 95, European Central Bank.
    25. Liebermann, Joelle, 2011. "Real-Time Nowcasting of GDP: Factor Model versus Professional Forecasters," Research Technical Papers 3/RT/11, Central Bank of Ireland.
    26. Barhoumi, K. & Rünstler, G. & Cristadoro, R. & Den Reijer, A. & Jakaitiene, A. & Jelonek, P. & Rua, A. & Ruth, K. & Benk, S. & Van Nieuwenhuyze, C., 2008. "Short-term forecasting of GDP using large monthly datasets: a pseudo real-time forecast evaluation exercise," Working papers 215, Banque de France.
    27. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank.
    28. Germán López, 2015. "Forecast Accuracy of Small and Large Scale Dynamic Factor Models in Developing Economies," Working Papers. Serie AD 2015-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    29. D’Elia Enrico, 2014. "Predictions vs. Preliminary Sample Estimates: The Case of Eurozone Quarterly GDP," Journal of Official Statistics, Sciendo, vol. 30(3), pages 499-520, September.
    30. Mayerlen, Frank & Sola, Pierre & Be Duc, Louis, 2008. "The monetary presentation of the euro area balance of payments," Occasional Paper Series 96, European Central Bank.
    31. Laurent Ferrara & Dominique Guégan & Patrick Rakotomarolahy, 2010. "GDP nowcasting with ragged-edge data: a semi-parametric modeling," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 186-199.
    32. Marianna Cervená & Martin Schneider, 2010. "Short-term forecasting GDP with a DSGE model augmented by monthly indicators," Working Papers 163, Oesterreichische Nationalbank (Austrian Central Bank).
    33. Poloni, Paolo & Agresti, Anna Maria & Baudino, Patrizia, 2008. "The ECB and IMF indicators for the macro-prudential analysis of the banking sector: a comparison of the two approaches," Occasional Paper Series 99, European Central Bank.
    34. Kennickell, Arthur & Fitzpatrick, Trevor & Ehrmann, Michael & Bonci, Riccardo & Museux, Jean-Marc & Honkkila, Juha & Vilmunen, Jouko & Herrala, Risto & Komprej, Irena & Jeran, Matjaž & Geršak, Uroš & , 2009. "Survey data on household finance and consumption: research summary and policy use," Occasional Paper Series 100, European Central Bank.
    35. Katerina Arnostova & David Havrlant & Luboš Rùžièka & Peter Tóth, 2011. "Short-Term Forecasting of Czech Quarterly GDP Using Monthly Indicators," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(6), pages 566-583, December.
    36. Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Nowcasting," Working Papers ECARES ECARES 2010-021, ULB -- Universite Libre de Bruxelles.
    37. Ch. Piette & G. Langenus, 2014. "Using BREL to nowcast the Belgian business cycle: the role of survey data," Economic Review, National Bank of Belgium, issue i, pages 75-98, June.
    38. Rüffer, Rasmus & di Mauro, Filippo & Bunda, Irina, 2008. "The changing role of the exchange rate in a globalised economy," Occasional Paper Series 94, European Central Bank.
    39. Reichlin, Lucrezia & Camba-Mendez, Gonzalo & Angelini, Elena & Rünstler, Gerhard & Giannone, Domenico, 2008. "Short-term Forecasts of Euro Area GDP Growth," CEPR Discussion Papers 6746, C.E.P.R. Discussion Papers.
    40. António Rua, 2011. "A wavelet approach for factor‐augmented forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(7), pages 666-678, November.
    41. Köhler-Ulbrich, Petra & Asimakopoulos, Yannis & Doyle, Nicola & Magono, Ruth & Zachary, Marie-Denise & Walko, Zoltan & Stoess, Elmar & Kok, Christoffer & Wagner, Karin & Valckx, Nico & Martínez Pagés,, 2009. "Housing finance in the euro area," Occasional Paper Series 101, European Central Bank.
    42. Smith Paul, 2016. "Nowcasting UK GDP during the depression," Working Papers 1606, University of Strathclyde Business School, Department of Economics.
    43. Maximo Camacho & Gabriel Perez-Quiros, 2008. "Introducing the EURO-STING: Short Term INdicator of Euro Area Growth," Working Papers 0807, Banco de España.
    44. Mr. Troy D Matheson, 2011. "New Indicators for Tracking Growth in Real Time," IMF Working Papers 2011/043, International Monetary Fund.
    45. Morgese Borys, Magdalena & Polgár, Éva Katalin & Zlate, Andrei, 2008. "Real convergence and the determinants of growth in EU candidate and potential candidate countries: a panel data approach," Occasional Paper Series 86, European Central Bank.
    46. di Mauro, Filippo & Kaufmann, Robert K. & Karadeloglou, Pavlos, 2008. "Will oil prices decline over the long run?," Occasional Paper Series 98, European Central Bank.
    47. Gómez-Salvador, Ramón & Leiner-Killinger, Nadine, 2008. "An analysis of youth unemployment in the euro area," Occasional Paper Series 89, European Central Bank.
    48. Kai Carstensen & Steffen Henzel & Johannes Mayr & Klaus Wohlrabe, 2009. "IFOCAST: Methoden der ifo-Kurzfristprognose," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(23), pages 15-28, December.
    49. Trabandt, Mathias & Attinasi, Maria Grazia & Stark, Jürgen & Lalouette, Laure & Nickel, Christiane & Valenta, Vilém & van Riet, Ad & Leiner-Killinger, Nadine & Afonso, António & Warmedinger, Thomas & , 2010. "Euro area fiscal policies and the crisis," Occasional Paper Series 109, European Central Bank.
    50. Kajal Lahiri & George Monokroussos, 2011. "Nowcasting US GDP: The role of ISM Business Surveys," Discussion Papers 11-01, University at Albany, SUNY, Department of Economics.
    51. Liebermann, Joëlle, 2012. "Short-term forecasting of quarterly gross domestic product growth," Quarterly Bulletin Articles, Central Bank of Ireland, pages 74-84, February.
    52. Juraj Hucek & Alexander Karsay & Marian Vavra, 2015. "Short-term Forecasting of Real GDP Using Monthly Data," Working and Discussion Papers OP 1/2015, Research Department, National Bank of Slovakia.
    53. D'Elia, Enrico, 2010. "Predictions vs preliminary sample estimates," MPRA Paper 36070, University Library of Munich, Germany.
    54. Ritter, Raymond, 2009. "Transnational governance in global finance: the principles for stable capital flows and fair debt restructuring in emerging markets," Occasional Paper Series 103, European Central Bank.
    55. Liu, Philip & Matheson, Troy & Romeu, Rafael, 2012. "Real-time forecasts of economic activity for Latin American economies," Economic Modelling, Elsevier, vol. 29(4), pages 1090-1098.
    56. Vitale, Giovanni & Moutot, Philippe, 2009. "Monetary policy strategy in a global environment," Occasional Paper Series 106, European Central Bank.
    57. Strauch, Rolf & Gómez-Salvador, Ramón & Ward-Warmedinger, Melanie & Turunen, Jarkko & Leiner-Killinger, Nadine & Masuch, Klaus, 2008. "Labour supply and employment in the euro area countries: developments and challenges," Occasional Paper Series 87, European Central Bank.
    58. Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 28-49, February.
    59. Bjørn Eraker & Ching Wai (Jeremy) Chiu & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2015. "Bayesian Mixed Frequency VARs," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 698-721.
    60. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.
    61. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    62. Stéphanie Guichard & Elena Rusticelli, 2011. "A Dynamic Factor Model for World Trade Growth," OECD Economics Department Working Papers 874, OECD Publishing.
    63. KETENCI, Natalya, 2010. "Cointegration Analysis Of Tourism Demand For Turkey," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 10(1).
    64. Winkler, Adalbert & Polański, Zbigniew, 2008. "Russia, EU enlargement and the euro," Occasional Paper Series 93, European Central Bank.
    65. Massimiliano Marcellino & Christian Schumacher, 2010. "Factor MIDAS for Nowcasting and Forecasting with Ragged‐Edge Data: A Model Comparison for German GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 518-550, August.
    66. Мекенбаева Камила // Mekenbayeva Kamila & Karel Musil, 2017. "Система прогнозирования в Национальном Банке Казахстана: наукаст на основа опросов // Forecasting system at the National Bank of Kazakhstan: survey-based nowcasting," Working Papers #2017-1, National Bank of Kazakhstan.
    67. Laurent Ferrara & Dominique Guegan & Patrick Rakotomarolahy, 2009. "GDP nowcasting with ragged-edge data : A semi-parametric modelling," Post-Print halshs-00344839, HAL.
    68. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting monthly industrial production in real-time: from single equations to factor-based models," Empirical Economics, Springer, vol. 39(2), pages 303-336, October.
    69. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
    70. Chen, Pu, 2009. "A Note on Updating Forecasts When New Information Arrives between Two Periods," Economics Discussion Papers 2009-22, Kiel Institute for the World Economy (IfW Kiel).
    71. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.
    72. Mäkinen, Mikko, 2016. "Nowcasting of Russian GDP growth," BOFIT Policy Briefs 4/2016, Bank of Finland Institute for Emerging Economies (BOFIT).
    73. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.
    74. C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.

  23. António Rua & Francisco Craveiro Dias, 2008. "Forecasting Using Targeted Diffusion Indexes," Working Papers w200807, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. José R. Maria & Sara Serra, . "Previsão do Investimento em Portugal com Base em Indicadores Qualitativos e Quantitativos," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    2. Jo~ao B. Assunc{c}~ao & Pedro Afonso Fernandes, 2022. "Nowcasting the Portuguese GDP with Monthly Data," Papers 2206.06823, arXiv.org.
    3. José R. Maria & Sara Serra, 2008. "Forecasting investment: A fishing contest using survey data," Working Papers w200818, Banco de Portugal, Economics and Research Department.
    4. João B. Assunção & Pedro Afonso Fernandes, 2022. "Nowcasting GDP: An Application to Portugal," Forecasting, MDPI, vol. 4(3), pages 1-15, August.
    5. Demetrescu, Matei & Hacıoğlu Hoke, Sinem, 2019. "Predictive regressions under asymmetric loss: Factor augmentation and model selection," International Journal of Forecasting, Elsevier, vol. 35(1), pages 80-99.
    6. Goodness C. Aye & Mehmet Balcilar Author-Name-First Mehmet & Rangan Gupta & Anandamayee Majumdar, 2014. "Forecasting Aggregate Retail Sales: The Case of South Africa," Working Papers 15-21, Eastern Mediterranean University, Department of Economics.
    7. Dias, Francisco & Pinheiro, Maximiano & Rua, António, 2015. "Forecasting Portuguese GDP with factor models: Pre- and post-crisis evidence," Economic Modelling, Elsevier, vol. 44(C), pages 266-272.
    8. Francisco Dias & Maximiano Pinheiro & António Rua, 2018. "A bottom-up approach for forecasting GDP in a data-rich environment," Applied Economics Letters, Taylor & Francis Journals, vol. 25(10), pages 718-723, June.
    9. Johannes Tang Kristensen, 2013. "Diffusion Indexes with Sparse Loadings," CREATES Research Papers 2013-22, Department of Economics and Business Economics, Aarhus University.
    10. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.

  24. António Rua & Cláudia Duarte & Francisco Craveiro Dias, 2007. "Inflation (mis)perceptions in the euro area," Working Papers w200715, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Bernd Hayo & Florian Neumeier, 2018. "Households’ Inflation Perceptions and Expectations: Survey Evidence from New Zealand," ifo Working Paper Series 255, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Tomasz Lyziak, 2010. "Measuring consumer inflation expectations in Europe and examining their forward-lookingness," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The IFC's contribution to the 57th ISI Session, Durban, August 2009, volume 33, pages 155-201, Bank for International Settlements.
    3. Francisco Dias & Cláudia Duarte & António Rua, 2010. "Inflation expectations in the euro area: are consumers rational?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 146(3), pages 591-607, September.
    4. Sarah M. Lein & Thomas Maag, 2011. "The Formation Of Inflation Perceptions: Some Empirical Facts For European Countries," Scottish Journal of Political Economy, Scottish Economic Society, vol. 58(2), pages 155-188, May.
    5. Ewa Stanisławska, 2019. "Consumers’ Perception of Inflation in Inflationary and Deflationary Environment," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(1), pages 41-71, April.
    6. Arnold, Ivo J.M., 2024. "The effect of fragmentation risk on monetary conditions in the euro area," Journal of International Money and Finance, Elsevier, vol. 146(C).
    7. Pooja Kapoor & Sujata Kar, 2022. "A Critical Evaluation of the Consumer Confidence Survey from India," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 7, pages 172-198.
    8. Tomasz Łyziak, 2013. "Non-Positive Scaling Factor in Probability Quantification Methods: Deriving Consumer Inflation Perceptions and Expectations in the Whole Euro Area and Ireland," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 55(1), pages 77-98, March.
    9. Arnold, Ivo J.M. & Soederhuizen, Beau, 2016. "Internal or external devaluation? What does the EC Consumer Survey tell us about macroeconomic adjustment in the Euro area?," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 88-103.

  25. António Rua & Hugo Reis, 2006. "An input-output analysis: linkages vs leakages," Working Papers w200617, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. João Carlos Lopes & João Ferreira do Amaral, 2013. "The Structure and Evolution of Production, Employment and Human Capital in Portugal: an Input-Output Approach," Working Papers Department of Economics 2013/24, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    2. Surugiu, Marius-Răzvan & Surugiu, Camelia, 2010. "Comparative structural approaches regarding relevant indicators of Input-Output analysis at macro and sectoral level: a case study of some European Union countries," MPRA Paper 23772, University Library of Munich, Germany, revised 25 Oct 2010.
    3. Ezzahid, Elhadj & Chatri, Abdellatif, 2015. "Imports contents, value added generation and structural change in morocco: input output analysis," MPRA Paper 63512, University Library of Munich, Germany.
    4. ELALAOUI, Aicha & EZZAHIDI, Elhadj & TOUNSI, Said & NIHOO, Abdelazziz, 2011. "Key sectors in the Moroccan economy: an application of input-output analysis," MPRA Paper 56822, University Library of Munich, Germany, revised 2012.
    5. Zhen, Wei & Zhong, Zhangqi & Wang, Yichen & Miao, Lu & Qin, Quande & Wei, Yi-Ming, 2019. "Evolution of urban household indirect carbon emission responsibility from an inter-sectoral perspective: A case study of Guangdong, China," Energy Economics, Elsevier, vol. 83(C), pages 197-207.
    6. João Ferreira do Amaral & João Carlos Lopes, 2015. "The Trade-off Unemployment Rate/External Deficit: Assessing the Economic Adjustment Program of the Troika (European Commission, ECB and IMF) for Portugal using an Input-Output Approach," Working Papers Department of Economics 2015/04, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    7. Tounsi, Said & Ezzahid, El hadj & Alaoui, Aicha El & Nihou, Abdelaziz, 2013. "Key sectors in the Moroccan economy: An application of input-output analysis," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 7, pages 1-19.
    8. Mehmet Demiral, 2016. "Has EU Accession Caused Structural Change in New Entrants? Intersectoral Linkage Analyses on Bulgaria and Romania," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 671-681.
    9. Calzada Olvera, Beatriz & Foster-McGregor, Neil, 2018. "What is the potential of natural resource based industrialisation in Latin America? An Input-Output analysis of the extractive sectors," MERIT Working Papers 2018-015, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    10. João Amador & Sónia Cabral, . "A Especialização Vertical no Comércio Internacional Português," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    11. João Amador & Sónia Cabral, 2008. "International Fragmentation of Production in the Portuguese Economy: What do Different Measures Tell Us?," Working Papers w200811, Banco de Portugal, Economics and Research Department.
    12. Chatri, Abdellatif & Maarouf, Abdelwahab & Ezzahid, Elhaj, 2015. "Productivité agricole, intégration et transformation structurelle de l’économie marocaine [Agricultural productivity, integration and structural transformation of the Moroccan economy]," MPRA Paper 71774, University Library of Munich, Germany, revised Jan 2016.
    13. Nuno Leitão & Horácio Faustino & Yushi Yoshida, 2009. "Determinants of Vertical Intra-Industry Trade in the Automobile Manufacturing Sector: globalization and fragmentation," Working Papers Department of Economics 2009/06, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    14. Bhoj Raj Khanal & Christopher Gan & Susanne Becken, 2014. "Tourism Inter-Industry Linkages in the Lao PDR Economy: An Input—Output Analysis," Tourism Economics, , vol. 20(1), pages 171-194, February.

  26. António Rua & Cláudia Duarte, 2005. "Forecasting Inflation Through a Bottom-Up Approach: The Portuguese Case," Working Papers w200502, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. O. De Bandt & E. Michaux & C. Bruneau & A. Flageollet, 2007. "Forecasting inflation using economic indicators: the case of France," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(1), pages 1-22.
    2. Barakchian , Seyed Mahdi & Bayat , Saeed & Karami , Hooman, 2013. "Common Factors of CPI Sub-aggregates and Forecast of Inflation," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 8(4), pages 1-17, October.

  27. António Rua & Luís Catela Nunes, 2003. "Coincident and Leading Indicators for the Euro Area: A Frequency Band Approach," Working Papers w200307, Banco de Portugal, Economics and Research Department.

    Cited by:

    1. Jens J. Krüger, 2021. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 293-319, December.
    2. Gazi Salah Uddin & Mohamed Arouri & Aviral Kumar Tiwari, 2014. "Co-movements between Germany and International Stock Markets: Some New Evidence from DCC-GARCH and Wavelet Approaches," Working Papers 2014-143, Department of Research, Ipag Business School.
    3. de Carvalho, Miguel & Rua, António, 2017. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.
    4. Luc Dresse & Christophe Van Nieuwenhuyze, 2008. "Do survey indicators let us see the business cycle ? A frequency decomposition," Working Paper Research 131, National Bank of Belgium.
    5. Cravo, Túlio A., 2011. "Are small employers more cyclically sensitive? Evidence from Brazil," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 754-769.
    6. Rua, António, 2010. "Measuring comovement in the time-frequency space," Journal of Macroeconomics, Elsevier, vol. 32(2), pages 685-691, June.
    7. Abberger, Klaus & Graff, Michael & Siliverstovs, Boriss & Sturm, Jan-Egbert, 2018. "Using rule-based updating procedures to improve the performance of composite indicators," Economic Modelling, Elsevier, vol. 68(C), pages 127-144.
    8. Éric Dubois, 2006. "Présentation générale," Économie et Prévision, Programme National Persée, vol. 172(1), pages 1-9.
    9. António Rua & Artur Silva Lopes, 2012. "Cohesion within the euro area and the U. S.: a wavelet-based view," Working Papers w201204, Banco de Portugal, Economics and Research Department.
    10. Soh, Ann-Ni, 2020. "A Review on the Leading Indicator Approach towards Economic Forecasting," MPRA Paper 103854, University Library of Munich, Germany.
    11. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2007. "Consumer confidence in Europe : United in diversity," Other publications TiSEM ea8c3268-2c0b-4fcc-9d4a-6, Tilburg University, School of Economics and Management.
    12. Miljkovic, Dragan & Vatsa, Puneet, 2023. "On the linkages between energy and agricultural commodity prices: A dynamic time warping analysis," International Review of Financial Analysis, Elsevier, vol. 90(C).
    13. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    14. Ftiti, Zied & Guesmi, Khaled & Abid, Ilyes, 2016. "Oil price and stock market co-movement: What can we learn from time-scale approaches?," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 266-280.
    15. Gallegati, Marco & Delli Gatti, Domenico, 2018. "Macrofinancial imbalances in historical perspective: A global crisis index," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 190-205.
    16. Krüger, Jens J., 2024. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 149438, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    17. Junyi Shi, 2020. "Re-Measurement Of Short-Term International Capital Flows And Its Application: Evidence From China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 65(06), pages 1645-1665, December.
    18. Kosei Fukuda, 2008. "Differentiating between business cycles and growth cycles: evidence from 15 developed countries," Applied Economics, Taylor & Francis Journals, vol. 40(7), pages 875-883.

  28. Joao Valle e Azevedo & Siem Jan Koopman & Antonio Rua, 2003. "Tracking Growth and the Business Cycle: a Stochastic Common Cycle Model for the Euro Area," Tinbergen Institute Discussion Papers 03-069/4, Tinbergen Institute.

    Cited by:

    1. Cayen, Jean-Philippe & van Norden, Simon, 2004. "The reliability of Canadian output gap estimates," Discussion Paper Series 1: Economic Studies 2004,29, Deutsche Bundesbank.
    2. Edoardo Otranto, 2005. "Extraction of Common Signal from Series with Different Frequency," Econometrics 0502011, University Library of Munich, Germany.
    3. Julien Garnier, 2004. "UK in or UK Out? A Common Cycle Analysis Between the UK and the Euro Zone," Working Papers 2004-17, CEPII research center.

Articles

  1. João Pedro Pereira & Vasco Pesquita & Paulo M. M. Rodrigues & António Rua, 2019. "Market integration and the persistence of electricity prices," Empirical Economics, Springer, vol. 57(5), pages 1495-1514, November.
    See citations under working paper version above.
  2. Rua, António, 2018. "Modelling currency demand in a small open economy within a monetary union," Economic Modelling, Elsevier, vol. 74(C), pages 88-96.
    See citations under working paper version above.
  3. Francisco Dias & Maximiano Pinheiro & António Rua, 2018. "A bottom-up approach for forecasting GDP in a data-rich environment," Applied Economics Letters, Taylor & Francis Journals, vol. 25(10), pages 718-723, June.

    Cited by:

    1. Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021. "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, vol. 96(C), pages 445-454.
    2. Yutaka Kurihara & Akio Fukushima, 2019. "AR Model or Machine Learning for Forecasting GDP and Consumer Price for G7 Countries," Applied Economics and Finance, Redfame publishing, vol. 6(3), pages 1-6, May.

  4. João Pedro Pereira & António Rua, 2018. "Asset Pricing with a Bank Risk Factor," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(5), pages 993-1032, August.
    See citations under working paper version above.
  5. Duarte, Cláudia & Rodrigues, Paulo M.M. & Rua, António, 2017. "A mixed frequency approach to the forecasting of private consumption with ATM/POS data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 61-75.

    Cited by:

    1. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2022. "Machine Learning Time Series Regressions With an Application to Nowcasting," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1094-1106, June.
    2. Raquel Nadal Cesar Gonçalves, 2022. "Nowcasting Brazilian GDP with Electronic Payments Data," Working Papers Series 564, Central Bank of Brazil, Research Department.
    3. Valadkhani, Abbas & Smyth, Russell, 2017. "How do daily changes in oil prices affect US monthly industrial output?," Energy Economics, Elsevier, vol. 67(C), pages 83-90.
    4. Zhang, Yue-Jun & Wang, Jin-Li, 2019. "Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models," Energy Economics, Elsevier, vol. 78(C), pages 192-201.
    5. Guillermo Carlomagno & Nicolas Eterovic & L. G. Hernández-Román, 2023. "Disentangling Demand and Supply Inflation Shocks from Chilean Electronic Payment Data," Working Papers Central Bank of Chile 986, Central Bank of Chile.
    6. Ludmila Fadejeva & Boriss Siliverstovs & Karlis Vilerts & Anete Brinke, 2022. "Consumer Spending in the Covid-19 Pandemic: Evidence from Card Transactions in Latvia," Discussion Papers 2022/01, Latvijas Banka.
    7. García, Juan R. & Pacce, Matías & Rodrigo, Tomasa & Ruiz de Aguirre, Pep & Ulloa, Camilo A., 2021. "Measuring and forecasting retail trade in real time using card transactional data," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1235-1246.
    8. Timo Wollmershäuser & Stefan Ederer & Maximilian Fell & Friederike Fourné & Max Lay & Robert Lehmann & Sebastian Link & Sascha Möhrle & Ann-Christin Rathje & Radek Šauer & Moritz Schasching & Marcus S, 2023. "ifo Konjunkturprognose Sommer 2023: Inflation flaut langsam ab – aber Konjunktur lahmt noch," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 76(Sonderaus), pages 01-53, June.
    9. James Chapman & Ajit Desai, 2021. "Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19," Staff Working Papers 21-2, Bank of Canada.
    10. Santiago Etchegaray Alvarez, 2022. "Proyecciones macroeconómicas con datos en frecuencias mixtas. Modelos ADL-MIDAS, U-MIDAS y TF-MIDAS con aplicaciones para Uruguay," Documentos de trabajo 2022004, Banco Central del Uruguay.
    11. Qifa Xu & Zezhou Wang & Cuixia Jiang & Yezheng Liu, 2023. "Deep learning on mixed frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2099-2120, December.
    12. James T. E. Chapman & Ajit Desai, 2022. "Macroeconomic Predictions using Payments Data and Machine Learning," Papers 2209.00948, arXiv.org.
    13. Gurgul Henryk & Suder Marcin, 2016. "Calendar and Seasonal Effects on the Size of Withdrawals from Atms Managed By Euronet," Statistics in Transition New Series, Statistics Poland, vol. 17(4), pages 691-722, December.
    14. Valentina Aprigliano & Guerino Ardizzi & Alessia Cassetta & Alessandro Cavallero & Simone Emiliozzi & Alessandro Gambini & Nazzareno Renzi & Roberta Zizza, 2021. "Exploiting payments to track Italian economic activity: the experience at Banca d’Italia," Questioni di Economia e Finanza (Occasional Papers) 609, Bank of Italy, Economic Research and International Relations Area.
    15. Ali B. Barlas & Seda Guler Mert & Berk Orkun Isa & Alvaro Ortiz & Tomasa Rodrigo & Baris Soybilgen & Ege Yazgan, 2024. "Big data financial transactions and GDP nowcasting: The case of Turkey," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 227-248, March.
    16. Galbraith, John W. & Tkacz, Greg, 2018. "Nowcasting with payments system data," International Journal of Forecasting, Elsevier, vol. 34(2), pages 366-376.
    17. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    18. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    19. Dean Croushore & Stephanie M. Wilshusen, 2020. "Forecasting Consumption Spending Using Credit Bureau Data," Working Papers 20-22, Federal Reserve Bank of Philadelphia.
    20. Bonino-Gayoso, Nicolás & García-Hiernaux, Alfredo, 2019. "TF-MIDAS: a new mixed-frequency model to forecast macroeconomic variables," MPRA Paper 93366, University Library of Munich, Germany.
    21. Anete Brinke & Ludmila Fadejeva & Boriss Siliverstovs & Kārlis Vilerts, 2023. "Assessing the informational content of card transactions for nowcasting retail trade: Evidence for Latvia," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 566-577, April.
    22. Ali B. Barlas & Seda Guler Mert & Berk Orkun Isa & Alvaro Ortiz & Tomasa Rodrigo & Baris Soybilgen & Ege Yazgan, 2021. "Big Data Information and Nowcasting: Consumption and Investment from Bank Transactions in Turkey," Papers 2107.03299, arXiv.org.
    23. María Gil & Javier J. Pérez & Alberto Urtasun, 2019. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
    24. Lourenço, Nuno & Rua, António, 2021. "The Daily Economic Indicator: tracking economic activity daily during the lockdown," Economic Modelling, Elsevier, vol. 100(C).
    25. Diego Bodas & Juan R. García López & Tomasa Rodrigo López & Pep Ruiz de Aguirre & Camilo A. Ulloa & Juan Murillo Arias & Juan de Dios Romero Palop & Heribert Valero Lapaz & Matías J. Pacce, 2019. "Measuring retail trade using card transactional data," Working Papers 1921, Banco de España.
    26. Andrianady, Josué R. & Rajaonarison, Njakanasandratra R. & Razanajatovo, Yves H., 2023. "Estimating Madagascar economic growth using the Mixed Data Sampling (MIDAS) approach," MPRA Paper 118267, University Library of Munich, Germany.
    27. Alberto Urtasun & Mara Gil & Javier J. Perez, 2017. "Nowcasting private consumption: traditional indicators, uncertainty measures, and the role of internet search query data," EcoMod2017 10745, EcoMod.
    28. Xu, Qifa & Zhuo, Xingxuan & Jiang, Cuixia & Liu, Xi & Liu, Yezheng, 2018. "Group penalized unrestricted mixed data sampling model with application to forecasting US GDP growth," Economic Modelling, Elsevier, vol. 75(C), pages 221-236.
    29. Maghyereh Aktham & Sweidan Osama & Awartani Basel, 2020. "Asymmetric Responses of Economic Growth to Daily Oil Price Changes: New Global Evidence from Mixed-data Sampling Approach," Review of Economics, De Gruyter, vol. 71(2), pages 81-99, August.
    30. Mahmut Gunay, 2020. "Nowcasting Turkish GDP with MIDAS: Role of Functional Form of the Lag Polynomial," Working Papers 2002, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.

  6. de Carvalho, Miguel & Rua, António, 2017. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.
    See citations under working paper version above.
  7. Rua, António, 2017. "A wavelet-based multivariate multiscale approach for forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 581-590.
    See citations under working paper version above.
  8. Elena Bobeica & Paulo Esteves & António Rua & Karsten Staehr, 2016. "Exports and domestic demand pressure: a dynamic panel data model for the euro area countries," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 152(1), pages 107-125, February.
    See citations under working paper version above.
  9. Dias, Francisco & Pinheiro, Maximiano & Rua, António, 2015. "Forecasting Portuguese GDP with factor models: Pre- and post-crisis evidence," Economic Modelling, Elsevier, vol. 44(C), pages 266-272.

    Cited by:

    1. Dušan Marković & Igor Mladenović & Miloš Milovančević, 2017. "RETRACTED ARTICLE: Estimation of the most influential science and technology factors for economic growth forecasting by soft computing technique," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1133-1146, May.
    2. Jo~ao B. Assunc{c}~ao & Pedro Afonso Fernandes, 2022. "Nowcasting the Portuguese GDP with Monthly Data," Papers 2206.06823, arXiv.org.
    3. Duarte, Cláudia & Rodrigues, Paulo M.M. & Rua, António, 2017. "A mixed frequency approach to the forecasting of private consumption with ATM/POS data," International Journal of Forecasting, Elsevier, vol. 33(1), pages 61-75.
    4. Sokolov-Mladenović, Svetlana & Milovančević, Milos & Mladenović, Igor, 2017. "Evaluation of trade influence on economic growth rate by computational intelligence approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 358-362.
    5. João B. Assunção & Pedro Afonso Fernandes, 2022. "Nowcasting GDP: An Application to Portugal," Forecasting, MDPI, vol. 4(3), pages 1-15, August.
    6. Petra Karanikić & Igor Mladenović & Svetlana Sokolov-Mladenović & Meysam Alizamir, 2017. "RETRACTED ARTICLE: Prediction of economic growth by extreme learning approach based on science and technology transfer," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1395-1401, May.
    7. Marković, Dušan & Petković, Dalibor & Nikolić, Vlastimir & Milovančević, Miloš & Petković, Biljana, 2017. "Soft computing prediction of economic growth based in science and technology factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 217-220.
    8. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
    9. Jiang, Yu & Guo, Yongji & Zhang, Yihao, 2017. "Forecasting China's GDP growth using dynamic factors and mixed-frequency data," Economic Modelling, Elsevier, vol. 66(C), pages 132-138.
    10. Poghosyan, Karen & Poghosyan, Ruben, 2021. "On the applicability of dynamic factor models for forecasting real GDP growth in Armenia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 28-46.
    11. Boriss Siliverstovs, 2015. "Dissecting Models' Forecasting Performance," KOF Working papers 15-397, KOF Swiss Economic Institute, ETH Zurich.
    12. Abdić Ademir & Resić Emina & Abdić Adem, 2020. "Modelling and forecasting GDP using factor model: An empirical study from Bosnia and Herzegovina," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 10-26, May.
    13. Abdić Ademir & Resić Emina & Abdić Adem & Rovčanin Adnan, 2020. "Nowcasting GDP of Bosnia and Herzegovina: A Comparison of Forecast Accuracy Models," South East European Journal of Economics and Business, Sciendo, vol. 15(2), pages 1-14, December.
    14. Đokić, Aleksandar & Jović, Srđan, 2017. "Evaluation of agriculture and industry effect on economic health by ANFIS approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 396-399.
    15. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    16. Kordanuli, Bojana & Barjaktarović, Lidija & Jeremić, Ljiljana & Alizamir, Meysam, 2017. "Appraisal of artificial neural network for forecasting of economic parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 515-519.
    17. Francisco Dias & Maximiano Pinheiro & António Rua, 2018. "A bottom-up approach for forecasting GDP in a data-rich environment," Applied Economics Letters, Taylor & Francis Journals, vol. 25(10), pages 718-723, June.
    18. Eric W. K. See-To & Eric W. T. Ngai, 2018. "Customer reviews for demand distribution and sales nowcasting: a big data approach," Annals of Operations Research, Springer, vol. 270(1), pages 415-431, November.
    19. Samvel S. Lazaryan & Nikita E. German, 2018. "Forecasting Current GDP Dynamics With Google Search Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 83-94, December.
    20. Milačić, Ljubiša & Jović, Srđan & Vujović, Tanja & Miljković, Jovica, 2017. "Application of artificial neural network with extreme learning machine for economic growth estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 285-288.
    21. Dimitar EFTIMOSKI, 2019. "Improving Short-Term Forecasting of Macedonian GDP: Comparing the Factor Model with the Macroeconomic Structural Equation Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 32-53, June.
    22. Igor Mladenović & Miloš Milovančević & Svetlana Sokolov-Mladenović, 2017. "RETRACTED ARTICLE: Analyzing of innovations influence on economic growth by fuzzy system," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1297-1304, May.
    23. Maksimović, Goran & Jović, Srđan & Jovanović, Radomir, 2017. "Economic growth rate management by soft computing approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 520-524.

  10. António Rua & Artur Silva Lopes, 2015. "Cohesion within the euro area and the US: A wavelet-based view," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2014(2), pages 63-76.
    See citations under working paper version above.
  11. Paulo Esteves & António Rua, 2015. "Is there a role for domestic demand pressure on export performance?," Empirical Economics, Springer, vol. 49(4), pages 1173-1189, December.
    See citations under working paper version above.
  12. Miguel Carvalho & António Rua, 2014. "Extremal Dependence in International Output Growth: Tales from the Tails," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(4), pages 605-620, August.
    See citations under working paper version above.
  13. Dias Francisco & Pinheiro Maximiano & Rua António, 2013. "Determining the number of global and country-specific factors in the euro area," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 573-617, December.

    Cited by:

    1. Simon Freyaldenhoven, 2017. "A Generalized Factor Model with Local Factors," 2017 Papers pfr361, Job Market Papers.
    2. Simon Freyaldenhoven, 2020. "Identification Through Sparsity in Factor Models," Working Papers 20-25, Federal Reserve Bank of Philadelphia.
    3. In Choi & Rui Lin & Yongcheol Shin, 2020. "Canonical Correlation-based Model Selection for the Multilevel Factors," Working Papers 2008, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    4. Kim Dukpa & Kim Yunjung & Bak Yuhyeon, 2017. "Multi-level factor analysis of bond risk premia," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(5), pages 1-19, December.
    5. António Rua & Francisco Dias, 2020. "A non-hierarchical dynamic factor model for three-way data," Working Papers w202007, Banco de Portugal, Economics and Research Department.
    6. Simon Freyaldenhoven, 2021. "Factor Models with Local Factors—Determining the Number of Relevant Factors," Working Papers 21-15, Federal Reserve Bank of Philadelphia.
    7. In Choi & Dukpa Kim & Yun Jung Kim & Noh-Sun Kwark, 2016. "A Multilevel Factor Model: Identification, Asymptotic Theory and Applications," Working Papers 1609, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    8. Byoungsoo Cho, 2020. "The Monetary Policy Reaction Function in Korea with Multi-level Factors," Korean Economic Review, Korean Economic Association, vol. 36, pages 353-376.
    9. Bai, Jushan & Liao, Yuan, 2016. "Efficient estimation of approximate factor models via penalized maximum likelihood," Journal of Econometrics, Elsevier, vol. 191(1), pages 1-18.
    10. Matteo Barigozzi & Marc Hallin & Stefano Soccorsi, 2017. "Identification of Global and National Shocks in International Financial Markets via General Dynamic Factor Models," Working Papers ECARES ECARES 2017-10, ULB -- Universite Libre de Bruxelles.

  14. M. de Carvalho & K. F. Turkman & A. Rua, 2013. "Dynamic threshold modelling and the US business cycle," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(4), pages 535-550, August.

    Cited by:

    1. Miguel Carvalho & António Rua, 2014. "Extremal Dependence in International Output Growth: Tales from the Tails," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(4), pages 605-620, August.

  15. Maximiano Pinheiro & António Rua & Francisco Dias, 2013. "Dynamic Factor Models with Jagged Edge Panel Data: Taking on Board the Dynamics of the Idiosyncratic Components," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(1), pages 80-102, February.
    See citations under working paper version above.
  16. de Carvalho, Miguel & Rodrigues, Paulo C. & Rua, António, 2012. "Tracking the US business cycle with a singular spectrum analysis," Economics Letters, Elsevier, vol. 114(1), pages 32-35.
    See citations under working paper version above.
  17. António Rua, 2012. "Money Growth and Inflation in the Euro Area: A Time-Frequency View," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(6), pages 875-885, December.
    See citations under working paper version above.
  18. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
    See citations under working paper version above.
  19. António Rua, 2011. "A wavelet approach for factor‐augmented forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(7), pages 666-678, November.
    See citations under working paper version above.
  20. Francisco Dias & Cláudia Duarte & António Rua, 2010. "Inflation expectations in the euro area: are consumers rational?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 146(3), pages 591-607, September.
    See citations under working paper version above.
  21. Francisco Dias & Cláudia Duarte & António Rua, 2010. "Inflation (mis)perceptions in the euro area," Empirical Economics, Springer, vol. 39(2), pages 353-369, October.
    See citations under working paper version above.
  22. Francisco Dias & Maximiano Pinheiro & António Rua, 2010. "Forecasting using targeted diffusion indexes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 341-352.
    See citations under working paper version above.
  23. Rua, António, 2010. "Measuring comovement in the time-frequency space," Journal of Macroeconomics, Elsevier, vol. 32(2), pages 685-691, June.
    See citations under working paper version above.
  24. Rua, António & Nunes, Luís C., 2009. "International comovement of stock market returns: A wavelet analysis," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 632-639, September.
    See citations under working paper version above.
  25. Hugo Reis & Antonio Rua, 2009. "An Input-Output Analysis: Linkages versus Leakages," International Economic Journal, Taylor & Francis Journals, vol. 23(4), pages 527-544.

    Cited by:

    1. Juhyun Oh & Dong Hee Suh, 2019. "The Industrial Linkages and Supply Effects of the U.S. R&D Sector: Comparison with OECD Countries," Social Sciences, MDPI, vol. 8(3), pages 1-10, March.
    2. Mariolis, Theodore & Leriou, Eirini & Soklis, George, 2019. "Dissecting the Input-Output Structure of the Greek Economy," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 72(4), pages 453-474.

  26. G. Rünstler & K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze, 2009. "Short-term forecasting of GDP using large datasets: a pseudo real-time forecast evaluation exercise," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 595-611.

    Cited by:

    1. Michele Modugno & Lucrezia Reichlin & Domenico Giannone & Marta Banbura, 2012. "Nowcasting with Daily Data," 2012 Meeting Papers 555, Society for Economic Dynamics.
    2. António Rua & Carlos Melo Gouveia & Nuno Lourenço, 2020. "Forecasting tourism with targeted predictors in a data-rich environment," Working Papers w202005, Banco de Portugal, Economics and Research Department.
    3. Ard Reijer, 2013. "Forecasting Dutch GDP and inflation using alternative factor model specifications based on large and small datasets," Empirical Economics, Springer, vol. 44(2), pages 435-453, April.
    4. Mikosch, Heiner & Solanko, Laura, 2017. "Should one follow movements in the oil price or in money supply? Forecasting quarterly GDP growth in Russia with higher-frequency indicators," BOFIT Discussion Papers 19/2017, Bank of Finland Institute for Emerging Economies (BOFIT).
    5. Doll, Jens & Rosenthal, Beatrice & Volkenand, Jonas & Hamella, Sandra, 2017. "Nowcasting des deutschen BIP," Weidener Diskussionspapiere 59, University of Applied Sciences Amberg-Weiden (OTH).
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    7. Schwarzmüller, Tim, 2015. "Model pooling and changes in the informational content of predictors: An empirical investigation for the euro area," Kiel Working Papers 1982, Kiel Institute for the World Economy (IfW Kiel).
    8. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.
    9. Andrejs Bessonovs, 2015. "Suite of Latvia's GDP forecasting models," Working Papers 2015/01, Latvijas Banka.
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    11. Francisco Dias & Cláudia Duarte & António Rua, 2010. "Inflation expectations in the euro area: are consumers rational?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 146(3), pages 591-607, September.
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    17. Lombardi, Marco J. & Maier, Philipp, 2011. "Forecasting economic growth in the euro area during the Great Moderation and the Great Recession," Working Paper Series 1379, European Central Bank.
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    19. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    20. Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in real-time: A density combination approach," Working Paper 2011/11, Norges Bank.
    21. an de Meulen, Philipp, 2015. "Das RWI-Kurzfristprognosemodell," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 66(2), pages 25-46.
    22. Danilo Cascaldi-Garcia & Thiago Revil T. Ferreira & Domenico Giannone & Michele Modugno, 2021. "Back to the Present: Learning about the Euro Area through a Now-casting Model," International Finance Discussion Papers 1313, Board of Governors of the Federal Reserve System (U.S.).
    23. Matteo Luciani & Lorenzo Ricci, 2014. "Nowcasting Norway," International Journal of Central Banking, International Journal of Central Banking, vol. 10(4), pages 215-248, December.
    24. Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014. "A multi-country approach to forecasting output growth using PMIs," Globalization Institute Working Papers 213, Federal Reserve Bank of Dallas.
    25. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    26. Germán López, 2015. "Forecast Accuracy of Small and Large Scale Dynamic Factor Models in Developing Economies," Working Papers. Serie AD 2015-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    27. Bhattacharya, Rudrani & Pandey, Radhika & Veronese, Giovanni, 2011. "Tracking India Growth in Real Time," Working Papers 11/90, National Institute of Public Finance and Policy.
    28. Boriss Siliverstovs, 2015. "Dissecting Models' Forecasting Performance," KOF Working papers 15-397, KOF Swiss Economic Institute, ETH Zurich.
    29. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    30. Alessandro Borin & Riccardo Cristadoro & Roberto Golinelli & Giuseppe Parigi, 2012. "Forecasting world output: the rising importance of emerging economies," Temi di discussione (Economic working papers) 853, Bank of Italy, Economic Research and International Relations Area.
    31. Lourenço, Nuno & Gouveia, Carlos Melo & Rua, António, 2021. "Forecasting tourism with targeted predictors in a data-rich environment," Economic Modelling, Elsevier, vol. 96(C), pages 445-454.
    32. Bańbura, Marta & Belousova, Irina & Bodnár, Katalin & Tóth, Máté Barnabás, 2023. "Nowcasting employment in the euro area," Working Paper Series 2815, European Central Bank.
    33. Esteves, Paulo Soares, 2013. "Direct vs bottom–up approach when forecasting GDP: Reconciling literature results with institutional practice," Economic Modelling, Elsevier, vol. 33(C), pages 416-420.
    34. António Rua, 2011. "A wavelet approach for factor‐augmented forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(7), pages 666-678, November.
    35. Martin Feldkircher & Florian Huber & Josef Schreiner & Marcel Tirpák & Peter Tóth & Julia Wörz, 2015. "Bridging the information gap: small-scale nowcasting models of GDP growth for selected CESEE countries," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 56-75.
    36. Marek Rusnak, 2013. "Nowcasting Czech GDP in Real Time," Working Papers 2013/06, Czech National Bank.
    37. Anna Norin, 2011. "Nowcasting of the Gross Regional Product," ERSA conference papers ersa10p768, European Regional Science Association.
    38. Caruso, Alberto, 2019. "Macroeconomic news and market reaction: Surprise indexes meet nowcasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1725-1734.
    39. Schumacher, Christian, 2016. "A comparison of MIDAS and bridge equations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 257-270.
    40. Dias, Francisco & Pinheiro, Maximiano & Rua, António, 2015. "Forecasting Portuguese GDP with factor models: Pre- and post-crisis evidence," Economic Modelling, Elsevier, vol. 44(C), pages 266-272.
    41. Francisco Dias & Maximiano Pinheiro & António Rua, 2018. "A bottom-up approach for forecasting GDP in a data-rich environment," Applied Economics Letters, Taylor & Francis Journals, vol. 25(10), pages 718-723, June.
    42. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.
    43. João Valle e Azevedo & Ana Pereira, 2008. "Approximating and Forecasting Macroeconomic Signals in Real-Time," Working Papers w200819, Banco de Portugal, Economics and Research Department.
    44. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
    45. Irma Hindrayanto & Siem Jan Koopman & Jasper de Winter, 2014. "Nowcasting and Forecasting Economic Growth in the Euro Area using Principal Components," Tinbergen Institute Discussion Papers 14-113/III, Tinbergen Institute.
    46. Danilo Cascaldi-Garcia & Matteo Luciani & Michele Modugno, 2023. "Lessons from Nowcasting GDP across the World," International Finance Discussion Papers 1385, Board of Governors of the Federal Reserve System (U.S.).
    47. Kajal Lahiri & George Monokroussos, 2011. "Nowcasting US GDP: The role of ISM Business Surveys," Discussion Papers 11-01, University at Albany, SUNY, Department of Economics.
    48. Hindrayanto, Irma & Koopman, Siem Jan & de Winter, Jasper, 2016. "Forecasting and nowcasting economic growth in the euro area using factor models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1284-1305.
    49. Liebermann, Joëlle, 2012. "Short-term forecasting of quarterly gross domestic product growth," Quarterly Bulletin Articles, Central Bank of Ireland, pages 74-84, February.
    50. Pinkwart, Nicolas, 2018. "Short-term forecasting economic activity in Germany: A supply and demand side system of bridge equations," Discussion Papers 36/2018, Deutsche Bundesbank.
    51. Guido Bulligan & Roberto Golinelli & Giuseppe Parigi, 2010. "Forecasting industrial production: the role of information and methods," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The IFC's contribution to the 57th ISI Session, Durban, August 2009, volume 33, pages 227-235, Bank for International Settlements.
    52. Lopez-Buenache, German, 2019. "The evolution of monetary policy effectiveness under macroeconomic instability," Economic Modelling, Elsevier, vol. 83(C), pages 221-233.
    53. Roman Horvath, 2012. "Do Confidence Indicators Help Predict Economic Activity? The Case of the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(5), pages 398-412, November.
    54. Jos Jansen, W. & Jin, Xiaowen & Winter, Jasper M. de, 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," Munich Reprints in Economics 43488, University of Munich, Department of Economics.
    55. Heinisch, Katja, 2024. "Step by step - A quarterly evaluation of EU Commission's GDP forecasts," IWH Discussion Papers 22/2024, Halle Institute for Economic Research (IWH).
    56. Dimitra Lamprou, 2015. "Nowcasting GDP in Greece: A Note on Forecasting Improvements from the Use of Bridge Models," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 13(1), pages 85-100.
    57. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    58. Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
    59. Alberto Caruso, 2015. "Nowcasting Mexican GDP," Working Papers ECARES ECARES 2015-40, ULB -- Universite Libre de Bruxelles.
    60. Martin Feldkircher & Florian Huber & Josef Schreiner & Julia Woerz & Marcel Tirpak & Peter Toth, 2015. "Small-scale nowcasting models of GDP for selected CESEE countries," Working and Discussion Papers WP 4/2015, Research Department, National Bank of Slovakia.
    61. Danilo Leiva-Leon & Gabriel Pérez-Quirós & Eyno Rots, 2020. "Real-Time Weakness of the Global Economy: A First Assessment of the Coronavirus Crisis," MNB Working Papers 2020/4, Magyar Nemzeti Bank (Central Bank of Hungary).
    62. Kitlinski, Tobias & an de Meulen, Philipp, 2015. "The role of targeted predictors for nowcasting GDP with bridge models: Application to the Euro area," Ruhr Economic Papers 559, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    63. Pirschel, Inske, 2015. "Forecasting Euro Area Recessions in real-time with a mixed-frequency Bayesian VAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113031, Verein für Socialpolitik / German Economic Association.
    64. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2010. "Are disaggregate data useful for factor analysis in forecasting French GDP?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 132-144.
    65. Ard Reijer & Andreas Johansson, 2019. "Nowcasting Swedish GDP with a large and unbalanced data set," Empirical Economics, Springer, vol. 57(4), pages 1351-1373, October.

  27. Duarte, Claudia & Rua, Antonio, 2007. "Forecasting inflation through a bottom-up approach: How bottom is bottom?," Economic Modelling, Elsevier, vol. 24(6), pages 941-953, November.

    Cited by:

    1. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    2. Thiago Carlomagno Carlo & Emerson Fernandes Marçal, 2016. "Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon," Applied Economics, Taylor & Francis Journals, vol. 48(50), pages 4846-4860, October.
    3. Ellis W. Tallman & Saeed Zaman, 2015. "Forecasting Inflation: Phillips Curve Effects on Services Price Measures," Working Papers (Old Series) 1519, Federal Reserve Bank of Cleveland.
    4. Carrera, Cesar & Ledesma, Alan, 2015. "Proyección de la inflación agregada con modelos de vectores autorregresivos bayesianos," Working Papers 2015-003, Banco Central de Reserva del Perú.
    5. Macias, Paweł & Stelmasiak, Damian & Szafranek, Karol, 2023. "Nowcasting food inflation with a massive amount of online prices," International Journal of Forecasting, Elsevier, vol. 39(2), pages 809-826.
    6. Barhoumi, K. & Rünstler, G. & Cristadoro, R. & Den Reijer, A. & Jakaitiene, A. & Jelonek, P. & Rua, A. & Ruth, K. & Benk, S. & Van Nieuwenhuyze, C., 2008. "Short-term forecasting of GDP using large monthly datasets: a pseudo real-time forecast evaluation exercise," Working papers 215, Banque de France.
    7. Chalmovianský, Jakub & Porqueddu, Mario & Sokol, Andrej, 2020. "Weigh(t)ing the basket: aggregate and component-based inflation forecasts for the euro area," Working Paper Series 2501, European Central Bank.
    8. Bermingham, Colin & D'Agostino, Antonello, 2011. "Understanding and forecasting aggregate and disaggregate price dynamics," Working Paper Series 1365, European Central Bank.
    9. Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski.
    10. Espasa, Antoni & Mayo-Burgos, Iván, 2013. "Forecasting aggregates and disaggregates with common features," International Journal of Forecasting, Elsevier, vol. 29(4), pages 718-732.
    11. Reichlin, Lucrezia & Camba-Mendez, Gonzalo & Angelini, Elena & Rünstler, Gerhard & Giannone, Domenico, 2008. "Short-term Forecasts of Euro Area GDP Growth," CEPR Discussion Papers 6746, C.E.P.R. Discussion Papers.
    12. Esteves, Paulo Soares, 2013. "Direct vs bottom–up approach when forecasting GDP: Reconciling literature results with institutional practice," Economic Modelling, Elsevier, vol. 33(C), pages 416-420.
    13. Chronis, George A., 2016. "Modelling the extreme variability of the US Consumer Price Index inflation with a stable non-symmetric distribution," Economic Modelling, Elsevier, vol. 59(C), pages 271-277.
    14. Cobb, Marcus P A, 2017. "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper 81585, University Library of Munich, Germany.
    15. Karol Szafranek & Aleksandra Hałka, 2017. "Determinants of low inflation in an emerging, small open economy. A comparison of aggregated and disaggregated approaches," NBP Working Papers 267, Narodowy Bank Polski.
    16. Rodion Latypov & Elena Akhmedova & Egor Postolit & Marina Mikitchuk, 2024. "Bottom-up Inflation Forecasting Using Machine Learning Methods," Russian Journal of Money and Finance, Bank of Russia, vol. 83(3), pages 23-44, September.
    17. Vaughan Daniel, 2013. "An Analysis of the Process of Disinflationary Structural Change: The Case of Mexico," Working Papers 2013-12, Banco de México.
    18. Francisco Dias & Maximiano Pinheiro & António Rua, 2018. "A bottom-up approach for forecasting GDP in a data-rich environment," Applied Economics Letters, Taylor & Francis Journals, vol. 25(10), pages 718-723, June.
    19. Ibarra, Raul, 2012. "Do disaggregated CPI data improve the accuracy of inflation forecasts?," Economic Modelling, Elsevier, vol. 29(4), pages 1305-1313.
    20. Byron Botha & Rulof Burger & Kevin Kotze & Neil Rankin & Daan Steenkamp, 2022. "Big data forecasting of South African inflation," School of Economics Macroeconomic Discussion Paper Series 2022-03, School of Economics, University of Cape Town.
    21. Capistrán, Carlos & Constandse, Christian & Ramos-Francia, Manuel, 2010. "Multi-horizon inflation forecasts using disaggregated data," Economic Modelling, Elsevier, vol. 27(3), pages 666-677, May.
    22. D'Elia, Enrico, 2010. "Predictions vs preliminary sample estimates," MPRA Paper 36070, University Library of Munich, Germany.
    23. Stavros Degiannakis, 2023. "The D-model for GDP nowcasting," Working Papers 317, Bank of Greece.
    24. G. Rünstler & K. Barhoumi & S. Benk & R. Cristadoro & A. Den Reijer & A. Jakaitiene & P. Jelonek & A. Rua & K. Ruth & C. Van Nieuwenhuyze, 2009. "Short-term forecasting of GDP using large datasets: a pseudo real-time forecast evaluation exercise," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 595-611.
    25. Cesar Carrera & Alan Ledesma, 2015. "Aggregate Inflation Forecast with Bayesian Vector Autoregressive Models," Working Papers 50, Peruvian Economic Association.
    26. Andrejs Bessonovs & Olegs Krasnopjorovs, 2020. "Short-Term Inflation Projections Model and Its Assessment in Latvia," Working Papers 2020/01, Latvijas Banka.
    27. Célérier, C., 2009. "Forecasting inflation in France," Working papers 262, Banque de France.

  28. Valle e Azevedo, Joao & Koopman, Siem Jan & Rua, Antonio, 2006. "Tracking the Business Cycle of the Euro Area: A Multivariate Model-Based Bandpass Filter," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 278-290, July.

    Cited by:

    1. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    2. António Rua, . "Dating the Portuguese business cycle," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    3. Drew Creal & Siem Jan Koopman & Eric Zivot, 2010. "Extracting a robust US business cycle using a time-varying multivariate model-based bandpass filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 695-719.
    4. Peter Fuleky & Carl Bonham, 2010. "Forecasting Based on Common Trends in Mixed Frequency Samples," Working Papers 2010-17R1, University of Hawaii Economic Research Organization, University of Hawaii at Manoa, revised Jul 2013.
    5. de Carvalho, Miguel & Rodrigues, Paulo C. & Rua, António, 2012. "Tracking the US business cycle with a singular spectrum analysis," Economics Letters, Elsevier, vol. 114(1), pages 32-35.
    6. Philippe Moës, 2006. "The production function approach to the Belgian output gap, estimation of a multivariate structural time series model," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 49(1), pages 59-91.
    7. de Carvalho, Miguel & Rua, António, 2017. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.
    8. Jasper de Winter & Siem Jan Koopman & Irma Hindrayanto, 2022. "Joint Decomposition of Business and Financial Cycles: Evidence from Eight Advanced Economies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(1), pages 57-79, February.
    9. Peter Fuleky & Carl S. Bonham, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 201305, University of Hawaii at Manoa, Department of Economics.
    10. Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2010. "New Eurocoin: Tracking Economic Growth in Real Time," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1024-1034, November.
    11. Rünstler, Gerhard & Vlekke, Marente, 2016. "Business, housing and credit cycles," Working Paper Series 1915, European Central Bank.
    12. Kai Carstensen & Felix Kießner & Thies Rossian, 2023. "Estimation of the TFP Gap for the Largest Five EMU Countries," CESifo Working Paper Series 10245, CESifo.
    13. Rozite, Kristiana & Bezemer, Dirk J. & Jacobs, Jan P.A.M., 2019. "Towards a financial cycle for the U.S., 1973–2014," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    14. Gabriele Galati & Irma Hindrayanto & Siem Jan Koopman & Marente Vlekke, 2016. "Measuring Financial Cycles in a Model-Based Analysis: Empirical Evidence for the United States and the Euro Area," Tinbergen Institute Discussion Papers 16-029/III, Tinbergen Institute.
    15. Chalmovianský, Jakub & Němec, Daniel, 2022. "Assessing uncertainty of output gap estimates: Evidence from Visegrad countries," Economic Modelling, Elsevier, vol. 116(C).
    16. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.
    17. Andrew Lee-Poy, 2018. "Characterizing the Canadian Financial Cycle with Frequency Filtering Approaches," Staff Analytical Notes 2018-34, Bank of Canada.
    18. González-Astudillo, Manuel, 2019. "An output gap measure for the euro area: Exploiting country-level and cross-sectional data heterogeneity," European Economic Review, Elsevier, vol. 120(C).
    19. Siem Jan Koopman & Rutger Lit & Andre Lucas, 2016. "Model-based Business Cycle and Financial Cycle Decomposition for Europe and the U.S," Tinbergen Institute Discussion Papers 16-051/IV, Tinbergen Institute.
    20. Efe Can KILINÇ & Cafer Necat BERBEROĞLU, 2019. "The Relationship Between Saving, Profit Rates and Business CyclesAbstract:There are different approaches of economics schools on the sources, causes and determinants of business cycles. These approach," Sosyoekonomi Journal, Sosyoekonomi Society.
    21. Martínez, Wilmer & Nieto, Fabio H. & Poncela, Pilar, 2016. "Choosing a dynamic common factor as a coincident index," Statistics & Probability Letters, Elsevier, vol. 109(C), pages 89-98.
    22. Beate Schirwitz & Christian Seiler & Klaus Wohlrabe, 2009. "Regionale Konjunkturzyklen in Deutschland – Teil II: Die Zyklendatierung," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(14), pages 24-31, July.
    23. Rünstler, Gerhard & Balfoussia, Hiona & Burlon, Lorenzo & Buss, Ginters & Comunale, Mariarosaria & De Backer, Bruno & Dewachter, Hans & Guarda, Paolo & Haavio, Markus & Hindrayanto, Irma & Iskrev, Nik, 2018. "Real and financial cycles in EU countries - Stylised facts and modelling implications," Occasional Paper Series 205, European Central Bank.
    24. Tucker S. McElroy & Thomas M. Trimbur, 2012. "Signal extraction for nonstationary multivariate time series with illustrations for trend inflation," Finance and Economics Discussion Series 2012-45, Board of Governors of the Federal Reserve System (U.S.).
    25. João Valle e Azevedo & Ana Pereira, 2008. "Approximating and Forecasting Macroeconomic Signals in Real-Time," Working Papers w200819, Banco de Portugal, Economics and Research Department.
    26. Planas, C. & Roeger, W. & Rossi, A., 2013. "The information content of capacity utilization for detrending total factor productivity," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 577-590.
    27. Martyna Marczak & Víctor Gómez, 2017. "Monthly US business cycle indicators: a new multivariate approach based on a band-pass filter," Empirical Economics, Springer, vol. 52(4), pages 1379-1408, June.
    28. Lenza, Michele & Jarociński, Marek, 2016. "An inflation-predicting measure of the output gap in the euro area," Working Paper Series 1966, European Central Bank.
    29. Łukasz Lenart & Mateusz Pipień, 2017. "Non-Parametric Test for the Existence of the Common Deterministic Cycle: The Case of the Selected European Countries," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 201-241, September.
    30. Ferrara, L. & Koopman, S J., 2010. "Common business and housing market cycles in the Euro area from a multivariate decomposition," Working papers 275, Banque de France.
    31. António Rua, 2016. "A wavelet-based multivariate multiscale approach for forecasting," Working Papers w201612, Banco de Portugal, Economics and Research Department.
    32. Lourenço, Nuno & Rua, António, 2021. "The Daily Economic Indicator: tracking economic activity daily during the lockdown," Economic Modelling, Elsevier, vol. 100(C).
    33. Matteo M. Pelagatti, 2005. "Business cycle and sector cycles," Econometrics 0503006, University Library of Munich, Germany.
    34. Greg Farrell & Esti Kemp, 2020. "Measuring the Financial Cycle in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 88(2), pages 123-144, June.
    35. João Valle e Azevedo, 2007. "A Multivariate Band-Pass Filter," Working Papers w200717, Banco de Portugal, Economics and Research Department.
    36. Marczak, Martyna & Gómez, Víctor, 2012. "Cyclicality of real wages in the USA and Germany: New insights from wavelet analysis," FZID Discussion Papers 50-2012, University of Hohenheim, Center for Research on Innovation and Services (FZID).
    37. Weigand Roland & Wanger Susanne & Zapf Ines, 2018. "Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany," Journal of Official Statistics, Sciendo, vol. 34(1), pages 265-301, March.
    38. Beate Schirwitz, 2013. "Business Fluctuations, Job Flows and Trade Unions - Dynamics in the Economy," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 47.
    39. Dutra, Tiago Mota & Dias, José Carlos & Teixeira, João C.A., 2022. "Measuring financial cycles: Empirical evidence for Germany, United Kingdom and United States of America," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 599-630.
    40. de Groot, E.A. & Segers, R. & Prins, D., 2021. "Disentangling the enigma of multi-structured economic cycles - A new appearance of the golden ratio," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    41. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The University of Manchester.
    42. Łukasz Lenart, 2018. "Bayesian inference for deterministic cycle with time-varying amplitude: the case of growth cycle in European countries," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(3), pages 233-262, September.
    43. João Veríssimo LISBOA & Mário Gomes AUGUSTO & Juan PIÑEIRO-CHOUSA, 2015. "A Combined Approach To Access Short Term Changes In Economic Activity Of Portugal And Spain," Revista Galega de Economía, University of Santiago de Compostela. Faculty of Economics and Business., vol. 24(2), pages 99-110.
    44. Leippold, Markus & Yang, Hanlin, 2019. "Particle filtering, learning, and smoothing for mixed-frequency state-space models," Econometrics and Statistics, Elsevier, vol. 12(C), pages 25-41.

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