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Tatsuma Wada

Citations

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Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Tatsuma Wada & Pierre Perron, 2005. "Trend and Cycles: A New Approach and Explanations of Some Old Puzzles," Computing in Economics and Finance 2005 252, Society for Computational Economics.

    Mentioned in:

    1. Efectos no neutrales en los shocks monetarios
      by Nicolas Cachanosky in Punto de Vista Economico on 2013-11-15 09:01:59

Working papers

  1. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2017. "An Alternative Estimation Method of a Time-Varying Parameter Model," Papers 1707.06837, arXiv.org, revised Dec 2017.

    Cited by:

    1. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.
    2. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Nov 2024.

  2. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "Time-Varying Comovement of Foreign Exchange Markets," Papers 1610.04334, arXiv.org.

    Cited by:

    1. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2022. "An Alternative Estimation Method for Time-Varying Parameter Models," Econometrics, MDPI, vol. 10(2), pages 1-27, April.

  3. Tatsuma Wada & Pierre Perron, 2014. "Measuring Business Cycles with Structural Breaks and Outliers: Applications to International Data," Boston University - Department of Economics - Working Papers Series 2014-004, Boston University - Department of Economics.

    Cited by:

    1. Spinola, Danilo, 2023. "Instability constraints and development traps: an empirical analysis of growth cycles and economic volatility in Latin America," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    2. Rodríguez, Gabriel, 2017. "Modeling Latin-American stock and Forex markets volatility: Empirical application of a model with random level shifts and genuine long memory," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 393-420.
    3. James Morley & Irina B Panovska, 2016. "Is Business Cycle Asymmetry Intrinsic in Industrialized Economies?," Discussion Papers 2016-12, School of Economics, The University of New South Wales.
    4. Gabriel Rodríguez & Junior A. Ojeda Cunya & José Carlos Gonzáles Tanaka, 2019. "An empirical note about estimation and forecasting Latin American Forex returns volatility: the role of long memory and random level shifts components," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 18(2), pages 107-123, June.
    5. José R. Maria & Paulo Júlio, 2023. "Trends and cycles during the COVID-19 pandemic period," Working Papers w202311, Banco de Portugal, Economics and Research Department.
    6. Panovska, Irina & Ramamurthy, Srikanth, 2022. "Decomposing the output gap with inflation learning," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    7. Ye Li & Pierre Perron & Jiawen Xu, 2017. "Modelling exchange rate volatility with random level shifts," Applied Economics, Taylor & Francis Journals, vol. 49(26), pages 2579-2589, June.
    8. Tino Berger & James Morley & Benjamin Wong, 2020. "Nowcasting the output gap," CAMA Working Papers 2020-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Etro, Federico, 2017. "Research in economics and macroeconomics," Research in Economics, Elsevier, vol. 71(3), pages 373-383.
    10. Cremaschini, Alessandro & Maruotti, Antonello, 2023. "A finite mixture analysis of structural breaks in the G-7 gross domestic product series," Research in Economics, Elsevier, vol. 77(1), pages 76-90.
    11. Arčabić, Vladimir & Panovska, Irina & Tica, Josip, 2024. "Business cycle synchronization and asymmetry in the European Union," Economic Modelling, Elsevier, vol. 139(C).
    12. Quast, Josefine & Wolters, Maik H., 2019. "Reliable Real-time Output Gap Estimates Based on a Modified Hamilton Filter," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203535, Verein für Socialpolitik / German Economic Association.
    13. Steven M. Fazzari & James Morley & Irina B. Panovska, 2017. "When Do Discretionary Changes in Government Spending or Taxes Have Larger Effects?," Discussion Papers 2017-04, School of Economics, The University of New South Wales.
    14. Shingo Watanabe, 2019. "What Do British Historical Data Tell Us About Government Spending Multipliers?," Economic Inquiry, Western Economic Association International, vol. 57(2), pages 1141-1162, April.
    15. Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).
    16. Elroukh, Ahmed W. & Nikolsko-Rzhevskyy, Alex & Panovska, Irina, 2020. "A look at jobless recoveries in G7 countries," Journal of Macroeconomics, Elsevier, vol. 64(C).
    17. James Morley, 2019. "The business cycle: periodic pandemic or rollercoaster ride?," International Journal of Economic Policy Studies, Springer, vol. 13(2), pages 425-431, August.

  4. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2012. "International Stock Market Efficiency: A Non-Bayesian Time-Varying Model Approach," Papers 1203.5176, arXiv.org, revised May 2014.

    Cited by:

    1. Mariam Camarero & Juan Sapena & Cecilio Tamarit, 2020. "Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 87-114, June.
    2. Vieito, João Paulo & Wong, Wing-Keung & Zhu, Zhenzhen, 2015. "Could the global financial crisis improve the performance of the G7 stocks markets?," MPRA Paper 66521, University Library of Munich, Germany.
    3. Shah, Anand & Bahri, Anu, 2022. "Metanomics: Adaptive market and volatility behaviour in Metaverse," MPRA Paper 114442, University Library of Munich, Germany.
    4. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    5. Okoroafor, Ugochi Chibuzor & Leirvik, Thomas, 2022. "Time varying market efficiency in the Brent and WTI crude market," Finance Research Letters, Elsevier, vol. 45(C).
    6. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    7. Noda, Akihiko, 2016. "A test of the adaptive market hypothesis using a time-varying AR model in Japan," Finance Research Letters, Elsevier, vol. 17(C), pages 66-71.
    8. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2022. "An Alternative Estimation Method for Time-Varying Parameter Models," Econometrics, MDPI, vol. 10(2), pages 1-27, April.
    9. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    10. Akihiko Noda, 2019. "On the Evolution of Cryptocurrency Market Efficiency," Papers 1904.09403, arXiv.org, revised Jul 2020.
    11. Dzung Phan Tran Trung & Hung Pham Quang, 2019. "Adaptive Market Hypothesis: Evidence from the Vietnamese Stock Market," JRFM, MDPI, vol. 12(2), pages 1-16, May.
    12. Charfeddine, Lanouar & Khediri, Karim Ben & Aye, Goodness C. & Gupta, Rangan, 2018. "Time-varying efficiency of developed and emerging bond markets: Evidence from long-spans of historical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 632-647.
    13. Kenichi Hirayama & Akihiko Noda, 2019. "Measuring the Time-Varying Market Efficiency in the Prewar and Wartime Japanese Stock Market, 1924-1943," Papers 1911.04059, arXiv.org, revised May 2024.
    14. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2018. "The futures premium and rice market efficiency in prewar Japan," Economic History Review, Economic History Society, vol. 71(3), pages 909-937, August.
    15. Yuxin Pang & Dehui Wang, 2024. "A New Random Coefficient Autoregressive Model Driven by an Unobservable State Variable," Mathematics, MDPI, vol. 12(24), pages 1-16, December.
    16. Deniz Erer & Elif Erer & Selim Güngör, 2023. "The aggregate and sectoral time-varying market efficiency during crisis periods in Turkey: a comparative analysis with COVID-19 outbreak and the global financial crisis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.
    17. Askari, Abolfazl & Hajizadeh, Ehsan, 2024. "Exploring market efficiency levels: A powerful approach based on a gamma distribution," Finance Research Letters, Elsevier, vol. 66(C).
    18. Maria Kulikova & Gennady Kulikov, 2023. "Estimation of market efficiency process within time-varying autoregressive models by extended Kalman filtering approach," Papers 2310.04125, arXiv.org.
    19. Achal Awasthi & Oleg Malafeyev, 2015. "Is the Indian Stock Market efficient - A comprehensive study of Bombay Stock Exchange Indices," Papers 1510.03704, arXiv.org.
    20. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    21. Pınar Evrim Mandacı & F. Dilvin Taskın & Zeliha Can Ergun, 2019. "Adaptive Market Hypothesis," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(4), pages 84-101.
    22. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.
    23. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2017. "An Alternative Estimation Method of a Time-Varying Parameter Model," Papers 1707.06837, arXiv.org, revised Dec 2017.
    24. Jiang, Jinjin & Li, Haiqi, 2020. "A new measure for market efficiency and its application," Finance Research Letters, Elsevier, vol. 34(C).
    25. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    26. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "Time-Varying Comovement of Foreign Exchange Markets," Papers 1610.04334, arXiv.org.
    27. Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
    28. Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
    29. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Nov 2024.
    30. Aslam, Faheem & Memon, Bilal Ahmed & Hunjra, Ahmed Imran & Bouri, Elie, 2023. "The dynamics of market efficiency of major cryptocurrencies," Global Finance Journal, Elsevier, vol. 58(C).
    31. Onur Özdemir, 2022. "Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: evidence from DCC-GARCH and wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-38, December.

  5. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2012. "The Evolution of Stock Market Efficiency in the US: A Non-Bayesian Time-Varying Model Approach," Papers 1202.0100, arXiv.org, revised Aug 2015.

    Cited by:

    1. Shah, Anand & Bahri, Anu, 2022. "Metanomics: Adaptive market and volatility behaviour in Metaverse," MPRA Paper 114442, University Library of Munich, Germany.
    2. Richard S.Grossman, 2017. "Stocks for the Long Run: New Monthly Indices of British Equities, 1869-1929," Wesleyan Economics Working Papers 2017-004, Wesleyan University, Department of Economics.
    3. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
    4. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    5. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    6. Noda, Akihiko, 2016. "A test of the adaptive market hypothesis using a time-varying AR model in Japan," Finance Research Letters, Elsevier, vol. 17(C), pages 66-71.
    7. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2022. "An Alternative Estimation Method for Time-Varying Parameter Models," Econometrics, MDPI, vol. 10(2), pages 1-27, April.
    8. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2017. "Discretion versus Policy Rules in Futures Markets: A Case of the Osaka-Dojima Rice Exchange, 1914-1939," Papers 1704.00985, arXiv.org, revised Jan 2018.
    9. Campbell, Gareth & Grossman, Richard S. & Turner, John D., 2019. "Before the cult of equity: New monthly indices of the British share market, 1829-1929," QUCEH Working Paper Series 2019-01, Queen's University Belfast, Queen's University Centre for Economic History.
    10. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    11. Dzung Phan Tran Trung & Hung Pham Quang, 2019. "Adaptive Market Hypothesis: Evidence from the Vietnamese Stock Market," JRFM, MDPI, vol. 12(2), pages 1-16, May.
    12. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2014. "Market Efficiency and Government Interventions in Prewar Japanese Rice Futures Markets," Papers 1404.1164, arXiv.org, revised Feb 2017.
    13. Charfeddine, Lanouar & Khediri, Karim Ben & Aye, Goodness C. & Gupta, Rangan, 2018. "Time-varying efficiency of developed and emerging bond markets: Evidence from long-spans of historical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 632-647.
    14. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2018. "The futures premium and rice market efficiency in prewar Japan," Economic History Review, Economic History Society, vol. 71(3), pages 909-937, August.
    15. Yuxin Pang & Dehui Wang, 2024. "A New Random Coefficient Autoregressive Model Driven by an Unobservable State Variable," Mathematics, MDPI, vol. 12(24), pages 1-16, December.
    16. Deniz Erer & Elif Erer & Selim Güngör, 2023. "The aggregate and sectoral time-varying market efficiency during crisis periods in Turkey: a comparative analysis with COVID-19 outbreak and the global financial crisis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.
    17. Vasile Brătian & Ana-Maria Acu & Camelia Oprean-Stan & Emil Dinga & Gabriela-Mariana Ionescu, 2021. "Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
    18. Al-Shboul, Mohammad & Alsharari, Nizar, 2019. "The dynamic behavior of evolving efficiency: Evidence from the UAE stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 119-135.
    19. Askari, Abolfazl & Hajizadeh, Ehsan, 2024. "Exploring market efficiency levels: A powerful approach based on a gamma distribution," Finance Research Letters, Elsevier, vol. 66(C).
    20. Oktay Ozkan, 2020. "Time-varying return predictability and adaptive markets hypothesis: Evidence on MIST countries from a novel wild bootstrap likelihood ratio approach," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(2), pages 101-113.
    21. Maria Kulikova & Gennady Kulikov, 2023. "Estimation of market efficiency process within time-varying autoregressive models by extended Kalman filtering approach," Papers 2310.04125, arXiv.org.
    22. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    23. Kalugala Vidanalage Aruna Shantha, 2019. "Individual Investors’ Learning Behavior and Its Impact on Their Herd Bias: An Integrated Analysis in the Context of Stock Trading," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    24. Pınar Evrim Mandacı & F. Dilvin Taskın & Zeliha Can Ergun, 2019. "Adaptive Market Hypothesis," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(4), pages 84-101.
    25. Jiang, Jinjin & Li, Haiqi, 2020. "A new measure for market efficiency and its application," Finance Research Letters, Elsevier, vol. 34(C).
    26. Ali Fayyaz Munir & Mohd Edil Abd. Sukor & Shahrin Saaid Shaharuddin, 2022. "Adaptive Market Hypothesis and Time-varying Contrarian Effect: Evidence From Emerging Stock Markets of South Asia," SAGE Open, , vol. 12(1), pages 21582440211, January.
    27. Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
    28. Urquhart, Andrew & McGroarty, Frank, 2016. "Are stock markets really efficient? Evidence of the adaptive market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 39-49.
    29. Koichiro Moriya & Akihiko Noda, 2023. "On the Time-Varying Structure of the Arbitrage Pricing Theory using the Japanese Sector Indices," Papers 2305.05998, arXiv.org, revised Mar 2024.
    30. Nevi Danila, 2022. "Random Walk of Socially Responsible Investment in Emerging Market," Sustainability, MDPI, vol. 14(19), pages 1-13, September.

  6. Wada, Tatsuma, 2011. "The Real Exchange Rate and Real Interest Differentials: The Role of the Trend-Cycle Decomposition," MPRA Paper 41755, University Library of Munich, Germany.

    Cited by:

    1. Works, Richard Floyd, 2016. "Econometric modeling of exchange rate determinants by market classification: An empirical analysis of Japan and South Korea using the sticky-price monetary theory," MPRA Paper 76382, University Library of Munich, Germany.
    2. Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).

  7. Wada, Tatsuma, 2011. "On the Correlations of Trend-Cycle Errors," MPRA Paper 41754, University Library of Munich, Germany.

    Cited by:

    1. Tobias Hartl & Rolf Tschernig & Enzo Weber, 2020. "Fractional trends and cycles in macroeconomic time series," Papers 2005.05266, arXiv.org, revised May 2020.
    2. Manuel González-Astudillo & John M. Roberts, 2022. "When are trend–cycle decompositions of GDP reliable?," Empirical Economics, Springer, vol. 62(5), pages 2417-2460, May.

  8. Tatsuma Wada & Pierre Perron, 2006. "State Space Model with Mixtures of Normals: Specifications and Applications to International Data," Boston University - Department of Economics - Working Papers Series WP2006-029, Boston University - Department of Economics.

    Cited by:

    1. Xu, Jiawen & Perron, Pierre, 2014. "Forecasting return volatility: Level shifts with varying jump probability and mean reversion," International Journal of Forecasting, Elsevier, vol. 30(3), pages 449-463.
    2. Rasmus Tangsgaard Varneskov & Pierre Perron, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," CREATES Research Papers 2011-26, Department of Economics and Business Economics, Aarhus University.
    3. Gabriel Rodríguez & Roxana Tramontana Tocto, 2015. "Application of a Short Memory Model With Random Level Shifts to the Volatility of Latin American Stock Market Returns," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 52(2), pages 185-211, November.
    4. Yang K. Lu & Pierre Perron, 2008. "Modeling and Forecasting Stock Return Volatility Using a Random Level Shift Model," Boston University - Department of Economics - Working Papers Series wp2008-012, Boston University - Department of Economics.
    5. Junior A. Ojeda Cunya & Gabriel Rodríguez, 2016. "An application of a random level shifts model to the volatility of Peruvian stock and exchange rate returns," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 9(1), pages 34-55, March.
    6. Perron, Pierre & Wada, Tatsuma, 2009. "Let's take a break: Trends and cycles in US real GDP," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 749-765, September.
    7. Ángel Guillén & Gabriel Rodríguez, 2014. "Trend-cycle decomposition for Peruvian GDP: application of an alternative method," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 23(1), pages 1-44, December.
    8. Tara Sinclair & Sinchan Mitra, 2008. "Output Fluctuations in the G-7: An Unobserved Components Approach," Working Papers 2008-04, The George Washington University, Institute for International Economic Policy.
    9. Karim Barhoumi & Reda Cherif & Mr. Nooman Rebei, 2016. "Stochastic Trends, Debt Sustainability and Fiscal Policy," IMF Working Papers 2016/059, International Monetary Fund.
    10. Barhoumi, Karim & Cherif, Reda & Rebei, Nooman, 2018. "Stochastic trends and fiscal policy," Economic Modelling, Elsevier, vol. 75(C), pages 256-267.
    11. Gabriel Rodríguez, 2015. "Modeling Latin-American Stock Markets Volatility: Varying Probabilities and Mean Reversion in a Random Level Shifts Model," Documentos de Trabajo / Working Papers 2015-403, Departamento de Economía - Pontificia Universidad Católica del Perú.
    12. Gabriel Rodríguez, 2016. "Modeling Latin-American Stock and Forex Markets Volatility: Empirical Application of a Model with Random Level Shifts and Genuine Long Memory [Modelando la volatilidad de los mercados bursátiles y cam," Documentos de Trabajo / Working Papers 2016-416, Departamento de Economía - Pontificia Universidad Católica del Perú.
    13. Gabriel Rodríguez & José Carlos Gonzáles Tanaka, 2016. "An Empirical Application of a Random Level Shifts Model with Time-Varying Probability and Mean Reversion to the Volatility of Latin-American Forex Markets Returns [Una aplicación empírica de un modelo," Documentos de Trabajo / Working Papers 2016-415, Departamento de Economía - Pontificia Universidad Católica del Perú.
    14. Eduardo Loría & Emmanuel Salas, 2014. "Ciclos, crecimiento económico y crisis en México, 1980.1-2013.4," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 29(2), pages 131-161.

  9. Tatsuma Wada & Pierre Perron, 2005. "An Alternative Trend-Cycle Decomposition using a State Space Model with Mixtures of Normals: Specifications and Applications to International Data," Boston University - Department of Economics - Working Papers Series WP2005-43, Boston University - Department of Economics.

    Cited by:

    1. Gabriel Rodríguez & Roxana Tramontana Tocto, 2015. "Application of a Short Memory Model With Random Level Shifts to the Volatility of Latin American Stock Market Returns," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 52(2), pages 185-211, November.
    2. Junior A. Ojeda Cunya & Gabriel Rodríguez, 2016. "An application of a random level shifts model to the volatility of Peruvian stock and exchange rate returns," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 9(1), pages 34-55, March.
    3. Ángel Guillén & Gabriel Rodríguez, 2014. "Trend-cycle decomposition for Peruvian GDP: application of an alternative method," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 23(1), pages 1-44, December.
    4. Gabriel Rodríguez, 2015. "Modeling Latin-American Stock Markets Volatility: Varying Probabilities and Mean Reversion in a Random Level Shifts Model," Documentos de Trabajo / Working Papers 2015-403, Departamento de Economía - Pontificia Universidad Católica del Perú.
    5. Benz, Ulrich & Hagist, Christian, 2008. "Technischer Anhang zu "Konjunktur und Generationenbilanz: Eine Analyse anhand des HP-Filters"," FZG Discussion Papers 23, University of Freiburg, Research Center for Generational Contracts (FZG).

  10. Tatsuma Wada & Pierre Perron, 2005. "Trend and Cycles: A New Approach and Explanations of Some Old Puzzles," Computing in Economics and Finance 2005 252, Society for Computational Economics.

    Cited by:

    1. Perron, Pierre & Yabu, Tomoyoshi, 2009. "Testing for Shifts in Trend With an Integrated or Stationary Noise Component," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 369-396.
    2. B. Bhaskara Rao, 2010. "Deterministic and stochastic trends in the time series models: a guide for the applied economist," Applied Economics, Taylor & Francis Journals, vol. 42(17), pages 2193-2202.
    3. Arabinda Basistha, 2007. "Trend‐cycle correlation, drift break and the estimation of trend and cycle in Canadian GDP," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 40(2), pages 584-606, May.
    4. Ghent, Andra, 2006. "Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?," MPRA Paper 180, University Library of Munich, Germany.
    5. Arabinda Basistha, 2009. "Hours per capita and productivity: evidence from correlated unobserved components models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 187-206.
    6. Nicolás Cachanosky & Alexander W. Salter, 2017. "The view from Vienna: An analysis of the renewed interest in the Mises-Hayek theory of the business cycle," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 30(2), pages 169-192, June.

  11. Pierre Perron† & Tatsuma Wada, 2005. "Let’s Take a Break: Trends and Cycles in US Real GDP?," Boston University - Department of Economics - Working Papers Series WP2005-031, Boston University - Department of Economics, revised Oct 2005.

    Cited by:

    1. Güneş Kamber & James Morley & Benjamin Wong, 2017. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," Reserve Bank of New Zealand Discussion Paper Series DP2017/01, Reserve Bank of New Zealand.
    2. Jaeho Kim & Sora Chon, 2020. "Why are Bayesian trend-cycle decompositions of US real GDP so different?," Empirical Economics, Springer, vol. 58(3), pages 1339-1354, March.
    3. Marlon Fritz & Thomas Gries & Yuanhua Feng, 2019. "Growth Trends and Systematic Patterns of Booms and Busts‐Testing 200 Years of Business Cycle Dynamics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(1), pages 62-78, February.
    4. Yu-Fan Huang & Sui Luo, 2018. "Potential output and inflation dynamics after the Great Recession," Empirical Economics, Springer, vol. 55(2), pages 495-517, September.
    5. Nooman Rebei & Rashid Sbia, 2021. "Transitory and permanent shocks in the global market for crude oil," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 1047-1064, November.
    6. Guido Ascari & Efrem Castelnuovo & Lorenza Rossi, 2010. "Calvo vs. Rotemberg in a Trend Inflation World: An Empirical Investigation," "Marco Fanno" Working Papers 0116, Dipartimento di Scienze Economiche "Marco Fanno".
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Articles

  1. Wada, Tatsuma, 2022. "Out-of-sample forecasting of foreign exchange rates: The band spectral regression and LASSO," Journal of International Money and Finance, Elsevier, vol. 128(C).

    Cited by:

    1. Wang, Jia & Wang, Xinyi & Wang, Xu, 2024. "International oil shocks and the volatility forecasting of Chinese stock market based on machine learning combination models," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).

  2. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.

    Cited by:

    1. Mikio Ito, 2022. "Detecting Structural Breaks in Foreign Exchange Markets by using the group LASSO technique," Papers 2202.02988, arXiv.org.

  3. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "The evolution of stock market efficiency in the US: a non-Bayesian time-varying model approach," Applied Economics, Taylor & Francis Journals, vol. 48(7), pages 621-635, February.
    See citations under working paper version above.
  4. Perron, Pierre & Wada, Tatsuma, 2016. "Measuring business cycles with structural breaks and outliers: Applications to international data," Research in Economics, Elsevier, vol. 70(2), pages 281-303.
    See citations under working paper version above.
  5. Herrera, Ana María & Lagalo, Latika Gupta & Wada, Tatsuma, 2015. "Asymmetries in the response of economic activity to oil price increases and decreases?," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 108-133.

    Cited by:

    1. Basel Awartani & Aktham Maghyereh & Julie Ayton, 2019. "Oil Price Changes And Industrial Output In The Mena Region: Nonlinearities And Asymmetries," Working Papers 1342, Economic Research Forum, revised 20 Sep 2019.
    2. Abdhut Deheri & Stefy Carmel, 2024. "Do fluctuations in global crude oil prices have an asymmetric effect on oil product pricing in India?," Economic Change and Restructuring, Springer, vol. 57(1), pages 1-22, February.
    3. Oguzhan Ozcelebi & Kaya Tokmakcioglu, 2022. "Assessment of the asymmetric impacts of the geopolitical risk on oil market dynamics," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 275-289, January.
    4. Goktug Sahin & Nukhet Dogan & M. Hakan Berument, 2023. "The effects of two benchmarks on Russian crude oil prices," Economic Change and Restructuring, Springer, vol. 56(2), pages 733-748, April.
    5. Siok Kun Sek, 2023. "A new look at asymmetric effect of oil price changes on inflation: Evidence from Malaysia," Energy & Environment, , vol. 34(5), pages 1524-1547, August.
    6. Luiggi Donayre & Neil A. Wilmot, 2016. "The Asymmetric Effects of Oil Price Shocks on the Canadian Economy," International Journal of Energy Economics and Policy, Econjournals, vol. 6(2), pages 167-182.
    7. Degiannakis, Stavros & Filis, George & Arora, Vipin, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," MPRA Paper 96270, University Library of Munich, Germany.
    8. Omotosho, Babatunde S. & Yang, Bo, 2024. "Oil price shocks and macroeconomic dynamics in resource-rich emerging economies under regime shifts," Journal of International Money and Finance, Elsevier, vol. 144(C).
    9. Christiane Baumeister & Lutz Kilian, 2016. "Lower Oil Prices and the U.S. Economy: Is This Time Different?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(2 (Fall)), pages 287-357.
    10. Evangelos Kyritsis and Apostolos Serletis, 2019. "Oil Prices and the Renewable Energy Sector," The Energy Journal, International Association for Energy Economics, vol. 0(The New E).
    11. Anthony Enisan Akinlo & Michael Segun Ojo, 2021. "Examining the asymmetric effects of oil price shocks on remittances inflows: evidence from Nigeria," SN Business & Economics, Springer, vol. 1(10), pages 1-16, October.
    12. Nima Nonejad, 2022. "New Findings Regarding the Out-of-Sample Predictive Impact of the Price of Crude Oil on the United States Industrial Production," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(1), pages 1-35, March.
    13. Guo, Jin & Zheng, Xinye & Chen, Zhan-Ming, 2016. "How does coal price drive up inflation? Reexamining the relationship between coal price and general price level in China," Energy Economics, Elsevier, vol. 57(C), pages 265-276.
    14. Herrera, Ana María & Karaki, Mohamad B., 2015. "The effects of oil price shocks on job reallocation," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 95-113.
    15. Fernandes, Leonardo H.S. & de Araújo, Fernando H.A. & Silva, Igor E.M., 2020. "The (in)efficiency of NYMEX energy futures: A multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    16. Koirala, Niraj Prasad & Ma, Xiaohan, 2020. "Oil price uncertainty and U.S. employment growth," Energy Economics, Elsevier, vol. 91(C).
    17. Vatsa, Puneet & Baek, Jungho, 2024. "Asymmetric effects of oil demand and oil supply shocks on New Zealand's trade," Resources Policy, Elsevier, vol. 92(C).
    18. Maghyereh, Aktham & Abdoh, Hussein, 2020. "Asymmetric effects of oil price uncertainty on corporate investment," Energy Economics, Elsevier, vol. 86(C).
    19. Kamyabi, Najmeh & Chidmi, Benaissa, 2022. "Gasoline demand in the United States: An asymmetric economic analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    20. Peng Li & Yaofu Ouyang, 2023. "Oil price shocks and China’s consumer and entrepreneur sentiment: a Bayesian structural VAR approach," Empirical Economics, Springer, vol. 65(5), pages 2241-2271, November.
    21. Dobronravova, Elizaveta (Добронравова, Елизавета), 2018. "Monetary Policy Peculiarities in Countries with Natural Resources, with Significant Changes in Terms of Trade [Особенности Монетарной Политики В Странах, Наделенных Природными Ресурсами, При Значит," Working Papers 031811, Russian Presidential Academy of National Economy and Public Administration.
    22. Kasey Buckles & Daniel Hungerman & Steven Lugauer, 2021. "Is Fertility a Leading Economic Indicator?," The Economic Journal, Royal Economic Society, vol. 131(634), pages 541-565.
    23. Sek, Siok Kun, 2019. "Unveiling the factors of oil versus non-oil sources in affecting the global commodity prices: A combination of threshold and asymmetric modeling approach," Energy, Elsevier, vol. 176(C), pages 272-280.
    24. Evgenidis, Anastasios, 2016. "Do all oil price shocks have the same impact? Evidence from the Euro Area," Economic Letters 07/EL/16, Central Bank of Ireland.
    25. Malikov, Emir, 2015. "Dynamic Responses to Oil Price Shocks: Conditional vs Unconditional (A)symmetry," MPRA Paper 68453, University Library of Munich, Germany.
    26. Gonçalves, Sílvia & Herrera, Ana María & Kilian, Lutz & Pesavento, Elena, 2021. "Impulse response analysis for structural dynamic models with nonlinear regressors," Journal of Econometrics, Elsevier, vol. 225(1), pages 107-130.
    27. Abbas, Shujaat, 2020. "Impact of oil prices on remittances to Pakistan from GCC countries: evidence from panel asymmetric analysis," MPRA Paper 107246, University Library of Munich, Germany.
    28. Kang, Wensheng & Perez de Gracia, Fernando & Ratti, Ronald A., 2017. "Oil price shocks, policy uncertainty, and stock returns of oil and gas corporations," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 344-359.
    29. Charfeddine, Lanouar & Klein, Tony & Walther, Thomas, 2018. "Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?," QBS Working Paper Series 2018/03, Queen's University Belfast, Queen's Business School.
    30. Knotek, Edward S. & Zaman, Saeed, 2021. "Asymmetric responses of consumer spending to energy prices: A threshold VAR approach," Energy Economics, Elsevier, vol. 95(C).
    31. Nonejad, Nima, 2021. "The price of crude oil and (conditional) out-of-sample predictability of world industrial production," Journal of Commodity Markets, Elsevier, vol. 23(C).
    32. Rehman, Mobeen Ur, 2018. "Do oil shocks predict economic policy uncertainty?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 498(C), pages 123-136.
    33. Borozan, Djula & Lolic Cipcic, Marina, 2022. "Asymmetric and nonlinear oil price pass-through to economic growth in Croatia: Do oil-related policy shocks matter?," Resources Policy, Elsevier, vol. 76(C).
    34. Sun-Yong Choi & Changsoo Hong, 2020. "Relationship between uncertainty in the oil and stock markets before and after the shale gas revolution: Evidence from the OVX, VIX, and VKOSPI volatility indices," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-26, May.
    35. Agboola, Emmanuel & Chowdhury, Rosen & Yang, Bo, 2024. "Oil price fluctuations and their impact on oil-exporting emerging economies," Economic Modelling, Elsevier, vol. 132(C).
    36. Ahmad Al-Harbi & Moid U. Ahmad, 2024. "Can Oil Prices Volatility Explain Economic Growth?," International Journal of Energy Economics and Policy, Econjournals, vol. 14(6), pages 614-620, November.
    37. Yin, Libo & Zhou, Yimin, 2016. "What drives long-term oil market volatility? Fundamentals versus Speculation," Economics Discussion Papers 2016-2, Kiel Institute for the World Economy (IfW Kiel).
    38. Yeliz Yalcin & Cengiz Arikan & Furkan Emirmahmutoglu, 2015. "Determining the asymmetric effects of oil price changes on macroeconomic variables: a case study of Turkey," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(4), pages 737-746, November.
    39. Mont'Alverne Duarte, Angelo & Gaglianone, Wagner Piazza & de Carvalho Guillén, Osmani Teixeira & Issler, João Victor, 2021. "Commodity prices and global economic activity: A derived-demand approach," Energy Economics, Elsevier, vol. 96(C).
    40. Ozge Kandemir Kocaaslan, 2021. "Are the responses of output and investment to oil price shocks asymmetric?: The case of an oil-importing small open economy," Empirical Economics, Springer, vol. 61(5), pages 2501-2516, November.
    41. Chen, Yufeng & Qu, Fang, 2019. "Leverage effect and dynamics correlation between international crude oil and China’s precious metals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    42. Jibril, Halima & Chaudhuri, Kausik & Mohaddes, Kamiar, 2020. "Asymmetric oil prices and trade imbalances: Does the source of the oil shock matter?," Energy Policy, Elsevier, vol. 137(C).
    43. Sam Olofin & Afees A. Salisu, 2017. "Modelling oil price-inflation nexus: The role of asymmetries and structural breaks," Working Papers 020, Centre for Econometric and Allied Research, University of Ibadan.
    44. Hernández Vega Marco A. & Hernández del Valle Gerardo & Guerrero Santiago, 2018. "Do heterogeneous countries respond differently to oil price shocks?," Working Papers 2018-09, Banco de México.
    45. Salim Bagadeem, 2023. "Oil Volatility and Economic Growth: Evidences from Top Oil Trading Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 381-387, November.
    46. Aktham I. Maghyereh & Osama D. Sweidan, 2020. "Do structural shocks in the crude oil market affect biofuel prices?," International Economics, CEPII research center, issue 164, pages 183-193.
    47. Ahmadi, Maryam & Manera, Matteo, 2021. "Oil Price Shocks and Economic Growth in Oil-Exporting Countries," FEEM Working Papers 311052, Fondazione Eni Enrico Mattei (FEEM).
    48. Heidorn, Thomas & Van Huellen, Sophie & Ruehl, C. & Woebbeking, F., 2017. "The long- and short-run impact of oil price changes on major global economies," Frankfurt School - Working Paper Series 225, Frankfurt School of Finance and Management.
    49. Brown, Stephen P.A., 2018. "New estimates of the security costs of U.S. oil consumption," Energy Policy, Elsevier, vol. 113(C), pages 171-192.
    50. Aimer, Najmi & Lusta, Abdulmula, 2022. "Asymmetric effects of oil shocks on economic policy uncertainty," Energy, Elsevier, vol. 241(C).
    51. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2021. "Oil price shocks, real economic activity and uncertainty," Bulletin of Economic Research, Wiley Blackwell, vol. 73(3), pages 364-392, July.
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    53. Libo Yin, 2022. "The role of intermediary capital risk in predicting oil volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 401-416, January.
    54. Mohammad Sharik Essa & Evangelos Giouvris, 2020. "Oil Price, Oil Price Implied Volatility (OVX) and Illiquidity Premiums in the US: (A)symmetry and the Impact of Macroeconomic Factors," JRFM, MDPI, vol. 13(4), pages 1-40, April.
    55. Ibrahim, Mansor H., 2019. "Oil and macro-financial linkages: Evidence from the GCC countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 1-13.
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    57. Abdhut Deheri & Stefy Carmel, 2024. "Are the Responses of Oil Products Prices Asymmetrical to Global Crude Oil Price Shocks? Evidence from India," Working Papers 2024-265, Madras School of Economics,Chennai,India.
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    60. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
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    66. Aktham I. Maghyereh & Basil Awartani & Osama D. Sweidan, 2019. "Oil price uncertainty and real output growth: new evidence from selected oil-importing countries in the Middle East," Empirical Economics, Springer, vol. 56(5), pages 1601-1621, May.
    67. Diab, Sara & Karaki, Mohamad B., 2023. "Do increases in gasoline prices cause higher food prices?," Energy Economics, Elsevier, vol. 127(PB).
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    Cited by:

    1. Pierre Perron & Tatsuma Wada, 2015. "Measuring Business Cycles with Structural Breaks and Outliers: Applications to International Data," Boston University - Department of Economics - Working Papers Series wp2015-016, Boston University - Department of Economics.

  8. Wada, Tatsuma, 2012. "On the correlations of trend–cycle errors," Economics Letters, Elsevier, vol. 116(3), pages 396-400.
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  9. Tatsuma Wada, 2012. "The Real Exchange Rate And Real Interest Differentials: The Role Of The Trend-Cycle Decomposition," Economic Inquiry, Western Economic Association International, vol. 50(4), pages 968-987, October.
    See citations under working paper version above.
  10. Herrera, Ana María & Lagalo, Latika Gupta & Wada, Tatsuma, 2011. "Oil Price Shocks And Industrial Production: Is The Relationship Linear?," Macroeconomic Dynamics, Cambridge University Press, vol. 15(S3), pages 472-497, November.

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    1. Mehmet Balcilar & Reneé van Eyden & Josine Uwilingiye & Rangan Gupta, 2014. "The impact of oil price on South African GDP growth: A Bayesian Markov Switching-VAR analysis," Working Papers 201470, University of Pretoria, Department of Economics.
    2. De Santis, Roberto A. & Tornese, Tommaso, 2023. "Energy supply shocks’ nonlinearities on output and prices," Working Paper Series 2834, European Central Bank.
    3. Dong Heon Kim, 2010. "What is an oil shock? Panel data evidence," Discussion Paper Series 1007, Institute of Economic Research, Korea University.
    4. Basel Awartani & Aktham Maghyereh & Julie Ayton, 2019. "Oil Price Changes And Industrial Output In The Mena Region: Nonlinearities And Asymmetries," Working Papers 1342, Economic Research Forum, revised 20 Sep 2019.
    5. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
    6. Abdhut Deheri & Stefy Carmel, 2024. "Do fluctuations in global crude oil prices have an asymmetric effect on oil product pricing in India?," Economic Change and Restructuring, Springer, vol. 57(1), pages 1-22, February.
    7. Suliman Zakaria S. Abdalla, 2014. "The Impact of Oil Price Fluctuations on the Sudanese Stock Market Performance," Working Papers 887, Economic Research Forum, revised Dec 2014.
    8. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2012. "Can Oil Prices Forecast Exchange Rates?," NBER Working Papers 17998, National Bureau of Economic Research, Inc.
    9. Rajesh H. Acharya & Anver C. Sadath, 2018. "Revisiting the relationship between oil price and macro economy: Evidence from India," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2018(1), pages 173-190.
    10. Goktug Sahin & Nukhet Dogan & M. Hakan Berument, 2023. "The effects of two benchmarks on Russian crude oil prices," Economic Change and Restructuring, Springer, vol. 56(2), pages 733-748, April.
    11. Narayan, Paresh Kumar & Sharma, Susan & Poon, Wai Ching & Westerlund, Joakim, 2014. "Do oil prices predict economic growth? New global evidence," Energy Economics, Elsevier, vol. 41(C), pages 137-146.
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    65. Zhang, Yali & Wang, Jun, 2019. "Linkage influence of energy market on financial market by multiscale complexity synchronization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 254-266.
    66. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
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