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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. 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.
    2. Panovska, Irina & Ramamurthy, Srikanth, 2022. "Decomposing the output gap with inflation learning," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    3. Morley, James & Panovska, Irina B., 2020. "Is Business Cycle Asymmetry Intrinsic In Industrialized Economies?," Macroeconomic Dynamics, Cambridge University Press, vol. 24(6), pages 1403-1436, September.
    4. 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.
    5. 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.
    6. Berger, Tino & Morley, James & Wong, Benjamin, 2023. "Nowcasting the output gap," Journal of Econometrics, Elsevier, vol. 232(1), pages 18-34.
      • 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.
    7. 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.
    8. Júlio, Paulo & Maria, José R., 2024. "Trends and cycles during the COVID-19 pandemic period," Economic Modelling, Elsevier, vol. 139(C).
    9. 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).
    10. Arčabić, Vladimir & Panovska, Irina & Tica, Josip, 2024. "Business cycle synchronization and asymmetry in the European Union," Economic Modelling, Elsevier, vol. 139(C).
    11. 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.
    12. 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.
    13. Elroukh, Ahmed W. & Nikolsko-Rzhevskyy, Alex & Panovska, Irina, 2020. "A look at jobless recoveries in G7 countries," Journal of Macroeconomics, Elsevier, vol. 64(C).
    14. 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.
    15. 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.
    16. 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.
    17. Etro, Federico, 2017. "Research in economics and macroeconomics," Research in Economics, Elsevier, vol. 71(3), pages 373-383.

  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. Jiang, Jinjin & Li, Haiqi, 2020. "A new measure for market efficiency and its application," Finance Research Letters, Elsevier, vol. 34(C).
    3. 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).
    4. 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.
    5. Shah, Anand & Bahri, Anu, 2022. "Metanomics: Adaptive market and volatility behaviour in Metaverse," MPRA Paper 114442, University Library of Munich, Germany.
    6. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "Time-Varying Comovement of Foreign Exchange Markets," Papers 1610.04334, arXiv.org.
    7. Mohamed Malek Belhoula & Walid Mensi & Kamel Naoui, 2024. "Impacts of investor's sentiment, uncertainty indexes, and macroeconomic factors on the dynamic efficiency of G7 stock markets," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(3), pages 2855-2886, June.
    8. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2014. "The Futures Premium and Rice Market Efficiency in Prewar Japan," Papers 1404.5381, arXiv.org, revised Sep 2017.
    9. Akihiko Noda, 2021. "On the evolution of cryptocurrency market efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 28(6), pages 433-439, March.
    10. 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.
    11. Askari, Abolfazl & Hajizadeh, Ehsan, 2024. "Exploring market efficiency levels: A powerful approach based on a gamma distribution," Finance Research Letters, Elsevier, vol. 66(C).
    12. 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.
    13. Khaled Mokni & Ghassen El Montasser & Ahdi Noomen Ajmi & Elie Bouri, 2024. "On the efficiency and its drivers in the cryptocurrency market: the case of Bitcoin and Ethereum," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-25, December.
    14. Achal Awasthi & Oleg Malafeyev, 2015. "Is the Indian Stock Market efficient - A comprehensive study of Bombay Stock Exchange Indices," Papers 1510.03704, arXiv.org.
    15. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    16. 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.
    17. Okoroafor, Ugochi Chibuzor & Leirvik, Thomas, 2022. "Time varying market efficiency in the Brent and WTI crude market," Finance Research Letters, Elsevier, vol. 45(C).
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    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.
    32. 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.
    33. 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.

  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. Gareth Campbell & Richard S.Grossman & John D. Turner, 2019. "Before the Cult of Equity:New Monthly Indices of the British Share Market, 1829-1929," Wesleyan Economics Working Papers 2019-003, Wesleyan University, Department of Economics.
    2. Madhur Bhatia, 2024. "Impact of the Local and the Global Crises on Stock Market Efficiency," Millennial Asia, , vol. 15(4), pages 572-596, December.
    3. Jiang, Jinjin & Li, Haiqi, 2020. "A new measure for market efficiency and its application," Finance Research Letters, Elsevier, vol. 34(C).
    4. 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.
    5. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    6. Shah, Anand & Bahri, Anu, 2022. "Metanomics: Adaptive market and volatility behaviour in Metaverse," MPRA Paper 114442, University Library of Munich, Germany.
    7. 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.
    8. Mohamed Malek Belhoula & Walid Mensi & Kamel Naoui, 2024. "Impacts of investor's sentiment, uncertainty indexes, and macroeconomic factors on the dynamic efficiency of G7 stock markets," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(3), pages 2855-2886, June.
    9. Mikio Ito & Kiyotaka Maeda & Akihiko Noda, 2014. "The Futures Premium and Rice Market Efficiency in Prewar Japan," Papers 1404.5381, arXiv.org, revised Sep 2017.
    10. 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.
    11. Askari, Abolfazl & Hajizadeh, Ehsan, 2024. "Exploring market efficiency levels: A powerful approach based on a gamma distribution," Finance Research Letters, Elsevier, vol. 66(C).
    12. 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.
    13. Ito, Mikio & Maeda, Kiyotaka & Noda, Akihiko, 2016. "Market efficiency and government interventions in prewar Japanese rice futures markets," Financial History Review, Cambridge University Press, vol. 23(3), pages 325-346, December.
    14. 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.
    15. Taylor, Nick, 2014. "The rise and fall of technical trading rule success," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 286-302.
    16. Khaled Mokni & Ghassen El Montasser & Ahdi Noomen Ajmi & Elie Bouri, 2024. "On the efficiency and its drivers in the cryptocurrency market: the case of Bitcoin and Ethereum," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-25, December.
    17. 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.
    18. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
    27. 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.
    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. 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.
    31. Nevi Danila, 2022. "Random Walk of Socially Responsible Investment in Emerging Market," Sustainability, MDPI, vol. 14(19), pages 1-13, September.
    32. 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.
    33. 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.

  6. 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.

  7. 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. 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).
    2. 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.

  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. 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.
    2. Lu, Yang K. & Perron, Pierre, 2010. "Modeling and forecasting stock return volatility using a random level shift model," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 138-156, January.
    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. Jiawen Xu & Pierre Perron, 2013. "Forecasting Return Volatility: Level Shifts with Varying Jump Probability and Mean Reversion," Boston University - Department of Economics - Working Papers Series 2013-021, Boston University - Department of Economics.
    5. 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.
    6. 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.
    7. Junior Ojeda & Gabriel Rodriguez, 2014. "An Application of a Random Level Shifts Model to the Volatility of Peruvian Stock and Exchange Rates Returns," Documentos de Trabajo / Working Papers 2014-383, Departamento de Economía - Pontificia Universidad Católica del Perú.
    8. Rodríguez, Gabriel & Tramontana, Roxana, 2015. "An Application of a Short Memory Model with Random Level Shifts to the Volatility of Latin American Stock Market Returns," Working Papers 2015-004, Banco Central de Reserva del Perú.
    9. Rasmus T. Varneskov & Pierre Perron, 2017. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2017-006, Boston University - Department of Economics.
    10. 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.
    11. 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.
    12. Karim Barhoumi & Reda Cherif & Mr. Nooman Rebei, 2016. "Stochastic Trends, Debt Sustainability and Fiscal Policy," IMF Working Papers 2016/059, International Monetary Fund.
    13. 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.
    14. Barhoumi, Karim & Cherif, Reda & Rebei, Nooman, 2018. "Stochastic trends and fiscal policy," Economic Modelling, Elsevier, vol. 75(C), pages 256-267.

  9. 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. 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.
    2. 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.
    3. 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.
    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.

  10. 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. 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.
    2. 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.
    3. Junior Ojeda & Gabriel Rodriguez, 2014. "An Application of a Random Level Shifts Model to the Volatility of Peruvian Stock and Exchange Rates Returns," Documentos de Trabajo / Working Papers 2014-383, Departamento de Economía - Pontificia Universidad Católica del Perú.
    4. Rodríguez, Gabriel & Tramontana, Roxana, 2015. "An Application of a Short Memory Model with Random Level Shifts to the Volatility of Latin American Stock Market Returns," Working Papers 2015-004, Banco Central de Reserva 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).

  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. Andreas Fuster & Benjamin Hebert & David Laibson, 2011. "Natural Expectations, Macroeconomic Dynamics, and Asset Pricing," NBER Working Papers 17301, National Bureau of Economic Research, Inc.
    2. Lu, Yang K. & Perron, Pierre, 2010. "Modeling and forecasting stock return volatility using a random level shift model," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 138-156, January.
    3. 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.
    4. 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 WP2005-44, Boston University - Department of Economics.
    5. 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.
    6. 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.
    7. Kim, Chang-Jin & Kim, Jaeho, 2013. "The `Pile-up Problem' in Trend-Cycle Decomposition of Real GDP: Classical and Bayesian Perspectives," MPRA Paper 51118, University Library of Munich, Germany.
    8. Philippe Moës, 2012. "Multivariate models with dual cycles: implications for output gap and potential growth measurement," Empirical Economics, Springer, vol. 42(3), pages 791-818, June.
    9. Tobias Hartl & Rolf Tschernig & Enzo Weber, 2020. "Fractional trends and cycles in macroeconomic time series," Papers 2005.05266, arXiv.org, revised May 2020.
    10. 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.
    11. Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in individual expectations, sentiment, and constant-gain learning," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 627-650.
    12. 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.
    13. Jiawen Xu & Pierre Perron, 2013. "Forecasting Return Volatility: Level Shifts with Varying Jump Probability and Mean Reversion," Boston University - Department of Economics - Working Papers Series 2013-021, Boston University - Department of Economics.
    14. 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.
    15. Francisco Estrada & Pierre Perron, "undated". "Detection and attribution of climate change through econometric methods," Boston University - Department of Economics - Working Papers Series 2013-015, Boston University - Department of Economics.
    16. Éva Gyurkovics & Tibor Takács, 2023. "Estimation of the potential GDP by a new robust filter method," 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. 31(4), pages 1183-1207, December.
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    20. 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.
    21. Juan Antolin-Diaz & Thomas Drechsel & Ivan Petrella, 2014. "Tracking the Slowdown in Long-Run GDP Growth," Discussion Papers 1604, Centre for Macroeconomics (CFM), revised Jan 2016.
    22. 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.
    23. Demetrescu, Matei & Kruse-Becher, Robinson, 2025. "Is U.S. real output growth non-normal? A tale of time-varying location and scale," Journal of Economic Dynamics and Control, Elsevier, vol. 171(C).
    24. 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.
    25. 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.
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    29. Stephan, Gaëtan & Lecumberry, Julien, 2015. "The German unemployment since the Hartz reforms: Permanent or transitory fall?," Economics Letters, Elsevier, vol. 136(C), pages 49-54.
    30. Kushal Banik Chowdhury & Nityananda Sarkar, 2017. "Is the Hybrid New Keynesian Phillips Curve Stable? Evidence from Some Emerging Economies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(3), pages 427-449, September.
    31. Angelia L. Grant & Joshua C.C. Chan, 2017. "A Bayesian Model Comparison for Trend‐Cycle Decompositions of Output," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(2-3), pages 525-552, March.
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    33. Dées, Stéphane & Pesaran, Hashem & Smith, Vanessa & Smith, Ron P., 2010. "Supply, demand and monetary policy shocks in a multi-country New Keynesian Model," Working Paper Series 1239, European Central Bank.
    34. Gaëtan Stephan & Julien Lecumberry, 2015. "The German unemployment since the Hartz reforms: Permanent or transitory fall?," Post-Print halshs-01238494, HAL.
    35. 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.
    36. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org.
    37. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
    38. David O. Cushman, 2012. "Mankiw vs. DeLong and Krugman on the CEA's Real GDP Forecasts in Early 2009: What Might a Time Series Econometrician Have Said?," Econ Journal Watch, Econ Journal Watch, vol. 9(3), pages 309-349, September.
    39. Enders, Walter & Li, Jing, 2015. "Trend-cycle decomposition allowing for multiple smooth structural changes in the trend of US real GDP," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 71-81.
    40. Yamada Hiroshi & Yoon Gawon, 2016. "Selecting the tuning parameter of the ℓ1 trend filter," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 97-105, February.
    41. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "Extracting a Robust U.S. Business Cycle Using a Time-Varying Multivariate Model-Based Bandpass Filter," Working Papers UWEC-2008-15-FC, University of Washington, Department of Economics.
    42. Yoon, Gawon, 2015. "Locating change-points in Hodrick–Prescott trends with an application to US real GDP: A generalized unobserved components model approach," Economic Modelling, Elsevier, vol. 45(C), pages 136-141.
    43. Mardi Dungey & Jan P.A.M. Jacobs & Jing Tian, 2017. "Forecasting output gaps in the G-7 countries: the role of correlated innovations and structural breaks," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4554-4566, September.
    44. Soloschenko, Max & Weber, Enzo, 2012. "Trend-Cycle Interactions and the Subprime Crisis: Analysis of US and Canadian Output," University of Regensburg Working Papers in Business, Economics and Management Information Systems 470, University of Regensburg, Department of Economics.
    45. Philippe Bacchetta & Eric Van Wincoop, 2006. "Incomplete information processing: a solution to the forward discount puzzle," Proceedings, Federal Reserve Bank of San Francisco, issue Jun.
    46. Agbeyegbe, Terence D., 2020. "Bayesian analysis of output gap in Barbados," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    47. 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.
    48. Junior Ojeda & Gabriel Rodriguez, 2014. "An Application of a Random Level Shifts Model to the Volatility of Peruvian Stock and Exchange Rates Returns," Documentos de Trabajo / Working Papers 2014-383, Departamento de Economía - Pontificia Universidad Católica del Perú.
    49. Hanno Lustig & Adrien Verdelhan, 2011. "The Cross-Section of Foreign Currency Risk Premia and Consumption Growth Risk: Reply," American Economic Review, American Economic Association, vol. 101(7), pages 3477-3500, December.
    50. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    51. Rodríguez, Gabriel & Tramontana, Roxana, 2015. "An Application of a Short Memory Model with Random Level Shifts to the Volatility of Latin American Stock Market Returns," Working Papers 2015-004, Banco Central de Reserva del Perú.
    52. Ulrich Haskamp, 2014. "Was Spanish fiscal policy sustainable?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(2), pages 273-286, May.
    53. Xuan, Chunji & Kim, Chang-Jin & Kim, Dong Heon, 2019. "New dynamics of consumption and output," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 50-59.
    54. 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.
    55. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
    56. Luis Eduardo Castillo & David Florián Hoyle, 2019. "Measuring the output gap, potential output growth and natural interest rate from a semi-structural dynamic model for Peru," Working Papers 159, Peruvian Economic Association.
    57. Ivan Mendieta-Munoz & Mengheng Li, 2019. "The Multivariate Simultaneous Unobserved Compenents Model and Identification via Heteroskedasticity," Working Paper Series, Department of Economics, University of Utah 2019_06, University of Utah, Department of Economics.
    58. Giovanni Razzu & Carl Singleton, 2013. "Are Business Cycles Gender Neutral?," Economics Discussion Papers em-dp2013-07, Department of Economics, University of Reading.
    59. Stephan B. Bruns & Zsuzsanna Csereklyei & David I. Stern, 2018. "A Multicointegration Model of Global Climate Change," CCEP Working Papers 1801, Centre for Climate & Energy Policy, Crawford School of Public Policy, The Australian National University.
    60. James Morley & Irina B. Panovska & Tara M. Sinclair, 2013. "Testing Stationarity for Unobserved Components Models," Discussion Papers 2012-41A, School of Economics, The University of New South Wales.
    61. Du, Ding & Hu, Ou, 2014. "The long-run component of foreign exchange volatility and stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 268-284.
    62. Wada, Tatsuma, 2012. "On the correlations of trend–cycle errors," Economics Letters, Elsevier, vol. 116(3), pages 396-400.
    63. Petrella, Ivan & Drechsel, Thomas & Antolin-Diaz, Juan, 2014. "Following the Trend: Tracking GDP when Long-Run Growth is Uncertain," CEPR Discussion Papers 10272, C.E.P.R. Discussion Papers.
    64. Bruns, Stephan B. & König, Johannes & Stern, David I., 2019. "Replication and robustness analysis of ‘energy and economic growth in the USA: A multivariate approach’," Energy Economics, Elsevier, vol. 82(C), pages 100-113.
    65. Chiara Perricone, 2013. "Clustering Macroeconomic Variables," CEIS Research Paper 283, Tor Vergata University, CEIS, revised 11 Jun 2013.
    66. Fritz, Marlon, 2019. "Steady state adjusting trends using a data-driven local polynomial regression," Economic Modelling, Elsevier, vol. 83(C), pages 312-325.
    67. 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.
    68. James Morley, 2014. "Measuring Economic Slack: A Forecast-Based Approach with Applications to Economies in Asia and the Pacific," BIS Working Papers 451, Bank for International Settlements.
    69. Cheptiş Alexandra, 2022. "The impact of external shocks on economic growth: An empirical study based on the SVAR models," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 16(1), pages 650-659, August.
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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, 2022. "An Alternative Estimation Method for Time-Varying Parameter Models," Econometrics, MDPI, vol. 10(2), pages 1-27, April.

    Cited by:

    1. Khaled Mokni & Ghassen El Montasser & Ahdi Noomen Ajmi & Elie Bouri, 2024. "On the efficiency and its drivers in the cryptocurrency market: the case of Bitcoin and Ethereum," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-25, December.

  3. 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.

  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. 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.
  6. 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. Kamyabi, Najmeh & Chidmi, Benaissa, 2022. "Gasoline demand in the United States: An asymmetric economic analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    2. Brice V. Dupoyet & Corey A. Shank, 2018. "Oil prices implied volatility or direction: Which matters more to financial markets?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(3), pages 275-295, August.
    3. 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.
    4. Alsamara, Mouyad Kassm & Mrabet, Zouhair & Elafif, Mohamed & Gangopadhyay, Partha, 2017. "The asymmetric effects of oil price on economic growth in Turkey and Saudi Arabia: new evidence from nonlinear ARDL approach," International Journal of Development and Conflict, Gokhale Institute of Politics and Economics, vol. 7(2), pages 97-118.
    5. Hilde C. Bjørnland & Julia Zhulanova, 2019. "The shale oil boom and the U.S. economy: Spillovers and time-varying effects," Working Paper 2019/14, Norges Bank.
    6. 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.
    7. Maghyereh, Aktham I. & Sweidan, Osama D., 2020. "Do structural shocks in the crude oil market affect biofuel prices?," International Economics, Elsevier, vol. 164(C), pages 183-193.
    8. 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.
    9. 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.
    10. Kyritsis, Evangelos & Serletis, Apostolos, 2017. "Oil Prices and the Renewable Energy Sector," Discussion Papers 2017/15, Norwegian School of Economics, Department of Business and Management Science.
    11. Glocker, Christian & Wegmüller, Philipp, 2024. "Energy price surges and inflation: Fiscal policy to the rescue?," Journal of International Money and Finance, Elsevier, vol. 149(C).
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Malikov, Emir, 2015. "Dynamic Responses to Oil Price Shocks: Conditional vs Unconditional (A)symmetry," MPRA Paper 68453, University Library of Munich, Germany.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2021. "Oil Price Shocks, Real Economic Activity and Uncertainty," Post-Print hal-03284089, HAL.
    23. 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.
    24. 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.
    25. 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.
    26. Atalla, Tarek & Blazquez, Jorge & Hunt, Lester C. & Manzano, Baltasar, 2017. "Prices versus policy: An analysis of the drivers of the primary fossil fuel mix," Energy Policy, Elsevier, vol. 106(C), pages 536-546.
    27. Knotek, Edward S. & Zaman, Saeed, 2021. "Asymmetric responses of consumer spending to energy prices: A threshold VAR approach," Energy Economics, Elsevier, vol. 95(C).
    28. 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.
    29. Ahmadi, Maryam & Manera, Matteo, 2021. "Oil Price Shocks and Economic Growth in Oil-Exporting Countries," FEEM Working Papers 311052, Fondazione Eni Enrico Mattei (FEEM).
    30. 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.
    31. Christiane Baumeister & Lutz Kilian, 2017. "Lower Oil Prices and the U.S. Economy: Is this Time Different?," CESifo Working Paper Series 6322, CESifo.
    32. 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).
    33. 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.
    34. Clovis Wendji Miamo & Elvis Dze Achuo, 2022. "Can the resource curse be avoided? An empirical examination of the nexus between crude oil price and economic growth," SN Business & Economics, Springer, vol. 2(1), pages 1-23, January.
    35. Sek, Siok Kun, 2017. "Impact of oil price changes on domestic price inflation at disaggregated levels: Evidence from linear and nonlinear ARDL modeling," Energy, Elsevier, vol. 130(C), pages 204-217.
    36. 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.
    37. Deheri, Abdhut & Ramachandran, M., 2023. "Does Indian economy asymmetrically respond to oil price shocks?," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    38. Jungho Baek & Guimin Lu & Soojoong Nam, 2021. "On the asymmetric effects of changes in crude oil prices on economic growth: New evidence from China's 31 provinces," Australian Economic Papers, Wiley Blackwell, vol. 60(2), pages 328-360, June.
    39. Aimer, Najmi & Lusta, Abdulmula, 2022. "Asymmetric effects of oil shocks on economic policy uncertainty," Energy, Elsevier, vol. 241(C).
    40. 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.
    41. 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.
    42. 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).
    43. 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.
    44. 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).
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    47. Lan Bai & Xiafei Li & Yu Wei & Guiwu Wei, 2022. "Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3694-3712, July.
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    49. 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.
    50. 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.
    51. Mirko Abbritti & Juan Equiza-Goñi & Fernando Perez Gracia & Tommaso Trani, 2020. "The effect of oil price shocks on economic activity: a local projections approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(4), pages 708-723, October.
    52. Tarek Tawfik Yousef Alkhateeb & Haider Mahmood, 2020. "Oil Price and Energy Depletion Nexus in GCC Countries: Asymmetry Analyses," Energies, MDPI, vol. 13(12), pages 1-13, June.
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    54. 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.
    55. Maghyereh, Aktham & Abdoh, Hussein, 2021. "The impact of extreme structural oil-price shocks on clean energy and oil stocks," Energy, Elsevier, vol. 225(C).
    56. 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.
    57. 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.
    58. 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.
    59. Mohamad B. Karaki, 2020. "Monetary shocks and job flows: evidence from disaggregated data," Empirical Economics, Springer, vol. 58(6), pages 2911-2936, June.
    60. 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).
    61. 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.
    62. 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.
    63. Miescu, Mirela & Mumtaz, Haroon & Theodoridis, Konstantinos, 2024. "Non-linear Dynamics of Oil Supply News Shocks," Cardiff Economics Working Papers E2024/18, Cardiff University, Cardiff Business School, Economics Section.
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    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.

  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. Wada, Tatsuma, 2012. "On the correlations of trend–cycle errors," Economics Letters, Elsevier, vol. 116(3), pages 396-400.
    See citations under working paper version above.
  11. 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. Mario Porqueddu & Fabrizio Venditti, 2012. "Do food commodity prices have asymmetric effects on Euro-Area inflation?," Temi di discussione (Economic working papers) 878, Bank of Italy, Economic Research and International Relations Area.
    2. Kamyabi, Najmeh & Chidmi, Benaissa, 2022. "Gasoline demand in the United States: An asymmetric economic analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    3. Zhang, Wenbei & Qiu, Feng, 2024. "Rockets and Feathers in the Oil and Gasoline Markets: In-Depth Analysis of Three Asymmetries," 2024 Annual Meeting, July 28-30, New Orleans, LA 344062, Agricultural and Applied Economics Association.
    4. 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.
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    6. Gao, Liping & Kim, Hyeongwoo & Saba, Richard, 2014. "How Do Oil Price Shocks Affect Consumer Prices?," MPRA Paper 57259, University Library of Munich, Germany.
    7. Apostolos Serletis & Libo Xu, "undated". "Markov Switching Oil Price Uncertainty," Working Papers 2019-02, Department of Economics, University of Calgary, revised 02 Jan 2019.
    8. Hamilton, James D., 2011. "Nonlinearities And The Macroeconomic Effects Of Oil Prices," Macroeconomic Dynamics, Cambridge University Press, vol. 15(S3), pages 364-378, November.
    9. 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.
    10. De Santis, Roberto A. & Tornese, Tommaso, 2023. "Energy supply shocks’ nonlinearities on output and prices," Working Paper Series 2834, European Central Bank.
    11. Narayan, Paresh Kumar & Sharma, Susan Sunila & Poon, Wai Ching & Westerlund, Joakim, 2014. "Do oil prices predict economic growth? New global evidence," Working Papers fe_2014_09, Deakin University, Department of Economics.
    12. Lin, Boqiang & Lan, Tianxu, 2025. "The transmission of coal price shock to Chinese industry: Sub-sectors and regions heterogeneity," Energy, Elsevier, vol. 316(C).
    13. 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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    27. Rasool Dehghanzadeh Shahabad & Mehmet Balcilar, 2022. "Modelling the Dynamic Interaction between Economic Policy Uncertainty and Commodity Prices in India: The Dynamic Autoregressive Distributed Lag Approach," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
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    39. Melichar, Mark, 2016. "Energy price shocks and economic activity: Which energy price series should we be using?," Energy Economics, Elsevier, vol. 54(C), pages 431-443.
    40. Diaz, Elena Maria & Molero, Juan Carlos & Perez de Gracia, Fernando, 2016. "Oil price volatility and stock returns in the G7 economies," Energy Economics, Elsevier, vol. 54(C), pages 417-430.
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    43. De, Kuhelika & Compton, Ryan A. & Giedeman, Daniel C., 2022. "Oil shocks and the U.S. economy in a data-rich model," Economic Modelling, Elsevier, vol. 108(C).
    44. 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.
    45. Lance J Bachmeier & Benjamin D Keen, 2023. "Modeling the Asymmetric Effects of an Oil Price Shock," International Journal of Central Banking, International Journal of Central Banking, vol. 19(3), pages 1-47, August.
    46. 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.
    47. 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.
    48. Knotek, Edward S. & Zaman, Saeed, 2021. "Asymmetric responses of consumer spending to energy prices: A threshold VAR approach," Energy Economics, Elsevier, vol. 95(C).
    49. Mustafa Kocoglu, 2023. "Drivers of inflation in Turkey: a new Keynesian Phillips curve perspective," Economic Change and Restructuring, Springer, vol. 56(4), pages 2825-2853, August.
    50. Chen, Shiyi & Chen, Dengke & Härdle, Wolfgang Karl, 2014. "The influence of oil price shocks on China's macro-economy: A perspective of international trade," SFB 649 Discussion Papers 2014-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    51. Ahmadi, Maryam & Manera, Matteo, 2021. "Oil Price Shocks and Economic Growth in Oil-Exporting Countries," FEEM Working Papers 311052, Fondazione Eni Enrico Mattei (FEEM).
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    53. Nguyen, Bao H. & Okimoto, Tatsuyoshi & Tran, Trung Duc, 2022. "Uncertainty-dependent and sign-dependent effects of oil market shocks," Journal of Commodity Markets, Elsevier, vol. 26(C).
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    69. Chow, Sheung Chi & Vieito, João Paulo & Wong, Wing Keung, 2019. "Do both demand-following and supply-leading theories hold true in developing countries?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 536-554.
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