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Jouchi Nakajima

Citations

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

Working papers

  1. Harrison, Michael & Nakajima, Jouchi & Shabani, Mimoza, 2022. "An evolution of global and regional banking networks: A focus on Japanese banks’ international expansion," Discussion paper series HIAS-E-120, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.

    Cited by:

    1. Mikhail Stolbov & Daniil Parfenov, 2023. "Credit risk linkages in the international banking network, 2000–2019," Risk Management, Palgrave Macmillan, vol. 25(3), pages 1-38, September.

  2. Jouchi Nakajima & Hiroaki Yamagata & Tatsushi Okuda & Shinnosuke Katsuki & Takeshi Shinohara, 2021. "Extracting Firms' Short-Term Inflation Expectations from the Economy Watchers Survey Using Text Analysis," Bank of Japan Working Paper Series 21-E-12, Bank of Japan.

    Cited by:

    1. De Bandt Olivier & Bricongne Jean-Charles & Denes Julien & Dhenin Alexandre & De Gaye Annabelle & Robert Pierre-Antoine, 2023. "Using the Press to Construct a New Indicator of Inflation Perceptions in France," Working papers 921, Banque de France.

  3. Takuji Kawamoto & Takashi Nakazawa & Yui Kishaba & Kohei Matsumura & Jouchi Nakajima, 2021. "Supplementary Paper Series for the "Assessment" (2): Estimating Effects of Expansionary Monetary Policy since the Introduction of Quantitative and Qualitative Monetary Easing (QQE) Using the," Bank of Japan Working Paper Series 21-E-4, Bank of Japan.

    Cited by:

    1. Athanasios Orphanides, 2021. "The Power of Central Bank Balance Sheets," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 39, pages 35-54, November.
    2. Orphanides, Athanasios & Hofmann, Boris & Lombardi, Marco & Mojon, Benoit, 2021. "Fiscal and monetary policy interactions in a low interest rate world," CEPR Discussion Papers 16411, C.E.P.R. Discussion Papers.
    3. Allen, David & Mizuno, Hiro, 2021. "Monetary Policies, US influence and other Factors Affecting Stock Prices in Japan," MPRA Paper 111734, University Library of Munich, Germany.
    4. Richard Finlay & Dmitry Titkov & Michelle Xiang, 2022. "The Yield and Market Function Effects of the Reserve Bank of Australia's Bond Purchases," RBA Research Discussion Papers rdp2022-02, Reserve Bank of Australia.
    5. Takuji Kawamoto & Jouchi Nakajima & Tomoaki Mikami, 2021. "Supplementary Paper Series for the "Assessment" (3): Inflation-Overshooting Commitment:An Analysis Using a Macroeconomic Model," Bank of Japan Working Paper Series 21-E-9, Bank of Japan.

  4. Takeshi Shinohara & Tatsushi Okuda & Jouchi Nakajima, 2020. "Characteristics of Uncertainty Indices in the Macroeconomy," Bank of Japan Working Paper Series 20-E-6, Bank of Japan.

    Cited by:

    1. Honda, Tomohito & Uesugi, Iichiro, 2021. "COVID-19 and Precautionary Corporate Cash Holdings: Evidence from Japan," RCESR Discussion Paper Series DP21-2, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    2. Cosmas Dery & Apostolos Serletis, 2021. "Disentangling the Effects of Uncertainty, Monetary Policy and Leverage Shocks on the Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(5), pages 1029-1065, October.

  5. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.

    Cited by:

    1. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    2. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    3. Pantelis Samartsidis & Shaun R. Seaman & Silvia Montagna & André Charlett & Matthew Hickman & Daniela De Angelis, 2020. "A Bayesian multivariate factor analysis model for evaluating an intervention by using observational time series data on multiple outcomes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1437-1459, October.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
    6. Kenichiro McAlinn & Kosaku Takanashi, 2019. "Mean-shift least squares model averaging," Papers 1912.01194, arXiv.org.
    7. Knut Are Aastveit & Jamie L. Cross & Herman K. van Dijk, 2021. "Quantifying time-varying forecast uncertainty and risk for the real price of oil," Working Paper 2021/3, Norges Bank.
    8. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    9. Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
    10. Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
    11. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    12. Mike West, 2020. "Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 1-31, February.
    13. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    14. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    15. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    16. Yolanda S. Stander, 2023. "The Governance and Disclosure of IFRS 9 Economic Scenarios," JRFM, MDPI, vol. 16(1), pages 1-27, January.
    17. Bruno P. C. Levy & Hedibert F. Lopes, 2021. "Dynamic Ordering Learning in Multivariate Forecasting," Papers 2101.04164, arXiv.org, revised Nov 2021.
    18. Tony Chernis, 2023. "Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis," Staff Working Papers 23-45, Bank of Canada.
    19. Casarin, Roberto & Grassi, Stefano & Ravazzolo, Francesco & van Dijk, Herman K., 2023. "A flexible predictive density combination for large financial data sets in regular and crisis periods," Journal of Econometrics, Elsevier, vol. 237(2).
    20. Paolo Berta & Paolo Paruolo & Stefano Verzillo & Pietro Giorgio Lovaglio, 2020. "A bivariate prediction approach for adapting the health care system response to the spread of COVID-19," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-14, October.
    21. K=osaku Takanashi & Kenichiro McAlinn, 2019. "Equivariant online predictions of non-stationary time series," Papers 1911.08662, arXiv.org, revised Jun 2023.

  6. Andrew Filardo & Jouchi Nakajima, 2018. "Effectiveness of unconventional monetary policies in a low interest rate environment," BIS Working Papers 691, Bank for International Settlements.

    Cited by:

    1. Filardo, Andrew J. & Siklos, Pierre L., 2020. "The cross-border credit channel and lending standards surveys," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    2. Grahame Johnson & Sharon Kozicki & Romanos Priftis & Lena Suchanek & Jonathan Witmer & Jing Yang, 2020. "Implementation and Effectiveness of Extended Monetary Policy Tools: Lessons from the Literature," Discussion Papers 2020-16, Bank of Canada.
    3. Kirikos, Dimitris G., 2020. "Quantitative easing impotence in the liquidity trap: Further evidence," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 151-162.
    4. Jančoková, Martina & Pástor, Ľuboš & Fabo, Brian & Kempf, Elisabeth, 2021. "Fifty shades of QE: comparing findings of central bankers and academics," Working Paper Series 2584, European Central Bank.
    5. Brand, Claus & Bielecki, Marcin & Penalver, Adrian, 2018. "The natural rate of interest: estimates, drivers, and challenges to monetary policy JEL Classification: E52, E43," Occasional Paper Series 217, European Central Bank.
    6. Maria Sole Pagliari, 2021. "Does one (unconventional) size fit all? Effects of the ECB's unconventional monetary policies on the euro area economies," Working papers 829, Banque de France.
    7. Stéphane Lhuissier & Benoît Mojon & Juan Rubio-Ramírez, 2020. "Does the Liquidity Trap Exist?," Working papers 762, Banque de France.
    8. Dimitris G. Kirikos, 2024. "Quantitative easing effectiveness: Evidence from Euro private assets," Bulletin of Economic Research, Wiley Blackwell, vol. 76(2), pages 354-370, April.
    9. Halyna Alekseievska & Anzor Mumladze, 2020. "Quantitative Easing As The Main Instrument Of Unconventional Monetary Policy," Three Seas Economic Journal, Publishing house "Baltija Publishing", vol. 1(1).
    10. Andrea De Polis & Mario Pietrunti, 2019. "Exchange rate dynamics and unconventional monetary policies: it�s all in the shadows," Temi di discussione (Economic working papers) 1231, Bank of Italy, Economic Research and International Relations Area.

  7. Jouchi Nakajima, 2018. "The role of household debt heterogeneity on consumption: Evidence from Japanese household data," BIS Working Papers 736, Bank for International Settlements.

    Cited by:

    1. Deng, Xin & Yu, Mingzhe, 2021. "Does the marginal child increase household debt? – Evidence from the new fertility policy in China," International Review of Financial Analysis, Elsevier, vol. 77(C).
    2. Zhang, Dongyang & Guo, Rui, 2020. "The consumption response to household leverage in China: The role of investment at household level," International Review of Financial Analysis, Elsevier, vol. 71(C).
    3. Mr. Fei Han & Ms. Emilia M Jurzyk & Wei Guo & Yun He & Ms. Nadia Rendak, 2019. "Assessing Macro-Financial Risks of Household Debt in China," IMF Working Papers 2019/258, International Monetary Fund.
    4. Sarah Chan, 2020. "China’s Rising Household Debt: A New Debt Trap?," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 4, pages 567-578, December.
    5. Maiko Koga & Kohei Matsumura, "undated". "Marginal Propensity to Consume and the Housing Choice," Bank of Japan Working Paper Series 20-E-3, Bank of Japan.
    6. Kassouri, Yacouba & Alola, Andrew Adewale & Savaş, Savaş, 2021. "The dynamics of material consumption in phases of the economic cycle for selected emerging countries," Resources Policy, Elsevier, vol. 70(C).
    7. R. Basselier & G. Minne & G. Langenus, 2019. "Why has Belgian private consumption growth been so moderate in recent years?," Economic Review, National Bank of Belgium, issue i, pages 51-67, June.
    8. Sala, Hector & Trivín, Pedro, 2022. "Family Finances and Debt Overhang: Evolving Consumption Patterns of Spanish Households," IZA Discussion Papers 15222, Institute of Labor Economics (IZA).
    9. Yunchao, Cai & Abdullah Yusof, Selamah & Mohd Amin, Ruzita & Mohd Arshad, Mohd Nahar, 2020. "Household Debt and Household Spending Behavior: Evidence from Malaysia," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 54(1), pages 111-120.

  8. Shin-ichi Fukuda & Munehisa Kasuya & Jouchi Nakajima, 2018. "The Role of Corporate Governance in Japanese Unlisted Companies," CIRJE F-Series CIRJE-F-1081, CIRJE, Faculty of Economics, University of Tokyo.

    Cited by:

    1. Kojima Koji & Bishnu Kumar Adhikary & Le Tram, 2020. "Corporate Governance and Firm Performance: A Comparative Analysis between Listed Family and Non-Family Firms in Japan," JRFM, MDPI, vol. 13(9), pages 1-20, September.
    2. Kodama, Naomi & Murakami, Yoshiaki & Tanaka, Mari, 2021. "No Successor, No Success? Impact of a Little Son on Business Performance," Journal of the Japanese and International Economies, Elsevier, vol. 62(C).
    3. Ueda, Kenichi & Ishide, Akira & Goto, Yasuo, 2019. "Listing and financial constraints," Japan and the World Economy, Elsevier, vol. 49(C), pages 1-16.
    4. HANNAH, Leslie, 2018. "Corporate Governance, Accounting Transparency and Stock Exchange Sizes in Germany, Japan and “Anglo-Saxon” Economies, 1870-1950," Discussion paper series HIAS-E-77, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    5. Blind, Georg & Lottanti von Mandach, Stefania, 2017. "When Vultures Bring Blessings: Employment Growth in Japanese Businesses under Private Equity Ownership," MPRA Paper 77764, University Library of Munich, Germany.
    6. Tomeczek, Artur F., 2022. "The evolution of Japanese keiretsu networks: A review and text network analysis of their perceptions in economics," Japan and the World Economy, Elsevier, vol. 62(C).
    7. Fukuda, Akira, 2020. "The Effects of M&A on Corporate Performance in Japan:DID Analysis in the Era of Corporate Governance Reform," Japan and the World Economy, Elsevier, vol. 55(C).
    8. Ohk, Seungbin & Ju, Biung-Ghi, 2021. "Capitalizing on prospect theory value: The Asian developed stock markets," Japan and the World Economy, Elsevier, vol. 57(C).

  9. Takuji Fueki & Hiroka Higashi & Naoto Higashio & Jouchi Nakajima & Shinsuke Ohyama & Yoichiro Tamanyu, 2018. "Identifying oil price shocks and their consequences: the role of expectations in the crude oil market," BIS Working Papers 725, Bank for International Settlements.

    Cited by:

    1. Peter Y. Jang & Mario G. Beruvides, 2020. "Time-Varying Influences of Oil-Producing Countries on Global Oil Price," Energies, MDPI, vol. 13(6), pages 1-22, March.
    2. Nathan Sussman & Osnat Zohar, 2018. "Has inflation targeting become less credible?," BIS Working Papers 729, Bank for International Settlements.
    3. Omotosho, Babatunde S., 2020. "Oil price shocks, fuel subsidies and macroeconomic (in)stability in Nigeria," MPRA Paper 105464, University Library of Munich, Germany.
    4. Sakib Bin Amin & Noshin Nawal Audry & Ahmed Farah Ulfat, 2021. "The Nexus Between Oil Price Shock and the Exchange Rate in Bangladesh," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 427-435.
    5. 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).
    6. Considine, Jennifer & Hatipoglu, Emre & Aldayel, Abdullah, 2022. "The sensitivity of oil price shocks to preexisting market conditions: A GVAR analysis," Journal of Commodity Markets, Elsevier, vol. 27(C).
    7. Filardo, Andrew & Lombardi, Marco & Montoro, Carlos & Ferrari, Massimo, 2018. "Monetary policy spillovers, global commodity prices and cooperation," Working Papers 2018-002, Banco Central de Reserva del Perú.
    8. Piersanti, Giovanni & Piersanti, Mirko & Cicone, Antonio & Canofari, Paolo & Di Domizio, Marco, 2020. "An inquiry into the structure and dynamics of crude oil price using the fast iterative filtering algorithm," Energy Economics, Elsevier, vol. 92(C).
    9. Emanuel Kohlscheen & Aaron Mehrotra & Dubravko Mihaljek, 2020. "Residential Investment and Economic Activity: Evidence from the Past Five Decades," International Journal of Central Banking, International Journal of Central Banking, vol. 16(6), pages 287-329, December.
    10. Jiménez-Rodríguez, Rebeca, 2022. "Oil shocks and global economy," Energy Economics, Elsevier, vol. 115(C).
    11. Krzysztof Echaust & Małgorzata Just, 2021. "Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic," Energies, MDPI, vol. 14(14), pages 1-21, July.
    12. Nchofoung, Tii N., 2024. "Oil price shocks and energy transition in Africa," Energy Policy, Elsevier, vol. 184(C).
    13. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
    14. Gkillas, Konstantinos & Manickavasagam, Jeevananthan & Visalakshmi, S., 2022. "Effects of fundamentals, geopolitical risk and expectations factors on crude oil prices," Resources Policy, Elsevier, vol. 78(C).
    15. Umechukwu, Chisom & Olayungbo, D.O., 2022. "US oil supply shocks and economies of oil-exporting African countries: A GVAR-Oil Resource Analysis," Resources Policy, Elsevier, vol. 75(C).
    16. Mo, Bin & Zeng, Haiyu & Meng, Juan & Ding, Shaokai, 2024. "The connectedness between uncertainty and exchange rates of oil import countries: new evidence from time and frequency perspective," Resources Policy, Elsevier, vol. 88(C).
    17. Henry Egbezien Inegbedion & Emmanuel Inegbedion & Eseosa Obadiaru & Abiola Asaleye, 2020. "Petroleum Subsidy Withdrawal, Fuel Price Hikes and the Nigerian Economy," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 258-265.
    18. Yao Axel Ehouman, 2020. "Do oil-market shocks drive global liquidity?," EconomiX Working Papers 2020-33, University of Paris Nanterre, EconomiX.
    19. Even Comfort Hvinden, 2019. "OPEC's crude game," Working Papers No 10/2019, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    20. Tii N. Nchofoung, 2023. "Oil price shocks and energy transition in Africa," Working Papers of the African Governance and Development Institute. 23/064, African Governance and Development Institute..

  10. Takuji Fueki & Hiroka Higashi & Naoto Higashio & Jouchi Nakajima & Shinsuke Ohyama & Yoichiro Tamanyu, 2016. "Identifying Oil Price Shocks and Their Consequences:Role of Expectations and Financial Factors in the Crude Oil Market," Bank of Japan Working Paper Series 16-E-17, Bank of Japan.

    Cited by:

    1. Antonio J. Garz n & Luis . Hierro, 2018. "Fracking, Wars and Stock Market Crashes: The Price of Oil During the Great Recession," International Journal of Energy Economics and Policy, Econjournals, vol. 8(2), pages 20-30.
    2. Babak Fazelabdolabadi, 2019. "Uncertainty and energy-sector equity returns in Iran: a Bayesian and quasi-Monte Carlo time-varying analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-20, December.
    3. Neville Francis & Sergio Restrepo-Angel, 2018. "Sectoral and aggregate response to oil price shocks in the Colombian economy: SVAR and Local Projections approach," Borradores de Economia 1055, Banco de la Republica de Colombia.

  11. Jouchi Nakajima & Kosuke Takatomi & Tomoko Mori & Shinsuke Ohyama, 2016. "Slow Trade: Structural and Cyclical Factors in Global Trade Slowdown," Bank of Japan Research Papers 16-12-22, Bank of Japan.

    Cited by:

    1. Marcato, Marilia Bassetti & Dweck, Esther & Montanha, Rafael, 2022. "The densification of Chinese production chains in the context of vertically fragmented production," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 75-89.
    2. Ayako Obashi & Fukunari Kimura, 2018. "Are Production Networks Passé in East Asia? Not Yet," Asian Economic Papers, MIT Press, vol. 17(3), pages 86-107, Fall.
    3. Xuefeng Qian & Zhao Liu & Ying Pan, 2017. "China's Trade Slowdown: Cyclical or Structural?," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 25(6), pages 65-83, November.
    4. Mari Pangestu & Lili Yan Ing & Gracia Hadiwidjaja, 2018. "The Future of East Asia’s Trade: A Call for Better Globalization," Asian Economic Policy Review, Japan Center for Economic Research, vol. 13(2), pages 219-238, July.
    5. Ayako Obashi & Fukunari Kimura, "undated". "Are Production Networks Passé in East Asia? Not Yet," Working Papers DP-2018-03, Economic Research Institute for ASEAN and East Asia (ERIA).

  12. Koichiro Kamada & Jouchi Nakajima & Shusaku Nishiguchi, 2015. "Are Household Inflation Expectations Anchored in Japan?," Bank of Japan Working Paper Series 15-E-8, Bank of Japan.

    Cited by:

    1. Gunji, Hiroshi, 2024. "Impact of the Kuroda Bazooka on Japanese households’ borrowing intentions," Japan and the World Economy, Elsevier, vol. 69(C).
    2. Hattori, Masazumi & Yetman, James, 2017. "The evolution of inflation expectations in Japan," CIS Discussion paper series 662, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
    3. Nam, Minho & Go, Minji, 2018. "Nexus between Inflation, Inflation Perceptions and Expectations," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 40(3), pages 45-68.
    4. Sohei Kaihatsu & Noriyuki Shiraki, 2016. "Firms' Inflation Expectations and Wage-setting Behaviors," Bank of Japan Working Paper Series 16-E-10, Bank of Japan.
    5. Mr. Gee Hee Hong & Rahul Anand & Yaroslav Hul, 2019. "Achieving the Bank of Japan’s Inflation Target," IMF Working Papers 2019/229, International Monetary Fund.
    6. Pierre L. Siklos, 2017. "What has publishing inflation forecasts accomplished? Central banks and their competitors," CAMA Working Papers 2017-33, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Murasawa, Yasutomo, 2017. "Measuring the Distributions of Public Inflation Perceptions and Expectations in the UK," MPRA Paper 76244, University Library of Munich, Germany.
    8. Olivier Coibion & Yuriy Gorodnichenko & Saten Kumar & Mathieu Pedemonte, 2018. "Inflation Expectations as a Policy Tool?," NBER Working Papers 24788, National Bureau of Economic Research, Inc.
    9. Fructuoso Borrallo Egea & Pedro del Río López, 2021. "Monetary policy strategy and inflation in Japan," Occasional Papers 2116, Banco de España.
    10. Mototsugu Shintani & Naoto Soma, 2020. "The Effects of QQE on Long-run Inflation Expectations in Japan," CARF F-Series CARF-F-494, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    11. Takatoshi Ito, 2021. "An Assessment of Abenomics: Evolution and Achievements," Asian Economic Policy Review, Japan Center for Economic Research, vol. 16(2), pages 190-219, July.
    12. Yasutomo Murasawa, 2020. "Measuring public inflation perceptions and expectations in the UK," Empirical Economics, Springer, vol. 59(1), pages 315-344, July.
    13. James Yetman, 2022. "What's Up with Inflation Expectations?," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 55(1), pages 136-140, March.
    14. Yusuke Takahashi & Yoichiro Tamanyu, 2022. "Households' Perceived Inflation and CPI Inflation: the Case of Japan," Bank of Japan Working Paper Series 22-E-1, Bank of Japan.
    15. Tomiyuki Kitamura & Masaki Tanaka, 2019. "Firms' Inflation Expectations under Rational Inattention and Sticky Information: An Analysis with a Small-Scale Macroeconomic Model," Bank of Japan Working Paper Series 19-E-16, Bank of Japan.
    16. Fructuoso Borrallo Egea & Pedro del Río López, 2021. "Estrategia de política monetaria e inflación en Japón," Occasional Papers 2116, Banco de España.
    17. Evelyne Dourille-Feer, 2015. "Can the magic of Abenomics succeed?," Working Papers 2015-24, CEPII research center.
    18. Yuichiro Ito & Sohei Kaihatsu, 2016. "Effects of Inflation and Wage Expectations on Consumer Spending: Evidence from Micro Data," Bank of Japan Working Paper Series 16-E-7, Bank of Japan.

  13. Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2015. "Bayesian Modeling of Dynamic Extreme Values: Extension of Generalized Extreme Value Distributions with Latent Stochastic Processes ," CIRJE F-Series CIRJE-F-952, CIRJE, Faculty of Economics, University of Tokyo.

    Cited by:

    1. Gloria Gonzalez-Rivera & Yun Luo, 2020. "A Truncated Mixture Transition Model for Interval-valued Time Series," Working Papers 202005, University of California at Riverside, Department of Economics.
    2. Cathy W.S. Chen & Toshiaki Watanabe, 2019. "Bayesian modeling and forecasting of Value‐at‐Risk via threshold realized volatility," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 35(3), pages 747-765, May.
    3. Wulan Anggraeni & Sudradjat Supian & Sukono & Nurfadhlina Abdul Halim, 2023. "Catastrophe Bond Diversification Strategy Using Probabilistic–Possibilistic Bijective Transformation and Credibility Measures in Fuzzy Environment," Mathematics, MDPI, vol. 11(16), pages 1-30, August.

  14. Kei Imakubo & Haruki Kojima & Jouchi Nakajima, 2015. "The natural yield curve: its concept and measurement," Bank of Japan Working Paper Series 15-E-5, Bank of Japan.

    Cited by:

    1. Brand, Claus & Goy, Gavin W & Lemke, Wolfgang, 2020. "Natural rate chimera and bond pricing reality," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224546, Verein für Socialpolitik / German Economic Association.
    2. NAKAJIMA, Jouchi & SUDO, Nao & HOGEN, Yoshihiko & TAKIZUKA, Yasutaka, 2023. "On the estimation of the natural yield curve," Discussion Paper Series 753, Institute of Economic Research, Hitotsubashi University.
    3. Leeper, E.M. & Leith, C., 2016. "Understanding Inflation as a Joint Monetary–Fiscal Phenomenon," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 2305-2415, Elsevier.
    4. Campbell Leith & Eric Leeper, 2016. "Understanding Inflation as a Joint Monetary-Fiscal Phenomenon," Working Papers 2016_01, Business School - Economics, University of Glasgow.
    5. Mr. Fei Han, 2019. "Demographics and the Natural Rate of Interest in Japan," IMF Working Papers 2019/031, International Monetary Fund.
    6. Lee, Dong Jin & Hahm, Joon-Ho & Park, Hail & Park, Ki Young, 2020. "Measuring the Natural Rate of Interest with Financial Gaps: The Cases of Japan and South Korea," Japan and the World Economy, Elsevier, vol. 54(C).
    7. Koeda, Junko & Sekine, Atsushi, 2022. "Nelson–Siegel decay factor and term premia in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 64(C).
    8. Murasawa, Yasutomo, 2019. "Bayesian multivariate Beveridge--Nelson decomposition of I(1) and I(2) series with cointegration," MPRA Paper 91979, University Library of Munich, Germany.
    9. Yosuke Okazaki & Nao Sudo, 2018. "Natural Rate of Interest in Japan -- Measuring its size and identifying drivers based on a DSGE model --," Bank of Japan Working Paper Series 18-E-6, Bank of Japan.
    10. Kazutoshi Kan & Yui Kishaba & Tomohiro Tsuruga, 2016. "Supplementary Paper Series for the "Comprehensive Assessment" (3): Policy Effects since the Introduction of Quantitative and Qualitative Monetary Easing (QQE) -- Assessment Based on Bank of ," Bank of Japan Working Paper Series 16-E-15, Bank of Japan.
    11. Han, Fei, 2024. "The impact of demographic change on the natural rate of interest in Japan," Japan and the World Economy, Elsevier, vol. 69(C).

  15. Sohei Kaihatsu & Jouchi Nakajima, 2015. "Has Trend Inflation Shifted?: An Empirical Analysis with a Regime-Switching Model," Bank of Japan Working Paper Series 15-E-3, Bank of Japan.

    Cited by:

    1. Francesco Zanetti & Tatsushi Okuda & Tomohiro Tsuruga, 2019. "Imperfect Information, Shock Heterogeneity, and Inflation Dynamics," Economics Series Working Papers 881, University of Oxford, Department of Economics.
    2. Hattori, Masazumi & Yetman, James, 2017. "The evolution of inflation expectations in Japan," CIS Discussion paper series 662, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
    3. OKIMOTO Tatsuyoshi, 2018. "Trend Inflation and Monetary Policy Regimes in Japan," Discussion papers 18024, Research Institute of Economy, Trade and Industry (RIETI).
    4. Sohei Kaihatsu & Noriyuki Shiraki, 2016. "Firms' Inflation Expectations and Wage-setting Behaviors," Bank of Japan Working Paper Series 16-E-10, Bank of Japan.
    5. MIYAO Ryuzo & OKIMOTO Tatsuyoshi, 2017. "The Macroeconomic Effects of Japan's Unconventional Monetary Policies," Discussion papers 17065, Research Institute of Economy, Trade and Industry (RIETI).
    6. Mr. Gee Hee Hong & Rahul Anand & Yaroslav Hul, 2019. "Achieving the Bank of Japan’s Inflation Target," IMF Working Papers 2019/229, International Monetary Fund.
    7. Sohei Kaihatsu & Mitsuru Katagiri & Noriyuki Shiraki, 2017. "Phillips Curve and Price-Change Distribution under Declining Trend Inflation," Bank of Japan Working Paper Series 17-E-5, Bank of Japan.
    8. Adriana Lojschova, 2017. "Did quantitative easing boost bank lending? The Slovak experience," Working and Discussion Papers WP 1/2017, Research Department, National Bank of Slovakia.
    9. Yoshiyuki Kurachi & Kazuhiro Hiraki & Shinichi Nishioka, 2016. "Does a Higher Frequency of Micro-level Price Changes Matter for Macro Price Stickiness?: Assessing the Impact of Temporary Price Changes," Bank of Japan Working Paper Series 16-E-9, Bank of Japan.
    10. Yoshihiko Hogen & Ryoichi Okuma, 2018. "The Anchoring of Inflation Expectations in Japan: A Learning-Approach Perspective," Bank of Japan Working Paper Series 18-E-8, Bank of Japan.
    11. Koji Takahashi, 2016. "TIPS: The Trend Inflation Projection System and Estimation Results," Bank of Japan Working Paper Series 16-E-18, Bank of Japan.
    12. Dunne, Peter & Everett, Mary & Stuart, Rebecca, 2015. "The Expanded Asset Purchase Programme – What, Why and How of Euro Area QE," Quarterly Bulletin Articles, Central Bank of Ireland, pages 61-71, July.
    13. Hiroshi Ugai, 2015. "Transmission Channels and Welfare Implications of Unconventional Monetary Easing Policy in Japan," UTokyo Price Project Working Paper Series 060, University of Tokyo, Graduate School of Economics, revised Dec 2015.
    14. Hiroshi Ugai, "undated". "Transmission Channels and Welfare Implications of Unconventional Monetary Easing Policy in Japan," Working Papers e102, Tokyo Center for Economic Research.
    15. OKIMOTO, Tatsuyoshi, 2017. "Expected Inflation Regimes in Japan," Discussion paper series HIAS-E-41, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.

  16. Kei Imakubo & Jouchi Nakajima, 2015. "Estimating inflation risk premia from nominal and real yield curves using a shadow-rate model," Bank of Japan Working Paper Series 15-E-1, Bank of Japan.

    Cited by:

    1. Tomiyuki Kitamura & Ichiro Muto & Ikuo Takei, 2015. "How Do Japanese Banks Set Loan Interest Rates?: Estimating Pass-Through Using Bank-Level Data," Bank of Japan Working Paper Series 15-E-6, Bank of Japan.
    2. Samuel Howorth & Domenico Lombardi & Pierre L. Siklos, 2019. "Together or Apart? Monetary Policy Divergences in the G4," Open Economies Review, Springer, vol. 30(2), pages 191-217, April.
    3. Berardi, Andrea & Plazzi, Alberto, 2022. "Dissecting the yield curve: The international evidence," Journal of Banking & Finance, Elsevier, vol. 134(C).
    4. Wataru Miyamoto & Thuy Lan Nguyen & Dmitriy Sergeyev, 2017. "Government Spending Multipliers Under the Zero Lower Bound: Evidence from Japan," Staff Working Papers 17-40, Bank of Canada.
    5. Kazuhiro Hiraki & Wataru Hirata, 2020. "Market-based Long-term Inflation Expectations in Japan: A Refinement on Breakeven Inflation Rates," Bank of Japan Working Paper Series 20-E-5, Bank of Japan.
    6. Juan Andrés Espinosa-Torres & Luis Fernando Melo-Velandía & José Fernando Moreno-Gutiérrez, 2015. "Expectativas de inflación, prima de riesgo inflacionario y prima de liquidez: una descomposición del break-even inflation para los bonos del gobierno colombiano," Borradores de Economia 13700, Banco de la Republica.
    7. Harendra Behera & Sitikantha Pattanaik & Rajesh Kavediya, 2015. "Natural Interest Rate: Assessing the Stance of India’s Monetary Policy under Uncertainty," Working Papers id:7654, eSocialSciences.
    8. Rui WANG, 2019. "Estimating the Monetary Policy Measures of Japan in Shadow/ZLB Term Structure Model," Applied Economics and Finance, Redfame publishing, vol. 6(6), pages 126-139, November.
    9. Ichiro Fukunaga & Naoya Kato & Junko Koeda, 2015. "Maturity Structure and Supply Factors in Japanese Government Bond Markets," IMES Discussion Paper Series 15-E-10, Institute for Monetary and Economic Studies, Bank of Japan.
    10. Domenico Lombardi & Pierre L. Siklos & Xiangyou Xie, 2018. "Monetary policy transmission in systemically important economies and China’s impact," CAMA Working Papers 2018-50, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Juan Andrés Espinosa-Torres & Luis Fernando Melo-Velandia & José Fernando Moreno-Gutiérrez, 2017. "Expectativas de inflación, prima de riesgo inflacionario y prima de liquidez: una descomposición del break-even inflation para los bonos del Gobierno colombiano," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 78, February.
    12. Covarrubias, Enrique & Hernández-del-Valle, Gerardo, 2016. "Inflation expectations derived from a portfolio model," MPRA Paper 69489, University Library of Munich, Germany.
    13. Hiroshi Ugai, 2015. "Transmission Channels and Welfare Implications of Unconventional Monetary Easing Policy in Japan," UTokyo Price Project Working Paper Series 060, University of Tokyo, Graduate School of Economics, revised Dec 2015.
    14. Hiroshi Ugai, "undated". "Transmission Channels and Welfare Implications of Unconventional Monetary Easing Policy in Japan," Working Papers e102, Tokyo Center for Economic Research.
    15. Berardi, Andrea, 2023. "Term premia and short rate expectations in the euro area," Journal of Empirical Finance, Elsevier, vol. 74(C).
    16. Camba-Méndez, Gonzalo, 2020. "On the inflation risks embedded in sovereign bond yields," Working Paper Series 2423, European Central Bank.
    17. Argyropoulos, Efthymios & Tzavalis, Elias, 2021. "The influence of real interest rates and risk premium effects on the ability of the nominal term structure to forecast inflation," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 785-796.

  17. Kei Imakubo & Haruki Kojima & Jouchi Nakajima, 2015. "The natural yield curve: its concept and developments in Japan," Bank of Japan Research Laboratory Series 15-E-3, Bank of Japan.

    Cited by:

    1. Leeper, E.M. & Leith, C., 2016. "Understanding Inflation as a Joint Monetary–Fiscal Phenomenon," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 2305-2415, Elsevier.
    2. Sohei Kaihatsu & Koichiro Kamada & Mitsuru Katagiri, 2016. "Theoretical Foundations for Quantitative Easing," IMES Discussion Paper Series 16-E-04, Institute for Monetary and Economic Studies, Bank of Japan.
    3. Han, Fei, 2024. "The impact of demographic change on the natural rate of interest in Japan," Japan and the World Economy, Elsevier, vol. 69(C).

  18. Shusaku Nishiguchi & Jouchi Nakajima & Kei Imakubo, 2014. "Disagreement in households' inflation expectations and its evolution," Bank of Japan Review Series 14-E-1, Bank of Japan.

    Cited by:

    1. Yoshiyuki Nakazono, 2016. "Inflation expectations and monetary policy under disagreements," Bank of Japan Working Paper Series 16-E-1, Bank of Japan.
    2. Gunji, Hiroshi, 2024. "Impact of the Kuroda Bazooka on Japanese households’ borrowing intentions," Japan and the World Economy, Elsevier, vol. 69(C).
    3. Stan Du Plessis & Monique Reid & Pierre Siklos, 2018. "What drives household inflation expectations in South Africa? Demographics and anchoring under inflation targeting," CAMA Working Papers 2018-48, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Hattori, Masazumi & Yetman, James, 2017. "The evolution of inflation expectations in Japan," CIS Discussion paper series 662, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
    5. NAKAJIMA, Jouchi, 2023. "Estimation of firms' inflation expectations using the survey DI," Discussion Paper Series 749, Institute of Economic Research, Hitotsubashi University.
    6. Hunziker, Hans-Ueli & Raggi, Christian & Rosenblatt-Wisch, Rina & Zanetti, Attilio, 2022. "The impact of guidance, short-term dynamics and individual characteristics on firms’ long-term inflation expectations," Journal of Macroeconomics, Elsevier, vol. 71(C).
    7. Pierre L. Siklos, 2016. "Forecast Disagreement and the Inflation Outlook: New International Evidence," IMES Discussion Paper Series 16-E-03, Institute for Monetary and Economic Studies, Bank of Japan.
    8. Pierre L. Siklos, 2017. "What has publishing inflation forecasts accomplished? Central banks and their competitors," CAMA Working Papers 2017-33, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Mr. Serkan Arslanalp & Mr. Dennis P Botman, 2015. "Portfolio Rebalancing in Japan: Constraints and Implications for Quantitative Easing," IMF Working Papers 2015/186, International Monetary Fund.
    10. Mototsugu Shintani & Naoto Soma, 2020. "The Effects of QQE on Long-run Inflation Expectations in Japan," CARF F-Series CARF-F-494, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    11. Kei Imakubo & Jouchi Nakajima, 2015. "Estimating inflation risk premia from nominal and real yield curves using a shadow-rate model," Bank of Japan Working Paper Series 15-E-1, Bank of Japan.

  19. Takeshi Kimura & Jouchi Nakajima, 2013. "Identifying Conventional and Unconventional Monetary Policy Shocks: A Latent Threshold Approach," Bank of Japan Working Paper Series 13-E-7, Bank of Japan.

    Cited by:

    1. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.
    2. Alexandra Ferreira‐Lopes & Pedro Linhares & Luís Filipe Martins & Tiago Neves Sequeira, 2022. "Quantitative easing and economic growth in Japan: A meta‐analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 235-268, February.
    3. Dekle, Robert & Hamada, Koichi, 2015. "Japanese monetary policy and international spillovers," Journal of International Money and Finance, Elsevier, vol. 52(C), pages 175-199.
    4. Henrike Michaelis & Sebastian Watzka, 2014. "Are there Differences in the Effectiveness of Quantitative Easing at the Zero-Lower-Bound in Japan over Time?," CESifo Working Paper Series 4901, CESifo.
    5. Andrew Filardo & Jouchi Nakajima, 2018. "Effectiveness of unconventional monetary policies in a low interest rate environment," BIS Working Papers 691, Bank for International Settlements.
    6. Filipa Lima & Sonia Mota, 2017. "Unconventional monetary policy - is there a call for unconventional statistics?," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Statistical implications of the new financial landscape, volume 43, Bank for International Settlements.
    7. Georgios Georgiadis & Martina Jancokova, 2017. "Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks," Globalization Institute Working Papers 314, Federal Reserve Bank of Dallas.
    8. MIYAO Ryuzo & OKIMOTO Tatsuyoshi, 2017. "The Macroeconomic Effects of Japan's Unconventional Monetary Policies," Discussion papers 17065, Research Institute of Economy, Trade and Industry (RIETI).
    9. Fumio Hayashi & Junko Koeda, 2013. "A Regime-Switching SVAR Analysis of Quantitative Easing," CARF F-Series CARF-F-322, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    10. Renzhi, Nuobu, 2022. "Do house prices play a role in unconventional monetary policy transmission in Japan?," Journal of Asian Economics, Elsevier, vol. 83(C).
    11. Martin, Feldkircher & Thomas, Gruber & Florian, Huber, 2019. "International effects of a compression of euro area yield curves," Working Papers in Economics 2019-1, University of Salzburg.
    12. Michaelis, Henrike & Watzka, Sebastian, 2014. "Are there Differences in the Effectiveness of Quantitative Easing in Japan over Time?," Discussion Papers in Economics 21087, University of Munich, Department of Economics.
    13. Yusuke Tanahara & Kento Tango & Yoshiyuki Nakazono, 2023. "Information Effects of Monetary Policy," TUPD Discussion Papers 41, Graduate School of Economics and Management, Tohoku University.
    14. Nagao, Ryoya & Kondo, Yoshihiro & Nakazono, Yoshiyuki, 2021. "The macroeconomic effects of monetary policy: Evidence from Japan," Journal of the Japanese and International Economies, Elsevier, vol. 61(C).
    15. Cone, Thomas E., 2022. "Learning with unobserved regimes," Journal of Macroeconomics, Elsevier, vol. 73(C).
    16. Kansho Piotr Otsubo, 2018. "The Effects of Fiscal and Monetary Policies in Japan: What Combination of Policies Should Be Used?," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., vol. 9(01n02), pages 1-25, February.
    17. Morita, Hiroshi, 2015. "Japanese Fiscal Policy under the Zero Lower Bound of Nominal Interest Rates: Time-Varying Parameters Vector Autoregression," Discussion Paper Series 627, Institute of Economic Research, Hitotsubashi University.
    18. Hiroyuki Ijiri & Yoichi Matsubayashi, 2016. "Quantitative Easing Policy, Exchange Rates and Business Activity by Industry in Japan from 2001-2006," Discussion Papers 1611, Graduate School of Economics, Kobe University.
    19. Hanisch, Max, 2017. "The effectiveness of conventional and unconventional monetary policy: Evidence from a structural dynamic factor model for Japan," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 110-134.
    20. Mike West, 2020. "Reply to Discussion of “Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions”," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 41-44, February.
    21. Stéphane Lhuissier & Benoît Mojon & Juan Rubio-Ramírez, 2020. "Does the Liquidity Trap Exist?," Working papers 762, Banque de France.
    22. Fumio Hayashi & Junko Koeda, 2014. "Exiting from QE," NBER Working Papers 19938, National Bureau of Economic Research, Inc.
    23. Tatsuki Okamoto & Yoichi Matsubayashi, 2017. "Empirical Evidence from a Japanese Lending Survey within the TVP-VAR Framework: Does the Credit Channel Matter for Monetary Policy?," Discussion Papers 1709, Graduate School of Economics, Kobe University.
    24. Kiyotaka Nakashima & Masahiko Shibamoto & Koji Takahashi, 2019. "Identifying Quantitative and Qualitative Monetary Policy Shocks," Discussion Paper Series DP2019-09, Research Institute for Economics & Business Administration, Kobe University, revised Mar 2023.
    25. Yuto Iwasaki & Nao Sudo, 2017. "Myths and Observations on Unconventional Monetary Policy -- Takeaways from Post-Bubble Japan --," Bank of Japan Working Paper Series 17-E-11, Bank of Japan.
    26. Hiroyuki Kubota & Mototsugu Shintani, 2023. "Macroeconomic Effects of Monetary Policy in Japan: An Analysis Using Interest Rate Futures Surprises," CARF F-Series CARF-F-555, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    27. Hiroyuki Kubota & Mototsugu Shintani, 2020. "High-frequency Identification of Unconventional Monetary Policy Shocks in Japan," CARF F-Series CARF-F-502, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    28. Kiyotaka Nakashima & Masahiko Shibamoto & Koji Takahashi, 2017. "Identifying Unconventional Monetary Policy Shocks," Discussion Paper Series DP2017-05, Research Institute for Economics & Business Administration, Kobe University, revised Apr 2017.
    29. Gerti Shijaku, 2015. "The Macroeconomic Pass-through Effects of Monetary Policy through Sign Restrictions Approach: In the Case of Albania," IHEID Working Papers 11-2015, Economics Section, The Graduate Institute of International Studies.
    30. Bäurle Gregor & Kaufmann Daniel & Kaufmann Sylvia & Strachan Rodney, 2020. "Constrained interest rates and changing dynamics at the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-26, April.
    31. Ryuzo Miyao & Tatsuyoshi Okimoto, 2020. "Regime shifts in the effects of Japan’s unconventional monetary policies," Manchester School, University of Manchester, vol. 88(6), pages 749-772, December.
    32. Ahmed Ashour Abdullah & Ahmed Mohamed Hassanien, 2022. "Spillovers of US Unconventional Monetary Policy to Emerging Markets: Evidence from Egypt," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 14(6), pages 1-1, June.
    33. Annika Camehl & Tomasz Wo'zniak, 2023. "Time-Varying Identification of Monetary Policy Shocks," Papers 2311.05883, arXiv.org, revised May 2024.
    34. Junko Koeda, 2018. "Macroeconomic Effects of Quantitative and Qualitative Monetary Easing Measures," IMES Discussion Paper Series 18-E-16, Institute for Monetary and Economic Studies, Bank of Japan.

  20. Koichiro Kamada & Jouchi Nakajima, 2013. "On the Reliability of Japanese Inflation Expectations Using Purchasing Power Parity," Bank of Japan Working Paper Series 13-E-13, Bank of Japan.

    Cited by:

    1. Petra Gerlach-Kristen & Richhild Moessner & Rina Rosenblatt-Wisch, 2018. "Computing Long-Term Market Inflation Expectations for Countries without Inflation Expectation Markets," Russian Journal of Money and Finance, Bank of Russia, vol. 77(3), pages 23-48, September.
    2. Mr. Serkan Arslanalp & Mr. Dennis P Botman, 2015. "Portfolio Rebalancing in Japan: Constraints and Implications for Quantitative Easing," IMF Working Papers 2015/186, International Monetary Fund.
    3. Rosa Ferrentino & Luca Vota, 2022. "An Analysis of the Effectiveness of Japanese Monetary Policy Through a Statistical Mathematical Approach: a Simultaneous Equations Model (SEM)," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 11(1), pages 1-2.
    4. Hiroshi Ugai, 2015. "Transmission Channels and Welfare Implications of Unconventional Monetary Easing Policy in Japan," UTokyo Price Project Working Paper Series 060, University of Tokyo, Graduate School of Economics, revised Dec 2015.
    5. Hiroshi Ugai, "undated". "Transmission Channels and Welfare Implications of Unconventional Monetary Easing Policy in Japan," Working Papers e102, Tokyo Center for Economic Research.
    6. Chiang, Shu-Hen & Lee, Chien-Chiang & Liao, Ying, 2021. "Exploring the sources of inflation dynamics: New evidence from China," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 313-332.
    7. Christina Anderl & Guglielmo Maria Caporale, 2021. "Nonlinearities and asymmetric adjustment to PPP in an exchange rate model with inflation expectations," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 49(6), pages 937-959, August.

  21. Jouchi Nakajima & Toshiaki Watanabe, 2012. "Time-Varying Vector Autoregressive Model - A Survey with the Application to the Japanese Macroeconomic Data -," Global COE Hi-Stat Discussion Paper Series gd12-232, Institute of Economic Research, Hitotsubashi University.

    Cited by:

    1. Chaofeng Tang & Kentaka Aruga, 2020. "A Study on the Pass-Through Rate of the Exchange Rate on the Liquid Natural Gas (LNG) Import Price in China," IJFS, MDPI, vol. 8(4), pages 1-19, November.

  22. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," IMES Discussion Paper Series 11-E-09, Institute for Monetary and Economic Studies, Bank of Japan.

    Cited by:

    1. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    2. Huang, Yingying & Duan, Kun & Urquhart, Andrew, 2023. "Time-varying dependence between Bitcoin and green financial assets: A comparison between pre- and post-COVID-19 periods," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    3. Bogdan DIMA & Ştefana Maria DIMA & Flavia BARNA, 2019. "Inflation Contagion Effects in the Baltic Countries: A Time-varying Coefficients VAR with Stochastic Volatility Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 72-87, March.
    4. Rufei Zhang & Haizhen Zhang & Wang Gao & Ting Li & Shixiong Yang, 2022. "The Dynamic Effects of Oil Price Shocks on Exchange Rates—From a Time-Varying Perspective," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    5. Haque, Qazi & Magnusson, Leandro M., 2021. "Uncertainty shocks and inflation dynamics in the U.S," Economics Letters, Elsevier, vol. 202(C).
    6. Vittorio Peretti & Rangan Gupta & Roula Inglesi-Lotz, 2012. "Do House Prices Impact Consumption and Interest Rate in South Africa? Evidence from a Time-Varying Vector Autoregressive Model," Working Papers 201216, University of Pretoria, Department of Economics.
    7. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2023. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Empirical Economics, Springer, vol. 65(1), pages 93-110, July.
    8. Annalisa Cadonna & Sylvia Fruhwirth-Schnatter & Peter Knaus, 2019. "Triple the gamma -- A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models," Papers 1912.03100, arXiv.org.
    9. Angelo Marsiglia Fasolo, 2018. "Monetary Policy Volatility Shocks in Brazil," Working Papers Series 480, Central Bank of Brazil, Research Department.
    10. Zhao, Yang & Zhang, Maojun & Pei, Ziting & Nan, Jiangxia, 2023. "The effects of quantitative easing on Bitcoin prices," Finance Research Letters, Elsevier, vol. 57(C).
    11. Zhang, Zhikai & Wang, Yudong & Xiao, Jihong & Zhang, Yaojie, 2023. "Not all geopolitical shocks are alike: Identifying price dynamics in the crude oil market under tensions," Resources Policy, Elsevier, vol. 80(C).
    12. Qazi Haque & Leandro M. Magnusson & Kazuki Tomioka, 2019. "Empirical evidence on the dynamics of investment under uncertainty in the U.S," Economics Discussion / Working Papers 19-18, The University of Western Australia, Department of Economics.
    13. Coşkun Akdeniz, 2021. "Construction of the Monetary Conditions Index with TVP-VAR Model: Empirical Evidence for Turkish Economy," Springer Books, in: Burcu Adıgüzel Mercangöz (ed.), Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, edition 1, pages 215-228, Springer.
    14. Yang, Xite & Zhang, Qin & Liu, Haiyue & Liu, Zihan & Tao, Qiufan & Lai, Yongzeng & Huang, Linya, 2024. "Economic policy uncertainty, macroeconomic shocks, and systemic risk: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    15. Corina SAMAN, 2016. "The Impact of the US and Euro Area Financial Systemic Stress to the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 170-183, December.
    16. Simon Beyeler, 2019. "Streamlining Time-varying VAR with a Factor Structure in the Parameters," Working Papers 19.03, Swiss National Bank, Study Center Gerzensee.
    17. Ouyang, Zisheng & Lu, Min & Lai, Yongzeng, 2023. "Forecasting stock index return and volatility based on GAVMD- Carbon-BiLSTM: How important is carbon emission trading?," Energy Economics, Elsevier, vol. 128(C).
    18. He, Zhifang, 2020. "Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 131-153.
    19. 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.
    20. Jun Gao & Sheng Zhu & Niall O’Sullivan & Meadhbh Sherman, 2019. "The Role of Economic Uncertainty in UK Stock Returns," JRFM, MDPI, vol. 12(1), pages 1-16, January.
    21. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    22. Weina Cai & Sen Wang, 2018. "The Time-Varying Effects of Monetary Policy on House Prices in China: An Application of TVP-VAR Model with Stochastic Volatility," International Journal of Business and Management, Canadian Center of Science and Education, vol. 13(4), pages 149-149, March.
    23. Long, Shaobo & Guo, Jiaqi, 2022. "Infectious disease equity market volatility, geopolitical risk, speculation, and commodity returns: Comparative analysis of five epidemic outbreaks," Research in International Business and Finance, Elsevier, vol. 62(C).
    24. Zouhaier Dhifaoui & Sami Ben Jabeur & Rabeh Khalfaoui & Muhammad Ali Nasir, 2023. "Time‐varying partial‐directed coherence approach to forecast global energy prices with stochastic volatility model," Post-Print hal-04296385, HAL.
    25. Pami Dua & Deepika Goel, 2021. "Inflation Persistence in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(3), pages 525-553, September.
    26. Abdhut Deheri, 2021. "The Effects of Monetary Policy on Output and Inflation in India: A Time-varying Approach," Economics Bulletin, AccessEcon, vol. 41(3), pages 1603-1614.
    27. Zhong, Meirui & Zhang, Rui & Ren, Xiaohang, 2023. "The time-varying effects of liquidity and market efficiency of the European Union carbon market: Evidence from the TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 123(C).
    28. Nakajima, Jouchi & Kasuya, Munehisa & Watanabe, Toshiaki, 2011. "Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 225-245, September.
    29. Tomoyuki Yagi & Yoshiyuki Kurachi & Masato Takahashi & Kotone Yamada & Hiroshi Kawata, 2022. "Pass-Through of Cost-Push Pressures to Consumer Prices," Bank of Japan Working Paper Series 22-E-17, Bank of Japan.
    30. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    31. Sushanta K Mallick & Madhusudan Mohanty & Fabrizio Zampolli, 2017. "Market volatility, monetary policy and the term premium," BIS Working Papers 606, Bank for International Settlements.
    32. Etsuro Shioji, 2014. "A Pass-Through Revival," Asian Economic Policy Review, Japan Center for Economic Research, vol. 9(1), pages 120-138, January.
    33. Zhang, Xu & Ding, Zhijing & Hang, Jianqin & He, Qizhi, 2022. "How do stock price indices absorb the COVID-19 pandemic shocks?," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
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    6. Coşkun Akdeniz, 2021. "Construction of the Monetary Conditions Index with TVP-VAR Model: Empirical Evidence for Turkish Economy," Springer Books, in: Burcu Adıgüzel Mercangöz (ed.), Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, edition 1, pages 215-228, Springer.
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    9. Cai, Yifei, 2016. "短期资本流动、经济政策不确定性与恐慌指数—基于时变分析框架下的研究 [Short-term Capital Flow, Economic Policy Uncertainty and VIX—Evidence from a Time-varying Analysis Framework]," MPRA Paper 73213, University Library of Munich, Germany.
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    27. Fumio Hayashi & Junko Koeda, 2013. "A Regime-Switching SVAR Analysis of Quantitative Easing," CARF F-Series CARF-F-322, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
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    29. Michaelis, Henrike & Watzka, Sebastian, 2014. "Are there Differences in the Effectiveness of Quantitative Easing in Japan over Time?," Discussion Papers in Economics 21087, University of Munich, Department of Economics.
    30. Martina Danielova Zaharieva & Mark Trede & Bernd Wilfling, 2017. "Bayesian semiparametric multivariate stochastic volatility with an application to international stock-market co-movements," CQE Working Papers 6217, Center for Quantitative Economics (CQE), University of Muenster.
    31. Toparlı, Elif Akay & Çatık, Abdurrahman Nazif & Balcılar, Mehmet, 2019. "The impact of oil prices on the stock returns in Turkey: A TVP-VAR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
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    38. Kassouri, Yacouba & Kacou, Kacou Yves Thierry & Alola, Andrew Adewale, 2021. "Are oil-clean energy and high technology stock prices in the same straits? Bubbles speculation and time-varying perspectives," Energy, Elsevier, vol. 232(C).
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    41. Huang, Qian & Wang, Xiangning & Zhang, Shuguang, 2021. "The effects of exchange rate fluctuations on the stock market and the affecting mechanisms: Evidence from BRICS countries," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    42. Hanisch, Max, 2017. "The effectiveness of conventional and unconventional monetary policy: Evidence from a structural dynamic factor model for Japan," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 110-134.
    43. Joseph P. Byrne & Marco Lorusso & Bing Xu, 2017. "Oil Prices and Informational Frictions: The Time-Varying Impact of Fundamentals and Expectations," CEERP Working Paper Series 006, Centre for Energy Economics Research and Policy, Heriot-Watt University.
    44. Zareifard, Hamid & Rue, Håvard & Khaledi, Majid Jafari & Lindgren, Finn, 2016. "A skew Gaussian decomposable graphical model," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 58-72.
    45. Mohsen Khezri & Seyed Ehsan Hosseinidoust & Mohammad Kazem Naziri, 2019. "Investigating the Temporary and Permanent Influential Variables on Iran Inflation Using TVP-DMA Models," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 23(1), pages 209-234, Winter.
    46. Yoshiyuki Nakazono & Satoshi Ikeda, 2016. "Stock Market Responses Under Quantitative Easing: State Dependence and Transparency in Monetary Policy," Pacific Economic Review, Wiley Blackwell, vol. 21(5), pages 560-580, December.
    47. Iiboshi, Hirokuni & Iwata, Yasuharu & Kajita, Yuto & Soma, Naoto, 2019. "Time-varying Fiscal Multipliers Identified by Systematic Component: A Bayesian Approach to TVP-SVAR model," MPRA Paper 92631, University Library of Munich, Germany.
    48. Aubrey Poon, 2018. "The transmission mechanism of Malaysian monetary policy: a time-varying vector autoregression approach," Empirical Economics, Springer, vol. 55(2), pages 417-444, September.
    49. Lin, Boqiang & Bai, Rui, 2021. "Oil prices and economic policy uncertainty: Evidence from global, oil importers, and exporters’ perspective," Research in International Business and Finance, Elsevier, vol. 56(C).
    50. Choi, Sangyup, 2017. "Variability in the effects of uncertainty shocks: New stylized facts from OECD countries," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 127-144.
    51. Lin, Jie & Xiao, Hao & Chai, Jian, 2023. "Dynamic effects and driving intermediations of oil price shocks on major economies," Energy Economics, Elsevier, vol. 124(C).
    52. Jouchi Nakajima, 2017. "Bayesian analysis of multivariate stochastic volatility with skew return distribution," Econometric Reviews, Taylor & Francis Journals, vol. 36(5), pages 546-562, May.
    53. Zhong, Yufei & Chen, Xuesheng & Wang, Chengfang & Wang, Zhixian & Zhang, Yuchen, 2023. "The hedging performance of green bond markets in China and the U.S.: Novel evidence from cryptocurrency uncertainty," Energy Economics, Elsevier, vol. 128(C).
    54. Bala Dahiru Abdullahi, 2016. "Time-Varying VAR with Stochastic Volatility and Monetary Policy Dynamics in Nigeria," Economics Bulletin, AccessEcon, vol. 36(4), pages 2237-2249.
    55. Fumio Hayashi & Junko Koeda, 2014. "Exiting from QE," NBER Working Papers 19938, National Bureau of Economic Research, Inc.
    56. Tatsuki Okamoto & Yoichi Matsubayashi, 2017. "Empirical Evidence from a Japanese Lending Survey within the TVP-VAR Framework: Does the Credit Channel Matter for Monetary Policy?," Discussion Papers 1709, Graduate School of Economics, Kobe University.
    57. Kavanagh, Ella & Zhu, Sheng & O’Sullivan, Niall, 2022. "Monetary policy, trade-offs and the transmission of UK Monetary Policy," Journal of Policy Modeling, Elsevier, vol. 44(6), pages 1128-1147.
    58. Li, Jiazheng & Wang, Tingwei & Su, Zhifang, 2024. "Optimal monetary policy under digital technology shock," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    59. IIBOSHI, Hirokuni & IWATA, Yasuharu, 2023. "The Nexus between Public Debt and the Government Spending Multiplier: Fiscal Adjustments Matter," MPRA Paper 116347, University Library of Munich, Germany.
    60. Saadaoui, Zied & BOUFATEH, Talel & JIAO, Zhilun, 2023. "On the transmission of oil supply and demand shocks to CO2 emissions in the US by considering uncertainty: A time-varying perspective," Resources Policy, Elsevier, vol. 85(PB).
    61. Zhou, Ying-Zhe & Huang, Jian-Bai & Chen, Jin-Yu, 2019. "Time-varying effect of the financialization of nonferrous metals markets on China's industrial sector," Resources Policy, Elsevier, vol. 64(C).
    62. He, Yongda & Lin, Boqiang, 2018. "Time-varying effects of cyclical fluctuations in China's energy industry on the macro economy and carbon emissions," Energy, Elsevier, vol. 155(C), pages 1102-1112.
    63. Zhao, Lili & Wen, Fenghua & Wang, Xiong, 2020. "Interaction among China carbon emission trading markets: Nonlinear Granger causality and time-varying effect," Energy Economics, Elsevier, vol. 91(C).
    64. Gong, Xu & Chen, Liqiang & Lin, Boqiang, 2020. "Analyzing dynamic impacts of different oil shocks on oil price," Energy, Elsevier, vol. 198(C).
    65. Morita, Hiroshi, 2015. "State-dependent effects of fiscal policy in Japan: Do rule-of-thumb households increase the effects of fiscal policy?," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 49-61.
    66. Liang, Ruibin & Cheng, Sheng & Cao, Yan & Li, Xinran, 2024. "Multi-scale impacts of oil shocks on travel and leisure stocks: A MODWT-Bayesian TVP model with shrinkage approach," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    67. Boufateh, Talel & Saadaoui, Zied, 2021. "The time-varying responses of financial intermediation and inflation to oil supply and demand shocks in the US: Evidence from Bayesian TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 102(C).
    68. Chen, Yunping & Chen, Huanhuan & Li, Guorong & Jiao, Dongdan & Xu, Xiangyun, 2021. "Time-varying effect of macro-prudential policies on household credit growth: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 241-254.
    69. Ko, Jun-Hyung & Morita, Hiroshi, 2015. "Fiscal sustainability and regime shifts in Japan," Economic Modelling, Elsevier, vol. 46(C), pages 364-375.
    70. Hu, Guoheng & Liu, Shan & Wu, Guo & Hu, Peng & Li, Ruiqi & Chen, Liujie, 2023. "Economic policy uncertainty, geopolitical risks, and the heterogeneity of commodity price fluctuations in China ——an empirical study based on TVP-SV-VAR model," Resources Policy, Elsevier, vol. 85(PA).
    71. Junko Koeda, 2018. "Macroeconomic Effects of Quantitative and Qualitative Monetary Easing Measures," IMES Discussion Paper Series 18-E-16, Institute for Monetary and Economic Studies, Bank of Japan.
    72. Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.
    73. Wei, Jiangqiao & Ma, Zhe & Wang, Anjian & Li, Pengyuan & Sun, Xiaoyan & Yuan, Xiaojing & Hao, Hongchang & Jia, Hongxiang, 2022. "Multiscale nonlinear Granger causality and time-varying effect analysis of the relationship between iron ore futures and spot prices," Resources Policy, Elsevier, vol. 77(C).
    74. Su, Chi-Wei & Qin, Meng & Tao, Ran & Moldovan, Nicoleta-Claudia & Lobonţ, Oana-Ramona, 2020. "Factors driving oil price —— from the perspective of United States," Energy, Elsevier, vol. 197(C).

  24. Jouchi Nakajima, 2011. "Monetary Policy Transmission under Zero Interest Rates: An Extended Time-Varying Parameter Vector Autoregression Approach," IMES Discussion Paper Series 11-E-08, Institute for Monetary and Economic Studies, Bank of Japan.

    Cited by:

    1. IWATA, Yasuharu & IIBOSHI, Hirokuni, 2023. "The Nexus between Public Debt and the Government Spending Multiplier: Fiscal Adjustments Matter," MPRA Paper 116355, University Library of Munich, Germany.
    2. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    3. Nakajima, Jouchi & Kasuya, Munehisa & Watanabe, Toshiaki, 2011. "Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 225-245, September.
    4. Henrike Michaelis & Sebastian Watzka, 2014. "Are there Differences in the Effectiveness of Quantitative Easing at the Zero-Lower-Bound in Japan over Time?," CESifo Working Paper Series 4901, CESifo.
    5. Wang, Kuan-Min & Lee, Yuan-Ming, 2022. "Is gold a safe haven for exchange rate risks? An empirical study of major currency countries," Journal of Multinational Financial Management, Elsevier, vol. 63(C).
    6. Yoshino, Naoyuki & Taghizadeh–Hesary, Farhad & Miyamoto, Hiroaki, 2017. "The Effectiveness of Japan’s Negative Interest Rate Policy," ADBI Working Papers 652, Asian Development Bank Institute.
    7. Morita, Hiroshi, 2020. "Empirical Analysis on the Effects of Japanese Fiscal Policy under the Effective Lower Bound," Discussion paper series HIAS-E-97, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    8. Davide Debortoli & Ricardo Nunes, 2014. "Monetary Regime Switches and Central Bank Preferences," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(8), pages 1591-1626, December.
    9. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano & Mertens, Elmar, 2023. "Shadow-rate VARs," Discussion Papers 14/2023, Deutsche Bundesbank.
    10. Michaelis, Henrike & Watzka, Sebastian, 2014. "Are there Differences in the Effectiveness of Quantitative Easing in Japan over Time?," Discussion Papers in Economics 21087, University of Munich, Department of Economics.
    11. Kuan-Min Wang & Yuan-Ming Lee, 2023. "Are life insurance futures a safe haven during COVID-19?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    12. Morita, Hiroshi, 2015. "Japanese Fiscal Policy under the Zero Lower Bound of Nominal Interest Rates: Time-Varying Parameters Vector Autoregression," Discussion Paper Series 627, Institute of Economic Research, Hitotsubashi University.
    13. Gong, Xu & Lin, Boqiang, 2018. "Time-varying effects of oil supply and demand shocks on China's macro-economy," Energy, Elsevier, vol. 149(C), pages 424-437.
    14. Philip Liu & Konstantinos Theodoridis & Haroon Mumtaz & Francesco Zanetti, 2019. "Changing Macroeconomic Dynamics at the Zero Lower Bound," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 391-404, July.
    15. Jun Gao & Sheng Zhu, 2019. "A New Structural Analysis of Inflation and Economic Activity," International Journal of Economic Sciences, International Institute of Social and Economic Sciences, vol. 8(1), pages 35-51, June.
    16. Michal Bencik, 2017. "Do Fiscal Multipliers Vary with Different Character of Monetary-Fiscal Interactions?," Working and Discussion Papers WP 11/2017, Research Department, National Bank of Slovakia.
    17. Jhonatan Portilla & Gabriel Rodríguez & Paul Castillo B., 2022. "Evolution of Monetary Policy in Peru: An Empirical Application Using a Mixture Innovation TVP-VAR-SV Model [Metas de Inflación en Una Economía Dolarizada: La Experencia Del Perú]," CESifo Economic Studies, CESifo Group, vol. 68(1), pages 98-126.
    18. Yoshiyuki Nakazono & Satoshi Ikeda, 2016. "Stock Market Responses Under Quantitative Easing: State Dependence and Transparency in Monetary Policy," Pacific Economic Review, Wiley Blackwell, vol. 21(5), pages 560-580, December.
    19. Mr. Ugo Fasano-Filho & Mr. Qing Wang & Pelin Berkmen, 2012. "Bank of Japan's Quantitative and Credit Easing: Are they Now More Effective," IMF Working Papers 2012/002, International Monetary Fund.
    20. Tatsuki Okamoto & Yoichi Matsubayashi, 2017. "Empirical Evidence from a Japanese Lending Survey within the TVP-VAR Framework: Does the Credit Channel Matter for Monetary Policy?," Discussion Papers 1709, Graduate School of Economics, Kobe University.
    21. Kavanagh, Ella & Zhu, Sheng & O’Sullivan, Niall, 2022. "Monetary policy, trade-offs and the transmission of UK Monetary Policy," Journal of Policy Modeling, Elsevier, vol. 44(6), pages 1128-1147.
    22. IIBOSHI, Hirokuni & IWATA, Yasuharu, 2023. "The Nexus between Public Debt and the Government Spending Multiplier: Fiscal Adjustments Matter," MPRA Paper 116347, University Library of Munich, Germany.
    23. Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
    24. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2021. "Forecasting with Shadow-Rate VARs," Working Papers 21-09, Federal Reserve Bank of Cleveland.
    25. Bäurle Gregor & Kaufmann Daniel & Kaufmann Sylvia & Strachan Rodney, 2020. "Constrained interest rates and changing dynamics at the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-26, April.
    26. Michal Franta, 2011. "Identification of Monetary Policy Shocks in Japan Using Sign Restrictions within the TVP-VAR Framework," IMES Discussion Paper Series 11-E-13, Institute for Monetary and Economic Studies, Bank of Japan.
    27. Iwata, Yasuharu & Iiboshi, Hirokuni, 2020. "Fiscal Adjustments and Debt-Dependent Multipliers: Evidence from the U.S. Time Series," Discussion paper series HIAS-E-103, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    28. Helmi, Mohamad Husam & Çatık, Abdurrahman Nazif & Akdeniz, Coşkun, 2023. "The impact of central bank digital currency news on the stock and cryptocurrency markets: Evidence from the TVP-VAR model," Research in International Business and Finance, Elsevier, vol. 65(C).
    29. Benjamin Garcia & Arsenios Skaperdas, 2017. "Inferring the Shadow Rate from Real Activity," Finance and Economics Discussion Series 2017-106, Board of Governors of the Federal Reserve System (U.S.).
    30. Gregor Bäurle & Daniel Kaufmann, 2018. "Measuring Exchange Rate, Price, and Output Dynamics at the Effective Lower Bound," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(6), pages 1243-1266, December.

  25. Jouchi Nakajima & Yasuhiro Omori, 2010. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-Tailed Error Using GH Skew Student's t-Distribution Models," CIRJE F-Series CIRJE-F-738, CIRJE, Faculty of Economics, University of Tokyo.

    Cited by:

  26. Jouchi Nakajima & Shigenori Shiratsuka & Yuki Teranishi, 2010. "The Effects of Monetary Policy Commitment: Evidence from Time- varying Parameter VAR Analysis," IMES Discussion Paper Series 10-E-06, Institute for Monetary and Economic Studies, Bank of Japan.

    Cited by:

    1. Kagraoka, Yusho & Moussa, Zakaria, 2013. "Quantitative easing, credibility and the time-varying dynamics of the term structure of interest rate in Japan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 181-201.
    2. Pami Dua & Deepika Goel, 2021. "Inflation Persistence in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(3), pages 525-553, September.
    3. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    4. Jouchi Nakajima, 2011. "Monetary Policy Transmission under Zero Interest Rates: An Extended Time-Varying Parameter Vector Autoregression Approach," IMES Discussion Paper Series 11-E-08, Institute for Monetary and Economic Studies, Bank of Japan.
    5. Mohanty, Deepak & John, Joice, 2015. "Determinants of inflation in India," Journal of Asian Economics, Elsevier, vol. 36(C), pages 86-96.
    6. Wang, Kuan-Min & Lee, Yuan-Ming, 2022. "Is gold a safe haven for exchange rate risks? An empirical study of major currency countries," Journal of Multinational Financial Management, Elsevier, vol. 63(C).
    7. Fumio Hayashi & Junko Koeda, 2013. "A Regime-Switching SVAR Analysis of Quantitative Easing," CARF F-Series CARF-F-322, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    8. Jouchi Nakajima & Mike West, 2013. "Bayesian Analysis of Latent Threshold Dynamic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 151-164, April.
    9. Moussa, Zakaria, 2010. "The Japanese Quantitative Easing Policy under Scrutiny: A Time-Varying Parameter Factor-Augmented VAR Model," MPRA Paper 29429, University Library of Munich, Germany.
    10. Joice John, 2015. "Has Inflation Persistence In India Changed Over Time?," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 60(04), pages 1-16.
    11. Kang, Sang Hoon & Islam, Faridul & Kumar Tiwari, Aviral, 2019. "The dynamic relationships among CO2 emissions, renewable and non-renewable energy sources, and economic growth in India: Evidence from time-varying Bayesian VAR model," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 90-101.
    12. Hibiki Ichiue & Yoichi Ueno, 2018. "A Survey-based Shadow Rate and Unconventional Monetary Policy Effects," IMES Discussion Paper Series 18-E-05, Institute for Monetary and Economic Studies, Bank of Japan.
    13. Fumio Hayashi & Junko Koeda, 2014. "Exiting from QE," NBER Working Papers 19938, National Bureau of Economic Research, Inc.
    14. Yoshiyuki Nakazono & Kozo Ueda, 2011. "Policy Commitment and Market Expectations: Lessons Learned from Survey Based Evidence under Japan's Quantitative Easing Policy," IMES Discussion Paper Series 11-E-12, Institute for Monetary and Economic Studies, Bank of Japan.
    15. Junko Koeda, 2018. "Macroeconomic Effects of Quantitative and Qualitative Monetary Easing Measures," IMES Discussion Paper Series 18-E-16, Institute for Monetary and Economic Studies, Bank of Japan.

  27. Jouchi Nakajima & Nao Sudo & Takayuki Tsuruga, 2010. "How well do the sticky price models explain the disaggregated price responses to aggregate technology and monetary policy shocks?," IMES Discussion Paper Series 10-E-22, Institute for Monetary and Economic Studies, Bank of Japan.

    Cited by:

    1. Jalali-Naini , Ahmad. R. & Hemati , Maryam, 2012. "The Effect of Monetary Shocks on Disaggregated Prices in a Data Rich Environment: a Bayesian FAVAR Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 6(4), pages 27-60, July.
    2. Carlos Viana de Carvalho & Niels Arne Dam & Jae Won Lee, 2014. "Real Rigidities and the Cross-Sectional Distribution of Price Stickiness: Evidence from Micro and Macro Data Combined," Textos para discussão 634, Department of Economics PUC-Rio (Brazil).
    3. Christiane Baumeister & Philip Liu & Haroon Mumtaz, 2012. "Changes in the Effects of Monetary Policy on Disaggregate Price Dynamics," Staff Working Papers 12-13, Bank of Canada.
    4. Carlos Carvalho & Niels Arne Dam & Jae Won Lee, 2020. "The Cross-Sectional Distribution of Price Stickiness Implied by Aggregate Data," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 162-179, March.

  28. Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori & Sylvia Fruwirth-Scnatter, 2009. "Generalized Extreme Value Distribution with Time-Dependence Using the AR and MA Models in State Space Form," IMES Discussion Paper Series 09-E-32, Institute for Monetary and Economic Studies, Bank of Japan.

    Cited by:

    1. Stéphane Auray & Aurélien Eyquem & Frédéric Jouneau-Sion, 2014. "Modelling Tails of Aggregated Economic Processes in a Stochastic Growth Model," Post-Print halshs-00995703, HAL.
    2. Tsuyoshi Kunihama & Yasuhiro Omori & Zhengjun Zhang, 2010. "Bayesian Estimation and Particle Filter for Max-Stable Processes," CIRJE F-Series CIRJE-F-757, CIRJE, Faculty of Economics, University of Tokyo.
    3. Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2015. "Bayesian Modeling of Dynamic Extreme Values: Extension of Generalized Extreme Value Distributions with Latent Stochastic Processes ," CIRJE F-Series CIRJE-F-952, CIRJE, Faculty of Economics, University of Tokyo.
    4. Wang, Yixin & So, Mike K.P., 2016. "A Bayesian hierarchical model for spatial extremes with multiple durations," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 39-56.
    5. Tsuyoshi Kunihama & Yasuhiro Omori & Zhengjun Zhang, 2012. "Efficient estimation and particle filter for max‐stable processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(1), pages 61-80, January.
    6. Douissi, Soukaina & Es-Sebaiy, Khalifa & Alshahrani, Fatimah & Viens, Frederi G., 2022. "AR(1) processes driven by second-chaos white noise: Berry–Esséen bounds for quadratic variation and parameter estimation," Stochastic Processes and their Applications, Elsevier, vol. 150(C), pages 886-918.
    7. Chen, Lei & Kou, Yingxin & Li, Zhanwu & Xu, An & Wu, Cheng, 2018. "Empirical research on complex networks modeling of combat SoS based on data from real war-game, Part I: Statistical characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 754-773.
    8. Chao Huang & Jin-Guan Lin, 2014. "Modified maximum spacings method for generalized extreme value distribution and applications in real data analysis," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(7), pages 867-894, October.

  29. Jouchi Nakajima & Yuki Teranishi, 2009. "The Evolution of Loan Rate Stickiness Across the Euro Area," IMES Discussion Paper Series 09-E-10, Institute for Monetary and Economic Studies, Bank of Japan.

    Cited by:

    1. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    2. Hinterschweiger, Marc & Khairnar, Kunal & Ozden, Tolga & Stratton, Tom, 2021. "Macroprudential policy interactions in a sectoral DSGE model with staggered interest rates," Bank of England working papers 904, Bank of England.
    3. Mr. Sohrab Rafiq, 2015. "How Important are Debt and Growth Expectations for Interest Rates?," IMF Working Papers 2015/094, International Monetary Fund.

  30. Jouchi Nakajima & Munehisa Kasuya & Toshiaki Watanabe, 2009. "Bayesian Analysis of Time-Varying Parameter Vector Autoregressive Model for the Japanese Economy and Monetary Policy," Global COE Hi-Stat Discussion Paper Series gd09-072, Institute of Economic Research, Hitotsubashi University.

    Cited by:

    1. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.
    2. Liu, Dayu & Xu, Ning & Zhao, Tingting & Song, Yang, 2018. "Identifying the nonlinear correlation between business cycle and monetary policy rule: Evidence from China and the U.S," Economic Modelling, Elsevier, vol. 73(C), pages 45-54.
    3. Ligia Alba Melo-Becerra & Jorge Enrique Ramos-Forero & Ligia Marcela Parrado-Galvis & Hector Manuel Zarate-Solano, 2016. "Bonanzas y crisis de la actividad petrolera y su efecto sobre la economía colombiana," Borradores de Economia 961, Banco de la Republica de Colombia.
    4. Rufei Zhang & Haizhen Zhang & Wang Gao & Ting Li & Shixiong Yang, 2022. "The Dynamic Effects of Oil Price Shocks on Exchange Rates—From a Time-Varying Perspective," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    5. Haque, Qazi & Magnusson, Leandro M., 2021. "Uncertainty shocks and inflation dynamics in the U.S," Economics Letters, Elsevier, vol. 202(C).
    6. Jin‐Yu Chen & Xue‐Hong Zhu & Mei‐Rui Zhong, 2021. "Time‐varying effects and structural change of oil price shocks on industrial output: Evidence from China's oil industrial chain," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3460-3472, July.
    7. Steffen Henzel & Wolfgang Nierhaus & Tim Oliver Berg & Christian Breuer & Kai Carstensen & Christian Grimme & Oliver Hülsewig & Atanas Hristov & Nikolay Hristov & Michael Kleemann & Wolfgang Meister &, 2013. "Ifo Economic Forecast 2013/2014: German Economy Picks Up Steam," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(24), pages 20-67, December.
    8. Olawale Awe O. & Adedayo Adepoju A., 2018. "Modified Recursive Bayesian Algorithm For Estimating Time-Varying Parameters In Dynamic Linear Models," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 258-293, June.
    9. Qazi Haque & Leandro M. Magnusson & Kazuki Tomioka, 2019. "Empirical evidence on the dynamics of investment under uncertainty in the U.S," Economics Discussion / Working Papers 19-18, The University of Western Australia, Department of Economics.
    10. Coşkun Akdeniz, 2021. "Construction of the Monetary Conditions Index with TVP-VAR Model: Empirical Evidence for Turkish Economy," Springer Books, in: Burcu Adıgüzel Mercangöz (ed.), Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, edition 1, pages 215-228, Springer.
    11. Arratibel, Olga & Michaelis, Henrike, 2013. "The Impact of Monetary Policy and Exchange Rate Shocks in Poland: Evidence from a Time-Varying VAR," Discussion Papers in Economics 21088, University of Munich, Department of Economics.
    12. Kim, Soohyeon & Kim, Jihyo & Heo, Eunnyeong, 2021. "Speculative incentives to hoard aluminum: Relationship between capital gains and inventories," Resources Policy, Elsevier, vol. 70(C).
    13. IWATA, Yasuharu & IIBOSHI, Hirokuni, 2023. "The Nexus between Public Debt and the Government Spending Multiplier: Fiscal Adjustments Matter," MPRA Paper 116355, University Library of Munich, Germany.
    14. Qin, Meng & Zhang, Xiaojing & Li, Yameng & Badarcea, Roxana Maria, 2023. "Blockchain market and green finance: The enablers of carbon neutrality in China," Energy Economics, Elsevier, vol. 118(C).
    15. Ganwen Zheng & Songping Zhu, 2021. "Research on the Effectiveness of China’s Macro Control Policy on Output and Technological Progress under Economic Policy Uncertainty," Sustainability, MDPI, vol. 13(12), pages 1-18, June.
    16. Cai, Yifei, 2016. "短期资本流动、经济政策不确定性与恐慌指数—基于时变分析框架下的研究 [Short-term Capital Flow, Economic Policy Uncertainty and VIX—Evidence from a Time-varying Analysis Framework]," MPRA Paper 73213, University Library of Munich, Germany.
    17. Long, Shaobo & Guo, Jiaqi, 2022. "Infectious disease equity market volatility, geopolitical risk, speculation, and commodity returns: Comparative analysis of five epidemic outbreaks," Research in International Business and Finance, Elsevier, vol. 62(C).
    18. Kagraoka, Yusho & Moussa, Zakaria, 2013. "Quantitative easing, credibility and the time-varying dynamics of the term structure of interest rate in Japan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 25(C), pages 181-201.
    19. Pami Dua & Deepika Goel, 2021. "Inflation Persistence in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(3), pages 525-553, September.
    20. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    21. Zhao, Lili & Liu, Wenhua & Zhou, Min & Wen, Fenghua, 2022. "Extreme event shocks and dynamic volatility interactions: The stock, commodity, and carbon markets in China," Finance Research Letters, Elsevier, vol. 47(PA).
    22. Martin Feldkircher & Kazuhiko Kakamu, 2018. "How does monetary policy affect income inequality in Japan? Evidence from grouped data," Papers 1803.08868, arXiv.org, revised Jul 2021.
    23. Henrike Michaelis & Sebastian Watzka, 2014. "Are there Differences in the Effectiveness of Quantitative Easing at the Zero-Lower-Bound in Japan over Time?," CESifo Working Paper Series 4901, CESifo.
    24. Joseph P Byrne & Ryuta Sakemoto & Bing Xu, 2020. "Commodity price co-movement: heterogeneity and the time-varying impact of fundamentals [Oil price shocks and the stock market: evidence from Japan]," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(2), pages 499-528.
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    2. Hai-Chuan Xu & Fredj Jawadi & Jie Zhou & Wei-Xing Zhou, 2023. "Quantifying interconnectedness and centrality ranking among financial institutions with TVP-VAR framework," Empirical Economics, Springer, vol. 65(1), pages 93-110, July.
    3. Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
    4. Joshua C.C. Chan & Angelia L. Grant, 2014. "Issues in Comparing Stochastic Volatility Models Using the Deviance Information Criterion," CAMA Working Papers 2014-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Makoto Nakakita & Teruo Nakatsuma, 2021. "Bayesian Analysis of Intraday Stochastic Volatility Models of High-Frequency Stock Returns with Skew Heavy-Tailed Errors," JRFM, MDPI, vol. 14(4), pages 1-29, March.
    6. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors," CARF F-Series CARF-F-198, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    7. Chan, Joshua C.C., 2013. "Moving average stochastic volatility models with application to inflation forecast," Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
    8. Saikat Saha, 2015. "Noise Robust Online Inference for Linear Dynamic Systems," Papers 1504.05723, arXiv.org.
    9. Gregor Kastner & Sylvia Fruhwirth-Schnatter, 2017. "Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models," Papers 1706.05280, arXiv.org.
    10. Cabral, Celso Rômulo Barbosa & da-Silva, Cibele Queiroz & Migon, Helio S., 2014. "A dynamic linear model with extended skew-normal for the initial distribution of the state parameter," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 64-80.
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    13. Makoto Takahashi & Yasuhiro Omori & Toshiaki Watanabe, 2012. "News Impact Curve for Stochastic Volatility Models," Global COE Hi-Stat Discussion Paper Series gd12-242, Institute of Economic Research, Hitotsubashi University.
    14. Shi Bo & Minheng Xiao, 2022. "Dynamic Risk Measurement by EVT based on Stochastic Volatility models via MCMC," Papers 2201.09434, arXiv.org, revised Jun 2023.
    15. Geraci, Marco Valerio & Gnabo, Jean-Yves, 2018. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1371-1390, June.
    16. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2021. "Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility," Discussion paper series HIAS-E-104, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    17. Igor Ferreira Batista Martins & Hedibert Freitas Lopes, 2023. "Stochastic volatility models with skewness selection," Papers 2312.00282, arXiv.org.
    18. Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
    19. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
    20. Trojan, Sebastian, 2013. "Regime Switching Stochastic Volatility with Skew, Fat Tails and Leverage using Returns and Realized Volatility Contemporaneously," Economics Working Paper Series 1341, University of St. Gallen, School of Economics and Political Science, revised Aug 2014.
    21. Nakajima Jouchi, 2013. "Stochastic volatility model with regime-switching skewness in heavy-tailed errors for exchange rate returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 499-520, December.
    22. Roland Langrock & Théo Michelot & Alexander Sohn & Thomas Kneib, 2015. "Semiparametric stochastic volatility modelling using penalized splines," Computational Statistics, Springer, vol. 30(2), pages 517-537, June.
    23. Martin Iseringhausen, 2018. "The Time-Varying Asymmetry Of Exchange Rate Returns: A Stochastic Volatility – Stochastic Skewness Model," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 18/944, Ghent University, Faculty of Economics and Business Administration.
    24. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira Da Veiga, María Helena, 2013. "One for all : nesting asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws131110, Universidad Carlos III de Madrid. Departamento de Estadística.
    25. C. A. Abanto-Valle & V. H. Lachos & Dipak K. Dey, 2015. "Bayesian Estimation of a Skew-Student-t Stochastic Volatility Model," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 721-738, September.
    26. Lee, Cheol Woo & Kang, Kyu Ho, 2023. "Estimating and testing skewness in a stochastic volatility model," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 445-467.
    27. Laura Garcia-Jorcano & Alfonso Novales, 2020. "A dominance approach for comparing the performance of VaR forecasting models," Computational Statistics, Springer, vol. 35(3), pages 1411-1448, September.
    28. Deschamps, Philippe J., 2012. "Bayesian estimation of generalized hyperbolic skewed student GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3035-3054.
    29. Sakae Oya & Teruo Nakatsuma, 2021. "Identification in Bayesian Estimation of the Skewness Matrix in a Multivariate Skew-Elliptical Distribution," Papers 2108.04019, arXiv.org.
    30. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira Da Veiga, María Helena, 2014. "Score driven asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws142618, Universidad Carlos III de Madrid. Departamento de Estadística.
    31. Mengheng Li & Marcel Scharth, 2022. "Leverage, Asymmetry, and Heavy Tails in the High-Dimensional Factor Stochastic Volatility Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 285-301, January.
    32. Felicia Ramona Birău, 2012. "Stochastic Volatility Models For Financial Time Series Analysis," Anale. Seria Stiinte Economice. Timisoara, Faculty of Economics, Tibiscus University in Timisoara, vol. 0, pages 472-475, November.
    33. Deschamps, P., 2015. "Alternative Formulation of the Leverage Effect in a Stochastic Volatility Model with Asymmetric Heavy-Tailed Errors," LIDAM Discussion Papers CORE 2015020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    34. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2017. "Creating Investment Scheme with State Space Modeling," CARF F-Series cf406, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    35. Darjus Hosszejni & Gregor Kastner, 2019. "Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol," Papers 1906.12123, arXiv.org, revised Feb 2021.
    36. Patricia Lengua Lafosse & Cristian Bayes & Gabriel Rodríguez, 2015. "A Stochastic Volatility Model with GH Skew Student’s t-Distribution: Application to Latin-American Stock Returns," Documentos de Trabajo / Working Papers 2015-405, Departamento de Economía - Pontificia Universidad Católica del Perú.
    37. Omar Abbara & Mauricio Zevallos, 2022. "Maximum Likelihood Inference for Asymmetric Stochastic Volatility Models," Econometrics, MDPI, vol. 11(1), pages 1-18, December.
    38. Lengua Lafosse, Patricia & Rodríguez, Gabriel, 2018. "An empirical application of a stochastic volatility model with GH skew Student's t-distribution to the volatility of Latin-American stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 155-173.

  32. Jouchi Nakajima & Yasuhiro Omori, 2007. "Leverage, heavy-tails and correlated jumps in stochastic volatility models," CIRJE F-Series CIRJE-F-514, CIRJE, Faculty of Economics, University of Tokyo.

    Cited by:

    1. Bauwens, Luc & Rombouts, Jeroen V.K., 2012. "On marginal likelihood computation in change-point models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3415-3429.
    2. Antonio A. F. Santos, 2021. "Bayesian Estimation for High-Frequency Volatility Models in a Time Deformed Framework," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 455-479, February.
    3. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2020. "Volatility forecasts using stochastic volatility models with nonlinear leverage effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 143-154, March.
    4. Shang, Yuhuang & Liu, Lulu, 2017. "An extension of stochastic volatility model with mixed frequency information," Economics Letters, Elsevier, vol. 155(C), pages 144-148.
    5. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2676-2692, November.
    6. Xi, Yanhui & Peng, Hui & Qin, Yemei & Xie, Wenbiao & Chen, Xiaohong, 2015. "Bayesian analysis of heavy-tailed market microstructure model and its application in stock markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 117(C), pages 141-153.
    7. Makoto Takahashi & Yasuhiro Omori & Toshiaki Watanabe, 2007. "Estimating Stochastic Volatility Models Using Daily Returns and Realized Volatility Simultaneously," CIRJE F-Series CIRJE-F-515, CIRJE, Faculty of Economics, University of Tokyo.
    8. Willy Alanya & Gabriel Rodríguez, 2019. "Asymmetries in Volatility: An Empirical Study for the Peruvian Stock and Forex Markets," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-18, March.
    9. Makoto Nakakita & Teruo Nakatsuma, 2021. "Bayesian Analysis of Intraday Stochastic Volatility Models of High-Frequency Stock Returns with Skew Heavy-Tailed Errors," JRFM, MDPI, vol. 14(4), pages 1-29, March.
    10. Angelos Alexopoulos & Petros Dellaportas & Omiros Papaspiliopoulos, 2019. "Bayesian prediction of jumps in large panels of time series data," Papers 1904.05312, arXiv.org, revised Apr 2021.
    11. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors," CARF F-Series CARF-F-198, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    12. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2016. "Volatility Forecasts Using Nonlinear Leverage Effects," Papers 1605.06482, arXiv.org, revised Dec 2017.
    13. Joshua C C Chan & Cody Y L Hsiao, 2013. "Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence," CAMA Working Papers 2013-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Shi Bo & Minheng Xiao, 2022. "Dynamic Risk Measurement by EVT based on Stochastic Volatility models via MCMC," Papers 2201.09434, arXiv.org, revised Jun 2023.
    15. Jouchi Nakajima & Yasuhiro Omori, 2010. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-Tailed Error Using GH Skew Student's t-Distribution Models," CIRJE F-Series CIRJE-F-738, CIRJE, Faculty of Economics, University of Tokyo.
    16. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    17. Audrone Virbickaite & Hedibert F. Lopes & Maria Concepción Ausín & Pedro Galeano, 2018. "Particle Learning for Bayesian Semi-Parametric Stochastic Volatility Model," DEA Working Papers 88, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    18. Maria Kalli & Jim Griffin, 2015. "Flexible Modeling of Dependence in Volatility Processes," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 102-113, January.
    19. Abdelhakim Aknouche, 2017. "Periodic autoregressive stochastic volatility," Statistical Inference for Stochastic Processes, Springer, vol. 20(2), pages 139-177, July.
    20. Nakajima, Jouchi & Omori, Yasuhiro, 2012. "Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student’s t-distribution," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3690-3704.
    21. Frédéric Karamé, 2018. "A new particle filtering approach to estimate stochastic volatility models with Markov-switching," Post-Print hal-02296093, HAL.
    22. Audrone Virbickaite & Hedibert F. Lopes, 2018. "Bayesian Semi-Parametric Markov Switching Stochastic Volatility Model," DEA Working Papers 89, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    23. Shinichiro Shirota & Takayuki Hizu & Yasuhiro Omori, 2013. "Realized Stochastic Volatility with Leverage and Long Memory," CIRJE F-Series CIRJE-F-880, CIRJE, Faculty of Economics, University of Tokyo.
    24. Trojan, Sebastian, 2013. "Regime Switching Stochastic Volatility with Skew, Fat Tails and Leverage using Returns and Realized Volatility Contemporaneously," Economics Working Paper Series 1341, University of St. Gallen, School of Economics and Political Science, revised Aug 2014.
    25. Shang, Yuhuang & Zheng, Tingguo, 2021. "Mixed-frequency SV model for stock volatility and macroeconomics," Economic Modelling, Elsevier, vol. 95(C), pages 462-472.
    26. Nakajima Jouchi, 2013. "Stochastic volatility model with regime-switching skewness in heavy-tailed errors for exchange rate returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 499-520, December.
    27. Xiao-Bin Liu & Yong Li, 2013. "Bayesian testing volatility persistence in stochastic volatility models with jumps," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1415-1426, December.
    28. Aknouche, Abdelhakim, 2013. "Periodic autoregressive stochastic volatility," MPRA Paper 69571, University Library of Munich, Germany, revised 2015.
    29. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira Da Veiga, María Helena, 2013. "One for all : nesting asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws131110, Universidad Carlos III de Madrid. Departamento de Estadística.
    30. Raanju R. Sundararajan & Wagner Barreto‐Souza, 2023. "Student‐t stochastic volatility model with composite likelihood EM‐algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 125-147, January.
    31. Yanhui Xi & Hui Peng & Yemei Qin, 2016. "Modeling Financial Time Series Based on a Market Microstructure Model with Leverage Effect," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-15, February.
    32. Zhou, Yang & Wang, Xiaoxiao & Dong, Rebecca Kechen & Pu, Ruihui & Yue, Xiao-Guang, 2022. "Natural resources commodity prices volatility: Evidence from COVID-19 for the US economy," Resources Policy, Elsevier, vol. 78(C).
    33. Delatola, E.-I. & Griffin, J.E., 2013. "A Bayesian semiparametric model for volatility with a leverage effect," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 97-110.
    34. Arthur T. Rego & Thiago R. dos Santos, 2018. "Non-Gaussian Stochastic Volatility Model with Jumps via Gibbs Sampler," Papers 1809.01501, arXiv.org, revised Oct 2018.
    35. Darjus Hosszejni & Gregor Kastner, 2019. "Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage," Papers 1901.11491, arXiv.org, revised Nov 2019.
    36. Deschamps, P., 2015. "Alternative Formulation of the Leverage Effect in a Stochastic Volatility Model with Asymmetric Heavy-Tailed Errors," LIDAM Discussion Papers CORE 2015020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    37. Tak Kuen Siu, 2023. "Bayesian nonlinear expectation for time series modelling and its application to Bitcoin," Empirical Economics, Springer, vol. 64(1), pages 505-537, January.
    38. T. R. Santos, 2018. "A Bayesian GED-Gamma stochastic volatility model for return data: a marginal likelihood approach," Papers 1809.01489, arXiv.org.
    39. Patricia Lengua Lafosse & Cristian Bayes & Gabriel Rodríguez, 2015. "A Stochastic Volatility Model with GH Skew Student’s t-Distribution: Application to Latin-American Stock Returns," Documentos de Trabajo / Working Papers 2015-405, Departamento de Economía - Pontificia Universidad Católica del Perú.
    40. Watanabe, Toshiaki & Nakajima, Jouchi, 2023. "High-frequency realized stochastic volatility model," Discussion paper series HIAS-E-127, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    41. Pan, Qunxing & Mei, Xiaowen & Gao, Tianqing, 2022. "Modeling dynamic conditional correlations with leverage effects and volatility spillover effects: Evidence from the Chinese and US stock markets affected by the recent trade friction," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    42. Noriyuki Kunimoto & Kazuhiko Kakamu, 2021. "Is Bitcoin really a currency? A viewpoint of a stochastic volatility model," Papers 2111.15351, arXiv.org.
    43. Lengua Lafosse, Patricia & Rodríguez, Gabriel, 2018. "An empirical application of a stochastic volatility model with GH skew Student's t-distribution to the volatility of Latin-American stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 155-173.

  33. Shin-ichi Fukuda & Munehisa Kasuya & Jouchi Nakajima, 2005. "Deteriorating Bank Health and Lending in Japan: Evidence from Unlisted Companies Undergoing Financial Distress," CIRJE F-Series CIRJE-F-364, CIRJE, Faculty of Economics, University of Tokyo.

    Cited by:

    1. Uchida, Hirofumi & Miyakawa, Daisuke & Hosono, Kaoru & Ono, Arito & Uchino, Taisuke & Uesugi, Iichiro, 2014. "Natural Disaster and Natural Selection," HIT-REFINED Working Paper Series 10, Institute of Economic Research, Hitotsubashi University.
    2. Akiyoshi, Fumio & Kobayashi, Keiichiro, 2010. "Banking crisis and productivity of borrowing firms: Evidence from Japan," Japan and the World Economy, Elsevier, vol. 22(3), pages 141-150, August.
    3. Andreas Stephan & Andriy Tsapin & Oleksandr Talavera, 2009. "Why Do Firms Switch Their Main Bank?: Theory and Evidence from Ukraine," Discussion Papers of DIW Berlin 894, DIW Berlin, German Institute for Economic Research.
    4. David Archer, 2006. "Implications of recent changes in banking for the conduct of monetary policy," BIS Papers chapters, in: Bank for International Settlements (ed.), The banking system in emerging economies: how much progress has been made?, volume 28, pages 123-51, Bank for International Settlements.
    5. Andreas Stephan & Oleksandr Talavera & Andriy Tsapin, 2011. "Main bank power, Switching Costs, and Firm Performance. Evidence from Ukraine," University of East Anglia Applied and Financial Economics Working Paper Series 026, School of Economics, University of East Anglia, Norwich, UK..
    6. Shin-ichi Fukuda & Munehisa Kasuya & Kentaro Akashi, 2007. "The Role of Trade Credit for Small Firms : An Implication from Japan’s Banking Crisis," Finance Working Papers 22596, East Asian Bureau of Economic Research.

  34. Shin-ichi Fukuda & Munehisa Kasuya & Jouchi Nakajima, 2005. "Bank Health and Investment: An Analysis of Unlisted Companies in Japan," Bank of Japan Working Paper Series 05-E-5, Bank of Japan.

    Cited by:

    1. Shin-ichi Fukuda & Munehisa Kasuya & Jouchi Nakajima, 2005. "Deteriorating Bank Health and Lending in Japan: Evidence from Unlisted Companies Undergoing Financial Distress," CIRJE F-Series CIRJE-F-364, CIRJE, Faculty of Economics, University of Tokyo.
    2. Emmanuel De Veirman & Andrew T. Levin, 2012. "When Did Firms Become More Different? Time-Varying Firm-Specific Volatility in Japan," CAMA Working Papers 2012-43, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Shin-ichi Fukuda & Munehisa Kasuya & Jouchi Nakajima, 2005. "Deteriorating Bank Health and Lending in Japan: Evidence from Unlisted Companies Undergoing Financial Distress (Subsequently published in "Journal of the Asia Pacific Economy" Vo.11, No.4, D," CARF F-Series CARF-F-042, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    4. Shin-ichi Fukuda & Munehisa Kasuya & Kentaro Akashi, 2008. "Impaired Bank Health and Default Risk ( Forthcoming in "Pacific-Basin Finance Journal". )," CARF F-Series CARF-F-122, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    5. Shin-Ichi Fukuda & Munehisa Kasuya & Jouchi Nakajima, 2006. "Deteriorating Bank Health and Lending in Japan: Evidence from Unlisted Companies under Financial Distress," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 11(4), pages 482-501.
    6. Tsapin Andriy & Tsapin Oleksandr, 2014. "Corporate Investment and Financial Crisis: Can Under- and Overinvestment Be Mitigated by Banks in an Emerging Market?," EERC Working Paper Series 14/04e, EERC Research Network, Russia and CIS.
    7. Akiyoshi, Fumio & Kobayashi, Keiichiro, 2010. "Banking crisis and productivity of borrowing firms: Evidence from Japan," Japan and the World Economy, Elsevier, vol. 22(3), pages 141-150, August.
    8. Shin-ichi Fukuda & Munehisa Kasuya & Kentaro Akashi, 2008. "Impaired Bank Health and Default Risk," CIRJE F-Series CIRJE-F-564, CIRJE, Faculty of Economics, University of Tokyo.
    9. Imai, Kentaro, 2016. "A panel study of zombie SMEs in Japan: Identification, borrowing and investment behavior," Journal of the Japanese and International Economies, Elsevier, vol. 39(C), pages 91-107.
    10. Kazuo Ogawa, 2006. "Comment: What Caused Fixed Investment To Stagnate During The 1990s In Japan? Evidence From Panel Data Of Listed Companies," The Japanese Economic Review, Japanese Economic Association, vol. 57(2), pages 307-309, June.

  35. Yasuhiro Omori & Siddhartha Chib & Neil Shephard & Jouchi Nakajima, 2004. "Stochastic volatility with leverage: fast likelihood inference," Economics Papers 2004-W19, Economics Group, Nuffield College, University of Oxford.

    Cited by:

    1. Yuriy Kitsul & Jonathan H. Wright, 2012. "The Economics of Options-Implied Inflation Probability Density Functions," Economics Working Paper Archive 600, The Johns Hopkins University,Department of Economics.
    2. Hans J. Skaug & Jun Yu, 2007. "Automated Likelihood Based Inference for Stochastic Volatility Models," Working Papers CoFie-01-2007, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
    3. Toshitaka Sekine, 2006. "Time-varying exchange rate pass-through: experiences of some industrial countries," BIS Working Papers 202, Bank for International Settlements.
    4. Fruhwirth-Schnatter, Sylvia & Fruhwirth, Rudolf, 2007. "Auxiliary mixture sampling with applications to logistic models," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3509-3528, April.
    5. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2014. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-932, CIRJE, Faculty of Economics, University of Tokyo.
    6. Fulvia Focker & Umberto Triacca, 2006. "A new proxy of the average volatility of a basket of returns: A Monte Carlo study," Economics Bulletin, AccessEcon, vol. 3(15), pages 1-14.

Articles

  1. Takuji Fueki & Jouchi Nakajima & Shinsuke Ohyama & Yoichiro Tamanyu, 2021. "Identifying oil price shocks and their consequences: The role of expectations in the crude oil market," International Finance, Wiley Blackwell, vol. 24(1), pages 53-76, April.
    See citations under working paper version above.
  2. Nakajima, Jouchi, 2020. "The role of household debt heterogeneity on consumption: Evidence from Japanese household data," Economic Analysis and Policy, Elsevier, vol. 65(C), pages 186-197.
    See citations under working paper version above.
  3. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
    See citations under working paper version above.
  4. Jouchi Nakajima, 2020. "Skew selection for factor stochastic volatility models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(4), pages 582-601, March.

    Cited by:

    1. Roman V. Ivanov, 2023. "On the Stochastic Volatility in the Generalized Black-Scholes-Merton Model," Risks, MDPI, vol. 11(6), pages 1-23, June.
    2. Igor Ferreira Batista Martins & Hedibert Freitas Lopes, 2023. "Stochastic volatility models with skewness selection," Papers 2312.00282, arXiv.org.

  5. Fukuda, Shin-ichi & Kasuya, Munehisa & Nakajima, Jouchi, 2018. "The role of corporate governance in Japanese unlisted companies," Japan and the World Economy, Elsevier, vol. 47(C), pages 27-39.
    See citations under working paper version above.
  6. Kei Imakubo & Haruki Kojima & Jouchi Nakajima, 2018. "The natural yield curve: its concept and measurement," Empirical Economics, Springer, vol. 55(2), pages 551-572, September.
    See citations under working paper version above.
  7. Kaihatsu, Sohei & Nakajima, Jouchi, 2018. "Has trend inflation shifted?: An empirical analysis with an equally-spaced regime-switching model," Economic Analysis and Policy, Elsevier, vol. 59(C), pages 69-83.

    Cited by:

    1. Behera, Harendra Kumar & Patra, Michael Debabrata, 2022. "Measuring trend inflation in India," Journal of Asian Economics, Elsevier, vol. 80(C).
    2. NAKAJIMA, Jouchi & SUDO, Nao & HOGEN, Yoshihiko & TAKIZUKA, Yasutaka, 2023. "On the estimation of the natural yield curve," Discussion Paper Series 753, Institute of Economic Research, Hitotsubashi University.
    3. NAKAJIMA, Jouchi, 2023. "Estimation of firms' inflation expectations using the survey DI," Discussion Paper Series 749, Institute of Economic Research, Hitotsubashi University.
    4. Kosuke Aoki & Ko Munakata & Nao Sudo, 2019. "Prolonged Low Interest Rates and Banking Stability," IMES Discussion Paper Series 19-E-21, Institute for Monetary and Economic Studies, Bank of Japan.
    5. Takatoshi Ito, 2021. "An Assessment of Abenomics: Evolution and Achievements," Asian Economic Policy Review, Japan Center for Economic Research, vol. 16(2), pages 190-219, July.
    6. Masahiko Shibamoto, 2023. "Inflation, Business Cycle, and Monetary Policy: The Role of Inflationary Pressure," Discussion Paper Series DP2023-04, Research Institute for Economics & Business Administration, Kobe University.
    7. Ryuzo Miyao & Tatsuyoshi Okimoto, 2020. "Regime shifts in the effects of Japan’s unconventional monetary policies," Manchester School, University of Manchester, vol. 88(6), pages 749-772, December.
    8. Yui Kishaba & Tatsushi Okuda, 2023. "The Slope of the Phillips Curve for Service Prices in Japan: Regional Panel Data Approach," Bank of Japan Working Paper Series 23-E-8, Bank of Japan.

  8. Jouchi Nakajima & Tsuyoshi Kunihama & Yasuhiro Omori, 2017. "Bayesian modeling of dynamic extreme values: extension of generalized extreme value distributions with latent stochastic processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(7), pages 1248-1268, May.
    See citations under working paper version above.
  9. Jouchi Nakajima, 2017. "Bayesian analysis of multivariate stochastic volatility with skew return distribution," Econometric Reviews, Taylor & Francis Journals, vol. 36(5), pages 546-562, May.

    Cited by:

    1. Guanyu Hu & Ming-Hui Chen & Nalini Ravishanker, 2023. "Bayesian analysis of spherically parameterized dynamic multivariate stochastic volatility models," Computational Statistics, Springer, vol. 38(2), pages 845-869, June.
    2. Kurose, Yuta & Omori, Yasuhiro, 2020. "Multiple-block dynamic equicorrelations with realized measures, leverage and endogeneity," Econometrics and Statistics, Elsevier, vol. 13(C), pages 46-68.
    3. Anders Nõu & Darya Lapitskaya & Mustafa Hakan Eratalay & Rajesh Sharma, 2021. "Predicting Stock Return And Volatility With Machine Learning And Econometric Models: A Comparative Case Study Of The Baltic Stock Market," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 135, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    4. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    5. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    6. Szczygielski, Jan Jakub & Charteris, Ailie & Obojska, Lidia, 2023. "Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence," International Review of Financial Analysis, Elsevier, vol. 87(C).
    7. Sakae Oya & Teruo Nakatsuma, 2021. "Identification in Bayesian Estimation of the Skewness Matrix in a Multivariate Skew-Elliptical Distribution," Papers 2108.04019, arXiv.org.
    8. Watanabe, Toshiaki & Nakajima, Jouchi, 2023. "High-frequency realized stochastic volatility model," Discussion paper series HIAS-E-127, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.

  10. Nakajima, Jouchi & Watanabe, Toshiaki, 2017. "Econometric Analysis of Japanese Exports Using a Time-Varying Parameter Vector Autoregressive Model," Economic Review, Hitotsubashi University, vol. 68(3), pages 237-249, July.

    Cited by:

    1. Yosuke Okazaki & Nao Sudo, 2018. "Natural Rate of Interest in Japan -- Measuring its size and identifying drivers based on a DSGE model --," Bank of Japan Working Paper Series 18-E-6, Bank of Japan.

  11. Kimura Takeshi & Nakajima Jouchi, 2016. "Identifying conventional and unconventional monetary policy shocks: a latent threshold approach," The B.E. Journal of Macroeconomics, De Gruyter, vol. 16(1), pages 277-300, January.
    See citations under working paper version above.
  12. Koichiro Kamada & Jouchi Nakajima, 2014. "On the reliability of Japanese inflation expectations using purchasing power parity," Economic Analysis and Policy, Elsevier, vol. 44(3), pages 259-265.
    See citations under working paper version above.
  13. Zhou, Xiaocong & Nakajima, Jouchi & West, Mike, 2014. "Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 963-980.

    Cited by:

    1. Gruber, Lutz F. & West, Mike, 2017. "Bayesian online variable selection and scalable multivariate volatility forecasting in simultaneous graphical dynamic linear models," Econometrics and Statistics, Elsevier, vol. 3(C), pages 3-22.
    2. Florian Huber & Gregor Kastner & Martin Feldkircher, 2016. "Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models," Papers 1607.04532, arXiv.org, revised Jul 2018.
    3. Hui ‘Fox’ Ling & Christian Franzen, 2017. "Online learning of time-varying stochastic factor structure by variational sequential Bayesian factor analysis," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1277-1304, August.
    4. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    5. Nalan Basturk & Agnieszka Borowska & Stefano Grassi & Lennart Hoogerheide & Herman K. van Dijk, 2018. "Forecast Density Combinations of Dynamic Models and Data Driven Portfolio Strategies," Working Paper 2018/10, Norges Bank.
    6. Gregor Kastner, 2016. "Sparse Bayesian time-varying covariance estimation in many dimensions," Papers 1608.08468, arXiv.org, revised Nov 2017.
    7. Niyati Bhanja & Samia Nasreen & Arif Billah Dar & Aviral Kumar Tiwari, 2022. "Connectedness in International Crude Oil Markets," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 227-262, January.
    8. Gunawan, David & Kohn, Robert & Nott, David, 2021. "Variational Bayes approximation of factor stochastic volatility models," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1355-1375.
    9. Leif Anders Thorsrud, 2016. "Nowcasting using news topics. Big Data versus big bank," Working Paper 2016/20, Norges Bank.
    10. Masafumi Nakano & Akihiko Takahashi & Soichiro Takahashi, 2016. "A Return Prediction-based Investment with Particle Filtering and Anomaly Detection," CARF F-Series CARF-F-391, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    11. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in international dairy commodity markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(3), pages 704-728, July.
    12. Chaim, Pedro & Laurini, Márcio P., 2019. "Nonlinear dependence in cryptocurrency markets," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 32-47.
    13. Yuta Kurose & Yasuhiro Omori, 2016. "Multiple-block Dynamic Equicorrelations with Realized Measures, Leverage and Endogeneity," CIRJE F-Series CIRJE-F-1024, CIRJE, Faculty of Economics, University of Tokyo.
    14. Vegard H�ghaug Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Papers No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    15. Adriano S. Koshiyama & Nikan Firoozye & Philip Treleaven, 2019. "A derivatives trading recommendation system: The mid‐curve calendar spread case," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 26(2), pages 83-103, April.
    16. Leung, Dennis & Drton, Mathias, 2016. "Order-invariant prior specification in Bayesian factor analysis," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 60-66.
    17. Mike West, 2020. "Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 1-31, February.
    18. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    19. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    20. Leif Anders Thorsrud, 2016. "Words are the new numbers: A newsy coincident index of business cycles," Working Papers No 4/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    21. Zhenlong Jiang & Ran Ji & Kuo-Chu Chang, 2020. "A Machine Learning Integrated Portfolio Rebalance Framework with Risk-Aversion Adjustment," JRFM, MDPI, vol. 13(7), pages 1-20, July.
    22. Wilms, Ines & Croux, Christophe, 2016. "Forecasting using sparse cointegration," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1256-1267.
    23. McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
    24. Gregor Kastner & Sylvia Fruhwirth-Schnatter & Hedibert Freitas Lopes, 2016. "Efficient Bayesian Inference for Multivariate Factor Stochastic Volatility Models," Papers 1602.08154, arXiv.org, revised Jul 2017.
    25. Gillen, Benjamin J., 2014. "An empirical Bayesian approach to stein-optimal covariance matrix estimation," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 402-420.
    26. Darjus Hosszejni & Gregor Kastner, 2019. "Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol," Papers 1906.12123, arXiv.org, revised Feb 2021.
    27. Adriano Soares Koshiyama & Nick Firoozye & Philip Treleaven, 2018. "A Machine Learning-based Recommendation System for Swaptions Strategies," Papers 1810.02125, arXiv.org.

  14. Nakajima Jouchi, 2013. "Stochastic volatility model with regime-switching skewness in heavy-tailed errors for exchange rate returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 499-520, December.

    Cited by:

    1. Chen, Rongda & Zhou, Hanxian & Yu, Lean & Jin, Chenglu & Zhang, Shuonan, 2021. "An efficient method for pricing foreign currency options," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    2. Lhuissier Stéphane, 2022. "Financial Conditions and Macroeconomic Downside Risks in the Euro Area," Working papers 863, Banque de France.
    3. Stéphane Lhuissier, 2019. "Bayesian Inference for Markov-switching Skewed Autoregressive Models," Working papers 726, Banque de France.
    4. Iseringhausen, Martin, 2024. "A time-varying skewness model for Growth-at-Risk," International Journal of Forecasting, Elsevier, vol. 40(1), pages 229-246.
    5. Hainaut, Donatien & Moraux, Franck, 2019. "A switching self-exciting jump diffusion process for stock prices," LIDAM Reprints ISBA 2019017, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Jeffrey Chu & Saralees Nadarajah & Stephen Chan, 2015. "Statistical Analysis of the Exchange Rate of Bitcoin," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-27, July.
    7. Zhen Fang & Zhang Jin E., 2020. "Dissecting skewness under affine jump-diffusions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-19, September.
    8. Martin Iseringhausen, 2018. "The Time-Varying Asymmetry Of Exchange Rate Returns: A Stochastic Volatility – Stochastic Skewness Model," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 18/944, Ghent University, Faculty of Economics and Business Administration.
    9. Saldaña-Zepeda, Dayna P. & Velasco-Cruz, Ciro & Torres-Preciado, Víctor H., 2020. "Mexican peso-USD exchange rate: A switching linear dynamical model application," International Economics, Elsevier, vol. 162(C), pages 80-91.
    10. Carlos A. Abanto-Valle & Hernán B. Garrafa-Aragón, 2019. "Threshold Stochastic Volatility Models with Heavy Tails:A Bayesian Approach," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 42(83), pages 32-53.

  15. Jouchi Nakajima & Mike West, 2013. "Bayesian Analysis of Latent Threshold Dynamic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 151-164, April.

    Cited by:

    1. Liu, Dayu & Xu, Ning & Zhao, Tingting & Song, Yang, 2018. "Identifying the nonlinear correlation between business cycle and monetary policy rule: Evidence from China and the U.S," Economic Modelling, Elsevier, vol. 73(C), pages 45-54.
    2. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2020. "Volatility forecasts using stochastic volatility models with nonlinear leverage effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 143-154, March.
    3. Gruber, Lutz F. & West, Mike, 2017. "Bayesian online variable selection and scalable multivariate volatility forecasting in simultaneous graphical dynamic linear models," Econometrics and Statistics, Elsevier, vol. 3(C), pages 3-22.
    4. Kim, Hea-Jung & Choi, Taeryon & Jo, Seongil, 2016. "Bayesian factor analysis with uncertain functional constraints about factor loadings," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 110-128.
    5. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    6. Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2020. "Deep Dynamic Factor Models," Papers 2007.11887, arXiv.org, revised May 2023.
    7. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    8. Che, Ming & Zhu, Zixiang & Li, Yujia, 2023. "Geopolitical risk and economic policy uncertainty: Different roles in China's financial cycle," International Review of Financial Analysis, Elsevier, vol. 90(C).
    9. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2014. "Stochastic Model Specification Search for Time-Varying Parameter VARs," CAMA Working Papers 2014-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Dimitris Korobilis & Kenichi Shimizu, 2021. "Bayesian Approaches to Shrinkage and Sparse Estimation," Working Papers 2021_19, Business School - Economics, University of Glasgow.
    11. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    12. Henrike Michaelis & Sebastian Watzka, 2014. "Are there Differences in the Effectiveness of Quantitative Easing at the Zero-Lower-Bound in Japan over Time?," CESifo Working Paper Series 4901, CESifo.
    13. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    14. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    15. Shinichiro Shirota & Yasuhiro Omori & Hedibert. F. Lopes & Haixiang Piao, 2016. "Cholesky Realized Stochastic Volatility Model," CIRJE F-Series CIRJE-F-1019, CIRJE, Faculty of Economics, University of Tokyo.
    16. Bitto, Angela & Frühwirth-Schnatter, Sylvia, 2019. "Achieving shrinkage in a time-varying parameter model framework," Journal of Econometrics, Elsevier, vol. 210(1), pages 75-97.
    17. Sui, Yuelei & Holan, Scott H. & Yang, Wen-Hsi, 2023. "Bayesian circular lattice filters for computationally efficient estimation of multivariate time-varying autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 181(C).
    18. Vegard H. Larsen & Leif Anders Thorsrud, 2015. "The Value of News," Working Papers No 6/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    19. Leif Anders Thorsrud, 2016. "Nowcasting using news topics. Big Data versus big bank," Working Paper 2016/20, Norges Bank.
    20. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    21. Trojan, Sebastian, 2014. "Multivariate Stochastic Volatility with Dynamic Cross Leverage," Economics Working Paper Series 1424, University of St. Gallen, School of Economics and Political Science.
    22. Daniele Bianchi & Kenichiro McAlinn, 2018. "Large-Scale Dynamic Predictive Regressions," Papers 1803.06738, arXiv.org.
    23. Takahiro Yabe & Yunchang Zhang & Satish Ukkusuri, 2020. "Quantifying the Economic Impact of Extreme Shocks on Businesses using Human Mobility Data: a Bayesian Causal Inference Approach," Papers 2004.11121, arXiv.org.
    24. Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019. "News-driven inflation expectations and information rigidities," Working Paper 2019/5, Norges Bank.
    25. Hacioglu, Sinem & Tuzcuoglu, Kerem, 2016. "Interpreting the latent dynamic factors by threshold FAVAR model," Bank of England working papers 622, Bank of England.
    26. Gustavo Romero Cardoso & Marcio Issao Nakane, 2024. "What’s in a headline? News impact on the Brazilian economy," Working Papers, Department of Economics 2024_12, University of São Paulo (FEA-USP).
    27. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    28. Joshua C.C. Chan, 2015. "Specification tests for time-varying parameter models with stochastic volatility," CAMA Working Papers 2015-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    29. Michaelis, Henrike & Watzka, Sebastian, 2014. "Are there Differences in the Effectiveness of Quantitative Easing in Japan over Time?," Discussion Papers in Economics 21087, University of Munich, Department of Economics.
    30. Zijian Zeng & Meng Li, 2020. "Bayesian Median Autoregression for Robust Time Series Forecasting," Papers 2001.01116, arXiv.org, revised Dec 2020.
    31. Joshua C. C. Chan & Eric Eisenstat, 2018. "Bayesian model comparison for time‐varying parameter VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 509-532, June.
    32. Martin Feldkircher & Florian Huber & Isabella Moder, 2016. "Modeling the evolution of monetary policy rules in CESEE," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 1, pages 8-27.
    33. Larsen, Vegard H. & Thorsrud, Leif A., 2019. "The value of news for economic developments," Journal of Econometrics, Elsevier, vol. 210(1), pages 203-218.
    34. Vegard H�ghaug Larsen & Leif Anders Thorsrud, 2018. "Business cycle narratives," Working Papers No 6/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    35. Kenichiro McAlinn, 2021. "Mixed‐frequency Bayesian predictive synthesis for economic nowcasting," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1143-1163, November.
    36. Siem Jan Koopman & Geert Mesters, 2014. "Empirical Bayes Methods for Dynamic Factor Models," Tinbergen Institute Discussion Papers 14-061/III, Tinbergen Institute.
    37. Sergei Seleznev, 2019. "Truncated priors for tempered hierarchical Dirichlet process vector autoregression," Bank of Russia Working Paper Series wps47, Bank of Russia.
    38. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Paper 2019/2, Norges Bank.
    39. Florian Huber & Gary Koop & Michael Pfarrhofer, 2020. "Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations," Papers 2002.10274, arXiv.org.
    40. Leung, Dennis & Drton, Mathias, 2016. "Order-invariant prior specification in Bayesian factor analysis," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 60-66.
    41. Mike West, 2020. "Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 1-31, February.
    42. Leif Anders Thorsrud, 2016. "Words are the new numbers: A newsy coincident index of business cycles," Working Papers No 4/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    43. Tatsuki Okamoto & Yoichi Matsubayashi, 2017. "Empirical Evidence from a Japanese Lending Survey within the TVP-VAR Framework: Does the Credit Channel Matter for Monetary Policy?," Discussion Papers 1709, Graduate School of Economics, Kobe University.
    44. James Sampi, 2016. "High Dimensional Factor Models: An Empirical Bayes Approach," Working Papers 75, Peruvian Economic Association.
    45. Schepp, Zoltán & Abaligeti, Gallusz & Németh, Kristóf, 2018. "Időben változó Taylor-szabály a hazai monetáris politika jellemzésére [A time-varying parameter Taylor rule for Hungarian monetary policy]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(1), pages 24-43.
    46. McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
    47. Hauber, Philipp, 2022. "Real-time nowcasting with sparse factor models," EconStor Preprints 251551, ZBW - Leibniz Information Centre for Economics.
    48. Kimura Takeshi & Nakajima Jouchi, 2016. "Identifying conventional and unconventional monetary policy shocks: a latent threshold approach," The B.E. Journal of Macroeconomics, De Gruyter, vol. 16(1), pages 277-300, January.
    49. Rodríguez, Gabriel & Vassallo, Renato & Castillo B., Paul, 2023. "Effects of external shocks on macroeconomic fluctuations in Pacific Alliance countries," Economic Modelling, Elsevier, vol. 124(C).
    50. Bruno P. C. Levy & Hedibert F. Lopes, 2021. "Dynamic Ordering Learning in Multivariate Forecasting," Papers 2101.04164, arXiv.org, revised Nov 2021.
    51. Zeng, Zijian & Li, Meng, 2021. "Bayesian median autoregression for robust time series forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1000-1010.
    52. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    53. Bakerman, Jordan & Pazdernik, Karl & Korkmaz, Gizem & Wilson, Alyson G., 2022. "Dynamic logistic regression and variable selection: Forecasting and contextualizing civil unrest," International Journal of Forecasting, Elsevier, vol. 38(2), pages 648-661.
    54. Jouchi Nakajima, 2020. "Discussion of “Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions”," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 33-36, February.
    55. Junli Cheng & Feng Lin, 2022. "The Dynamic Effects of Urban–Rural Income Inequality on Sustainable Economic Growth under Urbanization and Monetary Policy in China," Sustainability, MDPI, vol. 14(11), pages 1-23, June.
    56. Eraslan, Sercan & Schröder, Maximilian, 2023. "Nowcasting GDP with a pool of factor models and a fast estimation algorithm," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1460-1476.
    57. Felix Abramovich & Vadim Grinshtein, 2013. "Estimation of a sparse group of sparse vectors," Biometrika, Biometrika Trust, vol. 100(2), pages 355-370.
    58. Gabriel Rodríguez & Renato Vassallo, 2022. "Time Evolution of External Shocks on Macroeconomic Fluctuations in Pacific Alliance Countries: Empirical Application using TVP-VAR-SV Models," Documentos de Trabajo / Working Papers 2022-508, Departamento de Economía - Pontificia Universidad Católica del Perú.
    59. Lopes, Hedibert F. & McCulloch, Robert E. & Tsay, Ruey S., 2022. "Parsimony inducing priors for large scale state–space models," Journal of Econometrics, Elsevier, vol. 230(1), pages 39-61.
    60. Fu, Bowen, 2020. "Is the slope of the Phillips curve time-varying? Evidence from unobserved components models," Economic Modelling, Elsevier, vol. 88(C), pages 320-340.
    61. Joshua C.C. Chan & Eric Eisenstat, 2018. "Comparing hybrid time-varying parameter VARs," CAMA Working Papers 2018-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    62. Zhou, Xiaocong & Nakajima, Jouchi & West, Mike, 2014. "Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models," International Journal of Forecasting, Elsevier, vol. 30(4), pages 963-980.
    63. Valentina Aprigliano, 2020. "A large Bayesian VAR with a block‐specific shrinkage: A forecasting application for Italian industrial production," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1291-1304, December.
    64. Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.

  16. Nakajima, Jouchi & Kunihama, Tsuyoshi & Omori, Yasuhiro & Frühwirth-Schnatter, Sylvia, 2012. "Generalized extreme value distribution with time-dependence using the AR and MA models in state space form," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3241-3259.
    See citations under working paper version above.
  17. Nakajima, Jouchi & Omori, Yasuhiro, 2012. "Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student’s t-distribution," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3690-3704.
    See citations under working paper version above.
  18. Jouchi Nakajima, 2012. "Bayesian Analysis Of Generalized Autoregressive Conditional Heteroskedasticity And Stochastic Volatility: Modeling Leverage, Jumps And Heavy‐Tails For Financial Time Series," The Japanese Economic Review, Japanese Economic Association, vol. 63(1), pages 81-103, March.

    Cited by:

    1. Jesús Fernández-Villaverde & Pablo A. Guerrón-Quintana, 2020. "Uncertainty Shocks and Business Cycle Research," NBER Working Papers 26768, National Bureau of Economic Research, Inc.
    2. Willy Alanya & Gabriel Rodríguez, 2019. "Asymmetries in Volatility: An Empirical Study for the Peruvian Stock and Forex Markets," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(01), pages 1-18, March.
    3. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2024. "A Bayesian approach for the determinants of bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 91(C).
    4. Makoto Nakakita & Teruo Nakatsuma, 2021. "Bayesian Analysis of Intraday Stochastic Volatility Models of High-Frequency Stock Returns with Skew Heavy-Tailed Errors," JRFM, MDPI, vol. 14(4), pages 1-29, March.
    5. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
    6. Darjus Hosszejni & Gregor Kastner, 2019. "Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol," Papers 1906.12123, arXiv.org, revised Feb 2021.
    7. Patricia Lengua Lafosse & Cristian Bayes & Gabriel Rodríguez, 2015. "A Stochastic Volatility Model with GH Skew Student’s t-Distribution: Application to Latin-American Stock Returns," Documentos de Trabajo / Working Papers 2015-405, Departamento de Economía - Pontificia Universidad Católica del Perú.
    8. Noriyuki Kunimoto & Kazuhiko Kakamu, 2021. "Is Bitcoin really a currency? A viewpoint of a stochastic volatility model," Papers 2111.15351, arXiv.org.
    9. Lengua Lafosse, Patricia & Rodríguez, Gabriel, 2018. "An empirical application of a stochastic volatility model with GH skew Student's t-distribution to the volatility of Latin-American stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 155-173.

  19. Nakajima, Jouchi & Watanabe, Toshiaki, 2012. "Time-Varying Vector Autoregressive Modei-A Survey with the Application to the Japanese Macroeconomic Data-," Economic Review, Hitotsubashi University, vol. 63(3), pages 193-208, July.
    See citations under working paper version above.
  20. Jouchi Nakajima & Mike West, 2012. "Dynamic Factor Volatility Modeling: A Bayesian Latent Threshold Approach," Journal of Financial Econometrics, Oxford University Press, vol. 11(1), pages 116-153, December.

    Cited by:

    1. Jouchi Nakajima & Mike West, 2013. "Bayesian Analysis of Latent Threshold Dynamic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 151-164, April.
    2. Víctor Peña & Kaoru Irie, 2022. "On the Relationship between Uhlig Extended and beta‐Bartlett Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 147-153, January.

  21. Nakajima, Jouchi & Kasuya, Munehisa & Watanabe, Toshiaki, 2011. "Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 225-245, September.
    See citations under working paper version above.
  22. Nakajima Jouchi, 2011. "Monetary Policy Transmission under Zero Interest Rates: An Extended Time-Varying Parameter Vector Autoregression Approach," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-24, October.
    See citations under working paper version above.
  23. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    See citations under working paper version above.
  24. Nakajima, Jouchi & Omori, Yasuhiro, 2009. "Leverage, heavy-tails and correlated jumps in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2335-2353, April.
    See citations under working paper version above.
  25. Omori, Yasuhiro & Chib, Siddhartha & Shephard, Neil & Nakajima, Jouchi, 2007. "Stochastic volatility with leverage: Fast and efficient likelihood inference," Journal of Econometrics, Elsevier, vol. 140(2), pages 425-449, October.

    Cited by:

    1. Leopoldo Catania & Nima Nonejad, 2016. "Density Forecasts and the Leverage Effect: Some Evidence from Observation and Parameter-Driven Volatility Models," Papers 1605.00230, arXiv.org, revised Nov 2016.
    2. Antonio A. F. Santos, 2021. "Bayesian Estimation for High-Frequency Volatility Models in a Time Deformed Framework," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 455-479, February.
    3. Martin Iseringhausen & Hauke Vierke, 2018. "What Drives Output Volatility? The Role of Demographics and Government Size Revisited," European Economy - Discussion Papers 075, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    4. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    5. Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
    6. Khorunzhina, Natalia & Richard, Jean-Francois, 2016. "Finite Gaussian Mixture Approximations to Analytically Intractable Density Kernels," MPRA Paper 72326, University Library of Munich, Germany.
    7. Kenichiro McAlinn & Asahi Ushio & Teruo Nakatsuma, 2020. "Volatility forecasts using stochastic volatility models with nonlinear leverage effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 143-154, March.
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    Cited by:

    1. Shin-ichi Fukuda & Munehisa Kasuya & Kentaro Akashi, 2007. "The Role of Trade Credit for Small Firms: An Implication from Japan's Banking Crisis," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 3(1), pages 27-50, December.
    2. Shin-ichi Fukuda & Munehisa Kasuya & Jouchi Nakajima, 2018. "The Role of Corporate Governance in Japanese Unlisted Companies," CIRJE F-Series CIRJE-F-1081, CIRJE, Faculty of Economics, University of Tokyo.
    3. HOSONO Kaoru, 2009. "Financial Crisis, Firm Dynamics and Aggregate Productivity in Japan," Discussion papers 09012, Research Institute of Economy, Trade and Industry (RIETI).
    4. Uchida, Hirofumi & Miyakawa, Daisuke & Hosono, Kaoru & Ono, Arito & Uchino, Taisuke & Uesugi, Iichiro, 2014. "Natural Disaster and Natural Selection," HIT-REFINED Working Paper Series 10, Institute of Economic Research, Hitotsubashi University.
    5. Berg, Tobias & Kaserer, Christoph, 2015. "Does contingent capital induce excessive risk-taking?," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 488, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    6. Akiyoshi, Fumio & Kobayashi, Keiichiro, 2010. "Banking crisis and productivity of borrowing firms: Evidence from Japan," Japan and the World Economy, Elsevier, vol. 22(3), pages 141-150, August.
    7. Kentaro Imai, 2013. "A Panel Study of Zombie SMEs in Japan: Identification, Borrowing and Investment Behavior," Discussion Papers in Economics and Business 13-16-Rev., Osaka University, Graduate School of Economics, revised Sep 2014.
    8. Hirofumi Uchida & Daisuke Miyakawa & Kaoru Hosono & Arito Ono & Taisuke Uchino & Ichiro Uesugi, 2015. "Financial Shocks, Bankruptcy, and Natural Selection," Mo.Fi.R. Working Papers 110, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    9. Scott Wilbur, 2019. "Credit Guarantees and Zombie Firms," Working Papers hal-02382926, HAL.
    10. Santiago Carbó‐Valverde & Francisco Rodríguez‐Fernández & Gregory F. Udell, 2016. "Trade Credit, the Financial Crisis, and SME Access to Finance," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(1), pages 113-143, February.
    11. Imai, Kentaro, 2016. "A panel study of zombie SMEs in Japan: Identification, borrowing and investment behavior," Journal of the Japanese and International Economies, Elsevier, vol. 39(C), pages 91-107.
    12. Kaihatsu, Sohei & Kurozumi, Takushi, 2014. "What caused Japan’s Great Stagnation in the 1990s? Evidence from an estimated DSGE model," Journal of the Japanese and International Economies, Elsevier, vol. 34(C), pages 217-235.
    13. Shin-ichi Fukuda & Munehisa Kasuya & Kentaro Akashi, 2007. "The Role of Trade Credit for Small Firms : An Implication from Japan’s Banking Crisis," Finance Working Papers 22596, East Asian Bureau of Economic Research.
    14. Kentaro Imai, 2013. "A Panel Study of eZombie f SMEs in Japan: Identification, Borrowing and Investment Behavior," Discussion Papers in Economics and Business 13-16, Osaka University, Graduate School of Economics.

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