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Thanaset Chevapatrakul

Personal Details

First Name:Thanaset
Middle Name:
Last Name:Chevapatrakul
Suffix:
RePEc Short-ID:pch489

Affiliation

Business School
University of Nottingham

Nottingham, United Kingdom
http://www.nottingham.ac.uk/business/
RePEc:edi:smnotuk (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Simona Mateut & Thanaset Chevapatrakul, 2017. "Customer financing, bargaining power and trade credit uptake," Discussion Papers 2017/04, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  2. Linh Xuan Diep Nguyen & Simona Mateut & Thanaset Chevapatrakul, 2016. "Business-Linkage Volatility Spillover between US Industries," Discussion Papers 2016/05, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  3. Thanaset Chevapatrakul & Kai-Hong Tee, 2014. "The Effects of News Events on Market Contagion: Evidence from the 2007-2009 Financial Crisis," Discussion Papers 2014/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  4. Thanaset Chevapatrakul & Tae-Hwan Kim & Paul Mizen, 2007. "Forecasting Changes in UK Interest Rates," Discussion Paper Series 2007_26, Department of Economics, Loughborough University, revised Nov 2007.

Articles

  1. Chevapatrakul, Thanaset, 2015. "Monetary environments and stock returns: International evidence based on the quantile regression technique," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 83-108.
  2. Chevapatrakul, Thanaset, 2014. "Monetary environments and stock returns revisited: A quantile regression approach," Economics Letters, Elsevier, vol. 123(2), pages 122-126.
  3. Thanaset Chevapatrakul & Juan Paez-Farrell, 2014. "Monetary Policy Reaction Functions in Small Open Economies: a Quantile Regression Approach," Manchester School, University of Manchester, vol. 82(2), pages 237-256, March.
  4. Thanaset Chevapatrakul & Juan Paez-farrell, 2013. "What determines the sacrifice ratio? A quantile regression approach," Economics Bulletin, AccessEcon, vol. 33(3), pages 1863-1874.
  5. Chevapatrakul, Thanaset, 2013. "Return sign forecasts based on conditional risk: Evidence from the UK stock market index," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2342-2353.
  6. Thanaset Chevapatrakul & Tae-Hwan Kim & Paul Mizen, 2009. "The Taylor Principle and Monetary Policy Approaching a Zero Bound on Nominal Rates: Quantile Regression Results for the United States and Japan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(8), pages 1705-1723, December.
  7. Tae-Hwan Kim & Paul Mizen & Thanaset Chevapatrakul, 2008. "Forecasting changes in UK interest rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 53-74.

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. Simona Mateut & Thanaset Chevapatrakul, 2017. "Customer financing, bargaining power and trade credit uptake," Discussion Papers 2017/04, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).

    Cited by:

    1. Hasan, Mostafa Monzur & Alam, Nurul, 2022. "Asset redeployability and trade credit," International Review of Financial Analysis, Elsevier, vol. 80(C).
    2. Xu, Hongkang & Dao, Mai, 2020. "Government contracts and trade credit," Advances in accounting, Elsevier, vol. 49(C).
    3. Van Tien Nguyen & Ngoc Thang Doan, 2023. "Open account, import decision and financial constraints: A cross‐country firm‐level study," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3918-3937, October.
    4. Sabina Scarpellini & José Ángel Gimeno & Pilar Portillo-Tarragona & Eva Llera-Sastresa, 2021. "Financial Resources for the Investments in Renewable Self-Consumption in a Circular Economy Framework," Sustainability, MDPI, vol. 13(12), pages 1-17, June.
    5. Yuming Zhang & Han Liu & Shuang Li & Chao Xing, 2023. "The Digital Transformation Effect in Trade Credit Uptake: The Buyer Perspective," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 59(7), pages 2056-2078, May.

  2. Linh Xuan Diep Nguyen & Simona Mateut & Thanaset Chevapatrakul, 2016. "Business-Linkage Volatility Spillover between US Industries," Discussion Papers 2016/05, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).

    Cited by:

    1. Samitas, Aristeidis & Kampouris, Elias & Polyzos, Stathis, 2022. "Covid-19 pandemic and spillover effects in stock markets: A financial network approach," International Review of Financial Analysis, Elsevier, vol. 80(C).
    2. Farooq Malik, 2022. "Volatility spillover among sector equity returns under structural breaks," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1063-1080, April.
    3. Gong, Xu & Xu, Jun & Liu, Tangyong & Zhou, Zicheng, 2022. "Dynamic volatility connectedness between industrial metal markets," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    4. Jia, Yanyan & Fang, Yi & Jing, Zhongbo & Lin, Faqin, 2022. "Price connectedness and input–output linkages: Evidence from China," Economic Modelling, Elsevier, vol. 116(C).
    5. Yabei Zhu & Xingguo Luo & Qi Xu, 2023. "Industry variance risk premium, cross‐industry correlation, and expected returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 3-32, January.
    6. Beibei Zhang & Xuemei Xie & Chunmei Li, 2023. "How Connected Is China’s Systemic Financial Risk Contagion Network?—A Dynamic Network Perspective Analysis," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    7. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    8. Liu, Bin & Xiao, Wen & Zhu, Xingting, 2023. "How does inter-industry spillover improve the performance of volatility forecasting?," The North American Journal of Economics and Finance, Elsevier, vol. 65(C).
    9. Xu, Qiuhua & Yan, Haoyang & Zhao, Tianyu, 2022. "Contagion effect of systemic risk among industry sectors in China’s stock market," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    10. Xiaoyang Chen & Liguo Zhou & Lin Wang & Yuelong Zheng, 2023. "Risk spillover in China’s real estate industry chain: a DCC-EGARCH-ΔCoVaR model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    11. Mensi, Walid & Nekhili, Ramzi & Vo, Xuan Vinh & Suleman, Tahir & Kang, Sang Hoon, 2021. "Asymmetric volatility connectedness among U.S. stock sectors," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

  3. Thanaset Chevapatrakul & Kai-Hong Tee, 2014. "The Effects of News Events on Market Contagion: Evidence from the 2007-2009 Financial Crisis," Discussion Papers 2014/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).

    Cited by:

    1. Jayech, Selma, 2016. "The contagion channels of July–August-2011 stock market crash: A DAG-copula based approach," European Journal of Operational Research, Elsevier, vol. 249(2), pages 631-646.
    2. Sila Alan, Nazli & Karagozoglu, Ahmet K. & Korkmaz, Sibel, 2016. "Growing pains: The evolution of new stock index futures in emerging markets," Research in International Business and Finance, Elsevier, vol. 37(C), pages 1-16.
    3. Valizadeh, Pourya & Karali, Berna & Ferreira, Susana, 2017. "Ripple effects of the 2011 Japan earthquake on international stock markets," Research in International Business and Finance, Elsevier, vol. 41(C), pages 556-576.
    4. Ye, Wuyi & Luo, Kebing & Liu, Xiaoquan, 2017. "Time-varying quantile association regression model with applications to financial contagion and VaR," European Journal of Operational Research, Elsevier, vol. 256(3), pages 1015-1028.
    5. Derbali, Abdelkader & Hallara, Slaheddine, 2016. "Systemic risk of European financial institutions: Estimation and ranking by the Marginal Expected Shortfall," Research in International Business and Finance, Elsevier, vol. 37(C), pages 113-134.
    6. Huang, Xuan & An, Haizhong & Fang, Wei & Gao, Xiangyun & Wang, Lijun & Sun, Xiaoqi, 2016. "Impact assessment of international anti-dumping events on synchronization and comovement of the Chinese photovoltaic stocks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 459-469.
    7. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol & Kurowski, Łukasz & Smaga, Paweł, 2021. "Two decades of contagion effect on stock markets: Which events are more contagious?," Journal of Financial Stability, Elsevier, vol. 55(C).
    8. Zbigniew Korzeb, 2014. "Influence Of The Economic And Financial Condition Of Strategic Shareholders Upon The Market Value Of Commercial Banks In The Polish Banking Sector," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 10(2), pages 38-43, August.
    9. Caporale, Guglielmo Maria & Sousa, Ricardo M., 2016. "Consumption, wealth, stock and housing returns: Evidence from emerging markets," Research in International Business and Finance, Elsevier, vol. 36(C), pages 562-578.
    10. Luchtenberg, Kimberly F. & Vu, Quang Viet, 2015. "The 2008 financial crisis: Stock market contagion and its determinants," Research in International Business and Finance, Elsevier, vol. 33(C), pages 178-203.
    11. Tony-Okeke, Uchenna & Ahmadu-Bello, Jaliyyah & Niklewski, Jacek & Rodgers, Timothy, 2018. "Financial contagion and capital asset pricing in Africa: The impact of the 2007–09 and Euro-Zone crises on natural resources sector Beta in African emerging markets," Research in International Business and Finance, Elsevier, vol. 45(C), pages 54-61.
    12. Ngwu, Franklin N. & Chen, Zheyang, 2016. "Regulation of securitisation in China: Learning from the US experience," Research in International Business and Finance, Elsevier, vol. 37(C), pages 477-488.
    13. Jiang, Hai & Tang, Shenfeng & Li, Lifang & Xu, Fangming & Di, Qian, 2022. "Re-examining the Contagion Channels of Global Financial Crises: Evidence from the Twelve Years since the US Subprime Crisis," Research in International Business and Finance, Elsevier, vol. 60(C).
    14. Zhang, Yi & Zhou, Long & Chen, Yajiao & Liu, Fang, 2022. "The contagion effect of jump risk across Asian stock markets during the Covid-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).

  4. Thanaset Chevapatrakul & Tae-Hwan Kim & Paul Mizen, 2007. "Forecasting Changes in UK Interest Rates," Discussion Paper Series 2007_26, Department of Economics, Loughborough University, revised Nov 2007.

    Cited by:

    1. Jan-Egbert Sturm & Jakob Haan, 2011. "Does central bank communication really lead to better forecasts of policy decisions? New evidence based on a Taylor rule model for the ECB," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 147(1), pages 41-58, April.
    2. Mizen, Paul & Tsoukas, Serafeim, 2012. "Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model," International Journal of Forecasting, Elsevier, vol. 28(1), pages 273-287.
    3. Chevapatrakul, Thanaset & Kim, Tae-Hwan & Mizen, Paul, 2012. "Monetary information and monetary policy decisions: Evidence from the euroarea and the UK," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 326-341.
    4. Lee A. Smales, 2013. "The Determinants of RBA Target Rate Decisions: A Choice Modelling Approach," The Economic Record, The Economic Society of Australia, vol. 89(287), pages 556-569, December.
    5. Paweł Baranowski, 2008. "Reguła Taylora i jej rozszerzenia," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 7-8, pages 1-23.
    6. Serafeim Tsoukas & Marina-Eliza Spaliara, 2014. "Market Implied Ratings and Financing Constraints: Evidence from US Firms," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 41(1-2), pages 242-269, January.
    7. Gustavo Nicolás Páez, 2015. "Prediciendo decisiones de agentes económicos: ¿Cómo determina el Banco de la República de Colombia la tasa de interés?," Documentos CEDE 12567, Universidad de los Andes, Facultad de Economía, CEDE.
    8. Sarah Brown & Mark N. Harris & Christopher Spencer, 2020. "Modelling Category Inflation with Multiple Inflation Processes: Estimation, Specification and Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1342-1361, December.
    9. Sermpinis, Georgios & Tsoukas, Serafeim & Zhang, Ping, 2018. "Modelling market implied ratings using LASSO variable selection techniques," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 19-35.
    10. Christina Bräuning & Ralf Fendel, 2018. "National information and euro area monetary policy: a generalized ordered choice approach," Empirical Economics, Springer, vol. 54(2), pages 501-522, March.
    11. Bergmeir, Christoph & Costantini, Mauro & Benítez, José M., 2014. "On the usefulness of cross-validation for directional forecast evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 132-143.

Articles

  1. Chevapatrakul, Thanaset, 2015. "Monetary environments and stock returns: International evidence based on the quantile regression technique," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 83-108.

    Cited by:

    1. Chevapatrakul, Thanaset & Xu, Zhongxiang & Yao, Kai, 2019. "The impact of tail risk on stock market returns: The role of market sentiment," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 289-301.
    2. Al-Nasseri, Alya & Menla Ali, Faek & Tucker, Allan, 2021. "Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors," International Review of Financial Analysis, Elsevier, vol. 78(C).
    3. Guo, Peng & Zhu, Huiming & You, Wanhai, 2018. "Asymmetric dependence between economic policy uncertainty and stock market returns in G7 and BRIC: A quantile regression approach," Finance Research Letters, Elsevier, vol. 25(C), pages 251-258.
    4. Stephanos Papadamou & Νikolaos A. Kyriazis & Panayiotis G. Tzeremes, 2020. "US non-linear causal effects on global equity indices in Normal times versus unconventional eras," International Economics and Economic Policy, Springer, vol. 17(2), pages 381-407, May.
    5. Mohammad Enamul Hoque & Mohd Azlan Shah Zaidi & M. Kabir Hassan, 2021. "Geopolitical Uncertainties and Malaysian Stock Market Returns: Do Market Conditions Matter?," Mathematics, MDPI, vol. 9(19), pages 1-16, September.

  2. Chevapatrakul, Thanaset, 2014. "Monetary environments and stock returns revisited: A quantile regression approach," Economics Letters, Elsevier, vol. 123(2), pages 122-126.

    Cited by:

    1. Yang, Sheng-Ping, 2017. "Exchange rate dynamics and stock prices in small open economies: Evidence from Asia-Pacific countries," Pacific-Basin Finance Journal, Elsevier, vol. 46(PB), pages 337-354.
    2. Chevapatrakul, Thanaset & Xu, Zhongxiang & Yao, Kai, 2019. "The impact of tail risk on stock market returns: The role of market sentiment," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 289-301.
    3. Chevapatrakul, Thanaset, 2015. "Monetary environments and stock returns: International evidence based on the quantile regression technique," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 83-108.
    4. Mohammad Sharik Essa & Evangelos Giouvris, 2020. "Oil Price, Oil Price Implied Volatility (OVX) and Illiquidity Premiums in the US: (A)symmetry and the Impact of Macroeconomic Factors," JRFM, MDPI, vol. 13(4), pages 1-40, April.
    5. Wen, Fenghua & Shui, Aojie & Cheng, Yuxiang & Gong, Xu, 2022. "Monetary policy uncertainty and stock returns in G7 and BRICS countries: A quantile-on-quantile approach," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 457-482.

  3. Thanaset Chevapatrakul & Juan Paez-Farrell, 2014. "Monetary Policy Reaction Functions in Small Open Economies: a Quantile Regression Approach," Manchester School, University of Manchester, vol. 82(2), pages 237-256, March.

    Cited by:

    1. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    2. Gabriela Bezerra Medeiros & Marcelo Savino Portugal & Edilean Kleber da Silva Bejarano Aragón, 2017. "Endogeneity and nonlinearities in Central Bank of Brazil’s reaction functions: an inverse quantile regression approach," Empirical Economics, Springer, vol. 53(4), pages 1503-1527, December.
    3. Kerry B. Hudson & Joaquin L. Vespignani, 2014. "Understanding the Deviations of the Taylor Rule: A New Methodology with an Application to Australia," CAMA Working Papers 2014-78, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Akosah, Nana & Alagidede, Imhotep & Schaling, Eric, 2019. "Unfolding the monetary policy rule in Ghana: quantile-based evidence within time-frequency framework," MPRA Paper 103260, University Library of Munich, Germany, revised 01 Oct 2020.
    5. Hudson, Kerry & Vespignani, Joaquin L., 2015. "Understanding the Taylor Rule in Australia," MPRA Paper 104679, University Library of Munich, Germany.
    6. Karamti, Chiraz, 2019. "Lopsided effects of telecom reforms on mobile markets in the enlarged EU: Evidence from dynamic quantile model," Telecommunications Policy, Elsevier, vol. 43(3), pages 238-261.
    7. Juan Paez-Farrell, 2015. "Taylor rules, central bank preferences and inflation targeting," Working Papers 2015023, The University of Sheffield, Department of Economics.
    8. Laura Ferrando & Román Ferrer & Francisco Jareño, 2017. "Interest Rate Sensitivity of Spanish Industries: A Quantile Regression Approach," Manchester School, University of Manchester, vol. 85(2), pages 212-242, March.
    9. González, María de la O & Jareño, Francisco, 2019. "Testing extensions of Fama & French models: A quantile regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 188-204.
    10. Ana Escribano & Francisco Jareño & Jose Ángel Cano, 2023. "Study of the leading European construction companies using risk factor models," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3386-3402, July.
    11. Gabriela Bezerra De Medeiros & Marcelo Savino Portugal & Edilean Kleber Da Silva Bejarano Aragon, 2016. "Endogeneity And Nonlinearities In Central Bank Of Brazil’S Reaction Functions: An Inverse Quantile Regression Approach," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 061, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    12. Helena Glebocki Keefe & Hedieh Shadmani, 2020. "Examining the asymmetric monetary policy response to foreign exchange market conditions in emerging and developing economies," International Economics and Economic Policy, Springer, vol. 17(2), pages 503-530, May.

  4. Thanaset Chevapatrakul & Juan Paez-farrell, 2013. "What determines the sacrifice ratio? A quantile regression approach," Economics Bulletin, AccessEcon, vol. 33(3), pages 1863-1874.

    Cited by:

    1. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2022. "Spillover effects between commodity and stock markets: A SDSES approach," Resources Policy, Elsevier, vol. 79(C).
    2. Antonio Rubia Serrano & Lidia Sanchis-Marco, 2015. "Measuring Tail-Risk Cross-Country Exposures in the Banking Industry," Working Papers. Serie AD 2015-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).

  5. Chevapatrakul, Thanaset, 2013. "Return sign forecasts based on conditional risk: Evidence from the UK stock market index," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2342-2353.

    Cited by:

    1. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    2. Liu, Yi & Liu, Huifang & Zhang, Lei, 2019. "Modeling and forecasting return jumps using realized variation measures," Economic Modelling, Elsevier, vol. 76(C), pages 63-80.
    3. Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2019. "Return Signal Momentum," QBS Working Paper Series 2019/04, Queen's University Belfast, Queen's Business School.
    4. Harri Pönkä, 2017. "Predicting the direction of US stock markets using industry returns," Empirical Economics, Springer, vol. 52(4), pages 1451-1480, June.
    5. Harri Pönkä, 2018. "Sentiment and sign predictability of stock returns," Economics Bulletin, AccessEcon, vol. 38(3), pages 1676-1684.
    6. Pönkä, Harri, 2015. "Real oil prices and the international sign predictability of stock returns," MPRA Paper 68330, University Library of Munich, Germany.
    7. de Resende, Charlene C. & Pereira, Adriano C.M. & Cardoso, Rodrigo T.N. & de Magalhães, A.R. Bosco, 2017. "Investigating market efficiency through a forecasting model based on differential equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 199-212.
    8. Garcia, M.M. & Machado Pereira, A.C. & Acebal, J.L. & Bosco de Magalhães, A.R., 2020. "Forecast model for financial time series: An approach based on harmonic oscillators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    9. Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2021. "Return signal momentum," Journal of Banking & Finance, Elsevier, vol. 124(C).
    10. Chronopoulos, Dimitris K. & Papadimitriou, Fotios I. & Vlastakis, Nikolaos, 2018. "Information demand and stock return predictability," Journal of International Money and Finance, Elsevier, vol. 80(C), pages 59-74.
    11. Luis H. R. Alvarez E. & Paavo Salminen, 2017. "Timing in the presence of directional predictability: optimal stopping of skew Brownian motion," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 86(2), pages 377-400, October.

  6. Thanaset Chevapatrakul & Tae-Hwan Kim & Paul Mizen, 2009. "The Taylor Principle and Monetary Policy Approaching a Zero Bound on Nominal Rates: Quantile Regression Results for the United States and Japan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(8), pages 1705-1723, December.

    Cited by:

    1. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    2. Tae-Hwan Kim & Christophe Muller, 2020. "Inconsistency transmission and variance reduction in two-stage quantile regression," Post-Print hal-02084505, HAL.
    3. Levine, Paul & McAdam, Peter & Pearlman, Joseph, 2012. "Probability models and robust policy rules," European Economic Review, Elsevier, vol. 56(2), pages 246-262.
    4. Haroon Mumtaz & Paolo Surico, 2015. "The Transmission Mechanism In Good And Bad Times," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1237-1260, November.
    5. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    6. Schultefrankenfeld Guido, 2013. "Forecast uncertainty and the Bank of England’s interest rate decisions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 1-20, February.
    7. Tae-Hwan Kim & Christophe Muller, 2017. "A Robust Test of Exogeneity Based on Quantile Regressions," Working Papers halshs-01508067, HAL.
    8. Pavel Gertler & Roman Horvath, 2017. "Market Reading of Central Bankers Words. A High-Frequency Evidence," Working and Discussion Papers WP 2/2017, Research Department, National Bank of Slovakia.
    9. Wolters, Maik Hendrik, 2010. "Estimating Monetary Policy Reaction Functions Using Quantile Regressions," MPRA Paper 23857, University Library of Munich, Germany.
    10. Gabriela Bezerra Medeiros & Marcelo Savino Portugal & Edilean Kleber da Silva Bejarano Aragón, 2017. "Endogeneity and nonlinearities in Central Bank of Brazil’s reaction functions: an inverse quantile regression approach," Empirical Economics, Springer, vol. 53(4), pages 1503-1527, December.
    11. Christophe Muller, 2019. "Linear Quantile Regression and Endogeneity Correction," Working Papers halshs-02272874, HAL.
    12. Christou Christina & Naraidoo Ruthira & Gupta Rangan, 2020. "Conventional and unconventional monetary policy reaction to uncertainty in advanced economies: evidence from quantile regressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(3), pages 1-17, June.
    13. Akosah, Nana & Alagidede, Imhotep & Schaling, Eric, 2019. "Unfolding the monetary policy rule in Ghana: quantile-based evidence within time-frequency framework," MPRA Paper 103260, University Library of Munich, Germany, revised 01 Oct 2020.
    14. Raghavan, Mala & Athanasopoulos, George, 2019. "Analysis of shock transmissions to a small open emerging economy using a SVARMA model," Economic Modelling, Elsevier, vol. 77(C), pages 187-203.
    15. Tae-Hwan Kim & Christophe Muller, 2013. "A Test for Endogeneity in Conditional Quantiles," AMSE Working Papers 1342, Aix-Marseille School of Economics, France, revised Aug 2013.
    16. Chevapatrakul, Thanaset & Kim, Tae-Hwan & Mizen, Paul, 2012. "Monetary information and monetary policy decisions: Evidence from the euroarea and the UK," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 326-341.
    17. Christina Christou & Ruthira Naraidoo & Rangan Gupta & Christis Hassapis, 2019. "Monetary Policy Reaction to Uncertainty in Japan: Evidence from a Quantile-on-Quantile Interest Rate Rule," Working Papers 201929, University of Pretoria, Department of Economics.
    18. Tae-Hwan Kim, & Christophe Muller, 2012. "Bias Transmission and Variance Reduction in Two-Stage Quantile Regression," AMSE Working Papers 1221, Aix-Marseille School of Economics, France.
    19. Pierre L. Siklos, 2020. "Looking into the Rear-View Mirror: Lessons from Japan for the Eurozone and the U.S?," IMES Discussion Paper Series 20-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    20. Kiesel, Konstantin & Wolters, Maik H., 2014. "Estimating monetary policy rules when the zero lower bound on nominal interest rates is approached," Kiel Working Papers 1898, Kiel Institute for the World Economy (IfW Kiel).
    21. Christina Christou & Ruthira Naraidoo & Rangan Gupta & Won Joong Kim, 2017. "Monetary Policy Reaction Functions of the TICKs: A Quantile Regression Approach," Working Papers 201738, University of Pretoria, Department of Economics.
    22. Tae-Hwan Kim & Christophe Muller, 2015. "A Particular Form of Non-Constant Effect in Two-Stage Quantile Regression," Working papers 2015rwp-82, Yonsei University, Yonsei Economics Research Institute.
    23. Charles Evans & Jonas Fisher & Francois Gourio & Spencer Krane, 2015. "Risk Management for Monetary Policy Near the Zero Lower Bound," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 46(1 (Spring), pages 141-219.
    24. William Miles & Sam Schreyer, 2012. "Is monetary policy non-linear in Indonesia, Korea, Malaysia, and Thailand? A quantile regression analysis," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 26(2), pages 155-166, November.
    25. Jau-er Chen & Masanori Kashiwagi, 2017. "The Japanese Taylor rule estimated using censored quantile regressions," Empirical Economics, Springer, vol. 52(1), pages 357-371, February.
    26. Apergis, Nicholas & Christou, Christina, 2015. "The behaviour of the bank lending channel when interest rates approach the zero lower bound: Evidence from quantile regressions," Economic Modelling, Elsevier, vol. 49(C), pages 296-307.
    27. Neuenkirch, Matthias & Tillmann, Peter, 2014. "Inflation targeting, credibility, and non-linear Taylor rules," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 30-45.
    28. Gertler, Pavel & Horvath, Roman, 2018. "Central bank communication and financial markets: New high-frequency evidence," Journal of Financial Stability, Elsevier, vol. 36(C), pages 336-345.
    29. William Miles & Samuel Schreyer, 2014. "Is monetary policy non-linear in Latin America? a quantile regression approach to Brazil, Chile, Mexico and Peru," Journal of Developing Areas, Tennessee State University, College of Business, vol. 48(2), pages 169-183, April-Jun.
    30. Gabriela Bezerra De Medeiros & Marcelo Savino Portugal & Edilean Kleber Da Silva Bejarano Aragon, 2016. "Endogeneity And Nonlinearities In Central Bank Of Brazil’S Reaction Functions: An Inverse Quantile Regression Approach," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 061, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    31. Hyeong Ho Moon & Tae-Hwan Kim & Seongho Nah, 2012. "On measuring the nonlinear effect of interest rates on inflation and output," Working papers 2013rwp-53, Yonsei University, Yonsei Economics Research Institute.
    32. Xiaochun Liu, 2018. "How is the Taylor Rule Distributed under Endogenous Monetary Regimes?," International Review of Finance, International Review of Finance Ltd., vol. 18(2), pages 305-316, June.
    33. Thanaset Chevapatrakul & Juan Paez-Farrell, 2014. "Monetary Policy Reaction Functions in Small Open Economies: a Quantile Regression Approach," Manchester School, University of Manchester, vol. 82(2), pages 237-256, March.

  7. Tae-Hwan Kim & Paul Mizen & Thanaset Chevapatrakul, 2008. "Forecasting changes in UK interest rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 53-74.
    See citations under working paper version above.

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  1. NEP-BAN: Banking (1) 2014-08-20
  2. NEP-CFN: Corporate Finance (1) 2017-07-23
  3. NEP-CSE: Economics of Strategic Management (1) 2016-11-27
  4. NEP-NET: Network Economics (1) 2014-08-16

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