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Laurent L. Pauwels

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. Imbs, Jean & Pauwels, Laurent, 2020. "High Order Openness," CEPR Discussion Papers 14653, C.E.P.R. Discussion Papers.

    Cited by:

    1. Baldwin, Richard & Freeman, Rebecca & Theodorakopoulos, Angelos, 2022. "Horses for courses: measuring foreign supply chain exposure," Bank of England working papers 996, Bank of England.

  2. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Ruben Loaiza‐Maya & Gael M. Martin & David T. Frazier, 2021. "Focused Bayesian prediction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 517-543, August.
    2. Gael M. Martin & Rub'en Loaiza-Maya & David T. Frazier & Worapree Maneesoonthorn & Andr'es Ram'irez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Papers 2009.09592, arXiv.org.
    3. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    4. 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.

  3. Pauwels, Laurent & Vasnev, Andrey, 2013. "Practical considerations for optimal weights in density forecast combi nation," Working Papers 01/2013, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Magnus, Jan R. & Vasnev, Andrey L., 2015. "Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations," International Journal of Forecasting, Elsevier, vol. 31(3), pages 769-781.

  4. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 02/2013, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Goodness C. Aye & Christina Christou & Luis A. Gil-Alana & Rangan Gupta, 2016. "Forecasting the Probability of Recessions in South Africa: The Role of Decomposed Term-Spread and Economic Policy Uncertainty," Working Papers 201680, University of Pretoria, Department of Economics.
    2. Ahmar, Ansari Saleh, 2019. "Reliability Test of SutteARIMA to Forecast Artificial Data," OSF Preprints 9zn7v, Center for Open Science.
    3. Pirschel, Inske, 2015. "Forecasting Euro Area Recessions in real-time with a mixed-frequency Bayesian VAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113031, Verein für Socialpolitik / German Economic Association.

  5. Pauwels, Laurent & Vasnev, Andrey, 2011. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Working Papers 11/2011, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 02/2013, University of Sydney Business School, Discipline of Business Analytics.
    2. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    3. Pauwels, Laurent, 2019. "Predicting China’s Monetary Policy with Forecast Combinations," Working Papers BAWP-2019-07, University of Sydney Business School, Discipline of Business Analytics.
    4. Kim, Hyerim & Kang, Kyu Ho, 2022. "The Bank of Korea watch," Journal of International Money and Finance, Elsevier, vol. 126(C).

  6. Li-gang Liu & Laurent Pauwels & Jun-yu Chan, 2008. "Do External Political Pressures Affect the Renminbi Exchange Rate?," Working Papers 0805, Hong Kong Monetary Authority.

    Cited by:

    1. Kawai, Masahiro & Liu, Li-Gang, 2015. "Trilemma Challenges for the People's Republic of China," ADBI Working Papers 513, Asian Development Bank Institute.
    2. Li, Xue & Liu, Yanghui & Li, Hanxu & Li, Jie, 2021. "Onshore spot and offshore forward markets for RMB: Evidence from the “8.11” exchange rate regime reform," China Economic Review, Elsevier, vol. 67(C).
    3. Owyong, David & Wong, Wing-Keung & Horowitz, Ira, 2015. "Cointegration and Causality among the Onshore and Offshore Markets for China's Currency," MPRA Paper 71107, University Library of Munich, Germany.
    4. Zhang, Chen & Fang, Ying & Niu, Linlin, 2022. "Changing anchor of the renminbi: A Bayesian learning approach to the decade-long transition," Economic Modelling, Elsevier, vol. 116(C).
    5. Wei Jiang & Yaqin Wang & Tao Wang, 2023. "The Political Economy of American Exchange Rate Bill Voting: From the Perspective of RMB Appreciation," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 13(1), pages 1-3.
    6. Jia, Fei & Shen, Yao & Ren, Junfan & Xu, Xiangyun, 2021. "The impact of offshore exchange rate expectations on onshore exchange rates: The case of Chinese RMB," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    7. Dimitar Gueorguiev & Daniel McDowell & David A. Steinberg, 2020. "The Impact of Economic Coercion on Public Opinion: The Case of US–China Currency Relations," Journal of Conflict Resolution, Peace Science Society (International), vol. 64(9), pages 1555-1583, October.
    8. López Noria Gabriela & Bush Georgia, 2019. "Uncertainty and Exchange Rate Volatility: the Case of Mexico," Working Papers 2019-12, Banco de México.
    9. Ping Wang & Peijie Wang, 2022. "Assessment on estimations of currency basket weights—With coefficient correction for common factor dominance," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1401-1418, January.
    10. Ge, Futing & Zhang, Weiguo, 2022. "The determinants of cross-border bond risk premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    11. Löchel, H. & Packham, N. & Walisch, F., 2016. "Determinants of the onshore and offshore Chinese government yield curves," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 77-93.
    12. Chunming Shen, 2022. "Digital RMB, RMB Internationalization and Sustainable Development of the International Monetary System," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    13. Wei Guo & Zhongfei Chen, 2023. "China–US economic and trade relations, trade news, and short‐term fluctuation of the RMB exchange rate," Review of International Economics, Wiley Blackwell, vol. 31(1), pages 180-203, February.
    14. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2018. "Public information arrival, price discovery and dynamic correlations in the Chinese renminbi markets," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 168-186.
    15. Guo, Wei & Chen, Zhongfei & Šević, Aleksandar, 2021. "The political pressure from the US upon RMB exchange rate," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    16. Niu, Zibo & Wang, Chenlu & Zhang, Hongwei, 2023. "Forecasting stock market volatility with various geopolitical risks categories: New evidence from machine learning models," International Review of Financial Analysis, Elsevier, vol. 89(C).
    17. Ding, Shusheng & Cui, Tianxiang & Zhang, Yongmin, 2020. "Incorporating the RMB internationalization effect into its exchange rate volatility forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    18. Wan, Xiaoli & Yan, Yuruo & Zeng, Zhixiong, 2020. "Exchange rate regimes and market integration: evidence from the dynamic relations between renminbi onshore and offshore markets," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    19. Loechel, Horst & Packham, Natalie & Walisch, Fabian, 2013. "Determinants of the onshore and offshore Chinese Government yield curves," Frankfurt School - Working Paper Series 202, Frankfurt School of Finance and Management.
    20. Tsuchiya, Yoichi, 2016. "Asymmetric loss and rationality of Chinese renminbi forecasts: An implication for the trade between China and the US," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 116-127.
    21. Ma, Xiuying & Yang, Zhihua & Xu, Xiangyun & Wang, Chengqi, 2018. "The impact of Chinese financial markets on commodity currency exchange rates," Global Finance Journal, Elsevier, vol. 37(C), pages 186-198.
    22. Liao, Jia & Qian, Qi & Xu, Xiangyun, 2018. "Whether the fluctuation of China’s financial markets have impact on global commodity prices?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1030-1040.
    23. Xiaojing Zhang & Tao Sun, 2009. "Spillovers of the U.S. Subprime Financial Turmoil to Mainland China and Hong Kong SAR: Evidence from Stock Markets," IMF Working Papers 2009/166, International Monetary Fund.

  7. Dong He & Laurent Pauwels, 2008. "What Prompts the People's Bank of China to Change its Monetary Policy Stance? Evidence from a Discrete Choice Model," Working Papers 0806, Hong Kong Monetary Authority.

    Cited by:

    1. Chang Shu & Dong He & Xiaoqiang Cheng, 2014. "One currency, two markets: the renminbi’s growing influence in Asia-Pacific," BIS Working Papers 446, Bank for International Settlements.
    2. Xiong, Qiyue, 2013. "The role of the bank lending channel and impacts of stricter capital requirements on the Chinese banking industry," BOFIT Discussion Papers 7/2013, Bank of Finland Institute for Emerging Economies (BOFIT).
    3. Hyeongwoo Kim & Wen Shi, 2017. "The Determinants of the Benchmark Interest Rates in China: A Discrete Choice Model Approach," Auburn Economics Working Paper Series auwp2017-04, Department of Economics, Auburn University.
    4. Dong He & Honglin Wang, 2011. "Dual-Track Interest Rates and the Conduct of Monetary Policy in China," Working Papers 212011, Hong Kong Institute for Monetary Research.
    5. Dong He & Paul Luk, 2013. "A Model of Chinese Capital Account Liberalisation," Working Papers 122013, Hong Kong Institute for Monetary Research.
    6. Jakub Borowski & Adam Czerniak, 2012. "Determinanty polityki pieniężnej Ludowego Banku Chin," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 1-2, pages 97-116.
    7. Sun, Rongrong, 2012. "Does Monetary Policy Matter in China? A Narrative Approach," MPRA Paper 45023, University Library of Munich, Germany.
    8. Thang, Doan Ngoc & Anh, Pham Thi Hoang & Long, Trinh & Dong, Do Phy & Dat, Luong Van, 2022. "Monetary Stance and Favorableness of Monetary Policy in the Media: The Case of Viet Nam," ADBI Working Papers 1325, Asian Development Bank Institute.
    9. Dong He & Honglin Wang & Xiangrong Yu, 2015. "Interest Rate Determination in China: Past, Present, and Future," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 255-277, December.
    10. Klingelhöfer, Jan & Sun, Rongrong, 2019. "Macroprudential policy, central banks and financial stability: Evidence from China," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 19-41.
    11. Fredj Jawadi & Sushanta K. Mallick & Ricardo M. Sousa, 2011. "Monetary Policy Rules in the BRICS: How Important is Nonlinearity?," NIPE Working Papers 18/2011, NIPE - Universidade do Minho.
    12. Dong He & Honglin Wang, 2013. "Monetary Policy and Bank Lending in China - Evidence from Loan-Level Data," Working Papers 162013, Hong Kong Institute for Monetary Research.
    13. Kim, Hyeongwoo & Shi, Wen, 2018. "The determinants of the benchmark interest rates in China," Journal of Policy Modeling, Elsevier, vol. 40(2), pages 395-417.
    14. Rongrong Sun, 2018. "Monetary Policy Announcements and Market Interest Rates Response: Evidence from China," CFDS Discussion Paper Series 2018/5, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
    15. Eric Girardin & Sandrine Lunven & Guonan Ma, 2014. "Inflation and China's monetary policy reaction function: 2002-2013," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation, inflation and monetary policy in Asia and the Pacific, volume 77, pages 159-170, Bank for International Settlements.
    16. Rongrong Sun, 2018. "A Narrative indicator of Monetary Conditions in China," International Journal of Central Banking, International Journal of Central Banking, vol. 14(4), pages 1-42, September.
    17. Eric Girardin & Sandrine Lunven & Guonan Ma, 2017. "China's evolving monetary policy rule: from inflation-accommodating to anti-inflation policy," BIS Working Papers 641, Bank for International Settlements.
    18. Jeannine Bailliu & Xinfen Han & Barbara Sadaba & Mark Kruger, 2021. "Chinese Monetary Policy and Text Analytics: Connecting Words and Deeds," Staff Working Papers 21-3, Bank of Canada.
    19. Rongrong Sun, 2015. "What Measures Chinese Monetary Policy?," Working Papers 072015, Hong Kong Institute for Monetary Research.
    20. Körner, Finn Marten & Ehnts, Dirk H., 2013. "Chinese monetary policy – from theory to practice," MPRA Paper 44264, University Library of Munich, Germany.
    21. Michael Funke & Andrew Tsang, 2021. "The Direction and Intensity of China’s Monetary Policy: A Dynamic Factor Modelling Approach," The Economic Record, The Economic Society of Australia, vol. 97(316), pages 100-122, March.
    22. Chen, Hongyi & Chow, Kenneth & Tillmann, Peter, 2017. "The effectiveness of monetary policy in China: Evidence from a Qual VAR," China Economic Review, Elsevier, vol. 43(C), pages 216-231.
    23. Xiong, Weibo, 2012. "Measuring the monetary policy stance of the People's bank of china: An ordered probit analysis," China Economic Review, Elsevier, vol. 23(3), pages 512-533.
    24. Paul G. Egan & Anthony J. Leddin, 2016. "Examining Monetary Policy Transmission in the People's Republic of China–Structural Change Models with a Monetary Policy Index," Asian Development Review, MIT Press, vol. 33(1), pages 74-110, March.
    25. Peter Tillmann, 2014. "Unconventional Monetary Policy Shocks and the Spillovers to Emerging Markets," Working Papers 182014, Hong Kong Institute for Monetary Research.
    26. Stefan Angrick & Naoyuki Yoshino, 2020. "From Window Guidance to Interbank Rates: Tracing the Transition of Monetary Policy in Japan and China," International Journal of Central Banking, International Journal of Central Banking, vol. 16(3), pages 279-316, June.
    27. Pauwels, Laurent, 2019. "Predicting China’s Monetary Policy with Forecast Combinations," Working Papers BAWP-2019-07, University of Sydney Business School, Discipline of Business Analytics.
    28. Klingelhöfer, Jan & Sun, Rongrong, 2018. "China's regime-switching monetary policy," Economic Modelling, Elsevier, vol. 68(C), pages 32-40.
    29. Soyoung Kim & Hongyi Chen, 2022. "From a Quantity to an Interest Rate‐Based Framework: Multiple Monetary Policy Instruments and Their Effects in China," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(7), pages 2103-2123, October.
    30. Tillmann, Peter, 2016. "Unconventional monetary policy and the spillovers to emerging markets," Journal of International Money and Finance, Elsevier, vol. 66(C), pages 136-156.
    31. Alex, Dony, 2021. "Anchoring of inflation expectations in large emerging economies," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    32. Dong He, 2014. "Comments on Eric Girardin, Sandrine Lunven and Guonan Ma's paper," BIS Papers chapters, in: Bank for International Settlements (ed.), Globalisation, inflation and monetary policy in Asia and the Pacific, volume 77, pages 171-174, Bank for International Settlements.

  8. Li-gang Liu & Laurent Pauwels & Andrew Tsang, 2007. "Hong Kong's Consumption Function Revisited," Working Papers 0716, Hong Kong Monetary Authority.

    Cited by:

    1. Funke, Michael & Paetz, Michael & Pytlarczyk, Ernest, 2009. "Stock market wealth effects in an estimated DSGE model for Hong Kong," BOFIT Discussion Papers 14/2009, Bank of Finland Institute for Emerging Economies (BOFIT).
    2. Li-gang Liu & Laurent Pauwels & Andrew Tsang, 2007. "How Large is the Wealth Effect on Hong Kong¡¦s Consumption? Evidence from a Habit Formation Model of Consumption," Working Papers 0720, Hong Kong Monetary Authority.

  9. Li-gang Liu & Laurent Pauwels & Andrew Tsang, 2007. "How Large is the Wealth Effect on Hong Kong¡¦s Consumption? Evidence from a Habit Formation Model of Consumption," Working Papers 0720, Hong Kong Monetary Authority.

    Cited by:

    1. Funke, Michael & Paetz, Michael & Pytlarczyk, Ernest, 2009. "Stock market wealth effects in an estimated DSGE model for Hong Kong," BOFIT Discussion Papers 14/2009, Bank of Finland Institute for Emerging Economies (BOFIT).

  10. Felix Chan Tommaso Mancini-Griffoli Laurent L. Pauwels, 2006. "Stability Tests for Heterogeneous Panel Data," IHEID Working Papers 24-2006, Economics Section, The Graduate Institute of International Studies, revised Dec 2006.

    Cited by:

    1. Chan, Felix & Pauwels, Laurent, 2011. "Model specification in panel data unit root tests with an unknown break," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1299-1309.
    2. Chiu, Yi-Bin & Lee, Chien-Chiang & Sun, Chia-Hung, 2010. "The U.S. trade imbalance and real exchange rate: An application of the heterogeneous panel cointegration method," Economic Modelling, Elsevier, vol. 27(3), pages 705-716, May.
    3. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    4. Huanjun Zhu & Vasilis Sarafidis & Mervyn Silvapulle & Jiti Gao, 2015. "Testing for a Structural Break in Dynamic Panel Data Models with Common Factors," Monash Econometrics and Business Statistics Working Papers 20/15, Monash University, Department of Econometrics and Business Statistics.

  11. Tommaso Mancini-Griffoli & Laurent L. Pauwels, 2006. "Is There a Euro Effect on Trade? An Application of End-of-Sample Structural Break Tests for Panel Data," IHEID Working Papers 04-2006, Economics Section, The Graduate Institute of International Studies, revised Apr 2006.

    Cited by:

    1. Rao, B. Bhaskara & Tamazian, Artur & Kumar, Saten, 2009. "Systems GMM estimates of the Feldstein-Horioka puzzle for the OECD countries and tests for structural breaks," MPRA Paper 15312, University Library of Munich, Germany.
    2. Baldwin, Richard & Di Nino, Virginia, 2006. "Euros and Zeros: The Common Currency Effect on Trade in New Goods," CEPR Discussion Papers 5973, C.E.P.R. Discussion Papers.
    3. Bangake, Chrysost & Eggoh, Jude C., 2012. "Pooled Mean Group estimation on international capital mobility in African countries," Research in Economics, Elsevier, vol. 66(1), pages 7-17.
    4. Tommaso Mancini Griffoli, 2006. "Explaining the Euro's Effect on Trade? Interest Rates in an Augmented Gravity Equation," IHEID Working Papers 10-2006, Economics Section, The Graduate Institute of International Studies.
    5. Verstegen, Loes & van Groezen, Bas & Meijdam, Lex, 2017. "Benefits of EMU Participation : Estimates using the Synthetic Control Method," Discussion Paper 2017-032, Tilburg University, Center for Economic Research.
    6. Chen, Mei-Ping & Chen, Wen-Yi & Tseng, Tseng-Chan, 2017. "Co-movements of returns in the health care sectors from the US, UK, and Germany stock markets: Evidence from the continuous wavelet analyses," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 484-498.
    7. Theo Eicher & Christian Henn, 2009. "One Money, One Market: A Revised Benchmark," Working Papers UWEC-2009-08-FC, University of Washington, Department of Economics.
    8. Aleksander Aristovnik & Matevz Meze, 2010. "The Economic and Monetary Union???s Effect on (International) Trade: the Case of Slovenia Before Euro Adoption," William Davidson Institute Working Papers Series wp982, William Davidson Institute at the University of Michigan.
    9. Giovanni Mellace & Alessandra Pasquini, 2019. "Identify More, Observe Less: Mediation Analysis Synthetic Control," CEIS Research Paper 474, Tor Vergata University, CEIS, revised 20 Nov 2019.
    10. Mellace, Giovanni & Pasquini, Alessandra, 2019. "Identify More, Observe Less: Mediation Analysis: Mediation Analysis Synthetic Control," Discussion Papers on Economics 12/2019, University of Southern Denmark, Department of Economics.
    11. Kumar, Saten, 2015. "Regional integration, capital mobility and financial intermediation revisited: Application of general to specific method in panel data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 36(C), pages 1-17.
    12. Rao, B. Bhaskara & Tamazian, Artur & Singh, Prakash, 2009. "Demand for Money in the Asian Countries: A Systems GMM Panel Data Approach and Structural Breaks," MPRA Paper 15030, University Library of Munich, Germany.
    13. Kumar, Saten & Chowdhury, Mamta & Rao, B. Bhaskara, 2010. "Demand for Money in the Selected OECD Countries: A Time Series Panel Data Approach and Structural Breaks," MPRA Paper 22204, University Library of Munich, Germany.
    14. Juan Pi??eiro Chousa, & Artur Tamazian, & Davit N. Melikyan,, 2008. "MARKET RISK DYNAMICS AND COMPETITIVENESS AFTER THE EURO: Evidence from EMU Members," William Davidson Institute Working Papers Series wp916, William Davidson Institute at the University of Michigan.
    15. Mariam Camarero & Estrella Gómez & Cecilio Tamarit, 2013. "EMU and Trade Revisited: Long-Run Evidence Using Gravity Equations," The World Economy, Wiley Blackwell, vol. 36(9), pages 1146-1164, September.
    16. Puzzello, Laura & Gomis-Porqueras, Pedro, 2018. "Winners and losers from the €uro," European Economic Review, Elsevier, vol. 108(C), pages 129-152.
    17. Yasin YILDIRIM, 2018. "Is The Adoption Of The Euro A Story Of Success Or Failure? An Assessment Under Economic And Political Reflections," Contemporary Economy Journal, Constantin Brancoveanu University, vol. 3(2), pages 107-117.
    18. Mariam Camarero & Estrella Gómez & Cecilio Tamarit, 2012. "EMU and intra-European trade. Long-run evidence using gravity equations," ThE Papers 10/25, Department of Economic Theory and Economic History of the University of Granada..

  12. Hans Genberg & Laurent L. Pauwels, 2004. "Wage-Price Dynamics and Deflation in Hong Kong," IHEID Working Papers 06-2004, Economics Section, The Graduate Institute of International Studies.

    Cited by:

    1. Nicolas Canry & Julien Fouquau & Sébastien Lechevalier, 2007. "Price Dynamics in Japan (1981-2001):A Structural Analysis of Mechanisms in the Goods and Labord Markets," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00222890, HAL.
    2. Hans Genberg, 2005. "External shocks, transmission mechanisms and deflation in Asia," BIS Working Papers 187, Bank for International Settlements.
    3. Gregor W. Smith, 2006. "The Spectre Of Deflation: A Review Of Empirical Evidence," Working Paper 1086, Economics Department, Queen's University.
    4. James Yetman, 2009. "Hong Kong Consumer Prices are Flexible," Working Papers 052009, Hong Kong Institute for Monetary Research.
    5. Pierre L. Siklos & Diana N. Weymark, 2007. "Is Sterilized Intervention Effective? New International Evidence," Working Papers 142007, Hong Kong Institute for Monetary Research.
    6. Li-gang Liu & Andrew Tsang, 2008. "Exchange Rate Pass-Through to Domestic Inflation in Hong Kong," Working Papers 0802, Hong Kong Monetary Authority.
    7. Shin-ichi Fukuda & Junji Yamada, 2012. "Why Did Large-scale Deflation Occur? What Did It Bring About?: From Hong Kong's Experiences in the First Half of the 2000s," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 8(1), pages 93-122, June.
    8. Michael K. Salemi, 2007. "Long-run and Cyclic Movements in the Unemployment Rate in Hong Kong: A Dynamic, General Equilibrium Approach," Working Papers 192007, Hong Kong Institute for Monetary Research.
    9. Claudio Borio & Magdalena Erdem & Andrew Filardo & Boris Hofmann, 2015. "The costs of deflations: a historical perspective," BIS Quarterly Review, Bank for International Settlements, March.

  13. Suhejla Hoti & Michael McAleer & Laurent L. Pauwels, 2004. "Modelling Environmental Risk," IHEID Working Papers 08-2004, Economics Section, The Graduate Institute of International Studies.

    Cited by:

    1. LanFen Chu & Michael McAleer & Chi-Chung Chen, 2011. "How Volatile is ENSO?," Documentos de Trabajo del ICAE 2011-21, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Ishtiaq Ahmad & Judit Oláh & József Popp & Domicián Máté, 2018. "Does Business Group Affiliation Matter for Superior Performance? Evidence from Pakistan," Sustainability, MDPI, vol. 10(9), pages 1-19, August.
    3. Chen, P-Y. & Chang, C-L. & Chen, C-C. & McAleer, M.J., 2010. "Modeling the Effect of Oil Price on Global Fertilizer Prices," Econometric Institute Research Papers EI 2010-56, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Ping-Yu Chen & Chia-Lin Chang & Chi-Chung Chen & Michael McAleer, 2010. "Modeling the Volatility in Global Fertilizer Prices," KIER Working Papers 705, Kyoto University, Institute of Economic Research.
    5. Daniel Cupriak & Katarzyna Kuziak & Tomasz Popczyk, 2020. "Risk Management Opportunities between Socially Responsible Investments and Selected Commodities," Sustainability, MDPI, vol. 12(5), pages 1-20, March.
    6. Borja Diez-Cañamero & Tania Bishara & Jose Ramon Otegi-Olaso & Rikardo Minguez & José María Fernández, 2020. "Measurement of Corporate Social Responsibility: A Review of Corporate Sustainability Indexes, Rankings and Ratings," Sustainability, MDPI, vol. 12(5), pages 1-36, March.
    7. McAleer, Michael, 1994. "Sherlock Holmes and the Search for Truth: A Diagnostic Tale," Journal of Economic Surveys, Wiley Blackwell, vol. 8(4), pages 317-370, December.
    8. Viorica Chirila, 2013. "Analysis Of The Returns And Volatility Of The Environmental Stock Leaders," CES Working Papers, Centre for European Studies, Alexandru Ioan Cuza University, vol. 5(3), pages 359-377, September.
    9. Keuzenkamp, H.A. & McAleer, M., 1994. "Simplicity, scientific inference and econometric modelling," Discussion Paper 1994-56, Tilburg University, Center for Economic Research.
    10. Hoti, Suhejla & McAleer, Michael & Pauwels, Laurent L., 2008. "Multivariate volatility in environmental finance," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 189-199.
    11. Steven Cook, 2001. "Observations on the practice of data-mining: comments on the JEM symposium," Journal of Economic Methodology, Taylor & Francis Journals, vol. 8(3), pages 415-419.
    12. S. Sudha, 2015. "Risk-return and Volatility analysis of Sustainability Index in India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 17(6), pages 1329-1342, December.
    13. Sadorsky, Perry, 2014. "Modeling volatility and conditional correlations between socially responsible investments, gold and oil," Economic Modelling, Elsevier, vol. 38(C), pages 609-618.

  14. Hans Genberg & Laurent Pauwels, 2003. "Inlation in Hong Kong, SAR- In Search of a Transmission Mechanism," Working Papers 012003, Hong Kong Institute for Monetary Research.

    Cited by:

    1. Paul D. McNelis, 2009. "Structural Change and Counterfactual Inflation-Targeting in Hong Kong," Working Papers 232009, Hong Kong Institute for Monetary Research.
    2. Hans Genberg, 2003. "Foreign versus domestic factors as sources of macroeconomic fluctuations in Hong Kong," IHEID Working Papers 05-2003, Economics Section, The Graduate Institute of International Studies.
    3. Kwan, Yum K. & Leung, Charles Ka Yui & Dong, Jinyue, 2015. "Comparing consumption-based asset pricing models: The case of an Asian city," Journal of Housing Economics, Elsevier, vol. 28(C), pages 18-41.
    4. Hans Genberg & Laurent L. Pauwels, 2003. "An Open Economy New Keynesian Phillips Curve: Evidence from Hong Kong," IHEID Working Papers 03-2003, Economics Section, The Graduate Institute of International Studies.
    5. Gerlach-Kristen, Petra, 2006. "Internal and external shocks in Hong Kong: Empirical evidence and policy options," Economic Modelling, Elsevier, vol. 23(1), pages 56-75, January.
    6. Echeverria Garaigorta, Paulina Elisa & Iza Padilla, María Amaya, 2010. "Prices and the Real Exchange Rate in Hong Kong: 1985-2006," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    7. Weshah A. Razzak, 2003. "Wage-Price Dynamics, the Labour Market and Deflation in Hong Kong," Working Papers 242003, Hong Kong Institute for Monetary Research.

  15. Hans Genberg & Laurent L. Pauwels, 2003. "An Open Economy New Keynesian Phillips Curve: Evidence from Hong Kong," IHEID Working Papers 03-2003, Economics Section, The Graduate Institute of International Studies.

    Cited by:

    1. Kai Liu, 2014. "Public Finances, Business Cycles and Structural Fiscal Balances," Cambridge Working Papers in Economics 1411, Faculty of Economics, University of Cambridge.
    2. Somayeh Mardaneh, 2015. "Inflation Dynamics in a Dutch Disease Economy," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(3), pages 295-324, Autumn.
    3. Agenor, Pierre-Richard & Bayraktar, Nihal, 2003. "Contracting models of the Phillips curve - empirical estimates for Middle-income countries," Policy Research Working Paper Series 3139, The World Bank.
    4. Faith Christian Cacnio, 2013. "Analysing inflation dynamics in the Philippines using the new Keynesian Phililips curve," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 50(2), pages 53-82, December.
    5. Pami Dua, 2009. "Determination of Inflation in an Open Economy Phillips Curve Framework: The Case of Developed and Developing Asian Countries," Working Papers id:1973, eSocialSciences.
    6. Michael Cheng & Wai-Yip Alex Ho, 2009. "A Structural Investigation into the Price and Wage Dynamics in Hong Kong," Working Papers 0920, Hong Kong Monetary Authority.
    7. Blagov, Boris & Funke, Michael, 2013. "The regime-dependent evolution of credibility: A fresh look at Hong Kong s linked exchange rate system," BOFIT Discussion Papers 24/2013, Bank of Finland Institute for Emerging Economies (BOFIT).
    8. Michael K. Salemi, 2007. "Long-run and Cyclic Movements in the Unemployment Rate in Hong Kong: A Dynamic, General Equilibrium Approach," Working Papers 192007, Hong Kong Institute for Monetary Research.
    9. Marcelo Sánchez, 2010. "What Drives Business Cycles and International Trade in Emerging Market Economies?," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 28(61), pages 198-271, August.
    10. Pym Manopimoke, 2012. "Hong Kong Inflation Dynamics: Trend and Cycle Relationships with the U.S. and China," Working Papers 232012, Hong Kong Institute for Monetary Research.
    11. Sigal Ribon, 2004. "A New Phillips Curve for Israel," Bank of Israel Working Papers 2004.11, Bank of Israel.
    12. Somayeh Mardaneh, 2012. "Inflation Dynamics in a Dutch Disease Economy," Discussion Papers in Economics 12/25, Division of Economics, School of Business, University of Leicester.
    13. Vararat Khemangkorn & Roong Poshyananda Mallikamas & Pranee Sutthasri, 2008. "Inflation Dynamics and Implications on Monetary Policy," Working Papers 2008-02, Monetary Policy Group, Bank of Thailand.

Articles

  1. Chan, Felix & Pauwels, Laurent L., 2018. "Some theoretical results on forecast combinations," International Journal of Forecasting, Elsevier, vol. 34(1), pages 64-74.

    Cited by:

    1. Smyl, Slawek, 2020. "A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting," International Journal of Forecasting, Elsevier, vol. 36(1), pages 75-85.
    2. Zhen Chu & Mingwang Cheng & Ning Neil Yu, 2022. "Development potential of Chinese smart cities and its spatio‐temporal pattern: A new hybrid MADM method using combination weight," Growth and Change, Wiley Blackwell, vol. 53(4), pages 1546-1566, December.
    3. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    4. Saidjon Shiralievich Tavarov & Alexander Sidorov & Zsolt Čonka & Murodbek Safaraliev & Pavel Matrenin & Mihail Senyuk & Svetlana Beryozkina & Inga Zicmane, 2023. "Control of Operational Modes of an Urban Distribution Grid under Conditions of Uncertainty," Energies, MDPI, vol. 16(8), pages 1-18, April.
    5. Pinto, Jeronymo Marcondes & Marçal, Emerson Fernandes, 2019. "Cross-validation based forecasting method: a machine learning approach," Textos para discussão 498, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    6. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2019. "Robust optimization of forecast combinations," International Journal of Forecasting, Elsevier, vol. 35(3), pages 910-926.
    7. 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.
    8. Chuanhua Wei & Chenping Du & Nana Zheng, 2020. "A Changing Weights Spatial Forecast Combination Approach with an Application to Housing Price Prediction," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 12(4), pages 1-11, April.
    9. Xin Gao & Xiaobing Li & Bing Zhao & Weijia Ji & Xiao Jing & Yang He, 2019. "Short-Term Electricity Load Forecasting Model Based on EMD-GRU with Feature Selection," Energies, MDPI, vol. 12(6), pages 1-18, March.
    10. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
    11. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
    12. Wang, Yudong & Hao, Xianfeng & Wu, Chongfeng, 2021. "Forecasting stock returns: A time-dependent weighted least squares approach," Journal of Financial Markets, Elsevier, vol. 53(C).
    13. Grzegorz Dudek, 2022. "A Comprehensive Study of Random Forest for Short-Term Load Forecasting," Energies, MDPI, vol. 15(20), pages 1-19, October.
    14. Chan, Felix & Pauwels, Laurent, 2019. "Equivalence of optimal forecast combinations under affine constraints," Working Papers BAWP-2019-02, University of Sydney Business School, Discipline of Business Analytics.
    15. Kourentzes, Nikolaos & Barrow, Devon & Petropoulos, Fotios, 2019. "Another look at forecast selection and combination: Evidence from forecast pooling," International Journal of Production Economics, Elsevier, vol. 209(C), pages 226-235.
    16. Aysun Kapucugil Ikiz & Gizem Halil Utma, 2023. "Combined Forecasts of Intermittent Demand for Stock-keeping Units (SKUs)," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 9(1), pages 1-31, June.
    17. Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.
    18. Ji Wu & Xian Cheng & Stephen Shaoyi Liao, 2020. "Tourism forecast combination using the stochastic frontier analysis technique," Tourism Economics, , vol. 26(7), pages 1086-1107, November.
    19. 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.
    20. Spiliotis, Evangelos & Nikolopoulos, Konstantinos & Assimakopoulos, Vassilios, 2019. "Tales from tails: On the empirical distributions of forecasting errors and their implication to risk," International Journal of Forecasting, Elsevier, vol. 35(2), pages 687-698.
    21. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.

  2. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    See citations under working paper version above.
  3. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.

    Cited by:

    1. Li, Li & Kang, Yanfei & Li, Feng, 2023. "Bayesian forecast combination using time-varying features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1287-1302.
    2. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    3. Li, Jingrui & Wang, Rui & Wang, Jianzhou & Li, Yifan, 2018. "Analysis and forecasting of the oil consumption in China based on combination models optimized by artificial intelligence algorithms," Energy, Elsevier, vol. 144(C), pages 243-264.
    4. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    5. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    6. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Working Papers halshs-01317974, HAL.
    7. Edward S. Knotek & Saeed Zaman, 2020. "Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach," Working Papers 20-31, Federal Reserve Bank of Cleveland.
    8. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    9. Pauwels, Laurent, 2019. "Predicting China’s Monetary Policy with Forecast Combinations," Working Papers BAWP-2019-07, University of Sydney Business School, Discipline of Business Analytics.
    10. Knut Are Aastveit & James Mitchell & Francesco Ravazzolo & Herman van Dijk, 2018. "The Evolution of Forecast Density Combinations in Economics," Tinbergen Institute Discussion Papers 18-069/III, Tinbergen Institute.
    11. 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.
    12. McAdam, Peter & Warne, Anders, 2020. "Density forecast combinations: the real-time dimension," Working Paper Series 2378, European Central Bank.

  4. Pauwels, Laurent & Vasnev, Andrey, 2014. "Forecast combination for U.S. recessions with real-time data," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 138-148.
    See citations under working paper version above.
  5. Andrey Vasnev & Margaret Skirtun & Laurent Pauwels, 2013. "Forecasting Monetary Policy Decisions in Australia: A Forecast Combinations Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(2), pages 151-166, March.

    Cited by:

    1. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 02/2013, University of Sydney Business School, Discipline of Business Analytics.
    2. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    3. Charalampos Stasinakis & Georgios Sermpinis & Konstantinos Theofilatos & Andreas Karathanasopoulos, 2016. "Forecasting US Unemployment with Radial Basis Neural Networks, Kalman Filters and Support Vector Regressions," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 569-587, April.
    4. Pauwels, Laurent, 2019. "Predicting China’s Monetary Policy with Forecast Combinations," Working Papers BAWP-2019-07, University of Sydney Business School, Discipline of Business Analytics.
    5. Chan, Felix & Pauwels, Laurent L. & Wongsosaputro, Johnathan, 2013. "The impact of serial correlation on testing for structural change in binary choice model: Monte Carlo evidence," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 175-189.

  6. Chan, Felix & Pauwels, Laurent L. & Wongsosaputro, Johnathan, 2013. "The impact of serial correlation on testing for structural change in binary choice model: Monte Carlo evidence," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 175-189.

    Cited by:

    1. Michael McAleer & Felix Chan & Les Oxley, 2013. "Modelling and Simulation: An Overview," Tinbergen Institute Discussion Papers 13-069/III, Tinbergen Institute.

  7. Liu, Li-Gang & Pauwels, Laurent L., 2012. "Do external political pressures affect the Renminbi exchange rate?," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1800-1818.
    See citations under working paper version above.
  8. Pauwels Laurent L. & Chan Felix & Mancini Griffoli Tommaso, 2012. "Testing for Structural Change in Heterogeneous Panels with an Application to the Euro's Trade Effect," Journal of Time Series Econometrics, De Gruyter, vol. 4(2), pages 1-35, November.

    Cited by:

    1. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    2. Oualid Bada & Alois Kneip & Dominik Liebl & Tim Mensinger & James Gualtieri & Robin C. Sickles, 2021. "A Wavelet Method for Panel Models with Jump Discontinuities in the Parameters," Papers 2109.10950, arXiv.org.
    3. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2015. "Estimation of Heterogeneous Panels with Structural Breaks," Center for Policy Research Working Papers 179, Center for Policy Research, Maxwell School, Syracuse University.
    4. Aparna Sengupta, 2017. "Testing for a Structural Break in a Spatial Panel Model," Econometrics, MDPI, vol. 5(1), pages 1-17, March.
    5. Yiannis Karavias & Elias Tzavalis, 2013. "The power performance of fixed-T panel unit root tests allowing for structural breaks," Discussion Papers 13/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    6. Jiang, Peiyun & Kurozumi, Eiji, 2021. "A new test for common breaks in heterogeneous panel data models," Discussion paper series HIAS-E-107, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    7. Apergis, Nicholas, 2022. "Money Market Funds (MMFs) and the Covid-19 pandemic: Has the MMLF benefited money markets?," Finance Research Letters, Elsevier, vol. 46(PA).
    8. Esposito, Piero & Messori, Marcello, 2016. "Improved Structural Competitiveness or Deep Recession? On the recent macroeconomic rebalances in the EMU," LEAP Working Papers 2016/3, Luiss Institute for European Analysis and Policy.

  9. Chan, Felix & Pauwels, Laurent, 2011. "Model specification in panel data unit root tests with an unknown break," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1299-1309.

    Cited by:

    1. Yiannis Karavias & Elias Tzavalis, 2017. "Local power of panel unit root tests allowing for structural breaks," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1123-1156, November.
    2. Rickard Sandberg, 2016. "Testing for unit roots in nonlinear heterogeneous panels with smoothly changing trends: an application to Scandinavian unemployment rates," Empirical Economics, Springer, vol. 51(3), pages 1053-1083, November.
    3. Yiannis Karavias & Elias Tzavalis, 2013. "The power performance of fixed-T panel unit root tests allowing for structural breaks," Discussion Papers 13/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    4. Karavias, Yiannis & Tzavalis, Elias, 2014. "Testing for unit roots in short panels allowing for a structural break," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 391-407.

  10. Hoti, Suhejla & McAleer, Michael & Pauwels, Laurent L., 2008. "Multivariate volatility in environmental finance," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 189-199.

    Cited by:

    1. Yen-Hsien Lee, 2013. "The Predictability of the Socially Responsible Investment Index: A New TMDCC Approach," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(1), pages 027-034, June.

  11. Dong He & Laurent L. Pauwels, 2008. "What Prompts the People's Bank of China to Change Its Monetary Policy Stance? Evidence from a Discrete Choice Model," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 16(6), pages 1-21, November.
    See citations under working paper version above.
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