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Laurent L Pauwels

Citations

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Working papers

  1. Imbs, Jean & Pauwels, Laurent, 2023. "An Empirical Approximation of the Effects of Trade Sanctions with an Application to Russia," CEPR Discussion Papers 18064, C.E.P.R. Discussion Papers.

    Cited by:

    1. Benchimol, Jonathan & Palumbo, Luigi, 2024. "Sanctions and Russian online prices," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 225, pages 483-521.
    2. Haishi Li & Zhi Li & Ziho Park & Yulin Wang & Jing Wu, 2024. "To Comply or Not to Comply: Understanding Neutral Country Supply Chain Responses to Russian Sanctions," CESifo Working Paper Series 11110, CESifo.
    3. Evgenii Monastyrenko & Pierre M. Picard, 2023. "Welfare implications of trade sanctions against Russia," DEM Discussion Paper Series 23-19, Department of Economics at the University of Luxembourg.
    4. Mukesh Eswaran, 2024. "A theory of hegemon-provoked instability, with an application to NATO and the Ukraine-Russia war," Indian Economic Review, Springer, vol. 59(2), pages 349-383, December.
    5. Mavrigiannakis, Konstantinos & Sakkas, Stelios, 2024. "EU sanctions on Russia and implications for a small open economy: the case of Cyprus," LSE Research Online Documents on Economics 125336, London School of Economics and Political Science, LSE Library.
    6. Ferrari Minesso, Massimo & Lebastard, Laura & Bagur, Olga Triay, 2026. "Interlinking payment systems and trade flows," Working Paper Series 3202, European Central Bank.
    7. Erdal Yalcin & Gabriel Felbermayr & Heider Kariem & Aleksandra Kirilakha & Ohyun Kwon & Constantinos Syropoulos & Yoto Yotov, 2025. "The Global Sanctions Data Base - Release 4: The Heterogeneous Effects of the Sanctions on Russia," Working Papers 2025002, Center for Global Policy Analysis, LeBow College of Business, Drexel University.

  2. Imbs, Jean & Pauwels, Laurent, 2022. "Measuring Openness," CEPR Discussion Papers 17230, C.E.P.R. Discussion Papers.
    • Jean Imbs & Laurent L. Pauwels, 2020. "Measuring Openness," CAMA Working Papers 2020-48, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, revised Jan 2023.

    Cited by:

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

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

    Cited by:

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

  4. Laurent Pauwels & Peter Radchenko & Andrey L. Vasnev, 2020. "High Moment Constraints for Predictive Density Combination," CAMA Working Papers 2020-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, revised Jun 2023.

    Cited by:

    1. 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.
    2. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    3. Chen, Yi-Ting & Liu, Chu-An & Su, Jiun-Hua, 2025. "Bregman model averaging for forecast combination," Journal of Econometrics, Elsevier, vol. 251(C).
    4. 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.

  5. 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 & 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.
    2. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    3. 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.
    4. 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.

  6. 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. 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.
    3. Lupu, Radu & Călin, Adrian Cantemir & Dumitrescu, Dan Gabriel & Lupu, Iulia, 2025. "Introducing a novel fragility index for assessing financial stability amid asset bubble episodes," The North American Journal of Economics and Finance, Elsevier, vol. 75(PA).
    4. Ahmar, Ansari Saleh, 2019. "Reliability Test of SutteARIMA to Forecast Artificial Data," OSF Preprints 9zn7v, Center for Open Science.

  7. 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.

  8. 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. Jungyeon Yoon & Juanjuan Fan, 2024. "Forecasting the direction of the Fed's monetary policy decisions using random forest," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2848-2859, November.
    2. Su, Shiwei & Ahmad, Ahmad Hassan & Wood, Justine & Jia, Songbo, 2025. "Monetary policy analysis using natural language processing: Evaluating the People's Bank of China's minutes and report summary with the Taylor Rule," Economic Modelling, Elsevier, vol. 149(C).
    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.
    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. 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.
    6. Kim, Hyerim & Kang, Kyu Ho, 2022. "The Bank of Korea watch," Journal of International Money and Finance, Elsevier, vol. 126(C).

  9. 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. Masahiro Kawai & Li-Gang Liu, 2015. "Trilemma Challenges for the People's Republic of China," Asian Development Review, MIT Press, vol. 32(1), pages 49-89, March.
    2. Huachen Li & Tiezheng Song, 2024. "Regime dependent dynamics of parallel and official exchange markets in China: evidence from cryptocurrency," Applied Economics, Taylor & Francis Journals, vol. 56(41), pages 4952-4973, September.
    3. Antonio Afonso & Valérie Mignon & Jamel Saadaoui, 2024. "On the time-varying impact of China’s bilateral political relations on its trading partners: “doux commerce” or “trade follows the flag”?," Working Papers of BETA 2024-17, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    4. 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.
    5. Chunming Shen, 2022. "Digital RMB, RMB Internationalization and Sustainable Development of the International Monetary System," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    6. 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).
    7. 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).
    8. 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.
    9. 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.
    10. Zhang, Qisi & Frömmel, Michael & Baidoo, Edwin, 2024. "Donald Trump's tweets, political value judgment, and the Renminbi exchange rate," International Review of Financial Analysis, Elsevier, vol. 93(C).
    11. 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).
    12. Chen Zhang & Ying Fang & Linlin Niu, 2022. "Changing anchor of the renminbi: A Bayesian learning approach to the decade-long transition," Working Papers 2022-08-24, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    13. 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).
    14. 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.
    15. Valérie Mignon & António Afonso & Jamel Saadaoui, 2023. "On the time-varying impact of China's bilateral political relations on its trading partners (1960-2022)," EconomiX Working Papers 2023-33, University of Paris Nanterre, EconomiX.
    16. 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.
    17. 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).
    18. 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.
    19. López Noria Gabriela & Bush Georgia, 2019. "Uncertainty and Exchange Rate Volatility: the Case of Mexico," Working Papers 2019-12, Banco de México.
    20. 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.
    21. 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).
    22. 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.
    23. 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.
    24. 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.
    25. 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).
    26. 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.
    27. 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.

  10. 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. Dong He & Paul Luk, 2013. "A Model of Chinese Capital Account Liberalisation," Working Papers 122013, Hong Kong Institute for Monetary Research.
    2. 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.
    3. 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.
    4. Peter Tillmann, 2014. "Unconventional Monetary Policy Shocks and the Spillovers to Emerging Markets," Working Papers 182014, Hong Kong Institute for Monetary Research.
    5. Klingelhöfer, Jan & Sun, Rongrong, 2017. "Macroprudential Policy, Central Banks and Financial Stability: Evidence from China," MPRA Paper 79033, University Library of Munich, Germany.
    6. Shu, Chang & He, Dong & Cheng, Xiaoqiang, 2015. "One currency, two markets: the renminbi's growing influence in Asia-Pacific," China Economic Review, Elsevier, vol. 33(C), pages 163-178.
    7. Hongyi Chen & Kenneth ChowAuthor-Workplace-Name: Hong Kong Monetary Authority & Peter Tillmann, 2016. "The Effectiveness of Monetary Policy in China: Evidence from a Qual VAR," Working Papers 062016, Hong Kong Institute for Monetary Research.
    8. Hyeongwoo Kim & Wen Shi, 2016. "The Determinants of the Benchmark Interest Rates in China: A Discrete Choice Model Approach," Auburn Economics Working Paper Series auwp2016-14, Department of Economics, Auburn University.
    9. 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.
    10. Angrick, Stefan & Naoyuki, Yoshino, 2018. "From window guidance to interbank rates: Tracing the transition of monetary policy in Japan and China," BOFIT Discussion Papers 4/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
    11. Sun, Rongrong, 2014. "What Measures Chinese Monetary Policy?," MPRA Paper 58514, University Library of Munich, Germany.
    12. Dong He & Honglin Wang & Xiangrong Yu, 2014. "Interest Rate Determination in China: Past, Present, and Future," Working Papers 042014, Hong Kong Institute for Monetary Research.
    13. Doan Ngoc Thang & Pham Thi Hoang Anh & Trinh Long & Do Phy Dong & Luong Van Dat, 2022. "Monetary Stance and Favorableness of Monetary Policy in the Media: The Case of Viet Nam," ADBI Working Papers 1325, Asian Development Bank Institute.
    14. 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.
    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. Su, Shiwei & Ahmad, Ahmad Hassan & Wood, Justine & Jia, Songbo, 2025. "Monetary policy analysis using natural language processing: Evaluating the People's Bank of China's minutes and report summary with the Taylor Rule," Economic Modelling, Elsevier, vol. 149(C).
    17. Körner, Finn Marten & Ehnts, Dirk H., 2013. "Chinese monetary policy – from theory to practice," MPRA Paper 44264, University Library of Munich, Germany.
    18. 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.
    19. Klingelhöfer, Jan & Sun, Rongrong, 2018. "China's regime-switching monetary policy," Economic Modelling, Elsevier, vol. 68(C), pages 32-40.
    20. 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.
    21. Alex, Dony, 2021. "Anchoring of inflation expectations in large emerging economies," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    22. 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).
    23. Sun, Rongrong, 2012. "Does Monetary Policy Matter in China? A Narrative Approach," MPRA Paper 45023, University Library of Munich, Germany.
    24. 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.
    25. He, Dong & Wang, Honglin, 2012. "Dual-track interest rates and the conduct of monetary policy in China," China Economic Review, Elsevier, vol. 23(4), pages 928-947.
    26. 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.
    27. 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.
    28. 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.
    29. Sun, Rongrong, 2018. "Monetary Policy Announcements and Market Interest Rates’ Response: Evidence from China," MPRA Paper 87703, University Library of Munich, Germany.
    30. 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.
    31. 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.
    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.
    33. Sun, Rongrong, 2015. "A Narrative Indicator of Monetary Conditions in China," MPRA Paper 64166, University Library of Munich, Germany.

  11. 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, 2011. "Stock market wealth effects in an estimated DSGE model for Hong Kong," Economic Modelling, Elsevier, vol. 28(1), pages 316-334.
    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.

  12. 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, 2011. "Stock market wealth effects in an estimated DSGE model for Hong Kong," Economic Modelling, Elsevier, vol. 28(1), pages 316-334.

  13. Félix Chan & Tommaso Mancini-Griffoli & Laurent L. Pauwels, 2006. "Stability tests for heterogeneous panel data," PSE Working Papers halshs-00589114, HAL.

    Cited by:

    1. 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.
    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. 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.

  14. 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. 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.
    2. 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.
    3. Saten Kumar & Mamta B. Chowdhury & B. Bhaskara Rao, 2013. "Demand for money in the selected OECD countries: a time series panel data approach and structural breaks," Applied Economics, Taylor & Francis Journals, vol. 45(14), pages 1767-1776, May.
    4. 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.
    5. Puzzello, Laura & Gomis-Porqueras, Pedro, 2018. "Winners and losers from the €uro," European Economic Review, Elsevier, vol. 108(C), pages 129-152.
    6. 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.
    7. 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.
    8. Rao, B. Bhaskara & Tamazian, Artur & Kumar, Saten, 2010. "Systems GMM estimates of the Feldstein-Horioka puzzle for the OECD countries and tests for structural breaks," Economic Modelling, Elsevier, vol. 27(5), pages 1269-1273, September.
    9. 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.
    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. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Christian Henn & Theo S. Eicher, 2009. "One Money, One Market—A Revised Benchmark," IMF Working Papers 2009/186, International Monetary Fund.
    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..

  15. 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. Pierre L. Siklos & Diana N. Weymark, 2007. "Is Sterilized Intervention Effective? New International Evidence," Working Papers 142007, Hong Kong Institute for Monetary Research.
    2. Canry, Nicolas & Fouquau, Julien & Lechevalier, Sébastien, 2007. "Price Dynamics in Japan (1981-2001): A Structural Analysis of Mechanisms in the Goods and Labor Markets," Discussion Paper Series a493, Institute of Economic Research, Hitotsubashi University.
    3. Li-gang Liu & Andrew Tsang, 2008. "Exchange Rate Pass-Through to Domestic Inflation in Hong Kong," Working Papers 0802, Hong Kong Monetary Authority.
    4. Hans Genberg, 2005. "External Shocks, Transmission Mechanisms and Deflation in Asia," Working Papers 062005, Hong Kong Institute for Monetary Research.
    5. James Yetman, 2009. "Hong Kong Consumer Prices are Flexible," Working Papers 052009, Hong Kong Institute for Monetary Research.
    6. 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.
    7. Gregor W. Smith, 2006. "The spectre of deflation: a review of empirical evidence," Canadian Journal of Economics, Canadian Economics Association, vol. 39(4), pages 1041-1072, November.
    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.

  16. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Chu, L. & McAleer, M.J. & Chen, C-C., 2009. "How Volatile is ENSO?," Econometric Institute Research Papers EI 2009-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. 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.
    7. 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.
    8. 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.
    9. Sadorsky, Perry, 2014. "Modeling volatility and conditional correlations between socially responsible investments, gold and oil," Economic Modelling, Elsevier, vol. 38(C), pages 609-618.
    10. 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.
    11. Chen, P-Y. & Chang, C-L. & Chen, C-C. & McAleer, M.J., 2010. "Modeling the Volatility in Global Fertilizer Prices," Econometric Institute Research Papers EI 2010-42, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. 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.
    13. Keuzenkamp, H.A. & McAleer, M., 1994. "Simplicity, scientific inference and econometric modelling," Discussion Paper 1994-56, Tilburg University, Center for Economic Research.

  17. 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 & 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.
    3. 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.
    4. 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.
    5. Kwan, Yum K. & Leung, Charles Ka Yui & Dong, Jinyue, 2014. "Comparing Consumption-based Asset Pricing Models: The Case of an Asian City," MPRA Paper 60513, University Library of Munich, Germany.
    6. Weshah A. Razzak, 2003. "Wage-Price Dynamics, the Labour Market and Deflation in Hong Kong," Working Papers 242003, Hong Kong Institute for Monetary Research.
    7. Hans Genberg, 2003. "Foreign Versus Domestic Factors as Souces of Macroeconomic Fluctuations in Hong Kong," Working Papers 172003, Hong Kong Institute for Monetary Research.

  18. 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. Burhan Biçer & Almila Burgac Cil, 2023. "Symmetric and Asymmetric Dynamics of Output Gap and Inflation Relation for Turkish Economy," Prague Economic Papers, Prague University of Economics and Business, vol. 2023(5), pages 520-549.
    2. Blagov, Boris & Funke, Michael, 2015. "The regime-dependent evolution of credibility: A fresh look at Hong Kong's linked exchange rate system," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112819, Verein für Socialpolitik / German Economic Association.
    3. 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.
    4. 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.
    5. Sigal Ribon, 2004. "A New Phillips Curve for Israel," Bank of Israel Working Papers 2004.11, Bank of Israel.
    6. 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.
    7. 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.
    8. Kai Liu, 2014. "Public Finances, Business Cycles and Structural Fiscal Balances," Cambridge Working Papers in Economics 1411, Faculty of Economics, University of Cambridge.
    9. 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.
    10. 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.
    11. 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.
    12. Pierre-Richard Agénor & Nihal Bayraktar, 2008. "Contracting Models of the Phillips Curve Empirical Estimates for Middle-Income Countries," Centre for Growth and Business Cycle Research Discussion Paper Series 94, Economics, The University of Manchester.
    13. Marcelo Sánchez, 2010. "What Drives Business Cycles and International Trade in Emerging Market Economies?," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 28(61), pages 198-271, August.

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. 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).
    4. Alexandra Bozhechkova & Urmat Dzhunkeev, 2024. "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, vol. 83(3), pages 45-69, September.
    5. 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.
    6. 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.
    7. 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.
    8. Han Su & Xiaojia Guo & Xiaoke Zhang, 2026. "Regularized Ensemble Forecasting for Learning Weights from Historical and Current Forecasts," Papers 2602.11379, arXiv.org.
    9. 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.
    10. 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.
    11. Li, Haohua & Mei, Yuhe & Hao, Xianfeng & Chen, Zhuo, 2024. "Out-of-sample equity premium predictability: An EMD-denoising based model," Pacific-Basin Finance Journal, Elsevier, vol. 88(C).
    12. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2020. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2020-01, University of Sydney Business School, Discipline of Business Analytics.
    13. 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.
    14. Eraslan, Sercan & Nöller, Marvin, 2020. "Recession probabilities falling from the STARs," Discussion Papers 08/2020, Deutsche Bundesbank.
    15. 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.
    16. Pietro Giorgio Lovaglio, 2025. "Cross‐Learning With Panel Data Modeling for Stacking and Forecast Time Series Employment in Europe," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 753-780, March.
    17. Zhikai Zhang & Yaojie Zhang & Yudong Wang, 2024. "Forecasting the equity premium using weighted regressions: Does the jump variation help?," Empirical Economics, Springer, vol. 66(5), pages 2049-2082, May.
    18. 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.
    19. Grzegorz Dudek, 2022. "A Comprehensive Study of Random Forest for Short-Term Load Forecasting," Energies, MDPI, vol. 15(20), pages 1-19, October.
    20. 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.
    21. 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.
    22. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2019. "Robust optimization of forecast combinations," International Journal of Forecasting, Elsevier, vol. 35(3), pages 910-926.
    23. Francis X. Diebold & Aaron Mora & Minchul Shin, 2026. "On the Wisdom of Crowds (of Economists)," Working Papers 26-14, Federal Reserve Bank of Philadelphia.
    24. 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.
    25. 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.
    26. 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).
    27. 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.
    28. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2024. "Climate Risks and Forecastability of US Inflation: Evidence from Dynamic Quantile Model Averaging," Working Papers 202420, University of Pretoria, Department of Economics.
    29. Chengwang Liao & Zhentao Shi & Yapeng Zheng, 2025. "A Relaxation Approach to Synthetic Control," Papers 2508.01793, arXiv.org.
    30. Li Liu & Xianfeng Hao & Yudong Wang, 2024. "Solving the Forecast Combination Puzzle Using Double Shrinkages," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 714-741, June.
    31. Jesús Molina‐Muñoz & Andrés Mora‐Valencia & Javier Perote, 2024. "Predicting carbon and oil price returns using hybrid models based on machine and deep learning," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
    32. Umair Muneer Butt & Sukumar Letchmunan & Fadratul Hafinaz Hassan & Tieng Wei Koh, 2022. "Hybrid of deep learning and exponential smoothing for enhancing crime forecasting accuracy," PLOS ONE, Public Library of Science, vol. 17(9), pages 1-22, September.

  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. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
    2. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01317974, HAL.
    3. 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.
    4. 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.
    5. McAdam, Peter & Warne, Anders, 2020. "Density forecast combinations: the real-time dimension," Working Paper Series 2378, European Central Bank.
    6. 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.
    7. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España.
    8. Chen, Yi-Ting & Liu, Chu-An & Su, Jiun-Hua, 2025. "Bregman model averaging for forecast combination," Journal of Econometrics, Elsevier, vol. 251(C).
    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. 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.
    13. 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.

  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. 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.
    2. 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.
    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. 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. 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.

  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. Karavias, Yiannis & Tzavalis, Elias, 2013. "The Power Performance of Fixed-T Panel Unit Root Tests allowing for Structural Breaks," MPRA Paper 46012, University Library of Munich, Germany.
    2. 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).
    3. Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    4. 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.
    5. 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.
    6. Jiang, Peiyun & Kurozumi, Eiji, 2026. "A new test for common breaks in heterogeneous panel data models," Econometrics and Statistics, Elsevier, vol. 37(C), pages 87-125.
    7. 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.
    8. Aparna Sengupta, 2017. "Testing for a Structural Break in a Spatial Panel Model," Econometrics, MDPI, vol. 5(1), pages 1-17, March.
    9. Piero Esposito & Marcello Messori, 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. 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.
    2. Karavias, Yiannis & Tzavalis, Elias, 2013. "The Power Performance of Fixed-T Panel Unit Root Tests allowing for Structural Breaks," MPRA Paper 46012, University Library of Munich, Germany.
    3. 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.
    4. Akpolat, Ahmet Gökce & Bakırtaş, Tahsin, 2024. "The nonlinear impact of renewable energy, fossil energy and CO2 emissions on human development index for the eight developing countries," Energy, Elsevier, vol. 312(C).
    5. 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.

  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.
  12. Suhejla Hoti & Michael McAleer & Laurent L. Pauwels, 2007. "Measuring Risk In Environmental Finance," Journal of Economic Surveys, Wiley Blackwell, vol. 21(5), pages 970-998, December.

    Cited by:

    1. Marouane Nakhcha & Mamdouh Tlaty, 2023. "The Emergence of Green Finance in the Digital Age: Catalyst for a Sustainable and Innovative Economy [L'émergence de la finance verte à l'ère numérique: Catalyseur d'une économie durable et innovante]," Post-Print hal-04333883, HAL.
    2. Emil Andersson & Mahim Hoque & Md Lutfur Rahman & Gazi Salah Uddin & Ranadeva Jayasekera, 2022. "ESG investment: What do we learn from its interaction with stock, currency and commodity markets?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3623-3639, July.
    3. Kumar, Bipul & Sinha, Piyush Kumar & Shukla, P. R. & Abhishek, 2013. "Broadening the Concept of Sustainability and Measuring its Impact on Firm’s Performance," IIMA Working Papers WP2013-08-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    4. Felipe Arias Fogliano de Souza Cunha & Erick Meira de Oliveira & Renato J. Orsato & Marcelo Cabus Klotzle & Fernando Luiz Cyrino Oliveira & Rodrigo Goyannes Gusmão Caiado, 2020. "Can sustainable investments outperform traditional benchmarks? Evidence from global stock markets," Business Strategy and the Environment, Wiley Blackwell, vol. 29(2), pages 682-697, February.
    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. Tao, Hu & Zhuang, Shan & Xue, Rui & Cao, Wei & Tian, Jinfang & Shan, Yuli, 2022. "Environmental Finance: An Interdisciplinary Review," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    7. Patricia Crifo & Vanina D. Forget, 2015. "The Economics Of Corporate Social Responsibility: A Firm-Level Perspective Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 112-130, February.
    8. Olaf Weber, 2014. "Environmental, Social and Governance Reporting in China," Business Strategy and the Environment, Wiley Blackwell, vol. 23(5), pages 303-317, July.
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