IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v89y2024ipap524-542.html
   My bibliography  Save this article

The asymmetric relationships between the Bitcoin futures’ return, volatility, and trading volume

Author

Listed:
  • Kao, Yu-Sheng
  • Zhao, Kai
  • Chuang, Hwei-Lin
  • Ku, Yu-Cheng

Abstract

This study investigated the asymmetric contemporaneous and lead-lag relationships between return and trading volume as well as return volatility and volume on the Bitcoin futures by analyzing the threshold and smooth transition effects based on the logistic smooth transition regression (LSTR) model with the logistic smooth transition GJR-GARCH framework. The main findings demonstrated that the asymmetric and smooth transition effects existed in both the contemporaneous and lead-lag return-volume and volatility-volume relationships. There were also a one-trading-day to three-trading-day delayed effects from volume to return and volatility. The implication of the findings suggests that there are arbitrage opportunities for investors in the Bitcoin futures market. Furthermore, we confirm that the Mixture of Distribution Hypothesis (MDH) was a better theory than the Sequential Information Arrival Hypothesis (SIAH) in explaining the volatility-volume relationships on the Bitcoin futures. Our findings also showed that the speed of information transmission increased as it got closer to the current trading day. This evidence supported the MDH in the Bitcoin futures market.

Suggested Citation

  • Kao, Yu-Sheng & Zhao, Kai & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2024. "The asymmetric relationships between the Bitcoin futures’ return, volatility, and trading volume," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 524-542.
    • Handle: RePEc:eee:reveco:v:89:y:2024:i:pa:p:524-542
    DOI: 10.1016/j.iref.2023.07.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056023002216
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.iref.2023.07.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Eleanor Xu, Xiaoqing & Chen, Peter & Wu, Chunchi, 2006. "Time and dynamic volume-volatility relation," Journal of Banking & Finance, Elsevier, vol. 30(5), pages 1535-1558, May.
    2. McMillan, David G., 2007. "Non-linear forecasting of stock returns: Does volume help?," International Journal of Forecasting, Elsevier, vol. 23(1), pages 115-126.
    3. Woodward, George & Marisetty, Vijaya B., 2005. "Introducing non-linear dynamics to the two-regime market model: Evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 45(4-5), pages 559-581, September.
    4. Le, Van & Zurbruegg, Ralf, 2010. "The role of trading volume in volatility forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 533-555, December.
    5. Atsalakis, George S. & Atsalaki, Ioanna G. & Pasiouras, Fotios & Zopounidis, Constantin, 2019. "Bitcoin price forecasting with neuro-fuzzy techniques," European Journal of Operational Research, Elsevier, vol. 276(2), pages 770-780.
    6. Eric Girard & Rita Biswas, 2007. "Trading Volume and Market Volatility: Developed versus Emerging Stock Markets," The Financial Review, Eastern Finance Association, vol. 42(3), pages 429-459, August.
    7. Chang, Chia-Lin & Jimenez-Martin, Juan-Angel & McAleer, Michael & Amaral, Teodosio Perez, 2013. "The rise and fall of S&P500 variance futures," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 151-167.
    8. Anirut Pisedtasalasai & Abeyratna Gunasekarage, 2007. "Causal and Dynamic Relationships among Stock Returns, Return Volatility and Trading Volume: Evidence from Emerging markets in South-East Asia," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(4), pages 277-297, December.
    9. Kapetanios, George & Shin, Yongcheol & Snell, Andy, 2003. "Testing for a unit root in the nonlinear STAR framework," Journal of Econometrics, Elsevier, vol. 112(2), pages 359-379, February.
    10. Darrat, Ali F. & Zhong, Maosen & Cheng, Louis T.W., 2007. "Intraday volume and volatility relations with and without public news," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2711-2729, September.
    11. Harris, Lawrence, 1986. "Cross-Security Tests of the Mixture of Distributions Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(1), pages 39-46, March.
    12. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    13. Hammoudeh, Shawkat & McAleer, Michael, 2013. "Risk management and financial derivatives: An overview," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 109-115.
    14. Bouri, Elie & Lucey, Brian & Roubaud, David, 2020. "The volatility surprise of leading cryptocurrencies: Transitory and permanent linkages," Finance Research Letters, Elsevier, vol. 33(C).
    15. Khuntia, Sashikanta & Pattanayak, J.K., 2020. "Adaptive long memory in volatility of intra-day bitcoin returns and the impact of trading volume," Finance Research Letters, Elsevier, vol. 32(C).
    16. Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
    17. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    18. Ainhoa Zarraga, 2003. "GMM-based testing procedures of the mixture of distributions model," Applied Financial Economics, Taylor & Francis Journals, vol. 13(11), pages 841-848.
    19. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    20. Li, Haiqi & Zhong, Wanling & Park, Sung Y., 2016. "Generalized cross-spectral test for nonlinear Granger causality with applications to money–output and price–volume relations," Economic Modelling, Elsevier, vol. 52(PB), pages 661-671.
    21. Lai, Ya-Wen & Lin, Chiou-Fa & Tang, Mei-Ling, 2017. "Mispricing and trader positions in the S&P 500 index futures market," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 250-265.
    22. Ning, Cathy & Wirjanto, Tony S., 2009. "Extreme return-volume dependence in East-Asian stock markets: A copula approach," Finance Research Letters, Elsevier, vol. 6(4), pages 202-209, December.
    23. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2020. "News and return volatility of Chinese bank stocks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 1095-1105.
    24. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    25. Shen, Dehua & Li, Xiao & Zhang, Wei, 2018. "Baidu news information flow and return volatility: Evidence for the Sequential Information Arrival Hypothesis," Economic Modelling, Elsevier, vol. 69(C), pages 127-133.
    26. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    27. Bouri, Elie & Gupta, Rangan & Lahiani, Amine & Shahbaz, Muhammad, 2018. "Testing for asymmetric nonlinear short- and long-run relationships between bitcoin, aggregate commodity and gold prices," Resources Policy, Elsevier, vol. 57(C), pages 224-235.
    28. Kim, Dongcheol & Kon, Stanley J, 1994. "Alternative Models for the Conditional Heteroscedasticity of Stock Returns," The Journal of Business, University of Chicago Press, vol. 67(4), pages 563-598, October.
    29. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    30. Shi, Yanlin & Ho, Kin-Yip, 2021. "News sentiment and states of stock return volatility: Evidence from long memory and discrete choice models," Finance Research Letters, Elsevier, vol. 38(C).
    31. Lee, Bong-Soo & Rui, Oliver M., 2002. "The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence," Journal of Banking & Finance, Elsevier, vol. 26(1), pages 51-78, January.
    32. M. F. Omran & E. McKenzie, 2000. "Heteroscedasticity in stock returns data revisited: volume versus GARCH effects," Applied Financial Economics, Taylor & Francis Journals, vol. 10(5), pages 553-560.
    33. Balduzzi, Pierluigi & Elton, Edwin J. & Green, T. Clifton, 2001. "Economic News and Bond Prices: Evidence from the U.S. Treasury Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(4), pages 523-543, December.
    34. Smirlock, Michael & Starks, Laura, 1988. "An empirical analysis of the stock price-volume relationship," Journal of Banking & Finance, Elsevier, vol. 12(1), pages 31-41, March.
    35. Michael Smirlock & Laura Starks, 1985. "A Further Examination Of Stock Price Changes And Transaction Volume," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 8(3), pages 217-226, September.
    36. Darrat, Ali F. & Rahman, Shafiqur & Zhong, Maosen, 2003. "Intraday trading volume and return volatility of the DJIA stocks: A note," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 2035-2043, October.
    37. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    38. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    39. Tu, Anthony H. & Hsieh, Wen-Liang G. & Wu, Wei-Shao, 2016. "Market uncertainty, expected volatility and the mispricing of S&P 500 index futures," Journal of Empirical Finance, Elsevier, vol. 35(C), pages 78-98.
    40. Telli, Şahin & Chen, Hongzhuan, 2020. "Multifractal behavior in return and volatility series of Bitcoin and gold in comparison," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    41. Yu-Sheng Kao & Hao-Yang Sun & Chien-Chung Nieh & Kai Zhao, 2018. "Does microtherm boost pharmaceutical companies’ market capitalization returns?," Applied Economics, Taylor & Francis Journals, vol. 50(14), pages 1522-1535, March.
    42. Tribhuvan N. Puri & George C. Philippatos, 2008. "Asymmetric Volume‐Return Relation and Concentrated Trading in LIFFE Futures," European Financial Management, European Financial Management Association, vol. 14(3), pages 528-563, June.
    43. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    44. Kalev, Petko S. & Liu, Wai-Man & Pham, Peter K. & Jarnecic, Elvis, 2004. "Public information arrival and volatility of intraday stock returns," Journal of Banking & Finance, Elsevier, vol. 28(6), pages 1441-1467, June.
    45. Chen, Shiu-Sheng, 2012. "Revisiting the empirical linkages between stock returns and trading volume," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1781-1788.
    46. Park, Beum-Jo, 2010. "Surprising information, the MDH, and the relationship between volatility and trading volume," Journal of Financial Markets, Elsevier, vol. 13(3), pages 344-366, August.
    47. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    48. Carroll, Rachael & Kearney, Colm, 2015. "Testing the mixture of distributions hypothesis on target stocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 1-14.
    49. Kim, Wonse & Lee, Junseok & Kang, Kyungwon, 2020. "The effects of the introduction of Bitcoin futures on the volatility of Bitcoin returns," Finance Research Letters, Elsevier, vol. 33(C).
    50. Giampiero Gallo & Barbara Pacini, 2000. "The effects of trading activity on market volatility," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 163-175.
    51. Gebka, Bartosz & Wohar, Mark E., 2013. "Causality between trading volume and returns: Evidence from quantile regressions," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 144-159.
    52. Ruan, Qingsong & Meng, Lu & Lv, Dayong, 2021. "Effect of introducing Bitcoin futures on the underlying Bitcoin market efficiency: A multifractal analysis," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    53. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    54. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    55. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    56. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    57. Pyun, Chong Soo & Lee, Sa Young & Nam, Kiseok, 2000. "Volatility and information flows in emerging equity market: A case of the Korean Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 9(4), pages 405-420.
    58. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
    59. Hutson, Elaine & Kearney, Colm & Lynch, Margaret, 2008. "Volume and skewness in international equity markets," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1255-1268, July.
    60. Jennings, Robert H & Starks, Laura T & Fellingham, John C, 1981. "An Equilibrium Model of Asset Trading with Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 36(1), pages 143-161, March.
    61. Wang, Jying-Nan & Liu, Hung-Chun & Hsu, Yuan-Teng, 2020. "Time-of-day periodicities of trading volume and volatility in Bitcoin exchange: Does the stock market matter?," Finance Research Letters, Elsevier, vol. 34(C).
    62. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    63. Fleming, Jeff & Kirby, Chris, 2011. "Long memory in volatility and trading volume," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1714-1726, July.
    64. Aalborg, Halvor Aarhus & Molnár, Peter & de Vries, Jon Erik, 2019. "What can explain the price, volatility and trading volume of Bitcoin?," Finance Research Letters, Elsevier, vol. 29(C), pages 255-265.
    65. Carl Chiarella & Boda Kang & Christina Sklibosios Nikitopoulos & Thuy‐Duong Tô, 2016. "The Return–Volatility Relation in Commodity Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(2), pages 127-152, February.
    66. Meir Statman & Steven Thorley & Keith Vorkink, 2006. "Investor Overconfidence and Trading Volume," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1531-1565.
    67. Akyildirim, Erdinc & Corbet, Shaen & Lucey, Brian & Sensoy, Ahmet & Yarovaya, Larisa, 2020. "The relationship between implied volatility and cryptocurrency returns," Finance Research Letters, Elsevier, vol. 33(C).
    68. Todorova, Neda & Souček, Michael, 2014. "The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range," Economic Modelling, Elsevier, vol. 36(C), pages 332-340.
    69. Harris, Lawrence, 1987. "Transaction Data Tests of the Mixture of Distributions Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(2), pages 127-141, June.
    70. Aris Kartsaklas, 2018. "Trader Type Effects On The Volatility‐Volume Relationship Evidence From The Kospi 200 Index Futures Market," Bulletin of Economic Research, Wiley Blackwell, vol. 70(3), pages 226-250, July.
    71. Tseng, Tseng-Chan & Lee, Chien-Chiang & Chen, Mei-Ping, 2015. "Volatility forecast of country ETF: The sequential information arrival hypothesis," Economic Modelling, Elsevier, vol. 47(C), pages 228-234.
    72. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    2. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    3. Pengfei Wang & Wei Zhang & Xiao Li & Dehua Shen, 2019. "Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 377-418, June.
    4. Koubaa, Yosra & Slim, Skander, 2019. "The relationship between trading activity and stock market volatility: Does the volume threshold matter?," Economic Modelling, Elsevier, vol. 82(C), pages 168-184.
    5. Farag, Hisham & Cressy, Robert, 2011. "Do regulatory policies affect the flow of information in emerging markets?," Research in International Business and Finance, Elsevier, vol. 25(3), pages 238-254, September.
    6. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    7. Kumar, Brajesh & Singh, Priyanka & Pandey, Ajay, 2009. "The Dynamic Relationship between Price and Trading Volume:Evidence from Indian Stock Market," IIMA Working Papers WP2009-12-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    8. Brajesh Kumar, 2010. "The Dynamic Relationship between Price and Trading Volume: Evidence from Indian Stock Market," Working Papers id:2379, eSocialSciences.
    9. Ngene, Geoffrey M. & Mungai, Ann Nduati, 2022. "Stock returns, trading volume, and volatility: The case of African stock markets," International Review of Financial Analysis, Elsevier, vol. 82(C).
    10. Chou, Ke-Hsin & Day, Min-Yuh & Chiu, Chien-Liang, 2023. "Do bitcoin news information flow and return volatility fit the sequential information arrival hypothesis and the mixture of distribution hypothesis?," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 365-385.
    11. Shen, Dehua & Li, Xiao & Zhang, Wei, 2018. "Baidu news information flow and return volatility: Evidence for the Sequential Information Arrival Hypothesis," Economic Modelling, Elsevier, vol. 69(C), pages 127-133.
    12. Eric Girard & Mohammed Omran, 2009. "On the relationship between trading volume and stock price volatility in CASE," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 5(1), pages 110-134, February.
    13. Sarika Mahajan & Balwinder Singh, 2008. "An Empirical Analysis of Stock Price-Volume Relationship in Indian Stock Market," Vision, , vol. 12(3), pages 1-13, July.
    14. Chuang, Wen-I & Liu, Hsiang-Hsi & Susmel, Rauli, 2012. "The bivariate GARCH approach to investigating the relation between stock returns, trading volume, and return volatility," Global Finance Journal, Elsevier, vol. 23(1), pages 1-15.
    15. Pramod Kumar Naik & Rangan Gupta & Puja Padhi, 2018. "The Relationship Between Stock Market Volatility And Trading Volume: Evidence From South Africa," Journal of Developing Areas, Tennessee State University, College of Business, vol. 52(1), pages 99-114, January-M.
    16. Carroll, Rachael & Kearney, Colm, 2015. "Testing the mixture of distributions hypothesis on target stocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 1-14.
    17. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "How does trading volume affect financial return distributions?," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 190-206.
    18. Abhinava Tripathi, 2021. "The Arrival of Information and Price Adjustment Across Extreme Quantiles: Global Evidence," IIM Kozhikode Society & Management Review, , vol. 10(1), pages 7-19, January.
    19. Cathy W.S. Chen & Mike K.P. So & Thomas C. Chiang, 2016. "Evidence of Stock Returns and Abnormal Trading Volume: A Threshold Quantile Regression Approach," The Japanese Economic Review, Japanese Economic Association, vol. 67(1), pages 96-124, March.
    20. Saswat Patra & Malay Bhattacharyya, 2021. "Does volume really matter? A risk management perspective using cross‐country evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 118-135, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reveco:v:89:y:2024:i:pa:p:524-542. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620165 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.