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Should Bitcoin be held under the U.S. partisan conflict?

    Chi-Wei Su Affiliation
    ; Meng Qin Affiliation
    ; Xiao-Lei Zhang Affiliation
    ; Ran Tao Affiliation
    ; Muhammad Umar Affiliation

Abstract

This paper probes the interrelationship between Bitcoin price (BP) and the U.S. partisan conflict (PC) by performing the bootstrap full- and sub-sample Granger causality tests. The positive influence from PC to BP reveals that Bitcoin can be considered as a tool to avoid the uncertainty caused by the rise in PC. However, this view cannot be supported by the negative impact, the major reason is that the burst of bubble undermines the hedging ability of Bitcoin. The above results are inconsistent with the intertemporal capital asset pricing model (ICAPM), underlining that high PC may drive BP to rise, in order to compensate for the losses and costs from factionalism. Conversely, BP has a negative impact on PC, suggesting that the U.S. political situation can be reflected by the Bitcoin market. Under the circumstance of the fiercer factionalism in the U.S., this investigation can benefit investors and related authorities.


First published online 04 February 2021

Keyword : Bitcoin price, U.S. partisan conflict, rolling- window, dynamic nexus

How to Cite
Su, C.-W., Qin, M., Zhang, X.-L., Tao, R., & Umar, M. (2021). Should Bitcoin be held under the U.S. partisan conflict?. Technological and Economic Development of Economy, 27(3), 511-529. https://doi.org/10.3846/tede.2021.14058
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May 25, 2021
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Akhtaruzzaman, M., Sensoy, A., & Corbet, S. (2019). The influence of Bitcoin on portfolio diversification and design. Finance Research Letters, 37, 101344. https://doi.org/10.1016/j.frl.2019.101344

Andrews, D. W. K. (1993). Tests for parameter instability and structural change with unknown change point. Econometrica, 61(4), 821–856. https://doi.org/10.2307/2951764

Andrews, D. W. K., & Ploberger, W. (1994). Optimal tests when a nuisance parameter is present only under the alternative. Econometrica, 62(6), 1383–1414. https://doi.org/10.2307/2951753

Azzimonti, M. (2014). Partisan conflict (Working Paper No. 14-19). FRB of Philadelphia. https://doi.org/10.2139/ssrn.2457406

Azzimonti, M. (2019). Does partisan conflict deter FDI inflows to the US? Journal of International Economics, 120, 162–178. https://doi.org/10.1016/j.jinteco.2019.06.001

Balcilar, M., & Ozdemir, Z. A. (2013). The export-output growth nexus in Japan: A bootstrap rolling window approach. Empirical Economics, 44, 639–660. https://doi.org/10.1007/s00181-012-0562-8

Balcilar, M., Ozdemir, Z. A., & Arslanturk, Y. (2010). Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window. Energy Economics, 32(6), 1398–1410. https://doi.org/10.1016/j.eneco.2010.05.015

Bartsch, Z. (2019). Economic policy uncertainty and dollar-pound exchange rate return volatility. Journal of International Money and Finance, 98, 102067. https://doi.org/10.1016/j.jimonfin.2019.102067

Baur, D. G., Dimpfl, T., & Kuck, K. (2018). Bitcoin, gold and the US dollar – A replication and extension. Finance Research Letters, 25, 103–110. https://doi.org/10.1016/j.frl.2017.10.012

Bouoiyour, J., Selmi, R., & Wohar, M. E. (2019). Safe havens in the face of presidential election uncertainty: A comparison between Bitcoin, oil and precious metals. Applied Economics, 51(57), 6076– 6088. https://doi.org/10.1080/00036846.2019.1645289

Bouri, E., & Gupta, R. (2019). Predicting Bitcoin returns: Comparing the roles of newspaper- and internet search-based measures of uncertainty. Finance Research Letters, 101398. https://doi.org/10.1016/j.frl.2019.101398

Bouri, E., Gupta, R., Lau, C. K. M., Roubaud, D., & Wang, S. X. (2018). Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles. The Quarterly Review of Economics and Finance, 69, 297–307. https://doi.org/10.1016/j.qref.2018.04.003

Bouri, E., Gupta, R., Tiwar, A. K., & Roubaud, D. (2017). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 23, 87–95. https://doi.org/10.1016/j.frl.2017.02.009

Cai, Y. F., & Wu, Y. R. (2019). Time-varied causality between US partisan conflict shock and crude oil return. Energy Economics, 84, 104512. https://doi.org/10.1016/j.eneco.2019.104512

Caldara, D., & Iacoviello, M. (2017). Measuring geopolitical risk (International Finance Discussion Papers No. 1222). Board of Governors of the Federal Reserve System. https://doi.org/10.17016/IFDP.2018.1222

Chan, W. G., Le, M., & Wu, Y. W. (2019). Holding Bitcoin longer: The dynamic hedging abilities of Bitcoin. The Quarterly Review of Economics and Finance, 71, 107–113. https://doi.org/10.1016/j.qref.2018.07.004

Cheng, C. G. J., Chiu, C. W., Hankins, W. B., & Stone, A. (2018). Partisan conflict, policy uncertainty and aggregate corporate cash holdings. Journal of Macroeconomics, 58, 78–90. https://doi.org/10.1016/j.jmacro.2018.08.010

Cheng, C. H. J., Hankins, W. B., & Chiu, C. W. (2016). Does US partisan conflict matter for the Euro area? Economics Letters, 138, 64–67. https://doi.org/10.1016/j.econlet.2015.11.030

Cifarelli, G., & Paladino, G. (2010). Oil price dynamics and speculation: A multivariate financial approach. Energy Economics, 32(2), 363–372. https://doi.org/10.1016/j.eneco.2009.08.014

Clance, M. W., Gupta, R., & Wohar, M. E. (2018). Geopolitical risks and recessions in a panel of advanced economies: Evidence from over a century of data. University of Pretoria, Department of Economics. https://repository.up.ac.za/bitstream/handle/2263/68295/Clance_Geopolitical_2019.pdf?sequence=1&isAllowed=y

Colon, F., Kim, C., Kim, H., & Kim, W. (2020). The effect of political and economic uncertainty on the cryptocurrency market. Finance Research Letters, 101621 (in Press). https://doi.org/10.1016/j.frl.2020.101621

Conlon, T., & McGee, R. (2020). Safe haven or risky hazard? Bitcoin during the Covid-19 bear market. Finance Research Letters, 35, 101607. https://doi.org/10.1016/j.frl.2020.101607

Demir, E., Gozgor, G., Lau, C. K. M., & Vigne, S. A. (2018). Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation. Finance Research Letters, 26, 145–149. https://doi.org/10.1016/j.frl.2018.01.005

Dyhrberg, A. H. (2016). Bitcoin, gold and the dollar – A GARCH volatility analysis. Finance Research Letters, 16, 85–92. https://doi.org/10.1016/j.frl.2015.10.008

Elwell, C. K., Murphy, M. M., & Seitzinger, M. V. (2013). Bitcoin: Questions, answers, and analysis of legal issues (Congressional Research Service Report).

Fang, L., Bouri, E., Gupta, R., & Roubaud, D. (2019). Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin? International Review of Financial Analysis, 61, 29–36. https://doi.org/10.1016/j.irfa.2018.12.010

Gleeson, D., Lexchin, J., Lopert, R., & Kilic, B. (2018). The Trans Pacific Partnership Agreement, intellectual property and medicines: Differential Outcomes for developed and developing countries. Global Social Policy, 18(1), 7–27. https://doi.org/10.1177/1468018117734153

Gøtzsche-Astrup, O. (2019). Personality moderates the relationship between uncertainty and political violence: Evidence from two large U.S. samples. Personality and Individual Differences, 139, 102–109. https://doi.org/10.1016/j.paid.2018.11.006

Gozgor, G., Tiwari, A. K., Demir, E., & Akron, S. (2019). The relationship between Bitcoin returns and trade policy uncertainty. Finance Research Letters, 29, 75–82. https://doi.org/10.1016/j.frl.2019.03.016

Gupta, R., Lau, C. K. M., Miller, S. M., & Wohar, M. (2017). U.S. fiscal policy and asset prices: The role of partisan conflict. International Review of Finance, 19(4), 851–862. https://doi.org/10.1111/irfi.12188

Gupta, R., Mwamba, J. W. M., & Wohar, M. E. (2018b). The role of partisan conflict in forecasting the U.S. equity premium: A nonparametric approach. Finance Research Letters, 25, 131–136. https://doi.org/10.1016/j.frl.2017.10.023

Gupta, R., Pierdzioch, C., Selmi, R., & Wohar, M. E. (2018a). Does partisan conflict predict a reduction in US stock market (realized) volatility? Evidence from a quantile-on-quantile regression model. The North American Journal of Economics and Finance, 43, 87–96. https://doi.org/10.1016/j.najef.2017.10.006

Hanson, B. E. (1992). Tests for parameter instability in regressions with I(1) processes. Journal of Business and Economic Statistics, 20(1), 45–59. https://doi.org/10.1198/073500102753410381

Jiang, X. D., & Shi, Y. L. (2018). Does US partisan conflict affect US–China bilateral trade? International Review of Economics & Finance. https://doi.org/10.2139/ssrn.3122322

Jiang, Y., Ren, Y. S., Ma, C. Q., Liu, J. L., & Sharp, B. (2020). Does the price of strategic commodities respond to U.S. partisan conflict? Resources Policy, 66, 101617. https://doi.org/10.1016/j.resourpol.2020.101617

Kalyvas, A., Papakyriakou, P., Sakkas, A., & Urquhart, A. (2019). What drives Bitcoin’s price crash risk? Economics Letters, 191, 108777. https://doi.org/10.1016/j.econlet.2019.108777

Klein, T., Thu, H. P., & Walther, T. (2018). Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance. International Review of Financial Analysis, 59, 105–116. https://doi.org/10.1016/j.irfa.2018.07.010

Kliber, A., Marszałek, P., Musiałkowska, I., & Świerczyńska, K. (2019). Bitcoin: Safe haven, hedge or diversifier? Perception of bitcoin in the context of a country’s economic situation – A stochastic volatility approach. Physica A: Statistical Mechanics and its Applications, 524, 246–257. https://doi.org/10.1016/j.physa.2019.04.145

Li, Z. Z., Tao, R., Su, C. W., & Lobont, O. R. (2018). Does Bitcoin bubble burst? Quality & Quantity, 53(2), 1–15. https://doi.org/10.1007/s11135-018-0728-3

Luther, W. J., & Salter, A. W. (2017). Bitcoin and the bailout. Quarterly Review of Economics & Finance, 66, 50–56. https://doi.org/10.1016/j.qref.2017.01.009

Mamun, M. A., Uddin, G. S., Suleman, M. T., & Kang, S. H. (2020). Geopolitical risk, uncertainty and Bitcoin investment. Physica A: Statistical Mechanics and its Applications, 54, 123107. https://doi.org/10.1016/j.physa.2019.123107

Matkovskyy, R., & Jalan, A. (2019). From financial markets to Bitcoin markets: A fresh look at the contagion effect. Finance Research Letters, 31, 93–97. https://doi.org/10.1016/j.frl.2019.04.007

Neves, R. H. D. (2020). Bitcoin pricing: impact of attractiveness variable. Financial Innovation, 6(1), 1–18. https://doi.org/10.1186/s40854-020-00176-3

Nyblom, J. (1989). Testing for the constancy of parameters over time. Journal of the American Statistical Association, 84(405), 223–230. https://doi.org/10.1080/01621459.1989.10478759

Pesaran, M. H., & Timmermann, A. (2005). Small sample properties of forecasts from autoregressive models under structural breaks. Journal of Econometrics, 129(1–2), 183–217. https://doi.org/10.1016/j.jeconom.2004.09.007

Pham, H. N. A., Ramiah, V., Moosa, N., Huynh, T., & Pham, N. (2018). The financial effects of Trumpism. Economic Modelling, 74, 264–274. https://doi.org/10.1016/j.econmod.2018.05.020

Pyo, S., & Lee, J. (2019). Do FOMC and macroeconomic announcements affect Bitcoin prices? Finance Research Letters, 37, 101386. https://doi.org/10.1016/j.frl.2019.101386

Qin, M., Su, C. W., & Tao, R. (2020). BitCoin: A new basket for eggs? Economic Modelling (in Press). https://doi.org/10.1016/j.econmod.2020.02.031

Regilme, S. S. F. (2019). The decline of American power and Donald Trump: Reflections on human rights, neoliberalism, and the world order. Geoforum, 102, 157–166. https://doi.org/10.1016/j.geoforum.2019.04.010

Ron, J., David, M., Charles, P., & Jones, K. (2018). Geographies of Brexit and its aftermath: Voting in England at the 2016 referendum and the 2017 general election. Space & Polity, 22(2), 162–187. https://doi.org/10.1080/13562576.2018.1486349

Shahzad, S. J. H., Bouri, E., Roubaud, D., & Kristoufek, L. (2020). Safe haven, hedge and diversification for G7 stock markets: Gold versus bitcoin. Economic Modelling, 87, 212–224. https://doi.org/10.1016/j.econmod.2019.07.023

Shahzad, S. J. H., Bouri, E., Roubaud, D., Kristoufek, L., & Lucey, B. (2019). Is Bitcoin a better safe-haven investment than gold and commodities? International Review of Financial Analysis, 63, 322–330. https://doi.org/10.1016/j.irfa.2019.01.002

Shaikh, I. (2020). Policy uncertainty and Bitcoin returns. Borsa Istanbul Review, 20(3), 257–268. https://doi.org/10.1016/j.bir.2020.02.003

Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance, 19(3), 425–442. https://doi.org/10.1111/j.1540-6261.1964.tb02865.x

Shukur, G., & Mantalos, P. (1997). Size and power of the RESET test as applied to systems of equations: A bootstrap approach (Working Paper). Department of Statistics, University of Lund.

Shukur, G., & Mantalos, P. (2000). A simple investigation of the Granger-causality test in integratedcointegrated VAR systems. Journal of Applied Statistics, 27(8), 1021–1031. https://doi.org/10.1080/02664760050173346

Su, C. W., Qin, M., Tao, R., & Umar, M. (2020a). Does oil price really matter for the wage arrears in Russia? Energy, 208, 118350. https://doi.org/10.1016/j.energy.2020.118350

Su, C. W., Qin, M., Tao, R., & Umar, M. (2020b). Financial implications of fourth industrial revolution: Can bitcoin improve prospects of energy investment? Technological Forecasting & Social Change, 158, 120178. https://doi.org/10.1016/j.techfore.2020.120178

Su, C. W., Qin, M., Tao, R., Nicoleta-Claudia, M., & Oana-Ramona, L. (2020c). Factors driving oil price – From the perspective of united states. Energy, 197, 117219. https://doi.org/10.1016/j.energy.2020.117219

Su, C. W., Qin, M., Tao, R., Shao, X. F., Albu, L. L., & Umar, M. (2020d). Can Bitcoin hedge the risks of geopolitical events? Technological Forecasting and Social Change, 159, 120182. https://doi.org/10.1016/j.techfore.2020.120182

Su, C. W., Wang, X. Q., Tao, R., & Oana-Ramona, L. (2019). Do oil prices drive agricultural commodity prices? Further evidence in a global bio-energy context. Energy, 172, 691–701. https://doi.org/10.1016/j.energy.2019.02.028

Xiong, J. W., Liu, Q., & Zhao, L. (2019). A new method to verify Bitcoin bubbles: Based on the production cost. North American Journal of Economics and Finance, 51, 101095. https://doi.org/10.1016/j.najef.2019.101095

Yen, K. C., & Cheng, H. P. (2020). Economic policy uncertainty and cryptocurrency volatility. Finance Research Letters, 101428 (in Press). https://doi.org/10.1016/j.frl.2020.101428