Cointegration between the European Union and the selected global markets following Sovereign Debt Crisis

  • Received July 3, 2017;
    Accepted December 13, 2017;
    Published January 17, 2018
  • Author(s)
    Anna Golab
    ORCID ,
    Ferry Jie
    ORCID ,
    Robert Powell
    ORCID ,
    Anna Zamojska
    ORCID
  • DOI
    http://dx.doi.org/10.21511/imfi.15(1).2018.05
  • Article Info
    Volume 15 2018, Issue #1, pp. 35-45
  • TO CITE АНОТАЦІЯ
  • Cited by
    6 articles
  • 1528 Views
  • 281 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

The purpose of this paper is to provide an analytical analysis of cointegration between Europe and the other significant trading partners, namely US, China, Japan and Australia, for the period from January 1, 2010 to December 30, 2016. This captures the impact of the sovereign European debt crisis and the Greek crisis. A range of parametric techniques were adopted including Johansen cointegration analysis, Vector Error Correction Model and Granger causality. The results of the crisis Granger causality test during the European sovereign crisis implies the highest influence to be that of the US and Japanese stock market over the other four markets. Overall, found that the Asia-Pacific region plus the US stay closely related to each other, while European countries influence all the studied markets except each other. For the post-crisis sub-period, the Granger causality is slightly different. It is observable that the UK and Germany are influencing all the markets. This is probably due to the recent Brexit referendum outcome and potential consequences not only for the EU, but also for the rest of the world too. Overall, the Granger outcome shows the dependence between Europe and other global markets, but there is no European interdependence during the sovereign debt crisis period. It may be concluded that there is a separation of Asian markets from the European markets and even though cointegration exists, the relationship is rather weak.

view full abstract hide full abstract
    • Figure 1. Index level and return series
    • Table 1. List of countries and market indices in the study sample
    • Table 2. Unit root tests with a breakpoint (ADF) on index levels and first differences
    • Table 3. Johansen cointegration rank test results
    • Table 4. Normalized cointegrating vectors
    • Table 5. Granger causality test for returns, crisis sub-period
    • Table 6. Granger causality test for returns, post-crisis sub-period
    • Allen, D. E., & MacDonald, G. (1995). The long-run gains from international equity diversification: Australian evidence from cointegration tests. Applied Financial Economics, 5, 33-42.
    • BBC News. (2016). Greece profile – Timeline.
    • Benati, L. (2012). Estimating the financial crisis’ impact on potential output. Economics Letters, 113-119.
    • Berkmen, S. P., Gelos, S., Rennhack, R., & Walsh, J. P. (2012). The global financial crisis: Explaining cross-country differences in the output impact. Journal of International Money and Finance, 31, 42-59.
    • Censky, A. (2010). 2010: The year of uncertainty and volatility. CNN Money.
    • Cheng, S. W. (2012). The U.S. Financial Crisis: Analysis and Interpretation. San Francisco: Long River Press.
    • Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive tome series with a unit root. Journal of the American Statistical Association, 74, 427-431.
    • Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with unit root. Econometrica, 49, 1057-1072.
    • Egert, B., & Kocenda, E. (2007). Interdependance between Eastern andWestern European Stock Markets: Evidence from Intraday day. Economic Systems, 31, 184-203.
    • European Commision Report (2011). General Report on the Activities of the European Union. Brussels, Belgium: Luxemburg: Publishing Office of the EU.
    • European Commision Report (2016). Top Trading Partners – Trade Statistics. Directorate General for Trade.
    • Fadhlaoui, K., Bellalah, M., Dherry, A., & Zouaouii, M. (2009). An Empirical Exmination of International Diversification Benefits in the Central European Emerging Equity Markets. International Journal of Business, 14(2), 163-173.
    • Fletcher, N. (2010). Debt crisis: European markets fluctuate as financial turmoil spreads to Spain. The Guardian.
    • Foerster, H. (2013). European Debt Crisis. New York, New York.
    • George, S. (2012, May 6). Corporate Europe Observatory.
    • Gilmore, C. G., & McManus, G. M. (2002). International portfolio diversification: US and Central European equity markets. Emerging Markets Review, 3, 69-83.
    • Gilmore, C. G., & McManus, G. M. (2003). Bilateral and Multilateral Cointegration properties between the Geramn and Central European Equity Markets. Studies in Economics and Finance, 21(1), 40-53.
    • Gilmore, C. G., Lucey, B. M., & McManus, G. M. (2005). The Dynamics of Central Equity Market Integration (IIIS Discussion paper No. 69).
    • Golab, A., Allen, D., & Powell, R. (2014). Aspects of Volatility and Correlations in European Emerging Economies. In N. Finch (Ed.), Emerging Markets and Sovereign Risk (pp. 59-80). London: Palgrave Macmillan.
    • Granger, C. W., & Engle, R. F. (1985). Dynamic model specification with equilibrium constraints: Cointegration and error correction. Mimeo. San Diego, CA, University of California.
    • Gupta, P., Mishra, D., & Sahay, R. (2007). Behavior of output during currency crises. Journal of International Economics, 72, 428-450.
    • Hansen , B. E. (2001). The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity. Journal of Economic Perspectives, 15(4), 117-128.
    • Hatheway, L., Cates, A., Donovan, P., & Constable, S. (2012). Impacts of the Euro sovereign debt crisis on global economic growth. Global economic review, 6-14.
    • Inklaar, R., & Yang, J. (2012). The impact of financial crises and tolerance for uncertainty. Journal of Development Economics, 97, 466-480.
    • Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59, 1551-1580.
    • Johansen, S., & Juselius, K. (1990). Maximum likelihood estomation and inference on cointegration with application to the demand for money. Oxford Bulletin of Economics and Statistics, 52, 169-210.
    • Kim, Y. H. (2001). The Asian crisis, private sector saving, and policy implications. Journal of Asian Economics, 12, 331-351.
    • Li, N., Shi, M., & Huang, W. (2013). Impacts of the Euro sovereign debt crisis on global trade and economic growth: A General Equilibrium Analysis based on GTAP model.
    • Luintel, K., & Khan, M. (1999). A quantitative reassessment of the finance-growth nexus: evidence from a multivariate VAR. Journal of Development Economics, 60(2), 381-405.
    • Lütkepohl , H., Saikkonen, P., & Trenkler, C. (2001). Maximum eigenvalue versus trace tests for the cointegrating rank of a VAR process. Econometrics Journal, 4(2), 8.
    • McDonald, S. (2011). Global Bonds Gain $132 Billion as Stock Rout Cuts $7.8 Trillion. Bloomberg Businessweek.
    • Mechanism, European Stability (2016). Before the ESM – EFSF – the temporary fiscal backstop.
    • Nelson, R. M., Belkin, P., Mix, D. E., & Weiss, M. A. (2012). The Eurozone Crisis: Overview and Issues for Congress. Unites States: Prepared for Members and Committees of Congress.
    • Phillips, P., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrica, 75, 335-346.
    • Roeder, D. (2011, ). Dow plummets 634 points amid downgrade backlash. The Herald News.
    • Scheicher, M. (2001). The comovements of stock makets in Hungry, Poland and the Czech Republic. International Journal of Finance and Economics, 6, 27-39.
    • Seddighi, H. R., & Shearing, D. F. (1997). The emand for tourism in North East England with special reference to Northumbria: An empirical analysis. Tourism Management, 18(8), 499-511.
    • Shellock, D. (2015). Stocks dented by deepening Greek crisis. Financial Times.
    • Swanson, E. T., & Williams, J. C. (2014). Measuring the Effect of the Zero Lower Bound on Medium- and Longer-Term Interest Rates. The American Economic Review, 104(10), 3154- 3185.
    • Syriopoulos, T. (2007). Dynamic linkages between emerging European and developed stock markets: Has the EMU any impact? International Review of Financial Analysis, 16, 41-60.
    • The Irish Times (2011). Dow plunges as $2.5tn erased from equities.
    • Voronkova, S. (2004). Equity market integration in Central European emerging markets: A cointegration analysis with shifting regimes. International Review of Financial Analysis, 13, 633-647.
    • Wearden, G. (2016). Greece debt crisis: timeline / Eurozone crisis. The Guardian.
Related Articles

  • Selection of the right proxy market portfolio for CAPM

    Rashmi ChaudharyORCID , Priti BakhshiORCID doi: http://dx.doi.org/10.21511/imfi.18(3).2021.02
    Investment Management and Financial Innovations Volume 18, 2021         Issue #3         pp. 16-26 Views: 3142 Downloads: 1550 TO CITE АНОТАЦІЯ

    The purpose of the paper is to select the right market proxy for calculating the expected return, since critically evaluating proxies or selecting the correct proxy market portfolio is essential for portfolio management because the change in the market portfolio proxy affects returns. In this study, monthly data of equity indices are evaluated to find out the better market proxy. The indices taken are BSE 30 (Sensex), Nifty 50, BSE 100, BSE 200, and BSE 500. The macroeconomic variables used in the study are industrial production index (IIP), consumer price index (CPI), money supply (M1), and exchange rate in India. To avoid the influence of COVID-19, the research period was from January 2013 to December 2019 to critically evaluate these proxies in order to find the most appropriate market proxy. This paper reveals a noteworthy relationship between stock market returns and macroeconomic factors, while suggesting that the BSE 500 is a better choice for all equity indices, as the index also shows a significant relationship with all macroeconomic variables. BSE500 is a composite index comprising all sectors with low, mid and large cap securities, therefore it reflects the impact of macroeconomic factors most efficiently, taking it as a market proxy. This study was carried out in the context of India and can be replicated for other countries.

  • Financial sector and manufacturing sector performance: evidence from Nigeria

    Abiola John AsaleyeORCID , Joseph Ibrahim AdamaORCID , Joseph Olufemi Ogunjobi doi: http://dx.doi.org/10.21511/imfi.15(3).2018.03
    Investment Management and Financial Innovations Volume 15, 2018         Issue #3         pp. 35-48 Views: 2516 Downloads: 367 TO CITE АНОТАЦІЯ

    Nigerian economy depends on oil as the major source of revenue, failure to diversify the revenue base has raised questions about its sustainability and implication on the economy. This study uses market capitalization, broad money stock, credit to private sector, prime interest rate and deposit liability as proxies for the financial sector, while output in the manufacturing sector and manufacturing employment are used as proxies for manufacturing performance. The study examines the causal effects, shock effect and long-run impact using Granger Non-Causality, Vector Error Correction Model, and Dynamic Ordinary Least Square method, respectively. The results showed unidirectional causality, confirming the hypothesis of the ‘supply-leading view’ and ‘demand-following view’ except for market capitalization and output in the manufacturing sector, where independence was observed. The variance decomposition shows that the forecast error shock of credit to private sector and prime interest rate show more variations in manufacturing sector performance than other financial indicators. The long-run result using output in manufacturing sector as dependent variable shows a positive significant relationship with other financial sector indicators, except for broad money stock and deposit liability. This study recommended credit channel for transmission of monetary policy using interest rate to improve the performance of manufacturing sector, among others.

  • Developing a system of anti-crisis measures for Ukraine’s economy in the spread of the coronavirus pandemic

    Bohdan DanylyshynORCID , Ivan BohdanORCID doi: http://dx.doi.org/10.21511/bbs.15(2).2020.01
    Banks and Bank Systems Volume 15, 2020         Issue #2         pp. 1-15 Views: 1607 Downloads: 212 TO CITE АНОТАЦІЯ

    The new global financial and economic crisis is caused by the spread of the coronavirus epidemic, the reduction in aggregate supply, the escalation of trade wars, and the outflow of capital from emerging markets. This requires national macroeconomic regulatory authorities to take prudent measures to protect national economies from destabilizing externalities. Therefore, the purpose of the article is to justify and develop a priority system of stabilization policy and anti-crisis measures to counter the spread of external shocks in the national economy, stabilize it, and create conditions for its further recovery and sustainable economic growth. To achieve this aim, the existing theoretical sources and research materials of international organizations were systematized, the legislative and regulatory framework in Ukraine was generalized, and statistical methods, a historical method, analysis and generalization were also used. As a result, the channels of impact of external shocks on Ukraine’s economy were identified, and the areas of internal vulnerability of the national economy that could significantly increase the negative effects of externalities were determined. The knowledge gained has become the basis for formulating conceptual directions of crisis management and developing a system of measures to counteract crisis phenomena, which include the monetary policy tools of the National Bank of Ukraine, the structural and fiscal policy of the Government, as well as the banking regulation and capital control policies.

Download Preview
Close
Investment Management and Financial Innovations
Investment Management and Financial Innovations