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Improvements in technology have reduced informational barriers that formerly restrained investment in international markets (Bekaert 1995). An overall movement towards fewer capital controls and reducing other market inefficiencies (e.g. poor credit ratings, high and variable inflation, exchange rate controls, etc ) due to globalization implies that equity markets are converging towards financial and economic integration over time (Bekaert, Harvey, Lundblad, Siegal 2011). Integration of emerging market economies into the world financial markets is generally followed by: a significantly larger and more liquid equity market, returns which are more volatile and more correlated with world market returns, a lower cost of capital (and thus lower risk premiums and increased investment), improved credit ratings, real exchange rate appreciation, and increased economic growth (Bekaert, Harvey, Lumsdaine).
Introduction and Literature Review
Theoretical Model
Data
Cointegration of Equity Returns in Brazil, Russia, India, China and South Africa (BRICS) By Dominic Anene, Florentine Eloundou, Timothy Larach, Melanie Lugo
Graphical Results
Numerical Results
Acknowledgements/References
Methodology
Models
(1)Testing for stationarity โข Unit root, Dickey-Fuller Test (2) Testing for Cointegration โข Extracting long run component variable from level model โข Testing the significance of long-run component in the Error Correction Model. (3) Granger/Causality Test โข Testing the joint significance test of lagged variables. (4) Graphical Viewing of Impulse Response Functions (IRF)
Over the next decade, the importance of the BRICS, and especially China, in world GDP will grow vastly. The IMF predicts that they will account for as much as 61% of global growth by 2016. This invites pertinent questions about the economic impact of fiscal and monetary policies in these countries, not only on the global economy, but also on the other members of the BRICS. We examine the co-integration of these countriesโ market returns over time, their response to economic shocks, and their intertwined Granger Causalities.
Research Question
Discussion
MSCI Emerging Markets Index (1993-2013, monthly) Morgan Stanley Capital International Index.
Cointegration between Brazil, India, & South Africa
(1)
VARIABLES D. ln_brazil
Uhat_B,I,SA -0.110***
(0.0252)
R-squared 0.438
Adjusted R-Square 0.431
Cointegration between China & Russia
(1)
VARIABLES D.ln_russia
Uhat_C,R -0.0296***
(0.0109)
R-squared 0.289
Adjusted R-Square 0.269
Cointegration between Brazil, China, & Russia
(1)
VARIABLES BCR
Uhat_B,C,R -0.0542***
(0.0191)
R-squared 0.474
Adjusted R-Square 0.462
Cointegration between India, China, & Russia
(1)
VARIABLES D.ln_india
Uhat_I,C,R -0.0430**
(0.0201)
R-squared 0.257
Adjusted R-Square 0.247
Cointegration between South Africa, China, & Russia
(1)
VARIABLES D.ln_southafrica
Uhat_SA,C,R 0.0114
(0.00943)
R-squared 0.459
Adjusted R-Square 0.452
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Granger Causality Matrix
References Bekaert, Geert, Campbell R. Harvey, and Robin L. Lumsdaine. "Dating the Integration of World Equity Markets." Journal of Finance Economics 00 (2002) 000-000. (August 2001): 1-43. Duke University Faculty. Duke University. Web. Bekaert, Geert, Campbell R. Harvey, Christian T. Lundblad, and Stephan Siegel. "What Segments Equity Markets?" Netspar Discussion Paper (February 2011): 1-38. Web. Henry, Peter Blair. "Do Stock Market Liberalizations Cause Investment Booms?" (April 2000): 1-43. Graduate School of Business, Stanford University, Stanford, CA 94305-5015, USA. Web. Korajczyk, Robert A. "A Measure of Stock Market Integration for Developed and Emerging Markets." World Bank Policy Research Working Paper No. 1482 (1995): 1-29. Print.
Acknowledgements We wish to thank the immensely helpful Dr. Bohara, the AEA Summer Training Program 2013 and RWJ Foundation Center for Health Policy. Supervised by Dr. Alok Bohara as partial fulfillment of the research requirement for ECON409: Intermediate Applied Econometrics (Department of Economics, UNM)
Hypothesis The lessening of capital controls in the 1980s and 1990s, along with increased availability of information, has caused the price of risk to be equalized across assets. We therefore expect to see diminishing differentials in BRICS equity returns over time as different markets now demand the same compensation (i.e. returns should be converging).
Brazil China Russia India South Africa
Brazil - Yes*** Yes*** Yes*** Yes***
China Yes** - Yes* Yes* Yes***
Russia Yes** No - Yes* Yes**
India Yes*** No No - Yes***
South Africa Yes*** Yes*** Yes** Yes*** -
P-Values: ***=1%, **=5%, *=10%
Conclusion and Further Research
The test for stationarity confirmed that MSCI returns in the BRICS are following a trend, and we needed to adjust for this non-stationarity (by differencing) in our model. The Error Correction Model suggest that the returns to equity in the BRICS follow a long-term trend. This result implies that if a shock drives any of these returns away from the current trend, in equilibrium, these returns will revert back to the trend. Our Granger Causality tests suggest that beyond cointegration, some of these markets Granger-cause each other. For example, equity market returns in South Africa, Granger-causes returns in all the other BRICS at the 1% significance level. In other words, one can use the results from the returns of one country to predict the returns from another. Because we orthogonalized the errors in the impulse response function, we can guarantee the consistency of the impulse response functions (IRF). With these functions, we can predict the impact that a shock on one countryโs returns will have on anotherโs.
American Economic Association
Our analysis of equity returns in the BRICS showed evidence of co-integration between returns in the BRICS, and that some of the returns Granger-cause each other. Further, we note that shocks in some marketsโ returns will affect othersโ. Therefore, our study leaves room for forecasting the future extent of correlation, and investigating the underlying force of the co-integration. We suspect that the driving force behind the cointegration is globalization. Further research will employ structural VAR modeling techniques to tease out multi-directional influences.
Take a one good closed economy, featuring a competitive market.
๐๐ ๐ข๐ก๐๐๐๐ง๐ ๐กโ๐ โฒ๐๐๐๐๐๐ก ๐๐๐ฅ๐๐๐๐ง๐๐ก๐๐๐ ๐๐ ๐๐๐๐๐ โฒ ๐๐ข๐๐๐ก๐๐๐ ๐๐๐ฅ ๐พ๐ผ๐ฟ1โ๐ผ โ ๐ค๐ฟ โ (๐ + ๐ฟ)๐พ = 0
Where (๐ + ๐ฟ) is the real cost of capital with r being the interest rate and ๐ฟ being the depreciation rate.
GDP=Y=๐พ๐ผ ๐ฟ 1โ๐ผ
By taking the first order condition with respect to capital (K) we obtain
๐ + ๐ฟ = ๐ผ๐พโโ1๐ฟ1โโ = ๐ผ๐พ ๐ผโ1
In a balanced growth path ๐พ = ๐พโ , is constant over time. Therefore, in the balanced growth path, r is constant over time meaning ๐ โ ๐ฟ(the real interest rate) is constant over time
With increased liquidity to additional capital flows and liberalization, the equity premium decreases, which reduces the cost of capital. The marginal product of capital of the firms will decrease to reflect the new cost of capital, which means, private investment and stock market returns increase. With newly lowered financial walls, investors will be able to take advantage of cross market arbitrage, and thus cross market returns will converge.
Error correction model (ECM)
1. Level model
y3๐ก = ๐ฝ0 + ๐ฝ1y1๐ก + ๐ฝ2y2๐ก + ๐ฝ4y4๐ก + ๐ฝ5y5๐ก + ๐๐
2. Error Correction Model
D.๐ฆ3๐ก = ๐ D. y3,๐กโ๐ ,๐ท. y1,๐กโ๐ ,
๐ท. y2,๐กโ๐ ,๐ท. y4,๐กโ๐ ,๐ท. y5,๐กโ๐ + ๐ฟ๐ ๐กโ1 + ํ๐ ,๐กโ๐
Vector Auto-regression Model (VAR) (Optimal Lag=1)
๐ฆ1
๐ฆ2๐ฆ3
๐ฆ4
๐ฆ5
=
๐ฃ1
๐ฃ2๐ฃ3
๐ฃ4
๐ฃ5
+
๐11,1 ๐12,1 ๐13,1 ๐14,1 ๐15,1
๐21,1 ๐22,1 ๐23,1 ๐24,1 ๐25,1
๐31,1
๐41,1
๐51,1
๐32,1
๐42,1
๐52,1
๐33,1 ๐34,1 ๐35,1
๐43,1 ๐44,1 ๐45,1
๐53,1 ๐54,1 ๐55,1
๐ฆ1,๐กโ1
๐ฆ2,๐กโ1๐ฆ3,๐กโ1
๐ฆ4,๐กโ1
๐ฆ5,๐กโ1
+
ํ1๐ก
ํ2๐กํ3๐ก
ํ4๐ก
ํ5๐ก
๐ฆ1 = Log ๐๐ ๐๐๐ข๐กโ ๐ด๐๐๐๐๐ ๐ ๐๐ก๐ข๐๐๐ ๐ฆ2 = Log ๐๐ ๐ต๐๐๐ง๐๐ ๐ ๐๐ก๐ข๐๐๐ ๐ฆ3 = Log๐๐ ๐ผ๐๐๐๐ ๐ ๐๐ก๐ข๐๐๐
๐ฆ4 = Log๐๐ ๐ ๐ข๐ ๐ ๐๐ ๐ ๐๐ก๐ข๐๐๐ ๐ฆ5 = Log๐๐ ๐ถโ๐๐๐ ๐ ๐๐ก๐ข๐๐๐
Orthogonal Impulse Response Function
๐ฆ๐ก= ๐ + ๐๐60๐=0 ๐ค๐กโ๐
๐: ๐ถ๐๐๐ ๐ก๐๐๐ก ๐ค:๐๐๐กโ๐๐๐๐๐๐๐๐ง๐๐ ๐๐๐๐๐
๐: 5๐ฅ5 ๐ ๐ก๐๐๐๐๐๐๐๐ง๐๐ ๐๐๐๐๐๐๐๐๐๐๐ก ๐๐๐ก๐๐๐ฅ ๐๐ข๐๐ก๐๐๐๐๐๐๐ ๐๐ ๐๐๐๐๐ฃ๐๐ก๐๐๐ ๐๐ก ๐๐๐๐๐๐๐๐๐ก ๐๐๐ ๐๐๐๐๐๐๐
Cointegration between the BRICS
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
(1)
VARIABLES D.ln_india
Uhat_I,B,C,R,SA -0.132***
(0.0351)
R-squared 0.392
Adjusted R-Square 0.367
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