Browsing by Author "Balamurali, N."

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Dynamic relationship between stock prices & exchange rates: Evidence from Sri Lanka
(University of Kelaniya, 2011) Balamurali, N.; Sivarajasingam, S.
At the end of the separatist war that continued for over three decades in Sri Lanka , the Colombo Stock Exchange (CSE) started to peak, and became one of the most promising and best performing stock markets in Asia . Therefore, it is interesting to investigate the issue of whether stock prices and exchange rates are related. This has received considerable attention after the world economic crisis. This paper examines the dynamic relationship between stock price and exchange rates in Sri Lanka. We used annual time series data on four foreign exchange rates and All Share Price index (ASPI) of the Colombo Stock Exchange for the period from 1990 to 2010. An assessment of the empirical evidence has been acquired through the co integration, error correction model and the Granger causality tests. This enabled us to search the relationship between stock prices and exchange rates both in the short –run and in the long –run. Empirical result shows that exchange rates and stock price data series are non stationary and integrated. Then we applied the Johansen procedure to test for the possibility of a co integration relationship. Results show that there is no co integration relationship between stock prices (ASPI) and any of the four exchange rates during the sample period. Finally, we applied the Granger causality test to find any causal relationship between stock prices and exchange rates. Outcomes show that there is one unidirectional causal relationship from stock prices to the US dollar exchange rate, from Sterling pound to stock prices not vice versa; there is a bidirectional causal relationship between Indian rupee and stock prices and no causal relationship between Japanese yen and stock prices. These results have important policy implications for potential investors as well as policy makers in the economy.
The Dynamic Sectoral Growth Linkages: Evidence from Sri Lanka
(5th National Conference on Applied Social Statistics (NRCASS) - 2019, Department of Social Statistics, Faculty of Social Sciences, University of Kelaniya, Sri Lanka, 2019) T. Sukirtha, T.; Sivarajasingham, S.; Balamurali, N.
An understanding of sectoral growth dynamics becomes more important for policy formulation in designing a balanced growth in the economy. This study attempts to examine the dynamic growth linkages among three major sectors; agriculture, industry and services of the Sri Lankan economy for the period 1960-2017. The variables used in this study are Agricultural GDP, Industrial GDP, Service GDP and Overall GDP. The data for the study are collected from the Central Bank Annual Report 2017. Graphical analysis including scatter plot, line graph, Confidence Ellipse and Nearest Neighbor fit are used to identify the basic features and the relationship between sectoral GDP series. Inter temporal correlation results show that there exists a high positive statistically significant correlation between all sectors GDP at 5 percent level. Unit root test results show that all GDP series are nonstationary. First difference of all log (GDPi) series are stationary. Engle-Granger (EG) co-integration test using fully modified OLS estimation provides evidence of long run equilibrium relationship between sectors. The results from ECM shows that the coefficient of error correction terms are statistically significant and had expected sign (negative) for all models, all sectors are positively related significantly even in the Short run. The diagnostic test results indicate that the results are robust. Granger causality tests indicate that Agriculture and Industrial Sector Granger cause economic growth significantly. It is also noted that overall economic growth Granger cause agriculture sector GDP. The investigation of causality analysis among sectors show that service and agriculture sectors are having two-way Granger causal relationship in the short run. In addition, Service sector Granger cause Industrial sector while Industrial Sector Granger cause Agricultural sector significantly. In contrast, Error correction term coefficient Granger causality indicator (ECT) shows that there is a significant causal relationship among sectors in the long run. Results indicate that agriculture sector Granger cause other sectors significantly and is base for livelihood for more people. Therefore, government needs to support agriculture sector to have stable overall economic growth. Empirical results indicate that all sectors are interlinked. However, study need to promote all sectors in effective and stable ways.
Informal Employment among Youth in the Post-War Northern Economy
(Sri Lanka Forum of University Economists (SLFUE), Department of Economics, Faculty of Social Sciences, University of Kelaniya, 2016) Balamurali, N.; Dunusinghe, P.