{"title":"Foreign Direct Investment and Economic Growth Evidence from Sri Lanka","authors":"W. N. Sandani Fernando","doi":"10.4038/ss.v50i2.4725","DOIUrl":"https://doi.org/10.4038/ss.v50i2.4725","url":null,"abstract":"","PeriodicalId":362386,"journal":{"name":"Staff Studies","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115555333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Medha Kumari, Janaka Maheepala, K. Koswatte, Sachira Perera
Elasticity of demand for imports of Sri Lanka in the post-Civil War period up to March 2021 and the change in them during the COVID-19 pandemic were estimated. (Relative) price elasticity, (production) activity elasticity and exchange rate elasticity were estimated for aggregate and disaggregated imports using Ordinary Least Squares (OLS) techniques with and without dummies, Autoregressive Distributed Lag (ARDL), and Error Correction Modeling. We found that price elasticity of aggregate import demand is inelastic. With the removal of fuel from aggregate imports, elasticities increase marginally. Activity elasticities of aggregate import demand, non-food consumer goods, intermediate goods and investment goods are inelastic over the short run and elastic over the long run while short run elasticity declined during the pandemic. Demand for food is elastic with respect to relative prices and the exchange rate and price elasticity declined during the pandemic. Intermediate goods are not significantly related to prices and exchange rates but are related to production activity. Our results are important for implementation of monetary, exchange-rate, fiscal, and trade policies of Sri Lanka.
{"title":"Import Demand Elasticities of Sri Lanka from January 2010 to March 2021 and the Change in Elasticities during the COVID-19 Pandemic","authors":"Medha Kumari, Janaka Maheepala, K. Koswatte, Sachira Perera","doi":"10.4038/ss.v50i2.4726","DOIUrl":"https://doi.org/10.4038/ss.v50i2.4726","url":null,"abstract":"Elasticity of demand for imports of Sri Lanka in the post-Civil War period up to March 2021 and the change in them during the COVID-19 pandemic were estimated. (Relative) price elasticity, (production) activity elasticity and exchange rate elasticity were estimated for aggregate and disaggregated imports using Ordinary Least Squares (OLS) techniques with and without dummies, Autoregressive Distributed Lag (ARDL), and Error Correction Modeling. We found that price elasticity of aggregate import demand is inelastic. With the removal of fuel from aggregate imports, elasticities increase marginally. Activity elasticities of aggregate import demand, non-food consumer goods, intermediate goods and investment goods are inelastic over the short run and elastic over the long run while short run elasticity declined during the pandemic. Demand for food is elastic with respect to relative prices and the exchange rate and price elasticity declined during the pandemic. Intermediate goods are not significantly related to prices and exchange rates but are related to production activity. Our results are important for implementation of monetary, exchange-rate, fiscal, and trade policies of Sri Lanka.","PeriodicalId":362386,"journal":{"name":"Staff Studies","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128881378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper explores the relationship between budget deficits and inflation in Sri Lanka using three approaches: the Granger causality test, Auto Regressive Distributed Lag (ARDL)/Bound test, and ARDL long run cointegration coefficients analysis with time series data for the time period of 1957-2016. Three statistical procedures are also exploited in the study, namely, Toda-Yamamoto (1995) Granger causality test, ARDL/Bound test procedure developed by Pesaran and Shin (1999) and Pesaran et al. (2001), and ARDL Error Correction Model. Moreover, four model specifications are formed that are distinguished by two budget deficit indicators, namely, the budget deficit scaled by narrow money (BDMI), which was developed by Catao and Terones (2003), conventional budget deficit indicator, which is the budget deficit as a per cent of Gross Domestic Product (BDGDP), and two inflation indicators, namely the Consumer Price Index (CPI) and GDP deflator. The findings of the study are statistically significant at acceptable levels (p=10%, p=5%, and p=1%). The results suggest a unidirectional causality coming from the budget deficits to inflation in Sri Lanka and the existence of a long run cointegration with high magnitudes, which interprets that a one percentage point change in natural logarithms of BDM1 and LNBDGDP, will result in a 1.5-2.5 per cent change in inflation in Sri Lanka as measured by natural logarithms of Colombo Consumer Price Index (LNCCPI) and Gross Domestic Product Deflator (LNGDPD). Further the study concludes that the importance of maintaining low budget deficits in view of reaching inflation targeting in Sri Lanka.
{"title":"Budget Deficits and Inflation: The Case of Sri Lanka","authors":"K. Munasinghe","doi":"10.4038/ss.v50i2.4723","DOIUrl":"https://doi.org/10.4038/ss.v50i2.4723","url":null,"abstract":"This paper explores the relationship between budget deficits and inflation in Sri Lanka using three approaches: the Granger causality test, Auto Regressive Distributed Lag (ARDL)/Bound test, and ARDL long run cointegration coefficients analysis with time series data for the time period of 1957-2016. Three statistical procedures are also exploited in the study, namely, Toda-Yamamoto (1995) Granger causality test, ARDL/Bound test procedure developed by Pesaran and Shin (1999) and Pesaran et al. (2001), and ARDL Error Correction Model. Moreover, four model specifications are formed that are distinguished by two budget deficit indicators, namely, the budget deficit scaled by narrow money (BDMI), which was developed by Catao and Terones (2003), conventional budget deficit indicator, which is the budget deficit as a per cent of Gross Domestic Product (BDGDP), and two inflation indicators, namely the Consumer Price Index (CPI) and GDP deflator. The findings of the study are statistically significant at acceptable levels (p=10%, p=5%, and p=1%). The results suggest a unidirectional causality coming from the budget deficits to inflation in Sri Lanka and the existence of a long run cointegration with high magnitudes, which interprets that a one percentage point change in natural logarithms of BDM1 and LNBDGDP, will result in a 1.5-2.5 per cent change in inflation in Sri Lanka as measured by natural logarithms of Colombo Consumer Price Index (LNCCPI) and Gross Domestic Product Deflator (LNGDPD). Further the study concludes that the importance of maintaining low budget deficits in view of reaching inflation targeting in Sri Lanka.","PeriodicalId":362386,"journal":{"name":"Staff Studies","volume":"1041 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116465549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research attempts to determine the effects of asset quality on the banking profitability of commercial banks in Sri Lanka. This study is based on secondary data for the period 2008 to 2016, which are obtained from annual reports published by 9 commercial banks in Sri Lanka. The analysis based on panel fixed effect regression indicates that asset quality factors had a negative impact on the bank’s profitability at a statistically insignificant level. This was mainly because asset quality does not solely determine the profitability of banks. Other factors such as capital adequacy, management efficiency, earnings performance and liquidity may also contribute to profitability. Based on the findings, this study recommends that improved investment assets levels and the low rate of non-performing assets needs to be realized through credit risk identification, measurement, monitoring and controlling, in order to achieve high asset quality levels. Accordingly, this study recommends that banks improve credit policy by obtaining collateral and adhering to strong credit risk assessment indicators by following post sanction risk monitoring mechanism.
{"title":"The Impact of Asset Quality on Profitability: A Panel Data Analysis of Domestic Commercial Banks in Sri Lanka","authors":"P. D. M. Sanathanee","doi":"10.4038/ss.v50i1.4722","DOIUrl":"https://doi.org/10.4038/ss.v50i1.4722","url":null,"abstract":"This research attempts to determine the effects of asset quality on the banking profitability of commercial banks in Sri Lanka. This study is based on secondary data for the period 2008 to 2016, which are obtained from annual reports published by 9 commercial banks in Sri Lanka. The analysis based on panel fixed effect regression indicates that asset quality factors had a negative impact on the bank’s profitability at a statistically insignificant level. This was mainly because asset quality does not solely determine the profitability of banks. Other factors such as capital adequacy, management efficiency, earnings performance and liquidity may also contribute to profitability. Based on the findings, this study recommends that improved investment assets levels and the low rate of non-performing assets needs to be realized through credit risk identification, measurement, monitoring and controlling, in order to achieve high asset quality levels. Accordingly, this study recommends that banks improve credit policy by obtaining collateral and adhering to strong credit risk assessment indicators by following post sanction risk monitoring mechanism.","PeriodicalId":362386,"journal":{"name":"Staff Studies","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125988744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study starts with an analysis of macroeconomic determinants on growth in the case of Sri Lanka, deploying the Autoregressive Distributed Lag (ARDL) approach using annual data from 1960 to 2018. Key findings of the study reveal that utilising the available policy spaces to create an investment conducive climate and to support exports is essential while revisiting the imports structure to understand the necessary potential improvements. Unexpectedly, total employment does not show a significant influence on the movement in real GDP, emphasizing the challenging need for labour market reforms for enhancing workplace efficiency and proper labour management. Results show that the civil war arrested the revival of the economy and rejected the tourism-led growth hypothesis. Beyond the ARDL model, a Generalised Least Squares Panel Data model is employed, to analyse the impact of regional integration in the South Asian context on the growth of the Sri Lankan economy. Results of the Fixed Effects models prove that trade liberalisation drives the growth of panel economies and the existence of a non-linear positive relationship between export concentration and real per capita GDP growth. Accordingly, one could conclude that the growth of SAARC economies could flourish with trading amongst themselves, accompanied by free trade agreements.
{"title":"Investigating Growth Performance of Sri Lanka","authors":"K. K. C. S. Kannangara","doi":"10.4038/ss.v50i1.4721","DOIUrl":"https://doi.org/10.4038/ss.v50i1.4721","url":null,"abstract":"This study starts with an analysis of macroeconomic determinants on growth in the case of Sri Lanka, deploying the Autoregressive Distributed Lag (ARDL) approach using annual data from 1960 to 2018. Key findings of the study reveal that utilising the available policy spaces to create an investment conducive climate and to support exports is essential while revisiting the imports structure to understand the necessary potential improvements. Unexpectedly, total employment does not show a significant influence on the movement in real GDP, emphasizing the challenging need for labour market reforms for enhancing workplace efficiency and proper labour management. Results show that the civil war arrested the revival of the economy and rejected the tourism-led growth hypothesis. Beyond the ARDL model, a Generalised Least Squares Panel Data model is employed, to analyse the impact of regional integration in the South Asian context on the growth of the Sri Lankan economy. Results of the Fixed Effects models prove that trade liberalisation drives the growth of panel economies and the existence of a non-linear positive relationship between export concentration and real per capita GDP growth. Accordingly, one could conclude that the growth of SAARC economies could flourish with trading amongst themselves, accompanied by free trade agreements.","PeriodicalId":362386,"journal":{"name":"Staff Studies","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124702448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Determinants of Microfinance Interest Rates: Case of Sri Lanka","authors":"Indeewari U. Colombage, Tharanga A. D. Wijayakoon","doi":"10.4038/ss.v49i2.4719","DOIUrl":"https://doi.org/10.4038/ss.v49i2.4719","url":null,"abstract":"","PeriodicalId":362386,"journal":{"name":"Staff Studies","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122391798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Real Wages, Inflation and Labour Productivity: Evidence from the Public and Private Sectors in Sri Lanka","authors":"R. D. Liyanage","doi":"10.4038/ss.v49i2.4718","DOIUrl":"https://doi.org/10.4038/ss.v49i2.4718","url":null,"abstract":"","PeriodicalId":362386,"journal":{"name":"Staff Studies","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123888626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Does Composition of Public Expenditure Matter for Economic Growth? Lessons from Sri Lanka","authors":"M. Kesavarajah","doi":"10.4038/ss.v49i2.4717","DOIUrl":"https://doi.org/10.4038/ss.v49i2.4717","url":null,"abstract":"","PeriodicalId":362386,"journal":{"name":"Staff Studies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126257975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study analyses Sri Lanka’s Total Factor Productivity (TFP) change during conflict and post-conflict periods to assess whether there has been any improvement during the post-conflict period using Solow’s Residual Method (SRM)) and an index number approach (Hicks-Moorsteen Total Factor Productivity Index - HMTFPI). Findings of both approaches reveal that the TFP growth during the conflict period was higher than that of the post-conflict period. Based on the decomposition of HMTFPI into Technological Change (TC) and Efficiency Change (EC) indices, it was revealed that the main source of TFP change throughout the sample period is TC. EC had been negative throughout the sample period.
{"title":"Sri Lanka’s Total Factor Productivity Change during Conflict and Post-Conflict Periods","authors":"Tharindi Nugawela","doi":"10.4038/ss.v49i1.4714","DOIUrl":"https://doi.org/10.4038/ss.v49i1.4714","url":null,"abstract":"This study analyses Sri Lanka’s Total Factor Productivity (TFP) change during conflict and post-conflict periods to assess whether there has been any improvement during the post-conflict period using Solow’s Residual Method (SRM)) and an index number approach (Hicks-Moorsteen Total Factor Productivity Index - HMTFPI). Findings of both approaches reveal that the TFP growth during the conflict period was higher than that of the post-conflict period. Based on the decomposition of HMTFPI into Technological Change (TC) and Efficiency Change (EC) indices, it was revealed that the main source of TFP change throughout the sample period is TC. EC had been negative throughout the sample period.","PeriodicalId":362386,"journal":{"name":"Staff Studies","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132430999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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