Browsing by Author "Kaluarachchi, S"

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Breaking the Glass Ceiling: The Impact of Board Gender Diversity on Firm Financial Performance in Sri Lanka
(Wiley, 2025-03-05) Kaluarachchi, S
The purpose of this study is to examine the influence of board gender diversity on the financial performance of firms in SriLanka. While extensive research has been conducted in developed countries, this study addresses the gap in literature by exam-ining how cultural and economic differences influence the relationship between gender diversity and corporate performance.Understanding this relationship in developing countries is crucial for shaping inclusive corporate governance policies and pro-moting sustainable development in diverse economic contexts. This study employs secondary data from the annual reports oflisted companies over the period 2012–2022, using panel regression and multiple linear regression models to explore the rela-tionship between board gender diversity and firm financial performance. The findings reveal that, despite Sri Lanka's corporateboards being predominantly male-dominated, the inclusion of female directors is positively associated with improved financialperformance. This is evident through factors such as the presence of female directors, female chairpersons, board size, CEOduality and firm age. In contrast, independent directors and leverage are found to have a negative impact on performance. Thestudy provides valuable insights for researchers, investors and policymakers, offering a roadmap for enhancing gender diversityin Sri Lanka's corporate governance and promoting sustainable development
Open Access
Impact of Socioeconomic Factors on Life Expectancy: A Global Perspective Across Income Levels
(John Wiley and Sons Ltd, 2026-01-26) Kaluarachchi, S; Jayathilaka, R
Socioeconomic factors influencing life expectancy are still underexplored across different income groups in global research.This study investigates the socioeconomic determinants of longevity across global income levels, drawing on World Bank datato analyze how various economic and social factors influence lifespan worldwide. A stepwise panel data regression analysiswas conducted to examine the determinants. The findings indicate that increase per capita gross domestic product and healthexpenditure substantially enhance lifespan, whereas increase population size, death rate, and infant mortality rate adverselyimpact life expectancy globally. In low-income countries, increase per capita gross domestic product, population size, and deathrate significantly shorten life expectancy. In lower-middle-income countries, growing population size and death rate progres-sively lower life expectancy. In upper-middle-income countries, higher per capita gross domestic product significantly boostslongevity, while increase carbon dioxide emissions, population size, death rate, and infant mortality rate substantially reducelife expectancy. In high-income countries, increase male education significantly raises lifespan, while increase population sizeand death rate reduce life expectancy. These findings can help policymakers, governments, the World Health Organisation, theUnited Nations, and the World Bank address key issues affecting life expectancy, promoting global health and sustainable eco-nomic growth
Open Access
Unveiling Sri Lanka’s brain drain and labour market pressure: A study of macroeconomic factors on migration
(Public Library of Science, 2024-03) Kaluarachchi, S; Jayathilaka, R
The purpose of this study is to explore the impact of GDP per capita income (GDPPCI), unemployment, higher education (HE), and economic growth (EG) on migration in Sri Lanka. Numerous global and local studies have explored the influence of macroeconomic and socioeconomic factors on migration. In the Sri Lankan context, fewer studies have probed the impact of GDPPCI, unemployment, HE, and EG on migration, particularly concerning brain drain and domestic labour market pressure. An applied research methodology was adopted, utilising annual data from 1986 to 2022. The statistical data were sourced from reports by the Sri Lanka Bureau of Foreign Employment (SLBFE), the Central Bank of Sri Lanka (CBSL), Labor Force Survey Data from the Department of Census and Statistics (LFSDCS), and University Grants Commissions (UGC). This study utilised the Vector Error Correlation model (VECM), Vector Auto-regression (VAR), and Granger Causality test through STATA. The empirical findings of the VAR model highlighted that GDPPCI and EG negatively impact migration, whereas unemployment and HE positively affect migration. The study’s implications demonstrated that GDPPCI, unemployment, HE, and EG were the primary factors influencing the country’s migration decisions. These findings will hopefully inform and guide the Sri Lankan government and policymakers for more effective decision-making. © 2024 Kaluarachchi, Jayathilaka. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Open Access
Unveiling Sri Lanka’s brain drain and labour market pressure: A study of macroeconomic factors on migration
(PLoS ONE, 2024-03-11) Kaluarachchi, S; Jayathilaka, R
The purpose of this study is to explore the impact of GDP per capita income (GDPPCI), unemployment, higher education (HE), and economic growth (EG) on migration in Sri Lanka. Numerous global and local studies have explored the influence of macroeconomic and socioeconomic factors on migration. In the Sri Lankan context, fewer studies have probed the impact of GDPPCI, unemployment, HE, and EG on migration, particularly concerning brain drain and domestic labour market pressure. An applied research methodology was adopted, utilising annual data from 1986 to 2022. The statistical data were sourced from reports by the Sri Lanka Bureau of Foreign Employment (SLBFE), the Central Bank of Sri Lanka (CBSL), Labor Force Survey Data from the Department of Census and Statistics (LFSDCS), and University Grants Commissions (UGC). This study utilised the Vector Error Correlation model (VECM), Vector Auto-regression (VAR), and Granger Causality test through STATA. The empirical findings of the VAR model highlighted that GDPPCI and EG negatively impact migration, whereas unemployment and HE positively affect migration. The study’s implications demonstrated that GDPPCI, unemployment, HE, and EG were the primary factors influencing the country’s migration decisions. These findings will hopefully inform and guide the Sri Lankan government and policymakers for more effective decision-making.