Does the causality between environmental sustainability, non-renewable energy consumption, geopolitical risks, and trade liberalization matter for Pakistan? Evidence from VECM analysis

The interconnectedness of energy consumption with economic growth: A granger causality analysis

In considering today's energy challenges, the link between the usage of renewable and non-renewable energy sources and economic growth has gained substantial policy attention. This research examines the complex relationship between these three variables to understand how non-renewable energy consumption and renewable energy consumption interact and what that means for economic growth. This study uses the Granger causality approach to explore the relationships between non-renewable energy consumption, renewable energy consumption, and economic development. It draws on a comprehensive dataset from the Word Bank database, including 152 nations from 1990 to 2019. The analysis is further disaggregated by four subgroups of countries; least developed, developed, transitional economies and developing countries. The result of this study provides valuable empirical evidence of uni-directional causality running from renewable energy consumption to economic growth and non-renewable energy consumption to economic growth in transitional economies. Furthermore, policymakers should focus on both variables when making decisions because the results show that energy consumption and economic growth are interconnected. Implementing global energy efficiency standards, reducing fossil fuel usage, and adopting regulatory measures are all viable policies for limiting adverse effects on the environment while encouraging economic development.

Unveiling Sri Lanka's brain drain and labour market pressure: A study of macroeconomic factors on migration

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.