Search results

This study empirically aims to examine the relationship between Bangladesh’s pharmaceutical industry growth and macroeconomic indicators such as the inflation rate, gross domestic product (GDP) growth, foreign direct investment (FDI) inflows, exchange rate and export growth through the long- and short-run relationship.

Using the time series data from 1986 to 2020, this study was developed based on the autoregressive distributed lag (ARDL) framework for co-integration. In contrast, the Toda–Yamamoto Granger Causality approach was also used for finding the direction of causality.

This study used the ARDL bounds test, which found strong co-integration among the variables, indicating a long-term relationship between them. In the long run, inflation, exchange rate and export growth significantly positively influence the pharmaceutical industry’s growth. Surprisingly, an FDI inflow has a negative impact. In the short term, the exchange rate and GDP growth were found to influence the growth of the pharmaceutical industry positively. Bidirectional causality between the growth of the pharmaceutical industry and the exchange rate was also identified using the Granger causality approach.

This paper emphasizes developing the policy as well as making concrete decisions regarding the development of the pharmaceutical industry and economic development in Bangladesh. The results also highlight the necessity for strategic macroeconomic management to support this sector’s long-term development and global competitiveness.

To the best of the authors’ knowledge, this paper is conducted to identify the short- and long-run relationship of pharmaceutical industry development with the economic indicators and progress, where no study has been found on this dimension.

This study aims to investigate the interplay between renewable energy development, unemployment and GDP growth within Bangladesh, India, Pakistan and Sri Lanka. The research underscores the significant role of renewable energy plays in stimulating economic growth and mitigating unemployment, offering crucial policy insights for sustainable growth in South Asia.

Utilizing the autoregressive distributive lag (ARDL) framework and Toda Yamamoto causality through the vector autoregressive (VAR) approach, the study analyzes the long-term and short-term impacts of these variables from 1990 to 2019.

This study reveals a significant co-integration among renewable energy consumption, unemployment and GDP growth in selected South Asian countries. The long-term estimation shows renewable energy consumption influences negatively economic progression in Bangladesh, with no notable correlation with unemployment. In contrast, Sri Lanka demonstrates an optimal relationship among all the variables. Short-run assessments reveal a significant positive relationship between renewable energy consumption and economic growth in India, while an inverse relationship is evident in Pakistan. Moreover, the relationship between unemployment and economic progression, the result shows a negative and significant relationship in India and Sri Lanka.

The study emphasizes the need for policy development concerning renewable energy development, unemployment reduction and sustainable economic growth in South Asia. While limitations exist, future research can expand upon this work by incorporating varied data, additional countries or alternative modeling techniques.

This research offers a unique exploration into the multidimensional impacts of renewable energy consumption, unemployment and economic growth in the South Asian context, an area previously unexplored in such depth.