2024

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    Impact of Artificial Intelligence (AI) on the Labor Market in Developing Countries
    (UMT, Lahore, 2024) Momina Humayun
    This study investigates the interplay between artificial intelligence (AI), technological adoption, and economic variables, focusing on their implications for unemployment and economic growth. Employing the Autoregressive Distributed Lag (ARDL) and Dynamic Ordinary Least Squares (DOLS) methodologies, the study examines macroeconomic data to uncover long-term determinants of unemployment. AI and machine learning (ML) adoption demonstrate a positive association with reduced unemployment, reflecting their potential to generate new job opportunities. Conversely, increased digitization through data science (DS) correlates with decreased unemployment, underscoring the importance of digital skills in modern economies. The key insights of this study shed light on the perspectives to existing literature, revealing complex interactions between AI adoption, economic growth, and labor markets. While supporting traditional economic theories on technological impacts, such as skill-based technological change (SBTC), the findings also challenge some prevailing notions. Overall, this research underscores the multifaceted nature of AI's economic impact, emphasizing the outcomes of the labor market in the developing countries. It further suggests some more avenues for future research by considering dynamics of technological adoption and economic outcomes
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    NEXUS OF PUBLIC EXPENDITURES AND ECONOMIC GROWTH: EVIDANCE FROM SELECTED DEVELOPING ASIAN COUNTRIES
    (UMT, Lahore, 2024) Israr Ullah
    This thesis delves into the intricate relationship between public expenditures and economic growth across 50 developing Asian countries from 2007 to 2019, employing the Feasible Generalized Least Squares (FGLS) method. Against the backdrop of rapid economic transformations and policy interventions in the region during this period, understanding the dynamics of public spending and its impact on economic development is crucial for informed policymaking. By examining a diverse sample of developing Asian nations, this study employs robust econometric techniques to analyze the multifaceted interplay between different categories of public expenditures and their implications for economic growth. Infrastructure development, education, healthcare, and defense spending are among the key areas scrutinized to uncover their respective impacts on economic performance. Utilizing the FGLS method allows for the mitigation of potential issues such as heteroscedasticity and serial correlation, ensuring the reliability of the statistical analyses conducted. The findings of this research contribute significantly to the existing body of knowledge on economic development strategies in Asia, offering nuanced insights into the effectiveness of public expenditure allocations in fostering sustainable and inclusive growth Keywords: Economic growth,