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Research Article
Policy Pathways for Progress: Study of Economic, Environmental, and Governance Determinants of HDI in Pakistan
expand article infoImran Ali§
‡ Government College university, Faisalabad, Pakistan
§ Higher school of Economics, Russia, NizhnyNovgorod, Russia
Open Access

Abstract

This study examines the key economic, environmental and governance determinants of the Human Development Index (HDI) in Pakistan, using a multidimensional framework to analyze their long- and short-term dynamics. Using annual data from 1990 to 2022 the research applies Johansen Cointegration Test and Vector Error Correction Model (VECM) to assess the relationships between HDI and factors that may exert influence on its dynamics, including exports, remittances, military expenditure, carbon dioxide emissions, debt service, population growth, and women’s parliamentary representation. Its findings reveal that governance and demographic factors, particularly women’s representation in parliament and population growth, have significant positive impacts on the country’s HDI in the long run, highlighting the importance of inclusive governance and resource management. Conversely, economic variables such as exports and remittances appear to have negative long-term effects on the HDI, suggesting structural inefficiencies in Pakistan’s trade and remittance policies. Environmental degradation, represented by carbon dioxide emissions, poses a significant challenge with adverse effects on the HDI, in both the short and long term. Military expenditure demonstrates dual effect: while it supports the HDI in the long run by fostering stability, in the short run it diverts resources away from critical social investments. The study emphasizes the need for policy reforms to diversify exports, formalize remittance channels, and adopt sustainability-focused environmental strategies. To promote equitable development, it is essential to increase women’s representation in governance and balance the defense and social spending. This research contributes new insights by integrating economic, environmental, and governance dimensions into unified analytical framework tailored to Pakistan’s socioeconomic context and provides actionable recommendations for policymakers to prioritize sustainable and inclusive development initiatives in line with the global Sustainable Development Goals (SDGs).

Keywords

HDI, Pakistan, governance, economic determinants, environmental impact, VECM Model, remittances, CO2 emissions, military expenditure.

JEL: I31, O53, Q56, F22, H56, J16.

1. Introduction

Human development as a multidimensional concept encompassing health, education and living standards is central to socio-economic progress, and global development paradigms increasingly focus on inclusive and sustainable growth. The Human Development Index (HDI) has become a key measure of the well-being of the world’s nations. For the Republic of Pakistan, a developing country facing socio-economic challenges, understanding the drivers of HDI should provide valuable insights for designing policy frameworks that promote equitable development. Despite progress in some areas, Pakistan lags behind in critical HDI components, education and health outcomes, which calls for a comprehensive examination of the factors influencing human development in the country. Global research highlights the importance of economic, environmental, and governance issues for human development outcomes. Trade, represented by exports, has been consistently considered a catalyst for economic growth and human development. As this study examines the drivers of HDI in Pakistan Jermsittiparsert et al. (2019) which confirmed government expenditure as a key driver of GDP growth. Given Pakistan’s fiscal challenges optimizing public spending could enhance both economic performance and human development outcomes. Some parallels can be drawn with Pakistan, but the country faces unique challenges, including low export diversification and infrastructure bottlenecks, which limit its ability to effectively use trade for human development. Remittances, another critical economic variable, play a transformative role in developing countries by contributing to improvements in education, income and life expectancy, all essential components of the HDI (Khan, 2015; Kashif Imran, 2017). However, their developmental potential remains underutilized in Pakistan owing to misallocation of resources and weak institutional frameworks. Military expenditure, often seen as a trade-off against human development, has a nuanced impact in different contexts. Pérez-Cárceles (2024) found a positive but diminishing effect of military spending on the HDI in the G20 countries, in contrast to Looney (1990) who highlighted its detrimental influence in South Asia. Environmental sustainability is another pressing concern, with carbon emissions often at odds with sustainable development goals. Li et al. (2022) point out the importance of decoupling economic growth from carbon emissions, which is a serious challenge for countries like Pakistan where energy efficiency remains low. Governance factors, such as female representation in parliament, also significantly influence human development as shown by Razmi et al. (2018) and Tandoh-Offin (2010) who found that increasing women’s participation in governance leads to inclusive policies that boost education and healthcare outcomes.

Figure 1. 

Results estimated using Excel Microsoft (authors’ analysis)

The graphically represented trends show the key factors that influenced HDI in Pakistan between 1990 and 2022. While rising women’s parliamentary representation reflects progress in inclusive governance, declining export contributions and increasing carbon emissions highlight structural incompetence and environmental challenges. Remittances that are critical to household incomes are underutilized in promoting HDI components, such as education and health. Taken together, these trends point to the need for multidimensional policy reforms to foster sustainable human development.

Figure 2. 

Results estimated using Excel Microsoft (authors’ analysis)

Despite the wealth of research, gaps remain in understanding the relationship between these variables in Pakistan’s unique socio-economic and political context. Although previous studies provide general insights into some of the factors affecting HDI globally or regionally, few of them have focused on Pakistan’s specific development dynamics. For example, studies of remittances and exports often overlook how institutional inefficiencies and governance failures mediate their effects. Similarly, while military expenditure and carbon emissions are widely analyzed in global contexts, their joint impact on human development in Pakistan remains underexplored; the role of gender representation in the country’s governance, particularly in shaping HDI outcomes, has not been sufficiently investigated.

The current literature tends to focus on isolated relationships, ignoring the holistic and interrelated nature of the variables. The paper addresses these gaps by using a multidimensional framework and powerful econometric techniques to identify the economic, environmental and governance determinants of HDI in Pakistan, incorporating both long- and short-term dynamics.

The research has critical policy relevance for Pakistan, a nation striving to improve its socio-economic indicators amidst economic instability and resource constraints. By identifying the factors that significantly influence the country’s HDI, it provides policymakers with actionable evidence to prioritize interventions that maximize human development. For instance, understanding the role of exports and remittances can help the government design trade and labor policies that align with development goals. Similarly, insights into trade-offs between military expenditure and HDI can inform budgetary decisions that balance security and social welfare.

The study also contributes to the global discourse on sustainable development as it highlights the interplay between environmental sustainability and human development in developing countries. Focusing on governance issues, such as women’s representation, that are in line with global gender equality goals, it has significant practical implications for promoting inclusive development in Pakistan.

The paper addresses the overarching question: what are the key economic, environmental, and governance determinants of the Human Development Index (HDI) in Pakistan, and how do they influence short- and long-term development outcomes? To answer this, it examines four critical sub-questions. First, it needs to find out how economic factors, such as exports, remittances, and debt service, impact the HDI in Pakistan. Second, the study explores the relationship between military expenditure and HDI, assessing potential trade-offs between defense spending and social welfare. Third, it assesses the impact of environmental factors, particularly carbon emissions, on human development, focusing on how environmental degradation intersects with development progress. Lastly, the paper examines the role of governance by analyzing how women’s parliamentary representation shapes HDI outcomes and contributes to inclusive policymaking.

The primary goal of this paper is to comprehensively analyze the determinants of HDI in Pakistan with a focus on economic, environmental, and governance factors. To achieve this, specific objectives are outlined. First, the study aims to assess the long-term and short-term impacts of economic variables — exports, remittances, and debt service — on the HDI, offering insights into their respective contributions to human development. Second, it seeks to investigate the trade-offs between military expenditure and human development for balancing the national security needs with investment in social sectors. Third, the research evaluates the effects of carbon dioxide emissions on HDI, highlighting the environmental sustainability dimension and the challenges posed by Pakistan’s carbon footprint. Finally, it examines female parliamentary representation as a governance variable, exploring its potential to foster equitable and inclusive development policies that enhance HDI.

By achieving these objectives, the study aims to gain a holistic understanding of the factors driving human development in Pakistan and provide evidence-based insights for policymakers to prioritize interventions that are consistent with sustainable and inclusive development goals. It contributes to the existing literature by integrating multiple dimensions of human development into unified analytical framework tailored to Pakistan’s socio-economic context. Unlike previous studies that have focused on individual variables, this research captures the interconnectedness of economic, environmental, and governance factors. The use of Vector Error Correction Model (VECM) allows the simultaneous examination of long- and short-term dynamics, providing nuanced understanding of how these factors interact over time. Furthermore, the study’s emphasis on governance variables, particularly women’s parliamentary representation, adds gender-focused perspective to the human development discourse, in line with global Sustainable Development Goals (SDGs). By addressing the environmental dimension through issues related to carbon emissions, the research highlights the importance of balancing economic growth with sustainability. Its comprehensive analysis of HDI determinants in Pakistan aims to fill key research gaps, advance academic understanding and inform evidence-based policymaking for sustainable and inclusive development.

2. Literature Review

Rohim et al. (2023) examined the impact of Human Development Index (HDI), government expenditure, exports and imports on economic growth in the ASEAN-5 countries from 2010 to 2021 using panel data regression; their findings indicate significant positive impact of exports on economic growth and emphasize the need to improve export performance through better administration, research and development, infrastructure investment, exchange rate stability, and market diversification.

Afzal et al. (2009) looked into short- and long-term relationships between human development, exports and economic growth in Pakistan using the ARDL framework and data between 1970–71 and 2008–09. The results show cointegration between economic growth, physical capital, exports and human development, with human development as the dependent variable; they support the “growth-driven exports hypothesis,” discovering a unidirectional causality from real GDP to exports, and reject the “export-led growth hypothesis” and the human capital-based endogenous growth theory.

Since 2009, however, significant structural changes have taken place in Pakistan’s economic and governance landscape necessitating updated empirical research into the HDI. Besides, Afzal et al. do not take into account the key contemporary challenges, such as environmental sustainability, governance reforms and changing macroeconomic conditions. Some recent studies have highlighted the evolving dynamics affecting HDI in Pakistan, e.g. Kashif (2017), who found that remittances are becoming more and more important for households but remain underutilized for productive investment, a factor not explored in previous research. Pervaiz and Farooq (2021) show the negative impact of carbon emissions on Pakistan’s HDI, in line with global trends of increasing environmental degradation. The long-run negative effect of debt servicing on GDP growth corroborates earlier findings on its detrimental impact on Pakistan’s human development trajectory (Ali et al., 2025) indicating broader socio-economic ramifications beyond macroeconomic stagnation.

Zehra, N., & Alam, S. (2015) emphasized the complex relationship between trade liberalization and HDI, in contrast to the linear export-driven growth model discussed by Afzal et al. Umar (2021) provided insights into how remittances influence the human development in Pakistan’s weaker institutional environment, a dimension absent in earlier studies.

The political landscape has also changed, particularly with the increased participation of women in politics, which has been shown to have a positive impact on human development (Seyed et al., 2012; Tripp & Kang, 2008). The present study takes a more comprehensive approach: it integrates the governance, economic and environmental determinants of HDI to capture both short- and long-term dynamics and updates the empirical understanding of these determinants in Pakistan with a multidimensional perspective, thus filling the crucial research gap and addressing structural inefficiencies in trade and use of remittances.

Gani (2019) examined the impact of export type on human development for a sample of 107 countries between 2009 and 2014, focusing on exports of high-tech products, fuels, ores, and agricultural raw materials. The study found that exports of fuel, ores and high-tech products are positively and significantly correlated with human development, the correlation coefficients being 0.020, 0.050, and 0.090, respectively. The export types, among other factors, influence human development with the coefficient of determination ranging from 0.460 for high-tech exports to 0.710 for fuel exports. This research highlights the crucial role of export diversification, particularly in high-tech sectors, as a driver of improving human development outcomes globally. Davies and Quinlivan (2006) explored the factors influencing human development by using Dynamic Panel Dat and GMM estimators. Their findings indicate that trade has a positive and significant impact on human development. Specifically, an increase in per capita imports, exports and trade leads to an increase in the HDI of 0.029, 0.024, and 0.025 points, respectively. Educational expenditures, per capita health expenditure, and foreign direct investment also positively and significantly influence human development. Ali (2024) identified structural inefficiencies in Pakistan’s export and remittance systems and revealed how overdependence on traditional sectors and informal remittance channels undermines long-term human capital investments. This aligns with findings that macroeconomic variables like exports and remittances may paradoxically hinder development if not coupled with institutional reforms. Such insights underscore need for diversified trade policies and formalized remittance mechanisms to enhance human development outcomes Nigar et al. (2022) compared the impact of trade liberalization on human development in the developed and developing countries using data from seven countries in each group for the period 2005 to 2019. The study found that trade liberalization and economic growth (GDP) promoted human development in both developed and developing economies, while population growth had a negative impact. The study highlighted the complex interplay between trade liberalization, economic growth, and human development across different economic contexts.

Li et al. (2022) looked into the relationship between carbon emissions and the Human Development Index (HDI). They analyzed the decoupling process between carbon emissions per capita and the HDI from 1990 to 2019 in 189 countries. The study has found that countries with high HDI tend to show strong decoupling and some of the countries with low HDI also achieved this, albeit in an unstable manner. The study identified economic development as the main inhibitor of achieving strong decoupling, while carbon productivity improvements in countries like the Czech Republic, Germany, and UK are significant drivers of CEP growth. In contrast, energy intensity and welfare effects hinder CEP in these countries and also in Turkey and South Korea. Minhas et al. (2021) examine the bidirectional relationships between healthcare expenditures, carbon dioxide (CO2) emissions and Human Development Index (HDI) in 33 OECD countries from 2006 to 2016. Using panel vector autoregression model based on generalized method of moments (GMM) estimations, they have found that all three variables - healthcare expenditures, CO2 emissions and HDI - are causally related: firstly, there is a bidirectional causality between healthcare expenditures and CO2 emissions, i.e. higher emissions lead to higher health expenditure and vice versa, and, secondly, there is a positive bidirectional relationship between health expenditure and HDI. The interplay between carbon emissions and HDI has become critical area of research as nations grapple with dual challenge of fostering economic growth while mitigating climate change. The adverse impact of carbon emissions on Pakistan’s HDI mirrors findings from cross-national studies. Ali et al. (2024) demonstrated that environmental sustainability is critical for equitable growth in emerging economies, emphasizing how unchecked industrialization compromises health and education outcomes. This validates urgency of integrating climate action into Pakistan’s development agenda to mitigate long-term ecological and social costs. Li et al. (2022) contributed to this discourse by examining the decoupling relationship between per capita carbon emissions and HDI, analyzed data from 189 countries between 1990 and 2019. Their study extended the low-carbon transition debate beyond purely environmental metrics integrating welfare dimensions to assess whether human well-being can advance without exacerbating carbon footprints. Abdulaziz and Alajlan (2021) analyze the relationship between carbon dioxide (CO2) emissions and the Human Development Index (HDI) using quantile regression for G20 countries and found a negative marginal relationship between CO2 emissions and HDI across the quantiles from 0.2 to 1, suggesting that higher human development is associated with lower CO2 emissions in these countries. This implies that, as the HDI increases thanks to improvements in socio-economic factors such as healthcare, education, and infrastructure, CO2 emissions tend to decrease. Pervaiz et al. (2021) examine the relationship between HDI and carbon dioxide emissions (COEM) and the role of health expenditure in ensuring sustainable development. They confirm the negative relationship between HDI and COEM, suggesting that higher HDI is associated with lower carbon emissions: as countries improve their human development, they are better able to reduce carbon emissions thereby promoting sustainable development. Alnail et al. (2019) analyze the relationship between HDI and sector-specific CO2 emissions in the top ten emitting countries. This relationship appears to be strong, i.e. as HDI increases, CO2 emissions continue to be influenced by factors such as economic growth and development. The results suggest that the progress in human development, driven by economic growth and other development factors, has a substantial impact on the level of carbon emissions in these countries. Jermsittiparsert et al. (2019) This paper explored the impact of government spending on economic growth in ASEAN-5 countries from 1990 to 2014. Used panel data, the study found that public expenditure significantly influences GDP growth, which is crucial for economic development. Since GDP per capita is key component of the HDI effective fiscal policies can indirectly boost HDI by improving income levels and enabling investments in health and education. However, inefficient spending may hinder growth. The study suggested future research should examine sector-specific expenditures to better understand their direct effects on HDI, helping policymakers optimize public spending for sustainable development.

Kerdrain, Koske, and Wanner (2011) explore how structural reforms that enhance productivity and increase public spending can contribute to healthier current account balance, which in turn can lead to improved HDI outcomes. Their study suggests that such reforms boost economic efficiency, foster sustainable growth and help stabilize the current account, which not only supports economic development but also positively influences social indicators, including HDI. The paper highlights the importance of economic policies aimed at boosting productivity and public investment for long-term human development. Banerjee and Goyal (2021) examine the role of domestic and external factors in current account imbalances for large emerging markets and conclude that emerging markets with better governance and financial development tend to have healthier current accounts and higher HDI outcomes through provision of improved public services. This means that effective governance and financial sector development are crucial for promoting sustainable economic growth and improving human development indicators.

Pérez-Cárceles (2024) uses panel data from G20 countries over period 1990-2021to explore the relationship between military expenditure and HDI. The study, which employs dynamic panel data models regarding military expenditure with a two-year lag as a determinant of the HDI, among other control variables, suggests that military expenditure has a positive effect on human development; this effect, however, diminishes in the second lag. The paper concludes that human security should be considered a complementary indicator of HDI. It demonstrates the importance of maintaining a stable environment for continued human development, especially in light of recent global events such as pandemics and geopolitical tensions. Akust (2024) examines the impact of military expenditures on sustainable development in the NATO countries using data from 1995 to 2019. According to the study, military expenditures and industrial production index have a negative impact on sustainable development in the NATO countries, while FDI has a positive impact. The impact of primary energy consumption is negative but less significant. The study also reveals significant differences in how military expenditures affect sustainable development across different NATO countries. Elgin et al. (2022) explore the relationship between military expenditures and HDI components, focusing on educational attainment, life expectancy, mortality, and poverty rates. They have found that military spending negatively impacts some of the HDI components, e.g. education and life expectancy, but correlates positively with mortality and poverty rates. Looney’s research (1990) into the relationship between defense spending and human capital development in Middle East and South Asia led the author to conclude that increased military spending adversely affects human resource development in these regions, suggesting a trade-off between defense spending and investment in human capital.

The work by Pradhan and Khan (2015) regarding the impact of remittances on the quality of life in Bangladesh, uses the HDI analysis based on data 1981 to 2011 and the VEC model to discover a long run causal relationship between remittances and HDI. The results suggest that increasing remittances positively influence income, education, and life expectancy – the key components of HDI – and therefore improve the overall quality of life. The study by Kashif Imran, 2017 examines the impact of migrant remittances on the household-based Human Development Index (HHDI) in Punjab, Pakistan and shows that households that receive remittances have better housing conditions and lower poverty levels compared to the households without migrating members. Remittances also promote skill development and entrepreneurship and thus contribute to achieving sustainable development goals and have positive influence on the HDI in the addressed countries. The paper by Mamtani, Lowenfels, Cheema, and Sheikh (2014) explores the impact of migrant workers, particularly guest workers, on HDI. The authors focus on the negative effect of migrant guest worker status on educational component of the HDI in highly or very highly developed countries, highlighting the importance of migration policy and its implications for human development in advanced economies. The complementarity between remittances and human capital development in reducing income inequality in emerging markets was examined by Kunofiw Tsaurai (2018), who showed how remittances could contribute to human capital development: when used effectively they can complement human capital development efforts by improving education, healthcare, and skill acquisition. This in turn may help reduce income inequality and promote more equitable economic growth in emerging markets. Umar (2021) has shown that personal remittances have a positive and significant impact on human development in sub-Saharan Africa, particularly in the countries with weak institutional environments, where they compensate for the lack of capital needed to improve the HDI. In Kenya, however, foreign remittances had a negative and significant impact on the education index, which probably means that these remittances were not spent on education. This misallocation affected the overall HDI through its education component: the remittances contributed to household income, but were not sufficiently directed towards long-term human capital development, such as education, which is essential for sustainable development.

The study by Wahyuningrum and Soesilowati (2021) shows that population growth has a significant positive effect on HDI in East Jav Province. This suggests that, as population increases, human development improves, possibly because of larger labor force and demographic factors that contribute to overall social development. At the same time, it appears that economic growth and unemployment rates have not had a significant impact on HDI in the region. Febrianty, Yosmaliza, and Suryantoro (2022) do not specifically analyze the impact of population dynamics on HDI; instead, they focus on the relationship between the HDI, population size and poverty levels in Papua from 2012 to 2017. This relationship tends to be negative, suggesting that increases in population may exacerbate poverty in the region, despite improvements in the HDI. The paper by Zgheib, Ahmed, Beldona, and Gebar (2006) looks at the impact of population growth on the HDI in Middle Eastern countries. Population growth in the region does not obviously have a substantial impact on the HDI, although it does reduce per capita income. The effects of population growth on education and health, the key components of HDI, are found to be insignificant. Faltsman (2022) emphasizes the need to regulate the population size in order to improve the HDI in developing countries. The researcher argues that reducing birth rates and controlling population growth can help alleviate poverty, reduce migration pressures, and lessen environmental impact of human activities. The paper by Sabyasachi and Tripathi (2021) shows that on the whole the urban populations positively correlate with the HDI values in both absolute and relative terms. However, the percentage of the urban population living in the largest cities can have a negative impact on the HDI, with the effect varying according to the countries’ development stage and urbanization levels. The research indicates that in Pakpaka Bharat district, increase in population can negatively affect the HDI. Finally, Hasna, F., & Ratnasari, R. T. (2023) find that urban population moderates the effect of health and labour force but not the effect of education on the HDI in the OIC member countries.

Governance factors, such as women’s representation in parliament, play a crucial role in shaping human development outcomes. Razmi et al. (2018) finds that increased female participation in governance leads to more inclusive policies, particularly in education and healthcare, contributing positively to the HDI. Likewise, Tandoh-Offin (2010) highlights that women’s representation in legislative bodies strengthens gender-sensitive policymaking and promotes equitable development. More recent studies support these findings demonstrating that higher women’s parliamentary representation correlates with improved social spending and policy inclusivity (Bush & Zetterberg, 2021; Tripp & Kang, 2008; Clayton, 2021). Given Pakistan’s socio-political landscape where gender disparities in political participation persist, research on the issues related to women’s representation in governance should provide valuable insights into its potential to enhance human development. The significance of female parliamentary representation in enhancing HDI resonates with governance-focused research. Ali (2024) highlighted how inclusive governance models in BRICS nations fostered resource allocation toward education and healthcare, directly boosting human capital. Similarly, progress hinges on amplifying women’s political participation to ensure equitable policy prioritization as structural inequalities persist in resource distribution (Ali et al., 2024). The paper by Stolt (2013) does not consider the numbers of women’s parliamentary seats but explores the broader relationship between gender equality in national parliaments and economic growth. Stolt argues that increased female representation in parliamentary bodies may lead to more inclusive policies, which could theoretically improve human capital development and contribute to higher economic growth. Although the paper does not provide direct evidence linking women’s parliamentary representation to HDI, it implies that promoting gender equality in political institutions can have positive implications for overall economic development and thus improve human development outcomes.

The existing literature provides a comprehensive understanding of the key determinants of the Human Development Index (HDI) including economic, environmental and governance factors. Studies on trade and remittances have widely acknowledged their role in promoting economic growth and human development, but the specific structural inefficiencies in the composition of Pakistan’s trade and the use of remittances remain underexplored. While prior research has established adverse effects of environmental degradation on HDI, there is a paucity of empirical studies integrating Pakistan’s carbon emissions profile within a holistic development framework. Governance variables, particularly the role of women’s parliamentary representation, have been analyzed in global and regional contexts; however, their impact on Pakistan’s HDI has not been thoroughly examined in relation to policy inclusivity and social development outcomes.

Despite extensive research contributions, significant gaps remain. First, while the relationship between exports and economic growth is well documented, the extent to which Pakistan’s exports translate into human development remains unclear due to limited product diversification and weak institutional support. Second, remittances are recognized as a critical financial inflow for developing economies; yet, their potential to improve Pakistan’s HDI through education and healthcare investment is not properly used, warranting further investigation into governance and financial policies that could optimize their impact. Third, although military spending has been analyzed globally in terms of its trade-offs with social spending, the dual effect it exhibits in Pakistan, promoting stability but potentially diverting resources from human development, requires deeper empirical investigation. Fourth, although environmental sustainability is a growing concern, research has largely focused on economic and energy dimensions without sufficiently integrating Pakistan’s environmental challenges into human development discussions. Finally, the governance factors, including women’s representation in parliament, have been linked to inclusive policy-making in various contexts, but their specific contribution to the HDI in Pakistan has not been comprehensively quantified. Addressing these gaps, the paper advances the literature by integrating economic, environmental and governance determinants into a unified analytical framework specific to Pakistan’s development trajectory. By using the VECM, it provides new insights into both the short- and long-term dynamics that affect HDI. This multidimensional approach enables a more nuanced understanding of how these factors interact over time, overcoming the limitations of the previous studies that have largely examined these determinants in isolation. The research is consistent with the broader discourse on sustainable and inclusive development and provides empirical evidence to inform policy reforms aimed at promoting equitable human development in Pakistan.

3. Data and Methodology

This study explores the determinants of Human Development Index (HDI) in Pakistan by using annual data from 1990 to 2022. The variables under investigation comprise economic, environmental, governance, and demographic factors, each of which is hypothesized to influence human development outcomes.

Table 1 summarizes the data sources and descriptions of variables used in the model, for the period from 1990 to 2022 for Pakistan.

Variable Description Data Source
Human Development
Index (HDI)
Composite index measuring the country’s average achievements in health, education, and income. United Nations Development
Programme (UNDP)
Exports of Goods and Services The total value of exports of goods and services as a percentage of GDP. World Bank (WDI)
Current Account Balance Balance of trade, net income from investments, and net current transfers. World Bank (WDI)
Carbon Dioxide Emissions (Per Capita) Total emissions of CO₂ divided by the population of the country. World Bank (WDI)
Military Expenditure Government’s total military spending as a percentage of GDP. World Bank (WDI)
Personal Remittances (Received) Total amount of remittances received by households from abroad, expressed as a percentage of GDP. World Bank (WDI)
Population Growth Annual percentage growth rate of the population. World Bank (WDI)
Share of Seats in Government (Female) Percentage of parliamentary seats held by women. United Nations Development
Programme (UNDP)
Total Debt Service Total amount of debt payments (interest + principal) as a percentage of GNI. World Bank (WDI)

The table gives a brief description of each variable. Data on the HDI is sourced from the United Nations Development Programme (UNDP); the other key indicators, such as exports as a percentage of GDP, personal remittances, total debt service, population growth, and carbon dioxide emissions per capita are retrieved from the World Development Indicators (WDI) database. The data on military expenditure come from the Stockholm International Peace Research Institute (SIPRI) via WDI, and information on women’s parliamentary representation is obtained from the Worldwide Governance Indicators (WGI). These sources ensure data reliability and comparability over time.

Figure 3. 

Results presented using Power point Microsoft (authors’ analysis)

Governance is a multidimensional concept involving political stability, regulatory quality, government effectiveness, rule of law, control of corruption and other institutional factors, as captured by the WDI and the World Bank. Among these, women’s representation in parliament is chosen as a focal variable because of its direct impact on policy-making processes that influence human development outcomes, particularly in education, health and economic inclusion. While previous studies (e.g., Seyed et al., 2012; Tandoh-Offin, 2010) provided foundational insights into the role of gender representation in governance, more recent research has reinforced its importance. Tripp & Kang (2008) and Clayton (2021) show the increasing influence of women working in legislative bodies on shaping inclusive policies, particularly in developing countries. Empirical evidence suggests that greater women’s participation in governance leads to a more equitable allocation of resources, increased social spending and improved development indicators (Bush & Zetterberg, 2021). In Pakistan where structural inequalities persist in political representation, analyzing the issues related to women’s parliamentary participation provides critical insights into how governance reforms can contribute to human development. Furthermore, the choice of this variable aligns with global commitments such as SDG 5 (gender equality) and SDG 10 (reduced inequalities) and highlights the importance of gender-responsive governance in national development strategies.

Model Specification

This study uses the Vector Error Correction Model (VECM) to analyze both long run-equilibrium relationships between the HDI and its determinants and their short-run dynamics. The choice of the VECM in this study is based on economic theory, which recognizes that independent economic variables can have both long- and short-term effects on human development. The two dominant schools of thought in economics, Classical and Keynesian, provide a theoretical basis for understanding these effects.

The Classical school developed by Adam Smith, David Ricardo, Solow (1956) and others emphasizes that economic growth and development are driven by long-term structural changes including capital accumulation, technological progress and institutional quality. According to Solow’s Growth Model, human capital investment, macroeconomic stability and governance reforms largely determine human development outcomes. Romer (1990) and Lucas, (1988) point out that exports, remittances and governance factors influence human development in the long run mainly by shaping productivity, labor market efficiency and institutional capacity, which is in line with endogenous growth theories holding that long-term development is determined by sustained investments in education, innovation and governance.

The Keynesian school of thought as articulated by Keynes (1936) and later expanded by Krugman (1998) focuses on short-term economic fluctuations and the role of government intervention in stabilizing the economy. Keynesian models suggest that fiscal policies, government spending and external shocks can have a direct impact on consumption, employment, investment and hence overall economic welfare in the short run. Like military spending, remittances and current account fluctuations can affect the HDI in the short term by changing household income and consumption patterns. This perspective underscores the importance of counter-cyclical policies, such as fiscal stimulus, targeted social spending and trade interventions, in mitigating the short-term volatility.

This study primarily adopts a Classical long-term perspective, focusing on the structural determinants of human development, while also incorporating short-term analysis to capture immediate policy effects. Its core objective is to identify long-term factors shaping HDI and to explore how economic, environmental and governance variables contribute to sustainable human development. The inclusion of error correction terms in the VECM enables nuanced understanding of how short-term shocks affect the HDI and how fast the system returns to the long-term equilibrium. By integrating both perspectives, this study bridges the gap between long-term development strategies and short-term policy responsiveness, offering a comprehensive analytical framework that is consistent with the realities of economic policymaking in Pakistan.

Johansen (1991) discussed the critical role of cointegration testing and stationarity in modeling long-run relationships between economic variables, which validates use of VECM. Further, Phillips and Perron (1988) provided foundational methodology for testing for unit roots in time series data, emphasizing its strength against autocorrelation and heteroscedasticity. Pesaran and Shin (1995) further elaborated on the importance of combining long-term equilibrium analysis with short-term dynamics, mainly in economic modeling frameworks. Finally, Asteriou and Hall (2015) outlined best practices in econometrics, underscoring the need for diagnostic tests to validate stationarity of variables before applying advanced models like VECM. The methodology is supported by preliminary statistical and diagnostic tests. Stationarity of variables is tested using Phillips-Perron (PP) test, which reveals that most variables are non-stationary at levels but become stationary after first differencing. The PP test checks stationarity in time series data, focusing on null hypothesis that series has unit root (non-stationary). It is based on the following augmented regression:

Yt = α + βt + γYt − 1 t-1pdiDγti + εt (1)

The Johansen Cointegration Test confirms the presence of long-term relationships among variables, validating the use of the VECM framework. The specified long-run model is expressed as follows:

HDIt = β0 + β1Expt + β2Remitt + β3MiltEt + β4Popt + β5FemPat + β6DebtSt + β7CO2Et + εt

Where: HDIt – Human Development Index, annual; Expt – export as a percentage of annual GDP; Remitt – ersonal remittances as a percentage of annual GDP; MiltEt – military expenditure as a percentage of annual GDP; Popt – annual population growth rate; FemPat – women’s representation in parliament as percentage of seats, annual; DebtSt – total debt service as percentage of GNI, annual; CO2Et – carbon dioxide emissions per capita, annual, and εt – error term.

For short-run dynamics, the VECM incorporates the error correction term (ECT), which quantifies how quickly deviations from long-run equilibrium are corrected. The short-run equation is as follows:

Yt = α + βt + γYt − 1 t-1pdiDγti + εt (2)

Here, Δ denotes first difference, γi are short-run coefficients, λ is speed of adjustment, and µt is disturbance term. The HDI is modeled as a function of export, remittances, military expenditure, population growth, female parliamentary representation, total debt service, and carbon dioxide emissions. The coefficients represent long-term impact of each variable on HDI, while error correction term in the VECM captures the speed of adjustment toward equilibrium following short-term shocks. Diagnostic tests including multicollinearity, heteroscedasticity, and autocorrelation checks are conducted to ensure model’s stability. The lag length is determined using Akaike Information Criterion (AIC), which optimizes the trade-off between model complexity and explanatory power. The results provide insights into how economic, governance, demographic, and environmental factors influence human development in Pakistan both in the short and long term. Diagnostic tests confirm the adequacy of VECM specification, ensuring that the model captures the dynamics between HDI and its determinants without significant bias and error (Engle & Granger, 1987; Stock & Watson, 1988; Lütkepohl, 2005; Hamilton, 2020).

This methodological approach allows for a comprehensive examination of the factors that shape human development in Pakistan, providing valuable policy insights for improving socio-economic outcomes. This study follows ethical research standards, ensuring truthful reporting and proper attribution of all secondary data sources.

The data is used within acceptable guidelines, with no modifications to ensure the reliability and authenticity of the analysis. The study recognizes certain limitations, such as reliance on secondary data, which may not fully capture nuanced socio-economic dynamics. In addition, the chosen econometric model assumes linearity, which may oversimplify some relationships. Further research could extend the analysis to include non-linear modeling or machine learning techniques for enhanced strength. This methodological framework provides wide-ranging structure for examining determinants of human development, offering insights into policy interventions aimed at achieving sustainable socio-economic progress (Hansen, 1999; Varian, 2014; Asteriou & Hall, 2015; UNDP, 2020).

4. Analysis and Results

Descriptive Statistics

The descriptive statistics expose moderate levels of variation across variables, providing insights into Pakistan’s socio-economic and environmental indicators.

Variable Mean Std. Dev. Min 25% Median 75% Max
HDI 0.4725 0.0502 0.3940 0.4230 0.4850 0.5190 0.5400
Exports GDP 12.541 2.836 8.222 10.543 12.165 15.353 17.271
Current_Account_GDP -2.468 2.601 -7.742 -4.152 -2.667 -0.936 3.936
CO2_Emissions 0.760 0.1207 0.566 0.664 0.760 0.828 0.999
Military_Expenditure_GDP 4.225 1.284 2.631 3.286 3.645 5.415 6.698
Remittances_GDP 4.367 2.089 1.081 2.947 3.528 5.854 8.984
Population_Growth 2.265 0.622 1.204 1.798 2.189 2.891 3.297
Female_Parliament 13.289 8.944 1.974 2.632 19.955 20.362 21.267
Debt_Service_GNI 3.249 1.587 1.327 1.812 3.018 4.505 6.815

For example, the HDI values over the study period show a modest increase, reflecting steady progress in health, education, and living standards. Export as a percentage of GDP demonstrates visible fluctuations, indicative of the economy’s exposure to global trade dynamics. Similarly, remittances show considerable volatility, highlighting their critical role as a source of foreign income for households. Military expenditure as a percentage of GDP remains consistently high, indicating its importance in national priorities, while population growth rates underscore the demographic pressure on resources and infrastructure. Carbon dioxide emissions per capita display steady upward trend, pointing to environmental concerns associated with economic activities.

Table 3.

Combined Table: Probability Values for Phillips-Perron Unit Root Test

Series Level: p-value First Difference: p-value
HUMAN_DEVELOPMENT_INDEX__VALUE_ 0.7677 0.0426
EXPORTS_OF_GOODS_AND_SERVICES__OF_GDP 0.5780 0.0001
CURRENT_ACCOUNT_BALANCE__OF_GDP 0.0936 0.0001
CARBON_DIOXIDE_EMISSIONS_PER_CAPITA 0.9186 0.0000
MILITARY_EXPENDITURE__OF_GDP 0.5331 0.0008
PERSONAL_REMITTANCES__RECEIVED__OF_GDP 0.9260 0.0002
POPULATION_GROWTH__ANNUAL__ 0.4648 0.0108
SHARE_OF_SEATS_IN_PARLIAMENT__FEMALE 0.6401 0.0001
TOTAL_DEBT_SERVICE__OF_GNI 0.3764 0.0000

Unit Root Test

The results of the Phillips-Perron (PP) unit root test show that all variables are non-stationary at level (value > 0.05) but become stationary after first differencing (p-value < 0.05), indicating integration of order one, I(1). This confirms the suitability of applying the Johansen Cointegration Test and the Vector Error Correction Model (VECM) to analyze both long-term relationships between the variables influencing HDI and their short-term dynamics (Phillips & Perron, 1988; Johansen, 1991; Pesaran & Shin, 1995; Asteriou & Hall, 2015).

Table 4.

Unrestricted Cointegration Rank Test (Trace)

Hypothesized No. of CE(s) Eigenvalue Trace Statistic Critical Value (5%) p-Value
None* 0.986672 386.2348 197.3709 0.0000
At most 1* 0.924651 252.3807 159.5297 0.0000
At most 2* 0.770206 172.2265 125.6154 0.0000
At most 3* 0.736529 126.6387 95.75366 0.0001
At most 4* 0.639278 85.29058 69.81889 0.0018
At most 5* 0.515975 53.68149 47.85613 0.0129
At most 6* 0.469693 31.18732 29.79707 0.0344
At most 7 0.297463 11.52402 15.49471 0.1812
At most 8 0.018512 0.579262 3.841465 0.4466

The Phillips-Perron (PP) unit root test results demonstrate that all variables are non-stationary at level (p value > 0.05) but become stationary after first differencing (p-value < 0.05), indicating integration order one, I (1). This confirms the suitability of using the Johansen Cointegration Test and Vector Error Correction Model (VECM) to analyze both the long-term relationships between the variables influencing HDI and their short-term dynamics.

Hypothesized No. of CE(s) Eigenvalue Max-Eigen Statistic Critical Value (5%) p-Value
None* 0.986672 133.8541 58.43354 0.0000
At most 1* 0.924651 80.15423 52.36261 0.0000
At most 2 0.770206 45.58778 46.23142 0.0585
At most 3* 0.736529 41.34815 40.07757 0.0358
At most 4 0.639278 31.60909 33.87687 0.0911
At most 5 0.515975 22.49417 27.58434 0.1961
At most 6 0.469693 19.66330 21.13162 0.0792
At most 7 0.297463 10.94476 14.26460 0.1570
At most 8 0.018512 0.579262 3.841465 0.4466

Johansen Cointegration Test Unrestricted Cointegration Rank Test (Trace and Maximum Eigenvalue)

The Trace test indicates the presence of seven cointegrating equations at 5% significance level, as the Trace statistic exceeds the critical values for up to seven equations (e.g., for “None, Trace Statistic = 386.2348 > Critical Value = 197.3709, p = 0.0000). This result confirms that the variables have long-term equilibrium relationships, making the VECM framework suitable for modelling their dynamics.

The trace test shows seven cointegrating equation(s) at the 0.05 level.

It denotes rejection of the hypothesis at the 0.05 level MacKinnon-Haug-Michelis (1999) p-values.

Unrestricted Cointegration Rank Test (Maximum Eigenvalue)

The Maximum Eigenvalue test involves two cointegrating equations at 5% significance level, as MaxEigen Statistic = 133.8541 > Critical Value = 58.43354, p = 0.0000). Although fewer cointegrating vectors are identified compared to the Trace test, evidence still supports the existence of robust long-term relationships between the variables.

Max-Eigenvalue test shows 2 cointegrating equation(s) at the 0.05 level.

It denotes rejection of the hypothesis at the 0.05 level MacKinnon-Haug-Michelis (1999) p-values.

The cointegration analysis confirms the presence of long-term relationships between the variables, as proved by both Trace and Maximum Eigenvalue tests. The identification of multiple cointegrating equations validates the use of the VECM, as it allows for capturing equilibrium dynamics while accounting for short-term deviations. By incorporating error correction terms, the VECM framework allows modelling how variables adjust over time towards their long-run equilibrium, providing deeper insights into the interplay between the HDI and its determinants.

VECM MODEL

1. Long-Run Coefficients (Cointegrating Equation)

The long-run coefficients from the VECM specify the equilibrium relationships between the variables and Human Development Index (HDI). Each coefficient reflects the magnitude and direction of each variable’s impact on the HDI, with all the relationships statistically significant as evidenced by their t-statistics.

Variable Coefficient (CointEq1) Standard Error t-Statistic
HUMAN_DEVELOPMENT_INDEX 1.000000 - -
EXPORTS_OF_GOODS_AND_SERVICES -0.003473 0.00016 -21.0783
CURRENT_ACCOUNT_BALANCE 0.001402 0.00012 12.0796
CARBON_DIOXIDE_EMISSIONS -0.208272 0.00539 -38.6049
MILITARY_EXPENDITURE 0.015505 0.00045 34.6546
PERSONAL_REMITTANCES -0.009215 0.00018 -51.3831
POPULATION_GROWTH 0.014379 0.00059 24.2638
SHARE_OF_SEATS_IN_GOVERNMENT 0.001087 6.1E-05 17.9641
TOTAL_DEBT_SERVICE 0.003411 0.00028 12.2703

The long-run relationships reveal significant impacts of economic, environmental, and governance variables on the HDI. While factors like current account balance, military expenditure, population growth, women’s representation and debt service show positive effects, the negative impacts of exports, carbon emissions, and remittances highlight structural inefficiencies and environmental challenges. These findings underscore the importance of targeted policies to maximize the development benefits of economic activities while addressing institutional and sustainability issues.

Variable Coefficient (Short Run) Standard Error t-Statistic
Error Correction Term (CointEq1) 0.007158 0.09518 0.07520
D(HUMAN_DEVELOPMENT_INDEX) 0.498049 0.32752 1.52066
D(EXPORT_OF_GOODS_AND_SERVICES) -6.90E-05 0.00047 -0.14825
D(CURRENT_ACCOUNT_BALANCE) -0.000485 0.00023 -2.10074
D(CARBON_DIOXIDE_EMISSIONS) -0.034204 0.02403 -1.42333
D(MILITARY_EXPENDITURE) -0.004043 0.00208 -1.93948
D(PERSONAL_REMITTANCES) 0.000351 0.00060 0.58688
D(POPULATION_GROWTH) -0.004744 0.00215 -2.20673
D(SHARE_OF_SEATS_IN_GOVERNMENT) 0.000302 0.00011 2.63239
D(TOTAL_DEBT_SERVICE) -0.000271 0.00044 -0.61282

2. Short-Run Coefficients (Error Correction Model)

The short-run coefficients of the VECM capture the immediate effects of changes in the variables on the HDI, sideways with the speed of the system’s adjustment towards the long-run equilibrium. The t-statistics indicate the significance of short-term relationships. The coefficient for ECM (0.0071580) is statistically insignificant (t = 0.07520), which means that the system does not rapidly adjust back to the long-term equilibrium when deviations occur. This suggests that the short-term shocks to the HDI and its determinants may persist for extended periods, reflecting rigidities and delays in policy responses.

The short-run VECM results highlight the mixed and mostly insignificant direct effects of the variables on the HDI. While current account balance, military expenditure, population growth, and female representation show significant short-term impacts, the other factors, i.e. export, carbon emissions, remittances and debt service, do not have direct influence. Statistically insignificant error correction term suggests that the system adjusts slowly to deviations from the long-run equilibrium, indicating persistence of short-term shocks. These findings underscore the need for targeted interventions to address immediate challenges while fostering long term development.

Statistic Value
R-squared 0.7397
Adjusted R-squared 0.6095
F-statistic 5.6826
Log Likelihood 156.0564
Akaike Information Criterion (AIC) -9.3585
Schwarz Criterion (SC) -8.8496

3. Model Fit Statistics

The model fit statistics indicate that the VECM effectively captures the relationships between the Human Development Index (HDI) and its determinants.

With R2 of 0.7397 and adjusted R2 of 0.6095, the model explains much of the HDI variation, while minimizing the risk of overfitting. The significant F-statistic (5.6826) confirms the collective relevance of explanatory variables. The log-likelihood value (156.0564) reproduces good model fit, while the negative values of (AIC, −9.3585) and Schwarz Criterion (SC, −8.8496) indicate that the model is both well-fitted and parsimonious. Together, these metrics validate the use of the VECM as a robust tool for analyzing the short- and long-term relationships between the HDI and economic, governance and environmental variables.

Test Statistic Degrees of Freedom (df) p-value
LRE Statistic* (Likelihood Ratio Test) 107.9362 81 0.0244
Rao F-statistic 1.367749 (81, 28.4) 0.1752

Test Results for Lag 1:

The test results for Lag 1 assess the optimal lag length for Vector Error Correction Model (VECM), balancing the model’s accuracy and parsimony.

The test results justify the selection of Lag 1 for the VECM, balancing the model complexity and fit. The significant LRE statistic reveals the necessity of including the lag to account for dynamic interactions, while non-significant Rao F-statistic suggests that greater lags are unnecessary. This supports the use of Lag 1 as the optimal choice for capturing the short-term dynamics without overparameterizing the model.

Figure 4. 

Results estimated using EViews 12 (authors’ analysis)

Normality Test

The residual diagnostics confirm that residuals from VECM are approximately normally distributed, unbiased, and exhibit low variability, supporting reliability of the model.

The mean of the residuals (−0.000452) is close to zero, indicating no systematic bias, while standard deviation (0.005247) reflects stable variability. The skewness (−0.004107) and kurtosis (2.0407502.0407502.040750) values are close to those expected under normality, suggesting symmetry and absence of heavy tails. These results enhance the credibility of the model’s ability to provide accurate and meaningful insights into the determinants of HDI.

5. Discussion

This section provides a detailed discussion of the VECM results for each of the eight variables that influence the Human Development Index (HDI) in Pakistan. The analysis contextualizes both long- and short-term relationships in the broader literature, aligning the findings with the study’s objectives of identifying the key economic, environmental, and governance determinants of HDI.

The VECM results show significant negative long-term relationship between export and HDI (Coefficient= −0.003473; t=−21.0783). This suggests that in Pakistan, export activities do not translate into developmental gains. This finding is consistent with Afzal et al. (2009), who showed that reliance on low value-added exports and limited diversification undermines the potential of exports to drive sustainable development. The short-term results show no significant relationship (t=−0.14825), indicating that exports do not contribute directly to human development. This reflects challenges, such as weak export infrastructure and ineffective trade policies. Globally, exports have been associated with improvements in HDI when accompanied by technological innovation and export diversification (Rohim et al., 2023). Pakistan’s experience underscores the need for policy reforms to enhance export competitiveness, diversify export products, and improve trade infrastructure, as suggested by Davies and Quinlivan (2006).

The current account balance has a positive impact on the HDI (coefficient=0.001402; t=12.0796), demonstrating that a stable current account supports long-term improvements in human development. This is consistent with Kerdrain, Koske, and Wanner (2011), who stressed the importance of a balanced current account in promoting sustainable growth and improving living standards. In the short run, the current account balance has a significant negative relationship with the HDI (t= −2.10074), reflecting economic pressures to maintain external balance, such as resource diversion and exchange rate volatility. These findings align with Banerjee and Goyal (2021), who emphasize the role of governance and structural reforms in mitigating the short-term challenges associated with current account adjustments. For Pakistan, policies aimed at stabilizing the current account through export diversification and prudent debt management are essential.

Carbon emissions have a significant negative effect on the HDI (coefficient=−0.208272; t=−38.6049), highlighting the detrimental impact of environmental degradation on health and quality of life. This finding is supported by Li et al. (2022) and Abdulaziz and Alajlan (2021), who found an inverse relationship between emissions and human development in developing countries. The short-term results reinforce the negative relationship (t=−1.42333t), highlighting the immediate health and environmental costs associated with high emission levels. These results call for policies to reduce emissions while promoting sustainable development. Lessons from Hossain and Chen (2021) suggest that decoupling economic growth from carbon emissions through the use of renewable energy and improved energy efficiency can mitigate these effects.

Military expenditure has shown positive long-term relationship with the HDI (Coefficient=0.015505; t=34.6546), suggesting that defense spending contributes to political stability and indirectly supports socioeconomic development. This aligns with Pérez-Cárceles (2024), who argued that military investments could create the environment conducive to human development. In the short run, military expenditure has a negative impact on HDI (t=-1.93948), suggesting a resource trade-off where funds allocated to defense reduce immediate investment in social sectors such as education and healthcare. These results reflect the dual nature of military spending. Stability and security can certainly yield long-term benefits, but excessive spending may undermine investment in human capital, as noted by Elgin et al. (2022) and Looney (1990). Policymakers need to balance defense and social spending to improve development outcomes.

Remittances have a significant negative relationship with the HDI (coefficient=-0.009215; t=-51.3831), suggesting that remittance inflows in Pakistan may not be used effectively for development purposes. This finding contrasts with Pradhan and Khan (2015) but is consistent with Kashif Imran, 2017, who noted that remittances in Pakistan often finance consumption rather than investment in education and health. In the short run, remittances have no significant effect on HDI (t=0.58688), suggesting limited direct developmental impact. Globally, remittances have been shown to enhance HDI in the regions with strong governance and financial inclusion (Umar, 2021). For Pakistan, formalizing remittance channels and incentivizing productive investment is critical to unlocking their potential for human development.

Population growth has showed positive long-term relationship with HDI (Coefficient=0.014379; t=24.2638), reflecting potential demographic dividends. This is in line with Wahyuningrum and Soesilowati (2021), who noted that population growth can improve development when accompanied by adequate resource management. In the short run, population growth has a negative impact on HDI (t=−2.20673t = 2.20673t=−2.20673), highlighting the immediate strain on resources and infrastructure. The dual nature of population dynamics underscores the importance of investment in education, health and employment opportunities to capitalize demographic advantages. These strategies are in line with global recommendations for managing population pressures (Fal’tsman, 2022).

Women’s parliamentary representation has a significant positive effect on the HDI (Coefficient=0.001087; t=17.9641), emphasizing the role of gender-inclusive governance in fostering development. This is consistent with Razmi et al. (2018), who highlighted transformative impact of women on policymaking in education and healthcare. The short-term results also show a positive relationship (t=2.63239t = 2.63239t=2.63239), reflecting the immediate benefits of inclusive policies for human development. These results reinforce the global consensus that increasing women’s participation in governance improves societal well-being. Efforts to promote gender equality and empower female legislators are vital for achieving sustainable development goals (SDGs) Razmi et al. (2018).

Total debt service positively affects HDI in long term (Coefficient=0.003411; t=12.2703), suggesting that debt management can support development by stabilizing economic conditions and promoting public investment. This is consistent with Kerdrain, Koske, and Wanner (2011), who highlighted the importance of sustainable debt practices for improving living standards. In the short term, the relationship is insignificant (t=−0.61282), indicating limited immediate effects of debt servicing on the HDI. Prudent debt management is critical for human development, as noted by Banerjee and Goyal (2021). It follows that in Pakistan the key strategies should aim to reduce reliance on external borrowing and improve fiscal discipline.

The VECM results provide valuable insights into the dynamic relationships between economic, environmental, and governance variables and Pakistan’s HDI. While some factors, such as women’s participation and the current account, show clear development benefits, the others, e.g. exports and remittances, highlight structural challenges. These findings emphasize the need for targeted policies that address short-term pressures and promote long-term human development. Future research could explore the regional disparities and incorporate non-linear models to improve understanding of the phenomena in question.

6. Conclusion

This study provides a comprehensive analysis of the determinants of Pakistan’s Human Development Index (HDI), encompassing economic, environmental, governance and demographic dimensions. The results show that while female parliamentary representation and current account stability contribute positively to human development, carbon dioxide emissions and inefficient use of remittances pose significant challenges. The dual nature of population growth, the mixed effects of military spending, and structural inefficiencies in Pakistan’s export and economic strategies further underscore the complexity of advancing the country’s human development. The key findings of the study suggest that Pakistan’s current development route requires recalibration to address both immediate and long-term challenges. The negative relationship between exports and HDI emphasizes need to diversify the country’s trade portfolio and invest in value-added sectors. Similarly, while remittances are an important source of external income, they are not fully used to improve education, health or infrastructure because of inefficiencies in resource allocation. The negative impact of environmental degradation on HDI means that Pakistan urgently needs to integrate sustainability into its national development framework. The paper also highlights the importance of governance, with women’s political participation emerging as a critical factor in promoting inclusive and sustainable development. These findings provide critical insights into the complex nature of human development and underscore the need for integrated policy approaches to achieve equitable growth in Pakistan.

To improve Pakistan’s HDI, policymakers need to adopt targeted policies that directly influence its three components: per capita income, life expectancy and education indicators. Implementing solar energy projects in rural areas can improve health outcomes by reducing indoor air pollution from biomass and kerosene use, which often cause respiratory diseases (Pervaiz & Farooq, 2021). Implementation of hydropower projects, such as the Diamer-Bhasha dam, can reduce power shortages and increase industrial productivity, job creation and per capita income. Tighter environmental regulations on carbon emissions can significantly improve life expectancy. Introducing carbon taxes on industries that emit large amounts of CO₂, particularly the cement and textile sectors, can reduce air pollution and directly improve health outcomes by reducing the incidence of lung and cardiovascular disease. (Li et al., 2022). Urban initiatives such as Lahore’s Clean Air Action Plan should be rolled out across the country to reduce vehicle emissions and thus improve air quality and public health.

A balanced fiscal approach that prioritizes education, health and infrastructure development is essential for improving both education and life expectancy. Allocating at least 4% of GDP to education as recommended by UNESCO can increase literacy rates and enhance the education component of the HDI (Zehra, N., & Alam, S. 2015). Expanding universal healthcare programs, such as the Sehat Sahulat Program, can enhance life expectancy by ensuring access to medical services for low-income population. Investing in sanitation and clean water infrastructure as outlined in Pakistan’s National Water Policy, can lower child mortality rates and improve overall health, further boosting life expectancy. Export diversification and industrialization are crucial for economic growth and improving per capita income. Shifting from low-value textile exports to high-value technology-based exports such as IT services and engineering goods can improve the trade balance and create higher-paying jobs (Afzal et al., 2009). Strengthening Special Economic Zones (SEZs) under the China-Pakistan Economic Corridor (CPEC) can attract foreign investment, generate employment and further contribute to economic development.

Formalizing remittance channels and enhancing financial inclusion can significantly impact both income per capita and education. Encouraging remittance-based investment schemes such as Roshan Digital Accounts can direct remittances toward education and infrastructure rather than unproductive consumption. Expanding microfinance programs for remittance-receiving households can promote entrepreneurship and increasing income per capita. Women’s representation in governance plays a pivotal role in improving both education and life expectancy. Greater women’s participation in local governance, for example through reserved seats in provincial assemblies, should lead to higher spending on education and better maternal healthcare policies (Tripp & Kang, 2008). Countries such as Rwanda have demonstrated that increased female legislative participation leads to policies that prioritize social development, which Pakistan can replicate to improve HDI indicators. By adopting these targeted policy interventions, Pakistan can effectively improve human development outcomes by ensuring a sustainable and inclusive growth trajectory.

While study sheds light on critical determinants of the HDI in Pakistan, several avenues for future research remain unexplored. First, regional analysis could examine disparities in human development across provinces to help policymakers design interventions tailored to specific socio-economic challenges. Understanding regional differences can also highlight specific drivers of growth and barriers to the country’s development. Second, employing non-linear models or machine learning techniques could provide deeper understanding of complex relationships between the HDI determinants. Where traditional econometric models may oversimplify interactions, the advanced methodologies can reveal nuanced dynamics and better predict long-term development outcomes. Third, future research should focus on sector-specific contributions to human development, particularly in agriculture, manufacturing, and services. Analysis of sectoral roles can help identify areas with the greatest potential for improving the HDI and guide sectoral policy priorities. Fourth, given the adverse impact of carbon emissions on the HDI, studies on climate change adaptation and resilience strategies are indeed vital. Research should investigate how climate vulnerabilities affect different components of HDI, particularly health and education, and explore the role of renewable energy in reducing environmental degradation and fostering economic growth. Future research should explore the relationship between governance quality and human development in greater detail. Investigating how different governance dimensions like accountability, transparency, and political stability affect HDI can provide actionable visions for institutional reforms. In addition, examining the role of digital governance and technology-enabled solutions in improving service delivery can contribute to the discourse on innovative development strategies.

The results of this study emphasize the need for multidimensional approach to human development in Pakistan. To achieve the country’s developmental goals, it is essential to address structural inefficiencies, promote sustainability and foster inclusive governance. Economic growth remains the key driver of development, but aligning growth with environmental preservation and social equity will ensure sustainable progress. By implementing the recommended policies and pursuing the identified research directions, Pakistan can create a resilient, equitable, and sustainable development trajectory that prioritizes overall well-being.

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