Research Article |
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Corresponding author: Imran Ali ( imranalieco@gmail.com ) Academic editor: Marina Sheresheva
© 2025 Imran Ali.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
ALI I (2025) Policy Pathways for Progress: Study of Economic, Environmental, and Governance Determinants of HDI in Pakistan. BRICS Journal of Economics 6(2): 59-90. https://doi.org/10.3897/brics-econ.6.e146935
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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).
HDI, Pakistan, governance, economic determinants, environmental impact, VECM Model, remittances, CO2 emissions, military expenditure.
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
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.
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.
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.
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.
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.
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;
The work by
The study by
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,
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.
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
| 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.
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;
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,
The Keynesian school of thought as articulated by Keynes (1936) and later expanded by
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.
∆Yt = α + βt + γYt − 1 − i + 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 − i + 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 (
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 (
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.
| 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 |
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 (
| 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 |
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.
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.
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 |
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 |
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 |
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.
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.
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
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
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
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
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
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
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
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.
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. (
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 (
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 (
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.