Pakistan Social And Living Standards Measurement Research Articles

Energy deprivation to financial prosperity: Unveiling multidimensional energy Poverty's influence

The purpose of this research is to assess how energy poverty affects an individual's social wellbeing and financial constraints. The present research examines the effects of energy deprivation on a family's well-being, educational attainment, and economic advancement using survey data from PSLM (Pakistan Social and Living Standard Measurement). The investigation's empirical findings imply that a household's needs for energy are directly correlated with the fuel type they use and how little or expensively they rely on renewable energy. The consequent implications of energy dependence on family prosperity are significant. Energy-poor households have been shown to be more prone to experience respiratory illnesses, pay more for health care, drop out of school, and have less employment opportunities.

Who Demands Technical and Vocational Education in Pakistan? A PSLM Analysis of Socio-Economic Determinants

Purpose: The present study investigates the influence of demographic factors on the demand for Technical and Vocational Education and Training (TVET) in Pakistan. The government of Pakistan has implemented various skill enhancement programs to harness the demographic dividend. However, only a small portion of the workforce receives any form of TVET, contributing to a shortage of skilled workers in the country. Many industries, particularly in manufacturing and mining, face deficits in the skilled labour. Consequently, this study aims to examine the role of demographic factors in shaping the demand for TVET within the Pakistani context. Methods: For the TVET demand's estimation, this study employed the Pakistan Social and Living Standard Measurement (PSLM) dataset of 2018–19 by using binary logistic regression analysis (BLRA). The demographic variables include the household's income, household head's education, household size, male proportion of the target age group, household head's age, and region of the household. Findings: The findings indicate that households in the higher income category do not demand TVET. Moreover, if the head of the household is highly educated, then the household is less likely to participate in TEVT. So, the higher the socio-economic status, the lower the probability of demand for TVET from the better-off students. Further, this study also indicates that boys are more likely to participate in TVET-related degrees, while females are less likely to participate in TVET due to the non-availability of institutes and hostel facilities, poor transportation, the limited number of trades available for females, and security issues. Conclusion: The findings provide insightful evidence to support the idea that the higher the socio-economic status of households, the lower the probability of demand for a TVET degree or diploma. Similarly, children of parents with university education are less likely to pursue TVET-related degrees. The reason is likely attributed to the perception that TVET-associated degrees and diplomas are considered inferior due to their lower standing and prestige as compared to general or professional degrees. This study suggests that the attractiveness of TVET can be enhanced by improving the quality of TVET, improving labour market outcomes, and creating a pathway to general education. Overall, this study not only contributes to empirical analyses of socio-economic determinants in TVET demand but also suggests that its findings can be applied not only to South Asian countries but also to other comparable nations with similar cultural ties and affinities.

Investigation of multidimensional poverty in Pakistan at the national, regional, and provincial level

AbstractTo achieve the sustainable development goal of “no poverty”, many attempts have been made to measure poverty so that policy intervention can target the right people with the correct intensity. Since the traditional method of a unidimensional approach using monetary indicators, such as income and consumption, is now considered insufficient, a multidimensional approach has been employed using non-monetary indicators. The latter approach encompasses the different poverty aspects affecting an individual’s capabilities and functioning. This study aimed to calculate multidimensional poverty in Pakistan using the Alkire & Foster method and Pakistan Social and Living Standards Measurement (PSLM) published by the Pakistan Bureau of Statistics data for 2018–19. To further complete the research, a binary logistic regression has been run to measure the effects of a deviation in income status on multidimensional poverty to see the impact of monetary income on non-monetary measures. Results show that the national global Multidimensional Poverty Index (MPI) is 0.24, meaning that multidimensionally poor people in Pakistan experience 24% of the total deprivations. The most deprived dimension of the three is education (44.7%), which needs special attention. Furthermore, if a household’s total annual income increases and becomes more significant than the mean income of the sample, the household’s probability of being multidimensionally poor will decrease. This implies that with the increase in average national income, the national poverty will reduce not only in absolute terms but also multidimensionally. This study’s findings have several implications for policymakers, and the results of the MPI should align the allocation of public sector resources calculated to give a geographical and sectoral image of the poverty situation, which will guide policy designs and allocation of budget and resources.

Unveiling the Dynamics of Household Poverty: Empirical Insights from a Developing Country

ABSTRACT This study examines the determinants of poverty across all provinces using 2019–20 data from the Pakistan Social and Living Standards Measurement (PSLM) survey. The results from binary logistic regression analysis reveal several significant findings; household size, the square of the household head’s age, marital status and province-specific factors are positively associated with a household head’s classification as poor. Conversely, the age and gender of the household head, educational levels of the household head, household characteristics, and assets exhibit negative correlations with poverty. The findings will offer valuable insights for policymakers to formulate targeted poverty reduction strategies toward potential solutions.

Demand for secondary schooling in Pakistan: A cross income group analysis

Secondary education for all is one of the UN’s attainable goals. Many countries, including Pakistan, are struggling to achieve this target. Earlier research has attempted to analyze the determinants of secondary schooling by taking the total income of households. However, households of different income groups respond differently to varying socio-economic factors. This study attempts to identify the household-level socio-economic determinants of secondary schooling across different income groups in Pakistan. It utilizes national survey data from the Pakistan Social and Living Standards Measurement (PSLM) Survey 2019-20. We selected households from the dataset that had at least one member of secondary school age (13-20 years). Households that enrolled a secondary school-age member in school or whose member achieved secondary schooling were categorized as having demand for secondary schooling. Furthermore, instead of taking the total income of households, study takes six categories of income. The results of logit estimation show that demand for secondary schooling increases across successive income groups, indicating secondary schooling is a normal commodity. The proportion of male school-going age members and having a female head increase the likelihood of demand for secondary schooling. The study recommends that policies to increase enrollment at the secondary level may focus more on lower-income groups and on the education of females.

Mitigate the Effect of Poverty on Food Security through Education in Developing Countries: A Case of Pakistan

The current research study finds the relationship among food security, poverty status and education in Pakistan and also found the education in the mediating role to mitigate the effect of poverty on food security. The research study also analyzes the impact of livestock, foreign remittances, age of respondent and female head of household on food security. PSLM (Pakistan Social and Living Standard Measurement) survey data of 2019-20 is used for empirical estimation of the current study. Using PSLM has certain benefits, PSLM survey is conducted by a team of experts and the survey covers all the regions of Pakistan, it also covers almost all indicators relating to food security, education and poverty etc. Research study finds that livestock, education, foreign remittances and house head female have a significant positive impact on food security and poverty has a significant negative impact on food security. Poor people facing threat toward food security in Pakistan. On the same time the people who are poor but have education are able to mitigate the effect of poverty on the food security in urban and rural areas. The research study also finds that there are wide gaps among urban and rural areas of Pakistan, level of education in Pakistan. The research study also presents policy recommendations that help’s government for better management of resources and to reduce poverty

The Myth of Missing Women: A Case Study of Pakistan

In the contemporary era, women's empowerment promises enormous gains ensuring a vigorous socio-economic boost for the economy. Further, the persistently changing world demands equity for both men and women as restrictions to women’s rights and opportunities cost an economy in terms of income losses. Hence, overcoming gender discrimination and inequality remains a challenge for developing economies. The idea of “missing women” is linked to the appalling absence of women in substantial parts of an economy. The prime objective of the study is to evaluate the myth of missing women for the economy of Pakistan. The study investigates whether the missing women problem exists in the economy or not. For this purpose, a multidimensional approach would be utilized to figure out various gender inequalities considered in the missing women paradigm. Given the available data and statistics opacity, the study would employ both time series (tentatively for the era of 1990-2020) and cross-sectional data of the Pakistan Social and Living Standards Measurement (PSLM) survey of 2019-20. The former would be collected from the websites of World Bank indicators while the latter would be gathered from the Pakistan Bureau of Statistics. Using a mixed approach, the study qualitatively investigates the aggregate indicators associated with the concept of missing women including the sex ratio, fertility rate, and population dividend of Pakistan with a comprehensive regional comparison. Whereas a quantitative analysis would be performed to examine different gender inequalities through the novel context of missing women. The authorities of Pakistan have made strides in reducing the gender gap through better educational enrolment rates and access to health care services. However, these improvements have not been well transmuted into an enhancement of equity and quality of women’s life. There is a dire need to broaden the horizon of gender equality and hence this study views gender inequality with the dimension of “missing women”.

The Myth of Missing Women: A Case Study of Pakistan

In the contemporary era, women's empowerment promises enormous gains ensuring a vigorous socio-economic boost for the economy. Further, the persistently changing world demands equity for both men and women as restrictions to women’s rights and opportunities cost an economy in terms of income losses. Hence, overcoming gender discrimination and inequality remains a challenge for developing economies. The idea of “missing women” is linked to the appalling absence of women in substantial parts of an economy. The prime objective of the study is to evaluate the myth of missing women for the economy of Pakistan. The study investigates whether the missing women problem exists in the economy or not. For this purpose, a multidimensional approach would be utilized to figure out various gender inequalities considered in the missing women paradigm. Given the available data and statistics opacity, the study would employ both time series (tentatively for the era of 1990-2020) and cross-sectional data of the Pakistan Social and Living Standards Measurement (PSLM) survey of 2019-20. The former would be collected from the websites of World Bank indicators while the latter would be gathered from the Pakistan Bureau of Statistics. Using a mixed approach, the study qualitatively investigates the aggregate indicators associated with the concept of missing women including the sex ratio, fertility rate, and population dividend of Pakistan with a comprehensive regional comparison. Whereas a quantitative analysis would be performed to examine different gender inequalities through the novel context of missing women. The authorities of Pakistan have made strides in reducing the gender gap through better educational enrolment rates and access to health care services. However, these improvements have not been well transmuted into an enhancement of equity and quality of women’s life. There is a dire need to broaden the horizon of gender equality and hence this study views gender inequality with the dimension of “missing women”.

Impact of Socioeconomic Determinants on Infant Mortality in Pakistan

The recent study was carried out to estimate the impact of socioeconomic, demographic and the aspect of health status on child mortality in Pakistan. The data for the study was collected from the PSLM (Pakistan Social and Living Standard measurement survey) for the year 2011-12. The data were analyzed through cross-tabulation and binary logistic model using MLE (Maximum likelihood estimation) technique. Overall, 13216 households were selected for the analysis. The result of the study of the cross-tabulation shows that the overall child mortality was low in Baluchistan province, the maximum number of children survived in Punjab province further, and the child mortality was low in an urban area where 290 children died out of 3984 houses as compared to rural area household in Pakistan. Child mortality was high among females than males in Pakistan. The result of binary logistics shows that out of the total independent variable, nine variables significantly affect child mortality in Pakistan, location of the household, gender, education of father, education of mother, income and mother feeding, positively associated the infant mortality; all these aspects reduce the chance of child mortality, while there was a less likely chance that child survives in Punjab, Sindh as compared to KPK in Pakistan. In the case of Baluchistan, there was also the same situation as KPK in terms of child mortality. Infant mortality was high in female children compared to male children, which means there is a less likely chance of surviving among the female child than the male child. All other variables were insignificant in Pakistan. It is suggested that the central authority provide basic children and mothers health facilities at minimum cost to the rural areas of Pakistan.

Selecting correct functional form in consumption function: Analysis of energy demand at household level.

In the estimation of demand functions for energy resources, parametric econometric models of energy demand are commonly used to predict future energy needs. The functional forms commonly assumed in parametric energy demand models include linear functional forms, log-linear forms, trans-log models, and an almost ideal demand system. It is frequently debated which is the "best" functional form to employ in order to accurately represent the underlying relationships between the demand for various energy resources and explanatory variables such as energy prices, income, and other demographic factors. The study has focused on developing proper non-nested tests to compare the two demand systems, the double log model and the LA-AIDS model. C-test is used to test the validity of using the two parametric functional forms in models of residential energy demand. Cross-sectional household-level data of the Pakistan Social and Living Standards Measurement (PSLM) 2013-14 and Asian Development Bank (ADB) Asia and Pacific 2018 are used. Results indicate that the LA-AIDS model is better than the double log model. The estimated elasticity of own prices, cross-prices, and income in terms of spending, family size, and equipment are particularly important to producers and policymakers in making investment and incentive choices. A significant part of the budget for families is for electricity, natural gas, firewood, and other fuels; smaller budget shares are set down to other items such as kerosene oil, cylinder gas, and diesel. Household per capita demand for energy resources will rise over the next decade; therefore, the government needs to make progress on developing energy-saving strategies. If not addressed the issue properly, we may face energy shortages and high energy import bills.

Spatial Differences and Socioeconomic Determinants of Health Poverty

The study aims to develop health poverty index (HPI) using the Alkire Foster (AF) Method for Pakistan based on district representative data obtained from Pakistan Social and Living Standards Measurement (PSLM) 2012-13. Using HPI, this study investigates the spatial differences of health poverty at sub-national level and explores the socioeconomic determinants. The analysis reveals that the headcount health poverty is 41 percent in Pakistan. Further, the ratio is very high in rural areas (50 percent) as compared to urban areas (22 percent). Provincial analysis shows that Punjab is the least poor province (36 percent) while Balochistan is the poorest province (62 percent). The majority of the households are deprived in term of cost of health services, post-natal care and child immunisation. Empirical analysis shows that income, regional variation, education and awareness play very important role in explaining health poverty. To eradicate health deprivation, area and dimension specific policies are required to make efficient use of scarce resources. JEL Classification: I12, I32, J18 Keywords: Health Poverty, Spatial Analysis, Alkire Foster Method

Inter-regional socioeconomic disparity levels within rural Sindh

The purpose of this study is to investigate the existence of socioeconomic disparity levels in rural Sindh. Determining the reasons behind such disparity is not the scope of this research. Previous studies reflected that compared to lower Sindh, upper Sindh has performed better as per socioeconomic indicators such as health and literacy rate, the Multidimensional Poverty Index (MPI) calculated shows no such pattern on a closer look. Even though the MPI values for upper Sindh district are lower in comparison to lower Sindh, the intensity of poverty in upper Sindh is extreme. Pakistan Social and Living Standard Measurement (PSLM) household survey questionnaire was used to calculate the MPI of various districts selected through a stratified sampling technique. The results show the MPI values for districts in lower Sindh reflect a greater incidence of poverty compared to upper Sindh. However, the intensity of deprivation in upper Sindh is higher. For instance, the MPI value recorded for Qambar, an upper Sindh district was 0.091 and the intensity of poverty recorded was 0.67.

Can income growth alone increase household consumption of cleaner fuels? Evidence from Pakistan

Consumption of solid fuels by households is a major cause of indoor air pollution (IAP) and can severely damage health and the environment. The Environmental Kuznets Curve (EKC) literature suggests that as poor and middle-income countries grow, households will climb the ‘energy ladder' and adopt cleaner fuel technologies. This paper critically assesses that claim, using data from the Pakistan Social and Living Standards Measurement (PSLM) Survey 2013- 14. A novel aspect of our study is that, rather than treating the choice to use each fuel type as independent, we instead focus on the households' choice of fuel mix, using cluster analysis to determine in a data-driven way the fuel mixes that households actually employ. Importantly, despite income being a strong determinant of fuel mix selection, we show that income growth alone is unlikely to lead to substantial uptake of cleaner fuels. Our results challenge a practical aspect of countries moving along the EKC, and suggest that in order to reduce IAP direct policy intervention will be required.

Socio-Economic Determinants of Household access to Health Services in Selected District of Punjab


 Background: Sound health is basic right of every individual and access to health care is necessary. The right to use health services (HS) is a multifarious idea. In Pakistan provision of basic health facilities of health are inadequate. Current study was aimed at highlighting the primary reasons behind it.
 Methods: This study used cross sectional data from Pakistan Social and Living Standard Measurement (PSLM) to determine the social and economic determinants of health care services in selected districts of province Punjab. Logistic regression technique is used to measure the impact of selected variables on health access.
 Results: Results of the study showed that the health access services in the district of Faisalabad are greater as compared to the Rawalpindi and Layyah districts. Moreover, people were using private health facilities as compared to government health facilities.
 Conclusion: The study indicated that the education level, household (HH) head gender, work status, region and place of residence, and economic situation, affect the health access services in selected regions. Measures should be taken to reduce the monopoly of private health sector by providing better government health facilities.

International Remittances and Women’s Reproductive Health Care: Evidence from Pakistan

ABSTRACT This paper determines the effect of international remittances on the healthcare utilization of childbearing mothers in Pakistan using the Pakistan Social and Living Standards Measurement (PSLM) survey, 2018–19. The study reports a significant and positive effect of international remittances on the healthcare outcomes of childbearing mothers. Importantly, the remittance-receiving households have 0.615, 0.208 and 0.306 times the odds of the non-receiving households, utilizing prenatal healthcare, postnatal healthcare, and healthcare decision making, respectively, and all of them are statistically significant. Consequently, the analysis confirms that remittance receiving-households do in fact influence and increase the likelihood of utilizing prenatal healthcare, postnatal healthcare and decisions about medical treatment for women. As regression-based estimation of remittances is prone to selection bias due to the nature of the non-experimental data set, we also used propensity score matching methods, which also confirmed a significant and positive effect of international remittances on healthcare outcomes of the childbearing mothers. Thus, financial support or social development programs by the government or non-governmental organization are pivotal in enhancing the healthcare outcomes and ultimately the living standards of childbearing mothers.

Remittances and Healthcare Expenditures: Evidence from Pakistan

This study, examines the effect of remittances on healthcare expenditure in Pakistan by utilising the Pakistan Social and Living standards Measurement (PSLM) survey. The total healthcare expenditure is classified into two categories, i.e. expenditure on medicines and expenditure on clinical services. The study analyses these categories in case of both rural and urban areas of the country. Such data is generally characterised by selection bias; therefore, we employ Propensity Score Matching (PSM) instead of the commonly used econometric techniques. Findings of the study indicate that remittances enhance spending on both the clinical services and medicines. This result is robust across the urban and rural areas of Pakistan. The comparison between the clinical services and medicines shows that the impact is higher on clinical services as compared to the impact on medicines. This suggests that remittances help to improve the preventive nature of health outcomes in Pakistan. JEL Classification: D10; I21; O15 Keywords: Remittances, Healthcare Expenditure, Medical Expenditure, Clinical Expenditure, Propensity Score Matching

WELFARE IMPLICATIONS OF ECONOMIC GROWTH: AN EMPIRICAL ASSESSMENT FOR PAKISTAN

Purpose of the study: GDP Growth does not necessarily bring improvements in the lives of people belonging to lower social strata. The objective of this study is to analyse the welfare implications of economic growth in Pakistan. We aim to investigate that to what extent economic growth has been successful to bring improvements in the welfare of the poor segments of the society. Methodology: By using the data of different waves of Household Integrated Economic Survey (HIES), Pakistan Integrated Household Survey (PIHS), Pakistan Social and Living Standards Measurement (PSLM) Survey over the period of 1990-2017, we have done an analysis of income shares received by different income groups. We have also constructed Ahluwalia-Chenery Equal Weighted and Poverty Weighted Welfare Indices (Ahluwalia and Chenery, 1974). In order to analyse the welfare implications of economic growth in the country, these indices have been compared with another index termed as Income Weighted Index (IWI). Main Findings: Empirical results indicate that substantial income gaps exist among different income groups. In the absence of an effective fiscal policy, these gaps do not seem to be narrower.

One partition, many divisions? Ethnicities and education in Pakistan

If historical shocks influence educational outcomes, how long does the effect last, and does it differ among ethnic groups? This study answers these questions by exploiting the historical experiment of partition—that is the splitting of the British Raj into India and Pakistan—and by presenting a theoretical model that explains the trade-offs such a shock uncovers for different ethnic groups that have to decide between assimilation through education and maintaining their ethnic specificity. We use different rounds of Pakistan social and living standard measurement (PSLM) survey and analyze the educational outcomes of the grandchildren of partition (i.e., whose grandparents were born during the partition). We show that the scar from partition is long-lasting, as the present generation is still living under its influence. More importantly, our results reveal the different adaptation strategies of ethnic and cultural groups in the long run.

Income-related inequality in distribution of health human resource among districts of Pakistan

BackgroundSolving inequality of health human resource (HHR) is one of the motives of Pakistan health policies, however, there is still exists a massive quantity of HHR inequality in almost every district of Pakistan. The main goal of this research is to scrutinize the disparity in allocation of human health resources among 114 regions of Pakistan from the year 2012 to 2016 and to expose the foundations and aspects of HHR inequality.MethodsThe data regarding this research has been obtained from Pakistan Statistical Bureau from the year 2012 to 2016. The statistics had also been collected from United Nation Development Program (UNDP) Pakistan 2017, Pakistan economic surveys, Ministry of finance Islamabad, Pakistan, Pakistan Social and Living standards Measurement (PSLM) Surveys from 2012 to 2016. The information incorporates district wise; the number of specialists and medical caretakers those are doctors and nurses, number of hospitals, number of beds, number of dispensaries, number of beds in dispensaries, urbanization, total estimated GNI per capita, infant mortality rate, geographical area, and population size. The concentration index is used to compute the extent of disparity in allocation of human health resources and decomposition analysis is also carried out to enumerate the contribution of each variable towards total inequality. Furthermore, the horizontal concentration was used to measure the participation of the need variable.Results7. The consequent Concentration Indexes (CI) of the doctors and nurses for the year 2016 are 0.60 (95% CI= 0.42, 0.78) and 0.67 (95% CI= 0.42, 0.92) respectively. Decomposition of the concentration indexes exposed that the monetary status accounts are the leading percentage contributor in doctors disparity (77.5, 44.9, 30.6, − 11.6% and 13%) and population size (− 20.7,-10.5%, 4.6, 49.8, 19.7%). Furthermore, the monetary status formulates the superior contribution HHR disparity from nurses inequality (104.5, 75.1, 59.2, − 54.3%, − 40.1%), and population size (− 53.7, − 53.6%, − 36.3, 83.8, 65.3%). Moreover, after the identification of the need variable the Horizontal Concentration Index (HCI) values of doctors from the year 2012 to 2016 are 0.62, 0.64, 0.63, 0.62 and 0.61 and HCI of the nurses are 0.69, 0.70, 0.69, 0.68 and 0.67.ConclusionThe pro-rich disparity in allocation of HHR has been scrutinized from the year 2012 to 2016 among 114 districts of Pakistan. The hard concern of HHR disparity should be concentrated by the complete procedures from a multidisciplinary approach.

Multidimensional Energy Poverty in Pakistan: Empirical Evidence from Household Level Micro Data

This paper estimates household level incidence and intensity of multidimensional energy poverty in Pakistan using a multidimensional energy poverty index with seven dimensions weighted based on their relative importance. Although being widely discussed in the literature as a basic human right for addressing energy access, reliable background estimates, and official statistics of national-level energy poverty are not available for Pakistan. This study thus provides necessary support in understanding energy poverty severity and the incidence with multiple dimensions. Some of the existing measurement approaches analyse multiple dimensions like lack of electricity access, access to clean cooking and heating fuels and inability to obtain sufficient and reliable amount of different energy services but are deficient in other vital dimensions. Hence, the study carried out a more comprehensive measurement with additional dimensions and indicators. Results analysing the Pakistan Social and Living Standards Measurement (PSLM) survey data for 2014–15 suggest that 55 percent of the households are multi-dimensionally energy-deprived in 30 percent of the selected dimensions in Pakistan. Robustness analysis depicts the change in multidimensional energy poverty estimates as a result of changes in energy poverty cut-off scores and weights. Results also provide insights into the underlying factors affecting multidimensional energy poverty in Pakistan.