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This study aims to analyze access of cotton growers to Sustainable Livelihoods Assets Pakistani Punjab.

This study uses the department for international development (DFID’s) sustainable livelihoods framework (DFID) (1999). Where data collection was done by using a well-structured questionnaire from 200 randomly selected cotton growers of the district Muzaffargarh. There are five livelihood assets (human assets, natural assets, financial assets, physical assets and social assets) in the SLF, this study has used three different indicators/proxies for each asset except natural assets, where four indicators were used to capture the salient features of the respondents’ access to that assets. Each indicator was given a weight by using the entropy technique to keep the consistency of the quantification. Livelihood assets indices were calculated in case of each livelihood asset for conducting Livelihood Assets Pentagon Analysis. Value of livelihood index ranged from 0–4.

Livelihoods Assets Pentagon analysis shows that cotton growers do not have proper access to all five livelihood assets. The asset with the highest capacity were social assets (sustainable livelihood index value = 0.3994), followed by natural assets (0.3294), financial assets (0.2511), human assets (0.2143) and physical assets (0.0897).

This study uses the SLF developed by DFID for analyzing factors affecting access to livelihoods assets of cotton growers in Pakistani Punjab. Sustainable agriculture and sustainable rural livelihoods lead to sustainable livelihoods where environment quality is taken into consideration. The study contains significant and new information.

This study aims to estimate the determinants of household spending on education and nutrition. Education and nutrition are noteworthy elements for human development and welfare. Separate estimates are being provided for male and female as gender determines household welfare and gender-based analysis of household spending evaluates the aptitude of decision power as well as measures their influential role in human welfare.

Fruits, milk and dairy products are taken as proxy of substantial portion of nutrition. The study used primary urban household-level data that collected from Faisalabad city. The authors used double hurdle model.

The findings of the study show that females are more likely to spend on education. Household size and number of children negatively determine the household spending on education and nutrition. Number of employed household members, level of income and education are positively associated with household spending on education and nutrition by male- and female-headed households. A very low public spending on education and nutrition have led to upsurge the hurdles of households in Pakistan.

The study recommends that government should provide the employment opportunities, especially for females for stable and increased household income that leads to improve the household welfare.

Several studies have examined the education spending (Mbanefoh et al., 1997; Ichoku and Leibbrandt, 2003; Donkoh and Amikuzuno, 2011; Cisse, 2011), but these studies ignored to investigate the gender role and household spending on nutrition and education. This study is crucial in drawing suitable policy recommendations for household welfare. This study filled the gaps and scrutinized the issues that interrelated with household spending.

Financial protection of households against catastrophic healthcare expenditure (CHE) is defined as one of the main goals in health systems. The purpose of this paper is to measure and decompose socioeconomic inequality in CHE among households in Kermanshah province, Western of Iran.

This cross-sectional study was carried out among 1,188 households in 2017. Data were extracted from the Household Income and Expenditure Survey which is conducted by the Statistical Center of Iran. The CHE is defined as household healthcare expenditure greater than or equal to the 40 percent of household’s “capacity to pay.” The concentration curve and the Wagstaff (W) and Erreygers (E) indexes were used to illustrate and measure the extent of socioeconomic inequality in CHE. In addition, the authors decomposed the W and E indexes to identify the main determinants of socioeconomic inequality in CHE.

The results indicated that the prevalence of CHE among households was 4.12 percent (95% confidence interval (CI): 3.13 to 5.42 percent). The estimated value of the W and E indexes were −0.2849 (95% CI: −0.4493 to −0.1205) and −0.0451 (95% CI: −0.0712 to −0.0190), respectively; suggesting the concentration of CHE prevalence among the poor households. Decomposition analyses indicated socioeconomic status as the most important factor contributing to the concentration of CHE among the poor. In contrast, health insurance coverage was found to increase the concentration of CHE among the rich in Iran.

The current study demonstrated a higher concentration of CHE among the poor households in Kermanshah province. These results call for the government’s efforts to reduce healthcare expenditure among socioeconomically disadvantaged populations. Further studies are required to understand the mechanisms through which health insurance coverage increased the probability of CHE among rich in Kermanshah province.