Search

As one of the dimensions of vulnerability, this paper empirically investigates the inability of rural dwellers to cope with negative income shocks. A variable coefficient regression model is applied to a two-period household panel dataset collected in the North-West Frontier Province, Pakistan, an area with high incidence of income poverty and low human development. The empirical model allows for a different ability to smooth consumption, approximated by a linear function of households’ attributes, and controls for the endogeneity of observed changes in income, using qualitative information on subjective risk assessment. Estimation results show that the ability to cope with negative income shocks is lower for households that are aged, landless and do not receive remittances regularly. [ABSTRACT FROM AUTHOR]

Indoor air pollution, due to household solid fuel use, is responsible for a significant burden of disease in developing countries. Fuel choice is often associated with household income. However, many other socio-economic and environmental factors also influence the choice of fuel and the resultant indoor air pollution exposure. The aim of this paper is to assess the role of poverty on indoor air pollution in Pakistan through fuel choice. Furthermore, a multinomial logit model has been used to predict the determinants of fuel choice. The results indicate that although poverty makes a significant contribution, other factors such as household location and area, household size, low level of human capital, asset ownership structure and access to basic utilities are the important correlates of fuel choice. Knowledge relating to the proximate determinants for fuel choice is crucial to inform policy and can play a pivotal role in designing sustainable intervention strategies to reduce the risk of exposure to indoor air pollution in Pakistan. [ABSTRACT FROM PUBLISHER]

Landlessness and poverty are closely linked to each other. Being agricultural country, land is considered as a principal asset in Pakistan. This study aims to identify the poverty situation of landless peasants in Pakistan. Primary data are collected by simple random sampling method. Binary logistic regression model are used to estimate the relationship between landlessness and poverty. Result shows that high age of household head, education level, land ownership, operational land holding, and income earners in a household significantly reduces the chances of household's poverty. The value of Gini coefficient is found 0.63 that indicates that there is high income inequality. [ABSTRACT FROM AUTHOR]

This study uses a computable general equilibrium (CGE) model specially constructed for investigating gender dimensions of the effects of trade liberalization in Pakistan in both production and consumption. The model employs various indicators to measure the gendered impacts, including income poverty (Foster-Greer-Thorbecke [FGT] Indices), time poverty (leisure), capability poverty (literacy and infant mortality), and welfare (Equivalent Variation [EV]). The simulation results show that revenue-neutral trade liberalization in Pakistan increased women's employment in unskilled jobs and increased women's real wage income more than men's for all types of labor, but kept the division of labor biased against women. The study finds that Pakistan's trade liberalization adversely affected women in relatively poor households by increasing their workload, deteriorating capabilities, and increasing relative income poverty. However, the effects remained gender neutral or favored women in the richest group of households. [ABSTRACT FROM AUTHOR]