Poverty and Its Determinants in Pakistan: Evidence from Pslm 2010-11

This study estimates the poverty in terms of head count ratio, poverty gap and squared poverty gap by using the fresh available PSLM data for the year 2010-11 in Pakistan. This study also finds its economic determinants by estimating multiple OLS regression.The results show that the headcount ratio, poverty gap and squared poverty gap are statistically significant 15.06 %, 2.29 % and 0.55 %, respectively in Pakistan. All of the poverty estimates arestatistically significant almost double in rural areas as compared to urban areas. The comparisons of the poverty estimates of this year with the previous ones of2007-08 at urban, rural and nationallevel show that poverty decreased statistically significantly. Among the provinces it is the highest in Baluchistan and the lowest in Sindh. The comparison of provincial poverty estimates of this year with the same ones of previous year (2007-08) depict that poverty decreased in all of the provinces, but it is statistically significant only in case of Baluchistan.Further the resultsshow that Poverty has statistically significantinverse relationship with education. Households having animals for transportation, owning residential buildings, shops and commercial buildings and living in urban areas have less poverty than those who do not. But it hasstatistically significant positive association with the household size and dependency ratio. The household size is greater in poor families than the rich ones. As far as household head’s employment status, occupation and industry is concerned, it is highest in sharecroppers,elementary occupations, and community, social services. At a policy level, it is suggested that Govt. should focus more on education and generationof employment opportunities. Further it should provide loansto lower income groups on reduced rates for housing facilities andto start their own businesses like shops.Family planning should be encouraged especially in poor families.All such policies should focus more on rural areas of especially Baluchistan and KPK in Pakistan. Keywords: Poverty; Education; Animal for transportation; Household size;  Dependency ratio; Family planning; Residential building;Shops; Pakistan

Trends and Determinants of Rural Poverty: A Logistic Regression Analysis of Selected Districts of Punjab

Poverty is widespread in the rural areas, where the people are in a state of human deprivation with regard to incomes, clothing, housing, health care, education, sanitary facilities and human rights. Nearly 61 percent of the country’s populations live in rural areas. In Pakistan poverty has been increased in rural areas and is higher than urban areas. Of the total rural population 65 percent are directly or indirectly linked with agriculture sector. In Pakistan more than 44.8 percent people generate their income from agriculture sector, and the higher rate of increase in poverty in the rural areas has provoked debate on growth and productivity trends in the agriculture sector. Therefore, it is the need of the hour to determine such factors which affect the poverty status of a rural household. Utilising unique IFPRI (International Food Policy Research Institute) panel data together with sub-sample of PRHS (Pakistan Rural Household Survey) for two districts of Punjab (Attock and Faisalabad) the present study aim at analysing and estimating the rural poverty trends and determinants of rural poverty from the late 1980s to 2002. The data was analysed by using binary logistic model and head count measure. The results show that the chance of a household tripping to poverty increased due to increase in household size, dependency ratio, while, education, value of livestock, remittances and farming decreased the likelihood of being a poor. Moreover, the socio-economic opportunities as represented by the availability of infrastructure in the residential region also play a significant role in the level of poverty faced by a household. This study makes a modest contribution by attempting to analyse the need for focusing on anti-poverty policies, which can nip the evil in the bud.Rural Poverty, Poverty Trends, Agriculture Growth, Determinants

Measuring Multidimensional Poverty and Inequality in Pakistan

The key development objective of Pakistan, since its existence, has been to reduce poverty, inequality and to improve the condition of its people. While this goal seems very important in itself yet is also necessary for the eradication of other social, political and economic problems. The objective to eradicate poverty has remained same but methodology to analysing this has changed. It can be said that failure of most of the poverty strategies is due to lack of clear choice of poverty definition. A sound development policy including poverty alleviation hinges upon accurate and well-defined measurements of multidimensional socio-economic characteristics which reflect the ground realities confronting the poor and down trodden rather than using some abstract/income based criteria for poverty measurement. Conventionally welfare has generally been measured using income or expenditures criteria. Similarly, in Pakistan poverty has been measured mostly in uni-dimension, income or expenditures variables. However, recent literature on poverty has pointed out some drawbacks in measuring uni-dimensional poverty in terms of money. It is argued that uni-dimensional poverty measures are insufficient to understand the wellbeing of individuals. Poverty is a multidimensional concept rather than a unidimensional. Uni-dimensional poverty is unable to capture a true picture of poverty because poverty is more than income deprivatio

Trends and Determinants of Rural Poverty: A Logistic Regression Analysis of Selected Districts of Punjab

Poverty has many dimensions, like malnourishment, no shelter, being ill and not having ability to visit a doctor, no facility to go to school, unemployment, uncertainty of tomorrow, surviving only one day at a time. Poverty is losing a kid to illness due to the infected water. Powerlessness, lack of representation and freedom is another name of poverty. Poverty is of many types varying from place to place and time to time, and, has been portrayed in various manners. Poverty is the “incapability to maintain a minimum living standard anticipated with respect to basic consumption needs or some amount of income required for satisfying them [World Bank (2006)]. The bulk of the global poor are rural and will linger on thus for numerous decades. The major portion of their expenditure is generally on staple food. They have little assets such as land and others, lack of schooling and face lots of interconnecting obstacles to develop. Approximately 1.2 billion people globally expend less than a standard; “dollara- day”; and are in “dollar poverty”; 44 percent in South Asia about 24 percent each in Sub-Saharan Africa and East Asia and 32 percent in Latin America and the Caribbean. Almost 75 percent of the dollar poor lived and worked in rural areas in 2001. Projection made in 2001 suggested that 60 percent would continue to be in this state in 2005 [IFAD (2001)]. Pakistan’s population is estimated at around 155 million, and is growing at 1.9 percent per annum. Nearly 61 percent of the country’s populations live in rural areas. While 65 percent of the rural population is directly or indirectly linked with agriculture sector, it constitutes only 45 percent of their income [Pakistan (2006)]. According to the official statistics, poverty in the rural areas has gone down form 39 percent in 2001-02 to 28 percent in 2005-06. [Pakistan (2006)]. However, some studies have contradicted these contentions and argue that in contrast, the rural poverty has remained unchanged or even been trending higher over this period or at least not decreased as much as shown in official statistics. [Kemal (2003); Malik (2005); World Bank (2006); Anwar (2006)]

Incidence, Profile and Economic Determinants of Poverty in Pakistan: HIES 2005-06

This study estimates the incidence, profile and economic determinants of poverty in Pakistan using the HIES data 2005-06. The results show that headcount ratio was about 23 percent in Pakistan. Poverty incidence was more than double in rural area as compared to urban area. Decomposition of poverty into socio-economic characteristics depicts that poverty is higher in those households whose heads are illiterate or have never attended school. It decreases as the level of education increases. It is positively related with the dependency ratio.  It is higher in those households who have no access to basic facilities-electricity, gas and telephone. It is the highest in those households whose head’s employment status, sector and occupation is sharecropper, construction and elementary, respectively. Household size is higher in poor families. The results of OLS multiple regression model depict that the poverty incidence is inversely related with age, education and owned land; while it is positively associated with household size. Households who receive foreign remittances or have sewing machine or live stock experience less poverty incidence than those who do not receive or have. At a policy level it is suggested that more investment and development should be focused in agro-based industries. Live stock development can give impetus to the poverty reduction derive. Free education for those who are unable to afford the expenses, with special attention to vocational education should be provided. Broad-based overseas employment strategy should be designed. Family planning should be promoted especially in poor families. Land reforms should be implemented in letter and spirit.Key words: Poverty incidence; Dependency ratio; Education; Foreign remittances; Sewing machine;  Employment sector; Occupation; Employment status; Pakista

INDIRECT TAXES AND ECONOMIC GROWTH: An Empirical Analysis of Pakistan

The study investigates the empirical relationship between indirect taxes and economic growth in Pakistan. For estimation, the annual time series data (1974 to 2010) was used. The main purpose of the research is to find the long-run and short-run relationship between indirect taxes and economic growth. Philips Perron and Augmented Dickey fuller unit root tests were used to check the stationarity of every variable in the study. Auto Regressive Distributed Lag (ARDL) bounds testing approach for cointegrations (developed in 2001) was applied to estimate the long-run and short-run relationship among the variables. Indirect taxes have negative and significant effect on economic growth in long-run while its coefficents in short-run were insignificant. Due to one per cent increase in indirect taxes, economic growth would decrease by 1.68 per cent. ECM coefficient of indirect taxes shows 45 per cent speed of adjustment in a year. According to the research results it is imperative to decrease indirect taxes and increase the direct taxes, if we want to augment the economic growth. Currently, contribution of direct taxes out of total tax revenue is only 33 per cent and the share of indirect taxes is 63 per cent, while it should be reversed if economic growth has to increase

Education and within groups earning inequality in Pakistan

The present study focuses on identifying and estimating the extent of earning inequality due to increase in the level of education in Pakistan. Utilizing four rounds of household level surveys conducted at national level during 2001-2014, the study analyzes the effect of education on earning inequality within workers having same level of education. Quantile regression is employed to estimate and test earning inequality within workers having primary, secondary and tertiary education respectively. The results confirm that there is significant heterogeneity in the returns within each level of education. Such disparities are shown to be larger for workers at upper quantiles of the earnings distribution versus the lower counterpart. The results also show that within-group earning inequality is higher for workers with tertiary education than with secondary and primary education. Finally, the findings suggest that earning inequality does not remain same over time. These dynamic changes have enlarged lower as well as upper tail of earning distribution causing further income inequality in Pakistan. Therefore, these findings has identified that heterogeneity in the returns has very serious implication for distribution of income, general welfare and labor markets in Pakistan