The Effect of Income Inequality on Pricing of Food Items in Quetta


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Income inequality has no necessary connection with poverty, the lack of material resources for a decent life, such as adequate food, shelter, and clothing. A society with great income inequality may have no poor people, and a society with no income inequality may have nothing but poor people. For the first time, we have begun to acknowledge still with a curious reluctance that in many societies GNP can increase while human lives shrivel.


This study intends to examine the effect of income inequality on pricing of food items in Quetta. A substantial number of studies have been conducted earlier on the same issue but the major contribution of this study would be specifically for the region of Quetta. The study is designed probably to be conducted in three segments. First segment includes household surveys of different houses that are divided on the basis of their locations. The second source for acquiring data would be an empirical source that is CPI Index. Lastly, analyzing the results using software.

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Rising inequality is a global phenomenon. Oxfam’s briefings paper ‘An economy for the 99%’ reports only eight men today have the same wealth as 3.6 billion of the world’s population. In the last three decades seven out of 10 people living in a country have been facing inequality. Also the report mentions that in the next 25 years, the world will have its first trillionaire.

In Pakistan agriculture is the predominant sector of the economy accounting 46.2% of the gross domestic product in 2008-09 which provides livelihood for 60.94% of its rural population where its 27% poor reside (GoP, 2009). Due to food inflation of 26.61 percent in 2008-09, food expenditure are increasingly dominating household budget, the poor are consuming even less than before and the quality of their diet has deteriorated further indicating a 30% undernourished population (UNDP,2003). The ‘Household Integrated Economic Survey (HIES),2005-06 demonstrates that, out of total expenditure on average 43.05% goes for food mainly for essential food, i.e. cereals, pluses, milk, oil, vegetables and sugar where it constitutes 81% of food budget share for bottom 20% poor population.

While multidimensional poverty in Islamabad, Lahore, Karachi and Rawalpindi is below 10pc, it exceeds 90pc in Killa Abdullah, Harnai, Barkhan, Sherani Kohistan. Therefore, some Pakistani districts are as well-off as any developed country while others are on par with the poorest in sub-Saharan Africa,” report says. Oxfam’s another report titled Commitment to Reducing Inequality (CRI) ranks Pakistan at number 139 out of 152 countries. In spending on education, health and social protection, it is ranked on 146; progressive taxation is ranked at number 98 and labour rights is ranked at number 118. The table shows the gini coefficient in provinces of Pakistan for two different time periods, as gini coefficient is a measure of inequality and ranges from 0-1 and the two time periods are 1987-1988 and 2013-2014, according to which inequality has tend to increase in all regions of Pakistan except rural region of sindh, shown with a negative sign.

The effect of income inequality on food pricing, this study can be termed as a quanti-lative study that is it includes both the qualitative as well as quantitative data. This study would be a great source of help for household consumers as it would give them a framework regarding their decision making, also enables them to see the role of different factors in price determination of food items.

The scope of this study is only limited to the city of Quetta, despite the fact that it can be conducted for the province of Balochistan but due to some constraints in terms of resources and time it is only conducted under the premises of Quetta.

Literature Review

To examine the relationship between prices and household income, Broda et al. use household-level data from the 2005 Nielsen “Homescan” dataset. This dataset contains information on food purchases made by 40,000 U.S. households.

Strength of the Nielsen dataset is that it includes price data, household income, and some other household characteristic data, and allows for direct comparisons of the prices paid for the same items (food products with the same UPC codes). However, both the price and household income data have considerable limitations. The price of each food item purchased by a household is either imputed by Nielsen based on average weekly prices paid at the store or directly entered by the household. As discussed further below, both processes for recording prices paid are subject to error.

The household income data in the Nielsen survey is relatively limited and imprecise: households are simply given a list of income ranges and asked to select the one that their household income falls into. This method is unlikely to result in reliable income estimates for lower-income households. Even in sophisticated public surveys that rely on professional interviewers using computer-assisted interviewing tools to collect data and include an array of detailed questions about specific income sources, income tends to be underreported among low-income households, particularly income from public transfers.

To investigate this issue per capita inequality and welfare in the distribution of food consumption expenditures across consumer units has been focused of this research. Using the Kakwani (1980) disaggregation of Gini index and Sen (1974) welfare function, inequality and welfare in food expenditure components have been examined by employing full sample of ‘Household Integrated Economic Survey’ 2005-06.

The total food expenditure is decomposed in essential and non essential food components, having budget share of 77.37 percent and 22.63 percent respectively. Cereals and dairy products; the basic foodstuff, find its relative importance in food budget share in urban and rural areas. Inequality parameters indicate that distribution in food expenditure is more pronounced in urban area as compare to rural area. The decile dispersion ratio indicates that disparity in non essential food expenditure is quite high within urban households. It can be seen that the concentration index of dairy products, meat, fruits and all readymade food products are higher than overall Gini coefficient which implies that expenditures on these commodities are unevenly distributed over the total expenditure in favour of rich families. It is evident that cereals and dairy products are the major source of welfare in urban, rural and overall Pakistan.


Participants are selected from this pool using the following geographic and demographic targets:

  • household size (grouped into four levels)
  •  Household income (grouped into four levels)
  •  Household-head age (grouped into four levels)
  •  Female-head education (grouped into four levels)
  •  Male-head education (grouped into four levels)• Presence of children (present or not present)
  •  Household-head occupation (three levels)

Besides demographic Information, households are also asked about their preference in making choice for food and their other expenditures including transportation, financial services are also to be taken under consideration in this survey.

Sample size would comprise of 1500 households and the sampling technique would be systematic random sampling.


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