Pakistan Socio-Economic Factors

Socio-Economic Factors in Pakistan Play a Crucial Role in How People Access and Use Media and Communication Technologies [1]

Using demographic factors-education attained and income levels, we analyze how these factors intersect in Pakistan and determine people's access to media and ICTs

Fifty two percent of the survey respondents identified themselves are illiterate; making iliteracy and lack of higher education a significant issue in Pakistan.   In addition, due to low levels of development and lack of opportunities, a high education does not necessarily translate into higher income levels. [2]

However, those with higher education do enjoy some advantages- certain technical skills (reading ability, familiarity with technology, etc) that are helpful to internet and mobile phone use as well as for reading newspapers, etc. In addition, those with higher levels of education are more likely to understand English (the official language of government, commerce and upward social mobility-see table below).

Table 1: Percent of those respondents who say they understand English
         
           BBC Pakistan 2008: survey of adults (15+) n = 4020

Media and ICT Access Trends
Respondents were asked to report their access to media and ICTs in their households as well as “anywhere”.  Television access “anywhere” was between 80 percent and 90 percent for all income and education groups. In terms of household access though, those with higher incomes education levels, were more likely to have television access at home (See table 1). Similarly, the probability of people having cable television or a satellite dish at home also increased with as income or education level rose.

Table 2: Household Access by Income and Education

BBC Pakistan, survey of urban adults, n = 4020 adults, education: 1342 illiterate, 1144 grades 1-9, 1118 Secondary, 416 Post Secondary; 940 low income, 1166 middle income, 1642 high income. Excluded categories: digital set top box, internet, high speed internet, i-Pod/Mp3 Player.

Both income and education showed positve correlation with household access to mobile phones, radios and computers.

Media Use and Socio-Economic Status

Chart 1 
       

Both income and education correlated with all media use, although reading newspapers and using the internet (which is still in nascent stages) showed deeper correlation with education (charts 1 and 2).

Chart 2
        

General radio use did not fluctuate as much with age; yet how people listened to it had some correlation with income and education. As both income and education levels increased, radio listeners migrated from listening on their radio sets at home to listening wherever they were via their mobile phones (table 3).

Table 3: Radio Listening Locations
Percent of those radio listeners who said they listened to radio at home or on mobile phones
        

In addition to radio listening locations, education levels also seemed to correlate with the kind of radio programming people tuned in to listen.

As table 4 shows, as education increases, so does listenership of news programs and programs discussing political issues. Listenership to religious programs on the other hand declines, whereas a heavy interest in music programs is observed across all education groups.

Table 4
           

Related Links:

Urban-Rural Regional Divide in Communication
Gender Divide in Communication

Youth and Communication Use and Access

Attitudes to News and Information
Religious Media: A Cable TV Phenomenon
High News Consumers in Pakistan

News Radio: What Choices Do Some Pakistanis Have?
News Television: Who's Watching?


[1] For the purpose of this article, socio economic factors under consideration are education and income. BBC Pakistan, survey of urban adults, n = 4020 adults, education: 1342 illiterate, 1144 grades 1-9, 1118 Secondary, 416 Post Secondary; 940 low income, 1166 middle income, 1642 high income.

[2] For this survey, the Pearson’s Correlation, a familiar measure of dependence between two quantities was applied to determine a relation between income and education. It is obtained by dividing the covariance of the two variables by the product of their standard deviations. The  correlation coefficient between education and income was .316 at 0.01 levels of significance, signifying very little correlation between both these factors.