Discussion Paper

No. 2011-21 | July 01, 2011
Human Capital and the Adoption of Information and Communications Technologies: Evidence from Investment Climate Survey of Pakistan

Abstract

This paper studies the impact of human capital on the adoption and diffusion of Information and Communications Technologies (ICT) in the Pakistani firms using the World Bank Enterprise Survey 2002-07. The paper considers various indicators of human capital and measures of ICT adoption and diffusion. On-the-job training, manager’s level of qualification and production workers’ level of education are found to positively determine the use of emails, website and other means of communication in a firm. The results are robust to the inclusion of geographical, sectoral and structural control variables. Firm size, sales and workers’ compensation are also positively associated with the use of ICT. The findings show the importance of accumulation and development of human capital in the productivity growth in the era of skill-biased technical change. A concerted national effort for the enhancement of the workforce’s computing skills is therefore a must if a developing economy such as Pakistan is to improve its competitiveness.

JEL Classification

I21 O10

Cite As

Mazhar Mughal and Barassou Diawara (2011). Human Capital and the Adoption of Information and Communications Technologies: Evidence from Investment Climate Survey of Pakistan. Economics Discussion Papers, No 2011-21, Kiel Institute for the World Economy. http://www.economics-ejournal.org/economics/discussionpapers/2011-21

Assessment



Comments and Questions


Anonymous - Human Capital and the Adoption of Information and Communications Technologies: Evidence from Investment Climate Survey of Pakistan
July 15, 2011 - 20:58

Mughal and Diawara try to study the impact of human capital and the adoption of information and communications technologies in Pakistan. The idea is indeed very interesting. The authors used data drawn from World Bank Enterprise Survey (2002-2007). The paper gives a detailed review of literature, and three relevant assumptions ...[more]

... (H1,H2,H3) are tested.
Here are some comments and suggestions:
Authors may give more details about the econometric technique used, especially about the “random-effect panel model”
Figure 1 authors do not explain why the telephone lines per 100 people increased slowly while the mobile cellular and internet users increased rapidly. Section 2 (stylized facts) needs more details, for example regions with higher ICT adoption, and figures about firms should be given
Econometric analysis
In equation (1) “i” must be defined exactly, i=1,…? And k is not defined
Authors should explain the intuition behind explanatory variables
Table 3 summary statistics; mean and std Dev are not useful for binary variable. Contingency table will be better.
Are H2 and H3 verified ?
The paper can be published with the above mentioned minor modifications.

Farid Makhlouf


Mazhar Mughal - Reply
July 17, 2011 - 23:11

We are grateful that you took time to read and comment on our paper. Here are my replies to your questions and comments:
1. The explosion of mobile industry and a concomitant sickly growth in land lines is a common phenomenon in the developing countries. The telephone line sector in ...[more]

... most of the developing countries has traditionally been in the hands of state owned enterprises, unchallenged by market forces. On the other hand, the mobile telecom sector is recent and is much more open to competition by the private sector, implying lower prices, more options for the consumers and tougher competition. This has led to an explosion of mobile connection subscription in the developing world, including in Pakistan. We will duely add a line mentioning this evolution. Thanks for that.
2. We didn't give much details of the surveyed firms' geographical distribution. We will briefly describe our firm sample. Thanks for pointing it.
3. i, as mentioned just below the equation, refers to the firm observed. k, however, was not defined.
the equation is modified accordingly. Thanks again for pointing it.
4. Intuition behind our included variables: We think, we have given space to description of all the main variables, briefly in the introduction, and more formally in section 3. We will be happy to reconsider if you point out an important variable we missed.
5. We beg to differ. The mean and st. deviation of binary variables are not meaningless. For instance, the mean of the binary International Quality Certification variable means that 30 percent of the firms surveyed possess such certification.
6. On the verification of H2 and H3: On page 10, we mention the validity of H2:
"There is also some support for the second hypothesis. Workers’ education is found to be positively and significantly associated with the percentage of workers using computers and the proportion of computer-controlled production whereas its impact on the proportion of website and email use is not significant."
and that of H3 on page 12:
"Subsequently, we can state that our third hypothesis is also partially verified. Sales and the possession of international quality certification is important in the probability of website and email use but not on the proportion of workers using computers."
We also recap these results in the conclusions.


Anonymous - Referee Report 1
August 09, 2011 - 08:41

see attached file


Anonymous - Referee Report 2
October 18, 2011 - 16:02

See attached file


Mazhar Mughal - Reply to second reviewer's report
October 19, 2011 - 14:34

Please see attachment