Understanding Punjab’s rural non-farm economy

Usman Naeem

Where is Pakistan’s growing labor force going to find jobs? Many argue that, given the limits of arable land, agriculture cannot create much new employment, pushing job-seekers to cities. However, just because future job growth may not be agricultural, that doesn’t mean it won’t be rural. This is because of the rural non-farm (RNF) economy, which has the potential to absorb a large part of the labor force, slow migration to already congested cities, add to GDP, and alleviate poverty and inequality.

The RNF economy has been neglected by policymakers because few understand the sector and its role in development. That is not surprising given the dearth of research on RNF activity in Pakistan.

To fill this knowledge gap, the most rigorous evidence on Punjab’s RNF economy has been digitized by the International Growth Centre (IGC).^[1] The IGC project is based on a census of small and cottage industry in Punjab that was conducted by the Punjab Small Industries Corporation^[2] (PSIC) from 2011 to 2013. Following strict protocols^[3], data for 352 unique activities covering 24,210 rural clusters (villages)^[4] in 36 districts of Punjab was recorded.

The PSIC survey reveals important data to understand RNF activity in Punjab, where 63 percent of the population now live in rural areas. Following is a brief overview of the most important data.

Dividing Punjab into North, Center, South, and West regions based on the classification adopted by Cheema, Khalid and Patnam (2008), the project revealed significant regional differences in the kinds of economic activity found in villages. These differences can be explained by historical variation in the economy, agrarian structure, road and irrigation infrastructure, human development, and other factors that distinguish these regions.

Table 1 reports the average per cluster of different types of RNF activity at the level of Punjab and regions.

Table 1: Snapshot of the non-farm economic activities at Punjab and regional levels

* Non-dwelling units (NDU’s) were units that were being used for non-residential purposes, i.e., for economic and non-economic activities.
** This includes farm and non-economic activities and those that were unidentified because of incomplete or illegible information.

The PSIC data not only shows the kind of RNF activity, but also the intensity of it. The intensity of economic activity (IEA) in villages, defined as the number of non-farm economic activities in a village per 100 households, is mapped at the district level in Figure 1:

Figure 1: Average intensity of non-farm economic activity in a village by district

IEA is low in the North region, high in four out of the seven districts in the West region, high in all but one district in the South region (with the exception of D. G. Khan), and it varies from high to medium in the Centre region.

We then looked at how the seven most important categories of RNF activity were distributed regionally, as shown in Table 2:

Table 2: Main non-farm economic activities in percentage by region

Going forward, researchers should use the data set to answer a broader set of questions for this sector. Policy research stemming from this will act as a tool for policymakers to understand and subsequently tap into the true potential of Punjab’s RNF economy.

The data set is available upon request at igc.pakistan@theigc.org. Anyone wanting access to the data set should send in a request with his or her name, title, organization and a brief write-up on the proposed research, to the above address.

Usman Naeem is a Pakistan Country Economist at the International Growth Centre.

[1] This post is based on the IGC-funded project, ‘Development of an electronic database of Industrial and Commercial Activity and a Spatial Analysis of Small and Cottage Industries in Punjab, Pakistan’, the research team on which included Syed M. Hasan, Attique ur Rehman, Ijaz Nabi, Naved Hamid, and Usman Naeem.

[2] PSIC is an affiliated organization of the Industries, Commerce and Investment Department (IC&ID) with a mandate to “promote sustained industrial development through provision of market driven credit, infrastructure and technological support to contribute towards poverty alleviation through job creation and socioeconomic uplift of the province”.

[3] Data was only entered for rural clusters in Punjab, and in order to ensure quality, the data was entered in-house and under the direct supervision of the research team. In order to minimize subjectivity, a macro-enabled excel-based data entry system was designed that automated much of the data entry operations. In addition, three Stata programs were also written for improved data entry management and quality assurance.

[4] This consists of Mouzas (villages), which are the smallest revenue units recognized by the unique Hadbast number, within a Tehsil (an administrative sub-division of a district). There are a total of 25,914 Mouzas or rural clusters in Punjab.