A Hazy Picture On Employment In India
- Indicators of structural transformation in an economy
- Data Collection on employment – Issues
- Positives from PLFS
- Negatives exist – still
- What can be done to resolve this issue at hand?
In the context of PLFS data over the last 3 years, examine the structural changes in unemployment in India. (10 marks, 150 words)
Can we say that the data on unemployment in India from various surveys do not help us infer any long term trends? Elucidate. (15 marks, 250 words)
The economy’s growth rate, as measured by gross value added (GVA) at constant prices, surged from 4.27 percent before the economic reforms to 6.34 percent after the reforms, and to 6.58 percent between 201011 and 201920 at 201112 prices. This growth trajectory was followed by a persistent reduction in agriculture’s percentage of total economic production, from 30% in 199091 to 18% in 201920, and a steady increase in nonagriculture output share of total economic output. Similar shift is not observed in employment numbers.
Indicators of structural transformation in an economy
- Rate of growth and change in the structural composition of output
- Rate of growth and change in the structural composition in Employment
India has seen reasonably regular changes in the first indicator, particularly since the 1991 reforms, but there has been no consistent or clear pattern in employment.
Data Collection on employment – Issues
There are huge differences in the understanding of results and research in employment patterns in India. This is partially owing to changes in the labour force and employment caused by economic, sociological, and technological
causes, and partly due to data gaps on various aspects of employment. The sources of data include:
- Decennial population census – last available data 2011
- Nationwide quinquennial surveys on employment and unemployment by the National Sample Survey Oﬃce (NSSO) – available upto 2011-12
- Periodic Labour Force Survey (PLFS) – available annually since 2017-18
The PLFS is based on a diﬀerent sampling framework and uses a diﬀerent analytical approach visavis NSSO surveys on employment.
- As a result, the NSSO surveys’ time series data on employment and unemployment are not comparable to the PLFS data. The NSSO data can be utilised as a starting point at best.
- PLFS data cannot be used to infer an underlying trend, as they are available only for three years
- The PLFS data can be used to reveal the eﬀect of various policies and developments during the current political regime as well as to understand and shape the employment scenario based on concrete statistics.
Positives from PLFS
- The worker to population (WPR) ratio increased from 34.7 percent in 201718 to 38.2 percent in 201920. This is a reversal of the previous pattern, which saw WPR fall after 200405. It means employment has increased at a considerably quicker rate than population growth.
- WPR has risen in both the rural and urban populations, as well as in both male and female populations. This increase in WPR is all the more significant because it coincides with a rise in the labour force participation rate.
- PLFS surveys does not support the claim that women are leaving the workforce. Between 201718 and 201920, the female WPR ratio increased from 17.5 percent to 24 percent.
- Also, the participation rate discrepancy between male and female workers is shrinking. In 201718, there were 32 female workers in the workforce, compared to 100 male workers. In 201920, this number grew to 40.
- The female labour force in rural areas has a lower unemployment rate than the male labour force, whereas the reverse is true in metropolitan areas. Despite the fact that the female labour force participation rate in rural India is 33% greater than in urban areas, this is the case. The reason for this could be that in the informal sector, which dominates rural areas, there is less gender discrimination than in the formal sector, which dominates metropolitan areas.
- The unemployment rate based on principal status plus subsidiary status decreased from 6.1 percent in 201718 to 4.8 percent in 201920. This indicates that between 201718 and 201920, the number of jobs increased at a quicker rate than the number of job seekers.
Despite this, the number of unemployed people increased by 2.3 million between 2017 and 2018, owing primarily to a rise in the number of job seekers (52.8 million) over the same period.
Sectoral composition of workforce
|Agriculture & Allied
- The share of industry and services in overall employment has not increased. This indicates that the agricultural labour force is not being displaced. 56.4 million new employment were produced between 201920 and 201718. 57.4 percent of these jobs were created in agriculture and related industries
- Within the wide industry group, manufacturing employment increased by only 1.8 million in the last two years, while construction activity added 6.4 million new jobs.
- The problem is that only a handful of the young labour force, which is becoming increasingly educated, were able to find more lucrative work outside of agriculture. This is due to the adoption of capital-intensive and, in many cases, labor-displacing technologies and production practises by the manufacturing and service sectors. This is exacerbated by the increasing usage of modern technologies such as Artificial Intelligence and the Internet of Things.
It is a pretty wellknown reality for postliberalisation India that there is a paradox between the expanding share of industry and services in national GDP and the lack of a significant growth in employment share. This calls into doubt the relevance of traditional economic growth and development models, which centred on a largescale movement of the labour force from agricultural to industry.
What Can Be Done to Resolve This Issue at Hand?
Perhaps it is time to reconsider traditional economic development models and their applicability to growing economies such as India. We may have consider more relevant agricentric model of economic transformation in order to create more appealing, remunerative, and rewarding jobs in and around agriculture.
Besides this there is also an urgent need to generate much more employment in the manufacturing and services sector compared to the number of jobs they have oﬀered in the recent past. This should include
- Modifications in labour regulations that discourage industry from adopting labor-intensive production
- Employment-related production incentives
- Special assistance for labor-intensive economic activity.
Back to the Basics: Understanding the terms used:
Worker Population Ratio (WPR): the percentage of persons employed among the persons in the population
Labour Force: The number of people who are employed plus the unemployed who are looking for work
Labour force participation rates: Calculated as the labour force divided by the total working-age population
Usual Principal Status (PS)
UPS approach relates to the activity status of a person during the 365 days preceding the date of survey. The activity status on which a person has spent relatively longer time (183 days or more) during the period is considered the usual principal activity status of the person. A person unemployed under this approach indicates chronic unemployment.
Usual Principal Status and Subsidiary Status (PS+SS)
Usual Principal Status and Subsidiary Status approach is an extension to the principal status approach. If a person has engaged in any economic activity for a period of 30 days or more during the preceding 365 days a person is considered as employed under this approach.