Gist of EPW November Week 3, 2021

The Economic and Political Weekly (EPW) is an important source of study material for IAS, especially for the current affairs segment. In this section, we give you the gist of the EPW magazine every week. The important topics covered in the weekly are analyzed and explained in a simple language, all from a UPSC perspective.
TABLE OF CONTENTS

1. Are Subsidies Trade-distortionary?
2. Caste Dimensions of Poverty and Wealth

1. Are Subsidies Trade-distortionary?

Context

The article analyses the changes in India’s labour and workforces and highlights the patterns observed with respect to them.

Note:

The analysis is based on comparing the two Periodic ­Labour Force Surveys (2017–18 and 2018–19) with the Employment and Unemployment Survey of 2011–12.

Introduction

• The agriculture sector has been the most labour absorbing sector in the case of India and it is a challenge for the policymakers to generate job opportunities outside of the agricultural sector.
• For the past decades, there has been the problem of jobless growth in India affecting the employability of the economy.
• The transition in the demography of India has resulted in decelerated population growth and thus the labour and workforces are receding.
• The participation rates have declined since the late 1990s, especially those of women.
• The labour force includes all those who are ready to work or searching for employment, and the workforce includes all those who have found a job and are doing the same.

Employment and Unemployment Surveys (EUS) and Periodic Labour Force Survey (PLFS I & II)

• The Employment and Unemployment surveys conducted by the National Sample Survey are the primary sources of data on various indicators of the labour force at National and State levels.
• The Periodic Labour Force Survey measures the dynamics in labour force participation and employment status.

• PLFS 1 and II contain information on the gross monthly earnings of self-employed and regular, salaried, and daily/weekly wage-earning casual labourers.
• They measure the working intensity across different types of occupations as hours actually worked.

Change in Nature of Employment

• The estimate based on PLFS II indicates that there has been a slight improvement (0.6 percentage points) in the overall labour force participation rate (LFPR) and workforce participation rate from PLFS I (2017–18) across all ages in India.
• The LFPR of males did not change much across the three surveys, but WPR declined between 2011–12 and 2017–18; yet, it is less than the decline in the Worker Population Ratio (WPR) observed for females during the same period.
• Therefore, the decline in the overall LFPR and WPR between 2011–12 and 2017–18 was largely due to a decline in LFPR and WPR among females.

Image source: EPW

Patterns Amongst The Youth

• There was a remarkable decline in LFPR and WPR between 2011–12 and 2017–18.
• A drastic decline in the youth WPR over LFPR resulted in a remarkably high unemployment rate in this population.
• PLFS I found that 17.8% of young persons (ages 15–29 years) in the labour force were unemployed.
• The decline in the LFPR of the working-age population is largely due to a decline in the youth participation rate.
• Unemployed youth contribute to more than four-fifths (82.2%) of the total unemployed people in the labour force.

Image source: EPW

Rural & Urban Differences

• Rural and urban differences in LFPR and WPR in India have declined drastically and become homogeneous, but unemployment rates are still higher in urban areas.
• The participation rates were slightly higher for urban males than their rural counterparts.
• The participation rates for females were far higher among rural females than their urban counterparts.
  • But this is declining since the mechanisation of agriculture is pushing out rural female labour, and the stifled rural non-agricultural sector is incapable of absorbing them.

Structural Changes

• There is a tilt towards the non-agricultural sector since 2011–12 as the share of the workforce that engages in agriculture declined remarkably from 47.8% in 2011–12 to 40.9% in 2018–19.
• There was a corresponding increase in the share of the non-agricultural sector from 52% to 59% in this period.
• The share of both male and female workforce in agriculture has declined.
• The female workforce engaged in casual labour in agriculture declined by nearly 9 million during the period between 2011–12 and 2018–19.
• There was a remarkable increase in the size of the female regular, salaried, or wage-employed workforce, particularly in the non-agricultural sector.
• There was a growth in the urban female labour and workforce, but that did not compensate for the decline in the rural female workforce in agriculture.

Reasons For The Structural Shifts

• The increasing mechanisation of the otherwise feminised agriculture is shrinking opportunities for women in agriculture.
• Women with low levels of education are disinclined towards engaging in casual labour in the agricultural and non-agricultural sectors.
• Employment avenues in urban areas have not been very promising for rural women due to certain factors such as mobility, transportation, cultural norms, and security.
• The decline in the rural female workforce may have accelerated with the COVID-19 outbreak.
• The Government of India launched Garib Kalyan Rojgar Abhiyan in 2020 to empower and provide livelihood opportunities to people in areas with a large number of returnee migrant workers affected by the devastating COVID-19 pandemic.

Overview

• The overall size of the labour force increased in 2018–19 from 2011–12 and 2017–18.
• The participation rates slightly improved in PLFS II from PLFS I, they were still far below those of EUS, 2011–12.
• Capital-intensive agriculture is reshaping the labour structures for women and the declining rural female workforce may be further adversely affected by the return of male migrant workers.
• The employment policies and strategies are required to consider the loopholes behind the adversities of the present labour force seriously.

2. Caste Dimensions of Poverty and Wealth

Context

The article highlights the wealth deficit of discriminated groups, Scheduled Tribes, Scheduled Castes and Other Backward Classes.

Introduction

• The recent reports highlighted the issue of continued deprivations faced by the discriminated groups.
• The Global Multidimensional Poverty Index 2021 reveals the high incidence of poverty among the Scheduled Tribe, Scheduled Caste, and Other Backward Class segments.
  • The report is published by the Oxford Poverty and Human Development Initiative and the United Nations Development Programme.
• All-India Debt and Investment Survey 2019 highlights the disproportionately meagre wealth held by the STs, SCs, and OBCs.
  • The report is published by the National Statistical Office.

Findings of The Reports

• GMPI 2021 
• • Five of six people living in multidimensional poverty in India are from disadvantaged tribes and castes. 
  • Poverty levels were highest among the STs followed by SCs and OBCs.
  • The poverty levels among the STs was more than thrice that of the other advantaged communities, while the poverty of SCs and OBCs was almost double their levels.
• AIDIS 2019 
• • AIDIS collated data on household wealth that includes land, buildings, livestock, machinery, transport equipment, deposits, shares, etc. and notes that the distribution of wealth among social groups was even more skewed. 
  • It shows that in the rural areas, the ST and SC households were the most disadvantaged. 
  • The average assets of ST and SC households were only around one-third of the average assets of other households, a group that includes all communities other than STs, SCs, and OBCs.
  • The urban sector distribution of wealth was even more skewed. 
  • The SCs have an average household wealth of Rs13 lakh which is just about half that of the Rs27 lakh averaged by the urban households in general.
  • The disparities in wealth between castes have widened with urbanisation.
  • In the rural sector, the assets of ST households were lower than the state or union territory average in 27 of the 36 states and union territories.
  • The average assets of SC households were lower than the state/union territory average in 29 jurisdictions. 
  • For the OBCs, their household assets were lower than the state or union territory average in 15 jurisdictions. 
  • The average wealth of the ST households in urban areas were lower than the state/union territory average in 24 jurisdictions. 
  • The number of states and union territories where the SC households had lower-than-average assets shot up to 30. 
  • The number of states where the urban wealth of OBC households was less than the state/union territory average extended to 28. 

Overview

• The wealth deficit of the disadvantaged castes is extensive in both rural and urban sectors.
• States like Delhi, Punjab, Maharashtra, and Kerala have the highest wealth deficit for the ST and SC households, in the rural sector.
• In states like Goa, Delhi, Punjab, Madhya Pradesh, Jharkhand, and the UT of Jammu and Kashmir, the asset size of the ST and SC households was less than half the state average.
• The deficits are relatively higher in the richer states of India and there is a serious need to re-look the status of the disadvantaged groups for equitable entitlements.

Read previous EPW articles in the link.

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