Employment- Gender gap and skill mismatch alarming

The latest Periodic Labor Force Survey (PLFS), released three weeks ago by the National Statistical office (NSO), provides some very useful insights into the current employment conditions in the country. The following are some of the key observations from the Survey report.

Key definitions

The Worker Population Ratio (WPR-U): Percentage of potential workers, i.e., the population aged between 15-60yr of age, in urban areas.

The Worker Population Ratio (WPR-R): Percentage of potential workers, i.e., the population aged between 15-60yr of age, in rural areas.

Youth WPR-U: Worker Population Ratio for population aged between 15-29yr in urban areas.

Youth WPR-R: Worker Population Ratio for population aged between 15-29yr in rural areas.

The Labor Force Participation Rate (LFPR-U) is defined as the percentage of population offering or willing to work in urban areas, whether currently employed or unemployed.

The Labor Force Participation Rate (LFPR-R) is defined as the percentage of population offering or willing to work in rural areas, whether currently employed or unemployed.

The Worker-U: Person in the labor force currently employed in urban areas.

The Worker-R: Person in the labor force currently employed in rural areas.

The Good

·         The employment conditions have improved during FY23. The WPR-U improved by almost 150to 200bps for all ages and both genders. The Youth WPR-U improved from 30.5% (4QFY22) to 32.6% (4QFY23). For all workers, WPR-U improved 43.4% to 45.2% during this period.

·         The LFPR-U improved from 38.2% in (4QFY22) to 39.4% in (4QFY23) for youth and from 37.2% to 38.11% for all workers.

·         Self-employed female workers increased in urban areas from 35.3% to 38.5% while the number of self-employed male workers in urban areas reduced from 40.4% to 39.7%.

·         Unemployment rate in urban areas has reduced from 8.2% (4QFY22) to 6.8% (4QFY23).

The Bad

·         The percentage of “own account workers” in urban areas reduced by 40bps from 33.1% (4QFY22) to 32.7% (4QFy23).

·         The percentage of regular wage/salary workers increased marginally from 48.3% (4QFY22) to 48.9% (4QFY23); however, the female regular wage workers in urban areas reduced sharply from 56.7% to 54.2% during the same period. More females were employed as helpers in household enterprises 10.2% in 4QFY22 to 11.7% in 4QFY23.

·         The proportion of female workers increased from 8% to 9.3% in the agriculture sector while it declined both in secondary and tertiary sectors. While it was the opposite for male workers.

The Ugly

·         LFPR-U for female workers remains very low at 18% (4QFY23) vs 57.3% for males; even though it has shown improvement from 16.2% in 4QFY22. Even for Young females (15-29yr age) it remains materially lower at19.3% (vs 57.6% for males).

·         Youth unemployment in urban areas remains very high at 17.3% (22.9% for young females); even though it came down from 20.2% a year ago.

·         Assam (41.7%). Himachal (49%), Kerala (42.8%), Rajasthan (43%), and J&K (59.3%) had the worst urban unemployment rate amongst young female workers. Only Delhi (9.9%) and Gujarat (9.7%) had an urban unemployment rate less than 10% for young female workers.

Conclusion

The huge gender gap in the labor force is a cause of serious concern. Female workers, especially young (15-29yr) females, are getting much fewer employment opportunities. The gender gap in the workforce is alarming and does not augur well for the acceleration in the growth rate. If we juxtapose this data with the education statistics, we find that bridging the education gap between male and female population has not resulted in equal opportunity for females in employment.

Another cause of concern is that the unemployment remains materially higher amongst the young workers (17.3%) as compared to overall unemployment level in urban areas (6.8%). The reason could be multifold like unemployability (skill mismatch and/or sub-standard education), reducing employment intensity of GDP, and poor employment growth in manufacturing sector. Nonetheless, it substantially diminishes the demographic dividend for the Indian economy.

Persistently, high ratio of self-employed and casual labor, inter alia, indicates (i) lower employment elasticity in the organized sector and (ii) skill mismatch.