The Banyan Shades

Unemployment data in India and its analysis 

By Abhijit Suresh and Richa Thakur

Unemployment statistics need to be demystified so that policy commentators, lawmakers and the general populace can be informed about definitions concerning unemployment rates across different sections of populations in Indian villages and cities. This analysis uses the data from the Economic Survey of India 2022-23 to understand the variations created in the employment statistics in the pre-pandemic and post-pandemic time period.

We start with the analysis of India’s unemployment calculated as per “usual status” based on the data sourced from the Economic Survey of 2022-23. This gives us a bird’s eye view of the employment scenario in India and the general trends of the same.

Employment rates as per usual status is calculated as such:

“For a person to be categorized as employed as per usual status, he/she must have pursued an economic activity for at least 30 days during the 365 days preceding the date of the survey.”(Economic Survey of 2022-23)

Subsequently, we also provide data and analysis for employment rates from a specific time frame to show how the pandemic affected the employment situation in India. For this I use employment rates as per current week status, also sourced from the Economic Survey of 2022-23.

The data collected over a longer period of time (usual status) gives us a more comprehensive perspective of the country’s employment situation, compared to the data from just one week (current week status). When we look at the long-term data, it is evident that the country has been steadily reducing its unemployment rates. This trend has remained consistent over the past few decades and shows the positive effects of the numerous government programs and the strong growth of the Indian economy.

General trend in Unemployment in India

A careful analysis of the graph brings out certain insights which prove multiple hypotheses floated by policy analysts over the years:

  1. Unemployment rates have exhibited a consistent downward trend amongst rural and urban males and females.
  2. Unemployment rates are much lower in rural areas than in urban areas.
  3. While in rural areas, the percentage of unemployment amongst women has been lower than that in men, we observe the opposite in the case of urban areas.

A similar analysis of the employment trends during COVID-19 would inform us about specific fluctuations during the pandemic. “While usual status has a long reference period of one year, current weekly status (CWS) is a stricter benchmark. It can capture the loss in duration of employment during events such as a pandemic, with a reference period of one week.” (Economic Survey of 2022-23)

Trend specific to pre and post COVID-19

A careful study of the data and its representation points to the following observations:

  1. A higher unemployment rate according to current weekly status in comparison to the usual status could suggest a more volatile labour market. This suggests an increase in short-term and temporary jobs. The data before the pandemic and during the pandemic remains consistent in showing the volatility of the labour market.
  2. The data informs us about the differences in recovery in the labour market in urban and rural areas. The recovery in unemployment rates among rural males and females has been much steeper in comparison to that in urban areas. Unemployment rates in rural areas post pandemic have fallen below pre-pandemic levels. However, the same has not been the case with urban areas.
  3. The difference in impact of the pandemic on unemployment rates between urban and rural areas is also insightful. It shows the difference in impact on connectivity globalisation has had on urban areas as opposed to that in rural India. Employment in urban India, more dependent on global forces, took a greater hit due to the pandemic. The rural economy, on the other hand, was relatively immune to the drastic spurts in unemployment rates influenced by the pandemic.
  4. During the pandemic, the data suggests that a lot more women in rural areas were employed as compared to the pre pandemic levels. The workforce has retained the women who joined during the pandemic hence leading to the fall of unemployment rates among rural women in general.
  5. Greater fluctuations in employment rates in men was observed in both urban and rural areas as compared to that among urban and rural women. The greater volatility of employment among men has to be further analysed, along with factors influencing relative stability of employment rates among women. Further research can also look into nature and duration of employment.

Conclusion

The statistics based on usual status shows the general trend in fall in unemployment rates in India over the past few years. Additionally, the weekly statistics indicate that women have remained more consistently employed as compared to men in urban and rural sectors.

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