Productivity & Innovation

Post-Covid informal manufacturing growth: How states fared

  • Blog Post Date 04 November, 2024
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Suresh Chand Aggarwal

Institute of Human Development

sureshchag@yahoo.com

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Bishwanath Goldar

Institute of Economic Growth

b_goldar77@yahoo.com

Recently released official data show an expansion in informal manufacturing in India in the post-pandemic period. In this post, Goldar and Aggarwal conduct a cross-state analysis and highlight that Bihar led the growth story in terms of the number of enterprises and employment generation. An additional notable trend is the feminisation of industrial labour. Financial assistance by the government helped support the recovery, particularly in rural areas. 

The recently released data of the ‘Annual Survey of Unincorporated Sector Enterprises’ (ASUSE)1 for 2021-22 and 2022-23 show that the estimated number of establishments in unincorporated sector manufacturing (hereafter, informal manufacturing) increased from 17.25 million in 2021-22 (April 2021 to March 2022) to 17.83 million in 2022-23 (October 2022 to September 2023)2 – an annual increase of 2.2%. The number of workers in such manufacturing establishments increased by 6.3% in 2022-23, and gross value added (GVA) at current prices grew by about 19%, which translates into a remarkable 12% growth rate in real GVA after adjusting for inflation.  

The observed growth in the number of establishments, workers, and real GVA in India’s informal manufacturing reflects partly the underlying growth dynamics of the sector and partly a recovery from the adverse effects of Covid-19 (because the second lockdown3 associated with the pandemic occurred in the initial part of 2021-22, and the effect persisted for several months of the year). In this post, we discuss the state-wise growth pattern, which bears, to some extent, the imprint of the reverse migration linked to lockdowns4.

Post-Covid informal manufacturing: Bihar leads the growth story

Comparison across states reveals that the largest annual increase in the number of informal manufacturing establishments – at about 33% – occurred in Bihar, up from 525,000 in 2021-22 to 808,000 in 2022-23. Other Indian states that had at least 75,000 informal manufacturing establishments in 2021-22 and recorded relatively fast growth in 2022-23 include Himachal Pradesh, Rajasthan, and Uttar Pradesh, attaining a growth rate of about 11-12% in the number of informal manufacturing establishments (Figure 1).

Figure 1. Growth in informal manufacturing establishments and change in women’s ownership of such establishments between 2021-22 and 2022-23

Source: Authors’ computations based on ASUSE data. 

Note: Only states with at least 75,000 informal manufacturing establishments in 2021-22 are considered. 

Bihar had not only the most significant (percentage) increase in the number of informal manufacturing establishments between 2021-22 and 2022-23, but it also recorded the largest increase in the proportion of such establishments owned by women. The women-owned establishments per 1,000 informal manufacturing establishments in Bihar increased from 310 in 2021-22 to 452 in 2022-23. Himachal Pradesh and Uttar Pradesh had the second and third highest growth in informal manufacturing establishments (within the groups of states compared in Figure 1) and had respectively the second and third largest increase in women’s ownership of such establishments. A positive correlation between increases in women-owned manufacturing establishments and the growth rate of the total number of such establishments is indicated in Figure 1. The cross-state correlation coefficient is 0.6, which is statistically significant.

The growth divergence among state – significant growth in establishments in Bihar, Odisha and Uttar Pradesh, and weak or negative growth in Karnataka, Gujarat, Tamil Nadu and Telangana – appears to be a consequence of reverse migration, at least partly. It is noteworthy that despite substantial reverse migration from Maharashtra post-Covid, manufacturing establishments in the state increased significantly in 2022-23, perhaps because of a substantial increase in women ownership of enterprises. 

Industrial development led by female and informal employment

Our recent research (Goldar and Aggarwal, 2024a, 2024b) reveals that a women-centric industrial development has been taking place in India in recent years. Women workers accounted for about 64% of the incremental manufacturing employment between 2017-18 and 2022-23, indicating the feminisation of industrial labour. We find a positive cross-state correlation between women’s ownership of informal manufacturing establishments and the share of women in manufacturing employment. Figure 1 above further supports our narrative of women-centric industrial development in India in recent years.

Having discussed the growth in the number of establishments, let us consider the growth in the number of workers in informal manufacturing. Bihar excelled in terms of growth in the number of workers in informal manufacturing. While at the all-India level, the growth rate in informal manufacturing workers between 2021-22 and 2022-23 was 6.3%, in the case of Bihar, the employment growth rate was 60% (with the growth rate of female workers being about 80%). The growth rates for informal manufacturing employment in 2022-23 in some of the other states were 27% in Rajasthan (female workers growth rate, 27%), 24% in Chhattisgarh (female workers growth rate, 45%), 12% in Himachal Pradesh (female workers growth rate, 30%), 11% in Uttar Pradesh (female workers growth rate, 18%), and 10% in Maharashtra (female workers growth rate, 17%). Among the states with at least 75,000 informal manufacturing establishments in 2021-22, the growth rate in both female workers and total number of workers in informal manufacturing was the highest in Bihar. 

Between 2021-22 and 2022-22, Bihar accounted for about half of the increase in the total number of informal manufacturing establishments in India and 30% of the incremental employment (and 33% of incremental female employment) in such establishments. This is an extraordinary achievement for a state ranked the lowest among 33 states and union territories (UTs) in per capita gross state domestic product (GSDP) in 2022-23 (with a per capita GSDP about one-sixth of that of Telangana and Karnataka).  

Among the states considered in Figure 1, Bihar ranked second in terms of the rate of increase in female workforce participation in rural areas between 2019-20 and 2023-24, a 22 percentage points increase. This increase in workforce participation rate has undoubtedly spurred an increase in female entrepreneurship and employment in manufacturing in Bihar. 

Did government assistance help?

There are reasons to expect that financial and other assistance and provided by the Indian government to MSMEs (micro, small and medium enterprises) helped them recover from the adverse effects of the pandemic5. 

To assess whether government financial assistance contributed to growth in establishments and employment in informal manufacturing, we have undertaken an analysis at the level of NSS regions6 using ASUSE unit-level data. For each NSS region, the growth in the number of informal manufacturing establishments and employment between 2021-22 and 2022-23 is juxtaposed against the percentage of non-agricultural unincorporated enterprises stating that they received some government funding during the year, including grants and donations from the government, or production subsidy, interest subsidy, or capital transfer like building grants. 

The analysis shows that an average of 34% of the respondents reported receiving government financial assistance. The NSS regions were divided into two groups: regions where more than 34% of respondents said they received government financial assistance, and the rest. The median growth rate in informal manufacturing establishments and workers was 8.9% and 12.7%, respectively in the former group of NSS regions, and (-)1% and 4%, respectively, in the second group7. This fact highlights the role that government financial assistance has played in helping MSMEs recover from the effect of Covid-19. We reach the same conclusion when we consider for each NSS regions the percentage of non-agricultural unincorporated enterprises having institutional loans (taking 32% as cut-off to form groups). 

From a deeper analysis, we find that in NSS regions that are pre-dominantly rural (that is, more than 60% of the enterprises are in rural areas), institutional loans and government financial assistance made a big difference to the growth rate of establishments and employment. However, in NSS regions that are rural-urban mix or predominantly urban (about two-thirds of the NSS regions, as per the above criterion), the growth rates are low and institutional loans and government financial assistance yielded only a modest gain in growth performance (Figure 2).

Figure 2. Government financial assistance, institutional loans and informal manufacturing growth

Source: Authors’ computation using ASUSE unit-level data. 

Notes: (i) NSS region-level estimates are used. (ii) Median growth rates among NSS regions in a group are shown. (iii) About one-third of NSS regions are included in the predominantly rural category, based on the criterion that more than 60% of enterprises are in rural areas. 

A final word: Need to raise productivity of women-owned establishments

Although there has been an increase in women-owned establishments in the informal manufacturing sector, particularly in the state of Bihar, a typical female-owned informal manufacturing unit is still about half the size of a male-owned unit. The GVA per establishment is one-seventh, and the GVA per worker is about one-third. While female-owned informal manufacturing enterprises have significantly contributed to growth in recent years, enhancing such enterprises’ productivity is necessary as we move toward Viksit Bharat (Developed India). This needs financial and technical assistance from the government, and training focusing on women-owned industrial enterprises.

Notes:

  1. This survey is carried out by the National Sample Survey Office, Ministry of Statistics and Programme Implementation.
  2. The difference in the months of the year covered in two surveys needs to be taken into consideration while computing annual growth rate.
  3. The periods of significant lockdown due to Covid-19 were 24 March 2020 to 31 May 2020 in the first wave and 5 April 2021 to 15 June 2021 in the second wave. For a discussion on the impact of Covid-19 on manufacturing, particularly the unorganised segment, see Goldar and Aggarwal (2023a, 2023b).
  4. On post-Covid reverse migration in India, see Mitra and Srivastava (2024), Behera et al. (2021), among others.
  5. Sharma (2022) notes that some of the schemes that provided support to the MSMEs were: (i) Emergency Credit Line Guarantee Scheme, (ii) Credit Guarantee Scheme for Subordinate Debt, (iii) equity infusion for MSMEs through ‘Fund of Funds’ and (iv) Interest Subvention Scheme for Shishu loans under Pradhan Mantri Mudra Yojana (PMMY)
  6. This comprises 87 regions, which are more disaggregated than the state level. The analysis cannot be done at the district level, because the survey design does not permit district-level estimates.
  7. When regression equations are estimated by regressing the growth rates in the number of establishments and workers on the extent of government financial assistance using data on NSS regions, the coefficient is found positive and statistically significant.

Further Reading

  • Behera, Minaketan, Sibanarayan Mishra and Alok Ranjan Behera (2021), “The COVID-19-Led Reverse Migration on Labour Supply in Rural Economy: Challenges, Opportunities and Road Ahead in Odisha”, Indian Economic Journal, 69(3): 392-409.
  • Goldar, B and SC Aggarwal (2023a), ‘Impact of COVID-19 on Growth in Employment and Gross Value Added in India’s Unorganized Manufacturing’. Available at SSRN.
  • Goldar, Bishwanath and Suresh Chand Aggarwal (2023b), “Trends in Employment, Productivity, Real Wages and Labour Standards in Indian Manufacturing in Recent Years”, Indian Journal of Labour Economics, 66(2): 561-581. 
  • Goldar, B and SC Aggarwal (2024a), ‘Employment Growth in India in Recent Years: Contributions of A Women-Centric Industrial Development’. Available at SSRN.
  • Goldar, B and SC Aggarwal (2024b), ‘Growth in Aggregate and Manufacturing Employment in India, 2017-18 to 2023-24: Trends and Some Underlying Factors’. Available at ResearchGate.
  • Mitra, Aruap and Puneet Kumar Shrivastav (2024), “Understanding Migration Behaviour in India from PLFS Data: Post-lockdown and Future Perspective”, Economic and Political Weekly, 59(1): 47-54.
  • Sharma, Akhilesh K (2022), “Implications of Policy Initiatives for MSMEs amid Economic Disruptions Caused by COVID-19”, Vikalpa: The Journal for Decision Makers. 47(1): 7-18.
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