Finance Constraints and Firm Transition in the Informal Sector: Evidence from Indian Manufacturing

Abstract

This paper focuses on the role of finance constraints in determining the lack of transition of firms in India from very small family firms, which are the predominant type of firms in the informal sector, into larger informal firms that employ non-family labour. Using a rich firm-level data-set drawn from nationally representative surveys of the Indian informal manufacturing sector, this paper tests for the role played by finance constraints in firm transition in the informal sector at the firm and district level. There is evidence that the difficulty that firms face in accessing external finance acts as a significant constraint to small firm growth in the informal sector. Looking at data from India's districts, it is found that the financial development in a given district increases the likelihood that firms in the district will make the transition from household enterprises into non-household enterprises.

JEL Classification::

• O17
• L25
• D22

The authors thank the Central Statistical Organisation for providing access to data. An earlier version of this paper was presented at the 4th IGC-ISI India Development Policy Conference held at the Indian Statistical Institute, New Delhi, on 17–18 December 2013 and at the IGC South Asia Growth Conference held on 11–13 March 2014 in Lahore, Pakistan. The authors thank the participants for their useful comments. The authors also thank the editor and two anonymous reviewers for their helpful and extensive comments. The usual disclaimers apply.

Notes

¹ An exception is Ranis & Stewart (1999), who divide the informal sector (which they term the V-sector) into a traditional, stagnant component and a modernising, dynamic component. As they argue, ‘such a differentiation significantly enriches (the) analysis … (and is) much more representative of real world conditions’ (p. 263). In our categorisation of informal enterprises, pure household enterprises and non-household enterprises broadly correspond to the traditional and modern components of the V sector in the Ranis–Stewart approach.

² Our definition of the informal sector corresponds to a conceptualisation of informal firms such as those that are minimally registered and below size thresholds for taxation or labour regulation. As Harriss-White (2010) notes, in this definition of informality, “it is not the intrinsic characteristic of activities, but rather the boundaries of state regulation, that determine the degree of informality” (p. 171).

³ In the enterprise surveys undertaken by the World Bank, 35% of the small firms view the cost of finance as a major growth constraint and 30% view the access to finance as a major growth constraint (Beck, 2007).

⁴ In the Indian context, the difficulty that micro and small enterprises face in receiving financing from formal sources has been documented by Shah et al. (2007) and Bhattacharya (2013).

⁵T-tests on differences in labour productivity between PHEs and MHEs, and MHEs and NHEs are significant at the 1% level for the entire period and for each of the 3 years, 2000–2001, 2005–2006 and 2010–2011.

⁶ The model would explain the probabilities of a firm falling into the three enterprise types. For more discussion on the ordered probit model, see Wooldridge (2010).

⁷ Informal enterprises in India are often registered under different State Acts or Government Authorities. State Acts include the Sales Tax Act, Provident Fund Act and Shops and Establishment Act. Government Authorities include the District Industries Centre, Khadi and Village Industries Commission, Coir Board, Silk Board, Jute Commissioner and municipal corporations.

⁸ Kumar et al. (2005) use credit per capita and deposits per capita as an alternative measure of supply of financial institutions to examine the trends in financial access in Brazil.

⁹ The two terms, “informal sector” and “unorganised sector”, are used interchangeably in the Indian context.

¹⁰ The NSSO survey data for the year 1994–1995 also lacks information on LINKAGE, ASSISTANCE, ACMAINT, REGIS and ELEC.

¹¹ The states included are Andhra Pradesh (AP), Assam, Bihar, Gujarat, Haryana, Karnataka, Kerala, Madhya Pradesh (MP), Maharashtra, Orissa, Punjab, Rajasthan, Tamil Nadu (TN), Uttar Pradesh (UP) and West Bengal (WB).

¹² We also estimate Equation (1) for each year and we find that the results are consistent across years. Hence, the results for the pooled sample are being presented.

¹³ To ensure brevity, the results are not presented here. These are available in Raj & Sen (2013).

¹⁴ We tested for the presence of endogeneity by estimating a linear IV model.

¹⁵ As a further robustness test, we also estimate our regressions by split samples by generating quartiles by capital intensity, and find that finance constraints have a greater impact in more capital-intensive industries. As firms in capital-intensive industries are likely to need more external finance, this provides further support to our findings.

Additional information

Funding

This paper forms part of a larger study funded by the International Growth Centre (IGC), London School of Economics. The authors thank the IGC for financial support.