Financial markets, financial intermediaries and investment in India

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Journal of International Development J. Int. Dev. 14, 211–228 (2002) DOI: 10.1002/jid.873

DOES THE SOURCE OF FINANCING MATTER? FINANCIAL MARKETS, FINANCIAL INTERMEDIARIES AND INVESTMENT IN INDIA A. GANESH-KUMAR,1,2 KUNAL SEN2 and RAJENDRA R. VAIDYA1* 1 Indira Gandhi Institute of Development Research, Mumbai, India 2 School of Development Studies, University of East Anglia, UK

Abstract: This paper extends the literature on finance and investment by examining the source of finance constraints on the firm’s investment decisions. Using a panel of 714 Indian manufacturing firms for the period 1993–98, we find that the degree of ‘finance constraint’ differs significantly across external suppliers of funds with investments being most sensitive to borrowings from development finance institutions (DFIs) and considerably less sensitive to funds from capital markets and commercial banks. Capital markets and commercial banks seem to use outward orientation as a signal of the firm’s ability to succeed whereas DFIs do not seem to have adopted such a criterion. Copyright # 2002 John Wiley & Sons, Ltd.

1

INTRODUCTION

There is now a substantial literature, both theoretical and applied, that establishes a positive link between financial development and economic growth. Specifically, the literature highlights the importance of financial markets and institutions in influencing investment and facilitating technological innovation by identifying and funding those firms with the greatest chances of success (King and Levine, 1993). Comparative research on the link between financial systems and economic growth finds that industries and firms located in economies with well-developed financial intermediaries and stock markets have grown faster than those located in economies with weak financial systems (Atje and Jovanovich, 1993; Demirguc-Kunt and Maksimovic, 1996; Levine and Zervos, 1996; Rajan and Zingales, 1996). For developing countries, the relationship between the financial system and investment is especially relevant as it has been shown that firms in these countries rely more on external funds for their investment than firms in developed

*Correspondence to: R. R. Vaidya, Indira Gandhi Institute of Development Research, Mumbai, India. E-mail: [email protected]

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countries (Singh and Hamid, 1992). If particular markets and institutions in the financial sector do not play their part in allocating investible funds to the firms with the greatest potential for growth, this may act as a serious constraint on economic growth. From a microeconomic perspective, market imperfections in the financial sector arise fundamentally due to information asymmetries between corporate insiders and investors resulting in conflict of interests. This conflict of interests can prevent/make it more expensive for firms to raise all the resources that they need to finance their investment projects; i.e., they are finance constrained. To overcome the problems of information asymmetries, transaction costs have to be incurred. A well functioning financial system (which includes financial markets, intermediaries and instruments) minimizes these transaction costs and enables firms to be as close as possible to their desired/optimal capital stock. Historically, different countries have evolved different financial systems in their attempts to overcome this fundamental problem. The Anglo-Saxon system is one in which capital markets play a dominant role while in the German-Japanese system, commercial banks play a vital role. There has been considerable debate in recent years on what should be the ‘optimal’ financial structure for developing countries. Mayer (1990) and Singh (1993) have argued that, to the extent developing countries have a choice, they should attempt to foster bank-based financial systems than to establish and encourage stock markets. Within bank-based systems, several authors have advocated the creation and development of development finance institutions (World Bank, 1993; Bhatt, 1995). This position is based on the observation that scarcity of long-term finance is a key impediment to greater investment and growth in developing countries (Caprio and Demirguc-Kunt, 1998). Furthermore, the experiences of Japan and Korea with specialized financial institutions suggest that these institutions furthered the growth of the financial sector by establishing procedures for project financing and monitoring that commercial banks then copied (World Bank, 1993, p. 350). The question that arises in this context is which markets/institutions impose the least finance constraints on firms? Several studies have explored the empirical implications of the presence of agency costs and informational asymmetries in financial markets for developing countries (Athey and Laumas, 1994; Harris et al., 1994; Jaramillo et al., 1996; Hermes and Lensink, 1998; Eastwood and Kohli, 1999; Athey and Reeser, 2000; Ganesh-Kumar et al., 2001). These studies confine themselves to testing for the presence of finance constraints on the investment decisions of certain type of firms, and do not investigate the source of the finance constraint. This is a serious limitation in two respects. Firstly, given the nature of financial policies in developing countries with a very strong intervention by the state in almost every aspect of the financial sector and the firm’s investment and output decisions, the relationship between the lender and a particular type of firm may differ from lender to lender. Thus, the finding that some firms do not face finance constraints in their investment decisions on the aggregate may mask a great deal of variation in these firms’ financing patterns, and it would be quite possible that these firms may face finance constraints from a key set of financial institutions or markets, but not from others. Secondly, following from the previous point, it could be argued that it is not as useful to know that finance constraints exist on the investment decisions of some firms as it is to know which markets or institutions are the cause of the constraint. Unlike most developed countries, financial markets and institutions for a particular developing country may function under quite disparate regulatory regimes and institutional constraints, and thus, some markets or institutions may work better than others. The role of public policy in this Copyright # 2002 John Wiley & Sons, Ltd.

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case is to identify why these constraints exist and to find ways to make these market or institutions work better. This paper extends the literature on finance and investment by asking the question: does the source of financing matter in the firm’s investment decisions? For our empirical analysis, we use a sample of 714 Indian corporate firms in the manufacturing sector over the period 1993 to 1998, disaggregating the source of external funds by the main providers of funds in India—capital markets, commercial banks and non-bank financial institutions. India provides a relevant case study as a transitional economy that has undergone significant economic reform after 1991, with significant liberalization of the financial sector, where banks and other financial institutions have been given considerable freedom in their lending decisions and major financial markets deregulated. India is also probably unique among low-income developing countries in having a relatively developed financial sector, with a wide range of financial markets and institutions. The common methodology used in the studies cited earlier to test for finance constraints on the firm’s investment decisions is to split the sample of firms into those that are likely to face finance constraints and those that are not using an exogenous attribute of the firm such as firm size. Recently, Ganesh-Kumar et al., 2001) have argued that in developing country context, the manner in which finance constraints manifest themselves would depend on the institutional context of those countries. In the Indian context, they proposed ‘outward orientation’ as measured by the export to sales ratio as a more relevant criteria for distinguishing firms that may be finance-constrained from those that may not be finance constrained. In this paper, we adopt a similar approach. The rest of the paper is organized in five sections. The next section discusses the data used in the empirical analysis. Section 3 highlights the key features of the financial intermediation process in India, with particular reference to the post-reform period. Section 4 presents the framework that is commonly used in testing for finance constraints on the firm’s investment decisions and discusses how we propose to extend this framework to test for differences in finance constraints across different providers of external funds. Section 5 reports the empirical analysis and Section 6 concludes.

2

DATA

For our analysis of private corporate firms we use the firm level database called PROWESS provided by Centre for Monitoring Indian Economy (CMIE), Mumbai. This is a database containing time series information on financial performance (income—expenditure statement, balance sheet, and other details from the annual reports) of firms which are listed on various stock exchanges in the country. Thus, the unorganized/small-scale firms who form about 30 per cent of the manufacturing sector as a whole in India is not covered in this database. The database covers all industries in the manufacturing sector. To the extent that a particular industry is dominated by the unorganized/small-scale firms, it is under-represented in the database. The sample period for analysis considered here is from 1993 to 1998. Though the database provides information on corporate firms from 1989 onwards, we choose to confine our analysis to the period 1993 to 1998. The coverage in the database in terms of the number of firms has been increasing over the years as a result of which a balanced panel beginning from 1989 has too few firms. By confining ourselves to the post-1993 period, we have expanded dramatically on the cross-section across firms but have ended up Copyright # 2002 John Wiley & Sons, Ltd.

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losing four years data. Only those firms for which data are available for all the years of our sample period are considered for the analysis here. Only those firms satisfying the following criteria were included in this balanced panel. (i) The firm is a private corporate firm. Thus, public sector firms are excluded. Investments by public sector enterprises are directly controlled by the Ministry of Industry and arguably such decisions cannot be analyzed in the framework of this study. (ii) The net worth of the firm is positive for at least five years out of the six years, so that firms undergoing restructuring and/or bankruptcy are kept out of the analysis. (iii) Manufacturing sales contribute at least 75 per cent of the total sales of the firm for at least two-thirds of the sample period. That is, we exclude firms whose primary activity is not manufacturing. We have a balanced panel of 714 firms from 21 manufacturing industries satisfying the above criteria. These firms were categorized as ‘domestic firms’ and ‘exporting firms’ depending on whether they have had a consistent history of exports and/or must have earned a sizeable portion of its revenues from exports in a few years. The focus here is on firms with a demonstrated ability to service international markets, and not necessarily those with exports as the main activity. Accordingly, if the exports to sales ratio of a firm exceeds 25 per cent for at least two years in the sample period and/or is consistently above 1 per cent for at least five out of six years, then the firm is considered to be an ‘exporting firm’; ‘domestic firm’ otherwise.1 Out of the total 714 firms, 380 were exporters and 334 were domestic firms. Table 1 reports the number of firms in our balanced panel by industry and by type (domestic/exporting firms).2 3 FINANCIAL MARKETS AND FINANCIAL INTERMEDIARIES IN INDIA Firms in India obtain their funds from three main sources—commercial banks, non-bank financial institutions (NBFIs) and the capital market. Two important features of financial markets and financial intermediaries in India are; (i) credit markets are highly segmented with commercial banks being the dominant players in the short-term credit market (i.e., credit for less than one year, mainly used to finance inventories), and NBFIs are the dominant players in the long-term credit market (mainly used to finance investments in plant and machinery); and (ii) Stock markets in India are relatively well developed when compared with other developing countries. 3.1

Commercial Banks

In the two decades since independence, banks in India operated in a relatively liberal environment. The nationalization of 14 commercial banks in 1969 was a turning point in 1 We have also experimented with somewhat more stringent cut offs. For example, we tried 5 per cent exports for all years and/or 25 per cent for half the sample period, which resulted in marginal changes in the composition of exporting and domestic firms and more importantly no significant change in the empirical results. 2 Note that in the Indian case, the exporter/domestic distinction between firms is by no means the same as the small/large distinction. For further details, see Ganesh-Kumar et al., 2001.

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Does the Source of Financing Matter? Table 1.

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Number of firms in sample classified by categories

Industry name 1. Readymade garments 2. Cotton cloth 3. Electrical machinery 4. Industrial chemicals 5. Diamonds and jewelry 6. Drugs and pharmaceuticals 7. Ferrous metals 8. Rubber and rubber products 9. Auto ancillaries 10. Cement 11. Bicycles and two wheelers 12. Leather and leather products 13. Paints and varnishes 14. Sugar 15. Vegetable oils and fats 16. Cotton blended textiles 17. Dyes and pigments 18. Other food products 19. Synthetic textiles 20. Tea 21. Tobacco products Total

All firms 5 29 72 58 8 62 102 20 64 23 9 3 9 22 24 73 40 32 33 23 3 714

Domestic firms 1 9 42 30 0 15 60 10 25 15 1 0 7 20 15 23 11 20 17 13 0 334

Exporting firms 4 20 30 28 8 47 42 10 39 8 8 3 2 2 9 50 29 12 16 10 3 380

the evolution of banking sector policies in India. The Reserve Bank of India (RBI) now began to play a more direct and active role with banking policies re-oriented to act ’as an active instrument of growth’ (RBI, 1983, p. 7) and to meet social objectives such as the reduction in inequalities of income and the concentration of economic power. As a consequence, policies of financial repression—interest rate controls, directed credit programmes, etc.—increased in magnitude during this period. The social control of banking and the push by the government for banks to open branches in rural areas led to significant growth in the commercial banking system both in geographical coverage and amount of resources mobilized, with a sevenfold increase in the number of bank branches and a trebling of the ratio of bank deposits to national income from 15.3 per cent in 1969 to 51.8 per cent in 1994 (Sen and Vaidya, 1997). However, there was increasing recourse to the banking sector by the government to finance its escalating deficits in the 1980s. This was done by the means of mandatory requirements for banks to invest in government securities and cash reserve ratio requirements, both of which increased steadily in the 1980s. At the same time, there were severe restrictions placed on commercial banks by the government regarding both the pricing and allocation of credit and mandatory lending requirements to the ’priority sectors’ (such as small-scale industry, exports, and agriculture). In 1991, as a part of the economic reform package, there was considerable relaxation on the entry of new private banks and existing public sector banks were allowed to issue fresh capital to the public through the capital market. However, the ownership of the dominant commercial banks in the Indian financial sector remained in government hands. Mandatory requirements to invest in government securities and hold cash were scaled down drastically. This increased the ability of banks to lend, but there was very little change in Copyright # 2002 John Wiley & Sons, Ltd.

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the restrictive environment with regard to the deployment of credit; i.e., there was no reduction in the priority sector lending requirements. With respect to regulations on the pricing of credit, most of the interest rate controls were lifted by 1994 in a gradual manner. The most significant change in the banking environment from the viewpoint of the private corporate sector was the interest rate deregulation. Banks were now allowed to charge differential interest rates for firms based on their risk perceptions, which was not the case prior to the deregulation. In the restrictive environment before 1991, credit rationing occurred as an outcome of the credit policy of the government. Banks faced fixed targets for lending to particular sets of borrowers irrespective of their risk-return characteristics. Indeed, official documents of the government3 itself recognize that there was evidence of growing political and administrative intervention in the credit decision making process. In this milieu, some firms would have faced a situation of being denied credit arbitrarily. Following the reforms, lending decisions now rest with the banks themselves and political and administrative interventions have dramatically reduced. This coupled with the interest rate deregulation implied that credit rationing was now primarily an outcome of information asymmetries (Stiglitz and Weiss, 1981). 3.2

Non-bank Financial Institutions

Non-bank financial institutions in India can be classified into three groups, namely, the insurance sector, mutual funds and development finance institutions (also know as term lending institutions in India). The insurance firms and the mutual funds provide funds to firms primarily through the capital market by subscribing to new issues of shares, bonds, debentures and fixed deposits. They are also the most dominant players on the stock market. The insurance sector is as yet completely government owned following its nationalization in 1956. Major reforms in the insurance sector such as allowing the entry of domestic and foreign private insurance companies, have been initiated only in 2000. The mutual funds sector is still dominated by the Unit Trust of India (UTI) (established in 1964) which is a government owned mutual fund. Financial liberalization of this sector has proceeded via a removal of legal barriers to entry and a strengthening of regulations aimed at ensuring transparency to investors. This sector has since seen a large number of new private entrants. The development finance institutions (DFIs) have traditionally been the most important source of long-term borrowings for private corporate firms. The two largest DFIs are (i) the Industrial Development Bank of India (IDBI) which was set up by the RBI in collaboration with other financial institutions and (ii) the Industrial Credit and Investment Corporation of India (ICICI). Prior to the reforms, the government controlled the operations of the DFIs with regard to both the sources and uses of their funds. The government provided subsidized credit to these DFIs. These institutions were not allowed to choose the firms (either new or established ones) to whom they could lend. They were instead ‘directed’ to lend at a fixed rate of interest to those firms that had acquired a license either to create new capacity in an industry or to expand its existing capacity. These licenses were issued by the government in accordance with its plan priorities. The plans had both industry-specific real capacity targets and a financial plan to ensure the realization of these targets. In such a scenario, where DFI lending was based on licensing policies and at an interest rate that 3

See Reserve Bank of India (1985), Chakravarty committee report.

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was invariant across firms with projects of varying risk-return profiles, these DFIs had very limited screening role to perform. Financial liberalization has brought about three important changes to the operations of DFIs. Firstly, both IDBI and ICICI have seen a dramatic reduction in their access to subsidized funds from the government. Consequently, these institutions have increasingly raised funds through the capital market by issuing new shares, bonds, debentures and fixed deposits. Secondly, interest rate deregulation in this sector took place as early as August 1991 when the government permitted all DFIs to charge interest rates in accordance with the perceived risks inherent in the projects funded subject to a minimum lending rate. Finally, with the abolition of industrial licensing and the re-orientation of the economy away from planning industry specific capacity targets to market driven allocation of resources, long-term credit provided by the DFIs is no more ‘directed’ by the government. In this scenario, the DFIs are key financial intermediaries who would channelize investments based on market signals and as a result of their screening function. Thus, here too the Stiglitz–Weiss type credit rationing can occur in the post-liberalization period.

3.3

Capital Markets

Unlike other developing countries, India has had fairly well developed stock markets and their role in the overall financial system has dramatically increased since the eighties. Prior to 1992, the primary issues market was very closely regulated by the government in almost every aspect. The government put in place various regulations under the Capital Issues (Controls) Act, 1947, with regard to the pricing, quantum and timing of new issues and also forced certain industry-specific debt/equity ratio norms on firms, leaving little leeway for firms to choose their capital structure. Such severe restrictions discouraged corporations from using new issues to raise funds. More importantly, such administratively determined price of new issues completely lacked any information content for investors. In 1992 there was a substantial deregulation of the stock market especially with respect to the new issues market. Price controls on the issue of new shares were lifted and new guidelines that were less restrictive than those in the pre-1991 period were put in place. Also, in September 1992 the Government of India allowed unrestricted entry in terms of volumes of investments in both primary and secondary markets to reputed Foreign Institutional Investors such as pension funds, mutual funds, investment trusts and asset management companies. Following these reforms, the three years 1992 to 1995 saw a boom in the primary market as large number of firms raised new equity, bonds and debentures through the stock market after which there was a distinct lull. In this changed and market signals driven environment, problems of asymmetric information would need to be overcome. As pointed out by Myers and Majluf (1984) investors (who are unable to distinguish the quality of new issues) would demand a premium to purchase the shares of relatively good firms to compensate the potential losses that they face by purchasing the shares of bad firms.

3.4

Patterns and Trends in the Sources of Funds for Indian Firms

The reforms outlined above have had a profound impact on the relative importance of the various sources of funds tapped by firms to finance their investments. Financial sector Copyright # 2002 John Wiley & Sons, Ltd.

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reforms made it possible for firms to respond to changes in the cost of funds from various sources. This is reflected in the sources and uses of funds statements of the domestic and exporting firms presented in Table 2. The following points stand out clearly: firstly, it is interesting to note that the sources and uses of funds for domestic and exporting firms are more or less similar. Both groups of firms invest a similar proportion of total funds raised in gross fixed assets. Secondly, with respect to the sources of funds, both groups of firms depend primarily on external sources, which is a distinctive feature of these firms, especially when compared with firms in developed countries (Mayer 1990; Singh and Hamid, 1992). Thirdly, the quantum of funds raised by exporting firms is far larger than that by domestic firms, with the total sources/uses of funds per firm in the case of exporters being more than double than that in the case of domestic firms. Finally, within external sources, capital markets seem to play a much larger role for exporting firms, especially during 1993, 1994 and 1995. On the other hand, financial institutions seem to play a larger role for financing investments of domestic firms as compared to exporting firms. We explore in the following sections whether this heterogeneity in financing patterns within external sources have any implications for finance constraints across financial markets/institutions for the two groups of firms.

4

METHODOLOGY

Recent developments in the theories of asymmetric information and contract enforcement as applied to financial markets postulate that the availability of external finance has a strong positive relationship with investment expenditures of firms, independent of other determinants of the latter. According to this literature, external finance, if available at all, may be more costly than internal finance because of transaction costs, contract enforcement (agency cost) problems and asymmetric information.4 The argument rests on the distinction between ‘insiders’ (the firm’s owners/managers) who have full information about a particular firm’s investment prospects, and ‘outsiders’ who may correctly perceive the prospects for a population of firms but cannot distinguish the quality of individual firms. In particular, there may exist certain firms that face high information costs in financial markets, and there would be others who face negligible information costs. An important empirical implication of this literature is that that the availability of finance may constrain the investment decisions of ‘high information-cost’ firms, while ‘lowinformation-cost’ firms are less likely to be constrained by the availability of finance in their investment decisions. The standard method of testing for the finance constraint hypothesis is to estimate an investment function and we discuss issues relating to the specification of the investment function next.

4.1

Investment Function Specification

The standard procedure in the empirical literature on investment functions is to relate investment in fixed assets to a sales accelerator and internal funds/cash flow 4 See for example, Jensen and Meckling (1976); Stiglitz and Weiss (1981); Myers and Majluf (1984); Bernanke and Gertler (1990). Two useful surveys of this literature are Gertler (1988) and Hubbard (1998).

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Copyright # 2002 John Wiley & Sons, Ltd. 64.40 2.14 33.46 4327 12.96 334

Uses of funds Gross fixed assets Financial investments Current assets including inventories

Total sources/uses of funds (Rs. Crores) Total sources/uses of funds per firm (Rs. Crores)

No. of companies in panel

334

6280 18.80

55.18 5.24 39.58

27.57 19.62 7.95 72.43 30.45 30.11 0.35 41.98 3.04 11.66 26.70

1994

334

8549 25.60

44.16 12.05 43.79

25.88 16.56 9.31 74.12 36.00 27.38 8.62 38.12 18.24 7.90 12.06

1995

334

8650 25.90

57.87 4.96 37.18

34.57 21.75 12.82 65.43 16.36 13.64 2.72 49.07 17.99 9.58 21.48

1996

334

7030 21.05

73.90 3.18 22.92

33.46 10.93 22.53 66.54 16.78 9.67 7.11 49.76 13.91 17.11 18.75

1997

334

7872 23.57

67.38 1.53 31.09

29.07 8.17 20.90 70.92 19.09 11.41 7.51 51.84 20.33 15.94 15.63

1998

380

11854 31.19

58.08 1.43 40.62

26.55 11.85 14.69 73.45 36.49 24.29 12.20 36.96 12.86 16.95 7.16

1993

380

17518 46.10

52.80 16.14 31.05

24.08 15.54 8.54 75.92 43.20 26.52 16.69 32.72 2.36 6.10 24.38

1994

380

26945 70.91

47.40 12.28 40.32

25.71 17.24 8.46 74.29 29.29 28.20 1.08 45.00 17.60 6.80 20.52

1995

380

22828 60.07

64.93 0.64 35.71

33.28 20.45 12.83 66.72 16.10 13.91 2.19 50.63 22.81 8.88 18.84

1996

Exporting firms

380

17861 47.00

75.24 4.89 19.87

36.64 15.68 20.96 63.36 22.74 8.00 14.75 40.62 8.95 14.62 17.29

1997

380

18837 49.57

66.35 8.45 25.53

31.76 9.26 22.49 68.57 14.68 3.47 11.23 53.89 19.88 10.39 23.72

1998

Notes: Individual items of sources and uses of funds are reported as percentages of the total over all firms. Source: Firm level data are from PROWESS database, provided by the Centre for Monitoring Indian Economy (CMIE), Mumbai. The aggregates reported are based on authors’ calculations.

25.99 9.58 16.42 74.01 37.55 17.77 19.77 36.46 9.47 17.07 9.81

Sources of funds Internal sources Retained profits Depreciation External sources Capital markets Fresh capital (incl. Share premium) Fixed deposits/debentures/bonds Borrowings Bank borrowings Financial institutions Other borrowings

1993

Domestic firms

Table 2. Sources and uses of funds–domestic and exporting firms

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(Devereux and Schiantarelli, 1990; Harris et al., 1994). A typical empirical specification is as follows: Ii;t Si;t IFi;t ¼1 þ 2 þ i;t Ki;t1 Ki;t1 Ki;t1

(1)

i;t1 ¼ "i;t þ i þ t

and;

where, I is investment in fixed assets, K is capital stock, S is sales, IF is internal funds,  is error term,  is the time invariant firm specific effect,  is a common time effect, " is the idiosyncratic component of the error term, i is firm subscript and t is time subscript. The finding of a positive and significant coefficient for IF is taken as evidence supporting the presence of finance constraints on investment. In order to test for the excess sensitivity of investments to IF, the empirical literature groups firms into ‘high information cost’ and ‘low information cost’ categories based on some aspect of the firm’s characteristics. A higher value for the estimated coefficient 2 for the ‘high information cost’ group points to the excess sensitivity of this group to financing constraints. Among the firm’s characteristics, perhaps the most widely used is the ‘size’ of the firm, with the hypothesis that smaller firms are more likely to face finance constraints than the larger firms.

4.2

Testing for the Source of the Finance Constraint

The finding that the coefficient 2 is significant, positive and larger for ‘high-information cost’ firms than for ‘low-information cost’ firms simply establishes that finance constraints exist on investment for these firms. In order to determine the source of the finance constraint, one needs to begin by looking for the sensitivity of investments to the availability of external funds. Indeed, the problems of informational asymmetries inherent in capital markets really concerns external providers of funds whose concern is to develop contracts that align incentives and ensure repayment. For a group of firms which have low information costs the contracts which attempt to align incentives and ensure repayment will not cause the actual capital stock to fall far short of the desired capital stock because the wedge between costs of external and internal sources would not be very large. On the other hand, firms with high information costs will fall far short of their desired capital stocks indicating that these firms are finance constrained. In such a scenario, investments of the group of firms with low information costs will be much less sensitive to availability of external sources than the group of firms with high information costs. The empirical literature on finance constraints in the context of advanced countries emphasises the role of internal sources possibly because of the stylized fact that internal sources are the most important (the contribution of external sources being negligible in many cases) source of funds that is used to finance investment (Mayer, 1990). In an underdeveloped country context in general and for India in particular it is in fact external sources that are the most important source of funds (Singh and Hamid, 1992; Sen and Vaidya, 1997). Indeed this is the case with our sample of firms, as seen earlier. A possible reason for this could be that due to the inherent lumpiness of investments in plant and machinery (which are likely to be accentuated by the fact that firms in underdeveloped countries have a far smaller capital stock to begin with than firms in Copyright # 2002 John Wiley & Sons, Ltd.

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developed countries) firms find it impossible to finance such investments using internal sources. In such a situation, even though imperfections in capital markets would make external funds more expensive than internal funds, our focus should be on external funds and not on internal funds. It should be noted here that in many underdeveloped countries (including India) DFIs were set up precisely because it was perceived that lumpy investments required to spur growth could not be expected to be funded through internal sources. With this in mind, we replace IF with external funds (EF) in the investment function specification as follows: Ii;t Si;t EFi;t ¼ 01 þ 02 þ i;t : Ki;t1 Ki;t1 Ki;t1

ð2Þ

The replacement of IF with EF in the above equation can also be justified by invoking the flow of funds identity: I þ OUF ¼ IF þ EF ¼ Total Sources=Uses of Funds

ð3Þ

where OUF is other uses of funds. Thus, if in equation (2), the coefficient 02 is greater for high-information cost firms than for low-information cost firms, it can be taken as equivalent evidence in favour of the excess sensitivity of investments to the availability of external funds across different firm types. The advantage of using equation (2) to test for finance constraints is that it is possible to decompose EF into its constituents, and to identify the source(s) of external funds that is responsible for the finance constraint. For example in the Indian context, we could decompose EF into five components, namely, fresh capital including share premium (FC), fixed deposits, debentures and bonds (FDB), bank borrowings (BB), borrowings from development finance institutions (FIB) and other borrowings (OB). As we have observed in Table 2, these five items are all important in the external sources of funds for both domestic and exporting firms. Of these five components, FC and FDB are routed through capital markets. Other borrowings include inter-corporate loans and trade credit. Accordingly, equation (2) can be written as, Ii;t Si;t FCi;t FDBi;t BBi;t FIBi;t OBi;t ¼ 01 þ 02 þ 03 þ 04 þ 05 þ 06 þ i;t : Ki;t1 Ki;t1 Ki;t1 Ki;t1 Ki;t1 Ki;t1 Ki;t1

ð4Þ

In the next section, we report the estimates of equations (2) and (4) for the full sample and also for the two sub-samples in order to identify the source of finance constraints.

5 5.1

RESULTS Summary Statistics

In Table 3 we report the sample means, standard deviation, maximum and minimum values of the explanatory variables. All the variables are defined as ratios to the stock of Copyright # 2002 John Wiley & Sons, Ltd.

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A. Ganesh-Kumar et al. Table 3. Summary statistics of explanatory variables—all firms

Variables

Mean

Standard deviation

Maximum

Minimum

Sales Total external sources Fresh capital including share premium Fixed deposits, debentures and bonds Bank borrowings Borrowings from financial institutions Other borrowings

0.2624 0.2185 0.0370 0.0115 0.0553 0.0141 0.1007

1.2529 0.9010 0.1873 0.1021 0.2865 0.1238 0.8826

12.8673 19.7250 4.7043 2.1530 5.0311 1.7701 25.4000

23.0811 16.5897 1.5998 0.9617 5.6750 1.4191 17.5641

Notes: All variables are ratios to stock of capital.

capital.5 For all the external sources, the minimum values observed in the sample are negative indicating that some firms extinguished their debt obligations without raising any new debt from a particular source and also that some firms reduced their capital base. Table 4 presents the correlation matrix for the explanatory variables. It is seen that these correlations are by and large low and multicollinearity is unlikely to be an issue in our estimation. Table 4.

Sales Fresh capital including share premium Fixed deposits, debentures and bonds Bank borrowings Borrowings from financial institutions Other borrowings

Correlation amongst explanatory variables—all firms Sales

Fresh capital including share premium

Fixed deposits, debentures and bonds

Bank borrowings

Borrowings from financial institutions

1.000 0.135

0.135 1.000

0.018 0.134

0.242 0.274

0.029 0.023

0.278 0.022

0.018

0.134

1.000

0.032

0.039

0.013

0.242 0.029

0.274 0.023

0.032 0.039

1.000 0.020

0.020 1.000

0.315 0.019

0.278

0.022

0.013

0.315

0.019

1.000

Other borrowings

Notes: All variables are in first difference, and are all ratios to stock of capital.

5 We estimate the beginning of the period capital stock from book value using a method similar to Athey and Laumas (1994). The following assumptions are made:

(i) All the firm’s capital has an identical useful life Li. (ii) The firm’s initial end-of-period capital stock equals the book value of net fixed assets in current Rupees. (iii) Firms use the straight-line method of depreciation and actual depreciation is exponential with depreciation 1/Li. (iv) All investments are made at the beginning of the year and all depreciation is subtracted at the end of the year. We estimate the beginning-of-the-period capital stock by  Ki;t ¼

Pt Pt1



   1  Ii;t1 þ Ki;t1  1  Li

where, P is the wholesale price index of capital goods. Copyright # 2002 John Wiley & Sons, Ltd.

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223

Regression Results

Two sets of issues have to be handled while estimating equations (2) and (4). The first relates to the firm specific and time effects in the model and the second relates to the possible endogeneity of the regressors. Firm specific effects need to be included to account for unobserved time-invariant links between investment and the explanatory variables. Fixed time effects would have to be included to control for aggregate business cycle influences. With regard to the firm specific effects, we estimate the model in the first difference form in order to conserve degrees of freedom.6 To capture the time effects we use time dummies for each year in the sample. The endogeneity problem refers to the possibility that some of the external sources of funds may be closely related to the current level of operations of the firm represented by sales (amongst other variables). Here we need to note that three of the external sources, namely, FC, FDB and FIB, are long-term in nature, are infrequently used and are thus unlikely to be related to the current sales. Moreover, the frequency and extent of use of these three sources are likely to be influenced by factors completely external to the firm such as the conditions on the stock market and the level of interest rates prevailing in the economy. In Table 5, we report the frequency with which each of the external sources of funds was used by the firms in our sample. Well over 75 per cent of the firms have used these three sources for less than half the number of years in the sample. Thus, these three sources are unlikely to suffer from the endogeneity problem. On the other hand, BB and OB are primarily short-term in nature. In the Indian context, bank lending is predominantly short-term in nature intended to finance inventories, wages, salaries and other current expenditure. Banks also give long-term loans. Other borrowings usually consist of short-term trade credit that the firm receives against its purchase of material inputs. Both these sources are thus likely to be influenced by current sales. Table 5 suggests that these two sources were indeed used significantly more frequently by the firms. The endogeneity of all these variables was investigated econometrically using the Durbin–Wu–Hausman tests (Davidson and MacKinnon, 1993). The test results7 confirmed our above expectations regarding the exogeneity of FC, FDB and FIB and the endogeneity of BB and OB. This test was conducted for the total external funds also and it showed that Table 5.

Frequency of use of different external sources of funds—all firms

External source

Fresh capital including share premium Fixed deposits, debentures and bonds Bank borrowings Borrowings from financial institutions Other borrowings

Number of years 0

1

2

3

4

5

6

114 258 5 138 1

135 98 28 99 7

150 99 62 138 39

145 96 148 138 165

101 90 225 107 246

57 48 176 72 204

12 25 70 22 52

Notes: The numbers in the table refer to the number of firms that raised funds from a particular external source for a given number of years.

6

Note that the sales accelerator term is thus twice differenced. Not reported here, but would be made available upon request.

7

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224

A. Ganesh-Kumar et al. Table 6. Estimation results—equation (2) Variable

Domestic firms

Exporting firms

Constant

0.0389 (2.075) 0.0172 (2.574) 0.1127 (8.577) 0.0042 (0.159) 0.0481 (1.818) 0.0737 94.4 1002

0.0285 (1.319) 0.04063 (6.240) 0.0594 (8.071) 0.0195 (0.634) 0.0244 (0.796) 0.0697 100.5 1140

Sales External sources Year 1997 dummy Year 1998 dummy Adjusted R2 Wald test No. of observations

Notes: All variables are ratios to stock of capital. The estimation uses three years data only. T-values are reported in brackets. Wald test is for the joint significance of all the parameters. The Wald test for the significance of the time dummies consistently turned out to be insignificant at the 5 per cent level and hence not reported here.

EF does not suffer from endogeneity problem. Accordingly, we estimate equation (2) using the ordinary least squares (OLS) method only. Equation (4), on the other hand, was estimated using both OLS and two-stage least squares (2SLS). The instruments for BB and OB used in the 2SLS procedure were their lagged values. Additionally, lagged values of S=K (the accelerator) was used as its instrument. Equations (2) and (4) were estimated separately for each categories of firm; i.e., for all firms, domestic firms, and exporting firms. Tables 6 and 7 report the estimation results for equations (2) and (4), respectively. The results presented in Table 6 confirm the finding reported by Ganesh-Kumar et al. (2001)–that export-oriented firms face a far lesser degree of finance constraints than domestic firms (the coefficient on EF in the case of exporting firms is approximately half that of domestic firms).8 We also find that the year dummy for 1998 is significant in the case of domestic firms. As expected, the sales accelerator term (Sales)—highly significant for both domestic and exporting firms. The results in Table 7 clearly indicate that the source of financing matters, and that conventional tests for finance constraints mask the significant variation that is observed in the nature of finance constraint across different providers of funds. The size of the coefficient on the different sources of external funds suggest that investments are most sensitive to FI borrowings. This sensitivity is remarkably lower with regard to the other external sources. This is true across the full and the two sub-samples. The negative and significant coefficient on FDB for the exporting firms reflects the fact that many of these firms in fact extinguished this category of debt during our sample period. While exporting firms face a lower degree of finance constraints than domestic firms from the capital market and commercial banks, they face a higher degree of finance 8 In fact, we had estimated both Equations 2 and 4 with dummy variables for exporting firms, interacted with all the explanatory variables. In both cases, all these dummy interaction terms were significant confirming the need to distinguish between domestic and exporting firms in the regression analysis. These dummy variable regressions are not reported here for brevity.

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Table 7. Estimation results— equation (4) Variable

Constant Sales Fresh capital including share premium Fixed deposits, debentures and bonds Bank borrowings Borrowings from financial institutions Other borrowings Year 1997 dummy Year 1998 dummy Adjusted R2 Wald test No. of observations

Domestic firms OLS

2SLS

 0.0168 (  0.914)  0.0164 (  2.543) 0.1189 (3.922) 0.2646 (3.937) 0.1783 (4.879) 0.5758 (9.421) 0.0667 (4.608)  0.0213 (  0.833) 0.0209 (0.811) 0.1371 178.5 1002

 0.0239 (  1.262)  0.0408 (  3.626) 0.1196 (3.866) 0.2530 (3.727) 0.1241 (1.816) 0.5880 (9.535) 0.0500 (2.442)  0.0262 (  1.014) 0.0246 (0.946) 0.1194 153.2 1002

Exporting firms OLS  0.0323 (  1.573) 0.0335 (4.912) 0.0448 (1.651)  0.1918 (  2.862) 0.1187 (5.137) 0.9078 (13.829) 0.0531 (7.551) 0.0138 (0.478) 0.0139 (0.485) 0.2069 318.3 1140

2SLS  0.0331 (  1.550) 0.0016 (0.068) 0.0458 (1.023)  0.1808 (  2.296) 0.0623 (1.220) 0.9192 (13.580) 0.0207 (1.322)  0.0099 (  0.306) 0.0164 (0.554) 0.1782 230.6 1140

Notes: All variables are ratios to stock of capital. The estimation uses three years data only. One year’s data are lost in constructing Sales; another year’s data are lost in first-differencing; and a third year’s data are lost in using lagged values of Sales, Bank borrowings and Other borrowings as instruments. T-values are reported in brackets. Wald test is for the joint significance of all the parameters. The Wald test for the significance of the time dummies consistently turned out to be insignificant at the 5 per cent level and hence not reported here.

constraints from financial institutions—the coefficient on FIB in the case of exporting firms is 0.9192 as compared with a coefficient of 0.5880 in the case of domestic firms (for 2SLS estimates).9 While all other providers of funds seem to use outward-orientation as a signal of the firm’s ability to succeed in the increasingly competitive environment brought about by the economic reforms, the development finance institutions do not seem to have adopted such a criterion. Therefore, among the key players in India’s financial sector, the DFIs which provide long-term finance to Indian corporate firms seem to be a ‘weak link’ in allocating resources to arguably the more dynamic firms in the Indian manufacturing sector. At this point we need to take note of the potential influence of priority sector lending requirements10 on the coefficient of BB for exporting firms. There are plausible reasons to believe that this coefficient is not significantly influenced by such lending requirements. The relative size of the coefficients of FC, BB and OB are similar for exporters and 9 A referee has pointed out an alternative interpretation of these results as reflecting a preference on the part of both domestic and exporting firms for DFI funds. Such an interpretation, however, is not plausible because DFI’s have not been the most important source of external funds (see Table 2) nor are they the most commonly tapped external source (see Table 5). 10 The priority sector lending requirements stipulate that 40 percent of commercial banks total credit should be advanced to priority sectors. The identity of which sectors were classified as priority sectors has undergone some change over the years. In the context of our sample period the sectors so classified were agriculture and allied activities, small scale industry and export credit.

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domestic firms indicating that the influence of priority sector lending requirements, if any, is rather small. Clearly if the priority sector lending requirements were driving the results it would be highly unlikely that the overall pattern of results would be similar for both the groups of firms. Moreover, our definition of export oriented firms is rather liberal and in many cases exports would not form a very significant part of sales. In such a situation, the influence of export credit on the coefficient of BB would be substantially muted. What explains the weakness in the lending criteria of DFIs as compared with the capital markets and commercial banks? A complete answer to this question can only be provided with a detailed examination of the type of projects that DFIs provide funds for and is, thus, outside the scope of the paper. Here, we offer a partial answer based on our reading of the policy history of DFIs, and the changes in the environment faced by these institutions brought about by deregulation. As discussed in Section 3, a large proportion of the commercial banks and all non-bank finance institutions are government owned, either in part or in whole. Thus, public ownership per se cannot explain the difference in the lending behaviour of commercial banks versus DFIs. However, there are two important differences between these two sets of institutions with regard to the nature of the lending undertaken by these institutions in the pre- and post-reform periods. Firstly, DFIs provide long-term finance for investment while commercial banks provide mainly working capital finance. As argued by Bhatt (1995, p. 117), ‘commercial banks are in a position to identify the problems of the enterprise in time, as they are dealing with the enterprise on a day-to-day basis and the performance of the enterprise is reflected in their transactions with the commercial banks’.11 This is not the case with the DFIs, and may explain why their lending behaviour differs from that of commercial banks in the Indian case. Secondly, as we have noted in Section 3, in the pre-reform period the development finance institutions were merely passive conduits of funds, with little active involvement in the screening of firms. With deregulation, the lack of expertise in a core activity for financial intermediaries may have constrained the performance of DFIs in the post-reform period. Specifically, the development finance institutions may prefer to lend to domestic firms which are usually the larger and more established of Indian firms, even though trade reforms enacted since 1991 may increase the likelihood of such firms failing to remain profitable in the future.

6

CONCLUDING REMARKS

This study addresses the role of financial markets and intermediaries in the process of economic growth using India as a case study. Specifically, it examines whether key financial markets and intermediaries have played their part in allocating investible funds to the more dynamic firms in the Indian manufacturing sector (as evidenced by their ability to compete in world markets) following the economic reforms of 1991. The study finds that the degree of the ’finance constraint’ differs significantly across external suppliers of funds. Our results suggest that investments are most sensitive to borrowings from DFIs. This sensitivity is remarkably lower with regard to funds from capital markets and commercial banks. 11 In a different context, Fama (1985) argues that commercial banks have a comparative advantage over other lenders by the virtue of lending short-term. As Fama argues, the advantages of short-term inside debt is that the renewal process triggers periodic evaluation of the firm’s ability to meet ‘low priority fixed payoff claims’, and provides the bank with valuable inside information.

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Capital markets and commercial banks seem to use outward-orientation as a signal of the firm’s ability to succeed in the increasingly competitive environment brought about by the economic reforms whereas DFIs do not seem to have adopted such a criterion. Our results show that capital markets (both equity and debt segments) and commercial banks are found to impose a lesser finance constraint on outward-oriented firms than firms which sell primarily to the domestic market. The DFIs, however, are found to impose a higher finance constraint on outward oriented firms than domestic firms. In the aggregate, outward-oriented firms face a lower degree of finance constraints than domestic firms. Thus, among the key players in India’s financial sector, DFIs which provide long-term finance to Indian corporate firms seem to be a ‘weak link’ in allocating resources to arguably the more dynamic firms in the Indian manufacturing sector. If one were to argue that a crucial indicator of the success of India’s economic reforms would be an increasingly outward-oriented manufacturing sector, then the inability of the specialized financial institutions to support firms that have already began to make inroads into world markets may be considered to be a significant impediment to the success of the reforms. The functioning of development finance institutions in the Indian context seems quite different from those in the high-performing Asian economies, which were crucial to these economies’ growth performance. From a policy perspective, this study suggests that Indian financial reforms have not gone far enough to change the ‘rules of the game’ for the development finance institutions and that significant re-organisation of these institutions is necessary if they are to act as catalysts of financial and industrial development of the Indian economy.

ACKNOWLEDGEMENTS This study is an extension of the work done for a project titled ‘Finance and Changing Trade Patterns in Developing Countries’ funded by the International Development Research Centre (IDRC), Canada. We acknowledge comments received from participants at the International Conference on Development and Business Finance held at the University of Manchester on 5–6 April 2001. We would also like to thank Dr Kaushik Chaudhury and an anonymous referee for helpful comments on an earlier draft. Usual disclaimers apply.

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