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The Macro-Economic Effects of Directed Credit Policies: A Real-Financial CGE Evaluation for India C. W. M. Naastepad ABSTRACT The effectiveness of directed credit programmes as an instrument for economic development is the subject of considerable debate. However, the focus of this debate is almost exclusively on the intra-sectoral effects of directed credit and its adverse effects on financial sector performance, neglecting possible spillover effects on demand, production and investment in the rest of the economy. This article tries to fill this gap by examining the macroeconomic effects of directed credit in India with the help of a novel realfinancial computable general equilibrium (CGE) model. Focusing on credit rather than money, the model goes beyond earlier modelling approaches by (1) incorporating directed credit policy and credit rationing; (2) recognizing the dual role of credit for working capital and investment; and (3) allowing for switches between credit-constrained, capacity-constrained and demandconstrained regimes. The results from short- and medium-term simulation experiments with the model indicate that, when credit market failures result in rationing as in India's agricultural and small-scale industrial sectors, the macro-economic effects of directed credit are likely to be significant and positive. INTRODUCTION The effectiveness of directed credit programmes in stimulating investment, raising growth, and reducing poverty is the subject of considerable debate. This debate became particularly intense after the conventional wisdom Ð that directed credit is inferior to a market-based allocation of resources in achieving growth and redistributive objectives (Odedokun, 1996; World Bank, 1989; Yaron et al., 1998) Ð was challenged by empirical evidence that government-directed credit has substantially contributed to the successful industrialization and growth of Japan, South Korea and Taiwan (Amsden and Euh, 1993; Vittas and Cho, 1996; World Bank, 1993). However, the empirical evidence on the macro-economic effectiveness of directed credit programmes for economies other than the East Asian ones is limited, whereas there exists abundant micro-economic evidence of negative (efficiency) The author is grateful to an anonymous referee for very useful and constructive comments. Development and Change Vol. 32 (2001), 491±520. # Institute of Social Studies 2001. Published by Blackwell Publishers, 108 Cowley Road, Oxford OX4 1JF, UK. 492 C. W. M. Naastepad effects of directed credit policy, particularly on the banking sector's performance. As a result, the policy consensus Ð as exemplified by the financial policy under the IMF and World Bank structural adjustment programmes Ð that the phasing out of directed credit programmes is desirable, has not (yet) changed. The discussion of the effectiveness of directed credit assumes critical importance in the context of India, as its economy and financial sector are undergoing a structural adjustment programme (Khatkate, 1997; Kohli, 1997; Rao, 1994). Starting from the nationalization of the banking sector in 1969, India has had a consistent policy of targeting about 40 per cent of bank credit to certain priority sectors. But close observers (notably, Mujumdar, 1996; Sarkar and Agrawal, 1997) agree that the impact of the directed credit system on India's growth, employment, inflation and income distribution is not so clear and, as a result, a balanced appraisal of, or policy approach on this issue has not so far emerged. This article examines the macro-economic effectiveness of India's directed credit programme, using an expanded version of the computable general equilibrium (CGE) model, developed in Naastepad (1999), that embodies the characteristic elements from both the real and the financial sectors of the Indian economy. Identifying eleven sectors of production as well as the major financial actors, the model's focus is on the importance of credit availability for production, incomes and prices. Distinguishing features of the model are (i) it incorporates directed credit policies and credit rationing; (ii) credit affects investment as well as current production (through working capital loans); and (iii) it allows for endogenous shifts between financial regimes (that is, credit shortage versus excess credit), thus applying key insights from the recent theoretical literature on credit rationing and effective supply failures (Bhaduri, 1992; Blinder, 1987). The article is organized as follows. The following section briefly reviews the theory and empirical literature on directed credit programmes and discusses the Indian experience. The real-financial CGE model used to evaluate the economy-wide growth and distributional effects of a reduction in India's directed credit programme is then described. This is followed by a discussion of the results of the short-run simulation experiments, and an investigation into the medium-run effects of a scaling down of India's directed credit programme. The final section draws out the major (policy) implications from the model analysis. DIRECTED CREDIT: THEORY AND EVIDENCE Programmes of directed credit attempt to intervene in the way that banks allocate credit. In general, the most favoured targets of such policies are the small-scale industrial and the agricultural sectors. The interventions generally involve the administered allocation of credit to priority sectors at The Macro-Economic Effects of Directed Credit Policies 493 concessional interest rates. The theoretical rationale for such interventions is that, without government interference, banks will not fund those activities with high social returns but low private returns or those categories of creditworthy borrowers that are marginalized in credit markets (see Stiglitz, 1994). The Effectiveness of Directed Credit Programmes The effectiveness of directed credit programmes in enhancing long-term growth is not undisputed. One view has it that directed credit policies cause severe distortions in markets (Besley, 1994; Odedokun, 1996; World Bank, 1989), the major distortion being that the ability to borrow at cheap rates encourages less productive investment than would otherwise have been possible. The argument is that Ð assuming symmetric information between lender and borrowers Ð the allocation of credit to priority sectors reduces the credit available to the other sectors, resulting in a displacement of projects with potentially higher returns. Government interventions in financial markets thus constrain the size of the financial system with adverse consequences for investment and economic growth. This argument has provided the basis for the financial liberalization policies recommended by the World Bank (1989), which include the removal of interest rate ceilings and a move towards a market-based allocation of bank credit. However, another view argues that credit rationing is a problem not only in regulated but also in liberalized financial markets. Because of market failures in general and information asymmetries between lender and borrowers in particular, equilibrium credit-rationing is an inherent feature of financial markets (Cho, 1986; Gibson and Tsakalotos, 1994; Stiglitz and Weiss, 1981). Such rationing is bound to occur in situations where banks can distinguish between groups of borrowers (according, for example, to firm size or sector), but cannot distinguish between individual (good and bad) borrowers within a group and also cannot costlessly filter out those borrowers who are especially high risk. Banks cannot use the interest rate as a screening device, because (due to adverse selection) borrowers who are willing to pay high interest rates may be less worried about the prospect of nonrepayment. Stiglitz and Weiss (1981) show that, under these circumstances, a profit maximizing bank will practise credit rationing and be reluctant to raise interest rates in response to an excess demand. This has two implications. 1. High-risk groups may be completely excluded from the market even though their prospective investments offer a higher expected return. Agriculture is such a risky activity: because farmers face common (weather) shocks to their incomes and it is difficult to diversify rural banks' portfolios, the covariance of risks in this category of lending 494 C. W. M. Naastepad pre-empts farmers from accessing credit (Besley, 1994; Binswanger and Deininger, 1997). 2. Under asymmetric information, when borrowers have better information than lenders, investors who put their own wealth at risk can increase the confidence of outside lenders and thereby persuade them to give loans (Calomiris and Himmelberg, 1994). A corollary of this is that good projects may not receive the funding they deserve due to lack of collateral. Banks will discriminate against borrowers, who are too poor to have assets that could be collateralized (such as small-scale industrial firms), or against sectors in which poorly developed property rights make appropriating collateral in the event of default difficult Ð for example, the rural sector of many developing countries (Mushinski, 1999). Liberalized markets are thus unlikely to lead to allocative efficiency within an economy and, moreover, may be particularly bad at promoting longterm growth (Cho, 1986; Gibson and Tsakalatos, 1994). The existence of credit rationing even in liberalized markets points to a potential role for government in allocating credit to ensure that such groups do have access to investment funds. While it is true that there is no guarantee that government intervention in the form of directed credit policies will not be used for political rather than economic purposes (Besley, 1994; Yaron et al., 1998), this does not deny its potential importance. Rather it underscores the need for an analysis of factors which may allow for better government (see Gibson and Tsakalatos, 1994). The empirical evidence emerging from country experiences with directed credit programmes is mixed. Several empirical studies document a positive and statistically significant impact of government-directed credit on sectoral investment (Amsden and Eu, 1993; Calomiris and Himmelberg, 1994; Vittas and Cho, 1996; World Bank, 1993). However, other studies find only negative effects of directed credit policies, particularly on the banking sector's performance and repayment behaviour, or on the banking sector's productivity (Demetriades et al., 1998; Odedokun, 1996; Yaron et al., 1998). However, the available studies are micro-econometric in nature and focus Ð rather narrowly Ð on the intra-sectoral effects of government-directed credit, while there is reason to argue that directed credit programmes must be evaluated from a general equilibrium perspective. Firstly, even if the directed credit programme leads to growth in a particular sector, it may do so by crowding out growth in other sectors. Secondly, while directed credit policies may result in high intra-sectoral inefficiency costs, they could still be beneficial from a societal point of view if they overcome liquidity problems associated with highly imperfect credit markets. High returns to investment could result where they were previously infeasible and the effect on aggregate income and employment could be so large that the benefits exceed the cost of the credit programme to government or society. Therefore, a The Macro-Economic Effects of Directed Credit Policies 495 more complete appraisal demands an investigation into the generalequilibrium effects of these programmes. This is the approach taken in this article. Directed Credit in the Indian Economy In India, directed credit policies have been used for promoting agriculture and small-scale industry following the nationalization of the major commercial banks in 1969 (Kohli, 1997). As is evident from Table 1, there was a massive expansion of priority lending up to 1988 and an appreciable reduction since 1991, when India began its process of structural reforms. The bulk of the priority lending accrues to farmers and small-scale industrialists. The aim of the priority lending scheme for agriculture was to facilitate the introduction of risky new technology to increase agricultural productivity. Agriculture was targeted because it is a risky activity and credit-rationed (see Kochar, 1997; Swaminathan, 1991). Hence, after their nationalization, the major commercial and co-operative banks were directed to expand their rural branch networks and intensify their lending to agriculture. Empirical evidence shows that the increased availability of (directed) credit has raised agricultural investment in India (see Binswanger and Khandker, 1995; Binswanger et al., 1993; Gandhi, 1996). However, India's rural directed credit programme has not been a success in all respects. First, because the agricultural lending rates set by the government are lower than commercial and industrial rates, commercial banks have to cover the cost of their agricultural loan administration from profits arising from other operations and cross-subsidize the agricultural operations (Binswanger and Khandker, 1995; Rao, 1994). Second, relatively high levels of overdue and bad loans in agriculture have built up a liability that must eventually be made good by the government (Rao, 1994). Investments in small-scale industry were perceived to have high social returns (particularly in terms of employment creation) but to be constrained by inadequate access to the formal banking sector. A comparison between the large and small industries' share in bank credit (in Table 1) shows that the share of large firms in bank credit came down considerably during 1969± 96, while the share of small firms increased. But as a share of GNP, bank credit to both large and small firms increased, which suggests that the directed credit programme for small firms need not have reduced credit availability for large firms. Recent econometric research shows that directed credit did allow investment in small firms to be higher than would otherwise have been the case (Kohli, 1997). Notwithstanding the empirical support for the positive growth effects of government-directed credit in both agriculture and small-scale industry, the focus of India's recent financial reforms is on the phasing-out of its directed credit programme. As exemplified by the Report of the Narasimham 496 C. W. M. Naastepad Table 1. Directed Credit in India, 1989±1998 (as Percentage of Gross Bank Credit) Pattern of Lending Food procurement Large industry Wholesale trade and other Directed credit (1) Agriculture (2) Small-scale industry (3) Others Gross bank credit Bank credit to large industry/GNP Bank credit to small industry/GNP 1969 1988 1992 1998 6.5 78.2 1.0 3.1 36.3 19.1 4.3 38.4 22.6 4.1 39.1 23.7 14.0 5.2 7.9 0.9 100.0 41.5 17.1 15.5 8.9 100.0 34.7 14.0 13.8 6.9 100.0 33.1 11.6 14.5 7.0 100.0 7.1 0.8 7.4 3.1 8.2 2.9 7.4 2.7 Source: Reserve Bank of India (various issues). Committee on the Financial System (1991), the recent financial reform is primarily concerned with the decline in productivity and efficiency of the banking sector. The Report identifies directed credit programmes as one of the main responsible factors, arguing that directed credit has had negative effects on banks' incomes through concessional interest rates and the high administrative costs of such loans. To improve efficiency, the Narasimham Committee recommended that directed credit be drastically reduced from the prevailing 40 per cent to just 10 per cent of total loans over a three year period. Because of strong opposition from farmers and small-scale industry, the government has not officially accepted this recommendation, but actual priority sector lending was reduced to 33 per cent in 1998 (Table 1). Since 1993, the performance of the directed credit programme has been improved significantly by reducing interest rate subsidies (on loans of over Rs 200,000) and laying greater emphasis on lending along commercial lines to reduce non-performing loans (Sarkar and Agrawal, 1997). The important point however is that the discussion on India's financial reforms has focused rather narrowly on the efficiency impact of directed credit programmes on financial institutions' performance (Kohli, 1997). Their macro-economic impact on growth, employment, inflation and income distribution has played a less prominent role in the discussions so far and consequently a balanced appraisal of India's priority credit system has yet to take place (Mujumdar, 1996). THE REAL-FINANCIAL MODEL IN OUTLINE To evaluate the growth and distributional implications of directed credit policies in India, an expanded version of the multiperiod real-financial CGE The Macro-Economic Effects of Directed Credit Policies 497 described in Naastepad (1999) is used (see the Appendix for details). There have been relatively few attempts to incorporate the financial sector in a CGE model.1 The present model builds on Rosensweig and Taylor (1990), but goes beyond it in three important respects. First, it recognizes the dual role of credit for working capital as well as for investment. Second, it allows for endogenous shifts between credit-, capacity- and demand-constrained regimes (see also Naastepad, 2001; Vos, 1998). Third, it is (sequentially) dynamic, incorporating the main intertemporal adjustment mechanisms required to assess the medium-term as well as short-term impact of directed credit policy. The model divides the economy into a real side, describing production, income generation and goods' demand, and a financial side, describing the portfolio behaviour of the government, households, firms, banks, non-bank financial institutions and the central bank. For each year, a complete equilibrium is calculated in terms of flows of goods and services, incomes, financial flows, and financial stocks. This section presents the CGE model in outline (see the Appendix for details and values of important model parameters).2 The Real Side The model distinguishes the following three types of production sectors: 1. Household sectors (sectors 1±4), which operate under competitive conditions; production is supply-determined and markets clear through price adjustments; the household sectors include agriculture (sector 1), small-scale industry (sectors 2±3) and services (sector 4). 2. Private corporate sectors (sectors 5±7), which operate under oligopolistic conditions; production is demand-determined; prices are formed through a mark-up on variable costs, including the costs of labour, imported inputs, domestic inputs, net indirect taxes, and the costs of working capital (Chatterji, 1989); markets clear through quantity adjustments as long as none of the supply-side constraints discussed below becomes binding. 3. Public sectors (sectors 8±11), where prices are administratively fixed, and output is demand-determined Ð unless the capacity constraint binds. The model's real side thus reflects the structural asymmetries between the unregistered (that is, the household) sectors and the registered (that 1. Those that do exist include Bourguignon et al. (1992), Easterly (1990), Kouwenaar (1988), Rosensweig and Taylor (1990), Vos (1998) and Yeldan (1997); see Naastepad (1999) for a review. 2. A complete list of model equations can be downloaded from one of the author's web sites: http://www.econ.uu/naastepad.htm or www.tbm.tudelft.nl/webstaf/ron/. The full model documentation can be found in Naastepad (1999). 498 C. W. M. Naastepad is, the private corporate and public) sectors, characteristic of the Indian economy. Nominal wage rates in the private corporate sectors and the public sectors are indexed to the consumer price index (CPI). The nominal wages in the unregistered sectors, in turn, are linked to the registered sectors' wage rate. The model further distinguishes three categories of private income, characterized by (empirically observed) different propensities to save and to consume, namely, agricultural income, non-agricultural wage income, and non-agricultural non-wage income. Agricultural income has the lowest propensity to save and non-agricultural non-wage income the highest (see the Appendix). Note that household sector savings are defined as the combined savings of the agricultural sector, the savings out of wage income earned in sectors 2±11, and the savings out of non-wage income of sectors 2±4. Consumption preferences differ between agricultural income earners and non-agricultural income earners according to a linear expenditure system. Government consumption demand is exogenous. Export and import demands (for i = 1, .., 7) are endogenous, assuming that these are imperfect substitutes for domestic goods (see the Appendix for an explanation). The determination of private investment demand (i = 1, .., 7) requires elaboration. Actual private investment demand (by sector of destination) is the minimum of unconstrained or desired investment Jipd and creditconstrained investment Jipc as follows: (1) Jip = min(Jipd , Jipc ) The level of desired investment Jipd depends positively on expected real income (in agriculture and the private corporate sectors) and on previous period public investment (in the non-agricultural household sectors). The determination of the credit-constrained level of investment, Jipc , is discussed below. Aggregate demand Xid for domestic good i (i = 1, .., 7) is the sum of the intermediate demand, private and public consumption demand, investment demand (including changes in stocks), and export demand Ð minus final import demand. As far as the sectoral supply of the private sectors (i = 1, .., 7) is concerned, the model distinguishes two possible constraints on output.3 First, output can be limited by production capacity, as determined by the installed capital stock and the sector's capital output ratio. This capacity-constrained level of output is called Xik . Note that the expansion of production capacity over time depends on public and private investment. 3. In order not to complicate our analysis of the macro effects of directed credit, we assume here that there are no supply-side constraints on the public sectors 8±11, that is, these sectors have sufficient access to the required physical and financial inputs. For an analysis of the impact of supply constraints in these sectors, see Naastepad (1999). The Macro-Economic Effects of Directed Credit Policies 499 Second, the level of output of sector i can be constrained by the availability of working capital credit (more on this below); the working-capital constrained level of output is labelled Xiw . For the household sectors i = 1, .., 4, the maximum level of output is defined as: (2) Xis = min(Xik , Xiw ) The equilibrium condition for these sectors is commodity market clearing, or: (3) Xid ÿ Xis = f ( pi ) = 0 Prices pi adjust until demand and supply are equalized in each of the household sectors. For the private corporate sectors (i = 5, 6, 7), the maximum level of output is defined as: (4) Xis = min(Xik , Xiw , Xid ) In addition to the two supply-side constraints on output, a third, demandside, constraint enters the output determination. The implication is that supply adjusts to demand as long as the aggregate demand for good i(i = 5, 6, 7) falls below the supply-constrained levels of output. In this case, supplydemand balance is instantaneously achieved. However, if demand rises above the maximum level of output that can be supplied, the resulting excess demands are removed through upward adjustments of the mark-up rate f i , or (5) Xid ÿ Xis = g (fi ) = 0 The mark-up rate reacts (positively) to demand pressure only when maximum production is reached. While demand±supply balance in the household sectors is always brought about by price adjustments (irrespective of which supply-side constraint is binding), demand±supply equality in the corporate sectors involves either quantity adjustments (that is, supply adjusting to demand in case Xid falls below Xik or Xiw ) or price (mark-up rate) adjustments (in case of an excess demand). It is important to note here that the nature of market-clearing in the private corporate sectors is not pre-specified, but varies endogenously depending on real-financial changes occurring within the model. Changes in the (sectoral) availability of working capital credit are a crucial factor responsible for a regime switch from a demand- to a working-capital credit supply-constrained equilibrium. Let us therefore look more closely at the financial side of the model to see how (sectoral) credit availability is being determined. 500 C. W. M. Naastepad The Financial Side On the financial side, the model describes the portfolio behaviour of the household sector, the private corporate sector, the government, the banks, non-bank financial institutions, and the central bank. Starting with the first, the household sector of the financial sub-model comprises production sectors 1±4 as well as all wage earners. We begin by defining the household sector's accumulated (physical and financial) wealth as the sum of initial (end-of-previous-period) assets, minus initial liabilities, plus current period savings. Next, the household sector's liability requirements, including working capital and investment loans are determined. The demand for working capital credit is a function of current variable costs; working capital credit is supplied only by banks. The demand for investment loans depends on sectoral investment plans. Investment credit is supplied from two sources: banks and non-bank financial institutions. The household sector's demand for investment credit from banks is determined as the residual of their total demand for investment credit after subtraction of whatever non-bank financial institutions have been willing to supply. The household sector's gross financial wealth Wi equals the sum of total (financial plus physical) wealth and liabilities minus the value of the stock of physical capital and inventories at the end of the current period. This financial wealth is allocated among eight financial assets: currency, provident fund deposits, bank deposits Dhb , deposits with non-bank financial institutions other than provident funds D o, claims on the government Lgh , and claims on the three private corporate sectors Lih (i = 5±7). Currency demand is assumed to be a function of nominal GDP at market prices. Contributions to provident funds, which are compulsory by law, are a function of current wage income. Ah equals Wh minus currency holdings and provident fund deposits. The allocation of Ah among the remaining six assets is derived from the maximization Ð by banks Ð of the utility from expected total earnings from these assets, subject to a wealth constraint (see the Appendix for details). The private corporate sector of the financial submodel comprises production sectors 5±7 of the real model. The model determines demand for working capital and investment credit for each corporate sector separately. The demand for investment loans from banks equals what remains after loans from households and non-bank financial institutions have been received. Each sector's net worth is defined as the sum of initial assets minus initial liabilities plus current savings. Any excess of funds (net worth plus loans acquired) over financing requirements (equalling the sum of the sector's capital stock, investments, inventory and change in stocks) is deposited in banks. Next comes the government portfolio. Because the government is confronted with a limit on its current revenues (from taxes and public enterprises), it is obliged to finance its resource gap through borrowing from banks, non-bank financial institutions, the household sector, the external The Macro-Economic Effects of Directed Credit Policies 501 sector, and the central bank. It is assumed that all government borrowings Ð except the borrowings from the central bank Ð are determined elsewhere, that is, in the portfolios of the lenders concerned. In the case of banks and non-bank financial institutions, the amount of lending to the government is determined by the so-called statutory liquidity requirements (SLR), under which these institutions are obliged to invest a certain percentage of their deposits in government securities (which generally fetch below-market rates of return). Banks and non-bank financial institutions are free to invest in government securities on top of SLR, but will only do so in times of slack in the credit markets. In our specification of the government portfolio, the government's recourse to central bank credit (or monetary financing) is endogenous. Banks accept as their deposits whatever financial savings households and private corporate sectors wish to hold in the form of bank deposits. These deposits are in turn used by banks to engage in new lending to the government and private producers and investors. The total amount of funds available for bank lending to the private sector equals the sum of bank deposits and borrowed reserves minus the sum of banks' required reserves and bank loans to the government under the SLR.4 In India, the allocation of bank credit between the various private sectors is partly a matter of the banks' choice, and partly a matter of (directed credit) policy: 40 per cent of bank credit to the private sector is reserved for the priority sectors (all of which are part of the household sector). The rest of bank credit is allocated over working capital loans and investment loans to the private sectors and loans to the government, according to their relative returns. The returns depend on two factors, namely, on the one hand, the rate of interest iib charged by banks on the loans to sector i (which is policy determined) and on the other hand, the costs cib to the lending institution, associated with loans issued to this particular debtor.5 The allocation is based Ð as in the case of the household sector portfolio Ð on the maximization of a CES utility function subject to a wealth constraint. Non-bank financial institutions utilize the deposits mobilized by them to invest in loans to the government, the private corporate sector, and the 4. Borrowed reserves are additional reserves borrowed from the central bank to support additional credit creation. Required reserves are reserves which banks are legally required to hold in cash out of their aggregate deposits. 5. The relative rate of return on bank loans rib is defined as: ÿ b ÿ b rib = (iib ÿ cib )/(ii ÿ ci ) ÿ b b ci ÿ where ii and are the `normal' rate of return on bank loans and the `normal' marginal cost to the banks of monitoring loans, including provision for expected defaults, respectively. The perceived costs of monitoring and default were estimated using sectoral data from banks' balance sheets; in the model, these costs are exogenous. See Naastepad (1999). 502 C. W. M. Naastepad household sector. Part of non-bank financial institutions' investments in government debt is compulsory under SLR. The remainder of non-bank financial institutions' resources is invested in claims on the private and government sectors, depending on their relative profitability. Finally, we arrive at the central bank's portfolio. The stock of government borrowing constitutes the major asset of the central bank, along with foreign exchange reserves. Foreign exchange reserves are determined as the sum of the stock of foreign exchange reserves at the end of the previous period, the current account balance of the balance of payments, and net claims on the rest of the world.6 The remaining asset side in the balance sheet is borrowed reserves (a policy variable). All items in the central bank's balance sheet are already determined in the other portfolios. Real-Financial Interactions, Credit Rationing and Credit Market Balance The main real-financial linkages in the model work through the demand for and supply of credit for working capital and investment. The demand for the two types of credit depends on the private sector's production and investment plans respectively. The supply of credit is determined by actual income and savings, private portfolio decisions, and policy (that is, the values of the policy instruments including the directed credit programme). How do supply and demand meet? It is important to underline that, in India, the interest rate does not play the role of an equilibrating mechanism (Bhaduri, 1992; Rakshit, 1994). Hence, the model assumes fixed interest rates and consequently, financial markets clear through quantity adjustments.7 We distinguish two regimes: an excess demand for and an excess supply of credit. An excess supply of credit has no impact on the rest of the economy; it remains unused by the private sector. Excess credit demand, on the other hand, is eliminated through rationing of credit-financed components of demand, notably, working capital and investment. The impact of credit rationing is different for the two types of credit. In the case of working capital credit constraints, the maximum output of sectors 1±7 permitted by available working capital credit Xiw is a positive 6. Note that it is not assumed that there is unlimited access to foreign loans. Foreign loans are assumed exogenous and any change in the BoP current account gets reflected in the country's foreign exchange reserves, as actually happened in 1991. See RBI (1994). 7. This reflects the fact that in India, until recently, interest rates were policy-determined. However, even after they were freed, they did not perform the role of an equilibrating mechanism due to oligopolistic conditions in the financial sector (Rakshit, 1994; RBI, 1994). It should be underlined that the notion of endogenous interest rates is not inconsistent with that of quantity adjustment as the final effective equilibrating mechanism of the credit market. See Rosensweig and Taylor (1990) and Vos (1998). The Macro-Economic Effects of Directed Credit Policies 503 function of available credit supply to sector i, Lws i , and a negative function of variable production costs VCi : (6) Xiw = z(Lws i , VCi ) Hence, if working capital credit supply to sector i declines (for example due to a reduction in directed credit supply) or variable production costs rise in sector i, the credit-constrained level of output is reduced. In the (priceclearing) household sectors, the result is upward pressure on prices, which lowers real demand until the excess demand for goods is reduced to zero. In the private corporate sectors, the decline in the credit-constrained level of output has no effect as long as maximum goods supply continues to exceed demand. When goods demand exceeds supply, excess demand is removed through mark-up rate adjustments. In the case of investment credit constraints, the maximum investment by sectors 1±7 permitted by available investment credit J pc i is a positive function of available credit supply to sector i, Lvs i and a negative function of the price of sector i's capital stock pik : (7) vs k J pc i = q(Li , pi ) The expression for credit-constrained investment is the reciprocal of the investment loan demand function, in which investment loan supply is substituted for investment loan demand. Shortage of investment credit necessitates downward adjustments of investment plans, until investment has reached the level compatible with available bank and non-bank finance. The short-run effect of a reduction of investment is to reduce demand, which leads to price reductions in sectors 1±4 and output reductions in sectors 5±7. The reduction in output and prices in turn lowers demand for working capital. Equilibrium in the financial markets is restored because of this double adjustment of investment and output, which reduces the demand for working capital as well as investment loans. Credit market balance implies that all credit excess demands be zero or v;s w;d w;s negative; that is, Lv;d ib ÿ Lib 0 and Lib ÿ Lib 0. It is assumed Ð in line with Indian practice (Rakshit, 1994; RBI, 1994) Ð that any excess supply of bank credit for working capital and/or investment purposes is invested in government debt.8 The government in turn uses this additional credit coming from banks to reduce its foreign debt. 8. For instance, in 1993±94 additional bank holdings of government securities amounted to 50 per cent of total loans, which was far in excess of the 25 per cent required under statutory liquidity rules. Due to the oligopolistic nature of India's banking sector, banks do not engage in loan-pushing or some form of cut-throat interest rate competition, but rather invest in low-risk government securities. 504 C. W. M. Naastepad This process of adjustment to a situation of excess credit has no consequences for the real side of the economy. A shortfall in credit supply relative to demand, by contrast, necessitates adjustments on the real side. The relative shortage of credit leads to credit rationing, due to which sectoral production and investment levels are lowered until the excess credit demand is removed. It is important to note that Ð given this specification Ð the nature of real-financial linkages is endogenous and may vary between being uni-directional (from the real to the financial side, in case of excess credit supply) and bi-directional (from the real to financial side and vice versa, in case of a credit shortage). Finally, it should be noted that the credit constraints on output and investment become binding only if there is a shortage of credit at the aggregate level. At the sectoral level, mismatches between credit supply, which follows endogenously from banks' portfolio decisions, and credit demand, which is based on sectors' production and investment plans, arise all the time, but so long as the aggregate demand for credit falls short of the aggregate supply, none of the constraints will bind. The reason is that banks use the available excess supply of (working capital and/or investment) credit to sector i to meet the excess demand for (working capital and/or investment) credit of sector j. This is no longer possible when aggregate credit demand exceeds aggregate credit supply. Credit rationing by banks occurs whenever an aggregate excess demand for bank credit arises simultaneously with an excess supply of (working capital or investment) credit at the sectoral level. In that case, banks pool together all the available sectoral excess credit supplies and ration it across the various categories of demand. In so doing, banks have a priority order of credit allocation Ð following the Stiglitz-Weiss notion that creditors can only distinguish between broad classes of risk. The rationing rule, based on observed differences in cib , is that banks preferentially meet the excess demands for working capital and investment credit by the private corporate sectors and the public sector and only then turn to satisfy the excess credit demands by the household sectors (see Naastepad, 1999 for details). SCALING DOWN THE DIRECTED CREDIT PROGRAMME: SHORT-RUN EFFECTS This section explores the short-run consequences for production, prices and income distribution in India of a sizeable reduction in the share of directed credit in gross bank lending Ð from 40 per cent in the base run to 35 per cent. The effects of scaling down India's directed credit programme are analysed under various assumptions concerning monetary policy. We further investigate the sensitivity of the simulation results to variations in the country's price elasticity of export demand. This was done because Ð unlike in the case of other parameters, such as the price elasticity of The Macro-Economic Effects of Directed Credit Policies 505 domestic food demand, and for want of firm empirical evidence Ð there exists a great deal of controversy on the price responsiveness of Indian exports, particularly following India's recent trade liberalization. The following experiments are reported here:9 . . . . E2M: directed credit is scaled down, assuming that (i) there is no constraint on government borrowing from the central bank (monetization is endogenous); and (ii) exports are relatively price sensitive (the price elasticity of the demand for Indian exportables is 72); E2cM: directed credit is reduced, assuming that (i) government borrowing from the central bank is fixed (monetization is exogenous); fiscal balance is maintained by a downward adjustment of government consumption; and (ii) the price elasticity of export demand is 72; E0M: directed credit is scaled down, assuming that (i) monetization is endogenous; and (ii) exports are relatively price insensitive: the price elasticity of export demand is 0; E0cM: directed credit supply is reduced, assuming that (i) monetization is exogenous; fiscal balance is maintained by adjustment of government consumption; and (ii) the export price elasticity is 0. Table 2 presents the major results from these four experiments, expressed as percentage deviations from base-year levels. Before proceeding to the discussion of the simulation results, it is important to point out that the base-year equilibrium is of a credit-constrained nature. There is an overall shortage of bank credit, which is manifested in the fact that all household sectors are working-capital credit constrained, all corporate sectors are investment credit constrained, and corporate sectors 6 and 7 are also working-capital credit constrained. Following the reduction in directed credit supplies to the household sectors, banks are free to reallocate their loans to the corporate sectors. As a result, in all four experiments, none of the corporate sectors face any binding credit constraint, whereas each household sector is hit by working-capital credit as well as investment credit constraints. Let us look first at experiment E2M. The re-shuffling of the banking sector's loan portfolio in favour of the corporate sectors has two opposing effects. First, the increased availability of working capital and investment credit raises output and investment levels in the corporate sectors. Second, the fall in credit availability to the household sectors squeezes their outputs and investment. The net effect on aggregate real GDP at market prices is negative, 78.7 per cent. The main cause of the contraction is the strong 9. Note that these are all experiments in which the share of directed credit is reduced. Experiments in which this share was raised indicate that the results are symmetric for realistic changes in the direct credit share. 506 C. W. M. Naastepad increase in household sector prices, triggered by the fall in outputs due to the decline in working capital credit supply. The agricultural price rises most (by more than 28 per cent) because, in low-income countries such as India, the demand for agricultural (food) products is relatively insensitive to changes in its price. The household sector price increases have important economywide implications. First, production costs in the corporate sectors increase, because (indexed) nominal wages as well as the prices of intermediate inputs rise. This cost-push process results in an increase in the GDP deflator of almost 11 per cent. Second, domestic consumption of other goods and services falls, because consumers are forced to spend more of their incomes on fixed quantities of necessary goods produced by the household sectors (particularly food). Third, given a fixed nominal exchange rate, the rise in domestic production costs and prices significantly erodes the country's international competitiveness, resulting in a drop in exports (by more than 12 per cent) and a rise in (competitive) imports (by 13.3 per cent); as a result, the BoP current account deficit increases to 5.5 per cent of GDP. Due to the decline in consumption and export demands, aggregate demand for corporate sector goods falls. At the same time, however, the workingcapital constrained level of output (X wi ,i = 5,6,7) increases, as banks now allocate more credit to the corporate sectors. The result is that actual private corporate production is no longer working-capital credit constrained, but becomes determined by the (lower) levels of demand. Taken together, the scaling down of the directed credit programme results in lower outputs and higher prices directly in the household sectors and indirectly in the corporate sectors. The policy change also has perverse fiscal and distributional implications. The government's budgetary position deteriorates significantly as the contraction leads to a serious decline in revenue from (direct and indirect) taxation and the inflation erodes the profits from public enterprises. Distributionally, agriculturalists gain from the reduction of directed credit: their real income (at factor cost) as well as their share in GDP at factor cost rises. It is crucial to point out here that, acknowledging that agricultural output drastically declines, the reduction in directed credit is likely to worsen the intra-agricultural distribution of incomes and to raise rural poverty. Although intra-agricultural income distribution is not explicitly modelled, we can infer Ð on the basis of the literature on rural poverty in India (see Sen, 1998) Ð that the predicted aggregate real income gain for agriculturalists is the net outcome of a real income loss of landless labourers and small (subsistence) farmers who, being net buyers of food, lose real income due to the inflation, and a substantial real income gain of large farmers (who are net sellers of food). The real incomes of non-agricultural wage earners and mark-up income recipients are negatively affected by the reduction in directed credit to the household sectors. This redistribution of incomes from (higher-saving) non-agriculture to (lower-saving) agriculture has a negative impact on aggregate private savings and hence on bank deposits. The resulting decline in deposits by 2.7 per cent puts a further The Macro-Economic Effects of Directed Credit Policies 507 Table 2. Reduction in Directed Credit: Short-run Results (in per cent deviation from the base run) Base Run (1) Prices and Wages 1. Agricultural Price 2. HH Capital Goods Price 3. HH Consumer Goods Price 4. HH Services Price 5. PC Capital Goods Price 6. PC Consumer Goods Price 7. PC Services Price CPI GDP Deflator HH Wage Rate PC Wage Rate 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.8 1.0 E2M (2) E2cM (3) E0M (4) E0cM (5) 28.8 6.6 9.9 9.8 4.5 10.4 5.0 13.6 10.7 3.8 3.8 29.7 6.2 728.1 710.7 70.6 2.1 0.6 7.3 4.6 2.1 2.1 31.7 11.4 31.3 17.6 7.1 14.9 7.1 17.3 14.1 4.8 4.8 16.7 8.1 75.2 76.4 0.7 3.1 1.0 5.6 4.1 1.6 1.6 Production 1. Agricultural Production 2. HH Capital Goods Production 3. HH Consumer Goods Production 4. HH Services Production 5. PC Capital Goods Production 6. PC Consumer Goods Production 7. PC Services Production 180545 85645 48071 113183 78527 58575 11148 714.8 711.2 711.5 711.9 77.3 710.6 78.3 714.1 713.1 0.2 79.8 78.5 77.7 713.3 716.5 715.4 720.1 716.0 78.3 711.8 79.3 78.2 712.8 73.1 76.1 75.9 76.4 79.6 National Accounts Real GDP (Market Prices) Private Consumption Public Consumption Gross Fixed Investment Exports Imports Real GDP (Factor Cost) Real Agricultural Income Real Income Public Enterprises Real Mark-up Income Real Wage Income 452229 285747 53640 107117 35004 45476 404226 127123 25547 136229 115327 78.7 710.3 0.0 0.5 712.4 13.3 79.7 2.3 733.1 712.6 714.3 79.9 710.5 724.9 0.5 0.7 4.9 710.7 11.1 717.9 727.6 713.1 79.8 711.9 0.0 0.5 1.6 24.7 711.2 70.5 743.3 79.3 718.0 76.9 77.0 719.1 0.5 70.9 2.0 77.2 5.4 716.4 714.7 77.2 Financial Variables Bank Deposits Bank Loans to PC Bank Loans to HH Bank Loans to Government 184020 86951 58005 43341 72.7 70.5 74.4 72.7 76.5 74.4 75.8 76.6 72.2 1.2 76.0 72.2 74.1 72.4 74.3 74.1 3.4 1.5 2.7 6.0 70.1 5.5 3.6 3.6 4.1 6.3 70.3 5.6 3.5 2.9 3.5 Percentage Shares of GDP Monetization (% of GDP) Gross Public Savings (% of GDP) BoP Current Account Deficit (% of GDP) 508 C. W. M. Naastepad squeeze on credit availability to the household sectors, which comes on top of the reduction in priority credit supply. In E2M, the reduction in directed credit occurs in conjunction with an accommodating monetary policy, as is clear from the rise in the monetized deficit (as a percentage of GDP) to 6 per cent. To address the question of how much of the inflation is due to this monetary policy stance, experiment E2cM investigates the effects of the same reduction in directed credit supply in combination with a non-accommodating monetary policy, in other words, the monetized deficit is kept constant in nominal terms. This is achieved by reducing public consumption expenditure, which Ð in view of the political economy of taxation in India (Roy, 1998) Ð is a more realistic option of budgetary adjustment than (direct or indirect) tax increases.10 As Table 2 shows, when combined with a non-accommodating monetary policy, the cut in directed credit supply turns out to be less inflationary than in E2M: the GDP deflator rises by `only' 4.6 per cent. The inflationary pressures are contained by a drastic cut (of almost 25 per cent) in real public consumption, due to which demand declines and hence price increases and cost-push pressures are contained (as compared to E2M). Prices even fall in sectors 3, 4, and 5, which raises export demand; the export growth in these sectors outweighs the export decline of the other sectors (the prices of which increased), and aggregate export earnings (in real terms) rise. Imports increase compared with the base run (though less than in E2M). This rise in imports, which is due to the substitution of foreign goods for the more expensive domestic goods, is one of the factors causing a drop in domestic demand and hence production. The other factors are the decline in government consumption (to keep the monetized deficit constant) and the rise in the agricultural price.11 These factors combined, result in a real GDP contraction of 9.9 per cent, which is larger than in E2M. Consequently, the distributional tensions arising out of E2cM are significantly higher than those due to E2M. Experiments E0M and E0cM assess whether the direction of the macroeconomic effects of a reduction in directed credit supply are affected by our assumption that export demands are relatively price sensitive. Table 2 shows that this is not the case. In fact, in E0M, the stagflationary effects of the policy change come out even more strongly. This is because, once export demand is not price responsive, the burden of demand±supply adjustment in the household sectors (and in agriculture in particular) falls entirely on the relatively price-inelastic domestic consumption demand. As a result, large 10. See Naastepad (1999) for a comparison of the macro-economic effects of different modes of financing (direct tax; indirect tax; bank debt; and monetization) of an otherwise equal budget deficit. 11. The price declines for goods 3, 4 and 5 create room for additional spending in the consumer budgets. As a result, consumer demand for agricultural products increases, which (given agricultural supply) leads to a higher agricultural price. The Macro-Economic Effects of Directed Credit Policies 509 price increases are required to bring down demand to the level of creditconstrained supply, leading to a strong rise of the GDP deflator (of 14 per cent). The household sector price increases have strong negative cross-price effects on the consumption demand for the other sectors; as a result, overall consumption declines by almost 12 per cent in real terms. Real GDP falls by 9.8 per cent. The real incomes of all income categories decline; distributionally, agriculturalists remain the principal beneficiaries of the policy change. The inflation has a serious negative impact on the (real) profits of public enterprises (743 per cent). This, in combination with a decline in tax revenues (caused by the decrease in the tax base following the contraction), erodes government savings and contributes to a significant step-up in government borrowing from the central bank (Table 2). The results from E0cM, finally, indicate that, when exports are priceinelastic, a non-accommodating monetary policy partially contains the stagflationary effects of a reduction in directed credit supply. Real GDP declines by about 7 per cent and inflation measured by the GDP deflator is 4 per cent, which is significantly less stagflationary than E2cM. In both experiments, the reduction in directed credit and the cut in government consumption lead to excess supplies in sectors 3 and 4; consequently, their prices decline, which lowers mark-up prices in sectors 5±7. In contrast to E0cM, the decline in corporate sector prices raises export demands, output levels, and hence working-capital credit demands of the corporate sectors in E2cM. Consequently, less working-capital credit is left over for the household sectors and accordingly credit constraints on household sector outputs are more stringent in E2cM than in E0cM. As a result, household sector outputs decline, their prices rise, the government's fiscal position threatens to increase (following the further contraction and the inflation), necessitating a further cut in public consumption in order to keep the monetized deficit constant. The eventual result of this process is a higher rate of inflation and a lower GDP in E2cM than in E0cM. In the latter experiment, more working capital credit remains available for the household sectors, and for agriculture in particular. Thus agricultural output declines less than in E2cM and accordingly the agricultural price rises less. This reduces cost-push pressures in the economy as a whole and also reduces the aggregate demand decline occurring via cross-price effects. THE MEDIUM-TERM EFFECTS The short-run consequences of a reduction in directed credit supply get carried over into the medium term through various channels, including production capacity expansion and nominal wage indexation. To evaluate the medium-term repercussions of the scaling down of the directed credit programme, we compare the results of E2M with the base run outcome over a period of four years in Table 3. Experiment E2M was chosen, because the 510 C. W. M. Naastepad higher price elasticity of exports probably more accurately reflects India's current, post-reform economy.12 In the base run, the average annual growth rate of real GDP (at market prices) is 4.3 per cent. This GDP expansion is driven by exports, (private and public) investment and consumption. Agricultural output growth (1.6 per cent per annum) is lagging behind the growth rates of the other sectors, mainly due to a reduced allocation of public investment to this sector. Inflation is relatively high in terms of both the GDP deflator (8.8 per cent per year) and the CPI (9 per cent per year). The inflation is due to the significant depreciation of the nominal foreign exchange rate (particularly in the second and third years), the relatively high agricultural price rise in the second and third years, and (working-capital) credit constraints in the first year (which carry over into high prices and indexed wages in the first and later years). Income distribution changes significantly in favour of non-agricultural mark-up income. What are the medium-term growth and distributional effects of a 5 per cent reduction in the directed credit supply to the household sectors as in E2M? Table 3 shows that, in contrast to what happens in the short term, inflation is now lower in E2M than in the base run. Inflationary pressures decline in response to the policy change, because of its impact on private investment. The major factor explaining this outcome is the decline in private sector investment as compared to its base-run level. This is illustrated in Table 4. It can be seen that, in E2M, investment by the private corporate sectors falls significantly below base-run levels in years 2 and 3, but exceeds the base run level in year 4. In contrast, household sector investment exceeds base-run levels in the first two years and declines in year 4. Private corporate investment declines in years 2 and 3 in response to the stagflation in the first year, due to which (real) profits and capacity utilization decline; as a result, corporate investment plans are drastically scaled down and corporate investment credit demands are lowered. This, in turn, implies that, in these years, more bank credit becomes available for household sector investment. Importantly, this increased credit availability makes it possible for agricultural investment to expand (in response to the higher agricultural price and increased real agricultural income). As a result, agricultural production capacity and supply increase (compared to their base-run levels), which puts further downward pressure on the agricultural price. Because the rise in this price is smaller, the overall price level rises less, nominal wage growth is less and inputs are less expensive than in the base run. This helps the private corporate sectors' profits to recover in years 3 and 4, which in turn triggers corporate investment growth. More bank credit is needed for private corporate investment and less is available for the household sectors; in year 4, 12. Due to lack of space and to avoid too much repetition, the medium-run results of the other experiments are not reported. These medium-run outcomes are similar to those of E2M. The Macro-Economic Effects of Directed Credit Policies 511 therefore, household sector investment becomes credit constrained and drops below its base-run level. In the medium run, when the private corporate profits and investments recover back to their base-run path, household sector investment tends to become credit-constrained (given the lower proportion of directed credit in total credit supply). Table 3. Reduction in Directed Credit: Medium-run Results (average annual growth rate) Base Run Prices and Wages 1. Agricultural Price 2. HH Capital Goods Price 3. HH Consumer Goods Price 4. HH Services Price 5. PC Capital Goods Price 6. PC Consumer Goods Price 7. PC Services Price CPI GDP Deflator Wage Rate Production 1. Agricultural Production 2. HH Capital Goods Production 3. HH Consumer Goods Production 4. HH Services Production 5. PC Capital Goods Production 6. PC Consumer Goods Production 7. PC Services Production National Accounts Real GDP (Market Prices) Private Consumption Public Consumption Gross Fixed Investment Exports Imports Real GDP (Factor Cost) Real Agricultural Income Real Income Public Enterprises Real Mark-up Income Real Wage Income Financial Variables Bank Deposits Bank Loans to PC Bank Loans to HH Bank Loans to Government Average Percentage Shares of GDP Monetization (% of GDP) Gross Public Savings (% of GDP) BoP Current Account Deficit (% of GDP) E2M 8.7 10.2 8.9 9.3 9.4 7.9 6.8 9.0 8.8 8.6 8.3 6.7 7.5 7.1 8.7 7.3 6.4 7.7 7.8 8.6 1.6 7.2 8.7 8.6 5.6 6.3 1.4 1.6 7.3 8.7 9.0 5.1 6.1 0.9 4.3 4.4 3.5 4.3 12.2 7.1 4.0 2.0 71.2 7.8 2.6 4.0 3.9 3.5 3.6 14.6 7.4 3.7 2.8 1.2 5.2 3.4 17.7 17.9 10.7 16.0 16.9 18.1 10.4 13.2 2.7 0.9 71.5 2.9 0.7 71.8 512 C. W. M. Naastepad Table 4. A Year-to-Year Comparison of Key Variables: Base Run and Experiment E2M Ratio Ratio Ratio Ratio of of of of Household sector Investment in E2M/Base Run Priv. Corporate Investment in E2M/Base Run Total Private Investment in E2M/Base Run Agricultural Price in E2M/Base Run Year 1 Year 2 Year 3 Year 4 1.01 1.01 1.01 1.29 1.07 0.48 0.90 0.98 1.00 0.91 0.96 0.98 0.88 1.05 0.95 0.98 In view of the fact that the country's medium-run export growth is higher following the policy change than before, the decline in private corporate investment in years 2 and 3 and the credit-squeeze based reduction in household sector investment in year 4 are the main factors responsible for a slowdown of real GDP growth in E2M as compared to the base run (Table 3). The investment decline is triggered by the erosion of non-agricultural markup income due to the rise in inflation and drop in demand for corporate sector output in year 1. Furthermore, the reduction in directed credit decreases government savings and raises monetization and the BoP's current account deficit (in absolute terms); however, the size of these medium-run effects (in absolute terms) is less than that of the short-run consequences. Distributionally, all income categories except mark-up income gain from the policy change. Agriculturalists gain from the expansion of agricultural production capacity, while wage earners and public enterprises benefit from the lower level of inflation. The medium-term impact on poverty can no longer unequivocally be inferred. On the one hand, poverty may fall on two accounts. First, the agricultural price increase is lower in E2M than in the base run (while the growth rate of agricultural output is the same), which will have a poverty-reducing impact through increased real wages. Second, production growth (and hence employment growth) in household sectors 2 and 4 is higher than in the base run. On the other hand, poverty may increase because of the following factors. First, aggregate private consumption growth is lower than in the base run, which Ð at India's low per capita consumption level Ð implies a rise in poverty (given an unchanged distribution). Second, production growth is lower in all private corporate sectors. The net impact on poverty cannot be ascertained by this model. The simulation results show that the medium-run effects on India's macro economy of a once-and-for-all reduction in its directed credit programme are non-negligible.13 As in the case of the short-run experiments, via crucial demand and supply linkages operating through goods and credit markets, 13. Note that a sensitivity analysis with regard to size of the simulated decline in the directed credit share (not reported here) indicates that the results are consistent in terms of direction and proportion of change. The Macro-Economic Effects of Directed Credit Policies 513 important benefits of the priority credit scheme accrue to the non-priority sectors of the economy: the corporate sectors and government. By implication, this result suggests that directed credit policies need not lead to crowding out of investment and growth in the non-targeted sectors. CONCLUSIONS In addition to the largely micro-economic literature on the effectiveness of directed credit policies in enhancing growth, this article has explored the short- and medium-term macro-economic consequences of reducing government-directed credit to priority sectors. This has been done for India, using a real-financial CGE model in which credit supply affects investment as well as current production (through working-capital loans). The model was used to evaluate the effects of a reduction in directed credit to India's household sectors, which include agriculture and small-scale industry. The simulation results can be summarized as follows: . . . In the short run, a reduction in directed credit is stagflationary, as real GDP contracts and inflation increases. The decrease in working-capital credit to the household sectors reduces their outputs and hence raises their prices. These price increases have strongly negative cross-price effects on the domestic demand for non-household sector goods and also erode the country's international competitiveness. Income distribution changes in favour of the (lower-saving) agricultural income earners. This, in combination with the contraction, reduces private savings and hence bank deposits, which adds to the credit squeeze and augments the stagflationary effects. The decline in household sector (agricultural) output in combination with the inflation imply a deterioration of the income distribution and a rise in poverty (notwithstanding the shortrun increase in aggregate real agricultural income). These results show that the spillover effects of directed credit are non-negligible: nonpriority sectors such as the private corporate sectors and the government are its principal beneficiaries. The reduction in directed credit supply is found to be more contractionary, but less inflationary when monetary policy is non-accommodating than when it is accommodating. This shows that, while a cut in government expenditure (or for that matter: a rise in taxation) is effective in lowering demand and prices, it does not address the main cause of the stagflation Ð the shortage of credit for the household sectors. The inflation reduction comes at the cost of an additional loss of real GDP. In qualitative terms, our main findings remain the same irrespective of whether export demands are price-elastic or not. When monetary policy is accommodating, the stagflationary effects of the policy change become stronger the more price-elastic is the nature of exports. 514 C. W. M. Naastepad . The scaling down of directed credit has a non-negligible negative medium-term impact on GDP growth, while its impact on poverty is ambiguous. The main reason for the income growth slowdown is the decline in investment in the non-priority (private corporate) sectors, caused by the erosion of corporate profits, in turn due to the rise in inflation and the drop in demand for corporate sector output associated with the policy change. The reduction of government-directed credit thus has significant negative spill-over effects on non-priority sectors and the government itself. This points to the need for general equilibrium evaluations of directed credit policy rather than the usual (intra-)sectoral approach. It also underscores that it is to the benefit of all sectors that adequate access to credit by certain key credit-rationed sectors (agriculture and small-scale industry) is maintained even when interest rates are deregulated and the financial sector is opened up to foreign parties. If this access cannot be guaranteed by a government-directed credit scheme, it is imperative for macro stability and growth to develop alternative, innovative financial institutions which can fill the credit gap faced by farmers and small-scale industrialists (for example, credit unions; see Mushinsky, 1999). Our results are open to the criticism that they overestimate the negative economy-wide effects of a reduction in the supply of directed credit, because the model ignores the possibility that household sector producers take loans from informal lenders. But empirical evidence shows that formal and informal credit markets are segmented by both collateral and the purpose of the loan,14 and hence the credit substitution between the two markets is limited for poor borrowers (Swaminathan, 1991). Even when informal sources of credit may be available, those sources may prove inadequate to meet the needs of any one household or the needs of all households (Binswanger and Deininger, 1997; Mushinski, 1999). Further, informal sources tend to offer credit at interest rates above formal credit market rates. Consequently, households which obtain credit from informal sources may not receive the amount they would obtain in a first-best world. In sum, inaccessibility of credit and wealth-based access to credit excludes low-wealth households also from informal sources. The incorporation of the household sectors' limited scope for substitution between formal and informal credit into the model analysis will therefore not qualitatively change our major findings. The simulation results suggest that, in a context in which pervasive credit market failures (due to information asymmetries) result in credit rationing, the macro-economic effects of India's directed credit programme, targeted to agriculture and small-scale industry, are significant and positive. The short-term significance of directed credit is due to its positive impact Ð via 14. Formal credit is allocated primarily for use in productive activities, while informal credit is used for consumption. See Swaminathan (1991). The Macro-Economic Effects of Directed Credit Policies 515 the availability of working capital loans Ð on output of crucial wage goods, produced by the household sectors (including agriculture). In the medium run, government-directed credit helps maintain private investment in sectors such as agriculture, with high social returns, without crowding out investment growth in the other sectors. Of course, the negative impact of India's directed credit programme, and of the subsidized lending rates in particular, on the banking sector's profitability and productivity has to be acknowledged and as far as possible be contained. But without downplaying the seriousness of these problems and the need to solve them urgently,15 the general equilibrium benefits of India's directed credit programme are such that they are unlikely to be outweighed by its costs. APPENDIX: MODEL STRUCTURE AND PARAMETERS A complete description of the model, including the equations and the realfinancial data base, is given in Naastepad (1999). Values of crucial model parameters are presented in Table A1. Sector Classification and Income Categories The economy is divided into eleven sectors: (1) agriculture; (2) household sector basic, intermediate and capital (BIC) goods; (3) household sector consumer goods; (4) household sector services; (5) private corporate sector BIC goods; (6) private corporate sector consumer goods; (7) private corporate sector services; (8) infrastructure; (9) public sector BIC goods; (10) public sector consumer goods; and (11) public sector services. The model distinguishes four categories of income: (i) agricultural income; (ii) non-agricultural wage income; (iii) non-agricultural mark-up income; and (iv) profits of public enterprises. Prices and Technology World prices for the traded goods (i = 1, .., 7) are exogenous. Prices of the household sector goods (i = 1, .., 4) are determined by the excess demand equations (3). Prices of the private corporate sector goods (i = 5, 6, 7) are mark-up prices. However, in case of excess demand for i = 5, 6, 7, the markup rate becomes endogenous as in equation (5). Nominal wages in the `registered' private corporate and government sectors are partially indexed to inflation (reflecting organized labour markets). Nominal wages in the household sectors are linked to the registered sectors' wages. Intermediate 15. See Vittas and Cho (1996) for a useful analysis of the conditions to make governmentdirected credit programmes an effective instrument for economic development. 516 C. W. M. Naastepad inputs are used in fixed proportions (Leontief assumption). Assuming a surplus of labour, sectoral output is a function of the installed capital stock and the sector's capital±output ratio. The capital±output ratios and sectoral labour productivities change exogenously over time. Income Generation and Distribution, Consumption and Savings Production generates the four categories of (factor) incomes. Private incomes are used for saving or consumption. Savings are a constant proportion of disposable income; the savings rates are exogenously fixed and differ between agricultural, wage and mark-up incomes. Commodity-wise private consumption demand by agricultural and non-agricultural income is represented by a linear expenditure system (LES). A noteworthy feature of the LES is the relatively high negative cross-price effect of an agricultural price rise on the demand for other goods (see Table A1); this corresponds with findings from consumer demand studies for India (see Naastepad, 1999, for references). Investment Desired private agricultural investment is a positive function of one-period lagged real income; the elasticity is 0.8 (Table A1). Real private investment in sectors i = 2, 3, 4 depends positively on previous-period public investment. Real private corporate sector investment depends on one-period lagged real mark-up income, representing the availability of internal funds. Public investment is a policy variable as is its distribution across sectors. Foreign Trade Export demand for i = 1, .., 7 is a function of the ratio of the domestic price (in foreign currency) to the world market price. The price elasticity of export demand is 72 in experiments E2M and E2cM. Complementary imports depend proportionately on the level of sectoral outputs. Using the Armington assumption, competitive imports depend on the ratio of the domestic to the world market price and the elasticity of substitution. Table A1 presents the Armington substitution elasticities used: they are high for the household sectors and lower for the private corporate sectors. The Financial Sector The specification of the financial sector is explained in the main text. Here, we elaborate the procedure adopted to model portfolio choice, using Ð following Rosensweig and Taylor (1990) Ð the CES utility function to The Macro-Economic Effects of Directed Credit Policies 517 describe portfolio behaviour. Consider the allocation of Ah (defined in the text), among the six assets Dhb , Do, Lgh and Lih as a constrained optimization problem. Assume that the per unit returns on the assets Dhb , Do, Lgh and Lih are, respectively, ib, in, ig and ii (i=5±7). The parameters ib , in , ig and ii are `normal' returns on these assets (see Rosensweig and Taylor, 1990). For ig and ii/ ii we will write, respectively, rb , rn , rg and ri . Houseib/ib , in/in , ig/ holds maximize utility from total earnings from the six assets: " # 7 ÿs ÿs ÿs X ÿs ÿ1=s h b h o h h d g rg Lgh d i ri Li h MaxU = d b rb D h d o ro D 15 subject to the wealth constraint 7 X o gh b Lih Ah = D h +D +L + 15 This yields the following expression for the share y hj of asset j in the household sector portfolio (see Naastepad, 1999: Appendix 8.1): jh71 = i i j j jh (8) y hj = d hj qh The share of a particular asset in Ah depends on its return ij/ij relative to the weighted average return on all assets, qh . The d hj are the CES distribution parameters and the j h = 1/(1+s) are the elasticities of substitution in the portfolio. Note that this specification makes sense only when the elasticity of substitution exceeds 1. The same approach is used to model the portfolio decisions of the commercial banks and the non-bank financial institutions. Table A.1 gives the value of the portfolio substitution elasticities, the base-run values of the cash-reserve ratio, the statutory liquidity ratio (SLR), and the sectorwise ratios of directed (working-capital and investment) credit to bank deposits. Table A.1 further presents the elasticities of working capital credit demand with respect to variable costs and of investment credit demand with respect to investment, used in equations (6) and (7). Equilibrium Conditions Equilibrium in the commodity markets implies that excess demands be zero in the price-clearing household sectors 1, .., 4 and zero or negative in the private corporate sectors i = 5, 6, 7. Equilibrium is always established by price adjustments in the household sectors. In the corporate sectors, equilibrium is brought about by quantity adjustments (that is, supply adjusting to demand) as long as excess demands are negative, and by price (that is, mark-up rate) adjustments when excess demands are positive. 518 C. W. M. Naastepad Equilibrium in the financial (credit) markets implies that the aggregate excess demand for working-capital and investment credit is zero or negative. Credit market equilibrium is established by quantity adjustments (the creation of excess credit supply) as long as the credit excess demand is negative; it is achieved via credit rationing (and consequent reductions in commodity outputs and investment) whenever the credit excess demand is positive. Macro-economic equilibrium implies the simultaneous occurrence of equilibrium of commodity and credit markets. Appendix Table A1. Major Model Parameters Elasticities Elasticity of private agricultural investment w.r.t. lagged real agricultural income Elasticity of household sector investment w.r.t. lagged public investment Elasticity of private corporate investment w.r.t. lagged mark-up income Elasticity of the nominal wage rate w.r.t. CPI Elasticity of currency demand w.r.t. GDP Armington substitution elasticity household sector Armington substitution elasticity corporate sector Substitution elasticity in portfolio of households, banks and non-bank financial institutions Cross-price elasticity of agricultural price w.r.t ± agricultural (non-agric.) demand for HH BIC goods ± agricultural (non-agric.) demand for HH consumer goods ± agricultural (non-agric.) demand for HH services ± agricultural (non-agric.) demand for PC BIC goods ± agricultural (non-agric.) demand for PC consumer goods ± agricultural (non-agric.) demand for PC services Elasticity of working-capital credit demand w.r.t. input costs Elasticity of investment credit demand w.r.t. investment 0.81 0.48 2.14 0.30 1.00 5.00 2.00 1.40 70.6 70.4 70.5 70.6 70.4 70.5 1.0 1.1 (70.5) (70.5) (70.3) (70.5) (70.3) (70.3) Other behavioural parameters Savings rate out of agricultural income Savings rate out of wage income Savings rate out of mark-up income 0.21 0.21 0.37 Policy variables Cash-reserve ratio Statutory liquidity ratio Percentage share in deposits Percentage share in deposits Percentage share in deposits Percentage share in deposits Percentage share in deposits Percentage share in deposits Percentage share in deposits Percentage share in deposits 0.17 0.24 7.16 8.21 5.09 6.53 2.54 2.86 2.67 3.93 of of of of of of of of directed directed directed directed directed directed directed directed working-capital credit to sector working-capital credit to sector working-capital credit to sector working-capital credit to sector investment credit to sector 1 investment credit to sector 2 investment credit to sector 3 investment credit to sector 4 1 2 3 4 The Macro-Economic Effects of Directed Credit Policies 519 REFERENCES Amsden, A. 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