Download The Macro-Economic Effects of Directed Credit Policies: A Real

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.
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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
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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
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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).
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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.
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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).
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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
1ˆ5
subject to the wealth constraint
7
X
o
gh
b
Lih
Ah = D h +D +L +
1ˆ5
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
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After obtaining her PhD at Erasmus University Rotterdam in 1998, C. W. M.
Naastepad joined Delft University of Technology and Utrecht University.
Her current research interests include the macroeconomics of employment,
wages and technological change and the comparative analysis of structural
change. Address for correspondence: Economics of Innovation, Faculty of
TBM, Delft University of Technology, Jaffalaan 5, 2628 BX Delft, tel.
+31±15±2786318, e-mail: [email protected].