How Do We Assess Monetary Policy Stance?

This paper develops a measure of the monetary policy stance from the detailed reading of various monetary policy announcements in India from 1973 to 1998. According to the proposed measure, the stance of monetary policy has been mildly contractionary over this period with its emphasis on inflation control. The constructed measure of monetary policy stance is then linked to output and prices in a three-variable vector autoregression framework, which indicates that, for the period of study, the potency of monetary policy seemed to have been more effective in price control vis-a-vis stimulating output growth.

How Do We Assess Monetary Policy Stance? Characterisation of a Narrative

Monetary Measure for India

This paper develops a measure of the monetary policy stance from the detailed reading of various monetary policy announcements in India from 1973 to 1998. According to the proposed measure, the stance of monetary policy has been mildly contractionary over this period with its emphasis on inflation control. The constructed measure of monetary policy stance is then linked to output and prices in a three-variable vector autoregression framework, which indicates that, for the period of study, the potency of monetary policy seemed to have been more effective in price control vis-a-vis stimulating output growth.

INDRANIL BHATTACHARYYA, PARTHA RAY

H
ow do we measure monetary policy? How do we infer that monetary policy implemented during a particular period has become contractionary or expansionary? The answers to these questions are invariably couched in terms of the actions of the central bank and its subjective interpretation by market participants. Clear articulation by the policy-maker about the objectives to be achieved and the rationale of policy measures are indicative of the stance of monetary policy. Nevertheless its quantification by numbers, in terms of the policy stance, is often beset with subjective evaluation errors.

In standard empirical research, a money market variable is usually taken as an indicator of changes in the monetary policy stance. There is no unanimity, however, on the choice of the appropriate indicator, whether a quantity variable (money supply) or a rate variable (short-term interest rate), as both are prone to fluctuations independent of monetary policy signals. In this context, an alternative “narrative approach” propounded by Romer and Romer (1989) has gained acceptance in the literature as a measure of shifts in policy stance. In this approach, originally explored in the US context, federal open market committee (FOMC) directives and related records are utilised and interpreted to identify the stance of the Federal Reserve on monetary policy over a period of time.

A logical extension of the basic narrative approach was the construction of a monetary policy index [Brunner and Meltzer 1989]. A monetary policy index depicts a numerical scale that indicates the stance of monetary policy as inferred from policy documents. It entails a mapping of the qualitative discussions in policy records to a quantitative scale by assigning a number indicating the degree of easing or tightening of policy stance. The basic advantage of such an index is that it provides a time series of values summarising monetary policy stance. There has been a plethora of studies in generating such indices, particularly in the US, providing a unique set of data, which, with appropriate statistical techniques can be used to verify the potency of monetary policy actions.

The present study generates a monetary policy index for India spanning a period of 25 years (i e, April 1973-March 1998) on a monthly basis. The choice of the period has been governed by two considerations. First, several volumes of monetary and credit policy circulars are available from 1973. These circulars sets outline the various monetary policy measures, the backdrop in which they were undertaken and their rationale. Second, the choice of the terminal period of March 1998 has been deliberate as from April 1998, the monetary policy framework shifted to a multiple indicator approach whereby the large importance attached earlier to monetary/credit aggregates was reduced and greater emphasis was placed on rate variables (having high frequency data) with consequent changes in the operating procedure of policy.1

The quantitative interpretations of policy statements in terms of indices in the present study are subjective and, thus, debatable. It is, however, largely unbiased, as the same criteria has been applied uniformly over the sample period. As Romer and Romer (1989) point out, “The fact that the selection of disturbances is judgmental and retrospective introduces the possibility [of] an unconscious bias”. Following Boschen and Mills (1995), in this paper we have tried to empirically establish causal relationships between our derived indices and some specific macroeconomic indicators so as to ascertain the impact of monetary policy actions during the sample period.

The paper is organised as follows. Section I provides a brief survey of the literature on narrative indices. The various instruments of monetary policy in India during the period under study are discussed in Section II. Section III illustrates the derivation of the monetary measure while Section IV discusses the empirical results. The concluding observations are presented in Section V.

I Received Literature

The pioneering work of Friedman and Schwartz (1963) is perhaps the ‘locus classicus’ of the narrative approach of monetary policy and has been highly influential. After this, however, for quite some time, work on the narrative approach to monetary policy was somewhat out of fashion. It has been resurrected in recent times by Romer and Romer (1989). In their study of US monetary policy, the authors identified some dates at which the monetary authority shifted policy towards an anti-inflationary stance.2 Utilising the minutes of the FOMC documents, they constructed a time series (known as Romer dates) that assumes a value of one on these dates and zero otherwise. An advantage of this approach is that it exploits information which is not included in standard statistical analysis – the intentions of the policy-makers to shift policy stance – as they are documented in the minutes of the FOMC. From the standpoint of econometric research, a second and more important advantage of this methodology is that it is robust to structural changes in the economy or to switches between alternative operating procedures.

Despite its appealing features, this methodology suffers from two fundamental shortcomings. First, it does not distinguish between endogenous and exogenous components in policy changes, which make their use as instruments of monetary policy unattractive on theoretical grounds. Second, the amount of information contained in this series is quite limited – neither the intensity as well as persistence of the contractions, nor expansionary episodes or other contractionary dates are recorded.

In an attempt to deal with the second group of deficiencies, Boschen and Mills (1991) have designed a monthly index of monetary policy stance that takes a value of -2, -1, 0, 1, or 2 of policy in a particular month is rated “strongly contractionary”, “mildly contractionary”, “neutral”, “mildly expansionary”, or “strongly expansionary” respectively. The rating is again based on a reading of FOMC documents and the assignment rule basically transforms the concerns of the policy-makers about inflation and unemployment and their stated intentions into one of the five values.

The claim that these qualitative measures solve the identification problem has prompted their use in several studies on the real effects of monetary policy [Romer and Romer 1994; Kashyap Stein and Wilcox 1993]. This narrative approach has been criticised from different angles. Leeper (1993) and Shapiro (1994) argue that the Romer dates are contaminated with larger endogenous components of monetary policy, and therefore cannot be regarded as exogenous shifts towards a disinflationary stance and used as instruments in econometric estimations. Sims and Zha (2006) take this argument a step further by stating that not only is there a significant anticipated component in the Romer dates but also that there is no evidence of exogenous contractionary movement around these episodes. Dotsey and Reid (1992) and Hoover and Perez (1994) show that the Romer dates lose their statistical properties in an output equation if oil price shocks are accounted for. They in fact assert that it is not altogether clear whether the evidence on the decline in industrial production reported in Romer and Romer (1989) can be attributed solely (if at all) to monetary policy shifts. Leeper (1997) also documents in a vector autoregression (VAR) context that the dynamic responses of some macroeconomic variables after an unanticipated innovation to Romer dates are inconsistent with standard monetary theory. Shapiro (1994) reports the reaction of inflation after a Romer episode and concludes that the disinflationary effect of the tightening is driven completely by the second oil price shock induced contraction of October 1979. It also documents some of these finding and extends the analysis by investigating the predictive power of both the Romer dates and the Boschen-Mills index in a VAR context, their influence on macroeconomic dynamics after a monetary policy shock, and more importantly by examining whether the intentions captured in these indicators are followed by appropriate actions.

Notwithstanding these critiques, the narrative approach to monetary policy continued to be a live topic of research. In fact, in a recent paper, Romer and Romer (2004) derived a new indicator of monetary policy shocks that avoids the problems inherent in both the change in the actual federal funds rate and the change in the funds rate target. They began by deriving a series on intended funds rate changes around meetings of the FOMC for the period 1969-96. To do this, they combined information on the Federal Reserve’s expected funds rate derived from the Weekly Report of the Manage of Open Market Operations with detailed readings of the Federal Reserve’s narrative accounts of each FOMC meeting. They found that even for those periods when the FOMC did not set an explicit funds rate target, the discussion of policy intentions provided a good indication of the desired changes in the funds rate. The resulting series on intended funds rate movements around FOMC meetings eliminated much of the endogenous relationship between interest rates and economic conditions and covers the crucial episodes missed by the existing series for the funds rate target.

II Major Instruments of Monetary Policy in India

Monetary policy instruments in India can be classified according to the area of their strongest initial impact, i e, whether they operate principally on the supply of money, through changes either in base money, the money multiplier, or on the demand for credit through cost and other influences [Singh, Shetty and Venkatachalam 1982]. The range of monetary policy instruments is wide, encompassing both direct (quantity) and indirect (price) approaches [Joshi and Little 1996]. Accordingly, against the backdrop of the literature on various attempts to develop narrative measures of monetary policy and as a prelude to our own efforts at constructing a narrative index for India, we present a brief account of the major instruments of monetary policy in India, which were commonly used during the period under study.3

Cash Reserve Ratio

Reserve requirements, viz, cash reserve ratio (CRR) is considered as a tax on intermediation that constrains growth of liquidity in the system. Traditional arguments in favour of the CRR have been that (i) it improves the precision in the conduct of monetary policy; (ii) it can be used for implementing policy changes;

(iii) it is a useful addition to the set of fiscal policy instruments and (iv) it facilitates the payment and settlement process [Hardy 1997]. The efficacy of the CRR, however, as an instrument of active liquidity management, in a modern financial system is very limited. It is expensive to administer frequent changes in reserve requirements and “using reserve requirements to fine tune the money supply is like trying to use a jackhammer to cut a diamond” [Mishkin 1997]. The CRR changes work with a lag and cannot be directed towards any specific segment of the financial market. Moreover, its impact is more enduring and is not quickly reversible.

In the Indian context, during the 1980s and particularly during the 1990s, the CRR, with its predictable impact has been most effective, both as an instrument of monetary control and as an anti-inflationary tool.4 Since 1973 and throughout the 1980s and the early 1990s, the CRR was progressively increased to neutralise the monetary impact of large-scale monetisation of government’s budget deficits [RBI 1985]. Since then, however, the CRR has been brought down sharply (Chart 1).5 At the minimum level, the CRR would cease to be an instrument of monetary control and would act as more of a prudential measure.

In India, the effectiveness of the CRR instrument has been further augmented on occasions by imposing additional CRR requirements (in the form of incremental CRR) from time to time.6 An incremental CRR of 10 per cent was effective for some time during the 1990s. In addition, an incremental CRR of 10 per cent was also levied on various non-resident deposits in order to restrict inflows, which has since been discontinued.

Statutory Liquidity Ratio

Central banks in many countries have resorted to stipulating liquid asset requirements in addition to cash reserve requirements but they are inefficient and redundant in most cases. However, adequately designed, they are helpful for prudential purposes in less developed economies, and can make the banking system more resilient to a crisis when the central bank has limited lender of last resort capabilities. Therefore, withdrawal of such a requirement

Bank Rate (per cent) SLR (per cent of NDTL) CRR (per cent of NDTL)

Effective Date

all on the following grounds: first, there may be some confusion about the central bank’s intentions and second, such changes often entail large fluctuations in the spread between market interest rates and the bank rate leading to large unintended fluctuations

it should not be used as an instrument of monetary control at

25-10-199717-09-199416-10-199321-08-199306-02-1993(29-02-1992)02-01-198806-07-198501-09-198430-10-198101-12-197808-12-1973

45.0

40.0

35.0

30.0

25.0

20.0

Chart 2: Changes in Statutory Liquidity Ratio: 1973-1998

Effective Date

29-06-1973

01-07-1974

04-09-1976

01-07-197821-08-198129-01-1982

27-05-1983

12-11-1983

01-12-1984

28-02-1987

23-04-1988

01-07-1989

(21-04-1992)

15-05-1993

06-08-1994

27-04-1996

26-10-1996

18-01-1997

06-12-1997

Chart 1: Changes in Cash Reserve Ratio: 1973-1998

17.00

15.00

13.00

11.00

9.00

7.00

5.00

3.00

13.0

12.0

11.0

10.0

9.0

8.0

7.0

31-05

1973

12-071981

23-071974

Effective Dates rates, viz, the direct signalling impact and indirect liquidity effect. While changes in the bank rate per se are reflective of a shift

Chart 3: Changes in the Bank Rate: 1973-1998 in the stance of policy and convey a message about the central bank’s assessment of monetary conditions, they have a direct effect on the cost of liquidity from the central bank, which, in turn, would have an impact on overall interest rates.

The most important advantage of the bank rate is that the central bank can use it to perform its role of a lender of last resort, particularly in the wake of several episodes of banking crises over the past few decades. However, it has been suggested that

04-07

1991

09-10

1991

16-04

1997

26-06

1997

22-10

1997

17-01

1998

19-03

1998

in the money supply. Therefore, bank rate changes can make it harder to control money supply [Goodfriend and King 1988].

In the Indian context, the RBI buys or rediscounts bills of exchange or other commercial papers eligible for purchase at the bank rate. It influences the cost of refinance and other financial accommodation extended to commercial banks, other specified groups of institutions and the government.8 An extremely significant measure introduced during the post-reform period was the reactivation of the bank rate in April 1997 by initially linking it to all other rates, including the Reserve Bank’s refinance rates (Chart 3).9 Consequently, changes in the bank rate, post 1997, were matched by commensurate changes in the prime lending rates (PLR) and deposit rates of banks. Since the quantum of refinance accommodation to commercial banks in India is rule based, the liquidity effect of changes in the bank rate on the cost of funds was largely limited.

Quantum and Cost of Refinance

The refinance mechanism is often used by central banks to influence the level of bank reserves and short-term interest rates. Although the relative importance of refinance has gone down

The bank rate is essentially the rate at which funds are available from the central bank and have a bearing on the cost of credit. Changes in the bank rate tend to have a dual impact on interest high as 38.5 per cent in 1992; however, subsequently it had been brought down to the statutory minimum level of 25 per cent by October 1997 (Chart 2). Hence, the efficacy of SLR, as a monetary instrument to meet policy objectives, is limited.

Bank Rate

economy and in the absence of well-developed securities market, the SLR mechanism provides a captive market for government securities while simultaneously restricting the flow of credit for commercial purposes, thus mitigating the prospects of unbridled monetary expansion [RBI 1985].

In India, the SLR prescription was systematically raised to finance the growing requirements of the government.7 It was as can only be addressed within the broader context of financial sector reforms and macroeconomic stability [Gulde Nascimento and Zamalloa 1997].

Commercial banks are generally required to hold liquid assets such as government securities against their deposit liabilities, which are commonly known as the supplementary reserve requirement or secondary reserve requirement. In a regulated in recent years, it plays an important role in emergency funding of end-of-day imbalances. The design of refinance instruments must take into account the exchange rate regime, the stage of development of the inter-bank market and the need to minimise central bank credit risk in refinance operations [Laurens 1997].

In India, refinance by RBI has generally functioned as one of the most active instruments of credit regulation during 1973-98. However, the relative importance has varied depending on the degree of liquidity constraints in the banking system.10 Access to refinance facilities was affected by raising the cost of such accommodation, which was implemented through “block pricing”. Recourse to higher levels of refinance beyond certain limits entailed higher rates of interest. The graduated system of higher rates sought to exercise a quantitative check on the quantum of refinance combined with a measure of cost escalation for such borrowing.

Interest on Deposits

Changes in deposit rates are indicative of the overall stance of monetary policy, which affects the cost of funds of banks and its profitability. During periods of financial fragility, active competition among banks is discouraged by the imposition of a ceiling rate on deposits. For example, until 1986 in the US, the Federal Reserve System had the power under “Regulation Q” to set maximum interest rates that banks could pay on savings deposits. In India, interest rates were largely administered in the pre-reform period with a plethora of interest rate regulations regarding the size of accounts, ceiling on rates, etc.11 In the absence of a market clearing mechanism in the credit market, the interest rates reflected the perspective of the issuer rather than the holder of deposits. Post-reform, there was a concerted effort to dismantle the administered structure and domestic interest rates have been fully deregulated with the sole exception of the savings bank interest rate. With regard to non-resident deposits, there are still some restrictions on tenure or cost.

Interest on Lending

Lending rates have an impact on the demand for credit and the investment scenario of the economy. While high lending rates may choke investment demand, they may themselves be indicative of the heating up of the economy, beyond full capacity utilisation. In the pre-1991 period, lending rates were also subjected to a host of regulations.12 Since the mid-1990s, considerable flexibility has been given to banks to determine their own lending rates with the introduction of the PLR slated for the best borrowers of the bank. Subsequent innovations in the form of medium term-lending rate (MTLR) were also introduced for project finance.

Open Market Operations

Open market operations (OMO) are widely used in many industrial countries to manage short-term liquidity and have become even more important in developing countries in their transitional phase towards deregulation and greater market orientation [Axilrod 1997]. Central banks use OMO as a key instrument in managing liquidity conditions in the system. The advantage of OMO is that it is precise and flexible and can be targeted at a specific segment of the financial market and is easily reversible. Thus, the lags of monetary policy operations are considerably reduced through OMO [Mishkin 1997]. In India, with increases in capital inflows since the mid-1990s, OMO have also served the added purpose of sterilising inflows to mitigate the monetary impact. Post-1991, OMO have supplanted the CRR as the principal monetary instrument for liquidity management.

Selective Credit Control

Selective credit control was introduced in 1956 as an adjunct to general credit control and was intended to ensure an adequate flow of credit to the desired sectors while preventing excessive credit withdrawal for less essential economic activities. It was usually applied to achieve a reduction in excessive advances against certain sensitive commodities in short supply and to reduce pressure on demand originating from bank credit.

Selective credit control was operated through one, or a combination, of the techniques of (i) minimum margin for lending against the value of specified securities (ii) ceiling on the level of credit and (iii) minimum rate of interest on advances. While the first two measures sought to control the quantum of credit, the third had a bearing on the cost of credit. The margin control was intended to act on the demand side by making such borrowings costlier while the ceiling impinged on the supply side [RBI 1982]. Over the years, selective control measures had become more complex and were subsequently phased out during the 1990s.

Table 1 provides a snapshot of the relative usage of the principal monetary policy instruments during the three decades covered by the period of study.13 It may be noted that with the reduction in financial repression, the emphasis on direct instruments substantially reduced.

III Construction of a Narrative Measure

During the period under study (i e, 1973-1998), the Indian economy can be broadly categorised into four phases from growth and inflation considerations, viz, (i) low growth and high inflation; (ii) low growth and low inflation; (iii) high growth and high inflation and; (iv) high growth and low inflation.14 If for expository convenience, we define 4 per cent and 10 per cent as the respective threshold levels of growth and inflation, then the first phase was typically the years of the oil shocks, viz, 1972-73, 1974-75 and 1979-80 and the balance of payments (BoP) crisis

Table 1: Usage of Major Monetary Policy Instruments by RBI

Instrument/Decade 1970s 1980s 1990s

CRR √√ √ SLR √√ √

Bank rate √ – √ (Reactivated since 1997-98) Refinance facilities √√ √ (sector specific refinance deemphasised) Administered interest rates √√ Deregulation of on deposits and lending interest rates OMO √ – √ (Reactivated since 1992-93) Selective credit control √√ Phased out

Note: √ corresponds to active use of the instrument.

– denotes dormant instrument.

Chart 4: Growth-Inflation Combination Table 2: Dates of Strong Contractionary Monetary Measures

No Dates Measures

-5.0 0.0 5.0 10.0 15.0 20.0 25.0 30.0 -6.0 -4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 Growth (per cent) Inflation (per cent) 74-75 73-74 79-80 80-81 91-92 72-73 71-72 94-95 76-77 Low growth and high inflation Low growthand low inflation High growthand high inflation High growthand low inflation

year of 1991-92. The second phase were the years of 1976-77, 1982-83 and 1987-88. The third phase was evidenced during 1973-74, 1980-81 and post-reform 1994-95. The fourth phase was represented by 1988-89 prior to reforms and the post reform years from 1995-96 to 1997-98 (Chart 4).

The monetary policy measures taken during these periods reflected the above challenges to the policy authorities. In this regard, the foremost challenge to the monetary authorities was containing inflationary pressures in the economy as it was deemed harmful, both from growth and equity considerations [Patel 1979].15 Inflation control during the oil shock years and in the BoP crisis years was of paramount importance as these shocks impinged on an economy having surplus liquidity; hence monetary measures were highly contractionary and geared towards inflation control.16 The first oil shock of 1973-74 was triggered off by the war in the west Asia. Taking into account the relentless increase in prices since January 1973, the Reserve Bank raised both the bank rate and CRR in May 1973. The measures were aimed at moderating the rapid expansion of bank credit so that excessive demand pressures did not develop in the economy [Jagannathan1973]. Similarly, in the wake of domestic political uncertainties and a monsoon failure, prices began to gallop from July 1979.17 The matter was further compounded by the outbreak of the second oil crisis resulting in the quadrupling of international crude oil prices. The measures undertaken by the Reserve Bank, in this context, were aimed at restricting the flow of credit to the commercial sector. Accordingly, the level of refinance available to banks from the Reserve Bank was sharply curtailed and the interest rate on advances against commodities subject to selective credit controls was raised [RBI 2006]. In a similar vein, monetary tightening was introduced during 1988-89 to check the unbridled expansion of credit arising out of a large fiscal expansion. Moreover, the east Asian crisis of 1997-98 merited tightening of policy through increases in both the CRR and bank rate in order to contain the adverse fallout of contagion [Reddy 2000]. The episodes of strong contractionary measures are listed in Table 2.

While monetary tightening measures were introduced to stem inflationary pressures during the three decades under consideration, it is interesting to note that the genesis of inflation, however, has emanated from different sources across the decades. Illustratively, during the 1970s, inflation was mainly of the cost-push variety as inflationary pressures were triggered by supply shocks in the form of increasing oil prices and crop failure due to drought.

1 May 1973 1) Bank rate increased from 6 per cent to 7 per cent. 2) CRR raised from 3 per cent to 5 per cent. 3) Minimum net liquidity ratio raised to 39 per cent. 4) For one percentage point fall in the net liquidity ratio, borrowing

rate increased from 7 per cent to 8 per cent. Thereafter, for every fall of 1 percentage point in net liquidity ratio, borrowing rate will go up by 1 per cent to a maximum of 12 per cent.

5) Interest rate on advances should not be less than 10 per cent except on exempted categories.

2 Nov 1973 1) Maximum borrowing rate from the Reserve Bank raised from 12 per cent to 15 per cent.

2) The minimum net liquidity ratio will continue at 40 per cent and for every fall of 1 percentage point or fraction thereof in the ratio, the borrowing rate would go up 1 per cent over the bank rate.

3) The maximum borrowing rate of 15 per cent would be applicable to a net liquidity ratio level of below 33 per cent. 4) The collateral facility given to bank for borrowing against bills arising from their public sector food advances will be discontinued. 5) Small-scale industry and agriculture will be exempted from the minimum lending rate of 10 per cent. 6) Loans against deposits will be at rates not lower than 2 per cent above the rate payable on the deposits. 7) Maximum rates on all other export credit excepting on deferred payment will be stepped up from 7 to 8 per cent.

8) The present minimum rate of 8 per cent on bill finance will be fixed 1 per cent below the minimum lending rates for advance, i e, at 9per cent.

9) The minimum lending rates for commodity covered by selective credit control will be raised in most cases from 12 to 13 per cent. 10) The minimum margin on advances to the sugar industry will be raised.

3 April 1974 1) SLR raised from 32 to 33 per cent.

2) While export refinance will continue to be available, the quantum of refinance will be available entirely at the discretion of the RBI and will be dependent on bank’s incremental performance in export, pattern of deployment of credit and deposit mobilisation.

3) Full refinance on bank credit for food procurement operations in excess of an outstanding level of Rs 400 crore at a rate fixed by the RBI.

4) The total sanction bill rediscount limit is reduced to about 40 per cent of the existing level for the system as a whole.

5) The maximum rate of interest on export credit is increased from 8 to 9 per cent for all other category and from 6 to 7 per cent in the case of export and deferred payments.

6) Rate of interest on food procurement credit is raised from 8 ½ to 9 per cent per annum.

4 July 1974 1) Bank rate raised by 2 percentage points from 7 per cent to 9 per cent. 2) Rate of interest on deposits over 5 years raised to 10 per cent. 3) Minimum lending rate raised from 11 per cent to 12.5 per cent. 4) Maximum rate of interest on export credit raised to 10.5 per cent

from 9 per cent. 5) Rate of interest on public food procurement credit raised from 9 per cent to 11 per cent.

5 May 1981 1) CRR raised from 6 to 7 per cent of NDTL. 2) Minimum interest rates on discretionary refinance raised from 11 per cent to 14 per cent. 3) Rate on rediscounting of bills raised from 11 to 14 per cent.

6 July 1981 1) Bank rate raised from 9 per cent to 10 per cent. 2) Increase in CRR preponed. 3) SLR raised from 34 per cent to 35 per cent. 4) Minimum margins of select commodities under selective credit

control raised by 10 basis points.

7 March 1989 1) CRR prescription of banks rationalised and CRR on overall NDTL

raised to 15 per cent. 2) Base dates for refinance on export credits advanced to 1987. 3) Interest rates on refinance on 182 days Treasury Bills raised from

10.2 to 10.7 percent. 4) Minimum margin on selective items are reduced under selective

credit control. 5) Interest rate ceiling on call notice money market is withdrawn. 6) Rate of interest on term deposits is increased.

8 July 1991 1) Bank rate raised from 10 per cent to 11 per cent. 2) Deposit rates of all maturity raised by 1 percentage points. 3) Interest rates on refinance increased.

9 October 1991 1) Bank rate raised by 1 percentage point. 2) Lending rates of scheduled commercial banks increased by 1.5

percentage points. 3) Deposits rates of banks raised by 1-2 per cent for various maturity. 4) Rate of interest on export credit increased. 5) Withdrawal of refinance facility on food credit. 6) Reduction in interest rate on eligible cash balances of CRR.

10 January 1998 1) Bank rate raised from 9 per cent to 11 per cent. 2) CRR raised from 10.0 per cent to 10.5 per cent. 3) Export credit refinance reduced from 100 per cent to 50 per cent. 4) Reduction in general refinance facility. 5) Interest rate surcharge increased on bank credit for imports.

Economic and Political Weekly March 31, 2007 Besides the regular instruments of monetary tightening such as the CRR and bank rate, the Reserve Bank also took recourse to selective credit control measures in order to restrict credit flow to sensitive commodities during this decade. During the 1980s, however, inflation was largely demand-pull as rising fiscal deficits, which were financed through greater monetisation, boosted aggregate demand. Consequently, the monetary impact of greater monetisation was sought to be neutralised by raising the CRR while unbridled credit expansion in the commercial sector was checked through the imposition of a higher SLR. Inflation during the mid-1990s continued to be demand driven but the source of liquidity overhang was a large increase in capital inflows, which supplanted monetisation of deficits as the primary driver of liquidity expansion. As a result, the RBI took greater recourse to OMO in mopping up liquidity from the system besides raising the CRR. Thus, the choice of and emphasis on a particular monetary policy instrument has varied across the decades, particularly, in the context of inflation emanating from different sources of accretion to liquidity.

Prior to financial sector reforms, the Indian economy was characterised by fiscal dominance where monetary policy played a subservient role and the main impetus to growth was provided by an expansionary fiscal policy [Mohan 2005]. Post reforms, however, with the gradual deregulation of financial markets and proliferation of financial instruments, monetary policy has played a more proactive role in facilitating and nurturing the growth process. Not surprisingly, therefore, the strongly expansionary measures were concentrated in the post-reform phase (Table 3).18 In order to revive the economy from the crisis of 1991-92, several expansionary measures were initiated during 1992-93 and 1993-94, which resulted in a consecutive high growth phase between 1994-95 and 1996-97. Similarly, measures were initiated to dismantle the administered structure of interest rates in the October policy of 1994 and deregulate the credit market, which resulted in a high credit growth of about 22 per cent in 1994-95. Finally, the 1997 April policy, coined, as the “big bang” credit policy by the electronic and print media, was largely influential in pushing the agenda of financial market reform by reactivating the bank rate and announcing a phased reduction in the CRR. This momentum was maintained in the subsequent October policy through further reductions in the CRR and bank rate and rationalisation of the SLR.

Besides these strong contractionary/expansionary measures, the Reserve Bank has initiated several measures from time-totime in order to counter episodes of disturbances or correct anomalies in the pursuit of the traditional growth-inflation objectives. These measures did not necessarily reflect a shift in monetary policy stance arising out of a change in policy priorities but have been more in the nature of regular central banking operations. In this regard, while tightening measures often reflected sector specific squeezing of liquidity, monetary easing measures were supportive of the process of institutional, instrumental and market reform. Such episodes of mild contraction/ expansion are listed in Table 4.

Derivation of the Index

The index has been prepared by interpreting the objectives of monetary policy, the rationale of policy measures and the measures per se obtained from the various circulars on monetary and credit policy from qualitative terms to quantitative numbers. Besides the bi-annual policy statements, we have also taken into account the various measures that were taken throughout the year. We have chosen a scale of five (-2, -1, 0, 1, 2) representation, which allows capturing the transition process because policy circulars have enumerated gradual shifts in stance, i e, from mild contraction/expansion to strong contraction/expansion. The index ranges from –2 through 2, with a value of –2 being indicative of a strong policy emphasis on monetary control and a value of 2 reflective of the policy authorities intent on monetary expansion. This classification scheme has been employed because the policy statements clarified the policy objectives and rationale in terms of its prospective impact on monetary expansion and, hence, inflation and economic activity. Further, while policy shift towards growth promotion was usually accompanied

Table 3: Dates of Strong Expansionary Monetary Measures

No Dates Measures
1 October 1992 1) Reduction in SLR by 0.75 percentage points.
2) Release of impounded cash balances under incremental
CRR.
3) Reduction in effective rate of interest on eligible cash
balances of CRR.
4) Reduction in export credit refinance limits.
5) Reduction by 1 percentage points in lending and deposit
rates of banks.
6) Exemption of FCON from CRR and SLR.
7) Introduction of refinance on government securities.
2 April 1993 1) SLR and CRR reduced by 1 percentage point.
2) Reduction in lending rates of scheduled commercial banks.
3) Reduction in deposits rates of NRE accounts.
4) Reduction on banks advances against shares and
debentures.
5) Minimum margins under selective credit control reduced by
15 percentage points.
3 October 1994 1) Reduction in lending rates. 2) Reduction in saving deposits rates of banks.
3) Reduction in interest rates on NRE deposits. 4) Reduction in SLR requirements.
5) Withdrawal of ceiling on term loans.
4 April 1997 1) Bank rate reduced by 1 percentage point.
2) Inter-bank liabilities exempted from CRR and SLR. 3) Ceiling on domestic term deposit rates and NRE accounts
of bank rate minus 2 percentage points. 5) Ceiling on interest rates on post-shipment rupee exports.
6) Introduction of a general refinance facility. 7) General line of credit to NABARD increased.
5 October 1997 1) Bank rate reduced by 1 per cent. 2) CRR reduced by 2 per cent.
3) Interest on eligible balances of CRR increased to 4 per cent. 4) SLR reduced to the statutory minimum of 25 per cent.
5) Interest on domestic term deposits of 30 days and above deregulated.
6) Ceiling imposed on lending rate. 7) Interest on pre-shipment rupee export credit reduced.
8) Partial liberalisation of capital account.

Table 4: Dates of Mild Contractionary and Expansionary Monetary Measures

Nature of Dates Monetary Policy

Mild contraction 1973:07, 1973:09, 1975:05, 1976:08, 1976:11, 1977:01, 1978:11, 1979:03, 1979:08, 1979:09, 1980:03, 1980:07, 1981:10, 1983:08, 1983:11, 1984:01, 1984:04, 1985:04, 1987:02, 1987:10, 1987:12, 1988:04, 1988:07, 1989:10, 1990:04, 1991:04, 1991:05, 1994:05, 1995:01, 1997:12

Mild expansion 1974:10, 1976:03, 1976:05, 1977:05, 1977:12, 1978:03, 1978:05, 1982:02, 1982:03, 1982:04, 1982:06, 1982:07, 1982:10, 1983:02, 1985:10, 1986:10, 1992:02, 1993:01, 1993:02, 1993:06, 1993:09, 1993:10, 1994:02, 1995:10, 1995:11, 1995:12, 1996:01, 1996:04, 1996:07, 1996:10, 1997:06, 1998:03

Note: Dates are indicated in “year: month” format. Thus, 1974:10 denotes October 1974.

by the lowering of reserve requirements, reductions in the bank rate and SLR, deregulation of interest rates, etc, the contrary was often enacted to check monetary expansion. Any single measure, either expansionary or contractionary, and of smaller magnitude are indicated by 1 and -1 respectively. Finally, 0 is assigned to neutral policy, which can either result from policy inaction in any period or by two measures in the opposite direction, one countervailing the other. Accordingly, the policies undertaken during the period 1973-74 to 1997-98, on a monthly basis, are mapped and presented in Table 5.

IV Attributes of Proposed Monetary Measure

What does the constructed monetary policy measure look like? To begin with, it may be noted that it is a monthly incremental measure. In other words, it measures whether (corresponding to the previous month) there has been any change in the elements of the vector called “monetary policy”. Table 6 presents the basic descriptive statistics of the monetary measure, while the frequency distribution is given in Table 7. Of the 25 years spanning 300 months, as per our proposed monetary measure, monetary policy has been contractionary on 10 occasions whereas it has been expansionary on five occasions.

How is the proposed monetary measure related to standard monetary and interest rate variables; viz, output and prices? Table 8 reports the correlation coefficient of the proposed measure with broad money (M3), reserve money (RM), bank reserves (BR) and call money rate (r). In general, the correlations are found to be low (considering the fact that there are 300 observations)

– both in levels as well as in first differences.

What is the performance of this measure with respect to the two basic target variables for monetary policy? Towards this end, we employ a basic three variable standard VAR model comprising of output (Y), prices (P) and the monetary policy index (called “measure”), of the following form:

A look at the impulse responses, over a two-year period, reveals two stylised facts. First, a shock in “measure” has a negative impact on prices – the impact is found to be quite sharp. Second, the impact on output seems to be rather insignificant. Since an increase in “measure” would tantamount to an easing of

Table 5: A Narrative Index of Monetary Policy Stance for India

Apr May June July Aug Sept Oct Nov Dec Jan Feb Mar
1973-74 0 -2 0 -1 0 -1 0 -2 0 0 0 0
1974-75 -2 0 0 -2 0 0 1 0 0 0 0 0
1975-76 0 -1 0 0 0 0 0 0 0 0 0 1
1976-77 0 1 0 0 -1 0 0 -1 0 -1 0 0
1977-78 0 1 0 0 0 0 0 0 1 0 0 1
1978-79 0 1 0 0 0 0 0 -1 0 0 0 -1
1979-80 0 0 0 0 -1 -1 0 0 0 0 0 -1
1980-81 0 0 0 -1 0 0 0 0 0 0 0 0
1981-82 0 -2 0 -2 0 0 -1 0 0 0 1 1
1992-83 1 0 1 1 0 0 1 0 0 0 1 0
1983-84 0 0 0 0 -1 0 0 -1 0 -1 0 0
1984-85 -1 0 0 0 0 0 0 0 0 0 0 0
1985-86 -1 0 0 0 0 0 1 0 0 0 0 0
1986-87 0 0 0 0 0 0 1 0 0 0 -1 0
1987-88 0 0 0 0 0 0 -1 0 -1 0 0 0
1988-89 -1 0 0 -1 0 0 0 0 0 0 0 -2
1989-90 0 0 0 0 0 0 -1 0 0 0 0 0
1990-91 -1 0 0 0 0 0 0 0 0 0 0 0
1991-92 -1 -1 0 -2 0 0 -2 0 0 0 1 0
1992-93 0 0 0 0 0 0 2 0 0 1 1 0
1993-94 2 0 1 0 0 1 1 0 0 0 1 0
1994-95 0 -1 0 0 0 0 2 0 0 -1 0 0
1995-96 0 0 0 0 0 0 1 1 1 1 0 0
1996-97 1 0 0 1 0 0 1 0 0 0 0 0
1997-98 2 0 1 0 0 0 2 0 -1 -2 0 1

Note: A value of -2 is indicative of a strong contractionary policy, -1 is mild contractionary while a value of 1 represents mild and 2 reflects strong expansionary policy, respectively. A value of 0 reflects neutral policy of no change.

Table 6: Descriptive Statistic of the Measure of Monetary Policy

Statistic Values
Mean -0.0267
Standard deviation 0.6382
Skewness -0.3641
Kurtosis 6.0370

iii

⎡⎤

b b b

⎡⎡⎤

⎤⎡

⎡⎤⎤

a

1

measure

measure e

1t11

12 iii 13 t

i

t

+

N

∑=

i1

Jarque-Bera statistics 121.916

Probability 0.0000

Observations 300

⎢ ⎢ ⎢⎣⎥ ⎥ ⎥⎦

⎢ ⎢ ⎢⎣

⎢ ⎢ ⎢⎣=

⎥ ⎥ ⎥⎦

⎥ ⎥ ⎥⎦⎢ ⎢ ⎢⎣

⎢ ⎢ ⎢⎣

+⎥ ⎥ ⎥⎦

⎥ ⎥ ⎥⎦

Yt

Pt

b b b Yt

a

e

2

21 22 23 i 2t

iii

b b b Pt

a

3

e

31 32 33 i 3t

where Yt, and Pt denote real economic activity and prices, respectively.19 Since the model is estimated using monthly data, we include 11 monthly dummies to take care of the seasonal effects as deterministic (exogenous) variables.

Since for a greater part of the period, the standard output indicator in India, namely GDP, is only available at a yearly interval, we took the monthly index of industrial production (IIP) as the activity variable. As far as prices are concerned, we use the wholesale price index (WPI).20 The VAR has been run over the period spanning April 1974 to March 1998.

How do the impulse responses look in the VAR model? Given its discrete nature, a standard deviation shock in “measure” ceases to be econometrically meaningful. Hence, instead of the orthogonalised (Choleski) impulse responses to a unit standard deviation shock, we have considered the impulse responses based on non-normalised residual in terms of setting the impulses to one unit of the residuals. Thus, we ignored the units of measurement and did not do any transformation.21 Chart 5 reports these impulse responses along with analytical standard error bands (represented by the dotted lines).

Table 7: Frequency Distribution of the Measureof Monetary Stance

Value Count Per Cent

-2 10 3.3 -1 30 10.0 0 223 74.3 1 32 10.7

2 5 1.7 Total 300 100.0

Table 8: Correlation Coefficients of the Measure of Monetary Policy with Select Monetary Variables

Level* First Difference**

M3 0.209 -0.177 RM 0.208 -0.219 BR 0.200 -0.214 Call Rate -0.131 -0.188

Notes: *: All the variables are in levels. **: All the variables (excepting the measure of monetary policy) are in first difference.

monetary policy, the second result seems to be somewhat the veracity of the results through the generalised impulses, as counter-intuitive. Taken literally and assuming the unbiasedness introduced by Pesaran and Shin (1998), which constructs an of “measure”, could this be indicative of the limited impact that orthogonal set of innovations that does not depend on the VAR monetary policy could have had on the output front as against ordering.23 The results (exhibited in Chart 6) are broadly in the more potent performance in the inflation front? Lack of any consonance with those obtained earlier. Secondly, as the VAR structural model does not allow us to provide a definitive answer (Choleski) impulses are sensitive to ordering, we checked the to this query.22 correlation structure of the residuals from the VAR model. As To ascertain the robustness of the results, we first cross-checked the correlation coefficients turned out to be fairly low and

Chart 5: Impulse Responses in the VAR Model

Response to Non-factorised One Unit Innovations ± 2 SE

Response of measure to measure Response of measure to LYM Response of measure to LPM
4 44 44
0 00 00
-4 -4-4 -4-4
-8 -8-8 -8-8
-12 -12 -12 -12 -12
-16 -16 -16 -16 -16
-20 22 44 66 88 10 12 14 16 18 2010 12 14 16 18 20 2222 2424 -20 -20 2 2 4 4 6 6 8 8 10 12 14 16 18 20 22 24 10 12 14 16 18 20 22 24 -20 -20 22 44 66 88 10 12 14 16 18 2010 12 14 16 18 20 22 2422 24
1.6 R e sp o n se o f L Y M t o M E A S U R E Response of LYM to measure 1.61.6 R e sp o n se o f L Y M t o L Y MResponse of LYM to LYM 1.61.6 R e sp o n se o f L Y M t o L P MResponse of LYM to LPM
1.2 1.21.2 1.21.2
0.8 0.80.8 0.80.8
0.4 0.40.4 0.40.4
0.0 0.00.0 0.00.0
-0.4 -0.4 -0.4 -0.4 -0.4
-0.8 -0.8 -0.8 -0.8 -0.8
22 44 66 88 10 12 14 16 18 20 22 2410 12 14 16 18 20 22 24 22 44 66 88 10 12 14 16 18 20 22 2410 12 14 16 18 20 22 24 22 44 66 88 10 12 14 16 18 20 22 2410 12 14 16 18 20 22 24
2.0 R e s p on s e of LP M t o M E A S U R EResponse of LPM to measure 2.02.0 R e sp o n se o f L P M t o L Y MResponse of LPM to LYM 2.02.0 R e s p ons e o f LP M t o L P MResponse of LPM to LPM
1.6 1.61.6 1.61.6
1.2 1.21.2 1.21.2
0.8 0.80.8 0.80.8
0.4 0.40.4 0.40.4
0.0 0.00.0 0.00.0
-0.4 -0.4 -0.4 -0.4 -0.4
2 4 6 8 10 12 14 16 18 20 22 24 2 4 6 8 10 12 14 16 18 20 22 24 2 4 6 8 10 12 14 16 18 20 22 24
Chart 6: Generalised Impulse Responses in the VAR Model

Response to Generalised One SD Innovations ± 2 SE Response of measure to measure

Response of measure to LYM Response of measure to LPM.7.7

.7.7 .6

.7 .6.6

.6.6 .5

.5.5

.5.5 .4

.4.4

.4.4 .3

.3 .3

.3 .3

.2 .2

.2 .2 .2

.1.1

.1.1 .0

.1 .0.0

.0.0 -.1

-.1

-.1

-.1

-.1

-.2

-.2

-.2

-.2

-.2

2 4 6 81012141618202224 2 4 6 81012141618202224 2 4 6 81012141618202224

2 4 6 8 101214161820 2224 2 4 6 8 101214161820 2224 2 4 6 8 101214161820 2224

Response of LYM to LYMResponse ofLYM to MEASURE

Response of LYM to measure

Response of LYM to LYM Response of LYM to LPM

Response of LYM to LPM

.04 .04

.04 .04

.04 .03

.03 .03

.03

.03 .02

.02 .02

.02

.02 .01

.01 .01

.01

.01 .00

.00 .00

.00 .00

-.01

-.01

-.01

-.01

-.01

2 4 6 81012141618202224 2 4 6 81012141618202224 2 4 6 81012141618202224

2 4 6 8 101214161820 2224 2 4 6 8 1012141618202224 2 4 6 8 101214161820 2224

Response of LPM to M EASURE Response of LPM to LYM Response of LPM to LPM

Response of LPM to LYM Response of LPM to LPMResponse of LPM to measure

.015 .015

.015 .015

.015 .010

.010 .010

.010

.010 .005

.005 .005

.005 .005

.000 .000

.000 .000

.000 -.005

-.005

-.005

-.005

-.005 2 4 6 8 101214161820 2224 2 4 6 8 101214161820 2224 2 4 6 8 101214161820 2224

Economic and Political Weekly March 31, 2007

insignificant, it is unlikely that results would have been sensitive to the ordering.24

V Concluding Observations

The paper develops a measure of monetary policy in India spanning a period of 25 years based on the qualitative interpretation of monetary policy measures implemented during this period. The measure is consistent with theory in terms of its correlation with select monetary indicators. The impulse response from the VAR model seems to indicate that monetary policy measures were more successful in controlling inflation rather than in stimulating output. This may not be surprising given the repeated episodes of supply shocks and their consequent impact on inflation. Moreover, the results seem to be fairly robust as it is not sensitive to the ordering of variables and broadly consistent with results derived from generalised impulse responses. Overall, the results provide support for the narrative approach in terms of consistency of interpretation and its relation to monetary indicators for empirical analysis of monetary policy actions.

As a caveat, it may be noted that the period of study has been restricted to 1973-1998, largely governed by the monetary policy framework adopted during this period. During this period, monetary policy measures were largely concentrated in the bi-annual policy statements which coincided with seasonal credit cycles. Post 1998, under a multiple indicator approach, policy measures have been more intermittent and frequent, reflecting proactive monetary management in order to tide over greater challenges in a deregulated environment. In this regard, a useful exercise would be to gauge the shift in monetary policy stance in the pre-1998 and post-1998 period, employing the same measure, and its causal impact on the growth-inflation trade-off. This is an agenda for future research and beyond the scope of the present paper.

m

Email: ibhattacharyya@hotmail.com; raypartha@hotmail.com

Notes

[The views expressed in the article are those of the authors and not of the institution to which they belong. The authors are grateful to Sanjay Hansda,Indranil Sen Gupta and Saibal Ghosh for their comments on an earlier draft of the paper. The usual disclaimer applies].

1 This is not to imply that there was no such shift during 1973-98. Such

changes were, however, less drastic in nature as compared to post-1998

changes.

2 These dates are 1947:10, 1955:09, 1968:12, 1974:04, 1978:08 and 1979:10,

with a new date 1988:12, added in a second paper on this subject, Romer

and Romer (1994).

3 See Mohanty et al (1997) and Mohan (2005) for a discussion on the various

monetary policy instruments.

4 Several factors, viz, the limited scope of open market operations, the low

levels of refinance and the continued popularity of fixed deposits as a

mode of financial savings led to the adoption of the CRR as a major

instrument of monetary control during this period.

5 During this period, there was an incremental CRR as well; which however,

is not captured in the chart.

6 The Chakravarty Committee had suggested that the incremental CRR

should be used sparingly, for short durations and only in special

circumstances requiring drastic monetary control measures.

7 Historically, the objective of SLR was to impose some financial discipline

on banks and provide some protection to depositors [RBI 1985].

8 The efficacy of the bank rate depends essentially upon commercial banks’

reliance on the Reserve Bank for funds and its influence on other interest

rates [RBI 1996-97].

9 From March 29, 2004, all liquidity support drawn from the Reserve Bank in the form of refinance were linked to the reverse repo rate (nomenclature changed to repo rate since October 2004). This is, however, beyond the scope of the present paper.

10 Traditional refinancing of commercial banks is a direct instrument for affecting their reserves and thereby the monetary base. In this context, refinance was the major instrument in the hands of the Reserve Bank to counter other sources of primary money creation [Singh Shetty and Venkatachalam 1982].

11 In order to provide a suitable framework for evolving deposit rates fordifferent maturities, the Chakravarty Committee had suggested that the Reserve Bank determines the interest on one-year deposits.

12 Again, the Chakravarty Committee suggested a 3 percentage point spread as an acceptable level of spread to banks between the maximum rate on deposits and the minimum lending rate.

13 For a detailed discussion on monetary policy in India across decades,see Mohanty et al (1997).

14 For the purpose of this categorisation, inflation above 10 per cent has been classified as high inflation and, keeping in view the Hindu rate of growth, high growth years have been classified as those over and above 4 per cent.

15 Also, it was further argued that among the multiplicity of objectives of economic policy, price stability can perhaps best be achieved throughmonetary policy [Rangarajan 1993].

16 It was, however, noted that the “inside lag” of monetary policy seems to have been quite large in reacting to inflationary pressures [Joshi and Little 1996].

17 It may be recalled that the Morarji Desai government fell and Charan Singh became the prime minister on July 17, 1979.

18 See Jadhav et al (2003).

19 The lag on the basis of Akaike’s information criteria has been found to be two.

20 As both IIP and WPI had undergone base changes over the period, we spliced both the series using data for the common periods.

21 The responses are the moving average (MA) coefficients of the infiniteMA order Wold representation of the VAR.

22 We have also checked the forecast error variance decomposition of both output and prices. “Measure” has explained a larger proportion of the price variance than output variance.

23 The generalised impulse responses from an innovation to the j-th variable are derived by applying a variable specific Choleski factor computed withthe j-th variable at the top of the Choleski ordering.

24 The residual correlation matrix is as follows:

Measure Output Prices
Measure 1.00 0.06 -0.07
Output Prices 1.00 0.01 1.00

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