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January 2001

 

January 2001


ECONOMIC REFORMS, CAPITAL INFLOWS


AND MACRO ECONOMIC IMPACT IN INDIA


Indrani Chakraborty


Working Paper No. 311


2


ECONOMIC REFORMS, CAPITAL INFLOWS AND


MACRO ECONOMIC IMPACT IN INDIA


Indrani Chakraborty


Centre for Development Studies


Thiruvananthapuram


January 2001


This is a revised version of the paper presented in an open seminar at the


Centre for Development Studies. I am grateful to Prof. K.N.Raj and Dr.


D. Narayana for helpful comments. Thanks are due to Mr.K. A. Anilkumar


3


ABSTRACT


The study attempts to explain the effects of inflows of private


foreign capital on some major macroeconomic variables in India using


quarterly data for the period 1993-99. The analyses of trends in private


foreign capital inflows and some other variables indicate instability.


Whereas net inflows of private foreign capital (FINV), foreign currency


assets, wholesale price index, money supply, real and nominal effective


exchange rates and exports follow an I(1) process, current account deficit


is the only series that follows I(0). Cointegration test confirms the


presence of long-run equilibrium relationships between a few pairs of


variables. But the dependence of each I(1) variable on FINV invalidates


such cointegration except in two cases: cointegration exists between


foreign currency assets and money supply and between nominal effective


exchange rate and exports, even after controlling for FINV. The Granger


Causality Test shows unidirectional causality from FINV to nominal


effective exchange rates- both trade-based and export-based-, which raises


concern about the RBI strategy in the foreign exchange market. Finally,


instability in the trend of foreign currency assets could be partially


explained by the instability in FINV with some lagged effect.


JEL Classification: F21, F41, and C22


Keywords: Private foreign capital, economic reforms, instability, India


4


Introduction


Deregulation of private foreign investment in India started in 1993


in the form of partial liberalization of the capital account. Outflows of


capital by the Indian residents remained strictly controlled, whereas


inflows and outflows of capital by non-residents were partially


deregulated. These changes in policy framework not only led to a surge


in inflows of private foreign capital but also contributed to a significant


change in the form in which private capital was coming in. External


commercial borrowing which was the major source of private foreign


capital inflows during the eighties became less important during the


nineties. In the nineties, the predominant role of the portfolio investment


followed by the foreign direct investment (FDI) has been envisaged1 .


Estimates of portfolio investment through foreign institutional investors


(FIIs) and global depository receipts (GDRs) are $9 billion and $6 billion,


respectively, covering the period 1993-98 (Ahluwalia, 1999). Distinct


changes in the guidelines for portfolio investment and FDI vis-à-vis


external commercial borrowing during August and September of 1992


certainly encouraged the former categories (R.B.I, 1992). A look at some


of the items in the new guidelines will make it clear:


a) Use of external commercial borrowing would be prioritised to


the infrastructure and core sector export-oriented and importsubstitution


units and also medium-sized / small-scale units.


Infrastructure or core sector included power, oil exploration and


refining, telecommunication, fertilizer and transport.


5


b) External commercial loans could be raised only for meeting


foreign exchange cost of capital investment. Expenditure on


working capital could not be met by external commercial


borrowing. In addition, all external commercial borrowing should


have a minimum final maturity period of five years.


c) Priority will be given to those proposals for external commercial


borrowing which will be used for total export productions, which


will be self-liquidating i.e. the principal installments and interest


would be entirely serviced out of export-earning and for which


no security would be provided by a commercial bank/financial


institution in India.


d) Foreign institutional investors (FII) would be welcome to invest


in all the securities tradable in the primary and the secondary


markets. There will be no restriction on the volume of investment


by the FIIs. Moreover, there would be no lock-in period for the


proposed investments by the FIIs.


e) FIIs would be given tax-benefits. Concessional tax rate of 20 per


cent was proposed for the dividend and interest income. In


addition, a tax rate of 10 per cent on long-term capital gains (more


than one year) and 30 per cent on short-term capital gain were


proposed.


f) In connection with the FDI, the limit of 40 per cent of foreign


shareholdings imposed by the Foreign Exchange Regulation Act


(FERA) of 1973 on the Indian companies was raised to 51 per


cent in July 1991. The approval of foreign direct investment in


the priority industries where high technology was thought to be


needed was made automatic. Criteria for approval were also made


liberalised, in general.


6


The trend of private foreign capital depicted in Fig.1 shows


that portfolio investment exceeded the other two sources


between 1993-94 and 1996-97. However, the trend of


portfolio investment exhibits instability. On the other hand,


the flow of FDI appears to be increasing steadily over the


years. External commercial borrowing, the only major


source of private foreign capital prior to reform, reached


its all time trough in 1992-93 when it became negative.


Afterwards it followed an upward trend and it exceeded


the other two forms of private foreign capital during the


last two years i.e., 1997-98 and 1998-99.


Fig. 1. Net Inflows of Foreign Capital


Year


Net Inflows of foreign capital in Rs. crores


ComB


Total


PORTF


FDI


.





Foreign direct investment (FDI)


Portfolio investment (PORTF)


External commercial borrowing (CoMB)


Total


7


A brief account of the net annual capital inflow in India since the


beginning of the 90’s is presented in Table 1. It reveals that net inflow of


private foreign capital increased from Rs.605.2 crores (0.86% of GDP)


in 1992-93, the year just prior to the deregulation of private foreign


investment, to Rs.15187.5 crores (1.87% of GDP) in 1993-94. Easing of


restrictions on inflows of private foreign capital has also led to its


increasing share in gross domestic capital formation from 2.85% in 1990-


91 to 8.05% in 1993-94 and 9.3% in 1997-98. In terms of net capital


account, private inflows of foreign capital accounted for 53.58% and


79.01% in 1993-94 and 1998-99, respectively, whereas the same stood


at only 21.16% in 1985-86.


Some important changes may also be observed in the exchange


rate policy since July 1991. A significant downward adjustment in the


exchange rate took place in July 1991. On July 1, 1991, exchange rate of


rupee per unit of dollar was devalued from Rs.21.40 to Rs.23.25 and on


July 3 to Rs.26. Since March 1992, dual exchange rate system was


instituted. It was characterised by the coexistence of the official exchange


rate determined by the RBI and the market rate determined in the interbank


foreign exchange market. Since March 1993, exchange rate of rupee


was left to be determined by the market forces. In March 1993, the


exchange rate of rupee per unit of dollar became Rs.31.40 and it remained


steady for over two years at that level. But since the middle of September


1995 there were periodic speculative pressures on the exchange rate which


called for active intervention by the Reserve Bank of India in the foreign


exchange market. In the floating exchange rate regime, the predominant


objective of India’s exchange rate policy was to maintain a stable REER


in order to prevent an erosion in the incentives available to exporters. To


meet this objective, it was announced that, "RBI stands ready to intervene


to maintain orderly market condition and to curb excessive speculation"


(G.O.I, 1995-96). The period after 1993, therefore, witnessed


8


interventions by the Reserve Bank of India several times to reduce the


excess volatility of the exchange rates.


Given these aspects of the reform programme, it is pertinent to


analyse the macroeconomic responses in the post-1993 period in India.


Importance of this issue can be traced back to different macroeconomic


consequences of liberalization of foreign capital in the countries of South-


East and East Asia vis-a-vis Latin America. Various studies observed


that in the post liberalization period in countries viz., Thailand, Indonesia,


Malaysia and Chile both investment and exports grew without any


substantial appreciation in real exchange rate. On the other hand,


Argentina, Mexico, Brazil, Columbia, Korea and Philippines experienced


a strong appreciation of their real exchange rate. In contrast to this


difference, it was further noted that in all these countries in both the


regions current account deficits and inflation increased (Khan and


Reinhart, 1995, World Bank, 1995 and Corbo and Hernandez, 1996). A


comparative picture of these two regions in terms of selected


macroeconomic indicators in the period of increasing inflow of foreign


capital is presented in Table 2.


The objective of this study is to observe and analyse the dynamics


of some selected macroeconomic indicators in relation to the inflows of


private foreign capital as a consequence of economic reforms in India.


The paper is organized as follows: section I discusses the trends in some


macroeconomic indicators and tries to explain them. Section II reports


the findings of some econometric analyses based on quarterly data from


1993.II to 1999.II. Finally we conclude in section III.


I. Trend behaviour of some Macroeconomic Indicators in relation to


Inflows of Private Foreign Capital in India with an Analytical Overview:


This section begins with the question: how might liberalization of


capital inflows affect macroeconomic aggregates in an open economy?


9


An economy seeking to attract foreign capital can experience different


macroeconomic consequences under different exchange rate regimes.


In what follows we consider the macroeconomic consequences under a


floating exchange rate regime and the discussion follows the arguments


available in the existing literature.


In a floating exchange rate regime, an increase in capital inflows


will lead to an appreciation of nominal exchange rate because of an excess


supply of foreign exchange. This appreciation under a floating exchange


rate regime generally leads to overshooting of nominal as well as real


exchange rate. This happens because as the financial market adjusts at a


faster rate than the goods market, surge of capital inflows may lead to


excessive appreciation of nominal and real exchange rates above their


equilibrium levels (Rangarajan, 1998). Overshooting of nominal


exchange rate will, in effect, ration the sale of foreign exchange for current


transactions. This will affect exports adversely because the consequence


will be similar to imposing an implicit tax on exports (Sachs, 1989).


Such a rationing, on the other hand, is likely to lead to the development


of a black market for foreign exchange. The rationing of foreign exchange


will lower the relative price of exports and bias production away from


exports. At the same time, imports may have increased due to the


appreciation of real exchange rate which, in turn, will have adverse effect


on the current account balance. In consequence expected depreciation


will generate pressure which will lead to excessive depreciation of


nominal exchange rate with some lag. This tendency of instability in


nominal exchange rate may result in a loss of confidence on the part of


the foreign institutional investors. Such adverse effects due to the


instability of the exchange rate may lead to a system of "managed float".


Under this system, the central bank intervenes in the foreign exchange


market to reduce the excess volatility in the exchange rate so that the


equilibrium is restored. There may be two types of central bank


intervention.


10


In the first type the central bank purchases foreign exchange against


the domestic currency. This will help control further appreciation of the


nominal exchange rate. On the other side, net foreign assets being one


component of reserve money, such intervention leads to the growth of


high-powered money and consequently increases the money supply in


the economy. With no change in the demand for money this will lead to


an increase in domestic absorption. Increased domestic absorption may


come through increased spending on either investment or consumption


or both. This increased spending will go to both the categories of goods


viz., tradables and nontradables. Increased expenditure on tradables will


increase the size of trade deficit. On the other hand, increased spending


on nontradables will increase the relative price of nontradables to


tradables. This, in effect, will have two consequences. One is the


reallocation of factors of production towards nontradable sector due to


the increase in its relative price. So it is interesting to observe that while


a large nontradable sector emerges, the consumer expenditure switches


from nontradables to tradables (Corbo and Henandez, 1996). The other


consequence is the effect on the real exchange rate. However, the direction


of change will depend on the rate of inflation relative to the initial


depreciation of the nominal exchange rate. If real exchange rate


appreciates there will be further deterioration of the current account


balance which will require further intervention by the central bank in


the form of buying foreign exchange. On the other hand, if real exchange


rate depreciates that may help improve the current account balance. But


depreciation of real exchange rate may also fail to produce all the desirable


results. Because too much depreciation may lead to reversal of capital


inflows simultaneously with the other effect. Hence, that will require


further intervention by the central bank but in the form of selling foreign


exchange so that nominal exchange rate appreciates to some extent. Such


intervention by the central bank will continue till a new "equilibrium" is


reached for the exchange rate.


11


The second type of central bank intervention is known as "sterilized


intervention". In this process the central bank buys foreign exchange in


exchange of government securities. It helps to curb the growth of money


supply in the economy and hence there will be no increase in domestic


absorption. In consequence, there will be no increase in the current


account deficit too. But it creates an upward pressure on the domestic


interest rate and hence increase fiscal deficits (Joshi and Little, 1994).


Further an increase in the interest rate may attract more foreign capital


which would aggravate the problem of management of capital inflows.


Another limitation of sterilized intervention is that the central bank has


to incur some costs while using this instrument. The associated cost will


be equivalent to the difference between the interest to be paid by the


central bank on government securities and the return enjoyed by the


central bank on holding foreign reserves. This will happen because


sterilized intervention by the central bank in the context of liberalization


of private foreign capital will lead to an increase in interest rate for


government securities2 .


In the light of the above discussion, let us now analyse the trend


behaviour of some macroeconomic indicators in India. For the trend


Fig. 2. Foreign Exchange Reserve


Year


Foreign exchange reserve in US $ million


12


analysis we have chosen the period 1990-91 to 1998-99 which will help


to form a comparative picture of the post-reform period and the period


just prior to the reform.


The foreign exchange reserve in India has increased considerably


since the initiation of economic reforms (Fig.2). The reserve has gone


up by US $27286 million between 1990-91 and 1998-99. Although it


was steadily increasing since 1991-92, the volume was not quite high


during the first three years. The reserve had started to peak up since


1993-94. It happened mainly because of intervention by RBI against the


surge of capital inflows. Initially RBI followed "sterilized intervention".


But since the treasury bill market was not properly developed this process


could not be continued for a longer time. During the later period


intervention by RBI was mostly through purchase of foreign currency


for domestic currency (Reddy, 1999, Rangarajan, 1998). Consequent


upon the increase in foreign currency assets due to RBI intervention in


the foreign exchange market, there was a rapid growth in money supply


in the post-reform period (Fig.3 and Table 4).


Fig. 3. Money Supply (M3)


Year


Money supply in Rs. crores


13


Let us now consider if the increase in money supply led to an


increased domestic spending in the post-1993 period. Figure 4 shows


that investment as a percentage of GDP follows an upward trend since


1993-94 and continued till 1997-98 when the level of investment was


much higher than that during the two years prior to 1993-94. The same


figure also reveals one of the important features in the post-reform period,


that is, a sharp increase in the private sector investment. However, this


achievement should not be attributed entirely to the liberalization of


capital inflows because some other reform measures have also contributed


towards this end. These reform measures include relaxation of restrictions


on industrial licensing and reduction of tariff on imports of capital goods


(Athukorala and Sen, 1995). Consumption expenditure as a percentage


of GDP, on the other hand, does not exhibit any upward rising trend in


general, but sharp increases are observed during the last two years (Fig.5).


Total consumption expenditure, combining both private and public,


Fig. 4. Savings and investment


Savings and investment as a % of GDP


Year


.




Gross domestic savings (GDMSAV)


(Total) Gross domestic cap form (GDMC)


(Private) Gross domestic cap form (GDMC)


(Public) Gross domestic cap form (GDMC)


Total GDMC


GDMSAV


Private GDMC


Private GDMC


14


increased sharply in 1997-98 to 75.8% of GDP from 67.9% of GDP in


1996-97. Interestingly enough, private consumption expenditure steadily


declined after economic reform until 1996-97 and then increased during


the last two years (Table 3). While disaggregated data on consumption


expenditure are not available, data on different categories of imports


suggest that the rising expenditure on consumption was not heavily driven


by manufactured imports (Table 3). In contrast to this it may be noted


that the Latin American countries experienced a consumption boom


mainly driven by imports of consumer durables in the post-liberalization


period. The period since 1993-94 also witnessed an increase in real GDP.


Although the growth in real GDP has reached its highest value in 1996-


97, it was varying between 7.2% and 7.5% during the period 1994-95 to


1996-97 (Table 3). However, it started to decline sharply since 1997-98.


Fig. 5. Consumption Expenditures


Year


Consumption expenditure as a % of GDP


.




(Total) Consumption Exp. As % of GDP


(Private) Consumption Exp. As % of GDP


(Public) Consumption Exp. As % of GDP Public


Total


Private


Public


15


Trend behaviour of savings as a percentage of GDP was almost similar


to that in investment except the fact that the gap between savings and


investment was widening since 1993-94 (Fig.4).


Trend behaviour of inflation is reported in Fig.6. Increased money


supply led to a rise in the inflationary pressure during the initial years


after reform viz. between 1990-91 and 1992-93. Due to the policy of


targetting inflation stabilization, however, it had been possible to keep


inflation below double digit level since 1993-94 excepting the year 1994-


95. Nominal effective exchange rate (NEER) and real effective exchange


rate (REER), (both export-based and trade-based) reveal a declining trend


since 1990-91 and it appears that the nominal effective exchange rate


depreciated at a faster rate than the real effective exchange rate (Fig.7).


Prior to 1993-94, it had been made possible by the devaluation of nominal


exchange rate of the rupee twice in July 1991 and by containing inflation


within a stable limit. Even after the liberalization of capital inflows since


1993-94, nominal effective exchange rate did not appreciate mainly


because of the direct intervention by the Reserve Bank of India in the


Fig. 6. Inflation


Year


Inflation as a percentage change in WPI


16


foreign exchange market, as discussed earlier. The real effective exchange


rate (REER), however, appreciated between 1993-94 and 1994-95


because of a rise in inflation in India in that period at a faster rate


compared to her trading partners. On the whole, movement of both the


Fig. 7. Nominal and Real Effective Exchange Rates (36 countrybased


weight)


Fig. 8. Current Account Deficits, Exports and Imports


Year


NEER, REER ( In SDR)


Year


Current account deficits, exports and imports as a % of GDP


REER (trd)


REER (ex)


NEER (trd)


NEER (ex)


. REER (ex) REER (trd) NEER (ex) NEER (trd)


Imports


Exports


CAD





CAD


Exp


Imp


17


indices of exchange rate in the downward direction during the entire


period 1990-91 to 1998-99 indicates that the policy of targetting REER


by adjusting NEER seems to have been partly successful during the 1990s.


Depreciation of REER seems to have improved the external trade


competitiveness because, it appears from Fig.8 that exports follow an


increasing trend since 1990-91. Imports as a percentage of GDP, on the


other hand, declined initially to 7.7% in 1991-92 from 8.1% in 1990-91


and started to increase thereafter. In relative terms, imports increased at


a faster rate than exports particularly in two years viz., from 1991-92 to


1992-93 and from 1994-95 to 1995-96. Hence, there were sharp increases


in the current account deficits during these two periods. If we look at


Fig.4 it is visible that, during these two periods there were sharp increases


in investment relative to savings too. Despite some fluctuations, the


overall trend in the current account deficit appears to be declining (Fig.8).


Thus, unlike some of the Latin American countries, the surge in the


inflows of capital, did not result in an increase in the current account


deficits in India.


II. Findings and Analysis


This section empirically analyses the effects of inflows of private


foreign capital on some of the major macroeconomic variables in India


using the quarterly data for the period 1993.II-1999.II. We try to


understand if the observed fluctuations in the time-series of some


macroeconomic variables viz., foreign currency assets3 , wholesale price


index, money supply, real and nominal effective exchange rates, exports


and current account deficit, as reported in the earlier section, can be


explained in relation to the fluctuations in the time series of inflows of


private foreign capital. Research done over the past decades shows that


before indulging in any econometric modelling using time-series data,


one should be concerned about the problem of non-stationarity or unit


18


root problem. Results from a regression exercise involving nonstationary


data is observed to be spurious (Granger and Newbold, 1974 and Granger,


1981). Therefore, the following empirical analysis is carried out in the


light of the recent developments in the time-series analysis.


In the first stage, stationarity of the series on each variable is


examined using both the Dickey-Fuller (DF) test and Augmented Dickey-


Fuller (ADF) test. The DF test is based on the following regression:


Yt = C + át + äYt-1 + åt…………….(1)


where C is a constant and t is the trend component.


The null hypothesis of unit root in Yt or nonstationarity of Yt is


rejected if ä is negative and statistically significant. If C and á failed


to be statistically significant we run the above regression dropping the


constant and trend. Critical values for ä in such a situation are noted to


be different from the one in equation (1) above.


For ADF test we include the lagged difference terms as regressors


in the above equation i.e.


k


Yt = C + át + äYt-1 + Ó âi Yt-i + åt ………………(2)


i =i


Following Enders (1995), to select the number of lagged


differenced terms we started with a relatively long lag length namely 15


in this case. Since the t -value for â at lag 15 was statistically insignificant


we estimated equation (2) with 14 lagged differenced terms and again


we tested for statistical significance of the t-value corresponding to â at


lag 14. This process is repeated until a lag is found which is statistically


significant. The number of lags chosen is reported below each equation


under ADF test.


19


The results are reported in Table 5. All the variables are transformed


to natural logarithm, except CAD which includes negative values. DF


test shows, for none of the variables at the level, the hypothesis of


nonstationarity can be rejected at 1% level of significance. However, it


is rejected at 5% level only for some of the variables viz., FINV, FNCA,


WPI, and CAD. But the DF test at the first difference of the series shows


that stationarity condition is uniformly supported at the 1% level of


significance by all the series except CAD. On the other hand, it follows


from the ADF test that none of the series, except CAD and NEERX are


stationary at the level. However, all the series except REERT, EXP and


CAD appear to be stationary at their first difference following ADF test.


Therefore, from these results it follows that all the series have unit roots


except CAD which is only stationary at the level.


The fact that all the series except CAD are I(1), or nonstationary


at the level, is important. What follows from the nonstationarity or the


presence of unit root in a time-series variable is that the time-path of the


variable is diverging from its equilibrium. The idea of convergence


towards equilibrium represents "stability" in the context of difference


equation, where lies the conceptual origin of the term "unit root". Thus


the presence of unit root indicates instability. However, if a set of


nonstationary variables is observed to be cointegrated then it follows


that the variables will come back to equilibrium in the long-run, even if


they drift away from equilibrium in the short-run. Hence it is necessary


to examine if there exists any cointegrating relationship between the set


of variables observed to have I(1) process before drawing any inference


regarding their instability.


Before going to the second stage, some diagnostic checking was


carried out to verify if the number of differenced lags was selected for


ADF test appropriately. The residual analysis for ADF regressions at the


20


first difference of each variable is reported in Table 6. The appropriate


number of lags in ADF regression should not reveal any significant


autocorrelation among the residuals or heteroscedasticity. Presence of


autocorrelation can be verified using Ljung-Box Q-statistic and Box-


Pierce Q-statistic whereas the presence of heteroscedasticity can be


verified using the ARCH test. Varying the number of lags in the residuals,


considering for example 2, 4 and 6 we observe that residuals exhibit no


autocorrelation for all the I(1) series except REERT and REERX. On


the other hand, ARCH test supports the assumption of homoscedasticity


for residuals of all the I(1) series4 .


In the second stage, tests for cointegration are applied to examine


if there exists any long-run equilibrium relationship between any pair of


I(1) variables. A number of series are said to be cointegrated if they are


nonstationary at the level and have same order of integration but there is


at least a linear combination of these variables which is stationary. We


have carried out cointegration test for each pair of variables having I(1)


series by making use of the methodology suggested by Engle and Granger


(1987). The results are reported in Table 7. We find, following either the


DF or ADF test results, that all the I(1) variables individually have


cointegrating relationship with FINV. In addition, cointegration is


observed between the following pairs of variables: FNCA and M3, M3


and WPI, WPI and REERX, WPI and REERT, REERX and EXP, REERT


and EXP, NEERX and EXP, NEERT and EXP. The results of


cointegration test in the latter sequence of relations suggest that the longrun


equilibrium relationship is restored between the following pairs of


variables viz, foreign currency assets and money supply, money supply


and inflation, inflation and real exchange rate, real exchange rate and


exports during the period 1993-99. These long-run relationships, based


on the observed data, reflect that the covariate fluctuations for the


variables in each pair are correlated over time. These relationships,


21


however, need to be analysed carefully, because such cointegration


relationship between variables in each pair breaks down in most of the


cases when we include FINV as a third variable. The results of the test


of cointegration, reported in Table 8, reveal that we fail to reject the null


hypothesis of no cointegration in all the cases but with two exceptions.


These two exceptional cases are (M3, FINV, FNCA) and (NEERX, FINV,


EXP) where these two sets are observed to be cointegrated following


the DF and ADF tests, respectively. The above results suggest that if we


control for the variable FINV, no long-run equilibrium relationship holds


between the variables for most of the above mentioned pairs of variables.


These findings are indicative of the fact that the increased inflows of


foreign capital in India since 1993 might account for the disturbances in


the equilibrium relationship between a number of macroeconomic


variables with a few exceptions. Exceptions, which follow from our study,


are between foreign currency assets and money supply and between


nominal effective exchange rate and exports.


The test of cointegration ignores the effect of the past values of


one variable on the current value of the other variable. So, finally, we


tried the Granger causality test to examine such possibilities. Since the


reliability of results of the Granger causality test depends on whether


the variables are stationary or not, we applied this test on the first


difference of the log transformed series which are reported to be


stationary. It is well-known that Granger causality test is sensitive to the


choice of lag length. To avoid this problem, as noted in Enders (1995)


we have applied Akaike information criterion to choose the optimum


lag length5 .


The results are reported in Table 9. Major observations are


discussed here. The most important observation is that FINV Granger


causes NEERT and NEERX. This has relevance for the exchange rate


22


policy. What it implies is that the past information on FINV improves


the predictability of NEERT and NEERX. As discussed earlier, RBI


intervened in the foreign exchange market with certain objectives since


1993, one of which was to "curb excessive speculation". The above


finding, however, challenges this objective. The direction of Granger


causality from FINV to NEERX and NEERT indicates that even if RBI


does not disclose its strategy of intervention a priori, it is possible to


speculate about the nominal exchange rate given the past information


on the inflows of private foreign capital. We further observe that FINV


Granger causes FNCA. This result suggests that, in the post reform period,


instability in the trend behaviour of foreign currency assets can be


explained partly by the instability in the trend behaviour of the inflows


of private foreign capital with some lagged effect. However, no causality


is observed between FINV and other variables having I(1) process.


III. Conclusion


A large volume of recent literature, while analysing the experiences


of Asian and Latin American countries, reveals that financial liberalization


led to severe macro-economic instability in several of those countries


and no unique pattern emerged in this respect. This study, therefore,


made a modest attempt to analyse the dynamics of some major


macroeconomic variables during the post-reform period in India. The


main focus of this study lies in analysing the behaviour of some selected


macro-economic indicators in relation to the surge in inflows of private


foreign capital in India since 1993, the year in which several major reform


programmes were initiated. A review of the analytical literature shows


that macroeconomic consequences of financial liberalization are the


results of the combined effect of monetary, fiscal as well as trade and


exchange rate policies followed by the government of a country. So,


there is no straightforward way of predicting the resulting macroeconomic


effects of financial liberalization in any country.


23


Major observations from the trend analysis, covering the period


1990-91 to 1998-99, are as follows: (a) Inflows of private foreign capital,


measured as the aggregates of foreign direct investment, portfolio


investment and external commercial borrowing, increased sharply since


1993-94. Although the volume of portfolio investment increased


enormously its trend exhibits instability. Flow of foreign direct


investment, on the other hand, increased steadily after the reforms. (b)


Foreign exchange reserve increased by a considerable amount which


indicates intervention of RBI against the surge of capital inflows.


Consequently, a rapid growth was observed in money supply. (c)


Investment as a percentage of GDP, private investment in particular,


followed an upward rising trend. Total consumption expenditure as a


percentage of GDP, on the other hand, did not reveal any clear pattern.


Private consumption expenditure, however, steadily declined. Real GDP


followed an increasing trend. (d) Inflationary pressure was mostly under


control except in the three years prior to 1993-94. Except in the two


years 1993-94 and 1994-95, real effective exchange rate (both exportbased


and trade-based) declined sharply. It had been made possible by


the downward adjustment of nominal effective exchange rate as well as


containment of inflation within a stable limit. (e) Unlike the Latin


American countries, current account deficits as a percentage of GDP did


not increase sharply excepting the two years 1992-93 and 1994-95.


Some econometric analyses based on quarterly data for the period


1993.II-1999.II reveal a number of interesting observations. It is found


that each of the following series viz., inflows of private foreign capital,


foreign currency assets, wholesale price index, money supply, real and


nominal effective exchange rates and exports follows an I(1) process


whereas the only series which follows an I(0) process is the current


account deficit. I(1) process indicates instability in the trend behaviour


of the variable under consideration. Tests for cointegration are applied


24


to examine if there exists any long-run equilibrium relationship between


any pair of I(1) variables. All the I(1) variables individually have


cointegrating relationship with FINV. In addition, cointegration is


observed between the following pairs of variables: FNCA and M3, M3


and WPI, WPI and REERX, WPI and REERT, REERX and EXP, REERT


and EXP, NEERX and EXP, NEERT and EXP. Further tests shows that


such cointegration relationship between variables in each pair breaks


down in most of the cases when we include FINV as a third variable.


The two exceptional cases where the cointegration relationship exists


even after controlling for FINV are foreign currency assets and money


supply and between nominal effective exchange rate and exports. Results


of the cointegration test are indicative of the fact that the increased inflows


of private foreign capital in India since 1993 might account for the


disturbances in the equilibrium relationship between a number of


macroeconomic variables with a few exceptions.


Finally, the Granger causality test is applied to examine if there is


any lagged effect of inflows of private foreign capital on the


macroeconomic variables under consideration. The direction of causality


from FINV to NEERX and NEERT has some relevance for the exchange


rate policy. It raises concern about the strategy of RBI intervention in


the foreign exchange market, one objective of which is to curb


speculation. Another finding from the causality test, that FINV Granger


causes FNCA, suggests that in the post reform period, instability in the


trend behaviour of foreign currency assets can be explained partly by


the instability in the trend behaviour of the inflows of private foreign


capital with some lagged effect.


25


Notes:


1. Private foreign capital may be classified into three categories viz., (a)


foreign direct investment (b) portfolio investment and (c) external


commercial borrowing. With the opening of the Indian stock market to


foreign institutional investors (FII) and allowing the private corporate


sector to issue global depository receipts (GDRs) in 1993, portfolio


investment entered as a new category into the private foreign investment


in India in the nineties. Nevertheless, liberalization of foreign capital in


the form of foreign direct investment can be traced back to the beginning


of 1980’s with a distinct change in the country’s foreign investment policy


(RBI, 1991). In 1980 a scheme was introduced to attract investments


from the oil-exporting developing countries. Under this scheme investors


from the Gulf region were allowed to invest in the equity capital of Indian


companies upto 40% of the total paid-up capital. Liberalised investment


facilities to non-resident Indians was another important policy decisions


taken during early 1980’s.


2. Prior to financial liberalization, interest rate on government securities


may be deliberately kept at a low level. But financial liberalization will


lead to a market-determined interest rate on government securities which


will be definitely higher than the earlier level.


3. Since foreign currency assets form the major component of foreign


exchange reserve that influence money supply in an open economy, we


have included foreign currency assets in our empirical analysis.


4. Absence of serial autocorrelation and heteroscedasticity in the estimated


residuals confirm that the power of ADF test is reliable. Absence of


heteoscedasticity is evident from the ARCH test results reported in Table


7. It justifies that Phillips-Perron test is not required under this


circumstance.


5. Some empirical studies which have applied this criterion include Samanta


and Mitra(1993),Masih and Masih(1994), Ghosh(1995).


26


References


Ahluwalia, Montek Singh (1999), "Reforming India’s Financial Sector:


An Overview, in James A. Hanson and Sanjay Kathuria (ed),


India: A Financial Sector for the Twenty-first Century, Oxford


University Press.


Athukorala, P. and Sen, K.(1995), "Economic Reforms and the Rate of


Savings in India", Economic and Political Weekly, 30 (35),


September 2.


Corbo Vittorio and Hernandez Leonardo (1996), "Macroeconomic


Adjustment to Capital Inflows: Lessons from Recent Latin


American and East Asian Experience", The World Bank Research


Observer, 11 (1), February.


Enders, Walter (1995), Applied Econometric Time Series, John Wiley &


Sons.


Engle, R.F. and Granger, C.W.J. (1987), "Cointegration and Error-


Correction: Representation, Estimation and Testing",


Econometrica, 55.


Ghosh, A.R. (1995), International Capital Mobility among the Major


Industrialised Countries: Too Little or Too Much?, Economic


Journal, 105 (428), January.


G.O.I. (1993-94 & 1995-96), Economic Survey.


Granger, C.W.J. (1981), "Some Properties of Time-Series Data and Their


Use in Econometric Model Specification", Journal of


Econometrics, 16.


Granger, C.W.J. and Newbold, P. (1974), "Spurious Regressions in


Econometrics", Journal of Econometrics, 2.


Joshi, Vijay and Little, I.M.D. (1994), India: Macroeconomics and


Political Economy, 1964-1991, Oxford University Press.


27


Joshi, Vijay and Little, I.M.D. (1998), India’s Economic Reforms: 1991-


2001, Oxford University Press.


Khan, Mohsin S. and Reinhart, Carmen M. (1995), "Macroeconomic


Management in APEC Economies: The Response to Capital Inflows"


in Khan, M.S. and Reinhart, C.M. (ed), Capital Flows in


the APEC Region, IMF Occasional Paper No. 122, March.


Masih, A.M. and Masih, R. (1994), "Temporal Causality between Money


and Prices in LDCs and the Error-Correction Approach: New


Evidence from India, Indian Economic Review, 29 (1).


Rangarajan, C. (1998), Indian Economy- Essays on Money and Finance,


UBSPD, New Delhi.


Reddy, Y.V. (1999), "Managing Capital Flows", Reserve Bank of India


Bulletin, January.


Reserve Bank of India (1991), Reserve Bank of India Bulletin, April.


Reserve Bank of India (1992), Reserve Bank of India Bulletin, November.


Sachs, Jeffrey D.(ed), (1989), Developing Country Debt and Economic


Performance, vol.2, University of Chicago Press.


Samanta, G.P. and Mitra, S. (1998), "Recent Divergence between Wholesale


and Consumer Prices in India – A Statistical Exploration",


RBI Occasional Papers, 19(4), December.


Sen, Kunal and Vaidya, Rajendra R. (1998)," India", in Fanelli, J.M. and


Medhora, Rohinton (ed), Financial reform in Developing Countries,


International Development Research Centre, Canada.


World Bank (1995), India: Recent Economic Developments and Prospects,


Washington, D.C.


28


Table 1. Net Annual Capital Flows (in Rs. Crores)


Year


FDI


Portfolio


External


Total Private


External


% share of net


Total


Total private


(1)


investment


Commercial


inflows of


Assistan


private capital


Capital


inflows of


(2)


borrowing


capital


(4)


inflows in


Account


capital as a %


(3)


(1) + (2) + (3)


GDP


(6)


of GDCF


(5)


(7)


1990-91


173.6


9.9


4034.4


4217.9


3964.9


0.78


12660.8


2.85


1991-92


329.8


9.9


3806.6


4146.3


7394.5


0.67


9812.5


2.86


1992-93


958.7


741.2


-1094.7


605.2


5749.7


0.86


12208.9


0.36


1993-94


1837.8


11444.8


1904.9


15187.5


5963.9


1.87


28341.9


8.05


1994-95


4216


11233.4


3237.8


18687.2


4798.3


1.93


27683


7.21


1995-96


7176.5


9097.1


4548


20821.6


3355.8


1.86


14271.1


6.85


1996-97


10094


11735.2


10003.6


31832.8


3998.3


2.5


39269.4


9.13


1997-98


13193.6


6766.6


14557.4


34517.6


3430.3


2.4


44532.8


9.3


1998-99


10387.7


-219.4


18557


28725.3


3485


1.85


36354


8.06


Notes:


1.


GDP at current price for the year 1997-98 is converted to 1980-81 prices. Basic data source is RBI (1999), Handbook of Statistics on Indian


Economy. Figures for 1988-99 in this column is obtained from C.S.O (1999), National Accounts Statistics.


2.


GDCF at current price is similarly computed and the source till 1997-98 is R.B.I (1999), as stated above. The same figure for 1998-99 is


computed on the basis that it is 23.4% of GDP, which information is collected from CMIE (June 2000), Monthly Review of the Indian


Economy.


3.


Source of "External Assistance" and "Total Capital Account" is R.B.I (1999), Handbook of Statistics on Indian Economy.


4.


Source of cols.(1), (2) and (3) is RBI Bulletin, various issues.


29


Table 2. Selected Macroeconomic Indicators


Country


Annual average from first year of inflows to 1994


Year in


% change


% change in


Capital


Current account


Real effective


which the


in real


prices


account


deficit as a


exchange


capital inflows


GDP


balance as


% of GDP


rate (%


began


a % of GDP


change)


AsiaIndonesia


1990


6.8


8.7


5.3


2.5


-6.2


Malaysia


1989


8.7


3.6


10.1


4.8


-3.9


Thailand


1988


10.0


5.0


9.4


6.0


1.9


Philippines


1992


2.3


8.5


8.3


4.2


20.9


Latin AmericaArgentina


1991


7.7


52.8


4.4


3.1


20.1


Mexico


1989


3.0


16.1


5.7


6.8


23.4


Brazil


1992


3.0


1941.9


2.0


0.2


57.9


Colombia


1991


4.1


25.6


2.8


4.2


37.1


Chile


1990


6.4


17.5


5.5


1.8


13.5


Source: Corbo and Hernandez (1996), International Financial Statistics (IMF) and World Economic Outlook (IMF)


30


Table 3 : Consumption Expenditure and Imports


Growth rate of Consumption Expenditure as a Manufacturing


RGDP % of GDP imports in total


imports(%)


Total Private Public


1990-91 5.4 73.6 62.1 11.5 12.88


1991-92 0.8 73.8 62.5 1.3 13.11


1992-93 5.3 72.8 61.7 11.1 12.64


1993-94 6 72.7 61.6 11.1 16.56


1994-95 7.2 70.2 59.7 10.5 17.75


1995-96 7.2 68.4 58 10.4 19.49


1996-97 7.5 67.9 57.5 10.3 15.83


1997-98 5 75.8 64.5 11.3 17.61


1998-99 3.8 75.9 63.6 12.3 15.02


Notes :


(i) Growth rate of real GDP in col.(1) represents percentage change


in GDP at factor cost (at constant prices) and the base is 1980-


81 =100


(ii) Source of cols. (1) to (4) is Monthly Review of the Indian


Economy, CMIE, various issues


(iii) Source of col.(5) is Foreign Trade Statistics of India, CMIE,


various issues


31


Table 4. Money Supply, Inflation and Exchange Rates


Money supply


Inflation


REER


REER


NEER


NEER


(M3)


(export based)


(trade-based)


(export-based)


(trade-based)


(Rs. Crores)


1990-91


265828


10.3


74.54


76.59


68.32


69.26


1991-92


277603


13.7


64.55


67.13


55.08


56.29


1992-93


366825


10


60.53


64.47


47.02


49.23


1993-94


378878


8.4


57.86


60.23


43.3


44.47


1994-95


452185


10.9


61.82


64.51


42.88


44.08


1995-96


530802


7.7


60.78


63.44


39.78


40.83


1996-97


696012


6.3


59.45


62.05


37.72


38.6


1997-98


821332


4.4


63.38


66.45


39.05


40.07


1998-99


972204


5.9


61.57


64.88


35.25


37.29


Notes:


(i)


Source of col.(1) is RBI Bulletin, RBI, various issues


(ii)


Source of col.(2) is Monthly Review of the Indian Economy, CMIE, various issues


(iii)


Source of cols. (3) to (6) is RBI Bulletin, RBI, various issues


(iv)


Inflation is measured as the % change in WPI and for WPI series base is 1980-81=100


(v)


36 country bilatateral weights are used for REER and NEER and the base is 1985 =100


32


Table 5. Test for Unit Roots


Variables (Xt)


DF test


ADF test


Levels


First Difference


Levels


First Difference


FINV


-3.1930**


-4.6582 *


-2.0690


-1.6255***


(with C)


(no C & T)


(15 lags, with C & T)


(14 lags, no C &T)


M3


-3.2267


-6.3117*


-2.3074


-2.8578***


(with C & T)


(with C)


(15 lags, with C)


(6 lags, with C )


WPI


-3.0611 **


-4.3817*


-3.1862


-4.5889*


(with C)


(with C & T)


(15 lags, with C &T)


( 9 lags, with C & T)


REERT


-2.5224


-7.5214*


1..5836


-2.8267


(with C)


(no C & T)


(15 lags, with C &


T)


(12 lags, no C &T)


REERX


-2.4996


-6.5821*


3.4028


-2.0187**


(with C)


(no C & T)


(15 lags, no C &T)


(13 lags, no C &T)


NEERT


-1.9669


-6.1035**


-1.8982***


-4.0576*


(with C & T)


(no C & T)


(11 lags no C &T)


(11 lags, with C &T)


NEERX


-1.9683


-5.3986*


-1.7740


-2.7765*


(with C & T)


(no C & T)


(11 lags, no C &T)


(10 lags, no C &T)


EXP


-2.8085


-8.0557*


1.7272


-1.2418


(with C & T)


(with C)


(15 lags ,no C & T)


(12 lags, no C & T)


cont'd


33


CAD


-4.6727 **


-5.5617 *


(with C & T)


(15 lags, with C & T)


FNCA


-3.3121***


-4.7181*


-5.5617*


3.2984


(with C & T)


(with C)


(15 lags, with C & T)


(10 lags, with C)


Note:


k


i.


ADF test is based on the regression Yt = C + át + äYt-1 +


Óâi Y


t-i + åt. The DF test is based on the same equation


i = 1


without the summation of the lagged difference terms on the right hand side. The figures reported in the table are tvalues


of ä.


ii.


‘C’ stands for constant and ‘T’ stands for trend


iii. * signifies statistically significant at 1 % level


iv.


** signifies statistically significant at 5 % level


v.


*** signifies statistically significant at 10 % level


Table 5. Cont'd....


Variables (Xt)


DF test


ADF test


Levels


First Difference


Levels


First Difference


34


Table 6: Residual Analysis for ADF Regression at First Difference


ADF first


Ljung-Box Q


Box-Pierce Q


ARCH Test


differenced


F-statistic


nR2


FINV


Q(2) = 1.52(0.46)


Q (2) = 1.26(0.53)


F(2) = 0.38(0.68)


Z(2) = 0.87(0.64)


Q(4) =2.69(0.61)


Q)(4) =2.17(0.70)


F(4) = 0.21(0.92)


Z(4) = 1.14(0.88)


Q(6) = 4.49(0.61)


Q(6)= 3.38(0.76)


F(6) = 0.64(0.69)


Z(6) = 4.88(0.56)


M3


Q(2) = 0.00(0.99)


Q(2) = 0.00(0.99)


F(2) = 0.71(0.50)


Z(2) =1.54(0.46)


Q(4) =0.37(0.98)


Q(4) = 0.28(0.99)


F(4) = 0.79(0.54)


Z(4) = 3.53(0.47)


Q(6)= 0.94(0.98)


Q(6) =0.68(0.99)


F(6) = 0.66 (0.68)


Z(6) = 4.82(0.56)


WPI


Q(2) = 2.93(0.23)


Q(2) = 2.46(0.29)


F(2) = 0.30(0.74)


Z(2) = 0.68(0.71)


Q(4) =4.66(0.32)


Q(4) = 3.84(0.43)


F(4) =0.18(0.94)


Z(4) =0.97(0.91)


Q(6) =6.48(0.37)


Q(6) =5.16(0.52)


F(6)= 0.68(0.66)


Z(6) = 4.94(0.55)


FNCA


Q(2) =1.58(0.45)


Q(2) = 1.40(0.49)


F(2) = 0.38(0.69)


Z(2) = 0.84(0.65)


Q(4) =1.97(0.74)


Q(4) = 1.69(0.79)


F(4) = 0.66(0.62)


Z(4) =3.02(0.55)


Q(6) = 2.29(0.89)


Q(6) = 1.92(0.93)


F(6) = 0.37(0.89)


Z(6) = 3.05(0.80)


REERT


Q(2) = 3.17(0.20)


Q(2) =2.69(0.26)


F(2)= 1.79(0.19)


Z(2) = 3.49(0.17)


Q(4) =4.09(0.39)


Q(4)= 3.42(0.49)


F(4) =0.75(0.57)


Z(4) = 3.36(0.49)


Q(6) =13.17(0.04)*


Q(6) =9.76(0.13)


F(6) =1.15(0.39)


Z(6) = 6.96(0.32)


REERX


Q(2) = 3.36(0.18)


Q(2) = 2.94(0.23)


F(2) = 0.35(0.71)


Z(2) = 0.78(0.67)


Q(4) = 4.37(0.36)


Q(4) = 3.72(0.44)


F(4) = 0.16(0.95)


Z(4) = 0.86(0.93)


Q(6) = 10.70(0.09)**


Q(6) = 8.14(0.23)


F(6) = 0.28(0.93)


Z(6) =2.46(0.87)


(cont'd)


35


NEERT


Q(2) = 1.76(0.41)


Q(2) = 1.52(0.46)


F(2) = 0.006(0.99)


Z(2) = 0.013(0.99)


Q(4) =3.68(0.45)


Q(4) = 3.01(0.55)


F(4) = 0.35(0.84)


Z(4) = 1.69 (0.79)


Q(6) = 4.80(0.57)


Q(6) = 3.81(0.70)


F(6) =0.38(0.87)


Z(6) = 3.07(0.79)


NEERX


Q(2) = 0.08(0.96)


Q(2) =0.06(0.96)


F(2) = 1.62(0.22)


Z(2) = 3.19(0.20)


Q(4) = 1.17(0.88)


Q(4) =0.92(0.92)


F(4) =1.68(0.20)


Z(4) = 6.20(0.18)


Q(6) =4.46(0.61)


Q(6) =3.20( 0.78)


F(6) =0.84(0.56)


Z(6) =5.68(0.46)


EXP


Q(2) = 0.65(0.72)


Q(2) = 0.56(0.75)


F(2) = 0.18(0.83)


Z(2) =0.42(0.80)


Q(4) = 1.43(0.84)


Q(4) =1.16(0.88)


F(4) = 0.10(0.97)


Z(4) = 0.54(0.97)


Q(6) = 3.14(0.79)


Q(6) = 2.37(0.88)


F(6) = 0.09(0.99)


Z(6) =0.85(0.99)


Notes :


(i)


Q(n) reports Ljung-Box Q/ Box-Pierce Q statistic for the autocorrelations of the n residuals of the estimated


model. With 24 observations, T/4 is equal to 6. Significance levels are in parentheses.


(ii)


F-statistic and nR2


provide ARCH test for the heteroscedasticity in the estimated residuals. ARCH test is


based on the specification that the squared residuals from the estimated model is related to the lagged


squared residuals. Each statistic is estimated using three different lags viz., 2, 4 and 6. nR2 statistic has a chisquare


distribution with degrees of freedom equal to the number of lagged squared residuals and here n


refers to the number of observations.


(iii)


* indicates significant at 1% level and ** indicates significant at 5% level.


Table 6. Cont'd.......


ADF first


Ljung-Box Q


Box-Pierce Q


ARCH Test


differenced


F-statistic


nR2


36


Table 7. Test for pairwise cointegration


Equations: Xt on Yt


µ


ã


DF


ADF


LFINV on LM3


6.45


0.12


-2.90*


-3.27*


(no C & T)


(1 lag, no C& T)


LM3 on LFINV


13.14


0.024


-2.26


-0.9952


(with C & T)


(3 lags, no C& T)


LFINV on LWPI


5.87


0.39


-2.89*


-3.2655*


(no C & T)


(1 lag, no C& T)


LWPI on LFINV


5.59


0.014


-1.38


-5.4491


(with C )


(1lag, with C& T)


LFINV on LFNCA


5.29


0.254


-2.6125


-2.1417**


(no C & T)


(5 lags, no C & T)


LFNCA on LFINV


9.80


0.16


-1.6114


-3.2052


(no C & T)


(3 lags, with C &T)


LFINV on LREERT


-13.73


5.26


-2.7195**


-2.16


(no C & T)


(5 lags, no C& T)


LREERT on LFINV


4.03


0.015


-2.0771**


12.8368*


(no C & T)


(10 lags, with C& T)


LFINV on LREERX


-17.78


6.30


-2.7253*


-6.1864*


(no C & T)


(10 lags, with C&T)


cont'd


37


LREERX on LFINV


3.97


0.016


-2.1369**


-28.5731*


(no C & T)


(10 lags, with C& T)


LFINV on LNEERT


6.49


0.442


-3.0257*


-2.0660**


(no C & T)


(5lags, no C& T)


LNEERT on LFINV


3.64


0.006


-0.6929


-0.7996


(no C & T)


(8 lags, no C& T)


LFINV on LNEERX


6.56


0.428


-3.0268*


-2.0667**


(no C & T)


(5 lags, no C& T)


LNEERX on LFINV


3.62


0.006


-0.6599


-3.3511


(no C & T)


(3 lags, with C& T)


LFINV on LEXP


3.87


0.418


-2.7207**


-2.1502**


(no C & T)


(5 lags, no C & T)


LEXP on LFINV


9.62


0.068


-2.4868


-2.6298


(with C & T)


(4 lags, no C& T)


LFNCA on LM3


-11.24


1.67


-3.0379*


-3.3395**


(no C & T)


(9 lags, with C & T )


LM3 on LFNCA


7.53


0.52


-3.3889***


-3.3449


(with C & T)


(9 lags, with C & T)


Table 7. Cont' d


Equations: Xt on Yt


µ


ã


DF


ADF


con'td


38


Equations: Xt on Yt


µã


DF


ADF


LM3 on LWPI


-0.016


2.34


-1.4261


-3.1806*


(no C & T)


(8 lags, no C& T)


LWPI on LM3


0.139


0.41


1.6485***


-3.2935*


(no C & T)


(8 lags, no C& T)


LWPI on LREERX


0.75


1.206


-1.9027


3.3791***


(with C & T)


(3 lags, with C& T)


LREERX on LWPI


3.60


0.088


-2.0074**


-7.7701*


(no C & T)


(10 lags, with C& T)


LWPI on LREERT


-0.38


1.468


-1.8706


-3.3334***


(with C & T)


(3 lags, with C& T)


LREERT on LWPI


3.46


0.12


-1.9661**


-3.4772*


(no C & T)


(7 lags, with C& T)


LREERX on LEXP


3.83


0.027


-2.1446**


-19.2301*


(no C & T)


(10 lags, with C & T)


LEXP on LREERX


3.08


1.72


-2.4502


-15.8815*


(with C & T)


(9 lags, with C& T)


LREERT on LEXP


3.74


0.04


-2.0952**


-3.7998**


(no C & T)


(7 lags, with C& T)


Table 7. Cont' d


Cont'd


39


LEXP on LREERT


0.68


2.28


-2.2895


-10.8381*


(with C & T)


(9 lags, with C& T)


LNEERX on LEXP


6.31


-0.26


-2.9133*


-3.3111*


(no C & T)


(6 lags, with C& T)


LEXP on LNEERX


21.95


-3.21


-3.4578*


-5.1963*


(no C & T)


(6 lags, with C& T)


LNEERT on LEXP


6.32


-0.25


-3.0249*


-0.8514


(no C & T)


(7 lags, no C& T)


LEXP on LNEERT


22.11


-3.23


-3.5563*


-4.2851*


(no C & T)


(6 lags, with C& T)


Note:


i.


Cointegration regression for two variables Xt and Yt is given by Xt = µ + ãYt + Zt where µ and ã are constant


and cointegrating parameter, respectively.


ii.


DF and ADF tests are carried out using regressions similar to that in Table 5.


iii.


* indicates significant at 1% level


iv.


** indicates significant at 5% level


v.


*** indicates significant at 10% level


Table 7. Cont'd


Equations: Xt on Y


t


µ


ã


DF


ADF


40


Table. 8 Test for Cointegration


Variables DF test ADF test


LFINVQ LM3Q LFNCA -4.8650** -0.7400


LFINVQ LM3Q LWPI -3.4596 -3.8497


LFINVQ LWPI LREERX -1.9165 -1.0948


LFINVQ LWPI LREERT -1.8686 -1.0545


LFINVQ LEXP LREERT -1.9000 -0.0209


LFINVQ LEXP LREERX -1.8856 0.0389


LFINVQ LEXP LNEERX -2.3841 -6.2334**


LFINVQ LEXP LNEERT -2.4095 -0.5647


Notes:


(i) Reported results are based on regressions including a constant


and a trend .


(ii) Reported results for ADF test correspond to 11 lags, the highest


possible number of lags that can be chosen for the given number


of observations. ADF test is also tried with other lags going


down to the least possible number of lags. The null hypothesis


of no cointegration is rejected in none of these case.


(iii) ** indicates significant at 5% level.


41


Table 9: Pairwise Granger Causality Test


Dependent


Explanatory


m


n


F- Statistic


p-value


Remarks


Variable


Variables


FINV


FINV, M3


1


1


1.09


0.31


No causality from M3 ¨ FINV


M3


M3, FINV


1


1


0.009


0.92


No causality from FINV ¨ M3


FINV


FINV, WPI


1


1


57


0.23


No causality from WPI ¨ FINV


WPI


WPI, FINV


2


1


0.38


0.54


No causality from FINV ¨ WPI


FINV


FINV,FNCA


1


1


0.075


0.78


No causality from FNCA¨ FINV


FNCA


FNCA, FINV


1


1


6.79


0.02


Causality from FINV ¨ FNCA


FINV


FINV, REERT


1


1


2.28


0.15


No causality from REERT ¨ FINV


REERT


REERT,FINV


1


1


2.01


0.17


No causality from FINV ¨ REERT


FINV


FINV, REERX


1


1


2.40


0.14


No causality from REERX ¨ FINV


REERX


REERX, FINV


1


1


2.09


0.16


No causality from FINV ¨ REERX


FINV


FINV, NEERX


1


1


2.04


0.17


No causality from NEERX ¨ FINV


NEERX


NEERX, FINV


1


1


3.74


0.06


Causality from FINV ¨ NEERX


FINV


FINV, NEERT


1


1


2.14


0.16


No causality from NEERT ¨ FINVcont'd


42


NEERT


NEERT, FINV


1


1


3.005


0.10


Causality from FINV ¨ NEERT


FINV


FINV, EXP


1


1


0.29


0.59


No causality from EXP ¨ FINV


EXP


EXP, FINV


4


1


0.13


0.72


No causality from FINV ¨ EXP


FNCA


FNCA, M3


1


1


0.026


0.87


No causality from M3 ¨ FNCA


M3


M3, FNCA


1


1


0.41


0.53


No causality from FNCA ¨ M3


M3


M3, WPI


1


1


0.15


0.70


No causality from WPI ¨ M3


WPI


WPI, M3


2


1


0.41


0.53


No causality from M3 ¨ WPI


REERX


REERX,WPI


1


1


2.15


0.16


No causality from WPI ¨ REERX


WPI


WPI, REERX


2


1


1.16


0.29


No causality from REERX ¨ WPI


REERT


REERT, WPI


1


1


2.33


0.14


No causality from WPI ¨ REERT


WPI


WPI, REERT


2


1


0.99


0.33


No causality from REERT¨ WPI


REERX


REERX, EXP


1


1


0.49


0.49


No causality from EXP ¨ REERX


EXP


EXP, REERX


4


4


2.12


0.15


No causality from REERX ¨ EXP


REERT


REERT, EXP


1


2


1.06


0.37


No causality from EXP ¨ REERT


EXP


EXP, REERT


4


4


2.27


0.12


No causality from REERT ¨ EXP


Notes: Optimum lag lengths (m, n) are determined by minimizing the Akaike Information Criteria.


Table 9 Cont'd


43


CENTRE FOR DEVELOPMENT STUDIES


LIST OF WORKING PAPERS


(From 1991 onwards)


MRIDUL EAPEN Hantex: An Economic Appraisal.


September, 1991, W.P.242


SUNIL MANI Government Intervention in Commercial Crop Development:


A Case of Flue Cured Virginia Tobacco.


November, 1991, W.P.243


K. PUSHPANGADAN Wage Determination in a Casual Labour Market: The


Case Study of Paddy Field Labour in Kerala.


January, 1992, W.P.244


K.N. NAIR & S.P. PADHI Dynamics of Land Distribution: An Alternative


Approach and Analysis with Reference to Kerala.


January, 1992, W.P.245


THOMAS ISAAC Estimates of External Trade Flows of Kerala - 1975-76 and


1980-81.


March, 1992, W.P.246


THOMAS ISAAC, RAM MANOHAR REDDY, NATA DUVVURRY Regional


Terms of Trade for the State of Kerala.


March, 1992, W.P.247


P. MOHANAN PILLAI Constraints on the Diffusion of Innovations in Kerala:


A Case Study of Smokeless Chulas.


March, 1992, W.P.248


R. ANANDRAJ Cyclicality in Industrial Growth in India: An Exploratory


Analysis.


April, 1992, W.P.249


T.M. THOMAS ISAAC, RAM MANOHAR REDDY, NATA DUVVURY


Balance of Trade, Remittance and Net Capital Flows: An Analysis of


Economic Development in Kerala since independence.


October, 1992, W.P.250


M. KABIR, T.N. KRISHNAN Social Intermediation and Health Transition:


Lessons from Kerala,


October, 1992, W.P.251


44


SUNIL MANI, P. NANDAKUMAR Aggregate Net Financial Flows to India:


The Relative Importance of Private Loan vis-a-vis Foreign Direct Investments.


August, 1993, W.P.252


PULAPRE BALAKRISHNAN Rationale and the Result of the Current


Stabilisation Programme.


November, 1993, W.P.253


K.K. SUBRAHMANIAN, P. MOHANAN PILLAI Modern Small Industry


in Kerala: A Review of Structural Change and Growth Performance.


January, 1994, W.P.254


DILIP M.MENON Becoming Hindu and Muslim : Identity and Conflict in


Malabar 1900-1936.


January, 1994, W.P.255


D. NARAYANA Government Intervention in Commodity Trade: An Analysis


of the Coffee Trade in India.


January, 1994, W.P.256


K.J. JOSEPH, P. NANDAKUMAR On the Determinants of Current Account


Deficits: A Comparative Analysis of India, China and South Korea.


January, 1994, W.P.257


K.K. SUBRAHMANIAN, K.J. JOSEPH Foreign Control and Export Intensity


of Firms in Indian Industry.


February, 1994, W.P.258


PULAPRE BALAKRISHNAN, K. PUSHPANGADAN Total Factor Productivity


Growth in Indian Manufacturing - A Fresh Look.


April 1994, W.P.259


D. NARAYANA, K.N. NAIR Role of the Leading Input in Shaping Institutions:


Tendency in the Context of Irrigation Uncertainty.


May, 1994, W.P.260


G. MURUGAN, K. PUSHPANGADAN Pricing of Drinking Water: An Application


of Coase Two-part Tariff.


December, 1994 W.P.261


MOHANAN PILLAI On the Mexican Crisis.


December, 1995, W.P.262


SUNIL MANI Financing Domestic Technology Development through the Venture


Capital Route.


December, 1995, W.P.263


45


T.T. SREEKUMAR Peasants and Formal Credit in Thiruvithamcore: The


State Institutions and Social Structure 1914-1940.


December, 1995 W.P.264


AMITABH Estimation of the Affordability of Land for Housing Purposes in


Lucknow City, Uttar Pradesh (India): 1970-1990.


March, 1996. W.P.265


K. PUSHPANGADAN, G. MURUGAN, K. NAVANEETHAM Travel Time,


User Rate & Cost of Supply: Drinking Water in Kerala, India:


June 1996. W.P.266


K.J. JOSEPH Structural Adjustment in India: A Survey of Recent Studies &


Issues for Further Research,


June 1996 W.P.267


D. NARAYANA Asian Fertility Transition: Is Gender Equity in Formal Occupations


an Explanatory Factor?


October, 1996 W.P.268


D. NARAYANA, SAIKAT SINHAROY Import and Domestic Production of


Capital Goods from Substitution to Complementarity,


October 1996. W.P.269


NEW SERIES


W.P. 270 ACHIN CHAKRABORTY On the Possibility of a Weighting System


for Functionings December 1996


W.P. 271 SRIJIT MISHRA Production and Grain Drain in two inland Regions


of Orissa December 1996


W.P. 272 SUNIL MANI Divestment and Public Sector Enterprise Reforms,


Indian Experience Since 1991 February 1997


W.P. 273 ROBERT E. EVENSON, K.J. JOSEPH Foreign Technology Licensing


in Indian Industry : An econometric analysis of the choice


of partners, terms of contract and the effect on licensees’ performance


March 1997


W.P. 274 K. PUSHPANGADAN, G. MURUGAN User Financing & Collective


action: Relevance sustainable Rural water supply in India.


March 1997.


W.P. 275 G. OMKARNATH Capabilities and the process of Development


March 1997


W. P. 276 V. SANTHAKUMAR Institutional Lock-in in Natural Resource


Management: The Case of Water Resources in Kerala, April 1997.


W. P. 277 PRADEEP KUMAR PANDA Living Arrangements of the Elderly


in Rural Orissa, May 1997.


46


W. P. 278 PRADEEP KUMAR PANDA The Effects of Safe Drinking Water


and Sanitation on Diarrhoeal Diseases Among Children in Rural


Orissa, May 1997.


W.P. 279 U.S. MISRA, MALA RAMANATHAN, S. IRUDAYA RAJAN


Induced Abortion Potential Among Indian Women, August 1997.


W.P. 280 PRADEEP KUMAR PANDA Female Headship, Poverty and


Child Welfare : A Study of Rural Orissa, India, August 1997.


W.P. 281 SUNIL MANI Government Intervention in Industrial R & D, Some


Lessons from the International Experience for India, August 1997.


W.P. 282 S. IRUDAYA RAJAN, K. C. ZACHARIAH Long Term Implications


of Low Fertility in Kerala, October 1997.


W.P. 283 INDRANI CHAKRABORTY Living Standard and Economic


Growth: A fresh Look at the Relationship Through the Non- Parametric


Approach, October 1997.


W.P. 284 K. P. KANNAN Political Economy of Labour and Development in


Kerala, January 1998.


W.P. 285 V. SANTHAKUMAR Inefficiency and Institutional Issues in the


Provision of Merit Goods, February 1998.


W.P. 286 ACHIN CHAKRABORTY The Irrelevance of Methodology and


the Art of the Possible : Reading Sen and Hirschman, February 1998.


W.P. 287 K. PUSHPANGADAN, G. MURUGAN Pricing with Changing


Welfare Criterion: An Application of Ramsey- Wilson Model to Urban


Water Supply, March 1998.


W.P. 288 S. SUDHA, S. IRUDAYA RAJAN Intensifying Masculinity of Sex


Ratios in India : New Evidence 1981-1991, May 1998.


W.P. 289 JOHN KURIEN Small Scale Fisheries in the Context of


Globalisation, October 1998.


W.P. 290 CHRISTOPHE Z. GUILMOTO, S. IRUDAYA RAJAN Regional


Heterogeneity and Fertility Behaviour in India, November 1998.


W.P. 291 P. K. MICHAEL THARAKAN Coffee, Tea or Pepper? Factors


Affecting Choice of Crops by Agro-Entrepreneurs in Nineteenth


Century South-West India, November 1998


W.P. 292 PRADEEP KUMAR PANDA Poverty and young Women's Employment:


Linkages in Kerala, February, 1999.


W.P. 293 MRIDUL EAPEN Economic Diversification In Kerala : A Spatial


Analysis, April, 1999.


W.P. 294 K. P. KANNAN Poverty Alleviation as Advancing Basic Human


Capabilities: Kerala's Achievements Compared, May, 1999.


47


W.P. 295 N. SHANTA AND J. DENNIS RAJA KUMAR Corporate Statistics:


The Missing Numbers, May, 1999.


W.P. 296 P.K. MICHAEL THARAKAN AND K. NAVANEETHAM


Population Projection and Policy Implications for Education:A


Discussion with Reference to Kerala, July, 1999.


W.P. 297 K.C. ZACHARIAH, E. T. MATHEW, S. IRUDAYA RAJAN


Impact of Migration on Kerala's Economy and Society, July, 1999.


W.P. 298 D. NARAYANA, K. K. HARI KURUP, Decentralisation of the


Health Care Sector in Kerala : Some Issues, January, 2000.


W.P. 299 JOHN KURIEN Factoring Social and Cultural Dimensions into


Food and Livelihood Security Issues of Marine Fisheries; A Case


Study of Kerala State, India, February, 2000.


W.P. 300 D. NARAYANA Banking Sector Reforms and the Emerging


Inequalities in Commercial Credit Deployment in India, March, 2000.


W.P. 301 P. L. BEENA An Analysis of Mergers in the Private Corporate


Sector in India, March, 2000.


W.P. 302 K. PUSHPANGADAN, G. MURUGAN, Gender Bias in a


Marginalised Community: A Study of Fisherfolk in Coastal Kerala,


May 2000.


W.P. 303 K. C. ZACHARIAH, E. T. MATHEW, S. IRUDAYA RAJAN ,


Socio-Economic and Demographic Consequenes of Migration in


Kerala, May 2000.


W.P. 304 K. P. KANNAN, Food Security in a Regional Perspective; A View


from 'Food Deficit' Kerala, July 2000.


W.P. 305 K. N. HARILAL, K.J. JOSEPH, Stagnation and Revival of Kerala


Economy: An Open Economy Perspective, August 2000.


W.P. 306 S. IRUDAYA RAJAN, Home Away From Home: A Survey of Oldage


Homes and inmates in Kerala, August 2000.


W.P. 307 K. NAVANEETHAM, A. DHARMALINGAM, Utilization of


Maternal Health Care Services in South India, October 2000.


W.P. 308 K. P. KANNAN, N . VIJAYAMOHANAN PILLAI, Plight of the


Power Sector in India : SEBs and their Saga of Inefficiency


November 2000.


W.P. 309 V. SANTHAKUMAR AND ACHIN CHAKRABORTY,


Environmental Valuation and its Implications on the Costs and


Benefits of a Hydroelectric Project in Kerala, India, November 2000.


W.P. 310 K. K. SUBRAHMANIAN, E. ABDUL AZEEZ, Industrial Growth


In Kerala: Trends And Explanations November 2000


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