DIÁLOGO CUARTO

INVESTMENT

The foregoing discussion has shown the positive effects of private sector investment on growth, in line with theoretical expectations. However, as pointed out earlier, investment itself can be an important channel of transmission for the indirect effects of inflation. Therefore, it is important to examine this issue.

Investment and national savings rates are highly positively correlated in virtually all countries (Baxter and Crucini 1993). This is puzzling for developed countries, as it apparently implies a low degree of international capital mobility. 49 On the other hand, for countries like India where international capital flows are known to be restricted, such a relationship should not be a puzzle. Most aggregate investment in India (more than 90 percent) comes from domestic savings. Therefore, the analysis of savings behaviour and the effects of inflation on savings are important for the analysis of investment. It may be recalled that investment in the growth models distinguished between private and public sector investment. While private sector investment has a significant positive effect on growth, public sector investment has an insignificant effect. Further, public sector investment can be considered more like an exogenous variable in the Indian context, where such investments have a lot of political and welfare overtones rather than profitability considerations. Therefore, the analysis in this section, focuses on private sector investment (GDIZPV) and gross national savings (GNSZ)50, both expressed as a fraction of gross domestic product.

Another important aspect of the Indian economy is that household saving forms more than 70 percent (and up to 80 percent during some periods) of total savings. The theoretical literature on aggregate consumption and savings behaviour is not unanimous regarding determinants. Some consumption is accounted for by life- cycle-permanent-income consumers, and some by simple Keynesian consumers. This is partly due to liquidity constraints and evidence to support the existence of buffer- stock saving (Dornbusch and Fischer 1994:316). For a developing country like India, three major considerations for savings can be identified in simple terms. First, in the absence of state social security, individuals are concerned with future survival. Second, the social order requires bulk spending on occasions like the marriage of

49 In economic literature this is known as the ‘Feldstein Horioka Puzzle’ after their famous paper on domestic saving and international capital mobility (Feldstein and Horioka 1980)

50 Some earlier studies on savings in India (for example Athukorala and Sen (2001) and Muhleisen (1997)), which focus more on the components of savings, have criticized the data compilation procedure on savings in India. Muhleisen (1997) has even generated his own series of different components. However, since the purpose o f the present analysis is to examine the effect of inflation on overall savings at aggregate level, the aggregate data on national savings is taken from The World Bank CDROM-2000, where the gross national savings is calculated by subtracting total consumption expenditure from the gross domestic product and adding net income and net current transfers from abroad. Therefore, in a way the analysis of savings is also an analysis of consumption behaviour. Full detail of data sources is provided in Appendix AA of this thesis.

children and several other religious ceremonies and people feel gratified by such expenditure. Thirdly, there is a strong desire to leave a bequest for children and spouse. Therefore, most individuals keep their own needs to a minimum and maintain a savings target.

In such a situation, saving is likely to increase in proportional terms with any increase in permanent or current income. Savers receive return in the form of interest or dividend and capital gains on stocks. Therefore, saving is also expected to increase51 if interests on deposits are more and government provides incentives in the form of infrastructure like institutional expansion and tax relief on savings.

However, savings behaviour becomes distorted in the presence of inflation. It may be cut short to meet already minimized physical consumption or small savers may become biased towards leveraged investments in tangible assets, especially real assets, like jewelry and consumer durables. Kane (1980) argues that, in the presence of deposit rate ceilings, accelerating inflation simply victimizes small savers who are disadvantaged in access to credit. On the other hand, if individuals are faced with economic uncertainty, they are expected to save more as predicted by the literature on precautionary savings. Athukorala and Sen (2001) proxy such economic uncertainty with inflation and argue that inflation may cause savings to rise. Therefore, it is important to understand the relationship between inflation and savings in order to appreciate the full effects of inflation on investment.

Drawing on the literature (see for example Athukorala (1998); Joshi and Little (1994); Frenkel and Razin (1994); Krishnamurty, et al. (1987); Davidson (1986); McKinnon (1973); Shaw (1973)) on savings, investment and development, and on the foregoing discussion, the following reduced form functions are considered appropriate for analyzing the effect of inflation on economic growth through an investment channel.

GDIZPV = f(R LR SBI, GNSZ, CGAPZ)

+ - / + (4.14)

GNSZ = f ( yp, DR1, Ap, UTID, TOT, CBDN)

+ + - +/- (4.15)

51 It may be noted that when saving is considered only as a means to finance retirement, it is likely that less saving would be required with an increased interest rate. Therefore, some economists believe that interest rates should either reduce savings or they cannot have any effect.

Here, GNSZ, GDIZPV, and Ap are the same as defined earlier. The other new variables are described as follows: RLRSBI is the real interest rate on lending by the state bank of India (SBI) calculated by subtracting the current annual inflation from the nominal lending rate (LRSBI). With increasing lending rates investment is expected to fall.

CGAPZ is the gap between combined total outlay and combined total current revenue of central and state governments as a percentage of GDP and is a proxy for the fiscal deficit. In the development literature, government spending on development projects has been considered to play an important role in boosting private investment (Bardhan 1984). However, excess government spending also leads to higher fiscal deficits, which is considered inflationary (Catao and Terronesi 2001) and an indicator of poor fundamentals from the point of view of private investor confidence. With an increasing fiscal deficit, it is also expected that resource allocation will become distorted and the private sector may find credit costly, causing private sector investment to fall. Yet a substantial portion of the deficit may be argued to arise from government expenditure on development projects, including in the agricultural sector, which has a stimulating effect on private investment. Therefore, it is preferred to use overall government deficit in the investment equation rather than expenditure alone. However, in view of the possibilities of mixed effects, the sign of CGAPZ is an empirical matter. The role of fiscal deficit in the creation of money and hence inflation will be discussed later in Chapter 7.

yp is the log of permanent income calculated from real GDP using the error- learning hypothesis of Laidler (1985:88) with a geometric weight of 0.5 for the current year and the remaining geometric weights distributed over the previous 10 years (see Appendix AA of this thesis for more details). An increase in permanent income is expected to increase savings and hence investment. DR1 is the interest rate paid by commercial banks on 1-3 year deposits. With an increase in deposit rates, the time deposits in commercial banks are expected to increase. At the same time, this may erode profitability of the banking sector in the presence of institutional rigidity and controls on lending rates, a point raised in Chapter 1.

UTID is the dividend paid by Unit Trust of India (UTI)52, which is a proxy for the loss of financial savings, particularly of the public sector (a higher dividend would have a negative effect on national savings) but it also provides an incentive for small savers in mutual funds, which may increase investment. TOT is terms of trade expressed in terms of ratio of unit value index of export (UVIE) to unit value index of imports (UVII). TOT is expected to have a positive correlation with both gross domestic product (GDP) and gross national savings (GNS). However, the effect of TOT on GNSZ may be positive or negative depending on the relative magnitude of its effect on GDP and GNS. CBDN is commercial bank density in the country measured as thousands of people per branch; it is expected that a fall in bank density would mean more banking facility for small saver in time deposit.

In order to capture the overall effects of direct and indirect variables on private investment, equations 5.14 and 5.15 can be written in reduced form as follows, where the real lending rate (RLRSBI) is now replaced with the nominal lending rate (LRSBI) and inflation, so that the overall effect of inflation on private investment can be measured in a straight forward way.

GDIZPV = f (LRSBI, CGAPZ, yp, D Rl Ap, UTID, TOT, CBDN) (4.16)

A summary of data is presented in Annexure 4.1 of this chapter. More details on data like sources and constructed data are provided in Appendix AA of the thesis. Again, all variables are tested for the unit root using the ADF method and test results are presented in Annexure 4.2. The key variables do not have the same order of integration. Particularly, GNSZ, Ap , y p, and CBDN are stationary when tested with intercept and no trend, while GDIZPV, LRSBI, CGAPZ, UTID, DRl, and TOT are integrated of order one. After taking the first difference, all the variables are stationary. However, in modeling savings and investment, it is important to capture some of the long-run relationships along with the short-run behaviour of the explanatory variables. This calls for modeling in the error correction framework.

Initial attempts to model through the cointegrating vector error correction modeling (VECM) approach failed to provide clear identification of the long-term relationships due to the presence of several stationary variables which resulted in

several cointegrating vectors. However, the alternative method of the single equation restricted error correction modeling (RECM) procedure of Hendry (1995), which allows the model to include lagged dependent and independent variables along with the terms of difference, proved to be more flexible (see section AB.4, Appendix AB for a note on general to specific modeling). A careful estimation with respect to the diagnostic properties of the residuals will guard against any spurious content. For this purpose the distributed lag model presented in equation 4.12 can be rearranged in terms of differences and lagged levels in the following unrestricted error correction form as follows. m- 1 ffi-1 az, = « +

£

’

,_,

X

;

c0y,_„

c,x,_m

Cr = -

c x =

2

and C0‘C, represents the long-run

multiplier for the system. Considering equation (4.17) as the ‘maintained hypothesis’ of the specification search, the general model is ‘tested down’ by the ordinary least square regression starting with adequate lags permitted by the sample size. The insignificant lagged terms are dropped systematically until a statistically acceptable model in a priory theoretical framework is obtained. The estimated reduced form model for private investment is presented in Table 4.5. The model is tested for possible unit root in the residuals, using the ADF method and the results are presented53. The diagnostic tests indicate that the model is statistically satisfactory and acceptable. The CUSUM test and the CUSUM-square test on the recursive residuals (not presented here) did not indicate any sign of structural breaks. The R- square and the R-bar square for the model are 0.90 and 0.76, which is high enough for reasonable predictions. The long-term relationship of GDIZPV with other variables is reproduced at the bottom of Table 4.5 with standard errors of coefficients estimated using variance-covariance matrix.

53 Considering the fact that the sample size is small, test statistics for unit root test applicable for multivariable case may not be reliably obtained from standard tables. However, considering the unit root test on residual as a single variable case, the 95 percent critical value is -3 .0 0 for the present sample size, which shows that the test statistic is satisfactory.

In the context of the subject matter o f this chapter, the important conclusion emerging from this estimation is that inflation is not a significant determinant of private investment per se, either in the long or the short run. The above finding leads to a conclusion that inflation does not exert any indirect influence on economic growth through private investment.

Table 4.5 Estimated model of gross domestic investment in private sector as ___________fraction of gross domestic product (1972-97)___________________

Model: GDIZPV

AGDIZPV = -0.882** - 0.948 GDIZPV (-1)* - 1.060 LRSBI (-1)* + 0.683 CGAPZ (-1)**

(0.337) (0.179) (0.293) (0.288)

+ 0.084 yp(-1) *-0.934 DR1 (-1)** + 0.085 Ap (-1) + 0.405 UTID (-l)**

(0.024) (0.426) (0.060) (0.174)

- 0.215 TOT (-1)*- 0.556 ALRSBI *** + 0.228 Ayp - 0.581 ADR 1 + 0.076 A(Ap)

(0.057) (0.300) (0.216) (0.391) (0.052)

- 0.540 AUTID - 0.090 ATOT (0.176) (0.037)

R-square = 0.90, R-bar-square = 0.76. SE of regression = 0.0087, F-Statistic F (14, 11) = 6.71[0.002]. DW statistics = 1.86. LM serial correlation CHSQ (1) = 0.226 [0.63], LM serial correlation CHSQ (3) = 2.125 [0.55]. Heteroscedasticity CHSQ (1) = 2.684 [0.10], ARCH (3) CHSQ (3) = 1.15 [0.76]. Functional form RESET CHSQ (1) = 0.015 [0.90]. Normality CHSQ (2) = 2.020 [0.36]. Unit root test for the residuals in second order ADF based on SBC model selection criterion = - 4.36. Predictive failure test (Chow’s second test) after breaking the sample at 1992 CHSQ (5) = 1.37 [0.93].

*significant at 1% level, **significant at 5% level and ***significant at 10% level; values in parenthesis () are standard errors and values in square brackets [] are p-values.

Long term coefficients of private investment

GDIZPV = constant-1.118 LRSBI*+ 0.721 CGAPZ** +0.088 yp * - 0.990 DR 1***

(0.415) (0.384) (0.023) (0.525)

+ 0.089 Ap + 0.427 UTID*** - 0.227 TOT**

(0.066) (0.221) (0.081)

Other important conclusions that can be drawn from the results in Table 4.5 are as follows. Nominal interest rates on lending as well as saving deposits tend to decrease private investment54. It may be pointed out that high deposit rates may lead

54 However, in the context of interest rate liberalization and directed credit, Ahluwalia (1999) argues that it is the timely availability of credit, which matters more than the interest rate.

to high lending rates, particularly in the face of likely inefficiency of the banking and the financial institutions, most of which are in the public sector in India. The coefficients of nominal interest rates and inflation do not appear to suggest that there is significant consideration of the real interest rate by investors in India. This may be due to the fact that inflation in India was still generally less than two digit levels during the sample period.

A significant positive sign of combined fiscal deficit in the long-run shows that a one percentage point increase in the combined deficit leads to an increase in private investment to the extent of about 0.72 percentage points in the long-term. This indicates that significant government spending is directed towards development activities and motivating the private sector. In this context, it can be argued that government spending on infrastructure, such as railways, roads, communication and subsidies like manufacturing fertilizers, motivate the private sector to increase investment. While fiscal deficit appears to positively affect private investment, its overall positive effect on economic growth through investment may be significantly less than its negative effect through inflation itself, which is discussed in Chapter 7 on money supply.

As expected, growth in permanent real income has a favourable effect on savings and investment. The terms of trade has a negative sign, which shows that the effect of improvement in the terms of trade is more in increasing consumption than savings and investment. Similarly, the increases in UTI dividends motivates saving and hence investment in the long term, but in the short-run it appears to increase consumption rather than re-investment. The change in bank density CBDN is not found to add to the explanatory power of this model, although it has been found significant in explaining savings in some studies such as Athukorala (1998).