SAVINGS AND INVESTMENT IN INDIA: A COINTEGRATION APPROACH SESHAIAH S.Venkata
and SRIYVAL.V Abstract
The purpose of this paper is to investigate the relationship between savings and investment. The results reveal that there is unidirectional causality from savings to investment. From variance decomposition method, we observe that with a lag of three periods, change in savings effects 85% of variance in investment (and 92%) by the end of ten periods. On the other hand, no significant part of variance of yield curve is caused by inflation (3% and 4% at the end of three periods and ten periods, respectively). The results also showed cointegration between savings, investment and yield spread. Yield spread and investment have not been found to Granger-cause savings indicating savings are independent of investment and yield spread.
JEL Classification: E21, E22, E4
Key words: capital mobility, yield curve, savings 1. Backdrop of the paper
There is a lot of literature focusing on the relationship between savings and investment. To our knowledge only a few studies made an attempt to assess the relationship between savings and investment in developing countries and India, in particular. It will be more interesting to test the applicability of theory to the countries like India because of the following reasons.
1. India is thickly populated country and for ages it believed in savings management
2. Two-thirds of the population depends on agricultural sector and this sector constantly faces the peril of either drought or floods.
Therefore savings became a question mark in this sector.
3. For decades, the unorganized sector has been dominating the organized sector and people engaged in agriculture have been exploited by higher interest rates, hence money has been moving from urban to rural sector.
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4. Political instability for the past one and half decade has been the cause of low confidence of the public and investors in the economy as a result of uncertainty regarding economic policies.
In this section we present theory related to the relationship between Savings, Investment and growth of the economy and intuitive discussion for the failure of classical view planned of savings being equal to planned investment before and after liberalization and also a brief on the Indian financial system. Section 2 deals with the review of literature, Section 3 deals with Data and Methodology; Section 4 deals with the Empirical Investigation and Section 5 Conclusion and Discussion.
Relationship between Savings, Investment and Economic Growth It is a well-established fact that growth of output of an economy depends on the amount of capital accumulation and the amount of capital accumulation in an economy is ultimately constrained by its rate of saving. As savings increase in the economy, more funds will be available for investment. Hence, the issue of ways and means to stimulate investment and bring about an increase in the level of savings and increased investment has assumed importance. Savings depend on the following factors:
1. The ability to save: This mainly depends on the income levels of the people and the kind of tax benefits that the government provides.
2. Willingness to Save: This is the most subjective factor and this depends on motive, love for family, provision for rainy days etc.
and moreover the willingness to save likely to be the existence of financial Institutions, interest rates and the range and availability of financial assets to suit savers with different needs.
Savings and Investment before liberalization:
Most researchers that worked on Savings and Investment mentioned that the relationship between savings and investment is complex but believe that for Indian economy the relationship between savings and investment complex but also always changing, mystifying and frustrating. Our results are quite frustrating one way and other way quite interesting. The results shows that there is a long run relationship between savings and investment which is the
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indication of planned savings are equal to planned investment but the figure-1 shows that investment is greater than the savings in almost all the periods. Hence we made an attempt to study the behavior of savings and investment before and after liberalization with help of figure-1. The study of the diagram is made with a mix of economic facts and intuition.
Most of the researchers argued that classical economist’s view of planned savings is equal to planned investment applicable only in the era of closed economy because of low capital mobility and hence domestic savings will finance the domestic investment. Here we argue that both Indian economy this is not the case in pre- liberalization (Closed economy) period as well as in post liberalization (open economy), even though our results show long relationship between savings and investment. We felt that the relationship between savings and investment is simply of accounting in nature. The reasons are as follows:
1. There was a continuous rise in the interest rates before liberalization, hence people saved more but the corporate sector faced the problem of undesirable investment because of higher inventories and hence from this angle, classical economists planned savings are equivalent to planned investment is not applicable even before liberalization.
2. It may be observed from Figure 1 that increase in savings could not finance investment. India has depended heavily on foreign aid.
3. Our intuition directed us that this might be because of the unorganized sector. Since 64% of the people depend on agriculture and this sector always suffers from crop failure, because of drought or floods, there is always a need for money.
Hence money will fly from urban to rural sector.
Savings and Investment after liberalization
Even though the second-generation reforms paved the way to liberalize the economies of various countries in 1991, India liberalized its economy in 1980 itself and in fact it has quickened in 1985 because of the following reasons.
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1. The second oil-price hike of 1979 had prompted the advanced industrial countries to raise interest rates (nominal), which had a serious, adverse impact on the borrowings by the developing countries, hiking up their debt servicing charges.
2. Anti-inflationary measures pursued by the advanced capitalist countries extended the impact of recession into the Third World countries. The recession in their markets led to lowered demand for developing country exports further adversely affecting their trade balances.
3. India's deficit on the current account increased throughout the eighties. From the mid-eighties it was pushed into greater dependence on high interest commercial loans from international banks to finance their deficits. The net outcome was that India’s external debt tripled during this decade of high growth. IMF provided a Standby Credit of $2.2 million in the year 1991 to come out of the mess.
4. The growth in private savings could not finance most of India’s investment especially in mid-1980s because they were already at a quite high level. As a result, during the late 1980s India depended heavily on foreign sources, which led to a balance of payment crisis in 1990’s.
Because of the cited reasons, India has no option except to liberalize the economy in order to receive new loans and even the companies, which were felt exporting is a prestige issue also has no option except liberalizing. After liberalization, there has been a free flow of capital without any barriers and money has become available at lower interest rates. Hence, the view of classical economists is not applicable even after liberalization. The new financial innovations in the Indian economy such as Global Depository Receipts (GDRs), American Depository Receipts (ADRs) and Foreign Currency Convertible Bonds (FCCBs) coupled with lower interest rates in other countries attracted Indian corporate and hence after liberalization also classical view’s failed. Moreover the investors lost confidence in the stock market and almost every three years once some scam takes place and savings of the public will be looted.
Hence we felt that rising interest rates, unorganized sector and scams in the stock market are the root cause of failure of classical
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economist’s views. Further, we feel that the Indian economy is supporting the argument of Keynes that is savings and investments are two independent variables. .
The Indian Financial System1
The Indian Financial system comprises of organized sector and unorganized sector. The organized sector is highly systematized having various finance products and it is a set of banks, financial institutions and money markets. After liberalization more private banks of India as well as abroad were entered. As per statistics, banks hold 65% of the total assets in the financial system alone, showing their importance in the economy. The unorganized financial system comprises relatively less controlled moneylenders, indigenous banks, lending pawnbrokers, landlords, traders, etc. There are a host of other financial companies, investment companies, chit funds, etc., which are not regulated by the Government.
In the India n capital markets, many financial innovations occurred after economic liberalization. The mutual fund industry and insurance sectors are going to rule the country by generating employment opportunities, since private players also involved. The investors also have a lot of opportunities to invest in various financial products not only in India but also in overseas markets. Markets also broadened due to foreign direct investment and foreign portfolio investment. The establishment of efficient financial systems will help India to grow, partly by mobilizing additional financial resources and partly by allocating those resources to best uses.
2. Review of Literature
The genesis of literature on the relationship between savings and investment is due to the seminal paper by Feldstein and Horioka (1980). In their study covering 16 OECD countries using data for the time period 1960-74, they found high correlation between domestic savings and investment that suggested the existence of limited capital mobility. This study gave rise to a new way of measuring
1 For a description of Indian financial system, see
http://www.trema.com/finance_online/7/2/Indian_Industry.html? 7
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international capital mobility derived from the extent of correlation between savings and investment.
From correlation, the focus of the study extended to the cointegration between these variables. Miller (1988) found that in U.S. (using data for 1946-87) both savings and investment were integrated of order 1 and shared a cointegrating relationship prior to the Second World War period and that the long-run relationship did not exist after. He concluded that this phenomenon could be explained by the increased international mobility after the War. Levy (1998) examined the relationship in the short run as well in the long run and finds evidence in favor of long run and cyclical relationship between savings and investment. The study also found stronger relationship between savings and investment relationship in the postwar period than during prewar period.
Frankel et al. (1986) used a sample of 64 countries (14 developed and 50 developing countries) in his study on savings-investment relationship and found that in case of all the countries except a few less developed countries2, savings and investment are highly correlated and shared a long-run equilibrium relationship. Arginon and Roldan (1994) investigate the observed correlation between domestic saving and investment in E.U. countries using annual data for the period 1960–1988. They distinguish between the pair of saving/investment of the private and public sector. Bayoumi (1990) argues that current account targeting by the Government could cause high correlation between the variables. However, both the studies suggest causality flowing from savings to investment without any feedback effect.
Another study in the US, which uses quarterly data, by Pollin and Justice (1994) suggests that saving and lending are not cointegrated, indicating that the period under study witnessed high capital mobility. De Vita and Abbott (2002) found similar results using an ARDL bounds testing procedure and so did Yamori (1995) for Japan.
Apergis and Tsoulfidis (1997) use similar econometric technique in
2 Countries heavily dependent on foreign aid and assistance programs
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their study for 14 EU countries and find that savings and investment are cointegrated which suggests that capital mobility is not as high even after the move towards economic integration in Europe has gained momentum. The study also finds that savings Granger-causes investment using Vector Error-Correction Model.
Krol (1996), examined the relationship between savings and investment using annual data, pooled for 21 OECD countries over the period 1962-90 and found that the estimated impact of saving on investment is considerably smaller than the estimates of the earlier researcher that were used averaged data (also see Pelagidis and Mastroyiannis, 2003 for Greece).
Jansen (1998) suggests that correlation between savings and investment in the long run is determined by one or more of these factors - limited capital mobility, current account targeting by the Government and inter-temporal budget constraint and the short-run co-movements are due to capital mobility. In addition, the paper also finds that the short-run correlation seems to vary across countries and is determined by country-specific business cycles (in line with Leachman, 1991; Jansen, 1996 and Taylor, 1996). Moreno (1997) extends the study to Japan along with the U.S.
Most of the studies have focused on developed countries, similar studies for developing countries have been few and far between.
Mamingi (1997) estimated the relationship between saving and investment correlations for 58 developing countries by assessing the degree of capital mobility in the Feldstein – Horioka sense for these developing countries. They found that the relationship between savings and investment in case of middle – income countries tend to be lower than those that of low-income countries. Sinha (2002) finds that Savings and Investment rates are cointegrated for Myanmar and Thailand indicating the growth of savings rate causes the growth of investment rate. Interestingly, reverse causality between savings rate and investment rate has been observed for Hong Kong, Malaysia, Myanmar and Singapore.
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Ghosh and Ostry (1995) use a current-account solvency model for some developing countries to explain the correlation of savings and investment co-movement in advanced and developing economies.
Their approach takes into account demand-side factors. Coakley, Hasan and Smith (1999) extend the study and find that the correlation is low in LDCs, which could be attributed to country-specific macroeconomic policies and not high mobility.
Sinha and Sinha (2004) use a huge sample of 123 countries to estimate the short run and long-run relationship between savings and investment rates using an error correction framework. Results suggest capital should be more mobile for the countries with high per capita income. They also found that the capital is mobile for 16 countries most with a low per-capita income.
3. Data and Methodology Data
For the study, we use annual data on savings and investment from the Reserve Bank of India database (http://www.rbi.org.in). We use annual data for the period 1970-71 to 2001-2002.
Methodology
The empirical exercise comprises two parts: (1) testing for a unit root, I (1), in each series and (2) testing for the number of cointegrating vectors in the system, provided that we cannot reject the null hypothesis of unit root in each of the time series being studied; and causality tests.
1. Unit Root Test To test for a unit root in each series, we employ the Augmented Dickey-Fuller (ADF) (Dickey and Fuller, 1981) methodology. The tests are conducted with and without a deterministic trend (t). The general form of ADF test is estimated by the following regression
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where a0 is constant, t is a deterministic trend, and enough lagged differences (p) are included to ensure that the error term becomes white noise. If the autoregressive representation of Yt contains a unit root, the t-ratio for a1 should be consistent with the hypothesis, a1=0.
However, the ADF test loses power for sufficiently large values of p.
Consequently, we employ another test by Phillips and Peron (PP) (Phillips and Perron, 1988), which is conducted by the following regression:
Where ut is serially correlated.
2. Cointegration Test To investigate the existence of a long-term relationship between savings and investments, we explore existence of any significant long-run relationships among the variables in our model. If the variables are cointegrated, then this will provide statistical evidence for the existence of a long-run relationship.
Though, a set of economic series are not stationary, there may exist some linear combination of the variables which exhibit a dynamic equilibrium in the long run (Engle and Granger, 1987). We employ the maximum-likelihood test procedure established by Johansen and Juselius (1990) and Johansen (1991).
Specifically, if Yt is a vector of n stochastic variables, then there exists a p-lag vector auto regression with Gaussian errors of the following form:
where G1, .. ... Gp-1 and ? are coefficient matrices, zt is a vector of white noise process and k contains all deterministic elements.
The focal point of conducting Johansen’s cointegration tests is to determine the rank (r) of matrix G k. In the present application, there are three possible outcomes. First, it can be of full rank, (r = n), which would imply that the variables are stationary processes, which would contradict the earlier finding of non-stationarity. Second, the rank of k can be zero (r = 0), indic ating that there is no long-run relationship among the variables. In instances when G k is of either
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full rank or zero rank, it will be appropriate to estimate the model in either levels or first differences, respectively. Finally, in the intermediate case when there are at most r cointegrating vectors 0 = r
= n (i.e., reduced rank), it suggests that there are (n -r) common stochastic trends. The number of lags used in the vector auto- regression is chosen based on the evidence provided by Akaike’s Information Criterion (AIC) (see Akaike 1974). The cointegration procedure yields two likelihood ratio test statistics, referred to as the maximum eigenvalue (?-max) test and the trace test, which will help determine which of the possibilities is supported by the data3.
According to Engle and Granger (1987), if two variables are co- integrated, then a more comprehensive test of causality, which has become known as an error-correction model, should be adopted. The VEC specification restricts the long-run behavior of the endogenous variables to converge to their cointegrating relationships while allowing a wide range of short-run dynamics (Granger Causality).
The cointegration term is known as the error correction term since the deviation from long-run equilibrium is corrected gradually through a series of partial short-run adjustments. The representation of VECM is
where α’β Yt-k denotes the error correction term.
4. Empirical Investigation
We have used both ADF and Phillips – Perron tests to find the existence of a unit root in each of the time series. The results are reported in Table 1 and the results suggests all the variables found to be non-stationary in levels but stationary in first difference from at 5% level of significance, that is, all variables are integrated of order 1
3 The trace test statistic is given by Trace = T Sni=r+1 ln (1- ?i) where ?r+1,... n are the (n- r) smallest squared canonical correlations between Yt-k a n d ? Yt series. The ? -max statistic is given by ?-max = T ln (1 - ?r+1) Critical values for each test are given by Osterwald-Lenum, 1993.
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[I (I)]. We apply Cointegration tests between the variables to detect any possible long-run equilibrium between the series. The null of no cointegrating vector can be rejected for all the variables used in the study (see Table 2 and Table 4) and the empirical findings reinforce the conclusions about the presence of long run relationship between savings and Investment.
The Granger Causality Approach
The results of the causality tests reported in Table 3 the empirical findings suggests that there is a significant long-run equilibrium relationship between savings, investment and yield curve. The results are also in consistent with other studies. It is observed from Table 3 with the help Granger Causality test that savings are significantly influencing the investment where as investment is not influencing the savings. Interestingly its observed from Table 6 after including the variable yield curve that savings and investment are showing bi- directional relationship where yield curve is not influenced by either savings or investment.
Variance Decomposition
The variance decomposition results of savings and investment, and savings, investment and yield curve are reported in Table 5 and Table 7 respectively. It is observed from table -5 that the savings are influencing the investment by 92% by the end of ten periods where as investment influencing the savings only by 4% at the end of ten periods. The results of variance decomposition that are reported in Table 7 reveals that the investment and yield curve together influencing the savings by 20% by the end of ten periods, savings and yield curve together influence by 71.5% and 13.45%, respectively, on the variance of Investment. The variance in the yield curve explained by savings and investment are 47.78% and 7.78%, respectively.
5. Conclusion and Discussion
The purpose of this paper is to investigate the relationship between savings and investment. The results are quite interesting showing that savings influencing the investment and where as investment is not influencing the savings. The savings are influencing the investment
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by 95% where as investment is influencing the savings by 5%. This might be because the savings are attracted at higher interest rates since 1970 to 1990 and at higher interest rates no provision for credit and hence the investment would have heavily depended on foreign aid (see.figure.1). The growth in savings could not finance most of India’s investment especially in mid-1980s because they were already at a quite high level. As a result, during the late 1980s India depended heavily on foreign sources that led to a balance of payment crisis in 1990’s. The rise in savings could not finance investment even after liberalization also, this might be because of the new financial innovations in the Indian economy such as GDRs, ADRs and FCCBs coupled with lower interest rates in other countries attracted Indian corporate and hence after liberalization also classical view’s failed. Moreover the investors lost confidence in the stock market and almost every three years once some scam takes place and savings of the public will be looted. Hence we felt that rising interest rates, unorganized sector and scams in the stock market are the root cause of failure of classical economist’s views. Further, we feel that the Indian economy is supporting the argument of Keynes that is savings and investments are two independent variables. . Therefore planned savings are not equal to planned investment.
The results also showed Cointegration between savings, investment and yield spared. Yield spread and investment have not been found to Granger-cause savings. This is a clear indication that savings are independent of investment and yield spread. This might be because of the unorganized sector that is prevailing in the Indian economy.
This is the reason why policy makers are compelled to go for optimal monetary. Fiscal policy mix aimed at low unemployment, low inflation and higher growth for example, reducing Cash Reserve Ratio (expansionary Monetary policy) and more tax benefits (fiscal policy), encourages savings. The reduction in CRR increases money supply and increase in money supply reduces interest rates, increases investment spending and aggregate demand which in turn increases the equilibrium output.
37 References
Apergis, N. and Tsoulfidis, L (1997) The relationship between saving and finance: theory and evidence from E.U. countrie s Research in Economics, Research in Economics, 51, pp. 333–358
Arginon, I. and Roldan, J. (1994) Saving, investment and international capital mobility in E.C. countries European Economic Review, 38, pp. 59–67
Bayoumi, T. (1990) Saving-investment correla tions: immobile capital, government policy, or endogenous behavior? International Monetary Fund Staff Papers, 37, pp. 360–387
Coakley, J., Hasan, F. and Smith, R. (1999) Saving, Investment, and Capital Mobility in LDCs, Review of International Economics, 7, pp.
632–640
De Vita, G and Abbott, A. (2002) Are saving and investment cointegrated? An ARDL bounds testing approach, Economics Letters, 77, pp. 293–299
Feldstein, M. and Horioka, C. (1980) Domestic saving and international capital flows, Economic Journal, 90, pp. 314–329
Frankel, J., Dooley, M. and Mathieson, D. (1986) International capital mobility in developing countries vs. industrial countries: what do savings investment correlations tell us, NBER Working Paper 2043
Ghosh, A. and Ostry, J. (1995) The Current Account in Developing Countries: A Perspective from the Consumption-Smoothing Approach, World Bank Economic Review, 9, pp. 305–33
Jansen, W.J. (1996) Estimating Saving-Investment Correlations:
Evidence for OECD Countries Based on an Error Correction Model, Journal of International Money and Finance, 15, pp. 749–781
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Jansen, W.J. (1998) Interpreting saving–investment correlations, Open Economies Review, 9, pp. 205–217
Krol, R. (1996) International capital mobility: evidence from panel data, Journal of International Money and Finance, 15, pp. 467-474 Leachman, L.L. (1991) Saving, Investment and Capital Mobility Among OECD Countries, Open Economies Review, 2, pp. 137–163 Levy, D. (2000) Investment-Savings Comovement and Capital Mobility: Evidence from Century Long U.S. Time Series, Review of Economic Dynamics, 2, pp. 100-136
Mamingi, N. (1997) Savings-Investment Correlations and Capital Mobility: The Evidence of Developing Countries, Journal of Policy Modeling, 19, pp. 605-626
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Moreno, R. (1997) Saving-investment dynamics and capital mobility in the US and Japan, Journal of International Money and Finance, 16, pp. 234-254
Pelagidis, T. and Mastroyiannis, T. (2003) The saving-investment correlation in Greece, 1960-1997: implications for capital mobility, Journal of Policy Modeling, 25, pp. 609-616
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Sinha, D. (2002) Saving-investment relationships for Japan and other Asian countries, Japan and the World Economy, 14, pp. 1-23
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Sinha, T. and Sinha, D. (2004) “The mother of all puzzles would not go away”, Economic Letters, 82, pp. 259-267
Taylor, A.M. (1996) International Capital Mobility in History: The Saving-Investment Relationship, NBER Working Paper 5743
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Tables
Table: 1 Unit Root Tests
ADF Test Without trend With trend
PP Test Without trend With trend
Savings
Levels 2.05 2.45 2.64 3.12
First Difference
6.66* 5.76* 5.98* 5.23*
Yield Curve
Levels -2.18 -2.43 -1. 76 -2.13
First Difference
–4.83* -5.17 * -7.23* –5.64*
Investment
Levels 2.14 2.03 2.65 2.73 First
Difference
5.43* 6.08* 7.81* 6.46*
Table:2 Cointegration test between investment and savings INVESTMENT SAVINGS
Likelihood 5 Percent 1 Percent Hypothesized Eigenvalue Ratio Critical Value Critical Value No. of CE(s) 0.375772 25.37143 15.41 20.04 None **
0.035542 1.809429 3.76 6.65 At most 1
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Table 3 Vector Error Correction Model for Savings and Investment Error Correction: D(SAVINGS) D(INV)
CointEq1 -0.885130* -0.436759*
(-5.22274) (-3.42578) D(SAVINGS(-1)) 0.076880 0.531154*
(0.45889) (4.21442) D(INV(-1)) 0.068328 -0.106347 (0.23703) (-0.49040)
C 95.97235* 56.88895*
(4.40426) (3.47040)
Table: 4 Cointegration test between investment, savings and Yield Curve
Yield Curve, Savings, Investments
Likelihood 5 Percent 1 Percent Hypothesized Eigenvalue Ratio Critical Value Critical Value No. of CE(s) 0.768701 56.41100 29.68 35.65 None **
0.397456 14.41773 15.41 20.04 At most 1 0.043083 1.233082 3.76 6.65 At most 2 Table: 5 Variance Decomposition of Savings (S) and Investments (IN)
Variance Decomposition of S Variance Decomposition of IN Period S.E. IN S Period S.E. IN S
1 121.08 0.00 100.00 1 196.03 43.24 56.75 2 188.04 3.61 96.38 2 233.98 19.96 80.03 3 228.56 3.42 96.57 3 280.79 15.35 84.64 4 265.43 3.85 96.14 4 315.34 12.47 87.52 5 296.80 3.93 96.06 5 348.44 10.92 89.05 6 325.52 4.06 95.93 6 377.90 9.86 90.13 7 351.77 4.13 95.86 7 405.51 9.12 90.87 8 376.24 4.19 95.80 8 431.24 8.55 91.44 9 399.19 4.23 95.76 9 455.57 8.11 91.88 10 420.91 4.27 95.72 10 478.64 7.76 92.23
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Table: 6 VECM for Savings, Investment and Yield Curve Error Correction: D(IN) D(S) D(Y) CointEq1 -0.001295* -0.001313 2.93E-05*
(-2.13450) (-1.40486) (2.41917) D(IN(-1)) -0.010264 0.726073 0.002057
(-0.03758) (1.72549) (0.37783) D(S(-1)) 0.304571 -0.315432 0.004025
(1.85616) (-1.24753) (1.23032) D(Y(-1)) -11.28563 -24.94767 -0.105803 (-1.27762) (-1.83283) (-0.60070) C 116.3092* 119.3993 -1.315282
(2.75897) (1.83803) (-1.56472)
*(**) denotes rejection of the hypothesis at 5%(1%) significance level Table: 7
Variance Decomposition of S:
Period S.E. S IN Y 1 142.59 100.0 0.00 0.00 2 218.05 96.43 3.52 0.03 3 321.03 93.88 3.76 2.35 4 427.64 90.95 5.13 3.91 5 547.59 88.48 5.66 5.85 6 672.15 86.36 6.29 7.34 7 803.82 84.61 6.66 8.71 8 939.26 83.15 7.02 9.82 9 1078.7 81.92 7.27 10.79 10 1220.9 80.88 7.50 11.61 Variance Decomposition of IN:
Period S.E. S IN Y 1 92.53 60.20 39.79 0.00 2 174.69 74.69 24.27 1.03 3 259.38 74.37 22.57 3.04 4 358.41 74.50 19.64 5.84 5 462.71 73.88 18.40 7.71 6 574.44 73.36 17.23 9.39 7 690.36 72.81 16.49 10.65
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8 810.67 72.34 15.86 11.78 9 933.92 71.91 15.39 12.68 10 1059.8 71.54 14.99 13.45 Variance Decomposition of Y:
Period S.E. S IN Y 1 1.84 11.88 7.80 80.31 2 2.10 20.55 8.35 71.09 3 2.19 20.37 9.42 70.20 4 2.24 19.70 9.40 70.88 5 2.26 19.84 9.39 70.76 6 2.29 21.57 9.15 69.27 7 2.35 25.88 8.76 65.35 8 2.47 32.19 8.37 59.42 9 2.66 39.71 8.01 52.26 10 2.90 47.08 7.78 45.12 Ordering: S IN Y
Fig1. Gross Savings and Investment movement
0 100000 200000 300000 400000 500000 600000
70-71 71-72 72-73 73-74 74-75 75-76 76-77 77-78 78-79 79-80 80-81 81-82 82-83 83-84 84-85 85-86 86-87 87-88 88-89 89-90 90-91 91-92 92-93 1993-94 1994-95 1995-96 1996-97 1997-98 1998-99 1999-00 2000-01 2001-02
0 50000 100000 150000 200000 250000 300000 350000 400000
Gross Savings Inv
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Fig 2. Response of savings and investment for one Standard deviation innovations
0 50 100 150 200
1 2 3 4 5 6 7 8 9 10
IN S
Response of S to One S.D. Innovations
20 40 60 80 100 120 140 160
1 2 3 4 5 6 7 8 9 10
IN S
Response of IN to One S.D. Innovations
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Fig 3. Response of savings, investment and yield curve for one Standard deviation innovations
-100 0 100 200 300 400 500 600
1 2 3 4 5 6 7 8 9 10
S IN Y
Response of S to One S.D. Innovations
0 100 200 300 400 500
1 2 3 4 5 6 7 8 9 10
S IN Y
Response of IN to One S.D. Innovations
-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0
1 2 3 4 5 6 7 8 9 10
S IN Y
Response of Y to One S.D. Innovations
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