Assessing the Relationship between Investment Climate and Domestic Savings in IndiaDr. Manjari AgarwalAssistant Professor

School of Management Studies and CommerceUttarakhand Open University,

HaldwaniState: Uttarakhand

Email Id: magarwal@uou.ac.in, manjarimeh@gmail.comMobile No. +919897033596

Official Address: Dr. Manjari Agarwal, School of Management Studies and Commerce, Uttarakhand Open University, Behind Transport Nagar, Teen Pani By Pass Road, Haldwani-263139

Abstract

Growth in an economy depends upon the savings and investments along with capital-output ratio

which determines level of income. Savings reflects long term economic viability of a country

and investment climate reflects the health of a nation's business environment in totality. Further,

there are broad and interrelated factors that affect the buoyancy of savings and investments in the

country. These can be macro factors at the economy level concerning economy and political

stability and the level of policies adopted towards investments. Hence, the present study assesses

the relationship between savings and investment climate. It tries to assess that how the savings of

the Country is important for shaping the investment climate in the country. It tries to explore the

impact of Gross Domestic Savings on the investment climate of the country.

The study used Correlation and Johansen Co-integration Method for identifying relationship and

on the basis of correlation and co-integration analysis, it was found that savings in the country is

an important factor that have significant impact on the investment climate. This means that Gross

Domestic Savings should be accelerated in the economy for developing healthy investment

climate in the country.

Key Words: Investment Climate, Investments, Savings, Granger Causality

Declaration

I , the undersigned declare that this manuscript is original, has not been published before and is not currently being considered for publication elsewhere.

Dr. Manjari AgarwalAssistant ProfessorSchool of Management Studies and CommerceUttarakhand Open University,Haldwani

Date: 24/11/2015Place: Haldwani, Nainital, Uttarakhand

Assessing the Relationship between Investment Climate and Domestic Savings in India

1. Introduction

Investment is the sacrifice of certain present value for the uncertain future profits. It includes

deciding on various aspects like type, amount timing, grade etc. of investments. Broadly

speaking an investment decision is a trade-off between risk and return. Accordingly, investment

means the engagements of funds with an objective of realizing additional income or growth in

investment value at a future date. Investment has been an activity attributable to the rich and

business class in the past, but today we find that investment is a word commonly used in

households and is quite familiar with people at each cadre. It is an activity by which resources

are actually committed to production. Investments generally promote larger consumption in

future as they lead to more income and larger capital appreciation. Moreover, Government

policies, technology, state of industry and stock of capital also influence expected future

earnings. Further, the amount of investments depends upon surplus funds generated by

individuals and organizations, which in turn get, invested in various investment options.

Therefore, investment is lifeblood of an economy, which flows in all sectors and without which a

country is difficult to prosper.

However, on the other hand, savings are the excess of income over expenditure for any economic

unit. Saving is abstaining from present consumption for a future use. Saving refers to the activity

by which claims to resources, which might be put to current consumption, are set aside and are

made available for other purpose in future. The total volume of savings in an economy therefore

depends mainly upon the size of its material income and its average propensity to consume,

which in turn, is broadly determined by the level and distribution of the income of the people.

Further, savings in an economy is composed of public and private savings. Public saving

comprises of the saving of the Government through budgetary channels and retained earnings of

public enterprises. They are greatly influenced by economic and fiscal policies, tax rates and

investment policies. Private saving includes household sector savings and business savings.

Business saving is also in the form of retained savings, surplus, provisions etc. They are also

called as corporate savings and are greatly influenced by the state of economy and industry, the

fiscal policies etc.

Additionally, finance is a link between savings and investment by which saving are consolidated

and put into the hands of those who are able and willing to invest. It is an activity by which

claims are assembled from the savings either from domestic avenues or from abroad and then

placed in the hands of the investors. Therefore, financial system is significant for capital

formation and this capital formation is yet again necessary for the development of an economy.

Thus, the function of financial system is to establish a bridge between savers and investors and

thereby help in removing gaps in the investment process. Hence, the financial system has an

important role to play in the mobilization of savings and their distribution among the various

productive activities.

Accordingly, growth in an economy depends upon the savings and investments along with

capital-output ratio which determines level of income. Further, by investing in physical assets

capital formation rises, which in turn returns into increase in output. Thus, the total capital -

output ratio for the economy, speaking in macro terms and the total volume of investments in the

economy would determine the growth of output and income.

Particularly in India, the net savers are the household sector whose savings are higher than their

investment, leading to their positive contribution of saving in the economy. On the other hand,

business and Government sectors are negative savers as investments are higher than the savings

leading to a net negative contribution. The foreign sector also contributes to net savings due to

larger inflow of funds through commercial borrowings and other forms of capital inflows. The

flow of funds in the form of saving and investment comes from the financial system and promote

production of goods and service in the real sector, leading to increase in output and incomes of

the people. Thus, overall, the importance of financial system is to increase savings and

investment in the economy and to increase these resources flowing into financial assets, which

are more productive than physical assets.

Accordingly, the flow of funds promotes production of goods and service in the real sector,

leading to a rise in output and income of the people. But sometimes it is also said that increase in

capital without suitable social, economic, political conditions cannot cause growth. On the other

hand favorable development in the conditions can achieve much greater growth with minimum

of capital. Thus, there are broad and interrelated factors that affect the buoyancy of savings and

investments in the country. These can be macro factors at the economy level concerning

economy and political stability and the level of policies adopted towards investments. Further,

these can be macro economic factors such as fiscal, monetary, exchange rate policies and

political stability which affect growth in investments. There can be other factors like governance

and regulatory framework both in the financial and legal systems and it may also include factors

like infrastructural facilities such as transportation, electricity and communication that are

necessary for productive investment in the country. These factors in totality may lead into

determining investment climate of a country. Thus, the investment climate

presents the reasoned expectations about the competitiveness, growth, prosperity

and profitability. As per the definition given by the World Bank in the World Development

Report, 2005 as “The investment climate reflects the many location-specific factors that shape

the opportunities and incentives for firms to invest productively, create jobs, and expand.”

Phillips (2006) divided investment climate into governance and infrastructure components while

stating that healthy investment climate includes economic and political stability, rule of law,

adequate infrastructure, tax and regulations conducive to doing business, labor policies, and

access to finance. Stern (2002) notes that it is the “The policy, institutional, and behavioral

environment, both present and expected, that influences the returns and risks associated with

investment. The notion of investment climate focuses on questions of institutions, governance,

policies, stability, and infrastructure that affect not just the level of capital investment but also

the productivity of existing investments indeed, of all factors of production and the willingness

to make productive investments for the longer term.” This conveys that besides the various

macroeconomic variables that may affects investment climate in the county, even savings also

plays a predominant role in explaining the investment climate in the Country.

Further, before 1991 i.e. before liberalization, investment in the prime areas of the economy was

under the hands of public sector, private investments were discouraged. The Government owned

and controlled almost all banking system and prevented foreign and domestic institutions from

entering it. The insurance and pension fund industry was Government owned and had to invest

most of its assets in low yielding Government securities. The Government set nearly all interest

rates and financial institutions were directed on how they should allocate some of their

investments. Capital Markets were constrained by few companies and corporate houses. Private

companies in capital markets were small and needed Government approval (including

Government determination of price and terms) on new capital issues. But after the reforms of

1991, there has been a substantial and steady liberalisation of the economy, which impedes the

importance of market forces. Permission is granted for the foreign investment to enter into debt

and equity market. Mutual funds territory is opened for private sector. Government control of the

prices of initial public offering has ended. Finally, better regulation, disclosures and investor

protection have greatly changed the savings and investment patterns of the individuals in the

country.

Thus on the basis of the above background the present study assesses the relationship between

savings and investment climate. It tries to assess that how the savings of the Country is important

for shaping the investment climate in the country. It tries to explore the impact of Gross

Domestic Savings on the investment climate of the country. For the purpose of the study,

operationally Investment climate is explained as Trade, investments, industrial and

manufacturing conditions in an economy that influences national and international individuals

and institutions for investing money and acquiring stake.

Savings reflects long term economic viability of a country and investment climate reflects the

health of a nation's business environment in totality.

2. Review of Literature

The relationship between savings and the investment has been incessant study not only in

developing countries but also in developed countries across the globe. Emmanuel Anorou in the

year 2001 conducted a study to explore relationship between savings and investments in context

to ASEAN Countries. The study found long run equilibrium association between the savings and

investments. The study was conducted using Johansen Juselius Co-integration method, Granger

Causality Test and VECM. The study explored that investment causes saving in the cases of

Indonesia and Singapore. For the Philippines, causality runs from saving to investment.

However, in case of Malaysia and Thailand, the study resulted into bi-directional causality

between saving and investment.

Jangili Ramesh in the year 2011 investigated the relationship between savings, investments and

economic growth for India. The study found unidirectional causality between savings and

investments. It was that higher savings and investments contribute into higher economic growth.

It was also found that saving and investment led growth has been contributed by the household

sector. The study also found that savings and investments of private sector endogenously

contributed in the growth of economic growth. Further the study also found that economic

growth is possible due to investments in public sector but the economic growth does not

contribute in the increase of public sector investments.

On an different dimension, Bahmani-Oskooee and Chakrabarti (2005) found that there was a

significant and positive relationship between the ratio of Gross Domestic Investments to GDP

and the ratio of Gross Domestic Savings to GDP. They found that a systematic effect of

‘‘country-size’’ and ‘‘openness’’ on the saving–investment relationship was robust for Higher-

Income Countries. The study was conducted on 126 economies over the period of 1960 to 2000.

The study was concentrated on the exploring the saving-investments relationship for the Higher-

Income, Low Income and Closed economies.

Narayan Paresh Kumar (2005) found that savings and investments are co-integrated for Japan.

Further he explored that bidirectional causality exists between savings and investments. The

direction of causation between saving and investment was explored using the bootstrap

approach. Though moderate rate of correlation between the variables. Further, the study found

that shocks to saving and investment have a permanent effect in case of Japan.

Ramesh Mohan (2006) investigated the relationship between the domestic savings and economic

growth for various economies. The study seeks to determine whether the direction of causality in

these economies is different based on their income class: namely low−income, low−middle

income, upper−middle income, and high−income countries. Granger causality tests conducted by

the researcher revealed that economic growth rate Granger causes growth rate of savings in 13

countries.

Komain Jiranyakul and Tantatape Brahmasrene (2008) tested the relationship between savings

and investments in Indonesia, Philippines and Thailand. The study also applied Bound Testing

Procedure for co-integration, the results does not found positive correlation between savings and

investments in the Indonesia, Philippines and Thailand.

Kaya Huseyin (2010) found the relationship between domestic saving –investment relationship

in Turkey. The researcher applied ARDL Bound testing Procedure and Bai and Perron Procedure

for founding structural breaks. The study found strong long-run relationship between total

investments and savings. However, the study didn’t found any long run relationship between

private savings and investments. The study was conducted over the period to 1984Q1-2007Q3.

Francesca and Fachin (2011) investigated long-run savings-investments relationship in OECD

economies over the period 1970 to 2007. The study concluded that the there is long run savings

investments in 18 OECD economies over the period 1970-2007. The study was undertaken by

using new bootstrap test for panel co integration in terms of short-run and long-run dependence

across units.

Nwogwugwu, & Odulukwe (2012) explored the factors that affects the investments in Nigeria.

The study used Johansen and Juselius Method to find co-integration among the variables. They

found that long run relationship exists among the variables. The study found that market size and

incremental capital ratios are key drivers of investments in case of Nigeria. The paper suggested

that Nigeria have to improve it Investment Climate and infrastructure to attract investments in

the Country.

Christopher K.U (2013) examined that how Nigerian investment climate can be improved for

fostering economic growth in the Country. The study explored that decline in investment rates is

one of the factor for the reduced economic performance. Accordingly, the study recommended

that Nigerian economy should foster investments by providing favorable fiscal regime and by

providing stable macroeconomic framework.

Ogbokor and Musilika (2014) found that there is a unidirectional causality between savings and

investments in Namibia . The study found one way causality between the variables and it was

inferred that Savings causes into Investments in Namibia but not vice versa. The study suggested

that there is no co-integration between savings and investments in the Country. Thus, no long-

run equilibrium relationship was derived between Savings and Investments.

On exploring in the dimension of FDI, Dollar et. al (2005) analysed the importance of

investment climate on exports and FDI for Latin American and Asian Countries using firm level

data. The study concluded that better investment climate in general encourages FDI. All

explanatory variables were considered for the study including physical and financial

infrastructure without giving specific effect of a particular variable.

Similar results were found by Kinda Tidiane (2010) investigated the constraints posed by

investment climate in restricting FDI in seventy seven developing Countries using firm level

data. The study suggested that physical and financial infrastructure magnifies the possibility of

attracting FDI.

Thus, from the review of literature, it was found that many studies have been conducted on

exploring the relationship between savings and investments. Further, studies have also been

undertaken for finding the relationship of investment climate on exports and FDI. However, any

study of exploring the specific relationship between savings and investment climate has not yet

been traced in context to India. In light of this, the study tried to fill this gap in some ways by

attempting to investigate the relationship between savings and investment climate in India using

relevant econometric techniques.

3. Objectives of the Study

The objective of the study is to find out the correlation and co integration between relationship

between savings and investment climate in India during the period from 1980 to 2013.

4. Hypotheses of the Study

H1: There is a positive correlation between savings and investment climate in India.

H2: The variables savings and investment climate in India are co-integrated.

5. Research Methodology

The present study is based on secondary data on Gross Domestic Savings and Investment climate

(proxies) which have been taken from the database of the World Bank (World Development

Indicators). Annual data has been used in the study over the period of 1980 to 2013. The stated

period witnessed significant economic and financial reforms and hence this period would be able

to comprehend about the relationship between the variables.

5.1 Variables of the Study

5.1.1 Gross Domestic Savings: This variable represents the Gross Domestic Product minus final

consumption expenditure/ total consumption in India in a particular year. The data is depicted as

current U.S. dollars. This variable is considered as a proxy of the savings of a country.

Variables for Investigating Investment Climate

As per the literature reviewed various factors has been taken for explaining the investment

climate in the country like macro stability, investments, access to finance, tax regulations, trade

regulations, infrastructure, production capacity, corruption, political stability and the likes.

However, for this study the following variables have been taken to reflect investment climate in

the country.

5.1.2 Investments: Investments refers to the total investments in the country. This ratio between

the investments and GDP portrays economic health [in terms of gross capital formation]. As per

World Bank, it is measured by the total value of the gross fixed capital formation and changes in

inventories and acquisitions less disposals of valuables for a unit or sector. Thus, this variable is

taken majorily for assessing Investment Climate in India.

5.1.3 Trade Openness: This variable Trade is the proxy for Trade Openness. It depicts the sum

of exports and imports of goods and services measured as a share of gross domestic product.

5.1.4 Industrial Climate/Contribution: This is variable for depicting the industrial climate of

an economy which in turns affects Investment Climate in the Country. This is an economic

indicator that measures changes in output for the industrial sector of the economy. The industrial

sector includes manufacturing, mining, and utilities. Data is in constant US$, and not seasonally

adjusted. The base year is 2005.

5.1.5 Value Addition by Manufacturing Sector: It is the proxy for manufacturing

contribution in the overall investment climate of the country. Thus, it depicts the total valued

added by the Manufacturing units in intensifying Investment Climate of India. As per the World

Bank, Value added is the net output of a sector after adding up all outputs and subtracting

intermediate inputs. It is calculated without making deductions for depreciation of fabricated

assets or depletion and degradation of natural resources. The data is depicted as current U.S.

dollars.

5.2 Method used

5.2.1 Correlation

The correlation assess the relationship between two variables and for studying the same various

methods and tools are used. This statistical tool is widely used for inferring the relationship

between the variables of the study. Two variables are termed to be correlated when increment or

decrement in one variable result into corresponding increment or decrement in the other. Thus, it

explains that change in one variable leads to subsequent change in the other variable. It assesses

the degree and direction of the relationship between the variables. However, correlation does not

depict co-integration of the variables.

A mathematical formula for measuring the intensity or the magnitude of linear relationship

between two variables series was suggested by Karl Pearson. The method is;

r=∑ dx dy

√∑ dx2 dy2 or cov (x , y )σ x σ y

5.2.2Co-integration

Variables are said to be co integrated if long run equilibrium relationship is found among them.

If the two series of Integrated of order one, then the partial difference between them might be

stable around a fixed mean. This narrates that the series are drifting together almost at the same

rate. Such series are said to be co-integrated and the resultant vectors (1,-β0 , β1 , β2¿ are called as

co integrating vectors.

Engle and Granger (1987) defined co-integration as the components of the vector x t=¿) are said

to be co integrated of order d, b, denoted by x t CT (d , b) explained by if, all components of x t

are integrated of order d. and there exists co integrating vector β=( β1 , β2 ,………. )such that the

linear combination βx t=β1 x1t +β2 x2 t …….+ βn xntis integrated of order (d-b) where b>0.

Johansen (1995) developed a maximum likelihood estimation procedure based on reduced rank

regression method. It is used for testing co-integration by interpreting the independent linear

combinations for a set of time series variables that has stationary roots. The Johansen test is

based on λ trace and λmax test statistics for assessing the co integration among the variables The

test for the number of characteristic roots that are insignificantly different from unity. The trace

and max statistics are depicted by ;

λ trace(r )=−T∑ ln (1− λ̂i)

λmax (r ,r+1 )=−Tln ln (1− λ̂r+1)

Where

λ̂ i=The estimated values of the characteristics roots obtained from the estimated π matrix

T= the number of usable observations.

The trace statistics tests the null hypothesis that the number of co-integrating vectors are less

than or equal to r against a general alternative. Maximum Eigen value statistics tests a null of r

co integrating vectors against the specific alternative of r+1.

6. Results

On the basis of the tests used in e-views, the following results were discerned;

6.1 Correlation:

The Table 1 depicts the findings of Karl Pearson Coefficient of Correlation. The figures of

correlation are duplicated in the matrix. It was found that strong positive correlation existed

between the Gross Domestic Savings and the factors that represented Investment Climate in the

Country. It can be interpreted that there is a sound and positive correlation between Gross

Domestic Savings and Industrial Climate. Similarly, there is a positive relationship between

Savings and Investments. Strong Positive relationship was also found between Savings and

Trade Openness. On the similar grounds strong positive correlation was also found between

Savings and Valued addition by Manufacturing Sector.

Thus it can be inferred that higher domestic savings can lead to spur Investment Climate in the

Country.

Table: 1 Correlation between Gross Domestic Savings and Proxies for Investment Climate

in India.

LNGDS LNINDUSTRY LNINVST LNTRADE LNMANU

LNGDS  1.000000  0.996952  0.951106  0.962366  0.994841

LNINDUSTRY  0.996952  1.000000  0.940061  0.966709  0.999424

LNINVST  0.951106  0.940061  1.000000  0.924990  0.939161

LNTRADE  0.962366  0.966709  0.924990  1.000000  0.965359

LNMANU  0.994841  0.999424  0.939161  0.965359  1.000000

6.2 Johansen Co-integration Test

To assess the linear combination of integrated variables, Johansen Co-integration was applied to

infer the co-integration between Domestic Savings and Investment Climate. The variable

Domestic Savings and proxies for investment climate were pretested to assess their order of

integration. The Augmented Dickey Fuller Test (ADF) was used in the present study on all the

series individually to assess the order of integration. ADF was used in E views 7 to infer the

stationarity of the variables. Accordingly, it was found that all the variables are integrated of

order 1 [I (1)], i.e. they are stationary at first difference (Table 2). Further, a VAR Lag Order

Selection Criteria was used in to assess the lag length criteria. The Johansen test is quite sensitive

to the lag length; therefore the lag length test was used in e views. It was found that t-statistic for

two lags is significant at the specified critical value. Hence, one lag criteria were found

appropriate according to these LR (Likelihood Ratio Criterion), AIC (Akaike Information

Criterion), SIC (Schwarz Information Criterion), FPE (Final Prediction Error), HQ (Hannan-

Quinn Information Criterion) criterion. Therefore, lag length 2 has been selected on the basis of

multivariate generalizations of the all the criteria. The undifferenced data was used in Johansen

Co-integration Test in EViews to assess the co-integration among the series. Further, the same

lag length as obtained from VAR Lag Order Selection Criteria in E Views has been taken.

As a guideline if the absolute value of the computed Trace and Maximum Eigen Value exceeds

the critical value then the null hypothesis of no co-integration is rejected and at least one way co

integration among the variables is accepted at 5% level of significance. On the basis of the result

of the test as depicted in Table No. 2 it was found that as per Trace statistics 84.266 is greater

than the critical value of 64.819 at 5% significance level, therefore, it is possible to reject the null

hypothesis of no co-integrating vectors and accept the alternative one or more co integrating

equations for the two series. Moreover, The Maximum Eigen Value test results that Maximum

Eigen statistic 38.055 exceeds the 33.87 percent critical value of the λmaxeigen and hence it is

possible to reject the null hypothesis of no co-integrating vectors and accept the alternative one

or more co-integrating equations for Domestic Savings and proxies for Investment Climate

series. Thus, the null hypothesis of no co-integration is strictly rejected at 5% level of

significance, implying long run relationship among the variables. Thus, it may be inferred that

there exist long run equilibrium relationship between Gross Domestic savings and Investment

Climate in India.

7. Conclusion

On the basis of the results derived by applying the Correlation and Co-integration test, it was

found that strong correlation was found between Domestic Savings and Investment Climate. This

means these two influences each other in the long run.

Thus, on the basis of correlation and co-integration analysis, it was found that null hypothesis of

no correlation and co-integration between Domestic savings and Investment Climate is strictly

rejected and the alternate hypothesis of significant correlation and co-integration among the

Domestic Savings and proxies of investment climate has been accepted. The results denotes that

savings in the country is an important factor that have significant impact on the investment

climate. This means that Gross Domestic Savings should be accelerated in the economy for

developing healthy investment climate in the country. Accordingly, this Gross Domestic Savings

may intensify Investment Climate in long run which will eventually results in attracting foreign

savings and thereby maintaining high growth rate in the economy.

Thus in the nutshell, Domestic Savings and Investment Climate are strongly related to each other

in India.

Tables: Results of the Test used

Table: 2 Results from Johansen Co-integration TestVAR Lag Order Selection CriteriaEndogenous variables: LNGDS LNINDUSTRY LNINVST LNTRADE LNMANU Exogenous variables: C Date: 07/01/15 Time: 08:47Sample: 1975 2013Included observations: 32

 Lag LogL LR FPE AIC SC HQ

0  162.6416 NA   3.62e-11 -9.852598 -9.623576 -9.7766831  278.5395   188.3341*   1.26e-13*  -15.53372*  -14.15959*  -15.07823*2  303.3228  32.52809  1.45e-13 -15.52017 -13.00094 -14.68512

 * indicates lag order selected by the criterion LR: sequential modified LR test statistic (each test at 5% level) FPE: Final prediction error AIC: Akaike information criterion SC: Schwarz information criterion HQ: Hannan-Quinn information criterion

Date: 07/02/15 Time: 07:38

Sample (adjusted): 1982 2013Included observations: 32 after adjustmentsTrend assumption: Linear deterministic trendSeries: LNGDS LNINDUSTRY LNINVST LNTRADE LNMANU Lags interval (in first differences): 1 to 1

Unrestricted Cointegration Rank Test (Trace)

Hypothesized Trace 0.05No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None *  0.695540  84.26690  69.81889  0.0023At most 1  0.468501  46.21199  47.85613  0.0708At most 2  0.407922  25.98625  29.79707  0.1291At most 3  0.213420  9.214491  15.49471  0.3459At most 4  0.046763  1.532535  3.841466  0.2157

 Trace test indicates 1 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values

Unrestricted Cointegration Rank Test (Maximum Eigenvalue)

Hypothesized Max-Eigen 0.05No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None *  0.695540  38.05491  33.87687  0.0149At most 1  0.468501  20.22573  27.58434  0.3257At most 2  0.407922  16.77176  21.13162  0.1830At most 3  0.213420  7.681956  14.26460  0.4120At most 4  0.046763  1.532535  3.841466  0.2157

 Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values

 Unrestricted Cointegrating Coefficients (normalized by b'*S11*b=I): 

LNGDS LNINDUSTRY LNINVST LNTRADE LNMANU 31.42263 -106.6407 -12.83069  2.112042  78.25086-14.55113  16.94014 -5.813558 -3.027525  3.120172 19.37197 -15.04070 -10.23365 -2.594479 -3.858295-6.684580  10.75392  16.73250 -7.224706 -3.088693-4.730101  26.00906 -4.457240 -3.632573 -16.90053

 Unrestricted Adjustment Coefficients (alpha): 

D(LNGDS) -0.051952 -0.012062 -0.009564 -0.048917  0.001545D(LNINDUSTRY

) -0.019645 -0.027326  0.002158 -0.034074 -0.003508D(LNINVST) -0.018777  0.016109  0.013542 -0.031882  0.003026D(LNTRADE) -0.009756 -0.012144  0.022788  0.001010  0.010848D(LNMANU) -0.027218 -0.031634  0.006818 -0.031422 -0.005796

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