A Study of Impact Investment in South-East Asian Countries

 

Harshita Gupta1, Mohd Azeem2

1Independent Researcher, Department of Commerce and Business Studies, Jamia Millia Islamia, New Delhi, India

2PG Student (second year), Department of Commerce and Business Studies, Jamia Millia Islamia, New Delhi, India

*Corresponding Author Email: harshita2381995@gmail.com, m.azeem1996@gmail.com

 

ABSTRACT:

The emergence of the concept of impact investment came alive a decade ago and became a new class of social finance assets. The aim with which this term was introduced was to affect a positive social impact and aid in construction of a stable investment market. The investment platform so created does not only cater to the investor’s impulse to invest their capital where their morals lie but also impacts the nation as a whole over the mere financial benefit through the overall societal development. Furthermore, impact investment also focuses on increasing the influx of private capital investments towards eradicating environmental and societal issues. Thus, owing to the ever-increasing importance of impact investment, this paper aims to study the concept and analyze the role of impact investment in south-east Asian countries.

 

KEYWORDS: Impact Investment, Socially Responsible Investing, South-east Asian counties, PIIs, DFIs.

JEL: C12, G23, N25

 

 


INTRODUCTION:

The ever-increasing need and demand for purpose oriented and socially responsible finance has carved the way for impact investment. Not only does it refute the old believe that projects benefiting the society should be looked after by philanthropy and financial projects by financial investors, but also open new avenues of investment for the mainstream investors.

 

Impact investments can be defined as those investments which intend to bring measurable positive advancement of environment and society as well as monetary returns. Impact investments can earn a range of returns, starting from a rate lower than the market rate to the existing market rate. The said rate of return depends upon the strategic objectives of the investor. Further, these investments can be done in developed and developing markets, both.

 

The rising market for impact investment results into capital flow around the world to aid in deal with the urgent problems like renewable energy, conservation, sustainable agriculture, microfinance, and affordable and easily accessible basic services such as education, healthcare, and housing.

 

FEATURES OF IMPACT INVESTMENT:

The features of impact investment practice are as follows:

 

INTENTIONALITY:

For an investment to be called as an impact investment, it is imperative to have an investor intending to bring advancement to environmental or societal cause through his investments.

 

INVESTMENT WITH RETURN EXPECTATIONS: Though the purpose of impact investments is to bring progress in social and environmental sectors, a rate of return on capital or at least the return of invested capital is still expected.

RANGE OF RETURN EXPECTATIONS AND ASSET CLASSES:

Impact investment supports investments in varying asset classes. These assets categories include and are not restricted to venture capital, cash equivalents, private equity, and fixed income. The rate of return from such projects can be market (risk-adjusted) rate or concessionary (less than market) rate.

 

IMPACT MEASUREMENT:

The practice of impact investment includes complete transparency and accountability, which is entrusted with the investors. Thus, it is crucial for an investor involved in impact investment to assess and report the so far accomplishments and improvements undertaken regarding the projects benefiting the society and environment.

 

How an investor views such impact measurements varies with an investor’s goals and potential. Thus, an investor’s objective and aspiration are generally underlined in his choice of measurement. Commonly, the elements of impact measurement include the following:

·       Construction and announcement of societal and environmental goals to the stakeholders.

·       Establishment of performance metrics, preferably with reference to standardized metrics, to measure the effectiveness of impact investments.

·       The investee’s performance is observed and supervised against the pre-established targets.

·       Regular reports on progress and performance of societal and environmental projects are disclosed to all stakeholders.

 

Unlike socially responsible investments, impact investing includes setting of objectives, constructing performance standards, and metrics to assess the progress of the pre-defined targets. The literal meaning of ‘impact’ is said to be ‘results attributed to a specific action or intervention’, however, impact assessment particularly indicates the outcome of an investment. Therefore, highlighting the key performance indicators with respect to the outcomes of a particular investment becomes central to the investors. Recent developments in the impact investing market have seen establishment of standards for assessing impact investments. IRIS (Impact Report and Investing Standards) are widely used parameters to assess financial, societal, and environmental performance of an organization. Investor’s intentions of initiating a society or environmental change through investment are central to impact investing, there by differentiating itself from other asset classes. Hence, IRIS standards construct a catalogue of social impact targets such as agricultural productivity, food security, financial services and community development, access to clean water, health improvement, etc. Selection of targets is followed by setting up of a performance metric which servers as desired benchmark for impact assessment. Impact assessment also target impact return and potential risk. Investments are assessed by consult rating agencies like GIIRS (Global Impact Investing Rating System) or by the investor’s team. On contrary to finance market investing, impact investment carries ‘mission drift’ risk. Mission drift risk is defined as the risk that leads to shifting of activities of an organization away from their primary concern or objective. This risk can prove to be tricky to mitigate, particularly when an investor wants to exit the market. Despite the likeliness of the occurrence of mission drift, many investors choose to overlook the precautionary actions.

 

Institutional Investors:

An institutional investor is commonly known as a huge organization with substantial liquid asset (mainly cash) reserves. These cash reserves are vested in various securities and assets. Generally, six types of institutional investors operate in the market and they are insurance companies, mutual funds, pension funds, hedge funds, commercial banks, and endowment funds. However, operating companies having vesting their returns in numerous asset classes, might also fall under the category of institutional investors.

 

Thus, by definition, an institutional investor is a non-bank entity or organization that invests and trades securities, on behalf of its members, in share volumes or dollar value so high that it is regarded for discounted commission and enjoys preferential treatment. Further, Institutional investors are believed to be self-protected and hugely informative. Hence, they are not restricted by many protective or safety regulations.

 

Development Financial Institutions:

A development finance institution (DFI) or development bank is a financial institution that provides risk capital for economic development projects. Generally, their projects are funded by charitable institutions, donations, or governments as their agendas are, seldomly, supported by commercial or private investors. These finance institutions propagate SRI (socially responsible investing) and impact investing and are often a part of Government’s developmental aid.

 

DFIs blankets bilateral development banks, community development financial institution, microfinance institutions, multilateral development banks and revolving loan funds. Typically backed by developed countries, a significant position is held by these institutions when it comes to procure credit in higher risk loan category or higher risk guarantees or risky equity positions. They help funding the private sector that promotes investments benefiting the society in developing economies of the world.

 

Impact Investment: Need of the hour:

Traditionally, the funding for causes relating to environment and society was undertaken, exclusively, by philanthropic charities and financial investments were looked after by market investors. Impact investing challenges this long-standing notion.It diversifies the market opportunities by creating new avenues for financial investors to earn monetary returns while investing in projects benefiting the society and environment. Impact investment market experiences a rise in its participants as more and more investors enter daily. Various types of investors join in impact investing with varying motivations. While, financial advisors, banks, wealth managers, and pension funds joins this market to provide investment avenues incurring returns along with catering to environmental and social needs to their clients, institutions and individuals alike; Family foundations and institutions focus on gaining leverage over significant assets to aid in growth of the main societal goal or environment objective along with increasing their financial returns. Evidence of financial feasibility for private sector investors, having vested interests in a particular social or environmental cause, is ensured by Development finance institutions and Government investors.

 

Thus, the presented paper attempts to add value to the existing literature by furthering the conceptual knowledge of impact investment and divulging into its significance and need for the world economy, with special reference to DFIs and Institutional investors operating in South-East Asia.

 

LITERATURE REVIEW:

(Grabenwarter and Liechtenstein, 2011) interviewed and analyzed the investors of impact investing market. The study implied that impact investment can be explained by the lack of a trade-off relation between financial profits and societal impact, disputing the general ‘misconception’ that impact investment usually entails a trade-off. (McWade, 2012) presented a case where his study explained that social investors could become a significant link between the social investing market and financial market by infusing fresh capital in developing countries. These finding were based on the study of existing literature on social investment and financial investment. (Hebb, 2013) presented a conceptual overview of impact investment. This study became the editorial introduction to a special edition of the Journal of Sustainable Finance and Investment. (Jackson, 2013) attempted to explain the link between theory of change and impact investment and how the former is a key element to better understand the theoretical framework of the latter. (Reeder and Colantonio, 2013) developed an approach to understand impact measurement of the capital invested by investors for social or environmental benefits. (Evans, 2013) put value addition in conceptual understanding of impact investment. The research brings out a contract theory to address a theoretical strategy making framework which enables impact investors to improve their financial performance along with benefiting the society. (Lazzarini et al., 2014) the purpose of this study was to comprehend an investor’s approach with regards to social and financial goals. It also provides a theoretical framework describing the time of alignment of these goals. (Erickson, 2014) examined societal impact investments with respect to secondary markets. The study was made with reference to various actors and instruments of investment. (Nicholls and Schwartz, 2014) examined different demand sources available for financial instrument SIBs (Social Impact Bonds) and sector-wise social impact investing. (Brandstetter and Lehner, 2015) evaluated the current standing of social and financial risk and profits (returns) through the filter of impact investment. Their research suggests a model for integration of the social investment parameters with conventional portfolio maximization, which takes risk and return into account. (Wharton Social Impact Initiative, Gray, Ashburn, Douglas, and Jeffers, 2015) collected data from impact investing markets and funds and analyzed it. Mission of the investee’s firm and exiting an impact investment, both parameters were taken into consideration. (Clarkin and L. Cangioni, 2015) adds value to the existing literature. The study provided a deep and well researched conceptual base of impact investment, highlighting its emergence and features. (Nicholls and Emerson, 2015) evaluated the conceptual data available on social impact investing and established its relationship with the wide-spread concept of social finance. Impact investing was found to be a sub-topic of social finance, conceptually. (Schwartz, Jones, and Nicholls, 2015) explained the development of intermediaries in the impact investing market which has resulted into increased flow of demand and supply. Further, the study has also classified the market infrastructures. (Nicholls, Nicholls, and Emerson, 2015) attempted to clarify the concept of impact measurement with special reference to social finance. Their research also brought out a contingency strategic model which aids in decision making regarding the application of impact measurement. (Ormiston, Charlton, Donald, and Seymour, 2015) interviewed and analyzed the data, thus collected, from existing investors of social impact market. The collection of data was centered upon the problems these investors faces while collecting market information. (Daggers and Nicholls, 2016) reviewed the existing literation on SII and provided detailed research base, for the future researchers, on the subject while attempting to provide conceptual overview on impact investment. (Pandit and Tamhane, 2017) brought out the emergence of impact investing in India in their report. Further ahead, they examined the possible challenges hampering the growth of impact investing in Indian investors and also brought out the significance and need of impact investment.

 

OBJECTIVES:

i.    To study the concept of Impact investing.

ii. To examine the relationship between the Impact investment made by PII and DFI in South-East Asian countries.

iii. To verify Stationarity in data collected over the years of the study.

 

METHODOLOGY:

Population:

The paper consists of study of 11 South East Asian countries which are Myanmar, Cambodia, East Timor, Indonesia, Laos, East Timor, Singapore, Malaysia, Thailand, Philippines, and Vietnam.

 

Time Period:

The period of study is from 2007to 2017.

 

Data Used:

The secondary data of capital deployed by PIIs and DFIs in impact investment available on GIIN website is used. Apart from this existing research paper were also used.

 

Tools and Techniques:

The data available was analyzed using various tools like Unit Root test, Granger Causality test and Coefficient of Variation. The Software used forthe above analysis was EViews for Unit Root test and Granger Causality test. For Descriptive statistics, SPSS was used.

 

HYPOTHESIS:

The following hypothesis are tested in our study:

Hypothesis-1

H0: Capital Deployed by PIIs does not have unit root.

H1: Capital Deployed by PIIs have unit root

 

Hypothesis-2

Ho: Capital Deployed by DFIs does not have unit root.

H1: Capital Deployed by DFIs have unit root

 

Hypothesis-3

Ho: Capital Deployed by DFIs does not granger cause Capital Deployed by PIIs

H1: Capital Deployed by DFIs t granger cause Capital Deployed by PIIs

 

Hypothesis-4

Ho: Capital Deployed by PIIs does not granger cause Capital Deployed by DFIs

H1: Capital Deployed by PIIs granger cause Capital Deployed by DFIs

FINDINGS:

The summary of the data set is shown below :

 

Table 1: Descriptive Statistics using SPSS

Statistics

 

VAR01

VAR02

N

Valid

11

11

Missing

0

0

Mean

82.2091

1025.1091

Median

36.0000

993.8000

Std. Deviation

72.39191

382.97118

Range

182.00

1345.20

Minimum

10.00

441.90

Maximum

192.00

1787.10

C.V.

.8806

.3736

Skewness

.497

.357

Kurtosis

-1.662

.439

 

The above table shows the descriptive statistics of VAR01(Capital deployed by PIIs) and VAR02 (Capital deployed by DFIs). The variability of the capital deployed by both investors is measured using Coefficient of Variation. VAR01 have high Variability in capital deployed and VAR02 have low variability in capital deployed.

 

I. Unit Test:

The unit root test on data was done using Augmented Dickey Fuller and Dickey Fuller T test. The analysishas shown presence of unit root in both SER01 (Capital deployed by PIIs) and SER02 (Capital deployed by DFIs) using both methods except test done on SER02 using Dickey-Fuller GLS (ERS) test at 5% and 10% Level.

 

(A) Augmented Dickey Fuller:

It is the most standard test used for unit root but it has low power of test and is not robust for serial correlation.

 

Table 2: ADF test on SER01 (Capital deployed by PIIs) using EViews

Null Hypothesis: SER01 has as unit root

Exogenous: Constant

Lag Length: 0 (Automatic – based on SIC, maxlag=1

 

t-Statistic

Prob*

Augmented Dickey-Fuller test statistic

-0.932166

0.7322

Test critical values:

1% level

-4.297073

 

5% level

-3.212696

 

10% level

-2.747676

 

*Mackinno (1996) one-sided p-values.

 

From the Above Table obtained from EViews on SER01 (Capital Deployed by PIIs) for 11 years through Augmented Dickey- Fuller test at various levels, we can see that at 1%, 5% and 10% significance level test, the critical value is -4.297073, -3.212696 and -2.747676 and the t test statistical value is -0.932166. Since the calculated ADF Test-statistic value is greater than the critical values at various levels, we can’t reject Ho. That means the PII Capital Deployed series has aunit root and is non-stationary.

Table 3: ADF test on SER02 (Capital deployed by DFIs) using EViews

Null Hypothesis: SER01 has as unit root

Exogenous: Constant

Lag Length: 0 (Automatic – based on SIC, maxlag=1

 

t-Statistic

Elliott-Rothenberg-Stock DF-GLS test statistic

-1.029381

Test critical values:

1% level

-2.816740

5% level

-1.982344

10% level

-1.601144

*MacKinnon (1996)

 

From the Above Table obtained from EViews on SER02(Capital Deployed by DFIs) for 11 years through Augmented Dickey- Fuller test at various levels, we can see that at 1%, 5% and 10% significance level test, the critical value is -4.297073, -3.212696 and -2.747676 and the t test statistical value is -1.987869. Since the calculated ADF Test-statistic value is greater than the critical values at various levels, we can’t reject Ho. That means the PII Capital Deployed series has a unit root and is non-stationary.

 

(B) Dickey-Fuller GLS (ERS) test:

It is the other unit test used on data. It has highest power of test to find presence of unit root among all tests used for finding unit root. It shows the presence of unit root at level.

 

Table 4: Dickey-Fuller GLS test on SER01 (Capital deployed by PIIs) using EViews

Null Hypothesis: SER02 has as unit root

Exogenous: Constant

Lag Length: 0 (Automatic – based on SIC, maxlag=1

 

t-Statistic

Elliott-Rothenberg-Stock DF-GLS test statistic

-2.109848

Test critical values:

1% level

-2.816740

5% level

-1.982344

10% level

-1.601144

*MacKinnon (1996)

 

From the Above Table obtained from EViews on SER01(Capital Deployed by PIIs) for 11 years through Dickey-Fuller GLS (ERS) test at various levels, we can see that at 1%, 5% and 10% significance level test, the critical value is -2.816740, -1.982344, -1.601144 and the t test statistical value is -1.029381. Since the calculatedDickey-Fuller GLS (ERS) TestStatistic value is greater than the critical values at various levels, we can’t reject Ho. That means the PII Capital Deployed series has n unit root andis non-stationary.

 

Table 5: Dickey-Fuller GLS test on SER02 (Capital deployed by DFIs) using EViews

Null Hypothesis: SER02 has as unit root

Exogenous: Constant

Lag Length: 0 (Automatic – based on SIC, maxlag=1

 

t-Statistic

Prob*

Augmented Dickey-Fuller test statistic

-1.987869

0.2863

Test critical values:

1% level

-4.297073

 

5% level

-3.212696

 

10% level

-2.747676

 

*Mackinno (1996) one-sided p-values.

From the Above Table obtained from EViews on SER02 (Capital Deployed by DFIs) for 11 years through Dickey-Fuller GLS (ERS) test at various levels. We can see that at 1%, 5% and 10% significance level test critical value are -2.816740, -1.982344, -1.601144 and the t test statistical value is -2.109848. Since the calculatedDickey-Fuller GLS (ERS) TestStatistic value is greater than the critical values at 1% level but it is smaller than the critical values at 5% and 10% level, we cannot conclude to reject Ho at 1% level but we can reject null hypothesis at 5% and 10% level. That means the PII Capital Deployed series has aunit root and is a non-stationary at 1% level but at 5% and 10% level it does not have unit root and the data is stationary.

 

II. Granger Causality Test:

It is used for finding the relationship between variables and checks the direction.

Using Granger Causality test on SER01(Capital Deployed by DFIs) and SER02 (Capital Deployed by DFIs) through EViewssoftware, the result obtained is given below:

 

Table 6: Granger Causality test on SER01 and SER02 (Capital deployed by PIIs and DFIs) using EViews

Pairwise Granger Causality Tests

Date: 12/08/18 Time: 13:15

Sample: 2007-2017

Lags: 2

Null Hypothesis

Obs

F-Statistic

Prob.

SER02 does not Granger Cause SER01

SER01 does not Granger Cause SER02

9

0.51753

0.6311

-

2.04080

0.2450

 

From the table, we can see that SER02 does not Granger Cause SER01 have probability of 0.6311, and 0.3689 is the probability of SER02 Granger Cause SER01.At the same time, SER01 does not Granger Cause SER02have probability of 0.245and 0.755 is the probability of SER01 Granger Cause SER02.

 

In both the cases the Probability values 0.6311 and 0.2450 are greater than 0.05. So, we reject the null hypothesis and accept the alternative hypothesis. It means Capital deployed by PIIs and DFIs are influenced by each other. Hence there is bi directional causality between DFIs and PIIs capital deployed.

 

CONCLUSION:

The analysis of data reveals that the capital deployed by PIIs and DFIs have unit root. And the same result was obtained through Dickey-Fuller GLS unit root test which have the highest power of test among all types of unit test. Unit root test done through Augmented Dickey Fuller and Dickey Fuller t test at level of capital deployed series of PIIs and DFIs accepted the null hypothesis of presence of unit roots which means their data is non-stationary except the analysis of data of DFI capital deployed at 5% and 10% donethrough Dickey-Fuller t test which rejected the null hypothesis showing its data series to be stationary. The relationship between variables of two series using Granger Causality test have shown that both Capital deployed by PIIs and DFIs influenced by each other The study can be useful for understanding the concept of impact investing and especially in South-East Asian countries. The result of the study can be used to make decisions with respect to impact investing by various kinds of investors.

 

LIMITATIONS:

The paper presented has scope limited to South East Asian countries only. The study which is being done is confined to 11 years period. Further the data analysis was done using limited tools like Selected Unit Root tests and Granger Causality Test. The said research can be undertaken using different countries and region, different tools and with a different time frame.

 

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Received on 07.01.2019         Modified on 20.01.2019

Accepted on 19.02.2019      ©AandV Publications All right reserved

Res.  J. Humanities and Social Sciences. 2019; 10(2):531-536.  

DOI: 10.5958/2321-5828.2019.00087.1