world development volume 59 issue 2014 [doi 10.1016%2fj.worlddev.2014.01.030] garg, reetika; dua,...

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Foreign Portfolio Investment Flows to India:

Determinants and Analysis

REETIKA GARG and PAMI DUA *

University of Delhi, India

Summary. This paper analyzes the macroeconomic determinants of portfolio flows to India and finds that lower exchange rate vol-atility and greater risk diversification opportunities are conducive to portfolio flows. However, higher equity returns of other emergingmarkets discourage these flows. Other conventional determinants of portfolio flows are domestic equity performance, exchange rate,interest rate differential and domestic output growth. An analysis of disaggregated portfolio flows shows that determinants of FIIsare similar to aggregate portfolio flows, while ADR/GDRs are significantly influenced only by domestic equity returns, exchange rate,domestic output growth, and foreign output growth.2014 Elsevier Ltd. All rights reserved.

Key words FPI, FII, ADR/GDRs, ARDL model

1. INTRODUCTION

According to international finance theory, foreign portfolioinvestment (FPI) flows are an inevitable outcome of investorswanting to invest across countries in order to diversify the riskof their portfolio and achieve higher returns. Some of the stud-ies that have documented the benefits of diversification acrosscountries include Grubel (1968), Levy and Sarnat (1970),Solnik (1974a), Grauer and Hakansson (1987), Harvey(1991), and De Santis and Gerard (1997). From the point ofview of the host country, especially the developing countries,portfolio flows are considered to play a pivotal role in bridging

the savinginvestment gap and providing the much neededforeign exchange to finance current account deficit. The devel-oping countries across the globe have been making consciousefforts to attract foreign financial capital which provides animpetus to economic growth and financial market develop-ment in the host country. DellAriccia et al. (2008) andObstfeld (2009) review the literature related to the benefitsof financial flows from the host country perspective.

The growing removal of restrictions on the trading of inter-national financial assets has led to a surge in the flow of finan-cial capital across the globe in the past two decades. Theinvestment by foreign investors is mainly geared toward thefast growing developing economies, including India, whichprovide profitable investment opportunities. Table 1indicatesthat portfolio equity flows to developing countries increased

five times from US $ 14 billion in 2000 to US $67 billion in2005 and almost nine times to US$ 128 billion in 2010. Ofall the developing countries the major recipients of portfolioequity flows have been China, Brazil, India, Russia, and SouthAfrica out of which China, India, and Brazil account for al-most 70% of the total portfolio equity flows to all developingcountries (Figure 1).

Notwithstanding the beneficial impacts of portfolio flows tothe investor as well as to the host country, these flows havealso been a source of concern. The foreign investor has to takeinto consideration country and currency risk in addition toother factors compared to investing in the home country.From the host country perspective, portfolio flows are proneto reversals and volatility. This is evident from the historicaland recent financial crises that have brought into focus the fact

that these flows can expose the countries to new macroeco-nomic challenges.

India has not remained untouched by the developments inthe global financial markets due to greater linkages of the In-dian markets with the international markets. During the Asiancrisis as well as during the recent sub-prime crisis, overall bal-ance of payments deteriorated due to massive reversal of port-folio flows. Table 1 indicates that in 2008, portfolio equityflows to the Indian economy faced the sharpest reversal fol-lowed by the largest bounce back in 2009 compared to otherdeveloping countries. In 2010, while flows to other economiesdeclined or increased marginally, portfolio equity flows to In-

dia increased by almost 90% compared to 2009, which indi-cates the confidence of the investor in the Indian economythat can be attributed to strong domestic fundamentals.

In the recent uncertain global scenario, it is important tounderstand the factors that drive portfolio flows, to facilitateefficient management of these flows in order to avoid anyimbalances arising out of large inflows beyond the absorptivecapacity of the economy or sudden reversal of financial capitalleading to a situation of capital crunch.

The literature that analyzes the determinants of portfolioflows to developing countries has debated on the relative sig-nificance of domestic and external factors. Studies by Calvo,Leiderman, and Reinhart (1993, 1996), Taylor and Sarno(1997), Fernaindez-Arias (1996) and Kim (2000), Byrne andFiess (2011) have emphasized that global factors like decline

in interest rates and slowdown in growth of industrializedcountries, have pushed capital to developing economies. Onthe other hand Bohn and Tesar (1996), The World Bank(1997), Mody, Taylor, and Kim (2001) and Felices andOrskaug (2008), find that domestic factors like equity index,sufficient availability of domestic reserves, and countrycreditworthiness have attracted portfolio flows to developing

* We thank the anonymous referees for their valuable comments and su-

ggestions. We are also grateful for the comments and suggestions received

on preliminary versions of this paper presented at the 48th Annual Con-

ference of The Indian Econometric Society (TIES) and The Asian Meeting

of the Econometric Society (AMES). Final revision accepted: January 25,

2014.

World DevelopmentVol. 59, pp. 1628, 2014 2014 Elsevier Ltd. All rights reserved.

0305-750X/$ - see front matter

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countries. Another set of studies in literature advocate compli-mentarity between domestic and external factors. These in-cludeChuhan, Claessens, and Mamingi (1993), Montiel andReinhart (1999)andDe Vita and Kyaw (2007) among others.

To explore further, this study examines the macroeconomicdeterminants of portfolio flows to India. The determinants ofdisaggregated components of portfolio flows i.e., ForeignInstitutional Investment flows (FII) and American/GlobalDepository Receipts (ADR/GDR) are also analyzed, in orderto assess whether different components of portfolio flows aredriven by similar or different factors.

This paper makes an important contribution to the litera-ture. Firstly, most of the literature that analyzes the determi-nants of portfolio flows has concentrated on the FIIcomponent only. ADR/GDR flows have not received muchattention despite the fact that it has increasingly being usedto raise foreign capital. This study will examine the macroeco-nomic determinants of not only FII but also ADR/GDR flowsto India in order to fulfill the existing gap in the literature.

Furthermore, this study examines a wider set of potentialdeterminants of FII flows to India compared to other studiespertaining to the Indian economy such asChakrabarti (2001),Kaur and Dhillon (2010), Kumar (2011), Srinivasan and Kal-aivani (2013). While the study byGordon and Gupta (2003)includes a wide range of determinants of portfolio flows, theOrdinary Least Squares (OLS) methodology is used that

may yield biased and inconsistent estimates if the regressors

are endogenous. This study follows the AutoregressiveDistributed Lag (ARDL) approach to cointegration for esti-mating the long-run coefficients which overcomes such prob-lems. The long-run coefficients are unbiased and the t-testsare also valid, even if the regressors included in the specifica-tion are endogenous (Harris & Sollis, 2003).

The following section discusses the trends along with thepolicy reforms related to portfolio flows in India. Section 3describes the potential factors that drive portfolio flows. Sec-tion4 discusses the empirical model, data, and methodology,used for estimation. Section5discusses the econometric results

and Section6 concludes.

2. TRENDS IN PORTFOLIO FLOWS AND POLICYREFORMS

In 1992, the Indian government allowed FIIs to invest in thefinancial markets which required registration of FIIs with theSecurities and Exchange Board of India (SEBI). SEBI pre-scribes certain norms which are to be followed by the FIIsfor registration that includes compliance with Foreign Ex-change Management Act 1999 for which they need permissionfrom Reserve Bank of India (RBI) and payment of registra-tion fees. Overtime, the regulatory measures of SEBI have be-come liberal, which mainly included procedural relaxations

related to entry and exit of FIIs, raising the ceilings on

Table 1. Portfolio Equity Flows to Developing Countries (US $ Billion)

Years All Developing Countries China Brazil South Africa Russian Federation India Mexico Thailand

2000 13.95 6.91 3.07 4.17 0.15 2.48 0.45 0.902001 5.60 0.80 2.50 1.00 0.50 2.90 0.20 0.402002 5.80 2.20 2.00 0.40 2.60 1.00 0.10 0.502003 24.30 7.70 3.00 0.70 0.40 8.20 0.10 1.802004 39.90 10.90 2.10 6.70 0.20 9.10 2.50 1.30

2005 67.47 20.35 6.45 7.23 0.10 12.15 3.35 5.122006 107.70 42.86 7.72 14.96 6.48 9.51 2.80 5.242007 132.95 18.51 26.22 8.67 18.67 32.86 0.48 4.272008 53.36 8.72 7.56 4.71 15.00 15.03 3.50 3.802009 108.75 28.16 37.07 9.36 3.37 21.11 4.17 1.332010 128.41 31.36 37.68 5.83 4.80 39.97 0.64 3.43

Source: Global Development Finance, various issues.

4.30

5.47

11.36

14.15

26.44

31.84

1.75

3.17

8.40

21.87

20.44

30.48

2.14

3.52

8.86

20.68

21.37

30.69

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00

Russian Federation

Thailand

South Africa

Brazil

India

China

2000-2010

2005-2010

2000-2004

Figure 1. Share of portfolio equity flows in total flows to all developing countries (percentages). Source: Calculations based on data from various issues of

Global Development Finance.

FOREIGN PORTFOLIO INVESTMENT FLOWS TO INDIA: DETERMINANTS AND ANALYSIS 17
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investment in companies and greater coverage related to typesof funds that could invest as FIIs and the instruments in whichFIIs can invest. Initially only broad based funds were allowedto invest in the Indian markets, but overtime foreign firms arealso allowed and even the definition of broad based funds hasalso been widened. Presently, the insurance companies, banks,hedge funds, mutual funds, asset management companies and

pension funds form the majority of FIIs investing in India.

1

Initially FIIs were allowed to invest only in the listed securitiesof Indian companies, but overtime they have been allowed toinvest in unlisted securities, government securities, commercialpaper, and derivatives.

With regard to ADR/GDRs, Indian companies were al-lowed to raise capital by issuing depository receipts in theworld financial markets in 1992. Initially in the 1990s Indianfirms refrained from listing in the US stock exchanges becauseof the stringent accounting standard requirements of US Gen-erally Accepted Accounting Principles (GAAP) and Securitiesand Exchange Commission (SEC). The most attractive desti-nation of the Indian firms was London Stock Exchange andLuxemburg Stock Exchange. However, as observed by Pag-ano, Roell, and Zechner (2002), poor liquidity in the European

stock exchanges made Indian companies change their prefer-ences and they started listing on US stock exchanges. Thiswas also because, overtime, Indian companies improved theiraccounting standards, reflecting greater transparency, whichallowed these firms to list in the US stock markets as well. Ini-tially most of the Indian companies listing in the US, listed onthe National Association of Securities Dealers AutomatedQuotation System (NASDAQ) and then later on New YorkStock Exchange (NYSE) as well because of the stricter normsof NYSE.

InFigure 2, the annual trends in FII investment show thatafter 199293, FII flows increased steadily till 199697. In199798 and 199899, India experienced a massive reversalin FII investment following the Asian crisis. Although Indian

economy was not directly involved in the crisis, and the inter-vention by RBI in the currency market as well as imposition ofcapital controls was used to insulate the Indian economy fromthe crisis (Dua & Sinha, 2007), still the foreign investment

flows to the Indian economy declined, specially the FIIs. How-ever as compared to other East Asian countries, the magnitudeof adverse impact on India was small and short lived.

In 19992000 FII flows to the Indian economy bouncedback to their pre-crisis levels, which reflected investor confi-dence in the Indian markets. In 200203 FII flows dipped toUS$ 2.77 billion but in 200304, increased to US$ 10.9 billion.

In 2003, a working group that was set up for streamlining theprocedures of FIIs, which suggested a relaxation in the proce-dure of taking approval from both SEBI and RBI, to an ap-proval only from SEBI. Moreover, in 2003, currencyhedging was allowed for FIIs without any restrictions.

From 200304 to 200607 FII flows followed a downwardtrend. In 200607, in the wake of rising inflationary pressuresand heightened liquidity, SEBI along with RBI tightened thecontrols on inflows and also liberalized outflows. Interest rateson Non-resident Indian (NRI) deposits were decreased, limitswere imposed on external commercial borrowings, restrictionon foreign investment by Indian companies and mutual fundswere eased. In 200708, FII flows surged to US$ 20 billion inthe backdrop of heightened global liquidity and bullishdomestic stock markets. In 200809, it was the huge reversal

in FII flows that created havoc in the Indian financial marketsand led to a sharp decline in the total portfolio investmentflows to India. However, 200910 saw a massive revival ofFII flows to India.

The trends in ADR/GDRs show that in the initial yearsafter liberalization, ADR/GDR investment flows were greaterthan FII flows received by the country. From 199596 to200203, India received considerable amount of ADR/GDRinvestment compared to FIIs. It was only after 200304 thatthe magnitude of ADR/GDR investment seemed to be smallcompared to FIIs but this was due to gigantic rise in FIIinvestment rather than a fall in ADR/GDR investment. TheADR/GDR flows displayed an increasing trend from 200304 onward and reached their historical peak in 200708.

What is also noticeable is that for the period 200203 to200607, while FII flows declined, ADR/GDR investmentflows increased. It may be possible that ADR/GDRs werebeing used to circumvent restrictions on FII flows. The Report

-16000

-6000

4000

14000

24000

34000

US$Million

ADR/GDR FII

Offshore Funds FPI

Figure 2. Trends in Components of FPI flows. Source: Reserve Bank of India, Handbook of Statistics 2013.

18 WORLD DEVELOPMENT
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of the Working Group on Foreign Investment by Ministry ofFinance, Government of India (2010), mentions that if thereare restrictions on entry and exit in the Indian financial mar-kets, then the foreign investor may direct its investment toinstruments of the Indian firms that are traded in financialmarkets outside India.

The composition of aggregate portfolio flows (Table 2)

shows that the share of FIIs in has always been higher thanthe share of investment flows received through ADR/GDRssince 199697, except in 200203 and in 200607. However,ADR/GDRs comprise a significant proportion of portfolioflows. Offshore funds have always been a minor portion ofthe total portfolio flows, however in the recent years since200809, India has not been receiving any investment on ac-count of offshore funds.

3. DETERMINANTS OF PORTFOLIO FLOWS

The discussion in the previous section indicates that Indiangovernment has followed a policy of gradual liberalization ofrestrictions on portfolio flows to India. This has been done

mainly through liberalizing the investment limits, relaxingthe eligibility requirement of the firms that could invest in In-dia and opening up greater number of instruments for foreigninvestment. This implies a reduction in barriers to capital flowsand gradual increase in the degree of integration of the Indianfinancial markets with the global markets. In this context thestudies on asset pricing which are relevant for the Indian econ-omy are those in the vein ofBekaert and Harvey (1995, 2003),Stulz (1999), Carrieri, Errunza, and Hogan (2007) andArouriand Foulquier (2012)among others that discuss asset pricing,assuming time varying integration of financial markets, whichis a realistic assumption to make for emerging economies.

The early works on asset pricing have not taken intoaccount the fact that financial markets may not be perfectly

integrated which could be due to the presence of capital flowrestrictions, taxes, informational asymmetry, or other risk fac-tors that deter free movement of capital across borders. Forinstance studies by Solnik (1974b), Stulz (1981a), Adler and

Dumas (1983)and Lewis (1999)that have extended the assetpricing models byMarkowitz (1959), Sharpe (1964)andLint-ner (1965) to an international setting, assume perfect capitalmarkets. Asset pricing models based on such assumptionsare not applicable to most of the emerging market economies,where there are restrictions to flow of capital and the financialmarkets in these countries are only partially integrated with

the global markets (Harvey, 1995).Some studies of international asset pricing have relaxed theassumption of perfectly integrated capital markets and assumepartial integration of financial markets such as Black (1974),Stulz (1981b), Errunza and Losq (1985, 1989), Eun and Jana-kiraman (1986), Alexander, Eun, and Janakiramanan (1987),Hietala (1989), Errunza, Losq, and Padmanabhan (1992),Cooper and Kaplanis (2000). A major implication of thesestudies is that assets to which investors have unrestricted ac-cess are priced lower than the assets to which investors haverestricted access. Although these studies assume partial inte-gration of markets, they hold the degree of financial marketintegration to be constant overtime. But what is more appro-priate is, to assume time varying market integration, which isdone in the studies byBekaert and Harvey (1995, 2003), Stulz

(1999), Carrieri et al. (2007)andArouri and Foulquier (2012)among others, that is better suited in the context of reductionin capital controls and gradual liberalization in emerging mar-kets overtime.

The degree of market integration can have an important im-pact on expected returns, which depends on the risk of thecountry portfolio. While in the case of complete integrationof financial markets, risk of a country portfolio depends onits covariance with the world market returns, in the case ofcomplete segregation of markets, it depends on the variancein its own returns. In case of partially integrated emergingeconomy, the investor expects to be compensated for the riskof the country portfolio that depends on boththe covariancewith the world market returns (as in the case of complete inte-

gration of markets) as well as the variance in its own returns(as in the case of complete segregation of markets) (Bekaert& Harvey, 1995). Moreover, greater the degree of integrationof the countrys financial markets with the world markets,higher is the influence of global factors in determining the for-eign investment received by the country (Bekaert, 1995).

It is expected that as the market integration increases, ex-pected returns from holding the countrys assets decreaseand correlation of countrys financial markets with the worldmarkets increases, which reduces the possibilities of risk diver-sification (Bekaert, 1995; Bekaert & Harvey, 2000, 2002).

The aforesaid asset pricing models that assume partial inte-gration of markets and time varying degree of integration ofmarkets indicate some of the factors such as correlation be-tween domestic stock returns and global equity returns, vari-

ance in domestic equity returns and global factors i.e.,global output growth and interest rates, that may influence ex-pected returns from assets in emerging economies and hencethe flow of capital to these countries. Based on these and otherfactors that are considered to be important in the literature,this study seeks to analyze the determinants of portfolio flowsto India. The potential variables used to explain portfolioflows are described in detail.

Domestic Stock Market Performance: The domestic stockmarket performance can have a positive or a negativeinfluence on portfolio flows. An increase in portfolio flowsin response to bullish stock markets (Agarwal, 1997; Chakrab-arti, 2001; Rai & Banumurthy, 2004; Richards, 2002) suggeststhat foreign investors are chasing returns. On the other hand,the relationship can turn negative if foreign investors buy (sell)

Table 2. Components of Total Portfolio Inflows (Percentage in Total FPI)

Years a. Global/Americandepository

receipts

b. Foreigninstitutional

investors

c. Offshore fundsand others

199697 41.24 58.15 0.60199798 35.28 53.56 11.16199899 442.62 639.34 96.72199900 25.38 70.56 4.06200001 30.11 66.92 2.97

200102 23.60 74.47 1.93200203 61.29 38.51 0.20200304 4.03 95.97 0.00200405 6.58 93.25 0.17200506 20.43 79.46 0.11200607 53.92 46.05 0.03200708 24.37 74.54 1.09200809 8.39 108.39 0.00200910 10.28 89.72 0.00201011 6.51 93.49 0.00201112 3.43 96.57 0.00201213* 0.69 101.47 0.00

Source: Calculations based on data from Reserve Bank of India, Hand-book of Statistics 2013.* Calculation based on provisional data.

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when equity index is falling (rising), with the expectation thatreturns will rise (fall) in future (Gordon & Gupta, 2003; Grif-fin, Nardari, & Stulz, 2002).

Domestic Growth: Domestic output growth indicates thesoundness of macroeconomic and institutional fundamentalsof the host country, which are important in attracting capitalflows. A higher economic growth of the host country indicates

rapidly expanding economic activity which in turn wouldmean greater profitability from investing in the corporate sec-tor.

Exchange Rate:In a world of flexible exchange rate, capitalcan earn a return not only through yields on assets, but alsothrough a change in exchange rate overtime. Appreciation ofcurrency of the host country is an additional avenue of gainingreturns for foreign investors.

Currency Risk: Volatility in exchange rate is expected tohave negative impact on portfolio flows because it representsa higher degree of uncertainty in the returns received by for-eign investor in terms of his home currency. Persson andSvensson (1989)observe that increased exchange rate variabil-ity has negative impact on international trade and capitalflows.

Country Risk:Availability of sufficient liquidity in the hostcountry indicates that in the event of withdrawal of funds bythe investors, the country does not default on the payments.It is expected that countries with sufficient stock of re-servesto cover for imports and meet short run obliga-tionsare perceived to be credit worthy and the probabilityof their defaulting is less. Thus lower financial risk of the coun-try attracts greater portfolio flows.

Stock Return Risk:While investing in a developing country,where stock markets are characterized by volatility, the for-eign investor takes into account not only the returns frominvestment in an asset, but also the variability associated withthe returns. This is important in determining the expected re-turns from investment. Unless the investor is sufficiently com-

pensated for the variance in returns, a higher variability inreturns discourages foreign investment.Risk Diversification: An investor invests in assets across

countries to diversify the risk of the portfolio. The objectiveof the investor is to reduce the variance of the overall portfo-lio. If the addition of a countrys assets reduces the overall riskof the portfolio (even if the variance of its own returns is high),there are potential gains from diversifying internationally.This depends on the degree of correlation between the domes-tic and the foreign markets. The lower the co-movement ofdomestic equity returns with the global equity returns, thegreater the benefits from diversification and hence higher theportfolio flows received by a country.

Global Liquidity: Output growth in industrialized countriesrepresents the profitability of investment in the corporate sec-

tor in these countries. A higher economic growth in industrial-ized countries could mean greater profits and hence greaterfunds available for investment in developing countries. Onthe other hand a slowdown in the economic growth could alsomean that the firms do not find it profitable to invest in theirhome country and hence they chose to invest in developingcountries. In both the cases economic growth in industrializedcountries could lead to an increased global liquidity. The evi-dence in this regard is mixed. While Calvoet al. (1993, 1996),Taylor and Sarno (1997) among others indicate a negativerelation between financial flows to developing countries andgrowth in industrial countries, Verma and Prakash (2011)indicate a positive relation for the case of India.

Interest Rate Differential: Interest rate differential betweenthe host and the source country also determines portfolio

flows. The traditional open economy macroeconomic modelsproposed by Mundell and Fleming suggest that in a worldwhere capital is mobile and exchange rates are fixed, capitalflows occur so as to restore interest parity, i.e., capital movesin or out of the country till the domestic and foreign interestrates equalize. Investors invest their capital wherever the inter-est rates adjusted for risk are higher. While most of the studies

in the literature find that portfolio flows are sensitive todomestic and/or foreign interest rates, Verma and Prakash(2011)find that FII flows to India are not sensitive to interestrate differentials.

Returns in Other Emerging Markets: While diversifyingglobally, foreign investors can either invest in emerging mar-kets or they can invest in financial markets of the industrial-ized countries. According to Buckberg (1996) investorsfollow a two step process in deciding capital allocation.Firstly, the total capital to be invested in emerging marketsis determined and then a part of that capital is allocated toeach emerging market depending on returns. This implies thatif total capital allocated to emerging markets is highwhichwill happen if equity returns in emerging markets is risingthen each emerging economy has a higher probability of

receiving greater amount of capital.Alternately, it is also important to view different emerging

economies as competitors to each other, where each economyis trying its best to receive a greater share of foreign invest-ment. In this case, higher equity returns in emerging marketsimplies a greater probability of foreign investment being re-ceived by competing economies.

Capital Controls: Although capital controls are used as atool to manage financial flows, the evidence regarding theireffectiveness in the literature 2 is mixed. The broad view inthe literature is that capital controls may not be effective ininfluencing the overall magnitude of capital flows, but theydo affect the composition.

The variables described above capture different aspects of

the mechanism that drive portfolio flows which can be put to-gether to obtain the empirical model that is discussed in thenext section.

4. EMPIRICAL MODEL, DATA AND METHODOLOGY

This study estimates the long-run macro econometric modelto analyze the determinants of portfolio flows to India. Basedon the factors discussed in the previous section, the followingempirical model is estimated:

Ft a bSt cet rCRt dMSCIt hiit fyt gy

t

qVolet xalphat ubetat W cclt. . . 1

b > or < 0; c > 0; r > 0; d > or < 0; h > 0; f > 0; g > or

< 0; q < 0; x < 0; u < 0

Net portfolio inflows, FII flows and ADR/GDR flows denom-inated in US $ billion are taken as the dependent variable ( F).Domestic stock market performance (S) is measured by themonthly average of the BSE sensitivity index. Exchange rate(e) is defined asthe nominal effective exchange rate 36 country(export based).3 Currency risk proxied by volatility inexchange rates (Vol(e)) is calculated using the GeneralizedAutoregressive Conditional Heteroskedasticity (GARCH)method.4 Interest rate differential (i i*) is defined as thedifference between 3 month Treasury bill rate for India

and 3 month London Inter Bank Offered Rate (LIBOR).

5

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Domestic output growth (y) is defined as the annual growthrate of index of industrial production (IIP) for India. Globalliquidity proxied by foreign output growth (y*) is measuredby annual growth rate of IIP for Organization for EconomicCo-operation and Development (OECD) countries. Both thegrowth series are calculated as the difference between loga-rithm of index of a particular month and the twelfth lagged

month. This also helps to remove the seasonality in the IIP ser-ies if there existsany.Country risk 6 is calculated using the methodology that is

similar to the one used by International Country Risk Guide(ICRG) for calculating financial risk. Based on the scale sug-gested by ICRG, risk points were assigned to foreign debt asa percentage of Gross Domestic Product (GDP) (annual data),net international liquidity as months of import cover (annualdata), foreign debt service as a percentage of exports of goodsand services (annual data) and current account as a percentageof exports of goods and services (quarterly data). These pointswere then aggregated to obtain credit risk indicator (CR)(which took the same values for three months in each quarter),where a higher risk point total suggests lower risk and vice ver-sa. The components of the indicator are based on ratios and

not absolute values which ensures comparability overtime.Emerging market MSCI Index 7 (MSCI) is used to capturethe stock performance in emerging markets. Stock return risk(alpha) is captured by twelve month standard deviation inMSCI-India. Risk Diversification (beta) is measured as thetwelve month correlation between MSCI-India and MSCI-World. 8 To capture the liberal reform measures in 200304(cc1) and restrictive capital controls (that restricted inflowsand liberalized outflows) in 200607 (cc2) dummy variablesare used. The impact of recent subprime crisis that originatedin US, but affected the real and financial flows across the globe,is captured through a dummy. When global liquidity is affecteddue to any given exogenous reason, the flows of financialinvestments to emerging economies get hit. Thus it is necessary

to control for such effects. The main sources of the data used inthe analysis are Handbook of Statistics and Current Statisticsof RBI, International Financial Statistics of InternationalMonetary Fund (IMF),www.mscibarra.com, Federal ReserveBank and Global Development Finance reports.

(a) Methodology

The DickeyFuller Test with Generalised Least SquaresDetrending (DFGLS) proposed by Elliott, Rothenberg, andStock (1996) is used to test if a series contains a unit root.To estimate the long-run coefficients, the Autoregressive Dis-tributed Lag (ARDL) approach to co-integration proposedby Pesaran and Shin (1999) and Pesaran, Shin, and Smith(2001)is used. This is because it is applicable irrespective of

the fact that the variables included in the analysis are I(0) orI(1) or fractionally integrated.

The augmented ARDL (p, q1, q2, . . . qk) is given by the fol-lowing equation (Pesaran & Pesaran, 1997; Pesaran et al., 2001)

uL;pytXk

i1

biL; qixit k0wt et 8t 1; . . . ; n 2

where

uL;p 1u1Lu2L2 . . . upL

p 3

biL; qi bi bi1L bi2L2 . . .biqiL

qi

8i 1; 2 . . . ; k 4

yt is an independent variable, L is the lag operator such thatLpyt= ytp, wt is the s 1 vector of the deterministic vari-ables such as the intercept term, time trends, dummies, orexogenous variables with fixed lags. xitrepresentsith indepen-dent variable where i= 1, 2, . . ., kwhere lag order ofith var-iable is qi.

The long-run slope coefficients of the endogenous variables

are estimated as follows:

Ui bi1; qi

/1; ^p8i 1; 2; . . . ; k 5

where pand qi,i= 1, 2, . . .,kare the selected (estimated) val-ues of ^pand qi, i= 1, 2, . . ., k.Ui gives the long-run impact ofxit on yt.The error correction model derived from the ARDL frame-

work is used to test for Granger causality. This is done by test-ing the joint significance of the error correction term and thelags of each of the explanatory variables.

Before proceeding with the ARDL estimation it is importantto test whether there exists a long-run relation between thevariables, for which bounds testing approach is used.

To test whether there exists a long-run relation between thevariables, when all the variables are integrated of different or-der i.e., I(0) or I(1), bounds testing approach is used. This in-volves testing the null hypothesis of p= p1= p2= . . . =pk= 0 against the alternative hypothesis of p1 p2 . . . pk 0 in the following equation

Dytc0 pyt1 p1x1;t1 p2x2;t1 . . . pkxk;t1

Xm

i1

wDytiXm

i1

w1iDx1;tiXm

i1

w2iDx2;ti

. . .Xm

i1

wkiDxk;ti lt 6

Pesaran and Pesaran (1997)have two sets of asymptotic criti-cal values for the F-statistic. One is the lower bound criticalvalue which assumes that all the variables are integrate of or-der zero i.e., I(0). The other is the upper bound critical valuewhich assumes that all the variables are I(1). If the calculatedF-statistic is greater than the upper bound critical value thenthe null hypothesis of no long-run relationship is rejectedand if it falls below the lower bound critical value, then thenull hypothesis of no long-run relationship is not rejected.

5. ECONOMETRIC RESULTS

(a) Results of the unit root test and the bounds test

The DFGLS unit root tests9

suggest that Indian outputgrowth, foreign output growth, volatility in exchange rateand beta of Indian market are stationary. All the other vari-ables i.e., net FPI inflows, net FII inflows, net ADR/GDRflows, domestic stock market index, exchange rate, emergingmarket stock returns index, stock return risk, asset reservesto imports ratio, and interest rate differential are integratedof order one. Since the variables under consideration are amix ofI(0) andI(1), hence the ARDL method was found suit-able for estimation.

The first step is to check for cointegration between thevariables using the ARDL bounds test suggested by Pesaranet al. (2001). A maximum lag value of four was used forimplementing the test. The dummy variable for crisis was alsoincluded in the FPI and FII specifications, since it was

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observed that these flows were affected the most during the re-cent subprime crisis. For ADR/GDR a dummy variable tocontrol for three outlier observations was included. For allthe specifications, the null hypothesis of no long-run relation-ship is rejected, as the calculated F-statistic lies above theupper bound critical Fvalue at 95% (Tables 35).

Once the bounds test ensures the presence of long-run coin-

tegration between the variables, the next step is to estimate theARDL model and obtain the long-run coefficients and thenperform Granger causality tests based on the short run errorcorrection model. The optimal lag length for the variables ischosen such that there is no residual serial correlation in theunderlying model.

(b)Aggregate foreign portfolio investment inflows and foreigninstitutional investment inflows

The decomposition of aggregate FPI flows shows that FIIflows are a dominant component of FPI flows and the peaksand the troughs in total FPI flows closely matches with thatin FII flows (Figure 2), hence as expected, the estimation resultof aggregate FPI flows is quite similar to that of FII flows

(Tables 6 and 7).For all the specifications of FPI and FII (Tables 6 and 7), the

coefficient on domestic stock market performance is found tobe positive and significant indicating that well performingdomestic stock markets attract flows to India. The aggregateFPI flows as well as the FII component respond in a positiveway to an appreciating exchange rate. This is because an appre-ciating exchange rate provides additional source of returns toforeign investors which induces them to invest in India.

The improvement in performance of emerging marketstocks has a negative impact on FII as well as aggregate FPIflows to India. This implies that when the overall returns frominvesting in emerging market stocks increases, foreign invest-ment received by India decreases. This can be analyzed in

terms of the income effect and the substitution effect. Whenemerging markets as a whole perform better, then income ef-fect would mean greater allocation of funds to emerging mar-kets by foreign investor, because of which the probability thatgreater funds are allotted to each emerging economy increases.Once the allocation of funds to emerging markets is done, thesubstitution effect comes into play i.e., each of the emergingeconomies competes with the others for receiving these flows.In case of India, substitution effect dominates the income effectwith regard to FII flows. Similar result holds for aggregateFPI flows.

The differential between domestic and foreign interest rateshas a positive association with portfolio and FII flows toIndia. This can be attributed to increasing investment in debtsecurities which are sensitive to interest rate differentials. InIndia, very recently during the crisis period, it has beenobserved that FIIs have increasingly been investing in debtinstruments, which are less risky. 10

Domestic output growth is positive and significant in all thespecifications for both FPI as well as FII. An increasingdomestic output growth indicates higher levels of economicactivity and hence increasing corporate profits which is anindicator of better investment opportunities in the country.Thus to a foreign investor better growth performance of thehost country is a signal that demand for investment in the hostcountry will remain high as it is a rapidly expanding economy,and hence the probability that returns from investment willfall in future will be low. Moreover, rising domestic outputgrowth also reflects strong economic fundamentals, whichencourages the investors to have greater faith in the Indianeconomy.

The long-run coefficient on volatility in exchange rate is neg-ative and significant in all the specifications, indicating that

higher currency risk discourages FIIs and aggregate portfolioflows to India. This is because increasing exchange rate vola-tility corresponds to increasing uncertainties in the returnsthat will be received by the foreign investors in terms of theirown currency. Also, if the volatility in exchange rate is attrib-utable to factors within the host country, then it also indicatesthe presence of destabilizing forces within the economy.

The negative and significant coefficient on risk diversifica-tion measured by beta indicates that if beta increases i.e.,comovement between Indian and global equity increases, thenaggregate FPI flows and FII flows decrease. On the other handdeclining beta indicates lower correlation between Indian andglobal equity returns that presents the opportunities for reduc-ing the risk of the portfolio by investing in Indian markets.

This confirms the fact that FIIs invest in India with the objec-tive of diversifying risks.The capital control dummy for restrictive policy reforms in

200607 is significant for FII but insignificant for aggregateFPI flows. This implies that the measures taken to restrict in-flows and liberalize outflows were significant in reducing FIIinvestment flows to India but aggregate portfolio flows re-mained unaffected. The liberal measures taken in 200304did not significantly influence both FPI as well as FII.

As expected, greater risk in asset returns discourages FIIflows as well as aggregate portfolio flows, however the effect

Table 3. ARDL Bounds Testing Approach for Cointegration Dependant Variable: Net Foreign Portfolio Investment flows (US$ Billion) 1995M102011M10

F-Statistic [p-value] Critical Fvalue (95%) Critical Fvalue (90%) Result

Lower Bound Upper Bound Lower Bound Upper Bound

Model I: FPI = f (S, e, CR,MSCI, i i*, y, y*, Vol (e), Dummy)F(9,146)=3.8679[.000] 2.272 3.447 1.956 3.085 Reject H0

Model II: FPI = f (S, e, MSCI, i i*, y, Vol (e), Dummy)F(7,156)=5.2065[.000] 2.476 3.646 2.141 3.250 Reject H0

Model III: FPI = f (S, e, MSCI, i i*, y, Vol (e),alpha, Dummy)F(8,151)=4.2707[.000] 2.365 3.553 2.035 3.153 Reject H0

Model IV: FPI = f (S, e, MSCI, i i*, y, Vol (e), beta, Dummy)F(8,151)=4.9321[.000] 2.365 3.553 2.035 3.153 Reject H0

Model V: FPI = f (S, e, MSCI, i i*, y, Vol (e), cc1, cc2, Dummy)F(7,154)=5.1915[.000] 2.476 3.646 2.141 3.250 Reject H0

H0: No long-run relationship.

H1: There exists long-run relationship.



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is statistically insignificant. Country risk is not significant ininfluencing portfolio flows as well as FII flows indicating high-er investor confidence in the Indian economy. Portfolio flowsand FIIs are driven more by domestic output growth com-

pared to foreign output growth.The Granger causality tests based on the error correction

model of the ARDL specification shows that all the variablesthat are significant determinants also significantly Grangercause FPI and FII flows to India. This means that they helpto improve the predictive performance of these flows (Tables8 and 9).

(c) American/global depository receipts

ADR/GDRs present a mechanism of indirect investment byforeign investor in the stocks of Indian companies. This pre-vents them from the complication of conversion of foreign cur-rency into domestic currency (rupees) and does not involve any

additional entry costs that would otherwise be incurred if the

foreign investor decided to invest directly in the Indian financialmarkets. In case, the investment by foreign investor is done di-rectly in the domestic (Indian) companies through the financialmarkets, then the foreign investor has to monitor not only the

changes in the price of assets in which he decides to invest, butalso the changes in exchange rate as the process involves con-version of foreign currency into domestic (Indian) currency.

But this does not imply that investment through ADR/GDRs is independent of exchange rate changes. It is onlythe case that the burden of currency risk is not explicitly borneby the foreign investor, who purchases the receipts. For in-stance, when ADR/GDRs are issued, then each receipt isbacked by a certain number of shares of the domestic (Indian)company. Once this ratio between ADR/GDR shares anddomestic shares is decided, the price of each receipt (ADR/GDR) is decided. The pricing decision is based on the priceof the shares of the company in the domestic (Indian) market,and the corresponding exchange rate between the two econo-

mies.

Table 5. ARDL Bounds Testing Approach for Cointegration Dependant Variable: Net American/Global Depository Receipt Inflows (US$ Billion) 1995M102011M10



Model I : ADR = f (S, e, CR,MSCI, i i*, y, y*, Vol (e), Dummy)F(9,146)=5.2562[.000] 2.272 3.447 1.956 3.085 Reject H0

Model II: ADR = f (S, e, MSCI, i i*, y, y*, Vol (e), Dummy)F(8,151)=6.1459[.000] 2.365 3.553 2.035 3.153 Reject H0

Model III: ADR = f (S, e, i i*, y, y*, Dummy)F(6,161)=9.9744[.000] 2.649 3.805 2.262 3.367 Reject H0

Model IV: ADR = f (S, e, y, y*, Dummy)

F(5,166)=12.8455[.000] 2.850 4.049 2.425 3.574 Reject H0

Model V: ADR = f (S, e, y, y*

, alpha, Dummy)F(6,161)=10.1512[.000] 2.649 3.805 2.262 3.367 Reject H0

Model VI: ADR = f (S, e, y, y*, beta, Dummy)

F(6,161)= 9.6733[.000] 2.649 3.805 2.262 3.367 Reject H0

Model VII: ADR = f (S, e, y, y*, cc1, cc2, Dummy)

F(5,164)=11.0678[.000] 2.850 4.049 2.425 3.574 Reject H0

H0: No long-run relationship.H1: There exists long-run relationship.

Table 4. ARDL Bounds Testing Approach for Cointegration Dependant Variable: Net Foreign Institutional Investment flows (US$ Billion) 1995M102011M10



Model I : FII = f (S, e, CR,MSCI, i i*, y, y*, Vol (e), Dummy)F(9,146)=4.0513[.000] 2.272 3.447 1.956 3.085 Reject H0

Model II: FII = f (S, e, MSCI, i i*, y, Vol (e), Dummy)F(7,156)=5.3720[.000] 2.476 3.646 2.141 3.250 Reject H0

Model III: FII = f (S, e, MSCI, i i*, y, Vol (e),alpha, Dummy)F(8,151)=4.3675[.000] 2.365 3.553 2.035 3.153 Reject H0

Model IV: FII = f (S, e, MSCI, i i*, y, Vol (e), beta, Dummy)F(8,151)=5.2981[.000] 2.365 3.553 2.035 3.153 Reject H0

Model V: FII = f (S, e, MSCI, i i*, y, Vol (e), cc1, cc2, Dummy)F(7,154)=5.3587[.000] 2.476 3.646 2.141 3.250 Reject H0

H0: No long-run relationship.H1: There exists long-run relationship.

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Now if the price of the shares of the company in the domes-tic (Indian) market increases, then the price of ADR/GDRwill also increase so that the zero arbitrage condition holds.In case the domestic currency (rupee) is getting devalued, theprice of ADR/GDR being issued will be higher.

Exchange rate also influences investment in ADR/GDRs inthe case when dividends are issued by the domestic (Indian)company. The domestic company will issue dividends in terms

of domestic currency (rupees) but this dividend will be received

by the foreign investor, who has purchased ADR/GDR, onlyafter conversion into foreign currency. In this case again, adevaluation in the domestic currency vis-a-vis the foreign cur-rency would mean a decline in the amount of dividend re-ceived by the foreign investor in terms of foreign currency.

The empirical results for the investment flows received byIndia on account of ADR/GDRs support both the abovearguments. The estimation of the long-run coefficients

(Table 10) show that the coefficient on domestic stock market

Table 6. Long-Run Coefficients Dependant Variable: Net Foreign Portfolio Inflows (US $ Billion) 1995M10 to 2011M10

Variable Coefficient [p-value]

Model I ARDL(4,1,2,1,1,1,2,1,1)

Model II ARDL(4,1,2,1,1,2,1)

Model III ARDL(4,1,2,1,1,2,1, 1)

Model IV ARDL(4,1,2,1,1,2,2,1)

Model V ARDL(4,1,2,1,1,2,2)

S .000401[.002] .000368[.002] .000404[.001] .000472[.000] .000457[.000]

e .175880[.013] .183200[.004] .150470[.023] .208990[.001] .138100[.029]

MSCI .00556[.021] .00509[.021] .00597[.011] .0065[.008] .004690[.023]CR .06365[.377]

i i* .120720[.178] .136060[.110] .10335[.267] .05270[.579] .067200[.439]y .116040[.032] .119040[.010] .14336[.004] .124090[.006] .125890[.004]y* .005151[.910]Vol(e) .37593[.046] .378680[.036] .31934[.086] .56554[.015] .40540[.017]

alpha .00408[.712]beta .73823[.065]

CC1 .48530[.211]CC2 1.0970[.158]

Crisis dummy Yes Yes Yes Yes YesIntercept Yes Yes Yes Yes Yes

Table 7. Long-Run Coefficients Dependant Variable: Net Foreign Institutional Investment Inflows (US $ Billion) 1995M10 to 2011M10


Model I ARDL(4,1,2,1,1,1,2,1,1)

Model II ARDL(4,1,2,1,1,2,2)

Model III ARDL(4,1,2,1,1,2,2,2)

Model IV ARDL(4,1,2,1,1,2,2,1)

Model V ARDL(4,1,2,1,1,2,2)

S .000387[.002] .000329[.004] .000374[.003] .000438[.001] .000432[.000]

e .118960[.079] .145900[.016] .110860[.088] .16392[.007] .098750[.093]MSCI .00590[.011] .00483[.026] .00562[.014] .0064[.007] .00439[.026]CR .065881[.342]

i i* .127350[.138] .155880[.060] .11274[.219] .0708[.442] .083400[.308]

y .092972[.070] .114600[.010] .13871[.004] .11628[.008] .120420[.003]y* .034617[.429]Vol(e) .37134[.040] .463880[.034] .43546[.059] .5432[.015] .4963[.013]

alpha .00899[.444]beta .66831[.085]

CC1 .4370[.231]CC2 1.3340[.065]

Crisis dummy Yes Yes Yes Yes YesIntercept Yes Yes Yes Yes Yes

Table 8. Granger Causality Test from ECM: Net Foreign Portfolio Inflows

Null hypothesis Chi-square statistic [p-value] Conclusion

Model II Model IV

Sdoes not Granger cause FPI 106.5756[.000] 108.7294[.000] Reject H0edoes not Granger cause FPI 68.7153[.000] 68.6112[.000] Reject H0MSCIdoes not Granger cause FPI 56.7942[.000] 58.0089[.000] Reject H0

i i*

does not Granger cause FPI 56.7825[.000] 58.8540[.000] Reject H0ydoes not Granger cause FPI 55.7905[.000] 57.1757[.000] Reject H0Vol(e) does not Granger cause FPI 77.4479[.000] 80.4300[.000] Reject H0beta does not Granger cause FPI 56.9355[.000] Reject H0



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returns and exchange rate is positive and significant in all thespecifications. This indicates that well performing domestic

stock markets and an appreciating domestic currency encour-ages ADR/GDR flows received by India.

This is because improvements in the performance of sharesof the company in the domestic stock market (which back theADR/GDRs) lead to improved performance of ADR/GDRs,through arbitrage. Similarly for the reasons stated above anappreciating rupee would lead to better returns from investingin ADR/GDR and a higher value of dividends issued onADR/GDR.

The estimated long-run coefficients also show that increasein foreign growth rate reduces the amount of ADR/GDRinvestment flows received by India. This is because a higherforeign growth rate implies a higher economic activity whichin turn means higher corporate profits and hence better invest-

ment opportunities in the developed countries. This could leadto diversion of investment by foreign investors toward thefinancial instruments of developed countries.

On the other hand increase in foreign growth rate which re-flects higher corporate profits, also means greater availabilityof funds with foreign investors for investment, and thus ahigher probability of increased investment in Indian securities.However, a negative sign on the coefficient of foreign outputgrowth means that these funds are not invested in ADR/GDR of Indian companies and the former effect dominates.

The coefficient on domestic output growth is positive whichmeans that an increase in the Indian growth increases theinvestment flows through ADR/GDR mechanism. This is be-cause on one hand the foreign investor perceives an improve-ment in growth performance of India (i.e., the country to

which the firm floating ADR/GDR belongs) as an indicator

that the returns on the instrument will be promising in futurebecause of the expansion in the economic activity of the coun-

try. On the other hand, more importantly, a higher growthrate also means an increase in the requirement of capital by In-dian firms for expansion, which is met by greater issuance ofADR/GDRs by Indian firms. Thus not only the demand forforeign investment by Indian firms increases, but foreigninvestors also find it profitable to invest in Indian ADR/GDRs when growth of the Indian economy increases. In thiscase both the demand as well as supply side factors facilitateincreased flow of foreign capital to India through ADR/GDRs.

Unlike FII flows the coefficient on risk diversification whichis measured by beta is insignificant for ADR/GDR flows.This indicates that investment through ADR/GDRs doesnot respond to risk diversification opportunities in India.

The emerging market equity performance, interest ratedifferential, country risk, currency risk, risk related to assetreturns and capital control measures are also found to beinsignificant in driving ADR/GDR investment. The Grangercausality tests indicate that domestic stock market perfor-mance, exchange rate, domestic and foreign output growth

Table 11. Granger Causality Test from ECM: Net American/GlobalDepository Receipt Inflows

Null hypothesis Chi-square statistic[p-value] Model IV

Conclusion

Sdoes not Granger cause ADR 87.1700[.000] Reject H0edoes not Granger cause ADR 108.0586[.000] Reject H0ydoes not Granger cause ADR 88.8691[.000] Reject H0

y

*

does not Granger cause ADR 89.3956[.000] Reject H0

Table 10. Long-Run Coefficients Dependant Variable: Net American/Global Depository Receipt Inflows (US $ Billion) 1995M10 to 2011M10


Model I ARDL(2,1,4,0,4,4,2,1,0)

Model II ARDL(2,2,4,0,4,2,2,0)

Model III ARDL(2,2,4,4,2,2)

Model IV ARDL(2,2,4,2,2)

Model V ARDL(2,2,4,2,2,3)

Model VI ARDL(2,2,4,2,2,1)

Model VIIARDL (2,2,4,2,2)

S .000034[.111] .000034[.100] .000020[.000] .000018[.000] .000023[.007] .000019[.000] .000032[.013]

e .041209[.002] .041924[.001] .036956[.001] .035407[.000] .03357[.001] .036502[.000] .033577[.001]

MSCI .00026[.505] .00025[.502]CR .003525[.787]i i* .002684[.870] .003399[.832] .000432[.977]

y .011093[.216] .011318[.205] .011000[.207] .010896[.198] .013041[.141] .011415[.177] .014838[.110]

y* .01672[.013] .01646[.016] .01652[.012] .01688[.007] .019522[.033] .01821[.005] .02131[.004]Vol(e) .00741[.736] .00635[.772]alpha .00076[.640]

beta .04042[.435]CC1 .04861[.485]CC2 .16323[.276]

Dummy Yes Yes Yes Yes Yes Yes YesIntercept Yes Yes Yes Yes Yes Yes Yes

Table 9. Granger Causality Test from ECM: Net Foreign Institutional Investment Inflows

Null hypothesis Chi-square statistic [p-value] Conclusion

Model II Model IV

Sdoes not Granger cause FII 106.153[.000] 102.909[.000] Reject H0edoes not Granger cause FII 61.1412[.000] 64.2641[.000] Reject H0MSCIdoes not Granger cause FII 49.9603[.000] 54.5394[.000] Reject H0

i i*

does not Granger cause FII 48.6887[.000] 54.0778[.000] Reject H0

ydoes not Granger cause FII 48.9052[.000] 53.2539[.000] Reject H0Vol(e) does not Granger cause FII 75.9569[.000] 79.6101[.000] Reject H0betadoes not Granger cause FII 54.0243[.000] Reject H0



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significantly Granger cause ADR/GDR flows to India(Table 11).

6. CONCLUSIONS AND IMPLICATIONS

This paper analyzes the macroeconomic determinants ofportfolio flows to India for the period 19952011 where port-folio flows to India have been increasing since 2002 and accel-erated in 2006 but slowed down in 2008 due to the globalfinancial crisis. The slowdown in portfolio flows occurred inthe backdrop of rising current account deficit.

In the past decade, nondebt creating capital flows (foreigndirect investment + portfolio flows) of which portfolio flows

is one of the components, have been sufficient to finance cur-rent account deficit as shown inFigure 3. However, more re-cently, the current account deficit has far exceeded theseflows implying that debt creating flows 11 are required to fi-nance the balance. This is substantiated by the recent rise indeposits of the nonresident Indians and external commercialborrowings.

In the current context identifying the determinants of port-folio flows is not only important to attract greater flows thatcan be used to finance the current account deficit but alsofor predicting these flows, so that policy reactions can be for-mulated in advance to manage these flows.

The results indicate that higher currency risk discouragesportfolio flows as it increases the uncertainty in returns re-ceived by the foreign investor in terms of its home currency.

It is also observed that higher equity returns in emerging mar-kets decrease portfolio flows to India indicating that Indiafaces competition from other emerging economies in termsof attracting portfolio flows. Evidence is also found in favorof the fact that investors invest in India with the objective ofrisk diversification. The conventional determinants i.e., well

performing domestic stock market, interest rate differentialand an appreciating exchange rate also encourage portfolioflows to India. Greater risk related to asset returns discour-aged portfolio flows though the effect is not significant. The re-sults also indicate that portfolio flows are determined more bystrong domestic output growth rather than foreign outputgrowth. Country risk does not significantly influence portfolioflows, which indicates greater investor confidence in the Indianeconomy.

An analysis of the disaggregated components of portfolioflows i.e., FII and ADR/GDR flows shows lower currencyrisk, lower emerging market equity returns and greater riskdiversification opportunities in addition to strong domesticequity performance, appreciating exchange rate, higher inter-

est rate differential and rising domestic growth are conduciveto FII flows. Higher asset returns risk discourages FIIs thoughthe effect is not significant. As observed for aggregate portfolioflows, country risk and foreign output growth are statisticallyinsignificant in influencing FIIs. For ADR/GDRs, domesticstock market performance, exchange rate, domestic outputgrowth, and foreign output growth, are observed to be impor-tant determinants. The results also suggest that the policyreforms that restricted inflows and liberalized outflows in200607 reduced FII flows to India but did not influenceinvestment through ADR/GDRs.

The results suggest that India may be able to attract portfo-lio flows by maintaining strong domestic growth, lower ex-change rate volatility through intervention in currencymarkets and making the domestic financial market perfor-

mance less vulnerable to global shocks by expanding thedomestic investor base in financial markets. To deal with theextreme episodes of turmoil or crisis, outflows of foreign cap-ital can be controlled using policy measures that include impo-sition of restrictions on capital outflows.

NOTES

1. Currently there are 1506 FIIs registered with SEBI out of which 56%belong to Mauritius (The Times of India, 2012). This may be because thefunds from other countries are also mobilized to India via Mauritius toensure tax benefits which accrue due to the Double Tax Avoidance

Agreement (DTAA) between India and Mauritius.

2. SeeHabermeier, Kokenyne, and Baba (2011)for a review of literature.

3. The results obtained broadly remain similar if nominal rupee-dollarexchange or 36 country trade based nominal effective exchange rate is

used.

-18000

2000

22000

42000

62000

82000

US$Million

FPI

FPI+FDI

Current Account Deficit

Figure 3. Current Account Deficit, Nondebt Creating Capital Flows (FPI + FDI) and FPI. Source: Reserve Bank of India, Handbook of Statistics 2013.



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4. To check for robustness, the 3 month moving average standarddeviation in nominal effective exchange rate was alternatively used tomeasure volatility in nominal effective exchange rate, and the results arequalitatively similar.

5. Alternately it can also be defined as the difference between 3 monthTreasury bill rate for India and 3 month Treasury bill rate for US. The

results are robust to this definition.

6. Country Risk is also calculated as the ratio of total reserves andimports, both denominated in US million dollars. The FPI, FII andADR/GDR specifications were estimated with reserves to import ratioand the results obtained were broadly similar. Aggregate portfolioflows as well as disaggregated FII and ADR/GDR flows to Indiaovertime were found to be insensitive to the credit worthiness of thecountry.

7. The Morgan Stanley Capital International (MSCI) Emerging MarketsIndex is a free float-adjusted market capitalization weighted index whichmeasures equity market performance of emerging markets. The MSCIEmerging Markets Index consists of 21 emerging market country indices.These include 5 five American countries (Brazil, Chile, Columbia, Mexico,

and Peru); 8 eight European, Middle East and African countries (CzechRepublic, Egypt, Hungary, Morocco, Poland, Russia, South Africa, andTurkey); and 8 eight Asian countries (China, India, Indonesia, Korea,Malaysia, Philippines, Taiwan, and Thailand)

8. Risk diversification is also captured by covariance between the Indianequity returns and global equity returns as a ratio of variance in globalequity returns. Lower the beta, greater the opportunity for diversificationand hence higher the portfolio flows received by India. This was calculatedas the ratio of twelve month covariance between MSCI-India and MSCI-World and twelve 12 month variance of MSCI-World. The FPI, FII, andADR/GDR specifications were estimated using this measure instead ofcorrelation and the results obtained were broadly similar.

9. Augmented Dickey-Fuller Test (Dicky & Fuller, 1979; Dicky &Fuller, 1981), Phillips-Perron Test (Phillips Peter & Perron, 1988), andthe Kwiatkowski, Phillips, Schmidt, and Shin Test (Kwiatkowski, Phillips,Schmidt, & Shin 1992) were also conducted and all of them give the sameresult as the DFGLS Test

10. The sensitivity of FII flows to interest rate differential indicates thatdebt securities are seen as a safer alternative to equity, especially duringglobal crisis period. This recent phenomenon of foreign investors investingin less risky debt securities, has been true for most of the developingcountries (Global Development Finance, 2012). For all the developingeconomies, debt flows increased almost 3 times from US$166 billion in2009 to US$ 495 billion in 2010. On the other hand equity flows increasedby about 25% from US$ 508 billion in 2009 to US$ 634 billion in 2010.

11. Non-debt creating flows include external assistance, external com-mercial borrowings, short-term trade credit, banking capital, non-residentIndians deposits.

REFERENCES

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