Determinants of Bank Foreign Direct Investment Inflow in India: A Dynamic Panel Data Approach

Abstract

India received highest foreign direct investment (FDI) in the world during the first half of 2015, leaving bigger economies like the US and China behind. In the process of globalization, India has liberalized all its sectors and invited FDI in most of the sectors, albeit with a sectoral cap. Internationalization of banks is perhaps the best example of India’s globalization. There are 44 foreign banks with 300 branches operating in India having a cap of 74 per cent and 20 per cent foreign investment in private and public sector banks, respectively. The present study aims to determine the motives behind bank FDI inflow into India. To accomplish that, a county-wise panel was constructed and bank FDI data from 2001 to 2013 was analyzed through generalized method of moments, a dynamic panel data model. The result of the study shows that bank FDI follows overall FDI, indicating that foreign banks follow their clients from their home country to serve them in the host country. However, locational advantages offer them profit-making opportunities and thus play a limited role in drawing bank FDI, which contribute to the development of the Indian economy. The argument that bank FDI inflow increases during a period of crisis is not relevant in the Indian context. The study suggests increasing the FDI cap in banking sector to attract more FDI and further relax the current restrictive policy on entry of foreign banks in India.

Keywords

Bank FDI foreign banks RBI panel data GMM

Introduction

Foreign Direct Investment (FDI) is considered to be a long-term capital investment. Most of the countries, irrespective of their being a developed or a developing economy, seek more FDI inflow for growth and development. According to International Monetary Fund (2013), developing countries created a history when they received more FDI than the developed countries in 2012. This is a signal that the developing countries are more attractive investment-wise. In fact, the increase in the thrust for FDI across countries has created a competition among them to attract more FDI. India attracted more FDI in the first half of the year 2015–16, leaving behind bigger economies such as the US and China (Hindustan Times, 2015). India received around 31 billion rupees in FDI during the year 2014–15. It is 27 per cent more than the previous year (Department of Industrial Policy and Promotion, 2015). India has attracted FDI in all sectors during its post-liberalization phase; however, the service sector has been most attractive of all and has bagged 17 per cent of overall FDI inflow. India needs FDI to grow rapidly and develop its infrastructure in order to improve the standard of living of the people. On the other hand, foreign investors are lured by high returns promised by the developing economy of India. Even then, different sectors of the economy attracted FDI due to a variety of reasons. This study is an attempt to explore the determinants of receiving FDI in Indian banking sector.

Integration of global economies has increased cross-border banking activities, mergers and acquisition across boundaries, and bank internationalization. With globalization and development in the communication systems, most of the developing economies have opened up their banking sector to FDI, which made it easy for foreign home regulators to monitor over banks in the host countries (Kim, 2010). With the intensified inflow of bank FDI and entry of foreign banks across economies, previous studies have raised many questions: What are the motives behind bank FDI inflow or entry of foreign banks into any host nation? What is or will be the impact of bank FDI on the host nation’s banking sector and its overall economy? Whether bank FDI follows overall FDI? Do foreign banks enter the host country to serve their home clients? Which mode of bank FDI is better for the host county—green field investment or brown field investment? Many empirical studies have attempted to answer these questions. Yet, empirical studies on the determinants of FDI in the banking sector are mainly focused on developed countries like the US, Japan, the UK, or Germany. The literature has hardly covered developing and emerging economies (Meng, 2009). Even then, recent studies have included several Asian counties, such as Indonesia, Thailand and South Korea, mainly due to the 100 per cent opening of their banking sector to FDI (Rajan, 2011).

India opened its banking sector to FDI following the recommendation of Narasimham Committee in 1991; however, it had phased out bank FDI over a period and Phase I began in 2005 followed by Phase II in 2013. In the first phase, the investment cap in private sector was raised to 74 per cent from the earlier 49 per cent. In the second phase, the Reserve Bank of India (RBI) incentivized foreign banks to enter India by providing them national treatment.¹ In a recent reform in November 2013, RBI has allowed foreign banks to open wholly owned subsidiary (WOS) and permitted them to expand in any Tier I to Tier VI cities in India without seeking RBI’s prior approval. Recently, taking advantage of this reform, Development Bank of Singapore announced that it will establish 150 WOSs in India. City Bank and Standard Chartered Bank also might follow suit. The announcement of permitting foreign banks to establish WOS was made in the year 2005, but no foreign bank has opened any WOS in India till date. This could mean that foreign banks in India follow their home clients and establish branches to serve them only (Massand & Gopalakrishna, 2015).

According to the consolidated foreign investment policy of 2015 (Department of Industrial Policy and Promotion, 2015), foreign banks can be present in India through any of the four modes: (i) it can open a branch, (ii) it can open a WOS, where a foreign bank can invest 100 per cent and have full control over it, (iii) it can have a representative office, and (iv) it can have a stake in any Indian domestic bank, subject to the cap of 74 per cent in private sector banks and 20 per cent in public sector banks. Moreover, there is also a limit of 5 per cent of paid-up capital in an Indian bank for an individual foreign investor. RBI has limited the voting rights to 10 per cent for foreign investors in Indian banks. The existing foreign banks can convert their branches to WOS also, but a foreign bank can be present in India only in a single mode, either as a branch or as a subsidiary. By March 2014, there were 44 foreign banks with more than 300 branches from 25 countries. Figure 1 and Figure 2 represent the non-resident investment in the private and public sector banks of India, respectively. Many banks like ING Vysya, ICICI and IndusInd have very high foreign investment (Figure 1), and among public sector banks, PNB, Bank of Baroda and Dena Bank have higher foreign investment (Figure 2).

Figure 1.

Source: Reserve Bank of India (2015).

Figure 2.

Source: Reserve Bank of India (2015).

Most of the studies determining the causes of bank internationalization have adopted asset share of foreign banks and number of foreign banks as the proxies for FDI in the banking sector (Focarelli & Pozzolo, 2005; Goldberg & Johnson, 1990; Kim, 2010; Mutinelli & Piscitello, 2001; Nigh, Cho, & Krishnan, 1986). The studies which used Bank FDI data are focused on developed countries; for example, Yamori (1998) on Japanese FDI in financial sector, Moshirian (2001) on FDI in the US, the UK and Germany, Wezel (2004) on Bank FDI from German multinational banks, and Mariscal, Zhang and Pascual (2012) on bank FDI in seven Latin American countries. To the best of our knowledge, no study on foreign banks in India has used bank FDI data to determine the entry of foreign banks or direct capital inflow into India. We employ bank FDI data to investigate the pull factors of entry of foreign banks in India. Figure 3 shows the yearly data of FDI in Indian banking sector, the data for which is available only from 2001. We believe that the lack of availability of data on bank FDI could be a reason for non-utilization of bank FDI variable in earlier literature.

Figure 3.

Source: Reserve Bank of India (2016).

Theoretical Support and Formation of Hypotheses

There are many theories which explain the inflow of FDI, for instance, the product life cycle hypotheses, Hymer’s theory, internalization theory, eclectic theory, the gravity model and agglomeration economies hypothesis. However, most of these are relevant to manufacturing sector. To reduce production costs, manufacturing firms may choose to establish their production platforms in foreign countries with cheap and skilled labour. However, banking is a non-tangible service industry which has production as well as consumption function at the same place. Being considered as a customer oriented industry, banks expand their business in profitable and large markets (Focarelli & Pozzolo, 2001). Factors affecting general FDI also can be determinants of banking FDI just as factors affecting bank FDI can be for general FDI. Thus, it is possible to map the determinants of general FDI to those of banking sector FDI. However, researchers have found only two theories, namely, internalization theory and eclectic theory that are appropriate to explain why banks invest in foreign countries (Kim, 2010).

Internalization theory claims that a firm fails to reach an efficient external market to earn profit by using its resources only in the home country and, that is why, it can create an internal market only by seeking business opportunities and investing abroad, in geographically diversified areas. Hence, a bank would invest abroad when its own market is saturated and it does not have more opportunities to expand business in its own country. Thus, a bank moves abroad by investing in other markets.

Dunning’s theory of eclectic paradigm also explains the same concept with some additional features in it (Dunning, 1979 & 1998). The eclectic theory is also known as OLI paradigm that represents three types of advantages: ownership, locational and internalization advantages. Ownership advantage is an advantage that a firm has over its competitors, for example, advanced technological advantages. Locational advantage is an advantage that a firm has in the target country, that is, a huge market to serve in terms of population, high savings, cheap and skilled labour and more resources. Internalization advantage happens when a firm decides to go abroad itself to gain more profit instead of licensing to another firm. Thus, Dunning’s theory takes into consideration all aspects of a service industry and provides the answer why a foreign bank would go abroad (Dunning, 1979).

Various studies have adopted one of these two theories and examined the issue empirically. Using bank FDI data, we formulate and test some hypotheses in the Indian context based on the work reported in the earlier literature. That foreign banks from the home countries enter the host country to serve their home clients is believed to have established the initial base in the host nation (Mutinelli & Piscitello, 2001). There are theoretical and empirical evidence that suggest the concept of ‘following the client’. It says that, for instance, if a client automobile company from a country enters the host country to expand its business, a bank in the home country follows its client in the host nation to offer its banking facility. There are studies that used bank FDI data and formulated hypotheses based on this assumption. Yamori (1998), for example, hypothesized ‘bank FDI follows manufacturing FDI’ in case of Japanese banks; Goldberg and Johnson (1990) hypothesized ‘bank FDI follows general FDI’; Moshirian (2001) and Mariscal et al. (2012) hypothesized ‘bank FDI follows non-financial FDI’ for the US, the UK, Germany, and seven Latin American countries; Wezel (2004) hypothesized ‘bank FDI follows non-bank FDI’ in case of German banks. However, many studies have stated that ‘follow the home client’ hypothesis has limited applicability in recent times (Nolle & Seth, 1996). We use Bank FDI data to check whether it follows overall FDI in India.

H₁: Bank FDI follows General FDI in India.

There is a school of thought that believes that foreign banks set up their branches where their home competitors and global competitors are also located. We further check if bank FDI follows bank FDI in India.

H₂: Bank FDI follows bank FDI in India.

According to OLI paradigm, competitive advantages and locational advantages are the main reasons for a bank to enter a host country. Several empirical studies have used the eclectic theory (Dunning, 1979) to claim that foreign banks enter to tap the untapped market, look for a huge customer base, cheap labour, economic growth, developed financial markets, etc. as available locational advantages. We formulate the following hypothesis for locational advantages:

H₃: Bank FDI seeks locational advantages of India.

H_3a: Low competition in banking sector invites bank FDI.

H_3b: High interest rates prevailing in India draws bank FDI.

H_3c: High savings in India draws bank FDI.

H_3d: High economic growth of India draws bank FDI.

There are studies claiming that an economic crisis in the host country attracts foreign direct investors to buy assets at cheaper rates and expand their businesses (Clarke, 2008; Mohan, 2006). To investigate the argument, we considered a period of crisis in India, that is, the global financial crisis of 2007–2009, vis-à-vis the entry of bank FDI into India.

H₄: Bank FDI enters during crisis period in India.

Review of Literature

The bank FDI inflow in the form of expansion of foreign banks across economies were initiated mostly between 1960 and 1985 but slowed down after mid-1980s (Brealey & Kaplanis, 1996). As a result, the number of studies on bank internationalization was also reduced after 1985. However, these studies have attracted scholars in the field again after 1995, in the post-WTO world, where the member countries signed an agreement to allow more foreign banks to operate in their economies. It was also the time when most of the developing countries liberalized their economies. However, the empirical literature is more focused on developed economies and has investigated two hypotheses in general, that is, ‘follow your client’ and ‘locational advantages’. An extensive cross-national study of that time was carried out by Brealey and Kaplanis (1996), which analyzed the role of trade and FDI as the determinants for bank internationalization. They analyzed 2000 bank offices across 37 home and 82 host countries and found that trade and FDI are strong determinants to pull foreign banks into host countries. They argued that the parent banks generated less business than their host country branches did abroad.

Nigh et al. (1986) empirically studied the decisions for bank FDI taken by US banks. The results indicated that the locational choice did not depend on local banking opportunity. However, the results of an empirical study on the entry of the US banks into other countries by Goldberg and Johnson (1990) proved that local opportunities do matter. Furthermore, the study found that host markets with greater per capita income, large foreign trade, less regulative measures and lower level of domestic deposits are the main determinants of bank FDI. The study also found that US banks do follow their clients abroad. However, their results specified that large banks followed their clients who had expanded abroad to serve them and help them establish their businesses quickly in the host nation, whereas it was not true in case of the smaller banks from the US. Nolle and Seth (1996) tested the hypothesis ‘follow your customers’ for multinational banks from Japan, Canada, France, Germany, Netherland, and the UK entering the US market. The results of the study claimed limited applicability of ‘following your client’ hypothesis. However, based on the results of an empirical study, Yamori (1998) claimed both locational advantages and following manufacturing FDI as the main reasons behind the decision of Japanese banks to enter various host markets including the US.

For the millennium years, the causes for bank FDI inflow in different countries are debatable between ‘follow your client’ and ‘locational advantages’ hypotheses. However, it is also a concern as to which locational advantages are responsible to pull more FDI into banking sector. Garcia Blandón (2001) tested the ‘follow your client’ hypothesis in case of multinational banks’ entry into Spain and found it as the major determinant for the entry. However, the study claimed that domestic advantages did not have any significant impact on attracting foreign banks in Spain. The empirical study by Mutinelli and Piscitello (2001) on the Italian bank FDI showed that foreign banks locate themselves in the places where they can exploit the bank–client relationship. Thus, the study supported ‘follow your client’ hypothesis in case of Italian banking sector. Moshirian (2001) analyzed a dynamic panel model using generalized method of moment (GMM) for FDI in banking sector in the US, the UK and Germany and found that bilateral trade, banks’ foreign assets, cost of capital, relative economic growth, exchange rates and FDI in non-finance industries were the major determinants.

Wezel (2004) studied the factors influencing the decision of German multinational banks to choose location for establishing their offices in Central and Eastern Europe, Latin America, and Asia between 1994 and 2001. The study found non-bank FDI as the main determinant besides other determinants such as developed financial markets and less market risk. Focarelli and Pozzolo (2005), using multinomial logit regression on 260 large banks from 29 OECD countries² for the period 1994–1997, found ‘profit opportunity’ as the main determinant for foreign investment inflow into the banking sector. Clarke (2008) showed that reduction in barriers to entry is strongly and positively related to increased market penetration by foreign commercial banks. The results also claimed that the likelihood of foreign acquisitions will be complicated by the existence of a bank crisis and seems to be positively related to the liberalization of European countries in the form of the adoption of the banking directives of European countries.

Song (2009) investigated the determinants of foreign bank investments in China from 1991 to 2008 and found the country’s growing economy (i.e., the GDP) as the most influencing factor. However, the empirical study by Clarke (2008) did not find China’s GDP as an influence for foreign banks to set up their branches in China. Wezel (2004) also did not find any relation between attracting foreign banks and GDP in case of German banks’ entry into Asia and other developing countries. Mariscal et al. (2012) adopted generalized least square method (GLS) on panel data and found that increase in the ratio of foreign asset share, economic crisis, removal of banking restrictions, and banking concentration (i.e., the assets share of top three banks to the total assets of all the commercial banks) were the main causes for the decision affecting bank FDI inflow in seven Latin American countries. Molyneux, Nguyen and Xie (2013), in their empirical study on the determinants of foreign bank entry in South East Asian countries after the financial crisis of 1997–98, found an opportunity for profit as the main determinant, whereas manufacturing FDI and bilateral trade were found to have little relation with foreign bank entry. Moreover, the study claimed that ‘follow your client’ argument is irrelevant. Temesvary (2015) developed a structural dynamic model for the choice of US multinational banks’ entry into 83 host countries for the period of 2003–2013. The results indicated bank profits and portfolio risk as the reasons behind the decision of US banks expanding into host markets.

Kim (2010), a lone study on the Indian context determining the causes of entry of foreign banks into India, empirically examined the pull factors of foreign banks in India from 1986 to 2007. The study has obtained two types of data, aggregate data and panel data that have been analyzed through Ordinary Least Square (OLS) and Panel OLS respectively. The study verified that ‘follow your client’ hypothesis holds good in the Indian context and concluded that foreign banks entered India to serve their home clients. The results of the study, however, did not support financial development as a requirement for foreign banks’ entry. On the other hand, the study supported that favourable policy reforms are a positive factor to attract foreign banks.

Methodology and Database

We use panel data to have more power and efficiency in testing hypotheses. Our panel dataset consists of 325 observations; with 25 host country-wise cross-section data and yearly data for 13 years from 2001 to 2013. We employ GMM, a dynamic panel data model technique to test a hypothesis. Our model is as follows:

BK_FDI_ij = f(BK_FDI_ij, FDII_ij, NIM_j, IRD_{(i – hj)}, NDS_j, GNP_CAP_j, CRISIS)

where, i represents the home country, j represents period in years, I represents real interest rates in India, h represents real interest rates in the home country. BK_FDI indicates foreign direct investment in Indian banking sector, FDII represents foreign direct investment inflow, NIM represents aggregate net interest margin of banks in India, IRD represents interest rate differential between India and the home country, NDS is net domestic savings. GNP_CAP is per capita gross national product, CRISIS is taken as a dummy variable for global financial crisis period (Table 1).

Table 1.

Operational Definition of Adopted Variables

Variable	Operational Definition
BK_FDI	FDI into Indian banking sector/GDP
FDII	Foreign direct investment inflow/GDP
NIM	Interest income—Interest expended/total asset
IRD	Real interest rate of India—Real interest rate of home country
NDS	Net domestic savings/GDP
GNP_CAP	Per capita gross national product
CRISIS	Dummy variable 1 for 2007, 2008, and 2009; 0 for the remaining years

Source: Authors’ own.

Expected Signs of Variables

FDII is adopted to prove the hypothesis ‘follow your client abroad,’ and is considered as a lagged variable for FDI inflow normalized by GDP. Based on their results, Kim (2010) claimed that foreign banks in India follow their clients. Hence we expect FDII to be positive. Moreover, it is also found that foreign banks tend to move to the countries where their global competitors have already started operations. This could be true in case of foreign banks entering India as well. Bank FDI inflow could be a reason for attracting bank FDI. Thus, to test the same bank FDI variable (BK_FDI) in lag period is also taken as the independent variable.

CRISIS is taken as a dummy variable in order to prove whether bank FDI inflow increases during crisis period to avail cheaper assets. The study by Clarke (2008) found increase in the entry of foreign banks during periods of crisis, whereas Ram Mohan (2013) observed that foreign banks seek entry during crisis in order to acquire assets at cheaper rates. Thus, we expect positive relationship between crisis and bank FDI.

The remaining variables are adopted to analyze the locational advantages of Indian economy that attract more bank FDI. Net interest margin (NIM) represents bank competition; so, high NIM indicates less banking competition. Hence, foreign banks would like to enter the markets with high NIM. According to Das (2013), the average NIM for the developed countries was below 2 per cent, but, in case of India, Mohan (2006) found very high NIM of 2.9 per cent and Das (2013) found it to be around 2.5 per cent on average. This means there is a scope for bank competition. Thus, we expect NIM to be positive.

Interest rate differential represents the profit opportunity in the Indian banking sector. The relatively high real interest rates in India would lead to earning high profits from Indian banking sector. Thus, we expect positive relationship between interest rate differential (IRD) and BK_FDI. High net domestic savings represents huge market opportunity, which could attract foreign banks to set up their operations in India. Thus, the relationship should be positive. Gross national product (GNP) per capita that represents huge potential market and high growth of economy could be a determinant of bank FDI. Thus, we expect positive sign for GNP per capita. However, Goldberg and Johnson (1990) found a negative relationship in case of US banks expanding abroad. Overall, less bank competition, huge market, profit earning opportunity and high growth in Indian economy are the representatives for locational advantage hypothesis.

All the variables discussed here are the standard variables found in the literature and are collected from reliable sources. Data for all variables except real interest rates are collected from Database on Indian economy, Statistical Tables Relating to Banks in India (Table 12: Selected ratios of scheduled commercial banks from 2001 to 2014; Table 15: Shareholding pattern of scheduled commercial banks) and Handbook of Statistics on Indian Economy (Table 2: Macro-economic aggregates; Table 10: Sector-wise domestic saving; Table 155: Foreign Investment Inflows) published by the RBI from year to year. The data on real interest rates are collected from the World Bank database (4.15 World Development Indicators: Monetary indicators). Table 2 represents the summary statistics and Table 3 shows correlation matrix of variables, which indicate that there exists no multicollinearity in the dataset.

Table 2.

Summary Statistics of Variables

	Mean	Maximum	Minimum	Std. Dev.	Number of Observation
BK_FDI	0.000171	0.010331	0	0.000862	273
FDII	0.000412	0.009708	0	0.001268	273
NIM	0.028779	0.0308	0.0255	0.001487	273
NDS	0.714424	0.942519	0.557864	0.127454	273
IRD	0.016608	0.34	–0.31	0.053649	273
GNP_CAP	10.4679	11.24096	9.873595	0.448002	273

Source: Authors’ calculation using E-View 9 software.

Table 3.

Correlation Matrix of Variables

	BK_FDI	FDII	NIM	IRD	NDS	GNP_CAP
BK_FDI	1
FDII	0.43832	1
NIM	–0.08594	0.07319	1
IRD	–0.04541	–0.10044	–0.00217	1
NDS	–0.13636	0.12757	0.32615	–0.10911	1
GNP_CAP	0.08886	0.00641	–0.55704	–0.01769	–0.35491	1

Source: Authors’ calculation using E-View 9 software.

Results and Discussion

First of all, we check the stationarity of all the variables by using Levin, Lin and Chu test and Augmented Dickey–Fuller (ADF)–Fisher test for panel data. The main motive to use two different tests is that Levin, Lin and Chu test assumes common unit root process and ADF–Fisher test assumes individual unit root test that uses p-values from unit root tests for each cross-section i. However, Individual unit root tests have limited power. Thus, Levin, Lin and Chu test that assumes common unit root process is employed. It allows p-values to vary across individuals (the null of Levin, Lin and Chu test is H0: each time series contains a unit root). Thus, we employ both tests here. We found that many of the variables are non-stationary at level (see Table 4). Thus we consider all the variables at first difference and run the mentioned tests again. The results of both the tests indicate that all the variables are stationary at first difference. Hence, flow data (where variables are taken in first difference) is considered to run the model. Table 5 represents the result of various dynamic panel data (DPD) models for the adopted variables. Initially, we used GMM model and later we adopted various DPD models to check the robustness of our model/ estimates. However, we find that GMM estimator is optimal for the given set of data as it addresses the concern of any endogeneity problem. Moreover, the insignificant results of most of the variables in other DPD models also suggest choosing GMM estimator. However, the main outcomes from all DPD models are in the same direction. Hence, we discuss only the results obtained through GMM estimator. The GMM model was run considering orthogonal deviation effect for cross-section data and white period was used as coefficient covariance method. Moreover, the GMM model having first difference presents almost similar results. FDII variable in lag of two is employed as an instrumental variable and is checked through Sargan’s J-statistics (see Table 5). The p-value of J-statistics indicates that FDII variable is an appropriate instrumental variable.

Table 4.

Results of Panel Unit Root Test

Tests	Levin, Lin, & Chu Test				ADF–Fisher Chi–square
Variables	At Level	p	At First Difference	p	At Level	p	At First Difference	p
BK_FDI	–5.33	0	–7.22	0	30.55*	0.4375	56.99	0.001
FDII	–450.91	0	–215.09	0	85.40	0.0013	118.00	0
NIM	–11.55	0	–12.57	0	83.75	0.002	111.55	0
IRD	–17.64	0	–2.913	0.001	104.91	0	69.46	0.004
NDS	–2.39	0.008	–12.38	0	45.21*	0.3392	137.04	0
GNP_CAP	–4.67	0	–12.82	0	4.63*	1	166.27	0

Source: Authors’ calculation using E-View 9 software.

Notes: *represents non-stationarity, p is probability value. Variables BK_FDI, NDS, and GNP_CAP are non-stationary at level. All the variables are stationary at first difference.

Table 5.

Results of Various DPD Models (Dynamic Panel Data Models)

Variables	GMM(Orthogonal)	GMM(First Difference)	FMOLS	GLM
BK_FDI (–1)	–0.0375***(–20.35)	–0.0374***(–41.94)	–0.0447(–0.81)	–0.0456(–0.94)
FDII (–1)	0.7382***(390.0)	0.7335***(300.76)	0.7453***(8.45)	0.7809***(10.82)
NIM	–0.0732***(–79.40)	–0.0746***(–71.65)	–0.0342(–0.53)	–0.0074(–0.23)
IRD	0.0093***(48.42)	0.0094***(195.41)	0.0008(0.72)	0.0008(1.00)
NDS	–0.0049***(–94.22)	–0.0050***(–133.35)	–0.0028(–1.59)	–0.0007(–1.46)
GNP_CAP	0.0155***(55.82)	0.0157***(57.73)	0.0132*(1.75)	0.0014***(2.59)
CRISIS	–0.0003***(–29.20)	–0.0003***(–22.58)	–9.42E–05(–0.29)	4.83E–05(0.35)
S.E. of regression	0.000871	0.001339	0.00091
J-statistic	17.35592	18.35406
Prob. (J-statistic)	0.298037	0.303575

Source: Authors’ calculation using E-View 9 software.

Notes: The dependent variable is BK_FDI. All the independent variables are flow variables. Parentheses represent t statistics in case of GMM and FMOLS and z-statistics in case of GLM.

*** shows significant level at 1 per cent and * shows significant level at 10 per cent.

GMM: Generalized Method of Moments.

FMOLS: Fully Modified Least Squares.

GLM: Generalized Linear Model.

The results of GMM estimator indicates that BK_FDI do follow general FDI in India (H₁) which shows that foreign banks in India followed their home clients but do not follow BK_FDI itself (H₂). Our results are consistent with the study on the Indian context by Kim (2010); however, the study has used foreign bank asset share and number of foreign banks as proxy for bank FDI in India. As we have formed country-wise panel data, the competitors within the country could not be studied and that could be a probable reason for the negative relation of BK_FDI with its lag that we found. Thus, we accept H₁ and reject H₂.

In India, NIM is comparatively quite high. High NIM represents less competition in the Indian banking markets. Our results indicate that as NIM increases, bank FDI declines, showing that bank FDI does not enter because of less competition in Indian banking sector (H_3a), or, in other words, despite less competition in the Indian banking sector, bank FDI or foreign banks’ entry does not increase. This means that there could be some policy-level restriction in the Indian market. According to Department of Industrial Policy and Promotion (2015), only 20 per cent FDI is allowed in Indian PSBs. Moreover, only 12 branches of all foreign banks (existing as well as new entrants) put together are permitted by RBI to open up in a single year.

There is a statistically significant positive relation between bank FDI and IRD that indicates that bank FDI gain good returns on their investment in India and hence they have advantage of internationalization of banks in India (H_3b). However, the result of net domestic savings indicates that bank FDI does not admire huge savings among Indians. Indians deposit their savings in domestic banks rather than in foreign banks due to better availability of bank branches or having more faith in the regional banks, which might discourage foreign banks to target domestic savings (H_3c). Moreover, foreign banks are present mostly in metropolitan and urban areas due to restrictions in opening of branches only in the Tier V and Tier VI cities in India (Kim, 2010). The growth in the economy in terms of GNP per capita does attract bank FDI in India (H_3d). This result is consistent with that of Song (2009) in case of China, whereas it is in conflict with the results of the study by Goldberg and Johnson (1990) for US banks. Growth in economy does pull foreign investment in Indian banking sector. Thus, the overall locational advantages to attract bank FDI are partially sensed. However, it shows that India is a locational choice for foreign banks to earn profits. So, we accept the hypothesis for locational advantage (H₃).

However, we find negative relation between crisis and bank FDI (so we reject H₄). Thus, it is not clear if bank FDI enter to buy Indian banking assets at reasonable rates during periods of crisis. It is also believed that 2008–2010 was a period of global financial crisis that affected all countries. This could be a reason of reduced investment during those years. There are, however, examples when bank FDI entered during periods of regional crisis, for example, in Thailand during the Asian financial crisis of 1997 (Clarke, 2008). However, we could not study the period of Asian financial crisis due to lack of availability of data.

Conclusion

The focus of the study was to determine the causes influencing bank FDI in India. The study adopts two hypotheses from empirical literature and theories, namely, ‘follow your client’ and ‘locational advantages’ as the possible determinants of bank FDI in India. Considering country-wise bank FDI data available from 2001, a panel dataset was constructed and analyzed through dynamic panel data model. The study tested the said hypotheses in the Indian context and found that bank FDI does follow the general FDI in India. The study did not find periods of crisis as a determinant of bank FDI in India. However, domestic advantages for foreign investments are partially responsible to draw bank FDI into India. India’s high economic growth and high returns on investment are the determinants for bank FDI inflow. However, lack of competition in the Indian banking sector and high savings among Indians has not attracted bank FDI or foreign banks. The cap on foreign investment in Indian banking sector and restricted entry of foreign banks could be the hindrances for further entry in the less competitive Indian banking sector. We suggest to increase bank sectoral cap for investment and to allow setting up of more branches of foreign banks in India.

Footnotes

Notes

References

Brealey

R. A.

, & Kaplanis

E. C.

(1996). The determination of foreign banking location. Journal of International Money and Finance, 15(4), 577–597. doi:10.1016/0261-5606(96)00022-8

Clarke

J. L.

(2008). An examination of bank sector deregulation on inbound FDI: Commercial bank acquisitions. International Review of Business Research Papers, 4(1), 85–100.

Das

T. B.

(2013). Net interest margin, financial crisis and bank behavior: Experience of Indian banks (RBI Working Paper Series, No. 10). Retrieved from https://www.rbi.org.in/scripts/PublicationsView.aspx?id=15418

Department of Industrial Policy and Promotion, Government of India. (2015). Factsheet on foreign direct investment (June). Retrieved from http://dipp.nic.in/English/Publications/FDI_Statistics/FDI_Statistics.aspx

Dunning

J. H.

(1979). Explaining changing patterns of international production: In defence of the eclectic theory. Oxford Bulletin of Economics and Statistics, 41(4), 269–295.

Dunning

J. H.

(1998). Location and the multinational enterprise: A neglected factor? Journal of International Business Studies, 29(1), 45–66.

Focarelli

, & Pozzolo

A. F.

(2001). The patterns of cross-border bank mergers and shareholdings in OEDC Countries. Journal of Banking and Finance, 25(12): 2305–2337.

Focarelli

, & Pozzolo

A. F.

(2005). Where do banks expand abroad? An empirical analysis. The Journal of Business, 78(6), 2435–2464.

Garcia Blandón

(2001). The timing of foreign direct investment under uncertainty: Evidence from the Spanish banking sector. Journal of Economic Behaviour and Organization, 45(2), 213–224.

10.

Goldberg

L. G.

, & Johnson

(1990). The determinants of the US banking activity abroad. Journal of International Money and Finance, 9(2), 123–137.

11.

Hindustan Times. (2015, September 30). India emerges top FDI destination leaving behind China, US in 2015. Retrieved from http://www.hindustantimes.com/business/india-emerges-top-fdi-destinationleaving-behind-china-us-in-2015/story-7Dno24ijpNUtLjehW1gnGI.html

12.

International Monetary Fund, Washington, DC. (2013). Global financial stability report: Transition challenges to stability. Retrieved from http://www.imf.org/External/Pubs/FT/GFSR/2013/02/pdf/text.pdf

13.

Kim

(2010). Foreign investment in the banking sector: A case study of India, 1986–2007 (PhD Thesis). Jawaharlal Nehru University, New Delhi.

14.

Mariscal

A. S.

, Zhang

, & Pascual

J. L.

(2012). Internationalization of multinational banks: A study of foreign direct investment in seven Latin American countries. The Service Industries Journal, 32(7), 1149–1170.

15.

Massand

, & Gopalakrishna

B. V.

(2015, February 20). Do foreign banks in India follow their home clients? Paper presented at the national conference on Emerging Issues in Banking and Finance in a Technology Driven Economy, National Institute of Technology Karnataka (NIT-Karnataka), Mangalore.

16.

Meng

(2009). Multinational banking in China: Theory and practice. Cheltenham, UK: Edward Elgar.

17.

Mohan

(2006). Reforms, Productivity and Efficiency in Banking: The Indian experience (Bank for International Settlement [BIS] review No. 15). Address at the 21st Annual General Meeting and Conference of the Pakistan Society of Development Economists, Islamabad, December 21, 2005. Retrieved from http://www.bis.org/review/r060308e.pdf

18.

Molyneux

, Nguyen

, & Xie

(2013). Foreign bank entry in South East Asia. International Review of Financial Analysis, 30(December), 26–35.

19.

Moshirian

(2001). International investment in financial services. Journal of Banking & Finance, 25(2), 317–337. doi:10.1016/S0378-4266(99)00125-9

20.

Mutinelli

, & Piscitello

(2001). Foreign direct investment in the banking sector: The case of Italian banks in the ’90s. International Business Review, 10(6), 661–685. doi:https://dx-doi-org.web.bisu.edu.cn/10.1016/S0969-5931(01)00037-3

21.

Nigh

, Cho

K. R.

, & Krishnan

(1986). The role of location-related factors in U.S. banking involvement abroad: An empirical examination. Journal of International Business Studies, 17(3), 59–72.

22.

Nolle

D. E.

, & Seth

(1996). Do foreign banks follow their customers abroad? (Federal Reserve Bank of New York Research Paper, No. 9620). Retrieved from https://www.newyorkfed.org/medialibrary/media/research/staff_reports/research_papers/9620.pdf

23.

Rajan

R. S.

(2011). Crisis, capital flows and FDI in emerging Asia. New Delhi: Oxford University Press.

24.

Ram Mohan

T. T.

(2013). Before and after the global crisis. New Delhi: Gyan Publishing House.

25.

Reserve Bank of India. (2015). Statistical Tables relating to banks in India (Table 15; in percentage, as on March 2014). Retrieved from https://www.rbi.org.in/Scripts/AnnualPublications.aspx?head=Statistical+Tables+Relating+to+Banks+in+India

26.

Reserve Bank of India. (2016). Handbook of statistics on the Indian economy (Table 155). Retrieved from https://www.rbi.org.in/Scripts/PublicationsView.aspx?id=15945

27.

Song

(2009, September 20–22). Empirical Study on Influencing Factors of Foreign Banks Entry in China. International Conference on Management and Service Science, MASS ’09. Retrieved from IEEE Explore Digital Library. doi:10.1109/ICMSS.2009.5302466

28.

Temesvary

(2015). Foreign activities of U.S. banks since 1997: The roles of regulations and market conditions in crises and normal times. Journal of International Money and Finance, 56, 202–222. doi:10.1016/j.jimonfin.2014.09.008

29.

Wezel

(2004). Foreign bank entry into emerging economies: An empirical assessment of the determinants and risk predicted on German FDI data (Discussion Paper Series 1: Studies on Economic Research Centre, No. 01/2004). Retrieved from https://www.bundesbank.de/Redaktion/EN/Downloads/Publications/Discussion_Paper_1/2004/2004_01_26_dkp_01.pdf?__blob=publicationFile

30.

Yamori

(1998). A note on the location choice of multinational banks: The case of Japanese financial institutions. Journal of Banking & Finance, 22(1), 109–120. doi:10.1016/S0378-4266(97)00040-X