FDI Outflows and Domestic Investment: Substitutes or Complements? Exploring the Indian Experience Nandita

Dasgupta, Nandita Working Paper FDI Outflows and Domestic Investment: Substitutes or Complements? Exploring the Indian Experience Nandita Copenhagen Discussion Papers, No. 2016-59 Provided in Cooperation with: Asia Research Community (ARC), Copenhagen Business School (CBS) Suggested Citation: Dasgupta, Nandita (2016) : FDI Outflows and Domestic Investment: Substitutes or Complements? Exploring the Indian Experience Nandita, Copenhagen Discussion Papers, No. 2016-59, Copenhagen Business School (CBS), Asia Research Centre (ARC), Frederiksberg, https://hdl.handle.net/10398/9294 This Version is available at: https://hdl.handle.net/10419/208657 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Copenhagen Discussion Papers cannot be republished, reprinted, or reproduced in any format without the permission of the paper's author or authors. Note: The views expressed in each paper are those of the author or authors of the paper. They do not represent the views of the Asia Research Centre or Copenhagen Business School. Editor of the Copenhagen Discussion Papers: Associate Professor Michael Jakobsen Asia Research Centre Copenhagen Business School Porcelænshaven 24 DK-2000 Frederiksberg Denmark Tel.: (+45) 3815 3396 Email: mj.[email protected] www.cbs.dk/arc FDI Outflows and Domestic Investment: Substitutes or Complements? Exploring the Indian Experience NANDITA DASGUPTA Ph.D. University of Maryland, Baltimore County e-mail: [email protected] Abstract The recent phenomenon of rising outward foreign direct investment (OFDI) flows has raised serious policy concerns about its effects on the domestic investment and capital formation in the countries of origin of such FDI flows. Does OFDI stimulate domestic investment or does it crowd it out? The concern arises because OFDI activities could shift not only some of the production activities from home to foreign destinations but also could possibly threaten the availability of scarce financial resources at home by allocating resources abroad. All this have the potential to reduce domestic investment, thus lowering the long run sustainable economic growth and employment of the home economies. The central goal of this paper is to empirically explore the evidence of the macroeconomic relationship between OFDI and levels of domestic capital formation in India. Our study reveals that OFDI has long run strong positive causality with domestic investment and thus figures out to be a significant factor affecting domestic investment in India. It becomes imperative therefore that the nation make special effort to promote its OFDI through the designing of appropriate OFDI policies that would help stimulate its domestic investment now and in the future so as to sustain economic growth and development in the long run. Key Words & Concepts: Domestic Investment, FDI Outflows, Structural Break, CMR Unit Root Test, ARDL Bounds Test JEL Classifications: E22, F21, F23, C32 1 FDI Outflows and Domestic Investment: Substitutes or Complements? Exploring the Indian Experience The emerging economies are recently demonstrating increasing alacrity of foreign direct investment (FDI)1 outflows to the rest of the world. It is common knowledge that outward FDI (OFDI) flows encourage economic cooperation and global integration between the source and host countries. They also result in technology and skill transfer, sharing of knowledge, access to international brand names and global markets and global resources and income generation for the host and recipient countries (UNCTAD, 2004). Despite the potential of developing a portfolio of such locational assets as a source of international competitiveness and visibility, the phenomenon of rising overseas FDI flows from emerging economies has raised serious policy concerns about their effects on the domestic investment in the countries of origin of such FDI flows. The question that naturally arises is that whether the current trend of overseas FDI outflows will be conducive for the economies to sustain long run economic development in the future, and if so, to what extent. Sustainable economic development depends crucially, among other things, on the extent of domestic investment undertaken by a country, as it is an effective instrument in the creation of national output and employment of an economy2. From a policy perspective, it is therefore important to understand the effect of OFDI flows from a country on its domestic capital formation. A review of the available theoretical and empirical literature on the association between domestic investment and OFDI provides two distinct economic views regarding the effect of OFDI on the home country investment – substitutability and 1 Foreign direct investment are the net flows of investment to acquire a lasting management interest (10% or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments (World Bank, 2012). 2 The early growth models of Harrod (1939) and Domar (1946) assumed that output was proportional to capital and thus growth rate of output would be proportionally related to the growth rate of capital that is investment. Later on, the endogenous growth models of Romer (1986), Lucas (1988) etc. based on the Harrod-Domar assumptions of constant returns to capital, also conclude that higher investment rates lead to a higher growth rate of output (Agarwal, Sahoo, Dash, 2007). 2 complementarity, each of which has its own implications on domestic economic growth and employment. Controversies exist in the relevant theoretical and empirical literature about the potential impact of OFDI on domestic investment. Policy concerns become especially pronounced when OFDI tends to substitute those domestic investments that could have sustained and enhanced home productivity. It becomes theoretically important and practically relevant therefore, to study the association between these two macroeconomic variables, because of the inherent growth and developmental implications of OFDI for the home countries and also for the rest of the world. The existing economic literature on OFDI-domestic investment nexus has been directed predominantly towards the developed countries such as the U.S., Sweden, Germany and Japan presumably because of the sheer volume of their foreign investment that have attracted wide research (Kim, S., 2000). Also, these are the countries that published detailed data on outward FDI already from an early stage of global capital flows, from the 1970s and onwards. For the emerging nations, however, not much relevant literature on OFDI has developed. There could be some understandable reasons for this. First, the phenomenon of OFDI is relatively new for the emerging economies and hence the consequently volume of OFDI activities in these countries is relatively less. And, for the same reason, contrary to the developed countries, the emerging economies naturally, could not generate data on outward FDI since the 1970s. But, the existing robust OFDIdomestic investment literature for the advanced economies of the world may not be generally relevant for the emerging countries because the consequences of outward FDI may vary, for example, between capital-rich and capital-scarce OFDImaking countries3. 3 This is because, OFDI outflows transfer part of private domestic savings abroad (Al-Sadig, 2013). 3 The rising prominence of OFDI from the emerging economies has generated the importance of investigating the bearing of OFDI on such home countries. Economists and policy-makers are increasingly focusing their attention on exploring the relationship between OFDI and domestic investment of OFDIoriginating emerging economies either for individual countries (Kim, 2000; Girma, Patnaik, Shah, 2010; Goh and Wong, 2012, 2014; Hsu and Cleggs, 2015), or for a panel of countries (Page and te Velde, 2004; Al-Sadig, 2013; Dasgupta, 2014). With panel data analysis, question arises as to whether the results of the generic studies4 which apply to the average country in the sample, are also applicable to specific regions or nations. This is because, OFDI, like any other macroeconomic variable, shows substantial cross country differences depending on the prevailing socioeconomic and political environment. Thus, country-specific study is more suitable if our objective is to estimate the relationship between outbound FDI and the home country investment of a particular economy of interest. The country-level analysis is very important, so as to identify the critical path of industrialization that each such country must adopt and implement in the present global economic environment and to define or redefine their engine of growth. Accordingly, the present research chooses to concentrate only on a single emerging economy5 -- India and explore the role of OFDI as stimulating or impairing its domestic investment in the long run for a period of 35 years from 1980 through 2014. Concern in India about the role of OFDI naturally got aggravated with the global economic crisis in 2008 when India, like other emerging economies, experienced acute capital withdrawal (Rajan, 2009) and decline in GDP growth. Also, the recent acquisition of foreign firms by prominent Indian business houses 4 Al-Sadig (2013) has recently accomplished a generic panel study on the relationship of OFDI with the domestic investment of 121 developing countries. 5 The emerging countries are considered to be those nations with social or business activity in the process of rapid growth, restructuring and industrialization along market-oriented lines to offer a wealth of opportunities in trade, technology transfers, and FDI. For additional information, read Li (2010), Sauvant (2005), Grant (2010). 4 such as the Tatas, Wipro, Infosys, etc. have ignited economic, political and academic interest on the nature of Indian OFDI flows. Design of the study This study is a time series analysis of the long run causality between OFDI and domestic investment for India over 1980-2014. The paper is divided into five sections that include this introduction (Section 1) and a conclusion (Section 5) bearing a summary of the findings, the relevant policy recommendations and the future research agenda. Section 2 documents the overall statistics of Indian OFDI and domestic investment. Section 3 delivers a review of the existing economic literature on this issue. In Section 4, we provide the details of the data, postulate the methodology, perform the econometric time series analysis and analyze the empirical results. We will try to keep all the technical discussions limited to the bare necessities for explaining the paper and instead provide the relevant references. 2. OFDI and Domestic Investment in India OFDI Leveraging FDI inflows for sustainable economic development has long been tested in India with mixed outcomes (Chakraborty and Mukherjee, 2012; Dolly, 2015). However, the reverse trend towards OFDI flows is relatively new to the country. Since the 1980s, Indian firms were making overseas investment, albeit under restrictive regulations and subject to conditions of no cash remittance and mandatory repatriation of dividend from the profits from the overseas projects (Khan, 2012). The adoption of the economic liberalization policies in 1991 in areas such as industrial deregulation, trade liberalization and inward FDI relaxation raised competitiveness of many Indian firms, thus encouraging many of those to undertake OFDI flows in joint ventures and wholly owned subsidiaries. Together 5 with private OFDI initiatives, Indian state-owned enterprises have been also getting involved in greenfield OFDI. In 1992, the ‘automatic route’ for overseas investments was introduced and cash remittances were allowed for the first time. Nonetheless, the total value was restricted to $2 million with a cash component not exceeding $0.5 million in a block of 3 years (Khan, 2012). India has experienced a steady rise in capital inflows, particularly in the second half of 2000s, which led to a favorable overall foreign exchange reserve position. It is in this backdrop that the Indian government undertook further relaxation of the capital controls and also simplified the procedures for OFDI from India (Khan, 2012). Till 1994, the approvals for OFDI were made by the Ministry of Commerce. It is from 1995, that a comprehensive policy framework was laid down and the task of OFDI approvals was undertaken by the Reserve Bank of India (RBI) in order to provide a single window clearance mechanism. A fast track route was adopted where the upper limits were raised from $2 million to $4 million and linked to average export earnings of the preceding three years. Cash remittance continued to be restricted to $0.5 million. Beyond $4 million, approvals were considered under the ‘Normal Route’ approved by a Special Committee comprising the senior representatives of the RBI (Chairman) and the Ministries of Finance, External Affairs and Commerce (members). Investment proposals in excess of $15 million were considered by the Ministry of Finance with the recommendations of the Special Committee and were generally approved if the required resources were raised through the global depository route (GDR). Together with the exporters, the exchange earners were incorporated under the fast track route in 1997. The Foreign Exchange Management Act (FEMA) was introduced in June 2000, expanding the scope for OFDI from India. Since then on, the OFDI policies have undergone massive overhauling. In 2002, the annual upper limit for automatic approval was raised to $100 million. In March 2003 the ceiling was further liberalized so that the Indian participants in the OFDI process could invest to the 6 controls on foreign exchange outflows and late advent of corporate globalization of Indian firms, on the other. India’s Position Relative to the World As is evident from above, the liberalization of the OFDI regime from regulatory protection and supportive industrial and technology policies in the early 1990s, played significant role in facilitating OFDI from India. India is now the largest outward investor among the countries affiliated to the South Asian Association for Regional Cooperation (SAARC) as per the data provided by the 2015 UNCTAD FDI Statistics. This is shown in Figure 4 that exhibits the OFDI flows of select SAARC countries -- India, Bangladesh, Pakistan and Sri Lanka. FDI statistics of the remaining SAARC nations – Bhutan, Nepal and Maldives over the entire time period – 1980 through 2014 is not provided by UNCTAD (2015) which naturally implies that the outward FDI from these countries is very likely to be negligible or close to zero. Source: World Investment Indicators, World Bank. -80% -60% -40% -20% 0% 20% 40% 60% 80% 100% Figure 4 OFDI Flows from Select SAARC Countries Sri Lanka Pakistan India Bangladesh 13 In order to comprehend India’s relative position in the global arena as an outward FDI-making economy, we further examine Table 1 that compares OFDI-GFCF ratio for India with select OECD countries in Europe and the United Kingdom (UK). We find that in these countries, OFDI corresponds to a large share of total domestic investment – in some cases up to one-third. Spectacularly high ratios (around 80% or more) were observed in 2000 with Finland, Netherlands, Sweden and the UK and 65% for Switzerland. This rise in OFDI-GFCF ratio in 2000 for these economies could be attributable to the historically high levels of OFDI in the service sector influenced by global privatization trends (Christiansen and Bertrand, 2004). During 1990-2000, the ratio for India was abysmally low, signifying very low OFDI in relation to the nation’s domestic investment. However, from 2001, while the European countries witnessed a sharp fall in their OFDI-domestic investment ratio, India experienced a gradual rise in this ratio, reaching as high as 5.5% in 2008 – the year of severe global crisis. This phenomenon in India can be explained by the introduction of FEMA in 2000 and extensive revamping in OFDI policies since then by the gradual liberalization of the capital account. 2005-2008 have been buoyant years for OFDI in India; according to Kumar (2008), OFDI from India rose remarkably from 2005 as shown by the increase in the number of approved projects from 220 in 1990-1991 to 395 in 1999-2000 and to 1,595 in 2007-2008. Although the ratio declined in 2012 and 2013, there has been a marginal recovery in 2014. Also, comparing India with China in Figure 5, we see that from 1990-2001, China had a low and declining OFDI-GFCF ratio, although more or less high than that of India. But from 2002 through 2010, the ratio has consistently fallen for China, compared to India. Even though since 2011 the ratio is higher for China, the gap between the two countries has been narrowing over the years. This overall growing trend of the OFDI-GFCF ratio of India in the global scenario draws our attention to the study of the trend of Indian OFDI and its impact on home country investment. 14 Table 1 OFDI-GFCF Ratio for Select Countries including India, 1990-2014 Year Finland Netherlands Sweden Switzerland United Kingdom India 1990 4.8 19.4 20.7 8.9 6.4 0.0 1991 - 0.3 18.2 10.4 8.4 6.3 - 0.0 1992 - 2.8 16.2 0.7 8.4 7.1 0.0 1993 9.0 13.0 3.4 13.2 12.1 0.0 1994 22.9 21.6 15.4 14.6 14.2 0.1 1995 5.4 20.1 21.8 14.1 18.0 0.1 1996 12.8 31.8 8.7 20.2 12.9 0.2 1997 19.1 27.0 24.2 25.7 22.6 0.1 1998 62.3 37.9 44.5 25.6 41.7 0.0 1999 21.8 55.4 37.9 45.8 67.2 0.1 2000 82.7 79.7 71.3 64.9 79.3 0.5 2001 28.3 52.9 13.5 26.7 20.2 1.2 2002 24.3 32.3 18.5 11.1 16.2 1.4 2003 - 6.1 47.1 30.0 18.3 19.0 1.2 2004 - 2.5 28.2 27.0 27.3 24.1 1.0 2005 9.0 77.0 32.2 51.3 18.0 1.2 2006 9.7 47.6 27.6 72.4 16.1 4.8 2007 11.7 30.8 33.3 43.6 58.3 4.2 2008 13.4 33.1 24.3 34.0 37.4 5.5 2009 9.9 14.5 27.3 21.5 5.5 3.7 2010 18.7 41.3 18.7 64.6 12.1 3.0 2011 8.2 19.2 23.4 29.6 25.8 2.0 2012 13.2 3.3 23.5 27.6 6.8 1.5 2013 - 13.3 36.5 22.5 6.4 - 3.4 0.3 15 2014 1.1 25.2 9.2 10.1 - 11.9 1.7 Source: World Investment Report, 2015, Table 6. Source: Developed by the author, based on World Investment Report, 2015, Table 6. 3. Literature Review Given the pattern of OFDI flows and domestic investments in India, we address the theoretical questions about the impact of OFDI on the economic growth and development for the economy. Does a fast growth of capital outflow in the form of OFDI imply that the domestic investment is losing attractiveness to the home country investors so that resources and consequently the economic activities are diverted abroad? Or whether the OFDI is actually a catalyst to domestic investment? The process of answering these questions leads us to a survey of the existing economic literature that points towards two opposite strands of thought – substitutability and complementarity -- in explaining the association between domestic investment and OFDI of the economies of origin. Rest of this section will - 1,0 - 1,0 2,0 3,0 4,0 5,0 6,0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Figure 5 OFDI-GFCF Ratio of China and India, 1990-2014 China India 16 explore the substitution and complementary association between the two variables both from the theoretical and empirical perspectives. 3.1 Substitution Theoretical Literature Economic literature predominantly indicates a relation of substitutability between OFDI and domestic investment and the resultant crowding out of investment in the home countries. This can happen in many ways. First, overseas relocation of domestic production may take place because of reduced investment opportunities at home. Such OFDI activities may not only shift some of the production activities from home to foreign destinations but also possibly threaten the availability of scarce financial resources at home by allocating resources abroad (Stevens and Lipsey, 1992). This outflow of capital that may diminish net external finance for domestic investments would also tend to substitute those domestic investments that could have sustained and enhanced home productivity. This has the potential to reduce the domestic productivity of home firms in the long run by lowering their rate of accumulation of physical capital, thereby impairing their domestic investment, which, in turn is detrimental to the long run rate of economic growth and employment of the country (Al-Sadig, 2013). Second, the domestic production of goods14 could be shifted overseas due to the lower cost of capital abroad, the preferential tax treatment to foreign profits of home country corporations and other fiscal incentives in the host countries (Stevens and Lipsey, 1992; Feldstein, 1995; Desai Foley and Hines, 2005 and Herzer and Schrooten, 2007). If the firms making such overseas investment partly self-finance the OFDI there will occur a foreign transfer of at least a part of their domestic savings. This raises the domestic interest rate and crowds out domestic investment thus deterring the creation of new capital in the home economy. Thus, 14 OFDI in services would have either neutral or positive effects on the rate of domestic investment because such FDI would not substitute exports (Al Sadig, 2013). 17 whether OFDI crowds out domestic investment also depends on how that FDI outflow was financed (Kim, 2000). Next, when a firm builds a production base in a foreign country with low labor costs, there exists a possibility that it will in future continue to devote resources and create jobs in these foreign outlets to enjoy the advantages of low wage cost coupled with market penetration. This would in turn have unfavorable effects on home country investment, employment, growth and development (Girma, Patnaik, Shah, 2010). Also, the capital control policies of a country may create a wedge between the capital cost of domestic versus foreign expansion and thus crowd out domestic investment. For example, in India, because it is cheaper for Indian firms to secure debt for creation of foreign assets rather than for domestic investment (Girma, Patnaik, Shah, 2010), more and more firms tend to be encouraged to shift their domestic production overseas with relatively lower interest rates. Thus OFDI substitutes domestic investment. But the lower rate of interest in the home country may attract more FDI from abroad and thus increase the capital availability that would consequently lower the price of capital. In this case, OFDI and domestic investment would have a complementary (positive) association. Thus the effect of OFDI on domestic investment could be ambiguous in the long run. Girma, Patnaik, Shah (2010) refer to “peculiar features of capital controls” in India where foreign debt capital is cheaper to raise, provided it would be employed for OFDI rather than for domestic investment. This creates a difference between the cost of capital for domestic versus foreign expansion and thus could possibly boost the growth of OFDI at the cost of home country investment. Crowding out of domestic investment might also be visible when domestic firms engage in offshore production with the primary objective of exporting back to home 18 markets. Thus, foreign production through OFDI flows replaces the home country exports of that very product, leading to the crowding out of domestic investment through its export-replacing effect (Kim, 2000). Desai, Foley and Hines (2005) have argued that in the case of horizontal OFDI there is a possibility of the diversion of domestic investment provided the domestic production have been substituted by overseas production by the home country firms. However, in latter stages after the accomplishment of the initial horizontal cross-border investment, if the foreign operations utilize their domestic set-up, OFDI and domestic investments could become complementary to each other. Finally, substitutability could also arise later in vertical OFDI when stages of the production process that were previously undertaken in the home country are now shifted to overseas locations. However, in such cases, where on the one hand, outward FDI displaces exports of finished products and on the other hand, promote exports of intermediate products from the parent or from other domestic firms in the home country to the firm’s foreign affiliate, the net impact becomes unclear (AlSadig, 2013). Empirical Findings Feldstein (1995) derived robust results on substitutability from aggregate cross country data of major OECD countries during the 1970s and 1980s. He found a roughly one-to-one negative correlation15 between OFDI and domestic investment indicating that outward investment and domestic investment are at least partial substitutes. One-to-one negative relation between OFDI and domestic investment has also been confirmed by Sauramo (2008) in his macroeconomic study for Finland over 1965–2006. Desai, Foley, and Hines (2005a) have also supported negative association between OFDI and domestic investment for OECD-countries for the 1980s and 1990s in line with Feldstein but with a larger sample set of 15 This means that every dollar amount of OFDI causes one dollar to be less invested at home thus indicating a perfect substitutability between the two variables. 19 OECD economies. Such substituting relationship, although less than dollar to dollar negative association was also confirmed by Andersen and Hainaut (1998), employing data for the United States (US), Japan, Germany, and the United Kingdom (UK) spanning from the 1960s until the 1990s. That the OFDI by Swedish multinationals had a negative effect on the size of their home country’s capital stock has been established by Svensson (1993). Herzer and Schrooten (2007) conducted a similar analysis for the US and Germany. They distinguished between the short-run and long-run effects of outward FDI on domestic investment in Germany and found that the long-run effect was negative for Germany. 3.2 Complements Theoretical Literature It is also recognized that OFDI can actually be instrumental in fostering positive linkages with the country of origin through the employment of domestic inputs and promotion of domestic investment in the manufacturing and service (information technology, management etc.) sectors while producing outputs in the host country. Such an increase in OFDI activities by home country multinationals may promote higher domestic investment and output, leading to long run economic growth (Desai, Foley and Hines, 2005)16. Positive or complementary association between OFDI and domestic investment could happen in situations of efficiency-seeking OFDI where the home and overseas production activities are deliberately combined by the investing firms to exploit the economies of scale, reduce costs and enhance the efficiency in domestic production and investment efforts. While foreign production through OFDI flows can replace the possibility of home country exports of that very product, such production could also be export16 The current deceleration in the growth of the emerging economies has once again made this question relevant. While the emerging markets as a group was growing at about 7% before the crisis (2003-08), their post crisis growth rate fell to about 5 by the next 5 years. Such synchronized deceleration has raised concern among the economists of the emerging nations as well as those of the developed countries because of the potential adverse spillover effects through trade and finance at the global level and eventual spillbacks on the original source economies themselves (Blanchard, Faruqee, Das, 2010; Harding, 2014). 20 supporting in that it could generate demand for the tangible and intangible resources, such as machinery and other capital equipment, raw materials, stores and spares, software technology and technical and managerial consultancy services from the domestic counterpart of the capital exporting firms. In other words, the overseas subsidiaries of home country firms may import significant amounts of inputs and technology from their parent companies as conduits of the initial FDI made from the home country. These products that may be provided by other parts of the parent company, its suppliers, or independent firms at home would possibly complement domestic investment (Kim, 2000) and thus generate increased economic activity and employment, as well as tax revenues, exports and also the spillover of imported technologies to the domestic firms. Moreover, the returns from overseas subsidiaries like dividends and interests may also enable Indian parent firms to expand in the long run leading to more employment opportunities (Pradhan, 2008). Such FDI where the production process is partly relocated to the home country, thus complementing exports of capital and intermediate goods and services are vertical (Braunerhjelm, Oxelheim and Thulin, 2006) and thus do not eventually reduce home country production (Al-Sadig, 2013). Thus, what initially started as horizontal investment (export-replacing) may also have strong positive effects on domestic investment by the generation of vertical links between domestic and foreign production via the demand for capital or intermediate goods and services by the foreign affiliates of the domestic companies. Also, OFDI-making firms from emerging economies may undertake naturalresource-seeking FDI outflows and export part or whole back to the home country to ensure a steady supply of inputs at stable prices that would be essential to their production processes at home (Anwar, Hasse, Rabbi, 2008; UNCTAD, 2005, Buckley, et al. (2007)). 21 Empirical Findings Desai, Foley and Hines (2005) have suggested positive relationship between OFDI and domestic investment. Using time-series data on capital expenditures of US multinational companies they found a direct association between their capital expenditure abroad and their domestic capital spending, thus establishing the complementarity between OFDI and domestic investment of these US firms. Strong positive association has also been found by Stevens and Lipsey (1992) who have employed firm-level data involving the domestic and foreign operations of seven US MNEs for a period of 16 to 20 years. Complementarity is established in Faeth (2006) for Australian balance of payments data. 4. Data, Methodology, Analysis 4.1 Data While gross fixed capital formation-GDP ratio (I) representing domestic investment is the dependent variable, the study considers a comprehensive set of five relevant macroeconomic variables that could be expected to explain domestic investment. OFDI and TR (export plus imports indicating overall trade in the economy) are the indicators of openness17; domestic credit availability to the private sector (DCP) and broad money supply (M2) are the indicators of financial deepening; and per capita GDP (GDPPC) signifies the aggregate demand conditions in the economy. 17 We have not included current account balance which serves as a direct measure of openness because the data for World Development Indicators of the World Bank provide current account balance data for India only from mid-1990s. We have also deliberately excluded FDI inflows as another openness factor determining domestic investment. This is because of the possible existence of multicollinearity between OFDI and FDI since more OFDI by home country firms could encourage greater levels of FDI into the home country, as there is greater awareness and appreciation of the economy’s potential and inherent strengths by the rest of the world (Pradhan, 2008) Another, equally convincing reason for not including FDI as a determinant of domestic investment is that there is an ambiguity as whether or not FDI is already included in the GFCF data. To clarify, while GFCF consists of outlays on additions to the fixed assets of the economy, FDI relates to financing, that is the purchase of shares in foreign companies where the buyer has a lasting interest (10 percent or more of voting stock). FDI can be used to finance fixed capital formation; however, it can also be used to cover a deficit in the company or paying off a loan. Thus, one cannot clearly conclude that FDI is always included in GFCF data. https://datahelpdesk.worldbank.org/knowledgebase/articles/195312-is-foreign-direct-investment-fdi-included-in-gro 22 Pesaran, Shin and Smith. So, before applying the ARDL test, we have also checked that our variables are not I(2) using the CMR unit root test, so as to avoid spurious results. Another beauty of the Pesaran and Shin ARDL model is that unlike other methods of estimating cointegrating relationships, the ARDL representation does not require symmetry of lag lengths; each variable can have a different number of lag terms. The basic framework for our ARDL model is as follows: ΔI = a0 + ∑𝑏𝑏𝑗𝑗∆𝐼𝐼𝑡𝑡−𝑗𝑗 𝑛𝑛 𝑗𝑗=1 + ∑𝑐𝑐𝑗𝑗∆𝑂𝑂𝑂𝑂𝑂𝑂𝐼𝐼𝑡𝑡−𝑗𝑗 𝑛𝑛 𝑗𝑗=0 + ∑𝑑𝑑𝑗𝑗∆𝑂𝑂𝐷𝐷𝐷𝐷𝑡𝑡−𝑗𝑗 𝑛𝑛 𝑗𝑗=0 + ∑𝑒𝑒𝑗𝑗∆𝐺𝐺𝑂𝑂𝐷𝐷𝐷𝐷𝐷𝐷𝑡𝑡−𝑗𝑗 𝑛𝑛 𝑗𝑗=0 + ∑𝑒𝑒𝑗𝑗∆𝑀𝑀2𝑡𝑡−𝑗𝑗 𝑛𝑛 𝑗𝑗=0 + ∑𝑓𝑓 𝑗𝑗∆𝑀𝑀2𝑡𝑡−𝑗𝑗 𝑛𝑛 𝑗𝑗=0 + ∑𝑔𝑔𝑗𝑗∆𝑇𝑇𝑇𝑇𝑡𝑡−𝑗𝑗 𝑛𝑛 𝑗𝑗=0 + β1It-1 + β2OFDIt-1 + β3DCPt-1 + β4GDPPCt-1 + β5M2t-1 + β6TRt-1 + ξt (3) The parameters βi (i = 1, 2, 3, 4, 5, 6) are the corresponding long-run multipliers, while the parameters bj, cj, dj, ej and fj are the short-run dynamic coefficients of the underlying ARDL model. The null hypothesis (i.e. H0: β1 = β 2 = β 3 = β 4 = β 5 = β 6 = 0, implying no cointegration) in the first step is tested by computing a general F statistic using all the variables. Using maximum of 4 lags for the dependent variable, I and maximum of 3 lags for the regressors and following the Akaike Information Criterion, we are ultimately interested in finding out the long-run relationship of the variables of interest. From the 4096 models evaluated, with varying lag structures, the optimum lag structure for the variables is obtained as (4, 3, 3, 1, 3, 2) – 4 lags for the dependent variable I, 3 lags for OFDI, 3 lags for DCP, 1 lag for GDPPC, 3 for M2 and 2 lags for TR. We have included the BREAKIOI0 dummy variable (to indicate the structural breakpoint years from the CMR IO unit root testing model at level I(0)), as well as an intercept and linear trend as (fixed) regressors (that is, they would not be 29 lagged). The R-squared is 0.99 and the probability of the F statistics is close to zero24. Since ARDL models are estimated by simple least squares, all of the views and procedures available to equation objects estimated by least squares are also available for ARDL models. The standard least squares output for the selected model is shown in Table 3. We observe that most of the regressors are statistically significant. The breakpoint dummy is not significant though. We also see that the coefficients on the one period and three period lags of the dependent variable, OFDI are very high at 5.67 and 5.93 respectively. This indicates strong positive lagged effect of OFDI on domestic investment, I. Table 3 ARDL Model – Least Squares Variable Coefficient Std. Error t-Statistic Prob.* I(-1) -0.805471 0.275838 -2.920088 0.0223 I(-2) -0.407880 0.212868 -1.916112 0.0969 I(-3) -0.791995 0.275307 -2.876772 0.0238 I(-4) -0.376448 0.222281 -1.693568 0.1342 OFDI -3.471348 1.822510 -1.904707 0.0985 OFDI(-1) 5.674693 1.587275 3.575118 0.0090 OFDI(-2) 4.731917 2.169498 2.181111 0.0655 OFDI(-3) 5.927564 1.721207 3.443841 0.0108 DCP 1.242338 0.360635 3.444858 0.0108 DCP(-1) 1.613687 0.394861 4.086723 0.0047 DCP(-2) 1.226073 0.366521 3.345159 0.0123 DCP(-3) -0.368321 0.235464 -1.564233 0.1617 24 Results will be shown up on request. 30 GDPPC -0.001681 0.005921 -0.283844 0.7847 GDPPC(-1) -0.017911 0.006615 -2.707661 0.0303 M2 -1.130072 0.300607 -3.759295 0.0071 M2(-1) -0.795822 0.269196 -2.956288 0.0212 M2(-2) -0.805148 0.292778 -2.750033 0.0285 M2(-3) -0.473631 0.223772 -2.116577 0.0721 TR 0.496687 0.152367 3.259801 0.0139 TR(-1) -0.525348 0.163662 -3.209961 0.0149 TR(-2) -0.748647 0.182607 -4.099782 0.0046 BREAKIOI0 -0.569138 0.484528 -1.174624 0.2786 C 95.61388 17.55850 5.445446 0.0010 @TREND 3.856128 0.808363 4.770293 0.0020 R-squared 0.993634 Mean dependent var 25.71531 Adjusted R-squared 0.972718 S.D. dependent var 4.269510 S.E. of regression 0.705208 Akaike info criterion 2.199663 Sum squared resid 3.481230 Schwarz criterion 3.309846 Log likelihood -10.09477 Hannan-Quinn criter. 2.561555 F-statistic 47.50521 Durbin-Watson stat 2.955467 Prob(F-statistic) 0.000012 *Note: p-values and any subsequent tests do not account for model selection. Figure 7, which provides a graph of the AIC of the top twenty models, shows the relative superiority of the selected model against alternatives. It is evident from the figure that the selected ARDL (4, 3, 3, 1, 3, 2) model is better than other ARDL models. It is notable that 16 out of 20 top models use 4 lags of the dependent variable. 31 Figure 7 Top 20 ARDL Models 2.15 2.20 2.25 2.30 2.35 2.40 2.45 2.50 2.55 ARDL(4, 3, 3, 1, 3, 2) ARDL(4, 3, 3, 2, 3, 2) ARDL(4, 3, 3, 2, 3, 3) ARDL(4, 3, 3, 1, 3, 3) ARDL(4, 3, 3, 3, 3, 2) ARDL(4, 3, 3, 3, 3, 3) ARDL(4, 3, 2, 1, 3, 3) ARDL(4, 3, 3, 2, 2, 3) ARDL(4, 3, 2, 2, 3, 3) ARDL(4, 3, 3, 3, 2, 3) ARDL(4, 3, 2, 3, 3, 3) ARDL(4, 3, 2, 3, 3, 2) ARDL(4, 3, 2, 1, 3, 2) ARDL(3, 3, 3, 1, 3, 2) ARDL(4, 3, 2, 2, 3, 2) ARDL(4, 3, 3, 1, 2, 3) ARDL(3, 3, 3, 1, 3, 3) ARDL(3, 3, 3, 2, 2, 3) ARDL(3, 3, 3, 2, 3, 3) ARDL(4, 3, 3, 3, 1, 3) Akaike Information Criteria (top 20 models) Author’s calculations using EViews 9. One of the main purposes of estimating an ARDL model is to use it as the basis for applying the "Bounds Test" of cointegration, shown in Table 4. The Bounds Test displays the F statistic and the 10%, 5%, 2.5% and 1% bounds for both the all I(0) and all I(1) cases. Upper and lower critical bound values for an F-test have been provided by Pesaran and Shin (1999). The use of the Pesarans’ bounds technique is based on three validations. First, Pesaran and Shin advocated the use of the ARDL model for the estimation of level relationships because the model suggests that once the order of the ARDL has been recognized, the relationship can be estimated by OLS. Second, the bounds test allows a mixture of I(1) and I(0) variables as regressors, that is, the order of integration of appropriate variables 32 may not necessarily be the same. Therefore, the ARDL technique has the advantage of not requiring a specific identification of the order of the underlying data. Third, this technique is suitable for small or finite sample size (Pesaran, Shin and Smith 2001). However, the bounds technique is not applicable for I(2) variables. The Bounds Test approach confirms the existence of the long run relationship on the basis of an F-test, which determines if the coefficients of all explanatory variables are jointly different from zero. The null hypothesis is that there is no long-run relationship between the variables. Applying the ARDL procedure, we find cointegration result. The value of F statistics is 7.06, which clearly exceeds even the Pesaran 1% upper critical bound 4.63. Accordingly, we strongly reject the hypothesis of "no long run relationship". Results thus confirm that our model fulfills the criterion of cointegration or long run relationship of the dependent variables with I (Table 4). Table 4 ARDL Bounds Test Sample: 5 35 Included observations: 31 Null Hypothesis: No long-run relationships exist Test Statistic Value k F-statistic 7.062508 5 Critical Value Bounds Significance I0 Bound I1 Bound 10% 2.49 3.38 5% 2.81 3.76 33 2.5% 3.11 4.13 1% 3.5 4.63 Author’s calculations using EViews 9. In the estimation results for our chosen ARDL model, we estimate the cointegration and long-run form of the model in Table 5. It is evident from the upper segment of the output of Table 5 that the cointegration coefficient is negative (-3.39), as required, and is statistically very significant (p value equal to zero). More importantly, the long-run coefficients are reported in the lower segment of Table 5, with their standard errors, t-statistics, and p-values. We observe that there is a statistically long-run equilibrium relationship between domestic investment, OFDI and other dependent variables as shown by the p values. Focusing our attention on OFDI, we find that a $1 rise in OFDI will raise the domestic investment by nearly 4 times. This shows that OFDI has a strong positive long run effect on domestic investment in India indicating complementarity between OFDI and domestic investment in India. Table 5 ARDL Cointegrating and Long Run Form Cointegrating Form Variable Coefficien t Std. Error t-Statistic Prob. D(I(-1)) 1.576549 0.228764 6.891595 0.0002 D(I(-2)) 1.159780 0.180430 6.427860 0.0004 D(I(-3)) 0.381795 0.126522 3.017615 0.0195 D(OFDI) -3.543526 0.710983 -4.983981 0.0016 34 D(OFDI(-1)) - 10.65739 0 1.539238 -6.923811 0.0002 D(OFDI(-2)) -5.870828 0.831417 -7.061233 0.0002 D(DCP) 1.247493 0.167228 7.459853 0.0001 D(DCP(-1)) -0.848708 0.165661 -5.123154 0.0014 D(DCP(-2)) 0.371802 0.108335 3.431964 0.0110 D(GDPPC) -0.002022 0.002401 -0.842125 0.4275 D(M2) -1.131352 0.137780 -8.211283 0.0001 D(M2(-1)) 1.277481 0.164858 7.748984 0.0001 D(M2(-2)) 0.472207 0.085871 5.498998 0.0009 D(TR) 0.497506 0.059974 8.295322 0.0001 D(TR(-1)) 0.749839 0.097501 7.690537 0.0001 D(BREAKIOI0) -0.657754 0.211955 -3.103278 0.0172 C 99.69747 0 9.952154 10.017678 0.0000 CointEq(-1) -3.389213 0.339327 -9.988058 0.0000 Cointeq = I - (3.8036*OFDIF + 1.0982*DCP -0.0058*GDPPC - 0.9476*M2 -0.2299*TR -0.1683*BREAKNOLOGIOI0 + 1.1403*@TREND ) Long Run Coefficients Variable Coefficien t Std. Error t-Statistic Prob. OFDI 3.803551 0.410352 9.268993 0.0000 DCP 1.098168 0.124346 8.831556 0.0000 GDPPC -0.005793 0.001381 -4.196266 0.0041 35 M2 -0.947626 0.119582 -7.924484 0.0001 TR -0.229851 0.045078 -5.098928 0.0014 BREAKIOI0 -0.168295 0.137911 -1.220318 0.2619 @TREND 1.140261 0.113794 10.020395 0.0000 Author’s calculations using EViews 9. We also find that a $1 rise in domestic credit availability increases domestic investment, I by about $1.1. Increase in credit availability to the private sector facilitates financing and thus causes a rise in the level of private investment with favorable effect on the long term productive capacity of the economy (Frimpong and Marbuah, 2010). Thus, the positive relationship concurs with the standard expectations. It is also evident that a dollar rise in M2 leads to a less than 1 dollar fall (coefficient is -0.95) in domestic investment. Although, this contradicts standard expectations, it is perfectly explicable in the Indian situation since the growth in money supply (M2) has consistently exceeded the GDP growth rate (Figure 8a), leading to a high inflation rate (Figure 8b) over the period25.Trade (TR) exhibits a small but negative relationship (coefficient is -0.23) with I. This is obvious, since Indian imports have consistently dominated exports (Figure 9), thus justifying the contention of Ndikumana (2000) that if the openness of an economy increases due to consumers preferring imported goods and services then domestic investment could fall. 25 It is common knowledge derived from macroeconomics theory that if the money supply of an economy grows much faster than the economy itself, then that causes rapid inflation. The value of money falls and this reduces the effectiveness of money as a store of value. Also, the continuous rise in prices makes money ineffective as a unit of account. Higher interest rates are charged for loans and credit to compensate lenders for the declining value of money, which consequently tends to restrict investment and spending. 36 Source: World Development Indicators, World Bank. Source: World Development Indicators, World Bank. 0 5 10 15 20 25 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Figure 8a Growth in Money Supply and GDP Growth in India over 1980-2014 GM2 GGDP 0 2 4 6 8 10 12 14 16 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Figure 8b Inflation Rate in India (CPI) over 1980-2014 37 The ARDL model derived above is stable because it satisfies the diagnostic test of stability (CUSUM test) shown in Figure 10. 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Peverelli - Port of Rotterdam in Chinese Eyes 2007-20 June: Chengxin Pan - What is Chinese about Chinese Business? Implications for U.S. Responses to China’s Rise 2007-21 September: Charles S. Costello III - The Irony of the Crane: Labour Issues in the Construction Industry in the New China 2007-22 October: Evelyn Devadason - Malaysia-China Network Trade: A Note on Product Upgrading 2007-23 October: LooSee Beh - Administrative Reform: Issues of Ethics and Governance in Malaysia and China 2007-24 November: Zhao Hong - ChinaU.S. Oil Rivalry in Africa 2008: 2008-25 January: Émile Kok-Kheng Yeoh - Ethnoregional Disparities, Fiscal Decentralization and Political Transition: The case of China 2008-26 February: Ng Beoy Kui - The Economic Emergence of China: Strategic Policy Implications for Southeast Asia 2008-27 September: Verner Worm - Chinese Personality: Center in a Network 2009: 2009-28 July: Xin Li, Verner Worm - Building China’s soft power for a peaceful rise 2009-29 July: Xin Li, Kjeld Erik Brødsgaard, Michael Jacobsen - Redefining Beijing Consensus: Ten general principles 2009-30 August: Michael Jacobsen - Frozen Identities. Inter-Ethnic Relations and Economic Development in Penang, Malaysia 2010: 2010-31 January: David Shambaugh – Reforming China’s Diplomacy 2010-32 March: Koen Rutten - Social Welfare in China: The role of equity in the transition from egalitarianism to capitalism 2010-33 March: Khoo Cheok Sin - The Success Stories of Malaysian SMEs in Promoting and Penetrating Global Markets through Business Competitiveness Strategies 2010-34 October: Rasmus Gjedssø and Steffen Møller – The Soft Power of American Missionary Universities in China and of their Legacies: Yenching University, St. John’s University and Yale in China 2010-35 November: Michael Jacobsen - Interdependency versus Notions of Decoupling in a Globalising World: Assessing the Impact of Global Economics on Industrial Developments and Inter-Ethnic Relations in Penang, Malaysia 2010-36 November: Kjeld Erik Brødsgaard – Chinese-Danish Relations: The Collapse of a special Relationship 2011: 2011-37 April: Masatoshi Fujiwara – Innovation by Defining Failures under Environmental and Competitive Pressures: A Case Study of the Laundry Detergent Market in Japan 2011-38 November: Kjeld Erik Brødsgaard - Western Transitology and Chinese Reality: Some Preliminary Thoughts 2012: 2012-39 December: Kjeld Erik Brødsgaard - Murder, Sex, Corruption: Will China Continue to Hold Together? 2013: 2013-40 January: Sudipta Bhattacharyya, Mathew Abraham and Anthony P. D’Costa - Political Economy of Agrarian Crisis and Slow Industrialization in India 2013-41 February: Yangfeng Cao, Kai Zhang and Wenhao Luo - What are the Sources of Leader Charisma? An Inductive Study from China 2013-42 April: Yangfeng Cao, Peter Ping Li, Peter Skat-Rørdam - Entrepreneurial Aspiration and Flexibility of Small and Medium-Sized Firms: How Headquarters Facilitate Business Model Innovation at the Subsidiary Level 2013-43 October: Zhiqian YU, Ning ZHU, Yuan ZHENG - Efficiency of Public Educational Expenditure in China 2013-44: November: Yangfeng Cao - Initiative-taking, Improvisational Capability, and Business Model Innovation in Emerging Markets 2014: 2014-45 January: Michael Jakobsen - International Business Studies and the Imperative of Context. Exploring the ‘Black Whole’ in Institutional Theory 2014-46 February: Xin Li - The hidden secrets of the Yin-Yang symbol 2015: 2015-47 March: Aradhna Aggarwal and Takahiro Sato – Identifying High Growth Firms in India: An Alternative Approach 2015-48 May: Michael Jakobsen - Exploring Key External and Internal Factors Affecting State Performance in Southeast Asia 2015-49 May: Xin Li, Peihong Xie and Verner Worm - Solutions to Organizational Paradox: A Philosophical Perspective 2015-50 June: Ari Kokko - Imbalances between the European Union and China 2015-51 August: Chin Yee Whah - Changes of Ownership and Identities of Malaysian Banks: Ethnicity, State and Globalization 2015-52 November: Abdul Rahman Embong - State, Development and Inequality in Selected ASEAN Countries: Internal and External Pressures and State Responses 2015-53 November: Verner Worm, Xin Li, Michael Jakobsen and Peihong Xie - Culture studies in the field of international business research: A tale of two paradigms