Examining the nonlinear impact of selected macroeconomic determinants on FDI inflows in India
| DOI | https://doi.org/10.1108/JABS-10-2019-0316 |
| Pages | 711-733 |
| Published date | 05 May 2020 |
| Date | 05 May 2020 |
| Author | Rajesh Sharma,Pradeep Kautish |
| Subject Matter | International business,Strategy |
Examining the nonlinear impact of
selected macroeconomic determinants on
FDI inflows in India
Rajesh Sharma and Pradeep Kautish
Abstract
Purpose –Over the years,India has witnessed irregular FDI inflows.Therefore, this study aims to explore
the asymmetric impact of per capita income, final consumption expenditure, globalization index and
exchangerate on FDI inflows in India.
Design/methodology/approach –Using the nonlinear autoregressive distributed lag bounds
frameworkand unknown structural break, the study investigates the impactsof selectedmacroeconomic
variablesin driving FDI inflows in India during the studyperiod (1979-2016).
Findings –The outcomes of the studyconfirm the asymmetric relationship betweenFDI inflows and its
determinants during the study period. The results have confirmed that the improvement in per capita
income, private consumption expenditure, globalization index and currency value appreciation play a
crucial role in increasing FDI inflows in India. In contrast, the downside movements in the volume of
consumption expenditure, globalization index and depreciation of the currency value in relation to the
trade partnersresult in reducing the volume of FDI inflows in the long run.
Originality/value –For determining FDI inflows, previous studies have considered the overall
impact of its potential determinants, which may provide partialinformation about the phenomenon.
The adopted nonlinear approach highlights that both the type s of fluctuations (i.e. upside and
downside) in the independent variables may affect FDI inflo ws differently and substantially. The
nonlinear association between FDI and selected determinants may be vital in formulating a long-
term policy.
Keywords India, FDI, Nonlinear auto regressive distributed lag (NARDL),Globalization index
Paper type Research paper
1. Introduction
Owing to the financial and technological dispossession, the developing countries have
perceived FDI to be an additional source for financing their growth programs (UNCTAD,
2013). Therefore, these countries have aligned their economic policies in favor of FDI
inflows (Asongu, 2014). In the early 1990s, the IndianGovernment opened the economy for
external investors and adopted a liberal trade policy to give an impetus to the economic
growth programs. Owing to these initiatives, India has experienced significant growth in the
economic front (Sharma et al., 2018).For example, in 2011, the service sector’s contribution
to the gross domestic product (GDP) increased to 56 per cent, which was merely 38 per
cent in the 1980s (Government of India, 2012). Theempirical studies have revealed that the
improvement of the service sector has immensely been influenced by FDI inflows in India
(UNCTAD, 2005;Dash and Parida, 2013). By considering the need for foreign investment,
the government has eased the process of FDI contracts(Bedi and Kharbanda, 2014), which
has turned India from sluggish to ready-to-invest destination for the potential investors
(Sharma et al., 2018).
Rajesh Sharma is based at
the Department of
Economics, School of
Business, Mody University
of Science and Technology,
Lakshmangarh, India.
Pradeep Kautish is based
at the Department of
Marketing, Institute of
Management, Nirma
University, Ahmedabad,
India.
Received 23 October 2019
Revised 28 January 2020
11 March 2020
Accepted 18 March 2020
DOI 10.1108/JABS-10-2019-0316 VOL. 14 NO. 5 2020, pp. 711-733, ©Emerald Publishing Limited, ISSN 1558-7894 jJOURNAL OF ASIA BUSINESS STUDIES jPAGE 711
However, maintaining the consistent FDI inflows has remained a matter of concern for the
governments, as its concentration and magnitude have significantly varied across regions
and times (OECD, 2002). With the help of FDI inflows, the host countries have tried to
pursue their economic and socio-political agendas (Dupasquier and Osakwe, 2006;
Asongu et al.,2018). Similarly, the investors have preferred comparatively more open,
politically stable, resources endowed and economically growing economies (Mottaleb,
2007;Phung, 2016). Corresponding to this argument, in terms of FDI confidence index,
India was spotted to be in the 5th place in 2013, whereas in 2018, India has slipped to the
11th place. According to the latest report of Kearney, the shift in India’s position is the
outcome of sluggish economic growth, cross-border disputes and exchange rate
fluctuations. Contrarily, in 2018, China has been able to secure 5th place because of its
consistent performance on the economic front and improving global presence in the
international market. Hence, FDI inflows to China have been significantly more than India
in the recent past (McCaffrey et al.,2018). However, the market-oriented economic policy of
the Indian Government may keep the country in the list of top 25 FDI attracting countries in
the coming years. Besides, the largepopulation base may continue to draw the attention of
foreign investors, which is a key factor behind attracting FDI inflows in the long run (Asongu
et al.,2018
). However, for ensuring the consistent FDI inflows, the government needs to
strengthen the overall economic environment, which can be ensuredby improving the trade
relationships, maintaining exchange rate stability and consistent performance in terms of
GDP growth (Blonigen and Piger, 2014;Delgado and McCloud, 2017). The country may
otherwise continue to struggle with the inconsistent FDI inflows, which is undesirable for a
developing country like India. Figure 1 highlights the magnitude of FDI in some countries in
Asia. Figure 1(a) reveals that in terms of FDI inflows, China significantly dominates over
India. However, in comparison to the other neighboring countries such as Pakistan,
Bangladesh and Sri Lanka, FDI inflows to India have remained substantially higher in the
preceding two decades.
Previous studies have reached the conclusion that economic factors such as GDP growth
rate, level of economic openness and global positioning, availability of the basic
infrastructure and market size in the host country have significantly shaped FDI inflows in
the long run (Alam and Zulfiqar, 2013;Bedi and Kharbanda, 2014;Kubo, 2015;Saini and
Singhania, 2018). However, the influence of socio-political factors on FDI is found to be
inconsistent because their impact may vary considerably across time and regions (Bevan
et al., 2004). Besides, the inter-country and intra-country convergences and fluctuations
may significantly change the direction and magnitude of FDI (UNCTAD, 2013). In favor of
Figure 1 Foreign direct investment(FDI) inflows in South Asian countries
0
1E+11
2E+11
3E+11
4E+11
India China
0
1E+10
2E+10
3E+10
4E+10
5E+10
20022004200620 08201020122014 2016
India Pakistan
Sri Lanka Bangladesh
(a) (b)
Notes: To show the recent trends in FDI inflows, the graphical
representation is made for the period of 2002-2016. However, the
NARDL results are computed for the period of 1979-2016
Source: World Bank (2019)
PAGE 712 jJOURNAL OF ASIA BUSINESS STUDIES jVOL. 14 NO. 5 2020
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