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India in the globalized economy : Growth spillovers & business cycle synchronization

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Abstract

In recent decades, in the wake of accelerated globalization, the issue of output coupling/decoupling has assumed considerable importance in academic as well as in policy debates. Special attention has been focussed on the following four issues (i) whether economies are getting increasingly synchronized in their cyclical behaviour and in particular whether EMEs are getting synchronized with the advanced group of countries (or otherwise) and/or among themselves ? (ii) whether similar synchronization is also evident in the growth profiles of EMEs and advanced economies ? (iii) what are the main factors driving this two types of synchronization ? and (iv) are the factors driving growth synchronization different from those driving business cycle co-movements? This is a single-country study which examines the decoupling issue from the perspective of the Indian economy over a fairly long time span viz. 1961–2008, dividing the same into three sub-periods characterized by relative insularity (1961–1978), restricted globalization (1979–1993) and full-scale globalization (1994–2008). Among the important potential determinants of co-movements suggested by the available literature are inter-industry and intra-industry trade intensities, co-ordination of fiscal and monetary policy, financial integration etc. Our key finding is that the economic determinants for India’s cyclical synchronization differ across short (16–32 months) and medium cycles (32–64 months) and vis-a-vis growth spillovers.

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Notes

  1. The term BRICS is now a common acronym for the following group of countries—Brazil, Russia, India, China and S. Africa

  2. See Willett et al. (2011) for a discussion on different ways the term decoupling has been used in the literature.

  3. “Growth spillovers” are likely to be explained by trade intensity and specialization, FDI (foreign direct investment) inflows, technology transfer etc. whereas “business cycle synchronization” is influenced by factors such as financial contagion, portfolio capital inflows, fiscal and monetary policy coordination etc.

  4. See e.g. Kalemli-Ozcan et al (2009), Mendoza and Quadrini (2010) etc. Morgan et al. (2004) indicate a similar ambiguity about the impact of banking integration on output co-movement, depending on whether financial shocks or total factor productivity shocks predominate.

  5. See Fidrmuc et al. (2008) on China and Jayaram et al. (2009) on India. Hsiao et al. (2003) study the impact of the U.S. economy on the Asia-Pacific Rim.

  6. Korea became a full member of the OECD group in December 1996. Its classification as an EME is somewhat contentious, as its current per capita gross national income is about two and a half times the norm of $ 11, 500 (US PPP) conventionally used in classifying EMEs. However, several features of the Korean economy still keep it akin to an EME (see e.g. the reasons cited by the MSCI (Morgan Stanley Capital International) in its decision to retain the emerging market status for Korea in http://news.xinhuanet.com/english2010/business/2011-06/22/c_13943427.htm) . Further much of the current comparative development literature still persists with this classification mainly with a view to maintaining historical continuity (see e.g. . Chui et al. (2002), He et al. (2007) etc.).

  7. It may appear that the shares of some countries like the Netherlands, Swedn or Spain may be insignificant, but taken as a group these countries’ share exceeded that of Japan, Korea and several other Asian EMEs (taken individually)

  8. An excellent advanced text on wavelets is Percival and Walden (2000). Easily readable accounts are available in Gencay et al. (2002), Crowley (2007), Nachane and Dubey (2013) etc.

  9. The actual derivation of the wavelet details and smooths may be done via the so-called discrete wavelet transform (DWT), which can be computed in several alternative ways. The intuitively most appealing procedure is the pyramid algorithm, suggested in Mallat (1989) (and fully explained in Percival and Walden (2000)).

  10. Wavelet coefficients are obtained by a projection of the wavelet filter onto the vector of observations (see Gencay et al. (2002), p. 120 fn. 12.

  11. We are grateful to an anonymous referee for this suggestion.

  12. Using this confidential data set the authors find that (for a group of 20 developed economies) increased financial integration seems to get reflected in less synchronized output movements.

  13. Our sample size is 216 for Period I, 180 for Periods II and III, and hence the maximum number of scales that we choose is five (see e.g. Crowley (2007)).

  14. Of course it need hardly be stressed that that the choice of the wavelet is guided by the characteristics of the signal one is analyzing. Given that our series of interest are relatively smooth over the period of analysis, a Symmlet was thought appropriate. For a discontinuous signal, the Haar wavelet, for example, could be a better choice.

  15. An adjustment has however to be done for the standard errors of the POLS estimator.

  16. Pre-determinedness requires that E(x j,τ u j, τ ) = 0, where j is the country index, τ is the time index and x j,τ is the vector of regressors.

  17. An additional consideration in our decision, being that the monetary policy measures across countries are defined differently. Besides, the targets of monetary policy for any given country have often shifted over the three periods of our analysis (e.g. India shifted from money supply (M3) targeting to repo rate targeting in the middle of Period III).

  18. Note that in computing the weight we use the aggregate GDP, data on which is obtained from the Penn World Tables (version 7.0).

  19. Considering ρ j,τ (k = s4) (which accounts for long-tem effects in conjunction with medium term cyclical effects (i.e. those with cycles between 32 to 64 months) produced results not materially different from those with ρ j,τ (k = s5), thus leading us to suppose that even shorter cycles (of less than 32 months) can affect long-term growth.

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Acknowledgments

We are very grateful to an anonymous referee for his valuable suggestions. Errors and shortcomings are the authors’ sole responsibility. Amlendu Dubey acknowledges the financial support he received from IIT Delhi for the work on this paper.

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  1. Indira Gandhi Institute of Development Research, Gen. A. K. Vaidya Marg, Goregaon (E), Mumbai, 400 065, India

    Dilip Nachane

  2. Department of Management Studies, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India

    Amlendu Dubey

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  1. Dilip Nachane
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Nachane, D., Dubey, A. India in the globalized economy : Growth spillovers & business cycle synchronization. Int Econ Econ Policy 15, 89–115 (2018). https://doi.org/10.1007/s10368-016-0367-x

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