Skip to main content

Advertisement

SpringerLink
Log in

New perspectives on the rise and fall of global imbalances: evidence from large emerging market economies

  • Original Paper
  • Published:
Review of World Economics Aims and scope Submit manuscript

Abstract

This paper estimates the impact of internal factors, such as governance institutions and financial development, versus external, such as capital flows uncertainty, on the excess savings of large emerging market economies (EMEs), identified as a major factor behind their trade surpluses. Using instrumental variables regression to control for endogeneity from institutions, we study eight major EMEs over 1995–2018 as well as a larger panel including both AEs and EMEs over 2001–2018 for robustness. Baseline estimates show that, along with financial development, democratic accountability and judiciary influence CA surpluses in both EMEs and AEs. Anti-corruption measures and government stability are influential specifically in AEs and EMEs respectively. For both EMEs and AEs, surpluses decrease with greater dependence on primary commodity exports supporting the “resource curse” thesis. That EME surpluses move negatively with better institutions and positively with capital flows uncertainty supports the precautionary motive. Sources of EME surpluses changed substantially from the pre- to the post-GFC years. During 2001–2008, higher growth, initial wealth, uncertainty in net capital flows increased surpluses. After 2008, reduced growth, lower CB intervention and better institutions rebalanced surpluses, particularly for Asia–Pacific nations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Source: World Bank

Fig. 2

Source: World Bank and IMF

Fig. 3

Source: IMF Coordinated Portfolio Investment Survey

Fig. 4

Source: World Bank

Fig. 5

Source: Authors’ estimates and World Bank

Similar content being viewed by others

Notes

  1. AEs have some exceptions. For example, Germany has persistently incurred surpluses on its current account. Such imbalances are more linked to AE country-specific factors like low investment (Cheung et al., 2020).

  2. Basic national income accounting shows that the net savings of a nation determines its CAB e.g. Spvt + Spub − I = X − M.

  3. National Savings = Spermanent + Suncertain.

  4. The role of foreign spillovers in EME imbalances has been already studied, for example, Djigbenou-Kre and Hail (2015) showed a significant linkage between AE monetary aggregates and imbalances in EMEs through global liquidity channel.

  5. Cooper (2007), however, argues that although the US savings rate was low compared to developing economies, it is understated. Allowance should be made for educational expenditure, expenditure on research and development or training and product branding that would create future returns.

  6. Existing papers like Chinn et al. (2014), Wang (2020) do not go into the micro-assessment of institutions, but include governance as a control. We believe greater insight is possible through a detailed study of governance. Our study also addresses a longer time span, including the post-GFC years.

  7. This sample is a follow-up of earlier papers e.g., Banerjee and Goyal (2021, 2022) where considerable presence of mercantilist efforts as well as monetary spillovers is found in the same sample of emerging markets. Recently, Aizenman et al. (2021) also study a similar sample of eight major emerging markets (EMs)—Brazil, China, India, Indonesia, Mexico, Russia, South Africa and Turkey because of their significant participation in global finance. These eight EMEs are the largest in terms of both absolute and per capita GDPs and account for a major share of inflows to developing economies. As per World Bank data, the total net portfolio inflows to these nations stood at $52 billion in 2020 and exceeded that of the entire “low and middle income” group ($34 billion) by a factor of 1.5.

  8. The start year is restricted to 1995 due to non-availability of several variables for China and Russia.

  9. We effectively use 19 AEs and EMEs since data on Canada was not completely available.

  10. Capital flows data which is origin-destination based, is collected taking US as origin. So the analysis is only for EMEs.

  11. Rey (2013) shows that the famous impossible trinity or trilemma boils down to a choice between independent monetary policy and capital controls in most of the developing economies when they face a tsunami of liquidity. However, measures like capital controls are limited, especially when the domestic need for capital is high. Again, capital controls to a great extent deflect capital from one EME to another (Forbes et al., 2016). In the absence of sufficient scope to impose direct controls, EMEs mop up reserves to ensure a competitive exchange rate as well as to defend against any future depreciation.

  12. Resource-rich economies have been observed to fall back in terms of growth and institutions (Papyrakis and Gerlagh, 2004). Development of a primary sector comes at a cost of losing out on manufacturing growth.

  13. An endogenous test of structural breaks supports significant breaks around 2000 and 2008.

  14. Current account balance is composed of net exports as well as remittances and other transfers. Data shows that the remittances, although a non-negligible component, is substantially stable over time for the current panel, and for developing economies at large. This finding is supported by existing studies (Ratha, 2005). Also, remittances inherently depend on external output, nominal exchange rate and other external factors which include global migration policies. Its inclusion would further complicate the analysis. For the above reasons, we choose not to include remittances.

  15. Defined as exports minus imports in goods and services.

  16. Unless mentioned otherwise, each variable is in terms of percentage.

  17. We take the lagged NFA ratio following Wang (2020).

  18. Dependency ratio is aimed to capture the impact of non-working dependent population, as per the Life Cycle Hypothesis. It is defined as number of dependents (old and young combined, e.g., < 15 or > 64 years age) per 100 working-age (15–64) population.

  19. Such normalization is similar to Fogli and Perri (2015).

  20. Significant persistence has been found in Saadaoui (2015) as well.

  21. We exclude fuels because crude oil introduces the role of oil production and cartels which is not the focus here. Crude oil exporting nations have a different dimension. The same argument of excess precautionary savings does not apply there. They have retained surpluses through crude oil exports.

  22. Life cycle hypothesis suggests consumption smoothing over the entire life span while earnings are limited only to working years. If an individual, with an average life-span T years from now, plans to work for another L years (earns Yt in current period, expects to earn Yet in (L-1) future periods), and if her initial endowment is W, she shall consume her lifetime earnings (LE) in T equal instalments.

    Her savings (St) in tth period is then given by:

    \(S_{t} = Y_{t} - LE/T = (1 - T^{ - 1} ) Y_{t} - (L - 1) T^{ - 1} Y_{et} - T^{ - 1} W(A)\)

    Differentiating equation (A), ΔSt/ΔYt > 0, ΔSt/ΔYet and ΔSt/ΔW < 0.

  23. More weight is given to the results of the latter which has better small sample properties.

  24. Divergent opinion exists on the choice of instrumental variables since it can be difficult to find such variables. Anderson and Hsiao (1984)proposed that in a N*T panel, the first differenced endogenous regressors can be instrumented through past values.

  25. Acemoglu (2008), Choi and Lee (2010) use the AH technique to address endogeneity in their estimations.

  26. Here it must be noted that GMM or the Generalized Method of Moments is commonly used for panel studies addressing endogeneity. However, for the dataset we study, we find AH method is most suitable and practical. GMM method is generally applicable for wide panels “short time series T, large cross sections N” since as a rule of thumb the number of instruments should not exceed the number of cross-sections. Since the panel we study is a “long” panel where T >  > N and N is small relative to the number of instruments, it does not satisfy the pre-conditions for GMM. In the context of both difference and system GMM, Roodman (2009) notes that with larger T, the number of instruments in a GMM estimation can be very large relative to observations leading to over-identification and increases the possibility for type I errors—false positives. Hence, given the constraints in data, we use AH instrumentation and the estimates are found to be robust.

  27. This involves regressing the test variable under consideration on exogenous variables in the system and using the residuals from these auxiliary regressions in place of the tested variable in the original regression. If the residuals are found to be significant, then this shows the null of exogeneity is rejected and points to endogeneity in the regressor.

  28. Since we are dealing with a panel that has historical commonalities as well as strong geo-political connections, Pesaran test for cross-dependence is used.

  29. They find − 0.11% change in CAB/GDP ratio for EMEs from increasing FD proxied through private sector credit. Their estimates, however, are based on the pre-GFC period, while ours include post-GFC years.

  30. DUM_CRS = 1 for 1997–1998 and 2007–2008, 0 otherwise.

  31. Similar to Arize et al. (2020).

  32. Absolute value of net capital flows is taken in the denominator as this ensures proper change of sign for years with negative figures in the data.

  33. This tests whether the residuals capture any additional ARCH effects. There should be no ARCH left in them if the variance equation is correctly specified.

  34. We use a GAUSS code replicating HR test by Ranjbar et al. (2014).

  35. D_01 = 1 for years 2001-2008.

     = 0 otherwise.

    D_09 = 1 for years 2009-2018.

     = 0 otherwise.

  36. The ratio was non-stationary in level, and hence its growth rate was taken.

References

  • Acemoglu, D., & Johnson, S. (2005). Unbundling institutions. Journal of Political Economy, 113(5), 949–995. https://doi.org/10.1086/432166

    Article  Google Scholar 

  • Acemoglu, D., Johnson, S., Robinson, J. A., & Yared, P. (2008). Income and democracy. American Economic Review, 98(3), 808–842. https://doi.org/10.1257/aer.98.3.808

    Article  Google Scholar 

  • Aisen, A., & Veiga, F. J. (2013). How does political instability affect economic growth? European Journal of Political Economy, 29, 151–167. https://doi.org/10.1016/j.ejpoleco.2012.11.001

    Article  Google Scholar 

  • Akkoyunlu, S., & Ramella, D. (2020). Corruption and economic development. Journal of Economic Development, 45, 63–94.

    Google Scholar 

  • Alesina, A., Cohen, G. D., & Roubini, N. (1992). Macroeconomic policy and elections in OECD democracies. Economics and Politics, 4(1), 1–30. https://doi.org/10.1111/j.1468-0343.1992.tb00052.x

    Article  Google Scholar 

  • Anderson, T. W., & Hsiao, C. (1984). Formulation and estimation of dynamic models using panel data. Journal of Econometrics, 18(1), 47–84.

    Article  Google Scholar 

  • Arize, A. C., Ogunc, A., Kalu, E. U., & Malindretos, J. (2020). New evidence on exchange-rate volatility and export flows in thailand: nonlinearity and asymmetric ARDL investigation. The International Trade Journal. https://doi.org/10.1080/08853908.2020.1799886

    Article  Google Scholar 

  • Athukorala, P., & Sen, K. (2004). The determinants of private saving in India. World Development, 32(3), 491–503. https://doi.org/10.1016/j.worlddev.2003.07.008

    Article  Google Scholar 

  • Bai, J., & Perron, P. (2003). Critical values for multiple structural change tests. Econometrics Journal, 18, 1–22.

    Google Scholar 

  • Banerjee, K., & Goyal, A. (2021). Behavioural equilibrium real exchange rates and misalignments: Evidence from large emerging markets. Economic Analysis and Policy, Elsevier, 70, 414–436. https://doi.org/10.1016/j.eap.2021.03.004

    Article  Google Scholar 

  • Banerjee, K., & Goyal, A. (2022). Monetary spillovers and real exchange rate misalignments in emerging markets. International Journal of Emerging Markets. Emerald, 17(2), 452–484. https://doi.org/10.1108/IJOEM-02-2020-0192

    Article  Google Scholar 

  • Bayraktar-Saglam, B., & Yalta, A. Y. (2015). Current account imbalances and capital flows: Further evidence from emerging markets. Global Journal of Emerging Market Economies, 7(2), 201–213.

    Article  Google Scholar 

  • Bergsten, C. F. (2013). Currency wars, the economy of the United States and reform of the international monetary system. Stavros Niarchos Foundation Lecture, Peterson Institute for International Economics.

  • Bernanke, B. (2005). The global saving glut and the U.S. current account deficit. Homer Jones Lecture, St. Louis, Missouri. http://www.federalreserve.gov/boarddocs/speeches/2005/20050414/default.htm.

  • Blanchard, O., & Milesi-Ferretti, G. M. (2011). (Why) Should current account balances be reduced? IMF Staff Discussion Note, SDN/11/03.

  • Caballero, R. (1991). Earnings uncertainty and aggregate wealth accumulation. American Economic Review, 81(4), 859–871.

    Google Scholar 

  • Caballero, R. J., Farhi, E., & Gourinchas, P.-O. (2008). An equilibrium model of “global imbalances” and low interest rates. American Economic Review, 98(1), 358–393. https://doi.org/10.1257/aer.98.1.358

    Article  Google Scholar 

  • Chen, J., Mancini-Griffoli, T., & Sahay, R. (2014). Spillovers from US monetary policy on emerging markets: different this time? IMF Working Papers, 14(240), p. 1, DOI: https://doi.org/10.5089/9781498380423.001.

  • Cheung, Y. W., Steinkamp, S., & Westermann, F. (2020). A tale of two surplus countries: China and Germany. Open Economies Review, 31, 131–158. https://doi.org/10.1007/s11079-019-09537-7

    Article  Google Scholar 

  • Chinn, M. D., Eichengreen, B., & Hiro, I. (2014). A forensic analysis of global imbalances. Oxford Economic Papers, 66(2), 465–490.

    Article  Google Scholar 

  • Chinn, M. D., & Ito, H. (2007). Current account balances, financial development and institutions: Assaying the world ‘‘saving glut.’ Journal of International Money and Finance, 26, 546–569.

    Article  Google Scholar 

  • Chinn, M. D., & Prasad, E. S. (2003). Medium-term determinants of current accounts in industrial and developing countries: An empirical exploration. Journal of International Economics, 59(1), 47–76. https://doi.org/10.1016/s0022-1996(02)00089-2

    Article  Google Scholar 

  • Choi, W. G., & Lee, I. H. (2010). Monetary transmission of global imbalances in Asian Countries. IMF Working Paper, WP/10/214, 1.

  • Cline, W. R. (2005). The United States as a Debtor Nation. Policy Note, Peterson Institute for International Economics. ISBN 0-88132-399-3

  • Cooper, R.N. (2007). Living with Global Imbalances. Brookings Papers on Economic Activity.

  • Davidson, R., & MacKinnon, J. G. (1993). Estimation and Inference in econometrics. Oxford University Press.

    Google Scholar 

  • Dhar, A. (2021). Identification of extreme capital flows in emerging markets. International Review of Economics & Finance, 71, 359–384.

    Article  Google Scholar 

  • Djigbenou-Kre, M.-L., & Hail, P. (2015). The Effects of global liquidity on global imbalances, Working Papers, No 2015–23, Economic Research Institute, Bank of Korea

  • Dooley, M. P., Folkerts-Landau D., & Garber, P. M. (2005). Savings gluts and interest rates: The missing link to Europe. NBER Working Paper 11520, 1. http://www.nber.org/papers/w11520

  • ECB, (2011). Is the narrowing of global imbalances since the financial crisis cyclical or permanent? Financial stability review, June issue

  • Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of united kingdom inflation. Econometrica, Econometric Society, 50(4), 987–1007.

    Article  Google Scholar 

  • Fogli, A., & Perri, F. (2015). Macroeconomic volatility and external imbalances. Journal of Monetary Economics, 69, 1–15. https://doi.org/10.1016/j.jmoneco.2014.12.003

    Article  Google Scholar 

  • Forbes, K., Fratzscher, M., Kostka, T., & Straub, R. (2016). Bubble thy neighbour: Portfolio effects and externalities from capital controls. Journal of International Economics, 99, 85–104. https://doi.org/10.1016/j.jinteco.2015.12.010

    Article  Google Scholar 

  • Gruber, J. W., & Kamin, S. B. (2007). Explaining the global pattern of current account imbalances. Journal of International Money and Finance, 26(4), 500–522. https://doi.org/10.1016/j.jimonfin.2007.03.003

    Article  Google Scholar 

  • Gruber, J., & Kamin, S. (2009). Do differences in financial development explain the global pattern of current account imbalances? Review of International Economics, 17(4), 667–688. https://doi.org/10.1111/j.1467-9396.2009.00842.x

    Article  Google Scholar 

  • Hadri, K., & Rao, Y. (2008). Panel stationarity test with structural breaks. Oxford Bulletin of Economics and Statistics, 70(2), 245–269.

    Article  Google Scholar 

  • Hansen, L. (1982). Large sample properties of generalized method of moments estimators. Econometrica, 50(3), 1029–1054.

    Article  Google Scholar 

  • Kim, N. –S., & Heshmati, A. (2017). The relationship between economic growth and democracy: Alternative representations of technological change. GLO Discussion Paper, 85, Global Labor Organization (GLO)

  • Kim, A. (2009). An empirical analysis of Korea’s trade imbalances with the US and Japan. Journal of the Asia Pacific Economy, 14(3), 211–226. https://doi.org/10.1080/13547860902974971

    Article  Google Scholar 

  • Kolstad, I., & Wiig, A. (2013). Digging in the dirt? Extractive industry FDI and corruption. Economics of Governance, 14(4), 369–383.

    Article  Google Scholar 

  • Mauro, P. (1995). Corruption and growth. The Quarterly Journal of Economics, 110(3), 681–712. https://doi.org/10.2307/2946696

    Article  Google Scholar 

  • Mendoza, E. G., Quadrini, V., & Rios-Rull, J.-V. (2007). Financial integration, financial deepness and global imbalances. NBER Working Paper, 12909, p. 1. https://doi.org/10.3386/w12909

  • Modigliani, F. (1966). The life cycle hypothesis of saving, the demand for wealth and the supply of capital. Social Research, 33(2), 160–217.

    Google Scholar 

  • Nayak, S., & Baig, M. A. (2019). International reserves and domestic money market disequilibrium: Empirics for India and China. International Journal of Emerging Markets, 14(5), 1081–1101. https://doi.org/10.1108/IJOEM-10-2018-0536

    Article  Google Scholar 

  • Obstfeld, M., & Rogoff, K. (2009). Global Imbalances and the Financial Crisis: Products of Common Causes. In Asia and the global financial crisis. Asia economic policy conference, Federal Reserve Bank of San Francisco

  • Papyrakis, E., & Gerlagh, R. (2004). The resource curse hypothesis and its transmission channels. Journal of Comparative Economics, 32(1), 181–193. https://doi.org/10.1016/j.jce.2003.11.002

    Article  Google Scholar 

  • Pellegrini, L., & Gerlagh, R. (2004). Corruption’s effect on growth and its transmission channels. Kyklos, 57(3), 429–456.

    Article  Google Scholar 

  • Rajan, R. G. (2019). The third pillar. HarperCollins Publishers.

    Google Scholar 

  • Ranjbar, O., Li, X.-L., Chang, T., & Lee, C.-C. (2014). Stability of long-run growth in East Asian countries: New evidence from panel stationarity test with structural breaks. The Journal of International Trade & Economic Development: An International and Comparative Review. https://doi.org/10.1080/09638199.2014.937352

    Article  Google Scholar 

  • Ratha, D. (2005). Workers’ remittances: An important and stable source of external development finance. Economics Seminar Series, p. 9. https://repository.stcloudstate.edu/econ_seminars/9

  • Roodman, D. (2009). Practitioners’ corner: A note on the theme of too many instruments. Oxford Bulletin of Economics and Statistics, 71(1), 0305–9049. https://doi.org/10.1111/j.1468-0084.2008.00542.x

    Article  Google Scholar 

  • Saadaoui, J. (2015). Does financial openness explain the increase of global imbalances before the crisis of 2008? International Economics, 143, 23–35.

    Article  Google Scholar 

  • Sarisoy-Guerin, S. (2012). The relationship between capital flows and current account: Volatility and causality. LUISS, Working Paper No. 36

  • Stasavage, D. (2002). Private investment and political institutions. Economics and Politics, 14(1), 41–63. https://doi.org/10.1111/1468-0343.00099

    Article  Google Scholar 

  • Svirydzenka, K. (2016). Introducing a New broad-based index of financial development. IMF Working Papers, 16, no. 5, 1

  • Tan, Z., Wei, S., Yao, Y., & Zhao, Y. (2015). Financial structure, corporate savings and current account imbalances. Journal of International Money and Finance, 54, 142–167.

    Article  Google Scholar 

  • Wang, P., Wen, Y., & Xu, Z. (2017). Two-way capital flows and global imbalances. The Economic Journal, 127(599), 229–269. https://doi.org/10.1111/ecoj.12290

    Article  Google Scholar 

  • Wang, X. (2020). Financial sector policies and current account imbalances: Cross country evidence. Journal of the Asia Pacific Economy. https://doi.org/10.1080/13547860.2019.1710426

    Article  Google Scholar 

  • Wang, Y. (2012). Seeking a balanced approach on the global economic rebalancing: China’s answers to international policy cooperation. Oxford Review of Economic Policy, 28(3), 569–586. https://doi.org/10.1093/oxrep/grs032

    Article  Google Scholar 

  • Yang, S. (2016). Capital flows, sterilization, and macro-prudential policy in China. Emerging Markets Finance and Trade, 52(8), 1797–1812. https://doi.org/10.1080/1540496X.2016.1148026

    Article  Google Scholar 

Download references

Acknowledgements

Valuable inputs from the Editor-in-Chief and anonymous referees of the journal are gratefully acknowledged. The authors are also grateful to Prof. Saibal Kar and Prof. Subrata Sarkar for useful comments on a preliminary version of the paper.

Author information

Authors and Affiliations

  1. Department of Management Studies and Industrial Engineering, Indian Institute of Technology (ISM), Dhanbad, Jharkhand, India

    Krittika Banerjee

  2. Indira Gandhi Institute of Development Research, Mumbai, India

    Ashima Goyal

Authors
  1. Krittika Banerjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ashima Goyal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Krittika Banerjee.

Ethics declarations

Conflict of interest

We have no conflicts of interest to disclose. This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Fig. 6
figure 6

Source: International Country Risk Guide (ICRG), 2017 and World Bank

Institutions and dependence on primary exports – ‘core’ EMEs.

Full size image

6,

Tables

Table 4 Descriptive statistics and data sources
Full size table

4,

Table 5 Panel unit root tests
Full size table

5,

Table 6 ARCH-LM test for conditional variance
Full size table

6,

Table 7 Baseline estimates including uncertainty—‘core’
Full size table

7,

Table 8 Test for structural breaks
Full size table

8,

Table 9 Estimates with Asia–Pacific dummy
Full size table

9 and

Table 10 Reserves: a potential channel
Full size table

10.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Banerjee, K., Goyal, A. New perspectives on the rise and fall of global imbalances: evidence from large emerging market economies. Rev World Econ (2023). https://doi.org/10.1007/s10290-023-00508-2

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10290-023-00508-2

Keywords

JEL Classification

Search

Navigation