adjusting local government debt swap, staff estimate that TSF stood at 203 percent of GDP in 2015.
cAverage selling prices estimated by IMF staff based on housing price data (Commodity Building Residential Price) of 70 large and mid-sized cities published by National Bureau of Statistics (NBS).
dAdjustments are made to the authorities’ fiscal budgetary balances to reflect consolidated general government balance, including government-managed funds, state-administered SOE funds, adjustment to the stabilization fund, and social security fund.
eEstimates of debt levels before 2015 include central government debt and explicit local government debt (identified by MoF and NPC in Sep 2015). The large increase in general government debt in 2014 reflects the authorities’ recognition of the off-budget local government debt borrowed previously. The estimation of debt levels after 2015 assumes zero off-budget borrowing from 2015 to 2021.
fExpenditure side nominal GDP.
gAugmented fiscal data expand the perimeter of government to include local government financing vehicles and other off-budget activity.
h“Augmented fiscal balance” = “augmented net lending/borrowing” — “net land sales proceeds” (in percent of GDP) as we treat net land sales proceeds as financing.
Appendix 2: India’s Economic Indicators
Sources: IMF Country Report, 2016, based on data provided by the Indian authorities; CBC Data Company Ltd; Bloomberg LP.; World Bank, World Development Indicators; and IMF staff estimates and projections.
aData are for April–March fiscal years.
bDiffers from official data, calculated with gross investment and current account. Gross investment includes errors and omissions.
cDivestment and license auction proceeds treated as below-the-line financing.
dIncludes combined domestic liabilities of the center and the states, and external debt at year-end exchange rates.
eFor 2015/16, as of 6 January 2016.
fFor 2015/16 year-to-date as of 6 January 2016.
gOn balance of payments basis.
hImports of goods and services projected over the following 12 months.
iShort-term debt on residual maturity basis, including estimated short-term NRI deposits on residual maturity basis.
jIn percent of current account receipts, excluding grants.
kFor 2015/16, year-to-date as of November 2015.
References
Burkitt, L. (2012). “Report: China’s Health Care System: Deeply Sick”, The Wall Street Journal, August 29.
Haung, Y. and T. Khanna (2003). “Can India Overtake China?”, Foreign Policy, July/August.
Maliszewski, W., S. Arslanalp, J. Caparusso, J. Garrido, S. Guo, J. S. Kang, W. R. Lam, T. D. Law, W. Liao, N. Rendak, P. Wingender, J. Yu and L. Zhang (2016). “Resolving China’s Corporate Debt Problem”, IMF Working Paper No. 16/203.
Nagaraj, R. (2013). “The dream run: 2003–08: Understanding the recent boom and its aftermath”, Economic and Political Weekly, 48.
Nagaraj, R. (2014). “Economic challenges to the new government: A policy proposal”, Economic and Political Weekly, 49(21).
Nagaraj, R. (2015). “Seeds of doubts on new GDP numbers: Private corporate sector over-estimated?”, Economic and Political Weekly, 50(13).
Shin, H. S. and L. Y. Zhao (2013). Firms as Surrogate intermediaries: Evidence from Emerging Economies, Asian Development Bank. Available at: http://www.princeton.edu/~hsshin/www/Firms_as_surrogate_intermediaries.pdf.
The Economist (2016). “Chinese property: When a bubble is not a bubble”, The Economist, October 13.
Wu, H. (2002). “How fast has Chinese industry grown? — Measuring the real output of Chinese industry”, The Review of Income and Wealth, 48(2): 179–204.
1Harry Wu of the Conference Board has been a long-time critic of the official statistics. More recently, Christopher Balding of HSBC Business School in Shenzhen has written extensively on the issue.
2More recently, officials at one of the provinces, Potemkin, admitted to falsifying output data “A big Chinese province admits faking its economic data” (The Economist, January 28, 2017).
3For a synoptic view of the debate between the official position and the critics’ viewpoints, see http://www.ideasforindia.in/article.aspx?article_id=1728; or, refer to the symposium. For details refer to Nagaraj (2015).
4Uprooting rural settlements to house them in multi-storied apartments seems to have caused considerable dislocation in rural economic activity and rural way of life.
5This is a gist of the India’s story of “Dream Run” of 9% growth rate. For a detailed account of the boom and bust, and policy options to revive growth, refer to (Nagaraj, 2013, 2014).
6Disconcertingly, much of the so-called FDI into India lately represents import-led growth financed by private equity funding of e-commerce companies.
7Before the 2008 financial crisis, very few really believed that there was a bubble in the sub-prime market in the US. There was an oblique hint of it in Raghuram Rajan’s paper in the 2006 Jackson Hole conference, a suggestion that Lawrence Summers rejected outright.
CHAPTER 4
Inter-Group Disparities in Growing Economies: India Among the BRICS
Achin Chakraborty and Simantini Mukhopadhyay
Institute of Development Studies Kolkata, India
Introduction
Discussions on economic inequality by scholars, policymakers, and others had never attained such visibility as they have in the recent years. “It’s a golden age for studying inequality”, commented The Economist (2016). Publication of a series of important, well-researched books by reputed economists in the recent years has triggered further interest in the issue of inequality and its different aspects.1 In spite of the renewed interest in the problem of inequality across the world, discussions on inequalities based on ethnic, racial, or caste groups have been less visible than general or interpersonal inequality. However, in contrast to this general neglect of inter-group inequality by economists in the context of the rest of the world, there has been a growing scholarly interest in assessing inequalities between the social groups (Scheduled Castes, Scheduled Tribes, and others) in India in the past two decades or so.
Even though a common characteristic of all the BRICS countries now is that the degree of inequality in interpersonal income distribution is rather high, Brazil stands out as it has experienced a decline in inequality in the past two decades unlike others. In this chapter, our focus is on inequality between groups, rather than interpersonal inequality as the former is less discussed in the context of BRICS.
The complex social stratification along