Person:

Subramanian, Arvind

India changed its data sources and methodology for estimating real gross domestic product (GDP) for the period since 2011-12. This paper shows that this change has led to a significant overestimation of growth. Official estimates place annual average GDP growth between 2011-12 and 2016-17 at about 7 percent. We estimate that actual growth may have been about 4.5 percent with a 95 percent confidence interval of 3.5 - 5.5 percent. The evidence, based on disaggregated data from India and cross-sectional/panel regressions, is robust. Lending further credence to the evidence, part of the overestimation can be related to a key methodological change, which affected the measurement of the formal manufacturing sector. These findings alter our understanding of India’s growth performance after the Global Financial Crisis, from spectacular to solid. Two important policy implications follow: the entire national income accounts estimation should be revisited, harnessing new opportunities created by the Goods and Services Tax to significantly improve it; and restoring growth should be the urgent priority for the new government.

We examine the pattern of growth in the 2010s. Standard explanations cannot account for the long slowdown, followed by a sharp collapse. Our explanation stresses both structural and cyclical factors, with finance as the distinctive, common element. In the immediate aftermath of the Global Financial Crisis (GFC), two key drivers of growth decelerated. Export growth slowed sharply as world trade stagnated, while investment fell victim to a homegrown Balance Sheet crisis, which came in two waves. The first wave—the Twin Balance Sheet crisis, encompassing banks and infrastructure companies—arrived when the infrastructure projects started during India’s investment boom of the mid-2000s began to go sour. The economy nonetheless continued to grow, despite temporary, adverse demonetization and GST shocks, propelled first by income gains from the large fall in international oil prices, then by government spending and a non-bank financial company (NBFC)-led credit boom. This credit boom financed unsustainable real estate inventory accumulation, inflating a bubble that finally burst in 2019. Consequently, consumption too has now sputtered, causing growth to collapse. As a result, India is now facing a Four Balance Sheet challenge—the original two sectors, plus NBFCs and real estate companies—and is trapped in an adverse interest-growth dynamic, in which risk aversion is leading to high interest rates, depressing growth, and generating more risk aversion. Standard remedies are unavailable: monetary policy is stymied by a broken transmission mechanism; large fiscal stimulus will only push up already-high interest rates, worsening the growth dynamic. The traditional structural reform agenda—land and labour market measures—are important for the medium run but will not address the current problems. Addressing the Four Balance Sheet problem decisively will be critical to durably reviving growth. Raising agricultural productivity is also high priority. And even before that, a Data Big Bang is needed to restore trust and enable better policy design.

My recent research paper “India's GDP Mis-estimation: Likelihood, Magnitudes, Mechanisms, and Implications,” (hereafter “GDP paper”) and the associated op-ed in the Indian Express on June 11, 2019 have generated considerable debate. This is encouraging because serious argument and counter-argument are the basis for good policy-making. Since the issue itself is of great importance, the counter-arguments to my analysis warrant a considered response. That is the aim of this note, which is a complement to the original paper, addressing both the larger issues and some of the specific points that have been raised.

The note is structured as follows. Section II describes my engagement with India’s GDP estimation when I was Chief Economic Adviser. Section III elaborates on the framework/approach underlying the GDP paper. Section IV makes explicit the key puzzle surrounding India’s growth estimates, and addresses the possible explanations for it. Section V explores the puzzle in greater detail. Section VI provides additional cross-country evidence on growth and price deflators, which support the findings of the original paper, namely that growth during 2011-16 was likely overestimated by a significant margin. Section VII addresses two broad objections to the main findings. Section VIII discusses some of the methodological critiques of the paper. Section IX offers some thoughts on the way forward.

We estimate the respective contributions of institutions, geography, and trade in determining income levels around the world, using recently developed instruments for institutions and trade. Our results indicate that the quality of institutions "trumps" everything else. Once institutions are controlled for, measures of geography have at best weak direct effects on incomes, although they have a strong indirect effect by influencing the quality of institutions. Similarly, once institutions are controlled for, trade is almost always insignificant, and often enters the income equation with the "wrong" (i.e., negative) sign, although trade too has a positive effect on institutional quality. We relate our results to recent literature, and where differences exist, trace their origins to choices on samples, specification, and instrumentation.