Spillover Analysis: India1
This chapter analyzes inward spillovers to India from: (i) macroeconomic shocks in systemic economies (China, the Euro Area, and the United States), (ii) oil price disturbances, and (iii) QE tapering in the United States. Furthermore, it studies outward spillovers from India to other South Asian countries and globally. A Global Vector Autoregression (GVAR) model is used to evaluate the nature and strength of economic linkages between globally-systemic countries and India, and to study the effects of different shocks. Spillovers are transmitted across economies via trade, financial, and commodity price channels. The results show that India is more sensitive to developments in the United States compared to those in the Euro Area and China. Shocks originating in India have smaller global implications (compared to systemic countries), but they are very important for several South Asian economies.
1. A GVAR model is used to determine the size and speed of the transmission of different shocks to/from India. This approach uses a dynamic multi-country framework for the analysis of the international transmission of shocks, and is based on a revised version (tailored toward Asian economies) of the models by Cashin et al. (2012a and 2012b).2 The framework comprises 31 region-specific models (among which a single Euro Area region comprising 8 of the 11 countries that joined Euro in 1999). Together, these countries account for over 90 percent of global economic output. These individual models are solved in a global setting where core macroeconomic variables of each economy are related to corresponding foreign variables (constructed exclusively to match the international trade pattern of the country under consideration). The model has both real and financial variables: real GDP, inflation, the real equity price, the real effective exchange rate, short and long-term interest rates, and the price of oil. All data are quarterly in frequency, for the period 1979Q2 to 2011Q2.
2. The results show that output shocks emanating in globally-systemic countries have important global effects, but their impact on India is limited (likely due to the specific trade-structure of India, its relatively closed capital account, and narrow financial exposures to the rest of the world. The effects of negative U.S., Euro Area, and Chinese real output shocks on India, other large emerging economies, and systemically-important countries are discussed next. This chapter also studies the macroeconomic consequences of oil-price fluctuations in India by identifying two groups of explanatory factors as the main drivers of the evolution of crude oil prices: (i) fast-growing demand due to high global economic growth; and (ii) declining supply or anticipated production shortfalls in the future. The results indicate that the economic consequences of a supply-driven oil-price shock are very different from those of an oil-demand shock driven by global economic activity. Also shown is that reducing the monthly purchase of assets by the U.S. Federal Reserve (QE tapering) is likely to have a pronounced effect on Indian financial markets.
Shock to Chinese GDP
3. A one percent negative GDP shock in China translates into lower overall economic growth globally (Figure 1). In particular, countries with large trade exposures to China are most vulnerable to a slowdown in this country. The effects on the GDP of the Euro Area, Japan, UK, and the United States are generally large (around 0.17, 0.25, 0.15, and 0.16 percent after one year, respectively). Other Asian countries3 also suffer a decline in economic output, by about 0.16 percent after one year (because some are included in the supply chain of China). Turning to emerging market countries in the BRICS, Figure 1 shows that following a negative GDP shock in China, the output of Brazil, South Africa, and India falls, with the effect on output being 0.15 and 0.11 percent for the first two and only about 0.05 for India. It seems, therefore, that China has a large impact on most countries in our sample apart from India, which has weaker trade links with China. These findings are somewhat to be expected, given the emergence of China as a key driver of the global economy over recent decades.4
Figure 1.Responses of Output to a Negative GDP Shock in China
Note: Depicts annual percent change in output of a given country associated with 1% decline in GDP of China, together with the 16th and 84th percentile error bands.
Shock to U.S. GDP
4. As a result of the dominance of the United States in the global economy, any slowdown in this country can bring about negative spillovers to other economies, as the recent global economic crisis has shown. Lower demand for commodities is one channel through which a negative U.S. shock affects countries. In particular, about one quarter of world oil demand emanates from the U.S., so it is not surprising that in response to the U.S. shock, oil prices and production levels decline. The commodity price channel conveys a negative impact on growth prospects of commodity-exporters (e.g. Gulf Cooperative Council, other oil exporters, and Brazil) and hence lower import-demand by these countries from other emerging market economies (China and India). Specifically, because China and India’s export portfolios fit well the import demand of many oil-exporting countries, and given their high trade volume with major oil exporters, we would expect lower import demand by oil exporters (due to income effects) to negatively affect aggregate demand in China and India. Furthermore, the continuing dominance of U.S. debt and equity markets, backed by the still-strong global role of the U.S. dollar, also plays an important role. The results of the GVAR model show that the influence of the U.S. on other economies remains larger than direct trade ties would suggest, owing to third-market effects together with increased financial integration that tends to foster the international transmission of business cycles (Figure 2). For instance, following a negative U.S. GDP shock, the Euro Area, and UK real outputs fall by between 0.25 and 0.28 percent after one year. The median effects of a negative U.S. output shock for Asian countries (including India) are generally negative and range between 0.12 and 0.22 percent.
Figure 2.Responses of Output to a Negative GDP Shock in the U.S.
Note: Depicts annual percent change in output of a given country associated with 1% decline in GDP of U.S., together with the 16th and 84th percentile error bands.
Shock to Euro Area GDP
5. The adverse impact on output of a one percent negative GDP shock in the Euro Area is most significant for the United Kingdom, reflecting its geographical proximity to the Euro Area, and the strength of its trade linkages with Europe (Figure 3). Beyond the UK, growth spillovers vary from country to country. High dependences are observed for Brazil, with annual output elasticity of about 0.23. Brazil is adversely affected by a downturn in Euro Area via both trade and commodity-price channels. In the case of other emerging market economies in our sample, South Africa and China are significantly affected by a downturn in the Euro Area, while the impact on India is modest due to its smaller trade linkages with the Euro Area (compared to China) and the improvement in the current account arising from lower oil prices. Estimated spillovers from the Euro Area to other systemic countries, which abstract from financial contagion and may therefore understate the magnitude of true spillovers, are nevertheless of meaningful size with output elasticities being between about 0.13 and 0.15 (Figure 3).
Figure 3.Responses of Output to a Negative GDP Shock in Euro Area
Note: Depicts annual percent change in output of a given country associated with 1% decline in GDP of Euro Area, together with the 16th and 84th percentile error bands.
Shock to Indian GDP
6. This section assesses outward spillovers from a GDP shock in India to other South Asian economies and the rest of the world. The GVAR results show that output shocks in India matter, particularly for its immediate neighborhood, but also have global implications (albeit to a lesser extent than those of China). A one percent decline in the GDP of India generates significant output losses in Nepal, corresponding to around 0.21 percent after one year. Nepal, with its peg to the Indian rupee, relies heavily on India as a market for exports (nearly 60 percent of Nepal’s exports are destined for India), as well as tourism, workers’ remittances, and foreign direct investment. A sustained downturn in India could lower remittance flows to Nepal.
7. However, an Indian slowdown only has a modest effect on other South Asian countries (Bangladesh, Pakistan, and Sri Lanka), with the average effect being 0.03 percent (see Figure 4). Output spillovers from India to the South Asia region are transmitted via trade, remittances, foreign direct investment (FDI), and commodity price channels. Direct financial linkages between India and the rest of South Asia and cross-border banking exposures are minor. Most financial sectors in the region are small and relatively closed to global flows. In addition, spillovers from India to other emerging market economies and advanced economies are generally weak.
Figure 4.Responses of Output to a Negative GDP Shock in India
Note: Depicts annual percent change in output of a given country associated with 1% decline in GDP of India, together with the 16th and 84th percentile error bands.
Shock to U.S. Long-term Interest Rates
8. Reducing the monthly purchase of assets by the U.S. Federal Reserve (QE tapering) is likely to have a pronounced effect on Indian financial markets. Tightening of liquidity conditions will make financing of the large current account deficit in India (mainly financed through short-term debt inflows) more difficult, due to potential capital outflows. With policy space significantly more limited than in 2008/09 and corporate balance sheets more stretched, the interaction between external risks and domestic vulnerabilities could create macroeconomic instability—where balance of payments pressures intensify, corporate balance sheets come under stress, and financial institutions’ asset quality deteriorates, lowering growth.
9. Assuming that long-term U.S. government bond yields rise by 100 bps during the first year of the U.S. financial shock (consistent with a 230 bps rise in long-term interest rates on a quarterly basis), this would generate a modest output loss of around 0.3 percentage points in India during the first year, operating through weak direct financial, trade (including through third-market countries), and commodity-price linkages.
10. A widening of the output gap together with higher long-term government bond yields in India (up by about 50 bps) and lower commodity prices (by about 10 percent due to weaker global growth) is likely to moderate inflation slightly by 0.6 percentage points over one year. Equity prices are likely to fall by about 2 percent, reflecting confidence effects and increased risk aversion, while the nominal exchange rate would depreciate significantly (by about 10 percent). On the capital account side, external commercial borrowing and portfolio investment flows would likely shrink, trade credit financing slow, while a drawdown of international reserves would fill any financing gap (see Figure 5).5
Figure 5.Responses of Indian Variables to a Long-term Interest-Rate Shock in U.S.
Note: Depicts annual percent change in REER, Equity Prices, and Oil Price, and annual percentage points change in GDP growth, Inflation, and 10-Year Bond Yield of a given country associated with a 100bps increase in long-term interest rate of U.S., together with the 16th and 84th percentile error bands.
Shock to Oil Prices
11. We discriminate between supply-driven and demand-driven oil-price shocks, and study the time profile of their macroeconomic effects for India. A negative oil supply shock is an exogenous shift of the oil supply curve along the oil demand schedule to the left, lowering oil production, and increasing oil prices. A good example of such a shock would be exogenous oil production disruptions caused by geopolitical tensions in the Middle-East. In contrast, a positive oil demand shock driven by global economic activity (represented by an upward shift of the oil demand curve along the oil supply schedule to the right) is a shock that increases both oil production and prices. The surge in oil demand on the back of strong economic growth in emerging economies would be an example. To identify these shocks, we impose a set of dynamic sign and contemporaneous quantity restrictions on the generalized impulse responses of a Global VAR model (estimated over 1979Q2-2011Q2). More specifically, we require negative oil-supply shocks to be associated with: (i) an increase in oil prices; (ii) a decrease in global oil production levels; and (iii) a decline in the sum of real output across all oil importers during the first year. This scheme is effective in identifying oil-supply disturbances as other shocks cannot move oil prices, oil production levels, and real GDP (across all oil-importing countries in opposite directions. For oil-demand shocks on the other hand, we require an increase in: (i) oil prices; (ii) oil production levels; and (iii) the sum of real output across the 38 countries/regions within the first year. We augment these restrictions with bounds on impact price elasticities of oil demand and oil supply to narrow the set of admissible structural models.
12. Figures 6–7 show the estimated median impulse responses (for up to 40 quarters) of key macroeconomic variables of India to an oil-price shock, together with the 16th and 84th percentile error bands.6 The results indicate that an oil-supply shock permanently decreases output and creates moderate inflationary pressure in India, due to low pass-through of higher international oil prices to domestic markets. The interest rate responses after an oil-supply shock are generally in accordance with the effects on inflation, i.e. monetary policy is temporarily tightened to stabilize inflation. Equity prices and real effective exchange rates fall. The rising demand for commodities by emerging markets (mainly by China and India, but also the Middle East and Latin America) is a frequently-cited factor in explaining the rise in oil-prices before the global financial crisis and its eventual impact on the global real economic activity (Figure 8). Following an oil-demand shock, India experiences long-run inflationary pressures and a short-run increase in real output. This finding is not surprising given that the oil-price spike is assumed to be determined endogenously by a shift in worldwide economic activity. Output can rise because the country itself is in a boom, or because it indirectly gains from trade with the rest of the world.
Figure 6.Impact of Oil-Supply Shocks on India
Source: IMF staff estimates.
Figure 7.Impact of Oil-Demand Shocks on India
Source: IMF staff estimates.
Figure 8.Crude Oil Consumption by Region, 1970–2011
Source: Cashin et al (2012) based on data from the British Petroleum Statistical Review of World Energy.
CashinP.K.MohaddesM.Raissi and M.Raissi2012a “The Differential Effects of Oil Demand and Supply Shocks on the Global Economy” IMF Working Paper WP/12/253 (Washington: International Monetary Fund).
CashinP.K.Mohaddes and M.Raissi2012b “The Global Impact of the Systemic Economies and MENA Business Cycles” IMF Working Paper WP/12/255 (Washington: International Monetary Fund).
Prepared by Paul Cashin and Mehdi Raissi.
Consisting of Australia, Indonesia, Korea, Malaysia, New Zealand, Philippines, Singapore, and Thailand.
The confidence intervals produced for different sub-groups in this chapter are at times wide, likely due to: model and parameter uncertainties; the possibility of measurement errors in the data (for South Asian countries in particular); and aggregation bias in creating regions. In such cases, the median responses are mainly used for inference as they contain useful information about the direction of the responses and their relative magnitudes (see Cashin et al. 2012a and 2012b for more details).
The magnitude of the effects is broadly in line with what occurred during the summer of 2013. Between May 22 and end-September, the REER depreciated by 7.6 percent, 10-year government bond yield increased by 20 basis points, the SENSEX index fell by 3 percent, and oil prices went up by 7 percent (mainly due to geopolitical events in the Middle East).
The error bands refer to the fact that there are many models with identified parameters that provide the same fit to the data. They are unrelated to sampling uncertainty, and do not show statistical significance.