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India: Selected Issues

Author(s):
International Monetary Fund. Asia and Pacific Dept
Published Date:
February 2014
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India: Defining and Explaining Inclusive Growth and Poverty Reduction1

Robust economic growth has been a major driver of poverty reduction and inclusiveness in India. Analysis using a new measure of inclusive growth indicates that social expenditures, spending on education, and educational attainment rates are important for fostering inclusive growth; while macro-financial stability, with particular attention to inflation risks, is critical for sustaining inclusive growth.

1. India has achieved notable progress in poverty reduction. High economic growth since the economic reforms of the early 1990s, with GDP growth averaging around 7 percent during 1993/94–2011/12, helped halve the poverty headcount rate from 45.3 percent to 21.9 percent. After growing at an average rate of 6¼ percent during 1993/94–2003/04, growth accelerated to 8½ percent during 2004/05–2009/10. This rapid economic growth has contributed to a substantial reduction in poverty. Poverty, measured by the national poverty line, declined by 1.5 percentage points per year in 2004/05–2009/10, double the rate of the preceding decade. High rates of economic growth have been more broadly shared than ever before across India during this latter period, with many poor states growing at double-digit rates.

2. However, the period of rapid growth and poverty reduction (2004/05–09/10) was also accompanied by a rise in inequality. During this period the Gini index rose from about 0.27 in rural and 0.35 in urban India to about 0.28 and 0.37, respectively. Inequality also widened between the rural and urban population, as well as across states. In particular, the ratio of urban to rural per capita consumption and the ratio of real per capita income of the richest state to that of the poorest state rose (Figures 1 and 2).

Figure 1.Ratio of Urban to Rural Real Consumption 1/

Sources: CEIC; and IMF staff estimates.

1/ Ratio in 1993/94 corresponds to nominal consumption.

Figure 2.Real NSDP Per Capita: Ratio of Richest to Poorest States

Sources: CEIC and IMF staff calculations.

3. Notwithstanding relatively higher growth of average urban consumption, the rural poverty headcount rate declined by more than the urban poverty headcount rate, reflecting a favorable shift in rural consumption distribution. Analysis of poverty reduction during 2004/05–2009/10 using Datt-Ravallion Growth-Inequality Decomposition (1992) reveals that stronger growth of average urban real consumption compared to rural consumption accounted for about 8 percentage points decline in urban poverty headcount rate compared to about 5 percentage points decline in rural poverty (Figure 3). However, rural poverty decline was boosted by about 3½ percentage points due to a favorable shift in the distribution of rural consumption. In contrast, the deterioration of urban consumption distribution subtracted almost 3 percentage points from urban poverty headcount rate reduction. Moreover, most of the gains from the distribution change in rural poverty headcount occurred among the poorest of rural households. Specifically, nearly half of the impact from the distribution shift in rural poverty reduction could be attributed to the bottom quartile of the rural poor—those with consumption below two thirds of the poverty line in 2004/05. Furthermore, the negative impact of the urban consumption distribution shift affected the poorest urban households disproportionately more. Specifically, about four fifths of the negative impact of the urban distribution shift was concentrated in the bottom quartile of the urban poor, those with expenditures below two thirds of the poverty line.2

Figure 3.Comparison of Growth and Inequality Contributions to Poverty Reduction Between Rural and Urban Households

Source: IMF staff estimates.

4. Growth incidence curves reveal a more unequal growth pattern among India’s urban population. Rural households experienced a remarkably uniform growth distribution compared with urban households. The two measures of average expenditure growth—a simple average and the average weighted by initial real expenditure levels—reveal the interaction of the initial inequality in 2004/05 and disparity of real expenditure growth over the next five years (Figure 4). The two measures are very close for the rural population, reflecting both a more uniform initial distribution, but indicate further widening of a more unequal initial urban distribution. In addition, rural households with 2004/05 real expenditures near the poverty line (both above and below) experienced above-average growth. In part, this reflects a lower growth of the more well-off rural households. In contrast, growth variation among urban households appears to be very high. Only about the richest five percent of urban population experienced above average growth, while the real consumption growth among households below the poverty line turned out to be much lower.

Figure 4.Comparison of Growth Incidence Curves Between Rural and Urban Households

Source: IMF staff estimates.

5. Inclusive growth integrates the pace and distribution of economic growth, thus providing a unifying depiction of the evolution of inclusiveness. Given that poverty reduction and promoting inclusive growth are the two most important policy priorities of the government, the measure developed by Anand and others (2013) allows combining analysis of poverty reduction, economic growth and inequality. In a nutshell, the measure represents a weighted average of household consumption growth where relatively poorer households are assigned higher weights. Consequently, one of the properties of this inclusive growth measure is that its value will exceed the average expenditure growth if the inclusiveness component contributes positively as expenditure distribution improves3. Staff analysis suggests that India’s inclusive growth measures fell short of the growth in average consumption over 2004/05–2009/10, reflecting deterioration of its inclusiveness component, primarily on account of rising urban-rural and intra-urban inequality. The analysis also reveals a positive contribution of the inclusiveness component to inclusive growth in rural India, suggesting a marginal improvement in equity in rural areas. On the other hand, the growing intraurban inequality was responsible for lower inclusive growth in urban areas.

6. The role of economic policies and macrofinancial conditions in explaining inclusive growth and its components is investigated over 1993/94–2009/10 using state-level panel data.4 By exploiting the variations across states and over time in financial conditions as well as public policies (e.g., government social spending, educational attainment, and financial system size) and growth inclusiveness outcomes, the factors associated with stronger and more inclusive growth are uncovered. Given the rise in urban-rural inequality, the cross-state inclusive growth performance for urban and rural populations is also conducted separately.

7. Social expenditures, spending on education and educational attainment rates are important for fostering inclusive growth. Robust economic growth is imperative for strong government revenue growth and, as a result, for ensuring adequate fiscal space for developmental spending, in particular social sector spending. Such government expenditures are closely linked to inclusive growth and poverty reduction (Tables 2 and 3). Specifically, our econometric results suggest that boosting social sector spending by about 1 percent of GDP is associated with about 0.5 percentage point decline in the poverty rate.5 Therefore, going forward with revenue-boosting reforms to create fiscal space for higher public investments and social expenditures, while supporting fiscal consolidation, would help make progress in reducing poverty.

Table 1.India: Evolution of Poverty
Annual Average Decline in Poverty
1993/942004/052009/102011/121993/94-2004/052004/05-2009/102004/05-2011/12
Poverty Headcount RatioRural50.141.833.825.70.81.63.2
In percentUrban31.825.720.913.70.61.02.4
Total45.337.229.821.90.71.53.1
Number of PoorRural328.6325.8278.2216.50.39.515.6
In millionsUrban74.581.476.552.8−0.61.04.1
Total403.7407.2354.7269.3-0.310.519.7
Sources: IMF staff calculations; Press Note on Poverty Estimates, 2011-12, July 2013.
Sources: IMF staff calculations; Press Note on Poverty Estimates, 2011-12, July 2013.
Table 2.India: Regression Analysis of Growth Inclusiveness: State-Level, Urban and Rural Households
Dependent Variable:Inclusive growth

In percent per year
Average expenditure component

In percent per year
Inclusiveness component

In percent per year
(1)(2)(3)(4)(5)(6)
Credit-to-GDP ratio0.019 **0.020 **0.013 *0.0110.0050.009 **
In percent, period average(0.009)(0.008)(0.007)(0.008)(0.004)(0.004)
Real per capita state social sector expenditure0.026 *0.023 **0.022 **0.0160.0050.008
In percent of poverty line, average per year(0.014)(0.011)(0.010)(0.011)(0.008)(0.006)
Inflation rate−0.724 ***−0.573 ***−0.563 ***−0.444 ***−0.159−0.136
In percent per year, period average(0.209)(0.207)(0.183)(0.193)(0.103)(0.093)
Increase in state spending on education0.096−0.4030.510 **
In percent of NSDP, over previous period’s average(0.425)(0.359)(0.227)
Increase in literacy rate0.836 ***0.551 **0.245 **
In percent per year(0.278)(0.224)(0.117)
Literacy rate, end of previous period0.061 **0.066 **−0.010
In percent of state’s rural population(0.029)(0.026)(0.012)
Number of observations484848484848
R20.400.570.300.440.530.60
Source: IMF staff estimates.Note: Period dummies included, not reported in the table. Robust standard errors in parentheses.Note: ***,**, * indicates 1,5, and 10 percent statistical significance, respectively.
Source: IMF staff estimates.Note: Period dummies included, not reported in the table. Robust standard errors in parentheses.Note: ***,**, * indicates 1,5, and 10 percent statistical significance, respectively.
Table 3.India: Regression Analysis of Poverty Reduction (Datt-Ravallion Decomposition): State-Level, Urban and Rural Households 1/
Dependent Variable:Poverty Reduction

In percent per year
Average expenditure component

In percent per year
Redistribution component

In percent per year
(1)(2)(3)(4)(5)(6)
Credit-to-GDP ratio0.0460.054−0.007−0.0310.0240.038
In percent, period average(0.048)(0.046)(0.034)(0.039)(0.032)(0.030)
Real per capita state social sector expenditure0.0690.0600.199 ***0.153 **−0.084−0.069
In percent of poverty line, average per year(0.125)(0.110)(0.058)(0.062)(0.081)(0.072)
Inflation rate−2.487 **−1.890 *−1.265−0.902−0.567−0.375
In percent per year, period average(1.014)(1.027)(0.932)(0.987)(0.816)(0.797)
Increase in state spending on education0.508−3.1391.372
In percent of NSDP, over the previous period average(1.918)(2.312)(1.482)
Increase in literacy rate3.378 ***1.0411.507 *
In percent per year(0.943)(1.148)(0.803)
Literacy rate, end of previous period10.231 ***0.312 *0.006
In percent of state’s rural population(0.099)(0.179)(0.083)
Number of observations484848484848
R20.760.790.380.450.800.93
Source: IMF staff estimates.

Average expenditure and redistribution components are measured as percentage point contributions to percentage decline in the poverty headcount.

Note: Period dummies included, not reported in the table. Robust standard errors in parentheses.Note: ***,**, * indicates 1,5, and 10 percent statistical significance, respectively.
Source: IMF staff estimates.

Average expenditure and redistribution components are measured as percentage point contributions to percentage decline in the poverty headcount.

Note: Period dummies included, not reported in the table. Robust standard errors in parentheses.Note: ***,**, * indicates 1,5, and 10 percent statistical significance, respectively.

8. A better-educated labor force provides a foundation for robust and inclusive growth as well as for continued poverty reduction. Staff analysis suggests that Indian states that boosted spending on education and those that boosted fundamental educational attainment rates had better inclusive growth outcomes. Furthermore, a positive association between a state’s initial literacy rates and inclusive growth outcomes may suggest that raising the quality of the labor force through better access to education can help unlock a virtuous cycle of higher potential growth. Nevertheless, the presence of appropriate labor market policies and continued structural reforms are critical to enable education to enhance and broaden economic growth.

9. Macro-financial stability, with particular attention to inflation risks, is also critical for sustaining inclusive growth. Lower inflation goes hand-in-hand with more inclusive growth and better poverty reduction outcomes (Tables 2 and 3). As staff analysis indicates, states with relatively deeper bank credit achieved better growth, through boosting inclusiveness in particular. Safeguarding financial stability is therefore critical for ensuring continued financial deepening, increasing access to finance, and broadening growth. Finally, anchoring the government’s socioeconomic development agenda to a sustainable financial position lays a cornerstone for broad macroeconomic and financial stability.

References

    AliI. and H.Son2007Measuring Inclusive GrowthAsian Development Review Vol. 24 No. 1 pp. 1131.

    AnandR.S.Mishra and S.J.Peiris2013Inclusive Growth: Measurement and DeterminantsIMF Working Paper 13/135 (Washington: International Monetary Fund).

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    RavallionM. and G.Datt1992Growth and Redistribution Components of Changes in Poverty Measures: A Decomposition with Applications to Brazil and India in the 1980sJournal of Development Economics Vol. 38 pp. 27595.

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    TopalovaP.2008India: Is the Rising Tide Lifting All Boats?IMF Working Paper 08/54 (Washington: International Monetary Fund).

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1

Prepared by Rahul Anand and Volodymyr Tulin. Based on a forthcoming IMF working paper by Rahul Anand, Volodymyr Tulin and Naresh Kumar.

2

It should be noted that real consumption of all segments of the rural and urban poor grew. The redistribution component of the Datt-Ravallion decomposition reflects differences in the growth rates across households.

3

In the spirit of the Datt-Ravallion decomposition, the inclusive growth measure can be split into contributions of average growth and change in inclusiveness.

4

The sixteen major states included in the analysis comprise about 90 percent of India’s population and national economy.

5

Based on the social spending coefficient estimate from column (4) in Table 3 and assuming unchanged welfare distribution.

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