Poverty & Inequality

Growth, structural change, and poverty reduction: Evidence from India

  • Blog Post Date 21 March, 2014
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Rana Hasan

Asian Development Bank

rhasan@adb.org

Poverty reduction in India has been relatively slow even in years of high economic growth. A possible explanation is that growth has mainly been driven by sectors that generate fewer jobs for the poor. This column analyses this explanation and finds that structural change or the reallocation of jobs from low productivity to high productivity sectors, plays a key role in reducing poverty.

Cross-country and within-country data show a close relationship between economic growth and poverty reduction. India’s experience is no exception. Over the three decades prior to the 1980s, when average Gross Domestic Product (GDP) per capita fluctuated between 1% and 2%, poverty rates showed little discernible trend. As economic growth picked up in the early 1980s, declines in poverty rates became the norm. Indeed, in the first decade of the 2000s India has witnessed both its fastest rates of economic growth as well as its most rapid reductions in poverty, both in terms of percentage points per year and absolute number of poor.

However, the pace of poverty reduction in India has been slow relative to many East and Southeast Asian countries. Crucially, differences in GDP growth rates1 alone cannot account for the differential performance in poverty reduction as India’s elasticity of poverty reduction to GDP growth2 was less than half of China, as computed over 10-20 year periods (Ravallion 2009).

What explains the relatively slow poverty reduction in India even in high economic growth years?

There are at least three types of explanations. The first highlights the role of weaknesses in India’s ‘initial conditions’ in terms of human development (nutritional, health, and educational status). As Ravallion and Datt (1999) have shown, Indian states with better initial levels of human development had higher growth elasticities of poverty reduction, suggesting that better education and health status enables the poor to seize, if not also create better economic opportunities.

A second explanation focuses on the location of growth. Growth in India has been lower in states that account for a large proportion of the country’s poor. Similarly, growth in rural India, which has accounted for nearly 80% of India’s poor, has been considerably slower than growth in urban India.

A third explanation focuses on the sectoral composition of growth. According to this, India’s growth has had less impact on poverty because it has been driven mainly by sectors that generate relatively few productive employment opportunities for the poor. Conversely, sectors that employ many poor have not experienced significant growth.

Sectoral composition of growth and poverty reduction

In a recent paper, we focus on the third explanation (Hasan, Lamba and Sen Gupta 2013). We consider Ravallion and Datt’s (1996) central finding that growth in Indian agriculture over 1951 to 1991 was significantly poverty reducing, growth in services also contributed, but growth in industry had no impact. If these relationships were to hold post-1991, then high aggregate growth characterised by limited growth in agriculture and robust growth in industry and services may be an explanation for the relatively weak growth-poverty reduction link in India. An examination of recent data on economic growth, productivity and employment levels across sectors suggests that this is how things have played out.

Figure 1. Sectoral contribution to GDP growth, Selected periods

Notes: Computed using national accounts data from the Central Statistical Organisation (CSO). GDP and sectoral growth rates are averages over the 10 year period reported. The sectors are: AGR (Agriculture and Allied Activities), CONS (Construction), CSP (Community, Social and Personal Services), FIRE (Finance, Insurance and Real Estate), GOV (Public Administration; Government Services), MIN (Mining and Quarrying), PU (Public Utilities), REG (Registered Manufacturing), TSC (Transport, Storage and Communications), UNREG (Unregistered Manufacturing), and WRT (Wholesale and Retail Trade, Restaurants and Hotels).
Source: Authors’ Estimates

In contrast, while growth in manufacturing - the key contributor to total employment and output in industry - has played an important role in driving aggregate growth, this has been on account of the skill- and capital-intensive formal (registered) manufacturing sector and which has been characterised by weak employment growth. The contribution of informal (unregistered) manufacturing - which employs around 80% of manufacturing workers and tends to be very labour intensive - to growth has been low and unchanged over time. Thus, employment opportunities in a non-agricultural sector with considerable potential for absorbing less-skilled workers at higher productivity than agriculture, expanded at an all too slow pace.

Figure 2. Employment shares and labour productivity differentials across sectors, 2009-2010

Notes: Sectors are same as in Figure 1.
Source: CSO and National Sample Survey Organisation (NSSO) reports.

Does structural change matter for poverty reduction?

The idea that growth in India would have been more poverty reducing had it been accompanied by larger increases in agricultural productivity, where many of the poor are employed, is uncontroversial in policy circles. However, insufficient policy attention has been given to understanding why growth outside agriculture has not been as poverty reducing as it seems to have been elsewhere in Asia.

We shed light on this issue. The starting point of our analysis is the wide variation in labour productivity across sectors (Figure 2) and its implications3. Increases in aggregate growth need not stem only from improvements in productivity within a given sector - reallocation of employment, or structural change, from lower productivity to higher productivity sectors can be growth enhancing as well. Moreover, since productivity and wages are related at the sector level, structural change should have implications for wages and thus poverty.

Accordingly, we investigate the contribution of within-sector productivity growth and structural change in increasing aggregate productivity across 15 Indian states, as well as their impact on reduction of poverty.

We find that between 1987 and 2009, both within-sector productivity growth and structural change have contributed positively to aggregate labour productivity growth in all states, although the extent of contribution has varied significantly. In Figure 3, the numbers above the bars indicate how various states rank with respect to the proportion of structural change in total productivity growth. The contribution of structural change to aggregate labour productivity is highest in Karnataka, followed by Maharashtra and Haryana. In contrast, Punjab, Bihar and West Bengal have benefitted the least from structural change.

Figure 3. Within-sector productivity growth and structural change in Indian states, 1987-2009

Notes: All values are in annualised percentage terms. States are sorted in order of the highest magnitude of total productivity growth.
Source: Author estimates based on CSO reports

Both, a higher pace of structural change as well as within-sector productivity growth, are positively associated with poverty reduction, with the former having a relatively bigger impact on poverty4. This holds for the entire time period covered in our study as well as only the post-liberalisation years, although the impact is larger in the post-liberalisation period.

Figure 4. Productivity and poverty reduction in Indian states, 1987-2009

Figure 5. Productivity growth decomposition by sector, 1987-2009

Notes: The sectors are: A: AGR, B: MIN, C: PU, D: CONS, E: WRT, F: TSC, G: FIRE, H: GOV, I: CSP, J: REGMFG, K: UNREG.

Contrast this with Karnataka, which like Bihar, experienced reallocation of employment out of agriculture. Some of this employment may have moved into unregistered manufacturing, the second lowest productivity sector, which experienced within-sector productivity improvements. Moreover, the employment share of unregistered manufacturing itself declined. Hence, overall employment share has moved unambiguously to significantly productive sectors, pulling people out of poverty. Two other major differences with Bihar are that high productivity registered manufacturing sector not only experienced a relatively high degree of within-sector productivity growth but also an increase in employment share, and the highest productivity sector (finance, insurance and real estate services), contributed significantly to structural change in the state.

Can policy influence structural change?

Given the importance of structural change in reducing poverty, we evaluate the policy or policy-amenable factors that may influence the extent of structural change. A state’s potential for structural change depends on the initial employment in agriculture, reflecting the base available for structural change, as well as share of educated workers, signaling the extent of occupational mobility. Furthermore, states with a more dynamic economic environment - well-developed financial systems, more competitive product markets and greater labour market flexibility – allow greater reallocation of resources from one economic activity to another. They may therefore be more likely to experience growth-enhancing structural change.

We find initial share of agriculture has a positive and significant impact on structural change, consistent with the idea that this factor captures the potential for structural change. Additionally, all three of our variables capturing elements of investment climate (labour and product market regulations, and especially, extent of financial development) have a positive and significant influence on structural change.

Overall, our findings are consistent with the view that a better investment climate is not only good for business - it is also an important means for making growth more pro-poor in a labour-abundant country.

Notes:

  1. GDP growth rates are commonly referred to as economic growth rates.
  2. This refers to the responsiveness of poverty to GDP growth – the percentage fall in poverty due to a one percentage increase in GDP.
  3. This was recently emphasised by McMillan and Rodrik (2011) in a cross-country context.
  4. Of course, the relationships are not watertight with the extent of poverty reduction in Kerala being far higher than suggested by rates of structural change and within sector productivity growth, and the other way around in Madhya Pradesh.

Further Reading

  • McMillan, Margaret S., and Rodrik, Dani (2011), ‘Globalization, Structural Change and Productivity Growth’, National Bureau of Economic Research Working Papers, 17143.
  • Hasan, Rana, Lamba, Sneha, and Sen Gupta, Abhijit (2013), ‘Growth, Structural Change and Poverty Reduction: Evidence from India’, ADB South Asia Working paper Series, No. 22.
  • Ravallion, Martin (2009), “A Comparative Perspective on Poverty Reduction in Brazil, China and India”, World Bank Policy Research Working Papers, 5080.
  • Ravallion, Martin, and Datt, Gaurav (1999), “When is Growth Pro-poor? Evidence from the Diverse Experiences of India´s States”, World Bank Policy Research Working Paper Series, 2263.
  • Ravallion, Martin, and Datt, Gaurav (1996), ‘How Important to India´s Poor is the Sectoral Composition of Economic Growth?’, World Bank Economic Review, 10 (1), pp. 1-25.
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