Is India Shining For the Poor too ?

Posted in Finance Articles, Total Reads: 3753 , Published on 05 February 2012
Advertisements

The Article written by Rajat Varna is the Third Prize winner of the January 2012 Article Writing Contest

Since the economic liberalization of 1991, India has been on a steady path of economic growth, at least from the point of view of the conventional economic parameters like GDP growth, industrial output or per capita income. In fact along with China, India today is one of the fastest growing economies in the world and recognized as one of the drivers of economic growth in the world. However with about one-third of the world’s poor living in India and 37.2 % of India’s population living below poverty level (according to Tendulkar committee), doubts have been cast over the effectiveness of India’s remarkable economic growth story over the issue of upliftment of the poor. We have investigated all these issues from an objective point of view using various economic and statistical measures. Also, India’s success with its economic reforms is compared vis-à-vis other emerging economies such as China and some macroeconomic policy alternatives are proposed in order to ensure that the poor are not left behind in India’s growth story.

Is India Shining for the Poor ?

Impact of Growth on Poverty Alleviation

India grew at a rate of 3.6% per annum for three decades from 1950-1980. After the eighties, India has performed better and grown at a faster pace. From 2000-2010, the average annual growth rate has been a healthy 7.3%. It appears plausible that the economic reforms carried out in the 1990s have helped in propelling India on this growth trajectory.

If we look at the sectoral breakups, we see that growth in Agricultural sector has always been the lowest. Hence, its share in GDP has reduced from 46% in the 50s to about 20% in 2000-08. On the other hand, service sector has grown at an impressive rate of 8.8% and its share in GDP has increased to 54%.

Table1: Decadal Average Annual Growth Rates in Real GDP

Periods

Agriculture

Industry

Services

Total GDP

1951‐1980

2.52%

5.20%

4.41%

3.62%

1981-1990

3.52%

6.19%

6.61%

5.40%

1991‐2000

3.16%

5.48%

7.52%

5.73%

2001‐2011

2.93%

7.89%

8.82%

7.28%










Annual Growth Rates in Real GDP

Openness of economy to external trade coupled with increase in productivity growth in domestic economy has resulted in a higher GDP growth. But higher growth has also resulted in a increase in inequality. In fact, these inequalities were far greater in India as compared to other emerging economies like China at the outset of their reform periods. Ravallion and Datt (2002) found a strong correlation between the initial level of human capital development and non-farm growth rate in determining the pace of poverty reduction at state level.

Entries in Table 2 show that economic growth in the pre-1990s period has reduced poverty. Higher values in column 2 and 3 of the following table shows that people who are further below the poverty line have benefited from the economic growth of pre-90s.

Table2: Elasticities of National Poverty Measures to Economic Growth in India, 1958-1991

Elasticity with respect to

Headcount Index

Poverty Gap Index

Squared Poverty Gap Index

Mean consumption from national sample surveys

-1.33

-1.88

-2.26

Mean private consumption from national accounts

-0.9

-1.36

-1.67

Mean net domestic product from national accounts

-0.75

-1.15

-1.45

Source; Ravallion and Datt (1996)

Regression Analysis

Headcount index v ln(GDP) at constant prices

Headcount index refers to the proportion of people living below the poverty line. It is measured as follows:

Headcount Index = q/N  (where q is the no of people below the poverty line and N is the total population)

Regression o/p is as follows:

Headcount index = 436.27-27.67*ln(GDP);  R squared =0.93

The negative coefficient shows that as real GDP growth increases the headcount ratio decreases. This is in line with what has happened in India and other emerging economies. But HCR doesn’t depend only on GDP growth. We need to include other factors as well. We should also be concerned about the depth and extent of poverty.

GINI v ln(GDP)

GINI coefficient is used to measure income inequality in this case.

GINI coefficient = -7.66 + 2.89*ln(GDP);   R squared = 0.21

GINI coefficient has been increasing over the years, which shows that higher economic growth has actually increased inequality in India. Hence, it is important to look at the growth in various sectors and also concentrate on pro-poor economic reforms in order to ensure that poor people are not left behind in India’s growth story.

Also, we see that the model doesn’t fit that well. We need to add more explanatory variables in order to better estimate the GINI coefficient of income inequality.

GINI Index v GDP contribution of various sectors and Developmental Spending

GINI = 67.69 -10.45*ln(GDP contribution from agriculture) -42.75*ln(GDP contribution from industry) + 48.71*ln(GDP contribution from services) - 2.1*ln(Govt Developmental Spending) ; R squared = 0.631

Negative coefficient between GDP contribution from agriculture and GINI coefficient of income inequality is due to the labor intensive nature of occupation. Close to 60% of the total workforce is in this sector and if productivity is improved then we can succeed in reducing inequality. Similarly, there exists a negative correlation between GDP contribution from industry and GINI coefficient. It can also be noted that inequality can be reduced to an extent by government’s developmental spending.

There exists a positive relationship between income inequality and GDP contribution from services sector. This can be due to many people opting for a career in the service sector at higher compensation packages vis-a-vis other sectors thus widening the ever increasing gap between rich and poor.

Trends in incidence of poverty

The table below shows the headcount ratio of poverty across some of the major states of India. In rural areas, the HCR has decreased from 45.76% in 1983 to 28.3% in 2004-05. For the urban areas, it has decreased from 42.27% in 1983 to 26.03% in 2004-05. Coefficient of variation of HCR of rural poverty decreased from 41 to 36 from 1983-1994 and increased to 55 in 2004-05. However, CV for urban poverty has been increasing from 1983 to 2004-05 with the values being 32, 46 and 55 respectively.

The reduction in inter-state inequality in rural poverty can be due to agricultural output of 80s. The widening gap in the later period can be attributed to worsening income inequality and migration of labor. The increasing trend of CV of HCR in urban poverty shows that higher economic growth has brought higher inequality with it. In order to effectively reduce poverty, just higher economic growth is not sufficient.

Table 3: Head count ratios across major states of India


Rural

Urban

All

State

1983

1993-94

2004-05

1983

1993-94

2004-05

1983

1993-94

2004-05

Andhra Pradesh

27.31

16.64

10.83

37.49

37.63

27.08

29.78

22.52

15.29

Assam

41.92

44.43

21.79

23.07

10.19

3.69

40

40.62

19.31

Bihar

64.89

57.24

43.45

47.49

36.54

29.5

62.69

54.4

41.57

Gujarat

27.92

22.44

19.46

38

29.44

14.19

31.15

24.93

17.43

Haryana

21.77

26.62

13.63

25.47

17.54

15.5

22.61

24.31

14.21

Himachal Pradesh

17.77

29.27

10.87

16.01

8.26

5.02

17.63

27.38

10.27

Jammu & Kashmir

25.23

19.73

4.51

17.48

7.38

10.82

23.54

16.72

6.13

Karnataka

37.51

30.24

20.05

42.88

39.67

33.25

39.09

33.25

24.7

Kerala

38.46

26.49

13.37

45.11

25.45

20.63

39.85

26.2

15.24

Madhya

48.21

40.43

37.67

53.11

48.29

41.39

49.24

42.33

38.62

Maharashtra

45.04

37.66

30.08

39.69

34.74

32.98

43.11

36.54

31.35

Orissa

67.52

50.11

47.81

49.19

41.02

42.6

65.28

48.81

46.99

Punjab

14.3

13.72

10.04

23.52

11.83

5.87

16.89

13.15

8.55

Rajasthan

37.72

26.89

18.76

38.81

31.55

32.28

37.95

27.99

21.95

Tamil Nadu

56.22

32.99

22.62

47.94

38.92

23.77

53.47

35.07

23.17

Uttar Pradesh

46.38

42.33

33.2

49.47

36.15

31.42

46.95

41.05

32.82

West Bengal

61.56

37.35

28.87

31.5

23.24

15.97

53.54

33.41

25.24

All

45.76

37.26

28.3

42.27

32.56

26.03

44.92

36.01

27.65

Coefficient of variation

41

36

55

32

46

55

37

34

51

Comparison of India’s progress in poverty alleviation vis-à-vis other developing countries like China etc.

Since the nature of poverty and the structural reforms in both these countries are quite different, so their progress on this issue has been quite different. China has seen higher proportionate rate of poverty reduction in the past two decades as compared to India. Growth promoting policies can be attributed towards this improvement in China.

Focus in China has been mainly in the expanding manufacturing and industrial production while India’s economic focus has shifted from agricultural to services sector. The increase in employment has been mainly in lower productivity activities and not in the organised sector.

The following are some of the salient features of China’s poverty and economic inequalities:

  1. The consumption distribution inequality has been rising in China(see Gini coefficient data). Also, there has been an increase in the difference between the urban and rural incomes, even though there has been some improvement in the rural economy through wage rises, land reforms and structural changes in the public finance.
  2. Equitable land distribution in rural areas helped to reduce the differences.
  3. Urban poverty has been on the rise owing to increasing unemployment. After restructuring of the state run enterprises there was lot of closure of such enterprises and large scale layoffs.
  4. Migrants from rural to urban areas constitute a part of the urban poor. Though they are employed in the urban cities, but they do not get proper availability of the housing and medical facilities.
  5. The share of agriculture in GDP and employment has decreased steadily since 1980s. Thus there has been a greater level of job creation in non-agricultural and manufacturing sector. Also, the agricultural value added per worker in agriculture has increased, nearly doubling since 1995. This acted as a stimulus in reducing rural poverty and the government supported it by increasing investment into welfare schemes, education and agricultural research.
  6. The profit from non-agricultural activities has been directed as investments into the developmental schemes for the poor. Government spending on education and healthcare services has been increasing in the past decade and they will have significant impact in poverty reduction.

Therefore, we can say that in both India and China the urban-rural inequality has increased. Due to the differences in nature of the causes of the differences, China should consider adopting an equitable income distribution policy and change its urban-focused growth policy. From India’s perspective, equitable land reform and labor-intensive industrial program should be given a greater emphasis.

Sound Macroeconomic Policy

There has been a rapid rise in the public debt in the second half of 1990s in emerging Asian countries like India and China. Even though efforts have been made to reduce foreign debts, domestic public debt has increased considerably. The borrowing has brought in growth but at the same time increased borrowing costs which in turn discourages private investment and limits the flexibility of fiscal policy. This in turn reduces social and infrastructure spending needed to sustain growth and reduce poverty. However fiscal reforms like tax reforms can help raise revenue as well as provide incentives to save, invest and work.

Agricultural Productivity

Under certain conditions agriculture productivity growth promotes both increased production and employment for poor farmers and landless labourers. A recent estimate shows that the number of dollar poor will reduce by 1.34 million in East Asia and 2.51 million in South Asia, following a one per cent increase in yields. Various improved techniques and scientific research have been instrumental for the success of various rural development initiatives in both India and China. But the latter successes are conditional on significant policy and institutional reforms that ensure equitable access to land, markets, credit, education, extension and infrastructure in rain-fed farming areas.

Table 4: Gini coefficients for consumption distribution in China

1978

1988

1997

2002

National


0.30


0.38


0.34


0.45

Rural


0.21


0.30


0.34


0.38

Urban


0.16


0.23


0.29


0.34

Source: UNDP China Human Development Report, 2005

India shining headcount ndex

Figure 1: Poverty in India compared to rest of the developing world

Business Implications

  1. Increasing public expenditure is necessary for alleviating poverty though undertaking various social welfare and infrastructure development programmes. However, such initiatives are highly capital intensive and hence they will incur a negative pressure on the already rising debt levels in the country increasing interest rates, leading to crowding out of the investments.
  2. There is a need to streamline the labor supply in the country in order to shift the focus from unproductive sectors to manufacturing and production. This will help in increasing employment as well as sustain the growth of the economy though increased production and in turn exports. Thus, it will help improve the income and consumption levels of the working laborers and reduce poverty.
  3. Technological advancement and research is necessary for improving agricultural productivity. Increased domestic agricultural production will help reduce dependence on imports. Hence reduced cost of imports will help reduce levels of sovereign debt and help government spending for the rural poor though various welfare schemes. Along with this equitable land distribution will help reduce rural inequalities and improve living standard of the poor farmers.

Conclusions

  • Economic growth in the pre-90s period has reduced both poverty headcount and the extent of poverty
  • Increasing trend of the Coefficient of HCR in urban poverty from 1983-2005 shows that higher economic growth has brought higher inter-state inequality
  • Headcount Index of poverty and real GDP growth are inversely related which means that high growth in real terms can uplift some of people who are below the poverty line. However, GINI coefficient of income inequality and real GDP growth are positively related
  • A better model for estimating GINI coefficient of income inequality shows that inequality decreases with rise in GDP share from agricultural and industrial sectors and increases with a rise in services sector’s GDP share.
  • Employment generation in non-agricultural and manufacturing sector has enabled China to reduce poverty at a higher rate as compared to India

References

  1. Raghav Gaiha, 2009. “Millenium Development Goal of Halving Poverty in Asia”. Journal of Asian and African Studies. SAGE Publications.
  2. Eckhard Siggel, 2010. “Poverty Alleviation and economic reforms in India”. Progress in Development Studies, 10, 3 (2010) pp. 247-59
  3. Jayati Ghosh, 2010."Poverty reduction in China and India: Policy implications of recent trends?,"Working Papers 92, United Nations, Department of Economics and Social Affairs.
  4. Data| World Bank from http://data.worldbank.org/
  5. Reserve Bank of India. Handbook of Statistics on Indian Economy from http://www.rbi.org.in/scripts/AnnualPublications.aspx?head=Handbook%20of%20Statistics%20on%20Indian%20Economy

This article has been authored by Rajat Varna from IIM Lucknow.

Image: Atanu Ghosh / FreeDigitalPhotos.net


Advertisements


If you are interested in writing articles for us, Submit Here