welfare dynamics: evidence from the erhs surveys

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Welfare Dynamics: Evidence from the ERHS Surveys

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Page 1: Welfare Dynamics: Evidence from the ERHS Surveys

Welfare Dynamics: Evidence from the ERHS Surveys

Page 2: Welfare Dynamics: Evidence from the ERHS Surveys

Introduction

• There is a wealth of cross-sectional information on dimensions of wellbeing in Ethiopia

• There is much less information or understanding of dynamics of poverty and welfare– The extent to which households move in and out of poverty over time

– Do public interventions have sustainable impacts on household welfare

– Will agricultural growth reduce poverty

– Are households “chronically poor” or merely “slow growing”

• The Ethiopian Rural Household Survey (ERHS) has been designed to answer questions such as these

• The ERHS has been supported financially by SIDA, USAID, WFP and the ESSP.

Page 3: Welfare Dynamics: Evidence from the ERHS Surveys

The Ethiopian Rural Household Survey(ERHS)

• The ERHS is a collaborative effort between the Department of Economics, Addis Ababa University; the University of Oxford; and IFPRI

• Capacity building has been an important component of the ERHS. More than 25 doctorates and 60 masters theses by Ethiopians have been based on the ERHS

• Two ERHS survey rounds were conducted in 1994. Subsequent rounds have been fielded in:– 1997 (with special emphasis on gender)

– 1999 (with special emphasis on agricultural productivity)

– 2004 (with special emphasis on recovery from the 2002 drought), and

– 2009 (with special emphasis on gender, productivity and insurance)

Page 4: Welfare Dynamics: Evidence from the ERHS Surveys

The Ethiopian Rural Household Survey

• The ERHS is a multi-purpose longitudinal household survey covering 15 villages and approximately 1400 households

• Population shares are consistent with the population shares in the three main sedentary farming systems– The plough based cereals farming systems of the Northern and Central Highlands

– Mixed plough/hoe cereals farming systems, and

– Farming systems based around enset

• Sample sizes approximate a self-weighting sample. When considered in terms of farming system: each person (approximately) represents the same number of persons found in the main farming systems as of 1994.

• Results should not be regarded as nationally representative. The sample excludes pastoral households and urban areas and only covers 15 villages

Page 5: Welfare Dynamics: Evidence from the ERHS Surveys
Page 6: Welfare Dynamics: Evidence from the ERHS Surveys

The Ethiopian Rural Household Survey:Further Strengths

• Low attrition. Approximately 84% of households interviewed in 1994 were re-interviewed in 2009

• Survey covers wide range of topics: demographic change; agricultural production; non-farm income; consumption; assets; human capital formation

• Institutional continuity has meant that there is consistency in measurement of key outcome variables over time

Page 7: Welfare Dynamics: Evidence from the ERHS Surveys

WELFARE DYNAMICS:1994-2004

Page 8: Welfare Dynamics: Evidence from the ERHS Surveys

CONSUMPTION

• We measure welfare in terms of per capita household consumption

• Consumption is defined narrowly as the sum of values of all food items, including purchased meals and non-investment non-food items.

– Use values of housing, durables and spending on health and education expenditures are excluded

– Because there has been accumulation of durables over this period, we understate consumption growth.

– These values are expressed in monthly per capita terms and deflated using the food price index with base year 1994.

Page 9: Welfare Dynamics: Evidence from the ERHS Surveys

CONSUMPTION

• Mean consumption per capita in 1994 was 71.1 birr per capita per month.

• By 2004, this had risen to 91.5 birr per capita in real (1994) terms.

• This implies mean average consumption growth of 2.6 percent per year. This is broadly comparable to the average annual rate of growth of real GDP per capita (2.1 per cent) and the increases reported using nationally representative household consumption data

• This growth has been distributionally neutral; there was no change in inequality over this period

Page 10: Welfare Dynamics: Evidence from the ERHS Surveys

POVERTY

• Poverty is based on a cost-of-basic-needs approach.

• Using the 1994 data, a food poverty line is constructed using a bundle of food items that would provide 2300Kcal per adult per day.

• To this, we add a non-food bundle using the method set out in Ravallion and Bidani (1994) and obtain a poverty line of 50 birr per capita per month in 1994 prices.

Page 11: Welfare Dynamics: Evidence from the ERHS Surveys

TRENDS IN CONSUMPTION AND POVERTY

Mean Consumption

per capita

MedianConsumption per

capitaHead count

poverty Poverty GapSquared

Poverty Gap

1994 71.1 51.6 0.48 0.21 0.12

1995 62.0 45.3 0.55 0.24 0.14

1997 90.9 70.7 0.33 0.12 0.06

1999 88.3 64.5 0.36 0.13 0.06

2004 91.5 65.1 0.35 0.13 0.07

Page 12: Welfare Dynamics: Evidence from the ERHS Surveys

MOVEMENTS IN AND OUT OF POVERTY BETWEEN 1994 AND 2004

Household is: Per cent

Poor in 1994

and Poor in 2004 18.8

Not poor in 1994

and

Poor in 2004

14.2

Poor in 1994

and

Not poor in 2004

26.8

Not poor in 1994

and

Not poor in 2004

34.7

Page 13: Welfare Dynamics: Evidence from the ERHS Surveys

What accounts for this reduction in poverty?

• Improving roads really matters. Access to all-weather roads:– Increases consumption growth by 16.3%.

– Reduces poverty by 6.9 percentage points

• Improvements in the road quality increase the likelihood of purchasing crop inputs (by 29–34%, depending on the season) and, for women, of selling artisanal products (by 39%).

• Receiving at least one extension visit: – Increases consumption growth by 7.1%.

– Reduces poverty by 9.8 percentage points

• Respondents say that development agents are an important source of information about the usage of modern inputs and cultivation practices

Page 14: Welfare Dynamics: Evidence from the ERHS Surveys

• Despite this impressive growth, 37% of ERHS households are chronically poor. Why?

• Location matters!

– A household residing in Gara Godo (an enset growing village) with household characteristics identical to a household in Sirbana Godeti (close to Debre Zeit) is 80 percent more likely to be chronically poor

– Having access to an all-weather road reduces the likelihood of being chronically poor by 37 percent

– Closeness to towns helps. Reducing the distance to the nearest town by 12kilometres lowers the probability of being chronically poor by 38 percent.

• Households residing in villages with, relatively speaking, many female adults are more likely to be chronically poor.

• Education matters!

– Completion of primary school by the household headed reduces the probability of being chronically poor by a fifth

What is poverty reduction faster for some households than for others?

Page 15: Welfare Dynamics: Evidence from the ERHS Surveys

WELFARE DYNAMICS:1994-20092004-2009

Page 16: Welfare Dynamics: Evidence from the ERHS Surveys

ERHS 2009

• The most recent round of the ERHS was fielded between April and July, 2009. Data entry was completed by end-August

• In addition to being comparable to earlier rounds, it contains modules covering:– Child labor

– Impact of migration

– Crop and technology change in agriculture

– Impact of land registration

– Willingness to pay for weather insurance

– Women’s status and participation in household decisionmaking

– Exposure and consequences of shocks, including rising food prices

– Access to the Productive Safety Nets Program

• Very preliminary analysis of these data shows the following

Page 17: Welfare Dynamics: Evidence from the ERHS Surveys

Self-Reported Perceptions of Poverty

2

1

8

11

20

33

13

13

8

0% 20% 40% 60% 80% 100%

2009

2004

1994

Destitute

Poor

Never quite enough

Can get by

Comfortable

Rich, very rich

Page 18: Welfare Dynamics: Evidence from the ERHS Surveys

Asset ownership

86

60

49

13

0

10

20

30

40

50

60

70

80

90

100

Hoes Beds Radios Cellphones

Pe

rce

nt

1994

2004

2009

Page 19: Welfare Dynamics: Evidence from the ERHS Surveys

Vulnerability

57

64

52

54

56

58

60

62

64

66

2004 2009

Pe

rce

nt

Could you raise ___ Birr in one week if you had an emergency

100 Birr

200 Birr

Page 20: Welfare Dynamics: Evidence from the ERHS Surveys

Enrollment: Children 7-14y

14

51

77

23

61

76

0

10

20

30

40

50

60

70

80

90

1994 2004 2009

Pe

rce

nt

Girls

Boys

Page 21: Welfare Dynamics: Evidence from the ERHS Surveys

• What has happened to consumption and poverty? – Do these changes reflect more than life cycle considerations?

– How has it changed spatially? Are there chronically poor localities or chronically poor households?

• How has agricultural growth affected consumption and poverty:

– How much does per capita consumption increase given a __% increase in agricultural production

– How much does per poverty decrease given a __% increase in agricultural production

– How much does per capita consumption increase given a __% increase in yield

– How much does poverty decrease given a __% increase in yield

A (partial) research agenda

Page 22: Welfare Dynamics: Evidence from the ERHS Surveys

• How have shocks – drought, food price rises and other adverse events –affected the evolution of poverty in these localities

• How has the position of women within these households changed. Have welfare improvements been gender neutral?

• Has out-migration benefitted these ERHS households

• Are households willing to purchase weather insurance? What factors, private (wealth, financial sophistication, past exposure to risk) and public (access to the PSNP) affect this willingness

A (partial) research agenda

Page 23: Welfare Dynamics: Evidence from the ERHS Surveys

Summary

• The ERHS tells us that:

– There was considerable growth in consumption between 1994 and 2004 with the result that there was a significant fall in poverty

– However, a significant fraction of households remained chronically poor:

• Remoteness, poor infrastructure and low levels of human capital were major factors

• Our preliminary work with the 2009 data suggests that, on average, several dimensions of wellbeing have continued to improve

• The challenge is to understand what underlines the pattern of these improvements and their determinants