dfg research unit 756 collecting data for vulnerability measurements: some initial findings from...

DFG Research Unit 756

Collecting Data for Vulnerability Measurements:

some initial findings from Thailandand Vietnam

Hermann Waibel

Seminar at Thailand Development and Research Institute, September 25, 2009

Seminar at TDRI, Bangkok, Thailand, 25 September 2009 13:41 2

Outline

Project Objectives

Why Vulnerability Research?

Data Collection to Measure Vulnerability

Results of 1st Phase: Some Examples

Plan for 2nd Phase (2010-2012)


Overall objective of the Project

“to advance the concept and the measurement of

vulnerability to poverty and assess the sources of

vulnerability through interdisciplinary economic

research in Thailand and Vietnam”


Expected Results

1. A comprehensive conceptual and empirical basis for the assessment of vulnerability to poverty in Thailand and Vietnam

2. The relative importance of the sectoral and regional determinants of vulnerability

3. Strategies for more timely, better targeted and more cost effective social risk management


Project Components

Agricultural Economics

Financial Institutions

EconomicGeography

Vulnerability +HH- dynamics

Vulnerability database

Agricultural Economics


EconomicGeography

Vulnerability +HH- dynamics

Vulnerability database


Study Areas

Bernd Hardeweg

Ich war nicht sicher, ob Sie diese meinten. Ist wahrscheinlich etws zu kontrastarm. Inhaltlich ist aber alles auf den übrigen Karten auch drauf - nur eben spezifisch für TH/VN.


I. Development Policy:

“Pockets" of poverty in emerging market economies

Poverty is a dynamic issue

Shocks make people vulnerable

How efficient do HH cope with shocks?

What policy interventions are appropriate?

Motivation for the project


II. Research:

Collection of data specifically for measuring vulnerability

Explore the “black box” (risks and shocks) Comparative study of vulnerability concepts Understand Household decision processes (e.g.

dynamics, multi-location) Risk matters: From fate to fear!

Motivation for the project


(1) Reducing vulnerability has an intrinsic value

Well-being: having good prospects now to have enough in the future

(2) Reducing vulnerability has an instrumental value

Poverty trap: ex ante risk mitigating prevents adoption of high average return portfolios

Why vulnerability Research?


Poverty Typology and Measurements

Criterion Description

Perspective ex post, ex ante

Time Horizon static, dynamic

Welfare indicator consumption, income,

assets, non-monetary

Poverty Type chronically-poor, transient-poor

- structural

- stochastic


Assets

Income (I)

Poverty line

Transient poverty

0<VTP<1

No poverty

VTP=0

Asset poverty lineVTP=0.5

Probability to be poor

Chronic poverty

VTP=1

Structural poverty Stochastic poverty

Asset based Vulnerability


Four prominent definitions of vulnerability

1. Uninsured exposure to risk and shocks (e.g. Jalan

and Ravallion, 1999)

2. Expected Poverty (e.g. Pritchett et al., 2000)

3. Low level of expected utility (Ligon and Schechter,

2003)

4. Expected deprivation or individual vulnerability to

poverty (Calvo and Dercon 2005)


Vulnerability as Expected Poverty (VEP)

Vh: vulnerability

ch: consumption of HH

z: poverty line

p: probability

EP: expected poverty

, , 1( )h t

EPh tV P c z


Measurement of vulnerability (Calvo and Dercon 2007)

V* = V(z,y,p)

z = benchmark, i.e. poverty line

y = vector of outcomes across n states of the world

p = a vector of corresponding probabilities.

Vulnerability as expected deprivation - accounting for the probabilities of negative future events and their severity :


Data Collection Procedure

Limit to Thailand and Vietnam Large Provincial sample > 400 - 1000 Panel data, (at least four waves planned) Multi-location households, (include the

migrants) Combine different fields of economics:

Welfare Economics and Poverty Dynamics Agricultural Economics Financial Institutions Economic Geography


Sampling procedure

T h a i l a n dT h a i l a n d

L a o sL a o s

V i e t n a mV i e t n a m

C h i n aC h i n a

M y a n m a rM y a n m a r

C a m b o d i aC a m b o d i a

M a l a y s i aM a l a y s i a

Dac Lac

Ha Tinh

Thua Thien Hue

Buri Ram Ubon Ratchathani

Nakhon Phanom

HANOI

BANGKOK

HO CHI MINH CITY

G u l fo f

T h a i l a n d

A n d a m a nS e a

S o u t hC h i n a

S e a

G u l fo f

T o n k i n

0 250 500125km

province

districts

villages

households

purposive sample(location, per capita income)

stratified random sample(e.g. population density, share agricultural households)

random sample

random sample (based on available lists)

2 surveys à 4,400 respondents

Study Areas and sampling procedure


Module / Content Main VariablesContribution to

vulnerability research

1*General survey

informationLocation

Location factors,Poverty and vulnerability

mapping

2Actual Household

CharacteristicsSize, composition and dynamics,

education, health

Testing and advancing the

concept

3

Shocks experienced during past five years and perceived risks

for the next five years

Type, timing, duration, scope, severity, financial consequence, ex post coping

measures, covariance, subjective assessment of risk and well-being;

type, frequency, severity, consequence of expected risks and ex

ante mitigation measures

Vulnerability concept, causes of

vulnerability, coping and mitigation

strategies

4Land, Agriculture and

Natural Resources

Land size and ownership status, land value, crop and livestock technology and production, self-consumption,

productivity, costs, returns, timing and extent of natural resource extraction

Source of income, causes of

vulnerability

Modules of questionnaire and variables to measure vulnerability


Module / Content Main VariablesContribution to

vulnerability research

5Off-farm employment including wage labour

Type, contractual arrangements, location, travel costs, job

acquisition costs, duration of work, wage and fringe benefits

Source of income, causes of vulnerability

6Non-farm self-

employment including cottage industries

Type, investment, costs and returns


7Borrowing, Lending,

Public and other transfers and insurance

Type, sources, contractual arrangements, conditions

amounts, payment frequencies


8Household

ConsumptionFood and non food items, other

expenditures Consumption

9 Assets including housePurchase value depreciation and

service life Coping capacity

Modules of questionnaire and variables to measure vulnerability


“Shock” module


Risk module


Selected Results

Descriptive Statistics

Income Composition

Demographic Characteristics

Pattern of shocks

Data Robustness Test and Aggregate Vulnerability

Risk Perception and Risk Attitude

Key messages of 1st project phase


Indicators of Data Quality

Total sample in 2007: 4,381

Missing cases 2007 ( ~ 2 %)

Total sample in 2008: 4,284

Attrition: ~ 2 %

Replacement rates : ~ 20 %

Standard Errors are acceptable

Initial assumptions confirmed

New issues emerged


Age structure in Buriram versus Thailand

Sources: DFG FOR756 Household survey 2007, Thailand: Institute for Population and Social Research (2003)

6 5 4 3 2 1 0 1 2 3 4 5 6

Age

gro

up

Population (%)

0-4

10 -14

20 -24

30 -34

40 -44

50 -54

60 -64

70 -74

80 -84

90 -94

100 +

Series5

Males Females

Thailand (Projection 2007)

Buriram (Survey 2007, n=3194)


Type of shocks by province for Thailand and Vietnam

0 200 400 600

Agriculture

Demographic

Economic

Social

Other Nakhon Phanom

Ubon Ratchathani

Buriram

0 200 400 600 800 1000

Agriculture

Demographic

Economic

Social

Other Dac Lac

Thua Thien-Hue

Ha Tinh

Source: DFG FOR756 Household survey 2007.


Educational Attainment of Household members

0

10

20

30

40

50

60

70

80

90

100

BR UR NP HT TH DLProvince

Perc

ent of

pop

ula

tion

> 1

5 y

ear

s

> secondary

secondary

intermediate

primary

< primary



Results: Income composition

Share of income component in %, crop year 2006/07

Buriram Ubon Nakhon Ha Tinh Thua Thien Dac LacIncome Source Ratchathani Phanom Hue

Remittances 21.50 16.87 24.21 18.18 11.11 1.93Agriculture and livestock 21.88 20.97 16.50 30.51 19.41 51.45Natural resource extraction 1.27 3.35 6.36 5.23 4.60 0.97Off-farm emplyment 34.22 33.75 33.37 19.18 27.71 27.42Non-farm self-employment 15.52 21.59 14.67 23.04 34.36 15.70Capital and transfer income 5.60 3.47 4.89 3.86 2.81 2.54

1. Wave


Results: Income composition

Share of income component in %, crop year 2007/08

2. Wave Buriram Ubon Nakhon Ha Tinh Thua Thien Dac LacIncome Source Ratchathani Phanom Hue

Remittances 20.80 8.95 7.52 9.87 10.69 2.76Agriculture and livestock 28.36 29.24 22.55 48.41 28.05 66.72Natural resource extraction 2.05 4.38 6.81 2.90 6.94 1.33Off-farm employment 22.95 30.46 35.73 13.82 18.53 10.99Non-farm self-employment 17.24 23.34 21.74 12.74 28.72 14.09Capital and transfer income 8.59 3.63 5.65 12.25 7.06 4.11


Income composition


Change in crop prices - Vietnam


Change in crop prices - Thailand


Robustness Tests: Stochastic Dominance Relations

Are conclusions on vulnerability driven by the choice of

the measure ?

Compare cumulative distributions of income and

consumption at provincial level and search for stochastic

dominance relations between these distributions

Search for stochastic dominance relations (FSD,

SSD,TSD) below the threshold income

Comparisons should allow for robust conclusions on

welfare with non censured data

Provide a benchmark for various vulnerability measures


Distribution of per capita income in Thai provinces


0.2

.4.6

.81

Cu

mu

lativ

e r

ela

tive

fre

qu

en

cy

-10.00 0.00 10.00 20.00 30.00 40.00Per capita income per day in $ (PPP)

Buriram Ubon Ratchathani

Nakhon Phanom

Distribution of per capita income


Dominance relations for provincial distributions and critical values: Per capita consumption

Source: DFG FOR756 Household surveys 2007.

Thailand Vietnam Cross-country

Buriram - Ubon'

Buriram - N’

Phanom

Ubon' - N’

Phanom

Ha Tinh - Hue

Ha Tinh - Dak Lak

Hue - Dak Lak

Ubon' - Dak Lak

N’ Phanom - Ha Tinh

> < < < > > > FSD 0.83 0.73 0.74 9.18 1.53 2.51 0.74

> < < > > SSD 1.72 0.75 1.90 1.97 5.11

> < < > > TSD

2.34 0.78 2.29 2.51 8.32


Consumption distributions – cross-country comparison

Source: DFG FOR756 Household surveys 2007, 2008.

0.2

.4.6

.81

F(X

)

0 2 4 6 8 10Consumption per capita and day

Ubon Ratchathani Dak Lak



Per capita income distributions 2007 - 2008


0.2

.4.6

.81

F(x

)

-10 0 10 20 30 40Per capita income per day ($PPP)

2007

2008

Ubon Ratchathani


Per capita income distributions 2007 – 2008 (lower part)


0.1

.2.3

.4.5

F(x

)

-4 -2 0 2 4Per capita income per day ($PPP)

2007

2008

Ubon Ratchathani


Summary Observations

No meaningful FSD relations -> all vulnerability comparisons depend on the measure used and the poverty line

For consumption data SDD occurs -> consistent with FGT vulnerability indices and the Calvo/Dercon measure

Consumption Vulnerability ordering by province in Thailand : NP < BR < UR

In Vietnam: Ha Tinh < Hue < Dak Lak Income and consumption vulnerability not

consistent No difference between per capita per adult

equivalent


Key Messages of 1st phase

Vulnerability data base reasonably valid data can be collected "but it takes time and it is expensive" spatial dimension of vulnerability is feasible

Vulnerability concept determinants of vulnerability vary downside risk matters Alternative benchmarks seem to be useful Household heterogeneity including gender matters


Agriculture: Part-time farming dominates (TH) Shocks and risk perception affects diversification within agriculture

and outside (TH&VN) Majority of shocks are in agriculture (TH&VN) Shocks can contribute to natural resource degradation (VN) Typical patterns of coping observed for shocks in farm households

(TH)

Key Messages of 1st project phase


Financial Markets: Consumption insurance of rural HH only partially possible Village level microfinance institutions improve access to credit but are

not an effective "shock absorber" (TH)

Economic Geography: non-agricultural wage employment has potential to reduce vulnerability

(TH) income diversification has positive effect on HH welfare (VN) Employment in rural-based industries more stable in the large firms (TH) Higher participation rates in non-agricultural wage labour among peri-

urban HH

Key Messages of 1st project phase


Project plan for next phase

Add another two panel waves in 2010 and 2011

Refine risk module and risk experiment

Add investment module

Add village business survey

Interview domestic migrants once (in 2010)


Economic Geography

- Vulnerability by region, HH types- Nature of off-farm employment by region

- Regional differences of crisis and vulnerability

- Differences in responses to shocks between agricultural and non-agricultural households

- Demand for skills of rural-based industries vs. human capital of rural households


-Finance as a shockabsorber?

-Issues of ruraldevelopment finance

-Risk attitudes, gender and cultural differences

Agriculture

-Economic crisis and de-velopment of agriculture in peripheral areas

-Economic crisis and natural environment

-Risk perceptions and decision making

Vulnerability and

HH dynamics

Managementof Vulnerability

Database

Risk preferences and perceptions

Non-agricultural

income

Thailand

Vietnam

Finan

cial

inst

itutio

ns

and e

mplo

ymen

t

Research Topics 2nd Project Phase


Thank you very much for your attention!


Risk attitudes

Risk is a major variable in vulnerability

assessments

Combining risk experiments with risk questions

in surveys

Simple self-assessment is validated by survey

evidence

Risk experiment may need to be adjusted to

cultural context and level of education

Gender does not seem to matter

More testing is needed !


Results: Risk attitudes, survey based

0.2

.4

0 5 10 0 5 10

Thailand Vietnam

De

nsi

ty

General willingness to take riskGraphs by Vietnam dummy


Results: Risk attitudes, experiment

0.0

05.0

1.0

15.0

2.0

25D

ensi

ty

0 50 100 150 200Certain payoff at switchpoint


Results: Coefficient of partial risk aversion (experiment)

05

1015

2025

Per

cent

-1 -.5 0 .5 1Coefficient of partial risk aversion

dfg research unit 756 collecting data for vulnerability measurements: some initial findings from...

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