BREAD 2008 - 1 IW Outes-Leon Nutrition and Growth in Rural Ethiopia BREAD Summer School 2008 Ingo W....

BREAD 2008 - 1

IW Outes-Leon

Nutrition and Growth in Rural Ethiopia

BREAD Summer School 2008

Ingo W. Outes-Leon, Oxford University

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IW Outes-Leon

Overview

A. Introduction

B. Data and Empirical Model

C. Results

D. Conclusions

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A.1 Introduction – Aim and Motivation

Test whether poor nutrition and health has a negative effect on a HHs ability to generate future consumption

We estimate effect of adult low BMI on HH consumption growth, after controlling for other HH assets.

Necessary, but not sufficient, condition for nutritional poverty traps to exist.

Combine Nutritional Poverty Trap (Dasgupta and Ray) - Productivity Effect Morbidity theories (Deaton (2005) and Fogel (1992)) - Health Effect

With Micro-Growth models (Jalan and Ravallion (2003), Antman and McKenzie (2005) and Dercon and Shapiro (2007))

And literature on Non-linearity in BMI (Dasgupta (1993) and Strauss and Thomas (1998))

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A.2 Introduction – Aim and Motivation

Take inspiration from Mankiw, Romer and Weil (1992), estimate: HH consumption growth (1995 to 2004) on Lagged dependent variable And HH Assets and Other characteristics on baseline (1995)

Adult Low BMI enters equation as further component of HH human capital

That is, Conditional convergence type of model. So no actual test of poverty traps But able to indicate if low BMI has a drag-down effect on HH

growth

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A.3 Introduction – Contribution and Challenges

Findings and Contribution:

IV methods provide evidence of negative Growth Effect of low BMI Evidence of Persistence of the 1984 Drought on 1995 adult BMI Application of ‘weak’ IV estimation and inference methods.

Estimation: IV Fuller Estimator Inferences: Conditional Likelihood Ratio (CLR) Moreira p-values

Challenges:

Validity of Instrumentation Methodology Doubtful, but IV estimates still interesting

Disentangle village-specific nutritional effects from individual HH effects Unobserved Village Effects vs local nutritional poverty traps (e.g. shocks

and HH infrastructure) Quartile regressions might provide further insight.

Treatment of Other Assets, especially Livestock

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B.1 ERHS Data – Is low BMI bad for growth?

ERHS: 1470 HHs in 15 villages in rural Ethiopia; 1994 to 2004 period; High poverty: 35% poor HHs in 1995 (Dercon and Krishnan (2003)) Incidence of Adult Underweight: 21% of HH Heads (<18.5) 1995-2004 Growth pa: 4.3% (all HHs) ; 6.0% (Low BMI HH Heads).

Kernel smoothing: No apparent Poverty Trap Quartile Kernel smoothing: ‘low BMI’ effect for poor HHS ?

-.1

.1

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-.2

0

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Ann

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15.5 16 16.5 17 17.5 18 18.5 19 19.5 20.5 21 21.5 22 22.5 23 23.5 24 24.515 20 25Body Mass Index, 1995

-.075

-.025

.025

.075

.125

-.1

-.05

0

.05

.1

.15

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15.5 16 16.5 17 17.5 18 18.5 19 19.5 20.5 21 21.5 22 22.5 23 23.5 24 24.515 20 25Body Mass Index, 1995

Quartile 1

Quartile 2

Quartile 3

Quartile 4

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B.2 Empirical Model

(1)

LHS: Food Consumption Growth (1995 to 2004), per annum

RHS: 1995 Baseline HH characteristics: Lagged Dependent Var: Log Consumption 1995 Life-cycle controls – cohort dummies HH Assets: low BMI, Livestock, Land, Education, HH structure Shocks: Rainfall, price shocks Village Characteristics/ Village Fixed Effects

Definition of Variables of Interest: ‘low BMI (Head)’ – dummy for BMI<18.5 of HH head; ‘low BMI (HH Share)’ – share of adults with BMI<18.5;

Endogeneity Concerns: low BMI, livestock and lagged dependent variable

1 2 3(ln ln ) / lnit it p it p it p it p it ity y p y X W S v

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B.3 Identification Strategies

Method A: Lagged Endogenous Variables – 1994

Strong but invalid instruments. LATE interpretation of estimates.

Method B: 1984 Drought Shock

IV: self-reported 1984 Drought Shock. Valid if self-reported shock is unrelated to growth, after controlling for assets. Some validity tests are passed – But validity remains questionable

Comparison OLS vs IV estimates still interesting: Analogous to LATE: BMI growth effect of long-term vulnerability

2004199519941984

tt-p

Growth (t to t-p)

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Consumption Growth Regressions

Naïve OLS Model

Endog: Low BMI and Consumption, 1995

Lagged Endog IV

Dependent: Change in Log Consumption, 1995-2004

IV: 1994OLS OLS IV GMM IV GMM(1a) (1b) (2a) (2b)

Log Consumption., t-1 -0.1036 -0.1021 -0.074 -0.078 -22.76 -21.65 -3.51 -3.5Low BMI (Head), t-1 -0.0112 -0.04 -1.28 -2.17 Low BMI (HH share), t-1 -0.0063 -0.069 -0.5 -2.49Livestock, Cat 1, t-2 0.0211 0.0196 0.013 0.016 1.90 1.75 1.11 1.32Livestock, Cat 2, t-2 0.0148 0.0153 0.008 0.012 1.44 1.48 0.72 1.06Livestock, Cat 3, t-2 0.0384 0.0347 0.035 0.037 3.4 3.06 2.96 3.16Livestock, Cat 4, t-2 0.054 0.0496 0.042 0.046 4.95 4.3 3.48 3.73Livestock, Cat 5, t-2 0.0568 0.0557 0.048 0.051 4.78 4.59 3.69 3.8Livestock, Cat 6, t-2 0.0814 0.078 0.073 0.077 4.39 4.2 3.53 3.64Land, t-1 -0.0063 -0.009 -0.02 -0.022 -0.48 -0.67 -1.37 -1.5Relative Land, t-1 0.0065 0.0076 0.007 0.008 1.3 1.52 1.35 1.61Schooling, 1994 -0.0003 0.0009 -0.003 -0.003 -0.03 0.11 -0.39 -0.33Chronic h. problem, 1994 -0.0029 -0.0024 0.007 0.005 -0.38 -0.31 0.86 0.72Rainfall Shock, t to t-1 0.0374 0.0377 0.026 0.027 4.84 4.83 2.52 2.47Price Shock, t to t-1 0.0017 0.0016 0.001 0.001 2.64 2.36 0.83 0.85Price Index, t-1 0.0013 0.0013 0 0 2.35 2.48 0.39 0.42_cons 0.312 0.2949 0.314 0.333 4.37 4.1 3.75 3.84Nr Instruments None None 2 2Cragg-Donald F-Stat - - 23.11 20.88Cohort, & demo. controls Yes Yes Yes YesVillage Dummies - FE No No No NoNr. Observations 764 764 764 764

C.1 Naïve and Lagged Endog. IVs

Note: T-statistics reported. Bold coefficients indicate significance at the 10% level. First-Stage estimates not reported. Periods defined as [t=2004], [t-1=1995] and [t-2=1994]. Livestock categories indicate single units of scaled livestock, except for categories 4 to 6 that correspond with ‘4 to 6’, ‘6 to 10’ and ‘more than 10’ scaled units respectively; livestock default category is ‘less than 1’. Cohort and demographic controls include: ‘hh size’, ‘nr male members’, ‘share of female members’, ‘Δ hh size’, ‘Δ nr children members’, ‘Δ nr female members’ and dummies for each decade of age of HH head.

Naïve: No BMI effect Livestock non-linearities

Lagged IV: ‘Low BMI (Head)’ reduces

growth by 4%

(Robustness checks omitted): BMI effect - robust to

changing length of Lag. But not robust to introduction

of Village FE

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C.2 Quartile IV Regressions – Lagged Endog IVs

Quartile Regressions, Endog: Low BMI (Head), 1995

by Av. Consumption, 1994-1995 IV: Low BMI 1994

Consumption Growth 1995 to 2004IV Fuller IV Fuller IV Fuller IV Fuller

Quartile 1 Quartile 2 Quartile 3 Quartile 4

Panel A - Standard Controls

Low BMI (Head), t-1 - 0.101 -0.046 0.0015 -0.0677

s.e. -2.71 *** -1.50 0.06 -1.74 *

F-Stat (First-Stage) 49.18 26.94 36.13 32.49

Panel B - Village Fixed Effects

Low BMI (Head), t-1 - 0.073 -0.0298 -0.0064 -0.0294

s.e. -1.91 * -1.17 -0.25 -0.81


Panel C – Consumption Quartiles by Village

Low BMI (Head), t-1 - 0.118 -0.0499 -0.0682 0.0107

s.e. -2.72 *** -1.88 * -1.78 * 0.36


Note: T-statistics reported. Coefficients highlighted in bold indicate significance at the 5% level. F-statistics reported in bold indicate the presence of ‘strong’ IVs. All regressions reported include same controls as in slide C.1

BMI effect most likely to exist only among poorest

Use village-specific quartiles

Effect is largest among the poor.

Robust to Village FE and Village-Specific Quartiles

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C.3 Drought IVs – IV GMMExogenous IV Regressions

Endog: Low BMI (Head), 1995IV Set 1: Drought and

Food Aid, 1984IV Set 2: Drought 1984

IV Set 3: Drought and Food Aid, 1984 to 1994

IV Set 1, with Village Means

IV GMM IV GMM IV GMM IV GMM (1) (2) (3) (4)

First Stage - IV Determinants of Low BMI, t

1984 Drought Dummy 0.0724 0.0784 0.0125 2.04 2.30 0.351984 Food Aid value -1.15E-05 -4.60E-06 -2.81 -1.301984 Drought X 1984 Food Aid 1.18E-05 1.12E-05 1.62 1.60Drought Dummy, 1984 to 1994 0.0603 1.76 Food Aid value, 1984 to 1994 -7.15E-06 -3.55 Drought X Food Aid, 1984 to 1994 4.48E-06 1.27

Second Stage - Consumption Growth, t to t-1

Aver. Log Cons., 1994 and 1995 -0.1122 -0.1149 -0.1069 -0.0986 -9.72 -8.92 -11.10 -10.30Low BMI (Head), t-1 -0.1683 -0.2498 -0.0981 0.0995 -1.43 -1.65 -1.70 1.09Vill. Consumption, t-1 -0.0180 -0.88Vill. Low BMI, t-1 -0.2932 -2.74Vill. Livestock, t-1 0.0123 2.87Vill. Land, t-1 -0.1353 -2.37First-Stage Nr Instruments 3 1 3 3F-Stat 5.57 5.31 6.26 1.23Second-Stage Hansen J Overid Test - p-value 0.31 - 0.24 0.67HH Asstes and Cohort Controls Yes Yes Yes YesVillage Dummies No No No NoR-Square 0.051 -0.285 0.233 0.256Nr. Observations 707 713 707 707

Note: T-statistics reported. Coefficients highlighted in bold indicate significance at the 10% level. Controls: HH Assets, Cohort dummies and HH demographic variables

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C.4 Drought IVs – Weak IVs

IV GMM (First-Stage) F-Stats: Stock and Yogo (2005) critical values F-Stats from [5.31] to [6.26] suggest: IV estimates include 30% to 20% of the

OLS Bias

Weak IV GMM estimates are unreliable – under finite-samples, (Murray (2006)): IV GMM point estimates can be substantially bias; Standard Errors tend to be invalid and smaller (!!)

Estimation: IV Fuller and IV LIML Methods are more robust to ‘weak’ IVs In the literature: IV Fuller method is preferred estimator. See Stock, Wright and Yogo (2002) and Murray (2006).

Inferences: CLR Moreira and Anderson-Rubin tests more robust CLR Moreira methods shown to dominate alternative methods See Andrews, Moreira and Stock (2005) and Murray (2006).

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C.5 Estimates and Inferences – Robust to ‘Weak’ IVs

Inference and Estimators, robust to Weak IVs

Endog: Low BMI (Head), 1995

IV Set 1: Drought and Food Aid, 1984

IV Set 2: Drought 1984IV Set 3: Drought and Food Aid,

1984 to 1994

(1) (2) (3)

IV GMM -0.1683 -0.2498 -0.0981

-1.43 -1.65 -1.70

IV LIML -0.2476 -0.2498 -0.2065

-1.49 -1.65 -2.18

IV Fuller -0.1532 -0.1539 -0.1503

-1.80 -2.03 -2.47

Wald, p-value 0.0740 0.0750 0.0390

CLR, p-value 0.0327 *** 0.0157 *** 0.0170 ***

Anderson-Rubin, p-value 0.0583 0.0157 0.0381

Wald, Confidence Interval [-0.519, 0.0239] [-0.5244, 0.0248] [-0.4023, -0.0108]

CLR, Confidence Interval [-2.1257, -0.0219] [-1.2636, -0.0449] [-0.6793, -0.037]

Anderson-Rubin, Confidence Interval [-47.669, 0.0075] [-1.2636, -0.0449] [-0.9795, -0.0096]

F Stat (First-Stage) 5.57 5.31 6.26

Hansen J Overid Test - p-value 0.3115 - 0.2431

R-Square (Second-Stage) 0.0509 -0.2847 0.2327

Nr. Observations 707 713 707

Nr Instruments 3 1 3

IV Period 1984 1984 1984 to 1994

Drought Dummy Yes Yes Yes

Food Aid value Yes No Yes

Drought X Food Aid Yes No Yes

Note: T-statistics reported. Coefficients highlighted in bold indicate significance at the 10% level. Wald, Moreira Conditional Likelihood Ratio (CLR) and Anderson-Rubin p-values and corresponding confidence intervals reported in square brackets.

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Food Aid - Validity Better connected HHs – obtain more Food Aid and grow faster. No bias appreciable when comparing with ‘IV Set 2: 1984 Drought Only’

Self-Reported Drought likely endogenous E.g. Better insured HHs in 1984 drought villages – not affected by Drought. No available HH information prior to 1984 drought. Use answer ‘Did “food sharing” increase during famine?’ as extra control.

Livestock Endogeneity and Low BMI Bias Current Implicit Ass: 1984 Drought affects exclusively HH health. Persistence in Livestock Assets might be behind ‘low BMI’ effects Over-id Drought IV estimates with Endog: Low BMI and Low Livestock

Model is unreliable due to ‘very weak’ IVs. But ‘Low BMI’ effect remains large [-0.10]. While ‘Low Livestock’ effect is increased substantially;

C.6 Further on Drought IVs

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C.8 Quartile IV Regressions – Drought IVs

Note: T-statistics reported. Coefficients highlighted in bold indicate significance at the 10% level. Moreira Conditional Likelihood Ratio (CLR) p-values reported in square brackets. ‘Undefined’ CLR p-value indicates that confidence intervals were unbounded. F-statistics reported in bold indicate the presence of ‘strong’ IVs. All regressions reported include same controls as in Slide C.4

Quartile Regressions, Endog: Low BMI (Head), 1995

by Av. Consumption, 1994-1995 IV: Drought 1984

Consumption Growth 1995 to 2004IV Fuller IV Fuller IV Fuller IV Fuller

Quartile 1 Quartile 2 Quartile 3 Quartile 4


Low BMI (Head), t-1 -0.1756 -0.0373 -0.0112 -0.0091

s.e. -2.65 -0.61 -0.81 -0.34

CLR Moreira p-value [0.0060] *** Undefined Undefined Undefined

F-Stat (First-Stage) 8.35 3.65 0.05 -0.52


Low BMI (Head), t-1 -0.0448 -0.0156 0.0079 0.017

s.e. -1.01 -0.31 0.52 3.11

CLR Moreira p-value Undefined Undefined Undefined Undefined



Low BMI (Head), t-1 -0.1249 -0.0193 0.0626 0.0248

s.e. -1.75 -3.90 2.35 0.42

CLR Moreira p-value [0.0628] ** Undefined Undefined Undefined


BMI effect most likely to exist only among poorest

With Village FE – ‘low BMI’ effect disappears

Although it is robust to Village-Specific Quartiles

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D.1 Conclusions

Uncover substantial persistence of 1984 drought on 1995 livestock and BMI

Low BMI has significant negative effect on subsequent HH growth. Lagged Endog IVs and Drought IVs provide results consistent with each other.

Growth effect of Low BMI might not be causal but can be interpreted as growth effect of low BMI persistence (Lagged IV) or

HH vulnerability (Drought IV).

This Low BMI burden is overwhelmingly borne by the poor.

Growth effect is large in magnitude For lowest quartile (with village FE), persistence of low BMI reduces

growth by 7% percentage points per annum, for a period of nine years.

Drought IV estimates suggest a very large effect – up to 15% percentage points per annum, for nine-year period.

But partly include village and ‘livestock’ effects.

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D.2 Going Forward

Alternative IVs; Alternative tests of validity;

Arellano-Bond Panel Estimation Can tackle Unobserved HH Heterogeneity Unpack HH FE – seek for 1984 Drought effect

Testing for Mechanism of low BMI: Income and productivity Higher morbidity

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Many Thanks

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Consumption Growth Regressions

Endog: Low BMI and Consumption, 1995

Lagged Endog IVLagged Endog IV, Lagged Endog IV,

Village Means Village FE

Dependent: Change in Log Consumption,

1995-2004

Growth: 1995-2004 IV: 1994

Growth: 1997-2004 IV: 1994

Growth: 1995-2004 IV: 1994

Growth: 1997-2004 IV: 1994

Growth: 1995-2004 IV: 1994

IV GMM IV GMM IV GMM IV GMM IV GMM IV GMM IV GMM IV GMM IV GMM IV GMM

(1a) (1b) (2a) (2b) (3a) (3b) (4a) (4b) (5a) (5b)

Log Consumption., t-1 -0.074 -0.078 -0.054 -0.054 -0.081 -0.084 -0.034 -0.037 -0.063 -0.065

-3.51 -3.5 -1.36 -1.45 -2.36 -2.32 -0.63 -0.74 -1.97 -1.96

Low BMI (Head), t-1 -0.04 -0.042 -0.033 -0.06 -0.019

-2.17 -1.34 -1.77 -1.78 -1.09

Low BMI (HH share), t-1 -0.069 -0.063 -0.058 -0.113 -0.037

-2.49 -1.36 -1.86 -2.13 -1.18

Vill. Consumption, t-1 -0.002 0.002 -0.04 -0.033

-0.05 0.05 -0.67 -0.57

Vill. Low BMI, t-1 -0.06 -0.04 0.091 0.119

-1.14 -0.71 1.31 1.59

Vill. Livestock, t-1 0.007 0.007 0.006 0.006

2.26 2.22 0.98 0.99

Vill. Land, t-1 -0.022 -0.024 0.045 0.043

-0.54 -0.56 0.69 0.67

First-Stage

Nr Instruments 2 2 2 2 2 2 2 2 2 2

Cragg-Donald F-Stat 23.11 20.88 12.83 13.47 10.74 10.7 8.58 8.97 11.21 11.1

Second-Stage

Asset, Cohort Controls Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Village Dummies - FE No No No No No No No No Yes Yes

R-Square 0.459 0.452 0.296 0.285 0.4822 0.4734 0.234 0.217 0.5 0.498

Nr. Observations 764 764 735 735 764 764 735 735 764 764

Note: T-statistics reported. Bold coefficients indicate significance at the 10% level. First-Stage estimates not reported. Periods defined as [t=2004], [t-1=1995] and [t-2=1994]. Controls: HH Assets, Cohort dummies and HH demographic variables

C.3 Lagged Endogenous IVs – Robustness

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VariablesAl HHs High Cons. HHs Low Cons. HHs Normal BMI (Head) Low BMI (Head)

(1) (2) (3) (4) (5)

Av. Food Cons. Growth, (t to t-1)/p0.0430 -0.0139 0.0999 0.0382 0.0605

Log Food Cons., t-1 3.8006 4.4676 3.1335 3.8865 3.4863

Height (HH head) 167.3367 167.6845 166.9889 167.1656 167.9628

BMI (HH head), t-1 19.9525 20.1294 19.7757 20.6267 17.4860

Low BMI (HH head), t-1 * 0.2147 0.1414 0.2880 0.0000 1.0000

Low BMI (HH share), t-1 0.2155 0.1575 0.2735 0.1031 0.6268

Livestock (Index), t-1 2.6872 2.8906 2.4838 2.7796 2.3491

Low Livestock, t-1 * 0.6505 0.5838 0.7173 0.5872 0.7166

Land (Hect. per AEq), t-1 0.3868 0.4985 0.2752 0.4097 0.3031

Relative Land, t-1 1.1116 1.1926 1.0307 1.1319 1.0377

Schooling (HH head), 1994 * 0.4398 0.4869 0.3927 0.4733 0.3171

Chronic health problem, 1994 * 0.2160 0.1885 0.2435 0.1800 0.3476

Rainfall Shock, t to t-1 -0.0432 -0.0022 -0.0842 -0.0296 -0.0929

Food Price Index (FPI), t-1 120.4468 122.4427 118.4509 121.0354 118.2934

Price Shock (ΔFPI), t to t-1 -5.6561 -6.5490 -4.7633 -6.1511 -3.8453

Adult Illness Shock, t 0.3704 0.3377 0.4031 0.3367 0.4939

Livestock Shock, t ** -0.2497 -0.2452 -0.2542 -0.2588 -0.2168

Agricultural Shock, t ** -0.1770 -0.1586 -0.1954 -0.1692 -0.2056

Δ HH size, t to t-1 -0.9908 -0.5209 -1.4607 -0.7633 -1.8232

Δ Nr. Female members, t to t-1 -0.5131 -0.2906 -0.7356 -0.3983 -0.9329

Δ Nr. Children, t to t-1 -0.3639 -0.0942 -0.6335 -0.3383 -0.4573

HH size, t-1 6.6361 5.7827 7.4895 6.4700 7.2439

Nr. Males Adult, t-1 1.6950 1.4764 1.9136 1.6000 2.0427

Female share in HH, t-1 0.4958 0.4996 0.4920 0.4951 0.4984

HH head Age, t-1 46.8261 44.8808 48.7663 45.6156 51.2472

Nr Observations 764 382 382 600 164

Note: (*) Indicates dummy variables. (**) Index between (0) and (-1), negative indicates a more serious shock. ‘High’ and ‘Low’ consumption HHs correspond with the top and bottom halves of the 1995 food consumption distribution. Variables used in the regressions models not reported here include: village asset means and decade-age dummies. Consumption growth variable is defined as the average growth between t and t-1, where p takes a value of nine years

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Note: Change in number of households from 713 to 707 is due to missing food aid information for 6 households. Pairs of columns (3)-(4) and (5)-(6) add to unity by village

Low BMI (Head)

1984 Drought Shock 1984-1994 Drought ShockNr Observ.

Av. Food Aid Value (1984)

Av. Food Aid Value (1984-1994)

1995 No Yes No Yes

Normal BMI - 1995 No 286 273 244 315 559 677 Birr 2001 Birr

Low BMI - 1995 Yes 52 102 44 110 154 446 Birr 771 Birr

Nr Observations 713 338 375 288 425 713 707 707

By Villages

Haresaw 12.50% 37.5% 62.5% 31.3% 68.8% 32 938 Birr 4532 Birr

Geblen 8.33% 83.3% 16.7% 83.3% 16.7% 24 49 Birr 17,055 Birr

Dinki 26.79% 8.9% 91.1% 5.4% 94.6% 56 406 Birr 406 Birr

Yetemen 10.26% 66.7% 33.3% 33.3% 66.7% 39 - -

Shumsha 8.62% 34.5% 65.5% 22.4% 77.6% 58 6,430 Birr 9,960 Birr

Sirbana Godeti 15.91% 95.5% 4.6% 88.6% 11.4% 44 - -

Adele Keke 14.29% 42.9% 57.1% 37.5% 62.5% 56 71 Birr 118 Birr

Korodegaga 34.55% 25.5% 74.6% 18.2% 81.8% 55 6 Birr 236 Birr

Trirufe Ketchema 22.73% 47.7% 52.3% 45.5% 54.6% 44 3 Birr 3 Birr

Imdibir 81.82% 15.2% 84.9% 15.2% 84.9% 33 122 Birr 206 Birr

Aze Deboa 25.00% 0.0% 100.0% 0.0% 100.0% 40 26 Birr 30 Birr

Adado 10.00% 100.0% 0.0% 100.0% 0.0% 40 - -

Gara Godo 35.59% 32.2% 67.8% 27.1% 72.9% 59 70 Birr 515 Birr

Doma 22.22% 42.2% 57.8% 20.0% 80.0% 45 63 Birr 314 Birr

Milki 0.00% 73.0% 27.0% 70.3% 29.7% 37 - -

Kormargefia 16.00% 84.0% 16.0% 80.0% 20.0% 25 - -

Karafino 14.29% 85.7% 14.3% 85.7% 14.3% 14 - -

Bokafia 16.67% 91.7% 8.3% 91.7% 8.3% 12 - -

All villages 21.60% 47.4% 52.6% 40.4% 59.6% 713 627 Birr 1734 Birr

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Note: Highlighted area indicates information used in the construction of the different sets of instruments. (*) Food aid totals reported include double-counting of households. That is, 201 households received food aid in 1984, but only a total of 371 different households received food aid at least once during the 1984 to 1994 period.

Year

1995 Round – Vulnerability Module, 20 year recall period1994 Round – Vulnerability Module,10 year

recall period

Nr of Household – Worse Drought

Nr of Household – 2nd Worse Drought

Nr of Household – 3rd Worse Drought

Total Food Aid Value (in Birr)

Nr of Households

1973 6 - -

1974 5 - 1

1975 1 3 -

1976 5 1 -

1978 2 - -

1979 4 1 -

1980 7 2 -

1981 6 - -

1982 16 2 -

1983 37 22 1

1984 375 62 19 67,342 201

1985 1 22 6 142,418 51

1986 2 11 8 37,579 14

1987 3 31 8 46,787 9

1988 3 13 4 4,025 12

1989 1 15 2 2,494 8

1990 5 11 13 7,286 22

1991 2 5 2 3,015 24

1992 4 15 6 8,246 28

1993 17 79 68 12,667 106

1994 12 8 7 - -

Total 514 303 145 331,859 475 (*)

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Note: T-statistics reported. Coefficients highlighted in bold indicate significance at the 10% level. Moreira Conditional Likelihood Ratio (CLR) p-values reported in square brackets. ‘Undefined’ CLR p-value indicates that confidence intervals were unbounded. F-statistics reported in bold indicate the presence of ‘strong’ IVs. All regressions reported include same controls as in Slide D.2

Quartile Regressions, Endog: Low BMI (Head), 1995 Endog: Low BMI (Head), 1995

by Av. Consumption, 1994-1995 IV: Low BMI 1994 IV: Drought 1984

Consumption Growth 1995 to 2004IV Fuller IV Fuller IV Fuller IV Fuller IV Fuller IV Fuller IV Fuller IV Fuller

Quartile 1 Quartile 2 Quartile 3 Quartile 4 Quartile 1 Quartile 2 Quartile 3 Quartile 4


Low BMI (Head), t-1 -0.101 -0.046 0.0015 -0.0677 -0.1756 -0.0373 -0.0112 -0.0091

-2.71 -1.50 0.06 -1.74 -2.65 -0.61 -0.81 -0.34

[0.0023] [0.1797] [0.9993] [0.0848] [0.0060] Undefined Undefined Undefined

F-Stat (First-Stage) 49.18 26.94 36.13 32.49 8.35 3.65 0.05 -0.52


Low BMI (Head), t-1 -0.073 -0.0298 -0.0064 -0.0294 -0.0448 -0.0156 0.0079 0.017

-1.91 -1.17 -0.25 -0.81 -1.01 -0.31 0.52 3.11

[0.0556] [0.4368] [0.8180] [0.4603] Undefined Undefined Undefined Undefined

F-Stat (First-Stage) 30.85 21.13 33.28 29.99 1.87 1.94 0.01 0.01


Low BMI (Head), t-1 -0.118 -0.0499 -0.0682 0.0107 -0.1249 -0.0193 0.0626 0.0248

-2.72 -1.88 -1.78 0.36 -1.75 -3.90 2.35 0.42

[0.0013] [0.0733] [0.0972] [0.7445] [0.0628] Undefined Undefined Undefined

F-Stat (First-Stage) 32.11 52.61 22.03 36.08 9.85 0.01 0.15 2.56

BREAD 2008 - 1 IW Outes-Leon Nutrition and Growth in Rural Ethiopia BREAD Summer School 2008 Ingo W....

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