food insecurity through a fiscal lens jose cuesta prmpr april 22, 2011
TRANSCRIPT
Outline• “Fiscal Lens”: Work Program
• Food Security and Agricultural Spending in Bolivia
• Vulnerability index
• Agricultural Spending
• The Analysis
• Findings and Conclusions
• A Peek into Tariff Reform and Nutrition in Cote d’Ivoire
Work Program
• How public use of resources affect distributional outcomes?– How fiscal policies affect welfare distribution– How inequality affects policy decisions
• 3 pillars of work:– How traditional tools/techniques can deal with “non
traditional sectors”– Regional disparities and public spending/revenue – Policy decisions during the crisis
Work on food security• “Non traditional” sector, regional perspective
• Other examples are:• Nutritional effects of tariffs in Cote d’Ivoire• Unequal access to justice in Indonesia• Benefit incidence of road investments in Thailand• Central vs. local spending/revenue in Indonesia
• Bolivia study is part of an Agricultural PER
• How agricultural spending affects vulnerability to food insecurity in Bolivia?
Food Insecurity and Public Agricultural Spending in Bolivia
Policy Research Working Paper 5604http://siteresources.worldbank.org/INTPOVERTY/Resources/WPS5604.pdf
Jose Cuesta, Svetlana Edmeades & Lucia Madrigal
A simple story of success
19961997
19981999
20002001
20022003
20042005
20062007
20080
1000
2000
3000
4000
5000
6000
Prefectura Municipio Central
1 2 3 4 50
10
20
30
40
50
Figure 2. Percentage of Municipalities by Vul-nerability Status
2003 2006 2007
VAM
Per
cent
age
Agricultural spending by administrative level
Food Security Definition in Bolivia • Based on “access to nutritious food” definition, that is:
“all people, at all times, have physical and economic access to sufficient, safe and nutritious food to meet their dietary needs, and food preferences for an active and healthy life”
• Bolivia follows this international definition around four dimensions:– Food availability– Access to food– Stable access to food– Safe use of food
• Definition of Vulnerability to Food also follows WFP’s VAM approach:– Risk exposure (e.g. natural disaster)– Capacity to address food insecurity (e.g., incomes, access to basic services)– Current situation as part of a historical trend (e.g. past malnutrition and poverty)
Food Security Policy in Bolivia• 2006 National Development Plan sets FS and sovereignty as
objectives of national production
• 2007 Agricultural Sector Strategy (Revolucion Rural, Agropecuaria y Forestal):– food security and sovereignty; – Increasing agricultural and forest production; and – sustainable management of natural resources
• Food Security Interventions (INE monitoring plan)– land redistribution; – promotion of food production and exports by state-owned enterprises– food security programs, including support to communities & small producers– nutritional programs (children, women) and school meals, among others.
FS Programs and Projects1. National Plan for Land Titling 2. National Plan for Land Distribution and Human Settlements 3. Planting the Right for Food (SEMBRAR)4. Creation of Rural Food Initiatives (CRIAR) 5. Organized Enterprises for Development (EMPODERAR) 6. Renewal of the Role of the State in Rural Food Businesses (RECREAR) 7. Development of territorial, integration and cross-sectoral production complexes 8. National Plan for Coca Development 9. Sustainable Use of Natural Resources (SUSTENTAR) 10. Conservation of Nature and Environmental Quality (CONSERVAR)11. Food Security Support Program (PASA) 12. Multisectoral Program of Zero Malnutrition 13. School Breakfast and Lunch Program
Source: Adapted from MVI Social (2010).
From programs to spendingArea (from AgPER) Category (for study) Type Current/Investment
Expenditure
Research, studies Research & Extension Restricted Current Technical assistance, seminars Research & Extension Restricted Current Water and irrigation Infrastructure Restricted Investment
Productive development Support & Development Restricted Current Assets and machinery Infrastructure Restricted Investment Seeds, fertilizer Support & Development Restricted Current Infrastructure Infrastructure Restricted Investment Plant & animal health support Support & Development Restricted Current Administration, regulation Administration & Procedures Restricted Current Development Support & Development Restricted Current Support Support & Development Restricted Current Roads and bridges Infrastructure Extended Investment Electricity infrastructure Infrastructure Extended Investment Warehousing and commercialization Support & Development Extended Current Risk management Administration & Procedures Extended Current Environmental management Administration & Procedures Extended Current Land organization Administration & Procedures Extended Current Organizational support Administration & Procedures Extended Current Education for Agriculture Research & Extension Extended Current
From definition to measurement of vulnerability
• Dependency rate• Life expectancy• Agricultural potential
(4 values on soil capacity)• Forestry potential (5 values)• Road density• Draught frequency• Frost days per year• Low weight at birth• Per capita household food
expenditures
• Urbanization rate• Rural population density (and
sq)• Prop. Institutionally attended
births• Schooling years• Log of per capita consumption• Under five malnutrition rate • Altitude • Rainfall• Flood Propensity (categorical 4
values)
From measurement to analysis VAM (Municipal Vulnerability Index)
1=very low, 2=low, 3=moderate, 4=high, 5=very high vulnerability
For 2003 each municipality is assigned a value 1 to 5 according to “agreed” vulnerability based on background study on vulnerability of 15 agro-ecological regions in the country (socioeconomic, demographic, ethnic and gender equity, climatic risks, subjective ability to respond to risks)
MNL of VAM2003 on 20 variables
MNL estimates allow 5 probabilities for VAMi=1…5 for each municipality
Estimated MNL on 10 variables for 2006 and 2007 (only those statistically significant in 2003)
Largest estimated prob(VAM=i) determines assigned VAM to each municipality
Some analytical caveats
A few obvious Original VAM 2003
Pragmatic selection of variables based on data considerations (availability and frequency)… too far?
Interdependence: Rural pop density and urbanization Low birth weight and institutional
delivery Floods, rainfall, draught
Not so obvious Inputs for and outcomes of FS
(e.g., malnutrition, urbanization)
Assumed same structural model between 2003 and 2007 (despite policies)
Little wiggle room for IV
A simple story of success… really?
19961997
19981999
20002001
20022003
20042005
20062007
20080
1000
2000
3000
4000
5000
6000
Prefectura Municipio Central
1 2 3 4 50
10
20
30
40
50
Figure 2. Percentage of Municipalities by Vul-nerability Status
2003 2006 2007
VAM
Per
cent
age
Agricultural spending by administrative level
Simple perhaps, but not uniform0
12
34
VA
M
Chuquisaca La Paz Cochabamba Oruro Potosi Tarija Santa Cruz Beni Pando
2003 2007
Mean
Figure 1. Vulnerability Status by Department
02,
000
4,00
06,
000
Chuquisaca La Paz Cochabamba Oruro Potosi Tarija Santa Cruz Beni Pando
2003 2007
Per Capita Agricultural Spending by Department (constant 2005 prices)
and not so simple
2000
2001
2002
2003
2004
2005
2006
2007
2008
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Current Investment
Distribution of Restricted Agricultural Spending
Table 1. Vulnerability Transition Matrix by Municipality 2006 2007
Low vulnerability High vulnerability Low vulnerability High vulnerability 2003 Low vulnerability 146 (45%) 14 (4%) 148 (45%) 12 (4%)
High vulnerability 35 (11%) 132 (40%) 54 (17%) 113 (35%)
Btw 15-20% of municipalities changed status For 1 that worsens, 3 improve
Substantive annual variations in investments
In fact, low correlation agr sp and VAM
020
040
060
0P
C e
xp_2
007
.5 .6 .7 .8 .9 1low07
PC exp_2007 Fitted values
Prob VAM 1, 2, 3
020
040
060
0P
C e
xp_2
007
.5 .6 .7 .8 .9high07
PC exp_2007 Fitted values
Prob VAM 4 or 5
Total PC AGR Expenditure and Prob of being in each VAM cat
Empirical strategy Probit of VAM ( high , low ) on pc capita agr spending
Several categories of spending considered Restricted vs. Extended Current vs. Investment Research & Extension; Infrastructure; Support & Development; Administrative
Regional dummies and region-clustered errors Single out level of spending from increases in spending Combine contemporaneous and lagged levels (not many IV
candidates) Robustness checks:
2006 data; ordered probit; total rather pc spending; Controls: CAPACITY, ELECTORAL. SOCIAL SPENDING variables
Findings
Positive impact of agr sp on high vam
Restricted significant
Investment drives results
Infrastructure significant, also R&D
Region specific effects
Table 3. Effects of Per Capita Agricultural Spending on Vulnerability to Food Insecurity 2007 (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended definitions
Current and investment categories
By function
Total expenditure 0.5843***
(0.220)
Restricted expenditure 1.2889***
(0.489)
Extended expenditure 0.3106
(0.286)
Current expenditures 0.6495
(0.577)
Investment expenditures 0.5714**
(0.281)
Research and extension 8.9864**
(4.128)
Infrastructure 0.6776*
(0.352)
Support and development 0.0562
(0.991)
Administration and procedures
0.2547
(0.860)
Chuquisaca 0.3885*** 0.3702*** 0.3995*** 0.3799***
(0.108) (0.112) (0.107) (0.110)
Cochabamba 0.0951 0.0825 0.1042 0.0782
(0.092) (0.091) (0.092) (0.092)
Oruro 0.1316 0.1024 0.1437 0.1226
(0.100) (0.100) (0.099) (0.100)
Potosí 0.3162*** 0.3089*** 0.3178*** 0.3080***
(0.096) (0.097) (0.096) (0.097)
Tarija -0.3516*** -0.3640*** -0.3485*** -0.3470***
(0.036) (0.032) (0.040) (0.035)
Santa Cruz -0.2899*** -0.2934*** -0.2830*** -0.2975***
(0.060) (0.058) (0.061) (0.057)
Beni -0.3164*** -0.3148*** -0.3124*** -0.3339***
(0.059) (0.057) (0.062) (0.053)
Pando -0.3711*** -0.3674*** -0.3750*** -0.3742***
(0.034) (0.032) (0.033) (0.033)
Observations 327 327 327 327
R2 0.217 0.223 0.217 0.226
*** p<0.01, ** p<0.05, * p<0.1
Findings
Positive impact of agr sp on high vam
Restricted, significant
Investment drives results
Infrastructure significant, also R&D
Region specific effects
Table 3. Effects of Per Capita Agricultural Spending on Vulnerability to Food Insecurity 2007 (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended definitions
Current and investment categories
By function
Total expenditure 0.5843***
(0.220)
Restricted expenditure 1.2889***
(0.489)
Extended expenditure 0.3106
(0.286)
Current expenditures 0.6495
(0.577)
Investment expenditures 0.5714**
(0.281)
Research and extension 8.9864**
(4.128)
Infrastructure 0.6776*
(0.352)
Support and development 0.0562
(0.991)
Administration and procedures
0.2547
(0.860)
Chuquisaca 0.3885*** 0.3702*** 0.3995*** 0.3799***
(0.108) (0.112) (0.107) (0.110)
Cochabamba 0.0951 0.0825 0.1042 0.0782
(0.092) (0.091) (0.092) (0.092)
Oruro 0.1316 0.1024 0.1437 0.1226
(0.100) (0.100) (0.099) (0.100)
Potosí 0.3162*** 0.3089*** 0.3178*** 0.3080***
(0.096) (0.097) (0.096) (0.097)
Tarija -0.3516*** -0.3640*** -0.3485*** -0.3470***
(0.036) (0.032) (0.040) (0.035)
Santa Cruz -0.2899*** -0.2934*** -0.2830*** -0.2975***
(0.060) (0.058) (0.061) (0.057)
Beni -0.3164*** -0.3148*** -0.3124*** -0.3339***
(0.059) (0.057) (0.062) (0.053)
Pando -0.3711*** -0.3674*** -0.3750*** -0.3742***
(0.034) (0.032) (0.033) (0.033)
Observations 327 327 327 327
R2 0.217 0.223 0.217 0.226
*** p<0.01, ** p<0.05, * p<0.1
Findings
Positive impact of agr sp on high vam
Restricted, significant
Investment drives results
Infrastructure significant, also R&D
Region specific effects
Table 3. Effects of Per Capita Agricultural Spending on Vulnerability to Food Insecurity 2007 (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended definitions
Current and investment categories
By function
Total expenditure 0.5843***
(0.220)
Restricted expenditure 1.2889***
(0.489)
Extended expenditure 0.3106
(0.286)
Current expenditures 0.6495
(0.577)
Investment expenditures 0.5714**
(0.281)
Research and extension 8.9864**
(4.128)
Infrastructure 0.6776*
(0.352)
Support and development 0.0562
(0.991)
Administration and procedures
0.2547
(0.860)
Chuquisaca 0.3885*** 0.3702*** 0.3995*** 0.3799***
(0.108) (0.112) (0.107) (0.110)
Cochabamba 0.0951 0.0825 0.1042 0.0782
(0.092) (0.091) (0.092) (0.092)
Oruro 0.1316 0.1024 0.1437 0.1226
(0.100) (0.100) (0.099) (0.100)
Potosí 0.3162*** 0.3089*** 0.3178*** 0.3080***
(0.096) (0.097) (0.096) (0.097)
Tarija -0.3516*** -0.3640*** -0.3485*** -0.3470***
(0.036) (0.032) (0.040) (0.035)
Santa Cruz -0.2899*** -0.2934*** -0.2830*** -0.2975***
(0.060) (0.058) (0.061) (0.057)
Beni -0.3164*** -0.3148*** -0.3124*** -0.3339***
(0.059) (0.057) (0.062) (0.053)
Pando -0.3711*** -0.3674*** -0.3750*** -0.3742***
(0.034) (0.032) (0.033) (0.033)
Observations 327 327 327 327
R2 0.217 0.223 0.217 0.226
*** p<0.01, ** p<0.05, * p<0.1
Findings
Positive impact of agr sp on high vam
Restricted, significant
Investment drives results
Infrastructure significant, also R&D
Region specific effects
Table 3. Effects of Per Capita Agricultural Spending on Vulnerability to Food Insecurity 2007 (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended definitions
Current and investment categories
By function
Total expenditure 0.5843***
(0.220)
Restricted expenditure 1.2889***
(0.489)
Extended expenditure 0.3106
(0.286)
Current expenditures 0.6495
(0.577)
Investment expenditures 0.5714**
(0.281)
Research and extension 8.9864**
(4.128)
Infrastructure 0.6776*
(0.352)
Support and development 0.0562
(0.991)
Administration and procedures
0.2547
(0.860)
Chuquisaca 0.3885*** 0.3702*** 0.3995*** 0.3799***
(0.108) (0.112) (0.107) (0.110)
Cochabamba 0.0951 0.0825 0.1042 0.0782
(0.092) (0.091) (0.092) (0.092)
Oruro 0.1316 0.1024 0.1437 0.1226
(0.100) (0.100) (0.099) (0.100)
Potosí 0.3162*** 0.3089*** 0.3178*** 0.3080***
(0.096) (0.097) (0.096) (0.097)
Tarija -0.3516*** -0.3640*** -0.3485*** -0.3470***
(0.036) (0.032) (0.040) (0.035)
Santa Cruz -0.2899*** -0.2934*** -0.2830*** -0.2975***
(0.060) (0.058) (0.061) (0.057)
Beni -0.3164*** -0.3148*** -0.3124*** -0.3339***
(0.059) (0.057) (0.062) (0.053)
Pando -0.3711*** -0.3674*** -0.3750*** -0.3742***
(0.034) (0.032) (0.033) (0.033)
Observations 327 327 327 327
R2 0.217 0.223 0.217 0.226
*** p<0.01, ** p<0.05, * p<0.1
Findings
Positive impact of agr sp on high vam
Restricted significant
Investment drives results
Infrastructure significant, also R&D
Region specific effects
Table 3. Effects of Per Capita Agricultural Spending on Vulnerability to Food Insecurity 2007 (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended definitions
Current and investment categories
By function
Total expenditure 0.5843***
(0.220)
Restricted expenditure 1.2889***
(0.489)
Extended expenditure 0.3106
(0.286)
Current expenditures 0.6495
(0.577)
Investment expenditures 0.5714**
(0.281)
Research and extension 8.9864**
(4.128)
Infrastructure 0.6776*
(0.352)
Support and development 0.0562
(0.991)
Administration and procedures
0.2547
(0.860)
Chuquisaca 0.3885*** 0.3702*** 0.3995*** 0.3799***
(0.108) (0.112) (0.107) (0.110)
Cochabamba 0.0951 0.0825 0.1042 0.0782
(0.092) (0.091) (0.092) (0.092)
Oruro 0.1316 0.1024 0.1437 0.1226
(0.100) (0.100) (0.099) (0.100)
Potosí 0.3162*** 0.3089*** 0.3178*** 0.3080***
(0.096) (0.097) (0.096) (0.097)
Tarija -0.3516*** -0.3640*** -0.3485*** -0.3470***
(0.036) (0.032) (0.040) (0.035)
Santa Cruz -0.2899*** -0.2934*** -0.2830*** -0.2975***
(0.060) (0.058) (0.061) (0.057)
Beni -0.3164*** -0.3148*** -0.3124*** -0.3339***
(0.059) (0.057) (0.062) (0.053)
Pando -0.3711*** -0.3674*** -0.3750*** -0.3742***
(0.034) (0.032) (0.033) (0.033)
Observations 327 327 327 327
R2 0.217 0.223 0.217 0.226
*** p<0.01, ** p<0.05, * p<0.1
Findings
Positive impact of agr sp on high vam
Restricted signficant
Investment drives results
Infrastructure significant, also R&D
Region specific effects
Table 3. Effects of Per Capita Agricultural Spending on Vulnerability to Food Insecurity 2007 (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended definitions
Current and investment categories
By function
Total expenditure 0.5843***
(0.220)
Restricted expenditure 1.2889***
(0.489)
Extended expenditure 0.3106
(0.286)
Current expenditures 0.6495
(0.577)
Investment expenditures 0.5714**
(0.281)
Research and extension 8.9864**
(4.128)
Infrastructure 0.6776*
(0.352)
Support and development 0.0562
(0.991)
Administration and procedures
0.2547
(0.860)
Chuquisaca 0.3885*** 0.3702*** 0.3995*** 0.3799***
(0.108) (0.112) (0.107) (0.110)
Cochabamba 0.0951 0.0825 0.1042 0.0782
(0.092) (0.091) (0.092) (0.092)
Oruro 0.1316 0.1024 0.1437 0.1226
(0.100) (0.100) (0.099) (0.100)
Potosí 0.3162*** 0.3089*** 0.3178*** 0.3080***
(0.096) (0.097) (0.096) (0.097)
Tarija -0.3516*** -0.3640*** -0.3485*** -0.3470***
(0.036) (0.032) (0.040) (0.035)
Santa Cruz -0.2899*** -0.2934*** -0.2830*** -0.2975***
(0.060) (0.058) (0.061) (0.057)
Beni -0.3164*** -0.3148*** -0.3124*** -0.3339***
(0.059) (0.057) (0.062) (0.053)
Pando -0.3711*** -0.3674*** -0.3750*** -0.3742***
(0.034) (0.032) (0.033) (0.033)
Observations 327 327 327 327
R2 0.217 0.223 0.217 0.226
*** p<0.01, ** p<0.05, * p<0.1
Findings
As before, positive impact of agr sp on high vam
Now both Restricted and Extended are significant
Investment keeps driving results
Infrastructure significant and so R&E (now negative!)
Region specific effects as before
Table 5. Effects of 2003 Per Capita Agricultural Spending on 2007 Vulnerability to Food Insecurity (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended
definitions
Current and investment categories
By function
Total expenditure 0.9888***
(0.338)
Restricted expenditure 1.2450**
(0.562)
Extended expenditure 0.6782**
(0.313)
Current expenditures -0.0250
(0.564)
Investment expenditures 1.3207***
(0.491)
Research and extension -11.1869**
(4.844)
Infrastructure 1.3973***
(0.531)
Support and development 1.8166
(1.723)
Administration and procedures -0.9973
(1.365)
Chuquisaca 0.3503*** 0.3273*** 0.3411*** 0.3331***
(0.115) (0.117) (0.117) (0.121)
Cochabamba 0.1067 0.1136 0.1066 0.1141
(0.093) (0.092) (0.094) (0.094)
Oruro 0.1036 0.1256 0.1224 0.1206
(0.102) (0.103) (0.103) (0.103)
Potosí 0.3239*** 0.3096*** 0.3300*** 0.3192***
(0.095) (0.096) (0.095) (0.095)
Tarija -0.2877*** -0.3020*** -0.2832*** -0.2883***
(0.086) (0.074) (0.090) (0.088)
Santa Cruz -0.2919*** -0.2965*** -0.2893*** -0.2816***
(0.062) (0.061) (0.063) (0.064)
Beni -0.3139*** -0.3130*** -0.3063*** -0.3046***
(0.068) (0.063) (0.072) (0.072)
Pando -0.3353*** -0.3765*** -0.3251*** -0.3303***
(0.064) (0.034) (0.074) (0.071)
Observations 327 327 327 327
Pseudo R2 0.223 0.218 0.227 0.235
*** p<0.01, ** p<0.05, * p<0.1
Findings
As before, positive impact of agr sp on high vam
Now both Restricted and Extended are significant
Investment keeps driving results
Infrastructure significant and so R&E (now negative!)
Region specific effects as before
Table 5. Effects of 2003 Per Capita Agricultural Spending on 2007 Vulnerability to Food Insecurity (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended
definitions
Current and investment categories
By function
Total expenditure 0.9888***
(0.338)
Restricted expenditure 1.2450**
(0.562)
Extended expenditure 0.6782**
(0.313)
Current expenditures -0.0250
(0.564)
Investment expenditures 1.3207***
(0.491)
Research and extension -11.1869**
(4.844)
Infrastructure 1.3973***
(0.531)
Support and development 1.8166
(1.723)
Administration and procedures -0.9973
(1.365)
Chuquisaca 0.3503*** 0.3273*** 0.3411*** 0.3331***
(0.115) (0.117) (0.117) (0.121)
Cochabamba 0.1067 0.1136 0.1066 0.1141
(0.093) (0.092) (0.094) (0.094)
Oruro 0.1036 0.1256 0.1224 0.1206
(0.102) (0.103) (0.103) (0.103)
Potosí 0.3239*** 0.3096*** 0.3300*** 0.3192***
(0.095) (0.096) (0.095) (0.095)
Tarija -0.2877*** -0.3020*** -0.2832*** -0.2883***
(0.086) (0.074) (0.090) (0.088)
Santa Cruz -0.2919*** -0.2965*** -0.2893*** -0.2816***
(0.062) (0.061) (0.063) (0.064)
Beni -0.3139*** -0.3130*** -0.3063*** -0.3046***
(0.068) (0.063) (0.072) (0.072)
Pando -0.3353*** -0.3765*** -0.3251*** -0.3303***
(0.064) (0.034) (0.074) (0.071)
Observations 327 327 327 327
Pseudo R2 0.223 0.218 0.227 0.235
*** p<0.01, ** p<0.05, * p<0.1
Findings
As before, positive impact of agr sp on high vam
Now both Restricted and Extended are significant
Investment keeps driving results
Infrastructure significant and so R&E (now negative!)
Region specific effects as before
Table 5. Effects of 2003 Per Capita Agricultural Spending on 2007 Vulnerability to Food Insecurity (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended
definitions
Current and investment categories
By function
Total expenditure 0.9888***
(0.338)
Restricted expenditure 1.2450**
(0.562)
Extended expenditure 0.6782**
(0.313)
Current expenditures -0.0250
(0.564)
Investment expenditures 1.3207***
(0.491)
Research and extension -11.1869**
(4.844)
Infrastructure 1.3973***
(0.531)
Support and development 1.8166
(1.723)
Administration and procedures -0.9973
(1.365)
Chuquisaca 0.3503*** 0.3273*** 0.3411*** 0.3331***
(0.115) (0.117) (0.117) (0.121)
Cochabamba 0.1067 0.1136 0.1066 0.1141
(0.093) (0.092) (0.094) (0.094)
Oruro 0.1036 0.1256 0.1224 0.1206
(0.102) (0.103) (0.103) (0.103)
Potosí 0.3239*** 0.3096*** 0.3300*** 0.3192***
(0.095) (0.096) (0.095) (0.095)
Tarija -0.2877*** -0.3020*** -0.2832*** -0.2883***
(0.086) (0.074) (0.090) (0.088)
Santa Cruz -0.2919*** -0.2965*** -0.2893*** -0.2816***
(0.062) (0.061) (0.063) (0.064)
Beni -0.3139*** -0.3130*** -0.3063*** -0.3046***
(0.068) (0.063) (0.072) (0.072)
Pando -0.3353*** -0.3765*** -0.3251*** -0.3303***
(0.064) (0.034) (0.074) (0.071)
Observations 327 327 327 327
Pseudo R2 0.223 0.218 0.227 0.235
*** p<0.01, ** p<0.05, * p<0.1
Findings
As before, positive impact of agr sp on high vam
Now both Restricted and Extended are significant
Investment keeps driving results
Infrastructure significant and so R&E (now negative!)
Region specific effects as before
Table 5. Effects of 2003 Per Capita Agricultural Spending on 2007 Vulnerability to Food Insecurity (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended
definitions
Current and investment categories
By function
Total expenditure 0.9888***
(0.338)
Restricted expenditure 1.2450**
(0.562)
Extended expenditure 0.6782**
(0.313)
Current expenditures -0.0250
(0.564)
Investment expenditures 1.3207***
(0.491)
Research and extension -11.1869**
(4.844)
Infrastructure 1.3973***
(0.531)
Support and development 1.8166
(1.723)
Administration and procedures -0.9973
(1.365)
Chuquisaca 0.3503*** 0.3273*** 0.3411*** 0.3331***
(0.115) (0.117) (0.117) (0.121)
Cochabamba 0.1067 0.1136 0.1066 0.1141
(0.093) (0.092) (0.094) (0.094)
Oruro 0.1036 0.1256 0.1224 0.1206
(0.102) (0.103) (0.103) (0.103)
Potosí 0.3239*** 0.3096*** 0.3300*** 0.3192***
(0.095) (0.096) (0.095) (0.095)
Tarija -0.2877*** -0.3020*** -0.2832*** -0.2883***
(0.086) (0.074) (0.090) (0.088)
Santa Cruz -0.2919*** -0.2965*** -0.2893*** -0.2816***
(0.062) (0.061) (0.063) (0.064)
Beni -0.3139*** -0.3130*** -0.3063*** -0.3046***
(0.068) (0.063) (0.072) (0.072)
Pando -0.3353*** -0.3765*** -0.3251*** -0.3303***
(0.064) (0.034) (0.074) (0.071)
Observations 327 327 327 327
Pseudo R2 0.223 0.218 0.227 0.235
*** p<0.01, ** p<0.05, * p<0.1
Findings
As before, positive impact of agr sp on high vam
Now both Restricted and Extended are significant
Investment keeps driving results
Infrastructure significant and so R&E (now negative!)
Region specific effects as before
Table 5. Effects of 2003 Per Capita Agricultural Spending on 2007 Vulnerability to Food Insecurity (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended
definitions
Current and investment categories
By function
Total expenditure 0.9888***
(0.338)
Restricted expenditure 1.2450**
(0.562)
Extended expenditure 0.6782**
(0.313)
Current expenditures -0.0250
(0.564)
Investment expenditures 1.3207***
(0.491)
Research and extension -11.1869**
(4.844)
Infrastructure 1.3973***
(0.531)
Support and development 1.8166
(1.723)
Administration and procedures -0.9973
(1.365)
Chuquisaca 0.3503*** 0.3273*** 0.3411*** 0.3331***
(0.115) (0.117) (0.117) (0.121)
Cochabamba 0.1067 0.1136 0.1066 0.1141
(0.093) (0.092) (0.094) (0.094)
Oruro 0.1036 0.1256 0.1224 0.1206
(0.102) (0.103) (0.103) (0.103)
Potosí 0.3239*** 0.3096*** 0.3300*** 0.3192***
(0.095) (0.096) (0.095) (0.095)
Tarija -0.2877*** -0.3020*** -0.2832*** -0.2883***
(0.086) (0.074) (0.090) (0.088)
Santa Cruz -0.2919*** -0.2965*** -0.2893*** -0.2816***
(0.062) (0.061) (0.063) (0.064)
Beni -0.3139*** -0.3130*** -0.3063*** -0.3046***
(0.068) (0.063) (0.072) (0.072)
Pando -0.3353*** -0.3765*** -0.3251*** -0.3303***
(0.064) (0.034) (0.074) (0.071)
Observations 327 327 327 327
Pseudo R2 0.223 0.218 0.227 0.235
*** p<0.01, ** p<0.05, * p<0.1
Findings
As before, positive impact of agr sp on high vam
Now both Restricted and Extended are significant
Investment keeps driving results
Infrastructure significant and so R&E (now negative!)
Region specific effects as before
Table 5. Effects of 2003 Per Capita Agricultural Spending on 2007 Vulnerability to Food Insecurity (1) (2) (3) (4)
VARIABLES Total exp Restricted and extended
definitions
Current and investment categories
By function
Total expenditure 0.9888***
(0.338)
Restricted expenditure 1.2450**
(0.562)
Extended expenditure 0.6782**
(0.313)
Current expenditures -0.0250
(0.564)
Investment expenditures 1.3207***
(0.491)
Research and extension -11.1869**
(4.844)
Infrastructure 1.3973***
(0.531)
Support and development 1.8166
(1.723)
Administration and procedures -0.9973
(1.365)
Chuquisaca 0.3503*** 0.3273*** 0.3411*** 0.3331***
(0.115) (0.117) (0.117) (0.121)
Cochabamba 0.1067 0.1136 0.1066 0.1141
(0.093) (0.092) (0.094) (0.094)
Oruro 0.1036 0.1256 0.1224 0.1206
(0.102) (0.103) (0.103) (0.103)
Potosí 0.3239*** 0.3096*** 0.3300*** 0.3192***
(0.095) (0.096) (0.095) (0.095)
Tarija -0.2877*** -0.3020*** -0.2832*** -0.2883***
(0.086) (0.074) (0.090) (0.088)
Santa Cruz -0.2919*** -0.2965*** -0.2893*** -0.2816***
(0.062) (0.061) (0.063) (0.064)
Beni -0.3139*** -0.3130*** -0.3063*** -0.3046***
(0.068) (0.063) (0.072) (0.072)
Pando -0.3353*** -0.3765*** -0.3251*** -0.3303***
(0.064) (0.034) (0.074) (0.071)
Observations 327 327 327 327
Pseudo R2 0.223 0.218 0.227 0.235
*** p<0.01, ** p<0.05, * p<0.1
Findings
Very much the same results as before in terms of signs and significance
Incremental spending is significant and negative but negligible in magnitude
Effects of Initial and Incremental Per Capita Spending on Vulnerability (1) (2) (3) (4) (5)
VARIABLES Total exp Total exp (quadratic form for change)
Restricted and extended definitions
Current and investment categories
By function
Total expenditure 2003 0.9950*** 0.9659***
(0.344) (0.338)
Restricted expenditure 2003 0.9361*
(0.533)
Extended expenditure 2003 1.0241**
(0.465)
Current expenditures 2003 0.0598
(0.562)
Investment expenditures 2003 1.2893***
(0.494)
Research and extension 2003 -10.5311*
(6.056)
Infrastructure 2003 1.3837**
(0.544)
Support and development 2003 1.7249
(1.746)
Administration and procedures 2003 -0.8587
(1.351)
Change in per capita agricultural spending 06-07 (“incremental “ effect)
-0.0001** 0.0001 -0.0001** -0.0001* -0.0001**
(0.000) (0.000) (0.000) (0.000) (0.000)
Change squared in per capita agricultural spending 06-07 (“incremental” effect)
-0.0000
(0.000)
Chuquisaca 0.3492*** 0.3479*** 0.3507*** 0.3411*** 0.3322***
(0.117) (0.118) (0.114) (0.119) (0.122)
Cochabamba 0.1234 0.1135 0.1235 0.1231 0.1304
(0.095) (0.094) (0.095) (0.095) (0.096)
Oruro 0.1238 0.1136 0.1245 0.1383 0.1262
(0.104) (0.103) (0.104) (0.104) (0.104)
Potosí 0.3438*** 0.3485*** 0.3444*** 0.3485*** 0.3385***
(0.097) (0.099) (0.097) (0.096) (0.097)
Tarija -0.2784*** -0.2794*** -0.2779*** -0.2739*** -0.2799***
(0.090) (0.078) (0.090) (0.094) (0.094)
Santa Cruz -0.2895*** -0.2823*** -0.2892*** -0.2874*** -0.2803***
(0.062) (0.061) (0.063) (0.063) (0.064)
Findings
Very much the same results as before in terms of signs and significance
Incremental spending is significant and negative but negligible in magnitude
Effects of Initial and Incremental Per Capita Spending on Vulnerability (1) (2) (3) (4) (5)
VARIABLES Total exp Total exp (quadratic form for change)
Restricted and extended definitions
Current and investment categories
By function
Total expenditure 2003 0.9950*** 0.9659***
(0.344) (0.338)
Restricted expenditure 2003 0.9361*
(0.533)
Extended expenditure 2003 1.0241**
(0.465)
Current expenditures 2003 0.0598
(0.562)
Investment expenditures 2003 1.2893***
(0.494)
Research and extension 2003 -10.5311*
(6.056)
Infrastructure 2003 1.3837**
(0.544)
Support and development 2003 1.7249
(1.746)
Administration and procedures 2003 -0.8587
(1.351)
Change in per capita agricultural spending 06-07 (“incremental “ effect)
-0.0001** 0.0001 -0.0001** -0.0001* -0.0001**
(0.000) (0.000) (0.000) (0.000) (0.000)
Change squared in per capita agricultural spending 06-07 (“incremental” effect)
-0.0000
(0.000)
Chuquisaca 0.3492*** 0.3479*** 0.3507*** 0.3411*** 0.3322***
(0.117) (0.118) (0.114) (0.119) (0.122)
Cochabamba 0.1234 0.1135 0.1235 0.1231 0.1304
(0.095) (0.094) (0.095) (0.095) (0.096)
Oruro 0.1238 0.1136 0.1245 0.1383 0.1262
(0.104) (0.103) (0.104) (0.104) (0.104)
Potosí 0.3438*** 0.3485*** 0.3444*** 0.3485*** 0.3385***
(0.097) (0.099) (0.097) (0.096) (0.097)
Tarija -0.2784*** -0.2794*** -0.2779*** -0.2739*** -0.2799***
(0.090) (0.078) (0.090) (0.094) (0.094)
Santa Cruz -0.2895*** -0.2823*** -0.2892*** -0.2874*** -0.2803***
(0.062) (0.061) (0.063) (0.063) (0.064)
Findings
Very much the same results as before in terms of signs and significance
Incremental spending is significant and negative but negligible in magnitude
Effects of Initial and Incremental Per Capita Spending on Vulnerability (1) (2) (3) (4) (5)
VARIABLES Total exp Total exp (quadratic form for change)
Restricted and extended definitions
Current and investment categories
By function
Total expenditure 2003 0.9950*** 0.9659***
(0.344) (0.338)
Restricted expenditure 2003 0.9361*
(0.533)
Extended expenditure 2003 1.0241**
(0.465)
Current expenditures 2003 0.0598
(0.562)
Investment expenditures 2003 1.2893***
(0.494)
Research and extension 2003 -10.5311*
(6.056)
Infrastructure 2003 1.3837**
(0.544)
Support and development 2003 1.7249
(1.746)
Administration and procedures 2003 -0.8587
(1.351)
Change in per capita agricultural spending 06-07 (“incremental “ effect)
-0.0001** 0.0001 -0.0001** -0.0001* -0.0001**
(0.000) (0.000) (0.000) (0.000) (0.000)
Change squared in per capita agricultural spending 06-07 (“incremental” effect)
-0.0000
(0.000)
Chuquisaca 0.3492*** 0.3479*** 0.3507*** 0.3411*** 0.3322***
(0.117) (0.118) (0.114) (0.119) (0.122)
Cochabamba 0.1234 0.1135 0.1235 0.1231 0.1304
(0.095) (0.094) (0.095) (0.095) (0.096)
Oruro 0.1238 0.1136 0.1245 0.1383 0.1262
(0.104) (0.103) (0.104) (0.104) (0.104)
Potosí 0.3438*** 0.3485*** 0.3444*** 0.3485*** 0.3385***
(0.097) (0.099) (0.097) (0.096) (0.097)
Tarija -0.2784*** -0.2794*** -0.2779*** -0.2739*** -0.2799***
(0.090) (0.078) (0.090) (0.094) (0.094)
Santa Cruz -0.2895*** -0.2823*** -0.2892*** -0.2874*** -0.2803***
(0.062) (0.061) (0.063) (0.063) (0.064)
Findings
Civil servants per capita not significant
% of budget executed over approved or % own resources invested significant but negligible
Political party in office (different from central government) not significant
Per capita social spending not significant
Table A3. Effects of Per Capita Agricultural Spending with Observed Controls, 2007 Variables (1) (2) (3) (4) (5) (6) (7) (8)
Total expenditure 0.5399** 0.5776*** 0.6113* 0.3190* 0.5842*** 0.5839*
(0.217) (0.221) (0.328) (0.178) (0.221) (0.325)
Restricted expenditure 1.7848**
(0.778)
Extended expenditure -0.0856
(0.522)
Current expenditure 0.8600
(0.964)
Investment expenditure 0.5380
(0.408)
Civil servants pc, 2006 2.0963 0.1927 -0.8149 0.6524
(11.532) (23.856) (22.781) (23.946)
Political party in office, 2006
0.0683 0.0782 0.0937 0.0792
(0.063) (0.078) (0.080) (0.078)
% budget executed over approved (2006)
-0.0003* -0.0003* -0.0003* -0.0003*
(0.000) (0.000) (0.000) (0.000)
% of investment financed by own resources (2006)
-0.0000***
(0.000)
Per capita social spending, 2006
-0.0000 -0.0001 -0.0001 -0.0002
(0.000) (0.000) (0.000) (0.000)
Regional dummies yes yes yes Yes yes yes yes yes
Population yes yes yes Yes yes yes yes yes
Observations 300 327 234 314 327 227 227 227
R2 0.214 0.22 0.237 0.27 0.217 0.225 0.235 0.225
*** p<0.01, ** p<0.05, * p<0.1
Findings
Civil servants per capita not significant
% of budget executed over approved or % own resources invested significant but negligible
Political party in office (different from central government) not significant
Per capita social spending not significant
Table A3. Effects of Per Capita Agricultural Spending with Observed Controls, 2007 Variables (1) (2) (3) (4) (5) (6) (7) (8)
Total expenditure 0.5399** 0.5776*** 0.6113* 0.3190* 0.5842*** 0.5839*
(0.217) (0.221) (0.328) (0.178) (0.221) (0.325)
Restricted expenditure 1.7848**
(0.778)
Extended expenditure -0.0856
(0.522)
Current expenditure 0.8600
(0.964)
Investment expenditure 0.5380
(0.408)
Civil servants pc, 2006 2.0963 0.1927 -0.8149 0.6524
(11.532) (23.856) (22.781) (23.946)
Political party in office, 2006
0.0683 0.0782 0.0937 0.0792
(0.063) (0.078) (0.080) (0.078)
% budget executed over approved (2006)
-0.0003* -0.0003* -0.0003* -0.0003*
(0.000) (0.000) (0.000) (0.000)
% of investment financed by own resources (2006)
-0.0000***
(0.000)
Per capita social spending, 2006
-0.0000 -0.0001 -0.0001 -0.0002
(0.000) (0.000) (0.000) (0.000)
Regional dummies yes yes yes Yes yes yes yes yes
Population yes yes yes Yes yes yes yes yes
Observations 300 327 234 314 327 227 227 227
R2 0.214 0.22 0.237 0.27 0.217 0.225 0.235 0.225
*** p<0.01, ** p<0.05, * p<0.1
Findings
Civil servants per capita not significant
% of budget executed over approved or % own resources invested significant but negligible
Political party in office (different from central government) not significant
Per capita social spending not significant
Table A3. Effects of Per Capita Agricultural Spending with Observed Controls, 2007 Variables (1) (2) (3) (4) (5) (6) (7) (8)
Total expenditure 0.5399** 0.5776*** 0.6113* 0.3190* 0.5842*** 0.5839*
(0.217) (0.221) (0.328) (0.178) (0.221) (0.325)
Restricted expenditure 1.7848**
(0.778)
Extended expenditure -0.0856
(0.522)
Current expenditure 0.8600
(0.964)
Investment expenditure 0.5380
(0.408)
Civil servants pc, 2006 2.0963 0.1927 -0.8149 0.6524
(11.532) (23.856) (22.781) (23.946)
Political party in office, 2006
0.0683 0.0782 0.0937 0.0792
(0.063) (0.078) (0.080) (0.078)
% budget executed over approved (2006)
-0.0003* -0.0003* -0.0003* -0.0003*
(0.000) (0.000) (0.000) (0.000)
% of investment financed by own resources (2006)
-0.0000***
(0.000)
Per capita social spending, 2006
-0.0000 -0.0001 -0.0001 -0.0002
(0.000) (0.000) (0.000) (0.000)
Regional dummies yes yes yes Yes yes yes yes yes
Population yes yes yes Yes yes yes yes yes
Observations 300 327 234 314 327 227 227 227
R2 0.214 0.22 0.237 0.27 0.217 0.225 0.235 0.225
*** p<0.01, ** p<0.05, * p<0.1
Conclusions• 2 facts: large increases in agr spending and lower
vulnerability to food insecurity in Bolivia
• The link between the two facts is no so clear:• Looking at levels of spending, it seems that agr spending goes where is
most needed
• A larger effect is observed when we allow for time to elapse
• When incorporating incremental spending, the sign implies some effectiveness in reducing high vulnerability
• But its magnitude shows a very small effect when significant
Two final thoughts
• These results are in line with previous evidence of decentralization leading to increased spending and investments where needed most but with only –at best– partial success (Faguet, Inchauste)
• 2 methodological caveats:– Proper account of (desirable) endogeneity– Further refinement of Food Security categories
Distributional effects of tariff reforms in Cote d’Ivoire
(on going)
Stefania Lovo, Jose Cuesta & Hassan Zaman
Tariff reform and nutrition in Cote d’Ivoire• CdI immersed in two trade integration processes working in
opposite directions:– Interim Economic Partnership Agreement with EU: elimination of
tariffs for 80% of the EU imports
– Common External Tariff with ECOWAS: potential increase of tariffs for rice, flour, edible oil and alcoholic beverages
• Tariff reforms will affect prices for critical foodstuffs, differently across commodities and across households
• How tariff reform in C d’Ivoire might affect nutritional outcomes across socioeconomic groups?
Several “housekeeping” issues• Aggregate 115 food categories in 2008 ENV into manageable
categories 9 categories: imported rice, flour, vegetable oils, sugar, alcoholic drinks, cereals, vegetables and fruits, meats and fish, milk & dairy, other.
• Convert reported consumption units into metric units Use standard conversion factors (Smith and Subandoro 2007, USDA) and econometric techniques (using household expenditure, reported q, regional metric prices)
• Convert consumption of foodstuffs into calories and proteins Use standard tables by FAO
Empirical strategy• After conversions done,
• Estimate a QUAIDS food demand system to obtain own and cross price elasticities
• Simulation of price changes across food ‘groups’ affected by tariffs on consumption and, ultimately, nutritional intakes
• Comparison across groups
A few additional issues• No population weights in the survey
• However, rich information available to exposure to conflict and intra-household allocation
• Analyze effects by
– Poor / Non Poor:
– N/S;
– male vs female dominant hhs;
– farmers vs non farmers;
Looking forward• Relatively low nutritional effects hypothesized
– Relatively low tariffs of some critical foodstuff (for example rice) may lead to small tariff changes
– The opposite effects of two diverging trade processes may lead to small net nutritional impacts
– A first look at the sources of calories and nutrients for P and NP suggest that there are not substantive difference in their sources