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Can Higher Food Prices Help the Rural Poor?
Some Insights on Potential Impacts of Climate Change
in Central Asia
Alisher Mirzabaev
01 February, 2013
Conceptual framework
Empirical steps and Data
Results
A Brief Literature Review
I
Hertel et al. (2010): A potential rise in major global staple
prices could decrease poverty among agricultural households.
I
Mendelsohn et al. (2007): Climate has statistically significant
effect on agricultural incomes and climate change is likely to
increase poverty among agricultural households.
I
Nelson et al. (2010): Increases in staple food prices due to
climate change may have negative effects on the eradication of
child malnutrition, including in Central Asia.
2
Conceptual framework
Empirical steps and Data
Results
Research Question and Objectives
I
How the climate volatility and the related income and price
changes may affect the livelihoods of the rural poor in Central
Asia?
1. Differentiate the possible income and price impacts of climate
shocks according to different income categories of households.
2. Account for households’ potentially interlinked decision
making on production and consumption.
3
Conceptual framework
Empirical steps and Data
Results
Theoretical Framework:
Agricultural Household Model
I
Potential endogeneity of consumption, production and labor
supply decisions among agricultural households
I
Addressing the endogeneity bias through use of instrumental
variables
I
Long-term temperature variability as an instrumental variable
in this setting
I
Temperature variability has important effects on agricultural
production, however, clearly it is not caused by current levels
of consumption of households residing in that location.
4
Conceptual framework
Empirical steps and Data
Results
Empirical Steps
1. Test for separability of the agricultural household model.
2. Assuming separability, quantile regression of food consumption
by households without accounting for endogeneity
3. The non-separability is alternatively assumed and quantile
regression is run with instrumented agricultural income.
5
Conceptual framework
Empirical steps and Data
Results
Data Sources
I
Nationally representative agricultural household surveys (4
countries, N = 1600), from ICARDA-led, ADB-funded project
on climate change in Central Asia.
I
Climate variables: temperature and precipitation
I
Institutional variables: market access, NASA night-time
lighting intensity series. In addition, several proxy variables are
created to capture some institutional characteristics.
6
Conceptual framework
Empirical steps and Data
Results
NASA Night-time Lighting Intensity Dataset
Source: National Geophysical Data Center, NOAA
7
Conceptual framework
Empirical steps and Data
Results
Testing for Separability
Variables
Labor market
Goods Market
*** p<0.01, ** p<0.05, * 0.1
Non-separable
Separable
Non-separable
Separable
Dependency ratio
Females to males ratio
Age of household head
Age of household head, squared
Gender of household head
Average family size
Average wage
Distance to Markets
Night-time lights
Market fragmentation
Farm size
Number of crops grown
Constant
-0.113
-0.0407
-0.0854*
0.000650
-0.137
0.0715**
-0.0961
0.191**
0.0304***
1.167***
-0.00114
1.797***
3.083**
0.0260
0.0909
0.0415
–0.000280
0.0536
–0.00579
0.0689
–0.127**
0.0117**
– 0.0835
1.28e-05
0.792***
-1.021
–74.12
–39.33
55.73**
–0.603**
–19.31
–47.37***
–833.2***
98.41*
11.14**
– 1,434***
0.0221
309.6***
175.1
–4,092
62.66
473.3
–8.357
6,925
1,113
–8,140
1,500
518.4
18,369
358.2***
6,052***
33,447
363
1169
1194
335
Number of households
Dependant variables: Household farm labor supply and net trade in agricultural goods,respectively
I Finite mixture regression is employed to identify latent idiosyncratic
non-separability among heterogeneous households.
8
Conceptual framework
Empirical steps and Data
Results
The Separable Agricultural Household Model
Dependent variable
Daily per capita food expenses, log
Farming profits (log)
Age of household head
Age of household head, squared
Education of household head
Education of household head, squared
Gender of household head, (0–female, 1–male)
Family non-farm workers
Family on-farm workers
Livestock value (USD)
Value of total assets (log)
Market fragmentation
Cooperation
Rural development
Night-time lighting intensity
Distance to markets (log)
Number of crops grown
Subsistence farmer (0–yes, 1–no)
Vegetable price (log)
Potato price (log)
Wheat price (log)
Maize price (log)
Net agri trade position
Share of privately owned land
Farm size (log)
Constant
Quantiles
10th
30th
50th
70th
90th
0.0438*
0.0215
-0.000262
0.132
-0.0272
-0.0169
0.0286
-0.0216
4.84e-07
0.0405
0.172
0.00511
0.000112
-0.00950
-0.0933
0.0449
0.295
-0.0338
0.708***
0.0329
-0.0797
-0.310***
-0.298**
0.0198
0.0318*
0.00143
-3.53e-05
-0.137
0.0279
-0.0851
0.0910***
-0.0593***
2.65e-07
0.0404***
–0.0229
0.0248
2.95e-05
-0.00365
-0.0683
0.00136
0.416
-0.0365
1.063***
-0.0709
-0.0439
-0.348***
-0.263***
0.0198
0.0427***
0.00218
-3.03e-05
-0.230***
0.0499***
-0.0452
0.0773***
-0.0627***
1.34e-08
0.0407**
0.0318
0.0353*
2.12e-05
-0.00525
-0.0492
-0.0237
0.413**
-0.0334
1.238***
0.0181
-0.0303
-0.292***
-0.207***
0.0218*
0.0370**
-0.00509
5.17e-05
-0.146
0.0319*
-0.0587
0.0818***
-0.0578***
-3.26e-07
0.0487**
0.0259
0.0456**
-1.49e-06
-0.00167
0.00240
-0.0147
0.424
-0.0492*
0.951***
-0.213
0.0649
-0.247***
-0.0913*
0.0356**
0.0291
-0.00756
9.80e-05
-0.0903
0.0147
-0.0223
0.0620**
-0.0631***
-7.33e-07
0.0519**
0.00709
0.0567
1.15e-05
-0.00389
-0.0463
-0.00621
0.253
-0.0550
0.831***
-0.120
0.0705
-0.250***
-0.165***
0.0362***
-0.698
0.718
1.301**
0.531
1.389*
9
Conceptual framework
Empirical steps and Data
Results
The Non-Separable Agricultural Household Model
Dependent variable
Daily per capita food expenses, log
Quantiles
10th
30th
50th
70th
90th
Farming profits (log), instrumented
Age of household head
Age of household head, squared
Education of household head
Education of household head, squared
Gender of household head, (0–female, 1–male)
Family non-farm workers
Family on-farm workers
Livestock value (USD)
Value of total assets (log)
Market fragmentation
Cooperation
Rural development
Night-time lighting intensity
Distance to markets (log)
Number of crops grown
Subsistence farmer (0–yes, 1–no)
Vegetable price (log)
Potato price (log)
Wheat price (log)
Maize price (log)
Net agri trade position
Share of privately owned land
Farm size (log)
0.614***
0.0280
-0.000326
0.00494
-0.0272
0.0489
0.0528*
-0.0373**
-1.27e-06
0.0672***
–0.129
0.00798
0.000116*
-0.0133***
-0.175***
0.0376*
0.302***
-0.0318
0.753***
0.154
-0.0654
-0.307***
-0.181*
0.0131
0.413***
0.0104
-0.000127
0.0353**
0.0279
-0.0986**
0.0720***
-0.0581***
3.39e-07
0.0611***
–0.0795
0.0156*
6.87e-05*
-0.00720**
-0.113***
0.0185
0.381***
-0.0492**
0.989***
0.117
-0.0380
-0.313***
-0.201***
0.00222
0.458***
-0.00812
7.45e-05
0.0420***
0.0499***
-0.0607
0.0708***
-0.0613***
7.76e-08
0.0593***
–0.0421
0.0235
3.75e-05
-0.00642
-0.0810**
0.00539
0.394***
-0.0260
0.991***
0.0552
0.0786
-0.235***
-0.0323
0.0219*
0.553***
-0.00394
4.29e-05
0.0462**
0.0319*
-0.130
0.0756***
-0.0610***
-2.14e-07
0.0565***
– 0.215**
0.0302
2.24e-05
-0.00491
-0.0710*
0.00757
0.296**
-0.0299
0.957***
-0.0626
0.0857
-0.166***
0.0153
0.0334***
0.448***
-0.0150
0.000133
0.0275
0.0147
-0.114
0.0624**
-0.0658***
-5.57e-07
0.0690***
0.0661
0.0266
-2.37e-05
-0.00142
-0.0508
-0.0218
0.147
-0.0647**
0.747***
0.0948
0.101*
-0.178***
0.0845
0.0305**
Constant
-4.549***
-1.915***
-1.692**
-2.543**
-1.074
10
Conceptual framework
Empirical steps and Data
Results
The Non-Separable Agricultural Household Model
Dependent variable
Daily per capita food expenses, log
Quantiles
10th
30th
50th
70th
90th
Farming profits (log), instrumented
Age of household head
Age of household head, squared
Education of household head
Education of household head, squared
Gender of household head, (0–female, 1–male)
Family non-farm workers
Family on-farm workers
Livestock value (USD)
Value of total assets (log)
Market fragmentation
Cooperation
Rural development
Night-time lighting intensity
Distance to markets (log)
Number of crops grown
Subsistence farmer (0–yes, 1–no)
Vegetable price (log)
Potato price (log)
Wheat price (log)
Maize price (log)
Net agri trade position
Share of privately owned land
Farm size (log)
0.614***
0.0280
-0.000326
0.00494
-0.0272
0.0489
0.0528*
-0.0373**
-1.27e-06
0.0672***
–0.129
0.00798
0.000116*
-0.0133***
-0.175***
0.0376*
0.302***
-0.0318
0.753***
0.154
-0.0654
-0.307***
-0.181*
0.0131
0.413***
0.0104
-0.000127
0.0353**
0.0279
-0.0986**
0.0720***
-0.0581***
3.39e-07
0.0611***
–0.0795
0.0156*
6.87e-05*
-0.00720**
-0.113***
0.0185
0.381***
-0.0492**
0.989***
0.117
-0.0380
-0.313***
-0.201***
0.00222
0.458***
-0.00812
7.45e-05
0.0420***
0.0499***
-0.0607
0.0708***
-0.0613***
7.76e-08
0.0593***
–0.0421
0.0235
3.75e-05
-0.00642
-0.0810**
0.00539
0.394***
-0.0260
0.991***
0.0552
0.0786
-0.235***
-0.0323
0.0219*
0.553***
-0.00394
4.29e-05
0.0462**
0.0319*
-0.130
0.0756***
-0.0610***
-2.14e-07
0.0565***
– 0.215**
0.0302
2.24e-05
-0.00491
-0.0710*
0.00757
0.296**
-0.0299
0.957***
-0.0626
0.0857
-0.166***
0.0153
0.0334***
0.448***
-0.0150
0.000133
0.0275
0.0147
-0.114
0.0624**
-0.0658***
-5.57e-07
0.0690***
0.0661
0.0266
-2.37e-05
-0.00142
-0.0508
-0.0218
0.147
-0.0647**
0.747***
0.0948
0.101*
-0.178***
0.0845
0.0305**
Constant
-4.549***
-1.915***
-1.692**
-2.543**
-1.074
10
Conceptual framework
Empirical steps and Data
Results
Engel curve: potato share
I Following Deaton (1989) and using non-parametric kernel regressions.
11
Conceptual framework
Empirical steps and Data
Results
Engel curve: potato share
12
Conceptual framework
Empirical steps and Data
Results
Proportion of Potato Producers and Sellers
13
Conceptual framework
Empirical steps and Data
Results
Welfare effects of potato price changes
14
Conceptual framework
Empirical steps and Data
Results
Welfare effects of potato price changes
15
Conceptual framework
Empirical steps and Data
Results
Key Conclusions
I
The poorest households are more vulnerable to the impacts of
weather and climate shocks since their food security more
strongly depends on their agricultural incomes.
16