Dynamic Implications of Production Shocks and Policy on Livestock Markets
and Household Welfare:A Sectoral and Economy-Wide Analysis
IFPRI-ILRI-EDRI Livestock InitiativeInformal seminar, April 20, 2011
Outline
• This seminar meant to introduce the project, present some preliminary results, get early feedback
1. Introduction2. Market analysis3. Demand analysis4. Discussion
Introduction
• A lot of micro and value chain analysis of livestock in Ethiopia, but little macro-analysis
• Macro-analysis obviously important for several reasons1. Livestock “revolutions” often thought to be demand-
led, not supply led (Delgado)2. In Ethiopia, macro issues important: some dynamism
in trade, lots of dynamism in prices related to inflation, seasonality, shocks, etc.
3. Micro work on improving supply can be “tested” at macro level; e.g. macro impact of improved technologies
Introduction
• So this study is multifaceted. At the moment we have completed a demand analysis, started a supply/price analysis, and gradually starting CGE and GIS analyses.
• Today we’ll mostly talk about supply/price analysis and demand analysis
Need for better macro-understanding
• A lot of micro and value chain analysis of livestock in Ethiopia, but little macro-analysis
• Macro-analysis obviously important for several reasons1. Livestock “revolutions” often thought to be demand-
led, not supply led (Delgado)2. In Ethiopia, macro issues important: some dynamism
in trade, lots of dynamism in prices related to inflation, seasonality, shocks, etc.
3. Micro work on improving supply can be “tested” at macro level; e.g. macro impact of improved technologies
Macro-picture and link with policy
• Construct a macro-picture of the livestock sector
• Understand more about long term constraints and how policy can foster development of livestock sector
• Understand more about shocks and potential for policy response
Figure x. Overview of the research components and their linkages with each other
Household demand analysis
of livestock
General equilibrium
model
Analysis of livestock prices & values chains
GIS (spatial) analysis of
livestock sector
Integration of markets; effect of shocks on prices; modeling scenarios
Patterns of production and market
access
Spatial data on rainfall & forage shocks
Elasticities of own price, cross-price & income demand
Partial equilibrium model of livestock
dynamicsImproved herd dynamics
Market analysis – supply constraints
• Goal here is to understand how the various livestock markets and production systems work and don’t work, and how prices are formed.
• In terms of understanding of production and trade, we are reviewing the existing literature, including a lot of ILRI work (e.g. IPMS)
• Important for understanding price formation, but also for modelling productivity shocks
• We see differences by sub-sector
An attempt to be diagnosticBeef Shoats Poultry Dairy Comments
Feed XXX XXX X XXX Regional & seasonal variation based on farming systems
Disease XX XX XXX X Particualrly acute for chickens, but a problem for all sub-sector
Marketing, processing, etc
XX X X XXX Dairy perishable, so market access critical; export constraints for beef & shoats
Breed quality XX XX XX XX Cross-breeding possible over medium/long run
Others: labor, credit, extension . . .
X X X X Difficult to judge
Market analysis – supply constraints
• If we roughly agree (?), what are the implications?
• Supply can be expanded with improved health care, breeding, marketing, etc, but feed constraints provide a key linkage to grain sector
• CGE could be useful here; e.g. model the effect of land-intensive vs land-extensive growth in crop production
Market analysis - prices
• How are livestock prices formed?• Important for understanding production
dynamics, supply response, impacts on consumers, etc
• Two issues of interest1.Integration of markets – Hypothesis – markets
are poorly integrated because of high transport costs. There is also product differentiation (different breeds).
Price formation situation• 2. Price formation, including integration with
international markets• Country has seen sharp rise in meat prices in recent
months. • Hard to see this as domestic demand story since price
rise is too big• If was a general inflation story then other prices should
rise (e.g. staples), but not really happening either• Hypothesis: sharp rise in international meat prices is
being transmitted into Ethiopian markets• So what is the trade story?
Changing composition of livestock exports – fall in hides, big rise in live bovine
Big rise in live animal export values, almost certainly related to increase international prices
But note the changing composition of trade routes and end markets: Djibouti down and Somalia and Sudan up (formal trade
replacing informal trade?). UAE way, way up!!
Price formation
Research Objectives • Assess if and how regional and central livestock markets are
integrated and• Identify factors that affect livestock pricing, study their effect on
livestock prices, and possibly their effect on trade routesProposed Methods of study:1. Integration of markets is to be studied using threshold
autoregression (TAR) model and2. Gathering data of factors related with price formation and
econometric model yet to be determined.
Objectives and a Brief Description of Proposed Study…contd.
Basic idea behind TAR:– To investigate if and how prices markets co-move and – how price shocks are transmitted
• Differs from simple correlation as it acknowledges there exist thresholds created by transaction costs,
Simple representation: , whereand is a white-noise error term. where c is the threshold value.With: when holds
t t-1P P t tP ( )i j
t tP P
t(1)
t-1
(2)t-1
| P |
| P |
if c
if c
t-1| P | c (1) 1
Data Description
• Market integration: – CSA price data spanning July 2001-January 2011, for 8 categories of
animals and 119 markets.
Data Description… contd.
Data Description… contd.
• On factors affecting price formation monthly data collected on:– International livestock, meat, and diary prices and indices,– Livestock and meat and meat products exports,– World crude petroleum and local exchange rate.
• Nominal livestock prices have strong correlation with all variables.
Data Description… contd.
Data Description… contd.
Observations:
• Some markets seem to be integrated with local markets others with neighboring countries.
• Local livestock prices seem to co-move with international livestock, meat, and dairy prices,
• Other factors also affect the price formation in local markets.
Comments on content so far welcome, on relevant data and data sources are even more welcome.
THANK YOU
• Nationally representative demand elasticity estimates for livestock products in Ethiopia are unavailable.
• Informs policy design and implementation, welfare analysis and CGE analysis
Introduction: Why Demand Elasticities?
• Livestock products account for 4.4% of total household expenditure and 8.7% of food expenditure.• Rural areas: 4.3% of total expenditure and 8% of food expenditure; Urban
areas: 5.2% of total expenditure and 12.7% of food expenditure.
Livestock Expenditure Share of Livestock Products (%)
• Source: Authors’ calculation using HICES (2004/05)
Consumption Patterns
Beef Mutton & goat meat
Chicken Other meat (camel, pork,
crocodile...)
Fish & fish
products
Dairy products
Egg Honey
National 40.9 8.3 7.3 0.5 0.4 39.5 2.6 0.8Urban 55.8 11.7 9.3 0.5 0.3 17.4 4.7 0.7Rural 37.9 7.6 6.9 0.5 0.5 44.1 2.2 0.9
Exp. QuintilesQ1 43.0 7.4 7.8 0.5 0.5 38.5 2.0 0.7Q2 39.9 7.5 7.1 0.5 0.4 42.1 2.0 0.8Q3 41.0 7.2 7.4 0.5 0.4 41.0 2.2 0.7Q4 40.5 8.8 7.4 0.4 0.5 39.2 2.7 0.9Q5 40.4 10.3 6.8 0.4 0.4 37.1 4.0 1.0
• Expenditure on meat represents the largest expenditure group followed by dairy products
• Shares of meat, chicken, egg are higher in urban areas while that of dairy products is higher in rural areas
• The Expenditure share of beef & dairy products falls with income/ expenditure.
• Conversely, the share of mutton & goat meat and egg appear to rise with income.
• The expenditure shares of fish & fish products, other meat are negligible.
Consumption Patterns (cont’d)
Per Capita Quantity Consumed (kg)
Source: Authors’ calculation using HICES (2004/05)
• Annual per capita meat consumption in Ethiopia is very low. – The African and East African average for the same period (2004) stand at
about 15 kg and 10 kg respectively (Ethiopian is 8 kg) (FAO, 2010 ).
Consumption Patterns (cont’d)
Beef Mutton & goat meat
Chicken Other meat (camel, pork,
crocodile...)
Fish & fish
products
Dairy products
Egg Honey Total Meat
National 2.6 1.3 0.6 0.1 0.1 13.2 0.2 0.1 3.9Urban 5.8 2.7 1.4 0.1 0.1 7.2 0.5 0.1 8.5Rural 2.0 1.0 0.5 0.1 0.1 14.4 0.1 0.1 3.0
Exp. QuintilesQ1 1.3 0.6 0.3 0.1 0.1 7.7 0.1 0.1 1.9Q2 1.7 0.8 0.4 0.1 0.1 11.6 0.1 0.1 2.5Q3 2.2 1.0 0.5 0.1 0.1 13.0 0.1 0.1 3.2Q4 2.9 1.4 0.7 0.1 0.1 15.6 0.2 0.1 4.3Q5 4.6 2.4 1.2 0.1 0.1 17.2 0.5 0.2 7.0
– Individuals in urban areas are likely to consume about three times as much as their rural counterparts.
– People in the richest quintile consume over three times more than those in the poorest quintile.
• Urban areas also have substantially higher consumption of chicken and eggs
• Dairy products represent the biggest consumption group.– The quantity consumed is considerably higher in rural areas
than in urban areas– Though its share appears to fall with income, the level
(quantity) of consumption rather rises with income.
Consumption Patterns (cont’d)
• Per capita calorie intake
Source: Authors’ calculation using HICES (2004/05)
• Livestock products contribute a very small share of daily calorie intake in Ethiopia (only 2.4%).– It appears urban households get more energy from livestock products than rural ones
(shares – 4.2% Vs 2.1%)
Consumption Patterns (cont’d)
Beef Mutton & goat meat
Chicken Other meat (camel, pork,
crocodile...)
Fish & fish
products
Dairy products
Egg Honey Total
National 14.5 7.4 3.1 0.5 0.4 27.6 1.0 0.7 55.2Urban 33.8 16.7 7.4 0.6 0.3 20.0 3.1 1.0 82.9Rural 10.6 5.6 2.2 0.4 0.4 29.1 0.6 0.6 49.5
Exp. QuintilesQ1 7.1 3.3 1.4 0.4 0.1 14.3 0.2 0.3 27.1Q2 9.1 4.8 1.8 0.5 0.5 24.9 0.3 0.5 42.4Q3 11.8 5.8 2.4 0.4 0.1 24.2 0.6 0.5 45.8Q4 15.8 7.8 3.2 0.5 0.5 33.0 0.8 0.6 62.2Q5 27.2 14.6 6.1 0.5 0.4 39.2 2.7 1.3 92.0
– People in the fifth exp. quintile get three times more calorie than those in the first quintile from livestock products.
• For all livestock products, per capita calorie intake rises with income.
• Among livestock products, dairy products are the most important source of calorie (50%) followed by meat.– Rural households get more calories from dairy products than
urban ones (share - 59% Vs 24%). – The richest 20% percent of households get three times more calorie
from dairy products than their poorest counterparts.
• People in urban areas get three times more calorie from meat (beef, mutton & goat meat) than those in rural areas.– People in the richest quintile get four times more calorie from
meat than their those in the poorest quintile.
Consumption Patterns (cont’d)
• Data
Nationally representative survey datasets for 2004/05 – Household Income, Consumption, and Expenditure Survey (HICES) and Welfare Monitoring Survey (WMS)
No price data, unit values proved to be problematic. So external price data from CSA’s price survey used.
Caveat
o The data used in this study excludes all zones of the Gambella region, and three predominantly non-sedentary zones of Afar region and six such zones of Somali region
Estimating elasticities - Methodology – Data
Expenditure Elasticities
Standard Errors in Brackets; ***,**,* are significance level at 1%, 5% & 10%
• All livestock products have positive and significant expenditure elasticity– Normal goods!
• The expenditure elasticity of beef is close to unity and is the highest, while that of dairy products is the lowest.– Beef appears superior to all other livestock products.
Results
Total Urban RuralBeef 0.939*** 0.896*** 0.985***
[0.0178] [0.0198] [0.0423]Mutton & Goat meat 0.671*** 0.304*** 0.917***
[0.1268] [0.1138] [0.1361]Other meat & animal products 0.538*** 0.519*** 1.045***
[0.0455] [0.0551] [0.0757]Dairy products 0.420*** 0.389*** 0.479***
[0.0148] [0.0136] [0.0061]
• Expenditure elasticities appear to be higher in rural areas than in urban areas.– The gap between the two sets of elasticities is particularly high
for beef, mutton & goat meat, and other meat & animal products• Urban areas have higher budget shares for these
commodities
– Dairy products: reluctance to change consumption habit…
Results (cont’d)
Results (cont’d) –Compensated own-Price and cross-price Elasticities
BeefMutton & Goat
meat
Other meat & animal
products Dairy products
Beef
Total-0.733*** 0.391*** 0.083*** 0.259***[0.0233] [0.0193] [0.0073] [0.0105]
Urban-0.665*** 0.382*** 0.136*** 0.147***[0.0235] [0.0176] [0.0071] [0.0087]
Rural-0.793*** 0.378*** 0.031 0.386***[0.0786] [0.0577] [0.0266] [0.0331]
Mutton & Goat meat
Total1.554*** -1.465*** 0.069 -0.158*[0.1003] [0.1144] [0.0426] [0.0846]
Urban1.889*** -1.882*** 0.184*** -0.192***[0.1103] [0.1144] [0.0378] [0.0613]
Rural2.822*** -2.008*** -0.292 -0.523**[0.6603] [0.4221] [0.2907] [0.2565]
Other meat & animal products
Total0.403*** 0.395*** -0.996*** 0.194***[0.0285] [0.0337] [0.0229] [0.0336]
Urban0.71*** 0.181*** -0.988*** 0.071**[0.0476] [0.0386] [0.0228] [0.0289]
Rural-0.056 0.289 -1.039*** 0.806***[0.233] [0.1926] [0.0698] [0.0989]
Dairy products
Total0.405*** -0.249*** 0.28*** -0.669***[0.0244] [0.0344] [0.0152] [0.0344]
Urban0.06 0.062 0.304*** -0.523**
[0.098] [0.0868] [0.0289] [0.2613]
Rural0.134 -0.009 0.247*** -0.151**
[0.1256] [0.0618] [0.0577] [0.0746]
• All own price effects are negative and significant.– Mutton/goat meat has the highest own price elasticity
• For beef, mutton/goat meat, and ‘other meat’, rural areas have higher own elasticities, while the opposite is true for dairy products.– Remember the budget shares?
• There is a strong substitution relationship between beef and mutton/goat meat.
• Dairy products are substitutes for beef and other meat & animal products, but complements for mutton & goat meat.– Effect is higher in rural areas.
Results (cont’d)
• Nationally representative demand elasticity estimates for livestock products in Ethiopia are unavailable.
• Informs policy design and implementation.
• Useful for Welfare analysis
• Useful for CGE analysis
Introduction: Why Demand Elasticities?
• Livestock products account for 4.4% of total household expenditure and 8.7% of food expenditure.• Rural areas: 4.3% of total expenditure and 8% of food expenditure; Urban
areas: 5.2% of total expenditure and 12.7% of food expenditure.
Livestock Expenditure Share of Livestock Products (%)
• Source: Authors’ calculation using HICES (2004/05)
Consumption Patterns
Beef Mutton & goat meat
Chicken Other meat (camel, pork,
crocodile...)
Fish & fish
products
Dairy products
Egg Honey
National 40.9 8.3 7.3 0.5 0.4 39.5 2.6 0.8Urban 55.8 11.7 9.3 0.5 0.3 17.4 4.7 0.7Rural 37.9 7.6 6.9 0.5 0.5 44.1 2.2 0.9
Exp. QuintilesQ1 43.0 7.4 7.8 0.5 0.5 38.5 2.0 0.7Q2 39.9 7.5 7.1 0.5 0.4 42.1 2.0 0.8Q3 41.0 7.2 7.4 0.5 0.4 41.0 2.2 0.7Q4 40.5 8.8 7.4 0.4 0.5 39.2 2.7 0.9Q5 40.4 10.3 6.8 0.4 0.4 37.1 4.0 1.0
• Expenditure on meat represents the largest expenditure group followed by dairy products
• Shares of meat, chicken, egg are higher in urban areas while that of dairy products is higher in rural areas
• The Expenditure share of beef & dairy products falls with income/ expenditure.
• Conversely, the share of mutton & goat meat and egg appear to rise with income.
• The expenditure shares of fish & fish products, other meat are negligible.
• Fish - The landlocked status of Ethiopia and/or lack of culture of fish consumption could be the reason.
Consumption Patterns (cont’d)
Per Capita Quantity Consumed (kg)
Source: Authors’ calculation using HICES (2004/05)
• Annual per capita meat consumption in Ethiopia is very low. – The African and East African average for the same period (2004) stand at
about 15 kg and 10 kg respectively (Ethiopian is 8 kg) (FAO, 2010 ).
Consumption Patterns (cont’d)
Beef Mutton & goat meat
Chicken Other meat (camel, pork,
crocodile...)
Fish & fish
products
Dairy products
Egg Honey Total Meat
National 3.1 1.4 0.7 0.1 0.1 16.7 0.2 0.1 4.6Urban 6.8 3.1 1.6 0.1 0.0 8.5 0.5 0.1 9.9Rural 2.4 1.1 0.5 0.1 0.1 18.4 0.1 0.1 3.5
Exp. QuintilesQ1 1.6 0.7 0.3 0.0 0.0 10.2 0.0 0.0 2.3Q2 2.1 1.0 0.4 0.1 0.1 15.2 0.1 0.1 3.1Q3 2.7 1.2 0.6 0.1 0.0 16.9 0.1 0.1 3.9Q4 3.5 1.6 0.7 0.1 0.1 19.9 0.2 0.1 5.0Q5 5.3 2.7 1.3 0.1 0.1 20.6 0.5 0.1 8.0
– Individuals in urban areas are likely to consume about three times as much as their rural counterparts.
– People in the richest quintile consume three times more than those in the poorest quintile.
• Urban areas also have substantially higher consumption of chicken, egg
• Dairy products represent the biggest consumption group.– The quantity consumed is considerably higher in rural areas than in
areas– Though its share appears to fall with income, the level (quantity) of
consumption rather rises with income.
Consumption Patterns (cont’d)
Per capita calorie intake
Source: Authors’ calculation using HICES (2004/05)
• Livestock products contribute a very small share of daily calorie intake in Ethiopia (only 2.4%).– It appears urban households get more energy from livestock products than rural ones
(shares – 4.2% Vs 2.1%)
Consumption Patterns (cont’d)
Beef Mutton & goat meat
Chicken Other meat (camel, pork,
crocodile...)
Fish & fish
products
Dairy products
Egg Honey Total
National 17.5 8.8 3.6 0.5 0.4 34.6 1.1 0.7 67.3Urban 39.2 19.3 8.6 0.7 0.3 23.1 3.5 1.2 95.8Rural 13.1 6.7 2.6 0.5 0.4 36.9 0.6 0.7 61.4
Exp. QuintilesQ1 9.0 4.0 1.6 0.4 0.1 18.9 0.3 0.3 34.7Q2 11.4 6.0 2.2 0.5 0.6 32.3 0.4 0.7 53.9Q3 14.8 7.2 2.9 0.5 0.1 31.7 0.6 0.5 58.3Q4 19.2 9.3 3.8 0.5 0.7 41.4 1.0 0.7 76.7Q5 31.3 16.6 7.1 0.6 0.4 46.1 3.0 1.4 106.6
– People in the fifth exp. quintile get three times more calorie than those in the first quintile from livestock products.
• For all livestock products, per capita calorie intake rises with income.
• Among livestock products, dairy products are the most important source of calorie (51%) followed by meat.– Rural households get more calories from dairy products than urban
ones (share - 60% Vs 24%). – The richest 20% percent of households get twice more calorie from
dairy products than their poorest counterparts.
• People in urban areas get three times more calorie from meat (beef, mutton & goat meat) than those in rural areas.– People in the richest quintile get about four times more calorie from
meat than their those in the poorest quintile.
Consumption Patterns (cont’d)
• Model - the QU-AIDS (Banks, Blundell and Lewbel (1997)).
• Restrictions
Methodology - Model
2
1
ln ln ln (1)( ) ( ) ( )
nh i h
ih i ij j ij
x xw p
a b al
a g b=
ì üé ù é ùï ïï ïê ú ê ú= + + + í ýê ú ê úï ïë û ë ûï ïî þå p p p
01 1 1
1ln ( ) ln ln ln (2)
2
n n n
k k kj k jk k j
a p p pa a g= = =
= + +å å åp
1
( ) (3)k
n
kk
b pb
=
=Õp
1 1 1
1; 0; 0; 0 (4)
0 (5)
n n n
i ij i ii i i i
ijj
ij ji
a g b l
g
g g
= = =
= = = =
=
=
å å å å
å (6)
• Zero expenditures/consumption
• Problem: Such censoring can produce biased and inconsistent parameter estimates;
• Solution: two-step estimation (Shonkwiler and Yen (1999)):
• Expenditure endogeneity
Use the residual from (8) with in the shares regression
Methodology - Issues
( ) ( , ) ( ) (7)ih ih i ih i i ih i ihw f edf¢ ¢=F + +z θ x μ z θ
1 1
0 1 2 3 4ln ln (8)R Z
h ij j k hk l hl r r z z hj k l r z
x p N a D D ea a a a a a- -
= + + + + + +å å å å å
ln hx
• Data
Nationally representative survey datasets for 2004/05 – Household Income, Consumption, and Expenditure Survey (HICES) and Welfare Monitoring Survey (WMS)
No price data, unit values proved to be problematic. So external price data from CSA’s price survey used.
Caveato The data used in this study excludes all zones of the Gambella region,
and three predominantly non-sedentary zones of Afar region and six such zones of Somali region
• Estimated Budget Share Equations
Methodology – Data; Specification
2
1
( ) ln ln ln + ( ) (9)( ) ( ) ( )
nh i h
i iih ih i ij j i i h i ih ihj
x xw p e
a b al
a g b t df x=
ì üï ïé ùæ ö æ öï ïï ï÷ ÷ç çê ú¢ ¢=F + + + + +÷ ÷í ýç ç÷ ÷ê ú÷ ÷ç çï ïè ø è øï ïë ûï ïî þåz θ z θ
p p p)$ $
Expenditure Elasticities
Standard Errors in Brackets; ***,**,* are significance level at 1%, 5% & 10%
• All livestock products have positive and significant expenditure elasticity– Normal goods!
• The expenditure elasticity of beef is close to unity and is the highest, while that of dairy products is the lowest.– Beef appears superior to all other livestock products.
Results
Total Urban RuralBeef 0.939*** 0.896*** 0.985***
[0.0178] [0.0198] [0.0423]Mutton & Goat meat 0.671*** 0.304*** 0.917***
[0.1268] [0.1138] [0.1361]Other meat & animal products 0.538*** 0.519*** 1.045***
[0.0455] [0.0551] [0.0757]Dairy products 0.420*** 0.389*** 0.479***
[0.0148] [0.0136] [0.0061]
• Expenditure elasticities appear to be higher in rural areas than in urban areas.– The gap between the two sets of elasticities is particularly high for beef,
mutton & goat meat, and other meat & animal products• Urban areas have higher budget shares for these commodities
– Dairy products: reluctance to change consumption habit…
Results (cont’d)
Compensated Price Elasticities
Standard Errors in Brackets; ***,**,* are significance level at 1%, 5% & 10%
Results (cont’d)
BeefMutton & Goat
meat
Other meat & animal
products Dairy products
Beef
Total-0.733*** 0.391*** 0.083*** 0.259***[0.0233] [0.0193] [0.0073] [0.0105]
Urban-0.665*** 0.382*** 0.136*** 0.147***[0.0235] [0.0176] [0.0071] [0.0087]
Rural-0.793*** 0.378*** 0.031 0.386***[0.0786] [0.0577] [0.0266] [0.0331]
Mutton & Goat meat
Total1.554*** -1.465*** 0.069 -0.158*[0.1003] [0.1144] [0.0426] [0.0846]
Urban1.889*** -1.882*** 0.184*** -0.192***[0.1103] [0.1144] [0.0378] [0.0613]
Rural2.822*** -2.008*** -0.292 -0.523**[0.6603] [0.4221] [0.2907] [0.2565]
Other meat & animal products
Total0.403*** 0.395*** -0.996*** 0.194***[0.0285] [0.0337] [0.0229] [0.0336]
Urban0.71*** 0.181*** -0.988*** 0.071**[0.0476] [0.0386] [0.0228] [0.0289]
Rural-0.056 0.289 -1.039*** 0.806***[0.233] [0.1926] [0.0698] [0.0989]
Dairy products
Total0.405*** -0.249*** 0.28*** -0.669***[0.0244] [0.0344] [0.0152] [0.0344]
Urban0.06 0.062 0.304*** -0.523**
[0.098] [0.0868] [0.0289] [0.2613]
Rural0.134 -0.009 0.247*** -0.151**
[0.1256] [0.0618] [0.0577] [0.0746]
• All own price effects are negative and significant.– Mutton/goat meat has the highest own price elasticity
• For beef, mutton/goat meat, and ‘other meat’, rural areas have higher own elasticities, while the opposite is true for dairy products.– Remember the budget shares?
• There is a strong substitution relationship between beef and mutton/goat meat.
• Dairy products are substitutes for beef and other meat & animal products, but complements for mutton & goat meat.– Effect is higher in rural areas.
Results (cont’d)