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Agricultural Price Incentives:
Towards Gender-differentiated Indicators
The Uganda case
David Laborde, Tess Lallemant (t.lallemant@cgiar.org)
MTID, International Food Policy Research Institute
Amsterdam | December 5th 2017
Research Question
 Have policy driven price distortions differentiated impacts between men
and women farmers? Ex-ante vs Ex-post consequences?
 Issue not addressed in existing literature, especially to develop cross-
country and intertemporal estimates
Sectoral
policy
distortions
database
Farm
production
data with
gender
module
Gender
specific
Distortions
Nominal Rate of Protection (NRP)
 Focus on price differences between domestic farm gate prices and world prices
 Expressed as a percentage of undistorted prices
 Compare like and like: adjustment for quality, processing and transportation
costs
Price Received
by Farmers
Policy impact
on prices
Price without
policies
X100 = NRP in %
2 Potential Questions
 Are men and women facing
different policy distortions for the
same product?
oContrasted literature on
differentiated prices, mark-up
and cost
oBut even with different costs,
NRP (policy distortions) could be
the same
 Are men and women specialized in
different products?
oExisting literature: yes (and our
data show it!)
oFarm and Trade policies vary a lot
from product to product
-60
-40
-20
0
20
40
60
80
100
Cassava Wheat Sugar Rice Cotton Maize Coffee Tea Bovine
Meat
Milk
NRP(%)
NRP by Product - Uganda 2009
Who controls the production?
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Share of Value of Production by Manager
WOMEN MEN
Cash CropsStaple Crops
Gendered NRP
-50
-40
-30
-20
-10
0
10
20
30
2005 2006 2007 2008 2009 2010 2011 2012 2013
NRP(%)
Women Control Men Control All
Policy Conclusions for Uganda
 Key role of the livestock sector
 Differentiated behavior among crops: staple vs cash crops
 Ex-post impacts of policies are not gender neutral
Policy reform will not be gender neutral!
Fertilizer use by control of outputs
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Women Control Men Control
Gender and Price Distortions
Farm Gate Price
Price at Point of
Competition
World Price
Transportation and
trade costs
Processing Margins
Transportation and
trade costs
Quality adjustments
Processing
Product A
e.g. Corn
Farm Gate Price
Price at Point of
Competition
World Price
Transportation and
trade costs
Processing Margins
Transportation and
trade costs
Quality adjustments
Processing
Product B
e.g. Milk
Gender
specific costs
and prices
Gender
specific
specialization

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Agricultural Price Incentives: Towards Gender-differentiated Indicators

  • 1. Agricultural Price Incentives: Towards Gender-differentiated Indicators The Uganda case David Laborde, Tess Lallemant (t.lallemant@cgiar.org) MTID, International Food Policy Research Institute Amsterdam | December 5th 2017
  • 2. Research Question  Have policy driven price distortions differentiated impacts between men and women farmers? Ex-ante vs Ex-post consequences?  Issue not addressed in existing literature, especially to develop cross- country and intertemporal estimates Sectoral policy distortions database Farm production data with gender module Gender specific Distortions
  • 3. Nominal Rate of Protection (NRP)  Focus on price differences between domestic farm gate prices and world prices  Expressed as a percentage of undistorted prices  Compare like and like: adjustment for quality, processing and transportation costs Price Received by Farmers Policy impact on prices Price without policies X100 = NRP in %
  • 4. 2 Potential Questions  Are men and women facing different policy distortions for the same product? oContrasted literature on differentiated prices, mark-up and cost oBut even with different costs, NRP (policy distortions) could be the same  Are men and women specialized in different products? oExisting literature: yes (and our data show it!) oFarm and Trade policies vary a lot from product to product -60 -40 -20 0 20 40 60 80 100 Cassava Wheat Sugar Rice Cotton Maize Coffee Tea Bovine Meat Milk NRP(%) NRP by Product - Uganda 2009
  • 5. Who controls the production? 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Share of Value of Production by Manager WOMEN MEN Cash CropsStaple Crops
  • 6. Gendered NRP -50 -40 -30 -20 -10 0 10 20 30 2005 2006 2007 2008 2009 2010 2011 2012 2013 NRP(%) Women Control Men Control All
  • 7. Policy Conclusions for Uganda  Key role of the livestock sector  Differentiated behavior among crops: staple vs cash crops  Ex-post impacts of policies are not gender neutral Policy reform will not be gender neutral!
  • 8. Fertilizer use by control of outputs 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Women Control Men Control
  • 9. Gender and Price Distortions Farm Gate Price Price at Point of Competition World Price Transportation and trade costs Processing Margins Transportation and trade costs Quality adjustments Processing Product A e.g. Corn Farm Gate Price Price at Point of Competition World Price Transportation and trade costs Processing Margins Transportation and trade costs Quality adjustments Processing Product B e.g. Milk Gender specific costs and prices Gender specific specialization

Editor's Notes

  1. LSMS questionaire – using on different countries.
  2. Negative NRP tax to farmers, while positive is protection
  3. Are men and women facing different policy distortions for the same product? Contrasted literature on differentiated prices, mark-up and cost But even with different costs, NRP (policy distortions) could be the same: Second order issue while looking at NRP Are men and women specialized in different products? Existing literature: yes (and our data show it!) Farm and Trade policies vary a lot from product to product [ADD A SMALL GRAPH VBAR avec NRP pour 1 annee] First order issue for policy analysis, and the goal of this paper
  4. Price did not follow the world price. Restrictions in commerce. Sanitation, esp in official statistifcs.
  5. Political economomy that causes these different NRPs because in certain cases it is a gender dimention that is explicit. Protections based on regions ethnic group, or dif livestock between crops etc. Gender not part of this literature. How these price distortions policies are formed. Is there a gender dimention behind it?