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Does adoption of improved rice
varieties impact farmers’ economic
efficiency? A case study of NERICA in
West Africa
Aminou Arouna and Aliou Diagne
Africa Rice Center (AfricaRice)
Outline
1. Introduction
2. Objectives
3. Data analysis methods
4. Data collection
5. Results
6. Conclusion and policy recommendation
Introduction
• Rice is the most important food crop of developing
world and staple food of 3.5 billion people
• In Africa, rice consumption is increasing at a rate of
5.7% (1980 to 2009)
• Local production of the continent is largely
insufficient to meet the demand
• The gap has increased over time, from 1.2 MT in
1960 to 8.3 MT in 2012
Introduction
Introduction
• New technologies (e.g. NERICA) have received
particular attention as a means to close the gap
• Recent estimates showed that land productivity of
rice has increased by 30% in Sub-Saharan Africa
• Closing gap between demand and local production
cannot be reach only by increasing the land
productivity but by increasing overall productivity
Introduction
• Does new technologies varieties improve the
efficiency efficiencies of rice farmers?
• To what extent rice production can be improved
under existing new technologies?
Objectives
• This study seeks to assess the impact of NERICA
adoption on technical, allocative and economic
efficiencies of rice farmers in West Africa.
• Specifically, the study aims to:
1. Estimate technical, allocative and economic
efficiencies of adopters and non-adopters
2. Analyze the determinants of technical, allocative
and economic efficiencies
3. Quantify the impact of NERICA adoption on
technical, allocative and economic efficiencies
Data analysis methods
 Efficiency analysis
• Use of stochastic
frontier approach
Weather disturbances and
heterogeneous
environmental factors like
soil quality and irrigation
access

• Double-log production
frontier is estimated for
both production and
cost functions
Data analysis methods
 Impact assessment

• Impact = outcome with the intervention
compared to what it would have been in the
absence of the intervention
Data analysis methods
 Impact assessment
Adopters

Better off

True impact

Y1

Y0
Y1

Naïve impact estimate
Selection bias

Outcome
Worse off

Y0
Non-adopters

Time

True Impact = Y1 – Y0 under participation
Naïve impact estimate = Y1 – Y0 (Difference of observed outcomes)
Selection bias = Y0 – Y0 > 0 Overestimation of benefits
10
Data analysis methods
Total unrealized potential impact at time t1

Total unrealized potential impact at time t2

Total Impact

Total potential impact
(assumed constant)

Total actual impact at time t1

t1

t2
Time
Total actual impact at time t2
Data analysis methods
Data analysis methods
Data collection
• Ex-post survey impact assessment
survey of the multinational NERICA
rice dissemination project in 2010
• Stratified random sampling
• Data collected from 3,096 riceproducing households in 250
villages in 7 west african countries
(Benin, Gambia, Ghana, Guinea,
Mali, Nigeria and Sierra Leone)
• Data collected concerned:
socioeconomic characteristic, rice
input and output, farm and nonfarm
activities, etc.
Results
• Gap efficiencies
Results
• Efficiencies for adopters and nonadopters
Results
• Determinants of farmers’ efficiencies
Technical
efficiency

Allocative
efficiency

Economic
efficiency

Coeff

Std. Err

Coeff

Std. Err

Coeff

Std. Err

Agriculture

-0.7988***

0.1923

-0.0062

0.0285

-0.3403**

0.1702

Education

0.0734

0.0453

-0.0064

0.0076

0.1115**

0.0429

Extension

-0.1259**

0.0585

0.0151

0.0093

-0.1296**

0.0508

-0.0010

0.0017

-0.0005*

0.0002

0.0001

0.0015

Age
Results
• Impact of adoption of NERICA varieties efficiencies
Technical
Efficiency

Allocative
Efficiency

Economic
Efficiency

LATE

0.3568***

0.0048

0.2344***

LATE1

0.4306**

0.0031

0.2674***

LATE0

0.0549

0.0125

0.1112

PSB

0.0738*

-0.0017

0.0329

-0.0272**

-0.0026**

-0.0511***

F(5, 694)=8.93***

F(5, 565)=18.37***

LATE

Observed
Diffmo
Wald test

F(5, 1066)=8.07***
Conclusion and implications
• Adoption of NERICA increases technical efficiency
for potential and actual adopters
• The impact on economic efficient is smaller but also
significant on potential and actual adopters
• High inefficiency among both adopters and nonadopters of NERICA varieties
• Providing farmers with improved varieties should be
accompanied by training on both good agricultural
practices and farm manage tools
Thank you!
Merci!

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Th4_Does adoption of improved rice varieties impact farmers’ economic efficiency?

  • 1. Does adoption of improved rice varieties impact farmers’ economic efficiency? A case study of NERICA in West Africa Aminou Arouna and Aliou Diagne Africa Rice Center (AfricaRice)
  • 2. Outline 1. Introduction 2. Objectives 3. Data analysis methods 4. Data collection 5. Results 6. Conclusion and policy recommendation
  • 3. Introduction • Rice is the most important food crop of developing world and staple food of 3.5 billion people • In Africa, rice consumption is increasing at a rate of 5.7% (1980 to 2009) • Local production of the continent is largely insufficient to meet the demand • The gap has increased over time, from 1.2 MT in 1960 to 8.3 MT in 2012
  • 5. Introduction • New technologies (e.g. NERICA) have received particular attention as a means to close the gap • Recent estimates showed that land productivity of rice has increased by 30% in Sub-Saharan Africa • Closing gap between demand and local production cannot be reach only by increasing the land productivity but by increasing overall productivity
  • 6. Introduction • Does new technologies varieties improve the efficiency efficiencies of rice farmers? • To what extent rice production can be improved under existing new technologies?
  • 7. Objectives • This study seeks to assess the impact of NERICA adoption on technical, allocative and economic efficiencies of rice farmers in West Africa. • Specifically, the study aims to: 1. Estimate technical, allocative and economic efficiencies of adopters and non-adopters 2. Analyze the determinants of technical, allocative and economic efficiencies 3. Quantify the impact of NERICA adoption on technical, allocative and economic efficiencies
  • 8. Data analysis methods  Efficiency analysis • Use of stochastic frontier approach Weather disturbances and heterogeneous environmental factors like soil quality and irrigation access • Double-log production frontier is estimated for both production and cost functions
  • 9. Data analysis methods  Impact assessment • Impact = outcome with the intervention compared to what it would have been in the absence of the intervention
  • 10. Data analysis methods  Impact assessment Adopters Better off True impact Y1 Y0 Y1 Naïve impact estimate Selection bias Outcome Worse off Y0 Non-adopters Time True Impact = Y1 – Y0 under participation Naïve impact estimate = Y1 – Y0 (Difference of observed outcomes) Selection bias = Y0 – Y0 > 0 Overestimation of benefits 10
  • 11. Data analysis methods Total unrealized potential impact at time t1 Total unrealized potential impact at time t2 Total Impact Total potential impact (assumed constant) Total actual impact at time t1 t1 t2 Time Total actual impact at time t2
  • 14. Data collection • Ex-post survey impact assessment survey of the multinational NERICA rice dissemination project in 2010 • Stratified random sampling • Data collected from 3,096 riceproducing households in 250 villages in 7 west african countries (Benin, Gambia, Ghana, Guinea, Mali, Nigeria and Sierra Leone) • Data collected concerned: socioeconomic characteristic, rice input and output, farm and nonfarm activities, etc.
  • 16. Results • Efficiencies for adopters and nonadopters
  • 17. Results • Determinants of farmers’ efficiencies Technical efficiency Allocative efficiency Economic efficiency Coeff Std. Err Coeff Std. Err Coeff Std. Err Agriculture -0.7988*** 0.1923 -0.0062 0.0285 -0.3403** 0.1702 Education 0.0734 0.0453 -0.0064 0.0076 0.1115** 0.0429 Extension -0.1259** 0.0585 0.0151 0.0093 -0.1296** 0.0508 -0.0010 0.0017 -0.0005* 0.0002 0.0001 0.0015 Age
  • 18. Results • Impact of adoption of NERICA varieties efficiencies Technical Efficiency Allocative Efficiency Economic Efficiency LATE 0.3568*** 0.0048 0.2344*** LATE1 0.4306** 0.0031 0.2674*** LATE0 0.0549 0.0125 0.1112 PSB 0.0738* -0.0017 0.0329 -0.0272** -0.0026** -0.0511*** F(5, 694)=8.93*** F(5, 565)=18.37*** LATE Observed Diffmo Wald test F(5, 1066)=8.07***
  • 19. Conclusion and implications • Adoption of NERICA increases technical efficiency for potential and actual adopters • The impact on economic efficient is smaller but also significant on potential and actual adopters • High inefficiency among both adopters and nonadopters of NERICA varieties • Providing farmers with improved varieties should be accompanied by training on both good agricultural practices and farm manage tools