dynamic supply response of farm households in ethiopia
TRANSCRIPT
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Fantu Nisrane Bachewe and Alemayehu Seyoum Taffesse
International Food Policy Research Institute (IFPRI)
CSAE Conference 2015: Economic Development in Africa
March 22-24, 2015
St Catherine's College, University of Oxford, UK
Dynamic Supply Response of Farm
Households in Ethiopia
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Outline
Motivation:
Methods and Data
Results
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Motivation Agricultural supply response to prices:
is weak, particularly in SSA ((Bond (1983), Muchapondwa (2009),Kavinya and Phiri (2014), and Mose et al. (2007));
is particularly important for interventions that work through prices –cooperativization, commercialisation
Agricultural supply response and liberalization
market reforms were motivated in part by their potential impact on priceresponses (Taffesse (2003));
supply responses of farmers were unaffected by market liberalizationpolicies in Uganda (Rudaheranwa et al. 2003) and in Kenya (Mose et al.2007).
Objectives
Estimate agricultural supply responses in Ethiopia
Explore the impact of market reforms on agricultural supply response inEthiopia
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ModelProcedure
Dynamic optimization problem with Leontief technology, quadratic costs, risk
neutrality, and rational expectations, AR processes for prices and costs
(Eckstein (1984, 1985), Tegene, Huffman, and Miranowski (1988), Taffesse
(2003));
Output supply is mapped on to acreage demand
Empirical Specification - Acreage equation
1 1 1 1 1 1 1
, 0 1 , 1 2 , 2 3 , 4 , 1 5 , 6 , 1 ,
) )
) )
);
)
3
( (3 4 1 1; 3, ,1 ( (1 1 1 11 2 1 1
(5 6 1
, 1 (1 1 1 2 1
;A A
i t i t i t i t i t i t i t i i tt
E P E PL SA P A PE A E A
E RLA R E A
A A A P P R R
k kx x k
k k
k kx
k k
k k k k k k k h u- - - -
+ + ³
+= =
- -
+=
- -
= + + + + + +
æ ö÷ç ÷ç ÷ç ÷÷çè ø
æ ö÷ç ÷ç ÷ç ÷÷çè ø
5
)
)
(1
, (1 1 1
E RSA R E A
x k=
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Model
Opportunity cost of Teff production
21
1
2
t gt gt gt
g
R P y A=
= å
R1 real opportunity cost of Teff;
g grains, 21 types of grains (with g = 1 representing Teff);
Pg real prices of grains other than Teff;
yg average product of land in crop g production, the respective zonal
average yields are used as the measure of the average product of land.
Ag acreage share of crop g in total area under grains other than Teff
(weight)
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Data and Methods
Data
Ethiopian Central Statistical Agency (CSA)
o Annual Agricultural Sample Survey (2004/05-2012/13)
o more than 30 thousand farm households are coveredannually
Four main regions covered
o Tigray, Amhara, Oromiya, and SNNP;
o on average these regions accounted for over 96% of thenationwide grain area and output during 2004/5-2012/13.
21 grains included;
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Data and Methods
Estimation
Acreage equation include lagged values of thedependent variable
OLS or within-groups panel estimator result biasedparameter estimates (Nickell 1981 and Hsiao 1986);
use dynamic panel data (DPD) models
o the linear dynamic panel-data method due toArellano and Bond (1991);
o the systems estimator due to Arellano and Bover(1995) and Blundell and Bond (1995);
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Descriptives – Teff Acreage
Region 2004/5 2005/6 2006/7 2007/8 2008/9 2009/10 2010/11 2011/12 2012/13 Average
All
regions
21.7
(11.1)
19.7
(10.1)
21.6
(11.7)
23.2
(13.6)
21.3
(10.1)
21.8
(11.0)
22.3
(11.8)
21.4
(11.3)
19.8
(10.8)
21.4
(11.3)
Tigray17.6
(5.7)
18.3
(7.0)
16.6
(6.4)
17.3
(5.3)
17.7
(5.5)
18.7
(5.9)
17.4
(6.3)
15.7
(6.8)
16.6
(6.2)
17.3
(9.6)
Amhara24.9
(5.7)
24.6
(7.0)
25.2
(6.4)
26.5
(5.3)
24.8
(5.5)
24.6
(5.9)
24.1
(6.3)
23
(6.8)
24.8
(6.2)
24.7
(5.9)
Oromiya18.7
(12.5)
18
(11.6)
19.8
(13.2)
19.2
(12.7)
19.8
(11.4)
20.7
(12.3)
20.7
(12.7)
20.6
(13.0)
19.5
(12.4)
19.7
(12.1)
SNNP23.5
(12.0)
19.2
(10.4)
22.6
(12.7)
26.2
(16.6)
21.6
(10.5)
22.2
(11.8)
24
(13.5)
22.5
(12.0)
18.5
(11.1)
22.3
(12.4)
Source: Authors’ computation using CSA AgSS data (CSA 2005-2014).
Note: Figures in parentheses are standard deviations.
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Descriptives – Real Teff prices
Region 2004/5 2005/6 2006/7 2007/8 2008/9 2009/10 2010/11 2011/12 2012/13 Average
All
regions
2.9
(0.37)
3.2
(0.37)
3.7
(0.35)
4.2
(0.41)
4.7
(0.58)
3.5
(0.49)
3.2
(0.41)
3.7
(0.37)
3.6
(0.43)
3.6
(0.66)
Tigray3.4
(0.36)
3.2
(0.48)
3.3
(0.32)
4.7
(0.39)
5.1
(0.38)
3.9
(0.43)
3.6
(0.39)
4
(0.33)
4
(0.31)
3.9
(0.65)
Amhara3.2
(0.36)
3.4
(0.48)
3.8
(0.32)
4.4
(0.39)
5
(0.38)
3.8
(0.43)
3.5
(0.39)
4
(0.33)
4.1
(0.31)
3.9
(0.64)
Oromiya2.8
(0.3)
3.1
(0.33)
3.7
(0.36)
4.1
(0.39)
4.5
(0.57)
3.2
(0.5)
3.1
(0.44)
3.6
(0.33)
3.4
(0.39)
3.5
(0.64)
SNNP2.8
(0.3)
3.2
(0.38)
3.8
(0.32)
4.2
(0.4)
4.6
(0.62)
3.4
(0.46)
3.1
(0.32)
3.6
(0.32)
3.5
(0.32)
3.6
(0.65)
Source: Authors’ computation using CSA AgSS data (CSA 2005-2014).
Note: Real Teff prices are Birr/kg in constant December 2006 prices. Figures in parentheses are standard deviations.
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Descriptives – Teff opportunity cost
Region 2004/5 2005/6 2006/7 2007/8 2008/9 2009/10 2010/11 2011/12 2012/13 Average
All
regions
2510
(739)
3086
(784)
3016
(928)
4715
(1032)
3758
(818)
3227
(928)
4421
(1078)
4281
(1049)
3929
(921)
3660
(1156)
Tigray2951
(620)
3297
(438)
3321
(605)
5656
(781)
4939
(447)
4666
(540)
5951
(462)
5403
(402)
5229
(314)
4601
(1325)
Amhara2707
(620)
3299
(438)
3604
(605)
5088
(781)
4161
(447)
3710
(540)
4937
(462)
4755
(402)
4510
(314)
4086
(919)
Oromiya2685
(533)
3318
(606)
3389
(778)
5122
(746)
3881
(500)
3215
(638)
4407
(860)
4608
(727)
4028
(471)
3850
(976)
SNNP2171
(798)
2747
(974)
2360
(890)
3984
(980)
3185
(796)
2666
(819)
3822
(918)
3524
(1075)
3263
(794)
3080
(1065)
Source: Authors’ computation using CSA AgSS data (CSA 2005-2014).
Note: Teff opportunity costs are Birr/hectare in constant December 2006 prices. Figures in parentheses are standard deviations.
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11
Variables Coefficients
Teff acreaget-1 0.481***
(0.032)
Teff acreaget-2 -0.096***
(0.034)
Teff pricet 0.022***
(0.007)
Teff pricet-1 0.017**
(0.008)
Opportunity cost of Tefft -0.0051***
(0.0004)
Opportunity cost of Tefft-1 0.0034***
(0.0003)
Constant 0.060*
(0.031)
χ2-equation 3708***
χ2-regressors 1038***
χ2-time dummies 424***
m1 -4.29***
m2 -0.98
χ2−Sargan/Hansen test 36
Number of observations 371
Estimated
Teff acreage
demand
equation
Notes: Figures in parentheses are standard errors. Coefficients with ***, **, and * are
significant at 1, 5, and 10 percent, respectively.
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12
Estimated Teff acreage demand elasticities
Teff price
Teff
opportunity
cost
Teff ‘quota’
‘quota’
rate
Long-run Teff acreage elasticity 1.07 (0.48) -0.48 (-0.93) -0.04
Short-run Teff acreage elasticity 0.37 (0.31) -0.87 (-0.13) 0.005
Teff Price:
Teff acreage demand responds positively to increases in its own-price elastic;
higher in the long run than in the short run;
Teff Opporunity Cost
Teff acreage demand responds negatively to rising opportunity cost;
Lower in the long run – cost of maintaining land productivity rises over time
(more fertilizers, less crop rotation, less suitable land);
Note: Figures in brackets and in the fourth column are Teff acreage demand elasticities
from Taffesse (2003).
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13
Estimated Teff acreage demand elasticities
Teff price
Teff
opportunity
cost
Teff ‘quota’
‘quota’
rate
Long-run Teff acreage elasticity 1.07 (0.48) -0.48 (-0.93) -0.04
Short-run Teff acreage elasticity 0.37 (0.31) -0.87 (-0.13) 0.005
Teff Price:
Teff acreage demand elasticity is higher after the reforms in the long-run;
Reason: greater opportunity to adjust more fully to price changes;
Teff Opporunity Cost
Teff acreage demand elasticity is higher (lower) in the short- (long) run after
the reforms;
Reason: greater flexibility in the SR, better allocation in the long-run;
Note: Figures in brackets and in the fourth column are Teff acreage demand elasticities
from Taffesse (2003).