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

Outline

Motivation:

Methods and Data

Results

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

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=

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)

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;

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);

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.

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.

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.

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.

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).

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).