Fantu Nisrane Bachewe and Alemayehu Seyoum Taffesse

International Food Policy Research Institute (IFPRI)(Ethiopia Strategy Support Program, ESSP-II)

The 11th International Conference on Ethiopian Economy20 July 2013

Addis Ababa, Ethiopia

Dynamic Acreage Demand and Supply Response of Farm Households in Ethiopia

Presentation Outline

1. Background of study2. Linear rational expectations model3. Elasticities4. Data description5. Results6. Summary of findings.

Background• Broadly agreed that farmers in developing countries respond

little for market incentives, such as prices• Most argue production is for subsistence,

• In Ethiopia, crop production is dominated by subsistence farm households with little marketed surplus. • Small holders accounted for about 97.5% of both area and output of grains

and all temporary crops in 2008/9 (2001 EC)• Shares declined in grains to 96.6% of area and 96% of output in 2010/11 • During 2008/9-10/11 grains consumption and sales were 62 & 21% output

• Previous works on farmers’ responses to prices covering the pre-1990 Ethiopia include Seyoum Taffesse (2003)

Background…contd.• Major changes that affected crop production since mid-1990s

• Liberalization of inputs and outputs market• Emphasis on agriculture and agriculture led development• Recent fast agricultural and economic growth and high food prices

• Farmers’ responses to recent changes studied little • Contributing to knowledge in area among objectives of this work

• Objectives: study acreage demand responses for changes in crop prices and costs of production

• Dynamic rational expectations (RE) farm household model used• Sargent (1987) and Hansen and Sargent (1980) – generic firm• Applications in agriculture: Eckstein (1984, 1985), Tegene, Huffman, Miranowski

(1988), and Seyoum Taffesse (2003)

Model• Crop production is linear in acreage allocated for 2 types of crops

• Non-land costs linear in acreage and incurred in periods t-1 and t

• With rational expectation assumption the Euler’s equation of the optimization problem is:

2, 1 , , 1 , 1 , 1 , 2, ( )

2i

i t i t i t i t i t i i t i t

bC v f A A d A A

, 1 ,, ; 0, 0,1,..., and =1,2i t i i t i t iQ y A y t i

11, 1 1, 1 1 1, 1 1 1, 1 1, 1

0

( ) [ ]

i

t t t t i t i t ii

A A E P y R V kd

Model.• In the empirical analyses teff takes the place of crop 1

• Selected due to high acreage share and proportion marketed

• Empirical teff acreage demand and price equations are:

1, 0 1 1, 1 2 1, 2 3 1, 4 1, 1 5 1, 6 1, 1

1, 1, 1 ,

3

| | 1, 2

t t t t t t t t

P Pt t i i t

A A A P P R R t

P P t

RE: Elasticities• The long-run acreage elasticity is positive with respect to (WRT)

price and negative WRT opportunity costs of teff acreage

• Sign of SR elasticities depend on the sign of d and the period i in which prices and costs are expected to change.

• Particularly and if d<0 or d>0 and i is odd.

1 1

1 1 1,

1 1 1

0(1 )(1 )

LA P

y EP

d EA

1 1

1 1,

1 1 1

0(1 )(1 )

LA R

ER

d EA

1 1

1, 0i

A P 1 1

1, 0i

A R

Data• Zonally aggregated data from FDRE Central Statistical Agency (CSA)

annual AgSS household used. The data• Cover the 2003/4-2010/11 period• Include zones in Tigray (5), Amhara (10), Oromiya (17), and SNNP (21)• Grains (cereals, pulses, and oilseeds)

• Zonal aggregation needed because: • HHS resampled each year and zones are representative of regions

• Price taking assumption made for HHs may not apply at zone level• Tests indicate no causality in both directions (price and acreage)

• Average monthly producers’ prices from CSA are also used.

Data…contd.Mean regional acreage & output shares and prices 2003/4-2010/11.

Variable National Tigray Amhara Oromiya SNNNGrains out of total agricultural output (%) 86 91 92 81 45Growth rate in grains output (%) 12 14 11 13 12

Teff output out of grains (%) 18 17 22 16 16Growth rate in teff output (%) 12 12 6 9 16

Grains out of total agricultural area (%) 92 91 92 81 45Growth rate in grains area (%) 4.6 5.9 4.5 6.2 4.7

Teff area out of grains (%) 23.2 18.0 25.2 19.4 22.7Growth rate in teff area (%) 4.7 3.1 3.1 6.8 6.7

Nominal teff price (birr/KG) 4.4 4.8 4.6 4.2 4.2Growth rate in nominal teff price (%) 20 20.7 19.4 20.5 20.1Real teff price (December 2006 birr/KG) 3.6 3.8 3.8 3.5 3.5Growth rate in real teff price (%) 3.5 5.3 3.0 4.2 3.0

Results: Acreage equation• Teff acreage and price equations estimated using Arellano-Bond and

AB-BB systems GMM

• Sign of coefficients as expected and significant except teff price in AB

• Acreage a positive function of both of its lags with declining effect

• Lagged price has slightly stronger effect

• Effect of current opportunity cost negative on teff acreage

Variable Systems (AB-BB) Arellano-Bond

Constant 0.022 -0.039***

Acreage (lagged) 0.419*** 0.573***

Acreage (twice lagged) 0.074** 0.283***

Teff price 0.019*** 0.001

Teff price (lagged) 0.021*** 0.022***

Rat -0.00016*** -0.00005***

Rat (lagged) 0.00005** 0.00003***

χ2/F statistics 3943 *** 1489 ***

N 318 318

Results…contd.

Dynamic panel data estimates of acreage demand function.

Results: Elasticities• Elasticities computed from coefficient estimates have expected signs;

•Acreage demand elasticity WRT own price • Long-run: 1.4 in systems and 2.7 in AB, and • Short-run: 0.34 in systems and 0.01 in AB.

•Acreage demand elasticity WRT opportunity cost of teff acreage• Long run: -0.36 in AB and -0.54 in systems, and • Short-run: -0.13 in AB and -0.38 in systems.

Results: Elasticities.

Dynamic panel data model

Long-run acreage elasticity WRT

Short-run acreage elasticity WRT

Teff price

Opp. Cost of teff

acreageTeff

price

Opp. Cost of teff

acreage

System (AB-BB) 1.38 -0.54 0.34 -0.38

Arellano-Bond 2.71 -0.36 0.01 -0.13

Calculated elasticities of acreage demand .

Further Results• We estimated unrestricted reduced form equations

• Not possible to recover all structural parameters and test their implications,

• However, was possible to uniquely identify some structural parameters

• The coefficients of lags of acreage ensure the stationarity conditions • They also imply , which with calculated elasticities imply d<0• The latter satisfies the requirement that d and have opposite signs,• That d is negative, in turn, implies decline in land preparation costs

outweigh the decline in marginal productivity

1 0.552

1

Results of previous analyses using rational expectations.

Summary and remarks.• LR price elasticity higher and SR comparable with those in relevant work• LR elasticity of opportunity cost of acreage lower and SR higher• Own price elasticities range from 0.2-2 (LR) & 0.01-1.2 (SR) in other works

Study Crop/ acreagePrice (Opp.

Cost)

Elasticity

Long run Short run

Seyoum Taffesse (2003) TeffOwn price 0.48 0.31Rat -0.93 -0.13

Mythili (2008)Wheat own

price/AVC0.24 0.07

Sugarcane 1.51 0.27

Ahouissoussi et al 1995 Soybean Own price 1.98 1.21Soybean Wheat price -1.57 -2.11

Eckstein (1994) Cotton Rt -0.13 -0.11

Tegene et al. (1988)Corn Own price 0.2 0.011

Thank you