AGRICULTURAL PRICES AND MARKETS
Sponsored by a Grant TÁMOP-4.1.2-08/2/A/KMR-2009-0041 Course Material Developed by Department of Economics,
Faculty of Social Sciences, Eötvös Loránd University Budapest (ELTE) Department of Economics, Eötvös Loránd University Budapest
Institute of Economics, Hungarian Academy of Sciences Balassi Kiadó, Budapest
2
Author: Imre Fertő Supervised by Imre Fertő
June 2011
Week 3
Agricultural supply Literature
• Tomek, W. G.–Robinson, K. (2003): Agricultural Product Prices. Cornell University Press, Chapter 4
• Hudson (2007): Agricultural Markets and Prices. Blacwell, Chapter 2
• Ferris. J. N. (1997): Agricultural Prices and Commodity Market Analysis. McGraw- Hill, Chapter 6
• Application:
– Chavas, J. P.–Johnson, S. (1982): Supply dynamics: the case of U.S.
broilers and turkeys. American Journal of Agricultural Economics. 64 558–
564
– Bakucs, L. Z., Fertő, I., Fogarasi,J., Latruffe, L. (2010) The impact of EU accession on farms’ technical efficiency in Hungary. Post-Communist Economies Vol. 22. (2). 165–175
3
Theory of agricultural
• Theory of agricultural supply
• Determining factors of demand
• Price elasticity of demand
• Characteristics of supply
• The methodologies of supply analysis – Distributed lags models
– Introduction to efficiency analysis
Theory of supply
• Demand theory assume that consumers
– Maximise their utility taking into account their budget constraints
• Supply theory assume that producers
– Maximise their profit taking into account their cost constraints – Usual assumptions,
• Problems of input combinations
• The analysis of firm/farm in terms of revenue and costs
• Can be described in the function of the output
– The problem of the firm is to choose the output which maximize its profit – Information on cost functions can be obtained from
• Production function
• Cost equations
4
• MC always intersects at the minimum of the ATC and AVC curves
• Proof:
– If VC=g(q), then
– MC=g’(q) and AVC=TC/q=g(q)/q – dAVC/dq=(q*g’(q)–g(q))/q2=0 – dAVC/dq=0, if nominator=0 – q*g’(q)–g(q)=0
– g’(q)=g(q)/q
• Similar proof can be applied for ATC-
• Π=TR–TC=p*q–g(q)–b
– Π partial derivatives for q and it should be equate to zero – dΠ/dq=p–g’(q)=0
– p=g’(q)
– Price=Marginal costs
– dΠ/dq sometimes we call marginal revenue because it is partial derivative of TC
– At the profit maximum
• In short run we assume that majority of factors are fix just some factors are changing
• Assume
– q=f(X1, X2) and – C=(r1*X1+r2*X2+b (fix
cost) – C=g(q)+b
• Total cost=the function of output+fix cost
• Four cost relationships – ATC=TC/q=g(q)+b
/q
– AVC=TVC/q=g(q)/
q
– AFC=FC/q=b/q – MC=dC/dQ=g’(q)
5
• MC=MR=p
• What happens if the price is changing
– If price increase or decrease the optimal output, where profit is the maximum increase or decrease, thus MC in the short run is the supply curve of the firm above AVC curve. (Below AVC curve firm does not produce, because VC is not already covered)
– If TR=p*q, then
• AR=TR/q=p*q/q=p
• MR=dTR/dq=p
• AR=MR=p
• Thus D curve is the market price for the firm
Determining factors of supply
• Supply function
• Qs=f(Pi, Ps, Pc, In, N, T, R, O), where – Qs: quantity of supply
– Pi: price of product
– Ps: price of substitute product – Pc: price of complementary product – In: price of inputs
– N: number of producers – T: technology
– R: distribution of producers – O: goal of the producers
6
How can various factors affect on supply quantity
– Pi: increase or decrease – Ps: increase or decrease – Pc: increase or decrease – In: increase
– N: increase or decrease – T: improve
– R: change – O: change
Supply elasticity
• Own price elasticity
– If Ep<1 elastic
– If Ep=1 unit elasticity – If Ep>1 inelastic
– If Ep=0 perfectly inelastic – If Ep=∞ perfectly elastic
) / /(
) / (
p
dQ dP P Q
E =
) /(
) (
) /(
)
(
0 1 0 1 0 1 0 1p
Q Q Q Q P P P P
E = − + × + −
7
Supply elasticities
• Cross price elasticities
– If Eij>0, then i and j substitute – If Eij<0, then i and j complementary – If Eij=0, then i and j independent
• Input price elasticity
Characteristics of supply
• Dependence on nature
• Production fluctuation due to wheather
• Durability of the products
• Long production cycle
• The large share of immobil production factors
• Limited use of economies of scale
• Consequences:
– Price inelastic supply – Risk aversion
– Inverse supply curve – “overproduction trap”
) / /(
) /
(
i j j iij
dQ dP P Q
E =
) / /(
) /
( dQ dI I Q
E
I=
8
Approaches of supply analysis
• Data:
– Time series
• Aggregate macro data – Cross-sectional data
• Households surve – Panel data
• Combination of time series and cross-sectional data
• Approaches
– Single equation models
Single equation models
Model Function Elasticity
Linear Y=α+βX β(X/Y)
Log-log logY=α+βlogX β
Log-lin logY=α+βX βX
Lin-log Y=α+βlogX β(1/Y)
Reciprocal Y=α+β(1/X) –β(1/XY)
9
Distributed lag
• Dynamic effects
– Policy takes time to have an effect
– The size and nature of the effect can vary over time – Permanent vs. Temporary effects
• Effect is distributed through time
– consumption function: effect of income through time – effect of income taxes on GDP happens with a lag – effect of monetary policy on output through time
The distributed lag effect
10
Two questions
• How far back?
– what is the length of the lag?
– finite or infinite
• Should the coefficients be restricted?
– e.g. smooth adjustment – let the data decide
Unrestricted finite distributed lag
• Finite: change in variable has an effect on another only for a fixed period – e.g. monetary policy affects GDP for 18 months
– the interval is assumed known with certainty
• Unrestricted (unstructured)
11 – the effect in period t+1 is not related to the effect in period t
n unstructured lags
no systematic structure imposed on the β’s the β’s are unrestricted
OLS will work
i.e. will produce consistent and unbiased estimates
Problems
1. n observations are lost with n-lag setup.
• data from 1960, 5 lags in model implies earliest point in regression is 1965
• use up degrees of freedom (n-k) 2. high degree of multicollinearity among xt-j’s
• xt is very similar to xt-1 – little independent information
• imprecise estimates
• large stn errors, low t-tests hypothesis tests uncertain.
3. Several LHS variables
• many degrees of freedom used for large n.
4. Could get greater precision using structure
12
Arithmetic lag
• Still finite: the effect of X eventually goes to zero
• The coefficients are not independent of each other
– The effect of each lag will be less than previous one
– E. g. monetary policy in 1995 will have less of an effect on GDP in 1998 than will monetary policy in 1996
• Note how this is different to the capital exp example
Arithmetic lag structure
(impulse response function)
13
The arithmetic lag structure
Polynomial distributed lag
14
Geometric lag model
(impulse response function)
15
Alternative lag models
• Adaptive expectations model
– A version of the geometric lag model
– If we assume that individuals have “adaptive expectation” then the geometric lag model will emerge
– Assume expectations
• Formed on the basis of past experience
• Expectations are updated in the light of errors – AE is not always consistent with “rational expectations”
• Partial Adjustment Model
– Another version of the geometric lag model – Assume individuals adjust to the ideal gradually
• Cost of adjusting, so don’t adjust quickly
16
Agricultural production
• Production function:
– Physical total product, TPP= Y=f(X)
– Physical average product : APP=Y/X=f(X)/X – Physical marginal product:
• MPP=dTPP/dX=dY/dX=df(X)/dX=f’(X) – Factor elasticity
• E=(dY/Y)/(dX/X)=(dY/dX)/(X/Y)=MPP/APP
Production and cost functions
• Estimation of production functions – Cobb–Douglas
– CES
– Translog etc.
• Estimation of cost functions
• Estimation of technical development
17
Types of economies of scale
Sources of economies of scale
• Sources of increasing economic of scale – Fix costs
– Division of labour
– Price advantage buying inputs
• Sources of decreasing economic of scale – Limitations of efficient management
– Limitation to control agroclimatic conditions – Changing nature of risk
18
Efficiency and productivity
• Definition of efficiency and productivity
• Methodologies
– Index numbers – DEA
– SFA
Technical efficency
19
20
SFA
21
22
A Hungarian example
Variable Coeff. SE robust-SE
Trend 0,19** 0,194 0,255
EU2004 –1,364*** 0,372 0,428
EU2005 –2,197*** 0,593 0,743
Company dummy –1,812** 0,526 0,733
Region 1 dummy –0,868*** 0,290 0,297
Region 2 dummy –0,543** 0,220 0,251
Land to Labour Ratio 4,825*** 1,608 1,102 Subsidies to Output Ratio 0,138*** 0,014 0,013 Subsidies 2004 to Output
Ratio 0,006 0,024 0,014
Subsidies 2005 to Output
Ratio 0,808*** 0,114 0,257
Livestock Output to Total
Output Ratio –2,912*** 1,128 0,969
Livestock Output to Total
Output Ratio2 2,997*** 1,229 1,054
Soil Quality Index –1,578*** 0,244 0,303
23
Conclusions
• Economic theory is useful for analysing of agricultural supply, but it should be taken into account the characteristics of agricultural supply
• Dependence on nature
• Production fluctuation due to wheather
• Durability of the products
• Long production cycle
• The large share of immobile production factors
• Limited use of economies of scale
• Consequences:
– Price inelastic supply – Risk aversion
