Towards a producer price

discovery system for SA

Koos Coetzee

Milk Producers Organisation

June 2016

K Coetzee

Scope

Background

Factors that influence producer prices

A regression model

Alternative: Milk futures

Way forward

1 683 commercial dairy farms

Many small non-commercial farmers

Milk production 3 049 million litres (2015)

Production per farm = 4 963 litres per day

Larger farms (> 5 000 litres/day produce 80% of milk

Secondary industry

4 large buyers/processors (CR4 = 54%)

Many smaller processors

130 producer-distributors (distribute own milk)

Concentrated retail sector

4 retailers handle 75%+ of total sales

Structure of SA dairy industry

Products

60% Liquid

40% Concentrated products

Free market system

Relatively low import tariffs

Various trade agreements

No national quota systems

No pricing structure

No minimum prices

In many cases no contracts!

No subsidies

Structure of SA dairy industry

Number of producers and production

1 600

1 800

2 000

2 200

2 400

2 600

2 800

3 000

1 500

2 000

2 500

3 000

3 500

4 000

4 500

5 000

5 500

6 000

2000 2002 2004 2006 2008 2010 2012 2014

Mil

k p

rod

uc

tio

n (

Mil

.L.)

Pro

du

cers

Milk production Right axis Producers Left axis

K Coetzee

Factors that influence producer prices

Supply-side

Milk production

Producer price

Feed price

Milk:feed ratio

Climate

Imports

Import parity prices

K Coetzee

Producer price

2,50

3,00

3,50

4,00

4,50

5,00

Jan 10 Jan 11 Jan 12 Jan 13 Jan 14 Jan 15 Jan 16

Rand per litre

Producer price 6,5% p.a. increase

K Coetzee

Feed price

1.500,00

2.000,00

2.500,00

3.000,00

3.500,00

4.000,00

4.500,00

5.000,00

Jan 10 Jan 11 Jan 12 Jan 13 Jan 14 Jan 15 Jan 16

Rand per ton

Feed price #% groiwth"

K Coetzee

Milk:feed price ratio

0,8

1

1,2

1,4

1,6

1,8

2

2,2

Jan 03 Jan 05 Jan 07 Jan 09 Jan 11 Jan 13 Jan 15

K Coetzee

Relationship between prices and production

-0,09

-0,04

0,01

0,06

0,11

0,16

0,8

1

1,2

1,4

1,6

% change in production Milk:feed price ratio

Climate

Driest in 50 years

Roughage shortage

Drier conditions in E

Cape

Farmers emotionally

fragile

Producer prices and import parity

2,60

3,10

3,60

4,10

4,60

5,10

5,60

6,10

6,60

7,10

Jan 12 Jul 12 Jan 13 Jul 13 Jan 14 Jul 14 Jan 15 Jul 15 Jan 16

Rand per litre

Producer price Import parity

Improving price discovery process

Step 1

Regression analysis

Step 2

Product on futures market

Regression model

𝑀𝑖𝑙𝑘 𝑃𝑟𝑜𝑑𝑢𝑐𝑒𝑟 𝑃𝑟𝑖𝑐𝑒𝑠 =𝑓(𝑀𝑖𝑙𝑘 𝑅𝑒𝑡𝑎𝑖𝑙 𝑃𝑟𝑖𝑐𝑒𝑠, 𝐼𝑚𝑝𝑜𝑟𝑡 𝑃𝑎𝑟𝑖𝑡𝑦 𝑜𝑓 𝑀𝑖𝑙𝑘, 𝐹𝑒𝑒𝑑 𝑃𝑟𝑖𝑐𝑒𝑠)

Results

1,5

2

2,5

3

3,5

4

4,5

Jan03

Mai03

Sep03

Jan04

Mai04

Sep04

Jan05

Mai05

Sep05

Jan06

Mai06

Sep06

Jan07

Mai07

Sep07

Jan08

Mai08

Sep08

Jan09

Mai09

Sep09

Jan10

Mai10

Sep10

Jan11

Mai11

Sep11

Jan12

Mai12

Sep12

Jan13

ACTUAL Fitted

Unilateral decrease by DairyBelle

2,50

2,70

2,90

3,10

3,30

3,50

3,70

3,90

4,10

4,30

4,50

Jul11

Aug11

Sep11

Okt11

Nov11

Dez11

Jan12

Feb12

Mrz12

Apr12

Mai12

Jun12

Jul12

Aug12

Sep12

Okt12

Nov12

Dez12

Jan13

Feb13

Mrz13

Apr13

Mai13

Jun13

Jul13

Aug13

Sep13

Okt13

Nov13

Dez13

Actual Extrapolated Data

Product on futures market

Well-run and active agricultural futures market

Product-settled contracts for

Maize

Other grains

High activity (maize = 10 times the crop)

Cash-settled contract for

Beef Grade A2/A3

Proposed milk contract

Cash settled

Problem to find reliable settlement price

Currently examining import parity model