Modelling Long-term Commodities: the Development of a Simulation Model for the South African Wine Industry within a Partial Equilibrium Framework Presenters:
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Modelling Long-term Commodities: the Development of a Simulation
Model for the South African Wine Industry within a Partial Equilibrium
Framework
Presenters: Michela CuttsSanri Reynolds
Other authors: Ferdi MeyerNick Vink
From Regulated to Competing in the International Arena
The dynamic, recursive partial equilibrium model built to assist the industry by answering “WHAT IF” questions
“What If”
Australian warning on oversupply - Worldbeat
Price and Exchange Rate Changes
Climate change risks devastating South
Africa's wine and fruit industries
MELBOURNE (Reuters) - Australia's drought could cut the 2008
wine grape vintage by more than half.
Data
• Domestic data: South African Wine Industry Council’s information unit, South African Wine Information and Systems (SAWIS).
• International Prices: Compendium of Wine Statistics
• Competing Crops: Abstract of Agricultural Statistics
• Macroeconomic variables: South African Reserve Bank and Statistics South Africa websites
Methodology
• Methodology developed by the Food and Agricultural Policy Research Institute (FAPRI) at the University of Missouri
• Adapted to suit the nature of a long-term commodity
Wine Grape Supply Block
• Divided into 8 production regions
• South Africa’s top 10 varietals by volume
• Given different slopes, trellising practices etc, vine numbers are used
• Grape production per varietal = vine numbers x yield
Plant vines or alternative fruits/crops based on expected real
gross return
vinesFruits/crops
Fruit/crop sector level model
Choice of varietal -based on weighted sum of expected real gross returns
allows for determination of cross price elasticities with competing crops and different varietals
Farmer’s Decision Making Process
From Grapes to Wine
• Juice (litres) = 0.85 x Grape production (tons)
JuiceNon-alc.
Rebate wine
Distilling wine
Good wine
Wine Demand Block
• Domestic Demand– Estimated for rebate,
distilling wine and good wine
– No quality attributes considered for wine.
– Per capita consumption = f(real wine price, GDP/capita)
• Export Demand– Disaggregated into red
and white wine
– Individual equations estimated for 10 country groupings
– Exp dem = f(exch, lagged exports, SA price, new world wine price)
Linking Grape and Wine
Price equations create the “link” between “grapes” and “wine”– Noble varietals price= f(lagged variety price, real wine price,
and production of the variety)
– Non-Noble varietals price= f(lagged variety price, real rebate and distilling wine price, and production of the variety)
• Wine price=f(producer wine sales, wine production, exchange rate)
• Rebate price = f(wine price, rebate wine production)• Distillate price=f(Rebate price, distillate production)
The Closing Block
• For equilibrium to be reached total demand = total supply
• System is closed using “change in stock”– wine production plus wine imports,
less exports and domestic consumption
• A benchmark of likely trends and levels of prices, production, consumption and trade under a particular set of assumptions
• Does not constitute a forecast
The Baseline – A Possible Outlook
Macroeconomic Assumptions
Sources: Global Insight
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Total population of SA 46.80 47.30 47.45 47.63 47.79 47.96 48.13 48.31 48.51 48.74
SA cents/US $ 636.23 676.72 718.00 762.06 812.46 859.66 901.67 945.74 991.96 1,040.44 SA cents/Euro 791.29 851.57 821.44 784.44 763.09 793.20 819.34 835.95 838.02 828.29
Real GDP per capita 16,069 16,654 17,329 18,179 19,127 20,171 21,305 22,510 23,819 25,270
GDP deflator 137.94 147.39 155.51 161.77 168.24 175.18 182.64 190.57 198.69 206.58
Ave. annual prime rate 10.62 11.16 12.50 12.56 12.62 12.69 12.75 12.81 12.88 12.94 Percentage
People (Millions)
Exchange rate
Rand ( constant 2000)
Index (2000 = 100)
Red Vines
Red Vines in Production
0
10,000
20,000
30,000
40,000
50,000
2002 2004 2006 2008 2010 2012 2014
1000 v
ines
0
1,000
2,000
3,000
4,000
5,000
Ran
ds/t
on
Cabernet Sauvignon MerlotPinotage ShirazReal Cabernet Sauvignon price Real Merlot priceReal Pinotage price Real Shiraz price
White Vines
White Vines in Production
0
5,000
10,000
15,000
20,000
25,000
30,000
2002 2004 2006 2008 2010 2012 2014
1000
vin
es
0
500
1,000
1,500
2,000
2,500
Ran
ds/t
on
Chardonnay Sauvignon Blanc
Real Chardonnay price Real Sauvignon Blanc price
Domestic and Total Demand
Producer Sales and Domestic consumption
0
200
400
600
800
1000
2002 2004 2006 2008 2010 2012 2014
Mil
lio
n l
itre
s
Producer sales Domestic consumption
What if…
…the Rand appreciates relative to the baseline?
• Baseline: Rand depreciates gradually from R7.18/USD in 2007 to R10.40/USD in 2014?
• Scenario: What if Rand stays constant over the baseline at R7.18/USD?
What if… (cont.)
Wine industry overview - % change from baseline
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
2007 2008 2009 2010 2011 2012 2013 2014
% c
ha
ng
e
Total vines Exports Good w ine price
Producer sales Dom. cons
What if … (cont.)
Vines in production - % change from baseline
-5.5%-5.0%-4.5%-4.0%-3.5%-3.0%-2.5%-2.0%-1.5%-1.0%-0.5%0.0%0.5%
2010 2011 2012 2013 2014
% c
ha
ng
e
Colombar Chardonnay Sauv. Blanc Chenin Blanc
Cab. Sauv. Pinotage Shiraz Merlot
What if … (cont.)
Prices (2010) and vines in production (2014) - % change from baseline
-18% -16% -14% -12% -10% -8% -6% -4% -2% 0% 2%
Colombar
Chardonnay
Sauv. Blanc
Chenin Blanc
Cab. Sauv.
Pinotage
Shiraz
Merlot
% change from baseline
Vines 2014 Price 2010
What if … (cont.)
Vines in production per region - % change from baseline
-3.00%
-2.50%
-2.00%
-1.50%
-1.00%
-0.50%
0.00%
2010 2011 2012 2013 2014
Little Karoo Malmesbury Olifants River Orange River
Paarl Robertson Stellenbosch Worcester
Conclusion
• So how do you use these results?
• Evaluate results critically and decide whether you agree
• It teaches us something about the system, market structures and price formation
• How exogenous factors influence the business and policy environment
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