CountryWatch Agricultural Forecast 2015

Transcription

1 CountryWatch Agricultural Forecast 2015 Global Agricultural Market Conditions The world agricultural markets mirrored the pace of economic activity and global weather patterns in early The key driving forces in the markets at the beginning of the year were the slowdown in the growth rate in the Chinese economy, recessionary forces in Europe, the strength of the US dollar and the dramatic plunge in world oil prices which has set off shock waves and is reducing capital investment in the energy industry. Table 1 below summarizes the current CountryWatch Macroeconomic Forecast 2015 projection of the global growth situation in the major industrial economies of the world in terms of GDP expressed in US dollars and the growth rate in real GDP expressed in the percentage growth in GDP expressed in US dollars with prices indexed to a based year of Table 1 Real GDP Growth Rate Constant $US 2005 Base Year GDP Rank China 7.4% 9.6% 8.0% 6.5% 5.0% 2 United States 3.0% 2.7% 2.8% 2.9% 3.0% 3 Japan 1.5% 4.6% 4.1% 3.6% 3.0% 4 Germany -1.5% 3.2% 3.1% 3.1% 3.1% 5 India 6.5% 8.0% 7.0% 6.0% 5.0% 6 Brazil 2.7% 5.0% 4.6% 4.3% 4.0% 7 Russian Federation 3.9% 5.0% 4.6% 4.3% 4.0% 8 France -2.6% 2.3% 2.6% 2.8% 3.1% 9 United Kingdom 2.1% 2.5% 2.6% 2.8% 3.0% 10 Canada 2.7% 2.6% 2.7% 2.9% 3.0% Source: CountryWatch Macroeconomic Forecast 2015 Global Agricultural Price Outlook These economic trends mentioned above put some downward price pressure in agricultural markets in 2014 and 2015 which we expect will turn around as more normal growth patterns emerge. Table 2 below provides a summary of the CountryWatch Agricultural Forecast 2015 in terms of the projections of prices of key industrial and precious metals over the forecast period. Table 2

2 Indices for the agricultural commodities (with 2010=1.00) reflecting these price projections are charted in Figure1 below: Figure 1 In terms of nominal price increases the estimated compound rate of change of prices over the forecast period from 2015 to 2035 is shown in Table 3 below ranked from estimated highest price increases to lowest price increases: Table 3

3 Global Agricultural Production Outlook On the production side the CountryWatch Agricultural Forecast 2015 estimates of production increases for each commodity group are shown in Table 4 below: Table 4 Production indices for the agricultural market (with 2010=1.00) reflecting these production projections are charted in Figure 2 below: Figure 2 The growth rate of production of each commodity over the forecast period is shown in Table 5 below:

4 Table 5 CountryWatch February 2015

5 CountryWatch Agricultural Forecast 2015 Methodology 2/25/2015 Global Economic Assumptions The CountryWatch Macroeconomic Forecast 2015 is used to project GDP growth, the US GDP deflator, and exchange rates for each country in the world. GDP in US dollars is computed for each country using projections of market exchange rates. Nominal values of GDP are converted to real GDP numbers using the US GDP deflator indexed in General Demand Assumptions for Agricultural Commodities The demand for each commodity (i.e. cocoa beans, coffee, maize, rice, soybeans, and wheat) is assumed to be a function of real GDP and the real price of each commodity. The general form of the demand equation is: (1) QDit=Yt*IEit*PEit Where: QDit=Quantity demanded of commodity i in year t Yt=Real GDP in US Dollars in year t indexed to 2005 $ i= cocoa beans, coffee, maize, rice, soybeans, wheat t=2014 to 2035 IEit=Income elasticity term for commodity i in year t where the income elasticity term in each year is equal to [(Yt/Yt 1) x AIEi+1] where Yt = Real GDP in the forecast year t and AIEi is a constant income elasticity assumption for each commodity. The constant income elasticity of demand assumptions for each agricultural commodity show the percent increase (in decimal form) in demand for each commodity (cocoa beans, coffee, maize, rice, soybeans, wheat) based on a 1% increase in GDP and were calculated based on a review of literature and judgmental assumptions by the CW staff for each commodity. The income elasticities of demand assumed for each commodity are shown in Table 1 along with an estimate of the price elasticities of supply and demand for each commodity and an estimate of the technical efficiency term. The technical efficiency term estimates the exogenous trend in the global economy to use less commodity per unit of gdp over time. `

6 Table 1 Agro Market Dynamics Price Price Elasticities Income Demand Supply cocoa beans coffee maize rice soybeans wheat Agricultural Productivity Output per Hectare PEit=Price elasticity of demand for each commodity i in year t where the price elasticity of demand term in each year is equal to [(PCTit/PCTit 1) x APCTEi+1] where PCTit is the real price of the ith commodity commodity in year t indexed in 2005 $ and APCTi is a constant price elasticity of demand assumption for each commodity. The constant demand price elasticity assumptions for each commodity show the percent decrease (in decimal form) in demand for each commodity based on a 1% increase in the real price for each commodity. These elasticities based on a review of literature and judgemental assumptions by the CW staff for each commodity. General Supply Assumptions for Agricultural Commodities The quantity of each commodity supplied for the ith agricultural commodity in year t is assumed to be a function of the recent 7 year trend in the production of each commodity in each country from 2006 to 2012 with a cap of.05 and the market price in real terms and a technical efficiency term which represents the increasing yield per acre of agricultural production due to advances in technology. (2) QSit=QSit 1*(1+g)*[(Pit/Pit 1)+1]*ASi*EEt Where: QSit is the quantity of the ith agricultural commodity supplied in year t g=the trend in the ith commodity supplied from 2006 to 2012 with a cap of.05 and the trend term was phased out over a 7 year period.

7 ASi is the constant price elasticity of supply of the ith commodity. The constant price elasticity of supply assumptions for each commodity show the percent increase (in decimal form) in supply for each commodity based on a 1% increase in the real price for each commodity and were calculated based on a review of literature and/or judgemental assumptions by the CW staff for each commodity. EEt=The technical efficiency term for Agricultural in year t. The technical efficiency term for each year is equal to [(QDit 1/Yt 1)*(1+AEE)] where AEE is a constant giving the percent (in decimal form) increase in overall agricultural yield per unit of real GDP each year due to the effects of technical change. This value was estimated by the USDA based on their assessment of the annual percentage increase in agriculture output in global agricultural production. Global Price Equilibrium for Agricultural Commodities The long run price of each agricultural commodity is determined by aggregating the quantity demanded and supplied for each commodity and for each country across the world. Each year of the forecast the price of the commodity is calculated in the model such that the supply and demand for that commodity are equal. CountryWatch February 2015