Linkages between macroeconomic factors and commodity market have been a subject of discussion for a long time. The discussion largely concentrates on oil and bullion market. However given the importance of agricultural production and its consequent impact on the prices in the commodity markets and role in the national output, it is quite evident that thought has to be given to the role these markets play. Production impacts the prices on the supply side and by extension there is bound to be influence on the GDP. Literature of late has been arguing on the declining influence of agro-commodity prices on the inflation levels and WPI. The paper examines the interlinkages between commodity prices and macroeconomic factors like GDP and inflation. Our study indicates no long term convergence between these macro-economic variables and the prices of rice, wheat and oilseeds...

1. 1
International Conference on
Agribusiness and Food Industry in
Developing Countries:
Opportunities and Challenges
Does Agro commodity Prices influenceDoes Agro commodity Prices influence
Macroeconomics: Exploring the InterlinkagesMacroeconomics: Exploring the Interlinkages
between macroeconomics and Agrobetween macroeconomics and Agro
commodity prices usingcommodity prices using
CoCo--integration Modelintegration Model
Presented By:Presented By:
Ms.Surabhi AgarwalMs.Surabhi Agarwal
Ms.Preeti LaddhaMs.Preeti Laddha

2. 2
Backdrop to the StudyBackdrop to the Study
• Agricultural production and its role in
commodity markets
• Agriculture vs. Services
– Agro production still contributes to the GDP to
a sizeable extent.
– 24% in Indian GDP
– Employs 57% of the work force.
Graph showing the Fluctuations in the NationalGraph showing the Fluctuations in the National
GDP of AgricultureGDP of Agriculture
Source : GoI StatisticsSource : GoI Statistics

3. 3
History of Commodity Markets
Existence of commodity markets in India for centuries,
- by and large unorganized.
Emergence of commodity exchanges and revival of futures
trading in recent years.
Strong interlinkages of Commodity prices with various
macroeconomic factors like GDP, inflation money supply
and exchange rates.
Objective Of the StudyObjective Of the Study
• Understanding the linkages between
macroeconomics and commodity markets in
India.
• Measuring the degree of influence of
commodity prices on macroeconomic factors
in India.
• Understanding what these relations mean for
the economy as a whole and agro based
industries in particular

4. 4
MethodologyMethodology
Examining the relationship between GDP, wholesale price
index (WPI) and agricultural yield and prices.
- Five major crops were selected namely rice , wheat ,
cotton ,sugar and oilseeds .
Hypothesizing that the macroeconomic indicators have a
significant influence on the commodity prices
- its impact on pricing mechanisms in the commodity
markets both at spot prices and futures.
Analysis with the use of:
- OLS Model
- Co-Integration Model
Some Facts…….

5. 5
Index Numbers for Commodity prices for selectIndex Numbers for Commodity prices for select
Crops (1995Crops (1995--96 to 200496 to 2004--05)05)((
1831741751421852004-05
1811581691391812003-04
1761381661351422002-03
1751131671461492001-02
1771031681531572000-01
1751221711561471999-00
1521391461541671998-99
1381141341341551997-98
1371151291191331996-97
1121171171131591995-96
WheatOilseedsRiceSugarCottonYear
Graph Showing the Commodity Prices inGraph Showing the Commodity Prices in
Different YearsDifferent Years
Commodity Prices in Various Years
0
20
40
60
80
100
120
140
160
180
200
1995-1996
1996-1997
97-98
98-99
99-00
00-01
2001-2002
2002-2003
2003-2004
2004-2005
Years
Prices
Rice(Prices)
WheatPrices)
CottonPrices)
SugarPrices)
Oilseeds(Prices)

6. 6
Yield of different Crops for differentYield of different Crops for different
YearsYears
7324.887.8234.217.12004-05
72.125.187236.213.82003-04
65.115.172.7281.68.72002-03
72.820.793.3297.2102001-02
69.718.4852969.52000-01
76.420.789.7299.311.51999-00
70.825.286295.712.21998-99
66.3825.583.5228014.81997-98
64.524.179.6273.614.31996-97
62.622.479.628313.11995-96
WheatOilseedsRiceSugarCottonYear
Graph Showing the Yield of Different CropsGraph Showing the Yield of Different Crops
Yield in different Years
0
50
100
150
200
250
300
350
19
95-
96
19
96-
97
19
97-
98
19
98-
99
19
99-
00
20
00-
01
20
01-
02
20
02-
03
20
03-
04
20
04-
05
Years
Yield
Wheat
Rice
Cotton
Sugar
Oilseeds

7. 7
Agricultural GDP Growth Rate andAgricultural GDP Growth Rate and
WPIWPI
187.91.12004-05
175.99.12003-04
166.8-5.22002-03
161.36.52001-02
155.7-0.12000-01
145.30.31999-2000
140.76.21998-99
132.8-2.41997-98
127.29.61996-97
121.6-0.91995-96
WPIGDPYear
Graph Showing The GDP Growth RateGraph Showing The GDP Growth Rate
GDP growth rate in Agri and Allied sector
-6
-4
-2
0
2
4
6
8
10
12
1995-
96
1996-
97
1997-
98
1998-
99
1999-
00
2000-
01
2001-
02
2002-
03
2003-
04
2004-
05
Year
GDPgrowthrate

8. 8
Graph Showing the changes in WPIGraph Showing the changes in WPI
WHOLESALE PRICE INDEX
0
20
40
60
80
100
120
140
160
180
200
1995-
96
1996-
97
1997-
98
1998-
99
1999-
00
2000-
01
2001-
02
2002-
03
2003-
04
2004-
05
Years
WPI
WPI
AnalysisAnalysis
Correlation analysis suggests that
commodity prices and WPI do share
a strong relationship. However,
testing the convergence among them
in the long run can be shown with
the help of co-integration model.

9. 9
Results Based on OLS ModelResults Based on OLS Model
0.883 0.7790.332 0.11Wheat
0.708 0.5010.539 0.29Oilseeds
0.87 0.760.50 0.25Rice
0.446 0.1990.241 0.058Sugar
0.563 0.3170.247 0.061Cotton
R R2R R2
WPI , PricesGDP ,Output , PricesCommodity
OLS Model Significance ResultsOLS Model Significance Results
SignificantNot significantWheat
SignificantSignificantOilseeds
SignificantSignificantRice
SignificantNot significantSugar
SignificantNot significantCotton
Significance LevelSignificance Level
WPI , PricesGDP ,Output , PricesCommodity

10. 10
CoCo--Integration ResultsIntegration Results
-0.1136 -2.365 Not
Significant
-2.227 -2.365 Not
Significant
Wheat
-1.6269 -2.365 Not
Significant
-1.723 -2.365 Not
Significant
Oilseeds
-1.7640 -2.365 Not
Significant
Not
-0.651 -2.365 Significant
Rice
-0.2114 -2.365 Not
Significant
-3.741 -2.365 SignificantSugar
-0.8137 -2.365 Not
Significant
-9.564 -2.365 SignificantCotton
T Stats Critical Significance
Value
T Stats Critical Significance
Value
WPI , PricesGDP ,Output , PricesCommodity
OLS Model & CoOLS Model & Co--Integration ModelIntegration Model
ResultsResults
OLS MODEL results give mixed picture.
- there lies a significant correlation between the prices
of rice and oilseeds and yield of corresponding prices
and the agricultural growth rate.
- the relationship is not significant in other cases.
CO- INTEGRATION results :
- only cotton and sugar exhibit stationarity in the case
where GDP is a function of Prices and Yield but not in
the case of WPI being a function of Prices.

11. 11
Our TakeOur Take
• High degree of correlation between WPI and commodity
prices
- sugar and cotton, the degree of co-relation with WPI is
less (56 and 44% respectively).
-both sugar and cotton have a high degree of weightage
attached to them in WPI composition compared to the other
three crops.
• Cotton and sugar though being co integrated, their
correlation is low.
• Macroeconomic influences are minimal or remain
oblivious to the changes in agricultural prices and
yield.
• Also reflected in the continuing decline in the
share of agriculture in the national GDP.
- a matter of concern
• Current nature of the industry is leading often to
overproduction
• The changing composition of WPI also is an
indicator of these trends.

12. 12
• Findings reflect the studies that there is a very
high impact of the commodity prices on WPI .
• To an extent the degree of impact of prices on
inflation does affect the net export position of the
country.
• The issue of the commodity prices
responding to aggregate demand shocks
also rises
• The availability of alternative instruments
might have reduced the hedging in
commodities which would have influenced
these prices.
• Prices may respond to short run shocks
indicating a high co-relation with the WPI
but may not sustain it in the longer run.

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