demand model, data on income were derived from monthly data on total personal disposable income for
the U.S. taken from the St. Louis Federal Reserve Bank’s FRED database on their web site (FRED,
2001). For export demand, the income variable was foreign gross domestic product (GDP), proxied by
GDP for Organization for Economic Cooperation and Development (OECD) countries after subtracting
U.S. GDP from the total.16 These data were available from various issues of Quarterly National Accounts
and National Accounts of OECD Countries, but monthly values were interpolated from the available
quarterly data by fitting a cubic spline to the data using PROC EXPAND in SAS. A similar procedure
was used to estimate monthly values of the level of foreign cotton stocks based on annual data obtained
from USDA’s Foreign Agricultural Service (FAS).
Annual data from 1975 through 2000 were used to estimate the cotton supply function.
Production levels were collected from various issues of the annual USDA publication, Cotton and Wool
Yearbook. For the annual supply function, the relevant price is the price that producers expect to receive
when they make their planting decision. This price determines the quantity that producers will choose to
supply (subject to random variation due to weather or other factors). After the planting decision has been
made, the quantity that will be produced is fairly unresponsive to price because biological factors (e.g.,
optimal planting season) largely prevent supply response in the short run.
To capture producers’ expectations of the market price, we used the average of the nearby
December futures prices over the months when most cotton is planted each year, calculated based on
information from CI’s monthly database.17 These futures prices should reflect all information available to
growers when they make their planting decision. An increase in the futures price implies that growers
expect to receive a higher market price for their crop at harvest. Other things being equal, a higher
expected price at planting time should induce growers to plant more cotton, either on land that was
formerly idle or previously had other crops grown on it.
16In addition, the Czech Republic, Korea, Hungary, and Poland were not included in the series for consistency because
their data were not included in OECD GDP estimates for the entire period from 1986 through 2000.
14