WIPO Journal - World Intellectual Property Organization

168 The WIPO Journal
so we can anticipate ε 1 to be higher than that of Darjeeling tea. Combining the information available from
published literature and secondary data sources we select 0.38 as ε 1 for Oolong tea. Owing to the uncertainty
of these estimates, the results include sensitivity analysis which indicates how the results change with
changes in input values presented here.
Supply elasticity of other inputs
The “other” non-land inputs include capital, purchased inputs such as fertiliser, hired farm labour and
family labour and management. Many of these inputs would be expected to be highly elastically supplied
in the medium to long term.
For example, given the small proportional use in all Chinese and Indian agriculture applied to tea, one
would expect the supply of fertiliser and chemicals to be very price elastic. In the short term, some of
these inputs such as managerial inputs, labour and capital may be less elastically supplied.
We are not aware of any studies estimating the supply elasticity of “other” inputs in agriculture. Hence
in this analysis we select ε 2 as 1, reflecting the elastic and inelastic nature of some of these inputs.
Cost shares
Distribution of any potential economic benefits (costs) from GI protection among land owners and producers
of “other” inputs depends on their respective cost shares: κ 1 and κ 2. In order to calculate the cost share of
land and “other” inputs in Oolong tea production, a field survey was conducted in Anxi County, Fujian
province in the year 2007. 40 Based on data from our field survey, the cost share of land (κ 1) in Oolong tea
production is 0.16.
Comparable data for Darjeeling tea is not available from India, mainly because of the very competitive
and secretive business strategy of each tea garden in the area. Owing to the non-availability of detailed
data on cost of production of Darjeeling tea we arbitrarily select κ 1 as 0.3.
This value reflects the strictly defined geographical boundaries of Darjeeling area in India which could
result in increased land rent in the region.
Elasticity of substitution
Estimates of the elasticity of substitution between land and other inputs vary, but these numbers typically
do not refer to substitution between land and all non-land inputs as an aggregate, for which the elasticity
of substitution should be smaller. 41 Following Hyman et al. 42 we calculated the elasticity of substitution
(σ) as:
(7)
40
The survey employed a stratified random selection method to choose two villages in two towns. According to the per capita income, the enumerators
divided all towns in Anxi County into two groups: rich towns and poor towns. One town from each group and one village from each town were randomly
selected. From each village 10 tea farmers were randomly selected for participating in the survey. The questionnaire used in the survey included
questions about tea production, costs and marketing. Even though the sample size is small, according to the local officials survey results reflect the
general trend in the region.
41
J.M. Alston, “Benefits and Beneficiaries from U.S. Farm Policy” (2007), at http://www.aei.org/docLib/20070515_alstonSubsidiesfinal.pdf
[Accessed March 15, 2011].
42
R.C. Hyman, J.M. Reilly, M.H. Babiker, A. De Masin and H.D. Jacoby, “Modeling Non-CO2 Greenhouse Gas Abatement” (2003) 8 Environmental
Modeling and Assessment 175.
(2011) 2 W.I.P.O.J., Issue 2 © 2011 Thomson Reuters (Professional) UK Limited