2.3 Discount Rates and the CAPM Used in Agriculture
The CAPM and the actualization rates have already been used in
agriculture long ago. The Capital Asset Pricing Model has been tested for
example to test the farm real estate market by Barry P. J. in the 1980's (Barry
P. J., 1980a). His conclusions were that the low betas (0.19 for the US)
observed for farm real estate made this investment valuable as a
diversification tool for portfolios and that the required rate of return for
the US farmland was 8.76%. Other studies have been done on the same subject to
test the interest for investors to diversify into farmland (Hanson & Myers,
1995). It seems that these conclusions remain true nowadays, as the foreign
investments in farmland increased strongly after the rise of the grain market
price in 2007.
Since then, the diversification into agricultural commodities
have been tested either. The results are interesting, because thanks to
negative correlation with other markets, this diversification reduces the risk
and are considered as profitable for investors (Sminou, 2010). The opposite
have been tested also, to see if farmers who own their lands have an interest
to diversify their investments with traditional financial tools (Nartea &
Webster, 2008). According to their results for New Zealand after the
deregulation of the market, the expected return of the farmers would increase
thanks to diversification, even if the expected return on farmland due to
capital gains (9.83%, 1988-2003) were higher than the expected returns of
ordinary shares (5.59%, for the same period). This potential gain comes from
the good diversification of the portfolio which reduces the risk but not the
overall return according to the authors.
On the other side, some studies have been done in agriculture
using the NPV method. Most of them
do not explain clearly how they chose
their discount factors. For example, investments in peach
orchards in India
have been tested with three discount rates proposed by NGOs: 6, 9 and 12% to
compare the NPV method with the amortization method (Gangwar,
Singh, & Mandal, 2008). Finally the authors retained the 12% discount
factor.
Barry P. J., at the beginning of the 1980's, has done a
research to evaluate the impacts of government support price programs on the
financial structure of the farms of US (Barry P. J., 1980b). In his
calculation, he used three pre-tax discount factors of 10%, 12% and 14%,
corresponding to an after tax discount factor of 7.8%, 8.16% and 7.0%
respectively. However, here the author selected the three pre-tax discount
factors arbitrarily.
More recently, Johnson M. R. (Johnson, 2002) presented its
method to calculate the capitalization rate for Kansas in a case study. He
starts first with the loan rate offered to farmers, and then he adds a
discretionary increase based on the risk premium and the tax effect. He obtains
a capitalization rate of 14.71% in 2000 (with a loan rate level of 8.94% and a
corporate tax rate at 30%). Using his method we would obtain around 10.5% of
capitalization rate for France (with a loan rate level of 3.5% and a corporate
tax rate at 33%). The discount factors found in the literature are therefore
ranging from 7.0% for the lowest, to 14.71% for the most recent study found
from the US. However, it would be hard to apply these methods to the French
context, because most of these discount factors are somehow based on
discretionary risk premiums or they are chosen totally arbitrarily.
| 
