Agriculture Reference
In-Depth Information
Price Index
. To generate the format-specific price index, we first select a comparable basket of
items (30 product categories, see table 5 for the details) available for all three formats. After
the basket is constructed, we then calculate the average household consumption pattern for
the selected product categories in the basket from the initialization sample. Using these base
quantities together with the format-specific category price indexes, we estimate the cost at
each format, which we refer as overall price index.
Price Premium
. Since we observe only the prices for the products chosen by the household,
we use the following procedure to recover the “missing prices,” i.e. the ones for the
alternative choice, and then construct the price premium of organic based on the price
difference between the two. First, we look for the prices for the alternative at 1) the same
store, 2) the top 3 stores that the household most frequently visited in the past, 3) the same
store chain, and 4) the format of the specific store. We then use the average prices from the
most relevant group of stores (i.e. in the above order) as the proxy for the missing prices of
the alternative choice.
Table 6 summarizes the average price premium of organic versus conventional product
(milk and eggs) by store format and shopper type based on the actual purchase of each
transaction. The data show that price premium varies among stores of different formats and
between organic and conventional shoppers. In particular, we observe that organic price
premiums are at minimum in value-oriented stores, while high-end stores feature much
higher organic price premiums. In addition, consumers who purchased organic products in
general face the lower organic price premium compared to those who purchased
conventional alternative at the outlets of the same store format, except for the case of eggs at
high-end stores. We also observe sizably diminishing organic price premiums for all outlets
over the two periods. For example, in the case of eggs, the organic price premiums in the
value-oriented stores dropped from 275% to 106%, which is less than half of the former. The
only exception is the case of organic milk purchased in the value-oriented stores, the price
premium was 18.81% in 2005-06 and 19.92% in 2007-06. It likely indicates that organic price
premium for milk may have reached the low-end retailers' pricing constraint bounded by a
certain level of markup above the high production costs of organics.
3.4 The regression results
Table 7 presents the parameter estimation results from maximum likelihood estimation
(MLE) regression. Several key findings emerge from our analysis. The first three rows of
table 7 reveal the statistical association between store loyalty and the likelihood of
purchasing organics. The results are quite mixed yielding no clear conclusion about a
discernable pattern of behavior. For example, consumers with higher loyalty to value-
oriented stores were less likely to purchase organic milk in both periods. However, for eggs
increasing loyalty did not affect the probability of purchasing organic in the early period
(insignificant parameter estimate) but increased the probability of purchasing organics in
the latter period. For supermarkets, increased loyalty is associated with a lower likelihood
of purchasing organics in all periods for both milk and eggs. For high-end stores, increased
loyalty led to an increased likelihood of purchasing organic milk in the early period but
decreased probability in the latter period. Increased loyalty to high-end stores had no
impact on organic egg purchasing.
When we look at loyalty with respect changes across the two time periods, there is a general
pattern of increased organic purchasing in formats that have increased their organic
offerings. Note that in the case of value-oriented formats and supermarkets, the parameters
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