Consumer Learning, Habit Formation, and Heterogeneity: A
November 15, 2005
I formulate an econometric model of consumer learning and experimentation about new products
in markets for packaged goods that nests alternative sources of dynamics, such as habit formation.
The model is estimated on household level scanner data of laundry detergent purchases, and the
results suggest that consumers have very similar expectations of their match value with new products
before consumption experience with the good, and that once consumers have learned their true
match values they are very heterogeneous. The estimation results also suggest significant habit
formation. Using counterfactual computations derived from the estimates of the structural demand
model, I demonstrate that the presence of habit formation with learning changes the implications of
the standard empirical learning model: the intermediate run impact of an introductory price cut on
a new products market share is significantly greater when consumers only form habits as opposed
to learning and forming habits at the same time, which suggests that firms should combine price
cuts with introductory advertising or free samples to increase their impact.
I am indebted to my advisors, Susan Athey, Timothy Bresnahan and Wesley Hartmann for their support and comments.
I would also like to thank Liran Einav and Dan Quint for helpful comments. I would like to thank the Stanford Institute
for Economic Policy Research for financial support, and the James M. Kilts Center, GSB, University of Chicago, for
provision of the data set used in this paper.
An experience good is a product that must be consumed before an individual learns how much she
likes it. This makes purchasing the product a dynamic decision, since the consumers decision to
experiment with a new product is an investment that will pay off if the consumer likes the product
and purchases it again in the future. Consumer learning in experience goods markets has been an
important subject of theoretical research in industrial organization and marketing since the 1970s.
Learning can be an especially important factor in the demand for new products, and there is a
small empirical literature that quantifies learning in household panel data using structural demand
models with forward-looking consumers (for example, Erdem and Keane (1996), Crawford and Shum
(2000)). In these papers it is assumed that the only type of dynamics in demand come from learning,
and alternative types of dynamics, such as habit formation, are not modeled. Similarly, papers that
estimate other forms of dynamics (see Chintagunta, Kyriazidou and Perktold (1999) for an example)
usually only allow for one type of dynamics in demand.
In this paper, I estimate a structural model of learning and experimentation that nests alternative
sources of dynamics in demand, such as habit formation. Learning can be empirically separated from
habit formation through differences in the effect of having made a first purchase of a new product on
a consumers current purchase relative to the effect of having used a product in the previous purchase
event. Allowing for habit formation in addition to learning changes the implications of the standard
empirical learning model. For example, switching products becomes more costly, so consumers may
be less likely to experiment with new products. Also, the intermediate run impact of an introductory
price cut may be increased when compared to the learning only case, since consumers who purchase
the product and find they have a low match value for the product (alternatively, a low permanent
taste for the product) may nonetheless become habituated to it. Another contribution of this paper
relative to the existing literature is that I use a recently developed technique allowing Bayesian
estimation of a dynamic discrete choice model to include a richer heterogeneity structure than has
been included in most papers.
To motivate the research I will present in this paper, I will discuss a simple example of learning
in a packaged goods market. Consider a market for a frequently purchased packaged good with two
products: an established product that has been available for a long time, and a new product for
which we observe the introduction. Suppose that consumers have an individual-level intrinsic match
value for the new product that does not change over time. A researcher in economics or marketing
may be interested in knowing whether consumers need to learn that match value by purchasing
and consuming the product (if consumers need to learn by experience, there is a potential role
for informative advertising or free samples), or if they know their match value beforehand through
other means, such as experience with the established product or by examining the new products
package. Suppose that consumers in fact do not perfectly know their true match values, but only
have expectations about their true match values and must consume the new product to learn about
it. What should the researcher expect to observe? First, if consumers are forward-looking they
will recognize that there is value to learning about the new product, since they might like it and
keep purchasing it in the future. Forward-looking consumers will therefore have an incentive to
experiment with the product, which means that they will purchase it sooner than they would have
were they myopic. Therefore, the researcher should observe consumers purchasing the new product
very soon after its introduction. Second, the researcher should be able to infer whether consumers
match values for the product are higher or lower than for the established product after their first
purchase of it. If the researcher observes individual behavior over time, consumers who have high
match values for the new product will continue to purchase it after experimenting, and consumers
who have low match values will switch back to the established product.
A problem for the researcher is that there may be dynamics in demand that are not learning.
For example, some consumers may be variety-seeking: holding fixed their intrinsic match values, a
previous purchase of the new product will decrease their current marginal utility for the product.
These consumers will tend to purchase the new product very soon after its introduction and will
switch away from it afterwards. To the researcher, it may look like these consumers experimented
with the product and found their match value was low. Alternatively, some consumers could be
habit-formers: holding fixed their intrinsic match values, their marginal utility for the new product
could be increased by a previous purchase. When a habit-former makes a first purchase of the
new product, she will be likely to keep on purchasing it. To the researcher it may look like these
consumers have high match values for the new product. The researcher will therefore need to take
into account that these other types of dynamics exist in order to properly isolate learning.
A second problem for the researcher is that consumers may be heterogeneous in their price
sensitivities. Suppose that when the new product is introduced, its price is initially low and then it
is raised. Suppose further that there is a group of consumers who are very responsive to price cuts.
These consumers will purchase the new product right after its introduction, when it is inexpensive,
and will switch away from it as it gets more expensive. It the researcher does not take into account
that they are price sensitive, it may look like they experimented with the product and disliked it.
This brings me to the first contribution of this paper, which is to estimate a model of consumer
learning and experimentation on household panel data that nests alternative sources of dynamics
in demand, such as habit formation and consumer taste for variety. In my model, consumers are
forward-looking and take into account the effect of learning and alternative dynamics on their
future utility. I also allow a rich distribution of heterogeneity in consumer tastes, price sensitivities,
expectations of new product match values, and alternative dynamics. This paper is the first to
estimate such a demand model.
The model is estimated on household-level panel data for laundry detergent purchases. During
the time the data was collected, three new product introductions are observed. The results of the
estimation support the hypothesis that consumers learn about the three new products by experience:
before consumers make their first purchases of the new product, they have very similar expectations
about their intrinsic match values. After they purchase it for the first time, consumers realized
match values are very heterogeneous across the population. The estimation results also suggest that
more learning occurs among smaller and lower income households, and that most households form
habits with products in addition to learning.
An important question to consider is why it might be important for a researcher to differentiate
between learning and alternative sour