Smith, V. Kerry

English

Research Papers in Economics

Some Issues in Discrete Response 
Contingent Valuation Studies 
V. Kerry Smith 
The use of survey or contingent valuation 
methods to estimate an individual's valuation 
of non-marketed goods, especially environ-
mental resources, has attracted increasing at-
tention in recent years. Initially, research ef-
forts in this area were viewed by a majority of 
the economics profession with considerable 
skepticism. However, with the increased need 
for information on individuals' valuation of a 
whole range of environmental resources and 
limitations on the ability of indirect market-
based methods for valuing all of these re-
sources, there has been a substantial increase 
in the use of contingent valuation methods to 
provide this information. Indeed, a recent 
state-of-the-art assessment (see Cummings et 
al. [1984]) of the contingent valuation method 
(CVM) has been able to develop a set of refer-
ence operating conditions under which it was 
reasonable to expect the CVM approach 
would yield estimates with accuracy that was 
approximately comparable to the indirect 
methods. Clearly the definition of these condi-
tions is a judgmental one. Nonetheless, it was 
based on a substantial number of comparative 
studies evaluating the relationship between 
CVM and indirect market estimates of the ben-
efits associated with changes in specific envi-
ronmental resources. Moreover, it does reflect 
the changing attitude toward the CVM ap-
proach. It is therefore particularly appropriate 
to consider new directions in the development 
of the contingent valuation method. 
Michael Hanemann has provided an insight-
ful discussion of several issues that could eas-
ily form the basis for a new line of research on 
refining the contingent valuation methodol-
ogy. My comments on his paper focus on two 
generic issues raised by his discussion of the 
relationship between discrete response model- 
Centennial Professor of Economics, Vanderbilt University. 
Partial support for this research was provided under Cooperative 
Agreement No. CR-811075 from the U.S. Environmental 
Protection Agency. The views expressed are the author's and not 
the funding institution. 
ing and contingent valuation studies. The first 
of these concerns the development of models 
that are capable of describing how individuals 
will respond to a contingent valuation experi-
ment and the use of these models in helping to 
understand CVM responses. The second is a 
somewhat general issue. It arises in Hane-
mann's discussion of extensions to the CVM 
methodology, and the role of maintained hy-
potheses in the development of benefit esti-
mates for environmental resources. After de-
scribing each topic in the next two sections, 
the paper will conclude with a brief summary. 
Modeling the Individual Response Process: 
The Role of Talking to a Data Point 
One of the central questions in interpreting 
contingent valuation survey results concerns 
how the individual respondent treats the ques-
tions that are posed to him (or her). Quite 
appropriately, Hanemann approaches this 
problem by suggesting that current research 
should move beyond the classification of sur-
vey biases and address the problem of model-
ing how individuals respond to contingent val-
uation questions. He suggests that CVM re-
sponses be treated as containing systematic 
and non-systematic components. The ana-
lysts' problem is to develop a framework 
that allows the systematic component to be 
uncovered from the overall responses. One 
way to recover the systematic portion of the 
response (which is assumed to be associated 
with the individual's true preferences) is to 
develop a formal model of individual behavior 
in responding to the hypothetical institutions 
posed by the CVM experiment. 
A variety of such models have been devel-
oped in the past. Thayer [1981], for example, 
was the first to propose that a contingent valu-
ation bid was the weighted average of the 
starting point suggested by the interviewer to 
the respondent along with the individual's true 
valuation of the resource (or the change in 2         April  1985 
resource). A number of other investigators, 
Carson, Casterline, and Mitchell [1984] for 
example, have used a variety of decision rules 
to describe the way in which individuals might 
be assumed to respond to CV questions. 
Hanemann extends this work by proposing 
that a formal optimizing model be used to de-
scribe an individual's preferences. Moreover, 
he outlines a framework for Unking that model 
to these CVM response decision rules in either 
a stochastic or a non-stochastic format. This is 
clearly a significant advance over the past lit-
erature because it provides an explicit behav-
ioral explanation of an individual decision rule 
rather than an ad hoc description of what 
might be governing the process. 
My principal suggestion is that such models 
should be based on attempts to understand 
how individuals interpret CVM questions. If 
economists are serious about the process of 
using survey research to understand individ-
uals' valuation of environmental resources, 
then it is important to learn what other social 
scientists have recognized long ago. Com-
munication with individuals is not automatic. 
Our terms, as well as our conception of how 
households will understand and adjust to an 
activity, may not correspond to what individ-
uals would describe on their own. This is not 
to suggest that economic models of individual 
behavior are irrelevant, but rather to acknowl-
edge that individuals' explanations of what 
they are doing may not correspond to the way 
we would describe their actions to them. Con-
sequently, we need to learn to listen before we 
ask or model individuals' responses to CVM 
questions. This suggestion not only reinforces 
McCloskey's [1983] recent call for greater tol-
erance to the use of questionnaires and self-
descriptions, but argues that they are not lim-
ited to testing preconceived theories. If we are 
to avoid what he describes as "foolish in-
quiries" and the misuse of survey respon-
dents, we must learn to communicate with the 
individuals we wish to interview. This will 
often mean asking them what they think we are 
asking for! 
As the complexity of the survey research 
tasks and the degree of discrimination we re-
quest of individuals increases, it is especially 
important to discuss with potential respon-
dents the questions we wish to ask, and how 
they interpret those questions. Often they can 
tell us how to explain the situation so as to 
elicit the information we want. In effect, this 
suggestion argues that there is a step which 
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precedes the introduction of a formal model. It 
is an inductive evaluation of how individuals 
perceive the questions asked of them before 
forming their responses to a contingent valua-
tion survey. After this step has been satisfied 
(and it will likely need to be satisfied in a wide 
array of CVM applications before it is possible 
to substantively improve the formal modeling 
of the individuals' responses), then we should 
be able to significantly enhance the behavioral 
restrictions used in decomposing individuals' 
responses to contingent valuation surveys.
1 
The Role of Maintained Hypotheses in 
Benefit Estimation 
Applied micro economic research has seen a 
systematic change in the way in which the 
behavior of economic entities, both house-
holds and firms, is described empirically. Ini-
tial empirical work in modeling household de-
mands for goods and services and in describ-
ing firm behavior used fairly "loose" spec-
ifications of the behavioral relationships esti-
mated in that no close ties to economic theory 
were offered. We have seen progressive en-
hancements in the practice of empirical re-
search in both areas with fairly detailed func-
tional forms developed as well as more atten-
tion to the criteria for selecting among them.
2 
There has been growing interest in the de-
velopment of models for benefit estimation 
based on specific maintained hypotheses. 
Hanemann's proposals to develop methods for 
enhancing the quality of contingent valuation 
results are examples of this type of model-
ing. This approach argues (in the case of de-
mand modeling) that the specific estimating 
equation should be derived, analytically, from 
a specific utility function and budget con-
straint under the assumption of constrained 
utility maximization. 
An alternative approach would impose 
fewer restrictions of the function estimated, 
arguing instead that it is an approximation to a 
function that would result from the same op-
timization process. Without knowledge of the 
1 This is an activity that economists feel uncomfortable with. 
Nonetheless, there is a growing recognition that this type of re 
search is essential to the design of survey instruments. Indeed, the 
use of focus groups in marketing research has been a significant 
basis for the design and evaluation of survey research (see Bel- 
lenger et al. [1979], Axelrod [1979], and Buggie [1983]. 
2 For discussion  of this work  in  production  modeling,  see 
Jorgenson [forthcoming]. A somewhat early survey of demand 
modeling is given in Powell [1974]. Smith 
form for the utility function, it is implicitly 
argued that few restrictions should be im-
posed. Rather the data are presumably al-
lowed to "tell their story." Neither approach 
is ideal for obvious reasons. To develop exact 
estimating equations that follow from the be-
havioral descriptions of household actions re-
quires that simple tractable utility functions 
and budget constraints be used in describing 
the household preferences. Often these func-
tions will impose significant structure on the 
nature of these demand functions. By neces-
sity, these restrictions become a part of the 
maintained hypotheses used in organizing 
sample information and therefore in the esti-
mation of benefits. 
The alternative often relies on "high speed 
(but hopefully mindful) groping" to describe 
the nature of an individual's demand. This has 
been widely criticized because it has tended to 
completely misuse the principles of classical 
inference (see Wallace [1977], Learner [1978], 
[1983], and Ziemer [1984] as examples). 
Hanemann' s proposal follows the general 
logic of the first approach and offers an in-
teresting adaptation for the case of CVM sur-
veys. He argues that individuals may not 
know what their valuation of a particular envi-
ronmental or natural resource might be. For 
example, he observes that 
"I want to suggest that, most of the time, people do 
not consciously know their preferences; they usually 
cannot introspect their utility functions. Instead, they 
discover their preferences when they actually make a 
choice: a decision 'pops into' their head. Their pref-
erences are revealed to them as part of the actual 
choice. However, preferences are fairly stable (there 
may be a random component but there also is a sub-
stantial deterministic component); therefore, if a per-
son has faced the same choice on several previous 
occasions, he can estimate his own preferences with 
reasonable accuracy—he can predict what he would 
do if the choice arose in the future—by observing his 
own past actions." (p. 3) 
Under these circumstances, Hanemann sug-
gests a contingent valuation question that asks 
the individual to gauge whether his (or her) 
willingness to pay for a change in an environ-
mental good exceeds some bound may be 
easier to respond to and therefore provide a 
more accurate response.
3 One might criticize 
this approach on the grounds that it is incon-
sistent with the estimation of valuation infor- 
3 This follows  the  approach used  by  Bishop and  Heberlein 
[1979] and has been discussed in detail in Hanemann (1984], 
Issues in Discrete Response         3 
mation. Hanemann's argument is that it need 
not be. The responses to such questions to-
gether with the assumption that a specific utility 
function describes individual's preferences will 
allow the analyst to recover an estimate of that 
individual's willingness to pay. Thus, this is a 
clear example of how the prior information from 
theory can be used to help in organizing 
sample responses. In this case, even though 
the responses are not specific willingness to 
pay bids, it is possible to recover estimates of 
these values. The maintained hypothesis of 
utility maximization together with the assump-
tion of a form for the utility function and the 
budget constraint provides the needed sup-
plementary information. 
This seems quite sensible given our conven-
tional models of household behavior. How-
ever, it is important to appreciate just how far 
we are ''pushing that theory.'' Consider, 
again, the explanation that is being used to 
describe how the individual responds. Each 
individual does not know his (or her) willing-
ness to pay for new or previously unexperi-
enced goods or services. As a result, they are 
best confronted with a threshold and asked to 
judge how their willingness to pay relates to it. 
However, economists that analyze their re-
sponses are assumed to know exactly what the 
nature of each individual's utility function is 
(up to a monotonic transformation). Oth-
erwise, it would not be possible to recover 
estimates of the individual's willingness to 
pay. This seems to be an unreasonable set of 
assumptions. It remains an open question 
whether, even accepting the Hanemann model 
of the decision process, the estimation strat-
egy involving a revised question and specific 
utility function will provide "better" esti-
mates of individual valuation than questions 
that elicit bids used together with less restric-
tive prior information. This general issue can 
be applied to the whole line of research which 
begins with utility (or production) functions 
and attempts to derive estimating equations. It 
is an important and as yet unresolved issue. 
As Hanemann is implicitly suggesting, it may 
be especially important to the CVM approach 
to benefit estimation. 
It is not sufficient to argue that the imposi-
tion of parametric utility functions insures 
consistency, permits extrapolation, and avoids 
large differences between willingness to pay 
and willingness to sell questions. Each of 
these results may be symptomatic of errors in 
the way in which we are modeling individual 4        April  1985 
preferences or the constraints to behavior. 
Imposing a set of rigid maintained hypotheses 
to eliminate these inconsistencies does not 
necessarily improve the quality of the informa-
tion we get as a result. 
Summary 
Hannemann's paper raises a number of impor-
tant and interesting issues associated with im-
proving the use of contingent valuation meth-
ods in benefit estimation. It will surely stimu-
late a wide range of research in this area. 
Moreover, in the process of developing his 
arguments, Hanemann implicitly raises an im-
portant issue for benefit estimation. That is, in 
the development of economic models to de-
scribe individual behavior two approaches 
have been used. One might be characterized 
as the detection of economic structure with 
some maintained hypotheses but relying on 
empirical searching of the potential models. 
The alternative to this approach has been to 
impose fairly rigid maintained hypotheses and 
thereby "smooth" or reduce erratic responses 
from a given data set. It is not clear that the 
latter is necessarily superior to the former. If 
empirical research seeks to improve the quality 
(in terms of both bias and precision of our 
estimates) and to learn how individuals make 
the decisions we wish to describe, some mix-
ture of the two strategies is likely to offer a 
better strategy. By exposing these issues, 
Hanemann has offered not only a specific 
guide to new research in the use of the CVM 
approach, but has also exposed a more general 
set of issues concerning the appropriate use 
of the deductive insights from economic 
theory and the inductive information from ob-
serving and talking to economic agents in 
benefit estimation. 
References 
Axelrod, Myril D., "10 Essentials for Good Qualitative 
Research" in J. B. Higginbotham and K. K. Cox, 
       editors, Focus Group Interviews: A Reader (Chicago:            
       American Marketing Association), 1979.    
Bellenger, D. N., K. L. Bernhardt and J. L. Goldstucker, 
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"Qualitative Research Techniques: Focus Group In-
terviews" in J. B. Higginbotham and K. K. Cox, 
editors, Focus Group Interviews: A Reader (Chicago: 
American Marketing Association), 1979. 
Bishop, Richard C. and Thomas A. Heberlein, "Measur-
ing Values of Extra-Market Goods: Are Indirect 
Measures Biased?" American Journal of Agricultural 
Economics 61(1979):926-930. 
Buggie, Frederick D., "Focus Groups: Search for the 
'Right Product'," Management Review (1983):39-
41. 
Calder, Bobby J., "Focus Groups and the Nature of Qual-
itative Marketing Research," Journal of Marketing 
Research 14(1977):353-364. 
Carson, Richard T., Gary L. Casterline, and Robert C. 
Mitchell, "A Note on Testing and Correcting for 
Starting Point Bias in Contingent Valuation Sur-
veys," Discussion Paper No. D-I16, Resources for 
the Future, 1984. 
Cummings, Ronald G., David S. Brookshire and William 
D. Schulze, Valuing Environmental Goods: A State 
of the Arts Assessment of the Contingent Valuation 
Method, draft monograph, University of New Mex-
ico, 1984. 
Hanemann, W. Michael, "Welfare Evaluations in Contin-
gent Valuation Experiments with Discrete Re-
sponses," American Journal of Agricultural Econom-
ics 66(1984): 332-341. 
Hanemann, W. Michael, "Statistical Issues in Discrete 
Response Contingent Valuation Studies," North-
eastern Journal of Agricultural and Resource Eco-
nomics, this issue. 
Jorgenson, Dale W., forthcoming, "Econometric Meth-
ods for Modeling Producer Behavior" in Handbook 
of Econometrics, Vol. HI edited by Z. Griliches and 
M. Intrilligator (Amsterdam: North Holland). 
Learner, Edward E., Specification Searches: Ad Hoc In-
ferences With Non Experimental Data (New York: 
John Wiley & Sons), 1978. 
Learner, Edward E., "Let's Take the Con out of Econo-
metrics,"  American Economic Review 73(1983):31-
43. 
McCloskey, Donald N., "The Rhetoric of Economics," 
Journal of Economic Literature 21(1983):481-517. 
Powell, Alan A., Empirical Analytics of Demand Systems 
(Lexington, MA: D. C. Heath Company), 1974. 
Thayer, M. A., "Contingent Valuation Techniques for 
Assessing Environmental Impacts: Further Evi-
dence,"  Journal of Environmental Economics and 
Management 8(1981):27-44. 
Wallace, T. Dudley, "Pretest Estimation in Regression: A 
Survey," American Journal of Agricultural Econom-
ics 59(1977):431-443. 
Ziemer, Rod F., "Reporting Econometric Results: Be-
lieve It or Not?," Land Economics 60(1984): 122-
127. 

10 Essentials for Good Qualitative Research&quot;

A Note on Testing and Correcting for Starting Point Bias in Contingent Valuation Surveys,&quot; Discussion Paper No. D-I16, Resources for the Future,

Contingent Valuation Techniques for Assessing Environmental Impacts: Further Evidence,&quot;

Empirical Analytics of Demand Systems

Focus Groups and the Nature of Qualitative Marketing Research,&quot;

Focus Groups: Search for the 'Right Product',&quot; Management Review

Let's Take the Con out of Econometrics,&quot;

Measuring Values of Extra-Market Goods: Are Indirect Measures Biased?&quot;

NJARE &quot;Qualitative Research Techniques: Focus Group Interviews&quot;

Pretest Estimation in Regression: A Survey,&quot;

Reporting Econometric Results: Believe It or Not?,&quot;

Specification Searches: Ad Hoc Inferences With Non Experimental Data

The Rhetoric of Economics,&quot;

Valuing Environmental Goods: A State of the Arts Assessment of the Contingent Valuation Method, draft monograph,

Welfare Evaluations in Contingent Valuation Experiments with Discrete Responses,&quot;

SOME ISSUES IN DISCRETE RESPONSE CONTINGENT VALUATION STUDIES

SOME ISSUES IN DISCRETE RESPONSE CONTINGENT VALUATION STUDIES

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Research Papers in Economics