Economics 435/535 – Natural Resource Economics Fall 2018.

 Problem Set #4 (optional if you have already submitted PS#1, PS#2 and PS#3) (Maximum possible points = 20.) We had two lectures that involved “choice models” as strategies for determining people’s willingness to pay for non-market public goods. Our lecture on November 6 covered a Stated Preference (SP) study designed to explore people’s preferences over alternative internal carbon pricing programs at UO. Updated slides for that lecture have been posted on Canvas. Our lecture on November 27 covered one Revealed Preference (RP) study that explores people’s preferences over alternative bird-watching (“birding”) destinations in Oregon and Washington states. We also looked briefly at another RP study that explores people’s preferences across alternative camping destinations in California. The same econometric approaches are used to analyze each type of data (either hypothetical choices for the carbon-price project, or the real choices, where available, as in the birding destination or camping destination studies). Most EC 435 students have not yet covered “choice models” in their econometrics training, so we outlined so-called “random utility models” that allow the researchers to estimate the marginal utilities associated with each attribute that can be quantified for every alternative. You can think of the parameter estimates as analogous to what would result from a regression of “utility from a trip to a given destination” on “the attributes of that destination.” 1. For the stated preference internal carbon pricing study (2 points each part, if graded) a. What were the main attributes of the different carbon-pricing programs described in the “choice experiments” that were featured in the survey? b. Do any of these programs currently exist at UO or elsewhere, so that we can observe which types of programs people prefer? Explain. c. We ended up with a range of different willingnesses to pay for any given carbon-pricing program for UO (i.e. the final sets of histograms). In the model, what accounts for heterogeneity in people’s willingnesses to pay for any specific program? d. Consider a basic program that would reduce carbon emissions by 40 percentage points, financed by a flat fee on all students and employees, with all the money spent on carbon-reduction projects at UO. Roughly what was the average WTP amount across the sample of respondents? e. How does this translate into a total WTP, across the university community, for a 40 percentage-point carbon reduction? How expensive could one big project be (to reduce UO’s carbon emissions by 40 percentage points), before the overall benefits to the university community would no longer justify the cost? Explain. f. Is this average WTP amount identical to the program cost that exactly half of the university’s population would vote to approve? Does a majority vote necessarily deliver an outcome with maximum net benefits? Explain (recalling the difference between a mean and a median if a distribution is skewed). 2. For the ecosystems services examples: i.e. the birding destination choice study or the campground choice study. (2 points each part, if graded) a. What were some of the destination attributes, besides species richness, that were included in the birding destination study? b. In the birding study, about how big is the average willingness to pay for one additional species at a destination? Does the number of species at a destination completely explain people’s willingness to pay to visit that destination? Explain. c. For the campground study, why do we not just use the entrance fee at the campground to estimate WTP for campground-or-nearby amenities? d. Is the campground study designed primarily to help campground managers decide how/whether to upgrade campground facilities, or what might be the maximum entrance fee that people would pay? Could it be used this way? Explain. e. What were some of the destination area attributes, besides just campground attributes like an indicator for the presence of flush toilets, that were used in the campground study? What did the presence of these other attributes permit the model to be used for? f. How do economists take (i.) an estimate of the marginal utility of a destination attribute and (ii.) an estimate of the marginal utility of (net) income (i.e. expenditures on all other goods and services) and convert this information into (iii.) an estimate of willingness to pay per unit of that destination attribute? g. How do we come up with an estimate of the representative consumer’s willingness to pay (i.e. willingness to incur private costs) to enjoy (consume?) a specific destination with specific attributes? h. (Harder) How do we figure out the overall welfare effect of a change in the level of a particular attribute at multiple destinations (e.g. an increase in average summer temperatures, or wildfires that obliterate almost all of the campgrounds in a large area of national forest)? i. (Harder) Must we assume that everyone would continue to visit the same sites the same number of times under changed conditions? What if people can re-optimize in their choice of sites (or just to do something else entirely)?