Economy

At one point in my life I thought it would be cool to publish a paper in Human Dimensions of Wildlife. So I sent this paper there in 2002 and received an R&R. Here is the response to the referees:

Response to Referees

The empirical models have undergone significant change. When incorporating the trout fishing, deer hunting, and wildlife watching models into the analysis we began exploring an expanded set of independent variables. This is important because controlling for all possible factors that may affect the responses is necessary when searching for differences in the 1991 and 1996 survey. Also we no longer present willingness to pay estimates for three reasons: (1) the regression models are sufficient to conduct the hypothesis test for temporal reliability, (2) brevity and (3) these estimates are presented in detail in the previous analyses of the Fishing, Hunting, and Wildlife-Associated Recreation (FHWAR) data. We have completely rewritten the paper to improve the clarity of our presentation. We address specific comments of each referee below.

Referee #1 (Comments on the HDW Review Comments Sheet)

Paragraph 1: The empirical approach has been simplified to avoid confusion. Our empirical model is the probit to maintain consistency between the previous analyses of these data. An expanded discussion of the censored probit model has been added.

Paragraph 2: We have rewritten the conclusions to increase the clarity of discussion about temporal reliability.

Paragraph 3: We have dropped discussion of the catch per trip as a potential influence on willingness to pay. We have included a discussion of potential omitted variables including demand and supply factors not included in the survey data.

Paragraph 4: The entire paper has been rewritten to improve clarity.

Referee #2 (Comments on white paper)

Paragraphs 4-6: We have focused on the analysis that adjusts the sample for the bid distribution and state of residence. We have discarded from both surveys respondents who took trips outside the state of residence. In the bass fishing, trout fishing, and deer hunting models the average (inflation adjusted) bid amount in the 1991 survey is lower than in the 1996 survey. We have randomly discarded respondents so that the average bid amounts are not statistically different across year of the survey. The adjustments to the sample are described in the “data” section of the paper. Note that the empirical results are robust to samples in which these two adjustments are not made.

Paragraph 7: The word “trends” has been purged from the paper.

Paragraph 8: We have expanded our analysis to include each of the contingent valuation questions that appear in both the 1991 and 1996 FHWAR surveys: bass and trout fishing, deer hunting, and wildlife watching.

Paragraph 9: Appendix 1 and 2 are deleted. We provide more discussion about the survey questions, including the exact text of both the 1991 and 1996 questions, in the “survey background and methods” section of the paper. We focus on the log normal functional form stating that similar results are found for other functional forms of the bid amount.

As you can see, they asked us to do a lot of work, including re-estimation with more dependent variables than just bass and trout fishing. The editor rejected the revision:

The reviewers suggested refocusing the manuscript to highlight how methodological changes in the survey over the years have potentially influenced the findings and conclusions. Both reviewers note specific recommendations in this regard. Because the topic of temporal reliability is important for surveys like FHWAR, I encourage you to revise and resubmit the paper along the lines they suggest. In particular, you will need to include the 2001 FHWAR data.

I used the 1991 and 1996 data in the paper and the editor thought it would be a good idea to update with another year’s worth of data. I didn’t think so, especially since the 2001 data asked a completely different type of willingness to pay question (open-ended). And, after reading two versions of the paper, the referees thought that the contingent valuation data wasn’t worth the trouble. Referee 1:

The strength of the paper lies not in the probit model, but in highlighting how methodology can influence the findings and the conclusions that can be drawn. A probit model might be still be used, but the variables in the model should be methodological variables (type of question asked [dichotomous choice versus iterative bid], recall period, etc.), rather than variables like PUBLIC, PRIVATE, PHOTO, etc.

Referee 2:

My view is that the authors should forget their probit analysis and concentrate on whether there appear to be “conventional” reliability and bias problems that make comparison of 1991 and 1996 likely to be a comparison dominated by bias or error rather than showing validity. …

My personal view is that there is probably enough in the current paper about changes and incompatibilities that the paper can be easily revamped along the lines suggested. In fact, at one point it seemed to me that the authors were going to study the distributions of responses for 1991 and 1996 and discover that response patterns were such that testing for temporal reliability made no sense.

In short, both referees thought a paper with a different focus would be a good idea and the editor agreed. As it was, the different paper wasn’t something that I wanted to write since it was really beyond my research interests. So, I sent the paper to JARE in 2002 (reject), the Journal of Leisure Research (JLR) in 2003 (reject) and Ecological Economics in 2005 (reject). I think it was a JLR referee who was so incensed at our analysis that he threatened to write a comment on the paper if it was published. After a cooling off period, I sent it to Applied Economics in 2005. Here is the editor’s response:

We have had difficulty in obtaining timely reports on your paper. Accordingly, I have read it myself and I have also sought the advice of an associate editor. We were both impressed with your paper and I have therefore decided to accept it without further revision for publication in Applied Economics. It is a good piece of applied work.

It was around this time that I may have decided it wasn’t such a great idea to engage with a more multi-disciplinary audience. 

I didn’t revise the paper for this journal but here is what I wanted to say:

Reviewer #1: 1. This is an important contribution. However, I feel it would be much more support to the cause of maintenance of the waterways if there was an equally valid assessment of the commercial fishing and towing industry that depend on the AIWW for their livelihood.

Response: Agreed. Someone should write this paper. 

2. The authors need to better explain the difference between their derived value of $97 that each boater is willing to pay from the 47% of boaters that are willing to pay up to $100.

Response: 47% of respondents said that they would pay $100. The willingness to pay estimate is $97 which arises because the highest bid amount is so close to 50% … [OK: nothing snarky here] 

3. I believe that there must be a difference in value for each foot of depth based upon the draft and length of the waterway. This is not explored in the text or noted in the table of survey results.

Report: The model first estimates how trips will change with different depths in a Tobit and then uses the predicted trips as a covariate in the willingness to pay model. Each additional trip leads to an increase in WTP of $1.31. We’ve added a table to break the $1.31 down into different depths. [Again, nothing snarky … good comment]

4. I did not see any indication of consideration of users outside of North Carolina such as the boaters that annually migrate south each Winter and north each summer through North Carolina.

Response: That is because our sample frame and survey only covered boaters licensed in North Carolina.

5. Two pages of references for a ten page paper seems out of balance.

Response: Good point but should we have more references or less?

6. The statements made “Exogenous factors such as high energy prices, water pollution, beach erosion and damage caused by coastal storms has limited waterway access and use. The future impacts of climate change and sea level rise will also have negative impacts on marine recreational boating.” are very sweeping without support in the document and in some cases very misleading if not incorrect. These should be revised by the author.

Response: How would that statement be “very misleading if correct”?

Total Economic Valuation of Great Lakes Recreational Fisheries: Attribute Non-attendance, Hypothetical Bias and Insensitivity to Scope

John C. Whitehead, Louis Cornicelli and Gregory Howard

Abstract: We use stated preference methods to estimate willingness to pay to avoid reductions in recreational catch in Great Lakes fisheries. We compare willingness to pay estimates where uncertain “in favor” votes are recoded to “against” votes to an attribute non-attendance model that focuses on the policy cost attribute. We find that the two hypothetical bias models yield similar results. We estimate another attribute non-attendance model that also considers the scope of the policy and find that the scope elasticity is significantly underestimated in other models. The willingness to pay in this last model is higher than in the other models.

Key Words: Attribute non-attendance, Hypothetical bias, Scope test, Willingess to pay

URL: https://econpapers.repec.org/paper/aplwpaper/24-10.htm

The Aggregate Economic Value of Great Lakes Recreational Fishing Trips

John C. Whitehead, Louis Cornicelli, Lisa Bragg and Rob Southwick

Abstract: We use the contingent valuation method in a survey of Great Lakes anglers to estimate the willingness to pay for a Great Lakes recreational fishing trip. Employing various assumptions and models, we find that the willingness to pay for a trip ranges from $54 to $101 ($2020). We then combine the willingness to pay per trip estimates with an estimate of the number of trips and find that the aggregate economic value of Great Lakes fishing trips in the U.S. is $611 million. We conduct a sensitivity analysis over the estimates of willingness to pay and the number of trips and estimate that the 90% confidence interval around the mean estimate of $632 million is ($182.5, $1,553) million. 

URL: https://econpapers.repec.org/paper/aplwpaper/24-11.htm

They doth protest too much, methinks: Reply to “Reply to Whitehead”

John C. Whitehead

No 24-04, Working Papers from Department of Economics, Appalachian State University

Abstract: Desvousges, Mathews and Train (2020) point out a mistake in my comment on their 2015 paper. When this mistake is corrected the conclusions drawn in my comment are unchanged. In addition, the authors claim that I make another 11 “mistakes”. In this paper I argue that these “mistakes” are mostly fairly standard practice in the contingent valuation method. Desvousges, Mathews and Train misread and distort this literature. In addition, I place the comments and reply in the context of a larger debate over using the Contingent Valuation Method for Natural Resource Damage Assessment.

URL: https://econpapers.repec.org/paper/aplwpaper/24-04.htm

From the inbox:

The International Review of Environmental and Resource Economics has published the following new issue. The articles in this issue are freely avaible until 20 February[*]. For other issues or for subscription information, please visit the journal webpage.

Wow.

*Note: the website says free until January 20, not February.

From the NORC NOW email:

$394 billion. That’s how much hunters, anglers, and wildlife observers spent on being in the wild in 2022, according to the latest National Survey of Fishing, Hunting, and Wildlife-Associated Recreation. When the survey first launched in 1955, the best way to ask Americans about those pursuits was through in-person interviews. Fast forward to 2020, when the Association of Fish & Wildlife Agencies—in partnership with the U.S. Fish & Wildlife Service—tasked NORC with mitigating declining survey response rates and reducing costs. NORC revitalized the survey by streamlining its content and replacing in-person interviewing with a “push to web” approach that invites randomly selected and targeted households through mailed invitations to take the survey online, on paper, or by phone. NORC’s AmeriSpeak® Panel helped identify rural residents and our TrueNorth® methodology reduced bias in the targeted sample.

NORC completed 100,000+ interviews, which revealed that 57 percent of Americans (148 million) watched wildlife, 15 percent (40 million) fished, and six percent (14.4 million) hunted. All of these suggest significant contributions to local economies. Survey findings will help local and state organizations fine-tune their efforts to preserve the habitats for both wildlife and its enthusiasts.  

Read: 2022 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation report

Good luck using that link to find the actual report. When I click on PDF it takes me to a list of other reports and then I survey for National Survey and I’m in a loop.

The USFWS used the Census to do these surveys for decades. As far as I can tell, this survey had the biggest contingent valuation method sample in history until budget cuts with, I think, the 2011 survey and they went from dichotomous choice back to open-ended willingness to pay questions. This survey and, I think, the previous one dropped the CVM questions.

Here’s the link to a paper I wrote with the data a long time ago: https://www.tandfonline.com/doi/abs/10.1080/00036840500438996.

I wrote a referee comment to the effect of:

Many contingent valuation method researchers use the nonparametrice Turnbull WTP estimates for hypothesis testing. This is inappropriate when the data must be “pooled” to get the willingness to pay (e.g., the “vote in favor” variable) to decrease with the cost amount. Sometimes, due to small samples, poorly chosen cost amounts or respondent inattentiveness, the percentage of “vote in favor” responses is not monotonically decreasing with the cost amount. The Turnbull estimator requires that the “vote in favor” responses are pooled over prices until the pooled responses are monotonically decreasing. This is, in effect, a recoding of the dependent variable. This makes the WTP estimates inappropriate for hypothesis testing. 

The authors halfway defended their practice because everyone does it. Do I have to be your parent? If everyone does it, does that make it right?

Are there any other examples in the literature where we allow researchers to recode their dependent variable so that it conforms to theory and then use the recoded data for hypothesis testing?

Authors: John Whitehead and Tanga Mohr [1]

Introduction

The Regional Greenhouse Gas Initiative (RGGI) is a cap-and-trade program that covers the electric power sector in more than 10 northeastern states. The cap-and-trade program creates markets for a limited number CO2 allowances, reducing greenhouse gases. Laboratory experiments were used to inform RGGI about the most efficient design for the primary auction and the secondary markets (e.g., Shobe et al. 2010). These experiments were single unit auctions but RGGI conducts multi-unit auctions. The purpose of this research is to explore the efficiency of multi-unit auction designs in the RGGI context.

Auctions

In first price auctions, bidders pay their bid. Theory predicts that bidders in first price auctions of a single unit will shade their bids. In second price auctions, all winning bidders pay the same market clearing bid. Theory predicts that bids will be equal to value in second price auctions of a single unit. Theory is not so clear in first and second price multi-unit auctions (Khezr and Cumpston 2022).

Real and Hypothetical Auctions

Real auctions are incentivized; i.e., subject earnings are real and depend on bidding behavior. Hypothetical auctions are not incentivized; i.e., subject earnings are fixed and do not depend on bidding behavior. We expect incentivized subjects to make bids closer to theoretical predictions (noting that theoretical predictions are not sharp in multi-unit auctions) (see Mohr and Whitehead 2023).

Methods

We conducted multi-unit induced value auctions using the VECONLAB platform. In induced value auctions, subjects are told how much an item is worth and then make a bid for that item. Each subject has demand for three units and the induced value for each unit differs in each round and over 18 rounds of bidding. We have 74 subjects in four treatments:

Real, 1st price auction
Hypothetical, 1st price auction
Real, 2nd price auction
Hypothetical, 2nd price auction

We use latent class regression models to explore various bidding strategies that were used by subjects.

Results

Using naive models (assuming that all subjects behave in the same way), we find no differences in bidding behavior in real and hypothetical experimental sessions.

Using latent class models we identify two different types of bidding behavior for both auctions. In the first price auctions one class suggests that subjects in the hypothetical session bid their value and shade their bids by 85% in the real sessions. In the other class, all subjects shade their bids by 68%.

In the second price auctions one class suggests that hypothetical and real subjects shade their bids by 88% and 84%, respectively. In the other class, hypothetical and real subjects shade their bids by 53% and 72% respectively.

Conclusions

We find some evidence that real auctions yield results closer to theory. Latent class models can lend additional insights to experimental auction behavior. We plan to conduct more incentivized first and second price auctions in the future. [2] 

References

Khezr, Peyman, and Anne Cumpston. “A review of multiunit auctions with homogeneous goods.” Journal of Economic Surveys 36, no. 4 (2022): 1225-1247.

Mohr, Tanga, and John C. Whitehead. External Validity of Inferred Attribute NonAttendance: Evidence from a Laboratory Experiment with Real and Hypothetical Payoffs. Department of Economics Working Paper No. 23-05. 2023.

Shobe, William, Karen Palmer, Erica Myers, Charles Holt, Jacob Goeree, and Dallas Burtraw. “An experimental analysis of auctioning emission allowances under a loose cap.” Agricultural and Resource Economics Review 39, no. 2 (2010): 162-175.

Note

[1] This study was funded by the Walker College of Business Dean’s Club. It was conducted with a student at Appalachian State University who was going to use it for an Honors Thesis. The student ghosted on us and we’re left with the responsibility for producing a poster for the Dean’s Club poster session (a requirement for securing Dean’s Club funding). 

[2] More detail to come over the next 6 days …