Environmental Economics

"How Large Are Global Energy Subsidies?"

David Coady, Ian W.H. Parry, Louis Sears and Baoping Shang:

This paper provides a comprehensive, updated picture of energy subsidies at the global and regional levels. It focuses on the broad notion of post-tax energy subsidies, which arise when consumer prices are below supply costs plus a tax to reflect environmental damage and an additional tax applied to all consumption goods to raise government revenues. Post-tax energy subsidies are dramatically higher than previously estimated, and are projected to remain high. These subsidies primarily reflect under-pricing from a domestic (rather than global) perspective, so even unilateral price reform is in countries’ own interests. The potential fiscal, environmental and welfare impacts of energy subsidy reform are substantial.

The key findings of the study are the following:

• Post-tax energy subsidies are dramatically higher than previously estimated—$4.9 trillion (6.5 percent of global GDP) in 2013, and projected to reach $5.3 trillion (6.5 percent of global GDP) in 2015.
• Post-tax subsidies are large and pervasive in both advanced and developing economies and among oil-producing and non-oil-producing countries alike. But these subsidies are especially large (about 13–18 percent) relative to GDP in Emerging and Developing Asia, the Middle East, North Africa, and Pakistan (MENAP), and the Commonwealth of Independent States (CIS).
• Among different energy products, coal accounts for the biggest subsidies, given its high environmental damage and because (unlike for road fuels) no country imposes meaningful excises on its consumption.
• Most energy subsidies arise from the failure to adequately charge for the cost of domestic environmental damage—only about one-quarter of the total is from climate change—so unilateral reform of energy subsidies is mostly in countries’ own interests, although global coordination could strengthen such efforts.
• The fiscal, environmental, and welfare impacts of energy subsidy reform are potentially enormous. Eliminating post-tax subsidies in 2015 could raise government revenue by $2.9 trillion (3.6 percent of global GDP), cut global CO2 emissions by more than 20 percent, and cut pre-mature air pollution deaths by more than half. After allowing for the higher energy costs faced by consumers, this action would raise global economic welfare by $1.8 trillion (2.2 percent of global GDP).

via www.envirovaluation.org

What market failure do energy subsidies correct? 

Here is the link: http://www.imf.org/external/pubs/cat/longres.aspx?sk=42940.0.

"Shell Assures Nation Most Arctic Wildlife To Go Extinct Well Before Next Spill"

The Onion:

Stating that any damage would be limited to just a handful of species that somehow managed to survive that long, officials from the Shell Oil Company assured the public Wednesday that most of the Arctic wildlife living near their proposed drilling site will be extinct well before their next oil spill. “After conducting several environmental impact studies, we can confidently say that our offshore drilling operations pose absolutely no threat to the Arctic’s hundreds of native species, which will have already been completely wiped out by the time any drilling mishap or crude oil spill takes place,” said Shell spokesman Curtis Smith, adding that the region’s polar bears, walruses, and bowhead whales will most likely be eliminated by some combination of overfishing, ocean acidification, and melting ice shelves long before the first drops of unrefined petroleum begin gushing into the Chuchki Sea. “We can assure you that there will be no repeat of the BP oil spill, in which a complex, thriving ecosystem was destroyed. At most, only some algae and maybe a few mackerel will still be around when our rig explodes and spews millions of gallons of oil into their habitat, and we believe those species will pretty much be on their last legs by then anyway.”

via www.theonion.com

Climate Change and Snot

I like when The Daily Show makes my job easy:

The Daily Show
Daily Show Full Episodes,  More Daily Show Videos,  Comedy Central Full Episodes

We've gotten to the point where journals should require social scientists to post their data before publication

And, at the least, every author should know that what they are submitting to journals is not made up data: 

Last week, [LaCour and Green's] finding that gay canvassers were in fact powerfully persuasive with people who had voted against same-sex marriage — published in December in Science, one of the world’s leading scientific journals — collapsed amid accusations that Mr. LaCour had misrepresented his study methods and lacked the evidence to back up his findings.

On Tuesday, Dr. Green asked the journal to retract the study because of Mr. LaCour’s failure to produce his original data. Mr. LaCour declined to be interviewed, but has said in statements that he stands by the findings.

The case has shaken not only the community of political scientists but also public trust in the way the scientific establishment vets new findings. It raises broad questions about the rigor of rules that guide a leading academic’s oversight of a graduate student’s research and of the peer review conducted of that research by Science.

New, previously unreported details have emerged that suggest serious lapses in the supervision of Mr. LaCour’s work. For example, Dr. Green said he had never asked Mr. LaCour to detail who was funding their research, and Mr. LaCour’s lawyer has told Science that Mr. LaCour did not pay participants in the study the fees he had claimed.

Dr. Green, who never saw the raw data on which the study was based, said he had repeatedly asked Mr. LaCour to post the data in a protected databank at the University of Michigan, where they could be examined later if needed. But Mr. LaCour did not.

“It’s a very delicate situation when a senior scholar makes a move to look at a junior scholar’s data set,” Dr. Green said. “This is his career, and if I reach in and grab it, it may seem like I’m boxing him out.”

But Dr. Ivan Oransky, A co-founder of “Retraction Watch,” which first published news of the allegations and Dr. Green’s retraction request, said, “At the end of the day he decided to trust LaCour, which was, in his own words, a mistake.” ...

Critics said the intense competition by graduate students to be published in prestigious journals, weak oversight by academic advisers and the rush by journals to publish studies that will attract attention too often led to sloppy and even unethical research methods. The now disputed study was covered by The New York Times, The Washington Post and The Wall Street Journal, among others.

“You don’t get a faculty position at Princeton by publishing something in the Journal Nobody-Ever-Heard-Of,” Dr. Oransky said. Is being lead author on a big study published in Science “enough to get a position in a prestigious university?” he asked, then answered: “They don’t care how well you taught. They don’t care about your peer reviews. They don’t care about your collegiality. They care about how many papers you publish in major journals.”

via www.nytimes.com

Here is what seems to have happened leading up to publication of this paper:

1. Junior scholar approaches senior scholar with an idea
2. Senior scholar is happy to be a co-author
3. Junior scholar makes up data
4. Senior scholar says post it at, I'm guessing, ICPSR
5. Junior scholar does not post the data at ICPSR
6. Senior scholar does not at any point of the process demand to see the data ("grab"? -- this suggests that collaborating scholars are thieves and there is no honor among thieves)
7. Senior scholar isn't curious about who funded the study
8. Senior scholar allows the paper to be submitted to Science, which isn't a second tier political science journal
9. The paper is discovered to be a fake, which was almost inevitable

These are not scholars at regional public state universities (one of them found that potential outcome to be very unattractive). This is the big time and the behavior is audacious. 

I've requested data from authors several times. Here are responses I've gotten:

1. Unanswered emails
2. Outright refusals because "we are still mining the data"
3. Receipt of the data and enough documentation to attempt replication

Number three is the only ethical response. The whole issue will be avoided when data must be made available as a requirement for publication. JAERE doesn't have a data policy in its instructions of authors. Neither does Resource and Energy Economics or JEEM or EARE. Only Land Economics has a data policy:

It is the policy of Land Economics to publish papers only on the condition that the data used in the analysis are: (1) clearly and precisely documented; (2) readily available to any researcher for purposes of replication; and (3) sufficiently detailed in the specifics of computation to permit replication. Appearance of an article in Land Economics constitutes evidence that authors understand these conditions and will abide by the stated requirements.

Here is the AER's Data Availability Policy. In short:

As soon as possible after acceptance, authors are expected to send their data, programs, and sufficient details to permit replication, in electronic form, to the AER office.

I think that every economics journal should adopt this policy. The benefit is that data is made available, results can be replicated and the social scientific endeavor is strengthened. The only cost, I think, is that authors must spend extra time putting their data into a format that is understandable by someone else. It is mostly an opportunity cost that will reduce the number of papers written in the long run. My guess is the papers that aren't written are the lowest quality papers so it really isn't much of a cost at all. The cost might even be a benefit (and, yes, I'm thinking of some of my papers). 

I'm claiming the credit and recognition I deserve

From the inbox:

Dear John,

On behalf of PLOS and the PLOS ONE editorial team, I would like to thank you for participating in the peer review process this past year at PLOS ONE. We very much appreciate your valuable input in 2014. We know there are many claims on your time and expertise but with your help, we have continued to publish an influential, lively and highly accessed Open Access journal. Simply put, we could not do it without you and the thousands of other volunteers for PLOS ONE and the other PLOS journals who graciously contributed time reviewing manuscripts.

A public “Thank You” to our 2014 reviewers – including you – was published in February 2015.

(2015) PLOS ONE 2014 Reviewer Thank You. PLoS ONE 10(2): e0121093. doi:10.1371/journal.pone.0121093

Your name is listed in the Supporting Information file associated with the article. I hope that you will be able to use this letter, along with the article citation, to claim the credit and recognition you deserve within your institution for supporting PLOS ONE and Open Access publishing.

From the webpage:

PLOS and the PLOS ONE editorial team would like to express our tremendous gratitude to all those individuals who participated in the peer review process this past year at PLOS ONE. 2014 was an amazing year for PLOS ONE; during the year, over 80,000 reviewers from around the world and across disciplines provided their expert input that led to publication of over 30,000 articles.

The names of our 2014 PLOS ONE reviewers are listed in S1 Reviewer List. It’s a lengthy list rivaled only by the depth of our gratitude. Thank you to all our reviewers for generously sharing your time, insight and expertise with PLOS ONE authors in the evaluation of their work. Your efforts are a key reason PLOS ONE is a successful publication and continues to be a force for positive change in scientific and medical publishing.

I clicked on the S1 Reviewer List *.txt link and this is what it looks like (you can find my name at the bottom): 

 

It’s a lengthy list rivaled only by ... it's lack of formatting. 

Bourbon barrel economics

From the inbox:

Bourbon Feels the Burn of a Barrel Shortage
by: Tripp Mickle
May 12, 2015

TOPICS: Supply and Demand

SUMMARY: Distilleries are navigating a bourbon-barrel shortage, as increased demand for the drink coincided with reduction of logging of the white oak wood. Prices of barrels are up sharply. The shortage reflects a supply-chain conundrum. Upstream, barrel makers face a wave of demand because a half dozen established bourbon distilleries and 300 new, craft distilleries are increasing production amid a bourbon boom. Downstream, they face a shortage of white oak wood used in barrels because the lumber industry hasn't rebounded from the housing market's collapse.

CLASSROOM APPLICATION: Students can evaluate the effect of an increased demand for bourbon barrels and white oak in general and the decrease in the supply of white oak on the equilibrium price of bourbon barrels.

QUESTIONS: 
1. (Introductory) Is the demand for bourbon barrels a derived demand?

2. (Introductory) What has caused the increasing demand for bourbon barrels? What has caused the increasing demand for white oak?

3. (Advanced) What has caused the decreased supply of white oak?

4. (Advanced) "Leroy McGinnis's Missouri-based company, McGinnis Wood Products Inc., gets about four email requests a day for barrels. He turns most down. Like many of his competitors, he has only enough capacity and wood to fill orders from longtime customers. The rest go on a waiting list, perpetuating a bourbon barrel shortage now entering its third year." Should Mr. McGinnis raise prices so as to eliminate the excess demand for his company's barrels?

Reviewed By: James Dearden, Lehigh University

Here are the quantities:

And from the article:

The logging industry last year rebounded to produce 8.6 billion board feet as the housing market recovered. But the white oak supply hasn’t caught up with demand from barrel makers. There was plenty of white oak to harvest, but not enough loggers to cut it, forestry experts say. “So many logging firms that went out of business or shrunk in size, their capacity was limited,” said Jeff Stringer, a University of Kentucky professor of hardwood silviculture and forest operations.

 

Mileage Taxes Coming to a State Near You?

Oregon is about to embark on a first-in-the-nation program that aims to charge car owners not for the fuel they use, but for the miles they drive.

The program is meant to help the state raise more revenue to pay for road and bridge projects at a time when money generated from gasoline taxes are declining across the country, in part, because of greater fuel efficiency and the increasing popularity of fuel-efficient, hybrid and electric cars.

Starting July 1, up to 5,000 volunteers in Oregon can sign up to drive with devices that collect data on how much they have driven and where. The volunteers will agree to pay 1.5 cents for each mile traveled on public roads within Oregon, instead of the tax now added when filling up at the pump.

via www.usatoday.com

Hmmmm...must be May and must be time for me to reharp on an idea I've been harping on for over 8 years now.  Here's the original harp:

All cars are subject to an annual fee based on miles driven.  The fee will be per mile driven and will be inversely proportional to the EPA calculated city fuel efficiency figure.  Keep reading for details...

Here's how it would work.  Each year, drivers will be required to have their mileage checked at an authorized service facility.  Based on the EPA certified city fuel efficiency rating provided by the EPA for the specific type of car, the car owner will pay a fee (call it F) per mile driven. The fee will be equal to the inverse of the EPA fuel efficiency figure. 

So consider two car types: a gas guzzler (GG) and a fuel efficient car (FE).  Suppose the gas guzzler has an EPA MPG rating of 15 mpg city and the FE car has a rating of 35 mpg city.  The per mile fuel efficiency payment for the gas guzzler will be $0.067 per mile drive (1/15) and the per mile fuel efficiency payment for the fuel efficient car will be $0.029 per mile driven.  If a driver of each type of car drives 12,000 miles a year, the GG driver will pay an annual fee of $804, and the FE driver will pay an annual fee of $348. 

The Fuel Efficiency Payment has a couple of nice features:

1) It places a higher burden on those driving less fuel efficient vehicles--that should satisfy those blaming the SUV drivers for all of the problems*.

2) It places a higher burden on those driving more.  By increasing the marginal cost per mile driven, total miles driven should decrease.

3) Assuming fuel efficiency and income are negatively correlated--that is, the rich tend to drive larger, more expensive, less fuel efficient cars--the Fuel Efficiency Payment places a higher burden on higher incomes.

4) It provides an incentive for drivers to switch to more fuel efficient vehicles.

Now that I've hopefully convinced you that a fuel efficiency payment will act as a type of gas guzzler tax that would be less of a burden on lower income drivers, would provide incentives for decreasing miles driven and would encourage a switch to more fuel efficient vehicles, I'd like to point out that the fuel efficiency payment is algebraically identical to a $1/gallon GAS TAX** that many economics including John and me think would go a long way toward solving many of the transportation related externalities.   

While flat mileage taxes like that proposed for Oregon have some advantages (they provide a more predictable and steadier stream of revenues), they do little to encourage higher fuel efficiency.  This seems particularly prescient given the recent shocking realization that low gas prices actually cause people to buy less fuel efficient vehicles:

With bargain gasoline prices putting more money in the pockets of Americans, owners of hybrids and electric vehicles are defecting to sport utility vehicles and other conventional models powered only by gasoline, according to Edmunds.com, an auto research firm.

There are limits, it appears, to how far consumers will go to own a car that became a rolling statement of environmental concern. In 2012, with gas prices soaring, an owner could expect a hybrid to pay back its higher upfront costs in as little as five years. Now, that oft-calculated payback period can extend to 10 years or more.

 

"Do demand curves slope upwards, or…downwards?"

Tyler Cowen:

I say downwards:

With bargain gasoline prices putting more money in the pockets of Americans, owners of hybrids and electric vehicles are defecting to sport utility vehicles and other conventional models powered only by gasoline, according to Edmunds.com, an auto research firm.

There are limits, it appears, to how far consumers will go to own a car that became a rolling statement of environmental concern. In 2012, with gas prices soaring, an owner could expect a hybrid to pay back its higher upfront costs in as little as five years. Now, that oft-calculated payback period can extend to 10 years or more.

“We’d all like to save the environment, but maybe not when it costs hundreds of dollars per year,” said Jessica Caldwell, director of industry analysis for Edmunds.com.

via marginalrevolution.com

The Institute for Environmental and Resource Economics in the Southern Appalachians

Source: http://www.phdcomics.com/comics.php?f=1801

At the risk of being called Professor know it all

I've spent most of the time since grades were submitted catching up on reviews. I'm getting old and tired of writing the same things over and over. For example, I tend to referee a few revealed and stated preference data combination papers each year. The data are typically collected from a survey eliciting recreational behavior. Data points should include:

1. ex-post revealed preference (RP) trips
2. ex-ante stated preference (SP) trips under most recent conditions (i.e., status quo)
3. SP trips under different conditions

Sometimes #2 is left out. Other times #1 and #2 are assumed equivalent in the empirical model. Here is a comment that I typically must include in a referee report:

The model includes a revealed preference trip question and a set of stated preference questions. This raises the possibility that hypothetical bias is present in all of the scenario change questions. Hypothetical bias can affect demand intercepts and shifts. This potential for bias needs to be explicitly addressed. See Whitehead et al., Marine Resource Economics 23(2):119-135, 2008.

I first heard the flippant remark that ex-post revealed preference trip data and ex-ante stated preference status quo trip data are essentially equivalent at a Camp Resources in Wilmington a long time ago. This is simply an assertion that has been shown to not always be true. If #1, #2 and #3 data points are collected then SP dummy (the kids call these "fixed effects") and slope change variables should be included in the model to test for hypothetical bias (i.e., RP and SP demands may be different). If data point #2 is not collected then the paper simply can not be used for policy analysis unless explicit caveats are made. For example, here is the caveat from Hynes and Greene, Land Economics (2012):

Also, it should be noted that Whitehead et al. (2008a) have shown that when the product of trips and consumer surplus per trip is taken as an estimate of consumer surplus per year in contingent behavior models, hypothetical bias may lead to upwardly biased seasonal consumer surplus estimates.¹² While this paper's contribution does not require the avoidance of this problem, we mention it in order to caution the reader who might wish to use the results for policy analysis.

--------------

¹²A possible solution to this problem is for the researcher to first ask respondents to report contingent behavior under the circumstances of no change in quality or site status prior to asking them to report contingent behavior under the circumstances of the change in the status quo.

I referee several other types of empirical paper that gives short shrift to data reporting. Here is a comment that I preach in the major capstone course and, somewhat surprisingly, must include in many referee reports:

The authors do not provide a summary of the data. Instead, table 1 is the regression analysis. In order to assess data quality and better understand the results of the regression analysis a univariate analysis of the dependent and independent variables is needed. One of these tables should include trip responses under each scenario.

The univariate tables can be the most interesting part of a paper. They lay out the potential relationships amongst the variables and make clear just what is included in the empirical model. Plus, when you don't include these numbers it looks like you are hiding something (e.g., crappy data). Here is the abstract from some recommended reading (it is on my reading list for senior capstone students):

A critical objective for many empirical studies is a thorough evaluation of both substantive importance and statistical significance. Feminist economists have critiqued neoclassical economics studies for an excessive focus on statistical machinery at the expense of substantive issues. Drawing from the ongoing debate about the rhetoric of economic inquiry and significance tests, this paper examines approaches for presenting empirical results effectively to ensure that the analysis is accurate, meaningful, and relevant for the conceptual and empirical context. To that end, it demonstrates several measurement issues that affect the interpretation of economic significance and are commonly overlooked in empirical studies. This paper provides guidelines for clearly communicating two distinct aspects of “significance” in empirical research, using prose, tables, and charts based on OLS, logit, and probit regression results. These guidelines are illustrated with samples of ineffective writing annotated to show weaknesses, followed by concrete examples and explanations of improved presentation.

Source: Miller, Jane E., and Yana van der Meulen Rodgers. "Economic importance and statistical significance: Guidelines for communicating empirical research." Feminist Economics 14, no. 2 (2008): 117-149.

I just submitted a review with both of these comments. So much for single blind peer review.