Soda tax really works in Berkeley

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A just released study on the effects of the Berkeley, California soda tax of one cent per ounce found that soda consumption has fallen 52% over the last four years. That is a remarkable price elasticity. Assuming a 20-ounce bottle costs $1.99, with a tax of 20 cents, that implies a price elasticity of -5. In other words, for every 1% o price increase, demand falls 5%. The study relied on household surveys, which are not always reliable about consumption quantities, so it would be interesting to see actual sales data.

Mismatch in job openings and the unemployed

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Evidence of how job training is lagging behind job needs. The U.S. Labor Department reported 7.3 million openings, but only 6.3 million people were actively seeking jobs and unemployed. Employers are not able to find the technically-trained individuals that they need for the changing economy. Only a small portion of this shortfall can be met through training in our standard educational institutions. We should be looking for other retraining solutions such as those in Europe.

Who says economists aren’t funny…

Willingness Toupee

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David M. McEvoyO. Ashton Morgan and John C. Whitehead

No 19-01, Working Papers from Department of Economics, Appalachian State University

Abstract: In this paper we tackle the hairy problem of male pattern baldness. We survey balding men and elicit their willingness to pay to move from their current sad situation to a more plentiful one. Then we comb-over the results. What’s the average willingness to pay to move from a glistening cue ball to a luscious mane? About $30,000.

Key Words: mullet, skullet, comb-over, ducktail, Beatlemania, buzz cut, whiffle, pageboy, attribute non-attendance

The sole reference: Carilli, Anthony M., “Scarcity, Specialization, and Squishees,” Chapter 1 in Homer economicus: The Simpsons and economics. Joshua Hall, ed., Stanford University Press, 2014.

Some sample footnotes:

  1. As is standard in the discipline, author order is determined by reverse Norwood Baldness Scale.
  2. The “stone piece” was a block of dark slate tied around the head to achieve the appearance of a full head of hair. While there are no sources of any such thing actually taking place, the authors imagine that it must have happened.
  3. “In ‘Simpson and Delilah,’ Homer attempts to pursue an executive position in which he doesn’t have a comparative advantage. Mr. Burns confuses Homer with a young go-getter and promotes him to an executive position after Homer has managed to scam himself some Dimoxinil–a miracle cure for baldness–and grow some hair.” (Carilli 2014, p. 11)
  4. It is important to note that the authors did not even bother looking for other studies.

7. Both of these models can be found in the NLogit manual (www.limdep.com) or via Google Scholar. They’re legit but we really don’t want to add any references besides the Simpsons book.

9.Referee #2 may try to claim that you cannot estimate WTP from a mixed logit model with a price parameter distribution that includes negative values because these respondents’ WTP will be undefined. Since distributions that constrain WTP to the positive realm do not perform as well statistically as the normal (we didn’t really check this) and (likely) generate goofy WTP estimates, we choose to present WTP estimated with the mean coefficients. The gullible, er, reasonable, reader will just go along with it since the MXL WTP number is so close to the ECLC WTP estimate and this lends reliability to our data.

Relying on short term changes diminishes the promise of energy storage

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I posted this response on EDF’s blog about energy storage:

This post accepts too easily the conventional industry “wisdom” that the only valid price signals come from short term responses and effects. In general, storage and demand response is likely to lead to increased renewables investment even if in the short run GHG emissions increase. This post hints at that possibility, but it doesn’t make this point explicitly. (The only exception might be increased viability of baseloaded coal plants in the East, but even then I think that the lower cost of renewables is displacing retiring coal.)

We have two facts about the electric grid system that undermine the validity of short-term electricity market functionality and pricing. First, regulatory imperatives to guarantee system reliability causes new capacity to be built prior to any evidence of capacity or energy shortages in the ISO balancing markets. Second, fossil fueled generation is no longer the incremental new resource in much of the U.S. electricity grid. While the ISO energy markets still rely on fossil fueled generation as the “marginal” bidder, these markets are in fact just transmission balancing markets and not sources for meeting new incremental loads. Most of that incremental load is now being met by renewables with near zero operational costs. Those resources do not directly set the short-term prices. Combined with first shortcoming, the total short term price is substantially below the true marginal costs of new resources.

Storage policy and pricing should be set using long-term values and emission changes based on expected resource additions, not on tomorrow’s energy imbalance market price.

So much for nuclear power adding “resilience”

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From Utility Dive: The Salem NGS Unit 2 in New Jersey shutdown due to ice forming in its cooling water intake during the latest polar vortex event.

Coal can’t win even in Texas…

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Texas generated 30% of its electricity last year with carbon-free resources (mostly wind.) Coals has shrunk over the last decade from 37% to 25%.

PG&E “buys dear, sells cheap”

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PG&E spends $275 million a year on energy efficiency investments that reduce demand by 100 MW. It also spends $65 million a year on demand response to reduce peak loads by 400 MW.  If we assume that energy efficiency investments are effective an average of 12 years the incremental cost of those investments is $66 per MWH (6.6 cents per kWh). For demand response the incremental cost, which should match the market value, is $163 per kilowatt-year (or $13.60 per kW-month). Both of these values are reasonable investments for long-term resources.

Yet, PG&E argues in the PCIA exit fee proceeding and its annual ERRA generation cost proceeding that the appropriate market valuation for its resources are the short-term fire sale values that it realizes in the daily markets. According to PG&E, customers do not realize any additional value from holding these resources beyond what those resources can be bought and sold for the CAISO markets and in bilateral short-term deals.

So we are left with the obvious question: Why is PG&E continuing to invest in energy efficiency and demand response if the utility states that it can meet all of its needs in the short-term markets? This hypocrisy is probably best explained by PG&E manipulating the regulatory process. PG&E’s proposed “market valuation” sets the exit fee for community choice aggregation (CCA) at a high level. Instead, that market valuation should reflect how much CCAs have saved bundled customers in avoided procurement, and what PG&E pays for adding new resources.

A counter to UC’s skepticism about CCAs

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Kevin Novan from UC Davis wrote an article in the University of California Giannini Foundation’s Agriculture and Resource Economics Update entitled “Should Communities Get into the Power Marketing Business?” Novan was skeptical of the gains from community choice aggregation (CCA), concluding that continued centrally planned procurement was preferable. Other UC-affiliated energy economists have also expressed skepticism, including Catherine Wolfram, Severin Borenstein, and Maximilian Auffhammer.

At the heart of this issue is the question of whether the gains of “perfect” coordination outweigh the losses from rent-seeking and increased risks from centralized decision making. I don’t consider myself an Austrian economist, but I’m becoming a fan of the principle that the overall outcomes of many decentralized decisions is likely to be better than a single “all eggs in one basket” decision. We pretend that the “central” planner is somehow omniscient and prudently minimizes risks. But after three decades of regulatory practice, I see that the regulators are not particularly competent at choosing the best course of action and have difficulty understanding key concepts in risk mitigation.By distributing decision making, we better capture a range of risk tolerances and bring more information to the market place. There are further social gains from dispersed political decision making that brings accountability much closer to home and increases transparency. Of course, there’s a limit on how far decentralization should go–each household can’t effectively negotiate separate power contracts. But we gain much more information by adding a number of generation service providers or “load serving entities” (LSE) to the market.

I found several shortcomings with with Novan’s article that would change the tenor. I take each in turn:

  • He wrote “it remains to be seen whether local governments will make prudent decisions…” However, he did not provide the background which explains at least in part why the CCAs have arisen in the first place. Largely over the last 40 years, the utilities have made imprudent procurement and planning decisions. Whether those have been pushed on the utilities by the CPUC and Legislature or whether the IOUs have some responsibility, the fact is that neither institution sees real consequences for these decisions, neither financially or politically. In fact, the one time that a CPUC commissioner attempted to deliver consequences to the IOUs, she was fired and replaced by a former utility CEO. The appropriate comparison for local government decision making is to the current baseline record, not an academic hypothetical that will never exist. And by the way, government enterprise agencies, including municipal utilities, have a relatively good record as demonstrated as by lower electricity rates and relatively well managed, almost invisible capital intensive water and sanitation utilities. The current CCAs have a more extensive portfolio risk management system than PG&E—my calculation of PG&E’s implicit risk hedge in its renewables portfolio is an astounding 3.3 cents per kilowatt-hour.
  • Novan complains that CCAs have “dual objectives.” In fact they have “triple objectives,” the added one to encourage local economic development (sometimes through lower rates). I suggest reading the mission statements of the CCAs that have been created, including the local Valley Clean Energy Authority .
  • It’s not clear that “purchasing locally produced renewable energy will likely lead to more expensive renewable output” for at least two reasons. The first is that local power can avoid further transmission investment. The current CAISO transmission access charges range from $11 to $39 per megawatt-hour and is forecasted to continue to rise significantly (indicating transmission marginal costs are much above average costs). In a commentary on a UC Energy Institute blog, it was revealed that the Sunrise line may have cost as much as $80 per MWH for power from the desert. This wipes out much of the difference between utility scale and DG solar power. Building locally avoids yet more expensive transmission investment to the southeast desert. [I worked on the DRECP for the CEC.] In addition, local power can avoid distribution investment and will be reflected in the IOU’s distribution resource plans (DRP). And second, the scale economies for solar PV plants largely disappears after about 10 MW. So larger plants don’t necessarily mean cheaper, (especially if they have to implement more extensive environmental mitigation.) [I prepared the Cost of Generation model and report for the CEC from 2001-2013.]
  • It’s not necessary that more renewable capacity is needed for local generation. The average line losses in the CAISO system are about 6%, and those are greater from the far desert region. Whether increased productivity overcomes that difference is an empirical question that I haven’t seen answered satisfactorily yet.
  • Novan left unstated his premise defining “greener” renewables, but I presume that it’s based almost entirely on GHG emissions. However, local power is likely “greener” because it avoids other environmental impacts as well. Local renewables are much more likely to be built on brownfields and even rooftops so there’s not added footprints. In contrast there is growing opposition to new plants in the desert region. The second advantage is the avoidance of added transmission corridors. One only needs to look at the Sunrise and Tehachipi lines to see how those consequences can slow down the process. Local DG can avoid distribution investment that has consequences as well. Further, local power provides local system support that can displace local natural gas generation. In fact, one of the key issues for Southern California is the need to maintain in-basin generation to support imports of renewables across the LA Basin interface. [I assessed the need for local generation in the LA Basin in the face of various environmental regulations for the CEC.]

I was on the City of Davis Community Choice Energy Advisory Committee, and I am testifying on behalf of the California CCAs on the setting of the PCIA in several dockets. I have a Ph.D. from Berkeley’s ARE program and have worked on energy, environmental and water issues for about 30 years.

 

 

 

 

CCAs add renewables while utilities stand pat

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California’s community choice aggegrators (CCAs) are on track to meet their state-mandated renewable portfolio standard obligations. PG&E, SCE and SDG&E have not signed significant new renewable power capacity since 2015, while CCAs have been building new projects. To achieve zero carbon electricity by 2050 will require aggressive plans to procure new renewables soon.

Will Amazon’s HQ2 pay off for New York?

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Even though I have conducted regional economic impact studies, I’m always a bit skeptical when a project is touted as a huge payoff for taxpayer investment. Amazon’s HQ2 is a case in point. New York is claiming a $24 billion net return over 25 years from the $3.6 billion in tax breaks, based on impact analysis done with the REMI economic model. I would be interested in a retrospective analysis on the impact of Amazon’s HQ1 in Seattle. The campus is fairly self contained and it should be fairly straightforward to track the growth of Amazon employment in Seattle since the last 1990s. Clearly, there would be uncertainty about how to attribute regional economic activity to Amazon activity, but we could see bounds on various factors such as jobs and tax revenues. We could then see a comparison against the estimates for New York City.