1. Skip to navigation
  2. Skip to content
  3. Skip to sidebar

Economic Currents

Keep up to date with the latest UHERO news.

Vog: Using Volcanic Eruptions to Estimate the Health Costs of Particulate

Posted August 20, 2018 | Categories: Hawaii's Environment, Blog

Since its inception, the Environmental Protection Agency (EPA) in the United States has proven itself to be effective at reducing air pollution. For the six ‘criteria’ pollutants that the EPA is mandated to regulate, emissions of all six have declined substantially. Particulates have declined by 38% since 1990. Furthermore, large reductions in particulate pollution in the 1970s have been shown to be a direct effect of EPA regulation. Now that air pollution in many parts of the US has declined significantly, an important policy question becomes how much further reduction is desirable.

Understanding the optimal level of air pollution is critical to setting the National Ambient Air Quality Standards or NAAQS. However, doing so is hampered by two challenges. The first is that, while the costs of pollution abatement are straight-forward to measure using units such as kilowatts of energy or laptops produced, the benefits are harder to quantify. Randomized trials are not an option because it is unethical to deliberately expose people to toxic air pollution. The second challenge is that while the NAAQS correspond to one pollutant (e.g. carbon monoxide or sulfur dioxide), most sources of pollution emit many pollutants at once. As a result, identifying the costs of any one pollutant is very difficult as any given pollutant is confounded by others. Assigning blame to particulates then becomes a challenge. In fact, many academic studies that look at the effect of particulates alongside other pollutants find that particulates have no effect on health outcomes. One way to address these two challenges is to find a ‘natural’ experiment – a situation where the general public has been randomly exposed to pollution and, specifically particulates, in a way that mimics an actual experiment.

The largest stationary source of sulfur dioxide pollution in the US is Kīlauea volcano located on the island of Hawai`i. This sulfur dioxide reacts with sunlight, oxygen, dust and water in the air to produce ‘vog’ (volcanic smog) which is one species of particulate pollution. The Hawaiian Islands typically have some of the best air quality in the world. But whenever Kīlauea volcano starts emitting gases and trade winds die down, the state’s 1.4 million residents experience short-term exposure to elevated levels of particulates. Particulates are far-and-away the main pollutant in the State of Hawai`i and they are very weakly correlated with other pollutants unlike other sources of particulates such as coal-fired power plants.

In a recent paper, we leverage volcanic emissions from Kīlauea over the period 2000-2012 to estimate the causal impact of particulates on emergency room (ER) admissions and charges. We employ measurements of air quality taken from various monitoring stations across the state and administrative data on ER utilisation due to pulmonary-related reasons. An important feature of our study is that our cost data are more accurate than the cost measures used in much of the literature. We isolate variation in particulate pollution on the island of Oahu (which is to the northwest of the island of Hawai`i) that is the consequence of emissions from Kilauea and wind direction to estimate the health costs of particulates.

We find strong evidence that daily exposure to particulate pollution increases pulmonary-related ER admissions. Our instrumental variables estimates indicate that one standard deviation increase in particulates on Oahu increases ER charges for pulmonary-related reasons by 25-35%. These effects are mostly concentrated among the very young. We provide evidence of harm due to particulate pollution below the NAAQS.

- Tim Halliday, John Lynham, and Aureo de Paula


Variable Pricing and the Cost of Renewable Power

How much will it cost to eliminate use of fossil fuels? There is reason for optimism. Technological progress has lowered the cost of wind and solar power to make them competitive with coal and natural gas on a levelized basis. Despite this progress, a recent study by Gowrisankaran, Reynolds and Samano, “Intermittency and the Value of Renewable Energy” (JPE, 2016) indicates that the variability of solar and wind power makes the system-wide costs grow considerably as their share of the power mix rises. While battery costs are falling too, they are still expensive, and cannot easily deal with seasonal or episodic variation in supply.

To economists, the obvious solution to intermittency is real-time retail pricing that reflects the incremental cost and marginal willingness to pay for electricity. Variable pricing would create powerful incentives to efficiently store energy on a distributed basis or otherwise shift consumption from times and places of relatively scarce renewable supply to times and places of plenty. Electricity consumers already have access to many low-cost appliances and devices that store energy in different forms. By carefully timing water heating, electric vehicle charging and water pumping, using ice storage for cooling systems, making micro-adjustments for some kinds of refrigeration, or other means, electricity use can be shifted from seconds to many hours at low cost. Such mechanisms would need to be automated by smart devices acting on customers' behalf. These technologies can make electricity demand highly substitutable over time, at least over horizons up to a day or so. In addition to shifting the timing of electricity consumption within the day, customers facing dynamic prices can also adjust the total amount of power they consume each day, reducing total consumption during extended periods when power is scarce, or increasing it when power is abundant.

In a new study, Imelda, Matthias Fripp and Michael Roberts develop a novel model of power supply and demand to examine the extent to which variable pricing can make renewable energy more cost effective in the state of Hawai‘i. The model is novel in the way it simultaneously optimizes investment in generation capacity, storage capacity, and real-time operation of the system, including an account of reserves, a demand system with different interhour elasticities for different end uses, as well as substitution between electric power and other goods and services. Both supply and demand sides of the model can also provide reserves. The model is an extension of Switch, developed by Matthias Fripp in his PhD dissertation and applied to California. Earlier versions of the model (lacking reserves and demand-side integration) have also been implemented the western United States and other areas. The model is open source and fully adaptable to other settings, but requires a rather substantial amount of data.

Consistent with earlier studies, the authors find that dynamic pricing provides little social benefit in fossil-fuel-dominated power systems, only 2.6 to 4.6 percent of baseline annual expenditure. But dynamic pricing leads to a much greater social benefit of 8.5 to 23.4 percent in a 100 percent renewable power system with otherwise similar assumptions, even if the overall demand for electricity is inelastic (0.1). If overall demand for electricity is elastic (2.0), the social benefits of renewable energy are even greater, and variable pricing can improve welfare by as much as 47 percent of baseline expenditure.

When fully optimized, future high renewable systems, including 100 percent renewable, are remarkably affordable. The welfare maximizing (unconstrained) generation portfolio under the utility's projected 2045 technology and pessimistic interhour demand flexibility uses 79 percent renewable energy, without even accounting for pollution externalities. This optimized share is over 80 percent with more elastic and/or flexible demand, and the cost of growing the share of renewables above this optimum is fairly modest until the last 5 to 10 percent of fossil fuels are eliminated.

Hawai‘i has a natural advantage in adoption of large shares of renewable energy, with plentiful renewable resources and expensive conventional generation. However, the intermittency challenge is especially acute in Hawai‘i, due to the state’s geographic concentration. In continental regions, transmission provides a potentially low-cost alternative to storage and demand response for managing intermittency challenges, as well as transferring renewable power from areas rich in renewable resources to areas that are renewable energy poor. The new modeling framework can assess the substitution possibilities between transmission and demand response, and optimize high-dimensional chronological power systems in a realistic way.


The social cost of renewable electricity relative to a fossil future with flat pricing.

Click graph to enlarge.

Notes: Each line shows the social cost—the loss in total economic surplus (PS + CS)—as the share renewable electricity rises above the least-cost share, holding all else the same. Social cost is measured as percent of expenditure in the baseline scenario, which is a predominantly fossil system with flat pricing in the year 2045. Thus, values less than zero imply a welfare improvement compared to using a conventional fossil system in the future (excluding externalities). Graphs on the left assume current (2016) costs, while graphs on the right assume future (2045) costs. Comparison of the top two rows shows the influence of electric vehicles (EV), contrasting the current fleet share of 0.5 percent EV with 100 percent EV. In the top two rows the overall demand elasticity is fixed at the baseline of θ = 0.1. Comparison of the bottom two rows shows the influence of a more elastic demand (θ = 2 versus θ = 0.1), while holding the EV share fixed at 50 percent. In all graphs, black lines show the social cost with flat prices; dark green line show the social cost with variable prices and pessimistic interhour substitutability; and the light green lines show social cost with variable prices and optimistic interhour substitutability.

- Michael Roberts
UHERO Research Fellow and Professor of Economics


Publication: Do electric vehicle incentives matter? Evidence from the 50 U.S. states

Posted June 7, 2018 | Categories: Blog

UHERO congratulates Sherilyn Wee, Makena Coffman, and Sumner La Croix on the publication of, "Do electric vehicle incentives matter? Evidence from the 50 U.S. states," in Research Policy. This research measures the effectiveness of state-level policies on the adoption of electric vehicles in the United States. Read more about this in The Role of Policy and Peers in EV Adoption.

Is the Hawaii Convention Center Profitable?

Posted June 4, 2018 | Categories: Blog

In his testimony before the House Committee on Tourism on February 13, 2018, Hawaii Tourism Authority (HTA) CEO George Szegeti said “In CY2017 the convention center turned a net operating profit of $1.1 million, marking its second consecutive year of profitability.” This is surprising news, indeed. Convention centers in the U.S. are not designed to make a profit. So what explains the Hawaii Convention Center’s (HCC) remarkable and atypical success? It depends on what one means by “profit.”

The Convention Center Advisor (CCA) notes that for convention centers profit is a fungible concept. Sometimes it is “expressed as you may see it in a public corporation’s annual report. Sometimes it is expressed where revenues include unearned income (such as a government contribution, normally a hotel tax).” CCA argues that the appropriate way to measure a convention center’s performance is EBITDA, defined as earnings before interest, taxes, depreciation, and amortization. This would leave out unearned revenues, including any hotel tax subsidy. What is left is a measure which shows whether earned revenues can cover operating expenses. If not, how much subsidy would be required to make up the difference.

Let’s look at the FY 2017 annual financial statement for the Hawaii Convention Center as published in the 2017 HTA Annual Report to the Hawaii State Legislature.

Hawaii Convention Center (HCC)
Fiscal Year (FY) 2017 Actuals ($000)
     TAT Deposits – Convention Center Enterprise Special Fund $26,500
     Convention Center Operations 10,288
     Transfer from Tourism Special Fund for Convention Center Sales and Marketing 5,069
     Investment Pool Interest/Miscellaneous Receipts 68
HCC Expenditures  
     Convention Center Operations $10,721
     Convention Center Sales and Marketing 5,069
     Convention Center Repair and Maintenance 5,100
     Governance (Includes Conventional Center Insurance) 583

     Total Expenditures Prior to Payments on Obligation to State Department of Budget and Finance

     Payments on Obligation to State Department of Budget and Finance $20,000

Source: Hawaii Tourism Authority, 2017 Annual Report to the Hawaii State Legislature

A quick glance at HCC’s financial statement for FY2017 shows that total revenues ($41.925 million) barely exceeded total expenditures ($41.473 million). It’s a different story once unearned revenues are excluded.

More detailed examination finds earned revenues from convention center operations totaled $10.288 million while total operating expenditures totaled $21.473 million, or a deficit of $11.185 million. (HCC separates sales and marketing and repair and maintenance expenditures from “convention center facility operations” expenditures. But they are all part of total operating expenses.) Earned revenues comprised only about 25% of HCC’s total (earned plus unearned) revenues. Seventy-five percent of HCC’s total revenues came from transient accommodation tax revenues appropriated by the Legislature.

The financial statement also shows that HTA paid $20 million to the State Department of Budget and Finance (B&F) for convention center debt service. It was actually obligated to pay $26.4 million to B&F, or $6.4 million more than it actually paid. HTA was supposed to pay $26.4 million annually in debt service to 2027. HTA’s unilateral decision to reduce debt service payments to B&F resulted “in a $6,000,000 general fund loss per year.”

In an interview with the Honolulu Star Advertiser (12/24/2017), Marc Togashi, HTA vice president of finance, attributed the reduced debt service payments to “Complications relating to the state’s purchase of the Turtle Bay conservation easement” that “reduced HTA’s statutory funding by $6.5 million annually” and left HTA “without sufficient funds to pay the full $26.4 million obligation while also ensuring the Hawaii Convention Center had adequate funds to operate.” Thus, state subsidy is essential to the continued operation of the convention center.

HCC was not profitable shortly after it opened for business in 1998. It was not profitable in FY2017. The following performance data on earned revenues and operating costs further show the convention center incurred operating deficits every year between FY2012 and FY2017:

Fiscal Year Earned Revenues Operating Costs Deficit
2017 $10.288 million $21.473 million $11.185 million
2016 12.123 17.670 5.547
2015 6.521 18.883 12.362
2014 8.276 17.138 8.862
2013 9.264 16.313 7.049
2012 9.225 19.310 10.085

In determining the profitability of an investment, economists include both operating and capital costs. If convention center capital costs (=interest + depreciation) were included, the annual deficits would be much higher than those displayed above.

The fact that the Hawaii Convention Center loses money like other convention centers in the U.S. doesn’t mean that it was built following a hasty decision. As I wrote in my 2008 book (Developing a Dream Destination… p. 126), HCC was not “born out of a sudden fit of ‘irrational exuberance.’ The State went into it after years of deliberation.” It was not motivated purely by civic pride. Hawaii’s economy was in the doldrums during the 1990s. Leisure travel was slowing down, and the State wanted to promote convention tourism to complement leisure travel.

The State’s initial goal for the convention center was to attract large convention groups to the Islands to diversify Hawaii’s economy and spur economic growth. At the planning stage, potential convention bookings and attendance, thus economic benefits, were greatly exaggerated. Its final environmental impact statement (dated July 1995) envisioned the convention center to reach its operating capacity by 2004-2006; by then it was projected to host 60 events per year with an average attendance of 6,200 to 7,500 delegates. Instead, in 2004, the convention center booked 39 events with an average delegate count of 3,300. In 2005, HCC booked 46 events with an average delegate count of 3,829; the corresponding numbers for 2006 were 37 events and 2,626 delegates. HTA’s 2016 annual report to the Legislature showed that it had 20 definite bookings for the year with an expected delegate count of 56,540 for an average attendance figure of 2,827. The initial goal has not been achieved.

In the beginning HTA would not allow local events to be held at the convention center to placate anxious hoteliers fearful that their own meetings and convention businesses would have to compete with a subsidized facility. Public outrage and weak convention bookings forced HTA to change its mind. To make efficient use of the convention center, today many local events are held at HCC.

Did HCC spur convention tourism in Hawaii? Before the convention center was officially opened in 1998, the number of convention visitors averaged 259,078 per year from 1990-1997; from 1998 to 2017, the number of convention visitors averaged 267,954 per year. Counting all meetings, convention and incentive (MCI) visitors, the average MCI visitor number per year was 445,706 before 1998 and 461,675 after HCC was opened. While there are many factors that explain the ups and downs of the convention business—and it is an extremely volatile business—these numbers paint a sobering picture of the impact of HCC on convention tourism in Hawaii.

With disappointment growing, HTA changed the convention center management company from SMG Hawaii to AEG Facilities starting January 1, 2014. The challenge ahead is steep. With leisure tourism booming in Hawaii driving hotel room rates up to the highest levels in the nation, it will be difficult to convince convention planners to hold their meetings in Honolulu. And competition from other convention centers is fierce. According to Heywood Sanders, a leading expert on U.S. convention centers, in 2000 there was 52.1 million square feet of convention space in the U.S.; by 2016 that number had risen to 71.2 million square feet. There is simply too much convention center space around the country. Yet, the Washington State Convention Center in Seattle is about to embark on a $1.6 billion expansion project that would double its current space. New convention centers or expansion of existing ones are in the works in Oklahoma City, Albany (New York), Los Angeles Convention Center, Laredo (Texas) and by Caesars Entertainment in Las Vegas.

The 2018 Hawaii State Legislature finally changed the way HCC is funded. HB2010 HD1 SD2 CD1 relieves HTA’s obligation to repay the remaining debt on the convention center, saving HTA $26.4 million annually to 2027. It reduces the amount of TAT revenues allocated to the convention center enterprise special fund each year from $26.5 million to $16.5 million. In sum, the Hawaii Convention Center remains a subsidized facility and will no doubt remain so over its economic life.

Debt forgiveness does not mean that the capital cost of the convention center can now be ignored in determining the profitability of the facility. Nonetheless, it would still be an admirable feat if HCC is only able to cover its annual operating costs with its own (earned) revenues. That has not been achieved thus far. That's o.k. as long as residents want to have a world-class convention center and are willing to subsidize it.


(I thank Paul Brewbaker and Frank Haas for their excellent comments on an earlier draft. All omissions and errors are mine.)

- James Mak
UHERO Research Fellow and Emeritus Professor of Economics


A Pocket Full of PIMs

In the arcane parlance of utility regulation, PIMs are “Performance Incentive Mechanisms.”

This is where we’re headed because, slightly against my expectation, Governor Ige recently signed SB 2939, a bill unanimously passed by the legislature that requires that the Public Utilities Commission:

“…establish performance incentives and penalty mechanisms that directly tie an electric utility revenues to that utility’s achievement on performance metrics and break the direct link between allowed revenues and investment levels.”

A nice summary can be found here. In the world of utility regulation, this act might be the equivalent of what Joe Biden called a “Big F[reaking] Deal” for health care. No other state has moved to change the investor-owned utility business model so radically, particularly to “break the direct link between allowed revenues and investment levels.” Like Obamacare, it’s still a compromise with the existing system, one that maintains our investor-owned utility but aims to change its incentives and business model in a profound way.

Just to be clear, PIMs are not new. They have been a part of utility regulation for a long time. But along the lines of what a colleague said the other day, existing PIMs are a bit like children splashing water against the hull of the Titanic in a futile effort to change its course. The core of the utility’s business model, in Hawai‘i and everywhere else, is revenue connected to an excessive rate of return on its own capital expenditure. This act promises to remove that, and make performance metrics the new profit engine.

Will it work?

Well, it depends. Like most things, the devil is in the details. It’s going to be important to get the performance metrics right, and to attach the right level of reward and penalty associated with each one.

In the old textbook model of utility regulation, the main performance metric is cost, and this is easily incentivized with a price cap, one that is just high enough for the utility to earn a fair return, and perhaps gradually lowered over time if the properly incentivized utility finds lower-cost ways of producing and delivering the goods. Sometimes the incentive to keep costs low needs to be buttressed with quality metrics, like customer service and reliability. This old Palgrave chapter by David Newberry has a nice review of the standard thinking.

But this standard thinking, or even Newberry’s longer treatment, probably won’t work with electric utility of the future currently envisioned in Hawai‘i and other places embracing renewables. What’s new is the growth of distributed resources. This isn’t just rooftop solar. It’s batteries, hot water heaters, air conditioners, electric cars and all manner of electricity uses that have potential flexibility in their timing, and can therefore be employed in a way that makes management of intermittent renewables less costly. This changes standard regulatory frameworks because the utility is unlikely to own most of these flexible distributed resources, yet the way they are used and integrated into the system is key to keeping costs low. And since these resources can compete with the utility’s own investments, it creates a palpable conflict with existing assets owned by HECO, those seeking to sell renewable energy storage services, and with customers.

In other words, the integrated system’s costs no longer equal the utility’s costs.

This new law directs the Public Utilities Commission to reconcile conflicts by using performance metrics to better align interests and find the least cost path toward a renewable energy future.

All of which begs the question: What are the best metrics?

So far, the proposed metrics target plethora of narrow issues, hence the title of this post. These fall well short of an encompassing framework that could redefine the utility’s business model. But I think it’s possible to build such a metric. Economics provides some guidance, with reasonably comprehensive monetary metrics of the net social value of our electricity system, including distributed resources. We could even add costs of pollution externalities to such a metric.

Some may quibble with some of the assumptions, and that's an important conversation to have and revisit regularly. But if a reasonable consensus can be achieved about both the assumptions and the model, the PUC could tie the utility’s allowed revenue to a measure of this net social value. Or, more precisely, the difference between a reasonable, agreed-upon target for this metric and the outcome actually achieved. The target would be tied to clearly identifiable input costs, like fuel prices, the cost of renewable energy, battery storage costs, and even costs of capital, so that performance would hinge on how well the various resources are integrated and managed, if the utility can negotiate good deals for certain inputs, or avoid unnecessary expenditures through smart management. Utility ownership of assets would have nothing to do with it -- the utility would simply make more money if it facilitated more social value.

This idea bears more than a little resemblance to a standard way the PUC has always managed rate cases every three years or so to set allowed revenues and rate schedules. When they do this, the utility, PUC and consumer advocate rely on optimization models that are used to estimate costs and set allowed revenue. The idea laid out above bears some similarity to this process, except that it would encompass costs and benefits that would in one way or another extend beyond the utility’s own costs. The new big piece is incorporation of the demand side–-customers' benefits from electricity use. That’s something myself, Mathias Fripp and Imelda, a UH Mānoa PhD student, recently figured out how to do in order to show how much variable pricing and demand response can lower the cost renewable energy.

In conventional utility regulation, the model is used as a cost baseline to set allowed revenue. Here it would set the target level of social value.

Allowed Revenue = a + b ( social value - target social value)

Besides the model assumptions, which would set the target social value, the PUC would need to set levels for a and b, which set baseline revenue for the utility and the degree to which the utility would be rewarded or punished for exceeding or falling short of the target.

All of this may seem abstract, and on some level, it is. I can’t argue with the idea that this is a “black box” model (except that that is publicly available, and there is always a black box model). It will take some work to make it clearer for a broader audience. We'll work on that. It’s still early….

Stepping back, the big picture idea here is to cut all engines on the Titanic and harness the coordinated efforts of its captain together with those of a hundred tugboats to push the ship in better direction for everyone. The metaphorical iceberg here is mass grid defection, which I fear could be more likely, and sooner, than many realize.

- Michael Roberts
UHERO Research Fellow and Professor of Economics


Page: 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9