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Sherilyn Wee at the UTC Awards Banquet January 7 in Washington D.C. with keynote speaker, Dr. Beverly Scott, CEO of Beverly Scott and Associates.
UHERO congratulates Sherilyn Wee on receiving an Outstanding Student of the Year award, presented by the U.S. Department of Transportation (DOT). Sherilyn was recognized in Washington D.C. for her contribution to the transportation field through her research and leadership with the Electric Vehicle Transportation Center. For 26 years, the University Transportation Centers (UTC) Program, under the management of the U.S. DOT's Office of the Assistant Secretary for Research and Technology, has advanced U.S. technology and expertise in transportation through education, research, and technology transfer.
Sherilyn Wee is a postdoctoral researcher and former graduate research assistant at UHERO. She holds a Ph.D. in Economics from the University of Hawaii.
The unexpected election of Donald Trump has thrown a monkey wrench into forecasting the US and global economy. During the Presidential race, candidate Trump promised an array of dramatic policy changes, many of which could have dramatic economic impacts. The question now is which policies President Trump will in fact advance, which will be watered down or fall by the wayside, and whether Congress might have very different ideas.
President-elect Trump’s most controversial proposals could have profoundly negative economic effects. The biggest near-term concern is trade, where the President has broad latitude to act. He has threatened to impose large punitive tariffs on China and to “renegotiate” or abandon the North American Free Trade Agreement. Not only would unilateral US trade action be met with swift retaliation by trade partners, but it would be directly damaging to American firms, who now rely heavily on border-spanning global value chain production arrangements. Such actions would not return to the US lost manufacturing jobs, which have declined largely because of technological change. Instead, trade disruption would create losses across a broad swath of the American economy. In the near term, uncertainty about trade disruption could also damage investment in export-oriented sectors.
The proposed plans for massive tax cuts and infrastructure spending are more of a mixed bag. Attention to the nation’s decaying infrastructure is long overdue, but the timing of these actions is problematic. With the economy now close to full employment levels of activity, a dramatic fiscal stimulus could spark an acceleration of inflation. In response, the Fed would hike short-term interest rates, raising the risk of tipping the economy into recession. Trump’s policies as proposed would blow up the federal budget, leading to a higher government debt burden. Financial markets have moved in anticipation of at least some fiscal expansion, with equity markets rising on expected stronger demand and the likelihood of favored treatment for some industries, while bond markets have swooned under the fear of higher rates and higher inflation. It is unclear how far Congress will go in supporting the Trump fiscal agenda. It seems likely that only a more modest package of tax cuts and spending will get through, although the track record of fiscal restraint by past Republican Congresses is not good.
There are a number of areas where President-elect Trump’s proposals could have longer-term economic impacts, mostly on the negative side. The Trump agenda on immigration would be expensive and potentially very disruptive to labor markets and business operations. An overhaul of health care that did not adequately provide for the twenty million people who have obtained insurance under the Affordable Care Act would lead inevitably to a less healthy and less-productive labor force. Tax cuts that primarily benefit wealthier households would exacerbate existing problems of income inequality, class resentment, and political polarization. A poorer trade environment would hamper US and global growth. Stacked up against these fairly tangible risks is the less certain possibility that lower taxes and a reasoned approach to regulatory reform might spur efficiency gains.
At this point, there is simply a lot we do not know. It seems likely that many of the most extreme actions that President-elect Trump raised on the campaign trail will be moderated in their implementation. In some cases he has already telegraphed his intent to do so. At the same time, his mercurial nature makes it very difficult to know how he will proceed once in office.
For a forecaster, the question is how to build in assumptions about future policy when so much remains uncertain. For now, we have adjusted upward modestly our forecast for gross domestic product in 2017 to 2019, to reflect moderate fiscal stimulus. We have adjusted downward by a bit our forecast for subsequent years, reflecting our view that the changing environment for trade, immigration, and income inequality will have a persistent depressing effect on growth over the medium term. Expect us to make further adjustments to our US and global economic outlook as the policy picture becomes clearer in 2017.
Last year nearly one in three U.S. travelers stayed in home-based accommodation units compared to one in ten in 2011.1 A search by the New Orleans Planning Commission found more than 40 websites that facilitate short-term rentals ranging from single rooms in private homes to entire villas.2 The most conspicuous among them is Airbnb, self-described as a people-to-people platform founded in San Francisco in 2008. In 2016, Airbnb listed 3 million homes and hosted 70 million guests; by 2025, analysts predict the company’s share of U.S. hotel and short-term rentals will rise to 13% compared to 2.3% in 2016. Other well-known short term rental platforms include HomeAway (VRBO) and TripAdvisor (FlipKey).
Lanikai Park (East) by Ethan of Chapman
The sharp rise in home-share accommodations has caused great dismay among hoteliers and some city and state governments. The hotel industry has argued that home-share accommodations don’t play on a level playing field as hosts don’t pay local occupancy taxes or comply with regulations that hoteliers must. The complaints have been blunted somewhat by Airbnb agreeing in 2016 to collect occupancy and other taxes in over 200 jurisdictions around the world.
However, other concerns remain. They include the perceived negative impacts of illegal home-share rentals on local housing shortage, safety, and neighborhood life. (Rental discrimination has surfaced as another troubling issue.) Last November, Airbnb and Expedia’s HomeAway division were each fined $635,000 by the government of Barcelona, Spain for facilitating the rental of accommodation units that city officials said were unlicensed. The mayor of Barcelona said “We want people to visit us. But we also want this activity to be compatible with neighborhood life.” Airbnb said it will appeal.3 In October, 2016, Airbnb sued New York state’s attorney general, New York City and its mayor challenging a law that would levy fines as high as $7,500 for hosts who illegally list properties on a home-share rental platform. Airbnb argued that the law benefitted hotels at the expense of ordinary New Yorkers.4 However, in less than two months, Airbnb dropped its lawsuit as long as the city levies its fines on hosts and not Airbnb.5 Earlier, in June 2016, Airbnb sued San Francisco over a bill that required all Airbnb hosts to register with the city and would allow the city to fine Airbnb for each listing by an unregistered host.6 Airbnb argued that the city has violated the federal Communications Decency Act, which prohibits the company from being held accountable for website contents posted by its users. In July 2016, Hawaii Governor David Ige vetoed House Bill 1850—supported by both Airbnb and the State Department of Taxation—that would have allowed Airbnb and other home-share platforms to collect general excise and transient accommodations taxes on the state’s behalf. The bill would not require home-share companies to reveal host names or addresses. Governor Ige explained that signing the bill into law would encourage the illegal rental market “at a time when affordable rental housing is in such short supply in our communities and homelessness remains to be a critical concern statewide.”7 Airbnb public policy manager for the Northwest and Hawaii estimates that Airbnb’s Hawaii market has between 9,000 and 10,000 listings, which may or may not be available on any given day.8 The Hawaii Tourism Authority's study of "individually advertised units" in Hawaii in 2015 identified over 27,000 units advertised on Airbnb, VRBO, FlipKey and ClearStay. Since approximately 10,000 were advertised on more than one site, the study estimates that there were roughly 17,000 “actual” individually advertised units—and predominantly entire rather than shared units—in Hawaii in that year.9 Most of the units were very likely unlicensed.
Kailua Aerial by Peter French
A recent development in New Orleans offers hope that there may be a solution to the impasse between Governor Ige and Airbnb. A story in the New York Times suggests that New Orleans may become the “new model for Airbnb to work with cities.”10 A New Orleans City Planning Commission study of short term rentals in the city indicated that there are about 4,000 to 5,000 listings; Airbnb reported nearly 2,400 listing in 2016.
In New Orleans, Airbnb exhibited a more cooperative approach in negotiating with the city over regulations of short-term rentals. (The more conciliatory approach, subsequently stated in writing in Airbnb Public Policy Tool Chest, lays out policy options on how it will work with communities to enforce short-term rental rules.) As a result, new rules were passed by the New Orleans city council in early December.11 Key principles include:
- 1. Limit and reign in the expansive growth of short term rentals (STR) citywide;
- 2. Protect neighborhood character and minimize impacts to residential areas;
- 3. Enable economic opportunities;
- 4. Generate revenue for the City to pay for both enforcement and services;
- 5. Prioritize sensible enforcement.
Among other things, the new rules state specifically:
- 1. Airbnb will agree to sign agreements with the City to collect taxes and fees.
- 2. Hosts must have permits (valid for one year), and Airbnb will submit registration applications to the City on the hosts behalf. Registration information would include: name, listing address, tax address, and contact information. Penalties for violations of permit rules include daily fines, property liens, revocation of permit and discontinuation of electric service.
3. Airbnb will also agree to share data with the City on the volume of short term rentals.
- 4. The City can contact the company to request identification of suspect listings.
The City also capped room rentals to 90 days per year when hosts rent out entire homes. City officials also correctly recognized that “[t]he key to establishing an effective regulatory regime for short term rentals is to have an effective and robust enforcement mechanism.” Too often enforcement is short-changed due to lack of a permanent funding source. New Orleans levies a $1 nightly fee (in addition to the local hotel occupancy tax) to fund enforcement.
While New Orleans and Hawaii are not exactly comparable—Airbnb has to deal with both the State and the counties in Hawaii—a new, more cooperative environment between the company and local governments everywhere bodes well for Hawaii to reach a compromise that could produce a win-win situation for all stakeholders. That said, Hawaii has a long way to go before the state and the counties achieve sensible regulation and enforcement of short-term rentals. Getting on-line platforms to agree to collect taxes and share host and rental information is a step in the right direction, but crafting sensible permitting and enforcement rules is arguably a more difficult challenge. At the start of its deliberative process, New Orleans recognized that there is a demand for home-based rentals (Airbnb’s customer base comprises largely of millennials). While admitting that such rentals can pose problems, short-term rentals can also present an economic opportunity. Thus, banning them is not a sensible option. Consequently, New Orleans developed a three-part permitting system with the most stringent regulations imposed on rentals in residential areas where they might cause the greatest disruptions to neighborhood life. By contrast, Hawaii seems to be focused on finding ways to prevent illegal rentals without first developing a vision of the role of home-share rentals in Hawaii that allows such rentals to grow. Honolulu put a moratorium on them in 1989 while the number of illegal rentals have soared. Hawaii Tourism Authority is about to contract another study of short-term rentals in Hawaii, but the study will do little to address Hawaii’s ineffective regulatory system if it ends only at data gathering.
1Travel Weekly Daily Bulletin, “Year in Review, 2016,” December 22, 2016.
2City Planning Commission, City of New Orleans, Short Term Rental Study, revised January 28, 2016.
3Travel Weekly Daily Bulletin, “Airbnb, HomeAway each fined by Barcelona officials,” November 29, 2016.
4Travel Weekly Daily Bulletin, “Airbnb drops lawsuit against NYC over new state law,” December 4, 2016; New York Times, “Airbnb stands to lose business in NYC after dropping lawsuit,” December 11, 2016.
5New York Times, “Airbnb Ends Fight With New York City Over Fines,” December 3, 2016.
6New York Times, “Airbnb in Disputes With New York and San Francisco,” June 28, 2016. 7Honolulu Star Advertiser, “Gov. Ige says ‘Airbnb bill’ hides illegal rentals,” July 13, 2016. 8Honolulu Star Advertiser, “Committee advances vacation rental tax measure,” February 11, 2016.
9Hawaii Tourism Authority, 2015 Visitor Plant Inventory.
10New York Times, “New Orleans Becomes New Model for Airbnb to Work With Cities,” December 7, 2016.
11City of New Orleans, Short Term Rental Zoning Amendments & Enforcement Regulations, December 1, 2016; also New York Times, “New Orleans Becomes New Model for Airbnb to Work With Cities,” December 7, 2016.
Revisiting the Energy Paradox: Do Quantity and Price of Energy Efficient Appliances Respond to Changes in Energy Prices and Interest Rates?
Abstract: The notion of an energy efficiency gap posits that people under-invest in energy efficiency, since the present value of savings from more energy-efficient appliances, cars and other energy-consuming durable goods tends to far exceed their additional up-front cost. A considerable literature demonstrates this gap, and it has been a key factor underpinning energy-efficiency regulations. Critics contend that evidence backing an energy efficiency gap is mainly cross-sectional, and may be confounded by unobserved attributes of durable goods that are associated with energy efficiency. Taking an approach somewhat similar to recent work by Alcott and Wozny (2014), we use data on prices and quantities for a near population of sales of individual models of refrigerators, clothes washers, dishwashers and room air conditioners to revisit the question of whether an energy efficiency gap exists and how large it may be. Specifically, we consider whether changes in interest rates and electricity prices, which can significantly influence the present value of more efficient versus less efficient appliances, affect changes in sales and relative prices of more versus less efficient appliances. Model fixed effects control for unobserved attributes. We find that lower interest rates and higher electricity prices have driven sharp increases in sales of more energy efficient appliances, but that these changes tend to drive prices for more energy efficient appliances down, not up, with the exception of room air conditioners. The results suggest persistence of a very large energy efficiency gap. The results also suggest that economies of scale and imperfect competition likely complicate cost-benefit analysis of energy standards and other efficiency-related policies.
- Hyun-Gyu Kim and Michael Roberts, University of Hawaii Department of Economics and UHERO
Review by Arlan Brucal
On February 12, 2016 the Department of Energy (DOE) proposed another energy efficiency standard (expressed in minimum lumen output per watt) for General Service Lamp (GSL), better known as light bulbs. Based on DOE’s calculation, the proposed energy conservation standards for GSLs would save households up to 16 percent of energy use relative to the no-new-standards case. This translates to total consumer savings ranging from $4.4 billion to $9.1 billion,1 compared to just $221 million estimated cost to manufacturers. This rule is expected to be issued by January 1, 2017.
If DOE’s information on cost savings is accurate, wouldn’t it be in consumers’ best interest to invest in more energy efficient lightbulbs (e.g. light emitting diode or LEDs)? Then how come incandescent halogens2 still represent roughly 50 percent of recent new bulb shipments to U.S. retailers?3 Does this mean that consumers are not making the most economically rational decision? Do we have sufficient evidence to say that there exist market imperfections to merit the imposition of more stringent energy efficiency standards? Do consumers need government intervention to help them achieve greater cost savings (and significant reductions in carbon emissions as well)? And if they do, is imposing standards the most efficient way to achieve that or it just more politically feasible? Does the so-called energy efficiency gap exist and how big is it?
To help revisit the issue on energy efficiency gap – the tendency of consumers to discount future energy savings against upfront cost, Hyun-Gyu Kim, a PhD candidate at the Department of Economics at UH Manoa, presents his work with Michael Roberts that measures the value of energy efficiency in major US appliances and verifies if the energy efficiency gap is indeed large and significant. Using the most recent data on US major appliances and an up-to-date empirical strategy, they find that the price of energy efficient products relative to non-energy efficient products was surprisingly decreasing.
The figure below illustrates the predicted change in the price of Energy Star-certified appliances relative to non-certified appliances using the estimated coefficients (the blue line) and the coefficient signifying consumers’ equal valuation between upfront cost and future energy savings (red dashed line). The green vertical line indicates the Energy-Star certification threshold in terms of annual electricity use (kWh). If consumers equally value the extra cost of buying Energy Star refrigerators and the present value of future energy savings, then the price of refrigerators should have increased by $152 (see top left panel). However, their estimates imply that the relative price may have actually decreased by $510. The same findings apply to clothes washers (top right panel) and dishwashers (bottom left panel), indicating a decline in the relative price of Energy Star-certified to non-certified appliances by $139 and $206, respectively. Room AC (bottom right panel) illustrates a different trend, indicating consumers’ undervaluation of future energy cost (i.e. the relative price should have increased by $90 as opposed to the observed price that remained relatively constant.
Figure 1. Estimated price change with $0.10 increase in electricity price.
Hyun-Gyu explained that this seemingly unusual relationship between the extra upfront cost and the present value of operating cost (PVOC) is likely driven by imperfections in the market. Manufacturers may be facing declining cost with respect to producing more energy-efficient products due to technological advance (e.g. increased automation) or competitive sourcing of components.4 If this is true, any shift in market demand for more energy-efficient products would translate into a drop in the price of these products relative to non-efficient ones.
Consumers may also exhibit more elastic demand due to continuous increases in electricity prices, and thus in PVOC. As PVOC increases, more consumers start looking at more energy efficient appliances. This makes demand shift and become flatter, making the relative price to fall (See figure below).
Figure 2. Market demand for Energy Star certified products become more elastic
Note: The figure illustrates the changes in price and quantity when the demand for Energy Star (ES)-certified appliance becomes more elastic (D1 to D2). The y-axis of the graph indicates the price difference between ES and non-ES certified appliances, and the x-axis shows the sales of ES certified appliances. The black solid line denotes the (constant) marginal cost of an additional ES certified appliance in the market.
While the study did not explicitly answer the question of whether the energy efficiency gap is small or not, it puts more qualifications on the issue by demonstrating that the dynamics behind the energy efficiency gap is more complex than most of us think. Certainly, the market on energy-using durable goods is characterized by a number of market failures, including, among others, information asymmetry, externalities and imperfect competition. Whether consumers indeed undervalue future energy savings or just do not have that many options in the market to choose from or it is a combination both demand and supply factors, remains an empirical question.
Arlan Brucal is a postdoctoral researcher at the University of Hawai`i Economic Research Organization (UHERO).
1The estimates are based on Net Present Value at 7-percent and 3-percent discount rate, respectively.
2 Incandescent halogens are the tweaked incandescent bulbs introduced to meet the first phase of the standards that went into effect between 2012 and 2014. These bulbs are less energy efficient than LEDs.3 Extracted from
4 Ellis, M., Jollands, N., Harrington, L., & Meier, A. (2007, June). Do energy efficient appliances cost more. In Proceedings of the ECEEE 2007 Conference, Summer Study, Panel (Vol. 6).
UHERO is proud to announce that "Forecasting in a Mixed Up World: Nowcasting Hawaii Tourism" by Ashley Hirashima, James Jones, Carl Bonham and Peter Fuleky was awarded the Polzin Prize for Best Paper at the 2016 AUBER fall conference!
We evaluate the short term forecasting performance of methods that systematically incorporate high frequency information via covariates. Our study provides a thorough introduction of these methods. We highlight the distinguishing features and limitations of each tool and evaluate their forecasting performance in two tourism-specific applications. Our results indicate that compared to the exclusive use of low frequency aggregates, including timely intra-period data in the forecasting process results in significant gains in predictive accuracy. Anticipating growing popularity of these techniques among empirical analysts, we present practical implementation guidelines to facilitate their adoption.
The AUBER Polzin Prize is named for Paul Polzin, emeritus director of the University of Montana Bureau of Business and Economic Research and was offered for the first time in 2016. AUBER is a professional association of business and economic research centers in public and private universities. Founded in 1947, it strives to unite its members in the shared purpose of advancing economic research, promoting the collection and dissemination of economic information, facilitating the improvement in the services of its members, and demonstrating the importance of the economic development, outreach and research roles of its members. The annual AUBER conference was held in Honolulu in 2012.