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Economic Currents

Keep up to date with the latest UHERO news.

Gauging Home Affordability: The Challenge

Posted December 2, 2015 | Categories: Hawaii's Economy, Blog

At a time of dwindling inventory and rising prices, housing affordability has once again become a hot topic in Hawaii. One way to quantify whether the typical single family home or condominium is “affordable” is to compare median sales prices to the value of a mortgage the median household income could support. However, mortgage payments do not capture all of the costs of homeownership. Below, we incorporate several additional costs and a number of different assumptions about mortgage characteristics to illustrate how they affect the affordability of a median priced homes and condos in Honolulu.

Beyond a down paymentand monthly mortgage payments, homeownership requires additional expenses. These include closing costs related to the purchase, which we estimate at 2% of the sale price, and periodic costs such as property taxes, insurance, and maintenance. Property taxes vary across counties, and residential property taxes as a percentage of the home’s assessed value range from 0.35% in Honolulu County to just over 1% in Hawaii County. Homeowner’s insurance is also quite variable, and a particular policy depends upon features of the home and surrounding area. We estimate insurance costs using the average of the 2015 premiums published by the State Department of Commerce and Consumer Affairs.

Condo association fees can range from less than $300 to well over $700 per month, and we take $500 per month as the approximate midpoint. All expenses associated with the structure, such as insurance and condo fees, are adjusted across time to reflect historical changes in construction costs. Finally, our estimates are contingent upon a buyer’s ability to come up with a down payment, which is a significant barrier to home ownership for many households. If a purchaser pays less than 20% as a down payment, lenders require insurance to cover non-payment of the mortgage. Based on data from the Federal Housing Administration, we use an annual mortgage insurance premium of 0.8% of the loan amount.

  

The first two figures plot single family home and condominium prices that are “affordable” for a family spending 30% of the median household income (estimated by the US Department of Housing and Urban Development) on homeownership under various scenarios. Not surprisingly, a simplified measure that focuses only on the downpayment and mortgage costs overstates the affordability of homes and condos in Honolulu. Using the assumptions listed above and UHERO’s forecasts for 2015 home prices and mortgage rates, the median household can only afford 75% of the median priced home. In contrast, condos remain within reach of the median household that can muster the 20% downpayment. For households making only a 5% downpayment, owning a median priced condo would require more than 30% of the median household income, with the exception of the period from 1997-2003 at the bottom of the last housing cycle. Finally, the last figure illustrates that families earning only 75% of the median household income can not afford a condominium if all the extra costs of ownership are factored in.

 

- Peter Fuleky


Research Driven Energy Policy

Hawaii is in the midst of transforming its electricity system into one with a lot more renewable energy. It’s an exciting time, but also a challenging one that is forcing the State to make tough decisions amid many uncertainties. There appears to be confusion about who bears responsibility for making these decisions. Take, for example, public discussion surrounding the potential merger of HECO and NextEra, which has focused at times on whether NextEra can be trusted to keep their commitments to meeting Hawaii’s clean energy goals. At face value, that discussion seems odd given the utility is regulated and obtains approval from the state Public Utilities Commission (PUC) for important policy changes. Meeting clean energy goals is a statutory mandate or regulatory requirement, not HECO’s or NextEra’s “choice”.*

It is possible that these concerns arise from the fact that the State’s goals have escape clauses. The Renewable Portfolio Standard (RPS), for example, includes a long list of reasons why the utility can be allowed to fall short of prescribed targets, including the cost of achieving the goals. Clearly, there are many ways the State might achieve its renewable energy goals, and the path we choose will have many consequences—for the cost of electricity, how the burden of those costs are allocated, how much energy we use, and the environmental impacts. Regardless of how the PUC decides the merger case, it is their job to ensure that the State’s goals are met in a cost effective manner.

Regardless of who owns the electric utility, given the pace and scale of changes to our electric system, there has to be a better way to fully utilize our local academic resources as we take on this formidable energy transformation. We need a mechanism for the utility, the PUC and other entities to engage in collaborative processes that results in an effective strategy befitting of the state’s multifaceted goals. These should include rigorous and transparent analysis of a wide range of policy alternatives from neutral parties.

We believe UHERO, as an objective data and research driven entity, can play a role in achieving the State’s clean energy goals and the need to lower and stabilize the cost of electricity. Several UHERO faculty and fellows have recently joined forces to form the Energy Policy and Planning Group. You may have seen some of the many blog posts or working papers we have released over the past year. A few things stand out from this line of research. First, is the merely obvious, reducing the cost of electricity in Hawaii can have significant impacts on our economy. Makena Coffman’s research showed that a 25% reduction in the price of electricity could raise Hawaii GDP by close to 1.5%. Moreover, focusing on making the business of contracting and pricing more efficient to get the incentives right is likely to create economic development opportunities through innovation in the production, delivery and use of energy.

Demand shifting is another active area of work that was discussed in some detail in "Efficient Design of Net Metering Agreements in Hawaii and Beyond" by Makena Coffman, Michael Roberts, Mathias Fripp, and Nori Tarui. This paper lays out several policy goals that are achievable in the near term, and some longer term goals. For example, Coffman et. al recommend an optional tariff, available for all customer classes, with hourly prices that reflect the continuous variation in supply and demand of electricity. In that way, customers will have incentives to reduce their use during times of high marginal cost (high loads with low renewable power production) and increase their demand during times of low marginal cost (low loads and/or high renewable power production). Customers who are able to shift demand will reduce their own costs and the system’s costs. And, variable pricing will open the door even wider to storage and related innovations. Such variable pricing will require smart meters, and HECO has already filed with the PUC to install smart meters.

There are thoughtful ways of incrementally modernizing the grid in a way that also facilitates customer choice. At first, smart meters need only be installed for households most willing to juggle variable pricing. Well-designed experimental pilots can be used to measure efficacy and guide future policies. To implement these policies it is imperative that the PUC possess the capacity to analyze the technical and economic merits of proposals or issues to be deliberated. UHERO faculty and fellows have been working on building such capabilities for several years. For example Matthias Fripp’s open source SWITCH model allows optimization of investment and electric system operation decisions to study alternative pathways to extremely high penetration renewables. And the UHERO electric sector model is tied to our General Equilibrium Model to translate energy systems decisions into economic outcomes.

We recommend using UHERO’s Energy Policy & Planning Group as a neutral, research-driven evaluator to model and analyze Hawaii’s energy policy. This role could be modeled after the role of the UH Hawaii Natural Energy Institute as a neutral evaluator of energy technology, or it could be less formal.

- Carl Bonham, Makena Coffman, and Michael Roberts

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*See also  "Who’s In Control Here" by Mina Morita.


Does PV Add Home Value?

Circuits with installed PV up to and greater than 250% of daytime minimum load. Source: HECO

Hawaii leads the nation with the highest per capita installation of solar photovoltaic (PV). High electricity rates—three times the national average, —a generous state tax credit, plummeting PV costs, and net energy metering (NEM) policy have all contributed to the proliferation of PV. Considering future cost savings, PV is an attractive investment, yielding an internal rate of return of 23% with the state tax credit, equivalent to a payback period of four years (Coffman et al., 2016). In a recent analysis I answer the question of how PV is capitalized into a home’s value.

Using econometric tools, I assess the impact of PV systems on home value for single-family resale homes on Oahu. Using home resale and PV building permit data from 2000-2013, I find that PV adds on average 5.4% to the value of a home. This translates to approximately $34,000 relative to the sales price of the median non-PV home of $630,000.  

This means that PV already installed on a home is worth about $4,000 more than the median value of a PV permit (approximately $30,000). While this may appear puzzling at first, issues of circuit saturation may well-explain this result. Calculating the stream of electricity savings* over 9 years (the average household tenure) and a typical 30-year mortgage respectively, reveals that a homebuyer is effectively paying $4,000 more for a PV home to receive between $14,000- 30,000 in electricity savings. This makes sense given many of the circuits in Hawaii have reached legal limits for PV installations and therefore new homebuyers have an expectation that future installations will be limited. Thus for many the choice isn’t purchasing a house without PV (and then installing it) but rather to gain access to PV (and future electricity savings).

An area of further inquiry in light of the recent PUC ruling is to extend the dataset to examine whether homes that are grandfathered under the NEM program are worth more.

- Sherilyn Wee



Coffman, M., Wee, S., Bonham, C., and Salim, G. (2016). “A Policy Analysis of Hawaii’s Solar Tax Credit Incentive.” Renewable Energy, 85, 1036-1043.

 

*The net present value calculation assumes a 5% discount rate, electricity price of 30 cents/kWh, a system cost of $4.50/watt (year 2013), 5.2 solar hours per day, 75% efficiency factor, and daily household consumption of 18 kWh.

Using Vog from Kilauea to Estimate the Health Consequences of Particulate and SO2 Pollution

Kīlauea volcano is the largest stationary source of sulfur dioxide (SO₂) pollution in the United States of America. The SO₂ that the volcano emits eventually forms particulate matter, another major pollutant. In a recent project, we use this exogenous source of pollution variation to estimate the impact of particulate matter and SO₂ on emergency room admissions and costs in the state of Hawai‘i.

To accomplish this, we employ two sources of data. The first is measurements of air quality collected by the Hawai‘i Department of Health taken from various monitoring stations across the state. The second is data on emergency room utilization due to cardio-pulmonary reasons which we obtained from the Hawai‘i Health Information Corporation. 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 then merged these data by region and day to obtain a comprehensive database of air quality and medical care utilization in the State of Hawai‘i. Importantly, we employed coarse geographic information on the patients’ residence (as opposed to the hospital in which they were admitted) when computing the utilization time series by region to ensure that our utilization measures corresponded more accurately with the pollution exposure. Using the merged database, we then employed regression techniques in which we related ER utilization and charges to measures of exposure to particulates and SO2 while controlling for comprehensive seasonal patterns and regional effects.

We find strong evidence that particulate pollution increases pulmonary-related hospitalization. Specifically, a one standard deviation increase in particulate pollution leads to a 2-3% increase in expenditures on emergency room visits for pulmonary-related outcomes. However, we do not find strong effects for pure SO₂ pollution or for cardiovascular outcomes. We also find no effect of volcanic pollution on fractures, our placebo outcome. Finally, the effects of particulate pollution on pulmonary-related admissions are most concentrated among the very young. Our estimates suggest that, since the large increase in emissions that began in 2008, the volcano has increased healthcare costs in Hawai‘i by approximately $6,277,204.

These estimates provide evidence of some of the external costs of particulate pollution. Importantly, other studies have had a difficult time unraveling the effects of particulate pollution from other types of pollution such as carbon monoxide because they tend to be highly correlated. In contrast, in our data, the correlation between particulate pollution and other pollutants (aside from SO2, of course) is considerably smaller than the other literature on the topic that largely relies on manmade sources of pollution. In this sense, we provide one of the best available estimates of the pure impact of particulate pollution on human health.

- Tim Halliday, John Lynham and Aureo de Paula

 


Visualizing Population Age Structure and the Economy

Changes in population age structure have important implications for the economies of all countries irrespective of their level of development. One reason age structure is so important is that children consume but produce little or nothing through their own labor. To survive and prosper they must depend on transfers from adults – their parents, of course, but also tax payers. High material standards of living are harder to achieve in countries with young populations, because the number of productive adults is low relative to the number of dependent children. Fertility decline has led to a demographic dividend as the number of dependent children has declined relative to the number of working-age adults. This phenomenon is captured by trends in the support ratio, a key summary measure shown in the Interactive Data Explorer. Other things equal, output per consumer is proportional to the support ratio, and the rate of growth of output per consumer equals the rate of growth of the support ratio.

The Interactive Data Explorer is based on National Transfer Accounts (NTA) and population estimates and projections for forty countries that vary greatly in their level of development, social, political and economic systems, and demographics. The interactive tool can be used to explore the economic role of age structure since 1950 and to assess the likely influence of demography over coming decades. The support ratio is a useful summary measure, but it is also important to drill more deeply into the data, a task made easier by the data explorer.

The rise in the support ratio or what we call the “first demographic dividend” can be seen by tracing the past of most high-income countries and many developing countries that now have low levels of fertility. South Korea’s support ratio, for example, increased from 0.67 in 1973 to 0.95 in 2006, a gain of over 30 percent. In some countries, like China and Vietnam, the gains are even greater. The Interactive Data Explorer shows that in other countries the first demographic dividend is more modest and that many African countries are just beginning to experience it.

An important question: Why does the support ratio rise more in some countries than others? One of the most important factors is the speed of fertility decline. The importance of this factor can be judged using the Interactive Data Explorer by selecting a country and a year in the future and then by choosing among alternative fertility scenarios. For Ethiopia in 2060, for example, the projected support ratio is 0.90 for the “Medium” fertility scenario as compared with 0.71 if fertility remains constant at the current level.

The economic impact of changing age structure depends on features of the economic lifecycle as measured by per capita consumption and labor income by age in National Transfer Accounts. On average, the gap between consumption and labor income is less for children and older adults in lower income countries than in higher income countries. In higher income countries, spending on the costly education of each child is relatively high, and often consumption by the elderly is much higher than consumption by younger adults. This can be seen by setting the Preview to “Per Capita Profiles” and looking at the thumbnails for 40 countries. (Spending on education, health, and other components of consumption is available in NTA but not shown in the data explorer.) General patterns can be seen in the per capita profiles, but also the importance of country-specific features. In a number of African countries the gap between consumption and labor income is high even among those in their 20s. This results in a depressed support ratio.

The rise in the support ratio is a transitory phenomenon and as populations begin to age the support ratio inevitably drops to lower levels. To see why this happens, pick a country, set Scale to “Percentages”, and press “play”, watching the upper right figure titled “Aggregate Consumption and Labor Income by Age”. Instead of high consumption among children, we have high consumption among the elderly. The transition is particularly strong in rapidly aging societies in East Asia and parts of Europe.

Fertility also plays a role here and given the low fertility scenario, aggregate consumption by the elderly would reach very high levels in many countries at time goes on. This can be seen by choosing some future year such as 2050 and varying the fertility level. The rise in old age consumption has a silver lining, however, to the extent that the elderly fund their own consumption by accumulating wealth or capital during their working years. Under these circumstances, the growth in old-age consumption will lead to a second demographic dividend as higher capital fuels development in the host country and possibly in other countries through higher rates of foreign investment.

- Ron Lee and Andy Mason

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