Ski Resort Real Estate: Does Supply prevent Appreciation?

This paper examines the behavior of ski resort property in a major New England market over the last 25 years. A constructed property price series reveals that nominal prices are quite volatile and only slightly higher today than in 1980. These ?uctuations and trends are investigated with a time series VAR model. The ?ndings indicate that (1) natural snowfall is crucial to business;(2) regional annual business is central to individual resort demand and hence price appreciation; and (3) resort supply responds so elastically to any movement in prices, that it effectively curtails any long-term property appreciation. Impulse responses reveal that positive demand shocks fail to generate any long-term (real) price appreciation because of excessive new development. This behavior could be typical of many other ski resorts.

The Secular and Cyclic Behavior of "True" Construction Costs

Current construction cost indices typically are derived by applying national weights to local costs for materials and labor. In this study, construction cost indices are developed that are based on actual contractor tenders for projects. As such, they incorporate full variation in factor proportions, as well as factor costs, contractor overhead, and profit. Cost indices are produced for two product types, office and multi-family residential, in six different MSAs using F.W. Dodge project cost data from 1967 through the first half of 2004. Standard ‘‘hedonic’’ analysis is applied to control for variation in project scale and features to extract the true time trends in costs for each market. The findings indicated that real construction costs generally have fallen slightly over the last 35 years. In addition, no correlation is found between costs and building activity. Causal (IV) analysis implies that the construction industry is elastically supplied to local real estate markets, with any ‘‘excess’’ profits going to land and developer entrepreneurship. This is consistent with the traditional ‘‘urban land economics’’ literature.

Gamma-Ray Spectral Characteristics of Thermal and Non-Thermal Emission from Three Black Holes

Cygnus X-1 and the gamma-ray transients GROJ0422+32 and GROJ1719-24 displayed similar spectral properties when they underwent transitions between the high and low gamma-ray (30 keV to few MeV) intensity states. When these sources were in the high gamma-ray intensity state (gamma-2, for Cygnus X-1), their spectra featured two components: a Comptonized shape below 200-300 keV with a soft power-law tail (photon index >3) that extended to ~1 MeV or beyond. When the sources were in the low-intensity state (gamma-0, for Cygnus X-1), the Comptonized spectral shape below 200 keV typically vanished and the entire spectrum from 30 keV to ~1 MeV can be characterized by a single power law with a relatively harder photon index ~2-2.7. Consequently the high- and low-intensity gamma-ray spectra intersect, generally in the ~400 keV - 1 MeV range, in contrast to the spectral pivoting seen previously at lower (~10 keV) energies. The presence of the power-law component in both the high- and low-intensity gamma-ray spectra strongly suggests that the non-thermal process is likely to be at work in both the high and the low-intensity situations. We have suggested a possible scenario (Ling & Wheaton, 2003), by combining the ADAF model of Esin et al. (1998) with a separate jet region that produces the non-thermal gamma-ray emission, and which explains the state transitions. Such a scenario will be discussed in the context of the observational evidence, summarized above, from the database produced by EBOP, JPL's BATSE earth occultation analysis system.Comment: 6 pages, 3 figures, accepted for publication in Proceedings of 2004 Microquasar Conference, Beijing, China, Chinese Journal of Astronomy and Astrophysics, minor corrections per refere

The 1998 ?2005 Housing "Bubble" and the Current "Correction": What’s Different This Time?

This paper examines the inflation in housing prices between 1998 and 2005 and investigates whether this run-up in prices can be ‘‘explained’’ by increases in demand fundamentals such as population, income growth, and the decline in interest rates over this period. Time series models are estimated for 59 MSA markets and price changes from 1998 to 2005 are dynamically forecast using actual economic fundamentals to drive the models. In all 59 markets, the growth in fundamentals from 1998 to 2005 forecasts price growth that is far below that which actually occurred. An examination of the 2005 forecast errors reveals they are greater in larger MSAs, in MSAs where second home and speculative buying was prevalent, and in MSAs where indicators suggest the sub-prime mortgage market was most active. These latter factors are unique to the recent housing market and hence make it difficult to asses if and how far housing prices will ‘‘correct’’ after 2005.

What Determined the Great Cap Rate Compression of 2000–2007, and the Dramatic Reversal During the 2008–2009 Financial Crisis?

In this paper we revisit the many studies that have attempted to explain the determinants of commercial real estate capitalization rates. We introduce two new innovations. First we are able to incorporate two macroeconomic factors that greatly impact cap rates besides treasury rates and local market fundamentals – the variables most commonly used in such research. These are the general corporate risk premium operating in the economy, and the growth rate of debt relative to GDP in the general economy (liquidity). The addition of these factors greatly adds to the ability of previous models to explain the secular fall of cap rates in the last decade and their recent rise – in terms of traditional measures of within-sample fit. Our second innovation is methodological; our analysis uses a large and robust quarterly panel data set of over 30 US metropolitan areas from 1980q1 through 2009q3. With this data we compare 3 models: a “base model” and then one that selectively adds each of our macro-economic variables. We test the ability of each of these models to fit the 2002–2009 period using “back test” dynamic forecasts. Our conclusion is that much of the secular decline in cap rates from 2000 through 2007 and their subsequent rise seem attributable to the macro-economic factors and less to movements in market fundamentals

Property Taxes Under "Classificiation:" Why Do Firms pay More?

This paper examines how communities will behave if they are given the option of taxing the property of commercial establishments (factories, shopping centers, office buildings, etc) at different rates from residential housing. In the last 2 decades many states have enacted legislation which allows communities to discriminate in this manner – called “classification”. We build a simple model wherein firms provide tax revenue without using local services and also create a valuable local job base. Towns thus confront a well defined choice: raise commercial taxes and gain revenue but risk loosing jobs. Firms in turn need to choose a community to locate in but do so with a (finite) negative elasticity with respect to the town taxes. The model yields two schedules between commercial tax rates and firm concentration in a community. A “demand” schedule has greater firm concentration leading a town to select higher commercial taxes, while a “supply” schedule has higher taxes leading to less firm concentration. The model comparative statics suggest that smaller and wealthier communities will encourage firms by keeping taxes low and rely less on their tax subsidy. Empirically we create a panel of towns in Massachusetts that covers the years prior to and after the state allowed such tax discrimination. With this data we find that towns with more pre-existing commerce chose to discriminate most, that such higher taxes gradually do discourage firm location, and that smaller and wealthier towns tend not to engage in tax discrimination

The Co-movement of housing sales and housing prices : empirics and theory

March 1, 200

What will it take to restore the housing market?

March 1, 200