11 research outputs found

    ACross-Sectional Analysis of CapRates by MSA

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    Much attention has been paid to capitalization rates or “cap rates?defined as the net operating income over transaction price, also known as a “going-in?current yield on commercial real estate when calculated at the time of purchase. We know that there are a number of global factors that drive capital markets and required rates of return that help to explain observed cap rates over time, but we know little about factors driving the geographical cross-sectional variation of these cap rates. Why are cap rates for similar sized and type property so much lower or higher in one metropolitan statistical area than another? Using data from Real Capital Analytics for multifamily properties we explore several models that combine the expected influences from housing demand growth, supply constraints, liquidity risk and the interaction of these. We document a very strong and robust relation between supply constraints and cap rates as well as evidence of capital flowing from larger markets to smaller markets in recent years. We also find weak but generally supportive evidence of influences from expected growth rates, liquidity and other risk factors.

    A Note on Lending Indicators of Housing Market Price Trends

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    Most indicators of changing housing demand and supply provide signals for longer term trends. Many market participants such as mortgage lenders, speculators, real estate brokers, developers, and appraisers, would benefit if short term price trends could be better monitored and predicted. This research builds upon several simple and straightforward statistical indicators of housing market price movements to analyze either local, regional, or national trends. It utilizes existing housing resale data as well as new housing market data.

    Japanese Purchases, Exchange Rates, and Speculation in Residential Real Estate Markets

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    Several luxury single-family home markets in Hawaii have experienced significant price movements in 1987 and 1988, along with a tremendous influx of Japanese buyers. Most noteworthy is the Waialae-Kahala neighborhood in Honolulu, where average price increases of over 60% in the past two years have occurred. This surge in prices has stimulated a great deal of speculative interest. The purpose of this article is to examine the effect of exchange rates (yen/dollar) and Japanese buyers on selected residential market prices and turnover. Using the most exhaustive and complete data set available in Hawaii covering 1986 through early 1988, hedonic pricing models as well as descriptive statistics are used to examine the effects of strong foreign interest in local housing submarkets.

    A Comment on "Tax Rates and Implicit Rates of Return on Owner-Occupied Single-Family Housing"

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    In the Webb and Rubens article on homeowner rates of returns (Journal of Real Estate Research 2:2), they use a model that tends to underestimate the true returns to housing. Both their model and assumptions are reviewed in the discussion below, and modified using the identical data, to show the extent of the bias, and a more realistic result.

    Leveling the playing field: Out-of-town buyer Premiums in US Housing Markets over time

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    Purpose Historically, research shows that out-of-town buyers of real estate are informationally disadvantaged and therefore pay higher prices compared to in-town buyers. However, with the recent advent of online housing platforms, a plethora of information about the housing market is provided for free. The purpose of this paper is to examine whether out-of-town buyers do in fact pay a premium and why, and whether this premium has decreased because of better information availability. Design/methodology/approach A hedonic regression model over a ten-year window (2005, 2015) is developed to analyze condominium transactions in Miami-Dade County. The results are validated by various robustness checks and the propensity score matching algorithm to identify a comparable control sample for 2015 in terms of relevant housing characteristics. Findings The results support the hypothesis that out-of-town buyers pay higher prices for real estate, compared to their local counterparts, and that both search costs and anchoring cause a premium in both years, whereas wealth only plays a significant role in 2005. The premium because of search costs, and therefore, information availability has decreased slightly over time. Originality/value This is the first out-of-town paper that compares two points in time versus a single cross-section analysis. Besides the premium caused by information asymmetry/search costs measured by distance and the anchoring effect, the regression model is extended by the wealth effect

    Residential Mortgage Default Forecasting: How Much Do Price Trends Matter? Part 1

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    Default rates on mortgage loans are driven by a number of factors, including but not limited to the following: 1. Income to mortgage payment ratio 2. Credit behavior and attitudes toward paying obligations as reflected in credit scores 3. Loss of a job or unexpected medical expense 4. Available liquid assets that may be tapped for mortgage payments 5. Perceived and/or actual equity in the home as reflected in current values While all of the above are important, the last factor seems to dominate all the others. Home equity is a function of current market value and the loan-to-value (LTV) ratio of the original mortgage, along with any other debt added during ownership, such as second mortgages and home equity lines of credit, (HELOC). Here we focus on this last factor, home equity

    The Impact of Water front Location on Residential Home Values Considering Flood Risks

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    We confirm existing findings of significant premiums for waterfront proximity, more so for oceans, bays, and large lakes than rivers. We then expand research on housing price trends immediately before and after major storms in directly affected markets. Our findings support a consensus view that single-family home prices rebound quickly to prior macro trends after major storms, with little persistent negative impact on value. In addition, using elevation as a proxy for flood risks associated with sea level rise, we find inconsistent evidence that the market perceives flood risk and discounts property prices accordingly. The absence of a permanent market reaction may change as the market is exposed to increases in insurance premiums or other direct pricing of the risks. Our results suggest either a short-term horizon for buyers of coastal properties at risk, or a moral hazard problem whereby residential owners are dependent upon and subsidized by government and mispriced flood risk insurance premiums

    The Impact of Interest Rates and Employment on Nominal Housing Prices

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    This research examines how well nominal income, nominal interest rates and employment explain temporal variation in nominal metropolitan area house prices. Rather than use a traditional model of real house prices, we explain nominal house prices with a measure of "intrinsic" house value that combines local economic factors with an affordable price based upon what the local median income household could afford to pay at prevailing interest rates. The affordable price variable captures local household income trends and current interest rates. We then relate temporal variation in observed house prices to "intrinsic" value and estimate the parameters of separate autoregressive house price models for 316 cities. We observe that the coastal markets exhibit much greater appreciation/ depreciation rates and much more volatility than cities in the central portions of the country. Here we focus primarily on the impact of interest rates on nominal prices in various MSAs, a factor that many housing analyst have pointed to when debating the existence of housing bubbles. Some markets are much more or less responsive to interest rates than others. Supply constraints may explain some of this increased responsiveness.housing prices; negative equity; interest rate impact

    House Prices and Economic Growth

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    Economic growth, House prices, Wealth effect, Collateral effect, Common correlated effects estimators, Long horizon predictability, E23, E24, R11,
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