Richard K. Green

Follow the Leader: How Changes in Residential and Non- Residential Investment Predict Changes in GDP

This paper examines the effect of different kinds of investments on the business cycle. Specifically, it examines whether residential and non-residential investment Granger cause GDP, and whether GDP Granger causes each of these types of investments. The paper uses quarterly National Income and Products Data for the period 1959 to 1992. Under a wide variety of time-series specifications, residential investment causes, but is not caused by GDP, while non-residential investment does not cause, but is caused by GDP. Thus, housing leads and other types of investment lag the business cycle. The results also suggest that policies designed to funnel capital away from housing into plant and equipment could produce severe short-run dislocations.

Home-ownership and Unemployment in the US

In this paper, we scrutinise Oswalds evidence that home-ownership and unemployment are correlated across the US states. In order to abstract from state fixed-effects in levels, we analyse the cross-sectional variation in changes in home-ownership and unemployment rates between 1970 and 1990. After duplicating (nearly) Oswalds result, we illustrate the importance of weighting the state observations by the fraction of total US households in 1970 that resided in the respective states and of abstracting from the ageing of the population between 1970 and 1990: this causes Oswalds correlation to to disappear. Secondly, we estimate the relationship for six different age-classes and for household heads and total population. We find that the relationship is non-existent for both young households and old households, but exists for middle-aged households. Young households have accumulated little wealth and have had less time to become attached to the geographical area than middle-aged households and thus are more likely to respond to unemployment by relocating. Older households employment cannot be greatly affected by home-ownership because their members are largely not in the labour force. Unemployment rates of household heads are affected less by tenure than those of the population as a whole.

New Place‐to‐Place Housing Price Indexes for U.S. Metropolitan Areas, and Their Determinants

Housing prices vary widely from market to market in the United States. The purpose of this study is to (1) construct new place-to-place indexes of the price of housing, using the 1990 Census, and (2) analyze the determinants of housing prices, with a particular focus on the supply side determinants-regulatory and natural constraint-as well as the usual demand determinants. Copyright American Real Estate and Urban Economics Association.

Age, housing demand, and real house prices

Abstract Real house prices are directly determined by the willingness of households to pay for (and willingness of builders to supply) a constant-quality house. Changes in the quantity of housing demanded will affect real prices only to the extent that the long-run housing supply schedule is positively sloped. In this paper we use 1980 census data to measure the impact of the age structure, education and income on the willingness of households to pay for a constant-quality house. We compute total and partial derivatives for the effect of age on housing demand. The total derivatives—which carry along with age all of the average characteristics (i.e. income, marital status and education) associated with that age—look much like the Mankiw-Weil age-demand results. But the partial derivatives suggest that holding all else constant, the demand for housing tends to be flat or rising slightly with age. Since much is in fact held constant over the life-cycle, we believe that our partial derivatives more accurately depict the age-demand relationship and thus that the aging of the population should not be expected to lower real house prices.

Should the Stagnant Homeownership Rate be a Source of Concern

The homeownership rate in the United States was essentially stagnant during the 1980s. This stagnation should be a source of concern if the rate reflects stagnant economic conditions and ownership opportunities, not if it simply reflects changing demographic conditions or preferences. Using a series of affordability measures, we find that homeownership opportunities improved almost everywhere during the 1980s, suggesting that the cause of the stagnant rate was something other than economic conditions. In fact, we find that both demographics and changes in preferences led to an increase in the proportion of households headed by single people; all else being equal, this would tend to push the owner-occupancy rate downward. We also found that while homeownership opportunities improved during the 1980s, the ex ante use cost of owning a home increased almost everywhere, reducing the financial attractiveness of owning a home. The combination of improving affordability conditions and worsening financial appeal had an overall neutral effect on the aggregate ownership rate.

Giving households credit: How changes in the U.S. tax code could promote homeownership

Abstract Recent U.S. government proposals intend to increase the homeownership rate by roughly 2.5 percentage points, to 67.5%, by the year 2000. The possible use of the U.S. income tax code is virtually ignored in these proposals. Using a user-cost framework incorporated into a tenure choice equation and both macro- and micro-level analyses, we demonstrate that the revenue-neutral replacement of the current deductibility of home mortgage interest and property taxes with a tax credit of the appropriate level alone can increase aggregate homeownership rates in the range of 3 to 5%. Moreover, these increases are even higher in lower-income neighborhoods, suggesting that such a policy could address the supplementary community development purpose of neighborhood stabilization.

Stock prices and house prices in California: new evidence of a wealth effect?

A crucial macroeconomic question facing the US economy is whether the value of the stock market has implications for consumption. If it does, it means that any severe downturn in the market could lead to a contraction of consumption, and therefore a contraction in the overall economy. The issue is one on which academics and the financial community seem to disagree. Rigorous academic works (Fama, 1981; Fisher and Merton, 1984; Barro, 1990; Poterba and Samwick, 1995), have generally found that the wealth effect on consumption is quite small, while research reports from financial service companies generally assert that the effect is real and important. This paper is different from its predecessors in that it focuses on one particular market: the San Francisco Bay area housing market. It will argue that this market is a prime candidate for a wealth effect to be large, and it will compare it to another market (Southern California) where we would expect the effect to be considerably smaller. We find that under circumscribed conditions, it is possible to 1 find a strong wealth effect in a particular market .

Optimal Comparable Weighting and Selection: A Comment

Vandell (1991) and Gau, et al. (1992) have recently developed rigorous methods for selecting and weighting comparables for the market comparison approach to valuation. This paper compares the statistical properties of the Vandell and Gau approaches; specifically, it examines the bias and variance produced by both approaches. Under classical OLS assumptions, Vandells method is preferable; when these assumptions are violated, the size and direction of the violation will determine which method is preferable. Finally, the paper concludes that when the regression producing the adjustment factors has an heteroskedastic error structure, corrections should be made to the regression itself, rather than as part of the comparable weighting and selection process. Copyright American Real Estate and Urban Economics Association.

Are Minorities or Minority Neighborhoods More Likely to Get Low Appraisals

We empirically examine the role of appraisal in the residential mortgage lending process—in particular, the incidence, consequences, and determinants of appraisal below contract purchase price. Using the Boston Federal Reserve Study data set, we find that, as expected, low appraised value significantly increases the probability of mortgage loan application rejection. We find no evidence that low appraised value is related to census tract racial composition, an important finding given the history of the appraisal industry; however, low appraised value is related to proxies for neighborhood quality. Moreover, properties securing adjustable rate mortgages, condominiums, and properties purchased by African American buyers show an increased probability of low appraisal, though the race effect result is highly sensitive to model specification.

Can we explain the Santa Clara county housing market

Abstract Santa Clara County has recently had the highest house prices of any large housing market in the nation. Part of the explanation lies in the extraordinarily low user cost of housing caused by the interaction of high incomes and the tax deductions available to homeowners. But this article also evaluates whether changes in stock wealth have been responsible for the recent increase in housing prices in Santa Clara County. Although three different stock market measures add explanatory power to a model of housing prices in the region, none of these indexes predicts the housing price increases seen in 1999 and 2000. In fact, the within‐sample models have .R‐squares of only 0.22, and even the best model (based on the Standard & Poors 500) does not forecast well out of sample. Still, the market is unusual in that stock prices seem to have some impact on house prices.