Carmelo Giaccotto

Estimating Price Indices for Residential Property: A Comparison of Repeat Sales and Assessed Value Methods

The repeat sales methodology for estimating residential price indices is based on actual appreciation of individual properties. On the other hand, the repeat sales method wastes data, typically discarding a large percentage of all sales. This article explores two issues related to the subsample of repeat sales. First, are paired sales representative of the entire population of properties that sold? Second, is there evidence that sample selectivity biases the price trend estimates? Evidence from five metropolitan areas supports a negative answer to the first question and the second question. It appears that a “lemon” or “starter home” effect causes repeat residential sales to be a biased subsample of all transactions. Cumulative price trends for the repeat subsamples can differ from the full samples over periods ranging from two to ten quarters. While short-term price trends can differ widely, there are no systematic differences among the samples over long periods of time (e.g., three years or more).

Housing Price Indices Based on All Transactions Compared to Repeat Subsamples

The set of real properties sold during a given period of time may be subdivided into several subsets comprising those properties that sold only once, only twice, and three or more times. The major reason for subdividing the sample is to allow estimation of residential price indices by the repeat‐sales methodology. The purpose of this paper is to compare price indices estimated with the repeat subsample to indices based on the entire sample. Our data for five metropolitan areas indicate that cumulative price trends for the repeat subsamples can differ from the full samples over periods ranging from two to ten quarters. While short‐term price trends can differ widely, there are no systematic differences among the samples over periods of three years or more. The data indicate that arbitrage typically forces prices for the repeat sample to grow at the same rate as those for the full sample. Whether this would be the case in areas experiencing greater disequilibrium than our towns in the Hartford area is uncertain.

Drug Prices and Research and Development Investment Behavior in the Pharmaceutical Industry

This paper argues theoretically and shows empirically that pharmaceutical R&D spending increases with real drug prices, after holding constant other determinants of research and development (R&D). Specifically, an estimated elasticity suggests that a 10 percent increase in the growth of real drug prices is associated with nearly a 6 percent increase in the growth of R&D intensity. Simulations that are based on our multiple‐regression model indicate that the capitalized value of pharmaceutical R&D spending would have been about 30 percent lower if the federal government had limited the rate of growth in drug price increases to the rate of growth in the general consumer price index during the period 1980–2001. Moreover, the results suggest that a drug price control regime would have resulted in 330–65 fewer new drugs, representing over one‐third of all actual new drug launches brought to the global market during that time period.

Hypothesis testing in event studies: The case of variance changes

Abstract Event study methods to test the effects of financial events on asset returns implicitly assume a stationary variance. Arbitrage theory [Ross (1989)], however, suggests that the variance of returns should change with the flow of information to the market. Empirical evidence confirms this theory—especially as it applies to financial events. In this paper, we develop a new event study test, based on the jackknife methodology, which is robust to changes in information flow during a financial event. We also consider the rank test of Corrado (1989), the sign test of Corrado and Zivney (1992), the generalized sign test of Cowan (1992), the cross-sectional test of Boehmer et al. (1991) and, of course, the standard OLS test. We have constructed a number of experiments to compare the performance of these six tests under four types of variance changes. Although no uniformly most powerful test emerged for all circumstances, our results suggest that if a researcher knows the exact day of the event, then the generalized sign test of Cowan should be applied. However, in most circumstances one must use a multiple-day window to capture the true event day; in this case, we recommend the jackknife test.

Appraisal‐Based Real Estate Returns under Alternative Market Regimes

In this article we use Monte Carlo simulation to study the statistical properties of real estate returns. We set up a model where transactions prices are noisy signals of true prices. We then consider a number of appraisal rules, derived from Bayesian and non-Bayesian theory, to estimate the current true price and rate of return. The class of exponential smoothing and Kalman filter rules perform well at both the disaggregate (returns on an individual property) and aggregate (returns on a real property portfolio) levels. A special case of exponential smoothing (αe 1.0) places all weight on current market data. Since this case eliminates smoothing, our results suggest that appraisers should place all weight on current data (no weight on past data) provided that they want to estimate returns rather than values. However, these results should be used with caution if sales prices are very noisy. Copyright American Real Estate and Urban Economics Association.

Price Indices Based on the Hedonic Repeat-Sales Method: Application to the Housing Market

Shiller (1993) proposes the hedonic repeated-measures (HRM) approach to measuring constant quality price indices for heterogeneous assets such as some bonds and real estate. We derive a mathematical relationship between the coefficients of the HRM model and those from the standard repeat-sales model, and we demonstrate how hedonic characteristics should be chosen for inclusion in the HRM model. Empirical estimates using Fairfax, Virginia, housing transactions data show that the HRM price index evaluated at the mean of the hedonic variable is virtually identical to the standard repeat sales index, just as predicted by our mathematical relationship. But the HRM allows estimation of different price paths for heterogeneous assets. We demonstrate that use of assessed value as the only hedonic characteristic allows parsimonious HRM estimates.

A study of several new and existing tests for heteroscedasticity in the general linear model

Abstract Several optimum non-parametric tests for heteroscedasticity are proposed and studied along with the tests introduced in the literature in terms of power and robustness properties. It is found that all tests are reasonably robust to the Ordinary Least Squares (OLS) residual estimates, number and character of the regressors. Only a few are robust to both the distributional and independence assumptions about the errors. The power of tests can be improved with the OLS residual estimates, the increased sample size and the variability of the regressors. It can be substantially reduced if the observations are not normally distributed, and may increase or decrease if the errors are dependent. Each test is optimum to detect a specific form of heteroscedasticity and a serious power loss may occur if the underlying heteroscedasticity assumption in the data generation deviates from it.

Three New Real Estate Price Indices for Geneva, Switzerland

This paper develops constant-quality price indices for three categories of real estate-apartment buildings, vacant land, and condominiums—for the city of Geneva, Switzerland. We use both the hedonic and repeat sales models to estimate the price level and, in turn, the rate of price change. The general pattern of each series suggests that real estate prices in Geneva were fairly stable throughout the 1970s, increased sharply during the 1980s, but gave back some of these gains in the early 1990s. Interestingly, the sharp rise in prices in the second half of the 1980s is very similar to that found in some regions of the United States. We also consider the problem, implicit in the repeat sales method, of revisions in previously estimated price indices as additional data become available in later years.

The Identical Distribution Hypothesis for Stock Market Prices—Location- and Scale-Shift Alternatives

Abstract This article explores the identical distribution hypothesis for stock-price changes through a set of optimum non-parametric tests for randomness against location- and scale-shift alternatives. An application of these tests to the daily, weekly, monthly, and quarterly rates of return from 1966 through 1976 for each of the first 15 stocks in the Dow Jones Industrial Average reveals that these series may have constant location parameters throughout the sample period, but the stability of their scale parameters is questionable.

Stochastic Modelling of Interest Rates: Actuarial vs. Equilibrium Approach

The purpose of this study is to develop a general methodology for analyzing insurance functions when interest rates are stochastic. Two alternative approaches are considered. For the actuarial case, a recursive algorithm is developed to value insurance functions for stationary as well as non-stationary interest rate processes. For the equilibrium approach, the Vasicek model for pricing zero coupon bonds is used to obtain the present value of two life insurance functions.