Norman G. Miller

Time on the Market and Selling Price

This study is primarily an analysis of tradeoff between selling time and price, both on a nominal and real basis. Sellers are seen as desiring to maximize their discounted real selling price and trading off the nominal selling price with expected selling time. The time a property remains on the market is important, not only because of its reflection on price, but also because of its possible reflection on the issue of submarket equilibrium-an assumption in most urban price studies. The empirical results of this study shed light on how similar studies can easily misinterpret the implications of time on the market on price and how further work may be improved. Copyright American Real Estate and Urban Economics Association.

Measuring Residential Real Estate Liquidity

There are many factors, other than price alone, that may affect the liquidity of real estate. This study develops a liquidity measure based on the Cox proportional hazard technique, a statistical model widely used in the epidemiologic and social sciences. The odds ratio, along with an estimate of market value for a home, are used to construct a liquidity measure. This measure can extract from the data a rich statistical profile of the variables that affect liquidity.

The Economic Impact of Anticipated House Price Changes—Evidence from Home Sales

If realized house prices have the wealth effect and the collateral effect on the economy, anticipated house price changes should have similar economic effects. This article empirically analyzes the effects of single‐family home sales, which are shown to be able to predict house prices in the literature, on economic production, using 372 metropolitan statistic areas in the United States from the first quarter of 1981 to the second quarter of 2008 in a panel vector error correction model. Changes in home sales are found to Granger because the growth rate of per‐capita gross metropolitan product and the dynamic effects are visualized with impulse response functions. Supporting evidence for the economic impact of home sales is also found in contemporaneous regressions.

Incentive commissions in residential real estate brokerage

Abstract Previous academic literature on residential real estate brokerage finds that a conflict of interest exists, at least in theory, between the seller and his broker under the prevailing fixed-percentage commission. This suggests a potential for slightly more complex “incentive commissions” to improve this principal-agent relationship. As noted by Anglin and Arnott, (1991), real world contracts are usually simpler than what is optimal according to principal/agent theory, and the reason for this discrepancy remains somewhat of a puzzle. The present paper attempts to shed light on this puzzle by using simulation analysis to quantify the magnitude of the effect of incentive contracts on both the seller and his broker under typical operating conditions. We find that time-incentive contracts offer negligible gains over the status quo fixed percentage commission. Price-incentive contracts, on the other hand, do appear to offer potential improvements for both the seller and broker, assuming symmetric information about the market for the house. However, with asymmetric information the price-incentive contract may be worse for the seller than the status quo fixed-percentage contract.

Forecasting Using Long-Order Autoregressive Processes: An Example Using Housing Starts

A long autoregressive (AR) modeling procedure for monthly U.S. housing starts data is considered. Neither differencing to remove the trend, nor differencing to remove the seasonal component is required in this method. The model is fitted by a Householder transformation-Akaike AIC criterion algorithm. Forecast performance is compared to that obtained by the Box-Jenkins ARIMA method. The prediction error variance of the long AR model method tends to be smaller than the prediction error variance of the Box-Jenkins model method. The long AR method is well suited for housing market time-series which are characterized by both strong seasonal and slowly changing trend components. Copyright American Real Estate and Urban Economics Association.