The Impact of Property Condition Disclosure Laws on Housing Prices: Evidence from an Event Study using Propensity Scores

We examine the impact of seller's Property Condition Disclosure Law on the residential real estate values. A disclosure law may address the information asymmetry in housing transactions shifting of risk from buyers and brokers to the sellers and raising housing prices as a result. We combine propensity score techniques from the treatment effects literature with a traditional event study approach. We assemble a unique set of economic and institutional attributes for a quarterly panel of 291 US Metropolitan Statistical Areas (MSAs) and 50 US States spanning 21 years from 1984 to 2004 is used to exploit the MSA level variation in house prices. The study finds that the average seller may be able to fetch a higher price (about three to four percent) for the house if she furnishes a state-mandated seller.s property condition disclosure statement to the buyer. When we compare the results from parametric and semi-parametric event analyses, we find that the semi-parametric or the propensity score analysis generals moderately larger estimated effects of the law on housing prices.

Property Condition Disclosure Law: Why Did States Mandate 'Seller Tell All'?

Thirty-six US states have already enacted some form of seller's property condition disclosure law. At a time when there is a movement in this direction nationally, this paper attempts to ascertain the factors that lead states to adopt disclosure law. Motivation for the study stems from the fact that not all states have yet adopted the law, and states that have enacted the law have done so in different years. The analytical structure employs hazard models, using a unique set of economic and institutional attributes for a panel of 50 US States spanning 21 years, from 1984 to 2004. The proportional hazard analysis of law adoption reveals that greater number of disciplinary actions tends to favor passage of the law. Greater broker supervision, implying generally higher awareness among real estate agents, seems to have a negative impact on the likelihood of a state adopting a property condition disclosure law.

Property Condition Disclosure Law: Does 'Seller Tell All' Matter in Property Values?

At the time when at least two-thirds of the US states have already mandated some form of seller's property condition disclosure statement and there is a movement in this direction nationally, this paper examines the impact of seller's property condition disclosure law on the residential real estate values, the information asymmetry in housing transactions and shift of risk from buyers and brokers to the sellers, and attempts to ascertain the factors that lead to adoption of the disclosur law. The analytical structure employs parametric panel data models, semi-parametric propensity score matching models, and an event study framework using a unique set of economic and institutional attributes for a quarterly panel of 291 US Metropolitan Statistical Areas (MSAs) and 50 US States spanning 21 years from 1984 to 2004. Exploiting the MSA level variation in house prices, the study finds that the average seller may be able to fetch a higher price (about three to four percent) for the house if she furnishes a state-mandated seller's property condition disclosure statement to the buyer.

The Time-Series Properties on Housing Prices: A Case Study of the Southern California Market

We examine the time-series relationship between housing prices in eight Southern California metropolitan statistical areas (MSAs). First, we perform cointegration tests of the housing price indexes for the MSAs, finding seven cointegrating vectors. Thus, the evidence suggests that one common trend links the housing prices in these eight MSAs, a purchasing power parity finding for the housing prices in Southern California. Second, we perform temporal Granger causality tests revealing intertwined temporal relationships. The Santa Anna MSA leads the pack in temporally causing housing prices in six of the other seven MSAs, excluding only the San Luis Obispo MSA. The Oxnard MSA experienced the largest number of temporal effects from other MSAs, six of the seven, excluding only Los Angeles. The Santa Barbara MSA proved the most isolated in that it temporally caused housing prices in only two other MSAs (Los Angels and Oxnard) and housing prices in the Santa Anna MSA temporally caused prices in Santa Barbara. Third, we calculate out-of-sample forecasts in each MSA, using various vector autoregressive (VAR) and vector error-correction (VEC) models, as well as Bayesian, spatial, and causality versions of these models with various priors. Different specifications provide superior forecasts in the different MSAs. Finally, we consider the ability of theses time-series models to provide accurate out-of-sample predictions of turning points in housing prices that occurred in 2006:Q4. Recursive forecasts, where the sample is updated each quarter, provide reasonably good forecasts of turning points.

Schools and Housing Markets: An Examination of School Segregation and Performance in Connecticut

This paper examines the relationship between house price levels, school performance, and the racial and ethnic composition of Connecticut school districts between 1995 and 2000. A panel of Connecticut school districts over both time and labor market areas is used to estimate a simultaneous equations model describing the determinants of these variables. Specifically, school district changes in price level, school performance, and racial and ethnic compositions depend upon each other, labor market wide changes in these variables, and the deviation of each school district from the overall metropolitan area. The specification is based on the differencing of dependent variables, as opposed to the use of level or fixed effects models and lagging level variables beyond the period over which change is considered; as a result the model is robust to persistence in the sample. Identification of the simultaneous system arises from the presence of multiple labor market areas in the sample, and the assumption that labor market changes in a variable due not directly influence the allocation of households across towns within a labor market area. We find that towns in labor markets that experience an inflow of minority households have greater increases in percent minority if those towns already ahve a substantial minoritypopulation. We find evidence that this sorting proces is reflected in housing price changes in the low priced segment of the housing market, not in the middle and upper segments.

Is the Great Moderation Ending? UK and US Evidence

The Great Moderation, the significant decline in the variability of economic activity, provides a most remarkable feature of the macroeconomic landscape in the last twenty years. A number of papers document the beginning of the Great Moderation in the US and the UK. In this paper, we use the Markov regime-switching models of Hamilton (1989) and Hamilton and Susmel (1994) to document the end of the Great Moderation. The Great Moderation in the US and the UK begin at different point in time. The explanations for the Great Moderation fall into generally three different categories -- good monetary policy, improved inventory management, or good luck. Summers (2005) argues that a combination of good monetary policy and better inventory management led to the Great Moderation. The end of the Great Moderation, however, occurs at approximately the same time in both the US and the UK. It seems unlikely that good monetary policy would turn into bad policy or that better inventory management would turn into worse management. Rather, the likely explanation comes from bad luck. Two likely culprits exist . energy-price and housing-price shocks.