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.
|Date of creation:||Nov 2005|
|Date of revision:||Jul 2006|
|Note:||This paper is adapted from the third chapter of my doctoral dissertation. I would like to thank my advisors - Stephen L. Ross, John M. Clapp, and Dennis R. Heffley for their insightful comments on the idea and methodology. I greatly benefited from helpful comments from James Davis and Katherine Pancak. Comments from Dhamika Dharmapala, Thomas Miceli, and seminar participants at the University of Connecticut, Economics Brownbag Seminar Series are acknowledged. I would also like to thank Tim Storey (National Conference of State Legislatures), Daniel Conti (Bureau of Labor Statistics) for assistance with data, and Sascha Becker of University of Munich for assistance with STATA module on propensity score matching algorithm (written by Sascha Becker and Andrea Ichino). All remaining rrors are mine.|
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- A. Smith, Jeffrey & E. Todd, Petra, 2005.
"Does matching overcome LaLonde's critique of nonexperimental estimators?,"
Journal of Econometrics,
Elsevier, vol. 125(1-2), pages 305-353.
- Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20035, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
- Arellano, Manuel & Honore, Bo, 2001.
"Panel data models: some recent developments,"
Handbook of Econometrics,
in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 53, pages 3229-3296
- Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004.
"How Much Should We Trust Differences-In-Differences Estimates?,"
The Quarterly Journal of Economics,
Oxford University Press, vol. 119(1), pages 249-275.
- Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2002. "How Much Should We Trust Differences-in-Differences Estimates?," NBER Working Papers 8841, National Bureau of Economic Research, Inc.
- James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
- Rajeev H. Dehejia & Sadek Wahba, 1998.
"Propensity Score Matching Methods for Non-experimental Causal Studies,"
NBER Working Papers
6829, National Bureau of Economic Research, Inc.
- Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
- Kiefer, Nicholas M, 1988. "Economic Duration Data and Hazard Functions," Journal of Economic Literature, American Economic Association, vol. 26(2), pages 646-79, June.
- Caliendo, Marco & Kopeinig, Sabine, 2005.
"Some Practical Guidance for the Implementation of Propensity Score Matching,"
IZA Discussion Papers
1588, Institute for the Study of Labor (IZA).
- Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, 02.
- Marco Caliendo & Sabine Kopeinig, 2005. "Some Practical Guidance for the Implementation of Propensity Score Matching," Discussion Papers of DIW Berlin 485, DIW Berlin, German Institute for Economic Research.
- Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
- Manuel Arellano & Stephen Bond, 1991.
"Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,"
Review of Economic Studies,
Oxford University Press, vol. 58(2), pages 277-297.
- Tom Doan, . "RATS program to replicate Arellano-Bond 1991 dynamic panel," Statistical Software Components RTZ00169, Boston College Department of Economics.
- Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
- James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," Review of Economic Studies, Oxford University Press, vol. 65(2), pages 261-294.
- Norman Miller & Liang Peng, 2006. "Exploring Metropolitan Housing Price Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 33(1), pages 5-18, August.
- Slottje, Daniel J. & Millimet, Daniel L. & Buchanan, Michael J., 2007. "Econometric analysis of copyrights," Journal of Econometrics, Elsevier, vol. 139(2), pages 303-317, August.
- Gabor Kezdi, 2005. "Robus Standard Error Estimation in Fixed-Effects Panel Models," Econometrics 0508018, EconWPA.
- Rajeev H. Dehejia & Sadek Wahba, 1998. "Causal Effects in Non-Experimental Studies: Re-Evaluating the Evaluation of Training Programs," NBER Working Papers 6586, National Bureau of Economic Research, Inc.
- Roberta Romano & Sanjai Bhagat, 2001. "Event Studies and the Law - Part I: Technique and Corporate Litigation," Yale School of Management Working Papers ysm182, Yale School of Management.
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