{"title":"Investor Confidence as a Determinant of China's Urban Housing Market Dynamics","authors":"Siqi Zheng, Weizeng Sun, Matthew E. Kahn","doi":"10.1111/1540-6229.12119","DOIUrl":"https://doi.org/10.1111/1540-6229.12119","url":null,"abstract":"China's urban housing market dynamics suggest that evolving investor confidence may be a relevant demand shifter. Such investors are continually updating their beliefs about the state of the macroeconomy and the policy uncertainty related to national and local housing policies. We build a 35 Chinese city real estate confidence index that varies over time and across cities. This index predicts subsequent house price appreciation and new housing sales. We document evidence of heterogeneous effects of investor confidence depending on a city's demographics and the city's elasticity of housing supply. Our results based on a new household‐level expectations survey bolster the case that investor expectations are an important determinant of real estate price dynamics.","PeriodicalId":259209,"journal":{"name":"Wiley-Blackwell: Real Estate Economics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130062936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Oil Prices and Urban Housing Demand","authors":"W. Larson, Weihua Zhao","doi":"10.1111/1540-6229.12227","DOIUrl":"https://doi.org/10.1111/1540-6229.12227","url":null,"abstract":"We develop a model of a monocentric, oil-exporting city. The model predicts a \"twist\" (rotation combined with a level shift) of the house price gradient with an oil price change due to the combined producer price and transportation cost effects. Using ZIP code level house price indices between 1975 and 2015, we show the slope of the house price gradient steepens in all cities when the price of oil is high and flattens when the price of oil is low. Areas specialized in oil and gas-related industries have house price changes that are positively linked with the price of oil. These results are consistent with theoretical predictions, and they quantify the large and differential risks to house prices associated with oil price changes both within and across all cities.","PeriodicalId":259209,"journal":{"name":"Wiley-Blackwell: Real Estate Economics","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130309603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Do House Price Levels Anticipate Subsequent Price Changes within Metropolitan Areas?","authors":"N. Lee, Tracey N. Seslen, William L. C. Wheaton","doi":"10.1111/1540-6229.12098","DOIUrl":"https://doi.org/10.1111/1540-6229.12098","url":null,"abstract":"type=\"main\"> This research examines the relationship between hedonically controlled housing price levels and subsequent changes in those prices across locations within MSAs. Are areas with a high price relative to an “imputed rent” paying for higher appreciation? In an efficient market (e.g., Gordon Growth Model), as fundamentals (impute rent) differ across locations and change over time, anticipation of these should generate a positive correlation between (residual) price levels and subsequent price changes. We undertake these tests in four different MSAs using a panel of repeat-sale house price indices that have been scaled to price levels with the hedonic attributes of the house and ZIP code. In three markets we find that identical houses in higher priced ZIP codes subsequently appreciate faster. In one market we find that there is little statistical difference.","PeriodicalId":259209,"journal":{"name":"Wiley-Blackwell: Real Estate Economics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130138816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hanqing Zhou, Yuan Yuan, Christopher Lako, Michael Sklarz, Charlesia McKinney
{"title":"Foreclosure Discount: Definition and Dynamic Patterns","authors":"Hanqing Zhou, Yuan Yuan, Christopher Lako, Michael Sklarz, Charlesia McKinney","doi":"10.1111/1540-6229.12089","DOIUrl":"https://doi.org/10.1111/1540-6229.12089","url":null,"abstract":"type=\"main\"> The lack of a consistent definition of foreclosure discount gives rise to discount rates that vary from nonexistent to sizeable across locations and time. We define the foreclosure discount as the discount of the real estate owned (REO) sale price relative to a normal-sale estimated market value. With a dataset of 1.34 million REO sale transactions, across 16 CBSAs between 2000 and 2012, we find three noteworthy empirical findings. First, a high REO sale concentration in a market increases the foreclosure discount. Second, foreclosure discount is negatively related to recent house-price appreciation. Third, the often reported high foreclosure discount for lower value properties is likely due to property condition.","PeriodicalId":259209,"journal":{"name":"Wiley-Blackwell: Real Estate Economics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130816517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Randal J. Verbrugge, A. Dorfman, W. Johnson, Fred J. Marsh, Robert Poole, O. Shoemaker
{"title":"Determinants of Differential Rent Changes: Mean Reversion Versus the Usual Suspects","authors":"Randal J. Verbrugge, A. Dorfman, W. Johnson, Fred J. Marsh, Robert Poole, O. Shoemaker","doi":"10.1111/1540-6229.12145","DOIUrl":"https://doi.org/10.1111/1540-6229.12145","url":null,"abstract":"We study 2001-2004 and 2004-2007 rent growth of 18,000 rental units, ending our study prior to the Great Recession. Which variables correlate with rent growth: Location? Age? Rent level? Occupancy duration? Structure type? The answers deepen understanding of the rental market, help statistical agencies make decisions about sample stratification and substitution, and expose coverage problems. We document significant rent stickiness. Initial relative rent level is the best predictor, though mainly due to mean reversion. \"Location\" comes in second, though often not statistically significantly: the relative value of location is persistent. Age and occupancy duration are also notable. Our findings are reassuring to statistical agencies.","PeriodicalId":259209,"journal":{"name":"Wiley-Blackwell: Real Estate Economics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116711390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Appraisers and Valuation Bias: An Empirical Analysis","authors":"K. Tzioumis","doi":"10.1111/1540-6229.12133","DOIUrl":"https://doi.org/10.1111/1540-6229.12133","url":null,"abstract":"Using appraisals from a lender across the 2005-06 period, we find that the association between appraisers' valuation inflation patterns and work volume varies across states. Moreover, we find a considerable occupational exit for appraisers, and provide evidence that appraisers, as applicants, did not receive better loan pricing compared with the population of applicants. Overall, this paper offers novel insights concerning the political economy of financial regulation through the lens of a specific profession.","PeriodicalId":259209,"journal":{"name":"Wiley-Blackwell: Real Estate Economics","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124204966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Effects of Property Tax Protests on the Assessment Uniformity of Residential Properties","authors":"Elizabeth Plummer","doi":"10.1111/1540-6229.12080","DOIUrl":"https://doi.org/10.1111/1540-6229.12080","url":null,"abstract":"type=\"main\"> This study examines whether the appeals process improves assessment uniformity for residential properties. The sample includes all single‑family residential properties in Harris County, Texas, for 2006–2008. I use a hedonic pricing model and Heckman's two‑stage approach to explain the assessed values of all properties before and after the appeals adjustments. Full sample results suggest that the appeals process increased assessment uniformity and that the value adjustments were appropriate in amount. I also present results across properties of different values (low, medium, high). The first‑stage probit model provides evidence on the factors that affect the likelihood that an owner will protest.","PeriodicalId":259209,"journal":{"name":"Wiley-Blackwell: Real Estate Economics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133529195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Percentage Rents with Agency","authors":"Joseph Williams","doi":"10.1111/1540-6229.12038","DOIUrl":"https://doi.org/10.1111/1540-6229.12038","url":null,"abstract":"Retail leases often include a constant percentage rent above a breakpoint. Most breakpoints are restricted to a natural breakpoint, calculated as base rent divided by percentage rent. Frequently, breakpoints are much greater than sales when leases are signed. Both within and across categories of retail, percentage rents vary widely. On average percentage rents are lowest for large stores, like anchors, and highest for small stores with high operating margins. Retail leases with these and other common characteristics are shown to support second-best investments by landlords in their stores both inside and outside shopping centers. The second-best schedule of breakpoints and percentage rents is calculated explicitly.","PeriodicalId":259209,"journal":{"name":"Wiley-Blackwell: Real Estate Economics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124330723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"First‐Price Sealed‐Bid Tender Versus English Open Auction: Evidence from Land Auctions","authors":"Yuen Leng Chow, J. Ooi","doi":"10.1111/1540-6229.12035","DOIUrl":"https://doi.org/10.1111/1540-6229.12035","url":null,"abstract":"type=\"main\"> This article compares whether the first-price sealed-bid tender or the ascending English open auction generates higher revenue for the seller. Using a unique set of data for land sales and accounting for the presence of an endogenous discrete mechanism choice variable, our results show that the first-price sealed-bid tender generates a lower land price, in the range of 1.2–9.6%, than the English open auction. Our results validate the theoretical prediction that open auctions result in higher prices because bidders can infer other bidders’ information by observing their bids in the common value auction paradigm.","PeriodicalId":259209,"journal":{"name":"Wiley-Blackwell: Real Estate Economics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131830506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mortgage Insurance Adoption in the Netherlands","authors":"Ruben Cox, Remco C. J. Zwinkels","doi":"10.1111/1540-6229.12157","DOIUrl":"https://doi.org/10.1111/1540-6229.12157","url":null,"abstract":"Individuals tend to underinsure on low probability, high consequence risks. Using a survey data set from a unique institutional context, we provide an assessment of the underinsurance puzzle by studying mortgage insurance adoption among Dutch homeowners. The results indicate that the demand for mortgage insurance is affected by risk exposure, type of mortgage lender, and the involvement of financial advisors. We document that wealthier and younger mortgagors are more likely to insure. However, locus of control, house price expectations, and precautionary savings are not related to insurance demand. Finally, we find evidence that borrower (over)confidence negatively affects the likelihood that insurance is bought.","PeriodicalId":259209,"journal":{"name":"Wiley-Blackwell: Real Estate Economics","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125156520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}