Developing a House Price Index for The Netherlands: A Practical Application of Weighted Repeat Sales

This paper describes the development of a house price index that has been introduced in May 2005 in The Netherlands. This monthly index, called Woningwaarde Index Kadaster (House Price Index Kadaster), is designed to detect changes in the price of the overall stock of owner-occupied homes. Fifty-five indices are calculated: one overall index, four regional indices, 12 provincial indices and 38 indices based on combinations of region/province and dwelling type. We used Case and Shiller’s geometric Weighted Repeat Sales Model to calculate monthly house price indices. We used recorded data on the sales of over 500,000 owner-occupied homes in The Netherlands, all representing repeat sales between January 1993 and December 2006. The accuracy of the index was determined using the 95% confidence interval. We observed that accuracy might become a problem in smaller sub samples. Revision volatility was explored by comparing the index values computed from all available data until December 2005 with the index values computed from the data available until December 2006. Our analysis showed that revision volatility does not seem to be a major problem to the index. We also explored heteroskedasticity in the Repeat Sales method but did not find conclusive evidence for the proposed heteroskedasticity. Given our target (a geometric mean index value) and the characteristics of the dataset (very large but without property characteristics) the Repeat Sales Method seems to be adequate for calculating a house price index for The Netherlands.

Controlling for Quality in House Price Indices

Given the importance of house prices it is not surprising that house price indices are used for many purposes. One of the factors that differentiates these indices is the house price determinants (such as structural characteristics and neighborhood quality) that are accounted for—that is, held constant. Indices are usually generated from house price regressions. It is shown that, regardless of the desired level of accounting, it is necessary to control for all significant determinants of house prices in these regressions to obtain unbiased estimates of the growth in house prices. An empirical example shows that not controlling for neighborhood quality can lead to substantial biases in estimates of house price appreciation rates even if the index does not account for this factor.     

Short Holds,the Distributions of First and Second Sales,and Bias in the Repeat-Sales Price Index

The Journal of Real Estate Finance and Economics -     

A Bayesian Approach to the Construction and Comparison of Alternative House Price Indices

Several repeat-sales models have been advanced over the years for estimating real estate price indices. This article proposes a general model which incorporates earlier works as special cases and compares the alternative repeat-sales models using posterior odds ratios as criteria. While the existing literature estimates the real estate indices from the sampling point of view, in this article indices are constructed and then compared using a Bayesian approach. In general, the two-error term models outperform the one-error models. The model with a nontemporal component proposed by Goetzmann and Spiegel is found to be superior in three out of four cities. There is a significant discrepancy among the returns and indices obtained from different models.     

Frequency of Transaction and House Price Modeling

This article examines the characteristics and price behavior of repeatedly transacted properties. Using data from four U.S. counties, we estimate hedonic price models of properties grouped by transaction frequency, and compare estimated standard deviations and estimated appreciation rates by group.For each of four counties studied, we find that estimated house price appreciation is systematically higher among properties that transact more frequently. One possible explanation for this result is that purchasers make property improvements that are not adequately reflected in the available data.We also find that estimated standard deviations of the disturbance term show a marked decrease as the frequency of transaction increases. Since frequently transacting properties are not found to be systematically more homogeneous than seldomly transacting properties, we do not attribute this to any increase in homogeneity for frequently transacting properties, but rather to the length of time elapsed between transactions of properties.The findings of this article suggest that repeat-sales price models may need to be adjusted to account for cross-sectional variation in transaction probabilities---that is, the selectivity of the subsample of properties that transacted (or transacted repeatedly) during any finite study period.     

The Effects of Attributes on the Repeat Sales Pattern of Residential Property in Hong Kong

There has been copious research work on the development of house price models and the construction of house price indices. However, results in some studies revealed that the accuracy of such indices could be subject to selection bias when using only information from a sample of sold properties to estimate value movements for the entire housing stock. In particular, estimated house price appreciation is usually systematically higher among properties that change hands more frequently. It therefore suggests that the determination of important factors affecting the transaction frequency or intensity of a housing unit should be a more fundamental research question. This paper examines the possible factors that determine the popularity of residential unit by means of a repeated sales pattern. The Poisson regression model and event history analysis techniques are employed to assess the effect of attributes on transaction frequency and intensity. The event history analyses technique can take account of transaction-specific as well as time-dependent covariates, and therefore is recommended for analyzing repeated sales data in a real estate market. All transaction records during the period 1993–2000 from the Land Registry of one of the most popular residential estates in Hong Kong were used to illustrate the method. Unlike a response to favorable transaction price, good quality units do not necessarily inherently display a high transaction frequency. Rather, units of average quality are more likely to be transactionally active.     

Evaluating the Usefulness of the American Housing Survey for Creating House Price Indices

The American Housing Survey (AHS) is a valuable source of information on houses and occupants over time. The AHS has several advantages over sales data for use in the creation of price indices: it is readily available, has frequent observations over time and space, has data from the late 1970s through the mid-1990s, includes houses that do not sell, as well as those that do, and has information on the occupants. The drawbacks include: a time lag between the interview and the release of the data, data suppression issues, owner-stated house values, and a lack of neighborhood information. In this study, we use the metropolitan version of the AHS, which has been supplemented with the original survey data as well as Census tract data for three cities over 14 years to examine whether the AHS can be used to create indices. Indices are estimated using hedonic, repeat valuation, and hybrid techniques, overcoming some of the problems inherent in the estimation of indices. We find that the data-suppression issues and the owner-stated house values are not problematic. The biggest drawback of the AHS is its lack of objective information on neighborhood quality.     

The Construction of Residential Housing Price Indices: A Comparison of Repeat-Sales,Hedonic-Regression,and Hybrid Approaches

This article examines a number of hypotheses that underpin the repeat-sales and hedonic approaches to the construction of housing price indices, as well as the practical problems associated with the implementation of either approach. We also examine a hybrid procedure that combines elements of both the repeat-sales and hedonic-regression techniques. For our sample of individual home sales in Oakland and Fremont California over an 18-year period, repeat-sales methods are subject to sample selection bias; the maintained assumption of time constancy of implicit prices of housing attributes is violated; the repeat-sales estimator is extremely sensitive to influential observations; and the usual method used to correct for heteroskedasticity in repeat-sale housing returns is inappropriate in our sample. Hedonic techniques are better suited to contend with index number problems per se, as they can accommodate changing attribute prices over time. They also appear to give rise to more reliable estimates of price indices, as unusual observations have less effect on estimated price indices. Drawbacks of the hedonic approach include the usual concern with omitted attributes, and their effect on the estimated price index.     

Joint Dynamics of House Prices and Foreclosures

This paper studies the joint transitional dynamics of the foreclosures and house prices in a standard life‐cycle incomplete markets model with housing and a realistic long‐term mortgage structure. We calibrate our model to match several long‐term features of the U.S. housing market, and analyze the effects of several unexpected and permanent shocks on the house price and the foreclosure rate both across the steady states and along the transition between the steady states. We examine permanent, unexpected shocks to the risk‐free interest rate, the minimum down‐payment ratio, and unemployment. During the transition, these shocks create large movements in house prices. More importantly, the foreclosure dynamics are quite significant along the transition compared to the steady‐state changes, and there are strong feedbacks between foreclosures and house prices. We assess the effects of a temporary reduction in the risk‐free interest rate, which has moderate effects on house prices but little effect on foreclosure dynamics. We also study the effects of an ex ante macroprudential policy, which establishes a minimum down‐payment requirement at a higher threshold. Such a macroprudential policy helps substantially stabilize both house prices and foreclosures.     

The Effect of House Price on Stock Market Participation in China: Evidence from the CHFS Microdata

This is an empirical study on the effect of house price on stock market participation and its depths based on unique China Household Finance Survey (CHFS) data in 2011 and 2013 including 36,213 sample households. We mainly found that, with an increase of one thousand RMB per square meter in macrohouse price, the probability to participate in the stock market will increase by 5.4% before controlling for wealth effect and 2.84% afterwards, indicating the existence of wealth effect. The participation depths of the stock-total asset ratio are expected to decrease by 0.23%, and absolute stock asset is observed to decrease by 5.8 thousand RMB in response to one thousand RMB increase of per square meter house price. The effect of house price on participation decision is also related to housing area, and the negative effect of house price on stock market participation depths gets more intense with the increase of the stock-total asset ratio.     

An Alternative View on Determinants of the Effective Tax Rate: Evidence from Chinese Listed Companies

This article proposes a new model for determining the effective tax rate (ETR), which incorporates the accounting-tax conformity theory and identifies ETR determinant variables to fit the Chinese taxation context. The results show that the ETR is statistically significantly associated with preferential tax rates, investment gains, nonoperating expenses, and provisions for impaired assets. The accounting-tax difference ETR determinant variables provide more consistent results than previous typical ETR determinants, such as size, return on assets, leverage, and capital intensity.     

Strategising in the midst of management controls: a case study on the relationship between management controls and promises on strategies

By understanding strategies as promises, this study investigates how management controls are implicated in organisations’ strategising practice under continuous changes of external forces. Based on a historical case study of a New Zealand electricity firm, the study shows how multiple management controls facilitate a strategising practice that focuses on repromising new futures for the firm by enabling senior managers, board members and operational staff to memorise, forget and forgive promises made. The study suggests that organisations seeking to move from one promised future to another use management controls to help develop, solidify and bridge promises.     

IRC Section 162(m) and the law of unintended consequences

In 1993, Section 162(m) of the U.S. Internal Revenue Code was passed into law with the intent to reign in outsized executive compensation by eliminating the tax-deductibility of executive compensation above $1 million unless the excess compensation was performance-based. An unintended consequence of the legislation was that executives' total compensation actually increased in the post-1993 period, largely due to a dramatic increase in employee stock options. Employee stock options have unintended consequences of their own. The economic value of stock options may be influenced by executive decision-making when the options are valued using the Black-Scholes model or some variant thereof. Our findings suggests an unintended consequence that executives used their discretion to positively impact the performance-based component of their compensation through actions increasing share price volatility and reducing dividend yields, assumptions implicit in option valuation models.     

Price impact of block trades: the curious case of downstairs trading in the EU emissions futures market

Using high-frequency data from the European Climate Exchange (ECX), we examine the determinants of price impact of €21 billion worth of block trades during 2008–2011 in the European carbon market. We find that wider bid-ask spreads and volatility are characterised by a smaller price impact. Larger levels of price impact are more likely to occur during the middle of the trading day, specifically the four-hour period between 11 a.m. and 3 p.m., than during the first or final hours. Purchase block trades induce a relatively smaller price impact on price run-up, while sell block trades exhibit a larger price impact on price run-up. We conclude that block trades on the ECX induce less price impact than in equity or conventional futures markets, and that a significant proportion of the effects contradict findings on block trades in those markets; thus, we provide the first evidence of the curious bent to block trading in the European Union emissions trading scheme.