Alex van de Minne

Land, structure and depreciation

We introduce a hedonic price model that enables us to disentangle the value of a property into the value of land and the value of structure. For given reconstruction costs, we are able to estimate the impact of physical deterioration, functional obsolescence and vintage effects on the structure and the impact of time on sale (and external obsolescence) on the land value simultaneously. Our findings show that maintenance has a substantial impact on the rate of physical deterioration. After 50 years of not or barely maintaining a home, a typical structure has lost around 43% of its value. In contrast, maintaining a home very well results in virtually no physical deterioration in the long run.

The Effect of Credit Conditions on the Dutch Housing Market

It is widely perceived that the supply of mortgages, especially since the extensive liberalization of the mortgage market of the 1980s, has had implications for the housing market in the Netherlands. In this paper we introduce a new method to estimate a credit condition index (CCI). The CCI represents changes in the supply of credit over time, apart from changes in interest rates and income. It has been estimated by an unobserved component in an error-correction model in which the average amount of new provided mortgages per period is explained by the borrowing capacity and additional control variables. The model has been estimated on data representing first time buyers (FTB). For FTB we can assume that the housing and non-housing wealth is essentially zero. The CCI has subsequently been used as an explanatory variable in an error-correction model for house prices representing not only FTB, but all households. The models have been estimated on quarterly data from 1995 to 2012. The estimated CCI has a high correlation with the Bank Lending Survey, a quarterly survey in which banks are asked whether there is a tightening or relaxation of (mortgage) lending standards compared to the preceding period. The CCI has explanatory power in the error-correction model for house prices. In real terms house prices declined about 25% from 2009 to 2012. The estimation results show that nearly half of this decline can be attributed to a decline in the CCI.

Do Different Price Points Exhibit Different Investment Risk and Return in Commercial Real Estate

Conventional real estate price indexes provide a single measure for the path of asset prices over time (controlling for the quality of the representative or average property). Properties could, however, have different price dynamics based on the price segment in which they are traded. On the demand side, investors at different price points are differentiated by the amount of capital they have at their disposal and the type and source of financing. Smaller, private investors cluster at lower price points, whereas large institutions dominate the high price points. On the supply side, properties at different price points may serve different space markets with different types of tenants and may reflect different supply elasticity and land/structure value ratios. In this article, the authors use an unconventional approach, quantile regression, to estimate price indexes for different price segments in commercial real estate. Their results show that there are indeed large differences in price dynamics for different price points. These differences are suggestive of a lack of integration in the property asset market because the authors find apparent differences in the risk–return relationship. Lower-price-point properties exhibit less risk (in the form of volatility and cycle amplitude) but have no evidence of lower total returns. Lower-price-point properties also show greater momentum and thus greater predictability.

A Bayesian Structural Time Series Approach to Constructing Rent Indexes: An Application to Indian Office Markets

We introduce new methodology for constructing real estate rent indices. Using unique data on contract rents from six Indian metropolitan markets, we pair subsequent rented units in the same building to create over 12,000 pseudo repeat rent pairs. We impose an autoregressive structure on the log rent returns in a structural time series variant of the repeat sales model widely used in real estate price indexing. We also allow for time-varying index signal and noise variance parameters. This method has several advantages, including low statistical estimation noise (even in small samples), fewer historical revisions, and the ability to capture changes in market volatility and its subsequent effect on the rent index and estimation error. Finally, we estimate the model using full Bayesian inference that gives the entire posterior distribution. The resulting indices are robust to property heterogeneity and omitted variables, and present well behaved quarterly depictions of the recent history of office market rents in the six cities.

Revisions in Granular Repeat Sales Indices

Price indices based on repeat sales are the most widely used type of real estate index based on asset transaction prices. But such indices are particularly prone to revision. When a new period of transaction data becomes available and is used to update the repeat sales model, all past index values can potentially be revised. These revisions are especially problematical for commercial real estate (as compared to housing), because commercial transactions are relatively scarce and properties are heterogeneous, reducing estimation precision. From a methodological perspective, the magnitude of expected revisions is a particularly useful measure of the quality of the empirical index, as it directly reflects both the precision of the index and its practical usefulness in economic and business applications, since revisions themselves are problematical in practice. This paper focuses on random revisions for indexes in thin, commercial property markets, the type of market that is most challenging for empirical price indexing. We present multiple specifications of the repeat sales model, seeking to reduce revisions. With the objective of minimizing the expected magnitude of revisions, among the specifications we explore, the best result obtains from an index methodology that specifies the periodic returns as a first order autoregressive process, that also uses the periodic returns of an aggregate index as an explanatory variable for more granular indices, and that allows the variance parameters of the signal and the noise to be time-varying. In our small-sample test cases, this model reduces overall index revisions by more than 50%.

The Effect of Green Retrofitting on US Office Properties: An Investment Perspective

Buildings are responsible for over one-third of all resource consumption, greenhouse gas emissions, and energy consumption. Commercial buildings represent approximately half of that total. In mature economies such as the United States, new construction annually represents only a small fraction of the existing stock of buildings. Hence, retrofitting of commercial buildings, through major renovation projects, is extremely important for sustainability within the built environment. Most studies of green building economics have focused on new construction. This paper is one of the first to focus specifically on retrofit green. Based on a larger sample than most previous studies of new construction, we quantify the magnitude of value enhancement created by green retrofit of US office buildings. This paper is also the first to consider the subsequent investment price dynamics effects of such sustainability. Methodologically, we introduce an innovative way to control for other effects to isolate the value impact and the investment risk and return impact of green retrofitting. We do this by applying a repeat-sales model of only (and all) buildings which will ultimately be retrofitted (in our sample). By using new real estate price indexing methodology, namely a structural time series model employing a hierarchical repeat-sales (HRS) specification, we can build statistically rigorous comparative price indexes of retrofit green, versus non-green, office buildings in the US, quarterly for the 2005-2014 period, even with relatively scarce transaction price data (441 pairs). We find substantial value enhancement in green retrofit projects (between 10% and 20%), and we find evidence that retrofitted green buildings provide investors with lower asset price volatility. But during and just after the Financial Crisis the premium dropped temporarily to near zero, suggesting that the demand for green property investment is income-elastic.

Demand and supply of mortgage credit

This paper estimates demand and supply of mortgage credit by using a hierarchical trend model. The empirical analysis is based on loan-level data covering the years 2005-2014 in the Netherlands. We find that high-income households take out higher loan amounts and have higher collateral values. Interest rates are negatively related to both loan amounts and collateral values. The common trend in the loan equation, a proxy for the changes in demand and supply of mortgage credit over time, suggests a large decline in mortgage demand and supply after 2007. The common trend in the collateral value equation is highly correlated with the common trend in the loan equation, suggesting a high pass-through rate of changes in credit conditions from loan to value. We also find that young household cohorts can afford to buy better quality houses in 2014 than in 2005, even if they could borrow less. On the contrary, older household cohorts take out higher loans in 2014 than in 2005, but their collateral values do not change. We argue that younger households took up less mortgage debt as they became more credit constraint over time. Older households on the other hand suffered from negative home equity, forcing them to take up higher mortgage loans.