Commercial Property Price Indices Research Articles

Compilation of Commercial Property Price Indices for Germany Tailored for Policy Use

Abstract The compilation of commercial property price indices (CPPIs) is challenging. Policymakers urge for timely, reliable and comprehensive data. In Germany, lack of data prevents the calculation of official figures by the national statistical authority. Different applications of price indices need different definitions of commercial real estate. CPPIs according to these definitions are constructed on the basis of existing data for 127 German towns and cities (that cover about one-third of German population). The overall price developments revealed by the various indices are rather similar in terms of central time series characteristics, while differences in detail can be explained by their specific compositions. Price increases for all definitions have been strongest in the seven largest cities. The definitions tend to lead to more marked differences for medium-sized towns.

Determinants of stock return of property and real estate companies in the developing market

Macroeconomic risk factors can determine the expected return on property and real estate stocks (Khan, Khan, Ahmad, & Bashir, 2021), in addition to other factors: property prices (Das, Füss, Hanle, & Russ, 2020) and financial performance (Medyawati & Yunanto, 2017). This study aims to empirically prove the effect of interest rates (SB), exchange rates (KURS), commercial property price index (IHPK), return on assets (ROA), debt-to-equity ratio (DER), and current ratio (CR) on stock returns estimated using panel data regression model. The sample of this research is 23 companies from 63 companies in the property and real estate industry which are listed on the Indonesia Stock Exchange (IDX) during the 2015–2019 period. The empirical findings of this study prove that the ROA, CR, IHPK, and KURS variables have a negative effect on stock returns, while the SB variable has a positive effect. The level of corporate debt (DER) was not proven to determine stock returns. The exchange rate has the greatest influence on stock returns, and the fact does show that the Indonesian stock market is dominated by foreign investors, so that every time foreign currencies appreciate because they leave the stock exchange, the stock price immediately declines. The results of this study have implications for investors that investment decisions to buy shares of property and real estate companies must understand the changes that occur, especially macroeconomic variables and also the company’s financial performance

Commercial Property Price Indices and Indicators: Review and Discussion of Issues Raised in the CPPI Statistical Report of Eurostat (2017)

Commercial property price indices (CPPIs) are needed to monitor financial stability, guide investment decisions by firms, and improve national accounts. Due to a lack of suitable data, however, reliable CPPIs are often hard to construct. Here we survey the current state of the CPPI literature and assess the contribution of the recently published Eurostat CPPI report.

Compilation of Commercial Property Price Indices for Germany Tailored for Policy Use

The compilation of commercial property price indices is a big challenge. In Germany, substantive data gaps prevent the calculation of official figures by the national statistical authority. By contrast, policymakers urge for timely, reliable and comprehensive data. In this paper, proposals are made as to how to aggregate and classify individual price information in order to best serve the intended policy uses. Experimental price indices according to various definitions of commercial real estate are constructed on the basis of two components: (i) the appraisals for transaction prices of houses, apartments, multi-family dwellings, office buildings and retail space in 127 German towns and cities provided by bulwiengesa, a real estate consulting company; and (ii) corresponding data on floor space which make it possible to derive coherent weighting schemes. The overall price developments revealed by the various indices are rather similar in terms of central time series characteristics, while differences in detail can be explained by their specific compositions. Analysts may find these indices helpful to better understand price developments in German commercial real estate markets. Statisticians may acquire from this exercise further knowledge about measurement practices, as official statistics are encouraged to take steps towards establishing thorough reporting on commercial real estate markets.

Commercial Property Price Indexes and the System of National Accounts

The paper studies the problems associated with the construction of price indexes for commercial properties that could be used in the System of National Accounts. Property price indexes are required for the stocks of commercial properties in the Balance Sheets of the country. Related service price indexes for the land and structure input components of a commercial property are required in the Production Accounts of the country if the Multifactor Productivity of the Commercial Property Industry is calculated as part of the System of National accounts. The paper reviews existing methods for constructing an overall Commercial Property Price Index (CPPI) and concludes that most methods are biased (due to their neglect of depreciation) and more importantly, not able to provide separate land and structure subindexes. A class of hedonic regression models that is not subject to these problems is discussed.

COMMERCIAL PROPERTY PRICE INDEXES AND THE SYSTEM OF NATIONAL ACCOUNTS

AbstractThis paper studies the problems associated with the construction of price indexes for commercial properties that could be used in the System of National Accounts (SNA). Property price indexes are required for the stocks of commercial properties in the Balance Sheets of the country. Related service price indexes for the land and structure input components of a commercial property are required in the Production Accounts of the country if the Multifactor Productivity of the Commercial Property Industry is calculated as part of the SNA. The paper reviews existing methods for constructing an overall Commercial Property Price Index (CPPI) and concludes that most methods are biased (due to their neglect of depreciation) and more importantly, not able to provide separate land and structure subindexes. A class of hedonic regression models that is not subject to these problems is discussed.

Commercial Property Price Indices – meeting your needs?

Commercial Property Price Indices – meeting your needs?

Understanding Commercial Real Estate Indices

This paper examines five indices in the commercial real estate (CRE) markets: the National Association of Real Estate Investment Trusts (NAREIT) Index, the National Council of Real Estate Investment Fiduciaries (NCREIF) Property Index (NPI), the Transaction Based Index (TBI), Moody’s/Real Commercial Property Price Indices (CPPI), and CoStar Commercial Repeat-Sale Indices (CCRSI). We find much heterogeneity in the information content of these indices. NAREIT, NPI, and TBI may not be appropriate measures of current CRE market conditions in general, even though these indices, and especially the first two, are commonly used. We find substantial information differences between CPPI (an index driven by high-value CRE properties) and CCRSI (an index driven by low-value CRE properties) and the difference in information content is notable. This finding indicates that high- and low-value CRE markets are not closely linked. As most CRE indices are driven by high-value CRE markets, our findings suggest that most of these indices may not be very useful to non-institutional CRE investors, local banks who are the main lenders of such loans, or investors in CMBS where the underlying assets include low-value CREs. Finally, based on either CCRSI or CCPI, we conclude that CRE markets are local.

Estimating Transaction-Based Price Indices of Local Commercial Real Estate Markets Using Public Assessment Data

This study examines the feasibility of constructing reliable commercial property price indices using property tax records. We employ the Clapp and Giacotto (Journal of American Statistical Association, 87(418), 300–306, 1992) assessed-value method to estimate price indices for commercial properties in Florida. The estimated Florida commercial property price index is compared to the Moody’s/REAL Commercial Property Price Index (CPPI) and to the transaction-based index (TBI) produced at MIT. Our results are promising, suggesting that this widely-available data source can be used to produce commercial property price indices for a variety of precise market locations and specific investor segments. A secondary but interesting objective of this paper is to use our rich and comprehensive database to examine the price performance of two specific subsets of properties in more detail. First, we narrow our range to focus on just the office sector for Florida. We compare price movements for the Florida office sector with the comparable CPPI. Estimates produce very similar price movements providing support to both methods. Second, we contrast the price performance of higher- and lower-valued properties and reject the hypothesis that their periodic price index levels are equal. The mean price changes of Florida commercial properties assessed at $2.5 million and above are observed to be slightly higher than for properties assessed below $2.5 million, although not statistically different. In particular, higher-valued properties had higher mean price changes relative to lower-valued properties during periods of economic expansion. This economic difference represents an important contribution toward beginning to understand the relative performance of smaller and investment-grade commercial properties.

REITS and Underlying Real Estate Markets: Is There a Link?

This paper utilizes the Carlson, Titman, and Tiu (2010) model of REIT returns to estimate the strength of the relationship between REIT and underlying real estate returns. Our work further offers an innovative method for computing the returns of the real estate properties underlying each REIT using the Moody’s/REAL commercial property price indices by region and property type. We find a statistically significant relationship between REIT and real estate returns only in the office sector. Other property types offer only very weak and insignificant relationships. This finding suggests that direct real estate investment or investment through the property price index derivatives cannot be replicated using REITs.

Estimating Transaction-Based Price Indices of Local Commercial Real Estate Markets

This study examines the feasibility of constructing reliable commercial property price indices using property tax records. We employ the Clapp and Giacotto (1992) assessed-value method to estimate price indices from 1988:4 to 2008:4 for commercial properties in Florida. The estimated Florida commercial property price index is compared to the Moody’s/REAL Commercial Property Price Index (CPPI) and to the transaction-based index (TBI) produced by the Commercial Real Estate Data Lab at MIT. Our results are promising, suggesting that this widely-available data source can be used to produce commercial price indices for a wide variety of precise market locations and specific investor segments on an ongoing basis. We use our comprehensive database to examine two specific subsets in more detail. First, we narrow our range to focus on just the office sector for Florida. We compare price movements for the Florida office sector with the comparable CPPI. Estimates produce very similar price movements providing support to both methods. Second, we contrast the price performance of higher- and lower-valued properties. Chow tests indicate that Florida commercial properties assessed at $2.5 million, or above, appreciated on average at greater rates than those assessed below $2.5 million. In addition, our estimates indicate that highervalued properties performed especially well during periods of economic expansion. This finding represents an important contribution toward understanding the relative performance of smaller and institutional-grade commercial properties.

REIT-Based Property Return Indices: A New Way to Track and Trade Commercial Real Estate

Using REIT return data, bond data, and property holding data, the authors construct property market segment-specific indices of asset returns. The authors show that these <i>pure-play</i> indices can be employed to make pure, targeted investments in the commercial real estate market while retaining the liquidity, transparency, and pricing efficiency benefits of the well-developed public market in REITs. These pure-play indices compare favorably with existing property market return indices, displaying volatilities similar to transaction-based indices, such as the Moody’s/REAL Commercial Property Price Index, but tending to lead the private market in time. The pure-play indices can be generated at a daily frequency without significant noise and at various levels of market segment granularity and, notably, have led the transactions-based direct property market indices during the recent market downturn. The authors’ findings suggest that the REIT-based pure-play indices may provide a unique, new information source about the commercial property market, as well as a unique capability to facilitate targeted investments, construct hedges, and potentially support derivatives trading. <b>TOPICS:</b>In markets, real estate, options

GMM Repeat Sales Price Indices

Illiquid assets are widely spread within the economy but their indices are difficult to measure. This paper proposes a Generalized Method of Moment (GMM) repeat sales regression for estimating illiquid asset price indices. This method has estimators that are arithmetic averages of individual asset returns. This method is able to estimate custom‐weighted indices, including equal‐ and value‐weighted indices. It can incorporate hedonic variables to improve estimation accuracy, and it can work with a reweighting technique to mitigate a biased sample problem. Simulations based on artificial markets indicate that the method is more accurate than some alternatives in both efficient and sluggish markets, with and without temporal aggregation. As an application, we use this method to estimate a commercial property price index.

A Repeat-Sales Transaction-Based Index of Commercial Property

This study employs the repeat-sales transaction-based methodology, pioneered in the housing literature, to estimate commercial property price indices for the state of Florida over the 1975-97 period. The study is designed to: (i) investigate the feasibility of applying this method to estimate reliable commercial property indices; (ii) compare the transaction-based indices with the widely-used NCREIF (appraisal-based) index and its sub-indices; and (iii) examine the differences in the price movements of large institutional-quality properties versus a broader sample of commercial properties.