House Price Index - Definition
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House Price Index (HPI) Definition
The House Price Index or HPI is a quarterly index that measures changes in single-family home prices in the United States. The HPI acts as an indicator of home pricing trends by measuring and collating average price changes of properties during resale or refinance. The Federal Housing Finance Agency (FHFA) publishes the HPI using data supplied by the Federal National Mortgage Association (Fannie Mae) and the Federal Home Loan Mortgage Corporation (Freddie Mac).
A Little More on What is the House Price Index (HPI)
The House Price Index has its roots on transactions involving conventional and conforming mortgages purchased or securitized by either Fannie Mae or Freddie Mac. The properties involved in such transactions are typically single-family homes. Although comprehensive HPI reports are issued quarterly, there also exists a monthly report that has been available since March 2008. S&P/Case-Shiller Home Price Indices are other renowned repeat-sales house price indices. However, these indices differ from regular HPIs in that a typical Case-Shiller index only applies purchase prices, while an HPI also encompasses refinance appraisals.
House Price Index, Fannie Mae, and Freddie Mac
Transactions finalized by Fannie Mae form the basis for the HPI. The primary objective of Fannie Mae is to maintain cash flow in mortgage markets, which it does by acquiring and guaranteeing mortgages from lenders such as banking institutions. Both Fannie Mae and Freddie Mac are government-backed agencies. Freddie Mac acquires mortgages and then guarantees and securitizes them as mortgage-backed securities. Such mortgage-backed securities come with a good credit rating and when issued, bring in liquidity to the mortgage market. In addition, since it is a government body, Freddie Mac typically borrows money at very competitive interest rates.
House Price Index and Other Economic Indicators
There exist three primary categories of economic indicators. They are: 1. Leading indicators, 2. Coincident indicators, and 3. Lagging indicators. Some common economic indicators that gauge global economic trends are: Gross Domestic Product (GDP) Crude Oil Prices Consumer Price Index (CPI) House Price Index (HPI) Unemployment Rate Wage Share Economic indicators are vital fiscal instruments that facilitate monitoring of economic trends and stock market fluctuations.
References for House Price Index
Academic Research on House Price Index (HPI)
Spatial dependence andhouse price indexconstruction, Se Can, A., & Megbolugbe, I. (1997). The Journal of Real Estate Finance and Economics,14(1-2), 203-222. This article explores the importance of accurate estimation of prevailing metropolitan housing prices for both business and research investigations of housing and mortgage markets. The article argues that spatial structure, especially spatial dependence latent in housing data sets, will affect the precision and accuracy of resulting price estimates. It further illustrates the importance of spatial dependence in both the specification and estimation of hedonic price models. Assessments are made on the importance of spatial dependence both on parameter estimates and on the accuracy of resulting indices. On choosing amonghouse price indexmethodologies, Case, B., Pollakowski, H. O., & Wachter, S. M. (1991). On choosing among house price index methodologies.Real estate economics,19(3), 286-307. This paper compares housing price indices estimated using three models with several sets of property transaction data. It analyses the hedonic model, the weighted repeat-sales model, and a hybrid model. This paper evaluates the performance of each type of model using a particularly rich local housing market database. The results confirm the problems with the repeat sales model, and suggests that systematic differences between repeattransacting and singletransacting properties lead to bias in the hedonic and hybrid models as well. A simple alternativehouse price indexmethod, Bourassa, S. C., Hoesli, M., & Sun, J. (2006). Journal of Housing Economics,15(1), 80-97. This paper presents the sale price appraisal ratio (SPAR) method for constructing house price indexes. The paper compares the official New Zealand indexes for three urban areas with repeat sales and hedonic indexes created from the same transactions data, and observe that the SPAR method produces an index very much like those produced by repeat sales methods. The paper suggests that the SPAR model be considered by government agencies elsewhere when developing house price indexes. A Long RunHouse Price Index: TheHerengracht Index, 16281973, Eichholtz, P. M. (1997). Real estate economics,25(2), 175-192. This article introduces a biennial historic index of real estate values for the period 1628 through 1973. This index is based on the transactions of the buildings on the Herengracht, one of the canals in Amsterdam. House price indexconstruction in the nascent housing market: the case of China, Wu, J., Deng, Y., & Liu, H. (2014). The Journal of Real Estate Finance and Economics,48(3), 522-545. Using the booming market in China as an example, this paper evaluates and compare the performances of three most common house price measurement methods in the newly-built housing sector, including the simple average method, the matching approach with the repeat sales modeling framework, and the hedonic modeling approach. The analyses suggest that the simple average method fails to account for the substantial complex-level quality changes over time of sales during the sample period, and the matching model fails to control for the effect of developers pricing behaviors when adopted in the newly-built sector, hence both are downward biased. Ahouse price indexbased on the SPAR method, De Vries, P., de Haan, J., Van der Wal, E., & Marin, G. (2009). Journal of housing economics,18(3), 214-223. This paper reports on the results of a project to develop a house price index for the Netherlands. It describes the SPAR method, compare it with repeat sales methods and assess the reliability of the official Dutch appraisal values. Empirical results for January 1995March 2009 are presented. The paper suggests that the SPAR method performs well compared to repeat sales, and that the results reported will be of interest to other countries that have, or could instigate, institutional arrangements similar to those in the Netherlands. Developing ahouse price indexfor the Netherlands: A practical application of weighted repeat sales, Jansen, S. J. T., de Vries, P., Coolen, H. C. C. H., Lamain, C. J. M., & Boelhouwer, P. J. (2008). The Journal of Real Estate Finance and Economics,37(2), 163-186. This paper describes the development of a house price index that has been introduced in May 2005 in The Netherlands. The paper suggests that the Repeat Sales Method seems to be adequate for calculating a house price index for The Netherlands. Housing affordability: A conceptual overview forhouse price index, Suhaida, M. S., Tawil, N. M., Hamzah, N., Che-Ani, A. I., Basri, H., & Yuzainee, M. Y. (2011). Procedia Engineering,20, 346-353. This paper examines housing affordability as a key measure of a country's socio-economy stability. This research is carried out to identify possible application of affordability measures including Price-Income Ratio (PIR) for measurement of first owned medium cost landed-house by the middle-income group in Malaysia. Precision in house price indices: Findings of a comparative study ofhouse price indexmethods, Case, B., & Szymanoski, E. J. (1995). Journal of Housing Research, 483-496. This study assesses the relative precision of alternative house price index modeling techniques by comparing several measures of precision for "simple" and "complex" versions of three available methodologies: the commonly used hedonic price model, the weighted repeat-sales model, and a hybrid model incorporating both approaches. The paper aims to show that the best estimate of cross-sectional variation in house prices can be derived using the complex hybrid model. Forecasting the US realhouse price index: Structural and non-structural models with and without fundamentals, Gupta, R., Kabundi, A., & Miller, S. M. (2011). Economic Modelling,28(4), 2013-2021. This paper employs a 10-variable dynamic structural general equilibrium model to forecast the US real house price index as well as its downturn in 2006. It also examines various Bayesian and classical time-series models in its forecasting exercise to compare to the dynamic stochastic general equilibrium model, estimated using Bayesian methods. Forecasting the US realhouse price index, Plakandaras, V., Gupta, R., Gogas, P., & Papadimitriou, T. (2015). Economic Modelling,45, 259-267. This paper investigates how the 2006 financial crisis revived forecasting interests of similar threats for economic stability. The paper proposes a novel hybrid forecasting methodology that combines the Ensemble Empirical Mode Decomposition (EEMD) from the field of signal processing with the Support Vector Regression (SVR) methodology that originates from machine learning. The paper tests the forecasting ability of the proposed model against a Random Walk (RW), a Bayesian Autoregressive and a Bayesian Vector Autoregressive model. It further argues that this new methodology can be used as an early warning system for forecasting sudden house price drops with direct policy implications. Accuracy and robustness ofhouse price indexmethods, Goh, Y. M., Costello, G., & Schwann, G. (2012). Housing Studies,27(5), 643-666. This paper evaluates the statistical properties of five different house price index methods with the objective of identifying one that is most accurate and robust when estimated at frequent time intervals and for distinctly local markets. Repeat saleshouse price indexmethodology, Nagaraja, C., Brown, L., & Wachter, S. (2014). Journal of Real Estate Literature,22(1), 23-46. This paper compares four traditional repeat sales indices to a recently developed autoregressive index that makes use of the repeat sales methodology but incorporates single sales and a location effect. This comparison addresses the effect of gap time on sales, use of hedonic information, and treatment of single and repeat sales.