Home price indexes (HPI), such as the CoreLogic HPI and the CoreLogic Case-Shiller Indexes, are vital tools for understanding valuation and risk trends in real-estate markets. The main ingredients in the CoreLogic indexes are prices on settled transactions, as subsequently recorded by local jurisdictions in publicly available records. Since it takes time to record transactions, collect data, and produce indexes, there is always a lag between the availability of the data and the calculation of the HPI. Thus, the effect of the COVID-19 disruptions on home sales may not appear in HPIs for another month or two.
On the other hand, the home buyer and seller agree to a price in their sales contract, which is generally signed about 30 to 45 days before a sale is settled. This information can be a leading indicator of what to expect over the next couple of months.
CoreLogic has developed a Pending Price Index using MLS data. The index is built on the price recorded on the contract date rather than the price on the closing date, and hence by design is a leading indicator of HPIs that utilize final recorded home price to generate the index. The Pending Price Index is built using a hedonic approach, which differs from repeat sales methods used for most other HPIs.1
To understand the time series relationship between the contracted price and the settlement price data, we estimated correlation coefficients for a 20-city composite Pending Price Index to its corresponding 20-city composite CoreLogic HPI. The 20-city composite index is the aggregated index for 20 major metropolitan areas. 2
Figure 1 shows the correlation between the month-over-month percent change of the 20-city composite CoreLogic HPI and the month-over-month percent change of different lags of the 20-city composite pending index, estimated over the January 2006 to February 2020 period.
As Figure 1 shows, the CoreLogic HPI has the highest correlation with the one-month and two-month lag of the Pending Price Index, which suggests the Pending HPI leads the CoreLogic HPI by one to two months. Hence, by leveraging March MLS data, it is possible for us to take a peek at home price trends in April. The CoreLogic HPI report released on May 5 provides indexes through March and has no April values.
Figure 2 shows the actual and projected3 year-over-year changes for the 20-city composite HPI. The Pending Price Index projects changes in the actual CoreLogic HPI very well. Home price appreciation started to slow down during April 2020, which reflects the impact of COVID-19 on the home sales as the April price would partially be driven by sales that were pending in March. Annual price growth had been accelerating in the 20-city CoreLogic HPI composite for the five months prior to April 2020. The Pending Price Index projects the annual price growth to slow by 0.3 percentage points between March and April.
The Pending Price Index uses additional information from MLS data about what is happening now in the housing market that will be reflected in the CoreLogic HPI in the future. By leveraging the information in the Pending Price Index, housing market participants can stay one step ahead and be alerted to what may happen in this rapidly changing market.
 Stephen Malpezzi, Hedonic Pricing Models: A selective and Applied Review, Housing Economics and Public Policy Chapter 5, 2008
 The 20 urban areas are Atlanta, Cambridge (MA), Charlotte, Chicago, Cleveland, Dallas, Denver, Detroit, Las Vegas, Los Angeles, Miami, Minneapolis, Phoenix, Portland, San Diego, San Francisco, Seattle, Nassau County-Suffolk County (NY), Tampa, and Washington DC. The composite index is the weighted average of indexes in these cities where the weight is the entire housing stock in units.
 The projection is one-period ahead projection. For instance, the April 2020 HPI is projected by using the March 2020 and February 2020 pending indexes, and the March 2020 HPI is projected by using the February 2020 and January 2020 pending index.