Academic journal article
By Reeder, Paul J.
Journal of Real Estate Literature , Vol. 9, No. 2
The author describes the SNL DataSource, an interactive database service, and its symbiotic relationship with the contemporary public real estate industry. First compiled with the advent of the current generation of real estate investment trusts in the early 1990s, DataSource contains eleven years of financial data on over 225 companies, tracks 1,300 separate capital issues and provides data on over 36,000 properties owned by these companies. DataSource is utilized for decision-making by analysts who track the companies, by investors in the industry, and is a unique source for academic research into the public real estate markets.
Most observers generally date the birth of the modern real estate investment trust (REIT) industry to the initial public offering of Kimco Realty Corporation in November 1991. From that point forward, the size of the REIT market has grown at a phenomenal rate, such that the industry in aggregate today is approximately twenty times the size it was at the end of 1991.
One of the benefits from this growth of the public real estate market is a greater scrutiny of the industry by the capital markets. There can be no doubt that real estate markets are more "transparent"-and therefore more efficient-now than they have ever been. Whereas the art of the real estate researcher in the 1980s resided in an ability to find the data, today the emphasized talent lies in organizing and managing the avalanche of available information. In 1994, SNL Securities1 decided to employ the information gathering and distribution expertise it had gained in the banking sector, which it had been covering since 1987, in the booming industry of public real estate. In particular, SNL perceived an excellent expansion opportunity, sensing that the reporting eccentricities of the industry (e.g., FFO) and the unique economics of real estate required the attention of an experienced specialist information provider.
The result is a powerful database-the SNL DataSource-that contains eleven years of financial data on 225 companies, tracks more than 1,300 separate capital issues of those companies and provides data on more than 36,000 of their properties. This data is entered, checked and updated on a daily basis by a team of twelve analysts in Charlottesville, Virginia. For example, information that is made public on Monday is entered in the DataSource and distributed electronically to all of SNL's clients by Tuesday. These clients include every investment bank on Wall Street and about half of the top fifty owners of real estate securities. SNL's clients use the DataSource to provide the foundation for their financial analysis of the real estate industry. Clients prefer SNL's DataSource to the products of other data providers because of the guaranteed quality of the data,2 the speed of new data entry, and the functionality of the program. In addition, DataSource clients use the program to access SNL's newsletters and news article archive. The newsletter is published overnight and contains a comprehensive round up of the prior day's industry news. The newsletter has been published continuously since March 1996 and all articles written since then are now available through SNL's News OnLine from a searchable database.
Appendix A is a PC desktop "screen shot" taken from the DataSource, which displays a table of information on a sample of the largest real estate companies that SNL covers. Standardized reports are available for convenience, but reports can be easily customized to show exactly the data needed. Included in the screen shot are typical data items, depicting whether or not the company is a REIT,3 what property type the company specializes in, the market value of its common shares, debt-to-capitalization and fixed-charges coverage ratios, as well as dividend yield. In this instance, all of these items are accurate as of the close of the last trading day of 2000. The items shown are selected from the more than 450 individual fields tracked in the DataSource. …