Tag Archives: Forecast

Sales Projections for Alabama Real Estate Markets 2012

ABRE Analytics studies correlation between unemployment rates and future real estate sales projections; projects statewide real estate sales growth of 13%

With the release of the metro unemployment data for January 2012, ABRE Analytics is pleased to present our combined projections and commentary for the Alabama real estate market. One note, the current projections are considerably more optimistic than the preliminary ones due to the much better than expected unemployment rates.

Area 2011 Projection 2011 Actual 2011 Error 2012 Projection Correlation% 2004-2011 % change from 2011
Statewide 37,118 36,965 -0.41% 41,992 83.68% 13.60%
Huntsville 8,259 8,610 4.23% 9,050 77.60% 5.11%
Birmingham 12,737 12,468 -2.15% 14,550 86.77% 16.70%
Auburn 1,016 1,132 10.27% 1,138 83.40% 0.49%
Tuscaloosa 1,662 1,743 4.64% 1,826 80.62% 4.78%
Montgomery 3,335 2,774 -20.24% 3,679 84.65% 32.63%

Preliminary looks at the Mobile and Baldwin county areas showed poor results, probably mostly due to exogenous events like hurricanes and oil spills. The projected increase for Montgomery seems out of line. It is also noted that the performance of the projection for 2011 in Montgomery was quite poor. Possible reasons include the high dependence on government employment and the high uncertainty surrounding it in spite of the low, and declining unemployment rate.

ABRE Analytics present these projections as a “work in progress” and as a tool for assessing how well current sales are performing against some level of “informed” expectation. You should not rely on them, but nonetheless we hope you will find them useful.

It is always possible that catastrophic financial events or natural disasters will dramatically change people’s outlook for the future and therefore immediately impact the plans for home purchases. For the time being however we do not see anything that predicts nearly as well as unemployment. Unemployment rates have issues such as people dropping out of the workforce, but overall dropping rates are one of the best indicators of consumer expectations, and therefore predictors of home buying intent.

In the process of developing this methodology we also tested it in other geographies and found similar results. Further, we tried to find correlations to mortgage interest rates and found them to be not at all predictive of home buying activity.

Month to month break-out of the yearly projections are done by taking the sum of the 2004-2011 monthly volumes, for each market, and deriving the monthly spread of sales from those volumes.

The monthly estimated volumes do show more variation since we are dealing at finer levels of detail. The monthly tables are located here http://goo.gl/WFHrO, along with all the worksheets for deriving the forecasts.. The detailed spreadsheets also show the 1st two months projections vs. actuals for 2012, which look quite accurate, except for the previously mentioned Montgomery.

About ABRE Analytics: Strategic collaboration is one of the keys to accelerating the flow of insights in the 21st century. The Alabama Center for Real Estate (ACRE) and Tom Brander has been successfully collaborating since 2009 when Mr. Brander was appointed to the ACRE Leadership Council. Council members provide insight and counsel on current market trends, and enhance the sustainability of ACRE through vision, resourcefulness, and creativity. Without creativity and collaboration, two recent ACRE projects, the “Alabama Real Estate Confidence Index” and the “Alabama Residential Data Center” gadget for smartphones would still be on the drawing board. The flow of ideas that in turn lead to solutions to better serve the Alabama real estate industry and consumers is virtually an endless stream and ACRE and Tom Brander are forming ABRE (ACRE/Brander Real Estate) Analytics as a strategic collaborative umbrella that will foster future creative thinking while also providing hands-on experience for student/interns of ACRE.

This latest initiative explores methods to project future residential real estate sales. “Late last year, Tom shared his published preliminary projections that were based on estimates of the US Bureau of Labor Statistics January unemployment rates for a limited area in Alabama. The preliminary results looked quite good and initial test showed high accuracy for 2011 (when calculated blind from the 2011 January unemployment data) and ACRE desired to broaden the project across applicable statewide markets”, according to Grayson Glaze, executive director of ACRE.

About ACRE: ACRE, housed within the UA’s Culverhouse College of Commerce, collects, maintains and analyzes the state’s real estate statistics, and is a trusted resource for Alabama real estate research, education and outreach. The relationship between the Center and our industry stakeholders is one of the Center’s greatest strengths. Alabama companies and individuals partner with the Center bringing a wealth of resources and experiences, becoming, in effect, extensions of the Center, a network through which our outreach to the Alabama real estate industry is enhanced and enriched.To learn more, please visit www.acre.cba.ua.edu.

About Tom Brander: Tom provides Real Estate market reporting services which can be found at http://tombrander.com and Software services for Web, mobile and Data analysis, using Open Source Software, more information at http://oswco.com . He is a senior member of the ACRE Advisory council, and assists ACRE in its research programs.

Alabama, Birmingham, and Huntsville Real Estate Market in 2012-Forecast

While the Real Estate market adage is “Location, Location, Location” I submit that based on this study that maybe it should be “Jobs, Jobs, Jobs”

Over the years, I have often been asked to predict what will happen in the future in the residential real estate market. I have generally resisted providing answers to this, pointing out that the current data which I provide gives some pretty strong hints.

However, in doing some consulting work I have come across some useful correlative data that holds promise for quantifiable, accurate, projections of future real estate sales.

While it is  important to keep the adage “correlation is not causation” in mind, correlations can be useful and dependable if they pass the “common sense” test.

I have found that for a given area, the Bureau of Labor Statistics Unemployment Statistics can reasonably and reliably predict future sales. This makes sense in that buying homes is not a spur of the moment decision, but rather influenced by consumer future expectation, which is nicely captured and influenced by the unemployment rate.

To date, I have tested this concept in multiple markets with similar results. I expect that additional implementation will show similar predictive capabilities.

Since both the real estate and labor market have large seasonal swings, I chose to use the January unemployment rate to project the entire year’s transaction volume. I then spread the volume over the individual months, based on the historical percentage of sales that a given month has in a year. The percentage sales in a month holds steady in “normal” years. I have currently used 2004-2011 to arrive at the percentage sales per month. I suspect that some inaccuracy comes from including 2010 when we had the really abnormal melt-down followed by the extraordinary tax credit. Rather than continue adjusting numbers, I have chosen to publish these preliminary findings in the hope that others can help with the methodology.

Summarizing the findings:

How Unemployment correlates to Real Estate Sales from 2004-2010:
Correlation rate:
Statewide         80%
Birmingham     83%
Huntsville         73%

I have also tested a few other areas, outside Alabama, with similar results.

Interestingly, when I included years before 2004, correlation rates went down. I suspect that this is due to the way financing changed in 2004. I also suspect that years before 2004 will show strong correlation, and that years post 2004 will continue to show even more correlation just not across the 2004 “divide”. This remains for more research. By the way I attempted to find some correlation based on mortgage interest rates. In short, there was none. There may be some very short term impact from interest rates, but nothing close to the jobs market.

Based on the initial correlations a linear regression can predict sales for 2011, and preliminarily for 2012 (based on the estimated January 2012 unemployment rate) for the same three markets.

Market 2010 (actual) 2011 (proj) 2012 (proj)
Statewide 36,234 37,407 39,429
Birmingham 12,235 12,736 13,430
Huntsville 8,543 8,321 8,507

The statewide totals are via the Alabama Center for Real Estate

The monthly projected results compared to the actuals for 2011for Birmingham are as follows:

2011 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov
proj 755 877 1135 1137 1239 1314 1180 1191 1090 933 914
actual 683 773 1072 1022 1106 1255 1237 1224 1145 983 944
%error -10.5 -14.9 -5.9 -11 -12 -4 4 2.7 4.8 5 3
Cumulative error 2.9

As you can see this is quite encouraging. The cumulative error for 2011 projections is under 3% for 2011. I believe that excluding 2010, to calculate the monthly changes, due to the tax credit impact will improve the monthly accuracy.

Why might this be useful?

If the results during the year do not unfold as projected one should be looking for the reasons such as the tax stimulus or similar government action. It is also likely that other impacts and shocks to consumer expectations will cause the market to react in ways that are not accounted for in the projections. One can think of major disasters such as the coastal oil spill and multiple weather events. I have not yet tried to see how the coastal markets can be projected.