Right across the street from our office building is a field. Every once in a while we'll notice farm equipment rolling onto the property, tending to the growing rows of various crops. It's prime real estate, almost 110 acres near the intersection of two major highways. The owners are members of one of Dallas' most notable old money families who, among other pursuits, are land developers. They are not farmers.
Yet, by leasing their land to a farmer who reaps a nominal harvest, they get an agriculture tax break that saves them about $545,000 each year in taxes. Their savings is lost money for cities, schools and county governments. Last year, two Morning News county reporters (Ed Housewright and Kevin Krause) and I decided to investigate just how much tax money schools, cities, and counties lost through these agricultural exemptions.
We also wanted to know which landowners profited the most from the tax break. Were they really farm families for whom the exemption was created almost 30 years ago? Or were they corporations, developers and land speculators looking to save millions in taxes by leasing the land for farming? Our goal was straightforward. We wanted to measure the taxable value of the agriculturally designated land and its market value.
Then we had to calculate taxes based on the agricultural value versus the market value to find the total revenue lost to exempt property. Our data came from property records from our four main counties: Dallas, Denton, Collin, and Tarrant. In Texas, entities called appraisal districts assess properties for the various taxing entities. The Tarrant Appraisal District had all of its data available for free download on its Web site.
The Denton district sent its data to us on CD. We had previously paid for Collin County data, but the appraisal district didn't charge us for this year's update, downloaded via FTP. Dallas district officials initially said they were going to charge us for our download, but never did. The format of each district's data varied. Dallas' was in Microsoft SQL Server format. Collin's was in dBASE. Denton's was comma delimited text.
Tarrant's initially came with special translation software, but it was too cumbersome so the technician there ended up sending a comma delimited file. The number of records ranged from about 270,000 for Collin to about 900,000 for Dallas, with a maximum of 30 fields. I talked to every database manager before coming up with my methodology to make sure I was using the right categories. After I finished, I outlined my step-by-step process and e-mailed it to them asking them to try to poke holes in it.
They responded that my methods were sound. The calculations were simple. Using Microsoft FoxPro, I created four separate smaller tables from the original large datasets (more than 1 million records in one case). I chose records in which the amount in the agricultural value field was greater than zero. I created a Microsoft Access database and imported the smaller files so I and the other reporters could work on them.
For each table, I ran a sum query on the market and agriculture (or taxable) value fields. The difference between market value and agriculture taxable value provided the value of taxable property exempt or "lost" to the taxing districts. I put these LOST numbers in a separate column. But it's not the amount of lost tax revenue yet. That takes another step. Each property record in an appraisal district database includes one or several fields to indicate that property's taxing entities.
I did a GROUP BY on each entity field and a SUM on the newly created LOST field. That gave me the total value lost by each entity. I had previously downloaded Excel or text files from the districts' Web sites with each taxing jurisdiction's tax rate. I plugged my LOST totals into those files. The result: The total amount of tax revenue each taxing entity lost this year because of the agriculture tax break.
One district in a fast-growing suburb north of Dallas was losing more than $20 million in revenue. Speculators and businesses with valuable land were paying a pittance in taxes because they either ran a farming operation on it themselves or leased it to a farmer to keep it agriculturally active. After we saw who the big losers were, we wanted to find the big winners. I started to calculate this by doing a GROUP BY on the taxpayer name field and a SUM on the LOST field.
I also grouped by taxpayer ID and by the taxpayer address field. I struggled to definitively say that a certain proportion of property owners claiming the exemption were big businesses or land speculators. So, I dumped my taxpayer file that I recently sorted into Excel. My intent was to find an easy way to prove that most – or more than half – the value of the ag exemption was held by major corporations or land speculators.
I started by sorting descending by the companies with the largest amount of taxable value deducted because of the exemption. I did a rolling sum of those values until the total sum equaled more than half the total sum of the exemption values. Through some calculations, and some eyeballing, I determined that most of the value was attributable to large corporations and property development companies.
We also decided to map the parcels receiving the tax break using ESRI ArcView 8.3, and the parcel shapefiles the districts gave us for free. Farmers and ranchers were the most vocal proponents of the system. Even though they're not benefiting directly from the tax break, they are able to lease cheap land and keep farming in an area where vacant farmland is disappearing.