Recent Case Engages Two Blue J Tax Predictors: Real Estate and Gross Negligence

Feb 26, 2018

A recent case, DaCosta v. The Queen, 2017 TCC 234 (“DaCosta”), demonstrates how Blue J Tax can be used to analyze multiple issues within a fact scenario. The case concerned gains on the sale of two condos purchased pre-construction and sold within one month of closing, engaging both the Real Estate and Gross Negligence Predictors.

Real estate profits deemed to be income from business

In determining whether the gains on the sale of the condos were to be treated on account of income or capital, the court took note of the following factors: whether there was a reasonable expectation that the properties would be held for 5 years or more, taxpayer C.D.’s real estate experience, and the length of time for which the properties were held.

The court did not accept the taxpayers’ argument that they intended to hold the condos on a long-term basis. Neither taxpayer had the financial resources to complete the sales at closing, let alone hold the properties as a long-term investment. In particular, taxpayer C.D.’s credit rating was so poor that she had to rely on short term loans from friends to bridge the time between closing and subsequent disposition. Given her 18 years of experience as a real estate agent, she should have been aware of the need for financing and requirements to obtain such financing in advance of closing. Both condo units were listed for sale prior to the taxpayers taking ownership. In fact, one unit was subject to a contract for sale prior to closing. The other was sold within a month of closing. There were no unexpected circumstances that frustrated the taxpayers’ purported intention to hold the condos as an investment.

Gross negligence finding influenced by business acumen and diligence

In determining whether the taxpayers were grossly negligent, the court examined the following factors: relevant business experience, the level of review of the tax return, and the scale of the omission in comparison to the taxable income reported.

The court’s analysis focused on the actions of taxpayer C.D., who directed the transactions at issue. As mentioned above, she had been a real estate agent for 18 years at the time the condos were originally purchased in 2006. By the time she filed the 2010 tax return at issue, she had been a real estate agent for 23 years. As such, she was well aware that the profits of the sale were taxable. Justice Graham found that taxpayer C.D. had not disclosed the sale to her accountant and that, in any case, her review of the tax return prepared by her accountant was cursory. In addition, the scale of the omission in comparison to the amount of taxable income she declared was significant—the amount omitted was more than five times as the amount reported.

Case Insights from Blue J Tax

  • Blue J Tax’s Real Estate Predictor correctly predicts that the condo profits were income from business with 95%+ confidence.

  • Blue J Tax’s Gross Negligence Predictor correctly predicts that taxpayer C.D. was grossly negligent with 95%+ confidence.

  • If there had been an unexpected circumstance outside the taxpayer’s control that made it impossible to fulfill a primary intention to hold the property for 5 years or more, the Real Estate outcome would be income from business with 70% confidence.  

  • In Real Estate cases where the taxpayer or someone with a shared interest in the property worked in a real estate-related business or occupation, the result was income from business in 68% of the cases.

  • In Gross Negligence cases where the tax return did not accurately reflect all records received by the taxpayer, the result was grossly negligent in 79% of the cases. 

 Additional Resources from Blue J Tax  

Blue J Tax also includes a Gross Negligence Primer. Primers complement Predictors and Case Finders by providing a short summary of the law, key concepts, and relevant considerations in each area covered. They draw on traditional legal research and insights gained from Blue J Tax’s case law data and machine learning algorithms.