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When Units Are Getting Snatched Up Quickly , The Programs Recommend A Price Increase . When Units Are Starting To Sit Longer , The Programs Recommend A Price Decrease ."
Algorithmic pricing models are extremely valuable to the rental housing market because they reduce trial and error pricing . When units are getting snatched up quickly , the programs recommend a price increase . When units start to sit vacant longer , the programs recommend a price decrease . The algorithm gets the housing provider closer to the elusive “ perfect information ” necessary for free markets to function at peak efficiency .
The primary benefit of these programs is the speed of information . Information on rental and vacancy rates has always been collected and used to set pricing . However , collecting that information has historically been very time intensive , and the information has been published no more frequently than quarterly , forcing managers to rely on 3-6-month-old data .
A good computerized pricing system also carefully tracks and allows comparisons of all attributes of various rental units . By avoiding comparing apples to oranges , housing providers can avoid applying price changes in urban one-bedroom units to unrelated suburban three-bedroom units , etc .
Like every product in a free market , rental rates go up and down based on supply and demand . When there are not enough rental housing units to go around , consumers bid against each other , and prices rise . When there are more rental housing units than needed , rental housing providers lower their asking prices until someone is eventually willing to rent the unit .
The fact that all housing costs ( including rental housing costs ) are uncomfortably high is caused by unintended consequences of government policy . Governments will not allow people to build enough housing units to meet demand . This artificial restriction on the supply of rental housing units results from a myriad of restrictions and taxes on development that include density prohibitions , height limitations , development fees , sales taxes on construction materials , accessibility requirements , energy efficiency requirements and neighborhood approvals . While all of these policies have some rationale behind them , we have reached a point where 37 % of the cost of a new residential rental housing unit is spent on some form of regulatory compliance . Consequently , we are all being artificially incentivized to build too few housing units .
We should not be calling on rental housing providers to abandon computers and mathematics or to hide rent and vacancy rates . Instead , we should be calling on governments to allow more homes to be built .
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Computer programs that identify when there are not enough housing units to go around are not the problem . People with hostility against these formulas are engaged in the flawed logic of blaming the thermometer that it is too cold outside .
Drew Hamrick Is The General Counsel & Senior VP of Government Affairs At Apartment Association of Metro Denver