The Wall Street Journal had an interesting article the other day about the changing nature of the stock market, which highlighted two important trends in our politics. The overreliance on inherently flawed economic models and the unseen damage that regulation has on the economy. Following the Enron scandal in the early aughts, Congress passed Sarbanes-Oxley which raised expenses for public companies by mandating increased financial reporting and oversight of public companies. In response, companies have been waiting much longer before going public, or not going public at all, contributing to the decline in publicly listed companies. What are the costs of tilting the economic scale towards private financing? What are the costs of denying John Q Public the opportunity to invest in the newest companies at their early stages? Did the economists who reviewed this bill accurately predict a massive decline in public companies? Well that last one at least has a definitive answer, no. In reality though, the full cost of this regulation remains nearly unquantifiable. Yet, to this day, such economic predictions are trotted out as writ of law despite their repeated failure in providing an accurate forecast. During Obama’s years we had grandiose predictions about the great economic growth that would come from the stimulus and the amazing cost reducing expansion of insurance. Today we gets its reverse when dealing with the GOP’s healthcare bill.

Much like the quantitative strategies described in the Journal’s piece, economic models are backwards looking, dealing with an economy that is different from today’s economy. Beyond the obvious gaming of the CBO’s scoring system, the conversation about the legislative impact on the economy is woefully inadequate. I can’t recall a time when an economic estimate was discussed in terms of its confidence interval or variance. This is attributable to our sound bite politics and lack of public expertise on statistical modeling, but the lack of depth to the discussion of these numbers creates an absurd overconfidence in their powers of predictability. The highest paid and most brilliant minds working in Wall Street are unable to accurately forecast the market, why should we expect politically tainted analysis to do any better? This doesn’t mean that there shouldn’t be efforts to estimate economic impacts, it just means that predictions should be understood as a biased, educated guesses.

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