[From the blog, “Opening up the analysis behind Elizabeth Warren’s wealth tax plan” posted at BITSS]

“Senator Elizabeth Warren declared her 2020 presidential bid on a platform based on policies to rebuild the American middle-class. A key part of her campaign will be a progressive wealth tax on the net worth of American households, including a 2% tax on net worth above $50 million, and an additional 1% tax on net worth above $1 billion.”

“UC Berkeley economists Emmanuel Saez and Gabriel Zucman—the researchers whose analysis forms the basis of the plan—estimate that “75,000 American households (less than 0.1%) would be liable for the wealth tax and that the tax would raise around $2.75 trillion” in the first ten years of its implementation.”

“…Saez and Zucman teamed up with BITSS to “open up” their analysis, publicly sharing all their data and methods to make it possible for anyone to assess its validity and credibility. Having worked with researchers in academia to tackle the credibility crisis in the social sciences by improving the transparency and reproducibility of research, BITSS is now looking to apply relevant lessons to policy analysis.”

“…the team developed an interactive plot to simulate the results of the analysis for different parameters…; an ‘open policy report‘ that details all data, code, and assumptions behind the analysis; and an open online repository that stores all materials necessary to reproduce the analysis from scratch. Using the interactive plot, readers can alter the number of tax brackets, apply different rates to each, and even adjust the estimated tax evasion rate, observing how each alteration affects the tax burden, tax base and projected revenue.”

“The open policy report then goes a step further, and details how Saez and Zucman constructed each parameter, spelling out each assumption behind the proposal, including their estimated tax evasion rate, one of the proposal’s most contentious elements. Finally, readers can download all materials from the online repository, and recreate the analysis in full with minimal effort.”

To read more, click here.