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New Research Highlights: December 2022
There’s a lot of new and interesting economic research being produced everyday. In this segment, I will point out and summarize research questions that are either novel ideas or have potential for significant policy implications.
Real Time Inequality by Blanchet, Saez, and Zucman
One issue faced by economists and policy makers is knowing what is the actual current state of the economy. As many fiscal or monetary decisions have delayed effects, it is important to know the current state of the economy rather than what was happening a quarter ago using delayed data. Blanchet, Saez, and Zucman use a variety of data sources that are published each month including monthly surveys, labor and wage censuses to estimate the current distribution of income in the US. They test their methodology by going back until 1976 and comparing their predicted results to actual data that we have for those time periods. Although this could lead to over-fitting (i.e. matching the past data too well, making it potentially a poor tool for modeling the future, especially if there was something unique about the past data that is no longer relevant today), I believe that this methodology can quickly be tested in the coming months/years as they post their estimates regularly on https://realtimeinequality.org/. According to the authors, since the start of the pandemic (April 2020), based on their data, the bottom 50th percentile of the income distribution has seen a real growth in income of 36.4%, similar to the income growth of the top 1%. On the other hand, the middle 40% (50th percentile to 90th percentile) saw only a rise of 11.4% in real incomes. In the last 5 years, growth of wages for the bottom 50th percentile and the top 1% have been similar (around 8-9%), whilst the middle 40% saw only growth of 2.3%.
Tax Collection Mechanisms – Using Divide-And-Conquer To Improve Tax Collection: Evidence From The Field by Del Caprio, Kapon, and Chassang
A big issue for many governments is tax collection. The US Tax Collections agency, the IRS, is considered to be one of the best investments for government spending. Every additional dollar of spending on the IRS, generates around 5 to 9 dollars for the US public according to the CBO. This is mainly because taxpayers (whether individuals or corporations) prefer to risk underpaying tax, as they assume that they will not be audited. Due to budgetary limitations, we are unable to freely increase the spend of the IRS. The authors of this paper look into ways to encourage tax compliance in a setting with a limited budget. By looking at the property tax collection of one of the wealthier districts in Lima, Peru, the authors find that the current tax collection system can be improved by implementing a priority collection system. By informing certain households that they owe taxes and that they are on a priority enforcement list, tax revenues collected went up by at least 2.8% (potentially up to 9%) while the enforcement costs went down. The selection of households that would receive the enforcement letter was based on certain observables such as size of the tax owed and past tax payment histories. This is a very interesting paper, showing that with limited budgets, targeted enforcement can be very effective in increasing tax revenue.
Expert Investors? – Predictably Bad Investments: Evidence from Venture Capitalists by Diag Davenport
Are early stage investors and venture capitalists better than an algorithm? This paper suggests that the answer to that question is ‘no’. Although venture capitalists outperform the broad stock market quite significantly, most of this overperformance is driven by only a subset of their investments. An algorithm can prune out the investments that are ‘predictably bad’. This increases returns by approximately 7–41%, creating an even larger magnitude of outperformance versus the stock market. The author believes the reason for the poor investment decisions is the over-weighing of the characteristics of the founders of startups. Interestingly, I wonder if there is a repeated interaction component that might be at play – if you back the founder during a failed investment, the founder might accept you as an investor in the future when they’ll have a more successful investment.