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Model for modeling initial claims using exponential decay within a mixed-effects framework

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Modeling Initial Claims as Quasi-Natural Disasters

Unprecedented is a word often used in the context of the economic data being generated in the post-COVID world, but are there historical episodes that may be useful in serving as guide in terms of thinking about near-term job losses after the initial shock observed in late March. What could the path of initial claims be over the next few months, and what should we expect in terms of the total number of claims during thi period?

In Bram & Deitz an interesting idea to answer this question is explored --- that the COVID shock to labor markets is more akin to a natural disaster like hurricane Katrina or Maria, rather than a classic recession-induced hit to employment. As they correctly point out

Recessions typically develop gradually over time, reflecting underlying economic and financial conditions, whereas the current economic situation developed suddenly as a consequence of a fast-moving global pandemic. A more appropriate comparison would be to a regional economy suffering the effects of a severe natural disaster, like Louisiana after Hurricane Katrina or Puerto Rico after Hurricane Maria. To illustrate this point, we track the recent path of unemployment claims in the United States, finding a much closer match with Louisiana after Katrina than the U.S. economy following the Great Recession.

While the national scope of the COVID shock is clearly different and unprecedented, there are similarities with natural disasters which by their nature, tend to be more localized. As such, they can provide insights into the way labor markets evolve in the short-run. We do this by estimating exponential decay models for different episodes, both natural-disaster related or recession-driven, and calibrate the parameters of this process to the historical data on claims.

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Model for modeling initial claims using exponential decay within a mixed-effects framework

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