Slow labor market recovery does not have to mean the core fix is or was nominal in nature, even if the original negative shock was nominal:
Recent critiques have demonstrated that existing attempts to account for the unemployment volatility puzzle of search models are inconsistent with the procylicality of the opportunity cost of employment, the cyclicality of wages, and the volatility of risk-free rates. We propose a model that is immune to these critiques and solves this puzzle by allowing for preferences that generate time-varying risk over the cycle, and so account for observed asset pricing fluctuations, and for human capital accumulation on the job, consistent with existing estimates of returns to labor market experience. Our model reproduces the observed fluctuations in unemployment because hiring a worker is a risky investment with long-duration surplus flows. Intuitively, since the price of risk in our model sharply increases in recessions as observed in the data, the benefit from creating new matches greatly drops, leading to a large decline in job vacancies and an increase in unemployment of the same magnitude as in the data.
That is from a new NBER working paper by Patrick J. Kehoe, Pierlauro Lopez, Virgiliu Midrigan, and Elena Pastorino. Essentially it is a story of real stickiness, institutional failure yes but not primarily nominal in nature.
Perhaps more explicitly yet, from the new AER Macro journal, by Sylvain Leduc and Zheng Liu:
We show that cyclical fluctuations in search and recruiting intensity are quantitatively important for explaining the weak job recovery from the Great Recession. We demonstrate this result using an estimated labor search model that features endogenous search and recruiting intensity. Since the textbook model with free entry implies constant recruiting intensity, we introduce a cost of vacancy creation, so that firms respond to aggregate shocks by adjusting both vacancies and recruiting intensity. Fluctuations in search and recruiting intensity driven by shocks to productivity and the discount factor help bridge the gap between the actual and model-predicted job-filling rate.
Again, a form of real stickiness more than nominal stickiness. The claim here is not that the market is doing a perfect job, or that the Great Depression was all about a big holiday, or something about video games that you might see mocked on Twitter. There is a very real and non-Pareto optimal coordination problem. Still, this model does not suggest that “lower interest rates” or a higher price inflation target from the Fed, say circa 2015, would have led to a quicker labor market recovery.
Even though the original shock had a huge negative blow to ngdp as a major part of it (which could have been countered more effectively by the Fed at the time).
I am not sure there is any analytical inaccuracy I see on Twitter more often than this one, namely to blame the Fed for being too conservative with monetary policy over the last few years.
And please note these pieces are not weird innovations, they are at the core of modern labor and macro and they are using fully standard methods. Yet the implications of such search models are hardly ever explored on social media, not even on Facebook or Instagram! You have a better chance finding them analyzed on Match.com.