Figure 1: Nonfarm payroll employment (blue), industrial production (red), personal income excluding transfers in Ch.2012$ (green), manufacturing and trade sales in Ch.2012$ (black), and monthly GDP in Ch.2012$ (pink), all log normalized to 2019M02=0. Source: BLS, Federal Reserve, BEA, via FRED, Macroeconomic Advisers (5/29 release), Bloomberg, and author’s calculations.
As of Friday, May 29th, NY Fed, Atlanta Fed and St. Louis Fed nowcasts for Q2 are -35.8%, -51.2%, and -49.75% (SAAR), respectively. IHS Markit is -42.9%.
That’s from an article today:
The White House will not release an updated round of economic projections this summer, breaking from precedent as the U.S. faces its deepest downturn since the Great Depression, two administration officials familiar with the decision confirmed to The Hill on Thursday.
I hear a lot about deaths rising with recessions. What does the data indicate about the robustness of such a relationship?
From the Washington Examiner, and op-ed, via AEI:
According to researchers at Columbia University, implementation of shelter-in-place/social distance measures one week earlier would’ve saved 36,000 lives. Given the GDP that was generated in that one week, this implies Trump’s implicit valuation of one life is $1.16 million (compared to typical Value of Statistical Life of about $11 million).
By the rest-of-the-world, i.e., countries that China did not retaliate against. Thanks, Trump!
See also Carter and Steinbach (2020).
Our reduced-form regression results indicate large and statistically significant trade effects of retaliatory tariff increases for the United States and non-retaliatory countries. The identification is robust to pre-existing trends and anticipatory effects and reveals substantial heterogeneity between products and trading partners. We find that the United States lost more than USD 15.6 billion in trade with retaliatory countries. Soybeans, pork products, and coarse grains recorded the most substantial trade destruction effects. These losses are only partially compensated by additional exports to non-retaliatory countries. At the same time, non-retaliatory countries were able to considerably expand their trade with retaliatory countries. The analysis shows that these countries gained USD 13.5 billion in additional trade with retaliatory countries. The trade diversion effects are dominated
by increasing exports of soybeans and pork products. The primary beneficiaries of retaliatory tariff increases are countries from South America such as Argentina, Brazil, and Chile. Retaliatory countries also increased their imports from Eastern Europe and the EU. These results indicate that the 2018 trade war had substantial redistribution effects for global agricultural and food trade.
A couple years ago, Ryan LeCloux and I were cataloging the ways in which to track the individual state economies, at higher than annual frequency (paper here). I think that topic will be of interest again. State employment figures for April will come out on the 22nd, Philadelphia Fed coincident indices on the 27th.
For now, consider the evolution of the coincident indices going from February to March.