Remember “austerity” and “expansionary contraction” stories? Well, if you don’t, then gird yourself for another round of claims (primarily by non-macroeconomists) about how state and local governments need to tighten up their finances, by cutting spending (and cutting taxes to necessitate further spending cuts). Perhaps, we should consider expanding federal transfers to the states and localities…From the fourth round survey of the IGM/Fivethirtyeight Covid-19 panel:
A reader defends the Trump administration’s implementation of public health policies in the face of the Covid-19 pandemic:
Trump never dismissed the pandemic, if you look at his full quotes rather than dishonest snippets. He has always followed the advice of his senior health policy officials. And Trump did a tremendous amount to manage the pandemic. Unfortunately, he gets little credit for that, since the media has actively suppressed the Administration’s accomplishments.
Why do reported growth rates differ for the same variable? Refer to the last three years of GDP data to see… [this is an updated version of this 2018 post]
Figure 1: Quarterly GDP, SAAR, FRED series GDPC1 (black line), annual, FRED series GDPCA (blue bars), in billions of Chained 2012$. 2018 annual (quarterly) growth rate (pink arrow); annual 2018 y/y growth rate (orange arrow); 2020Q1 annual quarterly growth rate (red arrow); 2020Q1 q/q SAAR growth rate (green arrow). Source: BEA, 2020Q1 3rd release via FRED, and author’s calculations.
Note: SAAR denotes Seasonally Adjusted at Annual Rates.
Conventions in the US are to cite q/q SAAR or y/y quarterly data (i.e., 4 quarter changes). In Europe, q/q growth rates are typically not annualized.
So, there are several ways to calculate the growth rate over the course of the year. They will almost invariably differ, perhaps substantially, when GDP is either growing very rapidly or shrinking very rapidly. And there is no “right” way. If one wants to calculate the most recent growth experience, one might stress q/q. If one wants to look at a longer horizon, then one might want to use the quarterly y/y. If one thinks quarterly series are very noisy, one might want to look at annual y/y.
Additional Note: One could average the q/q annualized growth rates over the four quarters of 2017 to try to get 2017 q4/q4 growth rate. This calculation leads to an approximation, which gets worse the more variable growth rates are (unless growth rates are calculated as log-differences — which is part of the reason economists like to express variables in logs and log differences…).
By the way, 10% decline combined with a 10% rise does not bring you back where you started — unless you calculate growth rates in logs. Here’s Jim Hamilton‘s take (for some reason, people start calling me names when I try to defend the use of logs.)
Goldman Sachs observes, over the weekend:
The US has experienced a dramatic resurgence of Covid over the last two weeks, with confirmed daily new cases surpassing 50,000. In response, officials have paused or reversed reopening in states containing more than half the population.
A combination of tighter state restrictions and voluntary social distancing is already having a noticeable impact on economic activity. States with the most severe deterioration in the Covid situation saw declines in consumer and workplace activity at the end of June that will likely continue into July, and activity flattened in other states.
The healthy rebound in consumer services spending seen since mid-April now appears likely to stall in July and August as authorities impose further restrictions to contain virus spread. The ongoing recovery in manufacturing and construction should be largely unaffected, however.
Some idle speculation as we head into more closures: What if hospitality and leisure and retail employment dropped back to May levels, and the rest of nonfarm payroll employment increased by 2 million (it increased by 1.972 million in June). Then what would overall employment look like?
Quarterly Census of Employment and Wages data show the divergence from the establishment survey measurment of total employment in the months before the peak.
Figure 1: Year-on-year growth rate in nonfarm payroll employment from establishment survey (red), from Quarterly Census of Employment and Wages (blue), both calculated as 12 month log differences. Source: BLS, author’s calculations.
NBER identified peak is 2020M02.