EconExtra: Does GDP Truly Reflect an Economy's Strength?
EconExtra is a series of posts that go beyond the textbook, relating current events and recent developments in economics to content standards, and providing resource suggestions to help you incorporate the current events into your lessons.
GDP headlines do not seem to mesh with the underlying health of the US Economy. We visited the recovery earlier this fall in GDP in the EconExtra “The Alphabet Soup of Economic Recoveries,” covering the prospects for a “K” shaped recovery from the pandemic downturn. Now that we have third quarter data, this post takes a look at the mathematics of the historic swings in GDP, and pulls in other pertinent data to try to complete the story of the health of the economy.
The Data: GDP
The first issue with GDP measurements is about the math. Quarterly GDP readings (the average of three months) are usually adequate to get a feel for what is going on with output in the US, because GDP levels typically change very little (1,2,3%) year over year. Annualizing small movements still gave an accurate picture. But with the historically unprecedented monthly fluctuations in GDP in 2020, the quarterly fluctuations are multiples of the typical annual changes, and reporting the movement at an annualized rate sounds crazy.
This NYT article explains this phenomenon well:
Quarterly averages obscure those big swings, however. G.D.P. fell 1.3 percent in the first quarter (when two relatively normal months were followed by the big drop in March) and 9 percent in the second (when output plunged in the first month of the quarter then rose in the next two).
(Consider the 20+ million jobs lost in March)
The big rebound in May and June meant that the third quarter effectively had a head start. In fact, even if there had been zero growth in July, August or September, and the economy had stayed exactly the same size as at the end of the second quarter, that would still represent 5.4 percent quarterly growth — the strongest gain on record
The historic 9% drop in real GDP 9% (31.4% annual rate) in the second quarter was followed by an historic gain in the third quarter of 7.5% (33.1%, annual rate). You have to think about the starting point when looking at this number. A 31.4% annual drop followed by a 33.1 % annual gain does NOT mean we are back to our starting point. In fact, GDP still sits almost 3% below year-end 2019. (Fred data)
The Data: Personal Income
So, GDP is on the upswing after a huge drop in the second quarter, but Personal Income changes are the mirror image of GDP for the same periods. A BEA Press Release explains the movements in nominal and real personal income, including the drivers, as well as movements in personal savings in the second and third quarters:
Current-dollar personal income decreased $540.6 billion in the third quarter, in contrast to an increase of $1.45 trillion in the second quarter. The decrease in personal income was more than accounted for by a decrease in personal current transfer receipts (notably, government social benefits related to pandemic relief programs) that was partly offset by increases in compensation and proprietors' income (table 8). Additional information on several factors impacting personal income can be found in "Effects of Selected Federal Pandemic Response Programs on Personal Income."
Disposable personal income decreased $636.7 billion, or 13.2 percent, in the third quarter, in contrast to an increase of $1.60 trillion, or 44.3 percent, in the second quarter. Real disposable personal income decreased 16.3 percent, in contrast to an increase of 46.6 percent.
Personal saving was $2.78 trillion in the third quarter, compared with $4.71 trillion in the second quarter. The personal saving rate—personal saving as a percentage of disposable personal income—was 15.8 percent in the third quarter, compared with 25.7 percent in the second quarter.
The Data: Unemployment
Unemployment is still at 6.9%, twice the pre-pandemic level. This translates to almost 11 million unemployed. This does not include those who have left the work force, like those (mostly women) who have stopped working to take care of children who are unable to attend school. (See EconExtra for more on employment/unemployment data.) Here are the relevant charts from the BLS reflecting data through October. (BLS data)
The BLS press release offers unemployed by number and percent in various job categories. (chart below). This could generate a conversation about which workers never stopped working (essential workers and those who can work from home), those who lost jobs with initial shutdowns but have returned, and those who have not returned.
Putting it all Together: The Narrative
Have students look at the data and put together a “snapshot” of the health of the economy. For example, what has changed between the second quarter and the third in terms of employment? Who is still unemployed, who has gone back to work, and who never stopped working? Is this reflected in GDP data? How do changes in personal income and savings reflect fiscal measures (stimulus checks and unemployment benefits)? What conclusions can students draw about the health of the economy.
Putting it all Together: Put on Your Forecasting Hat
While the fate (and size) of a second stimulus package remains unclear, economists nonetheless are forecasting GDP in the future. Why not have your students make their own forecasts for 4th quarter (and 1st quarter 2021) GDP based on what they see? You can wait until Congress adjourns for the year (they have already adjourned for Thanksgiving) to see if there will be a second CARES act or not, and if so, what measures will be taken, before forming a forecast. Or make a grid/table of growth rates (positive and negative) with the column values representing the 4th quarter GDP growth rate and the row values representing the 1st quarter GDP growth rate and have students “bet” on the square that represents their forecast (see below).
About the Author
Beth Tallman entered the working world armed with an M.B.A. in finance and thoroughly enjoyed her first career working in manufacturing and telecommunications, including a stint overseas. She took advantage of an involuntary separation to try teaching high school math, something she had always dreamed of doing. When fate stepped in once again, Beth jumped on the opportunity to combine her passion for numbers, money, and education to develop curriculum and teach personal finance at Oberlin College. Beth now spends her time writing on personal finance and financial education, conducting student workshops, and developing finance curricula and educational content. She is also the Treasurer of Ohio Jump$tart Coalition for Personal Financial Literacy.
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