Can You Think Like an Economist?
Let us take up a topic where everyone has an opinion — consumer spending. Your pop economists and TV talking heads do the sound-bite simplification:
- They talk in slogans, e.g., the "spent up consumer"
- They create stereotypes, e.g., "Joe Six-Pack"
- They take facts applying to some and impute these to the population.
We all know that times are tough, that some consumers borrowed too much, that many have lost jobs, that wealth has declined, and that many are cautious. Despite these facts, there are some who did not have much debt, have a secure job or retirement package, and continue to spend as usual.
Those who never took Econ 101 but often quote from the course use the stereotypes. Let us compare this to a real economist. Economists understand that the behavior of a population represents the actions of many individual actors. It is possible to summarize the behavior of the group with quantitative models. A marginal change in one variable leads to a marginal change in another.
In a nice article a few months ago, Menzie Chinn (one of our featured sources) made some estimates about how consumption might behave given various assumptions. Our point here is not so much the specific conclusion (although that is informative and worth reviewing), but the methodology, as follows:
The equations used are estimated over the 1969Q1-08Q3 period. They are:
Δc_durt = -1.49 – 0.18 (c_durt-1) + 0.14 (yt-1) – 0.33 r t-1 + 0.04 we t-1 + 0.10 wn t-1 + three lags of first differences + u t
Adj.R2 = 0.25, N=159, SER = 0.027, DW = 2.05; bold face denotes significant at 10% msl. we is equity wealth, wn is non-equity wealth.
- Long run income elasticity: 0.78.
- Long run interest semi-elasticity: -1.81.
- Long run equity wealth elasticity: 0.23.
Δc_ndur t = 0.006 – 0.07 (c_ndur t-1) + 0.03 (y t-1) – 0.05 r t-1 + 0.006 we t-1 + 0.10 wn t-1 + three lags of first differences + u t
Adj.R2 = 0.20, N=159, SER = 0.006, DW = 1.86
- Long run income elasticity: 0.43 (significant at 20% levels).
- Long run interest semi-elasticity: -0.81.
- Long run equity wealth elasticity: 0.09 (significant at 20% levels).
- Long run nonequity wealth elasticity: 0.28 (significant at 20% levels).
Δc_svcs t = 0.028 – 0.003 (c_svcs t-1) + 0.20 ( Δ c_svcs t-1) + 0.07 Δ(y t-1) – 0.14 ( Δ r t-1) – 0.09 ( Δ r t-3) + 0.036 ( Δ networth t-1) + 0.030 ( Δ networth t-3) + other nonsignificant lags of first differences + u t
Adj.R2 = 0.28, N=159, SER = 0.0036, DW = 2.06
- Short run income elasticity: 0.35.
- Short run interest semi-elasticity: 1.18.
- Short run net worth elasticity: 0.44.
This is an illustration of how an economist uses data to review and illuminate relationships. It is not the sort of thing that one sees on TV or reads in the big-time blogs by the pop economists. We understand that most readers were lost at "Hello."
The Example of Personal Consumption Expenditure Data
Looking more closely at Personal Consumption Expenditures, today's data showed an increase of 0.2% in real personal consumption expenditures, seasonally adjusted. There is a very nice summary of reactions by economists at the Real Time Economics blog. There always seems to be some eccentric factor affecting the data, and this month it is the Cash for Clunkers program. CARS stimulated spending in the last week of the month, although some think it depressed it earlier. PCE data from earlier this year were also influenced by transfer payments, causing a big decline because of the way such fund flows are counted. Next month will be another big "clunker" effect, and nearly everyone expects a decline after that.
In our work we look at quarterly data. The key question is whether there has been a massive collapse in consumer spending. Keep in mind that this was the prediction of many.
Our guess is that most would be surprised to learn that the decline from the peak has been about 1.6%. This is not good news, since it is below the normal trend in expenditure growth. For comparison, the quarterly peak to trough decline was about one percent in 1991 but over 1.8% in 1974. The 2000 era was barely a ripple. (Source: NewArc calculations from BEA data).
When we included this question as #8 in our Summer Quiz, we expected that few would be close to the correct answer. (The winners either knew or looked it up!) Our real objective is to highlight the mistakes people make every day. We have a prize for the winner of the quiz, but our guess is that anyone answering the questions correctly has already made a nice profit this summer. We asked the right questions, so it was a matter of readers finding the right answers.
There is a simple choice. There are some who deal in stereotypes and slogans. There are others who do quantitative analysis. Our mission at "A Dash" is to identify the best sources on every subject.
The pop economics sources have been wrong about the consumer for many years, as we have documented in prior articles.
We are not attempting to say that consumer spending is robust or that the economy is great. It is merely an effort to provide some much-needed perspective.