Econintersect analysis is that total consumer credit growth decelerated 0.2% month-over-month, and the year-over-year growth is 5.7%. The seasonally adjusted consumer credit headlines are showing a growth of 6.5%. The underlying dynamics are very interesting this month as there was a deceleration in the unadjusted data growth in both revolving and non-revolving credit.
In any event, consumer credit is not expanding at a rate which would suggest an accelerating economy – in fact it seems to be indicating the opposite. When student loans are backed out, the rate of expansion of consumer credit is:
- decelerating;
- consistent with the current growth of GDP.
The headline said:
In February, consumer credit increased at a seasonally adjusted annual rate of 6-1/2 percent. Revolving credit decreased at an annual rate of 3-1/2 percent, while nonrevolving credit increased at an annual rate of 10 percent.
Unadjusted Consumer Credit Outstanding
 | Month- over- Month Growth | Year- over- Year Growth | Month- over- Month Growth without Student Loans | Year- over- Year Growth without Student Loans |
Total | -0.2% | +5.7% | -0.2% | +2.4% |
Revolving | -0.5% | +0.5% | n/a | n/a |
Non- Revolving | -0.2% | +7.7% | -0.3% | +6.5% |
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Overall takeaways from this month’s data:
- Student loan growth has been decelerating for the past 12 months;
- There was a slow down in non-revolving credit growth rate following last month’s jump;
- Non-revolving credit growth (generally this is all consumer credit except credit cards) has been decelerating for the past 4 months;
- The backward revision this month again was slight.
The market expected consumer credit to expand $10.6 to $16.3 billion (consensus = $14.0 billion) versus the seasonally adjusted headline expansion of $16.5 billion reported.
Note that this consumer credit data series does not include mortgages.
The Econintersect analysis is different than the Fed’s:
- an effort is made to segregate student loans from consumer credit to see the underlying dynamics;
- this analysis expresses growth as year-over-year change, not one month’s change being projected as an annual change – which creates a lot of volatility.
- where our analysis expresses the change as month-over-month, month-over-month change is determined by subtracting the previous month’s year-over-year improvement from the current month’s year-over-year improvement.