The IMF considers the rich, JP Morgan Chase considers everyone, and upcoming budget cuts
1. Bas B. Bakker and Joshua Feldman just published an IMF working paper, "The Rich and the Great Recession," that shifts the focus from the role of the middle class to the role of the top 10% in the debate over the macro trends that led into the crisis.
They call both the inequality narrative, that stagnant wages led the middle class to over-borrow the rich's savings, and the wealth narrative, which ignores distribution and blames rollercoastering asset prices, flawed, and advance the idea that the rich, whose debt increased as quickly as that of the lower 90% in their methodology, were "active participants" in the boom that busted. Their work, including modeling, suggests that the savings rate of top 10% followed the same pattern as that of the lower 90%, and their model implies something they call, "…truly striking: between 1993 and 2003, about 55 percent of the increase in consumption came from the rich; over the last ten years, the share was even larger (71 percent)."
They focus on the savings rate from the National Income and Product Accounts, pointing out that in the early 1980s the savings rate was 10% and the share of income going to the top 10% one third, but by 2010 aggregated savings had slipped to 5%, and the upper share of income had risen to one half.
They do not believe, as none of us should, that the only process that would support the inequality scenario on its own, that the savings rate of the top 10% held steady over time while the rate of the lower 90% fell from 10% to zero, is plausible, especially as it requires both groups to have been saving at the same rate in the early eighties. They make the more likely assumption that the savings rate of the rich was well above that of all the rest in 1980, perhaps three times higher, and then fell much harder. Supporting this is the negative correlation between the share of wealth heading into cashmere pockets and the aggregate savings rate of the last 3 decades.
The Flow of Funds, the authors don't even bother with the new moniker, shows the debt of the top 10% rose as quickly as that of the less flush, and was likely a response to the increase of wealth. Wealth to income ratios rose from 721% in 1994 to 912% in 2007 for the top group, and from 373% to 404% for the bottom. With both savings rates traveling along the same curve, it makes sense that the top 10%, who enjoyed the lion's share of income and wealth gains, played a central role in both the boom and bust.
2. In a study of income and spending patterns of 100,000 of its account holders (a sample drawn from 27 million accounts), the JPMorgan Chase Foundation found high levels of volatility on both sides of the income statement, with close to all experiencing changes of 5% or more from month to month. Over a quarter, 26%, experienced income changes of 30% or more over the course of a year (10% of them a decline, 16% an increase). There was surprisingly little variation by income quintile – in fact the top quintile experienced somewhat more volatility than the bottom. This results generally show more volatility than previous studies have.
Income and consumption changes didn't move in tandem: just 28% of the sample, whom the bank called "responders," showed a tight correlation between the two. Responders were slightly more likely to be in the bottom quintile, to be maxed out on their credit cards, and on a fixed income. A third of the sample were "sticky optimists," meaning consumption increases typically exceed income increases by 10 percentage points or more; most increased consumption despite drops in income. The optimists tended to be higher earners, though obviously that kind of aggressive consumption isn't sustainable over the longer term. The largest share of accounts, 39%, were "sticky pessimists," meaning that consumption increases less than income by more than than 10 points or more. Their consumption rises less than income when income rises, and they cut back on spending when income drops. For a large minority, 39%, income and consumption changes between 2013 and 2014 moved in the opposite direction. The data suggests that few individuals follow a monthly budget: 60% of the sample showed average monthly changes in consumption of greater than 30%.
Of course, it's hard to generalize from just two years of data, but the looseness of fit between income and consumption changes is striking. It'd be interesting to know how these categories have been affected by the Great Recession – are consumers more cautious than they used to be? – but we just don't have the data.
The typical household in the sample just didn't have the savings cushion necessary to weather the income and spending volatility. The bank estimates that a middle-income household should have about $4,800 in liquid assets on hand to cope with normal monthly ups and downs – but they had only about $3,000. The shortfall was present in all but the top quintile.
Both the volatility and lack of cushion found in this study are usually thought to affect lower-income households, but that's clearly not the case. Better financial planning and budgeting could help mitigate the problem, but most Americans experience quite a bit of economic uncertainty. As the report says in its conclusion, "financial insecurity and scarcity exact a mental toll, making it more difficult for people to solve problems, exert self-discipline, and have the mental bandwidth to weigh the costs of borrowing or other short-term solutions."
3. In their April minutes, the FOMC noted that state and local governments cut back on construction spending in the first quarter. Bloomberg's Mark Nicette put together a nice roundup of state finances, citing, among others, the mighty Rockefeller Institute, that shows that despite better collections 32 states face gaps in their FY 2015 and/or 2016 budgets, and that, as we and others have pointed out, adjusted for inflation state revenues have not regained pre-recession peaks. This means new cuts.
As we often mention, the Great Recession is the only one on record where public sector employment fell, and hence could not function as an automatic stabilizer. Nicette ends his piece with a quote from Alabama's two-term Republican Governor Robert Bentley, who just asked for a tax hike (gasp). "We have a real crisis on our hands."
Like it or not, public employees are generally quite well paid, and they shop in the same stores as everyone else. The Bureau of Economic Analysis assigns a 2.22 economic multiplier to local (N.B.) governmental enterprises, just below residential construction's 2.27, and among the highest. And dead last? Federal banks, credit intermediation and related activities, 1.39. Uh oh.
What gas dividend?
Oil (and gasoline) prices have crept off their lows; they’re up about 25% this year, though they’re still well below year-ago prices. But many analysts have been scratching their heads wondering why the decline in energy prices hasn’t done more to goose up retail spending. It may be that's not really much of a conundrum.
Here are several ways of making that point. First, there’s the graph above, showing the annual growth rate in nominal expenditures on energy and all other forms of consumption from the national income accounts. If energy prices could add to or subtract from other forms of consumption, you’d expect the two lines to look more like mirror images. In fact, they move more together than apart. The correlation coefficient between the two series is 0.43. Lag the non-energy spending a year, on the supposition that there might be a delayed reaction time, and the correlation coefficient actually falls to 0.28.
Moves in energy consumption are overwhelmingly dominated by price. The correlation coefficient between the annual change in the gasoline price and energy expenditures is 0.97. (That’s made even more remarkable by the fact that more than a third of energy spending is on services like electricity, which are not priced like gas.) While people may drive more or less, or raise or lower the thermostat, based on price movements, it appears they don’t change their behavior all that much. They just take the price—and it doesn’t seem to have much effect on other spending.
One gets similar results looking at the BLS’s Consumer Expenditure Survey (often abbreviated CEX, so as not to confuse it with Current Employment Statistics, the official name of the payroll survey). The CEX can be volatile, and dependent on the unreliable memories of the surveyed in describing their spending habits, but it’s still the best household-based measure of expenditures we have—and it allows for fairly detailed demographic analysis.
As the first graph above shows, we don’t find the mirror image between energy and non-energy spending growth that you might expect in the aggregate. The correlation between energy and non-energy spending growth is 0.28—positive, not negative. And the story is similar when you look at poor (bottom quintile), middle-income (third quintile), and affluent (top quintile) households. The correlation weakens the higher you go up the income ladder (0.52 for the first, 0.42 for the third, and 0.14 for the fifth), but they remain positive for all five.
Not surprisingly, there’s a tight relation between income growth and spending. A regression of the annual change in non-energy spending in the CEX on the annual change in household income yields an impressively high r2 of 0.53. So the “mystery” of why lower energy prices are not translating into higher retail spending may not be a mystery at all. The best explanation of tepid retail growth is tepid income growth.