Over at PostEverything.
The work of the late economist Hyman Minsky has become increasingly relevant in recent years, as his understanding of the fragility of financial markets and their role in bubbles and busts was both deep and prescient.
Other economists generally viewed financial markets as playing not much more than an intermediary function, passively allocating excess savings to their most productive uses—in fact, many still see it that way. It’s one reason why virtually all business cycle modelers, including those at the Fed, didn’t see the great recession coming—their models either left out or underweighted the impact of the financial sector on the broader economy.
But a key Minsky insight, explained very readably here by John Cassidy, is that there’s a financial cycle within the business cycle, which basically goes from over-pricing to under-pricing risk. Caution yields to euphoria, hyper-cautious risk aversion to incautious risk seeking, and what I’ve dubbed the economic shampoo cycle—bubble, bust, repeat—is underway.
These thoughts came to mind as I read two articles over the past few days. The first describes what looks like a sharp uptick in merger activity, as debt is cheap, corporate earnings are strong, and “animal spirits” among the investor class, if not the middle class, are high and rising. The second is more of a microcosm; it’s a description of a hostile takeover bid by a hedge fund. The deal fell apart, but the hedge fund still walked away with over $2 billion in profit (the fund bought 10% of the target company’s stock, which rose sharply when a higher, rival bid was made).
Neither of these stories are obviously problematic (though the latter tells you a lot about our current inequality problem). A characteristic of the Minsky cycle is pervasive, diffuse credit, juiced by sloppy underwriting and “innovative” financial products, to borrowers who cannot realistically service the debt they’re taking on. The housing bubble is the classic example as its sustaining mechanism was ever-rising home values, since that was the only way many borrowers could pay their mortgages (by borrowing against their appreciating homes).
I don’t see that yet. These deals seem largely restricted to Wall St. as opposed to Main St. And many other signals show the US economy to be uniquely strong relative to most other advanced economies: GDP and job growth are solid if not flashy, household balance sheets are back to pre-recession, pre-leverage levels, and while interest rates are low (as they should be—there’s still too much slack in the economy), I don’t see a credit bubble.
But I suspect up there in economists’ heaven, Hy Minsky read the same articles I did—he probably called Keynes over to have a look—and raised an eyebrow. And when Minsky raises an eyebrow, we should all get a little nervous.
It is a common mistake to overestimate the contribution of immigration to the increase in poverty. Today’s purveyor of this erroneous association is the WaPo’s Robert Samuelson, who writes in the context of a discussion about immigration reform:
The influx of unskilled Hispanics has sharply boosted U.S. poverty. From 1990 to 2013, Hispanics accounted for 57 percent of the 11.7 million increase in the number of people below the poverty line.
But of course, not all Hispanics are immigrants, and since he’s allegedly talking about the poverty implications of immigration reform, he should really be looking at, ya know…immigrants!
In fact, there are crosscurrents to the impact of immigration on poverty. On the one hand, as Samuelson implies, immigrants tend to be poorer than average, so increasing their share, all else equal, leads to higher poverty. But there’s another factor in play: the trend in poverty rates among immigrants.
In fact, their population share has been rising which increases poverty, but their poverty rates have been falling, which pushes the other way.
The table shows these results. (The Census data on immigration start in 1993.)
Source: Census poverty data, tbl 23; my analysis.
The immigrant share of the population increases by 4.4 percentage points over these years, but immigrant poverty declines by almost five points, a larger decline than native born poverty which is only slightly down.
So how do we parse out the net effects of these contrary forces? The bottom panel of the table does two little simulations that have a go at this question.
The first line holds population shares of natives and immigrants at their 1993 level but multiplies those shares by 2013 poverty rates. The result is a simulated total poverty rate based on 2013 native and immigrant poverty rates but their 1993 population shares. The difference between this simulated rate and the actual rate can then be assigned to the growth in the immigrant share of the population (and the commensurate decline in the native-born share). As you see, that growth added only two-tenths of a percentage point to total poverty over this period.
The second line uses native shares and rates for 2013, but for immigrants, multiplies the 2013 population share by the 1993 poverty rate. Thus, the only difference between the actual total and this simulated total is the decline in immigrants’ poverty over the past 20 years. This shows that the decline in immigrant poverty reduced overall poverty by six-tenths of a point. In other words, had immigrant population shares shifted as they did since 1993 yet their poverty rate hadn’t declined, overall poverty would have been 15.1% last year, instead of its actual value of 14.5%.
These are very simple simulations which do not account for interactions—one could argue that native poverty rates would have fallen more but for immigrant competition. Also, endpoints matter—you get somewhat different results if you do this over different dates. But the story is pretty much the same (here are the data if you want to fool around with them yourself).
But the larger point is that there are numerous moving parts here. You have to account for not just increasing immigrants’ share of the population, but also “within-group” declines in their poverty rates. Once you do so, at least in my little exercise, you find that the latter lowers overall poverty more than the former raises it.
Who knows!? It’s lower than conventional estimates, but beyond that…over at the Upshot.