Tag Archives: marriage

Regnerus has the callous disregard for poor single mothers and their children, but doesn’t get policy

Taking questions onstage at the World Congress of Families, Mark Regnerus reportedly was asked whether he would support cutting welfare benefits to single mothers to encourage them to marry. The question is not on the video, but part of his answer is. I transcribe it below, but here’s the tape:

Regnerus said:

… lay of the land in terms of the attempts to stimulate marriage, how difficult that is – your policy, which is sort of associated with the idea of the marriage penalty for people who are on social welfare and not married to the father of their children. It’s possible, right? It’s one of those things where – my skepticism tends to – how do people act in certain situations – what should we expect of people. In that situation, it creates this entity where we have to identify who’s in the household, how often are they in the household, the relationship, etcetera. Your policy is not a bad one in terms of moving people toward marriage – we want to do that. Whether it will work – who knows? And, I’m totally not a policy analyst so I’m going to stop right there.

His trademark verbal incoherence makes this hard to follow, but it appears his only concern with such a policy is the problem of household-member surveillance. His callous disregard for poor single mothers is apparent — he’s not concerned with the principle of coercing people into marriage, or even with violation of rights associated with verifying household comings and goings. He’s just not sure it’s feasible.

The weird thing is he’s got it backwards. If you want to deny benefits to single mothers, why do you care if they have a boyfriend in the house? That’s the problem the government has when it tries to only give benefits to single mothers — when its afraid they’re concealing a man who is supporting them.

The policy of denying benefits to people who are single — but giving benefits to people who are married — is what Brad Wilcox and Marco Rubio are trying to accomplish with their convoluted and badly calibrated child tax credit reform (see this description by Matt Bruenig). Maybe Regnerus wants to do that, but also find a way to punish single mothers who are carrying on outside of marriage, but it’s hard to see how that’s part of the policy.

But then again, I’m not a policy analyst so I’m going to stop right there. If you think I’m not getting it, please enlighten me.

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I knew that marriage-is-good-for-the-economy thing sounded familiar

When I wrote the other day about Brad Wilcox’s “Strong Families, Prosperous States” report, I forgot about a conceptually similar foundation-money spoof he produced four years ago which claimed, among other things, that “Strong, sustainable families pay long-term dividends to the entire economy.” (It was part of a report that included such recommendations as “Clean up the culture” and “Respect the role of religion as a pronatal force.”)

One of the conclusions of Wilcox’s new report is that states with more married couples have higher household income than states with fewer married couples. Hm. I realize now that’s building on the report he wrote four years ago, basically saying that marriage makes households spend more, so Proctor and Gamble is excellent. I wrote about it here, but hardly any of you were reading back then, so here is an edited rehash:

Farce or fraud?

Did you know that married couples with children spend 50-times more on childcare than single adults without children? Well, if you didn’t you might not realize how good marriage is for “the economy.”

Brad Wilcox and Kathryn Sharpe have a contribution in the Bradley Foundation-funded report, “The Sustainable Demographic Dividend,” which aims to describe the benefits of marriage for the economy.

What they do is produce a simple table showing that married-couple-with-children households spend more on various things than single-childless households. If you’re thinking, “but there are more people in married-couple-with-children households,” then you may already have done more thinking than the report’s authors.

To explain why this spending pattern occurs, they offer several reasons, the first of which is “household size.” Wait — you’re still thinking — if household size explains the difference in spending, then it’s not a difference in spending, it’s a difference in accounting, just pooling the spending of several people and calling it a spending increase. So how does this help “the economy”? Believe it or not, this is their reasoning:

To serve the needs of all the adults and children in their homes, they are more likely to buy many brands in bulk, from Bounty to Tide, and to fill their shopping carts at the local grocery store.

I must be doing something wrong, because I thought I spent less in the end when I bought in bulk. (But then again, I’m apparently not as good at raising money from giant foundations, either.)

The data abused in this report are from the Consumer Expenditure Survey, which is the authoritative source on household spending in the U.S. It’s something I’ve used before to study household spending (here and here). And if you use it, all I can say in a sentence is: you better account for household size, since all the spending is reported for households, not individuals.

To illustrate this, I did a simple manipulation of the data in Wilcox and Sharpe’s report. They list average spending on specific categories for households according to family structure. Yes, households. Here is a taste of the table:

oldwilcoxtable

This shows, for example, that single-childless households average a paltry $1.40 per week on cereal, compared with a robust economic contribution of $4.44 for married-with-children households. This doesn’t just mean children are good for “the economy,” because single parents spend only $2.86. So spouses are good for “the economy” too.

Or, maybe this just means people eat cereal.

I took the data from their list and compared married-with-children households to the sum of single-childless and single-parent households. On average, if every adult buys one beer a day, and every child buys one glass of milk, then the level of spending in married-with-children households should be the same as the sum of spending in single-childless plus single-parent households (if they have the same number of children). This is not serious consumer science, but it’s appropriate for a blog-scale debunking. And the results:

This graph is for weekly expenses on small consumer items;* the graph for bigger ticket items looks about the same. If the dots fell along the dotted line, my beer-and-milk hypothesis would be supported. It’s pretty close — but tipping a little the way you would expect it to — toward bigger households spending less, since they have economies of scale (“buying in bulk”).

Anyway, the analysis is junk. But the more interesting question is: Is this farce or fraud? Maybe they really don’t know what they’re doing, in which case the foundation funding makes it a farce. Or maybe it’s fraud.** Maybe they are deliberately misleading the public, the foundation, and the major corporations they are hoping will spend their “philanthropy” money on such “public education” projects.

Actual recommendations:

Companies whose fortunes are linked to the health of the family, such as Procter & Gamble, spend billions of dollars each year on advertising. … Executives with oversight across brands should ask themselves a simple question: Do the messages used in our advertising make family life look attractive? Or do they exalt single living? Obviously, it’s in their long-term interest to do more of the former.

If you have another 3 minutes, consider watching this hilarious video they link to as an example of “family life = attractive.” It’s from Proctor & Gamble’s 75th anniversary in the Philippines (unless it’s a spoof, too), which includes images like this:

2015 Population addendum

Of course, people spend more than things that aren’t people, so population growth spurs economic growth. But not all economic growth is the same, because, for example, people without incomes create less “demand” (because they “choose” not to consume as much). As I explain in this one-minute animated video, rich families spend a lot more on their kids than poor families do. Is that waste, or economic stimulus? The answer might affect whether we want to take money from rich people and give it to poor people to spend on their kids, or coerce poor people into having fewer kids, or coerce rich people into having fewer kids — or convince rich men to marry poor women. My guess is that, if you want more people to grow the economy (which is not an unambiguously good thing, but for argument’s sake), the most efficient thing would be to get poor people to have more kids and then train those kids to be high-skilled workers. Also, allowing more poor people to immigrate. Probably getting rich people to have more kids and spend more on them is not as good, because there is so much waste on rich kids. But I could be wrong.

Anyway, none of this that I can see suggests much influence of “marriage” on the economy, and if it did I wouldn’t want the state to be promoting marriage anyway. If Proctor and Gamble wants to promote marriage, that’s fine, as long as they’re taxed at a sufficiently high rate, too.

* cereal, baked goods, beef, pork, other meat, poultry, seafood, eggs, dairy, fresh fruit, fresh veggies, processed fruit, processed veggies, sweets, non-alch bevs, oils, misc. food, alchohol, tobacco, personal care products and services, and household products and services.

** colloquial use of the term “fraud” in this blogosphere context is not meant to express or imply legally criminal fraud.

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Groups of people with more income are richer, Wilcox credulity edition

momoney

I’m having a hard time believing the latest Brad Wilcox marriage-promotion fake research event is as dumb as I think it is, but I think it really is. I don’t use such a judgmental word lightly, but rather with a heavy heart, because it means it’s time to waste another hour debunking him.

The new thing is a report published by the American Enterprise Institute and “launched” at an event they hosted (droning-strike video here). The report is called, “Strong Families, Prosperous States” (PDF). The news coverage was light, which is a good sign for our news media, with credulous reports showing up in the Washington Post wonkblog and the Deseret News (though with Ross Douthat on the panel, expect more ripples sooner or later).

The basic finding is that people with more money are richer. But Wilcox (with co-authors anti-gay activist Joseph Price and Robert Lerman) describe it like this:

Higher levels of marriage, and especially higher levels of married-parent families, are strongly associated with more economic growth, more economic mobility, less child poverty, and higher median family income at the state level in the United States.

Their analysis, using state data over time, calculates the relationship between the change in marriage rates and the change in income per capita, poverty rates, and family income (mobility is done differently, using a single cross section, and I’m setting that aside for now). Basically, all this would be true if the only difference between states with lots of marriage and states with less marriage is that the former had more high income families — which of course they would, because married-couple families have higher incomes. So, rich people are richer.

To show how dumb this is, I illustrate it using fictional states made up of real families, drawn from the 2013 American Community Survey (data from IPUMS.org). I took all the married-couple and single-parent families with children, and created four states: Heavcox, where everyone is married; Hellcox, where no one is married; and two states in between, Lowersham (86% married) and Highersham (40% married). The families were assigned to states randomly (with replacement, so some families are in more than one state).

Here are the four states, with their scores on the measures used by Wilcox:

fakestates

Heavcox has the lowest poverty, the highest median family income, and the highest per capita income (which means increase in marriage would lead to higher growth in per capita income).

The point is this has nothing to do with states, it’s composition: married-couple families more income, so their states do, too. The report includes a lot of statistical controls, but none that affect this basic pattern (for example, racial composition, average education level, and crime and tax rates). This is mostly because the units used for income and poverty are families. I’m not taking the time to do this, but I am pretty sure it would work if you randomly assigned individuals to families as well, that is, if the difference between married couples and single people was literally just the number of adults in the household. And with per capita income, more married-couple families means more high-income individuals, so higher income states. (Of course, there are interesting reasons married couples are richer, but they don’t have to do with states: they have more high-income earners, because high earners are more likely to get and stay married, and to a much lesser extent, because marriage helps people earn more.)

There is a funny note in the report, which says:

While these comparisons are based on median family income, we find similar gaps when we look at median household income or median household income adjusted for household size.

The adjustment for household size would help a little, but it still wouldn’t change the basic pattern, since married couple families have more earners, not just more people. But I completely distrust “we find similar…” if the numbers aren’t reported, since we know Wilcox lies a lot (frankly, even taking un-replicated numbers from one of his reports is dicey — I wouldn’t want to build a life raft out of it — but that’s the risk we take).

So, sure: “states show especially positive economic outcomes when a larger majority of their families are headed by married parents.” This is not news.

This is another case of think-tank public relations hype successfully masquerading as research, with journalists and funders as the intended audience. The American Enterprise Institute, which has a legal obligation to waste money, wants media mentions; reporters need easy stories expertly told and packaged for public consumption (unlike most real research); and political partisans want to click on and share things that support their assumptions. It is understandable that some honest reporters and editors fall for this stuff (and again, I’m appreciative of the many who didn’t). Washington Post reporter Jim Tankersley may have been trying to boost the legitimacy of the new report when he wrote this:

There is a story gaining steam among some academics that suggests the institution of marriage — particularly marriage for parents of young children — could play an important role in strengthening the American economy. It is a story about growth and poverty, about responsibility and work ethic.

But there is no evidence for the “gaining steam” thing in the story, except the existence of an American Enterprise Institute PR event.

Some reporters really try to check these stories out a little before running with them. But it’s hard for non-experts to do that, especially quickly. For example, Tankersley responded to a tweet I tweeted saying the report “appears to control for some of the factors you have raised flags about in the past.” Which is true, but this just shows the effectiveness of the PR, not the quality of the research. Which all means that as much as I don’t like the system we use to manage peer review, it’s still a good idea. There is nothing in this report that couldn’t have waited a few months for a real peer review before presenting it to the public.

If I’m wrong about this for some reason, and you can show my why — really show me, not just suggest other work I could do to check out your suspicions — I’ll be glad to admit it.

Aside: but why not?

You may be thinking, “sure, but isn’t it still the case that married couples are richer, so more people getting married would be good, right?” The first problem with that is that there is no known way to generate that outcome: the government’s marriage promotion has not worked at all, and I have seen no approach to trying that doesn’t impose religion or other values on people or shame them for their circumstances.

The second problem (which I wrote about a little here) is that the next marriage won’t bring the same benefits as the average existing marriage. If economics is one reason people don’t get married — and it is — then the economics of the currently-not-married will not be as beneficial as those experienced by the people who were in better shape to get married in the first place.

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Lifetime chance of marrying for Black and White women

I’m going to Princeton next week to give a talk at the Office of Population Research. It’s a world-class population center, with some of the best trainers and trainees in the business, so I figured I’d polish up a little formal demography for them. (I figure if I run through this really fast they won’t have time to figure any mistakes I made.)

The talk is about Black and White marriage markets, which I’ve written about quite a bit, including when I posted the figure below, showing the extremely low number of local same-race, employed, single men per women Black women experience relative to White women — especially when they have less than a BA degree.

This figure was the basis for a video we made for my book, titled “Why are there so many single Black women?” For years I’ve been supporting the strong (“Wilsonian“) case that low marriage rates for Black women are driven by the shortage of “marriageable” men — living, employed, single, free men. I promised last year that Joanna Pepin and I were working on a paper about this, and we still are. So I’ll present some of this at Princeton.

Predictions off

Five years ago I wrote about the famous 2001 paper by Joshua Goldstein and Catherine Kenney, which made lifetime marriage predictions for cohorts through the Baby Boom, the youngest of whom were only 30 in the 1995 data the paper used. That’s gutsy, predicting lifetime marriage at age 30, so there’s no shame that they missed. They were closer for White women. They predicted that 88.6% of White women born 1960-1964 would eventually marry, and by the age 49-53 (in the 2013 American Community Survey) they were at 90.2%, with another 2.3% likely to marry by my estimates (see below). For Black women they missed by more. For the 1960-1964 cohort, they predicted only 63.8% would ever marry, but 71.3% were already married by 2013, and I’m projecting another 7.5% will marry. (I also wrote about a similar prediction, here.) If they actually get to 79%, that will be very different from the prediction.

Their amazing paper has been cited another 100 times since I wrote about it in 2010, but it doesn’t look like anyone has tried to test or extend their predictions.

Mass incarceration

Interestingly, Goldstein and Kenney undershot Black women’s marriage rates even though incarceration rates continued to rise after they wrote — a trend strongly implicated in the Black-White marriage disparity. This issue has increased salience today, with the release of a powerful new piece by Ta-Nehisi Coates in the Atlantic (my old job), which exposes the long reach of mass incarceration into Black families in ways that go way beyond the simple statistics about “available” men. The large ripple effects implied by his analysis — drawing from his own reporting and research by Deva Pager, Bruce Western, and Robert Sampson — suggest that any statistical model attempting to identify the impact of incarceration on family structure is likely to miss a lot of the action. That’s because people who’ve been out of prison for years are still affected by it, as are their relationships, their communities — and their children in the next generation.

Some new projections

I should note that some readers unfamiliar with demographic analysis may find parts of what follows morbidly depressing.

To set up the marriage market analysis I’m doing with Joanna — which isn’t ready to show here yet — I’m going to introduce some marriage projections at the talk. These use a different method than Goldstein and Kenney, because I have a different kind of data. This is a lifetable approach, in which I use first-marriage rates at every age to calculate how many women would get married at least once before they die if they lived 2010 over and over again from birth to death. I can do this because, unlike Goldstein and Kenney in 2001, I now have the American Community Survey (ACS), which asks a giant sample of people if they have married in the previous year, and how many times they’ve been married before, so I can calculate a first-marriage rate at every age. To this I add in death rates — making what we call a multiple-decrement life table — so that there are two ways out of the birth cohort: marriage or death. (Give me marriage or give me death.)

The way this works is you start with 100,00 people, and each year some of them die and some of them get married — according to the rates you have measured at one point in time. For example, in my tables, of 100,000 Black women at the start of year 0, only 98.7% make it to age 15, the first year they can be counted as married in the data. By the time you get down to age 30, there are only 67,922 left, as 2,236 have died and 29,843 have married for the first time. And so on down to the bottom. In the last row of the table, when they are all dead, you calculate how many got married before dying.*

The bottom line: 85.3% of White women, and 78.4% of Black women born and stuck in 2010 forever are projected to marry before they die — a surprisingly small gap. The first figure shows you that basic result:

NHBW life tables 2010.xlsx

Note that my projections of 85.3% of White women and 78.4% of Black women ever marrying are lower than, for example, the roughly 96% of White women and 91% of Black that were actually ever-married at age 85+ in 2010 (reported here), for several reasons. First, I count dead people against the ever-married number (additionally, married people live longer, not necessarily because they’re married). Second, today’s 90+ year-olds mostly got married 70 years ago, when times were different; my estimates are a projection of nowadays.

A very interesting age pattern emerges here, which is relevant to the incarceration and “available men” question. If you look back at the figure, notice that the big difference in marriage opens up early — peaking at 28 points by age 33, before narrowing to 7 points at the end.The big difference in marriage is that White women marry earlier. In fact, as the next figure shows, after age 33 Black women are more likely to marry than are White women. I don’t think I knew that. Here are the number marrying at each age:

NHBW life tables 2010.xlsx

Specifically, although White women are twice as likely to marry in their mid-twenties, of our fictional 100,000 women stuck in 2010, just 15.6% of White women, compared with 36.8% of Black women end up marrying after age 33.

The other way of looking at this — and an answer to a common question about marriage rates — is to see the chances of marrying after a given age if you haven’t married yet. This figure shows, for example, that a White women who lives to age 45 without marrying has a 26% chance of someday marrying, compared with a whopping 49% for Black women.

NHBW life tables 2010.xlsx

It is surprising that Black women, with lower cumulative odds of marrying at every age in the cohort, are so much more likely to marry conditional on getting to their 40s without marrying. Maybe you’ve got a better interpretation of this, but this is mine. Black women are not against marriage, and they are not ineligible for marriage in some way (even though most of these single women are already mothers**). Rather, they have not married earlier because they couldn’t find someone to marry. That’s because of all the Black men who are themselves dead, incarcerated or unemployed (or scarred by those experiences in their past) — or married to someone else. So within their respective marriage markets (which remain very segregated), the 45-year-old single White woman is much more likely to be someone that either doesn’t want to marry or can’t marry for some reason, while the 45-year-old single Black woman is more active and eligible in the marriage market. This fits with the errors in the earlier predictions, which failed to pick up on the upward shift in marriage age for Black women — marriage delayed rather than foregone.

What do you think of that interpretation? If you have a better idea I’ll mention you at Princeton next week.

Note: I found so many mistakes as I was doing this that it seems impossible there are any more. Nevertheless, caveat emptor: This analysis hasn’t been peer reviewed yet, so consider it only as reliable the latest economist’s NBER paper you read about on the front page of the every newspaper and website on earth. (And if you’re a journalist feel free to refer to this as a new working paper.)

* Technical notes: I used death rates from 2010 (found here), and marriage rates from the five-year ACS file for 2008-2012 (which has 2010 as its midpoint), from IPUMS.org. I adjusted the death rates because never-married people are more likely to die than average (I told you this was depressing). I had to use a 2007 estimate of mortality by age and marital status for that (found here), which is not that precise because it was in 10-year increments, which I didn’t bother to smooth because they didn’t have much effect anyway. The details of how to do a multiple-decrement lifetable are nicely described (with a lot of math) by Sam Preston here (though if you really want to replicate this, note one of his formulas is missing a negative sign, so plan to spend an extra few days on it). To help, I’m sharing my spreadsheet here, which has the formulas. (Note that survival in the life table doesn’t refer to being alive, it refers to being both alive and never-married.) The mortality and marriage rates are for non-Hispanic women; the never-married adjustment is for all women. For the marriage rates I used all Black and White women regardless of what other races they also specified (very few are multiple-race when you exclude Hispanics).

** In 2010, 63% of never-married Black women who lived in their households had at least own of their own children living with them.

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Sex ratios as if not everyone is a college graduate

Quick: What percentage of 22-to-29-year-old, never-married Americans are college graduates? Not sure? Just look around at your friends and colleagues.

Actually, unlike among your friends and colleagues, the figure is only 27.5% (as of 2010). Yep, barely more than a quarter of singles in their 20s have finished college. Or, as the headlines for the last few days would have it: basically everyone.

The tweeted version of this Washington Post Wonkblog story was, “Why dating in America is completely unfair,” and the figure was titled “Best U.S. cities for dating” (subtitle: “based on college graduates ages 22-29”). This local news version listed “best U.S. cities for dating,” but never even said they were talking about college graduates only. The empirical point is simple: there are more women than men among young college graduates, so those women have a small pool to choose from, so we presume it’s hard for them to date.* (Also, in these stories everyone is straight.) In his Washington Post excerpt the author behind this, Jon Birger, talks all about college women. The headline is, “Hookup culture isn’t the real problem facing singles today. It’s math.” You have to get to the sixth paragraph before you find out that singles means college and post-college women.

In his Post interview the subject of less educated people did come up briefly — if they’re men:

Q: Some of these descriptions make it sound like the social progress and education that women have obtained has been a lose-lose situation: In the past women weren’t able to get college educations, today they can, but now they’re losing in this other realm [dating]. Is it implying that less educated men are still winning – they don’t go to college but they still get the pick of all these educated, more promiscuous women?

A: Actually, it’s the opposite. Less educated men are actually facing as challenging a dating and marriage market as the educated women. So for example, among non-college educated men in the U.S. age 22 to 29, there are 9.4 million single men versus 7.1 million single women. So the lesser-educated men face an extremely challenging data market. They do not have it easy at all.

It’s almost as if the non-college-educated woman is inconceivable. She’s certainly invisible. The people having trouble finding dates are college-educated women and non-college-educated men. By this simple sex-ratio logic, it should be raining men for the non-college women. Too bad no one thought to think of them.

Yes, the education-specific sex ratio is much better for women who haven’t been to college. That is, they are outnumbered by non-college men. But it’s not working out that well for them in mating-market terms.

I can’t show dating patterns with Census data (and neither can Birger), but I can show first-marriage rates — that is, the rate at which never-married people get married. Here are the education-specific sex ratios, and first-marriage rates, for 18-34-year-old never-married women in 279 metropolitan areas, from the 2009-2011 American Community Survey.** Blue circles for women with high school education or less, orange for BA-holders (click to enlarge):

educ-marpool

Note that for both groups marriage rates are lower for women when there are more of them relative to men — the downward sloping lines (which are weighted by population size). Fewer men for women to choose from, plus men eschew marriage when they’re surrounded by desperate women, so lower marriage rates for women. But wait: the sex ratios are so much better for non-college women — they are outnumbered by male peers in almost every market, and usually by a lot. Yet their marriage rates are still much lower than the college graduates’. Who cares?

I don’t have time to get into the reasons for this pattern; this post is media commentary more than social analysis. But let’s just agree to remember that non-college-educated women exist, and acknowledge that the marriage market is even more unfair for them. Imagine that.***


* I once argued that this could help explain why gender segregation has dropped so much faster for college graduates.

** It was 296 metro areas but I dropped the extreme ones: over 70% female and marriage rates over 0.3.

*** Remember, if we want to use marriage to solver poverty for poor single mothers, we have enough rich single men to go around, as I showed.

A little code:

I generated the figure using Stata. I got the data through a series of clunky Windows steps that aren’t easily shared, but here at least is the code for making a graph with two sets of weighted circles, each with its own weighted linear fit line, in case it helps you:

twoway (scatter Y1 X1 [w=count1], mc(none) mlc(blue) mlwidth(vthin)) ///

(scatter Y2 X2 [w=count2], mc(none) mlc(orange_red) mlwidth(vthin)) ///

(lfit Y1 X1 [w=count1], lc(blue)) ///

(lfit Y2 X2 [w=count2], lc(orange_red)) , ///

xlabel(30(10)70) ylabel(0(.1).3)

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Conservatives don’t have happier marriages

On Vice’s Munchies channel (who knew), Hillary Pollack links to an excruciating Fox News chat about how Republicans have happier marriages, which I wrote about the other day.

The Fox intro says, “According to a new study, Republicans are far happier, and more stable, than Democrats are.” (Then they inaccurately described the data as being about how “married couples who describe themselves…”, when the data are about individual spouses, not couples.)

I already showed the premise isn’t true, at least as far as expressed happiness in marriage. The two groups with the highest reported marriage happiness, with demographic controls, are strong Democrats and strong Republicans, and the difference between them isn’t statistically significant.

So we can take Brad Wilcox’s words of wisdom on the meaning of Republican marital bliss in that light — that is, not.

bw1

But there is another problem here, which is he is conflating party identification with political ideology. As when he tweeted this:

bw2

“Republican” is not the same as “conservative.” In fact, the General Social Survey — the data we’re using here — has a question on political ideology as well as party identification. (Thanks to Omar Lizardo for reminding me of this.) They ask whether you “think of yourself as liberal or conservative.” And 15% of people identifying as Democrats consider themselves conservative (Republicans are much more consistently conservative).

polviewpartyid

If you’re going to claim that “conservatives have happier marriages,” you should use the political views question.* And that is even worse for this theory than the party identification (which I’m sure has nothing to do with why Wilcox chose to use the variable he did). Here is my result from the other day, using political views instead**:

marital-happiness-partyid.xlsx

So, what was that about conservatives having happier marriages?

Extreme liberals are a small group, just 3% of the this GSS sample (compared with “strong Democrats, who are 12%). But that difference is big enough to be statistically significant, with control variables, from each of the other groups (at p<.05, except the extreme conservatives, p<.10, in two-tailed tests).

David Leonhardt and other journalists covering “reports” from Brad Wilcox should consider the merits of peer review or, absent that, checking around a little before serving up this bologna. I understand there isn’t time for our peer review system to vet every little partisan claim, and I’ve served up some non-peer-reviewed reports to the news media, too. I would always encourage journalists to at least check around before running with a splashy claim.

Notes:

* This doesn’t mean ideology is always a better measure, of course. For example, when it comes to attitudes toward health care spending, this paper by Stephen Morgan and Minhyoung Kang shows that party identification is a strong predictor even controlling for ideology. But in this case the issue is conservative values, not some partisan policy matter.

** Use the code I posted the other day, but with POLVIEWS instead of PARTYID

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Why it’s rotten to tell someone they’re poor because of when they had their kids

The “success sequence” is an idea from Ron Haskins and Isabel Sawhill at the Brookings Institution. They want to balance government investment and “personal responsibility” to reduce poverty. By personal responsibility, they mean adherence to what they call “the three norms”: complete high school, work full time, wait until you’re 21 and married to have children. If you do that — and smile while doing it — they’re willing to spot you a little welfare and some education.

I’ll describe it, and some criticism of the idea, then show a little data analysis.

Haskins and Sawhill claim to have analyzed data to show that when you follow all three of these norms, you have a 98% chance of not being poor. This is how they illustrate it (from this slideshow):

success-sequence-slideMatt Bruenig at Demos has an important post explaining how misleading — and wrong — this is. There are three main problems, briefly:

  1. The high school degree and full-time job is doing almost all of the work. With those two hurdles complete, you’re already down under 4% poverty. So the marriage stuff is mostly moralizing for political purposes.
  2. The data they used does not include the information necessary to see whether people were married when they had their children — it doesn’t have marital history. So they didn’t even do the analysis they said they did.
  3. Family complications mess this up badly. In particular, if a person (say, a man), has children with a partner and never lives with them, he shows up as having met the “norms” because the data don’t show him having any children — it’s a household survey, so absent parents aren’t parents in the data.

So if someone gives you the “success sequence” thing, just remember, the analysis is baloney, and the bottom line is decent full-time jobs are what keep people out of poverty (by the official poverty measure, of course).

Analysis

Anyway, I can go a little further using the American Community Survey, which includes data on the year of each person’s most recent marriage, and the number of times they’ve been married. So, limiting the data to first-time married parents, I can check the age of their oldest child and see whether it was born before they were married, and before the parent was age 21. Some of the above problems still apply, but this is something. And it enables me to underscore Bruenig’s point that step three of the success sequence is not pulling its weight.

(Note this analysis is just about the timing of births for people who are currently married. Single parents of course have higher poverty rates that you can’t attribute to the timing of their births without more information than the ACS has.)

Using the 2013 ACS provided by IPUMS, I took all married parents, living in their own households, age 18 or older, married for the first time, with a child under 18 in the household. Then I used the job norm (self or spouse full-time employed), the education norm (high school complete), and the parent norm in two parts (child born after marriage, child born after age 21), as well as other variables, to see their relative contribution to not being poor. The other variables were additional education (BA degree), race/ethnicity, age, sex, disability, and nativity

This figure shows the marginal effects. That is, how much does the chance of being in poverty change with each of these conditions, holding all the others constant at their means? Click to enlarge:

success sequence acs 2013.xlsx

If the oldest child in the family was born before the year of the parents’ marriage, the chance of being in poverty is increased by 0.4%. If the child was born before the parent was 21, the chance goes up by 0.6%. This seems reasonable to me, given the potential hardships associated with single and early parenthood. But compare: Not having a high school diploma increases the chance of poverty by 2.2%, and neither spouse having a full-time job increases the chance by 6.4%.

Remember, these are all effects holding constant everything else in the model. If you just look at the difference between those who fulfill the parenting “norm” and those who don’t, it’s much bigger. Among people with a full-time job in the family and a high school degree, the poverty rate is 2.8% for people whose oldest present child was born after they were married and 21, versus 9.1% for the people who let us all down on the childbearing norm. But that big difference is mostly because of education and race/ethnicity and disability, etc.

In short, this exposes how rotten it is to tell someone they are poor because of when they had their kids. A decent job and some education would mean a lot more than your sermon.

Code

Here is the IPUMS codebook for my download, and the Stata .do file for the analysis.

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