Some politicians lie (Maryland edition)

That’s just my opinion.

Meanwhile, Maryland Governor Larry Hogan is responding to the tax shortfall in his (our) state with a plan to cut taxes. And his justification, repeated during the campaign, and now during his State of the State message, includes these two claims:

“We’ve had the largest mass exodus of taxpayers fleeing our state – of any state in our region, and one of the worst in the nation.”

“Businesses, jobs and taxpayers have been fleeing our state at an alarming rate.”

As a dedicated public servant — who just got furloughed, lost a cost of living pay increase, and lost a merit pay increase, while our students are getting a tuition increase because of the state’s disastrous tax shortfall — I remain doggedly committed to pursuing truth.

So, the “mass exodus of taxpayers” fleeing our state:

Yes, population growth was a little slower than the regional and national averages for a couple years there. But the 25+ population has grown every year but one since 2001. Checking my definition of “exodus” now…

And the “jobs … fleeing our state at an alarming rate”:

Job growth faster than the national average, no (net) “fleeing.”

The source for both figures is my calculations from the American Community Survey via IPUMS.org.

Addendum: The Bureau of Labor Statistics reports Maryland employment trends here. Here is the employment trend from 2004:

Fewer births and divorces, more violence: how the recession affected the American family

I wrote this for The Conversation. Read the original here.

Observers may be quick to declare social trends “good” or “bad” for families, but such conclusions are rarely justified. What’s good for one family – or group of families – may be bad for another. And within families, interests do not always align. Divorce is “bad” for a family in the sense of breaking it apart, but it may be beneficial, or even essential, for one or both partners or their children.

This kind of ambiguity makes it difficult to assess what kind of impact the recent recession and its aftermath had on families. But for researchers, at least, it offers a lot of job security – so many questions, so much going on. In any case, here’s where we stand so far.

The effect of the Great Recession on family trends in the United States has been dramatic with regard to birth rates and divorce, and has been strongly suggestive of family violence, but less clear for marriage and cohabitation.

Marriage rates declined, and cohabitation rates increased, but these trends were already underway, and the recession didn’t alter them much. When trends don’t change direction it’s difficult to identify an effect of a shock this broad. However, with both birth rates and divorce, clear patterns emerged.

Birth rates: a sharp drop
The most dramatic impact was on birth rates, which dropped precipitously, especially for young women, as a result of the economic crisis. How do we know? First, the timing of the fertility decline is very suggestive. After increasing steadily from the beginning of 2002 until late 2007, birth rates dropped sharply. (The decline has since slowed for some groups after 2010, but the US still saw record-low birth rates for teenagers and women ages 20-24 as late as 2012.)

Second, the decline in fertility was steeper in states with greater increases in unemployment. Although we don’t have the data to determine which couple did or did not have a child in response to economic changes, this pattern supports the idea that financial concerns convinced some people to not have a child.

That interpretation is supported by the third trend: the fertility drop was more pronounced among younger women – and there was no drop at all among women over 40. That may mean the fertility decline represents births postponed by families that intend to have children later – an option older women may not have – which fits previous research on economic shocks.

It seems likely that people who are on the fence about having a baby can be swayed by perceived financial hardship or uncertainty. From research on 27 European countries, we know that people with troubled family financial situations are more likely to say they are unsure whether they will meet their stated childbearing goals – that is, economic uncertainty doesn’t change their familial aims but may increase uncertainty in whether they will be met.

However, some births delayed inevitably become births foregone. Based on the effect of unemployment on birth rates in earlier periods, it appears a substantial number of young women who postponed births will end up never having children. By one estimate, women who were in their early 20s during the Great Recession are projected to have some 400,000 fewer lifetime births and an additional 1.5% of them will never have a birth.

Divorce rates: a counter-intuitive reaction
In the case of divorce, the pattern is counter-intuitive. Although economic hardship and insecurity adds stress to relationships and increases the risk of divorce, the overall divorce rate usually drops when unemployment rates rise.

Researchers believe that, like births, people postpone divorces during economic crises because of the costs of divorcing – not just legal fees, but also housing transitions (which were especially difficult in the Great Recession) and employment disruptions.

My own research found that there was a sharp drop in the divorce rate in 2009 that can reasonably be attributed to the recession. But, as we suspect will be the case with births, there appears to have been a divorce-rate rebound in the years that followed.
Domestic violence: a spike along with joblessness
Family violence has become much less common since the 1990s. The reasons are not entirely clear, but they certainly include the overall drop in violent crime, improved response from social service and non-governmental organizations, and improvements in women’s relative economic status. However, when the recession hit there was a spike in intimate-partner violence, coinciding with the sharp rise in men’s unemployment rates (I show the trends here).

As with the other trends, it’s hard to make a case based on timing alone, but the evidence is fairly strong that the economic shock increased family stress and violence. For example, one study showed that mothers were more likely to report spanking their children in the months when consumer confidence fell. Another study found a jump in abusive head trauma cases during the recession in several regions. And there have been many anecdotal and journalist accounts of increases in family violence, emerging as early as 2009. Are these direct results of the economic stress or mere correlation? It’s hard to say for sure.

The ultimate impact of these trends on American families will likely take years to emerge. The recession may have affected the pattern of marriage in ways we don’t yet understand – how couples selected each other, who got married and who didn’t – and may create measurable group of marriages that are marked for future effects as yet unforeseen. Like the young adults who entered the labor market during the period of high unemployment and whose career trajectories will be forever altered unfavorably, how these families bear the scars cannot be predicted. Time will tell.

First look: 2013 divorce rates show big drop

The 2013 American Community Survey (ACS) is out, and with it the numbers we need to update the divorce rate trend.*

These are the estimates based on the giant sample: In 2013 there were 63,951,934 married men, and  63,619,135 married women. In 2013, 1,071,278 men and 1,197,095 women reported getting divorced in the 12 months prior to their interview. That means the refined divorce rates — divorces per 1,000 married people — were 16.8 for men and 18.8 for women. Wow! Look at the trend now:

That’s a very big drop, almost as big as the 2009 drop. What does this mean? It’s too early to say without more investigation, but consider it in light of my analysis of the recession period. Starting with the 2008 data, it looked to me like there was a big drop at the start of the recession — which we figure is related to the costs of divorce (legal fees, real estate, other transition costs) — and then a rebound as the postponed divorces start to materialize.

I didn’t just guess that based on the trends. I used the variables associated with divorce in 2008 (age at marriage, marital duration, education, race/ethnicity, etc.) to predict divorces in the later years, and found that the prediction was higher than the observed number of divorces, suggesting a deficit of realized divorces.

That interpretation might still be true (which is good, because the paper was published less than a year ago). But the ACS marital events (e.g. ,divorce) data only go back to 2008, so it’s difficult to evaluate the 2009 drop in historical perspective. Now we have to wonder: What if 2009 was really closer to the “normal” rate of divorce decline, and really the recession just gave us the 2010-2012 increase, and no drop? I’m not ready to conclude that, of course. My analysis still makes sense. And there is previous research (cited in the paper) that shows declines in divorce during recessions. But 2013 is going to have to be explained somehow.

I have an idea. I’ll just hop over to the government’s official divorce statistics page to compare these ACS numbers with the actual number of divorces recorded. Wait, what?

Hm. Well, OK, there’s no “detailed data” from the vital statistics system anymore. But surely there is at least a simple count available? I’ll just click on “National marriage and divorce rate trends,” to get those. Um…

So these numbers only go through 2011, and they exclude 6 states, which together account for 20% of all US divorces. Here’s a good data exercise: find another rich country that doesn’t have a count of its own marriages and divorces.

As I have pointed out in increasingly alarmed tones (in this post and earlier), the ACS marital events and marital history questions have been slated for removal by the budget powers that be.** Because if there’s one thing we don’t want to spend money on, it’s information. Why bother? We can just do a Google search or use Big Data to count up #imfinallydivorced hashtags. Yes, I just made that up. But the way things are going we may soon be begging Facebook and Google to tell us what’s going on. As Vonnegut might say, “Good luck, America!”

Notes

* The public use files are up on the IPUMS.org site, and the online analysis tool is available for quick analysis, but for this I used the numbers from the full survey, available on the Census Bureau’s American FactFinder, tables 1YR_B12503 and 1YR_B12001. I realize it’s odd that the rates for men and women here differ (by more than would be possible even if lots of women are divorcing other women). This is a survey question, not a count of legal divorces.

**The information about the planned cuts to the American Community Survey is here: https://www.federalregister.gov/articles/2014/10/31/2014-25912/proposed-information-collection-comment-request-the-american-community-survey-content-review-results:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

Comments will be accepted until December 30.

Marriage rates among people with disabilities (save the data edition)

Cross posted on the Families as They Really Are blog.

Disability is a very broad concept, representing a wide array of conditions that are not easily captured in a simple demographic survey. However, disabilities are very prevalent, especially in an aging society, and the people who experience disabilities differ in important ways from those who do not. Previously I reported — in a preliminary way — that people with disabilities are much more likely to divorce than those without. Here I present some numbers on marriage rates.

This isn’t the kind of thorough, probing analysis this subject requires. But I have two reasons to do it now. First is that I hope to motivate other people to pursue this issue in greater depth. And second, I want to highlight the importance of the data I’m using — the American Community Survey (ACS) — because it might be not available for much longer. These questions have been slated for demolition by the U.S. Census Bureau on cost-saving grounds. I put details about this issue — and how to register your opinion with the federal government — at the end of the post.

Disabilities

The ACS asks five disability questions (I put the shorthand label after each):

1. Is this person deaf or does he/she have serious difficulty hearing? (Hearing)
2. Is this person blind or does he/she have serious difficulty seeing even when wearing glasses? (Vision)
3. Because of a physical, mental, or emotional condition, does this person have serious difficulty concentrating, remembering, or making decisions? (Cognitive)
4. Does this person have serious difficulty walking or climbing stairs? (Ambulatory)
5. Does this person have difficulty dressing or bathing? (Independent living)

These aren’t perfect questions, but they cover a lot of ground, and the ACS — which involves about 3 million households — can’t get into too much detail.

One great thing about having these questions on the giant ACS is you can use the data to get all the way down to the local level, or into small race/ethnic groups. And with the marital events questions, you can combine disability information and marriage information.

First-marriage rates

Using marital events (did you get married in the last year), marital history (how many times have you been married), detailed race and ethnicity breakdowns, and the disability questions above, I produced the following figure. This uses the combined 2008-2012 ACS data because these are small groups, but even with five years of data these groups get quite small. There are about 90,000 non-Hispanic Whites with a cognitive disability in my sample, but only 356 people who are both White and American Indian with a hearing disability (the smallest group I included). This sample is people ages 18-49 who have never been married (or just got married).

The overall first-marriage rate for people ages 18-49 is 71.8 per 1,000. For people with disabilities it’s 41.1 (shown by the blue line). So that’s much lower than for the general population. But there is a very wide variation across these groups, from 15.5 per thousand for Blacks with disabilities in independent living all the way up to above the national average for Whites and White/American Indians with hearing disabilities. (For every condition, Blacks with disabilities have the lowest marriage rates.)

I don’t draw any conclusions here, except that this is an important subject and I hope more people will study it. Also, we need data like this.

In previous posts demonstrating the value of this data source, I wrote about:

• Divorce generally
• Divorce for “millennials” in 25 cities
• Divorce for Asian Americans from different national origins

Whether you are a researcher or some other member of the concerned public, I hope you will consider dropping the government a line about this before the end of the year.

The information about the planned cuts to the American Community Survey is here: https://www.federalregister.gov/articles/2014/10/31/2014-25912/proposed-information-collection-comment-request-the-american-community-survey-content-review-results:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

Comments will be accepted until December 30.

Certain death? Black-White death dispersions

New research report, after rumination.

Knowing the exact moment of death is a common fantasy. How would it change your life? Here’s a concrete example: when I got a usually-incurable form of cancer, and the oncologist told me the median survival for my condition was 10 to 20 years, I treated myself to the notion that at least I wasn’t going to the dentist anymore (6 years later, with no detectable cancer, I’m almost ready to give up another precious hour to dentistry).

I assume most people don’t want to die at a young age, but is that because it makes life shorter or because it makes them think about death sooner? When a child discovers a fear of death, isn’t it tempting to say, “don’t worry: you’re not going to die for a long, long time”? The reasonable certainty of long life changes a lot about how we think and interact (one of the many reasons you can’t understand modernity without knowing some basic demography). I wrote in that cancer post, “Nothing aggravates the modern identity like incalculable risk.” I don’t know that’s literally true, but I’m sure there’s some connection between incalculability and aggravation.

Consider people who have to decide whether to get tested for the genetic mutation that causes Huntington’s disease. It’s incurable and strikes in what should be “mid”-life. Among people with a family history of Huntington’s disease, Amy Harmon reported in the New York Times, the younger generation increasingly wants to know:

More informed about the genetics of the disease than any previous generation, they are convinced that they would rather know how many healthy years they have left than wake up one day to find the illness upon them.

The subject of Harmon’s story set to calculating (among other things) whether she’d finish paying off her student loans before her first symptoms appeared.

The personal is demographic

So what is the difference between two populations, one of which has a greater variance in age at death than the other? (In practice, greater variance usually means more early deaths, and the risk of a super long life probably isn’t as disturbing as fear of early death.) Researchers call the prevalence of early death — as distinct from a lower average age at death — “life disparity,” and it probably has a corrosive effect on social life:

Reducing early-life disparities helps people plan their less-uncertain lifetimes. A higher likelihood of surviving to old age makes savings more worthwhile, raises the value of individual and public investments in education and training, and increases the prevalence of long-term relationships. Hence, healthy longevity is a prime driver of a country’s wealth and well-being. While some degree of income inequality might create incentives to work harder, premature deaths bring little benefit and impose major costs. (source)

That’s why reducing life disparity may be as important socially as increasing life expectancy (the two are highly, but not perfectly, correlated).

New research

Consider a new paper in Demography by Glenn Firebaugh and colleagues, “Why Lifespans Are More Variable Among Blacks Than Among Whites in the United States.”

I previously reported on the greater life disparity and lower life expectancy among Blacks than among Whites. Here is Firebaugh et al’s representation of the pattern (the distribution of 100,000 deaths for each group):

Black deaths are earlier, on average, but also more dispersed. The innovation of the paper is that they decompose the difference in dispersion according to the causes of death and the timing of death for each cause. The difference in death timing results from some combination of three patterns. Here’s their figure explaining that (to which I added colors and descriptions, as practice for teaching myself to use an illustration program — click to enlarge):

The overall difference in death timing can result from the same causes of death, with different variance in timing for each around the same mean (spread); different causes of death, but with the same age pattern of death for each cause (allocation); and the same causes of death, but different average age at death for each (timing). Above I said greater variability in life expectancy usually means more early deaths, but with specific causes that’s not necessarily the case. For example, one group might have most of its accidental deaths at young ages, while another has them more spread over the life course.

Overall, the spread effect matters most. They conclude that even if Blacks and Whites died from the same causes, 87% of the difference in death timing would persist because of the greater variance in age at death for every major cause. There are differences in causes, but those mostly offset. Especially dramatic are greater variance in the timing of heart disease (especially for women), cancer, and asthma (presumably more early deaths), The offsetting causes are higher Black rates of homicide (for men) and HIV/AIDS deaths, versus high rates of suicide and accidental deaths among White men (especially drug overdoses).

The higher variance in causes of death seems consistent with problems of disease prevention and disparities in treatment access and quality. (I’m not expert on this stuff, so please don’t take it exclusively from me — read the paywalled paper or check with the authors if you want to pursue this.)

Are these differences in death timing enough to create differences in social life and outlook, or health-related behavior, between these two groups? I don’t know, but it’s worth considering.

So you want to know the Asian divorce rate (save the ACS marital events edition)

One of the most popular posts ever on this blog is about Asian incomes, and especially the variation in average incomes across Asian national-origin groups and cities. Turns out the diverse Asian groups have different divorce rates as well. Why not? It would be nuts to assume the immigrants and their descendants from everywhere from Bangladesh to Japan had common family practices and behavior.

We can figure this out with the American Community Survey (see below; data from which is provided by IPUMS.org). The ACS is big enough to measure divorce rates for Asian subgroups if you pool together a few years — for this I use the 2008-2012 file. For reliability, here I am just showing those groups that had a sample of at least 1,000 married people. And I’m including as separate groups those that selected more than one “race” — Japanese-White, Korean-White, and Filipino-White (you’ll see why I separated them out). Note these are multiple-race individuals, not couples in which the two spouses reported different races.

The national refined divorce rate — divorces per 1,000 people — fell from 20 to 18 at the start of the recession in 2008, before rebounding back up to 19 by 2012. So compare these numbers with about 19 as the national average divorce rate (click to enlarge).

Look at that spread! Now won’t you feel a little foolish for even asking what the “Asian” divorce rate is? I leave the interpretation to the relevant experts (media note: but I’ll be happy to speculate if it will help you get your story past the editor).

A further wrinkle: gender. Unfortunately, because the ACS is a household survey, if someone is divorced, the person they divorced is usually not living in the same household, which means we don’t know who they divorced (or even the other spouse’s gender!). Naturally, men and women in the same ethnic group can have different divorce rates to the extent that they marry outside their own group (or get gay divorced at different rates).

So here are the divorce rates for the same groups, but separately by gender. Groups above the line have higher divorce rates for men (Pakistanis, Cambodians), those below the line have higher divorce rates for women (Korean, Vietnamese, Korean-White). Click to enlarge:
By now you’ve realized what a wonderful treasure-trove of data this is for understanding the incredibly expanding family complexity that pulses all around us. Or, as they say, “Pretty nice data you got there. I’d hate to see something happen to it.” Read on.

Speak up

Last week I reported “millennial” generation divorce rates for 25 metropolitan areas. That’s something you can only get from the very large American Community Survey (because we have no national registry of marital events).

In addition to local areas, however, the vast size of the ACS lets us drill down into very small groups in the population — like small Asian subgroups. For another example, remember the big ruckus over same-sex marriage (you know, homogamy)? I for one would love to have good national data on same-sex marriage patterns when the equality-deniers finally lope back into their caves and the dust settles.

But now the feds are proposing to scrap the marital events (did you get married, divorced, or widowed last year?) and marital history (how many times have you been married, and when was the last time?) questions from the ACS just to save a few million dollars. I hope you’ll help demographic science convince them not to. (In the previous post I listed a bunch of divorce facts we only know because of the ACS questions.)

The information about the planned cuts to the American Community Survey is here: https://www.federalregister.gov/articles/2014/10/31/2014-25912/proposed-information-collection-comment-request-the-american-community-survey-content-review-results:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

Comments will be accepted until December 30.

* Contrary to popular belief, there is no “Asian” category on the Census/ACS form. People are identified as Asian if they pick any of the Asian national origins listed on the “race” question. It’s all pretty American-exceptional. Here is the question, from this form:

Top 25 cities for Millennial divorce (save the American Community Survey marital history and events questions edition)

First some news, then the urgent story behind the news.

All marriages and divorces are local. Whether and when people marry is dependent on who they meet and the conditions under which their relationships develop — social, economic, and even political. And divorce depends on local factors as well, such as the likelihood or feasibility of meeting alternative partners, the costs and consequences of divorce, and the norms and laws regulating divorce. (The same is true for forming and ending non-marital relationships, but those are harder to measure and their dynamics are different).

The Millennial Divorce Capital

So, I know the question you’re dying to have answered is: Where do Millennials get divorced? This question is so compelling that I’ve suspended my normal objection to arbitrary generational definitions, and let Mellennials be defined as anyone born in 1980 or later — so this is the divorce rate among people roughly ages 15 to 31 in the 2009-2011 American Community Survey.

Measuring divorce is complicated, because you’ve got a lot of choices. Here are two simple ways: The number of divorces among Millennials occurring in the previous year per 1,000 Millennials in the population (the crude Millennial divorce rate), and the number of those divorces per 100 married Millennials (the refined Millennial divorce rate). Think of the crude rate as the chance of meeting a Millennial who just got divorced walking down the street, and the refined rate as the chance that one of your married friends just got divorced. I’ve ranked them by the refined rate for this table, which we can use to crown Portland, Oregon the Millennial Divorce Capital of the United States (it’s #1 on both measures).

This is just the 25 largest Millennial population centers, for which we have the most reliable estimates of divorce rates. Nationally, 6.2 out of every 1,000 living Millennials reported getting divorced in the previous 12 months.

It’s complicated

The differences in the two rates I show can be very important. For example, if I expanded the list to the top 50, you would see that the city in which you are most likely to bump into a divorced Millennial at random (spilling your non-caffeinated beverage) is Salt Lake City, where an astonishing 9.7 out of every 1,000 Millennials got divorced in the past year. That’s not because they love divorce, however, it’s because they love marriage. An amazing 34% of Salt Lake City Millennials in 2009-2011 had already been married, compared to just 23% in Divorce Capital Portland.

On the other hand, it’s not just that more married people means more people available for divorce. It’s also the case that early marriage increases the risk of divorce. And more than that, places where early marriage is common have higher rates, even for people who get married at older ages. In this figure I show an adjusted divorce rate (technically, the predicted chance of divorcing in year 5 given marrying at age 23) by the average age at first marriage in each metro area: Divorce is less common in the late-marriage cities*:

(Note that, to produce this figure, you need a survey that asks millions of people how many times they’ve been married, the year they most recently got married, and whether they got divorced in the past year. You don’t just type this into a Google search box.)

But wait, I’m afraid it’s more complicated than that. And here I’m moving toward the urgent story behind the news.

People move around. Divorce may occur in a split second, but what demographers call “relationship dissolution” unfolds over time. People move after they divorce, they divorce after they move, and they may even get divorced in places other than where they live. The ACS data I’m using here help sort this out. This divorce incidence measure is based on a survey question, not a legal record. As with all the other questions on the survey (age, race, income, education, etc.), we more or less have to trust the answers people give (some implausible answers are edited out by the Census Bureau). If we really want to understand how and where divorce (or marriage) happens, we need to be creative and careful, and use the best data. And this is the best data.

Here’s a simple illustration. This figure shows the percentage of two groups of Millennials in each state who arrived in the past year: Those who are married, and those who just got divorced. For example, in Oregon, home of the Millennial Divorce Capital, 17% of the divorced Millennials lived in a different state last year. So either moving to Oregon led to their divorce, or their divorce led to an interstate migration. In contrast, only 7% of Oregon’s married Millennial population just got there (click to enlarge):

The red line is the diagonal, so states above the line — most states — have more divorced arrivals than married arrivals (I excluded a few states with few cases in the data). There are, naturally, a lot of fascinating ways you might approach these questions. Which brings me to the urgent news.

Save the American Community Survey marital events and history data

I know from experience that some of you are thinking things like, “Break it down by race!”, “What about gay couples?”, and “What about hypergamy?” If you want those answers, get out your wallets. This information doesn’t just happen, it’s garnered through a massive federal data collection, without which our ability to know ourselves and our society would be severely compromised. And that’s what might be about to happen.

The data I just showed came from the American Community Survey (ACS), the large Census Bureau survey that replaced the “long form” of the decennial census in the 2000s. (The data are wonderfully prepared and distributed by the good people at IPUMS.org.) Unlike a simple national random survey — which is a major undertaking in itself — the ACS uses a sophisticated rotating geographic design that samples from all around the country to gather the information we need for all levels of geographic detail – down to the neighborhood.

Filling out this survey, in 3.5 million households, is estimated to take about 2.3 million hours of the American people’s time and cost a fortune. Now the federal government is reviewing the different parts of the survey looking for unnecessary parts, and they have identified 7 questions that could be cut, including the ones I’ve been using here: marital events (did you get married, divorce, or widowed in the last year), marital history (how many times have you been married, when did you get married most recently), and a couple others. So I’m trying to convince you to submit a public comment urging them not to make the cuts.

Why do we need this?

Believe it or not, there is no national count of marriages and divorces. That’s right, your government cannot tell you how many legal marriages and divorces there are. They used to collect this from every state, but now they don’t. States collect this information, but it’s not standardized, and it’s not collected together. And, even if it were, we wouldn’t be able to analyze it with all the detail I’ve used here — using marriage duration, age at marriage, and other important factors. So, even at the national level, this is all we have.

However, just for national marriage and divorce statistics, we wouldn’t need the ACS. We could use a smaller survey, like the Current Population Survey or others. If they wanted to work out one of those alternatives before canceling these questions, that would be OK for national statistics.

However, for smaller populations — state and local populations, minority groups, gay and lesbian couples — there is no alternative. If we lose these questions on the ACS, we lose the ability to do all that. Unfortunately, there is no legal or legislative mandate to collect this information down to the local level, which is why it’s on the chopping block. It’s just super interesting and important, not legally required. So we need to communicate that up the chain of command and hope they listen.

To help motivate and inform you toward that end, here’s a list of what we would not know about divorce without the ACS marital events and history questions, and then the information for contacting the federal government with your comment. These are just from my blog, I haven’t done an exhaustive search. The point is not that I’ve done so much, but that there is so much of vital importance that we can learn from this data.

• The refined divorce rate in 2012 was 19 per 1,000 married people.
• The overall projected divorce rate for couples marrying in 2012 is about 50%. This requires using marriage, divorce, and widowhood incidence to calculate competing risks. You need all the ACS questions for that.
• We lost about 150,000 divorces during and after the recession. Then divorce rebounded to catch up to its (declining) trend. That’s the result of my analysis published in Population Research and Policy Review, which relied on a model using all the ACS individual data in all 50 states.
• People with disabilities are much more likely to get divorced than people without. The magnitude of the difference depends on the type of disability.
• Divorce rates in first marriages are more than three-times as high for Black women as for Asian women in the U.S.
• The 2008-09 refined divorce rate by state was correlated with Google searches for “colt 45 automatic” at .86 (on a scale of -1 to 1).
• The 2011 crude divorce rate by state was correlated with Google searches for “vasectomy reversal” at .79.
• The changing pattern of same-sex marriage across states and local areas. We don’t know this yet, but we should, and we’ll want to, and the ACS is the only way we’ll be able to.

Speak up

The information about the planned cuts to the American Community Survey is here: https://www.federalregister.gov/articles/2014/10/31/2014-25912/proposed-information-collection-comment-request-the-american-community-survey-content-review-results:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

Comments will be accepted until December 30.

* Here’s the mixed-effect multilevel regression testing the relationship between average age at marriage (meanagemarr) and odds of divorcing, controlling for age at marriage and duration of marriage, for 262,269 married people in 283 metro areas:

If you want to see serious research into the effects of age at marriage, local age at marriage, and religion, on divorce, this paper by Glass and Levchak is the right place to start.