Update on Pandemic Recession vs. Great Recession Unemployment by Race and Gender (incl. Asian Women)

10/22/20: Belated UPDATE through September data to charts below, originally shared on Twitter here. (I’ll make future updates here as well in order to keep in one place where some might look thanks to the new Center for American Progress report by Mike Madowitz and Diana Boesch published today.)

Today the BLS released their monthly “Employment Situation” report –and the report’s underlying data (which you can access here), including numbers on Asian women separated from Asian men which are not included in the report. Here’s a small, mostly quantitative update to my original post (with Mina Kim) from last month. First, the bottom-line/main-story bar chart:

… and below, the updated table with detailed unemployment stats by race and gender:

One thing I decided to adjust in the bar chart and add as note to the table is that April 2020 was when the unemployment rate peaked for the workforce overall as well as for most of the race-gender categories–except that the peak for Asians (both men and women) and for Black women (and Black overall but not Black men) happened in May. So the bar chart compares the absolute change in unemployment rate during the (aftermath of the) Great Recession compared with the change from this February to either April or May–whichever was the worst point for each race-gender category.

Some findings worth highlighting (or repeating):

  • Asian women fared the best in the Great Recession in that their absolute change in unemployment rate from the start of the recession to peak unemployment was the smallest of all race-gender categories;
  • From the start of the Pandemic Recession (Feb. 2020) to either peak unemployment in April or May, or to the latest data for September, White men have fared the best (their September unemployment rate is just 2.8 percentage points higher than in February);
  • Hispanic women fared the worst in the Pandemic Recession through this spring (April)–but up through September, Asian women have seen the largest increase in unemployment (+6.7 percentage points);
  • While Asian unemployment peaked in May at 16.6% for women and 13.2% for men, both had failed to recover as much as for other race-gender categories through August. Unemployment rates in August were 11.5% for Asian women and 10.0% for Asian men, still higher than they ever got even in the depths of the Great Recession. By September, Asian male unemployment (at 8.0%) was lower than at its peak in the Great Recession, yet Asian female unemployment (at 9.7%) was still higher than at any time in the last recession–and in fact, higher than ever measured in the BLS data.

As I hinted at in my first post on this subject, there are many different possible explanations for why this Pandemic Recession has been so hard on women (it’s the “She-cession”) and Asian women in particular. The intersection of Asian and female provides a uniquely-focused lens into what’s so different about this recession and how it’s affecting all workers through the roles and demands that Asian women just happen to disproportionately represent. To be continued!

More Pictures on the Pandemic “She-cession” by Race

Here are a bunch of charts that illustrate why the Pandemic Recession is also sometimes referred to as the “She-cession.” These are based on BLS monthly data through August (released last Friday, Sept. 4). I’m also re-posting the bar charts I put up on Twitter and here last Friday, so the latest figures are in one place. (See original post on “Seeing Asian Women…” here and the table with all the unemployment data through August by race-gender categories here.)

First, compare male minus female unemployment during the Great Recession to during the Pandemic Recession (thus far):

During the Great Recession (Dec. 2007-2009/10 recovery period), male unemployment relative to female unemployment grew dramatically–and in general/overall male unemployment stayed higher than female even years after.
During the Pandemic Recession (since Feb. 2020), female unemployment increased dramatically and surpassed male unemployment in all racial categories, and only among Black workers did male unemployment again exceed female unemployment this summer.

The differences in unemployment across racial categories have been stark. It’s not just a recession with disproportionate impact on women, but one with disproportionate impact on people of color. Zooming in a bit more recently, here’s what the unemployment rates by race since January 2019 look like:

Unemployment rates by race categories, men and women combined. Note that Asian unemployment started the very lowest in February 2020 and is the second highest in August 2020.

Going back to looking at the employment outcomes among women by race over the past year and a half (since January 2019), here are charts showing the unemployment rates, the employment-to-population ratios, and the labor force participation rates:

Female unemployment rates, by race, January 2019 through August 2020. Note that like for race categories overall, Asian females had the lowest unemployment rate in February 2020, but in August 2020 have the second highest–as Hispanic female unemployment has shown the best recovery since its peak in April.

Female employment-to-population ratios by race, January 2019 through August 2020. Hispanic women had the lowest e/pop at worst part of the Pandemic Recession and have traded places with Asian women a couple times since. Black women had had the highest e/pop going into the pandemic but in August, white women had surpassed black women.
Female labor force participation rates by race. Asian female participation was relatively low pre-pandemic, but is second highest this summer–showing that many Asian women consider themselves still “in the labor force” even if currently unemployed.

And below is the headline bar chart I previously posted comparing absolute changes in unemployment rates for women by race in the Great Recession vs. during this Pandemic Recession (through August):

The Pandemic Recession is a “She-cession” and has had disproportionate impact on women of color, particularly on Asian women–who face a still higher unemployment rate in August (at 11.5%) than at their worst point in the Great Recession (8.4%).

And looking at Asians alone (both men and women), the “double whammy” of being both Asian and female in this Pandemic Recession is underscored:

Asians (especially the women) had very low increases in unemployment during the Great Recession relative to other race categories. This time is totally different.

Seeing Asian Women to Better Understand the Pandemic ‘She-cession’

By Mina Kim and Diane Lim (with assistance from Taylor D. Jones), August 2020

This pandemic recession has been like nothing we’ve ever seen in our lifetime. The U.S. has experienced the largest contraction since the Great Depression. Every week, we eagerly await each data release for any sort of good news, only to be met with confirmation after confirmation of the calamitous impacts of the coronavirus pandemic. Economists were quick to point out early in the pandemic that increases in unemployment have been more severe for women than men and more severe for people of color than for White people. But in all the analyses, Asian women have been missing. Given the goal of national representativeness in most surveys, the “invisibleness” of Asian women is understandable. We represent a very small percentage of the population. We are also probably not as responsive to surveys given how 1st and 2nd generation Asian American women are taught to blend in and not stand out. (Both of us reflect on how this “blend in” behavior was reinforced in us very early on in our childhoods, by our teachers, classmates, and even our immigrant parents.) As Asian female economists, we had personal incentive to take a good look at the data—we just wanted to find ourselves there! What we found is that not only have Asian women experienced the largest increase in unemployment during the pandemic recession, but that the case of Asian working women probably best shines a spotlight on how women’s employment depends as much or more on what’s going on at home (and the demands for our time there) than on what’s going on with the market demand for our paid work. What follows is a story of what has happened to women in the labor market during this Pandemic Recession and how this recession is different from the last, made clearer by our ability to dive deeper into details across race categories.

NOTE: For this analysis we used the BLS “One-Screen Data Search” tool here. While the monthly employment reports of the Bureau of Labor Statistics (BLS) present breakdowns of the unemployment measure by race and by race-gender categories, they only show data for the Asian category as a whole because of the valid concern that the Asian sub-sample sizes are too small to be statistically comparable with other race-gender categories. But the BLS does publish and make publicly available the data on Asian women separated from Asian men on its website. All data are monthly and unadjusted (not seasonally adjusted), for the populations age 16 and over. The “Asian” category includes only people who identify themselves as (only) Asian on the Census survey, not those who identify as two or more races; it also does not include Pacific Islanders. (A helpful BLS report which explains their categorization of people by race and ethnicity is here.)

  1. The “Pandemic Recession” is a “She-cession” (Figure 1). C. Nicole Mason, CEO of the Institute for Women’s Policy Research, first dubbed the pandemic recession the “She-cession” back in early May in this New York Times story, when it had become apparent that more women than men had become unemployed since February. At the time, the leading explanation was that women make up a disproportionately large share of the workforce in the industries that have been most adversely impacted from the “stay-at-home” orders: the leisure/hospitality sector (think restaurants, bars, sports venues, concert halls, movie theatres), other people-intensive personal services businesses (think beauty salons/barbers, gyms, yoga studios), and non-emergency medical care offices (think general/family practices, dentists, eye doctors).

Now there is recognition of the role childcare (and in-person school), or the lack thereof, plays in affecting the ability of women to work (see Alon, Doepke, Olmstead-Rumsey and Tertilt; Mongey, Pilossoph, and Weinberg; Dingel, Patterson, and Vavra; Modestino, Ladge and Lincoln; and Heggeness). Compared with a typical economic recession that impacts male employment more than female, the Alon et al. paper stresses that the “She-cession” has more severe short-term/cyclical impact on economic activity due to diminished “within-household insurance”—a reduced ability for parents to trade off/coordinate roles at home vs. work—and will also lead to a longer-term (persistent) widening of the gender wage gap even after the recession is over.

Figure 1.
  1. This recession is very different from the last one (Figure 2). The “Great Recession” (left panel) impacted male-dominated jobs in the economy more than the female-dominated ones. Before the start of that recession, goods-producing jobs (particularly in the durable goods/”heavy” manufacturing sectors) had already begun a longer-term loss due to both offshoring and automation. As the economy began its long, slow recovery from the recession (officially in “recovery” by June 2009), unemployment rates continued to rise, peaking for men in early 2010 at a much higher rate than for women. Overall female unemployment peaked later (in the middle of 2010) but remained below male unemployment until the middle of 2011. Many of the men who had been laid off from their manufacturing jobs during the Great Recession never came back to those jobs after the economy recovered. These were disproportionately middle-aged, White men who came out on the other side of the recession saying “well, I guess I’m retired now.” (These were also the White men disproportionately represented in the “deaths of despair” that Anne Case and Angus Deaton revealed.)

This time (right panel) the economic impact was felt suddenly due to a non-market event and has fallen disproportionately on the employment of women. After several years of very low unemployment where women and men switched ranking but stayed very close to each other, female unemployment very quickly overtook male unemployment at the onset of the pandemic and has retained its “lead” thus far.

  1. Pandemic unemployment has been dominated by the laying off and rehiring of largely part-time workers (Figures 3 and 4). The part-time share of total employed fell as unemployment peaked (in April) and rose as unemployment has declined (since May). The timing is consistent with job losses concentrated in the leisure/hospitality, personal services, and retail sectors, where workers are disproportionately young, part-time, and low-wage (no benefits). (This is also why government assistance has been critical for households to be able to maintain basic consumption and prevent a more severe “reverse multiplier” effect on the economy more broadly.)
Figure 3.

While the trends in unemployment of part-time workers impact women more than men across all race categories, Black and Asian women more often work full-time jobs than do White or Hispanic women.

Figure 4.

If pandemic unemployment were mainly driven by occupational and industry factors (layoffs from part-time jobs in the leisure/hospitality, retail sales, and personal services sectors), we might see Hispanic and White women suffering the greatest unemployment, and Asian and Black women, less so. In fact, it’s not that simple…

  1. The “She-cession” story differs across race (Figures 5 and 6). It appears to have come and gone among Black Americans but has persisted for other race categories. By June, Black male unemployment was back above Black female unemployment, while in all other categories female unemployment has exceeded male unemployment since April. In the prior recession, men overall faced more severe unemployment than women, and it was especially severe for Black men. In this recession, Black men have not had as large an increase in unemployment as many of the women, but only because they started so high. Before the pandemic, in February, the Black male unemployment rate (at 7.3%) was the highest of all the race-gender categories. As of July, the Black male unemployment rate (at 15.6%) was still the highest of all the categories.
Figure 5.
Figure 6.
  1. The “She-cession” experience has had biggest impact on Asian women (Figures 7 and 8). Among all women, Asian women had the lowest unemployment rate in February, yet their unemployment rate has been above average and in line with the unemployment rate of other women of color during the pandemic. In terms of the change in unemployment rates during this pandemic recession so far, Asian women have experienced the single worst change in unemployment through July—not just among women but across all the race-gender categories. (Hispanic women suffered the largest increase in unemployment from February to April; besides figures below, see details in the Appendix Table at the end.)
Figure 7.
Figure 8. (Note: Worst point in the Great Recession is going to differ for each race category. See the Appendix Table for the exact dates.)

Caveats, Take-Aways, and “To Be Continued”s:

  • We’ve provided a one-step-more-granular analysis here, simply by including Asian females in our look at employment outcomes by race and gender. But this still doesn’t include everyone! “Asian” doesn’t include those who identify as only part-Asian (of multiple races), nor the “Pacific Islanders, American Indians, Alaska Natives, Native Hawaiians, and Other Pacific Islanders” who also tend to get left out of the “Asian” category in analyses by race—due to even smaller sample sizes than that of Asian females.
  • Yet, this race-gender intersectional analysis is still meaningful in that we do see clear differences in employment outcomes across both race and gender and all the race-gender categories. The analysis “works” because as broad as these race-gender categories are, and as heterogenous as the characteristics of the populations within each category, there are still enough characteristics that are common (or prevalent) within each category yet distinct enough from those in other categories. We suspect, for example, that the “Asian Female” category contains a sizable group of women who have relatively low educational attainment and work relatively low-skilled and low-paid personal services jobs (think nail salon), which would partially offset whatever we see that is driven by the high-skilled, higher-paid Asian women working in professional service jobs. Yet the average characteristics and outcomes within the Asian Female category still put the group as a whole in higher-skilled occupations and higher-paid jobs compared with women in the other race categories.
  • And those distinct characteristics and outcomes are not merely random differences. Race is a social construct, and that’s why it is useful in studying social and economic behaviors, influenced by social and cultural norms. Asian women look “special” in this analysis of unemployment during the Pandemic Recession because their roles in the labor market and at home and the resulting tradeoffs they face in making decisions about work vs. home are likely different enough from other women. For example, Asian women are less likely to experience the gender wage gap, probably because of their high educational attainment and occupational choices—and that’s a plus for holding onto jobs during this pandemic. (Distinct from other women, Asian women are more likely to work high-paid professional service jobs than low-paid leisure/hospitality or retail jobs.) But Asian women are also more likely to be in a traditional family structure, married with children, and married to a man who has even higher market-earning power. (We hope to do a follow-on piece on the family structure and marriage/”assortative mating” factors later.) So, as highly productive as an Asian woman might be in her job, she is likely to be the household’s “secondary earner” and also the household’s “primary caregiver.” This is why a deeper study of what’s going on with Asian women in this pandemic recession would shine a light on the struggles of all working mothers, who all face demands on their time at home with the kids. Those demands (regardless of the financial opportunity costs) too easily tip the scales in favor of staying at home and cutting back on or quitting their paid work.
  • For Asian women, the cultural factors influencing our labor market decisions are perhaps stronger than for other women. (See this paper on “Babies, Work, or Both?” by Mary Brinton and Eunsil Oh.) Many working-age Asian women are immigrants or children of immigrants. Diane’s parents immigrated to the U.S. from Korea (dad) and the Philippines (mom, of Chinese ethnicity) in the 1950s, both to pursue PhDs in Chemistry. Diane’s mom finished her PhD in 1962, just months after Diane was born, and spent nearly a decade staying at home with Diane and her younger sister Janice and was never able to make up for that lost first decade of her career. Mina’s parents immigrated from Korea in the 1970s to pursue a PhD in Physics (dad) and a Masters in Nursing (mom). Mina’s mom put her career on hold to take care of her and her two sisters when family could not help. Yet both moms constantly coached their daughters to “do it all”: to both stay ever-active in the workforce and take primary responsibility for the proper care of the kids on the home front.
  • This “first look” at Asian women’s employment outcomes has underscored the importance of considering how social and cultural expectations about the roles of women at home vs. at work influence female employment outcomes, especially in this pandemic with kids learning from home and daycare and elder care facilities closed or downsized (or viewed as undesirable/unsafe by families). It also suggests that the increased demands placed on women’s time on the home front does not just force women who earn relatively low wages (below the cost of child care) to give up their paid job, but is likely causing many higher-earning women (who can afford to pay for child care even as it has become scarcer) to cut back on or even drop out of the labor force, even when the financial and economic opportunity cost of doing so is high.
  • Further investigation is needed, going still more granular and down to more household-level data, to better understand what truly drives women’s choices and outcomes concerning work. These are questions fundamental to the study of Economics and requires research methods that have largely remained outside the Economics profession. Further research should: (i) start with interviews and focus groups; (ii) use these findings to develop surveys; and (iii) field the surveys to intentionally oversample the population subgroups that best represent and emphasize the decisions we are trying to better understand.

Appendix Table: detailed unemployment rates and changes, comparing previous to current recession

Thoughts on Coronavirus Economic Policy, Thinking as “Economist Mom”

L to R: Johnny, Diane (Mom, holding Taco), Grace, Allie, Becca, Bill (holding Tammy), Emily, and Danny

I know I haven’t been here very often since I “rebirthed” my Economist Mom blog!  But every glass half empty is also half full.  The coronavirus crisis and its required “social distancing” have provided me both the calling and the opportunity to think about the possible economic policy responses, not just relying on the same old economist’s toolkit but with the benefit of wisdom from my own children—who are experiencing this crisis much more than I.  I have come to the conclusion that the fastest, most helpful policy the federal government could implement would be to immediately put in place a tax deduction for donations to service-sector small businesses adversely impacted by the coronavirus shutdowns, which tax filers could claim off their 2019 returns that they are filing now.  How I got there is explained below—in my Economist Mom kind of way.

My husband Bill and I are really lucky.  We work as economists—policy “experts” they call us—in salaried positions where we can easily work from home or take paid sick leave.  The coronavirus pandemic affects us only in truly superficial ways that I am ashamed to even bring up: I am bummed that our planned trips to see family were cancelled and that we can’t otherwise spend our leisure time going out around town, and Bill is pretty lost without March Madness.  Today we took advantage of having few of our usual weekend pastimes to work on our 2019 tax return—a full month ahead of the April 15 “Tax Day” deadline.

Our own children: not so lucky.  We have six adult children between us.  Danny (Bill’s son) works for Amazon in Seattle.  A co-worker who works in an office near his has been diagnosed with the coronavirus, and Danny has been on mandatory work from home (WFH).  Becca (Bill’s daughter) works at Cedars Sinai in LA where several coronavirus patients are being treated.  Allie (my eldest daughter) works for Coursera in Mountain View, CA –another “hotspot” for coronavirus cases; she and her boyfriend, who together share an apartment with another roommate, are all on mandatory WFH in a really-too-small apartment to serve as an office for three.  Emily (my second daughter) and Grace (my youngest daughter) both live in Brooklyn, NY.  Emily is a Ph.D. student at NYU, adjunct teaching this semester at her undergrad alma mater, Sarah Lawrence College, in Bronxville, NY.  (Look that up in a map, and you’ll understand why we stayed in a hotel in New Rochelle when we attended Emily’s college graduation—and you’ll understand why Emily started teaching online last week and why she’s at high risk for being exposed.)  Grace is a 2019 graduate from NYU and works part time at the service counter and as wait staff of a high-end bakery in Brooklyn on a combination of low hourly wage and tips.  Her other part-time job is with a consultant who plans and stages events.  (They have no events planned now.)  She commutes to the bakery by subway and is face to face with customers all day long.  Her bakery is complying with the 50% capacity restriction by having removed half the tables in the café, but otherwise business is booming; on Saturday the customers lined up to buy out all the bread they had made that morning –so Grace had plenty of contact with many, many customers.  She tweeted out this morning that she cried while she was at work yesterday, so scared about how difficult it is for her to stay safe from this pandemic.  And that broke my heart.  Even my youngest, my son Johnny, a junior attending William and Mary, has not come out unscathed despite having gone straight from an indoor track championship last weekend in Boston to a spring break beach week in Charleston, SC with his track buddies.  While on break, he and his teammates learned their entire spring season was cancelled—which broke all their hearts.  (The ruling of the NCAA that spring season athletes will be granted another year of eligibility provides some compensation and consolation, but now we can expect to see a lot of track athletes with master’s degrees!)

I tell you about all the hardships on our children to provide context for the reason I write this post: their situations have made me see that the debilitating effects of the coronavirus pandemic on the economy require a very different kind of economic policy response from anything (“boomer”?) policy “experts” have thought about and worked on before.  The whole reason for the economic shutdown is because we’re trying to prevent the spread of the health problem.  If we could easily tell when someone was sick with or carrying the virus (i.e., if we had universally available and quick/instant testing), then we wouldn’t have to tell everyone to stay home.  But the invisible, stealthy nature of this virus and how fast it spreads requires that we all stay at home and practice safe “social distancing.”  This is not a problem for me and Bill who can work in social isolation all the time (as many economists like to do, but not me).  It is a much bigger hardship for our children—especially Grace who only gets paid when she shows up for work, relies more on tips than her hourly wage, and who works in an intensely face-to-face, hand-to-hand job.

Congress and the Administration are trying to come up with an economic policy response to the coronavirus crisis by dusting off policies from past economic crises.  (OK, Boomer…)  But those policies such as payroll tax cuts or enhanced unemployment benefits are not going to help hourly-wage workers like Grace who will either continue working as usual, worried about being or getting sick, or will work fewer (or no) hours and earn lower (or no) wages and tips.  What we really need is for workers like Grace to be paid their usual wage to stay at home.  But this is a totally radical concept for economists who overly obsess about price incentives in normal times: what, pay people to not work?  These are not normal times or a “normal” economic crisis.

DC’s most beloved restauranteur and chef, Jose Andres, just announced today that he is closing all his restaurants to reduce the risk of spreading the virus among staff and customers, and that he is increasing production of to-go meals in his community kitchens (many of which will operate inside his restaurant kitchens, keeping his healthy staff working).  The DC community is fortunate to have such a successful business owner be also such a generous man.  But other food service businesses cannot afford to keep their workers working and earning as usual when people aren’t coming out or the business is required to cut the number of customers they serve.  At the same time, people like me and Bill who are lucky enough to keep our usual paychecks and who would normally go out to eat and drink still have the discretionary income, and the desire, to support our favorite food and drink establishments—even if it means helping them make payroll and rent while they are forced to shut down.

Now, anyone could choose to help out their favorite local bar, restaurant, or bakery, by donating to that establishment’s Go Fund Me page if they were to set one up to help continue to pay their hourly workers even as their business is shuttered or reduced.  (I do recommend that small service-industry businesses do that; your usual patrons will support you!)  I’m here to help out my daughter Grace if she is forced to or wants to stop working at the bakery, and certainly if Bill and I were to benefit from some new tax cut we don’t need, we would most likely immediately hand it over to Grace and our other kids.  And while Congress may be trying to come up with legislation that better gets at the fundamental problem of steering dollars to the workers who will have to stay home because food and entertainment establishments and schools are shut down, let’s face it, nothing that government can do will happen soon enough to get people to stay home soon enough (as in right away) and stop spreading the virus. 

So that brings me back to Bill and I working on our 2019 tax return today.  Why not allow people to make individual financial donations to small service-providing businesses that have to shut down operations, and why not let government subsidize this by making such donations tax deductible?  (Current law allows deductions only for donations to charitable or nonprofit organizations, not any for-profit businesses.)  And why not take advantage of being in tax filing season by letting people immediately write off coronavirus donations (made now, in March 2020) from their 2019 taxes?  This is a way a government policy could have immediate impact.  No figuring out how to cut checks or send debit cards!  No need to send those checks to everyone (including people like me and Bill, who don’t need it).

If service-providing businesses reduce or shut down their human-facing operations, it provides a public good (reduced spread of the coronavirus) but at private cost (lost revenue).  Internalizing this positive externality requires that the good-for-society behavior (shutting down face-to-face, hand-to-hand services) be subsidized.  That subsidy can come from private individuals who care about the social good, but ideally comes from government as well.  Doing policy through the tax system can be handy when it sets up a public-private partnership of sorts: private citizens choose to make charitable contributions to the organizations they wish to help, and government matches the donation at a fraction equal to their marginal tax rates.  (Doesn’t have to be limited to the itemized deduction mechanism though—in fact, this is a perfect occasion to bring in the “above the line deduction.”)  And I just said all that as an economist, but it’s the mom in me (and the dad in Bill) that really motivates this policy idea.  We need to quickly get relief to businesses like the bakery Grace works for.  It’s critical to addressing not just the economic fallout from coronavirus but the underlying root of this crisis: the uncontrolled, invisible, and rapid spread of the virus.

Talking about “paying for stuff”–like an economist who’s also a mom

Sorry I have been pretty AWOL for awhile. It took a nice article in today’s NYTimes and last night’s Saturday Night Live show to spur me to post again. I loved last night’s SNL “cold open” (and Kate McKinnon’s brilliant rendition of Elizabeth Warren talking about how she would pay for “Medicare for All”) for its reference to how moms talk about stuff (vs. dads), and how economists explain things (see back of whiteboard in the skit). And a bonus for me: in this morning’s New York Times, Jim Tankersley quotes me about how little economists *actually* know about what the economic effects of a 6% tax on the highest wealth of the very wealthy would be:

Perhaps the biggest unknown is how the capitalist American economy would function with levels of taxation and spending more comparable to the social democracies of Scandinavia.

“It’s as much an art as a science, trying to figure out the economic effects of policies we haven’t seen before,” said Diane Lim, a former economist for congressional Democrats and senior economist at the White House Council of Economic Advisers, who now works for the Penn Wharton Budget Model. “I’m worried it’s unrealistic. It’s just unknown.”

Jim Tankersley, New York Times, Nov. 3, 2019, Section A, Page 1, “Trillion-Dollar Pledges Cement Democrats’ Bet on Taxing Rich.”

I’ve been working for Penn Wharton Budget Model as a “senior advisor” for a few months now–hoping to better connect their highly sophisticated, academically “rigorous” economic models to real-world policymaking, especially as the presidential campaigns heat up and begin to include (more specific) policy platforms. The policy ideas we’re already hearing about–like Warren’s Medicare for All and the taxes to pay for it–are really big and bold but also huge in terms of economists’ unfamiliarity with them. We will be relying on a lot of economic theory but not a lot of “economic practice” in offering our “expert” perspective. (In other words, we’re not exactly “experts” on this.)

Here is where the “art” within an economic model can actually inform the science, because where we don’t have previous real-world experience with such a policy, we can kind of “make up” and “try on” different kinds of behavior at the individual household and business levels and see how they add up to different outcomes for different types of households and the entire macroeconomy–and we can evaluate how likely the candidates’ tax proposals would actually raise the levels of revenue needed to pay for the candidates’ spending proposals.

I’ll try to keep my blog updated with news of Penn Wharton Budget Model’s analyses on presidential candidate proposals; we are still working on them now. My take here will always have that perspective that comes from my being a mom first (who will talk about the hard choices and realities very openly) and an economist second (who can translate the “econ-speak” of my profession into plain(er) and hopefully more useful English).

The (Desperate) Need for Economists to Consider “Intersectionality” and Our “Multiple Identities” in Our Work

This fascinating article by Duke psychology professor Sarah Gaither in the July 2019 issue of the American Psychological Association came across my radar because it was featured in the Behavioral Science & Policy Association e-newsletter I subscribe to.  As Sarah introduces her work:

“We all have multiple identities — race, gender, age, sexual orientation, occupation — the list goes on and on. However, psychology research has traditionally focused on the effects stemming from one identity (i.e., race OR gender), rather than trying to measure how belonging to multiple groups may actually shift our behavior or even perhaps change our results. The question I asked — does thinking about one’s self from a multifaceted angle shift your flexible thinking?”

Apparently being aware of one’s multiple identities (as opposed to where you might peg into a mono-dimensional category) makes a person more flexible and creative in one’s thinking.  As Sarah explains, it also reminds a person—even a child—that there a “more social categories in their world beyond just race and gender” and encourages the person “to move beyond their default thinking of either/or categories.”

This got me to thinking about one of my complaints about the economics discipline, that we economists are too often focused on “social well-being” as an aggregate concept (as if it could be representative of the well-being of any single one of us), or on the “distributional effects” of economic policies as a mere divvying up of the aggregate economic pie.  In economic analyses, even when we try to look more deeply at how a trend or a policy may affect some people differently from other people, we almost always only consider one dimension/attribute at a time—e.g., the distribution of the income tax burden by categories of household income levels (rich vs. poor), how government deficits and debt affect older people vs. younger people, how trade wars affect one country’s GDP or well-being over another country’s, how immigration policy affects immigrant vs. native-born employment and wages, how labor-market discrimination manifests itself in a gender pay gap (as in, only by gender and only according to pay).  Too often these analyses will only fuel a taking-sides phenomenon as soon as we are led to put ourselves into the “us” or the “them” category in the “us vs. them” dichotomy.  And we’re off to the partisan, polarized, combative, competitive races, where protecting one’s own interests means squashing someone else’s—or at least covering your ears or turning a blind eye to them.

What if economists could help people understand that in our society—and even in our dollar-measured economy—we each hold multiple roles and identities?  I am an Asian (Korean and Chinese) American, a professional economist, a volunteer English teacher, an adjunct professor, a part-time yoga teacher, a taxpayer, a mother of four 20-somethings, a daughter of immigrants, a (newly-remarried) wife, a middle-aged “baby boomer,” a northern Virginian, a native of Michigan, a consumer, a homeowner, a dog owner/lover.  I think about the economy and public policy—and lots of other things that affect my life—from all those perspectives, even more than based on where I got my Ph.D. or what political party I tend to vote for.  Expressing the full intersection of my perspectives, the full complement of identities in me, with the standard economist’s toolkit has always been challenging, and I find myself turning increasingly to qualitative descriptions expressed in words (which might make other economists view me as not as “technical” or “rigorous” as I was in my younger years when I built beautifully mathematical economic models).  Yet people of all types seem to be more likely to listen to and engage with my stories which highlight that I have an identity (or several identities) that maybe they have, too than to pay attention to any quantitative analysis of mine that shows precise debt-to-GDP ratios with calculated effects on aggregate GDP or even the economic income or “well-being” of one’s particular age cohort or income category. Being a mom has always been a more persuasive and compelling identity of mine than being an economist. (As the Wall Street Journal put it 10 years ago in featuring my blog: “How can you quibble with EconomistMom? What would your mother say?”)

Could economic analysis become more “relatable”—more often?  Could we do better at highlighting (and even measuring/quantifying) the commonalities, synergies, and interdependencies among and across people’s many and intersecting identities, so that we could become more likely as a society to pursue economic policies that are truly in our greatest individual and mutual interests?  Could we stop wasting resources and pursuing counter-productive policies with all our rhetoric and YELLING?

There’s plenty of evidence that people are more likely to be prejudiced, discriminatory, or outright hostile and hateful to “other” groups of people the less experience they have interacting with these “other” types of people.  (See factor #9 in this article, for example.)  But that “otherness” is often just the most superficial, obvious characteristic that makes someone appear very different from you (their race, their age, their gender, their social-media-posted politics).  People of different superficial categories can have many common identities as parents, community members, workers in a particular industry or occupation, etc., so maybe it’s not so much that we need more interactions with “other” people (“them”) but that we need to recognize that in the grand scheme of life, those “others” are us–and we are “them.” We are all in this together.

Sarah Gaither concludes her article, pitched mainly to her own psychology discipline, with this (my emphasis added):

“With rises in immigration, increases in interracial marriage, and shifts in language surrounding biracial and transgender populations, it is essential for research to acknowledge that we are all lots of things at the same time. Therefore, my work has both theoretical and practical relevance in highlighting that belonging to multiple groups — and acknowledgement of that membership — not only impacts our behavior and perceptions of others, but it also suggests that that variability that exists both between and within groups may have been overshadowed in research. By considering our multiplicity of belonging that has always existed we can push our fixed thinking about social groups to be more reflective of the flexibility that we all possess. Thus, I argue that as we continue to study behavior within this evolving cultural landscape, we must be aware of how multiple identity mindsets may impact our findings.”

Yes, it’s a far bigger reach to push this perspective of flexibility, intersectionality, and multiple identities onto economists, but it’s something I’d like to try.

Women Work A Lot of Jobs (Not Even Counting At Home)

The latest Bureau of Labor Statistics employment report (for July 2019), which came out on Friday, was kind of “same old, same old”: service-providing jobs (particularly in healthcare) strong, goods-producing jobs weak, the pace of job growth holding steady, the unemployment rate still really low (3.7%), and wages still rising decently. We’re now in the slowest, steadiest economic expansion on record (since June 2009 according to the NBER), and economists are constantly looking for signs we are finally due for a downturn and pondering if the signs we’re used to looking for aren’t so obvious anymore. With our mix of people who are the foundation of our economy, and the things we people (vs. robots and other countries’ people) do, changing all the time, I often wonder how economists can assume that the patterns the U.S. macroeconomy has followed in the past are well-informing our assessments of where we are headed. How can we predict or even recognize what we haven’t really seen before–something that might be called a “new normal” (clearly, an oxymoron).

One way we know that the economy is different from the last expansion, just from living and looking around us, is the changing nature of work. There are more “gig” or independent workers in the economy now compared with the last expansion, facilitated by the development of mobile online labor platforms that have made it possible for people to supplement their incomes from their main or “real” job with the income from being a Lyft or Uber driver, or a Rover dog walker, or a Thumbtack handyman, or a Grubhub restaurant-food deliverer. Technological advancements alone have likely made this economic recovery’s labor market look different from that of the last one–before such “gigs” ever existed.

So I decided to dig a little deeper into the latest jobs report to see what I could see as any evidence that this was not entirely just a “same old, same old” employment report during a typical (but long) economic expansion. It seemed to me that given the rise of alternative forms of work over the past 10 years, we might expect this to show up in the BLS data on workers who hold multiple jobs. An in-depth analysis of the household data on multiple jobholders was published in the BLS’s Monthly Labor Review in April 2015 on data that ran (only) through 2013. The article by Etienne Lale concluded that:

Multiple jobholding declined in the United States during the past two decades [1994-2013]. Data from the Current Population Survey show that the trend reflects a lower propensity to moonlight among single jobholders. Multiple jobholders, by contrast, did not become more likely to return to single jobholding…

In 2013, 6.8 million workers in the United States held more than one job. Twenty years before, the figure was 7.5 million, although the total number of workers with a job was lower by 15.9 million. The multiple-jobholding rate— the proportion of multiple jobholders among all employed workers—rose from 6.2 percent in 1994 to a high of 6.8 percent during the summer of 1995. It has declined steadily since then and was at 5.0 percent by the end of 2013. Inspection of data from the Current Population Survey…reveals that the downward trend holds across various sociodemographic groups of the working-age population (those 16 to 64 years old).

The above analysis had indeed picked up an apparent downward long-term (20-year, 1994-2013) trend in the rate of multiple jobholding among all workers, male and female, and across different age groups and educational attainment levels. The historical time series also revealed the short-term blips up in multiple jobholding that happened during the Great Recession which caused a temporary deviation or at least pause in the downward trend. This reminds us that people who hold multiple jobs often do so because they need the extra income or because one job alone (whether part- or full-time) doesn’t pay enough to pay one’s bills. Was the general downward trend from 1994-2013 due to more people having access to better-paying jobs because of long-term (not just cyclical) improvements in the economy–such that at least in non-recessionary times we should see continued declines in multiple jobholding?

I decided to take a quick spin through the most recent data available (through July 2019), to split the women from the men, and to look at multiple jobholding as a share of some broader populations–not just as % of employed (as BLS calculates for us in their report), but as % of the labor force and as % of overall population. The charts below show (really simple) annual averages of the unadjusted monthly data for all years from 2000 through 2019 (with 2019 showing the average of only the first 7 months in the year, which I can think of reasons why that would bias the number upward as well as downward).

Multiple jobholders as % of employed, annual averages of unadjusted (not seasonally-adjusted) monthly numbers, for employed women (age 16+) and employed men (age 16+), from BLS historical tables in the July 2019 employment report (https://www.bls.gov/cps/cpsatabs.htm).
Multiple jobholders as % of labor force, annual averages of unadjusted (not seasonally-adjusted) monthly numbers, for women (age 16+) in the labor force (i.e., employed or unemployed and looking for work) and men (age 16+) in the labor force. Calculated from BLS historical tables in the July 2019 employment report (https://www.bls.gov/cps/cpsatabs.htm).
Multiple jobholders as % of population, annual averages of unadjusted (not seasonally-adjusted) monthly numbers, for women (age 16+) and men (age 16+). Calculated from BLS historical tables in the July 2019 employment report (https://www.bls.gov/cps/cpsatabs.htm).

You can see why I titled this post “Women Work A Lot of Jobs”–because the difference between the story for men and the story for women is stark. In the 2015 article cited above, it was already apparent that multiple jobholding was more common for women than for men; since the late 1990s the fraction of employed women working multiple jobs has always exceeded–and increasingly so–the fraction of employed men working multiple jobs. The longer-term downward trend in multiple jobholding that first started in the late 1990s for both women and men appears to have bottomed out after the Great Recession and even started to rise again–a new trend that was hard to spot in the prior analysis that went only through 2013. For women in particular, something about the current economic expansion and whatever the “new normal” might be is causing multiple job holding to be a more common state. As of July 2019, 5.7% of employed women (age 16+) and 5.5% of women in the labor force were multiple jobholders–both the highest monthly shares since 2009 (when the overall unemployment rate hit 10%)! And from the last % of population chart, this says that any woman is now as likely to be a multiple jobholder as any man–regardless of whether they are in the labor market or not! (3.16% of total population for women and 3.25% for men as of July 2019; the chart shows only annual averages.) And that’s multiple jobs in the formal labor market–not even counting all the jobs we do at home before and after “work.”

Why is this happening to women–so differently from men? I can make up several different explanations (below), none of which could be confirmed or rejected without further breakdowns (“crosstabs”) of the data–such as women by age, educational attainment, and marital status–and/or (ideally, and) by conducting survey and focus group research on women vs. men who work multiple jobs and asking them “why?”

  • They need multiple jobs to add up to the pay of one job. Women are more likely to earn less than men in even a main, full-time job, holding constant their level of human capital (such as holding a Ph.D. in economics), for all the different reasons that could fill up an entire book: career interruptions having children, having more responsibility in caring for (young or old) family members, being less inclined to ask for raises and promotions, as well as outright (unfair) discrimination.
  • They need multiple jobs because their best single job opportunity would still leave them underemployed. Many women reentering the workforce after raising children may find it hard to get hired into a full-time role after so much time out of the labor market. They may also choose to intentionally signal to employers that they need some flexibility in their schedule to attend to their family when needed. This gives the employer an excuse to underpay and underemploy them. (Women who reveal they are not only mothers but also wives receive the double whammy of signaling that they don’t need a full-time job because they have a spouse to support them. Economists know this result from recent research showing the effects of the birth of a child on a father’s vs. a mother’s earnings.)
  • They choose to work multiple jobs not because of the money but because of how they want to spend their time and use their talents. I recently got remarried, and it kills me when women say “congratulations, you don’t have to work anymore!” (Men wouldn’t dare say that to me.) I’ve always worked multiple jobs even while having one really good full-time job, because I like doing things other than my main job, and sometimes I even get paid a little for those other things (like teaching economics one evening a week and teaching yoga on Saturday mornings). Did you know that women 55 and over are projected to be the single fastest growing segment of the labor force over the next decade? Many of us have high levels of human capital and have had productive careers thus far, but now that the kids are grown, we have more time and energy and wisdom and can actually work harder in the market economy than ever before–but we can also afford to be choosy about how we work, and often a combination of part-time roles that are customized to our skill sets and talents will be more attractive to us than one full-time, cookie-cutter role (which maybe any old man or younger person could fill).

So the phenomenon of holding more than one job is definitely not a thing of the past. It’s also not a thing that necessarily gets worse/more prevalent during recessionary times, given that its rates as a share of whatever denominator you use–employed, labor force, or total population–are as high now as during the Great Recession. It’s also not easy to blanket-characterize as a bad thing (forced by economic hardship) or a good thing (more opportunities to be productive in more ways). I think it’s a great example of something important happening in our economy which to better understand, we need to do more quantitative and qualitative research on–by analyzing more disaggregated (“granular”) data, and by having conversations with more individual people (those grains in granular!) who I know will have stories to tell, because I do, too.

My “Somewhat Irreverent View” on Economics and Economists

The alternative title on the Behavioral Economics course I teach at both George Washington University and Georgetown University has always been “Economics in Theory and Practice: A Somewhat Irreverent View.” I then spend the whole course going through the behavioral insights that in my mind expose key weaknesses in and limitations of traditional Economics—not just in the “purist” economic theories (which seem like “straw men” to me (wink)), but also in the way economists tend to “test” their theories and measure the size, features, and movements in the economy. I was never a student in a behavioral economics course, as I graduated college in 1983, and even in graduate economics programs throughout the 80s, the only class I took that had what is now labeled “behavioral” content was a financial economics course where I read Kahneman and Tversky’s “Prospect Theory” paper (published in 1979). But over the 30+ years of experiencing the “practice” of economics in my mostly non-academic career, I had become familiar with at least the most publicized parts of the behavioral field as they applied to the areas of public policy that I worked in. It was when I began to relate these behavioral concepts to my everyday life that I began to see that what drew me to the behavioral field was that it offered a huge caution to economists about the disconnect between how economics, in theory, is taught to us in school, and how economics should be practiced, in real life, to be most useful. And so, here is an elaboration on my “somewhat irreverent view” on both the discipline of economics and the economist profession. My critique is not really a behavioral economist’s take (because I’m not actually a formally trained behavioral economist, remember) but rather just a living, breathing, practicing economist mom’s reflection or “humble opinion” on how the economics profession has evolved the way it has—and how it will have to change to become more relevant and useful to our society.

First, some “excuses” for/rationalizing about how these faults and flaws in Economics (in theory and practice) came to be:

Economics was invented by a man. Adam Smith is often labeled the “father of economics” and his Wealth of Nations the “bible of capitalism.” He was a man who never married nor had children, and his mother took care of him and his house for free. It’s understandable that a man with little of his own social and family life would develop faith in and see the beauty of the “invisible-hand” forces of a market economy in steering a society’s resources to their highest valued purposes. As economics developed as an academic discipline, it was men in economics who led the way to distinguish economics from other social sciences by making it more quantitative (“mathy”) and rational, less qualitative and social/psychological. Economists became snobs to other social scientists, and Economics really became the discipline that explained the behavior of rational economic man (“homo economicus”)—emphasis on man.
Neoclassical economic theory and empirical science developed before computers. In the beginning, economists had to put pen to paper(!), and the ideas in their heads became the economic theories that served as the starting point in their research. When you start with a strong belief about how the world works, and then walk out into the world looking for evidence to support your belief, you will find it! Even after computers arrived, for decades the ability for economic research to process and analyze lots of data points was very limited. (The model I built and ran for my dissertation research—in the late 1980s—had to run overnight as a “batch job” on a mainframe computer.) Given the limited ability for an economist to both stay at his desk (yes, what he wanted and what made economists different from sociologists and anthropologists) yet somehow study the real-world workings of the economy, economists had to greatly simplify the research process. We were trained in grad school to first write down a theoretical model, then look to official government data (typically very aggregate and low-frequency) to run (usually simple linear) regressions that would “test” the theoretical model. Economists were not inclined to go out and gather the data ourselves (what, talk to people?!), and so we really did not have a lot of real-world, ground-level evidence on what was actually taking place in the economy. Hypothesized and often idiosyncratic (and ideological!) theories became the dog that wagged the “evidence” tail. This is just how we were taught economic research is done.
Economics prided itself in our main “schtick”—the beautiful and simple efficiency of the price system. Unlike other social sciences that were studying lots of different relationships and behaviors that are oh-so messy and too complicated to “model” (or fit into a one-size-fits-all description), economics had this elegant theory of the perfectly-competitive, perfectly-functioning market economy where prices were the wonderfully impersonal way to coordinate the decisions of all individuals in society such that selfish decisions would magically, thankfully lead to allocations of resources that maximized the common, social good. All our theories (as taught from principles courses onward) start with the presumption that the “invisible hand” gets the job done, and only when we have investigated and conclusively found a potential “market failure” (or demonstrated and convinced the majority of citizens of an egregious inequity) is there possibly a role for government to help get the economy and society to get to a better outcome than the free market produces.

Those are some historical reasons why Economics has become what it is. If you’re not already totally turned off by and wanting to tune out economists, I appeal to you to consider that many economists (including myself) went into economics not to be type cast into the caricatured mold described above (to become a shining example of “homo economicus”!)—but because we wanted to study society and social behavior (yes, economics is still labeled a social science) while using more analytical tools and skills. It doesn’t mean we economists all lack social or “people skills.” It doesn’t mean we are all bad at communicating economic concepts to ordinary people. And it doesn’t mean economists (all of us) can’t do better.

For economists to “do better” as a profession and to better understand and be better understood by real people, I have a few suggested caution flags/warning labels/motivational posters(?) to place around you as you do your work:

What you can see/measure is not all that there is. Nor all that matters. Stop assuming that measurable market outcomes are all that we need to pay attention to in our society and economy to understand if we’re doing our best and if there is a role for better (and more informed) public policies or better (and more informed) business and household behaviors. (Big “hat tip” or rather “hug” to Nancy Rose of MIT who called this “all you see is all there is” attitude of many economic researchers the “economic hubris” of our profession at an Aspen Institute economic meeting earlier this week.)
• People’s “objective function” (what they want to do/achieve) is not always—not usually even—objective. Or “well behaved” as the graduate textbooks often describe the utility functions characterizing people’s preferences. What does a “well behaved” utility maximization problem look like? Just some features:

–a utility function and budget constraint defined over continuous (not discrete) quantities and combinations of goods and services (or whatever quantifiable thing one cares about);
–the utility function and budget constraint apply to the entire universe of feasible options—and there’s nothing special about your current position/starting point (what economists like to label the “initial endowment”);
–starting assumption is that what contributes to individual utility is only individual consumption and that people are selfish and make individual decisions for individual gain;
–the utility function and budget constraint apply to a long, multiperiod (ultimately lifetime) time horizon rather than sequential, short horizons), the components of which and market prices on which are known and accounted for with perfect certainty.

In behavioral economics we spend a lot of time reading literature—and just reflecting on our own common sense—about why these theoretical assumptions about how people make economic decisions are unrealistic. Breaking out of the theoretical straitjacket and relaxing these assumptions is really a necessary first step before an economist can claim their analysis is real-world useful to policymaking.

Traditional economic statistics provide only a (necessarily) limited view of the economy. Official government statistics on the economy are limited in detail because the budgets made available to the government statistical agencies (via Congress) have been very limited. The data is thus necessarily low frequency and highly aggregated (and not just for privacy reasons). They tell us about economy aggregates or averages, but not enough detail closer to the individual household or business level to help us understand what drives the movements in these aggregates. The data also come with a long lag/wait. Even at whatever level of disaggregation the data are available, the measures are based on market outcomes (hours actually worked and wages actually earned, number of employees actually employed, levels of output actually produced, etc.)—i.e., the market equilibria that represent the (mere) intersection of supply and demand—and we have no ability to “see” the entire supply side (supply “curve”) and entire demand side (demand “curve”) in each market that interacted to produce those observable market outcomes. It’s as if we are looking at the economy through a really narrow viewfinder that takes only static snapshots of things once they are neatly in place (posing!), rather than a panoramic video camera that is constantly recording the movements in and out of and back into equilibrium.
The economist’s assumption/presumption that maximizing market income is a close proxy for maximizing utility (or happiness more broadly) leads to a poor understanding of human decision-making. The real-world choices people make are based on much wider considerations which just happen to have economic implications. If we start our economic analysis presuming people are behaving to maximize market income when many of them are not, we cannot possibly come up with good policy prescriptions, even as we claim we are doing “evidence-based” policymaking.
• Social welfare economics needs to be more than about how to “divide up the pie”; economists should recognize that how well people live and work together jointly determines how large the total pie can be. The economics profession doesn’t seem to study and measure how collaborative and cooperative relationships among people (or organizations or sectors or countries) can make overall productivity and well-being greater. Organizational behavior is something taught in business schools to help businesses organize and manage their staff to maximize their productivity and success. But the proven concept that the quality of interpersonal relationships improves worker productivity at the firm level surely applies to higher-order relationships as well. “Resource allocation” as a label to a central problem to solve in economics leads to a notion or tone of “dividing up” more than “joining forces”—as if the stock of resources is fixed. The apolitical emphasis in any economic “distributional analysis” on different ways that alternative policies divide the pie up may inadvertently worsen the already divisive and polarized social climate (the “us versus them” mentality) which has been so counterproductive to being the best we can be.
• All of the above about the origins, foundations, and various assumptions in our discipline suggests that traditional economics implicitly argues that men are superior to women. Men are more likely to conform to the caricature of “economic man”/homo economicus—and therefore to behave in ways that lead to higher/better market-based outcomes. And men’s superior market outcomes are perceived by society as deservedly so, because (as Katrine Marçal’s book “Who Cooked Adam Smith’s Dinner?” so well and cynically argues): they work harder (longer hours), they are more efficient at linear processing (single-pointed focus on tasks), they know how to seek and achieve their highest (market) valued uses of their time, they have more competitive drive, they don’t let emotions or soft feelings get in the way of their productivity at work, etc.

When economists choose to study the economy through the narrow lens of traditional economic theory, they end up viewing, assessing, and analyzing the economy in, frankly, sexist ways. It is just how our science was built and how it is still (for the most part) taught. It has led to a male-dominated profession and one that tends to conclude that men are deservedly the most successful and productive participants in our economy. This is just from my own (somewhat irreverent?) point of view. I do not at all hate my profession nor my many, many male colleagues. I have just gotten remarried, to another Ph.D. economist, who, like my first husband, earns far more than me in market income—and I believe deservedly so. But I believe the current state of our male-dominated and male-biased profession is preventing our profession from being the best we can be and contributing the most wisdom that we likely have to the broader social good.

Here are some of my ideas on how we economists, as a profession trained in our discipline, can change and do better:

• Get more real. Stop the naïve thinking about how the economy works and how economic decisions are made. Use common sense and relate it to your own personal life and ask if your assumptions in your own analysis pass your own personal “smell test.” My dissertation on “lifetime tax incidence” relied on a general-equilibrium model of tax policy that assumed people maximized lifetime utility subject to a lifetime budget constraint, with perfect knowledge of future labor income and market prices, and would respond to changes in a marginal tax rate by changing their labor supply and savings behavior and readjusting choices over the rest of their lifetime. Over the years I kept adjusting the degree of behavioral response in the model downward. I also realized that I myself: (i) was not sure what my marginal tax rate would be in the current tax year that I wouldn’t be filing a tax return for until next April, and (ii) could not just walk into my employer and explain that my marginal tax rate was going up and therefore I would like to work some odd fraction of my weekly hours less each week. (Right, I am very much not like Greg Mankiw who would surely reduce the “supply of Mankiw” in response but the link to that quip I cannot find right now.)
• Get more granular and qualitative. In gathering evidence, don’t just look or wait for the official government or other publicly-available data to come out on your topic of interest, go out and find more of exactly what you need for your analysis yourself. These days we have big data analytical tools such as Google Trends (which draw from Google search data) and it’s relatively easy to conduct one’s own online surveys—as well as to pick up the phone or laptop to do interviews with key informants and influencers on your topic. Combining quantitative analysis of official government statistics with online search data, surveys and qualitative methods to dive deeper into not just what choices are made and outcomes achieved, but the “how” and the “why” about those decision contexts and processes, will help economists better understand the economy from the bottom (or ground-level) up. (Remember, the macroeconomy is the adding up and interacting of many, many individual household- and business-level decisions.)
• Get more women. I mean in top economist roles! (Yes, this sounds self-serving.) Probably the most reliable way to encourage more female participation in our profession is to provide role models and mentors who are successful and inspiring women in economics. (Alice Rivlin was mine.) There is an unfortunate but common phenomenon in general organizational settings where it is difficult to get promoted in an organization where most people above you in the hierarchy look different from you (or rather you look different from them). It is not because these old white guys are intentionally biased or bigoted (not always at least), but because these leaders have a natural affinity toward those junior to them who remind them of younger versions of themselves. But the main reason why the economics profession needs more women is not for more balanced representation on a pure counting standpoint, but because women economists do tend to understand and practice economics differently from men. My critiques of our discipline’s theory and practice are more commonly recognized by women than men, because women are (and yes, I’m broadly generalizing): more maternal in instinct (concerned for the greater good and future generations), collaborative more than competitive, good at multi-tasking and considering several goals and factors at once, and have more personal experience with real-world tradeoffs that real people face daily—not all of which are seen in economic data.
• Get more personal. Dig deeper into what matters to people and what motivates and goes into their everyday decisions. Because of our own personal experiences, women may know better what to ask people about their circumstances and thought processes, and are more interested in asking (even a stranger) “how happy are you?” and “what makes you happy?” The basic concept of maximizing happiness subject to all kinds of social, familial, time, and (yes) budget/financial constraints still applies and is useful to remind policymakers of the tradeoffs that every person and society as a whole must make—that there are never really “free lunches” but rather costs that are not always visible or measureable.
• Get more helpful with public policy. Stop assuming that people will react to policy in the “rational man” way and recognize that the way a policy is designed and presented/explained to people can actually teach people how to make decisions that are best for them, whatever their objective function contains. Design policy with input/feedback from real people (via focus groups and pilot projects/test cases), not just based on what policy experts “know” (what “the literature says”) about what the effects of the policy will/should be. Think of this as analogous to how a consumer product manufacturer would develop and roll out new products to consumers to make sure it will do well in the market. (They are motivated by market share and profit maximization; public policy economists should be motivated by social impact and public net-benefit maximization.)

I hope this piece has been provocative but also gets people in our profession—male and female—to think about how we can remodel and refresh the way we do our work. Our discipline can have so much more positive impact on society if we stretch ourselves beyond how we were formally trained in grad school and how we have been stereotyped and typecast so far. We need to use a wider variety of research methods that come from other social science disciplines and remember that we are supposed to be a social science. We need to talk more with others and collaborate more across disciplines, organizations, and policy areas. We need to not just do our economic analyses but do better at communicating insights of our analyses to policymakers and the general public—because work that doesn’t engage or isn’t understood cannot have impact. And we need to introduce economics in this more “woke” and human form to students who will be inspired to join our profession.

It’s Mother’s Day, and I’m back!

Mother’s Day 2019: I started a blog on this site on Mother’s Day, 2008 (when my four kids were ages 9 1/2 to 16)–when I was working for the Concord Coalition–and wrote nearly every day for nearly 5 years (until I left for the Pew Charitable Trusts in early 2013). I’m back after a 6 1/2 year hiatus, my kids now ages 20 1/2 to 27. I’m (still) a Ph.D. economist living and working in the DC Metro Area. After a 20+ year first marriage (to another economist), I decided I wanted a divorce. A decade later I am getting remarried (and to another economist!)–something I never would have predicted would have happened if you had asked me 5-10 years ago. But I have learned a lot of things over my nearly 30 years of motherhood–more than I have learned over my 35 years of working as an economist. I like to think that the part of me that is “just a mom” gives me a unique perspective on the economy, because I am constantly testing the wisdom of economic theories and the usefulness of the economist’s standard analytical toolbox against what I see and experience in real life. Most of what I will do here is make observations and reflect on my own experiences, while also relating them to the various issues that economists and other social scientists study. I hope my musings will resonate with some of you–whether because of the economist in me or (maybe more likely) because of the mom in me. Thanks for reading, and Happy Mother’s Day to all fellow moms out there. (Please follow me on Twitter to keep up with my new posts here.)