Category Archives: wealth

State of economy for less-educated young people compounds growing Opportunity Gap

Pell City 2007 HS graduation; Flick/kwsanders

Pell City 2007 HS graduation; Flick/kwsanders

While parts of the economy have rebounded since the Great Recession of 2008, the effects have been much worse for the poor, and especially the less-educated young Americans, and those not fortunate enough to graduate from college.

Since 2008, the housing market has started to bounce back.

The stock market, for those fortunate enough to have net savings rather than a negative net worth has more than recovered its recessionary losses (pictured is the S&P500 index).

Recovery in S&P500 since 2009 recession

The economy has created 6.15 million jobs from March 2010 through April 2013 (based on provisional numbers for March/April 2013), enough to lower unemployment but only through many people giving up on finding jobs.  The  percentage of Americans employed in the population hasn’t budged over the last 3.5 years and remains fixed at between 58% and 59%. Larry Summers thinks that the numbers of long-term unemployed is the biggest problem facing this country and is at historically unprecedented in the period since the Great Recession of the 1920s and 1930s.

Put this together with the data that David Leonardt released (“The Idled Young Americans“) showing that the impact has disproportionately fallen on young folks.  Moreover, levels of employment among 16-24 year olds, even as recent as May 2013 remain stubbornly at 45%, at levels not seen in the US since the early 1960s.

Our own research on the fact that children born to less educated families are facing a growing opportunity gap.  American young adults from the bottom socioeconomic quarter are graduating from high school or dropping out with less of the hard academic skills or soft non-cognitive skills necessary for life success.  [We find significantly growing gaps between children from the top third or quarter of socioeconomic families and the bottom third or quarter on measures as diverse as involvement in extra-curriculars, involvement in sports, K-12 test scores, obesity, social trust, involvement with religion, social connectedness, volunteering, college attendance, and college completion.]

And the intersection of these two trends — consequences of the current lackluster economy being borne by the young adults and the growing opportunity gap — means that these gaps are borne disproportionately by less educated young adults.

For example, if one looks at employment to population ratios for 25-34 year olds in 2012, it was only 69.8% for those with a high-school degree (but no college), whereas it was 84.4% for those with 4-year college degrees or more.  Another way of putting this is that only 16% of college-educated 25-34 year olds were out of the labor market versus 30% of those with only a high school degree.

And if that were not enough, there is growing body of literature suggesting that experiences of unemployment or involuntarily being terminated from jobs create long-term scarring effects both on the lifetime earnings of these young people, but also their civic and social connectedness throughout their lives.  [See for example Davis/von Wachter or Gregg/Tominey or Brand/Burgard.]

[There is also unpublished data on this scarring effect in: Laurence, James, and Chaeyoon Lim. “The Long-Term and Deepening Scars of Job  Displacement on Civic Participation over the Life-course: A Cross-National Comparative  Study between the UK and the US.”]

We are brewing a recipe for long-term adverse consequences for these young Americans, especially the less educated ones, and our government ought to be POUND-wise, even if it is “PENNY-foolish” in the eyes of others and invest in jobs for these young 16-25 year olds to avoid the much longer long-term adverse effects.

Advertisements

Social capital and disaster recovery

I recently heard a talk by Daniel Aldrich (Purdue).  He has been pursuing a handful of projects over the last 5-6 years looking at how local social capital (at the neighborhood or zip code or prefecture) predicts more resilient disaster recovery. Aldrich points out that people are far more likely to be hit by a disaster in their life than be the victim of a terrorist attack and asserts that the number of disasters is increasing in recent years.

Aldrich has studied 4 different disasters (1923 Tokyo earthquake; 1995 Kobe earthquake; 2005 Katrina disaster; 2004 Indian Ocean Tsunami).  I think he is currently doing some work on the recovery from the recent Japanese tsunami (early thoughts by him here).  Aldrich measures social capital with local measures like: voting and participation in rallies (1923 Tokyo); non-profit organizations per capita (1995 Kobe); number of funerals attended in past year (Indian Tsunami); and voter turnout (Katrina). His outcome variables for economic recovery are things like population growth (1923 Tokyo; Kobe) in an area or amount of aid received (Indian Tsunami) or ability to keep FEMA trailers out of an area (Katrina).  [It wasn’t clear to me that this last measure is a measure of disaster recovery as much as NIMBY-ism, a topic that Aldrich has also written about.]

At one level, Aldrich’s findings are not surprising since places with low social capital tend to wait for the state to repair devastation and places with high social capital take more immediate self-action to repair.  This is reflected in Emily Chamlee-Wright’s recent book “The Cultural and Political Economy of Recovery: Social Learning in a post-disaster environment” and Robert Putnam observed this about Italian recovery from earthquakes: in places with high social capital one was unaware there had been an earthquake there several years later, whereas in low social capital places, the results of an earthquake were apparent 30-40 years later and residents were still blaming government for not adequately responding.

Aldrich’s work is very interesting and will appear next year as a U. Chicago press book “Building Resilience: Social Capital in Post-Disaster Recovery”.  [Brief presentation of his work here.] I would find his work even more interesting if he examined whether it is only the more political forms of social capital (like voting or protesting) that help in disaster recovery or whether it extends to “schmoozing” type variables at well (e.g., number of close friends, or knowing neighbors).   He might also be able to use volunteering data gathered by the CPS since 2002 to test that as a predictor or use datasets gathered by Rick Weil on social capital in New Orleans.  He also talks about the various types of social capital (bridging, bonding, linking) but his work doesn’t help sort out whether one type of social capital is more important than another for disaster recovery.  Also, given that social capital always rises after disasters and then most typically rapidly tails off, it would be useful if he tracked local social capital by neighborhood after a disaster since the shape of this drop-off in social capital need not be the same across communities; one might have more of a sustained burst of social capital than another.

His case study work does suggest that social capital is more important in disaster recovery than physical capital, physical infrastructure, or financial capital and more important than the conventional explanations that experts claim predict disaster recovery: amount of aid (positively predicting recovery); governance (stronger governance increases recovery); amount of devastation (less predicts greater recovery); wealth (positively predicting recovery); and population density (negatively predicting recovery).  He controls for these factors in his model and finds consistent and robust effects of social capital on post-disaster recovery.

Aldrich’s colleagues have also done some experiments of paying people to participate in focus groups, of giving people local “scrip” if they volunteer (which can be spent locally at farmers’ markets) and found that these built social capital and helped partially “inoculate” communities from the effects of disasters.  He didn’t present in any detail the methods or the results of these mini experiments.  He also recommends that post-disaster if we need to move survivors, we do them conscious of the clustering in their social networks,  so that they minimize the hit they take to their social capital.

Against this good news for social capital, there are three studies that find negative findings in the short-term, after disasters on outcomes like stress, health, etc. [I should note that Aldrich in his book addresses some negative outcomes of social capital in recoveries, for example, groups blocking certain castes from getting aid, or the Japanese promoting vicious attacks on Koreans after the 1923 Tokyo earthquake or ostracizing mercury victims in Minamata Bay from the late 1950s onward.] Basically the story of these other scholars is either that greater commitment to a community or greater social ties lead to worse ST outcomes, either because you feel it is really costly to leave or you are besieged by social and financial requests from other victims, which puts great strain on you unless you are wealthy.  The Rhodes et. al paper finds over longer term, people with more social capital do better, so this is a short-term finding only.  Weil and Lee, to my knowledge, have not looked at longer-term impacts.

See Jean Rhodes, Christian Chan, Christina Paxson, Cecelia Rouse, Mary C. Waters and Elizabeth Fussell. (2010) “The Impact of Hurricane Katrina on the Mental and Physical Health of Low-Income Parents in New Orleans.” American Journal of Orthopsychiatry 80(2):233-243. Not sure that their longer-term findings have been published.  See also manuscript from their project by Lowe, S. R., Chan, C. S., & Rhodes, J. E. “Pre-disaster social support protects against psychological distress: A longitudinal analysis of Hurricane Katrina survivors.”

Community Attachment and Negative Affective States in the Context of the BP Deepwater Horizon Disaster” by Matthew Lee and Troy Blanchard (LSU @ Baton Rouge) American Behavioral Scientist 55(12).  October 3, 2011

Weil, Frederick, Shihadeh, Edward, and Lee, Matthew. “The Burdens of Social Capital: How Socially-Involved People Dealt with Stress after Hurricane Katrina” Paper presented at the annual meeting of the American Sociological Association, 2006.

See also earlier blog post on disaster recovery from 2011 Japanese tsunami.

Americans far less trusting than per capita wealth would predict

Catherine Rampell has a couple of interesting charts describing the relationship of trust, income and equality (among countries).

The US is 10th most trusting of the 30 countries examined (with 48.7% saying that others can generally be trusted).  Norway and Denmark are the most trying with almost 90% saying that others can be trusted; Turkey and Mexico are the least trusting with only 20-25% of residents saying that others can be trusted.

Since wealthy countries generally are more trusting, it’s surprising that America is only ranked 10th.


The U.S. is the country in the top center of the graph, way above the black regression line with median equivalized income of $27,000 per person (y-axis) but trust just below 50% (x-axis).  If one moved the US over to the right until it hit the regression line it would have social trust levels of 90%, like Norway.  [better picture here.]

The reason for America’s low level of trust can be seen by looking at the levels of inequality in the US.  More equal countries tend to have higher levels of trust, and viewed through this lens, Americans are just as trusting as one would expect, down around the levels of trust and inequality of a Portugal or a Poland, which while far poorer than the US has similar levels of equality to the US.

The implicit conclusion seems to be that income equality trumps wealth when it comes to trust, which makes some sense as it may engender a “we’re-all-in-this-together” esprit de corps.  But the regression line, if anything, seems to better fit countries for the graph of trust against income per person than the level of trust maps onto levels of equality.  And notably, Denmark and Norway, have higher levels of trust than one would expect from their level of equality.

Food for thought…

See NY Times Economix, “Trust Me, We’re Rich” (Catherine Rampell, 4/18/11)

Money can’t buy you love, but can buy you happiness (II)

Betsey Stevenson and Justin Wolfers in a data rich paper conclude three things:

a) the rich are happier;

(b) rich countries are happier;

(c) economic growth is associated with greater happiness for their citizens; and

(d) they find little evidence for the “relative income hypothesis” (that happiness depends more on one’s income relative to others in one’s country or community than it does on absolute levels of income).

Justin Wolfers is blogging about the paper at Freakonomics blog. There are to be several posts, but this is the first post. The paper is also summarized in today’s New York Times, featuring a nice graphic, The authors also discussed the research on CNBC (4/16/08).

The paper by Betsey Stevenson and Justin Wolfers (both at Penn’s Wharton School) has the rather academic title of “Economic Growth and Subjective Well-being: Regressing the Easterlin Paradox

Earlier post on this subject available here discussing paper by Angus Deaton on this topic; Deaton’s conclusions were partially the same but he found a cut-off point beyond which economic growth did not lead to increases in happiness, perhaps because of the destabilizing impact of the growth.

Money can’t buy you love, but can it buy you happiness?

The common wisdom is that being wealthier as a country (beyond some minimal threshold) doesn’t make its residents happier.  [It’s a seeming paradox epnonymously named after Richard Easterlin.]

Angus Deaton’s recent study (“Income, Aging, Health and Wellbeing Around the World”, 2007) claims that this is incorrect; he finds that national level income does make you happier.  (Deaton thinks that the Easterlin paradox resulted from an overly high influence of former Soviet Union and Eastern European countries analyzed in a World Values Survey that have, post Communism, much lower life satisfaction than would be expected at their levels of income, but are less typical of the overall pattern.)

There is still some disagreement about how much this overturns the Easterlin paradox.  Deaton, and the Gallup World survey use a “ladder” question to evaluate life-satisfaction.  The question is of the form: ‘Imagine an eleven-rung ladder where the bottom (0) represents “the worst possible life for you” and the top (10) represents “the best possible life for you. On which step of the ladder do you feel you personally stand at the present time?”   Such ladder questions have tended to be more related to national income levels than the standard ‘subjective wellbeing question’ of the form:  “All things considered, how satisfied are you with your life as a whole nowadays? Please answer using a scale where 1 means extremely dissatisfied and 10 means extremely satisfied.” (This type of question can be asked with different number of points on the scale or labels for the points)

Moreover, Deaton does find that while ‘ladder-type’ wellbeing rises with national income, there is a negative relationship between economic growth and such wellbeing.  It is possible that the process of economic growth is de-stabilizing, anxiety-ridden and enervating, in a way that saps wellbeing in the short-term.

In any event, it should be noted, that at the individual-level it is RELATIVE income (being wealthier than one’s neighbors) that makes you happier, not absolute income.  So if you had the choice of living in a poorer neighborhood where you were wealthier than your neighbors, or living in a wealthy neighborhood where you were poorer than your neighbors, the former is the better strategy for being happy. (See Luttmer, Erzo. F. P. (2005). Neighbors As Negatives: Relative Earnings and Well-Being.)

To read the Deaton paper, see: “Income, Aging, Health and Wellbeing Around the World: Evidence from the Gallup World Poll” (NBER paper, Aug. 2007 by Angus Deaton)
Summary: During 2006, the Gallup Organization conducted a World Poll that used an identical questionnaire for national samples of adults from 132 countries.  I analyze the data on life satisfaction (happiness) and on health satisfaction and look at their relationships with national income, age, and life-expectancy.  Average happiness is strongly related to per capita national income; each doubling of income is associated with a near one point increase in life satisfaction on a scale from 0 to 10.  Unlike most previous findings, the effect holds across the range of international incomes; if anything, it is slightly stronger among rich countries.  Conditional on national income, recent economic growth makes people unhappier, improvements in life-expectancy make them happier, but life-expectancy itself has little effect. Age has an internationally inconsistent relationship with happiness.  National income moderates the effects of aging on self-reported health, and the decline in health satisfaction and rise in disability with age are much stronger in poor countries than in rich countries.  In line with earlier findings, people in much of Eastern Europe and in the countries of the former Soviet Union are particularly unhappy and particularly dissatisfied with their health, and older people in those countries are much less satisfied with their lives and with their health than are younger people.  HIV prevalence in Africa has little effect on Africans’ life or health satisfaction; the fraction of Kenyans who are satisfied with their personal health is the same as the fraction of Britons and higher than the fraction of Americans.  The US ranks 81st out of 115 countries in the fraction of people who have confidence in their healthcare system, and has a lower score than countries such as India, Iran, Malawi, or Sierra Leone.  While the strong relationship between life-satisfaction and income gives some credence to the measures, as do the low levels of life and health satisfaction in Eastern Europe and the countries of the former Soviet Union, the lack of correlations between life and health satisfaction and health measures shows that happiness (or self-reported health) measures cannot be regarded as useful summary indicators of human welfare in international comparisons.

Social Capital, education and other intangible capital 77% of world’s wealth

A team headed by World Bank economist Kirk Hamilton reported in Where Is The Weath of Nations?: Measuring Capital for the XXI Century that “intangible capital” represented 77% of the world’s total wealth and the largest share of wealth in virtually all countries — in developing countries it averages about 60% of wealth and in developed countries it averages 80% of wealth.  (Presumably these high percentages — somewhere in 80s or even 90s would apply across U.S. states, although their report only looks at the country level.)

To Hamilton’s team, intangible capital included raw labor, human capital (the stock of human skills and know-how), social capital and societal trust, and the quality of social institutions.  Under social institutions, they included governance elements that “boost the productivity of the economy. For example, if an economy has a very efficient judicial system, clear property rights, and an effective government, the result will be a higher total wealth and thus an increase in the intangible capital residual.”  (What the report rarely acknowledges is that social capital is a strong determinant in whether the judicial system or institutions of government operate efficiently, in whether there is less corruption, etc. )

Much more of the value of intangible capital was in the institutions and trust than it was in human capital (education).  Hamilton estimated that education accounted for roughly only 1/3 (36%) of the value of intangible capital, leaving roughly two-thirds for social capital and the value of institutions.

By rarely acknowledging the impact, they effectively underreport on the important role of social capital since they don’t count social capital under the institutional piece. Nonetheless, they  still report that: ” In the richest countries it is clear that technological change, institutional innovation, learning by doing, and social capital, to name a few factors, are fundamental drivers of the economy.” (p. xvii) 

One of the rare places where the talk about the link between social capital and governmental institutions is on p. 93 (Table 7.2) where they acknowledge the strong correlation between social capital and performance of governmental institutions.

You can read an interview of Ronald Bailey with Kirk Hamilton in Reason magazine (August 2007) here.

Complete report Where Is The Wealth of Nations?: Measuring Capital for the 21st century available here.