Category: Data Source

The economic costs of depression amongst the young

by  Tyler Cowen in

A growing body of evidence indicates that poor health early in life can leave lasting scars on adult health and economic outcomes. While much of this literature focuses on childhood experiences, mechanisms generating these lasting effects – recurrence of illness and interruption of human capital accumulation – are not limited to childhood. In this study, we examine how an episode of depression experienced in early adulthood affects subsequent labor market outcomes. We find that, at age 50, people who had met diagnostic criteria for depression when surveyed at ages 27-35 earn 10% lower hourly wages (conditional on occupation) and work 120-180 fewer hours annually, together generating 24% lower annual wage incomes. A portion of this income penalty (21-39%) occurs because depression is often a chronic condition, recurring later in life. But a substantial share (25-55%) occurs because depression in early adulthood disrupts human capital accumulation, by reducing work experience and by influencing selection into occupations with skill distributions that offer lower potential for wage growth. These lingering effects of early depression reinforce the importance of early and multifaceted intervention to address depression and its follow-on effects in the workplace.

That is from a new NBER working paper by Buyi Wang, Richard G. Frank, and Sherry A. Glied.

Is publication bias worse in economics?

by  Tyler Cowen in

Publication selection bias undermines the systematic accumulation of evidence. To assess the extent of this problem, we survey over 26,000 meta-analyses containing more than 800,000 effect size estimates from medicine, economics, and psychology. Our results indicate that meta-analyses in economics are the most severely contaminated by publication selection bias, closely followed by meta-analyses in psychology, whereas meta-analyses in medicine are contaminated the least. The median probability of the presence of an effect in economics decreased from 99.9% to 29.7% after adjusting for publication selection bias. This reduction was slightly lower in psychology (98.9% −→55.7%) and considerably lower in medicine (38.0% −→ 27.5%). The high prevalence of publication selection bias underscores the importance of adopting better research practices such as preregistration and registered reports.

Here is the full article by František Bartoš, et.al, via Paul Blossom.

Papua New Guinea no fact yet of the day

by  Tyler Cowen in

Papua New Guinea’s prime minister says he does not know the exact size of his country’s population after a report suggested that the number of people living in the Pacific nation could be almost twice the official figure.

A new study compiled by the UN Population Fund has implied that Papua New Guinea’s population may have ballooned to 17mn compared with the official figure of 9.4mn, according to a report in The Australian newspaper. James Marape, who was re-elected as Papua New Guinean prime minister in August, told the newspaper he believed that the population could be 11mn but admitted he might be wrong.

The lack of clarity around the size of the country’s population has serious implications for its economic status and raises doubts over its ability to provide services to its people.

If the study, which has not been published, is correct then it would almost halve the country’s gross domestic per capita levels from about 4,000 kina ($1,136), according to Maholopa Laveil, a fellow at the Lowy Institute think-tank and an economics lecturer.

Of course I am rooting for the higher number of people.  Here is the full FT story.

Lookism is everywhere, and mostly undetected

by  Tyler Cowen in

…some types of discrimination may be less apparent than others. Across seven studies (N=3,486, five preregistered), we find that attractiveness discrimination often goes undetected compared to more prototypical types of discrimination (i.e., gender and race discrimination). This blind spot does not emerge because people perceive attractiveness discrimination to be unproblematic or desirable. Rather, our findings suggest that people’s ability to detect discrimination is bounded. People only focus on a few salient dimensions, such as gender and race, when scrutinizing decision outcomes (e.g., hiring or sentencing decisions) for bias. Consistent with this account, two interventions that increased the salience of attractiveness increased the detection of attractiveness discrimination, but also decreased the detection of gender and race discrimination.

That is from a new paper by Bastian Jaeger, Gabriele Paolacci, and Johannes Boegershausen.  Via someone, I forget whom to thank, but recall they were good-looking!

Cognitive Behavioral Therapy among Ghana’s Rural Poor

by  Tyler Cowen in

We study the impact of group-based cognitive behavioral therapy (CBT) for individuals selected from the general population of poor households in rural Ghana (N = 7,227). Results from one to three months after the program show strong impacts on mental and perceived physical health, cognitive and socioemotional skills, and economic self-perceptions. These effects hold regardless of baseline mental distress. We argue that this is because CBT can improve well-being for a general population of poor individuals through two pathways: reducing vulnerability to deteriorating mental health and directly increasing cognitive capacity and socioemotional skills.

That is by Nathan Barker, Gharad Bryan, Dean Karlan, Angela Ofori-Atta and Christopher Udry, here is the AER Insights link.  Here are other versions.

Productivity in the two Irelands (extrapolate this)

by  Tyler Cowen in

Of the 17 sectors for which we have comparable data, productivity levels in Ireland noticeably exceed those of Northern Ireland in 14 sectors, with particularly large gaps in Administrative and support services activities;
Financial and insurance activities; Legal and accounting activities etc; and Scientific research and development. Northern Ireland has an advantage in the two sectors of Electricity and gas supply and Construction.

Productivity levels in the two regions were broadly equivalent in 2000. Over the period 2001 to 2020, productivity levels in Ireland have trended slightly upwards, while in Northern Ireland productivity levels have been trending downwards. By 2020, productivity per worker was approximately 40 per cent higher in Ireland compared to Northern Ireland.

That is from a new study by Adele Bergin and Seamus McGuinness, via Charles Klingman.  Of the seventeen sectors for which there are comparable data: ” Northern Ireland has an advantage in the two sectors of Electricity and gas supply and Construction.”  And from commentator David Jordan note this: “As the authors conclude, the failure of Northern Ireland’s economy to respond positively to increases in education, investment, and export intensity, suggests that other barriers to productivity growth exist.”

The cost of regulatory compliance in the U.S.

by  Tyler Cowen in

We quantify firms’ compliance costs of regulation from 2002 to 2014 in terms of their labor input expenditure to comply with government rules, a primary component of regulatory compliance spending for large portions of the U.S. economy. Detailed establishment-level occupation data, in combination with occupation-specific task information, allow us to recover the share of an establishment’s wage bill owing to employees engaged in regulatory compliance. Regulatory costs account on average for 1.34 percent of the total wage bill of a firm, but vary substantially across and within industries, and have increased over time. We investigate the returns to scale in regulatory compliance and find an inverted-U shape, with the percentage regulatory spending peaking for an establishment size of around 500 employees. Finally, we develop an instrumental variable methodology for decoupling the role of regulatory requirements from that of enforcement in driving firms’ compliance costs.

That is from a new NBER working paper from Francesco Trebbi and Miao Ben Zhang.  Keep in mind those are the costs of compliance narrowly interpreted, not the costs of regulation overall.  And they do not consider the longer-term innovation costs from “having to turn the firm over to the lawyers.”

Child care sentences to ponder

by  Tyler Cowen in

There is to date little or no evidence of beneficial effects of longer parental leave (or fathers’ quotas) on maternal participation and earnings. In most cases longer leave delays mothers’ return to work, without long-lasting consequences on their careers. More generous childcare funding instead encourages female participation whenever subsidized childcare replaces maternal childcare.

That is from a new NBER working paper by Stefania Albanesi, Claudia Olivetti, and Barbara Petrongolo.  Drawn from data across 24 countries.

Detective Wanted

by  Alex Tabarrok in

Nat Friedman is seeking a full-time solo technical leader to go on a modern day Indiana Jones-style treasure hunt. You will be responsible for starting and running a crowdsourced effort to crack an archaeological puzzle of great historical significance. Success would be global news, could rewrite large chunks of history, and is guaranteed to be a story you will tell your grandchildren.

This is a full-time position for a 3-6 month period (which is about how long we think it will take to crack the puzzle, or at least to set it on a course to be solved). Pay range is $120-250k/yr. Think of this as an adventurous interlude between your more lucrative commercial gigs.

You will act as a mini-CTO, making appropriate technical decisions, staying responsive, and allocating time and resources effectively. This role will require highly effective communication, the ability to make complex code understandable, the ability to write clear technical documentation, the ability to foster and grow an online community, coupled with solid software engineering knowledge.

The ideal candidate will have experience in creating, managing, maintaining, and contributing to open source software projects. A background in working with custom software and data pipelines for scientific research is desirable. Comfort with PyTorch, C++, and OpenCV is a big plus.

More here.

What determines graduate admissions for economics?

by  Tyler Cowen in

We introduce a model of the admissions process based upon standard agency theory and explore its implications with economics PhD admissions data from 2013-2019. We show that a subjective score that aggregates subjective ratings and recommendation letter features plays a more important role in determining admissions than an objective score based upon graduate record exam (GRE) scores. Subjective evaluations by references who write multiple letters are not only more influential than those of references who write one letter, but they are also more informative. Since multiple-letter references are also more highly ranked economists, this implies that there is a constraint on the supply of high-quality references. Moreover, we find that both the subjective and objective scores are correlated with job placement at a top economics department after the completion of the PhD. These indicators of individual achievement have a smaller effect than an undergraduate degree from an Ivy Plus school (i.e., Ivy League + Stanford, MIT, Duke, and Chicago). In the self-selected pool of applicants, Ivy Plus graduates are twice as likely to be admitted to a top 10 graduate program and are much more likely to obtain an assistant professor position at a top 10 program upon PhD completion. Given that Ivy Plus students must pass a stringent selection process to gain admission to their undergraduate program, we cannot reject the hypothesis that admission committees use information efficiently and fairly. However, this also implies that there may be a return to attending a selective undergraduate program in order to be pooled with highly skilled individuals.

That is from a new paper by Jessica Bai, Matthew Esche, W. Bentley MacLeod & Yifan Shi.

Why businesses fail

by  Tyler Cowen in

This paper is about micro-enterprises in Brazil, by Priscila de Oliviera:

Micro firms in low and middle income countries often have low profitability and do not grow over time. Several business training programs have tried to improve management and business practices, with limited effects. We run a field experiment with micro-entrepreneurs in Brazil (N=742) to study the under-adoption of improved business practices, and shed light on the constraints and behavioral biases that may hinder their adoption. We randomly offer entrepreneurs reminders and micro-incentives of either 20 BRL (4 USD) or 40 BRL (8 USD) to implement record keeping or marketing for three consecutive months, following a business training program. Compared to traditional business training, reminders and micro-incentives significantly increase adoption of marketing (13.2 p.p.) and record keeping (19.2 p.p.), with positive effects on firm survival and investment over four months. Our findings, together with additional survey evidence, suggest that behavioral biases inhibit the adoption of improved practices, and are consistent with inattention as a key driver of under-adoption. In addition, our survey evidence on information avoidance points to it as a limiting factor to the adoption of record keeping, but not marketing activities. Taken together, the results suggest that behavioral biases affect firm decisions, with significant impact on firm survival.

She is currently on the job market from UC Berkeley.  There should be many more papers on this kind of topic!

A Big and Embarrassing Challenge to DSGE Models

by  Alex Tabarrok in

Dynamic stochastic general equilibrium (DSGE) models are the leading models in macroeconomics. The earlier DSGE models were Real Business Cycle models and they were criticized by Keynesian economists like Solow, Summers and Krugman because of their non-Keynesian assumptions and conclusions but as DSGE models incorporated more and more Keynesian elements this critique began to lose its bite and many young macroeconomists began to feel that the old guard just weren’t up to the new techniques. Critiques of the assumptions remain but the typical answer has been to change assumption and incorporate more realistic institutions into the model. Thus, most new work today is done using a variant of this type of model by macroeconomists of all political stripes and schools.

Now along comes two statisticians, Daniel J. McDonald and the acerbic Cosma Rohilla Shalizi. McDonald and Shalizi subject the now standard Smet-Wouters DSGE model to some very basic statistical tests. First, they simulate the model and then ask how well can the model predict its own simulation? That is, when we know the true model of the economy how well can the DSGE discover the true parameters? [The authors suggest such tests haven’t been done before but that doesn’t seem correct, e.g. Table 1 here. Updated, AT] Not well at all.

If we take our estimated model and simulate several centuries of data from it, all in the stationary regime, and then re-estimate the model from the simulation, the results are disturbing. Forecasting error remains dismal and shrinks very slowly with the size of the data. Much the same is true of parameter estimates, with the important exception that many of the parameter estimates seem to be stuck around values which differ from the ones used to generate the data. These ill-behaved parameters include not just shock variances and autocorrelations, but also the “deep” ones whose presence is supposed to distinguish a micro-founded DSGE from mere time-series analysis or reduced-form regressions. All this happens in simulations where the model specification is correct, where the parameters are constant, and where the estimation can make use of centuries of stationary data, far more than will ever be available for the actual macroeconomy.

Now that is bad enough but I suppose one might argue that this is telling us something important about the world. Maybe the model is fine, it’s just a sad fact that we can’t uncover the true parameters even when we know the true model. Maybe but it gets worse. Much worse.

McDonald and Shalizi then swap variables and feed the model wages as if it were output and consumption as if it were wages and so forth. Now this should surely distort the model completely and produce nonsense. Right?

If we randomly re-label the macroeconomic time series and feed them into the DSGE, the results are no more comforting. Much of the time we get a model which predicts the (permuted) data better than the model predicts the unpermuted data. Even if one disdains forecasting as end in itself, it is hard to see how this is at all compatible with a model capturing something — anything — essential about the structure of the economy. Perhaps even more disturbing, many of the parameters of the model are essentially unchanged under permutation, including “deep” parameters supposedly representing tastes, technologies and institutions.

Oh boy. Imagine if you were trying to predict the motion of the planets but you accidentally substituted the mass of Jupiter for Venus and discovered that your model predicted better than the one fed the correct data. I have nothing against these models in principle and I will be interested in what the macroeconomists have to say, as this isn’t my field, but I can’t see any reason why this should happen in a good model. Embarrassing.

Addendum: Note that the statistical failure of the DSGE models does not imply that the reduced-form, toy models that say Paul Krugman favors are any better than DSGE in terms of “forecasting” or “predictions”–the two classes of models simply don’t compete on that level–but it does imply that the greater “rigor” of the DSGE models isn’t buying us anything and the rigor may be impeding understanding–rigor mortis as we used to say.

Addendum 2: Note that I said challenge. It goes without saying but I will say it anyway, the authors could have made mistakes. It should be easy to test these strategies in other DSGE models.