Macro Roundup

"...Comparing these synthetic countries to their European counterparts reveals a virtually identical gradient in inequality and intergenerational mobility...."

Thor Berger and Per Engzell, "Brave Old World: Immigration, inequality and intergenerational mobility in the US," Center for Economic and Policy Research, March 28, 2019, https://voxeu.org/article/immigration-inequality-and-intergenerational-mobility-us

"...We use the regional concentration of ancestral groups to create ‘synthetic’ European countries (aggregates of places within the US with a heavy overrepresentation of a given group). Comparing these synthetic countries to their European counterparts reveals a virtually identical gradient in inequality and intergenerational mobility. Hence, the Great Gatsby curve also emerges when one compares levels of income inequality and intergenerational mobility across these synthetic European countries (see Figure 1). Is it about people or places? Can these differences be taken as evidence for differences in income mobility between communities within the US rather than, for example, Scandinavian Americans being more upwardly mobile than their fellow countrymen? The answer is arguably yes, because the black population shows similar patterns of income mobility in these areas. Further support for this interpretation is found when we study outcomes for children that received different exposure to, for example, places with British and Scandinavian ancestry during their childhood, due to family moves. In other words, it seems that European immigrant groups have made their imprint on communities, which shape opportunities for the local population more broadly...."

"...We first needed to determine the political leanings of just a sample of economists, which we did by linking about 2,000 economists to their campaign contributions and political petition signatures. These economists represent faculty from all types of institutions including many from the most prestigious universities in the country. We determined that there was a 60-40 liberal-conservative split among the economists in our data....."

Zubin Jelveh, Bruce Kogut and Suresh Naidu, "Economists Aren’t As Nonpartisan As We Think, FiveThirtyEight, December 8, 2014, https://fivethirtyeight.com/features/economists-arent-as-nonpartisan-as-we-think/

We must point out that the relationships we describe are correlations — we can’t claim that ideology is causing different research results. Although people’s political beliefs don’t change drastically after their mid-20s, it could be that economists’ views are influenced by their findings throughout their careers. In our paper we describe different ways we investigated this possibility and found no impact on our results.

We also stress that our results don’t mean economists are deliberately altering findings. It’s more likely that these correlations are driven by research areas and the methodologies employed by economists of differing political stripes.10 Economics involves both methodological and normative judgments, and it is difficult to imagine that any social science could completely erase correlations between these two.

So what do our results mean for public policy and the science of economics?

Policymakers may need to “re-center” economists’ findings by adjusting for ideology. Take the area of tax rates for high earners. The average optimal tax rate reported by economists in our data is 41 percent. Using our model, we can also estimate that these economists as a group are slightly left of center. We can then figure out what optimal top tax rate a hypothetical centrist economist would report: 33 percent.11

Political disagreements inside economics are probably a healthy reflection of political debates in society overall. While some economists will disagree with this (even the claim that economics is politicized is probably itself political), it’s likely that all stakeholders in economic research understand that the science of economics contains the larger American political splits within it.

CLARIFICATION (Dec. 8, 10:58 a.m.): The article has been updated to make clear that the table only shows the most ideological phrases when economists write about macroeconomics.

CORRECTION (Dec. 14, 11:53 a.m.): A chart in an earlier version of this article was missing about 40 percent of its data points and made the relationship it showed look weaker than it actually is. We’ve updated the article with the correct version of the chart.

Using these associations, we could then predict the ideology of any economist not in our sample by feeding his or her body of work into our algorithm. The results weren’t perfect, but the algorithm showed promising ability in distinguishing between liberal and conservative economists. To understand how well it performed, imagine that you randomly pick two economists and predict their ideologies. Random guessing would get it right 50 percent of the time and a perfect model would be able to produce the right affiliation 100 percent of the time. Our algorithm got it right 74.1 percent of the time,6 and was consistently able to extract a signal from inherently noisy text. If peer review and other professional norms are working as intended, then we shouldn’t be able to find any connection between ideology and text.

We then used these predicted ideologies to get a better understanding of the role political beliefs play in economics.

We first found that an economist’s research area is correlated with his or her political leanings. For example, macroeconomists and financial economists are more right-leaning on average while labor economists tend to be left-leaning. Economists at business schools, no matter their specialty, lean conservative. Apparently, there is “political sorting” in the academic labor market.

If there is job-market sorting, then maybe editors of journals are responsible. After all, academics make their careers off publishing. So we looked at whether journal editors influenced the ideology of the papers appearing in their journals.

We have good news for economics here: There’s no evidence that publication decisions are determined by editor ideology.

Then what explains our ability to detect ideology from text? Since ideology differs by field, another possibility is that a journal’s peer reviewers are already ideologically aligned. Liberal economists may choose to study labor markets because they know others in the field have similar beliefs. This is not only more ideologically comforting — it also makes it easier for those who share an ideology with reviewers to publish.

At this point, you may object to the idea that the text of a paper completely captures the findings it reports. What if a conservative and a liberal economist used ideologically tinged language in their papers, but both came up with the same numerical result about, say, the fiscal spending multiplier? The size of these multipliers, which quantify how much an increase in government spending changes economic growth, were intenselydebated during the financial crisis, with conservatives faulting fiscal expansion for increasing the deficit with no economic gain and liberals advocating for much greater deficit spending.

To test if ideology influences policy, e.g. taxes or deficits, we collected numerical research results from fields that have direct impacts on public policy,7 including government spending, minimum wages, various tax rates, and income mobility. The results from these fields map quite nicely onto the liberal-conservative ideological spectrum. For example, liberals think the fiscal multiplier is high, meaning the government can improve economic growth by increasing spending, while conservatives believe the multiplier is close to zero or negative. A similar logic applies to numerical results in the other fields.

As the following chart shows, we found a (significant) correlation8 when we compared the ideologies of authors with the numerical results in their papers.9 That means that a left-leaning economist is more likely to report numerical results aligned with liberal ideology (and the same is true for right-leaning economists and conservative ideology).

Economists Aren’t As Nonpartisan As We Think

According to purists, the field of economics is supposed to be free of political ideology. Economics views itself as a science1 and the prevailing consensus, best articulated by Nobel-winner and Chicago-school doyen George Stigler, is that “the dominant influence” in economics “is the set of internal values and pressures of the discipline” which help keep it nonpartisan.

And yet most well-known economists achieve their star status in the political sphere. The econowonks reading this could name the politics of economists Paul Krugman and Greg Mankiw without much hesitation. And a little Googling would uncover the ideological leanings of Martin Feldstein, John Cochrane, Christina Romer or Jonathan Gruber. Even Thomas Malthus and David Ricardo had disagreements over free trade that were mirrored in the House of Commons.

Still, economists’ beliefs are separate from what makes them successful academics: their research prowess. We can easily discount the political opinions economists express in op-eds. But they’re also publishing research in peer-reviewed journals. Are findings on tax rates, minimum wages or government spending also influenced by ideology?

This is not just navel-gazing, as economics research informs public policy.2A recent Congressional Budget Office analysis of the minimum wage describes how results from academia influenced the CBO’s projections. If those findings were at least partially influenced by political beliefs, then the CBO’s assessments may be unwittingly biased.

So we set out to test the idea of nonpartisan economics on a large scale. In a recent paper, we researched whether economists’ political leanings were associated with their professional work.3 The answer: yes.

Our main proxy for research was the text that appeared in academic papers. To identify political leanings, we had to figure out a way to measure the ideology of any economist — not just people like Krugman and Mankiw. Luckily, there’s a growing body of research on how to detect people’s ideology (or mood or personality type) from the way they write.

We first needed to determine the political leanings of just a sample of economists, which we did by linking about 2,000 economists to their campaign contributions and political petition signatures.4 These economists represent faculty from all types of institutions including many from the most prestigious universities in the country. We determined that there was a 60-40 liberal-conservative split among the economists in our data.5

With this knowledge about actual ideology in hand, we built an algorithm that discovered the relationships between political leanings and word choice in about 18,000 academic papers written by our sample of economists. For example, when writing about business cycles, we discovered conservatives were more likely to write “laissez faire” or “monetary economics” while liberals more often discussed “Keynesian economics” and “labor markets.” (The table below shows the most ideological phrases when economists write about macroeconomics.)

"....The recent slowdown in U.S. population growth thus understates the problem in many places. Even as the national growth rate has decelerated, the share of all counties falling below it has increased steadily from 64% from 1990 to 2000, to 73% from 2000 to 2010, to 86% from 2010 to 2017. About half of U.S. counties are now losing population outright each year—an historically high proportion. Over 50 million people, or 15% of the U.S. population, live in counties that have shrunk over the past decade, and another 11 million live in counties with largely flat populations.... The story for prime working age population is even more dramatic, with 80% of counties losing population ages 25 to 54 over the last decade. Together these counties were home to 149 million Americans in 2017. The proportion of counties losing prime working age population annually has been well above historic highs since 2000, where Moody’s Analytics forecasts it to remain into the next decade. These projections mean that, by 2037, 67% of U.S. counties will contain fewer prime working age adults than they did in 1997, even though the United States as a whole will add 24.1 million prime working age adults and 98.8 million people in total over that same period...."

Adam Ozimek, Kenan Fikri and John Lettieri, "From Managing Decline to Building The Future Could A Heartland Visa Help Struggling Regions?" Economic Innovation Group, April 2019, https://eig.org/wp-content/uploads/2019/04/Heartland-Visas-Report.pdf

T. Robert Fetter, Andrew L. Steck, Christopher Timmins and Douglas Wrenn, "Learning by Viewing? Social Learning, Regulatory Disclosure, and Firm Productivity in Shale Gas," National Bureau of Economic Research, December 2018, https://www.nber.org/papers/w25401

"...Firms in the oil and gas industry, as in many industries, rely on secrecy as a mechanism to capture value from their investments in innovation and maintain their competitive advantage....In this paper, we shed light on whether innovations in fracturing fluids do in fact constitute a competitive advantage. In particular, we compare detailed, well-level information on inputs to test whether the chemicals used become more similar with public disclosure....Our paper makes three primary contributions. Our first contribution is to the literature on the relationship between secrecy and innovation: We provide insight into the importance of the social tradeoffs policy makers face when considering disclosure laws. There may be a compelling social benefit from disclosing specific information, such as when production processes involve toxic chemicals in residential areas, but this social benefit must be weighed against the ability of firms to realize economic returns from their innovations. We provide evidence that innovations in hydraulic fracturing chemicals are valuable, and furthermore that innovation decreases following the disclosure rule suggesting that this tradeoff may be important at least in this context.Second, this paper expands the literature on the empirical effects of transparency or disclosure regulations in a new direction. Our analysis is the first, to our knowledge, to combine a study of the effects of information disclosure regulations with social learning. We find strong evidence that disclosure regulations about an emerging technology can enable social learning or spillovers that would not have occurred otherwise.Prior papers in the industrial organization literature have examined the effect of price or quality disclosure on market structure and competition....while other work has documented the effects of disclosure laws on environmental and health outcomes.....as well as investor behavior....Separately, other authors have studied the phenomenon of social learning....without considering the role of disclosure regulations specifically. Our research bridges these streams. Third, we study the role that chemical additives have played in the development of hydraulic fracturing technology. Several recent papers, beginning with Covert (2015), and continuing with Steck (2018) and Agerton (2018), have documented the rise of hydraulic fracturing and the role that learning plays on different firm decisions. We are the first to seriously consider the role of chemicals in firm learning, and thereby contribute to the literature on hydraulic fracturing specifically and social learning about emerging technologies more generally.... We find evidence for convergence in chemical inputs following the mandatory public disclosure law, and a link between that convergence and well productivity. In sum, the evidence suggests that disclosure laws affecting oil and gas production firms in Pennsylvania opened a new channel for social learning, and that operators who exploited this channel were able to increase their wells' productivity. This finding supports the argument that public disclosure laws can erode innovative firms' competitive advantages. Our last finding, that the disclosure law may be associated with a reduction in innovative activity, further corroborates this concern, and suggests that policymakers ought to consider the potential long-run costs of reduced innovation. Nonetheless, the net effect of such disclosure laws on public welfare over the longer term remains an open question: any welfare loss from reduced innovation needs to be weighed against the gains from transparency and dissemination...."

they don't estimate a net effect on sector productivity, ie the increase in productivity versus decreased innovation

new working paper published in a journal affiliated with Cold Spring's Harbor Lab suggests a polygenic score can help predict who gets across the finish line in college.

"....Maximizing the flow of students through the science, technology, engineering, and math (STEM) pipeline is important to promoting human capital development and reducing economic inequality1. A critical juncture in the STEM pipeline is the highly-cumulative sequence of secondary school math courses2-5. Students from disadvantaged schools are less likely to complete advanced math courses, but debate continues about why6,7. Here, we address this question using student polygenic scores, which are DNA-based indicators of propensity to succeed in education8. We integrated genetic and official school transcript data from over 3,000 European-ancestry students from U.S. high schools. We used polygenic scores as a molecular tracer to understand how the flow of students through the high school math pipeline differs in socioeconomically advantaged versus disadvantaged schools. Students with higher education polygenic scores were tracked to more advanced math already at the beginning of high school and persisted in math for more years. Molecular tracer analyses revealed that the dynamics of the math pipeline differed by school advantage. Compared to disadvantaged schools, advantaged schools tracked more students with high polygenic scores into advanced math classes at the start of high school, and they buffered students with low polygenic scores from dropping out of math. Across all schools, even students with exceptional polygenic scores (top 2%) were unlikely to take the most advanced math classes, suggesting substantial room for improvement in the development of potential STEM talent.These results link new molecular genetic discoveries to a common target of educational-policy reforms.

K. Paige Harden, Benjamin Domingue, Daniel Belsky, Jason Boardman, Robert Crosnoe, Margherita Malanchini, Michel Nivard, Elliot Tucker-Drob, Kathleen Mullan Harris, "Genetic Associations with Mathematics Tracking and Persistence in Secondary School,"bioRxiv, April 5, 2019, https://www.biorxiv.org/content/biorxiv/early/2019/04/05/598532.full.pdf

Just an FYI, new study on minimum wage increases finds no impact on employment, suspect it will show up in the press as it got published in theQuarterly Journal of Economics

"....In this paper we infer the employment effects of the minimum wage from the change in the frequency distribution of wages. The key advantage of this approach is that it allows us to assess the overall impact of the minimum wage on low-wage workers, who are the primary target of minimum wage policies. We use an event study analysis exploiting 138 prominent minimum wage increases and provide a robust and comprehensive assessment of how minimum wages affect the frequency distribution of wages. Second, we calculate the number of missing jobs just below the minimum wage, the number of excess jobs at or slightly above the minimum wage, and also the job changes in the upper tail of the wage distribution. Our main estimates show that the number of excess jobs at and slightly above the minimum wage closely matches the number of missing jobs just below the minimum wage, while we find no evidence for employment changes at or more than $4 above the minimum wage. Asimilar pattern obtains for low-skilled workers, suggesting labor-labor substitution is unlikely to be a factor in our setting. Moreover, we find that the level of the minimum wages that we study—which range between 37% and 59% of the median wage—have yet to reach a point where the job losses become sizable. However, the employment consequences of a minimum wage that surpass the ones studied here remain an open question. Furthermore, if minimum wage increases affect tradable sectors more, our findings suggest employment effects may be more pronounced….”
Doruk Cengiz, Arindrajit Dube, Attila Lindner and Ben Zipperer, "The Effect of Minimum Wages on Low-Wage Jobs,"Quarterly Journal of Economics, April 1, 2019, https://www.dropbox.com/s/9lotsq60qfw4cw5/CDLZ_qje.pdf

New NBER paper provides evidence to how the market gradually builds institutional capabilities--workers are willing to take a pay-cut to get valuable on-the-job training. The paper uses data from Glassdoor and finds IT workers seek firms that are using emerging IT systems and are willing to take a haircut for that job.

"...This paper provides evidence that IT workers prefer employers that invest in emerging IT systems, and this is in part because they can acquire valuable skills on the job.Although prior studies have examined how IT assets affect performance, we show that those investments can influence firms’ competitiveness in the market for high-tech labor. In fact,IT investment may derive some of its performance value because workers are attracted to firms with a superior engineering brand. For a given wage, employers using new technologies can attract higher-productivity technical labor. These effects are large enough to be interesting. For a firm in which engineers account for a large percent of the workforce, a 2% to 4% reduction in the wage bill is a powerful financial incentive. Results from the productivity literature suggest that the total share of IT investment for Fortune 500 firms is 3% to 5% of total expenditures. Therefore, a reduction of a few percentage points in the wage bill (which can often account for 70% to 80% of total spending) can offset a large fraction of a firm’s IT costs. Of course, this does not imply that all firms should adopt emerging IT systems. These investments are associated with higher churn, which is itself costly, and firms differ in the costs they face when first adopting these systems. Our findings suggest only that ceteris paribus, firms with stronger engineering brands, in terms of technology and culture, can attract higher quality technical labor for a given wage. Our findings have several implications. Competition for IT labor has been a subject of policy discussion for a generation. Firms’ IT choices can be an important determinant of retention, and may be one reason why poaching in high-tech markets often requires higher wage premiums than other markets. Where workers feel that their skills are depreciating, they may be harder to retain than in environments where they learn new skills that will be valuable for their future careers.The argument that workers derive value from acquiring transferable skills has additional implications. Because being rewarded for these skills requires switching employers, workers may place greater value on IT experience in markets where mobility is unfettered by non-compete policies. This implies, in turn, that firms have greater incentives to adopt emerging IT in markets without mobility restrictions because they can capture more of the value they provide to workers through this channel. Finally, the heterogeneity of our findings by experience level suggests that IT factors can influence how different age workers sort across firms, which may be important given the many diversity concerns that high-tech firms face. There are caveats to our study. It would be valuable to know whether the results differ for workers who are not actively seeking jobs. Our data are also from a short panel, so we do not take a position on whether these effects are idiosyncratic to the time period we study or whether they are more broadly generalized to IT-enabled change. A more encompassing test might analyze data from more than one IT diffusion wave. Indeed, in the long run, firms and technology vendors may change the nature of their actions in a way that changes these relationships. There remains significant scope for work in this area. How firm characteristics, beyond IT investment, influence IT learning and IT wage structure merits further study. Moreover, how IT workers acquire skills, how these skills are rewarded, and how they depreciate all have implications for the IT labor force. Those implications include who chooses to be an IT worker and the wages they earn. These questions have received relatively little attention in the academic literature, but their answers are becoming important for workforce policy and for managing technology in a competitive labor market...."

Prasanna Tambe, Xuan Ye, Peter Cappelli, "Paying to Program? Engineering Brand and High-Tech Wage," National Bureau of Economic Research, February 2019, https://www.nber.org/papers/w25552

New Alesina that complements both his recent paper with Stantcheva we looked at and Putnum's research on the effects of increased diversity on support for redistribution
"....Europe is becoming more and more diverse. Over the short period we cover, the share of foreign-born has increased in our sample by 50% on average (from 8.4% in 2000 to 12.8% in 2015) and has more than doubled since 1980, with about two thirds of the increase generated by immigration from outside of Europe. While this increase in population diversity may have important economic bene ts in the long-run (Alesina et al., 2016), in the shortrun immigration and diversity are perceived by many as a threat to social cohesion and put welfare systems (as we document) and democracies (as we have witnessed) at risk. This paper shows that the increase in population heterogeneity in Europe correlates with attitudinal shifts against redistribution among European-born voters. This is especially the case for center-right voters in regions belonging to countries with large welfare systems and high levels of residential segregation between immigrants and natives. The effects are also stronger, not surprisingly, when immigrants are less skilled and when they come from culturally more distant... The effects are also stronger (~3x) when immigrants originate from Middle-Eastern countries.... countries.While our results are consistent with group loyalty effects (i.e., the fact that individuals prefer to redistribute towards the in-group { people of same race/culture/nationality) and less so towards the out-group, they are not exclusive of other channels that determine natives' attitudinal response to immigration.Other motives include taxpayers' fear of having to pay for the benefits of (poorer) immigrants that are sometimes portrayed as free-riding on the welfare system. Another possible channel relates to concerns of tighter labor market competition caused by immigrant labor and native workers' perception of higher risks of downward income mobility. To insure against this risk, native workers may demand more redistribution. Conversely, when immigrants are perceived to complement natives' labor and increase natives' wages, natives may lower their demand for redistribution since they are less likely to be on the receiving end of the welfare state. As already mentioned, we do not seek to disentangle these different motives as we believe that such attempt is unlikely to provide convincing results when using observational data.Instead, we focused our investigation on providing new evidence on the association between immigrants' shares and natives' support for redistribution at the regional level while at the same time accounting in the empirical analysis for a number of confounders that have plagued previous cross-country descriptive studies in the context of Europe...."
Alberto Alesina, Elie Murard, Hillel Rapoport,"Immigration and Preferences for Redistribution in Europe," National Bureau of Economic Research, February 2019, https://www.nber.org/papers/w25562