Macro Roundup

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

Bruce N. Gyory, "Trump As The Wizard Of Oz Can't Win Re-Election, But Democrats Could Still Lose The Presidency," Empire Report, April 7, 2019, https://empirereportnewyork.com/bruce-gyory-donald-trump-wizard-of-oz-2020-part-1/

Trump As The Wizard Of Oz Can't Win Re-Election, But Democrats Could Still Lose The Presidency

Rick Wilson is correct: Donald Trump can’t win re-election, but the Democrats could still lose the 2020 presidential election. That was the conclusion of Never-Trump Republican strategist Rick Wilson, in his excellent op-ed in last Sunday’s Daily News.

I had reached the same contradictory conclusions in doing the research for this column. A subsequent column will examine how the Democrats can reduce their risk of losing to Trump in 2020.

Why can’t Donald Trump win re-election? That assertion rests upon the plain fact that no one has actually explained to Donald Trump why he was elected President in 2016. Trump’s base was the bright tip of his Electoral College iceberg, but that it is not what elected Trump President. By playing only to his base, rather than trying to expand his support as President, Trump has done grievous damage to his re-election prospects.

Trump was elected because of a small but significant slippage in the Democrat’s share of white vote (Clinton got 37% of white vote according to exit polls vs. Obama’s 39% in 2012 and 43% in 2008) combined with a lower black turnout (African Americans turned out at 56% of all eligible voters in 2016 vs. turnout percentages among African Americans at 65% in 2008 and 66% in 2012; the white turnout percentage was 65% in 2016 vs 64% of all eligible white voters in 2012) and Clinton getting a lower share of the Hispanic vote(65% of Hispanics voted for Clinton in 2106 vs 71% for Obama in 2012).

Nevertheless, Trump still would not have carried a majority in the Electoral College had third party voting not been the balance of power in Pennsylvania, Michigan, Wisconsin and Florida (e.g., Jill Stein’s vote was greater than Trump’s margin of victory in Pennsylvania, Michigan and Wisconsin).

When you delve deeper into the exit poll numbers from 2016, it becomes clear that there were four swing voting blocs underlying Trump’s victory. First, the late swing against Clinton among married white women in the suburbs. Second, the near third of the electorate that had some college but not a four year degree—the so-called kids who stayed home (Trump according to the exit polls carried these voters by 9% whereas Obama carried this bloc by 4% in 2012). Third, middle aged Hispanic men gave Trump 35% of their vote (as opposed to Latino voters over 65 and under 45 in age who both gave Clinton 71% of their vote). The overall slippage among Hispanics (which included 6% of Hispanics who voted for third party candidates) cut off any chance Clinton had of holding Florida and carrying Arizona, North Carolina or Georgia (Clinton’s top raid targets in the Electoral College). Fourth, was independents (31% of the electorate according to exit polls) who Trump carried by 6%: 48-42% with a full 10% of Independents voting for third party candidates (Obama had carried Independents in 2008 and only narrowly lost Independents to Romney in 2012).

When you crunch these numbers, it becomes clear that these four voting blocs on top of the minority slippage in the urban cores had a decisive impact on 83% of the vote (49% of the nation’s vote according to the 2016 exit polls came from the Suburbs and 34% from urban areas), while only 17% of the electorate came from small town and rural communities. So the blue collar male vote from rural and small town America did surge for Trump and it had a clear impact, but those votes would have been mere shards of ice in the ocean, rather than the tip of the iceberg that elected Trump, had those four swing voting blocs (a much larger number of voters in the aggregate), not shifted against Clinton at the close of the campaign in 2016.

Two factors are worth noting in regard to these four swing voting blocs: one, polling data shows us that as President Trump is noticeably weaker today among each of these swing voting blocs than he was in November of 2016. Two, it is likely that these four swing voting blocs from 2016, will remain the swing voting blocs determining the outcome in the 2020 presidential race.

Yet, because Trump and derivatively most pundits, have been obsessed with Trump’s base, rather than the vast number of voters who actually enabled him to squeeze out a victory in the Electoral College, there has been precious little notice attending Trump’s slippage. Don’t take my word for Trump’s declining standing with these swing blocs, study the returns in the 2018 midterm elections both in terms of Democratic gains (Pennsylvania, Michigan, Wisconsin, Virginia, Colorado and Arizona) and the far narrower Republican margins of victory (Georgia, Florida and Texas).

Moreover, while the Mueller report’s finding of no criminal collusion by Trump or his campaign with the Russians, will be a shot of political adrenaline for Trump’s base, events are still threatening Trump’s public standing. The storm clouds threatening the economy (the inversion of the yield curve which has foreshadowed most recent recessions) and disorder in the world (from our relationship with NATO, to the potential for Brexit chaos, to the collapse of the North Korean nuclear arms talks, China’s advances in the Pacific and Europe, not to mention the prospect of turbulence in the Middle East) remain real threats to President Trump’s political standing, heading into next year’s election.

Nor can we be certain, as Judge Napolitano recently pointed out in his Fox News commentary, that there will not be a dragon’s tail from the Mueller report lashing Trump, once it comes out, particularly if Attorney General Barr’s March 24th letter is perceived as having whitewashed Mueller’s report. The traditional bread and butter issues of the economy and health care leavened by foreign policy threats, will of course dominate the electorate’s concerns, but the continuing investigations of Trump remain a dormant threat to his re-election prospects.

Thus, Trump is not a favorite to win re-election, unless economic growth were to jump next year towards the 4% growth level for GDP (i.e., the current Federal Reserve Board projections for 2020 are at the 1.9% growth level for GDP). The polling data bears this out. Trump as President has never hit, much less passed the 50% mark in his job approval rating, according to the Real Clear Averages data.

In Gallup’s data, Trump’s job approval ratings have stayed mostly in between the 38-42% levels (levels too low to sustain a President’s re-election). Four times President Trump has gone below the 35% level in Gallup’s polls, but only for an instant and only once did he hit 46% in job approval, back in his first week in office. That is significant because no President, has won the next presidential election, when their job approval in Gallup’s data has gotten below 35%. (I am using the Gallup polling data here as an illustrative example of the overall trend line, not as a dispositive source tracking public opinion).

Trump seems almost allergic to the concept of expanding his base, which renders his loss of support from the four key swing blocs from 2016 all the more significant. Consequently, if Trump is polling at or under 42% in the Fall of 2020, he will lose re-election, unless Howard Schultz’ candidacy (or a Schultz plus a Stein type candidacy from the left, frays the Democratic coalition from both ideological ends of the spectrum) proves to be the spoiler.

There is a decisive tactical play the Democrats can make in the 2020 presidential campaign: projecting a narrative that defines Trump as the veritable Wizard of Oz (i.e., establishing that there is really nothing behind the curtain). Democrats often abjure the power of narrative campaigning, preferring list campaigns (campaigns which focus upon a check list of issue based platform planks). That would be a mistake.

Narrative campaigning works, precisely because voters are busy and a clear and compelling narrative provides a clean hook for voters to hang their concerns upon. Inevitably, the 2020 campaign will become a referendum upon Donald Trump’s presidency. Democrats would be wise to find and project a narrative which resonates with voters.

The Wizard of Oz is a good narrative choice for three reasons. One, Trump is not on top of the details of either the policies his administration advances or the implementation of those policies. Two, the Wizard of Oz is something very understandable to older Americans, who will be the toughest swing voting bloc for Democrats to carry. Three, if this narrative catches hold with the public, being called the Wizard of Oz, will drive Trump nuts, because it vitiates his self-image as the all-powerful CEO. If Trump senses that people are laughing at him, he could explode, hastening his political demise with swing voters.

So why am I not advising the Democrats to crack open the champagne? Because I am not at all confident that the Democrats can pass their own 2020 math test. Can the Democrats get through the presidential primaries and produce a ticket for President and Vice-President, which simultaneously hits the following six electoral marks critical to winning both the popular vote and a majority in the Electoral College? One, crack 42% of the white vote. Many pundits subliminally convey that the Democratic problems with the white vote are connected to electing President Obama. In fact, Barack Obama got a higher percentage of white voters in his two races than Dukakis, Kerry and Hillary Clinton. The Democrats’ problems with white voters actually goes back to the McGovern era.

Two, next year can Democrats’ nurture a turnout percentage where African American voters turnout at the same levels as white voters (a la 2008 and 2012)? Three, the Democratic ticket needs to once again break the 70 % threshold among Hispanic voters (with an uptick in the Hispanic share of the total vote crossing the 12% threshold, from a 9% share in 2008 and 10% of the total vote in 2012). Four, Democrats need to carry the votes of those with some college but not a four year degree (roughly a third of the electorate, that is crucial in the Midwest and Southern Atlantic Coastal states). Five, juice the turnout of under 30 in age voters, so that their share of the total electorate crosses the 22% share level (given Trump’s chronic weakness with millennial voters). Six, carry independent voters by double digits (i.e., as in 2018, but not 2010, 2012 and 2014 when the GOP carried Independents). Given that the overwhelming majority of Independent voters are white, carrying Independents is an essential ingredient in the Democrats’ ability to shave the GOP’s traditional edge among white voters.

If Democrats hit all six of those targets they can’t lose next year’s presidential election and will win back control of the US Senate, as well as holding the House. If they hit four of those six targets, they will not lose the White House and will certainly hold the House of Representatives, with a chance to narrowly take control of the Senate. But if they hit only two of those six targets Trump could win re-election with accompanying Republican gains in the congressional races.

My fears that the Democrats could blow the chance to defeat Trump were reawakened by the political events emerging in the wake of the federal government shutdown. When following the unified leadership of Pelosi and Schumer, the Democrats drove Trump’s job approval ratings sharply down in the wake of the shutdown standoff (e.g., Gallup had Trump’s job approval down to 37% in its January 2-10th polling with a job approval rating of only 31% among Independents) to levels that could not sustain Trump’s re-election. Then Trump delivered a fumble free State of the Union, followed by the Democrats suffering a stilted roll out attending the Green New Deal and the debacle of Representative Omar’s anti-Semitic spasm of statements.

The political impact of this triad was predictable, for it sent troubling signals to a mix of suburban, faith based and independent voters who are predisposed to believe in institutions. No surprise then when voters eyes were averted from Trump’s repeated assaults on institutions, that Trump’s job approval rating in Gallup bounced back to 44% and his disapproval dropped from 59% to 52% (February 1-10 data). If Trump is at 45% job approval in November of 2020, he could still win re-election.

Once things stabilized, Trump’s job approval in Gallup’s March 1-10 data stood at 39% to a disapproval rating of 57%. It will be interesting to see what the impact is on Trump’s poll ratings from the Mueller report, followed so closely by the Trump administration’s attack on the ACA in the courts and the public’s reaction to all that, as it settles into the body politic.

Actually, Trump’s political standing, as reflected in the polling data, reminds me of a basketball team that is behind the whole game, but only trails by about five points heading into the last few minutes of the game. Experienced basketball fans know if the other team is not careful, that lead could vanish down stretch (e.g., the close of the 2016 campaign).

Democrats therefore have a choice heading into in 2020 presidential campaign. Would Democrats rather be right (in the eyes of their base) or would they rather elect a President by reforming the Blue Wall in the rust belt and by winning at least two of the four tough states starting to tilt away from the Republicans demographically (e.g., Florida, North Carolina, Georgia and Arizona)?

I am uncertain as to the choice Democratic candidates and their campaigns will ultimately make. That is why I feel confident concluding that Trump has no business winning re-election, but the Democrats could still lose next year’s presidential election.

".... But even being maximally optimistic about the wealth tax’s revenue potential by assuming that the estate tax is equivalent to a 0.27 percent wealth tax (the 13.5 percent effective estate tax rate multiplied by 2 percent mortality), we still get a revenue estimate for wealth taxation of only about $75 billion, or approximately 40 percent of the Saez and Zucman estimate....."
Natasha Sarin and Lawrence Summers, "A ‘wealth tax’ presents a revenue estimation puzzle,"Washington Post, April 4, 2019, https://www.washingtonpost.com/opinions/2019/04/04/wealth-tax-presents-revenue-estimation-puzzle/

"....A view deeply entrenched in mainstream macroeconomics is that trend productivity growth is the outcome of technological and institutional factors and can be treated essentially as an exogenous force, unresponsive to business cycles or monetary policy actions. The workhorse macroeconomic models used by international organizations and central banks are built upon this notion. This view, however, struggles to explain some key empirical facts.... recessions tend to be followed by prolonged slowdowns in productivity growth, causing persistent deviations of output from prerecession trends. This evidence suggests that recessions have an impact on long-run output, a phenomenon known as hysteresis...the Great Recession has been associated with permanent drops in the trend path of output in most advanced economies. These facts, as pointed out by several economists....suggest that the conventional wisdom might be incomplete and that trend productivity responds to changes in aggregate demand. In turn, this suggests that traditional views on the link between monetary policy and long-term growth need to be re-evaluated....."

Gianluca Benigno and Luca Fornaro, "The Keynesian Growth Approach to Macroeconomic Policy and Productivity," Federal Reserve Bank of New York, April 1, 2019, https://libertystreeteconomics.newyorkfed.org/2019/04/the-keynesian-growth-approach-to-macroeconomic-policy-and-productivity.html