Edward Conard

Top Ten New York Times Bestselling Author

  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
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  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
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  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
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Macro Roundup


Monday, January 14, 2019

AI Summary. Research indicates trade's net effect on U.S. employment is small: Chinese imports were associated with a net loss of about 200,000 jobs over roughly 16 years, against 3.3m export-driven job gains, and export growth created demand for 6.6m jobs including 4m in services.

Michael R. Strain Bloomberg
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Trade’s impact on domestic employment is minimal, as evidenced by research showing a net loss of only 200,000 jobs from 1991 to 2007 due to Chinese imports, offset by 3.3m export-driven job gains. @MichaelRStrain

Does trade create more jobs than it destroys?

Core argument: Research cited finds Chinese imports produced a net loss of 200,000 U.S. jobs from 1991 to 2007, offset by 3.3m jobs gained from exports.

Trade's impact on domestic employment is minimal, as evidenced by research showing a net loss of only 200,000 jobs from 1991 to 2007 due to Chinese imports, offset by 3.3m export-driven job gains. From 1995 to 2011, export growth created demand for 6.6m jobs, including 4m in services, while imports reduced demand, yet overall labor demand increased. The U.S. labor market's churn is significant, with 5.7m separations in September 2018 alone, and trade accounts for a small share of this churn. Policymakers should focus on aiding workers in adjusting to economic changes rather than blaming trade, which offers benefits like lower consumer prices and efficiency gains.

Takeaways by Macro Roundup® AI

  1. Research cited finds Chinese imports produced a net loss of 200,000 U.S. jobs from 1991 to 2007, offset by 3.3m jobs gained from exports.
  2. Export growth created demand for 6.6m jobs from 1995 to 2011, including 4m in services, and overall labor demand rose even as imports reduced demand.
  3. The U.S. labor market recorded 5.7m separations in September 2018 alone, with trade accounting for a small share of that churn.

“…. the right answer to the question is that trade doesn’t reduce overall employment. It doesn’t increase it, either. It’s a wash. Careful research by the economist Robert Feenstra and his co-authors shows that this simple conclusion is basically correct. In one paper, they find that the U.S. lost around 3.5 million manufacturing jobs due to Chinese imports from 1991 to 2007. At the same time, export-driven job gains totaled about 3.3 million. So the net effect was about 200,000 fewer jobs. Looking over the full two decades of the 1990s and 2000s, Feenstra finds even more balance between jobs gained due to exports and lost due to imports. In a second paper, Feenstra and Akira Sasahara use a different method to study the effects of U.S. exports and imports on labor demand. They found that export growth led to demand for 6.6 million jobs from 1995 to 2011, including 4 million service-sector jobs, while imports reduced demand. But on net, overall labor demand increased due to trade over this time period — with increases in services and declines in manufacturing. Of course, the level of employment is not the only outcome worth considering when thinking about the effects of trade. One is churn. Let’s take Feenstra’s estimate of 2 million fewer manufacturing jobs due to trade with China. That works out to an average loss of about 10,000 jobs per month over the 17 years in his estimate. To put this in context, compare it to the total level of turnover in the U.S. economy for September 2018, the most recent month for which data is available. That month, 3.6 million workers quit their jobs. Companies laid off or discharged 1.7 million workers. In total, 5.7 million workers separated from their employer. The amount of churn in the U.S. labor market is staggering. Trade causes a small share of that churn….”

Michael R. Strain, “You Can’t Be Pro-Jobs Without Being Pro-Trade,” Bloomberg, December 10, 2018, https://www.bloomberg.com/opinion/articles/2018-12-10/elizabeth-warren-is-wrong-about-jobs-and-trade

If Elizabeth Warren really wants to help workers, she could start with the facts.

Senator Elizabeth Warren, a likely 2020 presidential contender, recently laid out her vision for foreign policy in a speech at American University and an essay in Foreign Affairs. The Massachusetts Democrat was highly critical of traditional U.S. trade policy.

She writes that the trade deals negotiated by leaders of both political parties “mainly lifted the boats of the wealthy while leaving millions of working Americans to drown.” Her conclusion: “Policymakers were willing to sacrifice American jobs in hopes of lowering prices for consumer goods at home and spreading open markets abroad.”

Supporters of free trade would disagree with this characterization, of course. But they might agree that among the main benefits of trade are, as the senator says, lower-priced goods in U.S. stores and new markets around the world for American business.

But what about jobs?

From President Donald Trump’s bleak inaugural vision of American carnage to Warren’s drowning American workers, there is a growing bipartisan consensus that free trade reduces employment.

This view seems to forget that free trade should increase a country’s exports as well as its imports.

Increasing demand for imports can reduce demand for similar domestically produced goods and services. This can hurt employment opportunities and wages in those domestic industries. But the opposite is true of exports. As export demand increases, the demand for workers in those industries should rise, putting upward pressure on their wages and increasing jobs.

It’s also hard to square the trade-reduces-employment view with the existence of macroeconomic policy designed to achieve full employment. More specifically, if free trade creates a large number of unemployed workers, then the Fed will keep the economy running hot long enough to allow those workers to find new jobs.

So as a first pass, the right answer to the question is that trade doesn’t reduce overall employment. It doesn’t increase it, either. It’s a wash.

Careful research by the economist Robert Feenstra and his co-authors shows that this simple conclusion is basically correct. In one paper, they find that the U.S. lost around 3.5 million manufacturing jobs due to Chinese imports from 1991 to 2007. At the same time, export-driven job gains totaled about 3.3 million.

So the net effect was about 200,000 fewer jobs. Looking over the full two decades of the 1990s and 2000s, Feenstra finds even more balance between jobs gained due to exports and lost due to imports.

In a second paper, Feenstra and Akira Sasahara use a different method to study the effects of U.S. exports and imports on labor demand. They found that export growth led to demand for 6.6 million jobs from 1995 to 2011, including 4 million service-sector jobs, while imports reduced demand. But on net, overall labor demand increased due to trade over this time period — with increases in services and declines in manufacturing.

Of course, the level of employment is not the only outcome worth considering when thinking about the effects of trade. One is churn. Let’s take Feenstra’s estimate of 2 million fewer manufacturing jobs due to trade with China. That works out to an average loss of about 10,000 jobs per month over the 17 years in his estimate.

To put this in context, compare it to the total level of turnover in the U.S. economy for September 2018, the most recent month for which data is available. That month, 3.6 million workers quit their jobs. Companies laid off or discharged 1.7 million workers. In total, 5.7 million workers separated from their employer.

The amount of churn in the U.S. labor market is staggering. Trade causes a small share of that churn.

But trade-caused disruption does create winners and losers. Although economists have long understood this simple fact, some recent
research has demonstrated that the speed with which the U.S. economy adjusts to the disruption has been much slower than had been previously understood. This left local areas especially exposed to import competition with higher unemployment, fewer jobs and lower wages for much longer than many economists would have predicted.

And even if workers who lose a manufacturing job because of trade are able to get a job in the services sector, that doesn’t mean they will necessarily be happy about it. Those jobs often pay less, with fewer benefits, and are less stable than the job they lost to trade.

Policymakers should focus their efforts on dealing with those frustrations, and not on trade.

As we have seen, the problem with the U.S. labor market isn’t trade — trade does not have a significant impact on the level of employment or on churn in the labor market. And trade delivers a host of benefits to the U.S. economy, including a greater variety of and lower prices for consumer goods, along with productivity and efficiency gains.

But for a worker who loses his job due to trade, the macroeconomic picture hardly matters. The answer is not to erect walls around the U.S. Instead, public policy needs to do a much better job of helping workers manage the difficult adjustments that are required by a dynamic economy — whether those adjustments are driven by trade, or by anything else.

On this score, Warren’s speech and essay fall flat. Using trade agreements to go after tax havens, curtail large multinational firms and address climate change isn’t the answer. The same goes for her vague call for workers to “be meaningfully represented at the negotiating table.”

In the next two years, presidential aspirants will need to come up with policy ideas that pair global openness with support for workers. This is so difficult precisely because it is so needed, after decades of unsatisfactory attempts.

AI Summary. A global input-output analysis estimates that U.S. imports from China reduced labor demand by 2m jobs while U.S. exports supported demand for 6.6m jobs — 2m in manufacturing, 0.5m in resource industries, and 4.1m in services — leaving a net gain in labor demand driven by service exports.

Robert C. Feenstra and Akira Sasahara National Bureau of Economic Research
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Feenstra finds a fall in labor demand due to trade but a rise in labor demand due to service exports overall positive for job growth.

Do U.S. exports support more jobs than Chinese imports displace?

Core argument: The analysis finds the "China Shock" produced a net loss of 300,000 U.S. jobs, while the overall impact of trade on U.S. job creation from 1995–2011 was positive.

The analysis reveals that while the "China Shock" resulted in a net loss of 300,000 U.S. jobs, the overall impact of trade was positive for domestic job creation. From 1995-2011, U.S. exports spurred demand for 6.6m jobs, including 2m in manufacturing, 0.5m in resource industries, and 4.1m in services. Notably, service exports contributed significantly to job growth, with two-thirds of service sector jobs stemming from direct service exports. In contrast, U.S. imports from China reduced labor demand by 2m jobs, primarily in manufacturing and services. The net effect of U.S. merchandise exports relative to imports from China was a gain of 1.7m jobs. While merchandise trade showed a decline in net labor demand, the rise in service exports led to an overall increase in labor demand, underscoring the positive role of service exports in job growth.

Takeaways by Macro Roundup® AI

  1. The analysis finds the "China Shock" produced a net loss of 300,000 U.S. jobs, while the overall impact of trade on U.S. job creation from 1995–2011 was positive.
  2. U.S. exports generated demand for 6.6m jobs over 1995–2011, comprising 4.1m in services, 2m in manufacturing, and 0.5m in resource industries, with two-thirds of service sector jobs traced to direct service exports.
  3. U.S. imports from China reduced labor demand by 2m jobs, mainly in manufacturing and services, leaving a net gain of 1.7m jobs from U.S. merchandise exports relative to imports from China.

1/2 of the paper’ Strain flagged, it’s a Feenstra paper we looked at when it was released. (aside, we also “know” him (he helps oversee the Penn tables and was nice enough to check our data on evolution of the GDP/Capital Stock for the US and some peer economies)

net the “China Shock” left the US down 300,000 jobs; whereas overall trade was positive for domestic job creation, “… We find that the growth in U.S. exports led to increased demand for 2 million jobs in manufacturing, 0.5 million in resource industries, and a remarkable 4.1 million jobs in services, totaling 6.6 million. One-third of those service sector jobs are due to the intermediate demand from merchandise (manufacturing and resource) exports, so the total labor demand gain due to merchandise exports was 3.7 million jobs. In comparison, U.S. merchandise imports from China led to reduced demand of 1.4 million jobs in manufacturing and 0.6 million in services (with small losses in resource industries), with total job losses of 2.0 million. It follows that the expansion in U.S. merchandise exports to the world relative to imports from China over 1995-2011 created net demand for about 1.7 million jobs. Comparing the growth of U.S. merchandise exports to merchandise imports from all countries, we find a fall in net labor demand due to trade, but comparing the growth of total U.S. exports to total imports from all countries, then there is a rise in net labor demand because of the growth in service exports…”

Robert C. Feenstra and Akira Sasahara, The ‘China Shock’, Exports and U.S. Employment: A Global Input-Output Analysis,” National Bureau of Economic Research, November 2017, https://www.nber.org/papers/w24022.pdf

“….We find that the growth in exports led to demand for 2 million jobs in manufacturing, 0.5 million in resource industries, and a remarkable 4.1 million jobs in services over 1995-2011, totaling 6.6 million. Two-thirds of those service sectors jobs are due to the export of services themselves, whereas one-third is due to the intermediate demand from the manufacturing and resource – or what we call merchandise – exports, so the total demand gains from merchandise exports are 3.7 million jobs, with 1.9 million in manufacturing, 0.45 million in natural resource industries, and 1.3 million in services. That 1.9 million jobs in manufacturing is much the same as the 1.9 million added jobs for an earlier 16 year period, 1991-2007, estimated by Feenstra, Ma and Xu (2017)…..We find that the growth in U.S. merchandise exports over 1995-2011 led to demand for 1.9 million jobs in manufacturing, 0.45 million in resource industries, and 1.3 million jobs in services, totaling 3.7million. In comparison, U.S. merchandise imports from China over 1995-2011 led to reduced labor demand of 1.4 million jobs in manufacturing and 0.6 million in services (with small losses in resource industries), for total job losses of 2.0 million. It follows that the expansion in U.S. merchandise exports relative to imports from China over 1995-2011 led to the net demand for about 1.7 million jobs. Comparing the growth of U.S. merchandise exports to merchandise imports from all countries, we find a fall in net labor demand due to trade, but comparing the growth of total U.S. exports to total imports from all countries, then there is a rise in net labor demand because of the growth in service exports….The added demand for 1.9 million jobs in U.S. manufacturing exports that we have found much the same as the equilibrium increase of 1.9 million jobs for a 12 year period, 1999-2011, estimated by Feenstra, Ma and Xu (2017). That added demand for manufacturing jobs explains about one-half of the overall demand increase of 3.7 million jobs due to merchandise exports. The offsetting reduction in labor demand of 2.0 million jobs due to imports from China, mainly manufactures, is very close to Acemoglu, Autor, Dorn, Hanson and Price (2016), who find about 1.0 million manufacturing jobs lost in equilibrium during 1999- 2011, and another 1.0 million jobs lost by intermediate demand throughout the economy….Because the input-output analysis relies exclusively on the demand side of the labor market, one might have expected to get considerably larger shifts in demand that would then be offset by upward-sloping labor supply curves to obtain the (smaller) equilibrium changes. Instead, our findings are that the demand shifts from the input-output analysis are similar to the equilibrium changes in employment identified by regression analysis. There are two possible explanations for this result. The first is that there are near-horizontal labor supply curves at the regional level, reflecting movement in and out of unemployment or labor force participation, or movement between regions. But that is an unrealistic explanation: generally there is limited mobility across regions, except for immigrants who do respond to wages difference across regions (Caneda and Kovak, 2016). A different explanation for this finding is that regions with negative employment shocks from imports also have positive shocks from exports, so that the net shocks in regions are smaller than the gross (export and imports) shocks. That explanation is explored further in Feenstra, Ma and Xu (2017). Caliendo, Dvorkin and Parro (2015) and Dix- Carneiro and Kovak (2017) also incorporate careful specifications of the employment decisions and regional movement of individuals….We quantify the impact on U.S. employment from imports and exports during 1995-2011, using the World Input-Output Database. We find that the growth in U.S. exports led to increased demand for 2 million jobs in manufacturing, 0.5 million in resource industries, and a remarkable 4.1 million jobs in services, totaling 6.6 million. One-third of those service sector jobs are due to the intermediate demand from merchandise (manufacturing and resource) exports, so the total labor demand gain due to merchandise exports was 3.7 million jobs. In comparison, U.S. merchandise imports from China led to reduced demand of 1.4 million jobs in manufacturing and 0.6 million in services (with small losses in resource industries), with total job losses of 2.0 million. It follows that the expansion in U.S. merchandise exports to the world relative to imports from China over 1995-2011 created net demand for about 1.7 million jobs. Comparing the growth of U.S. merchandise exports to merchandise imports from all countries, we find a fall in net labor demand due to trade, but comparing the growth of total U.S. exports to total imports from all countries, then there is a rise in net labor demand because of the growth in service exports….

AI Summary. The authors estimate that US job losses from Chinese imports exceeded job gains from export expansion by roughly 0.2–0.3m jobs, and that over a longer window the net employment effect of import and export exposure was roughly balanced across local labor markets.

Robert C. Feenstra National Bureau of Economic Research
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Btw 1991 and 2007, US exports generated significant job opportunities but were slightly insufficient to offset job losses from Chinese imports, netting a 0.2-0.3m job loss.

Do export gains offset job losses from Chinese imports?

Core argument: The US lost a net 0.2–0.3m jobs between 1991 and 2007 from Chinese import competition, as employment created by global export expansion fell slightly short of offsetting those losses.

Between 1991 and 2007, the US experienced a net job loss of approximately 0.2-0.3m jobs due to the impact of Chinese imports, despite significant job creation from global export expansion. While US exports generated substantial employment opportunities, they were slightly insufficient to offset the job losses caused by Chinese imports. Extending the analysis to 1991-2011, the net job effect of import and export exposure was roughly balanced at the commuting zone level. The geographic correlation between job losses and gains suggests that local labor markets reached equilibrium despite limited regional mobility. This highlights the complex interplay between global trade dynamics and domestic employment trends, emphasizing the need for nuanced policy responses to address these challenges.

Takeaways by Macro Roundup® AI

  1. The US lost a net 0.2–0.3m jobs between 1991 and 2007 from Chinese import competition, as employment created by global export expansion fell slightly short of offsetting those losses.
  2. Extending the window to 1991–2011, the net job effect of import and export exposure was roughly balanced at the commuting zone level.
  3. The geographic correlation between trade-related job losses and gains suggests local labour markets reached equilibrium despite limited regional mobility.

2/2 of the paper Strain flagged. another Feenstra, mirrors his first

"...We examine the employment responses to import competition from China and to global export expansion from the United States, both of which have been expanding strongly during the past decades. We find that although Chinese imports reduce jobs, at both the industry level and the local commuting zone level, the global export expansion of US products also creates a considerable number of jobs. On balance over the entire 1991-2007 period, job gains due to changes in US global exports were slightly less than job losses due to Chinese imports. Using data at both the industry level and the commuting zone level, we find a net loss of around 0.2-0.3 million jobs. When we extend the analysis to 1991-2011, we find the net job effect of import and export exposure is roughly balanced at the commuting zone level.....In this paper, we have re-examined the employment impact of US exports, using exports to the world rather than just exports to China. We believe that this is a better way to evaluate the employment impact of US exports: the growth in Chinese demand as compared to the growth in demand from other countries for US goods are of equal interest when evaluating the employment impact, so there is no reason to focus on Chinese demand alone.12 But demand for US exports is endogenous, as we must correct for. Just like the `China shock' created a compelling supply-side instrument for Chinese exports to the US, i.e. by using its exports to other industrial countries, so too we have had to develop good instruments for US exports to the world. In addition to using the exports of other industrial countries to foreign markets, we have derived a gravity-like specification for US exports that uses those exports of other countries along with the tariffs charged in foreign countries, and distance. The derivation of this equation showed that the sector-year fixed effects would like reflect US supply shocks, so we have omitted those fi xed effects when constructing this second instrument.Our results t the `textbook story' that job opportunities in exports make up for jobs lost in import-competing industries, or nearly so. At the industry level, the US export of manufactured goods created enough jobs to o set all but 0.3-0.4 million of the jobs lost due to imports from China, over the entire 1991-2011 period. When we shift to considering CZ's, then the net job loss over 1991-2007 is still about 0.2 million jobs, but over the longer period 1991-2011 the job losses are just balanced with the job gains. There is also a positive geographic correlation between those losses and gains, so that CZ's with higher percentage losses are also more likely to have higher percentage gains. This result helps to explain how local labor markets reached equilibrium even in the absence of strong mobility across regions.It would be desirable to further explore the job losses and gains beyond the CZ level, such as within sector and within broader counties rather than CZ, to understand the equilibrating mechanism in local labor markets...."
Robert C. Feenstra, Hong Ma and Yuan Xu, "US Exports and Employment," National Bureau of Economic Research, November 2017, https://www.nber.org/papers/w24056

AI Summary. The share of working-age Americans with a college degree is now 20% higher in urban than rural areas, up from a 5% gap in 1970, a shift that coincides with the disappearance of mid-skilled city jobs to offshoring and automation. The urban wage premium now mainly benefits well-educated workers, with little wage boost for less-educated ones.

Economist Staff The Economist
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The share of working-age Americans with a college degree is now 20% higher in urban areas than rural ones, a significant increase from a 5% gap in 1970.

Do cities still raise wages for workers without college degrees?

Core argument: The share of the working-age population holding a college degree is now 20% higher in urban areas than rural ones, up from a 5% gap in 1970.

The share of the working-age population with a college degree is now 20% higher in urban areas than rural ones, a significant increase from a 5% gap in 1970. This shift coincides with the disappearance of mid-skilled jobs in cities, which have either moved abroad or been automated, leaving fewer opportunities for those without degrees. The urban wage premium, once benefiting all skill levels, now primarily advantages well-educated workers, while less-educated workers see little to no wage boost from urban employment. Consequently, the economic prospects for Americans without college degrees have dimmed, as they face limited job opportunities and stagnant wages, particularly in urban settings.

Takeaways by Macro Roundup® AI

  1. The share of the working-age population holding a college degree is now 20% higher in urban areas than rural ones, up from a 5% gap in 1970.
  2. Mid-skilled jobs in U.S. cities have disappeared, moving abroad or being automated, leaving fewer opportunities for workers without college degrees.
  3. The urban wage premium, which once benefited workers at all skill levels, now primarily advantages well-educated workers, with less-educated workers seeing little to no wage boost from urban employment.

Just an FYI so not including a tweet the Economist on Autor's lecture

"....David Autor of the Massachusetts Institute of Technology offered the most pointed characterisation, drawing on forthcoming research co-authored with Juliette Fournier, also of MIT. The earnings of workers without a college education have scarcely risen in 50 years, after adjusting for inflation; for men they have fallen. This stagnation coincided with tectonic changes in American employment. The share of jobs that require either a lot of training, or very little, has grown since 1970. Much of the production and office work that requires moderate training, which once employed vast numbers of workers without college degrees, has disappeared, either shipped abroad or offloaded on robots and computers..... Mr Autor and Ms Fournier provide important new context. In the 1950s, they show, there was almost no relationship between how densely populated a place was and the share of its residents with college degrees. That has changed utterly: the share of the working-age population with a college degree is now 20 percentage points higher in urban places than it is in rural ones. In 1970 that gap was just five percentage points. Several decades ago mid-skilled work was clustered in big cities, while low-skilled work was most prevalent in the countryside. No longer; those mid-skilled jobs that remain are more likely to be found in rural areas than in urban ones. As the geographical pattern of work has shifted, so has that of wages. Economists have long acknowledged the existence of an urban wage premium: workers in more densely populated places earn more, in part because of the productivity benefits of crowding together that nurture urban growth in the first place. This pay premium used to hold across the range of skills. In 1970 workers without any college education could expect to get a boost to their earnings when they moved to a big city, just as better-educated workers did. Since then the urban wage advantage for well-educated workers has become more pronounced, even as that for less-educated workers has all but disappeared...."
Economist, "The outlook is dim for Americans without college degrees,"The Economist, January 8, 2019, https://www.economist.com/finance-and-economics/2019/01/08/the-outlook-is-dim-for-americans-without-college-degrees

AI Summary. A model of innovation-driven growth estimates the optimal top income tax rate at 29%, far below the 92% rate that would maximize revenue if innovation spillovers are ignored. Because ideas raise productivity economy-wide, the author argues raising the top marginal rate from 50% to 75% would lower GDP per person by about 6% long run.

Charles Jones National Bureau of Economic Research
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Raising top tax rates can stifle innovation, a key driver of economic growth, according to Stanford’s Charles Jones @CharlesJones. His model suggests an optimal top tax rate of 29%, significantly lower than the revenue-maximizing rate of 92%.

How do innovation spillovers lower the optimal top income tax rate?

Core argument: Stanford's Charles Jones estimates the optimal top income tax rate at 29% once innovation spillovers are counted, below the 92% revenue-maximizing rate that ignores those spillovers.

Stanford's Charles Jones argues that raising the top tax rate can stifle innovation, which is a key driver of economic growth. His model suggests that the optimal top income tax rate is 29%, significantly lower than the revenue-maximizing rate of 92% when innovation spillovers are ignored. Increasing the top marginal tax rate from 50% to 75% could reduce GDP per person by ~6% in the long run, despite raising 2.5% of GDP in revenue before behavioral responses. This reduction in innovation impacts everyone's income, not just the top earners, as ideas are nonrival and enhance productivity across the board. The model indicates that if ideas are more crucial than assumed, the optimal tax rate could even be negative, as the income boost from subsidizing innovation outweighs redistribution benefits. Thus, high marginal tax rates may ultimately reduce social welfare by hindering the creation of new ideas that drive GDP growth.

Takeaways by Macro Roundup® AI

  1. Stanford's Charles Jones estimates the optimal top income tax rate at 29% once innovation spillovers are counted, below the 92% revenue-maximizing rate that ignores those spillovers.
  2. Jones's model implies that raising the top marginal rate from 50% to 75% could reduce GDP per person by about 6% in the long run, while raising 2.5% of GDP in revenue before behavioral responses.
  3. Because ideas are nonrival and raise productivity broadly, Jones argues reduced innovation lowers incomes for everyone rather than only top earners, and that the optimal top rate could be negative if ideas matter more than assumed.

Stanford's Charles Jones released a new paper showing that new ideas and innovation drive economic growth; and the reward for successful innovation and the associated risk-taking is a top income. His model suggests the optimal tax rate incorporating the role of innovation is 29%; if ideas are even more important than the model’s baseline it's possible for the optimal top income tax rate to turn negative as the growth related to higher innovation is greater than the social benefits of redistribution.

From Steve:

model of the optimum tax rate which a new constraint, ideas. 1) new ideas drive economic growth, 2) the reward for creating a successful innovation is a top income, and 3) innovation cannot be perfectly targeted by a separate research subsidy finds that, "...For example, consider raising the top marginal tax rate from 50% to 75%. As we discuss below, in the United States, the share of income that this top marginal rate applies to is around 10%, so the change raises about 2.5% of GDP in revenue before the behavioral response. In our baseline calibration, such an increase in the top marginal rate reduces innovation and lowers GDP per person in the long run by around 6 percent...."

Charles Jones, Taxing Top Incomes in a World of Ideas," National Bureau of Economic Research (Preliminary), September 6, 2018, https://www8.gsb.columbia.edu/faculty-research/sites/faculty-research/files/finance/Macro%20Workshop/toptax.pdf

"...The nonrivalry of ideas is key to this result and illustrates why incorporating physical capital or human capital into the top tax calculation is insufficient. If you add one unit of human capital or one unit of physical capital to an economy—think of adding a computer or an extra year of education for one person—youmake one workermore productive, because these goods are rival. But if you add a new idea — think of the computer code for the original spreadsheet or the blueprint for the electric generator —you can make any number of workers more productive. Because ideas are nonrival, each person’s wage is an increasing function of the entire stock of ideas. A distortion that reduces the production of new ideas therefore impacts everyone’s income, not just the income of the inventor herself.....The idea creation and implementation that occurs beyond formal R&D may be distorted by the tax system. In particular, high incomes are the prize that motivates entrepreneurs to turn a basic research insight that results from formal R&D into a product or process that ultimately benefits consumers. High marginal tax rates reduce this effort and therefore reduce innovation and the incomes of everyone in the economy....Taking this force into account is important quantitatively. For example, consider raising the top marginal tax rate from 50% to 75%. As we discuss below, in the United States, the share of income that this top marginal rate applies to is around 10%, so the change raises about 2.5% of GDP in revenue before the behavioral response. In our baseline calibration, such an increase in the top marginal rate reduces innovation and lowers GDP per person in the long run by around 6 percent. With a utilitarian welfare criterion, this obviously reduces welfare. But even redistributing the 2.5% of GDP to the bottom half of the population would leave them worse off on average: the 6% decline in their incomes is not offset by the 5% increase from redistribution. In other words, unless the social welfare function puts enormous weight on the poorest people in society, raising the top marginal rate from 50% to 75% reduces social welfare.....For example, in a baseline calculation, the revenue-maximizing top tax rate that ignores the innovation spillover is 92%. In contrast, the rate that incorporates innovation and maximizes a utilitarian social welfare function is just 29%. Moreover, if ideas play an even more important role than assumed in this baseline, it is possible for the optimal top income tax rate to turn negative: the increase in everyone’s income associated with subsidizing innovation exceeds the gains associated with redistribution.....This paper considers the taxation of top incomes when the following conditions apply: (i) new ideas drive economic growth, (ii) the reward for creating a successful innovation is a top income, and (iii) innovation cannot be perfectly targeted by a separate research subsidy — think about the business methods of Walmart, the creation of Uber, or the “idea” of Amazon.com. These conditions lead to a new term in the Saez (2001) formula for the optimal top tax rate: by slowing the creation of the new ideas that drive aggregate GDP, top income taxation reduces everyone’s income, not just the income at the top. When the creation of ideas is the ultimate source of economic growth, this force sharply constrains both revenue-maximizing and welfare-maximizing top tax rates. For example, for extreme parameter values, maximizing the welfare of the middle class requires a negative top tax rate: the higher income that results from the subsidy to innovation more than makes up for the lost redistribution. More generally, the calibrated model suggests that incorporating ideas and economic growth cuts the optimal top marginal tax rate substantially relative to the basic Saez calculation.... "

Tuesday, January 15, 2019

AI Summary. Full-time hourly wages for workers with a high school education or less have fallen, particularly in metro and urban areas, even as wages rose across the broader distribution. Rising urban rents, attributed to low-skilled immigration and high-skilled workers' success, mean after-rent real earnings for lower-skilled urban workers may be lower than they appear.

David Autor N/A
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David Autor’s analysis highlights a decline in full-time hourly wages for workers with high school or lower education, particularly in metro and urban areas, exacerbated by rising rental prices.

Are urban low-education workers' real wages falling once rents are counted?

Core argument: David Autor's analysis finds full-time hourly wages for workers with high school education or less have declined, especially in metro and urban areas, even as wages rise across the broader distribution.

David Autor's analysis highlights a decline in full-time hourly wages for workers with high school or lower education, particularly in metro and urban areas, exacerbated by rising rental prices. Despite a smaller share of working-age adults with only high school education in 2015 compared to 1980, the wage levels for low-education workers have fallen, even as wages generally rise across the broader distribution. This trend suggests that after accounting for rent, the real earnings of middle and lower-skilled urban workers may be lower than they appear. The influx of low-skilled immigrants and the success of high-skilled workers have driven up urban real estate values, further impacting after-rent incomes. Autor's work underscores the complex interplay between education, urbanization, and income distribution, raising questions about the economic viability of urban living for lower-paid workers and the broader implications for income inequality.

Takeaways by Macro Roundup® AI

  1. David Autor's analysis finds full-time hourly wages for workers with high school education or less have declined, especially in metro and urban areas, even as wages rise across the broader distribution.
  2. Autor notes the share of working-age adults with only a high school education was smaller in 2015 than in 1980, yet wage levels for low-education workers still fell.
  3. Autor attributes rising urban real estate values partly to an influx of low-skilled immigrants and the success of high-skilled workers, suggesting that after-rent real earnings of middle- and lower-skilled urban workers may be lower than they appear.

Autor Comment 2/2:My data suggest a fall in full-time hourly wages for workers with high school or lower education concentrated in metro + urban areas. Accounting for rising rental price in these areas would definitely accentuate this trend. But a substantially smaller share of working-age adults have high school or lower education in 2015 than did in 1980 (see below). So one could have falling wage levels for low education workers with generally rising wages across the unconditional distribution.

If you are willing to write a blurb, I would need it by June 13th. (Time is short but luckily the introductions and conclusions to each chapter convey 80% of the content with 20% of the words.)

No reader will agree with all of my conclusions. Hopefully, your blurb can carve its way to common ground between us. Of my last book for example, Andrei Shleifer chose a point he agreed with strongly and wrote: “Edward Conard’s book represents the most cogent and persuasive analysis of the financial crisis to date. It is deeper and likely more accurate than what we have seen so far from journalists, academics, and particularly former government officials.” Nouriel Roubini, who sits on the opposite side of the aisle from me, wrote: “Edward Conard provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.”

I know my views on trade and immigration are somewhat controversial, but I hope you will agree that I have written a serious book about conservative economics that addresses opposing sides of each issue fairly.

Throughout the book, I argue that properly trained talent and the economy’s capacity and willingness to take risk now constrain growth. If that’s true, then spreading these constrained (American) resources over more low-skilled workers (i.e., immigrant and offshore workers) ought to slow American low-wage wage growth relative to the rest of the economy. From my perspective, your recent work documents the downstream effects of the upstream structural forces my book tries to describe.

My second book, The Upside of Inequality: How Good Intentions Undermine the Middle Class(attached), is slated for publication September 13th. I would be honored if you would take the time to read the book and consider blurbing it.

David,

David

Thanks for the invite. I’ll give this some thought, and will try to find time to read the Intro and Conclusion, seeking inspiration for a blurb. No promises, but I appreciate your reaching out. And congratulations again on the second book!

Hi Ed,

Pages 7-14, 185-192, and 260-262 summarize the the book’s arguments more broadly.

Thank you for considering this. Despite the provocative title, I hope you find the arguments carefully considered even if you disagree with some of them. Your work is quote on page 57 in Chapter 2.

book! I enjoyed it thoroughly. It stimulated a whole set of new ideas in me."

Tyler Cowen offered to write a book review if I didn't need his blurb but privately said: "Great

Others are still reading (I hope!), but Glenn Hubbard said: “This provocative new book by Ed Conard is a must-read for serious students of economic policy. Conard’s core thesis—that advancement in living standards is constrained by risk capital and properly trained talent—suggests an inequality borne of returns from innovation. Many of his arguments will rankle either the left or the right, but his solutions are sensible and all the more compelling in the context of this paean to risk taking.”

Mitt Romney said: "Page after page, Conard challenges conventional wisdom about the causes of growing inequality, the constraints to growth, and the feasibility of commonly proposed solutions to advance a thought-provoking blueprint for growing middle- and working-class incomes in a world with an abundance of workers. Whether you agree or not, this is serious thinking for serious thinkers."

Any chance of you blurbing my book? I would be honored to include it but I would need it by Monday, so its down to the wire. Again, thank you for considering this.

Associate Department Head

Professor of Economics and

David

Best wishes,

I am hoping to get to it this weekend. But I cannot promise as I’m dealing simultaneously with many external and familial deadlines.

Dear Ed,

I understand. Thank you. If you do take the time, I hope you will see that even if you disagree with some of it, all of the arguments are well within the boundaries of serious economic thought.

Let me finally say that I’d be more than glad to find time when we are in the same city for a serious discussion of these issues. I’m no more of a fan of Piketty’s book than you are, and I think the single-minded focus on the 1% is misguided and counterproductive (indeed, I made that argument in a 2014 article inScience). I’m strongly opposed to vilifying success, and I’m strongly in favor of investing in skills. So, I’m sure we’d have much to discuss. No action required of course.

Given the above, I’m sort of a loss for a blurb that would be particularly useful for your book. I feel that if I endorsed one part of the argument (“rightly rejects the unsupported claim that the top 1% are the cause of all our troubles”), I’d want to qualify that with (“but asserts that they are in fact that cause of most of our prosperity, which is also unsupported”). But at least you can be sure that I did spend the time to take the book seriously.

I agree that the U.S. cultural of entrepreneurialism is fabulously important and a unique national asset. I concur that those who assert that the top 1% are “the cause” of stagnant median incomes and, moreover, are mostly a bunch of crony capitalists have no real evidentiary ground to stand on. But similarly, I’d say the claim that the top 1% are the key drivers of U.S. economic growth, or that taxing them more would have strongly deleterious consequences on further growth prospects, is equally unsupported by high quality evidence. (And to the extent that a substantial share of top 1% incomes derives from purely from exotic financial innovations, I think the claims are especially dubious.) Fundamentally, it is extremely hard to rigorously assess the marginal social product of the top 1%. Similarly, it is extraordinarily difficult to definitively assess the role that taxation plays in hindering or fostering entrepreneurship in the U.S. Pundits who claim that they definitely “know” the answers to these questions are either intellectually dishonest, self-deluded, or just sycophants.

As another example, the U.S. has not had better per capita growth performance than other rich countries to the best of my understanding. And most of the reason that the U.S. has higher median incomes than other rich countries is that U.S. households work more hours, not because U.S. workers and companies are more productive per hour (Japan is an exception: high hours, low productivity, though a lot of those ‘hours’ are really on the job recreation). Median income growth in the U.S. really has been quite stagnant, and real wages have fallen by more here among low-skilled workers than in almost any other advanced country.

I read the pages that you recommended, and I believe that I’ve gotten the gist of the book. I’m having trouble producing a blurb because I’m not persuaded by the arguments and — at the risk of giving offense, and taking it on faith that you’d prefer a candid answer — I do not think they are well supported by the evidence. Sure, it’s uncontroversial and doubtless correct to say that North Korea is a failed economic experiment and South Korea a successful one, but this tells us little about whether it is Germany or the U.S. that has too much or too little taxation, redistribution, or public investment.

Dear Ed,

 

PS I'd love to stop by and see you in Boston, or take you out for an A+ meal if/when you are in New York.

Again, thank you for taking the time to read/consider this.

You may not have read enough to buy/see all that, but how about giving the same (unsolicited) blurb Greg Mankiw gave my first book: "this book is more thoughtful than most economic books written for popular audiences."

Ultimately, this is a popular book, not an academic book, that express a point of view, explains why I have drawn the conclusions I have, (endeavors to) fairly explains the opposing points of view, and modulates my certianty in the body of chapters, albeit less so when I am expressing my own conclusions at the end of each chapter (mainly what you read). I warn readers that economists often work backward from their conclusions to a set of unprovable beleifs, that academics have gradually narrowed the boundaries of those beliefs, and that I have endeavored to stay within those boundaries.

As well US employment has grown 50% since 1980--2x Germany and France, 3x Japan. And the US has been more successful integrating immigrants and low socioeconomic workers.

Below-the median, America has provided a home for 55 million lesser-skilled Hispanics. US academic test score are lower. 20% of US student are low socioeconomic status vs 15% in high-wage Europe. Longer hours, yonger workers, lower unemployment rates, more women, and more first-generation immigrants all indicate a lower US marginal product of labor. And still the median is as higher or higher than high-wage Europe..

I think it's generous, however, to say Europe performs as well as the US, despite your per hour argument. Europe's productivity is pulled up by US innovation. The pay of above-the-median US workers relative to Europe is much higher than the median worker, higher still for Scandinavian-Americans, Asian-American, and other statistically significant demographics for which we have data. Similarly, high IQ US workers earn more (per your article in Science) than their counterparts elsewhere.

I warn readers that even if Europe cut taxes, it would take decades to build the institutional capabilities necessary to close this gap, and that Europe may never be able to close it (unless different technologies become the primary driver of growth). I concede that America's success could be the result of economies of scale. And I say that cutting US taxes would blow a huge hole in the deficit. I even mock Republicans who sell tax cuts by overpromising immediate growth. (And I propse swapping a lower corporate tax rate for a higher capital gains rate = the ordinary income rate to avoid enlarging the deficit). I also criticize Diamond and Saez for assuming the long term effects of lower taxes are zero with no confidnce interval whatsoever.

I do argue that relatively higher risk-adjusted payoffs for risk-taking motivates increased risk-taking, although I'm careful not to attribute higher payoffs to lower taxes but rather to a gradually compounding feedback loop where successful risk-taking creates companies like Google and Facebook that give US workers relatively more valuable on the job training. (I argue that) This coalesces into communities of experts, like Silicon Valley with synergistic and spillover benefits. It also put risk-bearing capital into the hands of investors with inside knowledge/expertise. Together these institutional capabilities increase risk-adjusted returns. The success of others also raises the bar for status. In turn, talent is more motivated to get the training and take the risks that produce innovation.

Nevertheless, I agree that the data on incentives is inconclusive, but largely because there simply aren't enough data points (although I think the evidence on the other side of the debate--economies with high taxes that have significantly outperformed their true peers--is asymmetrically thin).

I don't see incentives as the central thesis of the book. I see binding constraints as the core thesis--i.e., the economy's capacity and willingness to take risk, namely it's equity, and properly trained talent (2 sides of the same coin), and not labor or (risk-averse) savings, where economists (who don't acknowledge these constraints) tells displaced workers that competition between opportunistic entrepreneurs and other investors will restore capital per work, productivity, and wages, when the entrepreneurs have move to California and outsourced the blue collar jobs to Foxcom.

Thank you for taking a look.

Associate Department Head

Professor of Economics and

David

Hope that’s not prolix. Other deadlines call, but I know you needed a reply today.

“Conard makes a fresh argument for the productive value of inequality, which is that scarce entrepreneurial effort and risk-tolerant capital are the resources that are both most central to economic growth and most sensitive to the potential distortions imposed by taxation and regulation. Whether or not one accepts this argument, it’s an argument well worth having.”

Blurb wise, how about:

Yes, I’d be delighted to get together in either NYC or Cambridge, MA. Let’s look for an opportunity.

Dear Ed,

I also wondered about the “after-rent” wages of middle-skilled (and lower-skilled) urban workers. I believe/guess those workers are largely paid more to cover the higher cost of urban real estate, but that little of their incrementally higher pay ends up in their pocket after paying their incrementally higher rent. With the growing success of the most successful workers (and an influx of low-skilled immigrants willing to work for low wages) bidding up the value of urban real estate, it’s not hard to imagine the urban after-rent wages (and the other non-pecuniary costs of urban living for lower-paid workers) of middle and lower-skilled urban workers is not as high as it appears to be and might even be lower today than it has been.

I’m sure I’m not the first person to ask this question after watching your presentation, but I couldn’t help but wonder how the distribution of income by population density has changed over time independent of educational attainment. I’m skeptical that a college education creates much value for middle-skilled students (except where it provides technical training like nursing). If that’s true, then the pool of middle-skilled workers might have sorted into more talented workers with previously higher wages on average whose successive generations now earn college degrees but don’t earn more money (relative to the overall distribution of income, which has shifted upward within most statistically significant demographics, and partially downward from a mix shift to lesser paid demographics) but who now appear in your higher educated pool, and lesser-skilled workers who remain in the middle pool but appear to have lower wages on average, once the more talented middle-skilled workers are no longer included in the average of that pool. Seeing the changing distribution of income by population density independent of educational attainment would make that easier to adjudicate.

I watched your AEA presentation (as I do all your work). I am still pondering its implications. I appreciate this work and all your extraordinary contributions.

Ed Comment 1/2:

David

Best,

Good Q's, of course!

Sorry for the run-on sentences. As usual, your high-quality work has been on my mind. Thanks for that.

Yes, that only makes the story more troubling. No question that cost of living has risen faster in urban areas than elsewhere. So the declining non-COL urban wage gradient for non-college workers portends an even steeper fall in COL-adjusted real earnings for non-college workers in these places.

I also wondered about the “after-rent” wages of middle-skilled (and lower-skilled) urban workers. I believe/guess those workers are largely paid more to cover the higher cost of urban real estate, but that little of their incrementally higher pay ends up in their pocket after paying their incrementally higher rent. With the growing success of the most successful workers (and an influx of low-skilled immigrants willing to work for low wages) bidding up the value of urban real estate, it’s not hard to imagine the urban after-rent wages (and the other non-pecuniary costs of urban living for lower-paid workers) of middle and lower-skilled urban workers is not as high as it appears to be and might even be lower today than it has been.

I'm sure thataverageincomes have risen more in urban areas. I mean, they have to have. Urban areas have become much more highly skilled, high skill wages have increased, and they've increased by more in urban areas. Perhaps this will help. I'm attaching two plots of real mean log wages by five exhaustive and mutually exclusive education categories. The "1950" plot covers from 1950 to 2015. The 1980 plot covers 1980 to 2015 with more intervening years plotted (1980, 1990, 2000, 2007 2015).

I’m sure I’m not the first person to ask this question after watching your presentation, but I couldn’t help but wonder how the distribution of income by population density has changed over time independent of educational attainment. I’m skeptical that a college education creates much value for middle-skilled students (except where it provides technical training like nursing). If that’s true, then the pool of middle-skilled workers might have sorted into more talented workers with previously higher wages on average whose successive generations now earn college degrees but don’t earn more money (relative to the overall distribution of income, which has shifted upward within most statistically significant demographics, and partially downward from a mix shift to lesser paid demographics) but who now appear in your higher educated pool, and lesser-skilled workers who remain in the middle pool but appear to have lower wages on average, once the more talented middle-skilled workers are no longer included in the average of that pool. Seeing the changing distribution of income by population density independent of educational attainment would make that easier to adjudicate.

Dear Ed, Thanks for your message and for your Q's. I'm going to respondvbriefly because I'm under an urgent deadline towrite upthat Ely Lecture for the AEA conference publication.

Autor Comment 1/2:

Ed Comment 2/2:David,Thank you. No need to respond to this. I read your presentation as suggesting cities have contributed to a hollowing out the middle class. I suspect the rising price of urban real estate prices may make that true (for after-rent incomes). But I didn’t find much change to America’s distribution of income, just an upward shift (see attached). Perhaps middle-class Americas are just moving to locations where they can find higher standards of living. I can’t help but wonder how the choice of bookends (e.g., income or educational attainment) creates theappearance of a hollowing out. Anyway, I greatly appreciate your contributions.

AI Summary. The authors estimate that inventors are less likely to locate in U.S. states with higher taxes, with an elasticity to the after-tax income share of 0.11 for local inventors and 1.23 for non-local inventors. Both personal and corporate taxes are associated with the quantity and quality of innovation, though existing clusters of innovation reduce tax sensitivity.

Stefanie Stantcheva National Bureau of Economic Research
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Inventors are significantly less likely to locate in states with higher taxes, with an elasticity to the net-of-tax rate of 0.11 for local inventors and 1.23 for non-local inventors.

Do higher state taxes reduce where inventors locate and innovate?

Core argument: Inventors are less likely to locate in states with higher taxes, with an estimated elasticity to the net-of-tax rate of 0.11 for local inventors and 1.23 for non-local inventors.

Inventors are significantly less likely to locate in states with higher taxes, with an elasticity to the net-of-tax rate of 0.11 for local inventors and 1.23 for non-local inventors. Corporate inventors show high sensitivity to taxes, impacting both the quantity and quality of innovation. Agglomeration effects mitigate tax sensitivity when innovation is already present in a state. Both personal and corporate taxes influence innovation at macro and micro levels, affecting location decisions and innovation quality. The effects are economically large, with cross-state spillovers and extensive margin decisions compounding individual elasticities. The study highlights the importance of understanding tax impacts on innovation, suggesting that optimal tax formulas should consider these elasticities to balance efficiency costs against revenue gains.

Takeaways by Macro Roundup® AI

  1. Inventors are less likely to locate in states with higher taxes, with an estimated elasticity to the net-of-tax rate of 0.11 for local inventors and 1.23 for non-local inventors.
  2. Corporate inventors are highly sensitive to taxes, with personal and corporate taxes affecting the quantity and quality of innovation, while agglomeration effects mitigate tax sensitivity where innovation is already present.
  3. The estimated effects are economically large, with cross-state spillovers and extensive margin decisions compounding individual elasticities, and optimal tax formulas should weigh these elasticities against revenue gains.

"... We find that inventors are significantly less likely to locate in states with higher taxes. The elasticity to the net-of-tax rate of the number of inventors residing in a state is 0.11 for inventors who are from that state and 1.23 for inventors not from that state. Inventors who work for companies are particularly elastic to taxes. Agglomeration effects appear to matter for location as well: inventors are less sensitive to taxation in a potential destination state when there is already more innovation in that state in their particular field of inventive activity. This is also true if an inventor's employer already has a record of innovation activity in that state.We confirm that firms are responsive to corporate taxes when choosing where to locate by estimating a location choice model at the individual R&D lab level. Our main findings can therefore be summarized as follows. Taxation in the form of both personal income taxes and corporate income taxes matters for innovation along the intensive and extensive margins, and both at the micro and macro levels. Taxes affect the amount of innovation, the quality of innovation, and the location of inventive activity. The effects are economically large especially at the macro state-level, where cross-state spillovers and extensive margin location and entry decisions compound the micro, individual-level elasticities. Not all the effects of taxes at the macro-level are accounted for by cross-state business stealing or spillovers. Corporate inventors are most sensitive to taxation; and positive agglomeration effects play an important role, perhaps in offering a type of compensating differential for taxation.......We have studied the effects of personal and corporate income taxes on innovation in the United States during the 20th century using a series of newly constructed datasets. Our data is sufficiently wide-ranging that we can consider both inventors and firms engaged in inventive activity over a long time period, and we can exploit the numerous changes to the U.S. tax code taking place over the 20th century. We document the effect of taxes at the macro (state) and micro (inventors and firm) levels and attempt to identify the estimates empirically. We find that both personal and corporate taxes matter for innovation. The quantity, quality, and the location of innovation are all affected by the tax system and the effects are quantitatively important. In addition to being able to document and identify these important responses to taxation, our estimates can help calibrate the tax elasticities needed in optimal tax formulas for labor or capital income (see Saez (2001) and Saez and Stantcheva (2018)), as well as quantify the efficiency costs of taxation, which are traded off against the revenue gains. Furthermore, our empirical evidence provides a sense of how firms and inventors respond to the net return to innovation, and not only to tax rates, which are merely a component of that economic calculation. In future work, it would be fruitful to compare the U.S. experience to other countries, historically and contemporaneously. That would require a major data collection effort, as we have undertaken for the U.S., but our analysis highlights the benefits of such investments. Currently we know very little about the impact of taxation on innovation over long time horizons, and our analysis is therefore an important first-step in building a better understanding of a relationship that is critical in policy discussions. While our estimates show that the state-level effects of taxes are not purely due to zero-sum business-stealing, it is still an open question as to how the federal tax rate affects national-level innovation in the U.S., when taking into account the international mobility of inventors, firms and intellectual property. An answer to that question is central to a fuller understanding of a tax regime’s real impact...."
Ufuk Akcigit, John Grigsby, Tom Nicholas and Stefanie Stantcheva, "Taxation and Innovation in the 20th Century," National Bureau of Economic Research, September 2018, http://www.nber.org/papers/w24982

Stantcheva is a frequent Saez collaborator

AI Summary. The authors estimate a long-run elasticity of star scientists' location with respect to state personal income taxes of 1.7, implying lower top tax rates are associated with larger net inflows of top scientific talent. They estimate New York's cut in the top personal income tax rate from 7.5% to 6.85% raised net inflows about 3% annually.

Enrico Moretti American Economic Review
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NY State cutting personal income tax rate on top 1% of earners in 2006 increased net inflow of star scientists to NYS by +3% a year.

Do state income taxes influence where top scientists locate?

Core argument: Star scientists show a long-run mobility elasticity of 1.7 with respect to state personal income taxes, implying that lower top rates increase the inflow of top talent.

The elasticity of mobility for star scientists in response to state tax changes is notably high, with a long-run elasticity of 1.7 for personal income taxes. This suggests that a reduction in personal income tax rates can significantly increase the inflow of top talent. For instance, New York's 2006 cut in personal income tax rate for the top 1% from 7.5% to 6.85% resulted in a net inflow increase of star scientists by 3% annually. Over a decade, this policy added 30 star scientists to New York's stock, marking a 2.6% rise. These findings highlight the substantial impact of tax policy on the geographical distribution of highly skilled workers, although other factors like innovation clusters also play a crucial role in location decisions.

Takeaways by Macro Roundup® AI

  1. Star scientists show a long-run mobility elasticity of 1.7 with respect to state personal income taxes, implying that lower top rates increase the inflow of top talent.
  2. New York's 2006 cut in the top 1% personal income tax rate from 7.5% to 6.85% raised the net inflow of star scientists by 3% annually, adding 30 star scientists over a decade, a 2.6% increase in its stock.
  3. Tax policy shapes the geographical distribution of highly skilled workers, though other factors such as innovation clusters also influence location decisions.

We looked at a preliminary version of this paper but here is the final version. Moretti on the elasticity of mobility of human talent in the face of high tax rates. Findings should be useful.

"...We focus on the locational outcomes of star scientists, defined as scientists—in the private sector as well as academia and government—with patent counts in the top 5 percent of the distribution.....We define star inventors, in a given year, as those who are at or above the ninety-fifth percentile in number of patents over the past ten years. In other words, stars are exceptionally prolific patenters.....The state pair with the most bilateral flows over this decade was California-Texas; 26 star scientists per year moved from Texas to California and 25 per year moved from California to Texas. Close behind was California-Massachusetts, with 25 per year moving from Massachusetts to California and 24 moving in the opposite direction....We uncover large, stable, and precisely estimated effects of personal and corporate taxes on star scientists’ migration patterns. The long-run elasticity of mobility relative to taxes is 1.7 for personal income taxes, 1.8 for state corporate income tax, and 1.6 for the investment tax credit. In terms of stocks, our elasticities imply that if the net-of-tax rate increases in a state (holding other states’ rates constant), due to a cut in the personal income average tax rate or the corporate tax, the stock of scientists in the state will rise by 0.4 or 0.42 percent per year for as long as the increase in the net-of-tax rate differential lasts. These elasticities are economically large and significantly larger than the conventional labor supply elasticity. The effect on mobility is small in the short run, and tends to grow over time.While we can’t rule out that our estimates are biased by unobserved demand or supply shocks, a number of additional pieces of evidence lend credibility to a causal interpretation of our estimates. First, we find no evidence of pretrends: changes in mobility follow changes in taxes and do not to precede them. Second, the effect of corporate income taxes is concentrated among private sector inventors: no effect is found on academic and government researchers. Third, corporate taxes only matter in states where the wage bill enters the state’s formula for apportioning multistate income. No effect is found in states that apportion income based only on sales (in which case labor’s location has little or no effect on the tax bill). We also find no evidence that changes in state taxes are correlated with changes in the fortunes of local firms in the innovation sector in the years leading up to the tax change. Finally, within-firm evidence suggests that multistate firms adjust the share of employment in each state as a function of business taxes. Overall, we conclude that state taxes have significant effect on the geographical location of star scientists and possibly other highly skilled workers. While there are many other factors that drive when innovative individual and innovative companies decide to locate, there are enough firms and workers on the margin that relative taxes matter....Of course, taxes are not the only factor that can determine the location of star scientists. Indeed, we find a limited cross-sectional relationship between state taxes and number of star scientists in a state as the effect is swamped by all the other differences across states. California, for example, has relatively high taxes throughout our sample period, but it is also attractive to scientists because of the historical presence of innovation clusters like Silicon Valley and the San Diego biotech cluster....As an illustration, our estimates imply that the effect of New York cutting its statutory personal income tax rate on the top 1 percent of earners from 7.5 percent to 6.85 percent in 2006 was to increase the net inflow of star scientists to the state by about 3 per year, which is a sizable effect over time. Over a ten-year period, for instance, this implies an addition of 30 to New York’s stock of star scientists—a 2.6 percent increase...."

Enrico Moretti and Daniel Wilson, "The Effect of State Taxes on the Geographical Location of Top Earners: Evidence from Star Scientists,"American Economic Review, 2017, https://eml.berkeley.edu//~moretti/taxes.pdf

AI Summary. U.S. startup creation rates are closely correlated with population growth, with a 1% increase in population growth associated with a 0.871 percentage point higher startup rate, according to Moody's Analytics.

Adam Ozimek and Brendan Meighan Moodys
Date Posted:
Is Database:
Database

Moody’s Analytics shows a strong correlation btw US startup creation rates & population growth, with a 1% increase in population growth leading to a 0.871pp rise in the startup rate.

Does faster population growth raise startup creation rates?

Core argument: Moody's Analytics finds a 1% increase in U.S. population growth is associated with a 0.871 percentage point rise in the startup rate.

Moody's Analytics reveals a strong correlation between U.S. startup creation rates and population growth, with a 1% increase in population growth leading to a 0.871 percentage point rise in the startup rate. This data underscores the importance of demographic trends in fostering entrepreneurial activity, suggesting that regions experiencing population expansion are more likely to see a surge in new business ventures. The findings highlight the potential for economic revitalization in areas with growing populations, as increased firm creation can drive job creation and innovation. This relationship between population dynamics and entrepreneurship could inform policy decisions aimed at stimulating economic development through targeted support for regions with favorable demographic trends.

Takeaways by Macro Roundup® AI

  1. Moody's Analytics finds a 1% increase in U.S. population growth is associated with a 0.871 percentage point rise in the startup rate.
  2. Moody's Analytics data suggest U.S. regions with expanding populations are more likely to see increased new business creation.
  3. The relationship between population dynamics and entrepreneurship identified by Moody's Analytics could inform policy supporting regions with favorable demographic trends.

A study by Moody’s Analytics shows the U.S. start-up creation rate is highest in parts of the country that are seeing population growth, a “1% increase in population growth, the startup rate increased 0.871 percentage point.”

Adam Ozimek and Brendan Meighan. “Where the Entrepreneurs Are,” Moodys, December 12, 2018, https://www.economy.com/dismal/analysis/free/348933/Where-the-Entrepreneurs-Are/