Earlier this year the European Commission released a substantial report on R&D tax credits throughout the EU and several other OECD countries including the United States and Japan. R&D tax credits have been widely adopted across the developed world since the United States introduced the Research and Experimentation tax credit in 1981: only two countries in the EU do not have tax policies intended to encourage R&D.
The report is a thorough meta-study looking at the existing economics literature and available data on R&D-focused tax policy, including the impact of R&D tax policies on R&D expenditure, innovation, employment, productivity, and other factors. It also covers the literature on how corporate tax policy can affect the location of R&D and patents. Finally, the report examines the details of various tax policies and benchmarking them based on what they determine to be best practices.
The report makes a number of facts clear. First, despite a broad range of findings, “the vast majority” of studies surveyed show that R&D tax incentives are effective, with the most recent (and rigorous) studies finding that a 10% in the user cost of R&D results in a
A new report from Battelle based on methodology from the Academy of Radiology Research shows how federal R&D funding succeeds in producing patents. The report examines essentially all federal R&D, including not only the Department of Defense and the National Institutes of Health but also the Department of Energy, the National Science Foundation, NASA, and other agencies. It finds that, per patent, public-sector agencies provide a return comparable to private-sector ones—or even cheaper. Recent public sector budget cuts, therefore, can be expected to significantly hurt our scientific progress.
The agencies vary significantly in terms of how productive they are and how successful their patents are. Some agencies in particular, such as the National Institute of Biomedical Imaging and Bioengineering (NIBIB) have exceptional records for producing research that is widely useful: NIBIB is estimated to spur an additional $578.2 million, or 25 patents, for every $100 million in R&D expenditures. The DoD and NASA, on the other hand, are less efficient at producing patents at only around 2-3 patents per $100 million in R&D expenditures. (although, as the report notes, defense spending is more likely to be classified and thus not
A new SSRN paper finds that research and development (R&D) helps manufacturers keep ahead of competition from imports. U.S. manufacturing firms in industries with strong import competition from China fared better 50 percent better when they had larger stocks of capital used for R&D. While this finding is intuitive, it provides an important piece of evidence that reiterates a critical point about the U.S. economy: international competitiveness is extremely important and smart R&D policy (including tax credits) is a key method of maintaining it.
The authors Johan Hombert and Adrien Matray use granular industry-level data on imports from China and show that these imports have a significant impact on the performance of U.S. manufacturing firms. They then examine whether this impact changes depending on how much R&D capital firms have. In order to make sure the R&D capital isn’t related to other factors, they use state-level changes in R&D credit policy during the 1980s.
Their results here show that firms that had access to cheaper R&D and were thus more likely to acquire more R&D capital had an easier time “climbing the quality ladder” and staying competitive in the face
Senator and likely presidential hopeful Marco Rubio (R-FL) appeared on last Tuesday’s The Daily Show with Jon Stewart, promoting his new book and weathering an endless stream of jokes about his home state of Florida. While the discussion covered a range of policy ground, we wanted to highlight one comment by Senator Rubio that showed an all too common misunderstanding of innovation and automation.
Rubio said, “The concern I have about the minimum wage increase is that we have been told by the CBO and independent analysts that it will cost certain jobs. And that happens when some businesses will decide that well, you’ve now made our employees more expensive than machines so we’re going to automate. So in 5-10 years it’s going to happen anyway but this will accelerate this process, when you go to a fast food restaurant it will not be a person taking your order, there will be a touchscreen there that you will order from and when you get your order it will be right. [uneasy laughter] But the point is, if you make that person now more expensive than that new technology, they’re going
Ask any economist why some countries are poor and some countries are rich, and they will probably answer, “productivity”. Essentially, this means that people in rich countries are rich because they are able to create more wealth with less effort. But how do they do this? One of the primary ways is through better technology.
Unfortunately, instead of being recognized for its contribution to wealth, better technology is all too often demonized as a threat to employment, particularly in low-income countries without social safety nets. Intuitively, people care more about the jobs and income streams that already exist than the potential future savings from automating their jobs–a bird in hand, as they say. But a new paper by Mehmet Ugur and Arup Mitra of the University of Greenwich shows that even in very poor countries, technology is far less threatening than it may appear.
We have argued here before that robots are not taking our jobs: in the long run on a macro level productivity increases have no relationship with either the total number of people employed or with the level of unemployment. This is because when automation or
We’ve posted recently about how our current immigration policy is hurting Silicon Valley. But when the United States lets in more immigrants, what happens? Often it’s not what you would expect.
A new NBER paper by economists at the University of California Davis and Colgate University studies the effect of skilled H1-B immigrants in STEM occupations on more than 200 cities across the country. In cities with more STEM immigrants, wages for college-educated workers went up 7-8 percentage points, wages for non-college-educated workers went up about half as much, and there was no significant effect on employment.
Why this counterintuitive result? Economics 101 says that when the supply of something grows, the price should decrease, not increase. As is too often true, however, Economics 101 in this case tells us very little about the real world. Figuring out cause and effect in many types of markets, particularly labor markets, is tough because economies are not as simple as the textbook models might have you believe.
What actually happens is that when immigrants enter an economy, they do more than just offer their labor at a (potentially) lower price. They increase
The digital economy has been a major boon to U.S. domestic and international trade, as is documented by a new report by the United States International Trade Commission entitled Digital Trade in the U.S. and Global Economies (summary here). And even though the report shows important benefits from digital trade, those benefits are likely understated. This is because the report limited its analysis to “digitally intensive” sectors, which means that its numbers exclude contributions from firms that only use digital trade as a smaller part of their business.
Still, digital trade has made quite an impact: the report estimates that digital trade has raised real U.S. GDP by $517.1-$710.7 billion (3.4−4.8 percent) by increasing productivity and lowering the costs of trade. By raising GDP, digital trade increased average wages, and the increased wages likely contributed to increased employment by as much as 2.4 million jobs.
Within digitally intensive industries (and likely within many non-digitally intensive industries, although the report focused on the former), the internet has come to play a major role in everyday commerce. Firms in these industries sell nearly a trillion dollars’ worth of goods and services
In July 2014, ITIF’s Stephen Ezell testified before the Senate Finance Committee regarding the importance of manufacturing to America’s economy and the role that U.S. trade and technology policy plays in supporting American manufacturing. As part of his testimony, Ezell cited data describing the rapid decline of U.S. manufacturing employment to demonstrate the severity of the challenges faced by America’s manufacturing industries. For the reality is that, particularly since 2000, America’s manufacturing sector has been in a steep decline, with job losses outpacing those in many peer countries.
Following the hearing, Marc Levinson, a Section Research Manager with the Congressional Research Service, produced a report countering some of the data in Ezell’s testimony, and suggesting that there is not a clear cause for alarm regarding employment losses in the American manufacturing sector. However, Levinson’s account does not fully present all of the facts and only succeeds in further muddying this important policy debate.
One critique Levinson makes is charging Ezell with bias in selecting base years, which can have a sizable impact on analytical results. Levinson presents data using the years 1991 to 2000 and then the years from 2001
U.S. productivity growth is stagnating, and if the trend continues it could have a drastic impact on the U.S. economy. Without increasing productivity, the only way for a country to get richer is by working more or borrowing more. Furthermore, productivity is a crucial part of international competitiveness, because it is only by increasing our productivity that we can compete with other countries on cost.
A recent BLS news release does a good job of showing the worrying trends. Productivity growth has been abnormally low since approximately 2006, plummeting through the Great Recession, recovering slightly immediately afterward, and slowing considerably since 2010.
The first graph below (Chart 1) provides historical context back to 2000. There is a clear decline in labor productivity (the dark blue line) and also multifactor productivity (light blue). These are the two most common ways of understanding output growth: labor productivity estimates how much each worker produces and multifactor productivity tells us how much each worker and unit of capital can together invest.
Looking back a bit further in time, the next graph (Chart 2) estimates the amount that different factors contributed to total productivity growth.
It doesn’t take long to get the drift of a new report from the Center for Immigration Studies, a non-partisan, anti-immigration think tank. The title basically sums it up: “All Employment Growth Since 2000 Went to Immigrants.” The only question left to the reader is, why they didn’t simply title it “Immigrants stole all of our jobs”?
Perhaps it’s because immigrants didn’t steal our jobs, and the authors have no evidence that they did, but they’re doing their best to insinuate that they do.
Their main findings certainly look surprising at first blush: immigrant employment has increased significantly since 2000, but native employment has not increased at all, despite the fact that native population has increased twice as much as immigrant employment. It seems like a closed case: all the new jobs went to immigrants, therefore we should decrease immigration.
If only it were that simple. As intuitive as it might seem to argue that a job is a job and an unemployed person is an unemployed person, this is not how economies work. The Center makes a mistake common to many casual observers of the labor market: what economists