As Congress makes progress on a bipartisan infrastructure deal, Democrats turn their attention to the sizable $3.5 trillion reconciliation package. The bill includes major pieces of President Biden’s Build Back Better platform and the American Families and Jobs Plans. Some moderate Democrats have voiced concerns about the size and scope of the package—foretelling of difficult negotiations ahead.
As lawmakers begin those discussions, however, we should not forget about a group that doesn’t get a seat at the table for policy debates: the United States’ more than 73 million children. The reconciliation package should prioritize investments in kids, not just to equalize our relatively low rates of spending on youth, but because doing so has huge shared benefits and among the highest rates of return for any social investment.
Senate Democrats have promised that both the $579 billion Bipartisan Infrastructure Framework and the $3.5 trillion budget blueprint they are advancing this week will be “fully paid for.” While there’s a case for borrowing to finance the most pro-growth infrastructure investments when interest rates are low, lawmakers’ commitment to fiscal discipline is reassuring at a time when the national debt is at record levels and inflation concerns are heating up. But signs are emerging that lawmakers will struggle to keep that promise as they flesh out the details. The upcoming budget resolution is an important opportunity to begin developing clearer financing plans and safeguards to uphold the agreements.
President Joe Biden initially proposed tax increases on corporations and wealthy households that would raise roughly $3.3 trillion in new revenue over the next 10 years to finance his American Jobs and Families Plans. That revenue would almost be enough to pay for the $3.5 trillion in new spending agreed to by Senate Democratic leadership last week, but several key lawmakers have already called for reducing the scope of those tax hikes.
Meanwhile, on the spending side, the budget agreement incorporates provisions — such as a costly Medicare expansion — that weren’t included in either the Jobs or Families Plan. Negotiators have said they will keep the bill’s sticker price under $3.5 trillion by setting the duration of some programs, including an expansion of the Child Tax Credit, to arbitrarily expire after a few years. But this move would be nothing more than a gimmick: The Committee for a Responsible Federal Budget estimates the package could cost up to $5.5 trillion over the coming decade if lawmakers allowed all the policies slated for inclusion in the budget blueprint to become permanent (as is clearly their ultimate intention).
Similar problems with fuzzy accounting plague the Bipartisan Infrastructure Framework. For example, negotiators have said they will pay for $70 billion of spending by cutting fraud from unemployment benefits even though the Congressional Budget Office estimates that overpayments over the next decade will be less than half that amount. The framework also counts offsets such as selling the strategic petroleum reserve, which may need to be bought back at a higher price, and sales of spectrum that have already occurred or would occur under current law. The situation worsened over the weekend when Republicans demanded that increased funding to help the IRS collect unpaid taxes — one of the few legitimate sources of real revenue included in the bipartisan deal — be dropped from the package. .
Some economists and politicians would argue that the policies in these packages don’t need to be paid for because they are public investments in the future. On the one hand, it makes sense to borrow from future generations to pay for investments they will benefit from, particularly when interest rates are low. But on the other, the federal government is currently on track to spend roughly $8 trillion more on programs that aren’t public investment than it will collect in taxes over the next decade, and some of the policies under discussion would further add to that category of spending. Interest rates are also likely to rise between now and when the money in these bills is actually spent. Even if lawmakers are content to borrow $4 trillion for public investment, they should pair it with $4 trillion of revenue to reduce the “consumption deficit” that no responsible leader can defend.
Deficit spending, even for worthwhile long-term investments, could also have negative short- and medium-term consequences if it occurs at a time when the economy is overheating. Much of the $2 trillion spent on the American Rescue Plan earlier this year was necessary to help our economy recover from the pandemic recession, but it has also likely contributed to higher-than-expected inflation. Although most economists believe these recent spikes are likely transitory, nobody can know for sure until later this year or early next. Lawmakers should therefore be wary of committing to a massive new spending bill in the near future before having a plausible plan for how to pay for it.
The Senate will soon vote on a budget resolution that includes instructions telling Congressional committees how much their policies can add to the deficit in a reconciliation bill (the legislative vehicle that will allow Democrats to pass their $3.5 trillion agreement without any Republican votes). Even though lawmakers could pass a reconciliation bill that increases the deficit by less than the amount allowed by the budget resolution, neither the American Rescue Plan nor the 2017 Trump tax cuts left anything on the table.
Therefore, if Congress is serious about paying for the upcoming spending bills, it should safeguard the agreement by passing a budget resolution that instructs the reconciliation process not to increase total budget deficits at all (there could still be some modest deficit-spending in a bipartisan infrastructure bill). Lawmakers must also eschew timing gimmicks that hide the true cost of the policies they are enacting and create uncertainty for working families who may plan their lives around new programs. A broader menu of revenue options, such as a carbon tax, inheritance tax, or progressive consumption tax, should be on the table to cover the costs of these policies. And if lawmakers cannot get consensus on a revenue package big enough to cover their spending ambitions, they should prioritize the most pro-growth public investments and cut what they are unwilling to pay for.
The $3.5 trillion budget blueprint unveiled earlier this week by Senate Democrats would fund many policies from President Joe Biden’s American Jobs and Families Plans not covered by the $579 billion Bipartisan Infrastructure Framework. But among many worthwhile public investments is a new proposal that should give lawmakers pause: a costly expansion of Medicare paid for entirely by young Americans. Although lawmakers should be open to thoughtful improvements to Medicare, any changes must be financed in a way that is fair to Americans of all ages.
There are two possible changes to Medicare that Sen. Bernie Sanders, I-Vt., the chairman of the Senate Budget Committee, wants to include in the next major spending bill. The first proposal is to offer vision, dental, and hearing services not currently covered by Medicare at no additional cost to beneficiaries. The second proposal is to give Americans ages 60-64 the option to enroll in Medicare with the same premiums and benefits currently available to those over age 65 (which are heavily subsidized by income and payroll taxes paid by younger workers).
The problem with these proposals is that Medicare is already struggling to pay for the current suite of benefits it offers. Medicare Part A, which offers hospital insurance that is supposed to be fully funded by payroll taxes, will face a 10% budget shortfall five years from now. The amount of general revenue needed to subsidize Medicare Parts B and D, which cover physician services and prescription drug benefits, is projected to nearly double as a percent of gross domestic product over the next 20 years. These costs will impose a significant burden on young Americans, either by crowding out investments in their future or requiring them to pay higher taxes than current retirees did when they were in the workforce.
Giving today’s seniors, who have collectively enjoyed greater gains in income and wealth than younger Americans, a suite of new benefits they didn’t finance over their working lives or in retirement would only compound the intergenerational inequity built into current policy. That’s especially true if the Senate blueprint foregoes some investments in clean energy or child welfare, such as a permanent expansion of the Child Tax Credit, to make room for this costly expansion of Medicare.
There are better alternatives. Americans ages 60-64 could be allowed to buy into Medicare at a premium that covers the full cost of their coverage rather than the heavily subsidized one currently paid by people aged 65 and over. This option would still be cheaper for most beneficiaries than private insurance because Medicare is able to negotiate lower prices for services than private insurers. Any new vision, dental, or hearing benefits should have a significant share of the cost covered by income-based premiums and co-pays, as is currently the case for Parts B and D. A broad-based consumption tax that is paid by all consumers regardless of age could also help finance benefits in a way that doesn’t place the burden on anyone generation. Lawmakers should also consider pairing or preceding any benefit expansion with measures to close the existing financial shortfall in Medicare, such as the bipartisan TRUST Act.
For too long, Washington has allowed the growth of retirement programs to crowd out critical public investments in infrastructure, education, and scientific research. The new budget agreement is a once-in-a-generation opportunity to right this intergenerational wrong. It would be shameful for lawmakers to choose affluent retirees over working families yet again. Any expansion of Medicare should require some contribution by those who would benefit, or it should be dropped from the budget agreement altogether.
Today, the Labor Department released a new batch of inflation data for the year ending in June. The headline number for the consumer price index has sparked panic in some quarters, as year-over-year inflation is now at 5.4%, the highest annual rate since 2008.
While this backward-looking measure is currently above its recent historical average, there is little cause for concern based on market forecasts of future inflation. Medium-term inflation expectations remain well-anchored, as bond prices show an expected average rate of inflation of 2.2% between 5 and 10 years from today.
This is a very clear market signal that inflation pressures are transitory and will abate as supply chain issues caused by the pandemic work themselves out. Notably, motor vehicles represented 60% of the month-over-month inflation increase in June. As the global semiconductor shortage ebbs, we can expect motor vehicle inflation to return to its historical average.
Another way to strip out the most volatile sectors of the economy and get a clearer picture of where inflation is heading is to look at median CPI, which includes only the middle changing item in the CPI’s basket of goods and services. In contrast to headline CPI, median CPI remains stable at 2.2% year-over-year. In the chart below you can see that CPI is more volatile than median CPI, and historically it has reverted toward median CPI after short deviations.
Lastly, year-over-year inflation numbers remain plagued by base effects, as the economy was depressed in June 2020 due to the poor handling of the pandemic by the Trump administration. Looking at two-year core inflation numbers shows that inflation is still within its historical range at 2.8%. This number is entirely consistent with the Federal Reserve’s average inflation targeting framework, which targets 2% average inflation over the business cycle with short periods of above average inflation making up for periods of below average inflation.
While there is not yet much reason to panic about long-run inflation, there are still things policymakers can do today to decrease the risk of inflation expectations becoming unmoored. For the first time in decades, we have sufficient demand in the economy to support rapid growth. Now we just need supply side investments and reforms to make sure that demand turns into real growth rather than increased inflation. Three items immediately spring to mind for policymakers to work on.
First, Congress should double down on its efforts to pass a bipartisan infrastructure package. While it may seem odd to spend more money to tamp down inflation, infrastructure spending is a special kind of spending. It’s an investment in the future productivity of our economy.
Second, the administration needs to follow through on many of the commitments it made last week in its executive order on promoting competition. Sectors like health care have been driving a disproportionate share of inflation in recent years. Encouraging more competition in that sector and others will have a disinflationary effect. Similarly, policymakers should avoid an unforced error by inadvertently harming sectors like tech and e-commerce, which have been holding down inflation in recent years.
Third, the Biden administration should begin to roll back tariffs implemented during the Trump presidency. These are taxes ultimately borne by American consumers and they raise the input costs for American manufacturers, making them less competitive in global markets.
The Mosaic Economic Project application process is now open for the September 2021 Women Changing Policy workshop, scheduled for September 13-15, 2021.
“The Women Changing Policy workshop is an opportunity for diverse women with expertise in economics and technology to hone the skills needed to communicate their work and ideas to policy makers and the media,” said Crystal Swann, Mosaic Economic Project Lead and PPI Senior Fellow. “Through our interactive format, participants get hands-on experience learning the ins and outs of Washington politics and on how to become a go-to policy expert. And it’s a chance to expand their networks.”
This is the third Women Changing Policy workshop. Previous workshops have included candid conversations with influencers in public policy, including leaders and representatives from the United States Congress, the media, and other experts from the policymaking ecosystem.
We encourage women with expertise in economics, finance, technology, telecom and corporate governance to apply. Applicants should be well established in their careers – be it at a corporation, academic institution or NGO–and looking for opportunities to grow their influence on critical issues, from the wealth gap to infrastructure to health care. The Mosaic Economic Project aims to bring new voices to the policy arena. To that end, we value diversity in applicants. This workshop will be held virtually, and the deadline to apply is August 31, 2021.
The Mosaic Economic Project is a network of diverse women in fields of economics and technology. Mosaic programming provides coaching on presenting skills and focuses on connecting and advocating for cohort participants’ to engage in public policy debates, with a particular focus on engaging Congress and the media.
The Progressive Policy Institute (PPI) is a catalyst for policy innovation and political reform based in Washington, D.C. Its mission is to create radically pragmatic ideas for moving America beyond ideological and partisan deadlock. Learn more about PPI by visiting progressivepolicy.org.
For the firms that adopt them, artificial intelligence (AI) systems can offer revolutionary new products, increase productivity, raise wages, and expand consumer convenience.[1] But there are open questions about how well the ecosystem of small and medium-sized enterprises (SMEs) across the United States is prepared to adopt these new technologies. While AI systems offer some hope of narrowing the recent productivity gap between small and large firms, that can only happen if the technologies actually diffuse throughout the economy.
While some large firms in the U.S. are on the cutting edge of global AI adoption, the challenge for policymakers now is to help these technologies diffuse across the rest of the economy. To realize the full productivity potential of the U.S., AI tools need to be available to 89% of U.S. firms that have fewer than 20 employees and the 98% that have fewer than 100.[2] An AI-enabled productivity boost would be particularly timely as SMEs are recovering from the effects of the ongoing COVID-19 crisis.
The report discusses the promise for AI systems to increase productivity among U.S. SMEs, the current barriers to AI uptake, and policy tools that may be useful in managing the risks of AI while maximizing the benefits. In short: there is a wide range of policy levers that the U.S. can use to proactively provide the underlying digital and data infrastructure that will make it easier for SMEs to take the leap in adopting AI tools. Much of this infrastructure operates as a type of public good that will likely be underprovided by the market without public support.
Benefits of AI adoption:
The central case for AI adoption is that human cognition is limited in a variety of ways, most notably in time and processing power. Software tools can improve decision-making by increasing the speed and consistency with which decisions can be made, while also allowing more decisions to be planned out ahead of time in the event of various contingencies. Under this broad framework, we can think about “AI” as being a broad suite of technologies that are designed to automate or augment aspects of human decision-making.
While many of AI’s most eye-catching use cases will likely remain the preserve of large platforms, the technology also holds tremendous promise for SMEs. The adoption of third-party AI systems will notably enable SMEs to streamline mundane (but often costly) tasks such as marketing, customer relationship management, pre- and post-sales discussions with consumers, and Search Engine Optimization (SEO). These systems can provide a lifeline for SMEs who are overwhelmed by the many challenges of running a business, and they can expand the number of businesses that are eligible for certain financial supports. For example, AI tools can be used to improve the accuracy of credit risk underwriting models and using alternative data sources and a streamlined process, they can make it easier for SMEs to take out loans they otherwise might not qualify for under traditional methods. Along similar lines, research shows that AI-driven robotics have (and will continue) to boost the productivity of SMEs in the manufacturing industry.
Importantly, this upcoming wave of AI technology can help SMEs catch up with larger, international firms because it can democratize the benefits of large information technology (IT) investments that superstar firms have been seeing over the last decade.
The economist James Bessen has argued that the top 5% of firms in many industries have been increasingly pulling away from the rest of the field because they’ve made large investments in proprietary IT systems. Their smaller rivals struggle to develop their own systems because they lack the necessary scale to hire a large stable of in-house technical talent. Amazon, for example, has a team of 10,000 employees working to improve their Alexa and Echo systems.
While AI tools can’t fully reverse this trend, they can help shrink the gap when embedded into Software as a Service (SaaS) platforms that smaller firms can make use of without the same level of investment. Essentially, through general-purpose AI tools, SMEs can have access to a host of productivity enhancements that these proprietary IT systems offer, but at a price point that is economical for SMEs. By shrinking this productivity gap, smaller firms can begin to compete in earnest while differentiating from large firms through improved customer service and greater product diversity. This will give a large leg up to SMEs who adopt these AI systems and help them better compete with large global incumbent firms.
Consider a firm like Keelvar Systems, which uses advanced sourcing automation to help businesses rapidly shift supply chains around the globe in the event of disruptions or delays. Essentially, it replaces or augments the work that a large supply chain and sourcing office would do within a firm. By using their service, or others like it, SMEs have the ability to benefit from similar levels of sophistication in their supply chain management without having employees spend hundreds of hours on tedious tasks or maintaining expensive proprietary IT systems.
There are firms like Legal Robot that have created a series of tools to help small businesses access legal services that would otherwise require a small army of in-house lawyers. With their service, SMEs can use smart contract templates based on their industry, receive instant contract analysis to make sure they are receiving fair terms and can automate certain aspects of compliance with laws like the GDPR.
Likewise, companies like Bold360 have helped SMEs improve their customer service experiences by offering a variety of AI-powered-chatbots and tools. Many basic customer concerns about products or delivery can be handled by these basic chatbots, freeing up human customer representatives to focus their time on the hard or advanced cases. Again, the pattern here is there is a service that large, multinational companies have been investing billions of dollars to create proprietary versions of, and now the customizability of AI is helping this service become more accessible to SMEs.
What are the barriers to AI adoption for SMEs in the U.S. and what can policymakers do to help create a welcoming environment?
Data investment as a public good
Depending on the context, data can often have the same traits as other public goods. First, it is non-rival—the marginal cost of producing a new copy of a piece of data is zero. Stated differently, multiple individuals can use the same dataset at almost no additional cost. The second important trait is that data is hard to exclude. Consider this report. Once it has been posted online, it is difficult to prevent people from accessing and sharing it as they see fit. This is one of the reasons why copyright infringement is so hard to stamp out.
Oversimplifying, these two features can lead to two opposite problems. On the one hand, economic agents might underinvest in public goods, absent government-created appropriability mechanisms (such as patent and copyright protection). Conversely, public goods tend to be underutilized (at least from a static point of view). Any price that enables economic agents to recoup their investments in a public good will be above the good’s “socially optimal” marginal cost of zero. Public good policies thus involve a tradeoff between incentives to create and incentives to disseminate. For example, patents give inventors the exclusive right to make, use and sell their invention; but inventors must disclose their inventions, and these fall into the public domain after twenty years.
What does this mean for data and artificial intelligence? If policymakers think that data is an essential input for cutting-edge AI, then they should question whether obstacles currently prevent firms from investing in data generation or disseminating their data.
While policies in this space involve significant tradeoffs, some offer much higher returns to social welfare. For instance, to the extent policymakers believe existing datasets are being underutilized, purchasing private entities’ data (through voluntary exchanges) and placing it in public data trusts would be a better policy than imposing data sharing obligations (which could undermine firms incentive to produce data in the first place). This is akin to the idea of government patent buyouts.
Of particular interest for policymakers, however, is the fact that some SMEs are sitting on top of data flows that are not being fully utilized because it is expensive to make data usable and these datasets may not be very valuable in isolation. As an example, industry-level manufacturing data might be quite valuable to all firms in a sector, but the dataflows from one SME are much less valuable. The U.S. could align incentives by providing investment funds to quantify various aspects of business flows and then submit them to public data trusts, which could be accessible for use by all firms in the industry. This would essentially be treating valuable dataflows as a type of public infrastructure that needs government investment to be fully realized.
This kind of public investment can happen not only through incentives for private firms but through the public sector as well. Governments at all levels (state, local, and national) have valuable dataflows regarding infrastructure development, the organization of public transportation, and general macro-level economic data that can be turned into open datasets for public and commercial use. Particularly on the national level, the U.S. should consider investment in IT infrastructure that can coordinate the submission of open datasets on the state and local level.
Indeed, if key scientific or commercial datasets do not yet exist, the public sector may be best positioned to create them in the first place as a type of digital infrastructure provision. One notable structure that may help in this regard is the idea of a Focused Research Organization, which would provide a team of researchers with an ambitious budget and a nimble organizational structure with the specific goal of creating new public datasets or toolkits over a set time period.
Provide regulatory certainty
For SMEs deciding whether to invest in adopting AI tools, regulatory and compliance costs can be a significant deterrent. Policymakers should recognize that regulation is often more burdensome for small firms that generally have less ability to shoulder compliance costs. Especially in industries with low marginal costs, such as the tech sector, larger firms can spread fixed compliance costs across more consumers, giving them a competitive edge over smaller rivals. Regulation can thus act as a powerful barrier to entry. For instance, a study found that the European experiment with GDPR led to a 17% increase in industry concentration among technology vendors that provide support services to websites.
This is not to say that additional regulation is, or is not, necessary in the first place. Indeed, there are a host of malicious or unintentional harms that can occur from improperly calibrated AI systems. Regulation can be a powerful tool to prevent these harms and, when well-balanced, can promote greater trust in the overall ecosystem. But potential regulation should follow sound policymaking principles that reduce the regulatory burden imposed on firms, notably by making regulation easy to understand, risk based, and low-cost to comply with.
In the U.S. there is to date no overriding national AI regulation. Instead, each sectoral regulator (i.e. Federal Aviation Administration, Security and Exchange Commission, Federal Trade Commission, etc.) has been steadily increasing their oversight over the use of algorithms and software in their specific area. This is likely an appropriate approach, as the kinds of risks and tradeoffs at play are going to be very different in healthcare or financial decision-making when compared to consumer applications. As this approach develops, it would be prudent to develop a risk-based framework that allows for more scrutiny of algorithmic decision-making in sensitive areas while giving SMEs confidence to invest in low-risk areas with the knowledge they will not later take on large compliance costs.
However, regulation over data protection has been far more segmented and piecemeal. And the state-by-state patchwork of rules that has developed can be a significant deterrent for SMEs when considering whether to invest in the use of certain AI tools. Policymakers should consider an overriding national privacy law that would be able to set standard rules of the road over the protection of data in all 50 states so that U.S. SMEs can invest with confidence.
Finally, U.S. policymakers should consider aggregating all this information through the creation of a dedicated AI regulatory website that provides a toolkit of resources for SMEs about the benefits of AI adoption for their business, the potential obligations and roadblocks that they need to be aware of, and best practices for cybersecurity hygiene and data sharing.
Expand the AI talent pool
A lack of skilled talent is one of the biggest barriers to AI adoption as the technical skills required to build or adapt AI models are in short supply. In the U.S., especially, smaller companies struggle to compete with the high salaries paid out by large tech firms for top-end machine learning engineers and data scientists.
In broad strokes, this skills shortage can be alleviated in two ways: through upskilling the domestic population and by improving immigration pathways for global talent.
To upskill the domestic population, one relatively simple lever would be to pay some portion of the costs of individuals and businesses who wish to upskill. In the U.S., a portion of a worker’s retraining costs may be written off as a business expense so long as the worker is having their productivity improved in a role they currently occupy. But this expense is not tax deductible if the proposed training would enable them to take on a new role or trade.
For example, if a small manufacturing firm has technically competent IT staff who wish to attend a specialized training course on using machine vision systems in a warehouse environment, this expense would not currently be deductible as it would enable them to take on a new role within the company. This inadvertently creates an incentive to spend more on capital productivity investments than labor productivity investments. Addressing this imbalance would incentivize more firms to invest in worker retraining and help speed the creation of an AI workforce in the U.S.
Secondly, the U.S. needs to urgently address the shortcomings in the U.S. immigration system which make it more difficult for startups to compete with large incumbents on the basis of talent. Approximately 79% of the graduate students in computer science (and related subfields) studying in the U.S. are international students, which means a large majority of potential AI workers U.S. firms may look to recruit must operate through the immigration system. The cost, complexity, and length of this process inevitably favors large, incumbent firms who can afford to navigate the regulatory maze of procuring an H-1B or related work visa.
A recent NBER paper showed in detail the myriad ways in which access to international talent is important for startup success. Utilizing the random nature of the H-1B lottery system, the paper compared startups that randomly received a higher percentage of their visa applications approved to those who did not. The random nature of the H-1B lottery makes an ideal policy experiment because it allows for a clean test in which other potentially confounding variables are controlled for. The study found that a one standard deviation increase in the likelihood of successfully sponsoring an H-1B visa correlated with a 10% increase in the likelihood of receiving external funding, a 20% increase in the likelihood of a successful exit, a 23% increase in successful Initial Public Offering, and a 4.8% increase in the number of patents filed by the startup.
Policymakers could begin to counter this effect by waiving immigration fees for firms of a certain size and by streamlining the application process.
Further, policymakers should look to create a statutory startup visa so that international entrepreneurs have a viable pathway into the U.S. to launch firms of their own. According to research by Michael Roacha and John Skrentny, international STEM PhD students are just as likely to report wanting to work for or launch their own firm as native-born students, but the difficulty of our immigration system pushes them towards working at large incumbent firms.
Using these two levers of upskilling and immigration reform, the U.S. should increase the supply of AI talent available to SMEs or to launch SMEs themselves and thereby spur the adoption of AI adoption.
Conclusion
Artificial intelligence systems hold great potential to streamline the costs of doing business in a modern economy, particularly for SMEs. The last 20 years of the information technology revolution have helped large, established firms reach the cutting edge of productivity while smaller firms have been left behind. But general-purpose AI tools now provide an opportunity for SMEs to take advantage of many of these IT advancements at a cost and a scale that is feasible for them. Policymakers should attempt to proactively build out the digital infrastructure that will make it easier for SMEs to take the leap in adapting AI tools.
Summary of policy recommendations:
Data investment as a public good:
Where appropriate, align incentives for the private sector to contribute industry-level SME data to public and private data trusts that could be used by everyone.
Invest in making more government datasets open to the public.
Fund Focused Research Organizations or similar groups with the explicit goal of creating new scientific and commercial public datasets.
Provide regulatory certainty:
Clarify existing regulations and the obligations that SMEs must meet when utilizing a new AI tool.
Encourage the development of a risk-based framework that allows for more stringent regulation of sensitive applications while giving certainty to SMEs on investment in low-risk applications.
Pass an overriding national privacy law so that SMEs aren’t deterred from investing by a patchwork of differing state-by-state laws.
Consider the creation of a new SME regulatory website that provides informational resources to SMEs about the benefits of AI adoption for their business and the potential roadblocks that they need to be aware of.
Expand the AI talent pool
Encourage upskilling of the U.S. population by making worker retraining deductible as a business expense.
Reevaluate U.S. immigration pathways to make them more attractive for international technical talent.
Streamline the immigration application process and waive fees for firms below a certain size to make it easier for SMEs to compete for technical talent.
[1] This report is an adaptation of an earlier paper coauthored with Dirk Auer titled “Encouraging AI Adoption in the EU”.
[2] Annual Survey of Entrepreneurs – Characteristics of Businesses: 2016 Tables, United States Census Bureau
President Biden’s American Jobs Plan proposed to spend $300 billion on rebuilding America’s manufacturing sector. The funds would be distributed through a variety of channels, including $50 billion in semiconductor manufacturing and research, $50 billion for a new office to fund investments to support production of critical goods. Biden also called for the creation of a “new financing program to support debt and equity investments for manufacturing to strengthen the resilience of America’s supply chains.”
The US Innovation and Competition Act of 2021, which passed the Senate in early June, also highlights pro-manufacturing polices. These include funding for semiconductor manufacturing and research, money for regional technology hubs, and the creation of the position of Chief Manufacturing Officer in the White House to coordinate the nation’s manufacturing policies.
We believe that these plans are a big step in the right direction, and applaud the President’s and the Senate’s focus on manufacturing. But the nation’s policy framework for manufacturing needs more explicit emphasis on digitization of physical production, which is the only way that American manufacturers can compete over the long run and create new jobs. In addition, the 2017 Tax Cuts and Jobs Act (TCJA) introduced an odd quirk into the business tax code that will make it more expensive for some manufacturers to borrow. That quirk needs to be fixed.
First, we review the facts about manufacturing investment. Government figures show that domestic investment by manufacturers has been lagging the rest of the economy by a substantial margin. During the last business cycle—which started in 2007 and ended in 2019—the productive stock of equipment rose by 15% in the manufacturing sector, far less than the 47% increase in the rest of the non-farm business sector (see chart below). (Equipment includes everything from industrial machinery to trucks to computers and communications gear bought by manufacturers).
This weakness in factory investment undermines the usual argument that manufacturing workers have been mainly displaced by automation. Certainly automation has been progressing, but if capital investment in robots and the like were the main cause of job loss, the investment surge in equipment would have been much bigger. The White House 100-day supply chain review points out that “many SME manufacturers are underinvesting in new technology to increase their productivity.” Contrast this with the warehousing industry (including fulfillment centers) where the productive stock of equipment rose by 91% from 2007 to 2019, even as employment soared.
Moreover, manufacturers have been lagging in software and R&D investment as well. The productive stock of software in the manufacturing sector rose by 50 percent from 2007 to 2019, compared to a 135 percent increase in the non-manufacturing sector. The productive stock of research and development rose by 47 percent in the manufacturing sector, compared to a 63 percent increase in the non-manufacturing sector.
The investment picture gets even worse when we look at specific industries within manufacturing. Consider the computer and electronics products industry, which includes semiconductor manufacturing. The productive stock of equipment in this industry did not grow at all from 2007 to 2019, and similarly for the stock of software. In other words, the computer and electronics product industry, including semiconductors, had no net investment in equipment and software over this 12-year stretch. This may help explain why government action to boost semiconductor manufacturing investment is necessary now.
Similarly, capital investment in the motor vehicle industry has been lagging. The 22 percent increase in the productive stock of equipment (including robots) is above the norm for manufacturing, but well behind the average for the nonmanufacturing sector. And investment in motor vehicle R&D, while still strong in absolute terms, has barely kept up with the industry’s need to shift to electric vehicles. Once again, the investment data helps us identify manufacturing sectors that need help in competing with China.
We note that the manufacturing sector is responsible for the entire slowdown in equipment investment compared to the 1990s. That shows how important it is that the U.S. address the issue of weakness in investment in manufacturing.
So what can we do? Biden’s manufacturing plan and the Competition and Innovation Act passed by the Senate are both heading in the right direction, but they could be improved with an overarching vision. As PPI has noted in several reports, we need the American manufacturing industry to invest in digitization—not just robots on the factory floor, but manufacturing platforms that make it easier for American startups to join global supply chains. The Biden Administration should think in terms of an Internet of Goods, where manufacturers plug into a network of companies that are linked digitally. The Biden manufacturing initiative should build on existing platforms such as Xometry and Fictiv to connect smaller suppliers.
The other big issue is funding. Manufacturing requires large capital investments, so borrowing costs are always a consideration. Unfortunately, in an example of the law of unforeseen consequences, key provisions of the 2017 TCJA are about to make it much more expensive for manufacturers and other capital-heavy businesses to fund their investments, even before any potential increase in the corporate income tax rate.
First, the TCJA permitted full expensing for investments in short-lived assets such as machinery and equipment. However, the “bonus depreciation” will begin phasing out in 2023 and will be eliminated by 2027. That will make it more expensive for manufacturing investment.
Second, the TCJA reduced the amount of interest expenses that most businesses could deduct from 50 percent to 30 percent of a business’s “earnings before interest, taxes, depreciation, and amortization” (EBITDA). Because of the pandemic, the CARES Act temporarily relaxed this restriction for 2020, but it comes back into effect for 2021.
Third, as of 2022, the TCJA further reduces the tax deductibility of interest to 30 percent of business “earnings before interest and tax” (EBIT). The difference between EBIT and EIBTDA is depreciation and amortization, which can be enormous for asset-heavy manufacturers. This 2022 shift, as embodied in current law, will have the effect of reducing the amount of interest that a manufacturer or other investment-heavy company can deduct.
To understand the magnitude of this change, consider American Axle & Manufacturing, a leading automotive supplier that did $4.7 billion in sales in 2020. The company’s EBITDA was $720 million, and depreciation and amortization was $522 million. That means EBIT was only $188 million (Note: These numbers are all drawn from the company’s public 10K, with no contact with the company).
In 2020 American Axle paid $212 million in interest. Under the TCJA rules that apply to 2021, it would all be deductible, since $212 million is less than 30 percent of $720 million. Under the TCJA rules that apply to 2022 and after, assuming that all numbers remain the same, only $56 million of the interest payment will be deductible. Future borrowing will take the same hit.
When the TCJA was passed, the increased restrictions on the deductibility of interest seemed appealing to many policymakers for several reasons. First, it reduced the bias in the tax code toward debt financing. Second, it discouraged excess borrowing by companies. Third, it raised money and helped balance out the cost of cutting corporate income tax rates.
However, the increased restrictions are likely to disproportionately affect manufacturers, who as a whole paid $96 billion and $90 billion in interest in 2018 and 2019 respectively, more than any other sector of the economy except real estate (who could opt out of the new requirements). The impact of this provision on companies like American Axle will be even greater if interest rates rise, as seems likely.
Given the acknowledged importance of manufacturing, it might make sense for lawmakers to consider extending the provision of the CARES Act that relaxes the limitations on interest expense deductions to avoid imposing another financial burden on the U.S. manufacturing sector. This would also cover the coming shift to EBIT. Such a move might be especially appropriate if the current provisions of the tax law that phase out bonus depreciation stay in effect. If we care about domestic factory investment, it seems like a mistake to make it more expensive for manufacturers to borrow even while the depreciation rules become more restrictive.
President Biden has proposed to finance his $4 trillion American Jobs and Families Plans by raising taxes exclusively on corporations and households that earn above $400,000 — the top 1.5 percent of taxpayers. Biden is right that the rich should pay more than they currently do given the staggering income inequality in America that’s been made worse by the COVID pandemic.
Almost 60 percent of Americans support funding Biden’s spending plans with his proposed tax increases — seven times the share that supports debt-financing them. But while taxing the rich is smart policy and politics, funding America’s future and realizing Biden’s policy vision will also require asking more taxpayers to contribute to the public good.
Are Americans obsessed with their credit score? They have good reason to be worried, as there is much that ails the credit reporting industry.
Information at risk. As the Equifax breach in 2017 highlighted, the industry is vulnerable to cyberattacks that give hackers access to personal data and financial information.[1]
Reporting errors. According to a study by the Federal Trade Commission (FTC), one in five Americans had an error on their credit report.[2]
Credit reports are discriminatory. A study by the Consumer Financial Protection Board (CFPB) found that 45 million Americans have no (or an un-scorable) credit history — with the largest cohort of individuals residing in communities of color or low-income areas.[3]
Consumers have too little control over their credit reports. Historically, Americans have lacked any real control over their credit reports and credit reporting agencies have put in place barriers that make it very difficult to challenge errors in those reports.
Unfortunately, the leading legislative fix — creating a public credit reporting agency — would fail to remedy these serious problems.
The government has not proven to be a better guardian against cyberattacks any more than the private sector. Over 22 million Americans had their information stolen in the course of two separate attacks launched on the U.S. Office of Personnel Management between 2012 and 2015.
Error rates are common in government data, and trying to get them fixed is hardly simple. Anyone who has ever dealt with their local Department of Motor Vehicles (DMV) can attest to that. Furthermore, a public entity would be relying on the same data inputs as the private sector credit reporting agencies. So any errors in the data will still spoil the results.
Ensuring the algorithms used in credit scoring don’t have discriminatory impacts is long overdue. But the government doesn’t need to replace private credit agencies to ensure non‐traditional sources of data like rental history and utility bills are used to determine a fair credit report. Congress could just require it and give the FTC and CFPB the resource and staff to enforce the rules.
While well-intentioned, the proposal to create a public credit reporting agency is an example of a classic problem in policymaking, the misalignment between the policy problem and the policy solution. That’s a shame, because anyone who has ever dealt with the credit reporting agencies (basically everyone over the age of 18) knows the present system is rife with problems. But there are some ideas that could improve the credit reporting.
To safeguard private information, the credit reporting agencies should be required to adopt the latest and most effective anti-cyberattack protections — and be subject to fines and other penalties if they fail to do so. And if someone’s information is stolen, credit agencies should provide a free and seamless way to freeze and un-freeze their credit reports — as often as they want.
To help consumers keep tab on their credit report, Congress should enact legislation that requires the credit reporting agencies to continue the practice started during the Covid-19 pandemic — to provide free credit reports on a weekly basis.
Finally, to help reduce the discriminatory impacts of the credit ratings, Congress should enact a Community Reinvestment Act (CRA) type law for the credit reporting industry. Such a law would give the FTC and the CFPB the ability to limit the credit reporting agencies from using discriminatory data and to add non-traditional sources of information. The law would also would require the FTC and the CFPB to issue an annual report tracking the efforts of credit reporting agencies to reduce the discriminatory impacts.
America’s credit reporting system needs fixing. But success means we need to put in place the right policies. If we don’t, we will have missed a historic opportunity to protect consumer information, reduce errors, and eliminate discrimination in credit reporting.
Paul Weinstein Jr. is a PPI Senior Fellow and Director of the MA in Public Management at Johns Hopkins University.
[1] “Equifax Data Breach Settlement,” Federal Trade Commission, January, 2020.
[2] Michelle Black, “Millions of Americans have errors on their credit reports — do you?” bankrate.com, May 13, 2019
[3] Kelly Holland, “45 million Americans are living without a credit score,” CNBC, May 5, 2015
Join the National League of Cities as they launch the first report in a three-year initiative on the Future of Cities, with a panel featuring PPI’s Dr. Michael Mandel.
Retail – both online and brick and mortar – forms the foundation for local economies, our workforce and community main streets across the country. COVID-19 has dramatically accelerated disruptions and innovations across most industries with retail experiencing more significant shifts than ever before. To ensure their communities are best positioned for the future, city leaders are focusing on how land use, planning and zoning; economic opportunity and jobs; and emerging technology can support their retail sector.
Panel:
Dr. Michael Mandel, Chief Economic Strategist at PPI
More to come
The large tech and ecommerce companies have become massive job generating and income creating machines, hiring hundreds of thousands of workers in the United States. This is one of the great hiring surges in history, providing well-paying jobs for an unprecedented number of workers.
But just looking at hiring by the tech giants themselves does not fully answer the question of their impact on the labor market. It could be that, like tall trees, they block the sunlight and keep other tech companies and ecommerce companies stunted.
This “ecosystem dominance” would manifest as weak job and income growth in the tech-ecommerce sector as a whole. If true, this harm to workers becomes a powerful justification for strong regulatory and antitrust growth against the tech giants. In other words, chopping down the trees would help the rest of the forest grow.
Alternatively, strong job and income growth across all tech and ecommerce industries would show the tech giants–who invested a stunning $65 billion in the United States in 2020—are playing a crucial role in a thriving ecosystem that benefits workers, raises wages and generates tax revenues. Indeed, from 2015 to 2020—a period that includes the pandemic—the tech-ecommerce ecosystem generated 1.7 million net new jobs and added $289 billion in labor income. By comparison, the whole private sector lost 360,000 jobs. In that case, common sense would call for regulatory prudence. As the saying goes “if it ain’t broke, don’t fix it.”
California
For this blog post we will focus on the job, income, and tax impact of the tech-ecommerce sector on California, which is the headquarters of three out of the four tech giants. In addition, in the fourth quarter of 2020, Amazon employed more workers in California (153,000+) than it does in Washington (80,000+).
Our analysis builds on PPI’s April 2021 paper, “Innovative Job Growth in the 21st Century: Has the Tech-Ecommerce Ecosystem Become the New Manufacturing?”. The tech-ecommerce ecosystem includes five tech industries and three ecommerce industries. The tech industries are computer and electronic production manufacturing (NAICS 334); software publishing (NAICS 5112); data processing and hosting (NAICS 518); Internet publishing and search, and other information services (NAICS 519); and computer systems design and programming (NAICS 5415). The three ecommerce industries are electronic shopping and mail order houses (NAICS 4541); local delivery (NAICS 492); and ecommerce fulfillment and warehousing (NAICS 493).
We draw on Bureau of Labor Statistics data from the Quarterly Census of Employment and Wages (QCEW). This dataset reports on all wages, salaries, and bonuses, including ordinary income from exercised stock options. We look at the five-year period from 2015 to 2020, which includes the pandemic year.
Table 1. Strong Job and Labor Income Growth in California’s Tech-Ecommerce Sector
Percentage change, 2015-2020
Tech-ecommerce sector
California
Core tech counties*
Rest of California
United States
Jobs
38%
30%
43%
31%
Total wage and salary income**
76%
77%
74%
56%
*San Francisco, San Mateo, Santa Clara
**Includes exercised stock options
Data: BLS QCEW
Table 1 shows the growth of jobs and labor income in California’s tech-ecommerce sector from 2015 to 2020. Tech-ecommerce jobs rose by 38% over the five-year stretch in California, compared to 31% in the United States as a whole. Meanwhile, private sector jobs rose by 0.3% in California and fell by 0.3% nationally (not shown on table).
Wages and salaries in California’s tech-ecommerce sector rose by an astounding 76% from 2015-2020, compared to 56% nationally. Meanwhile, private sector wages and salaries rose by 31% in California, and 21% nationally.
Table 2 shows the importance of the tech-ecommerce sector for California’s economy. The tech-ecommerce sector added 350,000 jobs between 2015-2020 in the state, and $100 billion in additional wage and salary income. That means the tech-ecommerce sector accounted for 38% of the entire increase in private sector wages in the state over that period.
Table 2. Tech-Ecommerce Sector Powers California Income Growth
Tech-ecommerce sector
California
Core tech counties
Rest of California
United States
Increase in jobs, 2015-2020 (thousands)
350
113
237
1738
Increase in wage income, 2015-2020 (billions of dollars)
$100
$62
$37
$289
Share of private sector wages, 2020 (percent)
21%
45%
11%
11%
Share of private sector wage growth, 2015-2020 (percent)
38%
56%
25%
22%
*San Francisco, San Mateo, Santa Clara
**Includes exercised stock options
Data: BLS QCEW
Note that Table 1 and Table 2 break out the core tech counties, San Francisco, San Mateo, and Santa Clara, from the rest of the state. Taken together, the two tables show that both the core tech counties and the rest of the state have shown roughly equal rates of income growth from the tech-ecommerce sector.
Table 3 looks specifically at ecommerce and retail jobs in California. Obviously, the pandemic forced a dramatic decline of brick-and-mortar retail jobs in the state. At the same time, the number of ecommerce jobs increased by more than enough to counteract the decline of brick-and-mortar retail. Moreover, the ecommerce jobs were substantially better paid on average.
As a result, when we combine brick-and-mortar retail with ecommerce industries in California, the number of net jobs rose by 28,000. Average annual pay rose by 22 percent.
Table 3. California’s Ecommerce Industries Create Net New Jobs and Boost Average Pay
Brick-and mortar retail
Thousands of jobs
Average annual pay
2015
1611
33229
2020
1475
40199
Change, 2015-2020
-136
Ecommerce industries
2015
207
54078
2020
372
55882
Change, 2015-2020
164
Brick-and-mortar retail plus ecommerce
2015
1819
35608
2020
1847
43360
Change, 2015-2020
28
Data: BLS QCEW
Finally, we turn to the question of the impact of the tech-ecommerce sector on personal income taxes in California. Tax collections have come in much stronger than expected, with personal income tax collections in the first nine months of the 2020-21 fiscal year running at 17% or $14 billion above forecast. Personal income tax revenues in the 2020-21 fiscal year are now forecast to be 54% about 2015-2016 levels.
How much of that gain is accounted for by the tech-ecommerce sector? There are several issues with making this calculation. The state government reports and forecasts tax revenue data on a fiscal year basis, while our data on the tech-ecommerce sector is on a calendar year basis and stops with 2020. Second, our definition of the tech-ecommerce sector includes a wide variety of industries, with average annual pay that runs from roughly $50,000 to well over $300,000. Third, much of the surge in personal tax revenues is coming from capital gains, which is directly connected with the success of the tech-ecommerce sector but is not reported in the BLS QCEW data.
Nevertheless, we can make a back-of-the-envelope estimate of the personal tax revenue generated by the tech-ecommerce sector. First, let’s start by looking the increases in personal tax revenues coming from wage and salary income (included ordinary income from exercised stock options) over the 2015-2020 period. By our estimate, the increase in tech-ecommerce wages and salaries accounts for roughly 37% of the increase in personal tax revenues from wages and salaries in the 2015-2020 period.
But of course, there has been a surge in capital gains revenues as well. If we attribute half the unanticipated increase in capital gains in 2020 to the tech-ecommerce sector, then tech-ecommerce accounts for roughly 42% of the increase in California personal tax revenues from 2015 to 2020. This should be viewed as a rough estimate rather than a final number.
On Wednesday, the House Judiciary Committee is going to mark up five tech antitrust bills. Collectively, the bills mark a major departure from the traditional consumer welfare standard that has governed antitrust law over the last few decades. Instead of focusing on consumers, these new laws would single out just five large tech platforms and apply an entirely different set of standards. One bill would effectively ban them from making any future acquisitions, which might have the unintended consequence of reducing startup investment, and therefore reducing competition. Most concerningly, another one of the bills would lead to breakups of all five major tech companies. Vertical integration would effectively be prohibited because, according to the bill’s authors, it presents an irreconcilable conflict of interest.
But what this framing misses is all the consumer benefits that flow from integrated ecosystems. Many digital products are free to access because they are subsidized by ads elsewhere in the ecosystem. A hallmark of a seamless user experience is being able to switch between devices, websites, and apps without needing to re-enter all your information. Crucially, these integrated experiences are also safer for users because fewer players in the market have direct access to user data (which is why most government agencies do not allow federal employees to “jailbreak” their smartphone devices or sideload apps from unapproved app stores). And of course, private label goods on Amazon work just the same as they do in Walmart or CVS — they offer consumers similar quality to name brands at lower prices.
Here’s a more detailed breakdown of the five bills and what they would do to tech platforms (in order from most reasonable to least reasonable):
The budgets for the FTC and DOJ to conduct antitrust enforcement have fallen by 18% between 2010 and 2019, after adjusting for inflation. Over the same period of time, the economy has grown by 22%. To properly enforce the antitrust laws on the books, the DOJ and FTC need resources that match the scope of the problems they face. This bill would increase their enforcement resources by almost 30% and change the merger filing fee structure to fall more heavily on larger deals. There is significant bipartisan support for this bill and it is urgently needed.
For the next four bills, you need to understand what a “covered platform” is. All four bills define them the same way (and these new rules would only apply to covered platforms). A covered platform is a “website, online or mobile application operating system, digital assistant, or online service” that meets all three of the following conditions: (1) 50 million U.S.-based monthly active users or 100,000 U.S.-based monthly active business users; (2) greater than $600 billion in net annual sales or market capitalization; and (3) is a “critical trading partner” that can restrict business users access to customers.
As of today, there are only six companies in the U.S. that meet the $600 billion market capitalization threshold. Every commentator assumes Amazon, Apple, Facebook, and Google will qualify as covered platforms, and most agree that Microsoft will be included as well, considering it operates multiple large-scale platforms, such as Windows, Office, Xbox, and LinkedIn. It remains to be seen whether the “net annual sales” metric will be interpreted to cover financial services companies like Visa, JP Morgan Chase, and PayPal, which process a large volume of payments.
What seems clear, however, is that the subcommittee bills target big tech firms instead of probing economic concentration across the U.S. economy.
The ACCESS Act would require platforms to provide third parties with APIs, software that allows access to platform data. The bill leaves the definition of “data” up to the FTC to determine. Data portability done right can lower switching costs and improve competition in an industry. Consider the enormous success of telephone number portability in the telecom industry. Letting consumers own their telephone number lowers the cost of moving to a new provider. And because telephone numbers are a necessary and discrete piece of data that all carriers must use to operate a network, there was no risk of decreasing the incentive to invest in creating this data.
For tech platforms, there might be similar discrete, static, and critical data sets that should be subject to mandatory portability rules. For example, the social graph — the list of all your friends or connections on a social network — is a very important dataset for new startups to have access to. Users are more likely to use a new app if during the onboarding process they are able to share a social graph from another social network and find all their friends on the new platform with a single click.
However, the problem with this bill is that it is not narrowly tailored to discrete and critical data sets like the social graph. It merely says that “a covered platform shall maintain a set of transparent, third-party-accessible interfaces (including application programing interfaces) to enable the secure transfer of data to a user, or with the affirmative consent of a user, to a business user at the direction of a user, in a structured, commonly used, and machine-readable format.” The bill leaves it to the FTC to define what “data” means for the purpose of the bill. It would be very helpful if Congress offered more guidance on what kinds of data it intends to be covered by these rules.
If data is defined too broadly, then there might be unintended consequences for investment incentives. For example, tech companies are all racing to build the next great computing paradigm. Will it be virtual reality? Blockchain technology? Augmented reality? Smart devices? Or something else no one can predict? Regardless of which paradigm wins out, if the future winner is forced to give every one of its competitors access to all of its data, then that would decrease the incentive to invest in the next big platform today. The most tragic part of the scenario is that these will be unseen costs — we won’t know what we lost out on. The future will just be somewhat dimmer because a well intentioned policy backfired due to poor drafting and a rushed process.
The Platform Competition and Opportunity Act is effectively a ban on all mergers and acquisitions by platform companies. This bill would ban platforms from acquiring companies that:
“compete with the covered platform … for the sale … of any product or service”;
“constitute nascent or potential competition to the covered platform … for the sale … of any product or service”;
“increase the covered platform’s … market position”; or
“increase the covered platform’s … ability to maintain its market position”
Given how broad this language is, the bill would effectively ban all acquisitions by platform companies. Since more than 90% of startups provide a return for their founders, employees, and investors through an acquisition as opposed to going public, this bill has the potential to backfire and decrease investment in startups. A recent study found that “VC activity intensifies after enactment of country-level takeover friendly legislation and decreases following passage of state antitakeover laws in the U.S.” This bill would qualify as an antitakeover law.
This bill is aimed at remedying the perceived conflict of interest by platforms and businesses that leverage those platforms to reach consumers. In essence, this bill bans self-preferencing by requiring platform owners to refrain from any conduct that gives their own products an advantage over competitors’ products. Section 2 of the bill makes it clear how all encompassing this rule aims to be (emphasis added):
“It shall be unlawful for … a covered platform … to engage in any conduct that … advantages [its] own products, services, or lines of business over those of any other business user, excludes or disadvantages the products, services, or lines of business of another business user relative to the covered platform operator’s own products, services, or lines of business, or discriminates among similarly situated business users.
The bill then provides 10 examples of discriminatory conduct, including tying, anti-steering provisions, retaliation, and restrictions on pricing.
But those specific examples aren’t really necessary when the bill includes a blanket ban on any conduct that “advantages” the platform’s products over those of third parties. While this attempt to fix a conflict of interest may seem intuitive at first glance (think of Elizabeth’s Warren’s baseball analogy), the more you think about the idea, the less it makes sense. For example, consider how this rule would apply to Apple. The iPhone runs on Apple’s proprietary iOS operating system. Apple wouldn’t be allowed to “advantage” its App Store in any way, which means it can’t be pre-loaded on devices and it can’t be the default app store unless users select it. This same logic applies to every layer of the tech stack. Apple makes dozens of popular first-party apps, including FaceTime, iMessage, Mail, and Music. As the bill is currently written, Apple would not be allowed to pre-install those apps on iPhone devices because that would “advantage” them over other video conferencing, messaging, mail, and music apps.
Now consider how this law would apply to Google. If a user typed in “restaurants near me” on Google, the search engine wouldn’t be able to directly offer map results at the top of the page from Google Maps because that would give it an “advantage” over other mapping services. Google would be forced to merely provide links to competitive mapping services rather than give consumers the answer to their question. The same rule would apply to Google Shopping if a user searched for sneakers. Instead of showing the user sneakers, Google would have to show users links to shopping websites that sell sneakers. This would represent a huge loss to consumer convenience that makes these products so popular (91% of Americans have a favorable opinion of Amazon, 90% have a favorable opinion of Google, and 81% have a favorable opinion of Apple).
Most concerningly, this bill would break the safety and security of many features of the iPhone. If Apple has access to a piece of hardware, such as a sensor or communications chip, then it has to give equal and fair access to that same hardware function to all third parties. That sounds like a laudable goal if you want more options when it comes to payments (i.e., access to the NFC chip) or location services (i.e., access to GPS) or the microphone (e.g., the way say Siri is always listening for “Hey, Siri”). But the flip side of more competition in this context is that every bad actor with the intent to defraud consumers or invade their privacy now also has access to sensitive data by law.
Lastly, some argue that the affirmative defense section of this bill would allow some pro-consumer conduct by the platforms to continue (such as continuing to pre-install apps on phones). The platforms can “advantage” their own products so long as they “would not result in harm to the competitive process by restricting or impeding legitimate activity by business users; or was narrowly tailored, could not be achieved through less discriminatory means, was nonpretextual, and was necessary to prevent a violation of, or comply with, Federal or State law; or protect user privacy or other non-public data.” But pre-installation and default settings clearly give a leg up to the products controlled by the platform owner and therefore might “result in harm to the competitive process.” If the intent of the drafters is not to ban this type of conduct, they should clarify this section.
The most extreme and economically destructive of the five bills is The Ending Platform Monopolies Act. It tries to address the same problem as the American Innovation and Choice Online Act — conflicts of interest between platform owners and platform competitors. But instead of requiring platform owners to operate their platforms in a neutral fashion as the non-discrimination bill does, this bill bans vertical integration outright and would lead to the break up of every large tech company across multiple dimensions.
Google would have to spin off YouTube, Android, Chrome, the Play Store, and its apps (Gmail, Google Maps, Drive, etc.) into separate businesses. Of course, that would destroy Google’s current business model where revenue from search and display advertising is used to subsidize an ecosystem of free products for consumers. Post-breakup, the newly independent entities would likely need to start charging subscription fees or create their own advertising business from scratch (and add more ad units to their respective products).
Amazon would be forced to spin off its private label goods business (e.g., Amazon Basics) and Amazon Marketplace because those two lines of business compete with the traditional retailing model where Amazon takes inventory of the product from wholesalers and then resells it at a markup. Amazon would also be forced to spin off its Amazon Prime Video streaming service and Amazon Web Services.
It has not yet been properly appreciated that this bill is aimed at addressing the same alleged conflict of interest issue as the American Choice and Innovation Online Act. If they are passed together, this bill would obviate the other one. As independent technology analyst Ben Thompson pointed out, this could mean that Chairman David Cicilline is attempting to make his bill seem reasonable by comparison even though it also has radical implications for tech ecosystems. Legislators shouldn’t fall for this obvious gambit.
The DOJ and FTC desperately need more resources to adequately enforce the antitrust laws on the books, and a narrowly tailored data portability mandate could enhance digital platform competition. But blanket bans on acquisitions, self-preferencing, and vertical integration would destroy many of the consumer benefits that make the tech giants world leaders in their respective markets. Hobbling America’s tech giants without adequate evidence of consumer harm would be a capitulation to the populists on the far left and far right at a time when we need to be focused on economic recovery.
Tomorrow morning, the House Judiciary Committee will mark up a series of antitrust bills that, taken together, would stifle digital innovation and hinder the United States in economic competition with China.
Alec Stapp, Director of Technology Policy at the Progressive Policy Institute (PPI) released the following statement:
“Economic concentration in many sectors of the U.S. economy is a serious issue that demands scrutiny and creative responses from lawmakers. Unfortunately these five bills fail to grapple responsibly with this challenge. Instead, they single out a handful of America’s most innovative and globally competitive tech companies for divestiture and draconian regulation. These bills would be a major blow to job creation and innovation even as our economy struggles to recover from the pandemic recession.
“We hope the Members of the House Judiciary Committee will stand up for American workers, consumers and entrepreneurs by refusing to join in an ideological crusade to dismantle “big tech.” While well-tailored regulation is certainly worth debating, the extreme provisions written into these bills would do more harm than good, and set us back in our fight against foreign dominance in the tech/e-commerce industry.”
Earlier this year, PPI released a new report on job growth in the tech/e-commerce sector, which found that this sector is now the top job creator in the U.S. economy. The sector generated more than 1.2 million net new jobs from 2016 to 2020, including during the pandemic. On average, pay in the tech/e-commerce ecosystem was 44% higher than average pay in the private sector and 21% higher than average pay in manufacturing nationally. The report also found that the growth of tech/e-commerce jobs has expanded beyond the coasts and regions known as tech innovation hot spots, including growth during the pandemic in Arizona, Ohio, Texas, Indiana, and Florida.
On this week’s Radically Pragmatic Podcast, Crystal Swann, Senior Policy Fellow at the Progressive Policy Institute and Mosaic Economic Project lead, and Francella Ochillo, a Mosaic Economic Project Cohort Member, attorney and digital rights advocate, sit down with Representative Sharice Davids, D-Ks., to discuss the impact of the coronavirus on women business owners, entrepreneurs and workers.
“It’s been disheartening – although I don’t know that I would call it super surprising – to see that the pandemic and the impacts of a public health crisis, that has turned into also an economic crisis, has disproportionately impacted women…financially, in the workforce when it comes to child care, access to health care…Every single aspect of life has been disrupted by the pandemic.
“Particularly Black women and other women of color have been disproportionately negatively impacted. It’s something that – at least in the Democratic Caucus in Congress – we started talking about almost immediately. Because like I said, it’s disheartening and heartbreaking but it’s also not as surprising. And that’s because a lot of us know the negative impacts and disproportionate impacts that women experience anyway,” said Rep. Davids on the podcast.
Congresswoman Davids serves as a Vice Chair of the Committee on Transportation and Infrastructure, and also serves on the Small Business, Joint Economic, and the Steering and Policy Committees. Additionally, she is the New Democrat Coalition’s Member Services Vice Chair. She is currently serving in her second term of Congress.
In addition to the economic impact of the pandemic on communities of color and women, Rep. Davids and the hosts discuss the ongoing negotiations over the upcoming infrastructure legislative packages — the American Jobs Plan and the American Families Plan. They also dive into Rep. Davids’ background as a professional mixed martial arts (MMA) fighter.
This podcast was in partnership with PPI’s Mosaic Economic Project. The Mosaic Economic Project is a network of diverse and highly credentialed women in fields of economics and technology. Mosaic programming focuses on upskilling, connecting, and advocating for cohort participants’ meaningful engagement in public policy debates, with a particular focus on engaging Congress and the media.
The Progressive Policy Institute (PPI) is a catalyst for policy innovation and political reform based in Washington, D.C. Its mission is to create radically pragmatic ideas for moving America beyond ideological and partisan deadlock. Learn more about PPI by visiting progressivepolicy.org.
New legislative package would be a devastating blow to American technological leadership
Today, Members of the House of Representatives introduced a new package of bills aimed at stifling digital innovation through extreme antitrust legislation.
Alec Stapp, Director of Technology Policy at the Progressive Policy Institute (PPI) released the following statement:
“The package of bills proposed by Members of the Judiciary Committee would be a devastating blow to American technological leadership at a time when that leadership is more necessary — and more at risk — than ever. While the current system isn’t perfect — the FTC and DOJ urgently need more resources, for example — our antitrust institutions are part of the overall pro-innovation ecosystem that has enabled the United States to produce technology companies that are the envy of the world. These companies create good jobs for American workers — both directly and indirectly — as well as provide innovative products for consumers around the world.
“It makes no sense to apply a drastically different set of rules to a small handful of companies without clear evidence of consumer harms, and a compelling story for how these new rules would remedy those harms. On the contrary, radical measures such as line of business restrictions and bans on self-preferencing would destroy many of the integrated products consumers currently enjoy.
“Apple would no longer be allowed to make its own apps (the iPhone would arrive out of the box with an empty home screen). Google would no longer be allowed to offer Google Maps on Android devices or use it to show map results in search. Amazon would no longer be allowed to offer generic goods at lower prices (just as Walmart, Costco, and every other large retailer do). It’s hard to see how these rules would benefit anyone other than the small handful of competitors that have been trying to use regulation to kneecap America’s most successful companies.
“Lastly, the bill related to mergers is written so broadly that it would effectively ban all future acquisitions by large tech companies. This might have the unintended consequence of decreasing investment in startups because acquisitions are by far the most common way that founders, investors, and employees earn a return on their equity. Reforms are certainly necessary, especially on issues related to privacy, misinformation, and election interference, but these bills would do nothing to address those concerns and would cause more harm in the process.”
The Progressive Policy Institute (PPI) is a catalyst for policy innovation and political reform based in Washington, D.C. Its mission is to create radically pragmatic ideas for moving America beyond ideological and partisan deadlock. Learn more about PPI by visiting progressivepolicy.org.
While other companies cut back on spending as the coronavirus pandemic took hold last year, e-commerce giant Amazon boosted its domestic capital investments by 75% to nearly $34 billion—and helped set the stage for a robust economic recovery, according to a new report from the Progressive Policy Institute.
KEY FACTS
Capital investment by Amazon and its peers in the e-commerce, broadband and tech industries helps spur job creation, boosts production and distribution capacity and combats inflation by shoring up supply, the report’s authors argue.
In Amazon’s case, the extra investment on property and equipment last year was driven by the need to meet an enormous surge of demand during the pandemic, the report notes.
Those investments put the firm in PPI’s top slot on its list of “Investment Heroes.”
Verizon was second on PPI’s list with $16.1 billion in domestic capital investment last year, AT&T was third on the list with $15.6 billion invested, and Alphabet and Intel rounded out the top five with $14 billion and $12.5 billion invested, respectively.
BIG NUMBER
500,000. That’s how many workers Amazon added in 2020, according to the report.
CRUCIAL QUOTE
“The willingness of these companies to keep spending essentially made it possible for large chunks of the economy to move forward, despite the pandemic,” the report states.
KEY BACKGROUND
Despite its major investments in the U.S. economy last year, Amazon’s business practices have also been the target of criticism. The firm was recently sued by the attorney general of the District of Columbia over allegations that it engaged in anticompetitive practices that “have raised prices for consumers and stifled innovation and choice across the entire online retail market.” Rep. David Cicilline (D-R.I.) said Amazon’s recent purchase of film studio MGM is a sign that the company is “laser-focused on expanding and entrenching their monopoly power.” And that’s not to mention criticism over the way the company handled safety protocols for workers and drivers during the pandemic.
