Economy Archives - Page 28 of 81 - Progressive Policy Institute

Kim for The American Interest, “One of These Governors Could Save the Democrats in 2020”

Posted on October 24, 2017 by The Progressive Policy Institute

State-level Democratic leaders are showing how populism and pragmatism combined can energize liberal turnout while still winning crucial swing-state support.

Under a clear blue sky in late summer, with the peaks of the Gallatin Mountains as a backdrop, Montana Governor Steve Bullock mingles with guests at a private event on a ranch just outside Bozeman. Holding a plate piled high with barbecue, Bullock is half a head taller than most of the people here. He is genial and relaxed, in jeans and battered brown shoes. His nametag reads, “Governor Steve.”

A young mother brings over two little girls in flowered sundresses, and Bullock immediately drops down to eye level. A few minutes later, the girls leave with their mother, smiles on their faces, their votes no doubt locked up for 15 years hence when the girls will be old enough to cast a ballot. In half the conversations that swirl around Bullock, there are joking references to 2020 and hints about the Governor’s ambitions. It’s an open secret here that the Bullock might be running for President.

Just this past fall, Bullock won re-election over GOP challenger billionaire Greg Gianforte by four percentage points—50 percent to 46 percent—in a state where only 35 percent of voters chose Democrat Hillary Clinton for President and Donald Trump won by 20 points. That victory is Bullock’s calling card into the Democratic presidential sweepstakes, along with the prairie populist credentials he has burnished. As the state’s Attorney General, he endeared himself to sportsmen by authoring a state opinion guaranteeing access to public lands. He also took on the Supreme Court’s decision in Citizens United, defending the state’s ban on corporate spending (he lost when the Court reaffirmed its decision).

Continue reading at The American Interest.

The Next Ten Million Jobs–How to Read Tomorrow’s Employment Projections

Posted on October 23, 2017September 18, 2024 by The Progressive Policy Institute

Tomorrow (October 24th), the Bureau of Labor Statistics will release the latest version of their ten-year employment projections. They will likely project job growth of roughly ten million jobs over the next ten years.

Generally what gets the most attention is the BLS list of the fastest growing occupations, and those are certainly interesting. But as part of our The Next Ten Million Jobs project, we suggest that the job projections should really be sorted into three buckets. The first bucket consists of jobs in the health and education sector, both private and public. The previous set of BLS projections, released in 2015, suggested that 48% of net new job growth over the next decade would come from health and education. That’s stunning. Will the new projections be higher or lower, and can we afford to pay for all these health and education jobs?

The second bucket consists of jobs in the tech sector, such as computer systems design and software publishing. The last set of projections pegged those industries at roughly 6% of future job growth. We think that is greatly understated, and expect that number to rise. Moreover, the tech job growth can be found outside of the traditional tech hubs, as our report shows.

Finally, the third bucket consists of tech-enabled jobs in physical industries such as ecommerce, manufacturing, and agriculture. Here the previous set of projections did very poorly. For example, the BLS predicted that the warehouse and storage industry would expand by a very meager 28K jobs by 2024. Instead warehousing jobs have soared by 200K jobs over the last 3 years alone, riding the wave of ecommerce fulfillment centers. Moreover, the BLS does not have a separate projection for electronic shopping companies.

We believe that tech-enabled jobs in physical industries are going to be an extremely important source of job growth over the next ten years–but these are not broken out in the BLS projections. What’s more, these jobs are going to mainly benefit states that have been left behind behind by the digital revolution.

Stay tuned.

Ecommerce employment update for October

Posted on October 16, 2017September 18, 2024 by The Progressive Policy Institute

With the publication of my WSJ op-ed, “Get Ready for the Internet of Goods,” it’s time to update our ecommerce analysis for the third quarter. Rather than reaching back to 2007, as previously, I want to focus on a more recent period. First, take a look at the chart below, which graphs the full-time equivalent (FTE) employment for brick-and-mortar retail, with a 3-month moving average.

On a quarterly basis, brick-and-mortar FTE peaked in the third quarter of 2015, and since then has been drifting down at about a half percent annually. The figure for brick-and-mortar FTE in the third quarter of 2017 is probably a bit lower than it should be because of the effects of Hurricanes Harvey and Maria on hours worked in retail.

So let’s look at the two years since brick-and-mortar FTE peaked. Over those two years, brick-and-mortar retail FTE jobs fell by 123,000. That’s a decline of about 1%. The increase in FTE ecommerce jobs was 178,000 over the same stretch. That’s based on hours worked in the electronic shopping and mail-order industry, and the warehousing industry, where many fulfillment centers are reported. FTE jobs at couriers and messengers, including express delivery companies, rose by 58,000. All told, the gains in ecommerce and delivery services was almost twice the size of the losses in brick=and-mortar retail.

Change in FTE jobs, 3Q15-3Q17 (thousands)

Brick-and-mortar retail -123

Ecommerce +178

Express delivery and couriers +58

Data: BLS, PPI.

Several points: First, FTE adjusts for changes in hours worked per week. Second, we now see a significant employment impact on the delivery side. To put it a different way, those UPS drivers are working way hard. Third, a portion of the third quarter decline in brick-and-mortar FTE is likely to be due to Hurricanes Harvey and Maria reducing the number of hours for retail workers in Texas, Florida, and other storm-hit areas..

Iowa’s App Economy: A Summary

Posted on October 12, 2017 by The Progressive Policy Institute

When it comes to tech jobs, global hubs like Silicon Valley, New York, and Austin get all the attention. But, to an increasing degree, our research shows tech-driven employment growth is not restricted to those high-profile areas.

For example, our widely-cited March 2017 report “How the Startup Economy is Spreading Across the Country—and How It Can Be Accelerated” demonstrated that the startup mentality could be found in many regions. And our new report (“The Next Ten Million Jobs”) finds that tech and tech-related jobs grew by 51% in the “Heartland” states from 2007 to 2016, only slightly slower than the nation as a whole. In Iowa, tech and tech-related jobs grew by 83% over the same period (Figure 1), accounting for almost one-quarter of private-sector nonfarm job growth (Table 1).

The App Economy in Europe: Leading Countries and Cities, 2017

Posted on October 9, 2017 by The Progressive Policy Institute

In this new paper, we estimate that the European App Economy totals 1.89 million jobs as of January 2017, an increase of roughly 15 percent over a year earlier. In addition, this paper estimates the number of App Economy jobs by country and as a percentage of all jobs on a country-by-country basis. Next, we provide an overall and country-by-country breakdown of App Economy employment by operating system, comparing the number of jobs in the iOS ecosystem with the number of jobs in the Android ecosystem. Finally, we provide a ranking of the top 30 App Economy cities in Europe.

Expansion of the Joint Employer Doctrine Fails to Strike the Right Balance

Posted on October 5, 2017September 18, 2024 by The Progressive Policy Institute

Policymakers across the United States are struggling to figure out how to adapt to swift changes in the American workforce. So-called “alternative work arrangements,” for example, are growing: in 2015, 15.8 percent of workers were independent contractors, temporary workers, contracted workers, or “gig” workers—a 50 percent increase in just a decade. Yet some efforts at adaptation—such as expansion of the “joint employer” doctrine—may do more harm than good. PPI is committed to helping find solutions that balance worker protection with business productivity and investment and the expansion of the joint employer doctrine fails to strike that balance. We must figure out a better way forward that boosts economic dynamism without sacrificing worker interests.

At the end of July, the Save Local Business Act was introduced into the House of Representatives. The bill, with three Democratic cosponsors among over three dozen Republicans, aims to narrow the expanded definition of “joint employer” promulgated by the National Labor Relations Board (NLRB) in 2015. This elicited immediate praise from business groups—particularly those associated with franchises—and opposition from unions and other groups advocating for worker rights.

The joint employer doctrine is used by the NLRB and courts in determining legal responsibility for issues such as overtime pay when more than one employer is involved. If a bank, for example, contracts with a company to provide janitors to clean the bank facilities, the janitors are employees of the contract firm, not the bank. Yet, if the bank has some level of control over of the janitors’ wages and hours, it could be deemed a “joint employer” and would be responsible for appropriate legal compliance.

Not incidentally, the joint employer doctrine is central in shaping the ability of employees to engage in collective bargaining. Contract workers, temporary workers, and franchise employees—all of whom are affected by the joint employer doctrine—are difficult to unionize. Employees of franchise locations—fast-food restaurants, for example—are technically employees of the franchisee (the local operator), not the franchisor (the national brand). The entire purpose of the franchising model is to allow the franchisor to focus on brand and system, and leave the franchisee to focus on operations and local context, including employment.

Under the expanded joint employer doctrine of the NLRB, however, it is possible that both the franchisee and the franchisor could be considered employers of the workers at each individual franchise location. This “could fundamentally change business in the United States by destroying the franchise model.”

Until the 1980s, the NLRB threshold for a joint employer finding was “direct or indirect control” over working conditions. This was a fairly broad doctrine and, in certain circumstances, could be used to find that employees were subject to “control” by more than one employer. Nonetheless, the NLRB joint employer standard remained more modest than definitions used in Title VII of the Civil Rights Act and the Fair Labor Standards Act (FLSA).

Beginning in the 1980s, the NLRB gradually narrowed the definition to “direct and immediate” control over employment issues. The change from “indirect” to “immediate” had large implications in where the joint-employer line was drawn. If the bank “shares or codetermines” the conditions of employment of the contracted janitors, and “meaningfully affects” their hiring, firing, supervision, etc., the company could be a joint employer. Now, the NLRB says, no longer is “direct and immediate control” required—even the possession of authority to direct third-party employees is sufficient, regardless of whether the authority is exercised.

These subtleties in language and reliance on factual findings are classic examples of legalese, but cases involving worker rights and business interests frequently turn on choice of words and how those words are put into practice.

Business groups do not welcome a broader definition. Especially as it pertains to franchise arrangements, the more expansive standard could open up franchisors to greater liability and more attempts at collective bargaining. Already, we have seen arguments to apply the extended joint employer doctrine to other areas, such as student athletes. A challenge to the NLRB’s expansive interpretation is currently pending in front of the D.C. Circuit, and it is expected that the NLRB under President Trump will work to narrow the standard. In the Republican-controlled Congress, the Save Local Business Act could find easy passage and, at the state level, legislatures are being lobbied to pass laws saying that franchisors cannot be considered joint employers.

One problem is the likely response from franchisors to the expanded NLRB standard—in particular, we may see reduced business dynamism. Franchising is an engine of entrepreneurship in the United States, with independent operators who, despite the assistance of national brands, assume plenty of financial risk themselves. At the same time, we have seen the rise of large franchising operations that own hundreds of franchises across the country. Not surprisingly, large franchising operations are better able to comply with employment laws than small, single-operator franchisees. Faced with the new incentive structure of the expanded joint employer doctrine, franchisors will have a clear preference against smaller franchisees in favor of the larger organizations. This will make it much harder for new entrepreneurs to enter business through franchising, further raising barriers of entry for business creation.

The NLRB and other public agencies have the unenviable task of modifying law and policy to keep up with shifting employment arrangements, in an environment of stagnant wages for many workers, geographic concentration of economic rewards, and concerns about entire occupational categories being lost to automation. As mentioned, “alternative work” is growing. The Government Accountability Office (GAO) estimates that the “contingent workforce,” depending on the definitions used, could be anywhere from five to 40 percent of the total labor force. More people are receiving income from multiple sources, which includes new online and on-demand platforms. These changes have prompted calls for new legal classifications, such as the “independent worker” category proposed by the Hamilton Project two years ago.

Confronted with these challenges, expanding the joint employer doctrine is perhaps an understandable attempt to try to help workers cope. The fastest-growing type of alternative work arrangements is “workers provided by contract firms,” precisely those at the core of the joint employer doctrine. Yet we also need to help policymakers and businesses think creatively about other ways to manage and adapt to these challenges, as they will only increase in significance. In the face of a “fissured workplace,” how can policymakers help workers and businesses adapt and succeed together?

In managing these changes, we must ensure adequate worker protection and representation while also supporting (or at least not hindering) businesses to pursue innovation and productivity. Policymaking should be guided by certain principles, among which might be the following.

Clarity and certainty. Any standard leaves room for interpretation (and litigation), but workers and firms need to have clear ideas about where they stand regarding rights and responsibilities.
Get the incentives right. Policies should minimize the amount of “gaming” that might go on by firms in trying to avoid legal compliance. This doesn’t mean the presumption should be that all firms will act badly—policymakers need to pay attention to the incentives they establish.
New ways for workers to organize and improve. Despite the NLRB’s presumption, traditional unions may not be the best adaptive form of organizing in the modern workplace, and new Internet platforms have arisen to help fill the gap. Policy should facilitate these, but also focus on how new organizing tools can support learning and skill upgrading among workers, not just collective bargaining.
Informational equity and transparency. As the Roosevelt Institute has coherently outlined, employees in more sectors are subject to “opaque algorithms” that determine wages, scheduling, evaluation, and so on. Giving workers more transparency and control over this information will reduce asymmetry and empower workers to better manage their careers.

Most of the American labor force is still characterized by traditional employment, but new forms of work are growing rapidly, especially in sectors where low-wage and high-turnover work predominates. Addressing this challenge is a major priority, and we need to find ways that policy can jointly advance the interests of workers and firms.

Do California Legislators Understand What is Driving Rising Health Care Costs?

Posted on September 8, 2017September 18, 2024 by The Progressive Policy Institute

Based on newly revised Bureau of Economic Analysis data, we find that rising labor compensation for health care workers accounted for $55 billion, or 40%, of the increase in personal health care spending in 2016. By comparison, in May, 2017, we calculated that pharmaceuticals accounted for only $15 billion, or 11% of the rise in personal health care spending in 2016. In other words, the rising number of health care workers is by far the single most important factor driving higher health care costs.

This simple fact—which has held true every year we have done this analysis—makes us wonder about heavy-handed legislation like California’s SB17, now up for consideration. The bill would purportedly control rising health care costs by forcing pharma and biotech companies to give 60-day advance notification of most price increases. The bill would also require pharma and biotech companies to give “a description of the specific financial and nonfinancial factors used to make the decision to increase the wholesale acquisition cost of the drug“ – a regulatory requirement levied on almost no other sector of the economy.

In fact, the real health care cost problem in California, as in the rest of the country, is not the cost of pharmaceuticals. The real health care cost driver is that health care employment growth is far outpacing population growth. In 2016, California health care employment rose by 2.9%, more than four times as fast as the 0.7% increase of the state’s population, as reported by the Census Bureau (below).. As long as health care employment keeps growing out of control, intrusive bills like SB17 risk doing damage to the pharma and biotech industries without having any significant effect on the cost of health care for patients and employers. All pain, no gain.

Disassembling Kodak

Posted on September 6, 2017September 18, 2024 by The Progressive Policy Institute

Kodak is regularly held up as an example of how a “real” innovation company behaves. For example, a recent New York Times story compared Apple unfavorably to Kodak, saying.

“Think about the contrast between George Eastman, who pioneered fundamental innovations in photography, and Steve Jobs,” Mr. Summers wrote in 2014. “While Eastman’s innovations and their dissemination through the Eastman Kodak Co. provided a foundation for a prosperous middle class in Rochester for generations, no comparable impact has been created by Jobs’s innovations” at Apple.

But the NYT story did not actually look at the number of people employed by Kodak over time, and compare it to the workers employed by by Apple and other tech companies. So we’ve peered through years of annual reports to start disassembling Kodak.

Kodak was founded in 1888, but it incorporated in 1902 in its “modern” form. Its worldwide employment peaked at 145K in 1988. At that time, 40% of its workforce was outside the United States. After that point, the company’s workforce fell off sharply, heading towards bankruptcy in 2012 (not shown). Note that there is a gap in reported worldwide employment during the war years. Also, worldwide employment was not reported for 1902 and 1903, and US employment was not reported for 1902.

It took Kodak 51 years to reach 70K employees worldwide, and 65 years to reach 100K employees. By contrast, today’s tech leaders got to those employment levels much faster

	Years to reach this workforce
	70K	100K
Kodak	51	65
Amazon	16	17
Apple	32	35
Facebook	*	*
Google	13	*
Microsoft	22	30

Here’s some charts that show this difference graphically. We age-adjust employment by matching Kodak’s date of incorporation, 1902, with the 1981 FY of Apple’s IPO. This charge shows that at year 36, Apple’s workforce is almost triple the size of Kodak’s at the same age

Here are comparable charts for the other tech leaders.

An Analysis of Job and Wage Growth in the Tech/Telecom Sector

Posted on September 3, 2017 by The Progressive Policy Institute

This paper examines job growth at leading tech/telecom firms. We compare them to leading industrial firms, both in the first half of the 20th century and in the post-war era, and show that they have similar employment trajectories. Then we consider wage and industrial structure trends. We find that real wages in the tech/ telecom sector are higher and rising faster than in the physical sector. To correct for composition effects, we examine detailed occupational categories and find that, for middle-skill occupations such as sales and office support, the tech/telecom sector has significantly higher wages than the physical sector.

This paper incorporates and updates portions of earlier reports and blog posts, including: “A Historical Perspective on Tech Job Growth” (January 2017); “The Creation of a New Middle Class?: A Historical and Analytic Perspective on Job and Wage Growth in the Digital Sector, Part I” (March 2017); and “Do today’s tech/telecom companies employ too few workers?” (June 2017).

Fulfillment Centers: The Nodes of a Packet-Switched Physical Distribution Network?

Posted on August 27, 2017September 18, 2024 by The Progressive Policy Institute

Warning! Wonky post ahead.

At PPI, we are focused on understanding where the new jobs of the future are coming from, and how policymakers can help foster their growth. That sometimes requires identifying underlying trends that may not be obvious.

The growth of multiple networks of ecommerce fulfillment centers–built by retailers such as Amazon, Walmart, Nordstrom and many others–is effectively a transition from “circuit-switched” physical distribution networks to “packet-switched” physical distribution networks. Analogous to the shift from circuit-switched telephone networks to the packet-switched networks that make up the Internet, the new ecommerce distribution networks are capable of much greater flexibility and lower costs than the dumb warehouses which preceded them.

And just like the Internet helped create a wave of new industries in tech hubs, this new “Internet of Goods” is going to enable a new wave of business and job creation in domestic manufacturing and food production. With the right policy, this growth in domestic manufacturing and food production jobs will benefit states across the country.

Background

The old telephone networks were “circuit-switched”–that means the telephone company would set up a separate circuit for each call, and the callers would “own” the circuit until the call was over. The connections were solid, but they were not flexible, and they wasted network resources (since so much of a voice conversation is dead air). By contrast, the multiple networks that make up the Internet break down data (including voice) into packets, which are then routed to their destinations and reassembled. Packet switching requires a lot more intelligence in the system, but it’s much more flexible and lower cost than circuit switching.

As we’ve seen over the past two decades, the widespread introduction of packet switching in telecom opens up all sorts of possibility for entrepreneurs and existing companies to create new digital products and services. The Internet revolution transformed digital industries, creating millions of jobs in the process. In particular, since December 2007, the tech-ecommerce sector has generated 1.7 million jobs. That’s around half of private sector job growth, outside of health and education.

The old warehouse-retail distribution system was analogous to circuit switching. Big trucks would bring boxes of identical goods from manufacturers or importers. The warehouses would break down the incoming goods into predictable patterns. All the boxes of identical lamps, for example, would be stored together for easy retrieval when it was time to put together the shipments to individual retail stores. The shipments were regular and straightforward, and didn’t require much “intelligence” in the networks.

Ecommerce fulfillment centers are much more like the “routing nodes” of the Internet. They take in goods from a wide variety of sources, at irregular interviews, including returns from consumers. They store the goods according to their own internal schema. For example, Amazon uses a “random stow” method that distributes incoming products across the fulfillment center in a way that maximizes the odds of products in the same order being close together. Since most consumers don’t order multiples of the same item, the Amazon random stow method might distribute the most popular items across the whole fulfillment center, rather than clumping them all together. Then the ecommerce fulfillment center puts together consumer orders and ships them out.

The Internet of Goods

In effect, these multiple networks of fulfillment centers are creating a new packet-switched “Internet of Goods.” The first economic consequence, as we have described, is the creation of hundreds of thousands of jobs in electronic shopping companies and fulfillment centers. This is analogous to the first wave of Internet growth in the 1990s.

The next step, we believe, will be the creation of new businesses in domestic manufacturing and food production that make use of the flexibility and low cost of the Internet of Goods. For example, we can visualize custom manufacturing operations that are located near fulfillment centers. They take production orders from customers, and then ship out the product on the same day via the fulfillment center. The cost of distribution would go way down compared to today’s situation, giving domestic custom manufacturers a sustainable competitive advantage against foreign rivals.

To get an idea of magnitudes, consider that as of 2015, 57% of the retail price of furniture was the cost of distribution (transportation, wholesale, and retail). For women’s clothing, 59% of the retail price was the cost of distribution, and for food, 40% of the retail price was the cost of distribution. Reducing the cost of local distribution while shortening the distribution time could open up new sustainable business models for domestic manufacturers and food producers.

Gerwin for The Hill, “The bitter harvest of Trump’s protectionist stance”

Posted on August 1, 2017 by The Progressive Policy Institute

Donald Trump is infatuated with the 2016 election map, which underscores his dominance in red-coded rural counties. Candidate Trump repeatedly promised to “take care” of America’s rural voters who, in return, provided some of his biggest vote margins.

It’s ironic, then, that on issues from budgets to healthcare, America’s heartland stands to become an early and particular victim of Trump’s misplaced priorities. Nowhere is this more evident than with Trump’s wrongheaded, protectionist approach to trade.

Continue reading at The Hill.

Estimating the Impact of Ecommerce On Productivity Growth

Posted on July 31, 2017September 18, 2024 by The Progressive Policy Institute

In an earlier post, I estimated that the expansion of ecommerce since 2007 is saving American households 64 million hours per week in shopping time. What impact does this have on measured productivity? This is not an easy question. Unpaid shopping hours are part of “household production,” which is generally excluded from official calculations of GDP. That omission is a problem, because it undervalues the unpaid time that people contribute to their households, ranging from cooking and childcare to commuting.

The best way to tackle the impact of ecommerce on productivity is to build up a consistent set of national accounts integrating both the increased importance of data for economic growth (See Moving Beyond the Balance Sheet Economy), as well as shopping as an economic activity requiring both market hours (the retail worker) and nonmarket hours (driving to the store, choosing items from the shelves and so forth). For our purposes here, though, we are going to do a back of the envelope calculation to estimate the impact of ecommerce on productivity growth.

According to the BLS, the number of hours worked by employed workers in the nonfarm business sector rose by 2.1% from 2007 to 2016, or an increase of 79 million hours of work per week.* Suppose that we adjust for the reduction in household shopping hours, on a 1-to-1 basis.** Then total weekly hours only rise by 15 million from 2007 tp 2016, or only a 0.4% gain in hours. The annual percentage growth in hours goes down from 0.2% to virtually nothing.

This calculation suggests that factoring in ecommerce could raise measured productivity growth in the nonfarm business sector by 0.2 percentage points from 2007 to 2016. This is a significant difference, but obviously not enough by itself to reverse the slowdown in productivity growth. However, the relative gains in productivity should continue as the market share of ecommerce increases.

This type of productivity analysis, which integrates the impact of the data-driven economy on both market and household production, can be extended to other innovations as well, such as autonomous vehicles and artificial intelligence.

*The BLS reports annual hours in the nonfarm business sector, which I divided by 52 to get weekly hours.

**We could make a case for the adjustment factor to either be higher or lower than 1-to-1. We could value the household hours at the minimum wage, in which case they are less valuable than retail and fulfillment center worker hours. Or we could say that being stuck in traffic driving to the mall or waiting on checkout lines is really annoying, which would make those saved hours more valuable.