Traded Employment Losses Since 2001 in Upstate New York

Metropolitan areas in Central and Western New York, like others in the Rust Belt that had high concentrations of manufacturing employment, have been hit hard by the loss of manufacturing jobs.  Ninety-one thousand net manufacturing jobs were lost in the 2001-2010 decade in five upstate metropolitan areas – Utica-Rome, Syracuse, Rochester, Binghamton, and Buffalo-Niagara Falls. During that same period, only 62,000 net service sector jobs were created in these areas.  The period between 2001 and 2010 was an extraordinary decline in manufacturing, but it was not unique.  Manufacturing employment in these Central and Western New York metropolitan areas has declined in every decade, beginning in 1970.

The challenges facing upstate metropolitan areas that had high concentrations of manufacturing employment in the twentieth century are not unique.  In fact, most rust belt metropolitan areas have seen employment stagnate since 2001.  While manufacturing employment has significantly decreased, service sector employment in most rust belt metropolitan areas has grown more slowly than in the nation.  In fact, more than half of the region’s job creation deficit compared to the nation since 2001 is associated with slow service sector growth.

The weak performance of the region’s service sector is in part a reflection of the manufacturing employment losses, since much service sector employment has historically depended on manufacturing.  Almost all manufacturing firms are so-called “traded” businesses, since they sell products outside the regions where they are produced.  These businesses import income into regions through the sale of products and services that they export.  In contrast, local businesses sell products and services within regions.

Manufacturing industries typically produce products that are exported from the metropolitan areas where they are made.[1]  But, service providers operate in many cases within local markets.  For example, lawn care providers, hair dressers and barbers, restaurants and retail stores (other than those with an on-line presence) generally trade within a relatively small area.  Other service providers export their services.  Industries like financial services, information services, on-line retailers and institutions of higher education serve larger regional, national or international markets.

Because local services are bought in local, rather than regional or national markets, local service employment is proportional to local populations.  Because traded jobs export products and services and replace imports, they create more jobs within their regions.  Consequently, economic development strategies focus on strengthening existing traded industries, and attracting traded employment.

This post examines changes in traded industry employment in New York State, Michigan, Ohio and the United States.  The data shows that traded employment grew nationally from 2001 to 2016, but not in Central and Western New York metropolitan areas, or in Ohio and Michigan.  It also shows that while traded service sector employment has grown in most metropolitan areas in upstate New York and the rust belt, growth in some cases has been insufficient to offset losses in manufacturing employment. Even so, traded service employment continues to increase its share of total traded employment.  In 2016, more than 70% of traded employment in every New York metropolitan area except for Binghamton was in the service sector.  Nationally, 80% of traded employment was in service industries.

Employment Change – Traded and Local Industries

Except for the New York City and Albany-Schenectady-Troy metropolitan areas, traded industry employment in New York metropolitan areas and in Ohio and Michigan did not do as well between 2001 and 2016 as the United States, which grew by 13.3%.[2] The Rochester and Syracuse MSA’s saw decreases in traded employment of more than 6%, while in Utica-Rome it decreased by 12.4%.  The Binghamton MSA, which was hard hit by the closure of IBM’s first manufacturing plant, lost 24% of traded employment between 2001 and 2016.  New York City had an increase in traded employment of 19%, while Albany-Schenectady-Troy’s traded employment increased by 11%.

Metropolitan areas in Michigan and Ohio had greater employment losses between 2001 and 2010 than those in New York State, other than Binghamton.  Since 2010, Michigan and Ohio metros have recovered employment at nearly the rate of the nation growing 15% compared to 17%.

Local employment increased by 9% between 2001 and 2010 in the United States.  New York City metropolitan local employment growth during that period was greater than the nation – 13.4%.  Metropolitan areas upstate had much weaker growth. Albany-Schenectady-Troy local employment growth was strongest, at 5%.  Between 2010 and 2016, the New York City metropolitan area again had local industry employment growth that exceeded the nation – 18% to 16%.  Local industry employment growth in upstate metropolitan areas was much weaker – less than 10% in each case.

Traded Industry Employment – Manufacturing vs. Services

 Manufacturing

Between 2001 and 2010, 3,700,000 traded manufacturing jobs were lost in the United States – nearly three of every ten manufacturing jobs that existed in 2001.  Much of the lost manufacturing loss was the result of increased off-shore competition – 2.4 million jobs by one estimate.[3] But other factors were important as well.  Increases in productivity have played a significant role over the long-term in reducing manufacturing employment.  And, technological change has displaced major manufacturers, like Kodak, that depended on the sale of products like photographic film that became inferior to new competition.

Traded manufacturing employment losses hit New York State metropolitan areas harder between 2001 and 2010 than the United States.  Most metropolitan areas in New York State lost more than 30% of traded manufacturing jobs between 2001 and 2010, compared with 29% for the United States. Michigan/Ohio metropolitan areas were hit even harder than those in New York, losing 39% of manufacturing employment.  

Traded manufacturing employment began to rebound in 2010, gaining 727,000 jobs.  Nationally, traded manufacturing employment increased by 8%. Michigan and Ohio rebounded even more strongly, gaining 144,300 jobs – 18%.   Most metropolitan areas in New York State saw weaker recoveries, or continued manufacturing employment losses.  Three metropolitan areas saw increases – Albany-Schenectady-Troy gained 6,000 jobs (30%), Buffalo gained 2,700 (5.6%) and Utica-Rome gained 190 (1.7%).  The New York City metropolitan area, Syracuse, Rochester and Binghamton had continued losses.  Binghamton lost 19% of its traded manufacturing employment between 2010 and 2016 (2,600 jobs), after losing 6,600 traded manufacturing jobs between 2001 and 2010.

Services

Traded service sector employment in the United States increased in both the 2001-2010 and 2010-2016 periods, though the gain between 2010 and 2016 was larger than in the earlier period – 5,500,500 vs 3,000,000.  Between 2001 and 2010, only the Buffalo-Niagara metropolitan area equaled the national rate of increase – 9.6%.   The New York City metropolitan areas saw an employment increase that approached that for the United States – 8.1% vs. 9.6%.  Rochester and Syracuse had smaller increases, while service sector employment in Utica-Rome and Binghamton decreased.  Metropolitan areas in Michigan and Ohio also had slightly less service traded sector employment in 2010 than in 2001.

Between 2010 and 2016, national traded service sector employment increased by 16.4% compared with 9.6% in the earlier period.  New York City’s traded service employment increased by 18.4%, while metropolitan areas in Michigan and Ohio had an increase of 14.2%.  All the metropolitan areas in upstate New York had increases of less than 10%, with Albany-Schenectady-Troy showing the strongest growth – 9.1%, followed by Rochester with 8.9% and Buffalo-Niagara Falls with 8%.  Binghamton again lost traded service sector employment .

Traded Manufacturing and Service Employment 2010-2016

Following the great recession of 2008-2010, manufacturing employment rebounded nationally, as well as in several upstate New York metropolitan areas.  How much employment growth did traded manufacturing and service employment each contribute?

The performance of metropolitan areas showed substantial differences.  Nationally, manufacturing generated 11% of traded employment growth between 2010 and 2016.  But, in Albany-Schenectady-Troy. Utica-Rome and Michigan and Ohio metropolitan areas, manufacturing accounted for one-third or more of employment growth.  In Buffalo, manufacturing provided 20% of traded growth.  But in Binghamton, the New York City metropolitan area, Rochester and Syracuse, manufacturing employment continued to decline.

Because manufacturing employment dropped sharply between 2001 and 2016, and traded service employment generally increased, service employment now constitutes more than two-thirds of all traded employment nationally, and in most of the rust belt metropolitan areas studied.

Only the Binghamton metropolitan area has less than 70% of traded employment in service industries, and even that area has shifted towards services.

Conclusions

Over the 2001 – 2016 period, manufacturing dependent upstate metropolitan areas west of Albany-Schenectady-Troy and those in Michigan and Ohio did not do well. While traded employment in the United States increased by 13.3%, every upstate metropolitan area west of Albany and those in Ohio and Michigan and had less traded employment in 2016 than in 2001.  But, between 2001 and 2010 and 2010 and 2016, the employment of upstate metropolitan areas differed from other rust-belt metropolitan areas in Ohio and Michigan.  Ohio and Michigan had steeper traded employment declines between 2001 and 2010 and greater growth between 2010 and 2016 than did those in Western and Central New York.  The v-shaped employment change in Ohio and Michigan may have been primarily the result of the collapse and federal bail-out of the domestic auto industry during the great recession.

Traded service sector employment growth was relatively weak during both periods in Central and Western New York metropolitan areas.  Two small metropolitan areas – Utica-Rome and Binghamton had less traded service employment in 2016 than in 2001.  But, despite the relatively weak growth of traded service sector employment in Central and Western New York metropolitan areas, most traded employment growth in the region came from service sector industries.

State and local governments in the rust-belt seeking to strengthen regional economies face a challenging environment.  Because they have higher percentages of employment in declining and slow-growing industries than other regions, if rust-belt regions are to succeed in encouraging economic growth, they must focus on helping build employment in faster growing industries, while helping preserve the existing industrial base.   Because there are relatively few large business expansions and relocations in a given year (one estimate is 1,500)[4], attracting businesses in growing industries can be difficult – competition can be intense and incentive costs are often very high.  Supporting the growth of existing small businesses in faster growing sectors may be more cost-effective, but relatively few small businesses grow to become large employers.

Too often, policy makers think primarily of tax incentives as the primary tool to induce businesses to locate and expand within their jurisdictions.  But, tax incentives have crippling weaknesses as economic development policy tools.  First, they are extraordinarily wasteful.  Timothy J. Bartik, in “Who Benefits from Economic Development Incentives? How Incentive Effects on Local Incomes and the Income Distribution Vary with Different Assumptions about Incentive Policy and the Local Economy”[5] found that 85 to 90% of typical incentive spending is wasted, because it does not affect the existence of about 85 to 90% of the jobs that receive tax incentives. Bartik writes, ““But for” the typical incentives, the probability of the incented jobs choosing the state would have been reduced from 100 percent to 90 or 85 percent.” Because of this, Bartik concludes, “As a result, the direct budget costs of incentives significantly exceed fiscal benefits.”[6] Bartik estimates that fiscal benefits are 22% of incentive costs, based on his model’s assumptions.

In practical terms, the heavy use of tax incentives carries a large opportunity cost.  Given that state and local budgets are constrained by tax revenues, large tax incentive expenditures are likely to result in cuts to major state programs – primarily education and social assistance.  Alternatively, they can lead to tax increases, which decrease private sector demand because they reduce the number of dollars available to taxpayers to spend.

Development of successful economic development strategies at the state level requires understanding the needs of existing businesses within a region and the development of effective assistance strategies.  They require the creation and maintenance of strong relationships between state, local and regional economic development organizations.  They build knowledge of and relationships with existing traded businesses and seek to meet their needs.  Effective organizations maintain strong business visitation programs, assemble up to date site data, and work with private developers to expand site availability, work with training providers to ensure the availability of workers with needed skills, assist expanding businesses in expediting permit processes, and where needed, provide financial assistance for capital costs and worker training.

Because of the difficulties faced by upstate metropolitan areas west of Albany-Schenectady-Troy, Governor Cuomo has focused resources on the region. The Governor proposed legislation in 2011 creating Regional Economic Development Councils. The Councils are responsible for the creation and implementation of regional economic development plans.  The state provided funding to support their implementation.

The intent of the initiative is to give regions greater voice in decision making about state supported economic development efforts.  As of 2018, the state has spent $5.4 billion on projects selected through the Regional Councils.[7]  This year’s funding is $750,000,000.  $225 million is to be provided through grants and tax credits from Empire State Development, and $525 million through other state agency programs.  To be sure, much of the spending is through already existing programs, but there has been significant additional funding provided for regional initiatives.

Much of the emphasis of the regional strategies that were developed in response to the Governor’s call has been on growing advanced manufacturing and high technology within upstate New York regions.  And, the State has encouraged that focus with a series of large investments in high technology manufacturing facilities. It is clearly rational for regional economic developers to focus on retaining manufacturing employment, and it is possible for manufacturing employment to grow, as it has in some metropolitan areas.   But, over the past forty years, manufacturing employment’s share of national employment has declined.  High technology manufacturing has declined along with more traditional industries. Regional economic development strategies should recognize that most employment growth in upstate New York and elsewhere, even that in traded industries that export products and services, is in services.

Future posts will examine additional employment challenges faced by upstate metropolitan areas and the Governor’s Regional Economic Development initiative.

[1] One of the relatively rare exceptions might be found in the food processing industry, such as a few dairies that only sell their products within the metropolitan areas where they are located.

[2]Source:  Bureau of Labor Statistics – Current Employment Survey.  Traded employment estimated as proposed by Mercedes Delgado, Richard Bryden and Samantha Zyontz, in “Categorization of Traded and Local Industries in the US Economy,”   http://clustermapping.us/sites/default/files/files/page/Categorization%20of%20Traded%20and%20Local%20Industries%20in%20the%20US%20Economy.pdf.  In this paper the authors estimate the percentage of employment in two-digit NAICS codes that is traded.  Because two digit codes are broad categories, differences in industry mix within clusters between areas are possible sources of estimation error.

[3] “Import Competition and The Great U.S. Employment Sag of The 2000s” Daron Acemoglu, David Autor, David Dorn, Gordon H. Hanson, and Brendan Price, NBER Working Paper 20395, http://www.nber.org/papers/w20395.pdf

[4] Timothy J. Bartik, “Local Economic Development Policies,” Upjohn Institute Working Paper No. 03-91, W. E. Upjohn Institute, 2003.  http://research.upjohn.org/cgi/viewcontent.cgi?article=1108&context=up_workingpapers

[5] http://research.upjohn.org/cgi/viewcontent.cgi?article=1037&context=up_technicalreports

[6] Ibid, pp. viii-ix.

[7] https://regionalcouncils.ny.gov/about




Nexgen in Syracuse – Throwing Good Money after Bad?

Update:  Note that the Syracuse Post Standard carried the following article on January 4th:  http://www.syracuse.com/business-news/index.ssf/2018/01/ny_taxpayers_built_90m_factory_in_dewitt_for_firm_that_walked_away_didnt_create.html The article quotes ESD spokesman Jason Conwell.  “Conwall said the grant will be contingent on the company meeting its job commitments. Details of the grant’s terms will not be available until the grant disbursement agreement is executed later this month, but they will follow ESD’s standard practice of requiring companies to return a grant, or portions of it, if they fail to meet hiring milestones, he said.”  

Note that ESD General Project Plans, adopted by its Board, generally contain specific job and recapture requirements, and that the plan adopted by the Board in its December meeting does not.  However, as Conwell states, such a requirement could be included in the Grant Development Agreement, which both ESD and the company would sign.  If so, the action would address one of the issues in my commentary, below.

Recently, a news article in the Syracuse Post Standard, “Soraa walks away from $90M factory that NY built; $15M more brings new tenant,” described New York’s attempt to save its investment in a $90 million facility in Dewitt, near Syracuse, originally intended for Soraa, a manufacturer of LED lighting.  In addition to the facility, Empire State Development has awarded a $15 million grant to Nexgen, a power converter manufacturer.  Both the original agreement with Soraa and the construction of the facility, as well as the new grant to Nexgen contain highly questionable features that expose taxpayers to real, unnecessary risks, features that are common to a number of projects undertaken by the SUNY Polytechnic, SUNY Research Foundation and Fort Schuyler Management Corporation, a group of related state sponsored entities.

Soraa

In October, 2015, Governor Cuomo announced that Soraa, an industry leader in ultra-high performance lighting and LED technologies, will relocate its global manufacturing and research and development operations from California and overseas to SUNY Polytechnic’s Central New York Hub for Emerging Nano Industries. This move will create 420 new high-tech jobs in Central New York and is being made possible thanks to a $90 million state investment for the facility’s construction.”

The project, like the Solar City project in Buffalo that I examined in an earlier post, made the SUNY Research Foundation the owner of the facility being constructed. Like Solar City, Soraa was to be responsible for a $1 per year lease payment for the facility, and for shouldering operating expenses related to production.  In my earlier post, I pointed to a major problem with the model used in these projects:

  • “State taxpayers will be exposed to an unusually high degree of risk by the unprecedented structure of the SolarCity deal, under which Fort Schuyler Management Corp., a non-profit subsidiary of the State University’s College of Nanoscale Science and Engineering, is building the factory for the company, and will retain ownership. SolarCity’s up-front capital investment in the project is thus limited, weakening its incentive to remain in Buffalo after its dollar-a-year lease of the building expires in 10 years.”

This issue was present in the deal with Soraa, along with an additional problem – one which left the state’s investment exposed when Soraa pulled out of its deal with the SUNY Research Foundation.  SUNY’s deal with Solar City calls for graduated penalties if the company ceases production at the facility within the first 10 years after completion of the project.  The penalties would allow the state to recapture part of its investment of more than $750 million in the project if the company broke the lease during that time.  But, incredibly, SUNY’s deal with Soraa contained no recapture provision, leaving the state with no return on its $90 million investment in the building and equipment when Soraa decided not to go ahead with production in New York state.

Construction of the Soraa facility was delayed for a time because of the indictment by then U. S. Attorney for the Southern District of New York, Preet Bharara of Dr. Alain Kaloyeros, the head of SUNY Polytech, and of principals of Cor Development of Syracuse, on bribery, wire fraud, and other charges.

According to the Post Standard article, [Howard] Zemsky [Chairman of Empire State Development] said the delay may have been a factor in Soraa’s decision to abandon the local plant. But he said Soraa also is facing competitive pressures from Asian manufacturers. The company ultimately decided not to invest in the DeWitt plant.”

Nexgen Power Systems

The public was made aware of Soraa’s decision when Empire State Development’s Board of Directors approved a $15 million grant to a new occupant for the facility – Nexgen Power Systems.  On December 20th, the Syracuse Post Standard reported that

NexGen Power Systems, a startup company from California, plans to manufacture semiconductors for the electronics industry in the 82,000-square-foot plant in DeWitt, said Howard Zemsky, CEO of Empire State Development.

NexGen has promised to invest $40 million of its own in the facility and to create at least 290 jobs within seven years, state officials said. The company plans to move in sometime around the middle of 2018….

Despite the assurances of state officials, the NexGen deal has the same primary problem as  Soraa and Solar City deals, and some others as well.  Like the earlier deals, in the NexGen deal, New York State, through the SUNY Research Foundation retains ownership of the $90 million facility, leasing it to NexGen for $1 per year.  As a result, New York continues to bear the risk of ownership of the facility if NexGen does not continue to produce products at the Dewitt facility.

Although the Fort Schuyler Management Corporation website does not show an agreement with NexGen that describes its relationship with the company, Empire State Development’s website shows the General Project Plan for the $15 million grant that NexGen is receiving. While “Nexgen promises to employ 290 new full-time permanent employees within seven years of project completion,” the General Project Plan does not include a requirement setting the length of time the company must maintain the jobs or a provision for recapture of a portion of the value of the facility if the company leaves.  As a result, the employment commitment in the ESD grant appears to be unenforceable.  Also, though the Syracuse Post Standard quoted state officials as saying that “NexGen has promised to invest $40 million of its own in the facility,,,” The ESD Board materials contain no reference to any financial commitment by the company.

This raises another concern that is common to the projects undertaken by the SUNY Research Foundation.  Solar City, Soraa and Nexgen have relatively little company capital investment in their New York projects.  Because the state is providing essentially all of the capital costs of these projects, New York is getting very little leverage from the investment of State dollars.  This is in sharp contrast to prior state assistance to businesses – even for large projects like the semiconductor facility operated by Global Foundries in Malta – where ESD provided grants covering $650 million of the $3.2 billion capital investment (The company was also eligible for up to $600 mllion of Empire Zone benefits over 10 years).

Nexgen Power Systems – Company Risks

Nexgen is a startup company, and, there is little publicly available information concerning the production or distribution of established products.  In fact, the company’s website provides no specific information about the company’s financial resources or production capabilities.  Nor does publicly available information show that the company has received venture capital funding to support the $40 million that state officials say that it has promised to invest in operating costs related to production at the facility.

Press reports indicate that the company is a successor to Avogy, a failed startup, that produced laptop chargers that claimed to use the same gallium nitride technology that Nexgen promises to use in its Dewitt facility. One analysis (“Is Avogy Inc. Dead?” on PntPower.com) of Avogy’s failure pointed out, “Avogy developed a GaN/GaN power semiconductor device.  They own several patents in the field…But, according to all the people we discussed with, the distribution of these devices has never been large.”

According to Crunchbase.com, Avogy had received $40 million in a second round of venture capital funding in 2014 from Intel and Khosla Ventures, before disappearing in early 2017.  Court documents indicate that total venture funding for the company was $60,000,000.

Nexgen acquired Avogy’s intellectual property for $200,000. A report on Axios.com states that Khosla Ventures, the venture capital firm that had invested in Avogy, had sued Dinesh Ramanathan, the founder of Avogy and Nexgen.  The report states, “Vinod Khosla’s venture capital firm has sued the former CEO of a failed portfolio company, accusing him of fraud and extortion. But it’s not really about recovering the $60 million that Khosla Ventures invested, since that money is long gone. Instead, it’s about getting back at what Khosla believes is a duplicitous executive by exposing his alleged misdeeds.” The suit argues that Ramanathan engaged in self dealing by rejecting a slightly better offer for the intellectual property than his own bid, and attempted to illegally gain a cash payment from Soraa for the technology.

Nexgen’s website indicates that its core product is a laptop charger that is smaller and lighter than current devices.  The company claims to have switching technology that operates at higher frequencies than current silicon-based technology, reducing the size of inductors and capacitors in the circuit. The website describes the technology this way: “Avogy’s TrueGaN /XX platform…uses high frequency GaN switches in combination with a high efficiency circuit architecture, to enable at a fundamental level, the change required to build small power supplies, safely.”  In the past, gallium nitride based devices have been relatively expensive.

The charger is shown on a page on the Nexgen website that is not linked to the company’s home page.  Originally advertised at $99.95, the device is now available at $29.95 on Rakuten.com.  The charger is also sold on Amazon.com, where it has only three reviews, two of them negative, with comments about sparks and fire hazards.  Amazon.com indicates that the charger’s sales rank is 1,070 in the charger category.  It faces competition from FIXSix, which produces a similar small, laptop charger (FIXSix Dart).

While it was in business, Avogy produced a laptop charger through a subsidiary, Zolt, that claimed to use gallium nitride technology .  However, a teardown published on chipworks.com claimed that the charger used silicon technology, not Gallium Nitride.

The future prospects of Nexgen are unknown.  The company may continue to compete in the marketplace with a laptop charger that faces stiff competition from existing products.  It might also manufacture and sell power conversion semiconductors using its technology to product producers.  Whether it can succeed will depend on  a number of factors, including the advantages its technology offers, the price of its products, and its success in developing relationships with product producers and sellers.

Startup Companies and Venture Capital

When New York offered funding for the Global Foundries semiconductor chip fab it was dealing with an established company in an industry, because of the very large capital requirements and production expertise required, that has high barriers to entry.  But, barriers to entry are relatively low in other technology industries, like power conversion.  Additionally, investing in startup companies carries considerable risk, because the companies fail at relatively high rates. As a result, when New York acts as a venture capitalist, its investments carry high risks.

Startup companies often receive funding from venture capitalists, as Nexgen’s predecessor, Avogy, did.  Other sources include angel investors, and business incubators.  In these cases, investors get ownership stakes in the companies.  These investors generally participate in operational decisions of the companies that receive funding.  Financial, industry knowledge, marketing and networking expertise are generally provided.

New York, through the SUNY Research Foundation, does not provide the same kinds of assistance to the companies that it assists.  For example, the Memorandum of Agreement with Soraa made the Foundation responsible for constructing and equipping the facility for up to $90 million.  It also promised to help the company locate additional high technology jobs at the company’s contractors and suppliers in New York State, and to provide training for company staff.

Since New York State does not have an ownership interest in companies like Nexgen and Soraa, it has no real leverage to ensure that assisted companies will employ good financial practices, and is not offering to provide assistance in operational matters, such as developing relationships with product buyers and in product marketing.

As a venture capitalist, New York is in a relatively weak position, because it does not take ownership positions that would provide it some control over assisted companies, and has chosen to make large investments without finding partners to share risk.  By making large investments in a relatively small number of firms, the State’s approach increases the risk to its investments associated with company failures.

Conclusions

Soraa’s decision not to locate at the facility that New York had built for it in Dewitt left the state in a difficult position.  Because the state owns the building and equipment within it, it needed to find a tenant, to ensure that some return would be received on its investment.  Since the building had specialized design features and equipment intended for a company using gallium nitride technology, Nexgen appeared to offer a reasonably good solution to New York’s problem.  But, based on evidence now available, the state appears to be repeating mistakes that put it in the position of needing to find a tenant for a nearly $1o0 million facility.  Most importantly, while the Nexgen promised to employ at least 290 people at the facility, the General Project Plan adopted by Empire State Development does not specify the time period for which employees must be retained  and provides no penalties if the company does not meet its employment target.

At the same time, the State’s $105 million investment provides a very poor return on investment, based on the most optimistic assumptions.  The economic benefit of the project (tax revenues to state and local government plus net resident disposable income) according to Empire State Development’s Benefit-Cost evaluation is only 1.47 to 1, far below ESD’s benchmark for projects of 75 to 1.  The project’s fiscal (tax revenues to state and local governments) benefit cost ratio is negative: .12 to 1.

But, ESD’s benefit-cost analysis is not credible, because it assumes the project will maintain 290 new jobs over seven years.  Since the project plan does not contain any requirement for the period of time that jobs must be maintained, and since there is no recapture agreement in the event that jobs aren’t created, the analysis is based on an assumed set of circumstances that the agreement does not require the company to meet.

Finally, note that the decision to chase 290 high technology jobs in this case carries a high price tag – $105 million, an amount that is substantially larger than the amount ($86 million) that the region will receive in the coming year from the state’s primary regional economic development initiative – the 2017 Regional Council Competition.

New York, like other states has emphasized the pursuit of high technology companies as a key to the state’s future economic well-being.  In New York’s case, most of the state’s spending has been on high technology manufacturing, including the Global Foundries Chip Fab in Saratoga County, Solar City’s solar panel facility in Buffalo, Nexgen’s power converter plant in the Syracuse area, Norsk Titanium in Plattsburgh, and Danfoss Silicon Power near Utica.

But the price tag has been very high; several billion dollars in total, and other than Global Foundries, none of the facilities is expected to employ more than 500 people.  The long term prognosis for these facilities is also doubtful.  Over the past twenty years, employment in the electronics industry in the United States has cratered.  Employment at computer manufacturers in 2015 was less than 20% of what it was in 1998. Electronic component manufacturers employ 42% of the workers that they did in that year.  Semiconductor manufacturers employment is 45% of what it was in 1998.  In New York State, despite the opening of the Global Foundries facility in Malta, semiconductor manufacturing statewide is 17% lower (Source: U.S. Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School).

Perhaps it is time for policy makers to gain a better understanding which industries are growing nationally and in New York State, and to focus their attention on making sure that New York gets its share of national growth.  The state should also help existing businesses in New York compete by working with them to meet labor, facility and infrastructure needs.




Data, Key Punches, Blogging and the Upstate Economy

Fifty years ago, as a research assistant in graduate school at Syracuse University, I did some quantitative research for a professor on the effect of various factors on state policy outputs.

Technische Hochschule Aachen
Rechenzentrum

Doing the work required me find data in books in the university library and to go to a room in the university computer center, like the one in the illustration on the right, to put the data on cards using a key punch. Once the cards were punched, I gave the deck of cards to a member of the university’s computer staff. who then put them in a card reader connected to a computer.  On the computer, a statistical analysis program – SPSS (Statistical Package for the Social Sciences), provided the tools I needed to analyze my data.  Later, I would return to collect sheets of paper on which the results were printed.

The process was slow and cumbersome, involving hours of work to collect, input and analyze data.  Today, that data can be collected and analyzed in minutes on a laptop computer.  With the internet, I no longer have to comb through books from a specialized library, and with a personal computer, I no longer have to go to a central place to analyze data.

Information sharing is much easier, too.  In the past, if I wanted to share research data, I would have to find an institution that was willing to publish it – a process that sometimes required researchers to share in the cost of publication.  Today, the internet offers the possibility to reach readers directly.  Over the past two years, I’ve been able to publish more than two dozen research notes on my blog, reaching thousands of readers.

On this blog, I’ve written about data related to significant policy issues that face New York, particularly upstate New York.  As a long-time upstate resident, I am aware that much of the region, particularly those areas that were historically dependent on manufacturing, faces significant challenges in making it possible for residents to find good jobs that pay well.

While upstate New York faces the same challenges as the rest of the rust belt, its metropolitan areas differ from those in other rust belt places, such as Michigan and Ohio, because the impact of the loss of manufacturing has been less severe here.  Metropolitan areas like Buffalo, Rochester and Syracuse continue to have relatively affluent suburban populations, and overall have median household incomes that are near the national average.  Paradoxically, upstate central cities have among the highest poverty rates in the region, and several of the cities face fiscal distress.  The map, below, shows employment growth rates from 1998 to 2015 for economic regions in the Northeast and Midwest.  The weakest rates in the region are on a belt along the southern shores of the Great Lakes running from Wisconsin to Ohio.  Although Western and Central New York have done less well than much of the country, they have performed better than much of the Midwest.

Through my analyses, I’ve tried to strengthen policy discussions that focus on the decline of upstate cities and rust belt metropolitan areas, in order to avoid errors such as attributing most of the region’s decline to relatively high taxation levels, and misguided attempts to revive regional economies that create too much taxpayer risk by spending hundreds of billions of dollars to attract high technology businesses.  I’ve looked at the paradox of thriving suburbs and declining cities in New York’s metropolitan areas, and the growth of racial segregation upstate.  I’ve also provided data to help readers understand the real reasons why city schools are “failing.”

I’ve been happy to see that some of my pieces have been seen by a relatively large number of people.  Among the most popular have been:

The Decline of Manufacturing in New York and the Rust Belt, which has had more than 3,000 views.

As Private Sector Employee Incomes Stagnate, Local Government Workers Prosper, with more than 2,300 views.

New York’s Ineffective Business Tax Incentiveswith 1,600 views.

New York’s “Failing Schools” – The Wrong Diagnosis and a Misguided Solutionwith 1,300 views, and

The Crisis of Poverty in Upstate New York Cities, with more than 1,000 views.

In the coming year, I’ll be a Richard P. Nation research fellow the Rockefeller Institute at the University of Albany.  The fellowship will afford me the ability to work with other researchers on critical issues.  I also hope to work with the Institute’s staff to develop forums to discuss some of these issues and policies.  As a result, in the coming year, some of my research will be published on the Institute’s blog, or as research publications.  In those cases, I’ll be sure to provide links to that work on this blog.

In the past two years, much of the impetus for my work has come from accounts that I have read in various places on the internet, such as a story that appeared in the New York Times, “Spike Nation: Cheap, unpredictable and hard to regulate, synthetic marijuana has emergency responders scrambling to save lives.”, which contained the statement, “Syracuse is one of the poorest cities in America — more than a third of the people here live below the poverty line.”  Having lived in Syracuse in the 1960’s and 1970’s, I was aware that whenI lived there, that Syracuse was not one of the poorest cities in America.  The city had a mix of relatively poor and well-off areas.  That sparked my interest into researching what had happened to upstate metropolitan areas after I left Syracuse in 1971,  and led to several pieces on this blog.

Other pieces on this blog came from readers who asked questions about the proposed increase in the minimum wage, and about labor participation rates in upstate areas.  I hope that readers of this blog will continue to ask questions and offer their perspectives.  I may be contacted at  john.bacheller@policybynumbers.com.  

In the coming year, I plan to continue to look at labor participation and employment in New York State with a focus on disparities between cities and suburbs.  I’m also collecting data on city and town tax and revenue burdens and spending patterns to understand how they differ, and researching New York’s Regional Economic Development Council initiative to better assess strengths and weaknesses.  I also hope to take a look at some more data about student performance in New York schools.   I expect to publish findings via the Rockefeller Institute and on this blog in the coming months.

Illustrations are from Wikipedia.  Map is from: U.S. Cluster Mapping Project, Institute for Strategy and Competitiveness, Harvard Business School.    http://www.clustermapping.us/region




Left Behind: Characteristics of Low Labor Participation Counties

In my last post, I examined labor market participation in New York State counties.  I found that most New Yorkers, both upstate and downstate, live in counties where labor market participation differs only slightly from national levels, but upstate counties with small populations in many cases have labor participation rates that are significantly below the average.  In this post, I look more closely at the ways that low participation counties differ from those with higher labor market participation.  In particular, I examine how income compositions, and industry compositions differ.

The data shows that employment has decreased between 1970 and 2015 in upstate counties with low levels of labor participation, largely because weak service sector employment growth was insufficient to offset losses in non-service industries.  Earnings per employee were weak in low participation counties as well.  In 2015, per employee earnings overall were 16% lower in  upstate low labor participation counties than in high participation counties, and 47% lower than those in the New York city metropolitan area.  Differentials between per employee earnings were particularly large in relatively high paying service industries, such as information, financial services, and professional and business services.  Government transfer payments make up a larger part of personal income in counties with low labor participation because of low employment levels in these counties.  Government employment made up a larger part of total employment in low participation counties because of the low level of private sector employment in these counties.

Data from this post is from the U. S. Bureau of Economic Analysis – Local Area Personal Income and Employment tables.  Much of the BEA data referenced was taken from the data presentations found at the Headwaters Economics Economic Profile System.

County Population Size

On average, the fifteen upstate counties with the lowest levels of labor participation had populations that were much smaller than those with high levels of participation, or those in the New York State metropolitan area.  On average, low participation upstate counties populations were only 22% of high participation counties, and 6% of counties in the New York metro area.

Populations of both the top and bottom 15 participation counties upstate have been essentially stagnant since 1970.  While high participation counties showed a small amount of growth between 1990 and 2015, and low participation counties have declined since that year, populations in both have only increased by about 2% since 1970.  The populations of New York metropolitan area counties have increased by 12% since 1970, and by 18% since 1980.

Employment

Not surprisingly, full and part-time employment as the percentage of the population of low labor participation counties was lower than counties where labor participation was higher.

Low participation counties had lower levels of employment throughout the period than either high participation counties, or counties in the New York metropolitan area.  Significantly, the gap in employment levels between low participation counties and other counties has increased over time – from six to eight percent less in 1970 to 14% to 16% less in 2015.

Income

Average wages and salaries have consistently been highest in counties in the New York Metropolitan area, followed by high participation upstate counties, with low participation upstate counties having the lowest average wages and salaries.  While the difference between low and high participation counties upstate has been relatively constant since 1970 – about 15% – the gap between average wages and salaries in the New York City Metropolitan area and in high participation areas upstate has grown from 7% in 1970 to 24% in 2015.

The Bureau of Economic Analysis income data is average, not median, income.  In contrast, inflation adjusted median incomes have not risen significantly for the past 15 years, and have risen much less than average incomes over the period since 1970.  Median incomes have increased less than average incomes because most real income growth over the past several decades nationally has been received by high income workers, while typical workers have had much smaller income growth.  See, for example, the chart below, from “Distributional National Accounts: Methods and Estimates for the United States,” by Thomas Piketty, Emmanuel Saez, and Gabriel Zucman

Components of Personal Income

Labor income (work related compensation) is a smaller part of personal income in low labor participation counties than in high participation counties upstate and in the New York City metropolitan area, while transfer payments (such as Social Security benefits, medical benefits, veterans’ benefits, unemployment insurance benefits, liability payments for personal injury and corporate gifts to nonprofit institutions)  make up a larger part of personal income in these counties than elsewhere.  Transfer payments are 26.6% of total personal income in low participation counties upstate, compared with only 15.9% in the New York metropolitan area and 19.9% in high participation counties upstate.  Dividends, interest and rent are 14.6% of total personal income in low participation counties, compared with 21.8% in the New York City metropolitan area.

The fact that transfer payments make up more than 26% of per capital personal income in low participation counties compared to 16% in the New York metropolitan area might lead readers to conclude that the amount of government transfer payments per capita is greater in low participation counties  upstate than in high participation counties or in the New York City metropolitan area.  In fact, that is not the case – per capita transfer payment levels per capita differ little.  Instead, they are more important in low participation counties because wage, salary and benefit levels are lower than elsewhere.

Employment

Employment patterns in high and low labor participation counties upstate and in the New York City metropolitan areas differ. Low labor participation counties had much larger percentages of total employment in non-service sector industries and in government.

Employment in service industries was 79% of the total in the New York City metropolitan area in 2015, while in low labor participation counties upstate, service sector employment was only 56% of the total.  Service sector employment in high labor participation counties upstate was 70% of total employment.

Several relatively high paying service industries – information services, financial activities, professional and business services and education and health services were  concentrated in counties in the New York City metropolitan area, with 48% of total employment in the region in 2015. In high participation counties upstate, these industries were also relatively important, having 38% of total employment.  In low participation counties upstate, however, these industries only accounted for 24% of total employment. In contrast, relatively low paying service industries, like trade, transportation and utilities and leisure and hospitality accounted for between 27% and 28% of all employment in each region.

Non-Services related employment (primarily manufacturing and construction) was 19% of the total in low labor participation counties upstate, while it was only 7% of the total in the New York City metropolitan area.  Again, high participation counties upstate were between low participation counties and the New York City metropolitan area on this measure, with 13.2% of total employment in non-service related industries.  Manufacturing was 8.7% of total employment in high labor participation upstate counties, 13.3% in low participation upstate counties, and 2.9% in counties in the New York City metropolitan area in 2015.

In low participation counties in upstate New York, more than one-quarter (25.4%) of all employment is in government, while in the New York metropolitan area, government employment is only 13.5% of the total.  In high participation counties, upstate, government employment was 17% of total employment. Local government employment is a larger part of total employment in low participation counties upstate than elsewhere – 16% of the total.  State government employment is also a larger part of total employment in low participation areas than elsewhere – 8%.

Why is government employment a much larger percentage of total employment in low labor participation counties?  The table above shows that government employment is about the same percentage of the total population in high and low participation counties upstate – between 8% and 9%, while in New York City, government employment is about 6% of the population.  But, the percentage of the population that is employed in the private sector is much lower – 26% in low participation counties upstate, compared with 40% in upstate high participation counties and in counties in the New York metropolitan area.

Overall, total employment in low labor participation counties is only slightly more than one-third of the total population – 35%, compared with nearly half – between 46.4% and 48.5% in counties in the New York City metropolitan area and in high participation counties upstate.

Change in Employment by Industry Sector Since 1970

Low labor participation counties upstate differed from high labor participation counties upstate and those in the New York City metropolitan area in the fact that these counties lost employment between 1970 and 2015.  Employment decreased in these counties by 6.3% during the period.  Employment in the New York metropolitan area increased by 6.7%, while in upstate high participation counties, it increased by 12.2%.

While non-services employment declined slightly less in low labor participation counties in upstate New York than other counties studied — 52% vs. 56% and 66%,  service sector employment grew much more slowly than elsewhere – 26% vs. 35% and 58%.

Employment and Population Change

Employment in low labor participation counties upstate decreased as a percentage of the counties’ populations by 2.9 percent between 1970 and 2015.  In the New York metropolitan area, employment as a percentage of counties’ populations decreased by 2.1%. Only in upstate counties with high levels of labor participation did employment as a percentage of population increase – by 4.1%.

In low participation counties, non-services employment  as a percent of county populations in industries like manufacturing has decreased slightly less than elsewhere – by 7.2% compared with 7.5% and 8.5% between 1970 and 2015, but service sector employment as a percentage of population  in upstate counties with low labor participation grew slower than elsewhere in those years.  In low participation upstate counties, service sector employment as a percentage of population grew by 3.8% compared to 11.9% percent in high labor participation counties, and 6.4% in counties in the New York City metropolitan area.

Per Employee Earnings by Industry

Per employee earnings are the sum of wages and salaries, supplements to wages and salaries, and proprietors’ income divided by employment.  Per employee earnings overall, in the private sector, and in government were lower in low participation counties upstate than they were in counties in the New York City metropolitan area and in high participation counties upstate.  Overall, earnings per employee were 16% lower in low participation counties upstate than in high participation counties upstate.  Compared to counties in the New York City metropolitan area, earnings per employee were 47% lower in low participation counties upstate.

Per employee earnings in the service sector in low participation counties show the greatest weakness compared to high participation counties upstate  (25% lower) and counties in the New York city metropolitan area (58% lower).   Per employee earnings in non-service sector industries, such as manufacturing, in low participation counties upstate were 16% lower than in high participation counties upstate, and 26% lower than in counties in the metropolitan area.  Differences in government earnings per employee between low and high participation counties upstate and counties in the New York City metropolitan area. Per employee earnings in low income counties upstate were 14% lower than in high income counties upstate, and 25% lower than in counties in the New York City metropolitan area.

A closer look at per employee earnings by industry sector in 2015 shows that low labor participation rate counties upstate were at a greater disadvantage to others in some industries than others.  For information services, per employee earnings were 31,536 in low participation counties, compared with 69,604 in high participation counties upstate, and $131,767 in counties in the New York City metropolitan area.  For professional and business services, per capita employee earnings were $39,004 in low labor participation counties upstate, compared with $60,015 in high labor participation counties, and $99,132.  For financial activities, per capita earnings for low participation counties were $48,746, compared with $66,689 in high labor participation counties upstate, and $200,727 in the New York City metropolitan area.  The industries with the greatest differentials between low participation areas and other locations were industries with relatively high per employee earnings.   Industries with lower per employee earnings, like leisure and hospitality and education and health services had smaller differences in earnings per employee between upstate low and high participation counties and counties in the New York metropolitan area.

Conclusions

The data supports the notion that counties with low levels of labor participation have weak labor markets characterized by weak employment growth in service industries that have seen growth nationally, and relatively low earnings per employee in service industries that have comparatively high earnings per employee.  Both of these factors support the conclusion offered in my earlier post on the subject that, “Differences in participation within groups between counties that have low and high labor participation levels at least partially reflect the hypothesis that people have been unable to find jobs and have left the labor force.”  

But, in my earlier post, based on low levels of participation by low skilled workers, I argued that, “The low levels of participation of these groups in low participation counties probably reflect reinforcing factors, like lower average levels of education among minority group members, the decline of manufacturing industries that employed low skilled men, and low levels of demand for workers without college educations in places where there are relatively few jobs available.”  Instead, this data shows that labor market growth in low labor participation counties has been particularly weak in those industries in the service sector, like information, financial services and professional and technical services that have relatively high earnings per employee.

In my earlier post, I concluded that, “The ability of low participation counties in small metropolitan areas and rural locations to create the resources needed to diversify their economies to include occupations that match the qualifications of residents are likely to be limited, because of the significant advantages offered by locations that have larger labor pools.”  The data presented in this post does nothing to contradict that conclusion.  And, because these labor markets are typically small and lack concentrations of workers with skills that are in high demand in growing industries, reversing their decay would present substantial challenges to remedial policy efforts.

Government actions can give residents the opportunity to increase their social mobility, though, even if the way mobility can be achieved is to move to locations with greater opportunities.  In “Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States,” by Raj Chetty, Nathaniel Hedren, Patrick Kline, and Emmanuel Saenz, the authors found that higher mobility is associated with higher quality primary and secondary education, greater family stability, and less income inequality.  But, more economic mobility also is related to geographic mobility from low income locations – those places that had higher levels of economic mobility also had higher levels of out-migration.

In a recent study by Eleanor Krause and Richard V. Reeves, “Rural Dreams, Upward Mobility in America’s Countryside” the authors conclude that several actions could be taken to increase mobility.  These include “increase the number of Advanced Placement courses and improve career and college counseling.” and providing better funding for rural schools.  Another option might be to encourage charter schools to open in low labor participation areas.  Extending the availability of high speed fiber networks could benefit schools that lack access to online curricula, internet-based research and online testing.

Krause and Reeves also point to the need to encourage family stability.  Discouraging teen pregnancy is one approach to helping teens to make decisions that are more likely to lead to stable families with two parents.  Increasing access to long-acting reversible contraceptives is particularly important. They argue,  that residents of rural areas face obstacles to receiving health care that urban residents do not.  “Efforts to reduce these disparities are likely to include the protection or expansion of health coverage (particularly publicly-funded health insurance for low-income families), supporting publicly funded clinics, and promoting the availability of the full range of contraceptive options, including LARCS. School-based health centers and online programs could also help to reduce transportation barriers in more isolated areas. (Of course, online platforms will only prove effective if complemented by expanded access to broadband in some regions.)”




Left Behind: Missing from the Labor Market in New York State

A reader of this blog recently wrote, “We know that labor force participation rates across the country have declined noticeably for a number of years, and many economists have warned of the troubling implications of this.  Such rates across Upstate NY have declined as well, and in most cases are significantly below the national average – not an encouraging sign.  In the North Country and the Mohawk Valley, they are not much above 50%, and in some other Upstate regions just a couple of percentage points higher. Clearly some of this indeed is because people have not been able to find jobs, and thus have left the labor force.  I don’t think a low unemployment rate necessarily indicates that “Upstate’s problem is not that its residents cannot find jobs.”

Low rates of labor market participation might indeed show that people are dropping out of the job market because of limited opportunities.  But, other factors are at work as well, including the aging of the population.  This post reviews labor market participation data in New York’s counties to understand changes over time and how low participation counties differ from those with higher participation rates.

A recent Brookings Institution study, “What we Know and Don’t Know about Declining Labor Force Participation: A Review” points out that: “This steady decline in prime-age male participation rates and recent stagnation of prime-age female rates has adverse implications for national economic growth and individual well-being. Workers between the ages of 25 and 54 tend to be at their most productive, so these trends affect economic growth as well as individual income. Further, as discussed below, lower work rates might be contributing to the decline in marriage and to poorer health and psychological well-being, possibly leading to an increase in premature deaths among certain populations.”

A significant part of the decline is explained by the aging of the population, as older workers move into retirement. John Robertson and Ellyn Terry of the Atlanta Federal Reserve Bank report that “In 2007, about one in five Americans were over 60 years old. In 2015, almost one in four were over 60. Moreover, this demographic force will continue to suppress the overall LFPR as the share of older Americans increases further in coming years.

But, labor force participation has declined overall.  The Bureau of Labor Statistics reported in 2016 that, “From 2000 to 2015, most of the major demographic groups saw a decrease in labor force participation. Teenagers experienced the largest drop in participation, which coincided with a rise in their school enrollment rate. Young adults 20 to 24 years also showed a decline in labor force participation, but the decrease was not as steep as that for teenagers. The labor force participation rate of women 25 to 54 years also fell, with the decrease more pronounced for women who did not attend college. The labor force participation rate of men 25 to 54 years continued its long-term decline. As in the past, the decrease in participation among men with less education was greater than that of men with more education. However, labor force participation rates of men and women 55 years and older rose from 2000 to 2009 and subsequently leveled off.”

The causes of the decrease in labor force participation for prime age people include both the demand for workers and the supply of labor.  On the demand side, technology and trade have reduced the demand for low skilled manufacturing workers.  The disparity in demand for workers at low and high skill levels has increased, because technology has led to greater demand for workers with technical and managerial skills.  On the supply side, the Brookings Institution study points out that “the problems include not only a lack of skills but high reservation wages [the wage levels at which people are willing to accept jobs], poor health, and the availability of disability insurance or other forms of unearned income.


Labor Force Participation in New York State

In this post, I look at differences in the labor force participation level between counties in New York State.  Because the economic performance of the New York City Metropolitan area has been stronger than upstate New York since 2000, participation in the two regions is examined separately, where relevant.

This analysis is at the county level, and does not show differences in participation based on levels of economic disadvantage below the county level, particularly in urban centers where participation may also be low.

The data shows that while changes in labor market participation from 2005 to 2015 in the New York Metropolitan area, and in larger upstate metropolitan areas did not differ much from the nation as a whole, smaller metropolitan areas and rural upstate had greater declines than the nation.  Comparing county performance in 2015, large differences were found in the educational attainment of residents of better and worse performing counties.  The percentage of college graduates in the populations of the 15 counties in New York State was more than double that found in the 15 counties with the lowest level of participation.  The behavior of residents within particular socio-economic groups in counties with high and low labor market participation varied as well.  Disproportionately lower percentages of people who did not complete high school, residents who were black or Hispanic or male, and residents who were 25 and 34 years old and 55 and 64 participated in the labor market in counties where labor market participation was low.

Data is from the Census Bureau’s American Community Survey.  The Census Bureau data differs from the Bureau of Labor Statistics data referenced at the beginning of this post in its methodology and sample selection.   The differences in methodology are  discussed here.

In this post, I use two different data samples.   Beginning in 2005, county level labor force participation data is available from the Census Bureau’s American Community Survey.  The sample used for the section titled “Change over Time” is from single year samples of one percent of the United States population.  The single year samples are too small to permit an analysis of data for small population units.  Consequently, only 37 of 62 counties in New York State are included.  Because the sample is relatively small, estimates of smaller county characteristics can have relatively large errors – as much as 2.5% for labor force participation for the entire population, and as much as 5% for some groups within the overall population.

In the section “Comparison of Labor Force Participation at the County Level in 2015” I use a five-year sample of the population that includes 5% of the United States population.  Because the sample is larger, it includes all New York counties, and has less sampling error.  Smaller county estimates are likely to be within 1.3% of the true value.  Estimates of groups within the overall population should be within 3% of the true value.  But, because the data is an average of five-year data, it lags trends, since the midpoint for the time period covered for the 2015 five-year data, which includes surveys from 2011 to 2015, is 2013.

Because differences in labor force participation between counties are relatively small, it is important to recognize that their relative performance can vary from year to year because of sampling error.  For example, Schenectady County’s labor participation rate was reported as 63.7% in 2014, 61.7% in 2015, and 64.7% in 2016.  That kind of variation could reflect sample variation around the true participation level.


Change over Time

The tables showing change over time between 2005 and 1026 are based on the American Community Survey data for a single year.  Counties in the New York Metropolitan areas saw relatively wide variations in the change in the level of labor force participation between 2005 and 2016.  For example, Kings County (Bronx) saw an increase from 59.7% to 63.9% over the period, while Dutchess County saw a decrease of 6.2% from 68.4% to 62.2%.  Two thirds of the counties in the metropolitan area did better than the national average, based on the American Community Survey sample data.
Three quarters – nine of twelve counties in the New York metropolitan area had participation rates that were higher than the national average in 2016, compared with seven of twelve in 2005.

Census Bureau’s American Community Survey 2016 one year data includes 26 of 50 counties outside the New York Metropolitan area.

In upstate New York, larger metropolitan counties, like Monroe, Schenectady, Saratoga, Albany, Niagara and Erie County had smaller percentage labor force participation losses between 2005 and 2016 than did the nation .  Others, like Rensselaer County, Onondaga County and Cayuga County were near enough to the national average to be within the margin of error of the national estimate.

Many small upstate counties had larger declines than the nation as a whole.  Decreases in Broome County (5.8%), Ulster County (5.9%), St. Lawrence County (6.1%), Oswego County (6.2%), Chautauqua County (6.5%), Clinton County (6.7%), Ontario County (8.3%) and Sullivan County (9.9%) were all more than twice as great as the national average. It is also important to note that all of these counties had participation rates in 2015 that were significantly lower than the national average.  Chautauqua County was lowest at 55%. Seven upstate metropolitan areas had participation rates that were greater than the national average, compared with 18 that were below it.  In 2005, eight upstate counties had participation rates that were higher than the nation as a whole, and 17 were below.


Comparison of Labor Force Participation at the County Level

The American Community Survey five-year sample from 2011 to 2o15 used in the following section has a margin of error of approximately plus or minus 1.3% for counties, so differences of that size between counties should not be viewed as significant.  Because this data has a different time period (2011 to 2015) and sample size, the numbers differ from the discussion of change above.

Nationally, 63.7% of people 16 years old or older were in the labor force in 2015.  In New York State, participation in 2015 ranged from 67.6% in Putnam County, where 67.6% were in the labor force, to 50.8% in Hamilton County. Overall, participation levels were higher in the New York metropolitan area (65.3%) than in upstate counties (60.0%).

Two of five counties in New York City (New York, and Queens) had participation rates in 2015 that were above the national average, while three had rates that were below (Kings, Bronx and Richmond). Suburban counties in the New York City Metropolitan Area were above the national average.

Upstate, larger metropolitan counties, including counties around Albany-Schenectady-Troy, Rochester, Syracuse, and Buffalo-Niagara Falls, had labor participation rates that were higher than or within their margin of error compared with the national average.  Smaller urban areas upstate, like Utica-Rome (59.4%), Binghamton (58.7%), Jamestown (58.1%) and Elmira-Corning (56.9%) and rural counties generally had participation rates that were below the national average


Factors Related to Labor Force Participation Rates

Census data includes a number of factors that show significant relationships with levels of labor force participation.  Among the more important are:

Educational Level

At the individual level, education is a significant predictor of labor force participation.  People with a bachelor’s degree or higher are  27% more likely to be employed or seeking employment than those with have not graduated from high school.

  • Education: Population Characteristics

In 2015, there were large differences in educational attainment in the 15 counties with the highest labor market participation and the 15 with the lowest participation.  Counties with high levels of participation had 15% fewer people whose highest level of educational attainment was high school graduation than did counties with low levels of participation. Counties with high levels of participation in 2015 had 24% more people who had attained a Bachelor’s degree or higher than did the 15 counties with the lowest participation levels.

  • Labor Market Participation at Each Level of Educational Attainment

Comparing the top quarter of counties ranked by labor market participation with the bottom quarter, the largest divide in participation is for people with less than a high school degree.  On average, only 41% of those with less than a high school diploma were labor market participants in 2015 in the lowest quarter of counties ranked by participation.  In  the quarter of counties with the highest participation levels, 62% of those with less than a high school diploma participate.  At the opposite end of the educational spectrum, the difference in labor market participation levels for those with a Bachelor’s degree or more was only 3.3% – 87.1% vs. 83.3%.

 

Age

Like education, age is related to labor market participation at the individual level.  Young (16-19 years old)and old (60+) people participate at lower rates than workers of other ages.  As a result, it is not surprising that counties whose populations have higher percentages of older people have lower labor participation rates than counties with younger populations.

  • Age: Population Characteristics

This section compares labor market participation levels for two age groups:  younger workers aged 25-44 are in age groups that show the highest levels of labor market participation overall, and older people, aged 55+ who are beginning to leave the labor market.  The differences in the size of the older compared to the younger age group in the top 15 and bottom 15 counties are relatively small – in the top 15 counties, people between 25 and 44 make up 5% more of the total population than in the bottom 15 counties.  Older people, aged 55 or more, are 4% more of the total population in the lowest 15 counties than in the highest 15 counties.

  • Labor Market Participation at Each Age Range

Comparing labor force participation with age for the highest quarter of counties vs. the lowest quarter shows that participation levels differ most for those between 25 and 34 and for those who are 55 to 64 – in those cases the difference between participation levels is more than 10%.

Gender

  • Labor Market Participation:  Men vs. Women

Statewide, 81.4% of men and 72.8% of women were in the labor force in 2015.  Although difference between the labor participation rate of women living in the top quarter of counties ranked by labor participation compared with the lowest quarter of counties was 4.9%, the difference in participation rates for men in high versus low participation rates was much larger – 13.9%.

Race

For this analysis, the state has been separated into the New York City Metropolitan area and the rest of the state, because of significant differences in the levels of black/Afro-American and hispanic labor participation.  Because the number of black and Hispanic residents of low participation counties New York City Metropolitan Area is quite small, the comparisons presented here are between the top half of counties by labor market participation and the bottom half.

  • Race and Ethnicity: Population Characteristics

In the New York City Metropolitan area, the top half of counties ranked by labor market participation had populations in 2015 aged 16 or over that were 52% white, compared with 34% white for the lower participation counties.  High participation counties had 8% less black/Afro-American residents and 4.5% less Hispanic/Latino residents.

Upstate, the top half of counties ranked by labor market participation in 2015 had populations in 2015 that were 82% white, compared with 87% white in lower participation counties.  Blacks/African-Americans comprised 4.4% more of the population aged 16 or more in higher participation counties than in lower participation counties.

  • Labor Market Participation: Race and Ethnicity

In the New York City metropolitan area, participation rates for blacks/Afro-Americans, Hispanics and whites were similar in the low and high participation counties in 2015.  The difference in labor force participation in high and low participation counties was only 3.1%.  For black/Afro-American, participation is 63% in both high and low participation counties.  Hispanic and white residents participated more in the labor market in high participation counties by 3% and 4% respectively.

In upstate counties, the picture differs.  White labor market participation in high participation counties was 5.3% higher in 2015 than in low participation counties.  Hispanic labor market participation was 14% higher in high participation counties than in low participation counties.  For black/African-American residents, the difference was 25% in 2015, with participation averaging only 34% in low participation counties, compared with 59% in high participation counties.


Conclusions:

In the New York Metropolitan area, county populations aged 16 or over are large – averaging 650,000 for high participation counties, and 1.1 million for lower participation counties.  Additionally, the range of labor participation levels in the New York Metropolitan area was relatively small in 2015, and participation levels were higher overall than upstate.  In fact, the participation rate for the lowest county in the New York Metropolitan area – Staten Island – was within 1/10th of one percent of the average for upstate counties.

The range for upstate counties was much larger.  Saratoga County’s participation rate of 67.6% was the second highest in the state, while Hamilton County’s was 50.8%, almost 9% lower than the lowest county in the New York Metropolitan area.  In Upstate New York, labor force participation is higher in large metropolitan areas than in small ones.  This finding suggests that areas with smaller populations do not provide the opportunities for employment that are offered by larger ones.

Participation Differences Resulting from Differences in County Population Characteristics

Two characteristics showed consistent differences between counties with low and high participation levels – education and age.  Of the two, educational attainment showed much larger variations between counties with high participation levels and those with low levels of labor market participation.  The difference in the percentage of residents with college degrees or more is particularly striking:  45.4% in the 15 counties with the highest levels of labor market participation, and 21% in the 15 counties with the lowest levels.  In contrast, 35.5% of residents in counties with low participation levels had ended their education at high school graduation, while 21% of those in counties with high levels of participation had only graduated high school, a difference of 14%.

A portion of the variation in the educational attainment of residents between counties is likely to be a result of the differing levels of educational levels of educational attainment of young adults who were raised in those counties.  Another part stems from migration patterns of young people seeking and finding first jobs inside and outside their home counties.  Determining the relative contribution of each factor is beyond the scope of this research.

It was expected from previous research that counties having a higher proportion of older residents would have lower participation levels than those with younger residents.  But, the differences found in counties in New York State were less significant than those for educational attainment.  The percentage of residents aged 25-44 was about 5% higher in high participation counties than in low counties, while the percentage of those 55 years old or older was 4% less.

Differences in Participation within Groups in High and Low Participation Counties

There were also significant variations in labor market participation within groups in high and low participation counties.  Among the more notable were:

  • Much lower labor market participation by people who did not complete high school in the 15 lowest participation counties, compared with the highest participation counties – 41% vs. 62%.
  • Significantly lower participation by workers aged 25 to 34 and 60-74 in low participation counties: differences exceeded 10% between the bottom and top quarter of counties sorted by labor participation.
  • Much lower participation by males in the 15 lowest participation counties, compared to the 15 highest (14%) than by females (5%).
  • Very large differences in participation levels for black/Afro-American residents and Hispanic/Latino residents between upstate counties with low and high labor participation levels – 25% for black/Afro-American residents and 14% for hispanic residents.

Differences in participation within groups between counties that have low and high labor participation levels at least partially reflect the hypothesis that people have been unable to find jobs and have left the labor force.  But beyond that, the data shows that some groups are much more likely than others to be absent from the labor force in low participation counties.  These include people with little education, men, young and old workers, and blacks and Hispanics.   The low levels of participation of these groups in low participation counties probably reflect reinforcing factors, like lower average levels of education among minority group members, the decline of manufacturing industries that employed low skilled men, and low levels of demand for workers without college educations in places where there are relatively few jobs available.

These differences are not present in the New York City metropolitan area, where most counties have relatively high labor market participation levels, or in larger upstate metropolitan areas, like Buffalo, Rochester, Syracuse and Albany, but they are significant is smaller urban areas like Utica, Binghamton and Elmira, and in rural areas of New York State.

To the extent that New York’s development policies can be based on need, one focus should be on upstate’s small urban areas and rural communities.  If smaller counties are to see more labor market participation by their residents, the state must help them address the barriers that have discouraged participation by less educated people, men, blacks/Afro-Americans and Latinos, and find ways to generate jobs that retain college graduates.  At the same time, policy makers concerned about the well-being of New York residents must recognize that some policies that would help residents of low participation counties access jobs could increase out-migration to locations with more employment opportunities.  The ability of low participation counties in small metropolitan areas and rural locations to create the resources needed to diversify their economies to include occupations that match the qualifications of residents are likely to be limited, because of the significant advantages offered by locations that have larger labor pools.




President Trump to Upstate Residents: Move to Wisconsin

Recently, in an interview with the Wall Street Journal, President Trump suggested that upstate New York residents should leave the state for Wisconsin, where a new Foxconn LCD display panel manufacturing plant will be located, creating at least 3,000 jobs.  President Trump said, “I said, you know, Gary, you go to certain sections and you’re going to need people to work in these massive plants that we’re getting, that are moving in. Where do we have the people? You know where we have the people? In New York state that can’t get jobs, in many other places that can’t get jobs. And people are going to have to start moving. They’re going to move to Colorado and they’re going to move to Iowa and Wisconsin and places where – like if Foxconn goes to Wisconsin, which is one of the places they’re very strongly considering – but if Foxconn goes to Wisconsin and they have a very low rate and the governor’s done an excellent job, you’re going to have a situation where you got to get the people. But they’re going to start moving. And I’m going to start explaining to people when you have an area that just isn’t working – like upper New York state, where people are getting very badly hurt – and then you’ll have another area 500 miles away where you can’t – you can’t get people, I’m going to explain you can leave, it’s OK, don’t worry about your house.” Source, “Full transcript: Trump’s Wall Street Journal interview” Politico, August 1, 2017.

It is true that upstate employment performance has been weak, with most upstate metropolitan areas seeing decreases, while a few, like Buffalo, Glens Falls and Albany-Schenectady-Troy had small increases (Source – Bureau of Labor Statistics – Local Area Statistics). Many of the region’s smaller metropolitan areas had relatively large losses:  Binghamton, Elmira and Utica-Rome each lost more than 10% of its population.

On the other hand,   Median household incomes upstate were near the average for rust belt states, and the unemployment rate for upstate counties was the same as the national average in 2016: 4.9% in 2016 (Source: U. S. Department of Labor, Bureau of Labor Statistics, Local Area Unemployment Statistics).

The fact that the average unemployment rate in upstate counties is near the national average shows that the President’s statement, “You know where we have the people? In New York state that can’t get jobs…when you have an area that just isn’t working – like upper New York state, where people are getting very badly hurt,” is unfounded, given that unemployment upstate is no higher than the national average and that median household incomes are near it.  The labor force in upstate New York is stagnant or shrinking in most cases, but few labor force members are unemployed.  Upstate’s problem is not that its residents cannot find jobs, it is that the region’s population and workforce are stagnant or shrinking.

E. J. McMahon, in a recent New York Post op. ed., “Trump’s right, Cuomo wrong about the woes of Upstate” pointed out that many upstate New York counties are losing population.  McMahon argues, “From mid-2010 to mid-2016, nearly 194,000 people moved out of the 50 counties north of the New York City metro region — a net out-migration rate exceeded only by four states. Births and foreign immigrants made up some of the difference, but the total upstate population still dropped by nearly 60,000 people.”  McMahon’s statement is correct – many areas upstate have lost population since 2010 – in fact, 40 of 62 counties in New York State lost population between 2010 and 2016.

New York State is not unique in seeing population declines in some areas.  In Wisconsin, one of the places that the President said “they’re going to move to,” 36 of 70 counties saw population declines between 2010 and 2015.  In Ohio, included for comparison as another rust belt state which claims to have more business friendly policies than New York State, county populations decreased in 62 of 90 counties.

Since counties differ substantially in size within states, a better measure of the economic weakness of an area is the percentage of residents living in counties that are losing population.   In that respect, New York and Wisconsin performed similarly – in 2016, 13.2% of New Yorkers lived in areas with declining populations, while 9.2% of Wisconsin residents lived in declining areas.  In Ohio, 55.5% lived in declining population areas. Reflecting New  York’s regional divide, 61.3% of upstate residents lived in counties with declining populations, while none of the counties in the New York City Metropolitan area had declines.

(Table with full listing of counties is here:)

 

 

 

The data shows that population changes between 2000 and 2015 at the county level within New York, Wisconsin and Ohio varied significantly.  Like New York, Wisconsin and Ohio had counties that had significant population increases, and others that had large losses. Saratoga, Orange and Rockland Counties all had population increases between 2000 and 2016 that were greater than 10%.  New York’s least populous county, Hamilton, lost 15% of its population – a decrease of 834 residents. Wisconsin and Ohio saw similar variations. One county in Wisconsin had a 38% increase, while another lost 16% of its population.  In Ohio,  One county gained 75%, while another lost 10.5%.

“Business Friendly” Policies and Job Growth

E. J. McMahon argues in his New York Post piece that, “Trump, in effect, was simply prodding upstaters to act in their own best economic interests. …So, taxes aside, what advantages does Wisconsin offer over New York?….While Wisconsin Gov. Scott Walker has been an aggressive deregulator, New York’s regulatory climate in general is notoriously hostile to businesses. The 1970s-era State Environmental Quality Review Act, which has no equivalent in most states, hands a potent weapon to anti-development activists.”

Looking at New York, Wisconsin and Ohio from 2000 to 2015,  there is no evidence of consistent differences in performance that would reflect the effect of “business friendly” policies on job growth.  Instead, it shows that population and job growth vary substantially from local labor market to local labor market within New York State, and in Wisconsin and Ohio.  In each state, some areas are suffering, while others are doing relatively well.  New York had by far the strongest job growth overall between 2000 and 2015, but employment growth in New  York’s rural areas was the weakest of the three states.  Wisconsin’s performance was in the middle in both metropolitan areas and non-metropolitan areas, and Ohio’s was weakest in metropolitan areas, but stronger than New York’s in rural areas.

In a recent post, “Government Policies and Job Growth in the Rust Belt,” I showed that the relative performance of metropolitan areas over the rust belt differed substantially across time periods between 1990 and 2015.  If government policies, like “business friendliness” determined the economic performance of regions we would expect to see consistent advantages for states with states with business friendly attributes like low taxes or lax environmental regulation.  But, we do not.

Upstate’s relatively weak economic performance may be attributed to several factors  – most importantly, its past reliance on manufacturing employment.  In 1970, manufacturing employment was more than 40% of the private sector total in the Rochester and Binghamton metropolitan areas, and more than 35% of the total in Buffalo-Niagara Falls.  Today, in these areas, manufacturing employment is about 10% or less of the total.  In contrast, metropolitan areas that have had stronger growth recently, like New York City and the Albany-Schenectady-Troy metropolitan area, were less dependent on manufacturing.

Manufacturing Mega-Projects and Job Creation

Large manufacturing attraction projects, like the Foxconn plant in Wisconsin, the Solar City project in Buffalo,  and Global Foundries near Saratoga Springs cannot, in themselves be successful approaches to significantly improving the employment rate at the state level.

To encourage Foxconn to locate its facility in Wisconsin with a promise to create 3,000 jobs, the state agreed to provide three billion dollars in tax incentives and to waive environmental regulations  to allow Foxconn, without permits, to discharge dredged materials, fill wetlands, change the course of streams, build artificial bodies of water that connect with natural waterways and build on a riverbed or lakebed.Foxconn would also be exempt from having to create a state environmental impact statement, something required for much smaller projects.” Source: The Washington Post, “The Latest: Wisconsin Foxconn deal waives regulations,” July 28, 2017.

Projects that involve expenditures of as much as one million dollars per job are simply too expensive to replicate on a scale that would be large enough to meaningfully change  a regional economy.  New York’s employment was about 9,100,000 in 2016.  Increasing the state’s employment by even one percent – 91,000 – would cost ninety-one billion dollars at the cost of one million dollars per job for recent projects, assuming that enough large new job attractions were possible to enable that large an employment increase.  In fact, most job creation occurs at existing businesses, not at new facilities attracted because of government subsidies, while very few large manufacturing investments take place in a given year.

At the same time, the focus on attracting manufacturing is largely misguided.  Although manufacturing jobs are important, because they have higher average wages than jobs available to people without college educations in other sectors, manufacturing has been hemorrhaging jobs for forty years.  Mostly because of automation and productivity improvements, and less so because of import competition, manufacturing employment has sharply declined in the United States – from 20,000,000 in 1980 to 13,000,000 in 2016.   Between 2000 and 2015, New York lost 239,000 manufacturing jobs, while gaining 1,878,000 service sector jobs.  Ohio and Wisconsin also lost manufacturing employment, while gaining service sector employment. Because the growth of New York’s already strong service sector was particularly large – 25%, the state’s percentage job growth was much larger than the other states.

Because potential job growth continues to be likely to occur almost entirely in the service sector, focusing state resources on attracting manufacturing employment has a high opportunity cost.  Instead, policies and programs to support existing manufacturers in a region can be useful.

Upstate’s relative economic weakness is partly explained by the changing factors that drive location decisions in manufacturing and service industries. For manufacturers, upstate New York is a less attractive location than it once was because of factors including its location relatively far from the country’s population center, relatively high labor costs, difficult environmental permitting processes and relatively small and tight labor markets.  But, because manufacturing provides only about 10% of jobs upstate and nationally, manufacturing employment is a less significant economic driver than employment in other sectors is.

For high value added service industries, upstate New York suffers from relatively shallow labor markets, its relatively low percentages of college graduates compared to places like New York City and Boston, and the increasing concentration of industries in a few large companies headquartered in major cities.  Although the region has some significant strengths in higher education and health care, it has lost a number of corporate headquarters in financial services, because of the increasing concentration of the industry.

None of the problems faced by upstate New York, or for that matter, those parts of Ohio and Wisconsin that have stagnant economies, are easily resolvable.  But, leaders should recognize that the resurgence of these areas will not result from a policy of attracting manufacturing jobs to them – there are just too few opportunities to attract companies like Solar City, Foxconn or Global Foundries, and the cost is exorbitant.  Instead, leaders need to do what they can to anchor the companies in their area that have the potential to grow.  In most cases, those are service industries.  For these businesses, robust labor pools with appropriate skill sets are far more critical than the financial incentives or permitting issues that were critical to attracting large manufacturing facilities.




Lost Manufacturing Jobs – The Effects of Imports and Increased Productivity

The decline in manufacturing employment in the United States has caused a wrenching economic adjustment, as one path to relatively well paying jobs has narrowed, particularly for workers without college educations.  As the percentage of workers in our society who work in manufacturing industries decreases, and lower paying service employment has increased, wages have stagnated.

The causes of the decline in manufacturing employment have been hotly debated. President Trump promoted the idea that product imports are a major cause of the shift away from manufacturing employment.  There is certainly common-sense evidence to support this position.  Clothing that was sold in the 1960’s with labels like Levi’s and L. L. Bean were largely made in America.  Major television manufacturers, like RCA and Zenith also produced most of their products in this country.  And, most people drove Chevrolets, Fords, and Plymouths that were made in America.

But, there is a significant counter-argument.  Several studies have shown that increases in worker productivity from automated production processes have significantly reduced the number of employees required to produce manufactured products.  One recent New York Times headline proclaimed, “The Long-Term Jobs Killer is Not China.  It’s Automation.”[1]  The article goes on to argue, “Donald J. Trump told workers…that he would bring back their jobs by clamping down on trade, offshoring and immigration.  But economists say the bigger threat to their jobs has been something else:  automation.”

This post examines industry based employment and shipment data along with trade data to evaluate the import and automation arguments.

The Impact of Imports on Manufacturing Employment

 To understand the impact of imports on manufacturing employment, it is first necessary to know the value of goods shipped by manufacturers located in the united states, and the value of manufactured goods imported during the period examined.   In this post, I examine data from 1963 to 2015.

Manufactured Imports

 The data shows that manufacturing imports have significantly increased since 1963 to 2015, from 2.6% of the total of domestic plus imported manufacturing goods to 25.3%.  But the extent of import penetration varies significantly among manufacturing industries – from a low of 6.9% of food products, to 63.9% of textiles and apparel.  For apparel alone, 86.3% of goods shipped or imported were imported in 2015.[2]

 Manufacturing Employment

In 1963, manufacturing employment was 17,035,000.  By 1987, the number had increased to 20,935,000.   But since then, manufacturing jobs have consistently declined, reaching 12,320,000 in 2015.  Total displacement of domestic manufacturing employment associated with import penetration grew gradually over the 50+ year period, reaching 4,179,000 by 2015 – one third of current manufacturing employment in the United States.

The impact of import penetration varied significantly by industry.  Materials related industries, like wood products, foods, chemicals and petroleum were relatively unaffected by import penetration, while durable product industries, like machinery, transportation equipment and electronics saw high employment impacts.  Of the sectors examined, clothing and apparel lost the most domestic employment – nearly 1.8 million jobs.  Electrical and electronic products,  including computers and other high technology devices, had the greatest increase in foreign jobs for import production – almost one million jobs between 1963 and 2015.

The Impact of Productivity on Manufacturing Employment

Several studies have shown that automation and process improvements have made manufacturing significantly more efficient than in the past.  Thus, many manufactured products are significantly less expensive today than in the past, in real terms.  How large an impact has the substitution of imported manufactured goods had on manufacturing employment in the United States?

The data shows that productivity increases have had a very large impact on manufacturing jobs.  The value of domestically produced manufacturing shipments more than doubled between 1963 and 2015, in real dollars.  Thus, without productivity gains we would expect employment to substantially increase.  But, it hasn’t – in fact manufacturing employment is only 58% of what it was in the peak year – 1987.  About 4,000,000 of the lost jobs can be accounted for by import substitution, but many more (28,000,000) were estimated to be lost as the result of increased productivity.[3] Thus, imports have caused the loss of only 13% of total manufacturing employment losses, compared with 87% for productivity growth.

Full size table:  Click here:

Implications

The data shows that both import substitution and productivity gains have cost manufacturing jobs, but that increased productivity has been a far more significant cause of the decline in manufacturing employment.  Without the effects of import substitution and productivity gains, an estimated 44,000,000 domestic employees would be required to produce the goods made and imported to the United States in 2015.[4]  Productivity gains are estimated to have led to the loss of 28,500,000 jobs based on productivity at 1963 levels, and import substitution is estimated to have cost 4,179,000 jobs.

It is important to note that imports and productivity increases have substantially benefitted most U. S. residents, because they have resulted in significantly lower prices than would have been the case without the substitution of automation and more efficient processes for labor, and of lower cost foreign workers for better compensated American workers.  Since 152,000,000 people are employed full and part-time in the United States, and only 12,000,000 are employed by manufacturers, most people are better off than they would have been without productivity gains and import penetration.

There is no overall benefit, or practical method, to reverse the job losses that have occurred because of manufacturing automation and process improvements.  But, there is some potential benefit to addressing trade imbalances, though the benefits would be quite small in the scheme of things – an increase in the share of the workforce employed in manufacturing industries of a few percent, at most. A recent McKinsey Report, Manufacturing the Future:  The Next Era of Global Growth and Innovation,[6] points out that

“Policy makers must also be realistic about what they can achieve with manufacturing industry strategy…. Manufacturing has changed in ways that make approaches that are aimed primarily at large scale job creation in advanced economies increasingly ineffective and costly at a time of tight government budgets…. Manufacturing can continue to grow and contribute to value added and export growth…[and] create new jobs – but not in the volumes or at the same skill levels as seen in previous decades.”

Some approaches, such as the imposition of tariffs carry trade-offs that most likely exceed their potential benefits, both because they increase the prices of imported goods, and because they invite retaliation.  Others, like the proposed Border Adjustable Tax on businesses bear closer examination, since they would have the effect of shifting the net burden of taxes from exporters to importers.[5]  Also worth considering are questions of currency manipulation, and whether American producers have fair access to markets in nations that export to the United States.

Government policies to promote manufacturing should look beyond trade balances if they are to have significant impacts. Government has several tools available to encourage manufacturing, ranging from setting the regulatory environment, including labor, capital market and general business regulations, to enabling growth ‘with hard and soft infrastructure investments, educating and training a skilled workforce, supporting R&D and basic research and upgrading highways and ports.”[7] It can also provide investment support and shape demand through public purchasing and regulation.

Finally, given the reality that manufacturing employment is likely to continue to stagnate, most future employment growth will be in the service sector.  For that reason, emphasis should be on mechanisms to improve incomes in low paid service sector jobs. Here, government can use its regulatory powers to provide low skilled workers who lack power in the job market with tools like minimum wage policy and rules that promote collective bargaining rights.[8]  It can also provide better access to relevant post-secondary education for young people, and for workers needing retraining, and by providing direct aid to displaced manufacturing workers.

[1] https://www.nytimes.com/2016/12/21/upshot/the-long-term-jobs-killer-is-not-china-its-automation.html

[2] Data Sources:  Import Data – Statistical Abstract of the United States, various years: http://www.census.gov/library/publications/time-series/statistical_abstracts.html

Exports & Imports by NAICS Commodities:  https://usatrade.census.gov/data/Perspective60/Dim/dimension.aspx?ReportId=7028

Manufacturing Shipments:  Statistical Abstract of the United States- Various years:  http://www.census.gov/library/publications/time-series/statistical_abstracts.html,  U.S. Census Bureau – “Value of Manufacturers Shipments for Industry Groups,” various dates: https://www.census.gov/manufacturing/m3/index.html

[3] Producer Price Index data is from the Federal Reserve Bank of St. Louis:  https://fred.stlouisfed.org/series/PIEAMP01USA661N

Employment data is from the Statistical Abstract of the United States, various years, and from the U. S. Department of Labor, Bureau of Labor Statistics – Current Employment Series –  Table B-1a. Employees on nonfarm payrolls by industry sector and selected industry detail, seasonally adjusted – https://www.bls.gov/web/empsit/ceseeb1a.htm, various years.

[4] Note that without the lower prices that result from import substitution and productivity increases, prices would be significantly higher, and actual product demand significantly lower than estimated.

[5]For discussions see:  https://taxfoundation.org/house-gop-s-destination-based-cash-flow-tax-explained/

and pp. 10-11 of:  https://www.americanprogress.org/wp-content/uploads/issues/2010/12/pdf/auerbachpaper.pdf

and,https://www.washingtonpost.com/posteverything/wp/2016/12/30/my-take-on-the-republicans-new-interesting-corporate-tax-plan/?utm_term=.570520155032

[6] For a comprehensive review of manufacturing policy issues, see “Manufacturing the Future:  The Next Era of Global Growth and Innovation,” McKinsey Global Institute – McKinsey Operations Practice:  http://www.mckinsey.com/business-functions/operations/our-insights/the-future-of-manufacturing

[7] McKinsey, Ibid.

[8] Like other approaches, these policies carry trade-offs, since they can encourage employers to substitute automation for human labor.




The Decline of Manufacturing in New York and the Rust Belt

In a recent post I looked at employment changes in New York’s metropolitan areas and compared their performance with other metropolitan areas in the rust belt.  I found that change was inconsistent between cities in each state, and over different time periods.  I argued that industry mix probably was the primary cause of the differing results.

Here, I look at the decline of the manufacturing sector and its impact on employment change in New York State metropolitan areas.  Overall, rust belt metropolitan areas in this study have 4,500,000 less manufacturing jobs today than they did in 1970, compared with 28.4 million private sector workers in that year.  Overall, 1.2 million fewer people were employed in manufacturing in New York State in 2014 than in 1970, equal to 12.8% of the private sector employment total in 1970.  In two metropolitan areas (Binghamton and Utica-Rome), manufacturing job losses were about one-quarter of private sector employment in 1970, while in Buffalo and Rochester the manufacturing losses were about 20% of the total.

The loss of manufacturing jobs created a significant drag on job growth in the rust belt, and explains much of the growth of income inequality in the United States since the middle part of the last century.  Manufacturing jobs provided working class people with relatively high incomes.  Today, the opportunities that manufacturing provided to people with high school educations have sharply declined.

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Rochester provides a good example of the impact of the decline in manufacturing.  The chart above shows that in 1970, 152,000 people in the Rochester worked in industries in the manufacturing sector, with average earnings of $68,000 (in today’s dollars), compared with the regional average private sector earnings of $53,200.  In 2014, 61,800 people worked in manufacturing industries in the area, with average earnings of $74,500, compared with regional average private sector earnings of $51,400.  The loss of nearly 100,000 jobs paying significantly more than the regional average has large impact on Rochester and other rust belt metropolitan areas.

State Level Changes

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In this section, aggregate data for all metropolitan areas each rust belt state is examined.[1]  The data shows that while overall employment change in metropolitan areas was inconsistent over time, that between 1970 and 2014, manufacturing showed a larger decline in New York State than in metropolitan areas in other rust belt states.  New York metropolitan areas have lost 75% of the manufacturing jobs that existed in 1970.  Other rust belt states lost between 35% and 63%.  (Note that in the data, there is a discontinuity between the years 2000 and 2001, reflecting the change from the Standard Industrial Code Classification System and the North American Industry Classification System, which removed some industries from the manufacturing sector. As a result, the long-term data charts and tables exaggerate the change that took place between 2000 and 2001.  For that reason, shorter term charts and tables exclude the 2000-2001 data).

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(In the chart above, blue shaded cells performed better than the median for metropolitan areas)

Dividing that data into periods reflecting economic boom-bust cycles, there were significant differences in the relative performance of manufacturing in state metropolitan areas across economic cycles.  However, manufacturing employment in New York metropolitan areas decreased more than most metropolitan areas in other rust belt states in most periods. Only in the 2007-2009 recession did it outperform the rust belt median.[2]  Between 1970 and 1976, between 1992 and 2000, and between 2001 and 2007 manufacturing employment performance in New York metropolitan areas was the worst of the seven rust belt states.

Because more than two-thirds of New York residents live in the New York City Metropolitan area, the very large decrease in manufacturing employment in that area has had a disproportionate impact on the decline of manufacturing in the state.  But, while upstate metropolitan areas had smaller percentage decreases in manufacturing employment that the New York Metropolitan area, they were more dependent on manufacturing.  As a result, the loss of manufacturing jobs in those areas did more economic harm to them than the losses in the New York City area.

Despite the large losses in manufacturing employment, each metropolitan area in New York State has shown some private sector employment growth since 1970, but the growth has been uneven.  This data also makes clear that changes in manufacturing jobs are not the only factor driving employment change in metropolitan areas.   Because so much employment is now in service sector industries, the performance of industries within the service sector has had substantial effects on the relative ability of metropolitan area employment to withstand the declines in manufacturing employment.

Manufacturing Employment in New York’s Metropolitan Areaspicturea

As in other rust belt metropolitan areas, manufacturing employment in New York State metropolitan areas decreased during most periods.  The patterns of the declines varied, with some metropolitan areas, like Rochester and Binghamton, doing quite well in the 1970’s and 1980’s but going into steep declines in the late 1980’s and 1990’s.  Others, like Utica-Rome performed quite poorly in the 1970’s and 1980’s but performed better than other New York MSA’s in more recent periods.  New York City’s manufacturing employment losses were consistently larger in percentage terms than average.  In all the periods, every metropolitan area in New York State lost manufacturing employment, with the exception of the 2009-2015 period, where Albany-Schenecady-Troy gained 16%, and Buffalo-Niagara Falls gained 3.1%.pictureb1

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While there were losses in manufacturing employment in each metropolitan area in each decade except the present one, the patterns of losses varied.  New York City, Utica-Rome  and Buffalo-Niagara Fall had losses that were greatest between 1970 and 1990.  Binghamton and Rochester saw the largest losses between 1990 and 2010.  Syracuse’s losses were largest between 2000 and 2010.  Employment changes in non-manufacturing sectors in different decades led to sharply varying results.  For example, despite losing 36,600 manufacturing jobs between 1980 and 1990, Buffalo-Niagara Falls had a net gain of 48,400 jobs during the period, because non-manufacturing employment increased by 85,000.  From 2001 to 2010, Buffalo-Niagara Falls lost 30,600 manufacturing jobs, but gained only 24,600 non-manufacturing jobs.  As a result, the area lost private sector employment in that decade.  Rochester and Syracuse also performed well during the 1970 to 1990 period but did poorly during the first decade of this century.  In contrast, The New York City metropolitan area lost employment during the 1970’s, but has steadily gained strength since then.

Since 2001, two New York metropolitan areas have shown significant private sector employment growth – New York City and Albany-Schenectady-Troy.  Buffalo, Rochester and Syracuse did not do well between 2001 and 2010, but showed significant recoveries from 2010 to 2014.  Binghamton and Utica-Rome had employment losses in the 2001 to 2014 period.

Percentage of Private Sector Employment in Manufacturing

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Overall, 1.2 million fewer people were employed in manufacturing in New York State in 2014 than in 1970, equal to 12.8% of the private sector employment total in 1970. New York’s metropolitan areas each had substantial declines in manufacturing employment between 1970 and 2014.  Binghamton lost the highest percentage (26.66%) of manufacturing jobs compared with its private sector employment in 1970.  Albany-Schenectady-Troy, which lost 8.1%, was the least affected.

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Over the 44-year period between 1970 and 2014, manufacturing employment in New York State metropolitan areas both declined and converged.  Four metropolitan areas had significantly higher percentages of manufacturing employees compared to private sector employment in 1970 than the rust belt average:  Binghamton, Buffalo-Niagara Falls, Rochester, and Utica-Rome.  In 1970, more than four of ten private sector employees in the Rochester and Binghamton metropolitan areas were in manufacturing.  More than 35% worked for manufacturers in Buffalo-Niagara Falls and Utica-Rome.  Each of these metropolitan areas had larger decreases in the percentage of manufacturing employment than the average.  New York, and Albany-Schenectady-Troy had the lowest percentages of manufacturing employment in 1970 – 21.5% and 24.7% respectively, and had the smallest long-term declines – 18.7% and 19%. Note, however, that when metropolitan areas with similar concentrations of manufacturing employment are compared (see below), much of the difference in performance between New York metropolitan areas and other rust belt locations disappears.

In 2014, the areas with the highest percentages of manufacturing employment – Binghamton and Rochester – had only 11.4% and 10.9%. Only 2.9% of private sector employees in the New York metropolitan area and 5.8% of those in the Albany-Schenectady-Troy metropolitan area were employed in Manufacturing.  By 2014, only Binghamton, Rochester and Buffalo-Niagara Falls had higher percentages of manufacturing employment than the rust belt average.  The percentage of manufacturing employment in these two metropolitan areas exceeded the rust belt average by less than 2%, compared with 7% to 9% in 1970.

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Manufacturing and private sector employment change each varied substantially from decade to decade, but the relationship between the two was not constant.  Clearly, the decade from 2001 to 2010 was the worst decade for employment change in upstate New York, both for the private sector and for manufacturing.  On the average, more nearly one-third of manufacturing employees were lost during that decade, while overall, private sector employment declined by 1.7% on average.  From the perspective of manufacturing employment, 1980 to 1990 was the second worst decade in the period, but private sector employment had the second highest growth of the five time periods.  Rochester and Syracuse had the strongest private sector growth between 1970 and 1990, but showed little growth after 2000. New York City’s employment growth was the weakest in the state between 1970 and 1990 but among the strongest since 2001. 

Decreases in Concentration of Employment in Manufacturing Industries  

picturerrOverall, metropolitan areas[3] in the rust belt that had relatively greater percentages of private sector employment in manufacturing in 1970 lost a greater share of manufacturing employment than other areas with lower initial manufacturing employment concentrations. The data shows that metropolitan areas in New York State performed similarly to others with similar concentrations of employment in manufacturing industries. Buffalo, Rochester, Binghamton and Utica-Rome had both the highest concentrations of manufacturing employment and the greatest declines in the share of private sector employment in manufacturing.

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Between 2001 and 2014, the relationship between manufacturing’s share of private sector employment and the decline in the manufacturing share of employment was weaker, but still present.  In general, areas that had higher concentrations of manufacturing employment in 2001 had greater decreases in the concentration of manufacturing employment than those with lower concentrations.  Once again, metropolitan areas in New York State generally performed in a similar manner to those in the rust belt outside New York having similar concentrations of manufacturing employment.

The data in both periods points to the steep decline in manufacturing employment from an average of more than three in ten private sector jobs to an average of one in seven.  With the decline came a convergence of manufacturing employment in metropolitan areas, with the range in the percentage of private sector employment in manufacturing ranging from about 20% to 40% in 1970, compared with 5% to 20% in 2014. 

Decreases in Manufacturing Employment and Concentration of Employment in Manufacturing Industries

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Here, the percentage decrease in manufacturing employment is compared with the initial share of private sector employment in manufacturing industries.  The data shows little relationship between these two factors.  Over the 1970-2014, and in the 2001 to 2014 period, metropolitan areas in New York State performed relatively poorly compared to others in the rust belt.  However, over the more recent period from 2001 to 2014, New York metropolitan areas, other than New York City saw percentage decreases in manufacturing employment that were closer to other rust belt cities with similar concentrations of employment in manufacturing.

picture1zzManufacturing Employment Concentration vs. Private Sector Employment Change 

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In this section, the percentage of total private sector employment in manufacturing industries is compared with private sector employment change.  Between 1970 and 2014 overall, Albany-Schenectady-Troy had better performance than metropolitan areas with similar concentrations of manufacturing employment in 1970.  Syracuse and Rochesster were near the average.

picturedildo

Most metropolitan areas in New York State performed better in the 2001 -2014 period relative to other rust belt metros than they did in the longer term period, Binghamton being a notable exception.  The New York City metropolitan area had the best job creation performance of the rust belt metropolitan areas studied. Note also that the charts above show that when New York’s metropolitan areas are compared with other rust belt areas with similar concentrations of manufacturing employment, much of the apparent worse employment performance of New York metropolitan areas described in an earlier section disappears.

Over the 1970 to 2014 period, percentage decreases in manufacturing employment did not show an association with private sector employment change for the rust belt . However, metropolitan areas in New York State performed somewhat differently:  Areas with higher concentrations of manufacturing employment in 1970 showed less private sector employment growth than those with lower concentrations.  Similarly, in 2014, for the rust belt overall, there was not a significant relationship between the concentration of employment in manufacturing industries and private sector growth.  In that period, in New York State, areas with lower concentrations of manufacturing had greater private sector growth.   New York City had the greatest percentage growth in private sector employment during the period along with a low percentage of manufacturing employment.  Albany-Schenectady-Troy was another metropolitan area with relatively little manufacturing employment in 2001 and relatively high private sector employment growth.
  

Implications 

Since 1970, New York and the rust belt region have seen a substantial transition from high concentrations of manufacturing employment to lower ones.  In 1970, one third of all private sector jobs in the rust belt outside New York State, and more than 40% of private sector jobs in Rochester and Binghamton were in manufacturing.  In 2014, manufacturing employment in New York State metropolitan areas ranged from 2.8 to 11.4% of private sector jobs.  Since 2010, manufacturing employment has levelled off.  Whether this is a lasting change or a temporary stabilization after the very large manufacturing employment losses between 2000 and 2010 is not known.

This data shows that much of New York’s relatively large manufacturing employment loss resulted from the fact that a number of upstate cities had higher concentrations of manufacturing than average for the rust belt.  In New York, unlike metropolitan areas elsewhere in the rust belt, private sector employment growth appeared to be negatively related to the level of employment in the manufacturing sector.

All of the metropolitan areas in the rust belt were hurt by technological change, factory automation and the movement of manufacturing off-shore.  These trends reflect the continuing attempt of manufacturers to cut costs to be competitive.  In addition, the New York and the rust belt are no longer as good location to serve markets as they were when manufacturers in the United States primarily served domestic markets.  For those manufacturers that find it advantageous to serve domestic markets from the United States, the center of population has continued to move South and West.

Manufacturing employment losses in New York State had differing causes.  In Rochester, Kodak was initially threatened from foreign competition by Fuji, then saw its cash cow (film production) killed by the introduction of digital cameras.  In Syracuse, New Process Gear was closed by Fiat/Chrysler because of high labor costs.  Production continued at factories in Indiana and Tennessee, locations with lower labor costs and better geographic locations.  Carrier moved production of air conditioners from Syracuse to Tennessee, Texas, and Indiana (now being transferred to Mexico) for the same reasons.

Given transportation costs, the need for quick delivery of some products, and in a few cases technological leadership, some manufacturing continues in the United States.  In the competition to retain manufacturing, New York may continue to be handicapped by its location in the Northeast, its relatively high labor costs, and congestion in the New York metropolitan areas.

Future losses of manufacturing jobs have a smaller potential to harm regional economies because manufacturing employment is now only a small portion of private sector employment in the rust belt and New York State.  But, the loss of millions of relatively high paying jobs in manufacturing industries has had significant negative consequences for New York and rust belt metropolitan areas.

In New York, the decline of manufacturing has been a cause of private sector employment declines in places like Binghamton and Utica-Rome, and slow growth in Rochester, Syracuse and Buffalo-Niagara Falls.  And, though employee earnings are not the primary subject of this post, data from Rochester showed that the loss of 93,000 manufacturing jobs contributed to the stagnation in average private sector earnings in that metropolitan area, as well as greater earnings inequality.

In future posts I will examine employment change in service industries, and implications for metropolitan area wages.

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[1] The data for this post is from the Economic Profile System at www.headwaterseconomics.org  and the U. S. Department of Commerce, Bureau of Economic Accounts, Regional Economic Accounts.

[2] Periods were broken between 2000 and 2001 because of the change from the SIC to NAICS classification system, which creates a discontinuity because of changes in firms classified as manufacturers.

[3] Metropolitan areas included in rust belt comparison:  Illinois:  Champaign-Urbana, Chicago, Peoria, Rockford, Springfield; Indiana:  Elkhart, Evansville, Fort Wayne, Gary, Indianapolis; Massachusetts:  Boston, Springfield, Worcester; Michigan:  Ann Arbor, Detroit, Flint, Grand Rapids, Kalamazoo, Lansing; New York:  Albany-Schenectady-Troy, Binghamton, Buffalo-Niagara Falls, New York City, Rochester, Syracuse, Utica; Ohio:  Akron, Canton, Cincinnati, Cleveland, Columbus, Dayton, Toledo, Youngstown; Pennsylvania:  Allentown-Bethlehem-Easton, Erie, Harrisburg, Lancaster, Philadelphia, Pittsburgh, Reading, Scranton-Wilkes-Barre, York.




Government Policies and Job Growth in New York State and the Rust Belt

A recent Washington Post article, “As senator, Clinton promised 200,000 jobs in Upstate New York. Her efforts fell flat.”[1] points out that during Senator Clinton’s tenure between 2001 and 2009, Upstate New York saw job growth of only 0.2%, far from what Clinton claimed could be achieved.  While the article neglects to point out that the nation as a whole actually lost jobs during the period, since Clinton’s term ended near the low point of the recession of 2008-2009, it is clear that her claim was unfounded.

But, Senator Clinton’s emphasis on economic development and job creation is not unique.  Politicians in New York state and elsewhere regularly claim that their policies lead to job creation, often using statistics to tout their arguments.  In 1994, a significant element of Governor George Pataki’s first campaign for Governor focused on his claim that the state’s loss of jobs in the period immediately prior to the campaign was a result of Governor Mario Cuomo’s tax and regulatory policies.  Governor Pataki was fortunate, initially, because following the recession that took place in the early 1990’s, the national economy, and New York’s, improved.  Each month for the first five years of Pataki’s terms of office, his Administration pointed to the creation of thousands of jobs in New York State.

Then, in 2000, the nation again entered recession, which was exacerbated by the 9/11 attack on the World Trade Center. Not surprisingly, New York stopped seeing job growth, and the frequent press releases ceased.

More recently we have seen Governor Andrew Cuomo point to continued job growth during his administration.  In his 2016 State of the State speech, the Governor said, “We limited the state’s new spending to less than 2% a year. We passed a 2% property tax cap that has brought welcome relief to the citizens of our state and we have cut income, corporate and estate taxes. In total, we have reduced the tax burden on New Yorkers by $114 billion dollars. Why is that important? Because reducing taxes is part of our strategy to create jobs.”

During Governor Cuomo’s administration, like the first years of Governor Pataki’s administration, New York State has seen significant job growth.  But can governors or senators rightfully take credit for employment growth during their administrations?  Is New York’s relative job creation performance primarily the result of State and local tax and spending policy?  This post will examine patterns of job growth in New York, and will attempt to provide some answers.

Employment Change in New York State and the Nation

Many analyses of employment change focus on comparisons between New York State and the national average.  Between 1990 and 2015, private sector employment grew by 18.7 percent, compared with 33.5% for the nation (note, data in this report, unless otherwise noted, is from the U. S. Department of Labor, Bureau of Labor Statistics, Current Employment Statistics).  When New York is broken into regions – the New York City metropolitan region, and the rest of the state (Upstate) – there is a considerable difference in performance.  New York metropolitan employment grew by 24.5%, while Upstate employment grew by 6.1%.

NYS V US

 

But, a closer examination of the state’s performance shows significant variations in performance across different economic cycles.  Since 1990, the nation has experienced three significant growth periods, broken by recessions in 1990-1992, 2000-2002, and 2007-2009.  In the first growth period, 1992-2000, New York’s performance lagged the nation’s – private sector employment in the state as a whole grew by 15.2%, compared with 23.5% for the nation.  The difference in performance between upstate New York and the New York metropolitan area was substantial – downstate employment grew by 18.2%, while upstate job growth was 8.2%.

Percent Employment Change  – 1990-2015
    United States New York NYC Metro Upstate
 Recession   1990-1992  -0.08% -5.24% -6.84% -1.83%
 Growth   1992-2000  23.52% 15.18% 18.70% 8.06%
 Recession   2000-2002  -2.55% -4.38% -4.56% -3.97%
 Growth   2002-2007 6.39% 5.10% 6.43% 2.14%
 Recession   2007-2009  -7.54% -3.97% -4.04% -3.81%
 Growth   2009-2015 12.88% 12.65% 15.54% 6.00%

During the second growth period – from 2002-2007, New York’s performance again lagged the nation’s, but by significantly less than in the 1990’s.  Nationally, private sector employment grew by 6.4% compared with 5.1% for New York State.  Employment in the New York portion of the New York metropolitan area grew by 6.4%, which was greater than the national growth, while upstate employment grew by only 2.1%.

During the third growth period, from 2009-2015, private sector job growth in New York State about equaled the growth in the nation – 12.7% in New York vs 12.9% in the nation.  Growth in the New York portion of the New York Metropolitan area exceeded the nation’s – 15.54%, while that in upstate New York was again sub-par, at 6%.

New York Compared to Rust Belt States

Population growth in the United States has continued to shift south and west.  That factor alone contributes to regional variations in employment change.  Additionally, regions vary in “industry mix,” the relative proportions of their populations employed in different industries.  Given the historic importance of manufacturing in the rust belt, states in the Northeast and Midwest have suffered more than the rest of the nation.  For thirty years, manufacturing employment was stayed constant, at 18 million jobs, as service employment grew.  But, the decade from 2000 to 2010 saw one in every three manufacturing jobs disappear in the United States – from 17.3 million to 11.5 million.[2]

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Not surprisingly, employment growth in rust belt states in the first decade of this century reflected the weak performance of the manufacturing sector.  Even before the great recession of 2007-2009 rust belt states saw little or no private sector job growth.  For the rust belt, both the decade between 1990 and 2000 and that between 2010 and today saw much better economic performance.

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Employment Change in Rust Belt States – 1990-2015

 

 

Illinois Indiana Massachusetts  Michigan New York Ohio Pennsylvania
1990-1992 -0.18% 2.45% -3.93% 0.81% -5.26% -0.34% -1.19%
1992-2000 15.78% 17.93% 21.10% 20.55% 14.56% 17.18% 13.50%
2000-2007 -1.62% -1.04% -2.91% -11.85% 0.52% -5.22% 1.46%
2007-2009 -9.09% -10.31% -5.11% -12.44% -4.48% -9.78% -5.55%
2009-2015 9.00% 13.41% 11.50% 14.45% 12.73% 10.91% 7.67%

State and Local Tax Policy and Job Creation

Does the data support the argument that state economic performance is related to tax policy?  We have often seen arguments that New York, as a relatively high taxed state, is at a disadvantage to regional competitors with lower tax burdens.  The data shows that some states with relatively high tax burdens – Massachusetts and New York – did better than states with significantly lower burdens – Michigan and Ohio, for example. (source -State & Local Government Finance Data Query System. http://slfdqs.taxpolicycenter.org/pages.cfm. The Urban Institute-Brookings Institution Tax Policy Center. Data from U.S. Census Bureau, Annual Survey of State and Local Government Finances, Government Finances, Volume 4, and Census of Governments (1977-2013)).  It also shows that the relative performance of states varied from period to period.  For example, Michigan was one of the strongest performers in the rust belt from 1992 to 2000, but was among the weakest in the recessions of 2000-2002 and 2007 to 2009.

State and Local Taxes Per Capita

Region and State 2013
United States ……………………………………………………………………… $4,599
Massachusetts……………………………………………………………………… $5,723
New York……………………………………………………………………… $8,047
Pennsylvania……………………………………………………………………… $4,627
Illinois……………………………………………………………………… $5,374
Indiana……………………………………………………………………… $3,793
Michigan……………………………………………………………………… $3,750
Ohio……………………………………………………………………… $4,275

The Upstate Downstate Divide

For the past half century, Upstate New York has consistently grown more slowly than downstate, largely because of its historical dependence on manufacturing.  Even so, the chart below shows that there have been significant differences in private sector employment growth between New York’s metropolitan areas.  The New York City metropolitan area had the greatest employment growth – more than 25% – among those studied in New York State between 1990-2015.  The Albany Schenectady Troy metropolitan area was second, with about 20% private sector job growth.

NY Metros Jobs2

 

But other metropolitan areas upstate had little private sector employment growth, or in some cases, losses.  Rochester’s employment grew by about 5%, and Buffalo’s by 3%. Binghamton’s employment declined by more than 15% during the period.

The job creation performance of New York metropolitan areas compared to other metropolitan areas in the rust belt varied substantially during different periods of growth and recession, even within relatively short time periods.  Relative to other rust belt metropolitan areas, New York metropolitan areas showed the weakest performance in the 1990-1992 recession, and the strongest in the 2007-2009 recession.  These kinds of shifts can reflect the effects of differing economic environments as they relate to metropolitan areas’ industrial bases.  For example, in 2007-2009,  metropolitan areas in Michigan, highly dependent on the auto industry, were particularly hard hit while New York’s metropolitan areas generally did relatively well.  Syracuse and Buffalo’s performance was weak between 1990 and 2000, but did relatively well between 2000 and 2009.

upstate employment change rank

Is the large variation in private sector employment change between metropolitan areas in New York State found in other states?  A look at employment change in other rust belt states shows that it is.

Ohio

Ohio Employment

Michigan

michigan

Pennsylvania

pennsylvania

The differences in employment change between cities within each state were substantially larger than those between states.  For example, Columbus, Ohio metropolitan area private sector employment grew more than 40% between 1990 and 2015, while Youngstown saw a decline of nearly 10%.  In Michigan, Grand Rapids private sector employment grew by more than 40%, while Flint’s dropped by nearly 20%.  The high level of dispersion between the economic performance of individual cities within states points to the fact that in these historically relatively undiversified metropolitan areas, the performance of a dominant industry or company can significantly affect metropolitan area private sector employment change.  Both Detroit and Flint suffered signficantly from the woes of the domestic auto industry, while the Rochester area saw Eastman Kodak employment decrease from nearly 50,000 in 1988 to a small fraction of that today.

Implications

There is clear evidence that federal policies, whether relating to labor and environmental regulations, taxes, trade, or the use of fiscal and monetary policy, can have a significant impact on corporate decision making and job growth.  But, former Senator Clinton’s claims about growing the upstate economy foundered on several realities.  First, the Senator failed to recognize that the region’s job creation would largely depend on national economic conditions.  When the national economy contracted from 2007 to 2009, any chance that 200,000 jobs would be created in upstate New York disappeared.  And, it must be recognized that  as a junior senator in a body of 100 members, Senator Clinton’s influence on federal economic policy was very limited.

Policy claims about employment change in New York often center around the notion that New York’s high taxes have retarded the state’s growth.  These claims are rooted in historical experience.  Beginning in the 1960’s New York State began to see its manufacturing base erode, as textile manufacturers, appliance makers and others sought locations with lower labor costs and taxes, and easier regulatory policies.

But it is important to remember that even then, other factors influenced location decisions.  While some people and businesses moved south and west for lower living costs, quality of life was a factor as well, probably a more important one than tax costs.  People chose to locate in the sunbelt to avoid cold winters and snow, and to access new opportunities found in these areas. As the nation’s population grew in the South and West, New York and other rust belt states were no longer as competitive as locations to serve national markets as they had been.  Metropolitan areas in the rust belt stagnated as areas in the South and West grew.  Areas that were heavily dependent on manufacturing saw  the greatest losses.

The data shows that New York’s employment change over the past 25 years has been similar to that in other rust belt states.  The relatively small differences in performance at the state level do not show an association with state and local tax levels.  There were  large differences in relative job creation performance between metropolitan areas within states overall, and significant variations in the relative performance of metropolitan areas over relatively short time periods.

Both of these findings are inconsistent with the argument that state and local tax differences are a primary explanation of state economic performance, since state and local tax burdens within states do not significantly differ, and New York’s state and local tax burden relative to other rust belt states has not shifted significantly over time.  If tax levels were a significant factor influencing job growth, we would expect to find more consistent patterns of performance within states  and across time periods, and differences in job growth between states that would be consistent with differing tax burdens.  Instead, the data points to the fact that job creation in metropolitan areas depends mostly on their industry mix – the performance of the companies within the industries that make up their economies.

These findings reflect the fact that today, state and local tax costs are a very small percentage of total firm operating costs, and that differences between states are even smaller.  In earlier research, based on data from the Tax Foundation,  I found that state and local taxes amounted to less than 4% of business operating costs (less than 2% for manufacturing businesses), on average, and that differences between New York  taxes and  taxes in other states were less than 2% of operating costs. These relatively small differences pale compared with the large differences in labor costs between locations in the United States and in low wage countries.

One study, by Professor Peter Navarro, estimated that differences in labor costs between the United States and China could amount to 17% of the cost of production – more than ten times the impact of state and local taxes on manufacturing operating costs.  For manufacturers, the large differences in labor costs and the growth of global markets have led to the movement of manufacturing operations to locations outside the United States.

While New Yorkers might legitimately question whether the services they receive are good enough to justify paying state and local taxes that are 80% higher than the average for the nation, and substantially above the average for the rust belt, the data does not support the notion that high taxes have hurt employment levels in New York State.

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Metropolitan areas included in rust belt comparison:  Illinois:  Champaign-Urbana, Chicago, Peoria, Rockford, Springfield; Indiana:  Elkhart, Evansville, Fort Wayne, Gary, Indianapolis; Massachusetts:  Boston, Springfield, Worcester; Michigan:  Ann Arbor, Detroit, Flint, Grand Rapids, Kalamazoo, Lansing; New York:  Albany-Schenectady-Troy, Binghamton, Buffalo-Niagara Falls, New York City, Rochester, Syracuse, Utica; Ohio:  Akron, Canton, Cincinnati, Cleveland, Columbus, Dayton, Toledo, Youngstown; Pennsylvania:  Allentown-Bethlehem-Easton, Erie, Harrisburg, Lancaster, Philadelphia, Pittsburgh, Reading, Scranton-Wilkes-Barre, York.

[1] “As senator, Clinton promised 200,000 jobs in Upstate New York. Her efforts fell flat.” Jerry Markon, Washington Post, August 7, 2016.

[2] Economic Policy Institute, “The Manufacturing Footprint and the Importance of U. S. Manufacturing Jobs,” Robert E. Scott.  January 22, 2015.  http://www.epi.org/publication/the-manufacturing-footprint-and-the-importance-of-u-s-manufacturing-jobs/

 




Syracuse’s Empty Film Hub

The New York Times carried an article, “Cuomo’s $15 Million High-Tech Film Studio? It’s a Flop,”[1] on August 22nd.  The article points out that the Central New York Hub for Emerging Nano Industries, owned by the Fort Schuyler Management Corporation (FSMC), a non-profit subsidiary of the SUNY Research Foundation, is largely vacant, and has housed only two as yet unreleased film projects creating several hundred temporary jobs.  Currently, the facility employs only two workers, according to the Times.

When the film studio was initially  announced, the press release claimed it would create at least 350 high technology jobs.  The release stated, the Hub “will specialize in providing advanced visual production research and education to support Upstate New York’s rapidly growing film and television industry…. The film industry of tomorrow is being born today in Central New York.”[2]

In an earlier post, concerning the Solar City solar panel factory now being constructed in Buffalo,[3] I pointed out that the economic development model employed by SUNY carried significant risks, and questionable benefits. Among the most significant problems with the Solar City project are:

  • The fact that the SUNY created Fort Schuyler Management Corporation retained ownership of the solar panel factory, and leased it to Solar City, instead of providing a grant to Solar City for construction of the facility.
  • Because a state created entity retains ownership, it carries the risk that if Solar City discontinues operations in Buffalo, FSMC would be stuck with a specialized facility that would have little market value, and significant costs associated with redevelopment.
  • The project also suffers from inflated job creation claims, and enforcement responsibilities for job creation requirements are unclear.
  • FSMC has never disclosed decision processes or benchmarks used in structuring the project.

The Absence of a Lead Organization and Local Partners

The Central New York Hub poses some of the same problems as the Solar City development, along with others.  First, although the release claimed that the Hub would be a research and education center for advanced film production, it never identified the entities that would do research and provide education there.  Instead, it identified a film production company that would do post-production work at the facility, and though that company produced a film there, the use of the site was associated with only one project that was undertaken in the area.  In essence, the Hub was real estate development, without a well-developed business plan to utilize it. Today, no film production is underway, and there is no employment at the site by tenants.

A Convoluted Economic Development Model

The Central New York Nano Hub employs an economic development model used by the SUNY Research Foundation and FSMC that involves developing, and in some cases equipping, facilities for the use of real or potential tenants.  Tenants lease the facilities, in some cases for virtually no cost, with the expectation that they will create jobs.  Because a non-profit (FSMC) that is the child of the State University develops the facility, a state related intermediary (Empire State Development) is required to impose and enforce contract requirements on FSMC, and to disburse money to it.  But, because of the convoluted funding and ownership structure, Empire State Development has no direct relationship with the entities expected to create and retain jobs, complicating enforcement of any job requirements associated with the projects.

In contrast, in the past, economic development entities at the State and local levels provide funding subsidies to entities creating and retaining jobs themselves – manufacturers and service companies – not real estate developers.  Because of this direct relationship, enforcement of job requirements, by withholding or recapturing subsidies, is relatively simple.

The development of the Central New York Nano Hub was speculative.  As a result, the SUNY related entity FSMC has created a white elephant – a facility with no real likelihood that it will be used as intended.  Consequently, at this point there is no real expectation of job creation, let alone enforcement of job creation requirements.

A Project without an Economic Development Strategy

Because the Syracuse Hub did not build on the strengths of existing area institutions, such as Syracuse University, or local businesses with expertise in the field, it lacked the essential organizational capital needed to succeed.  This is in sharp contrast to the state supported development of nanotechnology and semiconductor manufacturing in the Albany area, which had strong leadership from Dr. Alan Kaloyeros at SUNY Albany, and relationships with significant technology leaders, including IBM and AMD, as well as semiconductor equipment manufacturers.

The Governor established a process of regional competitions for economic development funding that required the development or regional strategic plans.  The Central New York Regional Economic Development Council developed such a plan, “Central New York Regional Economic Development Council: Five Year Strategic Plan: 2012 – 2016,[4] and has updated it yearly.  The plan identifies the region’s economic characteristics, and develops a strategy to build on area strengths, and remedy weaknesses.  But the development of the Syracuse Nano Hub was done without reference to the plan or the area’s capacity to support film production research, education, or related businesses.  In effect, the project was dropped on the region by the State University, without involvement of local partners.

Implications

Without a disciplined approach to spending state dollars for economic development or for other purposes, taxpayer dollars are likely to be wasted.  Because SUNY, through the Fuller Road Management Corporation, has declined to provide information about how it makes funding decisions, or justification for acting as project developer and facility owner, taxpayers cannot be assured that their money is being used wisely. Because the Central New York Nano Hub was developed without regard to existing regional economic development strategies, it did not build on regional strengths or remedy weaknesses. And, because the project was developed without local organizational commitments and partners, it had no real chance of succeeding.

In the end, the State, through SUNY or Empire State Development, might find a tenant outside the film industry to create jobs in the region by providing additional financial incentives.  But if it does, the Hub will be a government funded facility, paid for by taxpayers, competing with locations developed by area private sector developers.

 

[1] http://www.nytimes.com/2016/08/23/nyregion/in-cuomos-film-hub-vacant-studios-lawsuits-and-little-action.html?hp&action=click&pgtype=Homepage&clickSource=story-heading&module=second-column-region&region=top-news&WT.nav=top-news&_r=0

[2] https://www.governor.ny.gov/news/governor-cuomo-announces-start-construction-new-central-new-york-film-hub

[3] http://policybynumbers.com/solar-city-the-risk-embedded-in-buffalos-billion

[4] http://regionalcouncils.ny.gov/themes/nyopenrc/rc-files/centralny/final%20CNY%20REDC%20plan%20single%20pages.pdf