How the State Senate Gerrymander Ultimately Hurt Upstate Residents

The November election brought a marked change in the composition of the New York State Senate that will have significant implications for upstate New York residents.  Tom Precious in the Buffalo News noted, “Majority party rules and minority party lawmakers are left with table scraps when it comes to funding and policy matters.  As a result, millions of upstate residents could see themselves lose the sole remaining seat at the table in closed door Capitol talks…”[1]

Kent Gardner wrote in the Rochester Beacon, “A New York State Legislature wholly controlled by downstate interests won’t stop sending education aid Upstate or close the state parks…. Complete control of the NYS Legislature by downstate reps will change things over time. Party aside, upstate has a lot at stake in this election.”

This post will seek to answer two questions:  Why did Republicans lose control of the State Senate, and why does upstate have so little majority party representation?

Republicans had controlled the State Senate from 1966, with only a brief break in 2012, when Democrats gained a majority and then splintered into two factions – one of which joined the Republicans to form a majority.  But in 2018, voters decisively gave control to Democrats, who will hold 40 of 63 seats.  The loss of Republican control will significantly reduce upstate’s representation in the party controlling the Senate, since only three seats outside the New York metropolitan area are held by Democrats.  In the most recent legislative session, 18 upstate Senators were in the Republican/Reform Democrat Senate Majority.

For many years, the Republican Senate majority was composed of a coalition of upstate, Long Island and Hudson Valley members.  In 2000, Republicans maintained control in the State Senate by winning 35 of 61 districts in all parts of the State – 17 in upstate New York, nine on Long Island, five in New York City, and four in the Hudson Valley portion of the metropolitan area.

In 2018, Senate Republicans won only three seats on Long Island, one in New York City and one in the Hudson Valley portion of the metropolitan area.  Only in upstate New York did the party increase its strength – to 18 seats.

The regions that moved towards the Democratic party – Long Island, New York City and the lower Hudson Valley — had substantial Democratic party representation by 2018.  Two-thirds of Senators from Long Island will be Democrats, all but one Senator in New York City and all but one in the Hudson Valley portion of the metropolitan area will be Democrats.

In upstate New York, only three of 21 State Senators will be Democrats.  Ironically, had the Senate’s legislative district apportionments more accurately represented voter party preferences, about half of upstate’s Senators would be Democrats.

Upstate’s majority party representation in the State Assembly will now be stronger than in the Senate.  Twenty-three of 48 upstate seats in the Assembly will be held by Democrats.[2]

Differences in Regional Party Affiliations

In New York City and in the lower Hudson Valley, Democrats and allied parties hold commanding registration advantages in 2018. Of those affiliated with a political party, 87% were Democrats in New York City and 62% in the lower Hudson Valley.  Long Island and Upstate New York are competitive – Democrats and allied parties are 52.5% of Long Island voters whore were affiliated with a political party in 2018, and in upstate New York, 52.7% were affiliated with Democrats or allied parties.

Upstate party registrations have shifted toward the Democratic party – from 47.3% to 52.7% between 2000 and 2018.  In 2000, in most upstate metropolitan areas Republicans and Conservatives were a majority of voters affiliated with a political party.[3]  By 2018, Republicans were in the majority in Binghamton and Utica, but Democrats (with Green Party, Working Family Party and the Women’s Equality Party) had majorities of party affiliated voters in the Albany-Schenectady-Troy, Buffalo-Niagara Falls, Rochester, and Syracuse metropolitan areas and in Tompkins County.

Within upstate New York, there are significant differences in the political affiliations of voters in metropolitan areas and outside them.  About one-third of upstate voters live outside the six metropolitan areas.  Almost 60% of these non-metropolitan residents who are affiliated with a party are Republicans.  But, residents of upstate’s larger metropolitan areas – Buffalo-Niagara Falls, Rochester, Albany-Schenectady-Troy and Syracuse lean Democratic.  Even the area’s smaller metropolitan areas – Utica-Rome and Binghamton show close to an even division between parties.

The significance of the split between registered Republicans and Democrats is somewhat weakened by the large number of upstate voters who are unaffiliated with a political party. 890,000 of the 3.84 million registered voters in upstate New York fall into this category.

Also note that the Independence Party was not included in this analysis because its candidate affiliations have been inconsistent.  Initially, In New York State, the party supported Tom Golisano, a wealthy Rochester businessman who ran on conservative a platform in 1994, 1998 and 2002.  More recently, the party has supported Democratic Gubernatorial candidates Eliot Spitzer and Andrew Cuomo.  The Independence Party is by far the largest splinter party in upstate New York, with 213,000 members.

Republican and Democrat Voting Strength in Upstate New York

This map, above (from Wikipedia), of the 2016 Presidential Election result suggests that Republican voters (in red) dominate upstate New York.  Other than metropolitan counties like Albany, Onondaga, Monroe and Erie, and a few counties in the Hudson Valley, most of upstate New York voted for Donald Trump, the Republican nominee.

This map looks like Republicans dominate upstate, but most of the red colored Republican Counties are sparsely populated, while the blue Democratic areas are population centers. And, the map is based on a single race. Voter preferences are more complex than can be captured in the results of a single face-off.

Contests for Congress and for Governor show that voting in elections in upstate New York is closely divided between Republicans and Democrats.  Republicans had more votes than Democrats upstate in the 2016 election for President and the 2018 election for Governor, but more votes were cast for Democrats in the 2012 Presidential election and the 2018 Senate and House of Representatives elections.

Why Upstate State Senate Representation Does Not Reflect Voter Preferences

Upstate representation in the State Senate does not reflect underlying party preferences as measured by party registration or voting behavior.  Democrats only hold three of twenty-one upstate State Senate seats, even though races at the State and Congressional levels have been highly competitive, with Democrats winning 5 of 9 upstate congressional districts in 2018, and 23 of 48 Assembly seats as well as gaining more votes in one of two presidential elections and in the most recent U. S. Senate election.  Why is the Senate unrepresentative of upstate party preferences and election performance?

When I began researching this question, I assumed that the primary cause of the difference in electoral results in upstate State Senate districts and other elections had to be legislative district gerrymandering.  After all, what else could explain the fact that Republicans control 18 of 21 districts, even though party preferences are about evenly split between the parties?  Though there is clear evidence that the controlling parties in the Legislature structured districts to favor members of their own parties, another factor appears to be important.  Republicans continue to succeed in electing candidates in upstate Senate districts where there are more Democrats than Republicans.

Gerrymandering

The State Legislature has historically controlled the redistricting process, creating gerrymandered districts that favored the parties in control.  In 2010, Republicans controlled the State Senate, and Democrats controlled the Assembly.  The result was a series of gerrymandered districts.

For example, State Senate District 50 in the Syracuse Metropolitan Area was carefully constructed to include suburban Republican votes, while excluding Democratic votes in the city of Syracuse.  The seat was held for many years by Senator John DeFrancisco until his retirement this year.  In the 2018 election, another Republican, Bob Antonacci, was the victor.

Assembly District 101, which looks like a worm that connects the town of Montgomery, just west of Newburgh with New Hartford – a suburb of Utica – is another example. The district, which carefully avoids nearby cities (with higher Democratic enrollment), is about 150 miles long and includes parts of Oneida, Herkimer, Otsego, Delaware, Ulster and Orange Counties! It is held by Republican Brian Miller.

Gerrymandering in the legislative apportionment process attempts to make one party waste as many votes as possible by concentrating voters in that party in overwhelmingly one-party districts, while spreading votes in the party benefiting from the gerrymander across districts in smaller, but safe majorities.

Since the mere requirement of population equality does not necessarily result in the creation of legislative districts that come close to reflecting the political preferences of residents, political parties within legislatures have taken advantage of the opportunity to maintain control, often creating legislative majorities that are much stronger than voter preferences would indicate, or in some cases, maintaining control despite the fact that only a minority of voters prefer them. Misalignments between voter preferences and public policy result from partisan gerrymanders.

Additionally, upstate Senate districts on average have fewer residents than downstate districts in order to strengthen upstate’s presence.  The difference in district sizes increased the region’s representation from 20 to 21 seats.  Under the law, legislative district populations may vary by 10%.

In upstate New York, State Senate districts were engineered to break up metropolitan areas into a series of districts that also contained large numbers of non-metropolitan residents, predominantly Republican voters.  The result has been to weaken the ability of democratic leaning metropolitan area voters to elect representatives who shared their political preferences.

For example, the Albany-Schenectady-Troy metropolitan area has 887,000 residents.  With 63 Senators, each Senate District should have approximately 315,000 residents.  The area has enough residents for almost three State Senate districts.  But the most recent Senate Reapportionment in 2016 split the metropolitan area into pieces of four State Senate districts that encompass large rural areas outside the metropolitan area.  In the process, three of the area’s primary cities – Troy, Schenectady and Saratoga Springs were each split into two Senate districts, disregarding their boundaries.

Similarly, the Rochester MSA, with a population of 1.1 million has enough residents to populate three and one third Senate districts but has been split into five Senate Districts including substantial non-metropolitan populations.

An analysis by Jeremy Creelan and Allison Douglas of the Rockefeller Institute, “New Tools to Challenge Partisan Redistricting in New York State”[4]  measured the extent of partisan gerrymandering in New York and examined the reviews of other authors and came to the conclusion that the extent of partisan gerrymandering in New York favoring Republicans was substantial, quoting an analysis by Simon Jackman of Stanford University that concluded that New York’s districts were “the most Republican favoring out of any state…”[5]

Democratic Underperformance

Although State Senate districts were structured to disadvantage Democratic party candidates by mixing Democratic majorities in metropolitan areas with rural, Republican voters, Democrats have not elected as many State Senators as would be expected from upstate Senate districts’ partisan makeups.  Eight of 21 upstate Senate districts have more Democratic voters than Republicans, but only three districts are represented by Democratic State Senators.  Several factors may account for Democrats’ underperformance.

  • The natural advantage conferred by incumbency is reinforced by gerrymandering. In 2018, 18 of 21 Senate contests involved Republican incumbents. The Democrats didn’t even field a candidate in 7 of these races. The three winning Democrats were incumbents. (A similar dynamic plays out in the Assembly. Eighteen of 48 Assembly contests were uncontested.)
  • There is a large fall-off in voting between statewide candidates, and those for the State Senate – 15% of those who voted in the election for U. S. Senate did not vote for a State Senate candidate. This may reflect Democratic voters’ decision to abstain from voting when the race is uncontested or manifestly uncompetitive.

Implications

Viewed purely with “sectional” eyes, upstate New York’s influence in Albany may have been greater because Republican gerrymandering granted upstate control of one of the Legislature’s two houses.  But that power meant that the views of about half of upstate’s residents – Democratic voters who make up the majority of residents of metropolitan areas – were underrepresented in the State Legislature.  The upstate Republican leadership of the State Senate primarily represented the interests of conservative rural and suburban residents.  Upstate city residents and people whose policy views corresponded with Democratic party positions received little Senate attention.

With Democratic party control of the State Senate, upstate now has less majority party representation than it would if Senate districts had not been gerrymandered in favor of Republicans, weakening the region’s voice in the State Capitol.

To be sure, fairer legislative districts would not ensure particular outcomes in State Senate races, because voters do not vote for parties in legislative elections any more than they do in elections for Governor or the U. S. Senate.  The large difference in the percentage of upstate voters who favored Andrew Cuomo (46%) against Republican Marcus Molinaro compared with the support given Kristin Gillibrand (57%) against Republican Chele Farley illustrates this point.  In fact, in much of upstate New York, party affiliations are relatively evenly divided, with electoral results in Statewide elections favoring each party in different races.

Reapportionment after the 2020 Census

Reapportionment after the 2020 Census is likely to create legislative districts that more accurately represent the partisan preferences of New York residents than past apportionments.  In 2012, New York voters passed a Constitutional amendment that reforms the apportionment process and institutes new Constitutional requirements for district representativeness.  The process is a mixed bag, containing features that could work against accurate voter representation, and others that could work for it.

The amendment sets up a ten-member redistricting commission with four members appointed by each of the major parties’ legislative leaders plus two additional members selected by the eight.  The amendment also requires that any plan developed receive the support from members nominated by both political parties.  The State Legislature must vote upon the plan submitted by the Commission without amendment. If two successive plans from the Commission fail to receive Legislative and gubernatorial approval, the Legislature is then empowered to present its own plan. As legislative approval is required, there will be an unnamed “third party” involved in the redistricting effort, the “Party of the Incumbency.” Logrolling and trading to preserve the prerogatives of incumbents and secure the required approvals may work against representation of voter preferences within legislative districts.[6]

The Constitutional amendment includes a prohibition against partisan gerrymandering, “[d]istricts shall not be drawn to discourage competition or for the purpose of favoring or disfavoring incumbents or other particular candidates or political parties.  This important provision is intended to prevent the redistricting commission from manipulating district boundaries to advantage particular parties and candidates and  creates a constitutional basis for a court challenge to a legislative districting plan that is gerrymandered.

Because of the statewide shift in voter preferences to the Democratic party, Republicans are unlikely to retake control of the State Senate, at least in the near future.  Upstate New York is unlikely to have as much influence as it had in the past in the State legislature.  But if the  passage of the 2012 constitutional amendment achieves the goal of representational equity,   the Senators who represent it will be more likely to represent the policy preferences of upstate residents.

(Note:  An abridged version of this post appears in the Rochester Beacon, titled, “The Cost of Gerrymandering”)

[1]Potential State Senate Power Shift Offers Big Implications for Upstate,” Tom Precious, Buffalo News, October 7, 2018.

[2] Upstate districts outside the New York metropolitan area are districts 101-103 and 106-150.

[3] The Independence Party is excluded from the analysis.

[4] Jeremy Creelan and Allison Douglas, New Tools to Challenge Partisan Redistricting in New York State?”, Rockefeller Institute of Government, August 31, 2017, https://rockinst.org/issue-area/new-tools-challenge-partisan-redistricting-new-york-state/

[5] Simon Jackman, “Assessing the Current Wisconsin State Legislative Districting Plan,”  July 7, 2015, http://www.campaignlegalcenter.org/sites/default/files/Jackman-WHITFORD%20V.%20NICHOL-Report_0.pdf

[6] Creelan and Douglas, op. cit.




Misconceptions About People in Poverty – Additional Information

This is an expanded version of the essay, “False Stereotypes Harm People in Poverty” that appeared in the Rochester Beacon, containing additional information relating to the five largest upstate metropolitan areas.

__________________________________________________

Misconceptions about people in poverty appear to drive proposed changes in social welfare policy, particularly the work requirements either being promoted by the Trump Administration and discussed or implemented in several states. A fuller understanding of factors underlying the problem of poverty suggests that these policies will be counterproductive, neither reducing the incidence of poverty nor helping those individuals and families targeted by these new policies.

The concentration of poor black and Hispanic people in central cities has allowed politicians to characterize the poor as “others”- people unlike white suburban majorities in upstate metropolitan areas, and to disparage them as dishonest, lacking in ambition and willingness to work.

For example, Ronald Reagan claimed the existence of a “welfare queen”, who supposedly cheated the government of $150,000.  Josh Levin, in “The Welfare Queen” describes Reagan’s line of argument, “When he ran for president in 1976, many of Reagan’s anecdotes converged on a single point: The welfare state is broken, and I’m the man to fix it. …. In Chicago, they found a woman who holds the record,” the former California governor declared at a campaign rally in January 1976. “She used 80 names, 30 addresses, 15 telephone numbers to collect food stamps, Social Security, veterans’ benefits for four nonexistent deceased veteran husbands, as well as welfare. Her tax-free cash income alone has been running $150,000 a year.”

The story was untrue.  The real welfare queen had defrauded the government of $8,000 using a few false identities.

Reagan was not alone in stoking resentment against poor beneficiaries of government assistance.  Donald Trump more recently claimed that, “I know people that work three jobs and they live next to somebody who doesn’t work at all. And the person who is not working at all and has no intention of working at all is making more money and doing better than the person that’s working his and her ass off.”  Trump also claimed in 2011, the existence of “a food stamp crime wave.”  Neither of these claims was supported by evidence.

Like much of the public, Trump believes that most black people are poor.  The New York Times reports that, “Trump also said to black voters: “You’re living in poverty; your schools are no good; you have no jobs.”

Those who see people in poverty as “others” are more likely to ascribe their condition exclusively to lack of personal responsibility, ignoring other factors, like education, disability, racial discrimination and family structure.  These beliefs often lead to support for coercive government assistance policies for the poor, such as work requirements for medical, food and housing assistance.

Poverty in Upstate Metropolitan Areas

More than one in seven (540,000) residents of five upstate metropolitan areas – Albany-Schenectady-Troy, Buffalo-Niagara Falls, Rochester, Syracuse and Utica-Rome – lived in poverty in 2016, roughly comparable to the national average of 15%.[1]

Most people view poverty as primarily a problem of the central cities.  Concentrations of poverty in upstate New York cities are far higher than in suburban areas. But the concentration of poverty in upstate cities does not tell the full story.  In each metropolitan area, about half of people in poverty live outside central cities.  In the Rochester and Syracuse Metropolitan areas, more than half lived outside central cities.

For example, in the Syracuse metropolitan area, 34% of city residents live in poverty, while 11% of those living outside the city are poor.  But, the population of Syracuse is only 21% of the metropolitan area total.  As a result, more than half (55%) of the people living in poverty in the Syracuse metropolitan area live outside the city of Syracuse.

Other metropolitan areas show similar patterns.  55% of poor people in the Rochester MSA live outside the City of Rochester.  49% of poor residents of the Albany-Schenectady-Troy MSA live outside central cities.  47% and 43% of poor residents in the Utica-Rome and Buffalo-Niagara Falls MSA’s live outside central cities.

Because about only one in ten people living outside central cities in upstate metropolitan areas is poor, the suburban poor are relatively invisible despite their relatively large numbers, while those living in central cities, with higher poverty concentrations, are much more visible.

Race

Many people believe that people living in poverty are primarily members of racial minorities, even though overall, in most upstate metropolitan areas most poor people identify as “white, non-Hispanic or Latino. Overall, 64.6% of all residents of upstate New York[2] living in poverty identify as white, not Hispanic or Latino.

  • In upstate New York, only in the Buffalo-Niagara metropolitan area did non-white residents make up most people living in poverty.
  • In the Albany-Schenectady-Troy, Syracuse and Utica-Rome metropolitan areas, more than six in ten people in poverty identified as “white alone, not Hispanic or Latino.”

Because of the high concentration of poor people in central cities, city residents living in poverty are more visible than those living in suburbs.  In upstate metropolitan areas, more than 60% of people in poverty outside central cities identify as “white alone, not Hispanic or Latino.”  In central cities, the picture differs. Only about 25% of central city residents in poverty identify as “white only.”

In the Rochester metropolitan area, 19% of city residents living in poverty identify as white, non-Hispanic or Latino, while outside Rochester, 81 percent of poor residents identify as non-Hispanic/Latino whites.  In the Syracuse metropolitan area, 25% of city residents living in poverty identify as non-Hispanic or Latino white, while outside Syracuse, 76% of poor residents identify as white alone, not Hispanic or Latino.

Similarly, there is a commonly held belief that most minority group members are poor.  But, in the United States, and in upstate New York metropolitan areas, most black and Hispanic residents do not live in poverty.  More than six in ten lived above the poverty line in 2016.

  • About nine of ten white, non-Hispanic or Latino households do not live in poverty.
  • The fact that a much larger percentage of minority residents of upstate metropolitan areas live in poverty than people who identify as white is a real problem, but the common perceptions that most poor people are minority group members, and that all (or most) blacks are poor are not true.

Work

In upstate metropolitan areas, a much smaller percentage of people over 16 living in poverty than those not in poverty worked full or part-time during 2016.  More than 80% of people between 16 and 64 not in poverty worked in 2016 in upstate metropolitan areas, while between 40% and 50% of those in poverty worked. Note that this data includes people who are disabled, caregivers and those in schools and colleges.

A Brookings Institution report notes that most of those who do not work nationally are caregivers (15%), students (13%), disabled (22%), or early retirees (6%).

Poor people who work in upstate metropolitan areas were much more likely to work part-time than full-time in 2016.  In contrast, most workers who were not in poverty worked full-time. About 80% of working people in poverty in upstate metropolitan areas reported working part-time in 2016.  In contrast, only about one-third of working people not on poverty reported that they worked part-time.

People in poverty work part-time for a variety of reasons, but the largest number – 33% — worked part-time involuntarily in 2016.  Caregivers (23%) and students (21%) were the next largest groups of part-time workers in poverty in 2016.

The high percentage of people who work less than full-time year around is the result of several factors.  A study by the Center for Budget Priorities points out that these include:

  • Low wage jobs often have irregular work schedules.
  • These jobs often lack paid sick leave or other paid leave.
  • Job turnover is high among low paid workers.
  • Many low paid workers are unable to find affordable child care arrangements.
  • Some low paid workers lack stable housing arrangements.

Work Requirements for Safety Net Programs

Stereotypes about people in poverty and their relatively low participation in the labor market have spurred policy proposals that make SNAP (food stamp) and Medicaid benefits conditional on beneficiaries participating in worker training or gaining employment.

President Trump’s Council of Economic Advisors (CEA) claims that employment levels of people on major government assistance programs are low: 60% of Medicaid recipients, 60% of SNAP (food stamps) recipients, and 52% of housing assistance recipients who were working age and not disabled worked less than 20 hours a week, or not at all.

The Council argues that “expanding work requirements, similar to those in place in TANF, to the three non-cash welfare programs discussed here (Medicaid, SNAP and housing assistance) would affect the majority of program recipients and require major increases in the work effort of non-disabled working-age adults, potentially helping recipients and their families.”

The CEA substantially overstates the number of poor people who receive government assistance who do not work. A Center for Budget and Policy Priorities analysis of the workforce participation data from the Council of Economic Advisors concluded it was based on a significant methodological error.  The CEA report looked at “whether an individual receiving assistance worked in a single month (December 2013), ignoring the fact that many workers have unstable jobs and receive help when they are between jobs.

A report by the Brookings Institution, “Work Requirements and Safety Net Programs” shows  42 percent being out of the labor force and roughly 11 percent unemployed in the one-month snapshot – leading to more than half of the group being labeled “not working” in the one month snapshot – [but] roughly 29% are out of work and just one percent are persistently unemployed over two years, meaning fewer than one third are not working consistently.”

Many people in poverty work less than full-time year around involuntarily.  If their work is seasonal or they have been subject to layoffs and recalls to employment, they would be likely to be subject to potential denials of benefits at those times when they were out of work – precisely the times that assistance would be most needed.  The Center for Budget Priorities report points out that

“SNAP participants often experience periods of joblessness and are more likely to participate in SNAP when they are out of work. Individuals who participated in SNAP at any point over a 3.5-year period from 2009 through 2013 worked most months over this period but were more likely to participate when they were out of work.

  • They participated in SNAP in over two-fifths of the months that they were working (44 percent).
  • They participated in SNAP in 62 percent of the months in which they were not working, a time when their income was lower and their need for help affording food was higher.”[4]

To be sure, personal responsibility can be a factor in poverty. Single parents are much more likely to encounter poverty, for example. It certainly makes sense to implement policies that educate and remind people of the difficulties faced by single parents, encourage family planning, and hold absent fathers responsible for a share of the cost of raising children.

Instituting additional work requirements for participation in programs like SNAP and Medicaid would likely reduce participation levels and would increase administrative costs associated with compliance requirements.  Many of those who could lose benefits would lose assistance when they most need it.  Brookings found that For those who qualify for exemptions, satisfy waiver requirements, or work enough to meet the requirements, there are still significant informational and administrative barriers to compliance. Program participants must understand how the work requirement policy relates to them, obtain and submit documentation, and do so at the frequency prescribed by the state (Wagner and Solomon 2018) …. These continuing roadblocks to participation, with attendant informational and transactional costs, are likely to result in lower take-up among the eligible population and disenrollment (Finkelstein and Notowidigdo 2018).”

An analysis of the implementation of work requirements for Medicaid in Arkansas by the Kaiser Family Foundation found that recipients lost benefits because “Many Medicaid enrollees [were] still not aware of program changes despite substantial outreach.  In addition, an online reporting requirement is proving difficult for many enrollees due to limited knowledge of the requirements as well as lack of computer literacy and internet access,”

The fundamental question that these approaches raise is whether the government should condition access to essentials for human life, such as government provided food or health care coverage for unemployed poor people, on participation in training programs or gaining employment.  If such an approach is an acceptable incentive, why not limit public schools, police and fire services to those who work as well?

Because of false stereotypes about people in poverty that emphasize their differences from white suburban majorities, attitudes of much of the public to programs like SNAP and Medicaid and the poor people who receive assistance from them are negative.  Politicians have fostered these attitudes by promoting ideas like the “welfare queen” who supposedly abused the system, and people who don’t work who do better than those who “work his and her ass off.”  They use these stereotypes to promote punitive approaches to policies that help people in poverty pay for food, receive medical care and find housing.  These coercive policies are not responsive to the practical obstacles  confronted by individuals and families in poverty. Instead, they will further harm some who need assistance.

[1] Note that the official measure of poverty does not reflect the market value of food stamps or tax benefits like the earned income tax credit.

[2] Residents of counties outside the New York City metropolitan area.




How Amazon Could Help Upstate New York

One of the Thanksgiving meal discussions at my house involved Amazon’s new HQ2 and why Governor Cuomo didn’t get the company to locate its new facility in upstate New York.  And, though my argument that upstate metropolitan areas lacked technology focused labor pools of sufficient size to be seriously considered by a technology based firm creating 25,000 jobs was received with skepticism, that is one of the real difficulties that upstate metropolitan areas faced in the competition.

But, my former colleague and friend from Empire State Development, Dave Catalfamo points out that with some effort from the Cuomo Administration, some of the benefits offered by Amazon might be more widely shared.  So, I’d encourage you to read the “Put Amazon to Work” on his blog, Exiled in Albany, for some ideas.




Amazon HQ2 – A Good Deal for New York?

It is not surprising that the decision by Governor Cuomo to give Amazon $1.8 billion in grants and refundable tax credits to come to New York City for half of their second headquarters generated controversy.  Some have questioned the need to subsidize Amazon given New York’s labor pool advantages[1], and the amount of money given the company to lure them to New York.  Others have questioned why New York would pay billions to encourage a business to locate in the part of New York State that is already doing well when the economy of much of the rest of New York is stagnant.  Residents of the area express concerns about likely higher housing prices and additional congestion resulting from the project.

To be sure, the process used by Amazon to choose its second headquarters sites, aptly dubbed “the hunger games” was structured to create a bidding war between potential locations.  And, there is no doubt that granting location incentives to businesses like Amazon has many downsides:

  • It shifts the costs of existing government services to other taxpayers in unfair ways.
  • It imposes additional subsidy costs on taxpayers who do not benefit.
  • It creates an expectation by other businesses considering relocations or expansions that they can get the same kinds of subsidies that Amazon received.

New York’s offer to Amazon consisted of a $505 million capital grant toward the $3.686 billion project cost and up to $1.2 billion in refundable tax credits through the state’s Excelsior program.  Virginia offered an incentive package including nearly $600 million in cash grants, plus $195 million in infrastructure improvements.  Amazon’s project cost in Virginia is expected to be $2.5 billion.

But, the benefits of the Amazon project to New York are real – 25,000 jobs paying an average of $150,000 annually to employees.  In fact, the Amazon project is by far the largest business attraction opportunity in memory.  Even in a metropolitan area as large as New York’s, the economic impact is significant, adding $3.75 billion in payroll spending to the metropolitan area each year, with a total annual economic benefit to the state of about $7.5 billion.[2]  The state estimates that the project will generate $560 million annually.  The cost of incentives would be paid back with additional tax revenue in about three years.

It is helpful to understand the challenges faced by state leaders in responding to Amazon’s second headquarters project.  The process involved in the Amazon location decision differed from virtually all previous corporate location decisions because of Amazon’s decision to create a public bidding war between locations.  That meant that every large city in the United States would put together an incentive proposal for Amazon HQ2 – 238 in all.

In most business attraction cases, companies work with site selection consultants that help them identify needs and wants. The consultants winnow down potential sites to a small number that receive serious consideration.  From that point, negotiations between companies, consultants and government take place confidentially.

Amazon eventually announced publicly that it had reduced the list of locations being considered to 20.  Once confidential discussions began between Amazon and state and local governments, information about competitive offers became harder to obtain.  But there was reason to believe that a successful incentive offer would have to be substantial to be successful.

Decision makers in state and city government knew that New Jersey’s proposal would receive serious consideration (New Jersey offered $7 billion in incentives).   Because much of New Jersey lies within the New York metropolitan area, it shares the same labor pool advantages offered by New York.  And, as Amazon’s ultimate decision demonstrated, the Washington D. C. metropolitan area had many of the same advantages offered by New York City, including a large pool of technology workers (Amazon received an $8 billion proposal from Maryland).

When governments negotiate corporate location incentives, they face some inherent disadvantages because they have less information than the business.  Government negotiators can estimate tax incentives available from competitive locations, but do not know how the company values them.  State and local negotiators cannot be certain what discretionary incentives are being offered by competitors.  Nor does government know how the company views the advantages and disadvantages of the sites that it is considering.  Finally, they cannot know whether companies are telling the truth when they make representations about other offers that they have received.

The difference in sizes between the New York’s and Virginia’s incentive packages probably reflects several factors.  It’s likely that one reason New York provided more assistance is the fact that Amazon’s New York project will cost almost $1.2 billion more than the Virginia project.  A second factor may be that New York advertises the availability of Excelsior tax credits.  Because these benefits are visible to the public in New York’s business marketing materials, businesses considering New York locations expect to receive them as a matter of course.  As a result, they are not a subject of negotiation.

Additionally, long-term tax credits like the Excelsior program do not use public dollars efficiently.  Research shows that long-term tax incentives are heavily discounted by businesses considering new locations because benefits paid soon are heavily favored over those in future years.[3]  Reducing or eliminating reliance on tax credit programs like Excelsior could save the state money for future business attractions.

It could be argued that state’s like New York should refuse to engage in incentive wars like Amazon’s, but such a course of action would be difficult from a political perspective.  Any governor or mayor who took his or her state out of a competition for thousands of jobs would provide potential future opponents with campaign fodder.

From a public policy perspective, although there are significant negative tradeoffs associated with a public subsidy of the magnitude that was provided to Amazon, the reality is that 25,000 good paying jobs are too many to give away to another location.  Even with the very large public subsidy provided to Amazon, there is a substantial net economic and fiscal benefit to the State from securing the jobs for New York.

In the end, financial incentives alone did not determine the choices that Amazon made.  In fact, Amazon passed up larger incentives from direct competitors to New York (New Jersey) and Virginia (Maryland).  But, to conclude from that New York or Virginia could have landed Amazon’s HQ2 without the use of incentives is wishful thinking.

[1] A recent Brookings Institution brief shows that the New York Metropolitan area has by far the largest number of workers in computer and mathematical occupations.  https://www.brookings.edu/blog/the-avenue/2018/11/13/for-amazon-hq2-location-decision-was-about-talent-talent-talent/

[2] Estimates derived from:  https://www.governor.ny.gov/news/governor-cuomo-and-mayor-de-blasio-announce-amazon-selects-long-island-city-new-corporate

[3] [17] Timothy Bartik, 2009. “What Works in State Economic Development?” In Growing the State Economy: Evidence-Based Policy Options, 1st edition, Stephanie Eddy, and Karen Bogenschneider, eds. Madison, WI: University of Wisconsin, pp. 19.




School Segregation is Increasing in New York’s Cities and Suburbs

Recent articles in the New York Times and The Nation have focused on efforts to resegregate schools in the South, by carving new predominantly white school districts out of larger county-wide school districts that are predominantly black and Hispanic.  The articles examined a recent federal court decision that permitted the creation of the Gardendale School District near Birmingham, Alabama.  The new district is 75% white, in a county school district that has a majority of black and Hispanic students.

In 1954, the United States Supreme Court, in Brown vs. Board of Education, outlawed the creation of segregated school systems by law.  While first efforts to combat segregation focused on legally created barriers to integration in the South, later, courts ordered busing to combat segregation in northern school districts, like Boston.  These efforts were met with fierce resistance from parents who did not want their children to be bused to schools that had large minority student populations outside their neighborhoods .

Resistance to school integration has been has been widespread.  While legally created separate schools in the same school system for white and black students have been eliminated, opposition to efforts to combat segregation based on residential patterns has been widespread and largely successful.  Today, the schools attended by black and Hispanic students typically have far higher concentrations of minority students than those attended by white students.  While segregation in the South was the result of laws that created separate school systems for white and black students, today much of the segregation results from the concentration of black and Hispanic students in cities with majority black and Hispanic populations.

In an earlier post, I examined the growth of segregation of black and Hispanic students in metropolitan areas in New York State.  In this post, I compare the concentration of black and Hispanic students with white students in schools in cities and suburbs in New York metropolitan areas.

Changes in School Enrollment 

In upstate metropolitan areas, and in the suburbs in the New York metropolitan area, enrollments of black and Hispanic students have increased substantially between 1990-91 and 2014-15 – by more than 50,000 upstate and by 140,000 in the New York suburbs.

  • Black student enrollments increased in upstate metropolitan areas grew by 23,000, while Hispanic enrollments grew by 32,000.
  • In Westchester, Orange and Rockland counties in the New York metropolitan area, black student enrollments grew by 15,000 and Hispanic enrollments grew by 45,000.
  • In New York City, black student enrollments decreased by 113,000 while Hispanic enrollments increased by 68,000.

White student enrollments decreased significantly both upstate (by 125,000) and in the New York metropolitan area (by 113,000).  Nationally, enrollments of black and Hispanic students increased by 7.4 million, between 1994 and 2014 (1990 data is not available) while white student enrollments decreased by 4.2 million.

Overall, school enrollments increased in New York City and its suburbs between 1990-91 and 2014-15, while they decreased in upstate metropolitan areas. Nationally, enrollments increased 12.6% between 1995 and 2014.

In percentage terms, school enrollments nationally were 49.2% white and 42.1% black and Hispanic in 2014-15.

  • Upstate metropolitan areas (66.3% white) and New York City suburbs (55.2% white) had higher percentages of white student enrollments than the nation, while New York City had higher percentages of black and Hispanic students.
  • National level data for 1990 showed a student population of 27.2% black and hispanic students, and 69.4% white students.

By 2014-15 the composition of student populations in schools had changed significantly from the 1990’s, nationally, in upstate New York metropolitan areas and in the New York metropolitan area, with large increases in the percentage of black and Hispanic students. New York City was the only exception – black and Hispanic students decreased as a percentage of the total.

Increasing Minority Student Concentrations in City Schools

In cities in upstate metropolitan areas, black and Hispanic student populations grew substantially as a percentage of the total – by nearly 25% on average.  Black and Hispanic student populations as a percentage of the total grew in suburbs as well, but the growth was much smaller – only 6.4% on average.  In the Orange-Rockland-Westchester portion of the New  York City metropolitan area, the growth of black and Hispanic students as a percentage of the total was about equal in cities and suburbs – 16% on average.

Most upstate cities have student populations that are majority black and Hispanic, while most suburban areas in upstate metropolitan areas have student bodies that are less than 10% black and hispanic.  On average, the gap in black and hispanic student percentages between upstate cities and suburbs grew from 44% to 63%.

Schools attended by Typical Black and Hispanic Students Differ from those attended by Typical White Students

This section compares the racial and ethnic composition of schools attended by typical black and Hispanic students with those attended by white students in 2014-15.  It does so by finding the percentage of black/Hispanic students at schools for a median student in each racial/ethnic group.  Computing the median involves sorting all the students in a group (black/Hispanic or white) in a metropolitan area by the percentage of minority students in the schools that they attend, and finding the percentage of black/Hispanic students in the school attended by a student who is at the exact middle of the sort.  Half of the white or Hispanic/black students would be attending schools with an equal or higher percentage of Hispanic/black students, while half would have an equal or lower percentage.

The data shows that in both cities and suburbs upstate, black and Hispanic students typically attend schools with higher concentrations of black and Hispanic students than do white students.

  • For example, in the Buffalo-Niagara Falls MSA, black and Hispanic students living in cities typically attend schools where 78% of the students are black or Hispanic.
  • White students in those cities typically attend schools whose student bodies are 46% black – a difference of 32%.
  • In other upstate Metropolitan areas, the concentration of black and Hispanic students in city schools ranges from no higher in the city of Binghamton to 20% higher in Utica-Rome.

Within suburban school districts in New York’s metropolitan areas, black and Hispanic students typically attend schools that have higher percentages of black and Hispanic students.

  • In the Rochester metropolitan area, black and Hispanic students living outside Rochester typically attend schools with 24% black and Hispanic students, while white students typically attend schools with 9% black and Hispanic students.
  • In other upstate metropolitan areas, the differences ranged from 2% to 11%.

Since most black and Hispanic students in metropolitan areas live in cities, while most white students live outside them, it is useful to compare the percentage of black and Hispanic students in schools typically attended by black and Hispanic students in cities with the percentage of black and Hispanic students in schools attended by typical white students outside cities.  Here, the contrast is stronger.

  • For example, In the Albany-Schenectady-Troy metropolitan area, a typical black or Hispanic student living in a city would attended a school that had 67.5% black and Hispanic students.
  • In contrast, typical white students living outside Albany, Schenectady and Troy attended schools that had 5.1% black and Hispanic students, a difference of 62.4%.

Differences were large in other upstate metropolitan areas, as well.  The difference in the percentage of black and Hispanic students in city schools attended by typical black and Hispanic students and schools outside cities attended by typical white students was 80.6% in the Rochester MSA, and 73% in the Buffalo-Niagara Falls MSA.

Conclusions

Since the 1954 Brown vs. Board of Education Supreme Court decision, it has been illegal to maintain separate schools for minority students and white students in a school district.  But, efforts to create racial balance in schools in cities and metropolitan areas in New York state and elsewhere have largely been unsuccessful.

In fact, the data shows that over the past 25 years, changes in living patterns have seen large increases in black and Hispanic populations in central cities in New York state, but relatively little change in areas outside them.  As a result, because school districts in New York State often follow city and town boundaries, black and Hispanic students are increasingly concentrated in city schools.

  • School districts in cities in upstate metropolitan areas have seen substantial increases in the percentage of students who are black and Hispanic – from 47.6% to 72.4% between 1990-91 and 2014-15.
  • In contrast outside Upstate cities, the average percentage of black and Hispanic students only grew from 2.8% to 9.2%.

The increasing concentration of black and Hispanic students within cities is not the full explanation of their increasing segregation.  Within cities and outside them, black and Hispanic students are likely to attend schools with higher percentages of black and Hispanic students than are whites.  This is largely the result of residential housing segregation within communities in our metropolitan areas.  As a result, the difference between the racial and ethnic composition of schools typically attended by black and Hispanic students and white students has grown larger – in five of seven metropolitan areas typical black and Hispanic students attended schools that had 65% or more black and Hispanic students, while in five of seven metropolitan areas typical white students attended schools whose populations had 5.1% or less black and Hispanic students.

The growth of racial segregation in New York schools is paralleled by its growth nationwide:  The U. S. General Accounting Office found in 2016 that “Over time, there has been a large increase in schools that are the most isolated by poverty and race. From school years 2000-01 to 2013-14 (most recent data available), both the percentage of K-12 public schools that were high poverty and comprised of mostly Black or Hispanic students (H/PBH) and the students attending these schools grew significantly. In these schools 75 to 100 percent of the students were eligible for free or reduced-price lunch, and 75 to 100 percent of the students were Black or Hispanic.”

Although there are significant potential benefits from schools that are more representative of the diversity of the population as a whole, the barriers to change are substantial.  While New York state has not seen the creation of white enclave school districts carved out of larger majority minority districts, the existing structure of local school districts has a similar effect.

There is no silver bullet that will remedy the growth of segregated schools in New York state, or elsewhere.  Remedies tried in the past, like school busing, have been very unpopular, and have generally failed.  Historically, federal housing policies in the 20th century supported racial segregation.  Similarly, suburban zoning laws and resistance to low and moderate income multi-family housing continue to play a role in preventing minority residents from living in them.  In the current political environment, with an administration in Washington, D. C. that is not supportive of federal intervention to promote integration, segregation in our schools is likely to continue to increase.

_________________________________________________________

Note:  For the Orange-Rockland-Westchester portion of the New York City Metropolitan Area, cities are:  Mount Vernon, New Rochelle, White Plains and Yonkers.




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.




More Regional Diversity but a Larger Racial/Ethnic Divide in New York Schools

This post examines changes in the ethnic and racial compositions of kindergarten through twelfth grade schools in New York State metropolitan areas over the past 25 years.  During that period, the student population, like the general population has become more diverse, with the percentage of students identified as white decreasing, while minority group members, particularly Hispanics, have become a larger proportion of the total population.  But, has the increased diversity of the overall student population been reflected in individual schools?  The data show that although New York’s metropolitan regions are more diverse than they were in the past, the gap in racial and ethnic composition in our schools is larger.

New York Metropolitan Areas and the Nation as a Whole are Racially and Ethnically more Diverse than in 1990

Between 1990 and 2015, the percentage of the national population that identified itself as white decreased from more than 75% to 62%, while Hispanics increased from 9% to 17%.  The number of people who identified as Asian increased from 2.8% to 5.1%. (Source: U.S. Census Bureau, 2011-2015 American Community Survey 5-Year Estimates, 1990 Decennial Census.) Upstate metropolitan areas are much less diverse than the nation as a whole.  Smaller metropolitan areas had very small minority group populations – the Binghamton metropolitan area was 87% white in 2015, while the Utica area was 86% white. Larger upstate metropolitan areas were also less diverse than the nation in 2015.  Buffalo was 78.5% white, while Rochester was 77.4% white.  In contrast, in the New York City metropolitan area, white residents were less than half of the population – 44.4% – while Hispanics were nearly one-quarter of the total.

Student Populations in the United States and in New York Metropolitan Areas are more Diverse than in 1990

The kindergarten through grade twelve population has shown a greater demographic shift than the population as a whole at the national level between the 1990-1991 school year and 2014-2015.  The percentage of students who identified as white decreased by 17.3%, from 69.4% to 52.1%.  The Hispanic population increased by 13.1%, while the percentage of students identified as Asian increased from 3.2% to 5.1%. Source:  National Center for Educational Statistics – Elementary and Secondary Information System.

Compared to the nearly even split between white and minority group students nationally, upstate metropolitan areas are relatively less diverse – particularly smaller metropolitan areas, like Binghamton, Utica and Syracuse.  But even these areas have seen significant increases in the percentage of students who are black, Hispanic and Asian since 1990.

  • Small metropolitan areas, like Binghamton and Utica-Rome, were about 80% white in 2014-2015, and had black and hispanic populations that each comprised less than 10% of the total.  In 1990-1991, these metropolitan areas were more than 90% white.
  • Medium sized metropolitan areas had k-12 student populations that were between 65% (Buffalo) and 75% (Syracuse) white in 2014-2015.  In 1990-91 the percentage of white students was 15% to 20% higher in each of these metropolitan areas.  In these metropolitan areas, the percentage of students who identified as black and Hispanic increased by about 10%.
  • In New York City, in 1990-91, the school population was 18.9% white in 1990-91, 37.6% black and 34.5% Hispanic.  By 2014-15 the white population had decreased to 15.5% of the total, while the black population decreased to 25.1%. The Hispanic population in New York schools increased to 40.9%, while the Asian population grew from 7.8% to 18.1%.
  • Suburban areas around New York City on Long Island, and Westchester, Orange and Rockland Counties had large decreases in the percentage of white students in school populations – more than 20%.  These areas saw large increases in Hispanic students, who increased by 15% to 17% as a percentage of school populations.

In the next section, I look at the question of whether the increased ethnic and racial diversity of student populations in metropolitan areas is associated with decreased racial and ethnic segregation in schools.

The Racial and Ethnic Composition of Schools attended by Whites, Blacks and Hispanics Differed more in 2015 than in 1990

This section compares the racial and ethnic composition of schools attended by typical black and Hispanic students with those attended by white students in 1990 and 2015.  It does so by finding the percentage of black/Hispanic students at a school for a median student in each racial/ethnic group.  Computing the median involves sorting all the students in a group (black/Hispanic or white) in a metropolitan area by the percentage of minority students in the schools that they attend, and finding the percentage of black/Hispanic students in the school attended by a student who is at the exact middle of the sort.  Half of the white or Hispanic/black students would be attending schools with an equal or higher percentage of Hispanic/black students, while half would have an equal or lower percentage.

The difference between the percentage of minority students in schools attended by typical white students compared to typical black/Hispanic students increased between 1990-1991 and 2014-2015, with one exception (New York City).  Despite the increase of Hispanic and black students from less than 10% (18% in Rochester) to between 20% and 30% of the student population in upstate metropolitan areas, typical white students attend schools with Hispanic/black populations that make up about 5% of the total.  In contrast, black and hispanic students typically attended schools in 2015 where black and Hispanic students make up more than 50% of the population.

Also of concern is the fact that the racial/ethnic gap between schools that typical white and Hispanic/black students attend increased between 1990-1991 and 2014-2015.

 

  • In the Albany-Schenectady-Troy metropolitan area, in 1990-1991, typical white students would have attended schools with 2% black and Hispanic students. Typical black and Hispanic students attended schools with 38% black students in that year.
  • In 2014-2015 typical white students attended schools with 5.8% black/Hispanic students, while typical black and Hispanic students attended schools with 55% black/Hispanic students.
  • The gap between the schools attended by typical white and typical black/Hispanic students increased from 36% to 49%.

Other upstate metropolitan areas had increases in the gap between white and black/Hispanic percentages as well:

  • In the Binghamton MSA, in 1990-1991 median white students attended schools that were 1.6% black/Hispanic while median black and Hispanic students attended schools that were 10.4% black/Hispanic.  In 2015, whites typically attended schools that were 4.7% black/Hispanic, while blacks and Hispanics typically attended schools that were 31.4% black/Hispanic.  The gap increased from 8.8% to 26.7%
  • In Buffalo-Niagara Falls, in 1990-91 median white students attended schools that were 1.4% black/Hispanic. Typical black/Hispanic students attended schools that were 54.9% black/Hispanic. In 2014-15 typical white students attended schools that were 5.3% black/Hispanic, while median black and Hispanic students attended schools that were 63% black/Hispanic. The gap increased from 53.3% to 57.7%
  • In the Rochester MSA in 1990-1991, typical white students attended schools that were 4.2% black/Hispanic, while black and Hispanic pupils attended schools that were 67.3% black/Hispanic.  In 2014-2015 the comparable numbers were 9.2% and 82.7%.  The gap increased from 63.1% to 73.5%
  • In Syracuse in 1990-1991 median white students attended schools that were 1.6% black/Hispanic, while typical black and Hispanic students attended schools that were 43.4% black/Hispanic.  In 2014-15 the percentages were 5.5% and 52.7%.  The gap increased from 41.8% to 47.2%
  • In Utica-Rome, in 1990-1991, typical white students attended schools that were 1.1% black/Hispanic, while median black and Hispanic students attended schools that were 23.3% black/Hispanic.  In 2014-15 the numbers were 3.3% for white students and 61.7% for black and Hispanic students.  The gap increased from 22.2% to 58.4%

Suburban counties in the New York City Metropolitan area saw similar changes:

  • In Nassau and Suffolk Counties in 1990-1991, typical white students attended schools at which black and Hispanic students made up 5.8% of the population.  In 1990-91, black and Hispanic students attended schools which were 50% black/Hispanic.
  • In 2014-15, white students typically attended schools that had 14.5% black/Hispanic students.  Typical Black/Hispanic students schools that were 64.8% black/Hispanic
  • The racial/ethnic gap increased by 6.1%.
  • In Westchester, Orange and Rockland Counties, in 1980-81, typical white students attended schools that were 7.1% black/Hispanic, while typical black/Hispanic students attended schools that were 49.9% black/Hispanic.
  • In 2014-2015, in those counties, typical white students attended schools that were 19.4% black/Hispanic, while typical black/Hispanic students attended schools that were 71.6% black/Hispanic.
  • The racial/ethnic gap in Westchester, Orange and Rockland counties increased by 9.4%.

New York City differed from other locations in New York state in that the differences in the racial/ethnic composition of schools attended by white students and black/Hispanic students has stayed constant at about 60% in 1990-91 and 2014-15.

Conclusions

Although our nation is often characterized as a melting pot that has absorbed many ethnicities and races, black/Hispanic students increasingly attend schools that are primarily black/Hispanic, while white students continue to attend schools that are overwhelmingly white.  Over the period between 1990-1991 and 2014-15, the gap between the schools typically attended by whites and those attended by blacks and Hispanics increased – in schools attended by median black and Hispanic students, the percentage of black and Hispanic students increased more than it did in schools attended by median white students.

This is important because black and Hispanic residents and whites have relatively little interaction in their neighborhoods, and in the schools that their children attend.  Cities and the schools within them continue to see large decreases in white populations.  City minority populations are stable or increasing, while suburban communities remain overwhelmingly white.  Housing segregation is reinforced by the fact that average incomes of blacks and Hispanics are substantially lower than white residents, so that relatively high suburban housing costs are a barrier to suburban housing choices.

Economic and residential separation is strongly rooted in New York and the United States. Causes include discriminatory government housing policies and non-governmental practices that denied black people access to home ownership in the growing suburbs of the post-World War II era,  historically lower average levels of minority educational attainment, and lower black and Hispanic incomes at the same levels of educational attainment as whites.

The concentration of minority students in schools with high percentages of minority students has negative consequences for minority students, largely because these schools typically have high concentrations of low-income students.  Economically disadvantaged students who attend schools with relatively few disadvantaged students do better on evaluations of student performance than those who attend schools with high concentrations of disadvantaged students (see this, and this).   The fact that black and hispanic students increasingly attend schools with high concentrations of minority students should be of concern.

Because white students in New York typically attend schools that have few black and Hispanics attending them, they do not gain the benefit of exposure to other cultures. Researchers have found that diverse schools promote reductions in levels of racial and ethnic prejudice, stereotyping and fears of “others” and that all students, including white students attending diverse schools, show “higher achievement in mathematics, science, language and reading.”

My next post will compare changes in minority and white student populations in cities and suburbs in New York state.




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.

picture1

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

picture2

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).

picture3

(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

picturec1

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

pictured1

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.

picturee1

picturef1

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.

pictureng

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.

picture1ss

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

picture123345

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 

picture1fff

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.

___________________________________________________
[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]

640

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.

rustbelt2

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.

________________________________________________________

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/

 




A $15 Minimum Wage for New York: Benefits and Risks

Recently, a friend and colleague from the time when I worked at Empire State Development suggested that I take a look at Governor Cuomo’s proposal to raise New York’s minimum wage to $15 from $9.00.  Like others, I’m sure that he wanted to cut through the competing claims about the impact of the proposed increase.

A columnist for the Albany Times-Union, Fred LeBrun, expressed the confusion felt by many, writing, “The truth is I don’t really know what the impact will be. I’m not sure anybody does. Predictions vary wildly. Nor are the Cuomo administration and the Democratic Assembly making any serious effort to find out.”  The reason for LeBrun’s confusion and frustration is that there is no certain answer to his question, nor can there be at this point in time, given the complexity of the factors involved in estimating the benefits of a minimum wage increase, and the lack of solid data available at the state level.

As with many political issues, there are sharply divergent perspectives to the costs and benefits of raising the minimum wage.  A well known Albany think tank, the Empire Center for Public Policy, released a report late last fall, “Higher Pay, Fewer Jobs,” written by Douglas Holtz-Eakin and Ben Gitlis of the American Action Forum, the policy arm of the American Action Network, a group that has provided substantial support for Republican candidates for Congress.  The report presents three models of the impact of the proposed increase in the minimum wage to $15, and finds that the proposal would reduce employment in the state by “at least 200,000 jobs, with proportionately larger employment decreases in upstate regions.”  The report also estimates that the proposal would increase wage earnings by $4.6 billion.

On the other side, the Center for Wage and Employment Dynamics (CWED), at the Institute on Labor and Employment at the University of California, Berkeley issued a report, “The Effects of a $15 Minimum Wage in New York State,” by Michael Reich, Sylvia Allegretto, Ken Jacobs and Claire Montialoux.  CWED has received funding from the Fiscal Policy Institute, a union funded think tank.  That report concluded that “a $15 statewide minimum wage would generate a 23.4% average wage increase for 3.16 million workers in the state, with a net value of $14.4 billion and would create an increase in jobs of 3,178.

Finally, Governor Cuomo, through the State Department of Labor issued a report in support of his proposal entitled “Built to Lead – Analysis: Raising New York’s Minimum Wage to $15.”  The report claims a benefit from increased wages of $15.7 billion and argues that, “A review of 70 studies on minimum wage increases found no discernible negative effect on employment.”

Problems Estimating Number of Employees Affected

Perhaps a good place to begin understanding how difficult it is to understand what impact an increase in the minimum wage might have is by looking at the question of how many people might be affected by the proposed change.  This is important, because the number of people affected impacts both the amount of wage benefits received in aggregate, and the number of people who might be affected by layoffs that could result from the proposed increase.  Here, there are differing estimates.
• Governor Cuomo’s report argues that 2.4 million people would benefit from a minimum wage increase.
• The Empire Center report estimates 3.1 million workers would be directly affected by the increase.
• The CWED report estimates that 2.4 million workers would be directly affected, with an additional 1.2 million indirectly affected.

How can there be such a large disparity in the estimates of the number of people affected?  The answer is that researchers seeking information about the number of people who would be receiving less than $15 per hour at the time of the proposed increase could not find data that directly answers the question, and had to develop estimates using other data that does not directly measure wage distributions at the state level.  In both cases, the authors used data from the Census Bureau’s American Community Survey, and because they used different techniques to estimate the percentage of the employed population from the available data, they arrived at significantly different answers.

Problems Estimating Possible Job Losses

The bigger problem associated with evaluating the effects of an increase in the minimum wage involves estimating the impact of the change on employment.  Until about 20 years ago, there was near unanimity among economists that there was a trade-off between employment and minimum wage increases, particularly for young and low skilled workers.  For example, a number of studies found that for a 10% increase in the minimum wage, teenage employment decreased by 1%-3%.  For adult workers, the impact was estimated to be smaller – perhaps 1% for a 10% increase.  Since almost 90% of minimum wage workers are 20 years old or older, the largest impact of a minimum wage increase is on adult workers, even considering the fact that a larger portion of teenage workers are paid at the minimum wage rate.

From the perspective of these studies, a minimum wage increase of $9 to $ 15, or 60%, as has been proposed by the Governor, would have a relatively large negative impact on jobs. In New York’s case, with roughly 9,000,000 workers, about 550,000 could be expected to lose their jobs, if the estimate is correct.

The report from the Empire Center presents three study models, one which is consistent with an analysis by the Congressional Budget Office, that estimates a loss of 200,000 jobs, a second by two economists, Jonathan Meer and Jeremy West, that estimates a loss of 432,500, and a third by economists Jeffrey Clemens and Michael Wither, that projects a loss of 588,800 jobs.

How is it possible that the Center for Wage and Employment Dynamics could conclude that increasing the minimum wage could result in a small increase in jobs?  The answer is that some more recent research has found no significant employment effect from increases in the minimum wage.  For example, Alison Wellington in “Effects of the Minimum Wage on the Employment Status of Youths: An Update.” found that a 10% increase in the minimum wage reduced teenage employment by only 0.6%.  In 1992, David Card and Alan Krueger studied the impact of a minimum wage increase in New Jersey on fast food restaurants by comparing their employment with those in nearby Eastern Pennsylvania and found that the wage increase was associated with slightly increased employment.  They also examined a set of more recent studies of a 1988 increase in the California minimum wage and the 1990 increase in the federal minimum wage and found no impact.  Subsequent studies have shown mixed results.  Some have shown employment decreases with increases in the minimum wage, others have not.

A better approach than providing a single estimate of job losses associated with increasing the minimum wage would recognize a variety of possible outcomes.  The Empire Center study does this to an extent, by presenting the outputs of several models.  But the study only presents one set of possible outcomes, reflecting the views of economists who believe that minimum wage increases are associated with job losses.  And, while the Empire Center presented a single estimate for job losses for the approach used by the Congressional Budget Office, the CBO itself said that a range of outcomes is possible.  In its study of a possible federal minimum wage increase from $7.25 to $10.10, it predicted a very slight job loss to one million jobs, with a central point of 500,000.  From my perspective, the best approach would recognize the uncertainty of any job loss estimate, and present a broader range of possibilities.

So, unfortunately for my friend, and for Fred LeBrun, who wanted to know what the impact of an increase to the minimum wage would be, there is no definite answer.  We do know that the proposal does have a positive economic impact on workers affected – estimates range from about $5 to $15 billion.  And, we know that it is not true that most beneficiaries would be teenagers flipping hamburgers at fast food outlets – in fact, they represent a small minority of workers who would be affected.  What we don’t know is whether there would be a significant trade off in lost jobs.

But, there are some significant reasons to be cautious about the impact of a proposal as large as the one that has been proposed by Governor Cuomo.  Many economists are concerned about the size of the proposed increase – an increase from $9 to $15 is much larger than previous increases, and is more likely to impose worker dislocations than a smaller increase – to $12 for example. Alan Krueger, former Chair of President Obama’s Council of Economic Advisors, and the author of the New Jersey study that found no negative impact of a minimum wage increase, wrote,

But $15 an hour is beyond international experience, and could well be counterproductive. Although some high-wage cities and states could probably absorb a $15-an-hour minimum wage with little or no job loss, it is far from clear that the same could be said for every state, city and town in the United States…Although the plight of low-wage workers is a national tragedy, the push for a nationwide $15 minimum wage strikes me as a risk not worth taking”