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.

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




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 Income Gap between Men and Women: 2015 vs. 1970

Since 1970,  inflation adjusted wage income growth has been almost nonexistent – only five percent over the 45 year period ending in 2015.  Income change in metropolitan areas in New York State has differed little from the nation.  Rochester and Buffalo were two exceptions – both had lower median real wage incomes in 2015 than in 1970.  Because of the declines in upstate’s two largest metropolitan areas, upstate real wage incomes overall were 5% lower in 2015 than they were in 1970.

In an earlier post examining inflation adjusted wage income changes in New York State Metropolitan areas, I found that although incomes have stagnated since 1970’s, education and age have become increasingly important in determining the changes that have occurred.  Overall, people aged between 25 and 29 with high school educations or less had median wage incomes in 2015 that were 38% lower than in 1970.  College graduates aged 50 or older had income gains averaging 6%

In a second post, I examined the gap in real wage incomes between black and white residents and found that the gap had not decreased over the 45 year period.  In fact, in upstate metropolitan areas, the gap was somewhat larger in 2015 than it was in 1970.

This post examines changes in inflation adjusted wage income as they affect men and women in New York State and the nation.  While real wages have been relatively stable since 1970,  wage incomes for men, particularly younger men with high school educations or less, have shown sharp declines, while those of women have substantially increased.  Nevertheless, a wage gap between the sexes remains.

The Data

The Census Bureau defines personal wage income as total pre-tax wage and salary income – that is, money received as an employee – for the previous year. Annual wage income includes the amount of wage income received by all people having wage income in a year, including those who worked full or part-time, and those who worked only part of a year as well as those who worked all year

Data, as in my earlier posts, is from Public Use Microdata samples made available by the U. S. Census Bureau (Steven Ruggles, Katie Genadek, Ronald Goeken, Josiah Grover, and Matthew Sobek. Integrated Public Use Microdata Series: Version 6.0 [dataset]. Minneapolis: University of Minnesota, 2015. http://doi.org/10.18128/D010.V6.0) Public Use Microdata Sample files (PUMS) are a sample of the responses to the American Community Survey and the Decennial Census and include most population and housing characteristics.  Because the data is from samples of households in metropolitan areas, sampling error is possible, particularly for smaller metropolitan areas.

Inflation Adjusted Wage Income – 1970

In 1970, real wage incomes of men were substantially higher than those of women.

In upstate metropolitan areas, women’s median wage incomes averaged between 40% and 50% of those of men.  Income differentials between men and women upstate were near the national average of 44%.  In the New York City metropolitan area, median wage incomes for women were higher, but were still only about 62% of those for men.  This is particularly significant, because the data here only reflects those women who reported earning wages during the year. The lower median incomes of female wage earners were not related to the fact that less than half of women were in the labor force in that year.

  • Male residents of the Rochester metropolitan area had the highest median incomes in 1970 – almost $60,000, which was substantially higher than the national median for men – $48,013.
  • In that year, the real median real wage income of men in the New ‘York City metropolitan area – $48,000  – only exceeded that in the Utica-Rome metropolitan area – $46,820.

For women, the picture was different – the real median income of women in the New York metropolitan areas was $29,500 – substantially higher than in any upstate metropolitan area or nationally.

Education

Here again, median wage incomes were strongly related to educational attainment, with college graduates earning at least 50% more than those with less than those who have less than four years of high school in most cases. For women, the differences in median wage incomes were even greater than for men — the median wage income of young women aged 25-34 was only $14,016, while that for those with 4 years of college was $33,698.  Because the effect of education on women’s income was stronger than for men in 1970, women and men with less education generally had larger median income gaps than those with more education.  But, even for women with four years of college, median incomes were substantially lower than for men – ranging from 40% to 60% of median male incomes at the same level of education.

In the New York City metropolitan area, the same relationships were present.  Women had wage incomes that were substantially lower than men, and less educated workers had much lower incomes than higher income workers.  At all levels, the gap in incomes between men and women was smaller in the New York City metropolitan area than it was in upstate metropolitan areas.   The difference between upstate metros and the New York City metropolitan area was particularly large for less educated women.

  • Women with less than four years of high school in the New York City metropolitan area had 55% to 60% of the median income of men with the same level of education, while in upstate metropolitan areas ranged from 33% to 47% of men’s median incomes, depending upon age.

For men, the picture was different – less educated male residents of upstate metropolitan areas had higher median incomes than those in the New York metropolitan area in 1970.  For college educated men, incomes were similar.

Inflation Adjusted Wage Income – 2015

By 2015, the income gap between men and women was much smaller than in 1970, but was not gone.  As in 1970, the income gap was smaller in the New York metropolitan area than it was in upstate metros.  But, the gap between men’s and women’s incomes was much smaller in both regions.

  • The median wage income for women upstate was 76.1% of the men’s median, while in New York City, the comparable percentage was 80%.
  • Two upstate metropolitan areas had the same gender wage gap as the New York City metropolitan area – Albany-Schenectady-Troy and Binghamton.

Education and the Gender Wage Gap

Though there has been progress in wage income equity since 1970, the progress has been uneven.

  • In upstate New York metropolitan areas, women with four or more years of college education have come closest to achieving equity with men – attaining median incomes of between 70% and 80% of men’s median wage incomes.
  • In contrast, women with less than four years of high school education have median wage incomes that are between 47% and 68% of men’s median incomes.
  • And, median incomes for young men and women with less than four years of high school in upstate metropolitan areas were very low in 2015- only $19,000 for men, and $9,450 for women under 35 years old.

In 2015, for men under 35 in upstate metropolitan areas, the median wage income for those with four or more years of college was $45,000 compared with $19,000 for those with less than four years of high school.  For women, the comparable numbers were $38,000 and $9,450.

In the New York metropolitan area the median wage gap between women and men was 20% – the median wage income for women in the metropolitan area was $40,000 compared with $50,000 for men.  For people with less than four years of high school, median wage incomes were more equal for men and women in the New York City metropolitan area in 2015 than they were in upstate metropolitan areas.

High levels of education were associated with large wage premiums for both women and men – those with four or more years of college had median incomes that were at least three times those with less than four years of high school education for all age groups.

The income gap between those with four years or more of college education and those with high school education or less has increased sharply since 1970.  The difference between median incomes for men with a high school education or less was 60% less than for men with four or more years of college in 1970.

By 2015, the gap had increased to 142%.  For women, the gap was 70% in 1970 and 155% in 2015.  This increase in the wage gap reflects the greater inequality of incomes in our society in 2015 compared to 1970.

Change in the Gender Gap Overall

Overall, the median wage gap between men and women decreased substantially between 1970 and 2015 – by 32% in upstate metropolitan areas and by 18% in the New York City metropolitan area.  While the decrease in the New York city area was smaller than that upstate, the New York City had a smaller wage gap than upstate metros in 1970, and continued to have the smallest gap in the state in 2015.

Upstate metropolitan areas and the New York metropolitan area also had smaller wage income gaps than the median for metropolitan areas nationally in 2015.

  • Nationally the difference between men’s and women’s median wage incomes was 29% in 2015.
  • For upstate metropolitan areas, the difference was 24%,
  • For the New York metropolitan area, the difference was 20%.

Inflation Adjusted Wage Income Gains and Losses – 2015 vs. 1970

Real median wage incomes have followed sharply different paths for men and women since 1970.  In most metropolitan areas, men’s median wage incomes have declined.  In a few, like Rochester, Binghamton, and Utica, the declines have been significant – 15% or more.  For women, the path has been up.

Median incomes for women were up sharply in 2015 compared with 1970.

  • Nationally, and in upstate metropolitan areas, the increase was slightly more than 50%.
  • In New York City, starting from a higher base in 1970, the increase was 35.5%.
  • Women’s median wage incomes were far lower in 1970 than men’s, and the gains made by women have not been large enough to erase the wage gap that existed.

In my earlier posts, I showed that inflation adjusted median incomes for people with less education were much lower in 2015 than they were in 1970.

  • The median income for those with high school educations or less was 38% lower, compared to 21% lower for those with four years of college or more.
  • In contrast, workers over fifty years old, at all educational levels had median incomes in 2015 that were close to those in 1970.

The table above shows the impact of education and age upon the difference in median wage incomes for men and women between 1970 and 2015.  It shows that for both genders, young people have fared less well than older people and that less educated workers have fared worse than more educated workers.

For young men, the decline in real median incomes between 1970 and 2015 is very troubling.

  • Young people with less than four years of high school education had real median incomes in 2015 that were 44% lower in the New York metropolitan area than in 1970, while in upstate metropolitan areas, median incomes were 53% lower.
  • The median income for men under 34 with some college experience was 37% lower in upstate metropolitan areas in 2015 than in 1970, while in the New York metropolitan area, the median real income was 43.2% lower in 2015.
  • The median income for young  workers with four or more years of college in upstate metropolitan areas was 24% lower in 2015 than 1970, while in the New York metropolitan area the decrease was 2%.

The income premium for those with four or more years of college remained substantial for young men, but in upstate New York, median incomes, even for college educated young people were substantially lower in 2015 than in 1970.

  • For less educated workers, the decline in median incomes extends to older workers as well, ranging from 35% to 45%, from 1970 to 2015.
  • But, workers with four or more years of college aged 35 or older saw only small decreases in median incomes.
  • In New York City, these workers had significant median income gains – 15% for those aged 35 to 49, and 24% for those from 50 to 64.

Less educated women – particularly those with less than four years of high school were not immune to the declines in median real incomes between 1970 and 2015.  losses ranged from 6% to 32%, and were not strongly related to age.  In fact, the gains that this group made compared with men in wage income simply reflected the declines in real wage income were smaller for women with low levels of educational attainment than they were for men.

In upstate metropolitan areas, women with four years of high school or more education had median income gains in most cases, with generally greater gains at higher educational levels.  In the New York metropolitan area, however, women in most age groups who had less than four years of college had lower median incomes in 2015 than in 1970.

The data points to the conclusion that but for the increase in the percentage of wage earners with four or more years of college, wage earners in metropolitan areas would have had much lower median wage incomes in 2015 than they did in 1970.  Clearly, the labor market has substantially less demand for workers with limited educational backgrounds than it did in 1970.

The erosion of median incomes of workers in the 25-34 year age group, especially in upstate metropolitan areas, should be of particular concern, because it may point to a long-term trend to lower wage incomes for workers who were in that age group in 2015.  As the table above shows – the performance of median incomes for men and women aged 25-34 between 1970 and 2015 was substantially weaker than it was for older workers.

  • The inflation adjusted median income of male workers between 35 and 64 in upstate metropolitan areas increased by 7.4%, while the median for those aged from 25-34 decreased by 29%.
  • The median income of women between 35 and 64 in upstate metropolitan areas was 90% higher in 2015 than in 1970.  For women aged 25-34 the increase was 40%.

Conclusions

The Pay Gap Between Men and Women

The narrowing of the wage gap between men and women is good news, although the fact that women’s median wage incomes continue to be lower than men’s is not.  In 1970, the median wage income for women was less than half of men in upstate metropolitan areas, and about 60% of that for men in the New  York metropolitan area.  In 2015, the gap between median incomes for men and women was between 20% and 30% in upstate metros, and 20% in the New York metropolitan area.

By controlling for education and age, the data shows that women with less educational attainment face larger income gaps than men, particularly upstate, where women with less than four years of  high school earn between 48%  and 68% of what comparably educated men in the same age groups earn.  Even so, the gap between college educated men’s and women’s real incomes ranged from 15% to 35%.

The data used in this analysis does not, in itself give explanations for the continuing wage gap.  While the effect of age and educational levels are controlled for here, the analysis does not compare people with the same jobs in the same industries to determine the extent of differences between women’s and men’s incomes.  If women participate more in lower paying occupations with similar educational qualifications than men, that could account for some of the difference in wage incomes.

The data from this study is consistent with other studies that do compare incomes of men and women in the same occupations.

This chart, reprinted from “The Simple Truth about the Gender Pay Gap (Spring 2017), published by the American Association of University Women, shows that weekly earnings of men in the same occupations as women are ten to twenty percent higher than women’s.  So, it is reasonable to ask, as in the case of the lower incomes of black/African-American workers, whether existing prohibitions against wage discrimination are being effectively enforced.  It is important to note that discrimination may or may not be explicit and intentional – but may also reflect the relative absence of women in high level management positions who could offer the equivalent of  “old boy networks” to help women get good jobs and higher pay.  Thus, enforcement could be very difficult.

A recent article in The Atlantic, “How Do We Close the Wage Gap in the U.S.?” by Bourree Lam suggests some solutions.  One part of the gap is believed to be caused by what is called “the motherhood penalty.”  Lam argues that, “There are two ways to go about fixing this huge part of the gender wage gap. The first is for companies or the government to implement policies that enable women to be both moms and workers, such as paid family leave and supported childcare. But there’s also a cultural shift that needs to happen: The assumption that mothers are not as good at their jobs, not deserving of promotions, or won’t work as hard is discrimination. Employers need to do their part in seeing women who are mothers as valued as employees.”

The second major part of the solution, according to Lam is pay transparency.  The Obama administration, in its last year proposed a regulation requiring “companies with 100 employees or more to report to the federal government how much they pay their employees broken down by race, gender, and ethnicity.”  Unfortunately, this action was revoked by President Trump, in one of his first executive orders this year. Trump’s executive order also revokes other worker protections contained in Obama’s regulation.

Large Decreases in Less Educated Workers’ Real Income 

Men and women with four years of high school education or less have seen large decreases in median real income since 1970.  The decrease is particularly severe for men with high school educations.

  • Men with less than four years of high school saw median income losses between 1970 and 2015 of between 35% and 53%.
  • Men under 50 years old lost between 26% and 42% of real income.
  • Women under 50 years old lost between 23% and 33% of real income.
  • In the New York metropolitan area, women with four years of high school lost between 22% and 40% of income.

At the same time, men with four years of college did not see losses as large  as those with lower educational attainment, and gained real income in some cases:

  • In metropolitan areas in upstate New York, median income declines for men under 35 with four years of college were less than half of the losses of people with less than four years of high school (25% vs 53%).
  • Older men in upstate metros saw small income losses – 5% to 8%.
  • Male residents of the New York metropolitan area saw gains in most cases, ranging from 15% to 24% for workers 35 years old or older.
  • Women with four or more years of college saw significant income gains, ranging from 11% to 66%, but started from much lower income levels in 1970 than did men.

The large real income losses of workers with low levels of educational attainment contrast with the better performance of median incomes for workers with more education.  This is one cause of the greater income inequality that has developed in the United States since 1970.

In earlier posts, I have described the loss of manufacturing employment in the rust belt, and its consequences for worker earnings.  The loss of millions of manufacturing jobs in the rust belt has resulted in the substitution of jobs in service industries that are on the average lower paying.  Unlike the manufacturing jobs that were lost, most service employment is not unionized, so workers have less negotiating power than more unionized manufacturing employees.

The causes of manufacturing employment losses have been debated in the political arena, but most researchers have concluded, as I did here, that the great majority were victims of automation and process improvements, not imports. But both increased automation in manufacturing production and importation of manufactured products resulted from the desire of owners and managers of manufacturing businesses to cut costs to gain or retain market share in competitive marketplaces.  Since labor has been a major element of manufactured product costs, the substitution of automation and lower cost foreign labor has been an attractive strategy to reduce costs.

To date, service employment has continued to grow in the United States, in the rust belt, and in New York State.  But, if anything, labor costs are a larger share of service industry costs than in manufacturing industries.  As a result, high labor costs per service unit make local labor employment vulnerable to substitution by lower cost labor elsewhere or by automation.  In many cases, services businesses have been unable to find substitutes for local labor that work well enough to prevent service employment growth, but in the future, technology may make more substitution possible.

Government could play a positive role, by taking regulatory actions that help low income workers, such as increasing the minimum wage and facilitating union representation of employees.  Though actions that increase labor costs might encourage substitution of automation or foreign labor for local labor, most studies show that the benefits of government assistance are likely to outweigh potential employment losses, as long as the actions do not dramatically increase unit costs.

Declines in Real Incomes of Young Workers

One of the more significant findings of this research was the disparate impact of real income decreases on workers under 35 years old.  This problem was particularly pronounced for male workers, particularly those with high school educations or less.  Overall, men between 25 and 34 had 21% lower real wage incomes in 2015 than they did in 1970.  Young male workers in at all educational levels, except for those with four or more years of college, had median real incomes that were more than 40% lower overall than in 1970.  The income losses extended to young women in the New York Metropolitan area, who also saw large real income losses compared with 1970.

A recent working paper by Fatih Guvenen, Greg Kaplan, Jae Song, and Justin Weidner of the Federal Reserve Bank of Minneapolis , “Lifetime Incomes in the United States over Six Decades,” presents two important findings:  First, “From the cohort that entered the labor market in 1967 to the cohort that entered in 1983, median lifetime income of men declined by 10% to 19%.  We find little to no rise in the lower three quarters of the percentiles of the male lifetime income distribution during the period…For women, lifetime income increased by 22%-33%, from the 1957 to 1983 cohort, but these gains were relative to very low lifetime incomes for the earliest cohort…Second, we find that inequality in lifetime incomes has increased substantially in each gender group.  However, the closing lifetime gender gap has kept overall lifetime inequality virtually flat.  The increase in inequality within gender groups is largely attributed to an increase in increase in inequality at young ages.”

The finding in my research that the 25-34 year old age group in 2015 had much lower incomes than older workers leads to the conclusion that the trend towards increased lifetime income inequality noted in young age cohorts ending in 1983 by Guyvenen, Kaplan, et. al. is likely to continue.  Options available to government to counter this negative trend could involve the Fed continuing to provide low federal fund rates, reducing the cost of borrowed capital, or stimulative federal fiscal policies that focus on things like infrastructure projects that could employ large numbers of construction workers, or increased income supports for low-income workers.  However, stimulative monetary or fiscal policy could, if used to excess, lead to inflation that would in itself erode workers’ purchasing power.

Robert Samuelson argues in “Trumps Low Growth Trap,” “We have entered a new era of low economic growth and high political disappointment. Our democratic system requires strong-enough economic growth to raise living standards and support activist government. These expectations, present in most advanced democracies, are no longer realistic, because the global economy has changed in ways that reduce growth….

Quoting an article by Ruchir Sharma that appeared in Foreign Affairs, he points out, ““The causes of the current slowdown can be summed up as the Three Ds: depopulation, deleveraging and deglobalization. Between the end of World War II and the financial crisis of 2008, the global economy was supercharged by explosive population growth, a debt boom that fueled investment and boosted productivity, and an astonishing increase in cross-border flows of goods, money and people. Today, all three trends have begun to sharply decelerate: families are having fewer children . . . , banks are not expanding their lending [as before] . . . , and countries are engaging in less cross-border trade.”

President Trump’s argument that by implementing tax cuts and regulatory relief, economic growth would increase from the current rate of slightly over two percent to four percent is simply unrealistic, given the headwinds that it faces.  And, anti-trade and immigration policies could actually slow economic growth.

Greater income inequality threatens the existence of a large and secure middle class, and creates greater economic and social distress for those whose incomes are below the median.  If the bottom half of the income distribution includes more people whose incomes are towards the extreme low-end of the income distribution, government will be faced with the choice of paying larger fiscal costs to support those whose wages are inadequate to provide a reasonably secure life, or of ignoring the needs of those who lack resources.   Recent political history also shows that people who sense that their well-being is declining are vulnerable to political appeals based on resentment to “undeserving” beneficiaries of government assistance, and towards other factors, such as international trade or immigration, that may be portrayed as the primary causes of income declines, despite the fact that they are not.

Reasonable policy options to counter the wage declines faced by less educated workers involve trade-offs like potentially increased inflation and greater substitution of automation and foreign labor for domestic workers.  Approaches that address claimed causes like immigration and trade that have played at most a small role in the decreases in income will be ineffective and have potentially large negative consequences.  As a result, they will increase cynicism beyond already high levels.  Leaders should not argue that “magic bullet” solutions exist.  Instead, they should promote reasonable expectations and acknowledge both benefits and costs.




The Persistent Gap Between White and Black Incomes in New York

There has long been a substantial gap between the incomes of white Americans and those who describe themselves as African/American or black.  As early as 1964, with the enactment of the Civil Rights Act, the Federal and state Governments began passing laws aimed at preventing discrimination in the workplace.  Has New York seen significant progress in reducing wage inequality between blacks and whites since 1970?  This post examines the changes in wage incomes of black and white New Yorkers between 1970 and 2015, and considers the impact of education levels on incomes.  This analysis does not consider the experience of other non-white groups, because small sample sizes would not yield reliable results.

The Census Bureau defines personal wage income as total pre-tax wage and salary income – that is, money received as an employee – for the previous year. Annual wage income includes the amount of wage income received by all people having wage income in a year, including those who worked full or part time, and those who worked only part of a year as well as those who worked all year.

Data, as in my last post, which examined the relationship between age, education and inflation adjusted wage income is based on Public Use Microdata Samples made available by the U. S. Census Bureau (Steven Ruggles, Katie Genadek, Ronald Goeken, Josiah Grover, and Matthew Sobek. Integrated Public Use Microdata Series: Version 6.0 [dataset]. Minneapolis: University of Minnesota, 2015. http://doi.org/10.18128/D010.V6.0.) Public Use Microdata Sample files (PUMS) are a sample of the actual responses to the American Community Survey and the Decennial Census and include most population and housing characteristics.  Because the data is from samples of households in metropolitan areas, sampling error is possible, particularly for smaller metropolitan areas.

This post compares inflation adjusted wage income differences between African-American and white New Yorkers in Upstate metropolitan areas and in the New York City Metropolitan area.  Since upstate New York has not historically been racially diverse, relatively few black/African-American wage earners are in the Census sample.  For that reason, data from the Upstate Metropolitan areas (Binghamton, Buffalo, Rochester, Syracuse, and Albany-Schenectady-Troy) examined in my earlier post on real wage income changes has been combined.  Even so, only 657 respondents identified themselves as black or African American in 1970 – 4.7% of the population of those metropolitan areas.  By 2015, the percentage of respondents identifying themselves as black or African-American in Upstate Metropolitan areas had increased to 8.6%.

The population of the New York City Metropolitan area has been consistently more diverse than that upstate. As a result, black/African-American residents comprised 21.5% of the sample in 2015, compared with 14.3% in 1970.

Differences in Real Wage Income – No Substantial Progress

The table above shows two significant things.  First, inflation adjusted wage income increased  between 1970 and 2015 for both white and African-American residents of the New York City Metropolitan area, but declined for blacks/African Americans in Upstate metropolitan areas.   White residents of upstate metropolitan areas saw stable incomes over the period.

Second, the percentage difference in incomes between whites and African-Americans/blacks decreased from 47% to 35% in the New York City Metropolitan area, but increased from 40% to 50% in Upstate metropolitan areas.

The data shows that overall, adjusted wage incomes did not substantially converge over the 45 year period. In Upstate metropolitan areas, the gap increased from 40% to 50%, while in New York City, white residents had more than one third more wage income than blacks/African-Americans in 2015.

Educational Disparities Remain

In my earlier post, the data showed that wage earners with more education fared better than those with less.  People with high school educations or less saw significant real declines in wage incomes over the 45 year period, in many cases.  But, because the educational backgrounds of New York residents have substantially improved, fewer people today have high school educations, or less, than in 1970.  This has offset some of the income decrease that would have otherwise occurred.

This data offers several important findings.  First, in 1970, in most cases people with less than four years of high school education were the largest single group – both in the New York City metropolitan area and Upstate.  The only exception was that the percentage of people with four years of high school was slightly larger than those with less than four years for white wage earners in Upstate metropolitan areas.  For black/African-American residents, more than half of New York City Metropolitan area wage earners had less than four years of high school, while upstate, nearly two-thirds had less than four years.

Second, in 1970, those with four or more years of college comprised less than 20% of the total.  For black/African-Americans, only 6% in the New York City metropolitan area, and 4% upstate had four or more years of college.

By 2015, the situation had changed dramatically.  Seventy percent of white wage earners in the New York Metropolitan area had some post-secondary education. More than half had four or more years of college.  In Upstate metropolitan areas, 67% had some post-secondary education, while 40% had four or more years of college.  For black/African-American wage earners in the New York City Metropolitan area, 58% had some post-secondary educational experience, while 31% had four or more years of college.   In Upstate metropolitan areas, 51% had had some post-secondary experience, while 19% had four or more years.

Third, by 2015, the percentage of New York City Metropolitan area wage earners with four or more years of college exceeded the percentage of Upstate metropolitan area wage earners with four or more years of college by more than 10%.  This may reflect the concentration of headquarters jobs in the New York City area, and the area’s greater ability to pull higher skilled workers into it compared with Upstate metropolitan areas.

While black/African-American wage earners have much higher levels of education than in 1970, the percentage increase in black/African American wage earners who have four or more years of college has lagged that of white wage earners. In 1970 about 12% more white wage earners had four or more years of college than black/African-American wage earners.  By 2015, the gap was 20%.  The increasing gap in highly educated wage earners between white and black/African-American wage earners contributes to the continuing disparities in wage incomes.  But, it is not the only reason why the gap persists.

Income Differences for Wage Earners with Similar Educations

While the differing educational levels of the populations of black/African American and white wage earners provide a partial explanation of the difference in wage income between the groups, they do not totally explain it.  In fact, black/African wage earners continue to have median wage incomes that are less than white wage earners with the same levels of educational attainment.

In 1970, at each educational level, differences in median wage income between Black/African-American and White wage earners were 20% or more.  In that year, wage differences between races did not appear to be related to educational level.  In 2015, results were more varied, with black/African-American workers with less than four years of high school in the New York City Metropolitan area having median wage incomes that were about 10% less than white wage earners.  But, at other wage levels, disparities were larger.  White wage earners with four or more years of college in the New York Metropolitan area earned more than one-third more than black/African-American workers.

In Upstate metropolitan areas, median wage disparities between black/African-American wage earners and white workers were larger in most cases than in the New York Metropolitan area.  For example, the median wage income for white wage earners with four years of high school was 56% higher than similar black/African-Americans.  The larger gap between white and black/African-American incomes in upstate areas leads to speculation that weak employment growth and the lack of racial diversity upstate may be related to larger racial income differentials.

Changes in disparities between white and African-American/black wage earner median incomes between 1970 and 2015 were inconsistent, though it is notable that black/African-American wage earners with four or more years of college fell further behind white wage earners in 2015 than they were in 1970.

Note that in the table above, overall, both whites and blacks did better than they did at specific educational levels.  This was the result on the large improvements in educational attainment that occurred between 1970 and 2015.  Much larger percentages of workers in 2015 had some college or four or more years of it than they did in 1970.

Comparing educational levels, white and black/African-American workers with less education fared worse than those with more education.  In New York City, white and black/African-American workers with four or more years of college saw gains in median inflation adjusted wage earnings.  Overall, black/African-American workers saw slightly larger median income gains than white wage earners.

Upstate, workers at all levels saw decreases, but wage earners at higher educational levels saw smaller median income losses.   Overall, however, black/African-American workers lost more wage income between 1970 and 2015 than did white wage earners.

Conclusions

The data shows that increasing educational levels in both white and African-American communities have offset much of the wage erosion that has occurred among those who have high school educations or less.  But, whites continue to to have higher levels of educational attainment than blacks/Afro-Americans, and that the gap has increased for those with four or more years of college education.

Differences in average educational attainment provide a partial explanation of the continued gap between median wage earnings of white and black/African-American workers. But, the fact that differences in median incomes between white and black/African Americans exist at similar educational levels points to the reality that policies promoting higher levels of education will not erase the median income deficit that this group faces.  While programs that “raise all boats” are more politically salable than those that address the needs of particularly disadvantaged groups, they cannot erase the income gap faced by African-American wage earners.

Because the wage gap between white and black wage earners persists, even among those at the same educational level, it is clear that the enactment of laws, like the Civil Rights Act of 1964, that have been aimed at erasing employment discrimination, are not in themselves enough to eliminate it.   The data from this analysis cannot provide the answer to the question of why this is true.  It does not show whether local, state and federal agencies need to do a better job of enforcing the laws, or whether the causes of the gap lie outside their purview. For example, it may be that white and black/African-American job candidates are often seen differently because many black candidates are products of central city school systems with high levels of poverty and low levels of academic achievement.

The racial gap in incomes remains a significant component of the inequalities that exist within our society.  If the wage gap between white and African-American workers is to be ameliorated, local, State and Federal governments must confront the realities that a better understanding of the causes of the gap is needed and that compensatory policies must have an implicit or explicit component that addresses racial differences in wage incomes.




As Private Sector Employee Incomes Stagnate, Local Government Workers Prosper

The slow growth of worker incomes since 2000 has been the subject of intense policy and political debates.  One of the clear messages of the 2012 Presidential campaign was the call to remedy perceived distortions in world trade that have disadvantaged American workers, particularly those had in the past held jobs in manufacturing industries.  The electoral discontent that arose, in part, from the weakness of the national economy played a significant role in the outcome of the recent Presidential election.

Nationally, the economy has suffered a bumpy ride during the current century, as the loss of manufacturing employment has cost more than five million jobs since 2000[1], and the country suffered two recessions, one in 2001, after the 9/11 attacks and the other in 2008, with the collapse of the country’s financial markets.  Average annual private sector employment[2] growth dropped from 2.5% between 1979 and 2000 to 1.3% between 2000 and 2015. Average earnings per employee only increased by 1.9% in real dollars in the entire period between 2000 and 2015[3]  – slightly more than 1/10th of one percent annually.

Given the lackluster performance of the U. S. economy, and the stagnation of worker earnings during the current century, how have local government employees fared?  As it turns out, remarkably well.  In fact, their earnings have shown steady growth, both in the latter part of the 20th century, when private sector employment and earnings were increasing relatively quickly, and during the current century, when they have stagnated.

In 1979, private sector workers and local government employees had average earnings that were nearly equal.  In 2015, nationally, local government employees’ average earnings were nearly 30% higher than private sector workers.

In New York State, the gap between average private sector earnings and the earnings of local government employees is far higher – in the Buffalo-Niagara Falls MSA local government employees’ earnings averaged $87,588 in 2015, while private sector earnings averaged 49,949, a difference of 75%.  In Utica-Rome local government employees averaged $68,979, compared with $41,186 for private sector workers – a difference of 68%.

Private Sector and Local Government Employee Earnings

 This post examines earnings of local government and private sector employees between 1979 and 2015.  Earnings are defined as wages and supplements to income, like health insurance and pension costs, and are a better measure of the total value of employee compensation than wages alone.  The data for private sector workers does not include farm workers.  Earnings are adjusted for inflation, and are shown in 2015 dollars.

Private Sector Earnings per Employee:  1979-2015

Over the thirty-six-year period between 1979 and 2015, real dollar earnings per employee in all metropolitan areas nationally increased on average by $10,948 (23.4%).  Real dollar earnings increased in most New York metropolitan areas, but by sharply varying rates.  The New York/New Jersey metropolitan area[4] had the strongest growth in the state – 38%.  Albany -Schenectady-Troy’s growth was second strongest – 22.3%.  Other upstate areas had growth that was significantly less than the average for metropolitan areas overall, but in most cases, New York metropolitan areas did see real private sector employee earnings growth.  The Binghamton, Kingston and Watertown MSA’s had losses.

Average private sector earnings per employee in most New York metropolitan areas declined significantly compared to the average of all metropolitan areas over the 1979-2015 period.  In 1979, average private sector earnings in large upstate metropolitan areas, like Buffalo, Rochester, and Syracuse were at or above the average.  In 2015, average private sector earnings were 14% below the national metropolitan average in the Buffalo MSA, 9% below the national average in the Rochester area, and 11% below it in the Syracuse area.  The New York City MSA was the only area to significantly exceed national growth – from 13% above the average to 28%.

Private Sector Earnings per Employee:  2000-2015

Between 1979 and 2000, private sector real earnings per employee in U. S. metropolitan areas increased by 18.9%, 0.8% annually on average. In the recent 2000-2015 period, private sector earnings per employee essentially flatlined, growing only by $1,073 – 1.9% nationally.   New York’s metropolitan areas generally reflected the slowdown of earnings growth, though their results varied.  Elmira did the best, with earnings per private sector employee growing by 14% between 2000 and 2015.  Albany-Schenectady-Troy also saw significant earnings growth – up 8.7%.  Other metropolitan areas saw much less growth, and in some cases decreases. The New York metropolitan area had a decline of almost 6% in earnings per private sector employee, but the regions’ earnings were still substantially higher in 2015 than the average for all metropolitan areas – $74,510 vs. $57,810.

Local Government Earnings per Employee:  1979-2015

Local government employees have seen significant increases in real earnings from 1979 to 2015 nationally and in New York State.  During that period, average earnings increased from $48,862 to $74,576 – an increase of 59%.  The real earnings of private sector employees also increased, but by only one third as much – 21% – from $47,737 to $57,810.  In 1979, local government and private sector earnings were nearly equal, but by 2014, local government employees had a 29% advantage in compensation, nationally.

Local government employees in New York State metropolitan areas had much greater increases in earnings between 1979 and 2015 than the average for United States metropolitan areas – in the Albany, Schenectady, Troy metropolitan area, earnings per employee doubled, and in Watertown and Kingston, they more than doubled.   In 1979, most metropolitan areas in New York State had average earnings per local government employee that were below the average for metropolitan areas across the nation.  Only Buffalo-Niagara Falls, Rochester and New York/Newark/Jersey-City were above the average.  Because of the rapid growth of local government earnings in New York metropolitan areas, by 2015, all New York metropolitan areas, except Glens Falls, Utica-Rome and Watertown were above the average for metropolitan areas across the nation.

Local Government Earnings per Employee:  2000-2015

While earnings of private sector employees showed only a 1.9% gain between 2000 and 2015, local government employee incomes increased by 14.4% on average in metropolitan areas across the nation.  In New York State, the increases were much larger – 27% in the Albany, Schenectady, Troy metropolitan area, 33% in the Rochester MSA and 45% in the Syracuse area.

 

Earnings Comparison

In 1979, private sector employees nationally and in New York State on average had earnings that were like or slightly exceeded those of local government workers.

By 2000, there was a significant difference between average earnings for private sector and local government employees: on average, local government employees earned 18% more than their private sector counterparts.

The difference in earnings was larger in many metropolitan areas in New York State – in the Albany-Schenectady-Troy MSA it was 33%, while in Buffalo-Niagara Falls, it was 44%.

By 2015, the difference had grown.  Nationally, local government employees in metropolitan areas averaged earnings that were 29% higher than private sector employees.  In New York State, the gap between local government and private sector earnings in metropolitan areas was much larger.  It ranged from 38% in the New York/New Jersey MSA to 156% in the Kingston MSA.[5]  In most metropolitan areas in New York, the difference between local government employee compensation ranged from 60% to 80%.Local Government Employment

Overall, local government employment grew more slowly than private sector employment in both the longer 1979-2015 and shorter 2000-2015 periods.  While results in New York State metropolitan areas varied, they followed a similar pattern – most showed slower local government employment growth than in the private sector.
During the 1979-2015 period, local government employment grew at about 60% of the rate of private employment growth – 53% compared to 91%.  In the 2000-2015 period, local government employment grew on average about 9%, compared to 22% for private employment.

 

 Growth of Total Private Sector and Local Government Employee Earnings

Even though local government employee growth was substantially slower than private sector employment growth, overall local government employee real earnings increased slightly more than private sector real earnings in U. S. metropolitan areas during the period because of the large increases in local government real earnings per employee.  Thus, local government employee earnings increased from 8.8% to 9.3% of the total of local government and private sector non-farm earnings during the 1979-2015 period.

New York State metropolitan areas, other than the New York City/New Jersey metropolitan area had larger increases in local government employees’ shares of local government plus private sector earnings.  For example, in the Kingston metropolitan area, local government employees’ share of earnings was 22.3% in 2015, compared with 13.5% in 1979.  In the Rochester area, local government employees had 14.2% of the total in 2015 compared with 9% in 1979.

During the 1979-2015 and 2000-2015 periods, the total earnings of local government employees increased by a greater percentage than that of private sector workers, both nationally and in New York State, but the differences were larger in New York State than the national metropolitan area average.  For example, in the Binghamton areas between 2000 and 2015, private sector employee earnings in the aggregate declined by 14%, while local government employee earnings increased by 21%.  In the Rochester area between 2000 and 2014, private sector earnings increased by only 1.8%, but local government worker earnings increased by 61%.

The contrast between the growth of total earnings of private sector versus local government employees was greater in 2000-2015 than in the overall 1979-2015 period.  While both local government and employee earnings in the aggregate increased significantly in most metropolitan areas, during the 2000-2015 period private sector earnings in the aggregate showed relatively small gains or losses, while local government earnings in the aggregate continued to show double digit increases.

Implications

 The data shows that local government and private sector employee earnings were similar in 1979, but that a large differential has developed, with local government employees averaging $74,576 in 2015 compared with $57,810 for private sector workers – a difference of 29%. It also shows that local government employees have been protected from the wage stagnation that has affected private sector workers in the United States since 2000, with average earnings increasing by 14%, compared with 1.9% for private sector workers.

While the causes of the growth of local government employees’ earnings relative to private sector workers cannot be discerned from this data by itself, there are several possible explanations for the trend.  These include:

  • Local governments do not face the same level of competitive pricing pressure encountered by private sector employers who compete in local, national or global markets.
  • Local government employees are highly unionized and enjoy the benefits of collective bargaining.
  • While government employees are barred from striking in 39 states, including New York, courts and legislatures have granted them protections (like the Triborough Doctrine and Triborough Amendment[6]) in the bargaining process that unions in the private sector do not enjoy.
  • The largest employers among local governments are typically public schools, whose employees are largely professionals who are required to have college degrees to qualify for employment, and continuing postgraduate training. More educated employees in the private and public workforce have made greater wage gains than workers with less education.
  • In areas like much of upstate New York, with large concentrations of manufacturing employment in 1979, private sector earnings growth has stagnated because of the shift from higher paying manufacturing employment to lower paid service sector jobs. The occupational mix among government employees has not shifted in the same way.  Thus, in these areas some of the gap in earnings between local government employees and private sector workers is like to have resulted from the changes in occupational composition of the two groups.

In most metropolitan areas in New York State, the contrast between private sector employee earnings stagnation and local government employee earnings growth has been greater than the average for all metropolitan areas, nationally.  Most of these New York metropolitan areas had been heavily dependent on high paying manufacturing jobs, and have lost most of them.  The jobs that have replaced manufacturing employment in areas like Binghamton, Buffalo, Rochester and Syracuse have been service sector jobs that pay less, on average, than the jobs that they replaced.  But the transition from manufacturing is not the only cause of the relatively greater gap between private sector and local government employee earnings in New York State.  The second factor is the more rapid growth of local government employee salaries in most metropolitan areas in New York compared to the nation.   For example, In Buffalo, local government employees earned 8% more than the national average in 1979.  In 2015 the difference was 17.4%.  In Syracuse, local government employees had earnings that were 7.1% below the national average in that year.  In 2015, Syracuse area local government employees earned 14.2% more than the national average.

There is no single cause for the increasing disparity between the earnings of private sector workers and local government employees, but the increasing gap between local government earnings per employee and private sector earnings raises questions of affordability in communities where residents’ incomes are growing slowly, if at all.  Because the differences in incomes are more pronounced in metropolitan areas in New York State outside New York City than elsewhere, the issue is particularly significant in Upstate New York.  And, the relative affluence of the public employees whose salaries are paid by taxpayer dollars may lead to increasing resentment, and electoral insecurity for local government officials.

_________________________________________________________

Profiles of Metropolitan Areas in New York State

Albany-Schenectady-Troy Metropolitan Area

 

Albany-Schenectady-Troy has historically been less dependent on manufacturing than most upstate metropolitan areas.  Thus, private sector earnings in the area are significantly greater than they were in 1979 – $55,074 vs. $42,719.  While the percentage growth in private sector earnings in the area was near the national average – 22.3% vs 23.4% — private sector earnings per employee remain below the national average of $57,810.  Private sector employment growth during the period was relatively strong compared to other metropolitan areas in the state, increasing by 60% compared to 1979.  Performance was relatively good during the 2000 to 2015 period as well, with private sector earnings per employee growing by 8.7% compared with 1.9% in metropolitan areas nationally.  Private sector employment grew by 14.5% during the period.

Local government earnings per employee grew substantially more than private sector employee earnings during both periods.  In 1979, government employees’ earnings averaged 5% lower than private sector employees.  By 2015, government employees’ earnings per worker averaged 55% higher.

The growth of the gap in earnings between local government and private sector workers from 1979 to 2015 was greater in the Albany-Schenectady-Troy area than it was in metropolitan areas, nationally.  While there was little difference in the relationship between local government earnings and private sector earnings in the Albany area and nationally in 1979, there was a 26% difference between the two in 2015 (55.2% vs. 29.0).  The periods where the gap between local government employee earnings and private sector earnings in the area increased most relative to the nation were between 1988 and 1994 and after 2003.

Between 2000 and 2015, private sector earnings increased by 8.5% in Albany – a relatively strong performance compared to the average of metropolitan areas across the nation, which had private sector earnings growth of 1.9%.  Local government earnings per employee grew much more, however, by 26.6%.

Binghamton Metropolitan Area

The Binghamton Metropolitan area is a relatively small metropolitan area (population – 251,725) that had a high concentration of jobs in manufacturing in 1970 – 42.2% of private sector employment.  By 2014 the area had lost 28,600 manufacturing jobs, and manufacturing jobs were only 11% of the private sector total.  Because of the relatively small size of the area and its dependence on a relatively small number of large manufacturing businesses, its economic performance over the past fifty years has been very weak.  Since 1979, the Binghamton area’s private sector employment has decreased by 4%, while per capita private sector earnings decreased by 3% to $44,938.  Between 2000 and 2015, private sector employment decreased by 10%, while earnings per employee decreased by 4%.  Local government earnings per employee grew strongly during the 2000 to 2015 period, increasing 22.8%.

Despite the continuing decline in private sector jobs and earnings, local government employee real dollar earnings per employee increased from $43,685 in 1979 to $74,869 – 66% higher than the area’s private sector average of $44,938.  The gap between local government and private sector earnings in the Binghamton MSA is more than double that (29%) in metropolitan areas nationally.

Buffalo-Niagara Falls Metropolitan Area

The Buffalo-Niagara Falls MSA has been hard hit by the loss of manufacturing employment over the past fifty years.  In 1970, 36% of private sector employment in Buffalo-Niagara Falls was in manufacturing.  By 2014, less than 10% of jobs were.  During the period, the area lost 121,000 manufacturing jobs.  The result has been that thousands of people who in the past had access to relatively high paying manufacturing jobs had to find employment in service industries.  In 2014, the earnings of workers in manufacturing jobs in Buffalo averaged $70,812, compared to $44,446 for jobs in the service sector.   At the same time, employment growth in the area has been slow – private sector employment increased by only 14% between 1979 and 2015 compared with 91% nationally. Between 2000 and 2015, Buffalo employment grew by 4% compared to 22% in metropolitan areas nationally.

But, local government employee earnings traced a different path.  After increasing steadily from 1979 to 1991, local government employee earnings plateaued during the 1990s, resuming their upward trend in 2003.  Thus, while private sector employees had real income growth of only 1% during the entire 1979 to 2015 period, local government employees’ earnings increased 73%.  Between 2000 and 2015, local government employees’ earnings increased by 23% compared with 1% for private sector workers.

Between 1979 and 2015, the earnings of Buffalo area local government employees increased, more quickly than in other metropolitan areas and were significantly higher than the national average by the end of that period.  During that same period, earnings of private sector workers in the area increased only slightly, with the result that they moved from the national average to significantly below it.

In 1979, Buffalo-Niagara Falls MSA local government employees averaged $50,650 compared with the national metropolitan average of $46,852 – an 8% difference.  Private sector employees in the Buffalo-Niagara MSA earned an average of $48,744 in 1979 compared with $47,737 for the nation- a 2% difference.  In 2015, Buffalo’s average private sector earnings ($49,949) were 14% lower than the national average ($57,810).  In contrast, local government employees earned an average of $87,588 – 17% higher than the national average for metropolitan areas of $74,576.  Thus, the gap between average local government employee earnings and private sector employee earnings in the Buffalo-Niagara MSA was 75.4% — two and one half times the average (29%) in metropolitan areas across the nation.

Between 2000 and 2015 private sector earnings per employee in the Buffalo-Niagara Falls MSA increased by 1.9%.  Local government earnings per employee increased by 23.2%.

New York/North Jersey Metropolitan Area

Unlike most metropolitan areas nationally since 2000, the New York/North Jersey metropolitan area has seen significant private sector job creation – 29% during the period.  Since 2000 the area’s job creation performance was among the strongest of metropolitan areas in nearby states, exceeded only by Boston’s performance.  Like the New York City metropolitan area, most of the places that showed strong employment gains in this century had large populations and small concentrations of manufacturing employment in 1979.

Over the 1979 – 2015 period, average private sector earnings in the New York MSA increased by 39%.  Average private sector earnings decreased by 6% during the 2000-2015 period.  Even so, average private sector earnings in the area are 28% higher than the national metropolitan area average.

Despite the New York metropolitan area’s relatively good private sector performance, local government employees have done significantly better.  For example, beginning in 2001, private sector earnings per employee decreased, but local government earnings increased by 19%.  Average earnings per capita for local government employees in the area are $103,000, compared to $74,000 for private sector employees – a 38% gap.

The growth of the earnings gap between local government employees and private sector workers has not differed greatly in the New York metropolitan area from other metropolitan areas across the nation.  Although the difference between local and private sector employee earnings was somewhat larger in the New York City area at the beginning and end of the study period, over much of the time, differences were small.

Rochester Metropolitan Area

Like most other upstate metropolitan areas, Rochester was historically heavily dependent on manufacturing.  Kodak and Xerox were both major employers in the Rochester area in the 1970’s.  Today, neither has a significant manufacturing presence.  Thus, Rochester has seen slow employment growth, and stagnant private sector earnings over the 36-year period between 1979 and 2015.

In 1979, average private sector earnings in Rochester were 7% above the national average, at $50,985 in inflation adjusted dollars.  By 2015, they were 9% below it, at $52,384.  At the same time, real earnings of local government employees have substantially increased – from $50,895 to $81,665.

Between 2000 and 2015, private sector earnings per employee decreased by 0.4% in the Rochester area.  Local government earnings per employee increased by 32.6%.

Because of the stagnation of private sector earnings per employee in Rochester and the steady growth of local government employee earnings, the gap between local government and private sector earnings in Rochester is substantially larger tha the average for metropolitan areas nationally – 56% vs.29%.

Syracuse Metropolitan Area

Although Syracuse employment in the 1970’s was less concentrated in manufacturing than places like Rochester and Buffalo, manufacturing was important to the area in the 1970’s, with major employers including General Electric, General Motors and Chrysler having operations In the area.

Like other areas that had a significant manufacturing focus, the area has seen little real private sector earnings growth over the 36-year period between 1979 and 2015.  Real earnings in the Syracuse area for private sector employees averaged $47,437 in 2979.  In 2015, private sector per employee earnings averaged $51,337.  Nationally, metropolitan areas saw private sector real earnings per employee grow from $47,737 to $57,810.

Between 2000 and 2015, private sector earnings per employee increased 2.7% in the Syracuse area.  Local government earnings per employee increased by 44.7%.

Local Government earnings per employee in Syracuse grew substantially between 1979 and 2015, despite private sector earnings stagnation.  In 1979 local government earnings per employee were $43,525.  By 2015, local government employee earnings had risen to $85,515.  Like other places, earnings of local government employees rose sharply during the current century, increasing by 44.7% since 2000.  By 2015, the gap between average earnings per local government employee and private sector employees’ earnings was 65.9% in the area, more than double the gap in income nationally.

Utica-Rome Metropolitan Area

In 1970, nearly 38% of employment in the Utica-Rome area was in manufacturing.  Since then, the Utica-Rome area has lost 29,000 manufacturing jobs, which now constitute 10% of the private sector total.

But, even in 1970, the Utica-Rome area had average private sector earnings per employee that were significantly below those in other upstate metropolitan areas.  In 1979, Utica-Rome’s average private sector earnings per employee was $40,669, compared with $47,437 in Syracuse, which is one hour away by car.  By 2015, the gap in private sector employee earnings was wider.  In Utica-Rome earnings averaged $41,186, while in Syracuse earnings averaged $51,337.  Utica-Rome’s relatively low private sector earnings level and growth are like other small metropolitan areas in the state.  Both Watertown and Glens-Falls had average private sector earnings per employee that were below $40,000 in real dollars in 1979.  Each is well below the national metropolitan average of $57,810 in 2015.

Earnings of local government employees, as in other metropolitan areas, have grown substantially in Utica-Rome, from $40,680 per employee in 1979 to $68,974 in 2015.  While local government employee earnings have grown in the area, they remain below the national average of $74,576.

Between 2000 and 2015, private sector earnings per employee in the Rochester area increased by 1.1%.  Local government earnings per employee increased by 20.4%.

Because Utica-Rome private sector earnings per employee have stagnated compared to the national metropolitan average, the gap between local government employee earnings and private sector earnings has grown to be substantially larger (67.5%) than the average for metropolitan areas (29%).

 

[1] http://money.cnn.com/2016/03/29/news/economy/us-manufacturing-jobs/

[2] Non-farm private sector employment.

[3] Source – U. S. Bureau of Economic Research, Table CA-5, Earnings by Industry.  Data is for all metropolitan areas. The Bureau defines “Earnings … [to be] the sum of three components of personal income–wages and salaries, supplements to wages and salaries, and proprietors’ income.”  All data has been adjusted to real dollars by use of the U. S. Bureau of Labor Statistics CPI-W measure for urban workers.

[4] Includes 12 counties in New York State (and 12 counties in New Jersey. See:  https://en.wikipedia.org/wiki/New_York_metropolitan_area

[5] The Kingston MSA has a small population – 182,493 in 2015, and was highly dependent on a large IBM facility that closed in 1994.  At its peak, the facility employed 7,100.[5]  See:  http://www.nytimes.com/1994/07/28/business/company-news-ibm-to-close-kingston-ny-plant-and-shift-jobs.html

[6] From http://sccea.org/the-triborough-doctrine/  :  In its 1972 Triborough Bridge & Tunnel Authority decision, the Public Employee Relations Board (PERB) interpreted the Taylor Law to prohibit employers from changing terms and conditions of employment while a successor agreement was being negotiated.

 

 




New York’s Dysfunctional School Spending Patterns

For many years, government spending in New York State has far exceeded the national average. State and local governments in New York had the second highest per capita spending in the nation in 2013.[1]

screen-shot-2016-12-08-at-8-52-07-am

Local government spending contributes significantly to New York’s high spending levels. Local government spending in New York averages $9,800 per person – the highest spending level in the nation.

screen-shot-2016-12-08-at-8-53-54-amSchools contribute the largest amount of local spending in New York.  They account for 49% of all local spending, and 61% of local taxes.  The contribution of schools to taxes is greater than to spending because a substantial portion of county spending is for social service programs funded by the State government.

New York school spending per student is far higher than the average for the nation – 87% higher.  Spending is particularly high in the suburbs surrounding New York City.  Because of the large regional disparities in school spending levels in New York State, they are likely to exacerbate educational inequality.

School Spending In New York State

screen-shot-2016-12-08-at-8-56-48-amCompared to other states, New York State spending per pupil is very high – 87% higher than the national average, and is significantly higher than the second state — Alaska (67% higher).[2] Even compared to neighboring states in the Northeast and Midwest, New York school spending is an outlier. New York’s spending per student is 16% higher than the states with the next highest expenditures – Connecticut and New Jersey and is much higher than the average for the northeast, excluding New York State – $20,610, vs. $15,639 – a difference of 32%.  The difference between New York and the average per pupil operating spending in the Midwestern states in the group was even larger – $20,610 vs. $11,556 – a difference of 78%.

This post will examine regional variations in school spending in New York state and in neighboring states, and regional variations within New York and neighboring states.

Household Income and School Spending

screen-shot-2016-12-08-at-8-58-18-amOperating spending per student is related to median household income at the state level, with income explaining about 40% of the variation in state average per pupil operating expenditures.  Schools in states with median household incomes below the national median of $51,939[3] spent $9,549 per student on average in 2014, compared with $14,268 for those above the average.  But, New York’s school spending is much higher than would be predicted from its residents’ median income.  New York’s median household income was $58,687, 13 percent higher than the national median.  The State’s average operating spending, $20,610, was 87% higher than the national average.

Regional Variations in Education Spending

screen-shot-2016-12-08-at-9-00-49-amAbout two-thirds of New York State’s 19,500,000 residents lived in the New York metropolitan area in 2014.  In that area, there is a sharp income division between the 8.4 million residents of New York City, whose median household income is $52,737 and the 4.9 million residents of suburbs in New York State around the city, which average $89,047.  The remaining 6.3 million New York residents who live outside the New York City metropolitan area have median household incomes that are like that in New York City and in the nation, about $53,000 on average.

Per pupil spending for current operations in New York State largely reflects regional household income differences.  Per pupil spending is much higher in the New York City suburbs than elsewhere, averaging $23,680 in 2014.  Spending in New York City was $18,579, while the average for upstate metropolitan counties was $16,846.

School spending in New York City suburban counties is much higher than for the rest of the state, and far exceeds per pupil expenditures measured at the state level outside New York State.   Expenditures in New York City, and in areas outside the New York City metropolitan area are lower, but are like those in the states with the highest spending levels in the region – Connecticut and New Jersey, and significantly higher than the Northeast median of $15,639 and the Midwest rust belt median of $11,556.

Cities and Suburbs – Income Disparities
screen-shot-2016-12-08-at-9-04-33-amTo understand spending differences between regions within New York State and areas outside the State, it is useful to look at per pupil spending within the major metropolitan areas in neighboring states, and outside those areas.  This is so because median incomes in metropolitan areas like New York City, Boston, and Philadelphia are significantly higher than in the rest of the states where they are located.  By comparing spending within and outside those areas, we can get a better understanding of how school spending differs in comparable areas within New York State and outside it.

Each of the four Northeastern states examined for regional disparities showed similar patterns of median household incomes.  Central City incomes were near or below state averages, as were incomes in areas outside major metropolitan areas.  Suburbs in major metropolitan areas showed very high incomes compared to state averages and central cities.

In each of the three major metropolitan areas studied median household incomes in central cities were between 32% and 52% less than in the suburban communities around them.  Philadelphia’s median household income is very low – $37,460, which is 51% less than median household income of the surrounding suburbs.  New York City’s median household income was 41% less than the surrounding suburbs in New York State.

Regional Spending Patterns
screen-shot-2016-12-08-at-9-10-37-amThe median household income for upstate metropolitan counties was like that in areas of Pennsylvania outside the Philadelphia metropolitan area, and below those in Massachusetts and New Jersey outside major metropolitan areas.  Per student operating expenditures in upstate metropolitan counties was higher than in neighboring states, averaging $16,846 compared with 12,641 in Pennsylvania and $13,883 in Massachusetts.

Median household income in suburbs around New York city was higher ($89,000) than in New Jersey ($71,000 around Philadelphia, and $75,000 around New York City), Pennsylvania ($76,915) and Massachusetts ($80,000).  New York City suburbs’ school spending per pupil was much higher than similar areas in nearby states – averaging $23,680 compared with $17,000 in New Jersey, $13,000 in Pennsylvania and $14,810 in Massachusetts.

New York City’s median household income was near that of Boston – $52,737 vs. $54,485, but per pupil expenditures in Boston were significantly higher than in New York city – $21,567 in Boston vs. $18,579 in New York City.  Philadelphia’s median household income was much lower than New York’s or Boston’s – $37,460, and per pupil expenditures were also relatively low for the region – $13,013.

The Impact of Disadvantaged Students on City Schools

Academic studies have consistently demonstrated that the cost of educating economically disadvantaged students is substantially higher than those from more affluent backgrounds.  For example, William Duncombe and John Yinger[4] of the Maxwell School at Syracuse University estimated the additional cost of estimating poor students and those with limited English proficiency to be 111% to 215%.

screen-shot-2016-12-08-at-9-11-45-amSince city school districts have much higher percentages of economically disadvantaged students than the suburban schools around them, to successfully educate their student bodies, per pupil spending should be higher in the cities than in the suburbs.  And, in Massachusetts, that is the case – Boston schools spend 48% more per pupil than the suburban schools around them.  But in New York State, the reverse is true – suburban schools spend 22% more per student than New York City schools.

Suburban areas around New York City, Philadelphia and Boston have significantly higher median incomes than those in the remainder of the states within which they are located.  In Massachusetts and Pennsylvania, per capita operating spending differs little from the suburbs of major cities to areas outside those metropolitan areas.  But in New York State, New York City metropolitan suburban school spending per student is far higher than in the remainder of the state.  Overall, there is substantially more regional spending inequality between suburban areas and New York City and the rest of the state than in similar areas in other states.

Implications

Overall, school operating spending per student in New York State is substantially higher than in neighboring Northeast states, and in the rust belt states of the Midwest.  Not surprisingly, the contrasts between New York’s high school spending levels are greater compared to schools in places like Ohio, Michigan, Indiana and Illinois than they are with New York’s immediate neighbors, like Massachusetts, Connecticut, Pennsylvania and New Jersey. When the State is broken down into regions – New York City, the suburbs in the New York Metropolitan area, and the rest of the state, only New York City shows spending levels that aren’t out of line with comparable regional entities.

The high spending levels found in New York State and its regions cannot be explained by differences in median household incomes, which are small compared with locations outside the state.   New York’s per student operating costs are 32% higher than the average of other Northeast states, and 78% higher than Midwest rust belt state.  Yet, New York’s median household income is significantly lower than some of its neighboring states, including New Jersey, where the median household income is 23% higher than in New York and in Massachusetts, where the median household income is 16% higher.

At the same time, New York has larger, regional variations in per pupil school spending that appear to exacerbate educational inequalities.  While the costs of meeting educational needs of students in districts with high concentrations of disadvantaged students are substantially higher than those in places with few of these students, wealthy New York City suburbs spend far more per student than New York City or other parts of the state. These large differences are not found in other nearby states.

[1] State and Local Finance Initiative – Data Query System:  http://slfdqs.taxpolicycenter.org/pages.cfm

[2] Source: U. S. Census Bureau:

http://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=SSF_2014_00A08&prodType=table

[3] In 2014.

[4] William D. Duncombe and John Yinger, “How Much More Does a Disadvantaged Student Cost?”  (2004) Center for Policy Research, Maxwell School of Citizenship and Public Affairs, Syracuse University. Paper 103.




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.

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

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

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

 




Can Charter Schools break the Poverty-Poor Student Performance Link?

In an earlier post, I argued that school based solutions to the problem of the poor performance of students in central city schools were not likely to succeed because they ignored the impact of the concentration of disadvantaged students on student achievement.  The data showed that 79% of the variation in performance in school performance in upstate New York metropolitan areas was related to the concentration of economically disadvantaged students within them.

Discussions about the benefits of charter schools tend to be heated – inflamed by ideological differences.  But whatever one’s feelings are about the virtues of preserving public education, or of competition in improving educational opportunity, before making judgements, we should examine the available data about their effectiveness.

At the outset, it should be noted that evaluating the true impact of charter schools is difficult.  Ideally, the performance of charter and public schools should be compared by selecting and assigning students at random and following their progress over a period of years.  But, in reality, students in charter schools are not selected at random, and matched samples of public school students are not available for comparison. Published analyses on the subject have pointed out the need to adjust performance comparisons of students at public and charter schools for selection bias, because charter school students are to a large degree self-selected.

Where competent analyses comparing charter and public schools have been done, the findings have been mixed. One review of the available studies concluded:

“Taken in the aggregate, the empirical evidence to date leads one to conclude that we do not have definitive knowledge about the impacts of public charter schools on students and schools. But in reviewing the existing evidence, one is also struck by the fact that the impacts of charter schools appear to be very contextual. Some public charter schools are better than others. Some are very successful in meeting student needs, and others are not very successful…. Consequently, the impacts of public charter schools should not be painted with one broad brush stroke. Each should be judged on its own evidence and performance.”

Other studies  have found significant advantages for charter schools in central cities. Atila Abdulkadiroglu, Joshua Angrist, Susan Dynarski, Thomas J. Kane and Parag Pathak, in “Accountability and Flexibility in Public Schools: Evidence from Boston’s Charters and Pilots” found:

“A consistent pattern has emerged from this research. In urban areas, where students are overwhelmingly low-achieving, poor and nonwhite, charter schools tend to do better than other public schools in improving student achievement. By contrast, outside of urban areas, where students tend to be white and middle class, charters do no better and sometimes do worse than public schools.”

My research is based on a reanalysis of state education data on the performance of students on the 2015 Statewide Student Assessment.  It cannot provide a controlled analysis of the performance of charter school students, compared with those in public schools.  For that reason, the data available to me cannot produce conclusive evidence about the effectiveness of charter schools.

Because publicly available data is cross-sectional, it provides information about the performance of students at a given point in time, but unlike longitudinal studies, it does not directly measure their gains over a year or years.  For that reason, when a  cross-sectional study finds out-performance, or under-performance, there is the danger of making an attribution error, because we don’t know whether the out-performance or under-performance was a characteristic of the student population that was unrelated to the effectiveness of the schools being evaluated.  For example, the students at out-performing schools might have characteristics related to their selection that would predispose them to perform better than other students.

With those limitations in mind, it is worth looking at the New York State Education Department data on student performance from the 2015 Statewide Student Assessment, controlling for the concentration of poverty in schools, to see whether students at charter schools do significantly better than those at public schools with similar concentrations of disadvantaged students.  The chart below shows the performance of students in public and charter schools in all counties in metropolitan areas, except for the City of New York:

Public Charter Outside NYC

Note that data was available for only 33 charter schools outside New York City, so conclusions from this group of schools must be regarded as tentative.  Still, a few things stand out.  First, the performance of charter schools was quite varied – several charter schools were among the worst performers compared to schools with similar concentrations of disadvantaged students, while a number of others, particularly those with high concentrations of disadvantaged students performed better.  Second, for charter schools, unlike public schools, student performance was not related to the concentration of poverty.

As a group, students at charter schools did slightly better than at public schools with the same concentrations of disadvantaged students. However, the fact that 24% (8 of 33) schools exceeded the percent of students predicted to pass by 20% or more, based on the concentration of poor students, is significant.  Only 1.9% of public schools outside New York City had student performance reaching that level.   And, as Abdulkadiroglu, et. al. found, the benefit from charter schools was most significant for students in schools with high concentrations of poor students.

The performance of the better charter schools in urban counties outside New York City was significantly better than average schools with high concentrations of disadvantaged students, but not as good as at schools with few poor students.  Most of the better performing charter schools had about 40% of students passing the Statewide Assessment, compared with as many as 60% in schools with few disadvantaged students.

School Performance in New York City

The concentration of disadvantaged students in New York City schools is associated with 52% of the variation in student performance between the schools.  Compared to public schools in urban counties outside New York City economic disadvantage is a less powerful predictor of student performance in City schools – 52% vs. 79%.  For charter schools, the relationship between the concentration of poverty and student performance was very weak – explaining only 8% of the difference in student performance.  As with other counties, the performance of charter schools was quite heterogeneous. Students at charter schools in New York City as a group did better than those at public schools with similar concentrations of disadvantaged students.  At the same time, a number of Charter schools performed less well than the average of public schools with the same concentration of poor students.

The weaker relationship between the concentration of poverty and student performance in New York City schools appears to be in part a consequence of the city’s policy of creating specialized schools with selective admission criteria.  For example, the Medgar Evers College Preparatory School includes questions about student performance on the Statewide assessment in its application form.  Another example is the TAG Young Scholars School, which describes its admission policy this way:  “Prospective students must be tested by The New York City Department of Education to determine whether they qualify for a seat in one of the City’s Gifted and Talented programs.” Note that while charter schools often use lotteries to select students, they are not permitted to use test performance as a selection criterion.

These selective public schools raise the issue of causal attribution, since unlike schools that do not choose students based on test scores, it is likely that student bodies enter the selective public schools at higher levels of performance than students at other public and charter schools, and that their better performance may primarily be a result of selection criteria, rather than teaching at the schools.

Public Charter NYC

Some charter schools and public schools in New York City did as well as schools with low percentages of disadvantaged students.  Some of the best performing public schools with high concentrations of disadvantaged students use test performance as one criterion for admission.  Since charter schools are not permitted to exclusively serve high performing populations, the performance of the best charter schools is more remarkable.  At 34 of 148 (23%) of charter schools, 20% or more students than were expected to pass based on the concentration of disadvantaged students passed the statewide assessment. Among public schools in New York City, including those that have selective admissions, 8.9% of schools exceeded their predicted performance level by 20% or more.

While this data cannot prove that the excellent performance of some charter schools was the result of the schools themselves, rather than some other factor, it is consistent with studies that have shown charter schools to be advantageous for disadvantaged students in central cities.

Implications

Much of the discussion about the performance of schools, and how to improve outcomes, has focused on the common core and its testing requirements.  The purpose of these requirements was to provide a universal set of assessment tools that would provide comparable data about student progress across systems.

The results of the testing have been disappointing to many, since, as the figures above show, large percentages of students did not achieve passing grades.  For example, Governor Cuomo’s 2015 The State of New York’s Failing Schools report stated, “It is incongruous that 99% of teachers were rated effective, while only 35.8 percent of our students are proficient in math and 31.4 percent in English language arts. How can so many of our teachers be succeeding when so many of our students are struggling?”

Governor Cuomo’s proposal to improve student performance included the creation of a teacher evaluation system that relied more heavily (50%) on the performance of students in standardized tests, a process to make it easier to remove substandard teachers, and a process to place under-performing schools in receivership.  Several of the proposals have problems.  Teacher evaluation systems that rely heavily on the progress of students on standardized tests suffer from statistical defects that result in low reliability of results – a subject for a future blog post.  The process for identifying under-performing schools does not effectively identify schools that are under-performing relative to the concentration of students in poverty within them.

Most significantly, by focusing almost exclusively on accountability for under performing teachers and schools, the proposal does not offer a strategy for overall improvement of New York’s schools.  Accountability focused methods focus on remedying or removing the worst five or ten percent of schools and teachers in the system, but do nothing to help the great majority achieve better results.

If New York’s education system is to make strides in improving student outcomes, it must encourage schools and teachers to adopt known classroom teaching strategies and effective curriculum choices that have the potential to improve overall outcomes.  Since a significant number of charter schools have achieved excellent student outcomes, it would be helpful if the strategies they use could be considered for adoption in schools that do not perform well.  The state should focus on finding ways to encourage the use of effective strategies, by disseminating information and incentivizing their adoption.

Considerable research has been done on the strategies employed by effective charter schools in improving student performance.  For example, “Getting Beneath the Veil of Effective Schools: Evidence from New York City,” by Will Dobbie and Roland G. Fryer of Harvard University found that:  “traditionally collected input measures – class size, per pupil expenditure, the fraction of teachers with no certification, and the fraction of teachers with an advanced degree – are not correlated with school effectiveness.  In stark contrast…an index of five policies…explains approximately 45% of the variation in school effectiveness.”  They are consistent with the approaches used by “no excuses” model charter schools that emphasize selective teacher hiring, extensive teacher feedback, increased instructional time, and a focus on discipline and academic achievement.

For most schools in cities with high concentrations of disadvantaged students in central cities, academic performance remains poor. In some of these schools less than 10% of students received passing grades on the statewide assessment, and the overwhelming majority of schools with concentrations of disadvantaged students of 90% or more had less than 20% of students passing.

But almost one quarter of charter schools and a few public schools have broken the link between poverty and poor school performance.  At these schools, more than 40% of students passed the statewide assessment, despite very high concentrations of poverty within them.

Accountability based approaches aimed at weeding out ineffective teachers, or taking control of schools from boards of education will benefit only a small minority of students statewide.  Instead, we should focus on making use of what works in improving student performance at the best charter schools, encouraging poor performing schools to adopt effective techniques.