New York State Education Department

Recognizing High Cost Factors in the Financing of Public Education:

The Calculation of A Regional Cost Index

                                                     December, 2003


  The State Aid Work Group

Executive Summary

The Regional Cost Index was developed in recognition of the geographic cost variations in different areas of New York State. The index, which is based on the work of researchers for the state of Oregon, uses median salaries in professional occupations that require similar credentials to that of positions in the education field. These occupational titles typically require a bachelor’s degree for employment at the entry level. The cost index was created from the wages of 63 professional, non-education occupations. Education-related titles were excluded to ensure that the index measured labor market costs and not the tastes or control of school districts.



Professional Cost Index for New York State

by Labor Force Region (2003)

Labor Force Region

Index Value

Purchasing Power of $1,000 by Region

Capital District



Southern Tier



Western New York



Hudson Valley



Long Island/NYC



Finger Lakes



Central New York



Mohawk Valley



North Country




 Construction of the Index

In order to adjust for geographic variations in the cost of educational resources, the regional cost index (RCI) was generated following a methodology similar to one developed by Rothstein and Smith[1] for the state of Oregon. This involved the use of a statewide index based on median salaries in professional occupations that require similar credentials to that of positions in the education field. In particular, these titles represented categories for which employment at the entry level typically requires a bachelor’s degree. The professional occupations selected for use in this index are based on a list of 94 occupational titles developed for use in the state of Oregon.

Due to insufficient wage information, the previous RCI was based on 77 of the 94 occupational titles used in the Oregon study. However, due to a lack of employment data within many of New York State’s ten Labor Force Regions, 63 titles were used for this edition of the RCI. The titles used appear in Appendix A. In addition to those titles with missing data, the final list excluded teachers, other educational positions and categories that tended to be restricted to federal and state government, since the markets for teachers and for many government positions tend not to be fully competitive. Education-related titles were also excluded in order to ensure that this index be entirely a measure of labor market costs, and not be subject to the tastes or control of districts. Therefore, we sought to measure genuine labor market costs, not the results of districts’ decisions to hire especially high quality teachers, or to influence the index value in later years by choosing to pay more for staff. By basing the index on the wages earned in the labor market by professionals with similar skills, we have created a measure of costs in the sector of the labor market in which districts compete for teachers and staff, in each region of the State. Since personnel salaries and benefits make up the vast majority of the costs faced by school districts, the RCI allows for an individual to compare the buying power of the educational dollar in the different labor force regions of the State

Selection of Occupational Titles

The data on which the RCI is based was made available through the New York State Department of Labor. Since the prior edition of the RCI, the structure of the occupational title system has been revised. This has resulted in the expansion of a number of titles. Through the use of a crosswalk provided by the Department of Labor, it was found that the 77 occupational titles used in the previous version of the RCI had increased to 105. However, due to a lack of employment data, a fair amount of the 105 titles were eliminated. In the end, 46 titles had both employment and wage data, six were plugged with wage data, and an additional 11 employment titles were plugged where data was available statewide and for nine of the ten labor force regions. In all, 63 occupational titles were used for this analysis. Fifty-five of these titles were direct matches with the 77 titles used in the previous version of the RCI.

Statewide Median Wage

The first step in generating a regional cost adjustment from the list of 63 titles was to establish a statewide median wage figure for which median wages in each labor force region could be compared for indexing purposes.The statewide median wage was calculated by taking the total number of employees in each of the 63 titles for the state as a whole for example, the total number of people working in the title “pharmacist” across the state), and multiplying that amount by the median annual wage for that title (15,103 pharmacists * $72,020). This result was then summed for all titles, and then divided by the total number of employees in all 63 occupational titles (972,073). This produced a weighted annual median wage of $65,189 for the professional titles making up the index.

Title Weightings

It was important to avoid the possibility that the index could be skewed due to compositional differences in the percentage distribution or mix of the individuals occupying the 63 selected titles. Therefore, if professional wages in the titles selected were found to be identical in two labor force regions, but 60 percent of the employees in region A occupied the 10 lowest salaries titles (vs. a 10 percent employee representation in these lower salary titles in region B), a simple summation of wages could lead to the erroneous conclusion that professional service costs were far higher in region B than in region A. In short, “apparent” cost differences would be due totally to differences in the title composition of the workforce, not to true wage differences in those titles.

This problem was avoided by weighting the wage for each title based on the relative importance of that title in the group of 63 titles statewide. Thus, in determining the regional differences in median wage, we assume that the “mix” of jobs in each region is the same as the “mix” in the state as a whole. These title weights were then applied to each region, therefore making the distribution or service “mix” of titles a constant across the state. For example, if sales managers made up 10% of the total number of employees statewide in the 63 titles, then a 0.10 compositional weighting was assigned to sales managers in every region. This title weighting procedure thus imputes to every labor force region precisely the same mix of employees across the 63 titles in every region.

Title weights were generated by dividing the statewide number of employees in a given title by the total number of employees in the 63 titles of the index. For example, the number of pharmacists statewide was 15,103, which was then divided by 972,073 (the total number of workers in the state in these 63 titles). This yielded a title weight of 0.0155. (Since this was performed for all the titles in the list, the sum of all title weightings equals one.)

Final Calculation of the Regional Index

Once the title weights were determined, they were incorporated into the data set for each of the ten labor force regions. The median annual wage for each title was multiplied by the title weight. This result was summed for all 63 titles, yielding a regional median wage. This regional median was divided by the statewide weighted median professional service wage to yield the final professional service wage index for each region. These results were then normed on the North Country.

When median wage data were missing for a title in a given region, two alternatives were explored for “plugging” these holes. One method involved a simple substitution of the state median wage for a given title for the missing wage information in a particular labor force region. However, it was recognized that this method of wage attribution was biased “upward” (toward the median) in low cost areas of the State, and biased downward in high cost areas of the State. The alternative solution, which was selected, was based on the creation of a similar regional cost index, using a smaller set of occupational titles (those titles, in which data was not missing in any region of the State, n=46). The smaller index, in conjunction with the statewide median salary information for any occupational title that was lacking salary information in a specific region, was used to estimate the missing regional salary item.


While the list of professional occupations used to create the RCI was based on the work of Rothstein and Smith in Oregon, the Bureau of Labor Statistics provided the wage data used in the index. The wage data was obtained from the 2001 Occupational Employment Statistics (OES) Survey, which allows employers to report the number of employees and wages for each title they employ. The United States Department of Labor has noted, “Establishment surveys have little information on the demographics of their employees, but…wages and earnings tend to be more accurately reported in establishment surveys as they are based upon administrative records rather than recall by respondents…These factors make establishment data the natural choice…[2]

The data from the 2001 Occupational Employment Survey for New York State was made available to the staff of the New York State Education Department through the New York State Department of Labor. Therefore, data was provided for all of the 671 occupational titles in each of the ten labor force regions in New York State, as well as a statewide total for all titles. The wage data obtained from the OES is based on “straight-time, gross pay, exclusive of premium pay. Base rate, cost-of-living allowances, guaranteed pay, hazardous-duty pay, incentive pay including commissions and production bonuses, tips, and on-call pay are included. Excluded are back pay, jury duty pay, overtime pay, severance pay, shift differentials, nonproduction bonuses, employer cost of supplementary benefits, and tuition reimbursements.”[3]

The Bureau of Labor Statistics develops its estimates through the use of an annual mail survey of about one-third of the establishments state- (and nation-) wide in occupational groups such as: business and financial operations; transportation and material moving; personal care and service; architecture and engineering; office and administrative support; and management.[4]  The survey is repeated in a three-year cycle, whereas the cycle continues, data from the third of establishments surveyed in current years builds on previous years’ data, in a process called wage updating. This results in detailed and precise estimates of wage levels even in small job categories or geographic regions. In the fourth year, the survey cycle starts over.

Since wage data is built-up over a three-year period, the approximations of wages become increasingly accurate and most precise in the third year. This year’s index calculations are based on the most accurate data-year in the cycle, and thus inspire confidence that the results are a good representation of the variation in professional service costs around the state. The triennial nature of the data suggests that the RCI need only be updated in those years for which the most accurate data in the cycle are available.

It should be noted that the index results for New York City and Long Island were combined. A single median wage was calculated for this labor force area, because there is evidence that these two areas actually function as a single labor market region. With professionals, especially those in the education professions, moving to jobs across the lines between New York City and Long Island, it is necessary to consider this entire region as a single area, with similar wage costs.

Regional Cost Index Variation by District Type and Need


In order to gain a greater understanding of the RCI, several analyses were conducted to measure the index in relation to school district type and need. As seen in Chart 1, school districts in the downstate region have higher labor costs when compared to other areas of the state. For example, with a median cost index value of 1.359, the labor costs of downstate small cities are 25.8 percent higher than their upstate counterparts. The difference in labor costs between the upstate and downstate regions are further displayed when examining suburban school districts. The purchasing power of downstate suburban districts was found to be 75.7 percent of upstate suburban districts. Therefore, every dollar spent to purchase goods and services in upstate suburban districts purchases 76 cents worth of these services in the downstate suburban areas.

As we shift our focus from district type to an examination of district need/fiscal capacity[5] in relation to the RCI, we find that an interesting relationship exists.  As shown in the decile table below, as need/fiscal capacity worsened districts are generally more likely to experience lower labor market costs. However, with its high pupil need and average wealth, New York City, which would be situated in the ninth decile, shares the same high labor costs as low need districts in the first decile. Therefore, for districts such as New York City, recognition of both labor market differences and need become important.


To further explore those districts that are located in high cost areas, have high pupil need, and whose wealth capacity is adequate, an additional analysis was conducted to examine regional cost by district need/resource capacity. As seen in Chart C, while low need-high wealth districts share the same high labor market costs as New York City, rural districts have the lowest regional costs when compared to the other categories of need.


It is also found that urban/suburban high need districts also have high costs. Since these districts operate in the same high cost labor market as their neighbors with more resources, they are unable to pay market rates. This creates difficulties for urban/suburban districts that seek to hire and retain highly qualified educators that can assist high-need student populations in meeting academic standards.

The variation in regional costs when comparing different types of districts shows that high costs are problematic in both high and low wealth areas. While the lowest cost areas of New York State tend to be rural, where salaries and the overall cost of living is lower, high cost areas are much more diverse. We have found that some of the wealthiest districts in the State are in high cost regions, yet some of the poorest districts face very high costs as well.

Alternative Methods of Calculating Regional Costs

There are several possible methods for developing an index to adjust for geographic variations in the cost of labor. Rothstein and Smith recommend the method used above in their work dealing with the state of Oregon. The Rothstein and Smith method, along with other methods that will be discussed below, are all designed to do the same thing – namely, to control for specific attributes of the goods and services being purchased, so that valid inter-area cost comparisons can be made. A brief description of each method follows:

Statewide Wage Index

Rothstein and Smith (1997) base their index on the claim that unlike the past, when teachers were predominantly female and underpaid, salaries have increased and the teacher labor market has become a part of a broader labor pool of college educated, professional workers. Other professionals in this group include accountants, health professionals, and managers.

Rothstein et al. suggest that insight into the regional variation in teacher cost can be gained by examining the regional variation in salary of other professionals within the broader competitive labor market of similarly educated and salaried individuals. Indeed, they argue that in many communities, the overwhelming majority of teachers are employed by (and thus costs controlled by) a single agency or a very few agencies – in effect, these agencies dominate the market for the purchase of educational components. In this market situation, one purchaser can heavily influence the expenditures/costs of professional compensation; therefore, it is more appropriate to use salaries of non-teacher professionals (which are subject to free market conditions) as the basis for price estimation. Since school districts have no control over the salary scales of other professions in their geographic area, a cost adjustment based on regional variations in these salaries is more likely to represent an accurate reflection of true variations in cost as opposed to factors under the direction of school districts.

Rothstein and Smith acknowledge that their index is focused mainly on labor costs, and that it does not take into account variations in non-labor inputs to education. They argue that this is acceptable because the vast majority of school expenses are for compensation of staff. (They estimate the percentage at around 85% of total costs.) Rothstein and Smith suggest that the index multiplier could be applied to the portion of school aid that is directly applied to salaries. These include 85% of operating aid, the total aid in categories that are focused on teachers and teacher improvement, and the proper proportion of other categorical aids.

A strong point of this index that Rothstein and Smith do not mention, but which is nevertheless important, is the fact than an index of wages is relatively easy to explain to policymakers, district leaders, teachers, parents and other interested parties. In addition, the data is easy to obtain, the calculations are simple and as discussed above, this index yields fairly stable results that only need to be recalculated every three years. These characteristics, as well as the focus on market wages and the fact that it is not subject to district control, provide an extremely practical means of calculating the differences in regional costs.  Therefore, this method was viewed as an appropriate choice in which to adjust for regional cost differences.

Consumer Price Index

Rothstein and Smith also suggest the use of the Consumer Price Index (CPI). In fact, they suggest that the CPI might be used alongside the RCI method to increase the precision of the measure. However, Rothstein and Smith also acknowledge serious limitations on the use of a CPI measure to determine regional costs. The first problem is that this information is collected on a different geographical basis than the wage data, making comparisons difficult. Should New York attempt to collect the price data based on its own internal regions, the cost would be prohibitive. In addition, the costs faced by school districts would be difficult to measure, since such precise local data is hard to collect. The CPI has been criticized for failing to incorporate new shopping patterns, and to account for differences in cost due to taste. Since shopping patterns and tastes for quality vary significantly around the State, it would be difficult to avoid confounding differences in shopping patterns with differences in cost. The method of calculating the RCI that was selected successfully avoids these problems.

Hedonic Wage Index

Chambers and Fowler (1995) suggest another type of cost index of teaching. This is based on a hedonic wage model that considers relevant conditions that may attract workers to a certain geographic area or certain positions. This cost adjustment uses a comprehensive statistical analysis (typically a series of hedonic equations) which predict the market price or wage compensation that would occur if certain personal characteristics of teachers, variations in local amenities, and job environment factors were presumed to be the same in each local geographic area. This method requires complex calculations and would be difficult to explain to decision-makers. In addition, the selection of relevant characteristics on which to measure districts and teachers could be open to significant political debate. The Rothstein and Smith method is preferred for its objectivity and simplicity.

Occupational Titles Used for the Regional Cost Index


  1. Chief Executives
  2. General and Operations Managers
  3. Advertising and Promotions Managers
  4. Marketing Managers
  5. Sales Managers
  6. Public Relations Managers
  7. Administrative Services Managers
  8. Computer and Information Systems Managers
  9. Financial Managers
  10. Human Resources Managers
  11. Industrial Production Managers
  12. Purchasing Managers
  13. Transportation, Storage, and Distribution Managers
  14. Construction Managers
  15. Engineering Managers
  16. Medical and Health Services Managers
  17. Property, Real Estate, and Community Association Managers
  18. Social and Community Service Managers
  19. Purchasing Agents, Except Wholesale, Retail, and Farm Products
  20. Cost Estimators
  21. Employment, Recruitment, and Placement Specialists
  22. Compensation, Benefits, and Job Analysis Specialists
  23. Training and Development Specialists
  24. Management Analysts
  25. Accountants and Auditors
  26. Budget Analysts
  27. Financial Analysts
  28. Loan Officers
  29. Computer Programmers
  30. Computer Systems Analysts
  31. Network and Computer Systems Administrators
  32. Civil Engineers
  33. Electrical Engineers
  34. Industrial Engineers
  35. Mechanical Engineers
  36. Civil Engineering Technicians
  37. Electrical and Electronic Engineering Technicians
  38. Environmental Scientists and Specialists, Including Health
  39. Market Research Analysts
  40. Clinical, Counseling, and School Psychologists
  41. Urban and Regional Planners
  42. Substance Abuse and Behavioral Disorder Counselors
  43. Rehabilitation Counselors
  44. Child, Family, and School Social Workers
  45. Medical and Public Health Social Workers
  46. Mental Health and Substance Abuse Social Workers
  47. Librarians
  48. Multi-Media Artists and Animators
  49. Graphic Designers
  50. Public Relations Specialists
  51. Writers and Authors
  52. Dietitians and Nutritionists
  53. Pharmacists
  54. Physician Assistants
  55. Physical Therapists
  56. Recreational Therapists
  57. Speech-Language Pathologists
  58. Medical and Clinical Laboratory Technologists
  59. Medical and Clinical Laboratory Technicians
  60. Police and Sheriff's Patrol Officers
  61. Recreation Workers
  62. Residential Advisors
  63. Interviewers, Except Eligibility and Loan


[1] This methodology is described in Rothstein, R., & Smith (1997).  Adjusting Oregon Education Expenditures for Regional Cost Differences: A Feasibility Study.  Sacramento, CA: Management Analysis & Planning Associates, L.L.C

[2] See U.S. Department of Labor, “Interarea Comparison of Compensation and Prices”, Report on the American Workforce, 1997, pp.69-97.

[3] United States Department of Labor’s Bureau of Labor Statistics Website. Technical Notes for 2001 OES Estimates.  (

[4] Ibid

[5] The need/fiscal capacity index consists of an extraordinary needs index without sparsity, divided by the Combined Wealth Ratio.  The need/fiscal capacity index is similar to the need/resource index in that it provides a measure of pupil need in relation to district wealth.