Background: Teachers are an important resource for implementing education interventions and appropriately valuing their time is essential to developing a valid estimate of an intervention's cost. Economic evaluation standards call for valuing teacher time using a market price equal to their compensation, inclusive of their wages and benefits (CASP, 2021). But it can be difficult to obtain reliable information on what an individual teacher is paid and their benefits. As a result, most economic evaluations of education programs value teacher time using average wages or benefits when estimating an intervention's cost. Choosing which average to use as a proxy for an individual teacher's wages and benefits is an important methodological decision for an economic evaluation. Average teacher compensation can vary across and within states, districts, and schools, according to teachers' education and experience levels, subject and grade taught, and local cost of living. Therefore, whether an average price is a good approximation for what a district pays a teacher depends on the unit of analysis. School-level average teacher salaries may be more precise than a district average teacher salary since schools can employ teachers with different qualifications that translate salary differences (e.g., more and less experienced teachers). Statewide or regional average teacher salaries may be less precise since teacher wages vary across districts and geographic areas. Even with knowing the potential for meaningful differences in average teacher salaries and benefits at varying levels of aggregation, many times analysts cannot obtain the most granular teacher compensation data, either because it is unavailable or the time and resources to obtain the data is prohibitive. As a result, cost analysts are challenged to select an average wage or benefit amount that both generalizes to the intended audience and for which data are available, but there is very little research to help guide decision making or evaluate the trade-offs when using average teacher compensation information at different levels of aggregation. This study fills this gap by providing new information on differences in average teacher wages and benefits at different levels of aggregation. Study design/analysis: We conducted several analyses using different administrative data sources that provide teacher compensation at varying levels of aggregation, in five states in different regions nationally. First, we analyzed state-level data to examine the extent to which teacher salaries varied between school districts, between schools within a district, and within schools in a district. We then explored whether teacher salaries varied according to specific student characteristics. We replicated these analyses in several large districts to understand whether the observed patterns of variance across schools and districts are sensitive to district size. Second, we conducted two additional analyses to further examine the extent to which students with different characteristics are systematically assigned to different types of teachers. The first set of analyses examines the extent to which teacher experience differs across student groups. Teacher pay is largely a function of experience, so we can think of experience as a proxy for teacher salary levels. In this analysis, we used student-level data from different states. Specifically, we matched each student to all teachers of record based on course linkages where both students and teachers are assigned to courses. We then calculated the average teacher experience for each student accounting for all teachers that were linked to a given student. Third, we considered the extent to which average teacher salaries published by the U.S. Department of Labor's Bureau of Labor Statistics' annual Occupation Employment and Wage Statistics (OEWS) data set are different from what is available from state and district personnel files. BLS data are publicly available and updated annually but are for geographic areas and not specific to a district. As a result, average wages from the BLS may not represent what a district pays teachers in places where a district's average wages are more or less than the average for all districts in a geographic area. To better understand how these limitations affect the precision in using BLS wage data to assign a market price for teacher time, we analyzed BLS teacher wage data for six states: 1) Delaware (DE), 2) Florida (FL), 3) Ohio (OH), 4) Pennsylvania (PA), 5) Texas (TX), and 6) Washington (WA). Specifically, we compared district average salaries for each county to the corresponding BLS-reported MSA and nonmetropolitan area salaries and explored the salary differences between the two data sources, across districts within states. Findings: First, we find that district- and school-level averages account for most of the meaningful variation in salaries that is related to student characteristics. While this could suggest that district-level average salaries might be an appropriate proxy for what a district pays for teacher time, we also know that teachers are sorted across schools within a district, with some schools having on average teachers with more experience and higher salaries. Using school-level average salaries, rather than a district-level average salary, accounts for this possibility when assigning prices for teacher time. Second, we find that although differences in salaries between teachers within a school account for much of the overall variation in salaries, there is little evidence to suggest that students with different characteristics within the same school have access to teachers with differing experience or qualifications. This suggests that efforts to obtain salaries for individual staff, linked to individual students, may not substantially improve the accuracy of school-level estimates for average teacher wages. Third, our analyses using the BLS suggest that, although there is variation in differences in district salaries and BLS OEWS salaries across states, the most frequently observed range of salary differences for teachers is small. As a result, cost analysts could utilize BLS OEWS salary data to fill information gaps in district salary data that are not filled with information from state personnel files or average salary information from district or school personnel files.