This report presents the first detailed comparison of resource allocation between rural and nonrural districts in the West Region. Three regional characteristics often associated with rural districts were chosen for the analysis: district enrollment, student population density within a district (students per square mile), and drive time from the center of a district to the nearest urban area/cluster. Two other types of factors thought to be associated with resource allocation were also investigated: student need (incidence of poverty, English language learner students, and students receiving special education services) and geographic differences in labor costs. The report first examines how average regional characteristics, student needs, and labor costs differed across rural and nonrural district locale categories in 2005/06. Next it analyzes how average measures of resource allocation (per student expenditures on instruction, administration and student support, and transportation; ratios of administrative, instructional, and student support staff to students; and ratios of district central administration and maintenance and operations spending to school-level spending) varied across district locale categories. Using regression analysis, the study then models how these measures of resource allocation varied with the three regional characteristics and whether the relationship between resource allocation and regional characteristics differed across the study states. This study finds that rural districts in the West Region spent more per student, hired more staff per 100 students, and had higher overhead ratios of district- to school-level resources than did city and suburban districts. Regional characteristics were more strongly related to resource allocation than were other cost factors studied. Appended are: (1) Distribution of school districts and students in West Region states by locale category, 2005/06; (2) Data sources and variable construction; (3) Modifications made to raw Common Core of Data and School District Finance Survey data files; (4) Results of pair-wise comparisons for district locales; (5) Missing and recoded records and variables; (6) Regression analysis methodology and models; and (7) Regression model results. (Contains 2 boxes, 24 figures, 32 tables, and 10 notes.) [For the summary report, see ED515212.]