tionship between inputs and outputs in education. It is yet to reach an agreement on the proper measure of student performance to serve as the outcome indicator. Also, there is not indicator that takes in account the students that do not speak English, as their first language, and children with disabilities who do not do as well in school as other students. Many production functions rely on cross sectional data to In his book, Monk uses the production function as the basic element in studying productivity in schools. He defines a production function as a model which links conceptually and mathematically outcomes, inputs, and the processes that transform the latter into the former in schools (Monk, p. 316). He notes that production functions are important for improving both technical and allocative efficiencies. However, despite their potential benefits, Monk recognizes the major obstacles that face the creation of production functions for education. Neither outcomes, inputs, nor processes are easily understood. In education, outcomes are multiple, jointly produced, and difficult to weigh against one another. The outcomes of education are not all translatable into a standard metric, such as money, which makes it very difficult to give them relative value. A further difficulty with outcomes has to do with the level at which they should be measured. At various times researchers have been interested in outcomes of individual students, classes of students, schools, school districts, states, nations, ethnic groups, age groups, gender groups, and all sorts of other subsets of the population. Monk is aware of the difficulties in dealing with both micro and macro analyses. He concludes that there is no one best approach. "... it is not always the case that microlevel data are better than macrolevel data. The proper level of analysis depends largely on the nature of the phenomenon being studied. Some phenomena are district rather than school or...
