Use the data in ELEM94_95 to answer this question. The findings can be compared with those in Table 4.1. The dependent variable lavgsal is the log of average teacher salary and bs is the ratio of average benefits to average salary (by school).

(i) Run the simple regression of lavgsal on bs. Is the estimated slope statistically different from zero? Is it statistically different from 21?

(ii) Add the variables lenrol and lstaff to the regression from part (i). What happens to the coefficient on bs? How does the situation compare with that in Table 4.1?

(iii) How come the standard error on the bs coefficient is smaller in part (ii) than in part (i)? (Hint:

What happens to the error variance versus multicollinearity when lenrol and lstaff are added?)

(iv) How come the coefficient on lstaff is negative? Is it large in magnitude?

(v) Now add the variable lunch to the regression. Holding other factors fixed, are teachers being compensated for teaching students from disadvantaged backgrounds? Explain.

(vi) Overall, is the pattern of results that you find with ELEM94_95 consistent with the pattern in Table 4.1?