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3. The scrap rate for a manufacturing firm is the number of defective items-products that must be discarded -out of every 100 produced. Thus, for a given number of items produced, a decrease in the scrap rate reflects higher worker productivity. Suppose we are interested in one hand about the efficiency of worker training on productivity and on the other hand whether firm size, mea- sured in terms of the number of employees, has an effect on productiv- it In order to investigate these matters, we specify the model as (1) log(scrap) Bo+Bhrsemp+ B2 log(sales)+Bs log(employ)+u, where scrap is the scrap rate, hrsemp is annual hours of training per employee, sales is annual firm sales (in euros), and employ is the number of firm employees An econometrician, however, suggested that in order to investigate also the effect of the firm size on the scrap rate the model should be specified as log(scrap-βο+8hrsemp+82 log(sales/employ)+dg log(employee)+u.a) Show that model in equation (1) can also written as in equation b) Explain why the specification in equation (2) is more appropri- ate to investigate the firm size effect on the scrap rate than the specification in equation (1). What would be the null hypothesis? Estimation of model (2) from a sample of 43 firms gave the following results Standard error t-value p-value 4.57 2.510.016 0.019-2.21 0.032 sales/employ-0.951 0.3702.57 0.014 0.2050.20 0.842 Coefficient 11.74 0.042 Constant hrsemp employ 0.041 n=43, R2=0.310 c) Is there empirical evidence that education improves productivity, and if so, how much an additional hour of employee training on average improves productivity (decreases scrap rate)? d) Is there empirical evidence that firm size measured in terms of the number of employee affects productivity? Use 5% significance level in your inferencesCan I please get an answer to this problem?

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