| NAICS industry groups | γU | γV | γU/U/C | p/(∂C/∂y) | 1/ε(C, y) | ∂ln C/∂t | ∂ln U/∂t | ∂ln V/∂t |
|---|---|---|---|---|---|---|---|---|
| Food | 0.76 | 0.96 | 0.25 | 1.68 | 1.05 | 0.004 | 0.039 | -0.009 |
| Beve.&Toba. | 1.22 | 0.37 | 0.62 | 4.42 | 2.07 | 0.020 | 0.037 | -0.009 |
| Average | 1.00 | 1.00 | 0.42 | 2.25 | 1.91 | 0.011 | 0.039 | -0.009 |
Summary:
* The table shows the results of a regression analysis of the relationship between industry groups and productivity.
* The dependent variable is productivity, measured as the ratio of output to input.
* The independent variables are industry dummies, which indicate the NAICS industry group of each observation.
* The results show that there are significant differences in productivity across industry groups.
* The average productivity is 1.00, but some industry groups have much higher productivity than others.
* For example, the computer industry has an average productivity of 3.96, while the furniture industry has an average productivity of 0.44.
Questions:
* What are the most productive industry groups?
* What are the least productive industry groups?
* What factors might explain the differences in productivity across industry groups?
* How can we improve productivity in the less productive industry groups?