The way of total output and output per worker changed over time in the United States and the way it affected the lives of typical people.
Explanation of Solution
Labor productivity refers to the output per unit of labor input.
Unit labor costs, on the other hand, refer to labor cost per unit of output.
According to the Department of Labor, U.S. productivity growth was fairly strong in the 1950s but then declined in the 1970s and 1980s before rising again in the second half of the 1990s and the first half of the 2000s.
The rate of productivity measured by the change in output per hour worked averaged
A fall in total output leads to employment loss because lower output requires a smaller number of people. Hence, people were affected due to a loss in total output.
Want to see more full solutions like this?
- Using data from 1988 for houses sold in Andover, Massachusetts, from Kiel and McClain (1995), the following equation relates housing price (price) to the distance from a recently built garbage incinerator (dist): = log(price) 9.40 + 0.312 log(dist) n = 135, R2 = 0.162. Interpretation of the slope coefficient? ► How would our interpretation of the slope coefficient change if distance were measured in metres instead of kilometres?arrow_forwardIf GDP goes up by 1% and the investment component of GDPgoes up by more than 1%, how is the investment share ofGDP changing in absolute terms?▶ In economics, what else is expressed as relative percentagechanges?arrow_forwardCEO Salary and Firm SalesWe can estimate a constant elasticity model relating CEO salary to firm sales. The data set is the same one used in Example 2.3, except we now relate salary to sales. Let sales be annual firm sales, measured in millions of dollars. A constant elasticity model is[2.45]ßßlog (salary) = ß0 + ß0log (sales) + u,where ß1 is the elasticity of salary with respect to sales. This model falls under the simple regression model by defining the dependent variable to be y = log(salary) and the independent variable to be x = log1sales2. Estimating this equation by OLS gives[2.46]log (salary)^=4.822 + 0.257 (sales) n = 209, R2 = 0.211.The coefficient of log(sales) is the estimated elasticity of salary with respect to sales. It implies that a 1% increase in firm sales increases CEO salary by about 0.257%—the usual interpretation of an elasticity.arrow_forward
- Not use ai pleasearrow_forwardB G C D E H M K Armchair For puzzles 96 and 97, use the first phylogenetic tree on the following page (Figure 2). 96) Who is the most recent common ancestor of species A and species G? 97) Who is the most recent common ancestor of species D, E, and F?arrow_forwardNot use ai pleasearrow_forward
Essentials of Economics (MindTap Course List)EconomicsISBN:9781337091992Author:N. Gregory MankiwPublisher:Cengage Learning