Explanation:
The labor supply curve is perfectly elastic in a labor market that is perfectly competitive. The average cost and marginal cost of labor are used to calculate the wage throughout the entire market. A company must hire workers until its marginal income equals its marginal cost in order to maximize profits.
Explanation:
The fundamental tenet of monopsony is that the labor supply curve to an individual employer is not infinitely elastic. As a result, an employer who reduces wages by 1c may find it more difficult to hire and retain employees, but they do not instantly lose all of their current employees to rivals as predicted by the perfectly competitive model.
Explanation:
The number of people or heads living below the established poverty line in terms of minimum consumption expenditures or per capita income is used to calculate absolute poverty. This method of determining absolute poverty is sometimes referred to as the "Head-Count Ratio Method" because it focuses on counting the number of people or "heads."
Explanation:
A company will continue to hire workers in a monopsonistic labor market until the marginal revenue product of labor a. equals the marginal factor (resource) cost, which leads to more people being hired at a lower wage than in a labor market with perfect competition.
Explanation:
A little change in salaries causes a larger change in employment levels when the demand for labor is elastic. On the other hand, if labor demand is inelastic, a large change in compensation rates will result in a lesser change in employment levels.
Explanation:
Given that achieving objectives on schedule essentially defines workplace productivity, it's critical to comprehend how to do so without compromising the caliber of the task. Employees therefore need to be accurate in addition to speedy. If maximizing productivity is the goal, efficiency cannot be disregarded.
Explanation:
Over the past 50 years, the country's Gini Index, which gauges income inequality, has been continuously rising. The American Community Survey statistics from the bureau's first year show that the Gini Index increased from 0.482 in 2017 to 0.485 in 2018.
