Answer:
c. short-run average total cost is typically above long-run average total cost
Explanation:
In the case when the average of the total cost of the short run should be compared with the average of the total cost of the long run for a given output level so this means that the average of the total cost of the short run should be more than the average of the total cost of the long run
Therefore as per the given situation, the option c is considered
The correct answer to this open question is the following.
Although there are no options attached, we can say the following.
As a database administrator, the data dimensions I would describe to top-level managers to obtain their support for data administration would be these.
First of all, the imperious necessity of protecting the information of the company and the clients'. Security comes first. Then the technological aspects to have modern equipment and software to facilitate the operations in the company. System DBA's are necessary to have applications that serve to merge old information into new databases without affecting the actual data. Then to have a proper cluster in which the company can manage different procedures such as finances, accounting, field operations, and more, knowing that data is properly stored and easily accessible.
Answer:
1. The elasticity of demand for movie tickets must be INELASTIC.
2. Demand curves become LESS elastic in the long run. This means that the ticket price increase will likely be MORE profitable in the long run.
Explanation:
1. As demand is inelastic, the percentage of price increase will be greater than the decrease in the quantity of tickets demanded, and consequently profit will increase.
2. In the long term, demand becomes inelastic. Consequently, in the long term the percentage of the price increase will continue to be greater than the percentage of decrease in the quantity of tickets demanded.
Answer:
1,333.33
Explanation:
Labor productivity is measures the hourly output of a country's economy. Specifically, it charts the amount of real gross domestic product (GDP) produced by an hour of labor.
total labor hours = 25milion x 36 hours per week
= 900 million
labor productivity = GDP ÷ total labor hours
labor productivity = $1,200 billion ÷ 900 million
$1,333.33 per hour
