The formula for Growth rate of per capita GDP is:
Growth Rate = (per capita GDP in 2016 - per capita GDP in 2014) * 100 / per capita GDP in 2014
Growth Rate = (1,200 - 900) * 100 / 900
= 300 * 100 / 900
= 30,000/900
= 33.33 or 33
Therefore, 33% is the per capita growth rate between 2014 and 2016.
Answer:
a. 5.40%
Explanation:
First, I will calculate the new cost of equity for both stock X and Y:
Required rate of return = risk free rate + (beta x market premium)
Re stock X = 8% + (1.6 x 6%) = 8% + 9.6% = 17.6%
Re stock Y = 8% + (0.7 x 6%) = 8% + 4.2% = 12.2%
The difference between the required rate of return = 17.6% - 12.2% = 5.4%
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Answer:
a. Overstates Inflation.
In the case of Mary and Bob, the CPI would have already increased but in this case the price of the minivan increased as well. This will overstate inflation because it will not measure the general rise in price alone (inflation), it will also measure the rise in price as a result of the new minivan having better features.
b. Understated Inflation
Donna's case represents an understated inflation because the quantity shrank yet the price stayed the same. This means that the price is now buying less quantity than it used to which is inflation because more dollars are now required to buy the previous amount. This was not however recorded as there was no change in price.
c. Overstates Inflation
In the case of Zach, the inflation will be overstated because Zach is no longer buying bagels and is now buying muffins so continuing to use bagels as a representative good in the basket of goods used to calculate CPI would be overstating it.
d. Accurate representation of Inflation
In Chris's case, the increase in the price of the same shoe over the years has been because of a general rise in prices and not because it is a different model. It is the same shoe and its price is rising generally so this is an accurate depiction of inflation.
Answer:
The correct answer is Generalizability.
Explanation:
The generalizability theory (theory G) allows to measure the reliability of a test by quantifying the importance of each of its sources of variability. The error is redefined, as a condition or facet of measurement, using the generalizability coefficient as a measure to estimate reliability. This approach does not contradict the fundamental approaches of the classical theory of tests, but can be seen as an extension of it.
