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dusya [7]
4 years ago
15

For every 1% increase in

Mathematics
1 answer:
givi [52]4 years ago
3 0

Answer:

The GDP gap is 9 % when there is 4.5 % unemployment.

Step-by-step explanation:

The statement shows a reverse relationship, where an increase in unemployment is following by decrease in potential GDP and can be translated into the following rate:

r = \frac{2\,\% \,GDP}{1\,\% unemp.}

The GDP gap at a given increase in unemployment can be estimated by the following expression:

\frac{g}{u} = r

g = r\cdot u

Where:

r - GDP gap-unemployment increase rate, dimensionless.

u - Increase in unemployment rate, measured in percentage.

g - GDP gap, measured in percentage.

If r = \frac{2\,\% \,GDP}{1\,\% unemp.} and u = 4.5\,\%\,unemp., the GDP gap is:

g = \left(\frac{2\,\%\,GDP}{1\,\%\,unemp.} \right)\cdot (4.5\,\%\,unemp.)

g = 9\,\%\,GDP

The GDP gap is 9 % when there is 4.5 % unemployment.

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Solution :

Transforming given equations :

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From above equations we can see that equation 1) has largest percentage growth rate and the percent growth rate is 12% .

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Answer:

n=\frac{0.5(1-0.5)}{(\frac{0.025}{2.58})^2}=2662.56  

And rounded up we have that n=2663

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".  

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Solution to the problem

In order to find the critical value we need to take in count that we are finding the interval for a proportion, so on this case we need to use the z distribution. Since our interval is at 99% of confidence, our significance level would be given by \alpha=1-0.99=0.01 and \alpha/2 =0.005. And the critical value would be given by:

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The margin of error for the proportion interval is given by this formula:  

ME=z_{\alpha/2}\sqrt{\frac{\hat p (1-\hat p)}{n}}    (a)  

And on this case we have that ME =\pm 0.025 and we are interested in order to find the value of n, if we solve n from equation (a) we got:  

n=\frac{\hat p (1-\hat p)}{(\frac{ME}{z})^2}   (b)  

We can assume an estimated proportion of \hat p =0.5 since we don't have prior info provided. And replacing into equation (b) the values from part a we got:

n=\frac{0.5(1-0.5)}{(\frac{0.025}{2.58})^2}=2662.56  

And rounded up we have that n=2663

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