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## ASSIGNMENT SOLUTION Case Solution

Question 1

The city improvement recommendation can only be made if the costs are lower than the expected benefits. Based on the waiting time elasticity of demand of -0.6, if the waiting time is reduced by 15 minutes, then the number of trips would increase by 45000 as shown in the excel calculations. This would be weekly figure therefore; we have multiplied it by 52 weeks to get an annual figure of 2340000. It is assumed that the subway travel would be open for 52 weeks and 16 hours per weekend. The total WTP revenues and expenses have been calculated. We have a net profit of \$ 651,000 therefore; the city should implement this improvement. The computations are shown below:

 SUBWAY IMPROVEMENT Waiting time E(d) -0.6 Trips per year 7800000 E(d) = % change in trips/% change in waiting time % change in waiting time 50% % change in trips 30% New Trips 2340000 Total Trips 10140000 Revenues WTP from new riders 70200000 WTP from existing riders 23400000 Total WTP 93600000 Less: Expenses Capital Stock expenses 3000000 New weekend employee wages 36608000 Tax Driver Wages 18304000 Other new employee wages 9152000 Costs of Subway rides 27885000 Add: Decrease in pollution \$2,000,000 Total Expenses \$92,949,000 Net benefit/ (cost) \$651,000

Question 2

a).

We have used the estimates calculated in column 2 because these have been adjusted for heteroskedasticity. Based on the percentage change in price estimate of -0.24, the new price that should be charged is \$ 2.8 per acre per residents. The computations are shown in excel spreadsheet. The developer wants to buy 20 acres of the land from the total of 717.504 acres. The total price that should be charged for these 20 acres should be \$ 30270.3 as shown below:

 MARKET PRICE TO CHARGE Percentage change in Price -0.24 Residents 19392 Acres of open space per resident 0.037 Total acres of open space 717.504 Acres to buy 20 Change in acres of open space 697.504 Market price per acre per resident 2.04 Market price to charge 2.8 Total market price 30270.3

b).

The above charge is based on the estimates developed by the model; therefore, the charge can be adjusted by lowering it if the developer wants and increasing it if the government wants. The estimate for the price elasticity is again based on a number of assumptions and historical data therefore, adjustments can be made. However, the above charge should be a fair charge as it is based on the estimates generated by the regression model.

Question 3

a).

The total tax that would be collected would be:

\$ 154, 500, 000 x 15 cents

Tax Revenues = \$ 23175000

b).

The net cost (deadweight loss) of the program to the society would be:

 Total Spent on Rolls 154500000 Cost/market price per roll 1.35 Total rolls bought 114444444 Tax increase per roll 0.15 New price 1.5 % change in price -10% E(d) -0.15 % change in demand 1.50% Decrease in Demand 1716667 Deadweight Loss (net cost) 2317500

Question 4

a).

The average life expectancy of the world in years and the standard deviation is as follows:

 Mean of Life Expectancy 72.521 Standard Deviation of Life Expectancy 8.453

b).

The unweighted regression of GDP per capital based on Gini, government consumption, debt as a percent of GDP and GDP percent agriculture has been generated in R software and in excels spreadsheet as well. The data has been collected from CIA world Factbook. The data set has been trimmed as we have limited data for GINI index of the world countries. Therefore, the total number of observations of all the variables is 145. The R programming regression output for multiple regression models is shown below:

##

## Call:

## lm(formula = GDP per capita ~ GINI INDEX + public debt as percent of GDP + GDP - % agriculture + Government consumption , family = "binomial",

##     data = CIA)

##

## Deviance Residuals:

##    Min      1Q  Median      3Q     Max

## -1.627  -0.866  -0.639   1.149   2.079

##

## Coefficients:

##                                                  Estimate Std. Error z value Pr(>|z|)

## (Intercept)                              -32129.045    1800.3244   -3.50  0.0000 ***

## GINI INDEX                          825.555    69.0863    2.07  0.0000 *

## public debt as percent of GDP  488.3202    21.2145    2.42  0.0000 *

## GDP - % agriculture               4.5709    24.1930   -3.23  0.8504 *

## Government consumption       51.5134    61.6157   -3.48  0.4046 ***

## ---

## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

##

## (Dispersion parameter for binomial family taken to be 1)

##

##     Null deviance: 139.98  on 144  degrees of freedom

## Residual deviance: 138.52  on 144  degrees of freedom

## AIC: 400.5

##

## Number of Fisher Scoring iterations: 13

Based on the results of the regression model, we can say that the world GDP per capita is significantly impacted by Gini, government consumption, debt as a percent of GDP and GDP percent agriculture as the p value of the model is 0.000. If we analyze the coefficients of all the independent variables, then we can see that only GINI INDEX and public debt as a percent of GDP have a significantly positive impact on the GDP per capita. Based on the above model, the GDP per capital of China for the next year would be as follows:......................................

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