Question

In: Accounting

The following regression model was estimated by an Australian-based MNC to determine its degree of economic...

The following regression model was estimated by an Australian-based MNC to determine its degree of economic exposure to the U.S. dollar (US$) and the South African Rand (SAR):



where the dependent variable is the percentage change in cash flows (PCF) measured in the company's home currency over period t. The explanatory variable (et) is the percentage change in the exchange rate of the foreign currency (e.g., A$/SAR) over period t. The regression was estimated over a single period for each of the two currencies, with the following results:

Regression Coefficient (a1)
US$ 0.10
SAR -0.76

Based on these results, which of the following statements is not true?

A.

The MNC was more sensitive to movements in the SAR than in the US$.

B.

On average, when the US$ appreciated, the MNC’s cashflows increased.

C.

The MNC likely imports more goods from South Africa than it exports.

D.

On average, when the SAR depreciated, the MNC’s cashflows decreased.

E.

All of the above are true.

Solutions

Expert Solution

Regression model helpd to understand the liner relationship between two variable

The formula is Y i.e. Percentage change in cash flow = a + bx

where a= % change in rate of foreign currency

a is the intercept and b is the slope of the line (regression coefficient)

The sign of the regression co-efficient helps to identify the co-relation between indepenent and dependent variables.

A positive co-efficient indicates that as the value of the independent variable increases the mean of dependent variable also increase whereas a negative co-efficient indicates that as the independent variable increases the dependent variable tends to decrease

Here we have a positive co-efficient with US $ = 0.10 and negative co-efficient with SAR = -0.76

Hence,

There is an inverse relationship with SAR, and so the company will be more sensitive towards SAR than with US $ as with every increase in SAR there will be decrease in Percentage cash flows of the Australian company and vice-versa

so the statement D i.e.on average when SAR depreciated the MNC's cash flow decreased is an incorrect statement as MNC's cash flows would increase upon decrease of SAR due to negative co-efficient


Related Solutions

Following is an Estimated Multiple Regression for Cigaretteconsumption in the US. Based on the estimated...
Following is an Estimated Multiple Regression for Cigarette consumption in the US. Based on the estimated parameters, and other statistics, Answer the following questions:CigaConsm = 14.5 + 0.06LnInc – 0.65LnCigPr. + 0.025LnExcTax + 0.034GenderT-stats:            (2.90) ( 1.30)         (-2.25)                (2.40)                   (1.67)Where CigaConsm represents cigarette consumption in millions of boxes per year in a given state; Inc is median household income of the State; Cigpr is cigarette price per pack; Exctax is Excise tax per pack of Cigarette,...
In a study for housing demand, the following regression model was estimated. The standard errors of...
In a study for housing demand, the following regression model was estimated. The standard errors of each coefficient are shown in the parentheses below. log Qt = 4.17 – 0.24 log Pt + 0.96 log Yt + 0.46 log MOR15t - 0.52 MOR30t + εt (0.03) (0.32) (0.23) (0.40) Adj R 2= 0.84, DW = 2.75, N=30. Where, Q = quantity of housing demanded P = price of unit of housing Y = family income MOR15 = 15-year mortgage rate...
A researcher estimated the following regression model with a sample size of 36. ?? = ?0...
A researcher estimated the following regression model with a sample size of 36. ?? = ?0 + ?1??1 + ?2??2 + ? The researcher wanted to find out whether there is heteroscedasticity in the error variance and so applied the White’s heteroscedasticity test. The result is as follows: ?? = −5.8417 + 2.5629??1 + 0.6918??2 − 0.4081??1 2 − 0.0491??2 2 + 0.0015??1??2 R 2 = 0.2143 What conclusion can you assist the researcher to draw at 5 percent and...
Explain the differences between the regression model, the regression equation, and the estimated-regression equation. Discuss the...
Explain the differences between the regression model, the regression equation, and the estimated-regression equation. Discuss the application of regression analysis in business decision making. Give examples on how the regression analysis can be used in business.
Based on the following regression equation of teenage BMI, which one is the estimated BMI for...
Based on the following regression equation of teenage BMI, which one is the estimated BMI for a teenage boy who watches 2 hours of TV per day, eats 6 meals per day, and whose mother’s BMI is 16? BMI = 3.5 + 1.01 * Female + 1.03 * TV/day + 1.02 * Meals/day + .9 * MotherBMI (Assuming the slope of all predictors are statistically significant at the alpha level of .05.) PLEASE SPECIFY CORRECT ANSWER None provided. 26.08 28.08...
Distinguish between the following: Heteroskedasticity and autocorrelation specified regression model vs estimated regression equation data type...
Distinguish between the following: Heteroskedasticity and autocorrelation specified regression model vs estimated regression equation data type vs level of measurement ANOVA and Multiple Regression Outliers vs Influencers
Distinguish between the following: Heteroskedasticity and autocorrelation specified regression model vs estimated regression equation data type...
Distinguish between the following: Heteroskedasticity and autocorrelation specified regression model vs estimated regression equation data type vs level of measurement ANOVA and Multiple Regression Outliers vs Influencers Based on question 1e above, do you think the following scatter plots contain any outliers or any influential data points? Justify your answers on each plot. (iii)                                                                                          (iv) (i)                                                                                            (ii)      
In a regression model involving 64 observations, the following estimated regression equation was obtained: Y=29+18X1+43X2+877X3 For...
In a regression model involving 64 observations, the following estimated regression equation was obtained: Y=29+18X1+43X2+877X3 For this model SSR=700 and SSE=500 Required: a. Calculate the coefficient of determination for the above model. b. Calculate the correlation coefficient. c- Calculate the MSR. d. Calculate the computed F statistics for testing the significance of the above model.
The following estimated regression equation based on 10 observations was presented. ŷ = 21.1370 + 0.5903x1...
The following estimated regression equation based on 10 observations was presented. ŷ = 21.1370 + 0.5903x1 + 0.4920x2 Here, SST = 6,736.125, SSR = 6,228.375, sb1 = 0.0819, and sb2 = 0.0563. (a) Compute MSR and MSE. (Round your answers to three decimal places.) MSR=MSE= (b) Compute F and perform the appropriate F test. Use α = 0.05. State the null and alternative hypotheses. H0: β1 < β2 Ha: β1 ≥ β2 H0: β1 > β2 Ha: β1 ≤ β2...
The following estimated regression equation based on 10 observations was presented. ŷ = 25.1670 + 0.5705x1...
The following estimated regression equation based on 10 observations was presented. ŷ = 25.1670 + 0.5705x1 + 0.4960x2 Here, SST = 6,732.125, SSR = 6,221.375, sb1 = 0.0818,  and  sb2 = 0.0561. a) Compute MSR and MSE. (Round your answers to three decimal places.) MSR= MSE= Find the value of the test statistic. (Round your answer to two decimal places.) F = Perform a t test for the significance of β1. Use α = 0.05. Find the value of the test statistic....
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT