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Question: Deferred tax allowance study. A study was conducted to identify accounting choice variables that influence a manager’s decision to change the level of the deferred tax asset allowance at the firm (The Engineering Economist, January/February 2004). Data were collected for a sample of 329 firms that reported deferred tax assets in 2000. The dependent variable of interest (DTVA) is measured as the change in the deferred tax asset valuation allowance divided by the deferred tax asset. The independent variables used as predictors of DTVA are listed as follows:

LEVERAGE: x1= ratio of debt book value to shareholder’s equity

BONUS: x2 = 1 if firm maintains a management bonus plan,

0 if not

MVALUE: x3 = market value of common stock

BBATH: x4 = 1 if operating earnings negative and lower than last year,

0 if not

EARN: x5 = change in operating earnings divided by total assets

A first-order model was fit to the data with the following results (p-values in parentheses):

Ra2 = .280

y^=0.044+0.006x1-0.035x2-0.001x3+0.296x4+0.010x5

(.070) (.228) (.157) (.678) (.001) (.869)

  1. Interpret the estimate of the β coefficient for x4.
  2. The “Big Bath” theory proposed by the researchers’ states that the mean DTVA for firms with negative earnings and earnings lower than last year will exceed the mean DTVA of other firms. Is there evidence to support this theory? Test using α = .05.
  3. Interpret the value of Ra2.

Short Answer

Expert verified

Answer

  1. The value of coefficient of is 0.296 which is positive indicating a positive relation among DTVA and BBATH(x4) .
  2. 95% significance level, it can be concluded that .β40Hence it can be concluded with enough evidence that is not statistically significant for the model.
  3. The value of R2ais 0.28 indicating about 28% of variation in the data is explained by the model. This value is very low indicating that the model fitted to the data is not a good fit or ideal fit for the data.

Step by step solution

01

Given Information 

The predicted model is given as:
y=0.044+0.006x1-0.035x2-0.001x3+0.296x4+0.010x5

Where y is the dependent variable and x’s are the dependent variable. The standard error of y is givens as 0.070, the standard error for the constant term is 0.228 and the standard error for x1,x2,x3,x4,x5,are 0.157, 0.678, 0.001, and 0.869 respectively. The value for and we have to conduct the test at α=.05.

02

Interpretation of  β4

a.

The value of coefficient of x4 is 0.296 which is positive indicating a positive relation among DTVA and BBATH (x4) . However, the lower value of the coefficient indicates that the changes in DTVA due to the variable might not be very high (slope of the line is very steep).

03

Significance of β4 

b.

H0:β4=0Ha:β40

Here, t-test statistic,

t=β^4sβ^4=0.2960.001=296

Value of t0.025,328is 1.96

H0 is rejected if t-statistic>t0.05,24,24. For α=0.025, since,t>t0.05,31 sufficient evidence to reject H0 at 95% confidence interval.

Therefore,β40.

Hence, it can be concluded with enough evidence thatis not statistically significant for the model.

04

Interpretation of  R2a

c.

The adjusted R squared is a modified version of R-squared.It is a corrected goodness of fit measures for linear models, here the value ofR2a is 0.28 indicating about 28% of variation in the data is explained by the model. This value is very low indicating that the model fitted to the data is not a good fit or ideal fit for the data.

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Most popular questions from this chapter

Independent random samples from normal populations produced the results shown in the next table.

Sample 1


Sample 2

1.23.11.72.83.0

4.22.73.63.9

a. Calculate the pooled estimate of σ2.

b. Do the data provide sufficient evidence to indicate that μ21? Test using α=.10.

c. Find a 90% confidence interval for (μ1μ2).

d. Which of the two inferential procedures, the test of hypothesis in part b or the confidence interval in part c, provides more information about (μ1μ2)?

Two populations are described in each of the following cases. In which cases would it be appropriate to apply the small-sample t-test to investigate the difference between the population means?

a.Population 1: Normal distribution with variance σ12. Population 2: Skewed to the right with varianceσ22=σ12.

b. Population 1: Normal distribution with variance σ12. Population 2: Normal distribution with variance σ22σ12.

c. Population 1: Skewed to the left with variance σ12. Population 2: Skewed to the left with varianceσ22=σ12.

d. Population 1: Normal distribution with varianceσ12 . Population 2: Normal distribution with varianceσ22=σ12 .

e. Population 1: Uniform distribution with varianceσ12 . Population 2: Uniform distribution with variance σ22=σ12.

Whistle-blowing among federal employees. Whistle blowing refers to an employee’s reporting of wrongdoing by co-workers. A survey found that about 5% of employees contacted had reported wrongdoing during the past 12 months. Assume that a sample of 25 employees in one agency are contacted and let x be the number who have observed and reported wrongdoing in the past 12 months. Assume that the probability of whistle-blowing is .05 for any federal employee over the past 12 months.

a. Find the mean and standard deviation of x. Can x be equal to its expected value? Explain.

b. Write the event that at least 5 of the employees are whistle-blowers in terms of x. Find the probability of the event.

c. If 5 of the 25 contacted have been whistle-blowers over the past 12 months, what would you conclude about the applicability of the 5% assumption to this

agency? Use your answer to part b to justify your conclusion.

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A random sample of n = 6 observations from a normal distribution resulted in the data shown in the table. Compute a 95% confidence interval for σ2

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