A common tactic to manage earnings is to “stuff the channels”, that is, to ship product prematurely to dealers and customers, thereby inflating sales for the period. A case in point is Bristol-Myers Squibb Co. (BMS), a multinational pharmaceutical company headquartered in New York. In August 2004, the SEC announced a $150 million penalty levied against BMS. This was part of an agreement to settle charges by the SEC that the company had engaged in a fraudulent scheme to inflate sales and earnings in order to meet analysts’ earnings forecasts.

The scheme involved recognition of revenue on pharmaceutical products shipped to its wholesalers in excess of the amounts demanded by them. These shipments amounted to $1.5 billion U.S. during 2001-2002. To persuade its wholesalers to accept this excess inventory, BMS agreed to cover their carrying costs, amounting to millions of dollars per quarter. In addition, BMS understated its accruals for rebates and discounts allowed to its large customers.

According to the SEC, the company also engaged in “cookie jar” accounting. That is, it created phony reserves for disposals of unneeded plants and divisions during high-profit quarters. These would be transferred to reduce operating expenses in low-profit quarters when BMS’s earnings still fell short of amounts needed to meet forecasts.

Required:

1. Give reasons why managers would resort to extreme earnings management tactics such as these.

[4 marks]

2. Evaluate the effectiveness of stuffing the channels as an earnings management device. Consider both from the standpoint of a single year and over a series of years.

[5 marks]

1. Evaluate the effectiveness of cookie jar accounting as an earnings management device.

The following six (4) questions are based on the following data:

When performing calculations in the following problems, use the numbers in the table as-is. I.e., do NOT convert 8.5985 to 8.5985% (or 0.085985). Just use plain 8.5985.

1. Using the basic market model regression, R p = α + β R m + ϵ, what is the beta of this portfolio? Yes, this is an opportunity to practice regression analysis. You can use Excel or other tool of choice.

2. For precision, find the portfolio beta using the excess return market model:

R p − R f = α + β ∗ ( R m − R f ) + ϵ

[Hint: compute annual excess returns first, then run regression.]

3. Using the excess return beta β ∗ from the previous problem, what is Jensen's alpha for the portfolio?

[Hint: use Equation (17.6) from Moore (2015)]

4. What is the portfolio's M2 measure?

The following data set provides information on the lottery sales, proceeds, and prizes by year in Iowa.

You decided to find the linear equation that corresponds to sales and year. Create a graph using the sales and year. Add the linear equation to the graph. What is the y-intercept of the linear equation?

Round each value below to the nearest integer.

Provide your answer below: ____E+ ___

Please Use R studio and show all the steps to answer this question

NY Marathon 2013 the table below shows the winning times (in minutes) for men and women in the new york city marathon between 1978 and 2013. (the race was not run in 2012 because of superstorm sandy.) assuming that performances in the big apple resemble performances elsewhere, we can think of these data as a sample of performance in marathon competitions. Create a 90% confidence interval for the mean difference in winning times for male and female marathon competitors.

Please Use R studio to answer this question

NY Marathon 2013 the table below shows the winning times (in minutes) for men and women in the new york city marathon between 1978 and 2013. (the race was not run in 2012 because of superstorm sandy.) assuming that performances in the big apple resemble performances elsewhere, we can think of these data as a sample of performance in marathon competitions. Create a 90% confidence interval for the mean difference in winning times for male and female marathon competitors.

3300 Econometric HW

Problem 2.

Use the data in the “Autocorrelation” tab to test

1. For Autocorrelation using the Durbin Watson Test

2. Graph the Residuals and determine whether they are distributed normally or whether they are biased

USING MATLAB:

Using the data from table below fit a fourth-order polynomial to the data, but use a label for the year starting at 1 instead of 1872. Plot the data and the fourth-order polynomial estimate you found, with appropriate labels. What values of coefficients did your program find? What is the LMS loss function value for your model on the data?

The data from Exhibit 3 is also in the Excel file income.xls on the course website. Use Excel, along with this file, to determine Mrs. Bella’s real income for the last fifteen years. Do this by first converting each price index from percent by dividing by 100. Then, divide gross income by your converted (adjusted) price index. Using Excel, find the mean, median, standard deviation, and variance of her past real income. Explain the meaning of these statistics. Can you use mean income to forecast future earnings? Take into account both statistical and non-statistical considerations.

What are the key benefits and risks for Petrobras in acquiring Pecom in 2002?

Harvard Case: Drilling South: Petrobras Evaluates Pecom

What is the Homeland Secuirty Act of 2002? How did it come about, and what did it do? Explain in FULL detail.