Perspectives such as behaviorism and social cognitive theory show us how the consequence (reinforcement or punishment) of a particular behavior affects the extent to which the behavior is likely to appear again. Attribution theory has cast a new light on this notion, maintaining that the consequences of behavior will affect each person’s learning and future behavior differently depending on how the individual interprets those consequences. Within the context of attribution theory:

a. Explain what motivation theorists mean when they talk about attributions.

b. Explain how learners’ responses to failure are likely to be different when they attribute that failure to a controllable cause or to an uncontrollable one. Give a concrete example to illustrate your explanation.

c. Describe three specific strategies you might use to foster more productive attributions in others. In each case, use attribution theory to explain why you think the strategy should be effective.

Indicate whether the following statement is true/false/uncertain and explain why:

1. The Heckscher-Ohlin-Samuelson theory is likely to explain the rise of the skill premium in the US and other industrialized countries in recent decades, because in the data we have observed a rise in the price of skill-intensive goods relative to unskilled labor-intensive goods over the same period.

2. In the Melitz model if the transport cost t is zero then opening up to trade does not force the least productive firms to exit the market (compared to autarky)

3. An individual worker may be better off as a result of trade in the short run, but maybe worse off in the long run.

4. The HOS theory predicts that, if countries start trading goods, the factor prices(returns to factors, for example wages) will become more similar across countries.

Assignment Steps Resources: Microsoft Excel®, Signature Assignment Databases, Signature Assignment Options, Part 3: Inferential Statistics Scenario: Upon successful completion of the MBA program, say you work in the analytics department for a consulting company. Your assignment is to analyze one of the following databases: Manufacturing Hospital Consumer Food Financial Select one of the databases based on the information in the Signature Assignment Options. Provide a 1,600-word detailed, statistical report including the following: Explain the context of the case Provide a research foundation for the topic Present graphs Explain outliers Prepare calculations Conduct hypotheses tests Discuss inferences you have made from the results This assignment is broken down into four parts: Part 1 - Preliminary Analysis Part 2 - Examination of Descriptive Statistics Part 3 - Examination of Inferential Statistics Part 4 - Conclusion/Recommendations Part 1 - Preliminary Analysis (3-4 paragraphs) Generally, as a statistics consultant, you will be given a problem and data. At times, you may have to gather additional data. For this assignment, assume all the data is already gathered for you. State the objective: What are the questions you are trying to address? Describe the population in the study clearly and in sufficient detail: What is the sample? Discuss the types of data and variables: Are the data quantitative or qualitative? What are levels of measurement for the data? Part 2 - Descriptive Statistics (3-4 paragraphs) Examine the given data. Present the descriptive statistics (mean, median, mode, range, standard deviation, variance, CV, and five-number summary). Identify any outliers in the data. Present any graphs or charts you think are appropriate for the data. Note: Ideally, we want to assess the conditions of normality too. However, for the purpose of this exercise, assume data is drawn from normal populations. Part 3 - Inferential Statistics (2-3 paragraphs) Use the Part 3: Inferential Statistics document. Create (formulate) hypotheses Run formal hypothesis tests Make decisions. Your decisions should be stated in non-technical terms. Hint: A final conclusion saying "reject the null hypothesis" by itself without explanation is basically worthless to those who hired you. Similarly, stating the conclusion is false or rejected is not sufficient. Part 4 - Conclusion and Recommendations (1-2 paragraphs) Include the following: What are your conclusions? What do you infer from the statistical analysis? State the interpretations in non-technical terms. What information might lead to a different conclusion? Are there any variables missing? What additional information would be valuable to help draw a more certain conclusion?

This week we learned about the Foreign Corrupt Practices Act (FCPA). In that learning we saw that a key to reducing the penalty is through keeping books and records that are clean and transparent. Consider this case:

A USA public company doing business in Freedonia (a made up name from another Marx Brothers movie!) is compelled to bribe local officials in order to be the first to receive a business license for a certain type of industry there. The competition is fierce, but local government officials have unabashedly spread the word that under the table bribery payments to them from the USA company can seal the deal and that's why the USA company is feeling the pressure to participate in the bribe. This would be a violation of the FCPA.

The USA company participates in the fraud, bribing the government officials sufficiently to get the license first, before their competition. The payments are on the books, but hidden, so to speak, in order to get the tax deduction. The payments are cleverly disguised in the expense accounts to appear as normal expenditures.

You are the USA government investigator searching for the fraud after the US government has been tipped off that the fraud happened in Freedonia.

1. What income statement expense accounts would you research for evidence of bribery payments being made even though not so indicated as bribery payments?
2. What type of evidence would you be looking to gather to prove the case?
3. Company officials of the USA company did not want to have all the bribery expenditures traceable directly to them. How else could they disguise the actual payments from the company?
4. Given from your answers above, that the financial statements are obviously misstated, why it is that we don't often see public companies reissue their financials when these FCPA frauds are caught or admitted to?   
5. The USA company hires you to institute policies and procedures to prevent the company and its employees from participating in bribery/corruption schemes in the future. Describe what you advise the company to do.

Assume that at maximum hourly productions levels, the United States can produce either 8 yards of fabric or 4 bushels of wheat, whereas Japan can produce either 5 yards of fabric or 6 bushels of wheat. Based on this information,

Reading code that you haven't written is a skill you must develop. Many times you are correcting this code that you didn't write so you have to 1) read the code, 2) find the errors, and 3) correct them.

# Describe the error found in this function:

def get_grade():

grade = int(input("Enter your test score > ")

# Describe the error found in this function:

def all_As(test1, test2, test3):

if test1 > 89:

if test2 > 89:

if test3 > 89:

print("Wow! ", end="")

print("You scored 90 or above on all your exams!")

print("Keep up the As!")

print()

# Describe the error found in this function:

def calc_average(test1, test2, test3):

average = test1 + test2 + test3 / 3

return average

# Describe the error found in this function:

def letter_grade(grade):

if grade >= 90:

print("You earned an A")

if grade >= 80:

print("You earned an B")

if grade >= 70:

print("You earned an C")

if grade >= 60:

print("You earned an D")

if grade < 60:

print("You earned an F")

from grades import (

all_As,

calc_average,

get_grade,

letter_grade

)

# THERE ARE NO ERRORS IN THE MAIN

# YOU DO NOT NEED TO CHANGE THE MAIN

#-----main-----

print("Enter 3 test scores:")

first_test = get_grade()

second_test = get_grade()

third_test = get_grade()

print()

all_As(first_test, second_test, third_test)

average = calc_average(first_test, second_test, third_test)

print("Your test average is",average)

letter_grade(average)

When the program is correct, it should have output like this:

Enter 3 test scores:
Enter your test score >  100
Enter your test score >  90
Enter your test score >  91

Wow! You scored 90 or above on all your exams!
Keep up the As!

Your test average is 93.66666666666667
You earned an A

Motor Corp. manufactures machine parts for boat engines. The CEO, James Hamilton, is considering an offer from a subcontractor who would provide 3,000 units of product AB100 for Hamilton at a price of $230,000. If Motor Corp. does not purchase these parts from the subcontractor it must produce them in-house with the following per-unit costs: Direct materials $ 40 Direct labor 25 Variable overhead 15 Allocated fixed overhead 4 In addition to the above costs, if the company produces part AB100, it would incur incremental fixed overhead costs of approximately $10,000. Required: a) What would be the impact on short-term operating income if the company were to accept the offer from the subcontractor? Show calculations to support your answer. b) What strategic factors/considerations are generally relevant to the special-order decision problem (i.e., whether a company should accept a one-time order from a customer with whom the company does not generally do business)? b

1. [Cournot Competition - I]

Consider a Cournot duopoly model. Suppose that market demand is P = a−q1−q2, a > 0. Also suppose that the cost functions of the two firms are TC1(q1) = q21 and TC2(q2) = q22

(a) Write the profit function, and the first order condition.

(b) Find out the profit maximizing output for each firm.

(c) Find the profit earned by each firm, total profit earned by the two firms together.

(d) Now assume that the two firms collude and act as a monopoly. Find quantity

sold by the new monopoly firm and the profit earned. Compare the profit earned

by the monopoly with the total profit earned by the two firms in (c).

Betty Vinson was the director of management reporting at WorldCom. She had worked there for five years when the fraud was uncovered and received two promotions during that time. Vinson’s salary increased from $50,000 when she started to $80,000 in 2002. Vinson reported to Buford Yates, director of general accounting, who reported to David Myers, senior vice president, and controller, who then reported to CFO Scott Sullivan. (See Figure 1 for an organizational chart.) A hard worker who often stayed late or brought work home, Vinson considered herself lucky to land the job at WorldCom, as it was located in her hometown of Clinton, Miss. Vinson graduated from Mississippi College in 1978 and married her college sweetheart, Tom Vinson, a printing-equipment salesman who earned $40,000 a year. The couple had one daughter and lived a typical suburban lifestyle. Prior to working at WorldCom, Vinson worked as an accountant for various banking enterprises in Louisiana and Kansas City from 1978 to 1996. She also earned the Certified Public Accountant (CPA) credential during that time.

Problems began to emerge in the telecommunications industry in the late 1990s. The industry had over expanded, and every company was beginning to feel the effects, including WorldCom. By 2000, WorldCom’s expenses were increasing faster than revenues. In September 2000, WorldCom had to find $828 million to meet earnings targets expected by Wall Street. Vinson and her accounting colleagues found $50 million, but it wasn’t nearly enough. Senior management instructed her and her accounting coworkers to reduce reserve accounts for line costs to cover this shortfall. Reserves had been set aside based on estimates of potential losses, but they needed to have enough reason to reduce the reserve. Meeting earnings targets wasn’t a valid reason. Sullivan pressed Myers and Vinson’s boss, Yates, to make this adjustment. Yates told his accounting team that he had reservations, too, but that Sullivan promised this was a one-time adjustment. They all agreed to go along with the accounting adjustment. Vinson felt uncomfortable with this and considered resigning. The corporate accounting department’s discomfort with the entries prompted Sullivan to call the accountants into his office. He used an analogy that WorldCom was an aircraft carrier, and they needed to land the planes that were in the air. He urged them to wait until the planes had landed, and then they could leave the company if they still wanted to. Sullivan assured them that nothing they would do was illegal and that it wouldn’t be repeated. After talking to her husband, Vinson decided against resigning because of her family’s dependence on her salary and health insurance. In April 2001, the gap in meeting earnings targets was $771 million. The reserve pools weren’t large enough to cover this gap. Sullivan’s new strategy was to shift line costs, recorded as expenses, to capital expenditure accounts. Yates objected. Sullivan insisted it was the only way to cover this gap. Vinson and her coworker both felt cornered; this was clearly fraudulent accounting. The only choices now were to resign or make the entries. The three-person accounting team identified the capital accounts to use, and Vinson made the entries to transfer the $771 million. She backdated entries to February in the computer system and then indicated to colleagues at WorldCom that she was going to look for another job. These entries continued quarterly through April 2002. The Securities & Exchange Commission (SEC) was informed of the problem in June 2002 as a result of the efforts of the WorldCom internal audit team. The SEC would ultimately charge CFO Scott Sullivan, Controller David Myers, and accountants Buford Yates, Troy Normand, and Betty Vinson. According to the SEC complaint: “At the direction of WorldCom senior management, Vinson and other WorldCom employees caused WorldCom to overstate materially its earnings in contravention of generally accepted accounting principles (GAAP) for at least seven successive fiscal quarters, from as early as October 2000 through April 2002. Vinson knew or was reckless in not knowing, that these entries were made without supporting documentation, were not in conformity with GAAP, were not disclosed to the investing public, and were designed to allow WorldCom to appear to meet Wall Street analysts’ quarterly earnings estimates

Mr. Sullivan said:
Paraphrase    one    of    Sullivan’s    arguments?
This argument best describes the ____________________________________ “reason and rationalization” of GVV because
In response to Mr. Sullivan’s argument, Betty or Troy could have countered with something like:
Paraphrase another (a second) of Sullivan’s arguments, and follow the format above, etc. . . .

This question requires you to interpret and communicate the findings of two linear regression models. The data is from an article that studies the relationship between salaries of legislators and representation of the working-classes in state legislatures in the US.

Background

If politicians in the United States were paid better, would more working-class people become politicians? It is often argued that if politicians are paid too little, then it is economically too difficult for lower-income citizens to hold positions of office. This could mean that low-paying political jobs lead to the under-representation of working-class people in politics. On the other hand, if politicians are paid more, then holding political office might become more attractive to wealthy people, and this might also lead to the under-representation of working-class people. To investigate these two contrasting hypotheses, we will examine data on the salaries paid in different state legislatures in the US and the percentage of legislators who come from working-class backgrounds.

Dataset The dataset includes salaries of state legislators from all 50 states in the US. It also includes variables measuring information unique to each state such as the length of the legislative session and the number of staffers in each legislature. The occupational backgrounds of legislators are also included, as well demographic data on the makeup of the population in each state. A detailed description of the dataset is provided in the table below.

Variable                           Description

pct_worker                    Percentage of legislators from working-class backgrounds

salary.                            Average salary of legislators in $100,000s

session_len                     Length of legislative session (in days)

staff_size                       Average number of full-time permanent staffers in the legislature.

term_limits.                  Binary indicator (0 or 1) of term limits for state legislators

income.                          Average per-capita income (in $1000s)

income_inequality        Percentage of income to top 1% of earners

pct_union.                    Percentage of workers belonging to a labour union

pct_black                       Percentage of state residents who are Black

pct_urban                       Percentage of state residents living in urban areas

poverty_rate.               Percent of state residents living below the poverty line

3a. Multiple Linear Regression

This question requires you to interpret and communicate the findings of two linear regression models from Table 1.

Model 1 presents results from a simple linear regression, where the independent variable is salary. Model 2 presents results from a multiple linear regression which includes a number of explanatory variables. The dependent variable for both models is the percentage of legislators from working-class backgrounds.

Your task is to interpret the models and write up the results as if you were writing the discussion for publication in a major journal/book. Interpret the two models statistically and substantively, and in comparison to one another. You should focus on determining which variables have coefficients that are significantly different from zero, and what the effect sizes mean in substantive terms. Simply listing the significant effects will be insufficient to receive full marks. You should also comment on how the estimates differ between the two models, and on the fit statistics of the two models.

              Table 1: Legislative salaries and working-class representation

Model1                              Model2

(Intercept)                                      155.49                               −199.48

(41.00)                              (103.85)

Salary                                              −0.56                                −0.61

(0.10)                                 (0.13)

term_limits                                     0.26                                   (0.84)

income                                           −0.03                                 (0.05)

income_inequality                        −0.26                                 (0.11)

poverty_rate                                  −0.05                                 (0.07)

pct_union                                       0.12                                   (0.04)

pct_black                                        −0.06                                (0.02)

pct_urban                                       −0.03                                 (0.02)

R2(Rsquared)                                 0.19                                   0.35

Adj.(Rsquared)                              0.18                                   0.31

Num. obs.                                       200                                     200

Note: Figures in parentheses are the standard errors of the regression coefficients.