Santos, as the head of the main regulatory body in Venezuela, must decide how to manage the effects

Joseph Glass, CFA, is a consultant who provides advisory services to large manufacturing companies. Glass has been retained by ABCO, a leading manufacturer of widgets for automobiles in the United States. ABCO has hired Glass to evaluate the possibility of expanding their current base of operations by building an additional facility in South America. Management of ABCO has identified anincrease in demand for widgets in South America over the past decade, and any new manufacturing facility would produce goods to satisfy that void and would be distributed and sold across South America.

Glass is not familiar with the current economic climate in South America, but is aware that several governments have attempted to encourage economic development in their countries through the enactment of pro-business legislation. Two of these countries, Venezuela and Peru, both have the reputations of being “friendly” to foreign economic investment within their borders. The two countries share some similarities: both, until the past twenty years, were primarily agricultural economies with little industrial development. Also, both countries can offer a relatively low-cost labor force, although their workers in general, are not highly skilled.

The government of Peru has declared that protecting the country’s environment is of utmost importance, and has established a regulatory body that oversees any environmental concerns that may arise as the country becomes more industrialized. Fairly stringent regulations have already been put into place in order to ensure that going forward, the operating practices of manufacturers within their country’s borders will be in balance with the government’s concern for their county’s natural resources. Regulations cover areas of concern such as air emissions, water conservation and the use of sustainable resources. Glass advised ABCO that a cost-benefit analysis must be performed to accurately determine both the direct and indirect costs of compliance with the regulations.

The Venezuelan government has taken steps to ensure that it can carefully manage the development of its country’s emerging economy, and to ensure that a competitive market is maintained. A regulatory agency was established five years ago to provide guidance for any new manufacturing concern seeking to operate in Venezuela. The head of the agency is Juan Santos, the former CEO of one of the first modernized manufacturing facilities in the country. During his tenure as head of the agency, he has demonstrated his ability to render decisions that attempt to simultaneously satisfy legislators, industry participants, and consumers. Glass is impressed by Santos’ work so far, but realizes that over the past five years, Venezuela has experienced a period of relatively slow economic development. Glass believes that Santos’ skills will truly be put to the test in the upcoming years of the anticipated economic expansion.

Glass acknowledges the need for governmental regulation of industry, but recognizes that there always are offsetting costs, both short-term and long-term of such controls. Based upon his knowledge of events that have occurred in the United States over the past thirty years, Glass recommends that ABCO continue to carefully monitor economic developments in both countries even after a site for a new manufacturing facility is selected.

Part 4)

The appointment of Santos, an industry “insider”, to head the regulatory agency in Venezuela has the potential to cause a reaction predicted by which of the following theories of regulatory behavior?

A) Rate-of-return regulation.

B) Share-the-gains, share-the-pains theory.

C) The capture hypothesis.

D) Cost-of-service regulation.

Joseph Glass, CFA, is a consultant who provides advisory services to large manufacturing companies. Glass has been retained by ABCO, a leading manufacturer of widgets for automobiles in the United States. ABCO has hired Glass to evaluate the possibility of expanding their current base of operations by building an additional facility in South America. Management of ABCO has identified anincrease in demand for widgets in South America over the past decade, and any new manufacturing facility would produce goods to satisfy that void and would be distributed and sold across South America.

Glass is not familiar with the current economic climate in South America, but is aware that several governments have attempted to encourage economic development in their countries through the enactment of pro-business legislation. Two of these countries, Venezuela and Peru, both have the reputations of being “friendly” to foreign economic investment within their borders. The two countries share some similarities: both, until the past twenty years, were primarily agricultural economies with little industrial development. Also, both countries can offer a relatively low-cost labor force, although their workers in general, are not highly skilled.

The government of Peru has declared that protecting the country’s environment is of utmost importance, and has established a regulatory body that oversees any environmental concerns that may arise as the country becomes more industrialized. Fairly stringent regulations have already been put into place in order to ensure that going forward, the operating practices of manufacturers within their country’s borders will be in balance with the government’s concern for their county’s natural resources. Regulations cover areas of concern such as air emissions, water conservation and the use of sustainable resources. Glass advised ABCO that a cost-benefit analysis must be performed to accurately determine both the direct and indirect costs of compliance with the regulations.

The Venezuelan government has taken steps to ensure that it can carefully manage the development of its country’s emerging economy, and to ensure that a competitive market is maintained. A regulatory agency was established five years ago to provide guidance for any new manufacturing concern seeking to operate in Venezuela. The head of the agency is Juan Santos, the former CEO of one of the first modernized manufacturing facilities in the country. During his tenure as head of the agency, he has demonstrated his ability to render decisions that attempt to simultaneously satisfy legislators, industry participants, and consumers. Glass is impressed by Santos’ work so far, but realizes that over the past five years, Venezuela has experienced a period of relatively slow economic development. Glass believes that Santos’ skills will truly be put to the test in the upcoming years of the anticipated economic expansion.

Glass acknowledges the need for governmental regulation of industry, but recognizes that there always are offsetting costs, both short-term and long-term of such controls. Based upon his knowledge of events that have occurred in the United States over the past thirty years, Glass recommends that ABCO continue to carefully monitor economic developments in both countries even after a site for a new manufacturing facility is selected.

Part 3)

If ABCO were to build its new facility in Peru, compliance with the country’s regulatory policies will increase the price of their product by approximately ten percent. Some consumers may respond by not replacing the widgets in their automobiles as frequently as before, which will cause decreased fuel efficiency. This unintended effect of regulation is an example of:

A) the capture hypothesis.

B) a creative response.

C) a feedback effect.

D) the share-the-gains, share-the-pains theory.

Joseph Glass, CFA, is a consultant who provides advisory services to large manufacturing companies. Glass has been retained by ABCO, a leading manufacturer of widgets for automobiles in the United States. ABCO has hired Glass to evaluate the possibility of expanding their current base of operations by building an additional facility in South America. Management of ABCO has identified anincrease in demand for widgets in South America over the past decade, and any new manufacturing facility would produce goods to satisfy that void and would be distributed and sold across South America.

Glass is not familiar with the current economic climate in South America, but is aware that several governments have attempted to encourage economic development in their countries through the enactment of pro-business legislation. Two of these countries, Venezuela and Peru, both have the reputations of being “friendly” to foreign economic investment within their borders. The two countries share some similarities: both, until the past twenty years, were primarily agricultural economies with little industrial development. Also, both countries can offer a relatively low-cost labor force, although their workers in general, are not highly skilled.

The government of Peru has declared that protecting the country’s environment is of utmost importance, and has established a regulatory body that oversees any environmental concerns that may arise as the country becomes more industrialized. Fairly stringent regulations have already been put into place in order to ensure that going forward, the operating practices of manufacturers within their country’s borders will be in balance with the government’s concern for their county’s natural resources. Regulations cover areas of concern such as air emissions, water conservation and the use of sustainable resources. Glass advised ABCO that a cost-benefit analysis must be performed to accurately determine both the direct and indirect costs of compliance with the regulations.

The Venezuelan government has taken steps to ensure that it can carefully manage the development of its country’s emerging economy, and to ensure that a competitive market is maintained. A regulatory agency was established five years ago to provide guidance for any new manufacturing concern seeking to operate in Venezuela. The head of the agency is Juan Santos, the former CEO of one of the first modernized manufacturing facilities in the country. During his tenure as head of the agency, he has demonstrated his ability to render decisions that attempt to simultaneously satisfy legislators, industry participants, and consumers. Glass is impressed by Santos’ work so far, but realizes that over the past five years, Venezuela has experienced a period of relatively slow economic development. Glass believes that Santos’ skills will truly be put to the test in the upcoming years of the anticipated economic expansion.

Glass acknowledges the need for governmental regulation of industry, but recognizes that there always are offsetting costs, both short-term and long-term of such controls. Based upon his knowledge of events that have occurred in the United States over the past thirty years, Glass recommends that ABCO continue to carefully monitor economic developments in both countries even after a site for a new manufacturing facility is selected.

Part 2)

The social regulation policies enacted by the government of Peru would least likely to cause which of the following outcomes?

A) Higher costs of production.

B) A disproportionately higher compliance expense for larger firms rather than smaller firms.

C) Higher prices for the end consumer.

D) Attempts by industry participants to avoid compliance through creative response.

Joseph Glass, CFA, is a consultant who provides advisory services to large manufacturing companies. Glass has been retained by ABCO, a leading manufacturer of widgets for automobiles in the United States. ABCO has hired Glass to evaluate the possibility of expanding their current base of operations by building an additional facility in South America. Management of ABCO has identified anincrease in demand for widgets in South America over the past decade, and any new manufacturing facility would produce goods to satisfy that void and would be distributed and sold across South America.

Glass is not familiar with the current economic climate in South America, but is aware that several governments have attempted to encourage economic development in their countries through the enactment of pro-business legislation. Two of these countries, Venezuela and Peru, both have the reputations of being “friendly” to foreign economic investment within their borders. The two countries share some similarities: both, until the past twenty years, were primarily agricultural economies with little industrial development. Also, both countries can offer a relatively low-cost labor force, although their workers in general, are not highly skilled.

The government of Peru has declared that protecting the country’s environment is of utmost importance, and has established a regulatory body that oversees any environmental concerns that may arise as the country becomes more industrialized. Fairly stringent regulations have already been put into place in order to ensure that going forward, the operating practices of manufacturers within their country’s borders will be in balance with the government’s concern for their county’s natural resources. Regulations cover areas of concern such as air emissions, water conservation and the use of sustainable resources. Glass advised ABCO that a cost-benefit analysis must be performed to accurately determine both the direct and indirect costs of compliance with the regulations.

The Venezuelan government has taken steps to ensure that it can carefully manage the development of its country’s emerging economy, and to ensure that a competitive market is maintained. A regulatory agency was established five years ago to provide guidance for any new manufacturing concern seeking to operate in Venezuela. The head of the agency is Juan Santos, the former CEO of one of the first modernized manufacturing facilities in the country. During his tenure as head of the agency, he has demonstrated his ability to render decisions that attempt to simultaneously satisfy legislators, industry participants, and consumers. Glass is impressed by Santos’ work so far, but realizes that over the past five years, Venezuela has experienced a period of relatively slow economic development. Glass believes that Santos’ skills will truly be put to the test in the upcoming years of the anticipated economic expansion.

Glass acknowledges the need for governmental regulation of industry, but recognizes that there always are offsetting costs, both short-term and long-term of such controls. Based upon his knowledge of events that have occurred in the United States over the past thirty years, Glass recommends that ABCO continue to carefully monitor economic developments in both countries even after a site for a new manufacturing facility is selected.

Part 1)

Should ABCO build a new facility in either of the two countries, it is almost a certainty that they would be the low-cost producer of widgets, with the capacity to satisfy nearly all demand in the region. A natural monopolist operating in an unregulated industry will produce at the point where:

A) marginal costs equal marginal revenue.

B) average costs equal marginal revenue.

C) average costs equal average revenue.

D) the marginal cost curve intersects the demand schedule.

Clara Holmes, CFA, is attempting to model the importation of an herbal tea into the United States. She gathers 24 years of annual data, which is in millions of inflation-adjusted dollars. The real dollar value of the tea imports has grown steadily from $30 million in the first year of the sample to $54 million in the most recent year.

She computes the following equation:

(Tea Imports)t = 3.8836 + 0.9288 × (Tea Imports)t ? 1 + et

t-statistics (0.9328)(9.0025)

R2 = 0.7942

Adj. R2 = 0.7844

SE = 3.0892

N = 23

Holmes and her colleague, John Briars, CFA, discuss the implication of the model and how they might improve it. Holmes is fairly satisfied with the results because, as she says “the model explains 78.44 percent of the variation in the dependent variable.” Briars says the model actually explains more than that.

Briars asks about the Durbin-Watson statistic. Holmes said that she did not compute it, so Briars reruns the model and computes its value to be 2.1073. Briars says “now we know serial correlation is not a problem.” Holmes counters by saying “rerunning the model and computing the Durbin-Watson statistic was unnecessary because serial correlation is never a problem in this type of time-series model.”

Briars and Holmes decide to ask their company’s statistician about the consequences of serial correlation. Based on what Briars and Holmes tell the statistician, the statistician informs them that serial correlation will only affect the standard errors and the coefficients are still unbiased. The statistician suggests that they employ the Hansen method, which corrects the standard errors for both serial correlation and heteroskedasticity.

Given the information from the statistician, Briars and Holmes decide to use the estimated coefficients to make some inferences. Holmes says the results do not look good for the future of tea imports because the coefficient on (Tea Import)t ? 1 is less than one. This means the process is mean reverting. Using the coefficients in the output, says Holmes, “we know that whenever tea imports are higher than 41.810, the next year they will tend to fall. Whenever the tea imports are less than 41.810, then they will tend to rise in the following year.” Briars agrees with the general assertion that the results suggest that imports will not grow in the long run and tend to revert to a long-run mean, but he says the actual long-run mean is 54.545. Briars then computes the forecast of imports three years into the future.

Part 6)

Given the output, the most obvious potential problem that Briars and Holmes need to investigate is:

A) a unit root.

B) conditional heteroskedasticity.

C) unconditional heteroskedasticity.

D) multicollinearity.

Clara Holmes, CFA, is attempting to model the importation of an herbal tea into the United States. She gathers 24 years of annual data, which is in millions of inflation-adjusted dollars. The real dollar value of the tea imports has grown steadily from $30 million in the first year of the sample to $54 million in the most recent year.

She computes the following equation:

(Tea Imports)t = 3.8836 + 0.9288 × (Tea Imports)t ? 1 + et

t-statistics (0.9328)(9.0025)

R2 = 0.7942

Adj. R2 = 0.7844

SE = 3.0892

N = 23

Holmes and her colleague, John Briars, CFA, discuss the implication of the model and how they might improve it. Holmes is fairly satisfied with the results because, as she says “the model explains 78.44 percent of the variation in the dependent variable.” Briars says the model actually explains more than that.

Briars asks about the Durbin-Watson statistic. Holmes said that she did not compute it, so Briars reruns the model and computes its value to be 2.1073. Briars says “now we know serial correlation is not a problem.” Holmes counters by saying “rerunning the model and computing the Durbin-Watson statistic was unnecessary because serial correlation is never a problem in this type of time-series model.”

Briars and Holmes decide to ask their company’s statistician about the consequences of serial correlation. Based on what Briars and Holmes tell the statistician, the statistician informs them that serial correlation will only affect the standard errors and the coefficients are still unbiased. The statistician suggests that they employ the Hansen method, which corrects the standard errors for both serial correlation and heteroskedasticity.

Given the information from the statistician, Briars and Holmes decide to use the estimated coefficients to make some inferences. Holmes says the results do not look good for the future of tea imports because the coefficient on (Tea Import)t ? 1 is less than one. This means the process is mean reverting. Using the coefficients in the output, says Holmes, “we know that whenever tea imports are higher than 41.810, the next year they will tend to fall. Whenever the tea imports are less than 41.810, then they will tend to rise in the following year.” Briars agrees with the general assertion that the results suggest that imports will not grow in the long run and tend to revert to a long-run mean, but he says the actual long-run mean is 54.545. Briars then computes the forecast of imports three years into the future.

Part 5)

With respect to the comments of Holmes and Briars concerning the mean reversion of the import data, the long-run mean value that:

A) Briars computes is correct, but the conclusion is probably not accurate.

B) Briars computes is not correct, but his conclusion is probably accurate.

C) Holmes computes is not correct, and her conclusion is probably not accurate.

D) Briars computes is correct, and his conclusion is probably accurate.

Clara Holmes, CFA, is attempting to model the importation of an herbal tea into the United States. She gathers 24 years of annual data, which is in millions of inflation-adjusted dollars. The real dollar value of the tea imports has grown steadily from $30 million in the first year of the sample to $54 million in the most recent year.

She computes the following equation:

(Tea Imports)t = 3.8836 + 0.9288 × (Tea Imports)t ? 1 + et

t-statistics (0.9328)(9.0025)

R2 = 0.7942

Adj. R2 = 0.7844

SE = 3.0892

N = 23

Holmes and her colleague, John Briars, CFA, discuss the implication of the model and how they might improve it. Holmes is fairly satisfied with the results because, as she says “the model explains 78.44 percent of the variation in the dependent variable.” Briars says the model actually explains more than that.

Briars asks about the Durbin-Watson statistic. Holmes said that she did not compute it, so Briars reruns the model and computes its value to be 2.1073. Briars says “now we know serial correlation is not a problem.” Holmes counters by saying “rerunning the model and computing the Durbin-Watson statistic was unnecessary because serial correlation is never a problem in this type of time-series model.”

Briars and Holmes decide to ask their company’s statistician about the consequences of serial correlation. Based on what Briars and Holmes tell the statistician, the statistician informs them that serial correlation will only affect the standard errors and the coefficients are still unbiased. The statistician suggests that they employ the Hansen method, which corrects the standard errors for both serial correlation and heteroskedasticity.

Given the information from the statistician, Briars and Holmes decide to use the estimated coefficients to make some inferences. Holmes says the results do not look good for the future of tea imports because the coefficient on (Tea Import)t ? 1 is less than one. This means the process is mean reverting. Using the coefficients in the output, says Holmes, “we know that whenever tea imports are higher than 41.810, the next year they will tend to fall. Whenever the tea imports are less than 41.810, then they will tend to rise in the following year.” Briars agrees with the general assertion that the results suggest that imports will not grow in the long run and tend to revert to a long-run mean, but he says the actual long-run mean is 54.545. Briars then computes the forecast of imports three years into the future.

Part 4)

Using the model’s results, Briar’s forecast for three years into the future is:

A) $54.108 million.

B) $47.151 million.

C) $51.450 million.

D) $54.543 million.

Clara Holmes, CFA, is attempting to model the importation of an herbal tea into the United States. She gathers 24 years of annual data, which is in millions of inflation-adjusted dollars. The real dollar value of the tea imports has grown steadily from $30 million in the first year of the sample to $54 million in the most recent year.

She computes the following equation:

(Tea Imports)t = 3.8836 + 0.9288 × (Tea Imports)t ? 1 + et

t-statistics (0.9328)(9.0025)

R2 = 0.7942

Adj. R2 = 0.7844

SE = 3.0892

N = 23

Holmes and her colleague, John Briars, CFA, discuss the implication of the model and how they might improve it. Holmes is fairly satisfied with the results because, as she says “the model explains 78.44 percent of the variation in the dependent variable.” Briars says the model actually explains more than that.

Briars asks about the Durbin-Watson statistic. Holmes said that she did not compute it, so Briars reruns the model and computes its value to be 2.1073. Briars says “now we know serial correlation is not a problem.” Holmes counters by saying “rerunning the model and computing the Durbin-Watson statistic was unnecessary because serial correlation is never a problem in this type of time-series model.”

Briars and Holmes decide to ask their company’s statistician about the consequences of serial correlation. Based on what Briars and Holmes tell the statistician, the statistician informs them that serial correlation will only affect the standard errors and the coefficients are still unbiased. The statistician suggests that they employ the Hansen method, which corrects the standard errors for both serial correlation and heteroskedasticity.

Given the information from the statistician, Briars and Holmes decide to use the estimated coefficients to make some inferences. Holmes says the results do not look good for the future of tea imports because the coefficient on (Tea Import)t ? 1 is less than one. This means the process is mean reverting. Using the coefficients in the output, says Holmes, “we know that whenever tea imports are higher than 41.810, the next year they will tend to fall. Whenever the tea imports are less than 41.810, then they will tend to rise in the following year.” Briars agrees with the general assertion that the results suggest that imports will not grow in the long run and tend to revert to a long-run mean, but he says the actual long-run mean is 54.545. Briars then computes the forecast of imports three years into the future.

Part 3)

The statistician’s statement concerning the benefits of the Hansen method is:

A) correct, because the Hansen method adjusts for problems associated with both serial correlation and heteroskedasticity.

B) not correct, because the Hansen method only adjusts for problems associated with serial correlation but not heteroskedasticity.

C) not correct, because the Hansen method only adjusts for problems associated with heteroskedasticity but not serial correlation.

D) not correct, because the Hansen method does not adjust for problems associated with either serial correlation or heteroskedasticity.

Clara Holmes, CFA, is attempting to model the importation of an herbal tea into the United States. She gathers 24 years of annual data, which is in millions of inflation-adjusted dollars. The real dollar value of the tea imports has grown steadily from $30 million in the first year of the sample to $54 million in the most recent year.

She computes the following equation:

(Tea Imports)t = 3.8836 + 0.9288 × (Tea Imports)t ? 1 + et

t-statistics (0.9328)(9.0025)

R2 = 0.7942

Adj. R2 = 0.7844

SE = 3.0892

N = 23

Holmes and her colleague, John Briars, CFA, discuss the implication of the model and how they might improve it. Holmes is fairly satisfied with the results because, as she says “the model explains 78.44 percent of the variation in the dependent variable.” Briars says the model actually explains more than that.

Briars asks about the Durbin-Watson statistic. Holmes said that she did not compute it, so Briars reruns the model and computes its value to be 2.1073. Briars says “now we know serial correlation is not a problem.” Holmes counters by saying “rerunning the model and computing the Durbin-Watson statistic was unnecessary because serial correlation is never a problem in this type of time-series model.”

Briars and Holmes decide to ask their company’s statistician about the consequences of serial correlation. Based on what Briars and Holmes tell the statistician, the statistician informs them that serial correlation will only affect the standard errors and the coefficients are still unbiased. The statistician suggests that they employ the Hansen method, which corrects the standard errors for both serial correlation and heteroskedasticity.

Given the information from the statistician, Briars and Holmes decide to use the estimated coefficients to make some inferences. Holmes says the results do not look good for the future of tea imports because the coefficient on (Tea Import)t ? 1 is less than one. This means the process is mean reverting. Using the coefficients in the output, says Holmes, “we know that whenever tea imports are higher than 41.810, the next year they will tend to fall. Whenever the tea imports are less than 41.810, then they will tend to rise in the following year.” Briars agrees with the general assertion that the results suggest that imports will not grow in the long run and tend to revert to a long-run mean, but he says the actual long-run mean is 54.545. Briars then computes the forecast of imports three years into the future.

Part 2)

With respect to the statement that the company’s statistician made concerning the consequences of serial correlation, assuming the company’s statistician is competent, we would most likely deduce that Holmes and Briars did not tell the statistician:

A) the sample size.

B) the value of the Durbin-Watson statistic.

C) that the intercept coefficient is not significant.

D) the model’s specification.

Clara Holmes, CFA, is attempting to model the importation of an herbal tea into the United States. She gathers 24 years of annual data, which is in millions of inflation-adjusted dollars. The real dollar value of the tea imports has grown steadily from $30 million in the first year of the sample to $54 million in the most recent year.

She computes the following equation:

(Tea Imports)t = 3.8836 + 0.9288 × (Tea Imports)t ? 1 + et

t-statistics (0.9328)(9.0025)

R2 = 0.7942

Adj. R2 = 0.7844

SE = 3.0892

N = 23

Holmes and her colleague, John Briars, CFA, discuss the implication of the model and how they might improve it. Holmes is fairly satisfied with the results because, as she says “the model explains 78.44 percent of the variation in the dependent variable.” Briars says the model actually explains more than that.

Briars asks about the Durbin-Watson statistic. Holmes said that she did not compute it, so Briars reruns the model and computes its value to be 2.1073. Briars says “now we know serial correlation is not a problem.” Holmes counters by saying “rerunning the model and computing the Durbin-Watson statistic was unnecessary because serial correlation is never a problem in this type of time-series model.”

Briars and Holmes decide to ask their company’s statistician about the consequences of serial correlation. Based on what Briars and Holmes tell the statistician, the statistician informs them that serial correlation will only affect the standard errors and the coefficients are still unbiased. The statistician suggests that they employ the Hansen method, which corrects the standard errors for both serial correlation and heteroskedasticity.

Given the information from the statistician, Briars and Holmes decide to use the estimated coefficients to make some inferences. Holmes says the results do not look good for the future of tea imports because the coefficient on (Tea Import)t ? 1 is less than one. This means the process is mean reverting. Using the coefficients in the output, says Holmes, “we know that whenever tea imports are higher than 41.810, the next year they will tend to fall. Whenever the tea imports are less than 41.810, then they will tend to rise in the following year.” Briars agrees with the general assertion that the results suggest that imports will not grow in the long run and tend to revert to a long-run mean, but he says the actual long-run mean is 54.545. Briars then computes the forecast of imports three years into the future.

Part 1)

With respect to the statements made by Holmes and Briars concerning serial correlation and the importance of the Durbin-Watson statistic:

A) Holmes was correct and Briars was incorrect.

B) Briars was correct and Holmes was incorrect.

C) they were both correct.

D) they were both incorrect.