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Background: Four students who are classmates in an Economics course decide to form a study group. They are holding their first study session in the college commons (aka cafeteria) for lunch after class; the lecture topic right before their study meeting was the supply and demand model; they have agreed that they should work first on that model. The study group is composed of three guys and one gal. The gal is a few minutes late for the meeting, so when she arrives the guys are already seated; the guys have all had a chance to look at the menu for the day.

Guy #1 says, "If they lowered the price of the special burger they would sell more of them."Guy # 2 says, "No, if they lowered the price of the special burger, demand for them would increase." Guy #3 says, I thought we were just taught that if they lowered the price of the special burger, their demand would increase, but their supply would decrease."

The gal decided earlier that she is going to invite the guy who has made the greatest contribution to the study session home to her new condo to pend the afternoon. She decides she will confine her assessment of the overall merits of the candidates to the issue on which they each have just made comment. Thus she will invite the guy who offered the correct analysis home with her for what she anticipates will be a very pleasant afternoon.

Question: Which guy should she invite, that is, which guy made the correct statement about the effect of lowering the price of the special burger? Assume that all three guys have the afternoon free and that all of them are equally attractive to our heroine. And, assume that she knows the correct answer because she took part of the same course last semester before she dropped so she could spend more hours at work to pay for the new condo. Explain your assessment fully.

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Divya Singh
Divya SinghLv10
28 Sep 2019

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Related questions

ECON102: SUPPLY AND DEMAND

THE BACKGROUND OF THE QUESTION IS STUPID, BUT IT'S NEEDED FOR THE QUESTION!!!

A student in a principles of economics course goes in to a coffee bar where she is scheduled to meet three classmates for a study session devoted to the market model of supply and demand. She orders her drink from the bar and sits down to join her classmates, who already have their drinks. The first guy says:"If this establishment lowered the price of their drinks the demand for them would increase." The second guy disagrees with the first guy and says, "If they lowered the price of drinks then only their quantity demanded would increase, but that lowering price, all other things equal, would not increase demand." The third guy counters, and insists that, "If the price of these drinks were to be lowered buy this outfit, demand would increase and supply would decrease." Our heroine wants to take the guy with the correct analysis home to her apartment to spend what she plans will be a very pleasant afternoon.

Which guy should she take home with her, that is, which guy did the correct analysis? Explain your reasoning fully. (Assume that the only relevant condition on her choice is correct analysis, that is, assume that all three guys are equally attractive and all are available for the afternoon.)

Case study : Protecting the public ( Engineering Economy )

The Greenacres City Council has just been informed that the city park may have had a lowgrade contaminant included with the latest annual mosquito spraying. The city’s health department has been assigned the task of testing for the contaminant and quantifying the health impact of exposure if the contaminant is present. Even though the department cannot yet quantify the effects, they have identified the causal chain for the health problems. The key link here is burning of contaminated vegetation, which puts the contaminant back in the air as a vapor. This vapor is irritating to the eyes and may cause acute damage to people wearing contact lenses. This is substantial evidence that there is no problem if it is touched or even eaten. Thus the chief danger appears to be campfires, disposal of windblown leaves (which would mix in with local residential area), or the chance of wildfire in the park. The health department has also verified that sunshine reduces the toxicity for the potential contaminant over a 2 to 3 year period. By year 4 the danger should be gone. Because of the adverse publicity that the council expects, it has decided that a benefit/cost analysis must be conducted immediately—before the health department can supply any results. In fact, their meeting is tomorrow night, and you (the city’s manager) have been ordered to have preliminary results by then. While they would like to have definitive conclusions, you believe that they will settle for an analysis that quantifies the two worst-case scenarios. One scenario involves removing all

vegetation and turning the park into a landfill, while the second scenario involves the maximum health cost in the complete absence of recovery efforts. The city engineer has dragged together the estimates for the landfill scenario. Here the first step is to remove the vegetation and burn it in a specially controlled environment where the exhaust is passed through a catalyst. Fortunately, the city is in an industrial area, so that facilities for disposal of hazardous wastes are available. If these facilities were not close by, then costs would be even higher than the expected $2 million to $5 million. The second step is to create a substantial cover by using the site as a temporary landfill. Fortunately, water table and location factors are positive, except that 20 homeowners will have to be bought out through eminent domain. The appraised value of their properties averages $135,400. The city engineer suggests that all of the other costs associated with using this as a landfill can be ignored, since the city would be incurring them at another site in any case. In about three years the cover would be deep enough and the landfill could be converted back into a park. The park currently emphasizes vegetation, jogging paths, and similar natural uses, but plantings and regrowth are likely to be far too slow. Thus the engineer has suggested using the area for a complex of playing fields for softball, baseball, soccer, and football. This would cut the regrowth time to the minimum and would only require $300,000 for construction. The planner for the city park department has looked at usage levels for other playing fields within the city, and has used benefit numbers developed for justification of another small group of playing fields last year. From this she has suggested that the playing field complex would have a “net benefit” stream of $125,000 annually after maintenance costs are considered. She also identified 5% as the discount rate that the city council accepted for that study. The scenario for health impacts if there is no recovery effort is far less defined. Here the difficulty lies in estimating the probability of different kinds of fires, and then estimating how many people might be affected. A wildfire is clearly the least likely; but it could affect the 35,000 people who live in moderate proximity to the park. The fire chief has estimated the normal wildfire possibility at .002, but this may increase to .01 due to publicity and arson. On the other hand, over a 3-year period, someone is almost certain to build a fire with a stick that has been sprayed. Over 20% of the park’s visitors are picnickers, and a quarter use wood, not charcoal fires. This year’s leaves are less of a problem, although taking all leaves to the special incinerator is likely to cost nearly $1 million (from close-by neighborhoods, as well as the park).
Cases in Engineering Economy 2nd by Peterson & Eschenbach

It is clear that, if the contaminant is there and if you burn it under your hamburger, there is still a sizable chance that you will have absolutely no problem. But, the exact danger is not known. It appears likely that the cumulative danger is related to park usage, which is currently 250,000 visitor-hours per year—growing at about 15,000 hours per year, slightly faster than the city’s population. You know that other uncertainties include the study period and the value of avoiding eye damage. Clearly, an exact answer is impossible. Nevertheless, an answer is required.

Suggestions to the Student 1. For the landfill/sports complex option, is it appropriate to include the benefits of the later years?

2. What study period, fraction of population with contacts, etc., must be guesstimated?

3. The role of population growth is likely to matter only for park usage, and not for potential eye damage. Why?

4. What other options should be suggested, based on the economic analysis? Which pieces of the two options have particularly good or poor benefit/cost impacts?

I need answer for this questions :

1) Case Study Description (it must be one page)

2) Case Study Questions .

3 ) Case Study Financials

What do you believe is the ultimate impact of technology on job creation? Should there be curbs to the pace of modernization?

(Answer in a paragraph(around 200 words))

What Econ 101 Can Teach Us About Artificial Intelligence

Here's why advancing technology often leads to more jobs for humans, not fewer

A Tesla Model X 75D semi-autonomous electric vehicle is parked at the Governor's Mansion in Olympia, Wash., this year. Goldman Sachs predicts that 25 years from now, driver employment will be growing by 300,000 less per year because of autonomous vehicles.

By Greg Ip

Aug 9, 2017

The first chart you draw in Economics 101 is the downward-sloping demand curve. It shows that when the price of something drops, people consume more of it.

This elementary rule of economics is remarkably helpful in discussing the effects of technological change. As I wrote last week, when technology makes something cheaper, we consume more of it, often by finding new uses. This lesson repeats through history: When coal-fueled steam power became more efficient in the 1800s, demand for steam power and coal spread. When automated teller machines made it cheaper to operate bank branches in the 1980s, banks opened more branches.

My column cites spreadsheet programs like Lotus 1-2-3, whose arrival in the early 1980s made repetitive recalculation vastly simpler and faster. This reduced demand for bookkeepers but created more demand for people who could run numbers in new and interesting ways, such as accountants and management consultants.

In a recent article for the Harvard Business Review, Ajay Agrawal, Joshua Gans and Avi Goldfarb, economists at the University of Toronto who study artificial intelligence, say that in the 1990s, economists didn’t buy into the hype that the internet and the World Wide Web would upend everything:

“It wasn’t that we didn’t recognize that something changed. It was that we recognized that the old economics lens remained useful for looking at the changes taking place. The economics of the ‘New Economy’ could be described at a high level: Digital technology would cause a reduction in the cost of search and communication. This would lead to more search, more communication, and more activities that go together with search and communication. That’s essentially what happened.”

They apply that lesson to artificial intelligence and more specifically to machine learning, the use of powerful algorithms to make predictions from patterns in large quantities of data. Machine learning, they say, means many problems will be reframed as prediction problems. Autonomous driving no longer involves programming the car to respond in a certain way to a variety of controlled scenarios, but instead, to watch what humans actually do and then respond the same way.

How does this affect jobs? The authors says it depends on whether the technology competes with or complements what you do. Spreadsheets competed with what bookkeepers do (record keeping and calculation) and thus made them less valuable, but complemented what accountants and consultants do (analysis), and made them more valuable.

Mssrs. Agrawal, Gans and Goldfarb say that AI reduces the value of those who predict things for a living, such as whether a mark on an X-ray is a tumor, but it raises the value of those who use predictions to make judgments:

“When prediction is cheap, diagnosis will be more frequent and convenient, and thus we’ll detect many more early-stage, treatable conditions. This will mean more decisions will be made about

medical treatment, which means greater demand for the application of ethics, and for emotional support, which are provided by humans.”

So AI will create winners and losers within and among industries and occupations. But what will the net effect be? More jobs or less, and for whom? This isn’t knowable, but history suggests that while a specific occupation or industry may suffer losses, the aggregate effects will be positive. The growth in accounting and analytical jobs since the early 1980s is much larger than the loss of bookkeeping jobs.

Nor did all those bookkeepers necessarily lose jobs; many probably became accountants or analysts. As Mr. Gans told me, bookkeepers may have been best placed to exploit the capabilities of spreadsheets: “If you were doing calculations all day as a bookkeeper, chances are you thought a bit about why you are doing that. When you got a spreadsheet, rather than doing one calculation per day you could do 10 to 50, so you had a better sense of what the [calculations] might say.”

Some readers said AI is a much bigger threat than spreadsheets because it has so many more potential applications—and they displace uniquely human abilities. I agree with the first part, less so with the second. I suspect workers in previous eras, whether they drove a horse and plow, handled a stock trade or connected a phone call, thought there was something about their job that a machine could never replace.

Will the disruptions this time around be greater? Maybe, but not necessarily. Goldman Sachs predicts that 25 years from now, driver employment will be growing by 300,000 less per year because of autonomous vehicles. That’s 25,000 jobs per month to make up, compared with the 5,000 per month that the decline in bookkeeping since 1985 represents. But it’s hardly insurmountable in a labor market where five million jobs are created and destroyed each month.

Others said I was ignoring the potential for rogue algorithms and robots to turn on us or strip us of our freedom.

The experts, of which I am not one, tell me AI is nowhere near that capability. (Before the robots can kill us they must first stop killing themselves.) And don’t assume spreadsheets have been all benign. Excel may not have slain anyone Terminator-style, but it did help wound J.P. Morgan through its role in the “London Whale” trading disaster.

Which brings me to the final point. We should not confuse what technology enables us to do with how much better off it makes us. Spreadsheets enabled analysts to construct much more intricate forecasts of stock prices and the economy, but didn’t make those forecasts any more accurate. AI may enable companies to better manage the risks of their products and actions, but those products and actions may not be more profitable. Many a CEO has wondered whether the money they spend on spreadsheet-wielding consultants yields any real value. Some day they may wonder the same thing about their AI-wielding consultants.

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