1. Economic Methods and Economic Questions
Microeconomics
Second Edition
Chapter 2
Economic Methods and Economic Questions

2. Learning Objectives
2.1 The Scientific Method 2.2 Causation and Correlation 2.3 Economic Questions and Answers

3. Key Ideas (1 of 2) A model is a simplified description of reality.
Economists use data to evaluate the accuracy of models and understand how the world works.
Correlation does not imply causality.

4. Key Ideas (2 of 2)
Experiments help economists to measure cause and effect.
Economic research focuses on questions that are important to society and can be answered with models and data.

5. Evidence-Based Economics (1 of 2)
Is college worth it?
During the 2015–2016 academic year, tuition averaged $3,435 for community colleges, $9,410 for instate public colleges, $23,893 for out-of-state public colleges, and $32,405 for nonprofit private colleges. And that’s not the only cost.
Your time is worth $10 or more per hour—this time value adds at least $15,000 per year to the opportunity cost of a college education.

6. Evidence-Based Economics (2 of 2)
Evidenced-Based Example: academic year tuition averaged $3,435 for community colleges $9,410 for instate public colleges $23,893 for out-of-state public colleges $32,405 for nonprofit private colleges At least $15,000 per year in opportunity cost
During the 2015–2016 academic year, tuition averaged $3,435 for community colleges, $9,410 for instate public colleges, $23,893 for out-of-state public colleges, and $32,405 for nonprofit private colleges. And that’s not the only cost.
Your time is worth $10 or more per hour—this time value adds at least $15,000 per year to the opportunity cost of a college education.

7. The Scientific Method (1 of 17)
The scientific method (also referred to as empiricism) is composed of two steps:
Developing models that explain some part of the world
Testing those models using data to see how closely the model matches what we actually observe

8. The Scientific Method (2 of 17)
What is this? Does it look like anyone you know?
Students will say that it’s a face—or some variation of a face.
When you ask them if it looks like anyone they know, they (hopefully) will say that it doesn’t. You can use this as an example of a model. It represents something, but very simply—it abstracts from reality.

9. The Scientific Method (3 of 17)
Model
A simplified description of reality Is this an airplane?
To bring the point even further, you can make a paper airplane. Ask students if this is an airplane? They may be a bit confused and say that it’s a paper airplane…Ask again, is this an airplane? They will say that it is not. Ask if it can fly. They’ll say that it can. Throw it out into the classroom and have someone throw it back. Point out that it does fly—it has aerodynamic qualities that can be adjusted (if you want, you can adjust the paper airplane a bit—bend one wing up and not the other to make it bank, for example). Throw it back and point out that it does turn.
Tell the story of the Wright brothers. Everyone else who was trying to make an airplane that could actually fly built real airplanes, tried to get them up in the air, but they crashed. The reason the Wright brothers were successful is because they built a wind tunnel and built models of airplanes, tested different designs until they found one that worked in the tunnel. Then they built an actual plane.
The point is that models are not meant to be perfect replications of the real world. They do give us insights into what is likely to happen. They are meant to convey an idea as simply as possible while still representing the essence of the idea.

10. The Scientific Method (4 of 17)
Exhibit 2.1 Flying from New York to Tokyo Requires More Than a Flat Map
What’s the shortest distance between two points?
Remind students that they have learned that the shortest distance between two points is a straight line. But not when you’re flying. At least it seems so. If you want to go from NYC to London and you’re just looking at a map, then a straight line is the shortest distance. But if you’re actually flying between the two cities, a straight line is not the shortest distance because flat maps distort the shape of the earth. When you take something that’s a sphere and flatten it into a map, the distances between points (especially the closer to the poles you are) get exaggerated and no longer reflect reality. In some cases, a flat map is a good model of reality, but in others, it is not. So flight paths, when viewed on flat maps, look much more like parabolas than straight lines.

11. The Scientific Method (5 of 17)
Evidenced-Based Example: Returns to education Assumption—one more year of education results in a 10% increase in future earnings
It is important to point out that all models are built on assumptions. It is also important to point out that assumptions are not just pulled out of the air. Instead, they are based on previous research results, or educated predictions about relationships. Assumptions are, however, simplifications of reality. Tell students that you will return to this assumption later.

12. The Scientific Method (6 of 17)
Returns to education: If you would earn $15 per hour with 13 years of education, with one more year of education (your 1st year of college) you would earn: First Year $15 × 1.10 = $16.50
Now taking the previous assumption and turning it into a mathematical model

13. The Scientific Method (7 of 17)
Returns to education: If you would earn $16.50 with 14 years of education, with one more year of education (2nd year of college), you would earn: Second Year $16.50 x 1.10 = $18.15

14. The Scientific Method (8 of 17)
Returns to education: The third year: $18.15 x 1.1 = $19.97 The fourth year: $19.97 x 1.1 = $21.97
$18.15 x 1.1 = $ ≈ $19.97 and $19.97 x 1.1 = $ ≈ $ You could also follow the text and use the factor of The math might be difficult for some students so the alternative is presented here.

15. The Scientific Method (9 of 17)
Returns to education: Hypothesis: Getting a college degree (years 13-16) increases wages from $15 to $21.97, or 46.5% [(($ $15)/$15) = .4647]

16. The Scientific Method (10 of 17)
Two important features of models:
They are not exact. Not everyone will see his or her wages increase by 10% with every additional year of education
They generate predictions that can be tested with data
Now ready to answer the evidence-based economics question

17. The Scientific Method (11 of 17)
Hypothesis: Each additional year of education increases wages by 10% True or False?

18. The Scientific Method (12 of 17)
Exhibit 2.3 Average Annual Earnings of 30-Year-Old Americans by Education Level (2014 data)

19. The Scientific Method (13 of 17)
How much higher is the wage for college graduates than for high school graduates? College = $51,215 High School = $32,912 College results in a wage that is 56% higher.
Re-emphasize that models are not going to predict reality exactly. In this case, the model predicted wages that are 46% higher; the data show they are 57% higher. This is a model that is a good approximation of reality in this case, although in other applications, we might prefer a smaller difference (for example, in the case of drug trials).
Model predicted 46% higher. Is that close enough?

20. The Scientific Method (14 of 17)
If college graduates earn, on average, $51,215/year, does that mean that all college graduates earn that much?
Emphasize that the data that are used for many kinds of model-testing are based on averages, or means. You can show an example computation or go to the next slide to bring the point home that means are often not illustrative of the whole.

21. The Scientific Method (15 of 17)
The median is the value in the middle of a group of numbers, and the mean is the average value of the group of numbers
Emphasize that the data that are used for many kinds of model-testing are based on averages, or means. You can show an example computation or go to the next slide to bring the point home that means are often not illustrative of the whole.

22. The Scientific Method (16 of 17)
Can Bill Gates make you rich? When the range of incomes is skewed the mean is not a very accurate measure
Tell the class to assume that you are going to go around the class and get everyone’s income from last year and compute an average, or mean (you can review how that would be done, if you’d like). You can say, let’s assume it’s $25,000. Since all the incomes in your room are within a fairly small range, this mean is probably not a bad measure of the actual income of any one person. Now assume that Bill Gates walks into the classroom. Ask, what just happened to our average income? You can express excitement at this turn of events: Woohoo, we all just became millionaires! You can make the point that when the range of incomes (or anything else) is tightly clustered, mean is a pretty good measure. But when it’s skewed (a few at the high or low end), the mean is not a very accurate measure.
To show you how to make convincing empirical arguments, this course uses lots of real data from large groups of people. Credible empirical arguments, based on many observations, are a key component of the scientific method.

23. The Scientific Method (17 of 17)
Speaking of Bill Gates… How does his level of education affect his income?
Tell your students that Bill Gates is a college drop-out. Does that mean that the returns to education model is worthless?
No, because that observation—that dropping out of college leads to billionaire status—is based on one person. Conclusions based on small samples are suspect.

24. Causation and Correlation (1 of 13)
Buttercup
Tell students that you’d like to report on the results of two different studies. One study, from England, showed that cows who were named gave more milk than unnamed cows. The second study found that gamblers over 65 years of age are healthier than non-gamblers of the same age group.
When these studies were originally released, the news reports strongly implied that the one caused the other: that naming caused greater milk production; that gambling caused increased health among older people.
Ask if that makes sense to them.

25. Causation and Correlation (2 of 13)
A study from England showed that cows who were named gave more milk than unnamed cows Causation? or Correlation?
Tell students that you’d like to report on the results of two different studies. One study, from England, showed that cows who were named gave more milk than unnamed cows. The second study found that gamblers over 65 years of age are healthier than non-gamblers of the same age group.
When these studies were originally released, the news reports strongly implied that the one caused the other: that naming caused greater milk production; that gambling caused increased health among older people.
Ask if that makes sense to them.
Buttercup

26. Causation and Correlation (3 of 13)
Tell students that you’d like to report on the results of two different studies. One study, from England, showed that cows who were named gave more milk than unnamed cows.
The second study found that gamblers over 65 years of age are healthier than non-gamblers of the same age group.
When these studies were originally released, the news reports strongly implied that the one caused the other: that naming caused greater milk production; that gambling caused increased health among older people.
Ask if that makes sense to them.
A study here in the US found that gamblers over 65 are healthier than non-gamblers over 65 Causation? or Correlation?

27. Causation and Correlation (4 of 13)
Causation - When one thing directly affects another.
Example: pulling an all-nighter will make you tired
The two previous examples—are they examples of causation or correlation?
Ask students for reasons that naming a cow and milk production might be correlated. Gambling and healthy older people?
For the data on hemlines and economic conditions, go to

28. Causation and Correlation (5 of 13)
Correlation - When two things are related
Positive correlation – they both change in the same direction
(Increase in health over 65 => Increase over 65 gambling)
Negative correlation – they change in opposite directions
The two previous examples—are they examples of causation or correlation?
Ask students for reasons that naming a cow and milk production might be correlated. Gambling and healthy older people?
For the data on hemlines and economic conditions, go to

29. Causation and Correlation (6 of 13)
Why isn’t correlation the same thing as causality? 1. Omitted variables If we ignore something that contributes to cause and effect, then that something is an omitted variable. A correlation might not make sense until the omitted variable is added.
Buttercup is an example of omitted variable bias. Cows who are named also are generally more cared for. So it’s the extra care that accounts for the increased milk production, not the name.

30. Causation and Correlation (7 of 13)
Omitted Variables
Buttercup

31. Causation and Correlation (8 of 13)
Why isn’t correlation the same thing as causality? 2. Reverse causality Reverse causality is when there is cause and effect, but it goes in the opposite direction as what we thought.
The example of gambling and healthier older people is an example of reverse causality. Instead of gambling causing increased health among older folks, the causality runs the other way—increased health among older people causes more of all activities outside the home, including gambling.

32. Causation and Correlation (9 of 13)
Reverse Causality

33. Causation and Correlation (10 of 13)
How can we tell the difference between causality and correlation?
Experiments
Controlled = subjects are randomly put into treatment (something happens) and control (nothing happens) groups by the researcher.
Problem: difficult to do with economics studies
Example: naming the cows and looking at milk production is an example of a controlled experiment. The researcher can randomly assign cows into groups that get named, get pampered and see what happens to milk production. This is difficult to do with people, though, since something similar could actually be cruel. In order to understand if the treatment is really effective, however, everything needs to be the same between the two groups except the treatment. Then, any differences between the two groups can be attributed to the treatment.

34. Causation and Correlation (11 of 13)
Experiments
Natural = subjects end up in treatment or control groups due to something that is not purposefully determined by the researcher
Example: observing whether healthy older people engage in more gambling behavior is a natural experiment. The researcher observes the outcomes, but doesn’t direct the subjects into certain behaviors. Therefore the “observation” is done through analysis of data, not direct observation of the subjects.

35. Causation and Correlation (12 of 13)
Evidence-Based Economics and Natural Experiments
How much is an extra year of school worth? In 1947, the U.K. raised the minimum drop-out age from 14 to 15. Those students reaching age 14 before 1947 = control group Those students reaching age 14 in 1947 or after = treatment group
Point out that researchers didn’t assign students into these two groups—the assignment of subjects into these groups was beyond researchers’ control. On average, staying in school an extra year increased earnings by 10%, which is the basis of the assumption we made in the beginning of the chapter.

36. Causation and Correlation (13 of 13)
How much is an extra year of school worth? On average, staying in school an extra year increased earnings by 10%, which is the basis of the assumption we made in the beginning of the chapter. Economic assumption was based on a robust data set
Point out that researchers didn’t assign students into these two groups—the assignment of subjects into these groups was beyond researchers’ control. On average, staying in school an extra year increased earnings by 10%, which is the basis of the assumption we made in the beginning of the chapter.

37. Economic Questions and Answers
Two Properties of a Good Economic Question: 1. Relevant and important Economic research contributes to social welfare 2. Can be answered Economic questions can be answered empirically
You might want to make sure that students do not confuse the term “social welfare” with the term “welfare” as used to describe government benefits. Social welfare is a common economic term, meaning the greater good, creating an outcome that maximizes the well-being of the greatest number of people.

38. Copyright