ECON 313 Lecture 15: 15-Econ 313 Notes

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amethystscorpion557

15 Feb 2017

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The data shows a positive correlation between years of schooling and wage earned: econometric problems. But what matters is quality: solutions. Control for other factors, but this is hard since how can we measure ability. Indonesia have oil revenues so they build 61,000 schools in 1973: schools built in priority where there are few schools to start with, so 2 levels of program: high (where there are few schools) and low. Primary schools: students between 7 and 12 years old: students aged 2 to 6 in 1974: full exposure, students aged 12 to 17 in 1974: no exposure, students aged 18 to 24 in 1974: no exposure. Can we compare high and low regions: no since high regions had less schools to start with (poorer) Can we compare young (2 to 6) and old: no since education increases over time. Idea: compare high and low, young to old.

Related Questions

Determine whether each of the following statements is best explained by correlation without causation, an omitted variable, or reverse causation.

a. In cities that have more police, crime rates are higher: (Click to select)An omitted variableCorrelation without causationReverse causation.

b. Many retired people live in states where everyone uses air conditioning during the summer: (Click to select)An omitted variableReverse causationCorrelation without causation.

c. More people come down with the flu during the Winter Olympics than during the Summer Olympics: (Click to select)Correlation without causationReverse causationAn omitted variable.

d. For the last five years, Punxsutawney Phil has seen his shadow on Groundhog Day, and spring has come late:

Alternative explanations of wage disparities

Suppose that a labor economist performs a statistical analysis on economy-wide worker wages using standard, measurable explanatory factors, such as job characteristics, years of schooling, and so forth.

How much of the variation in worker wages can be accounted for by such measurable explanatory factors?

-Somewhat more than 60%

-Somewhat less than 50%

-About 0%

-Nearly 100%

Which of the following factors are typically omitted from the quantitative analysis of wages but can help explain otherwise unaccounted for disparities? Check all that apply.

--Chance

--Natural ability

--Race

--Attractiveness

--Years of experience

Scientists are taught to follow the scientific method. In doing so, they should be assured that there is no bias in their science. However, is this always the case? Are there perspectives and beliefs that could bias a scientist's experiments and conclusions? Can you find examples?

Please list a short summary of the above question.

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ECON 313 Lecture 15: 15-Econ 313 Notes

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