To provide quantitative responses to policy issues (Points : 1) It is imperative to use common sense
You should qualify policy makers involved.
You should analyze empirical evidence.
Is typically impossible since policy questions are rarely quantifiable.
| Question 2. 2. Understanding the behavior of employment rates across the U.S. in December 2009 is an example of using: (Points : 1) |
Random controlled experiments
Experimental data
Panel data
Cross sectional data |
Question 3. 3. Cross-sectional data are data on one or more variables collected at several points in time, such as the census of population.
- (Points : 1)
|
True
False |
| Question 4. 4. Studying the impact of minimum wage changes in teenage unemployment in Asia from 1908 to today would be considered (Points : 1) |
Random controlled experiments
Time series data
Panel data
Cross sectional data |
| Question 5. 5. Economic theory makes statements or hypotheses that are mostly qualitative in nature. (Points : 1) |
True
False |
| Question 6. 6. Analyzing Hyper-inflation in country X from 1980 to 1990 can best be understood by all except. (Points : 1) |
Collecting empirical data.
Time series analysis
Econometrics
Economic and social reform |
| Question 7. 7. Most economic data is collected by way of : (Points : 1) |
Random controlled observations
Economic sense making
Prediction and estimation
Observations |
| Question 8. 8. All except ________ defines Econometrics. (Points : 1) |
The science of testing economic theory
Fitting mathematical economic models to real-world data.
A set of tools used for forecasting future values of economic variables.
Measuring the weight of economists and their view of the world. |
| Question 9. 9. Unlike physical sciences, most data collected in economics is experimental as the data collected is about understanding human behavior. (Points : 1) |
True
False |
| Question 10. 10. Analyzing Hyper-inflation in country X from 1980 to 2009 is representative of: (Points : 1) |
Random controlled experiments
Time series data
Panel data
Cross sectional data |
0 comments