FIN822 Li1 Welcome to Econometrics. FIN822 Li2 Why study Econometrics? An empirical analysis uses...
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Transcript of FIN822 Li1 Welcome to Econometrics. FIN822 Li2 Why study Econometrics? An empirical analysis uses...
![Page 1: FIN822 Li1 Welcome to Econometrics. FIN822 Li2 Why study Econometrics? An empirical analysis uses data to test a theory or to estimate a relationship.](https://reader036.fdocuments.net/reader036/viewer/2022062517/56649ed15503460f94bdf45a/html5/thumbnails/1.jpg)
FIN822 Li 1
Welcome to Econometrics
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FIN822 Li 2
Why study Econometrics?
An empirical analysis uses data to test a theory or to estimate a relationship
A formal economic model can be tested
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FIN822 Li 3
Types of Data
Cross-sectional data is a random sample Each observation is a new individual, firm,
etc. with information at the same point in time
Time series data has a separate observation for each time period – e.g. daily stock prices of IBM over year 2005.
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FIN822 Li 4
Types of Data – Panel
If we pool cross sections and time series data together.
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To describe a single variable,
We may draw a histogram to see its disributions.
For time series variable, we can also plot a time-series plot.
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reurn
reurnN(0.0003829,0.025187)
Test statistic for normality:
Chi-squared(2) = 530.783 pvalue = 0.00000
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FIN822 Li 8
To describe relationship between variables
Scatter plot
Correlations, Regressions
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FIN822 Li 9
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FIN822 Li 10
The Question of Causality
Simply establishing a relationship between variables does not necessarily imply causality.
Can be difficult to establish causality. Example, a person’ height and sister’s height are positively correlated, but none is causing the other.
Sometimes we do not care, so long as it is useful in forecasting. (example, dating)
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FIN822 Li 11
Advanced topics
To test whether a single variable follows some specific distribution, we can do a Q-Q plot against that distribution.To test relationship between two variables
1. Pearson correlation (the ordinary correlation you are already familiar with)
2. Spearman correlation (also called rank correlation)
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If a Q-Q plot looks like a straight line, then
your variable may follow that distribution.
FIN822 Li 12
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FIN822 Li 13