1. 178.280 Research Methods in Financial Economics
Lecture 2- Estimating the OLS Model

2. Introduction
Tough guys don’t do math. Tough guys fry chicken for a living.
-- Jaime Escalante (Stand and Deliver, 1988).

3. Outline Administration Readings: Simple OLS Model
Office Hours
Computer Labs
Readings:
Chapter 1, 2
Simple OLS Model
Objectives this week-
Find Eviews on the computer system
Practice working with data.
Estimate a simple OLS Model

4. Administration Tutorials and Labs start this week. Web site:
Signup sheets are still available.
Note: Labs are compulsory
Web site:
WebCT
Office hours will be announced this week.

5. Basic Stats We use statistical tools in this paper.
but it is not a course in statistics.
We estimate the value of certain parameters.
E.g. mean, regression-coefficient.
We signal our uncertainty about the parameter with ‘spreads’.
Examples
Variance
Standard Deviation
Standard error
This forms basis of hypothesis tests.

6. Recap
The main difference between statistics and other maths, is answers will have 2 dimensions
In normal algebra, variables combine to produce an explicit solution.
In statistics, we think in 2 dimensions
What we think the value of something is
How confident we are in that estimate

7. The OLS Regression
The OLS regression measures the relationship between 2 (or more) variables.
One variable is the dependent variable (Y).
One variable is the explanatory variable (X).
We estimate the relationship with the coefficient B1.
We measure the uncertainty about this estimate with its standard-error.

8. Aside OLS uses a least squares method.
It minimises the sum of the square of the residuals.
The estimate of Y consists of
Constant
Slope (beta)

9. Analysing the OLS Model
The model has a deterministic part.
That part of the value of Y we can successfully predict
Stochastic part
That part of Y we can’t explain or predict.
The stochastic part contains
Measurement errors
Missing variables
Genuine random effects
Non-linearities in the relationship.

10. Deterministic portion
General Equation
Dependent Variable
Explanatory Variable
Constant
Stochastic portion
Deterministic portion

11. What is B1?
How much Y changes, if we change X (all other things constant).
It is also the slope of the regression line.
Hence, it is dY/dX
Note
The slope changes if the units we measure X and Y change.
The slope approximates a derivative.

12. Eviews The Eviews window has: Tool bar
Top-pane (for manipulating variables)
Lower Scroll-bar (output may appear there)
Top Pane
Scroll
Bar

13. Data
New pane opens

14. Lab Introduction The data file is trade.wf1
We will estimate an ‘Absorption Model’ for NZ.
This uses National Income Accounting procedures.
Y=C+I+G+X-M
Hence
Y-C-I-G=X-M
Add/Substract TX from both sides
(Y-TX-C)-I+(TX-G)=(X-M)+TX-TX

15. Absorption Model Note- Y-TX-C equals Savings (S) So
(S-I)+(TX-G)=(X-M)
Net Private Savings + Net Public Savings = Current Account Balance
Net National Savings (NNS) = CAB
Implication: Economies with low savings rates (deficits) will run trade deficits.

16. Definitions C- Household consumption on final goods and services
I- Investment
G- Government Spending on goods and services
TX- Taxes
X- Exports
M- Imports (removed for double-counting purposes).
S- Household Income, less Consumption