Will you have issues related to multi-collinearity, heteroscedasticity and autocorrelation? If any of these problems exist, how can you fixed then after you do the regressions

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

DATA REPORT - REGRESSION

UPLOAD THE REGRESSION TABLES TO PROPER DROPBOX IN MyLS

This REGRESSION REPORT must include the following:

COVER PAGE

A tentative and interesting title for the paper.

Your name and student identification number.

INTRODUCTION

A FIFTH pass at formulating your RESEARCH QUESTION.

MOTIVATION: Why is your topic INTERESTING? Avoid stating personal reasons.

METHODOLOGY, REGRESSION EQUATION AND HYPOTHESES

Methodology:

Typically Ordinary Least Squares (OLS) regression

If using different econometric technique specify and describe technique and why it is useful for your analysis

If using fixed effects describe why the use of fixed effects is required in your study. Explain what the fixed effects variables are capturing.

If following an article in literature review

refer to it here and specify what you are adding to study

Empirical specification:

Explanation/description on how specification chosen

Specify regression equation using EQUATION EDITOR to type the equation

Y=α+β_1 X_1+β_2 X_2+β_2 X_2+ϵ

Better to give ACRONYMS to the variables in equation (but may get long) rather than X_i.

Use subscripts for variables that vary over time (t) or that vary by individual or by country or province.(i) or both i t

Y_it=α+β_1 X_1it+β_2 X_2it+β_2 X_2it+ϵ_it

These regression equations may include lag terms or quadratic terms if the effect of the variables is non-linear.

Y_it=α+β_1 X_1it+β_2 (X_1it )^2 + β_3 X_2it+β_4 X_3it+ϵ_it

If using lagged variables explain why lags are required. Below variable X_1it is lagged one period.

Y_it=α+β_1 X_1it+β_2 X_(1it-1) + β_3 X_2it+β_4 X_3it+ϵ_it

Describe SIGN of coefficients. Relate these signs to hypotheses being tested.

Assumptions made on ERROR TERM.

Will you have issues related to multi-collinearity, heteroscedasticity and autocorrelation? If any of these problems exist, how can you fixed then after you do the regressions, i.e., how can these problems be addressed?

REGRESSION ANALYSIS

You will run MORE regression specifications than you will include in report.Summarize regression results in TABLES (see table in the next page) For each regression in table need (see sample table below)

Coefficients

Identify with STARS significance level of coefficient (1%, 5% or 10%) In parenthesis below give t-statistic or p-value. Explain what these values mean in general terms  You may have more than one table of results.

FOOTNOTES in each table IDENTIFYING SIGNIFICANCE LEVELS.

Tables must be SINGLE SPACED.

The regression table should look more or less like this sample table:

Table 2: Regression results (Dependent variable, no. obs if same for all regressions)
Variable names	Regression 1	Regression 2	Regression 3	Regression 4	Regression 5
most important explanatory variable	0.9977 *** (t-stats/p-value)	0.9931 *** (0.15)	0.9761 *** (0.22)	0.9531 (1.15)	0.8937 (1.15)
		3.126 ** (2.21)	3.326 ** (2.21)	3.818 ** (2.21)	3.056 ** (2.21)
			0.2667 ** (0.15)	0.2811 ** (0.18)	0.1811 (0.19)
					2.1716 *** (0.21)
Fixed effects (if any)	Yes or No	Yes or No	Yes or No	Yes or No	Yes or No
No. obs if vary by regression
or adjusted

Note that you can create this table using STATA. You were taught how to do this in your econometric courses. A file with the instructions on how to do this will be available in MyLS under content.

A FIRST DRAFT of commenting on your results IN BULLET FORM.

Discuss your findings.

Discuss and interpret significance of most important variables included in your analysis

INTERPRET AND QUANTIFY YOUR RESULTS: For example, a 1% increase in variable X_i increases the dependent variable Y by 2%.

If the increase in Y is too small, try increasing X_i by 1 STANDARD DEVIATION and see what effect it has on Y, this calculation will have to be done manually using the regression coefficient for this variable.

Talk ONLY about the most important results. You will not have time to discuss all of your results.

CONCLUSION

What you LEARNED from your analysis.

Summarize your findings.

If you find that the coefficients were not statistically significantly different from zero for some variable, give a plausible explanation why this is the case.

Attachments:

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