Instructions
1) Describe the problem
a) Explain the motivation
b) Formulate the working hypothesis
2) Formulate a model (functional relationship) → use a linear regression model
a) OLS modeling
b) GARCH modeling
c) AMRA modeling
i) All must be stationary variables
ii) If variable is non stationary, use 1st difference
iii) Use delta log if you use numbers in percentages
• Cointigration model
• Vector Error Correlation (VEC)
3) Testing steps
a) Check for unit root for stationarity
b) Adjust the model
c) Optimize the model
i) Find the form which maximizes the log likelihood ratio and at the same time minimizes AIC and SIC criterium
ii) Avoid models with high R2 (use ARMA and GARCH models)
d) Explain the results
e) Propose policy solutions
4) In case of multivariate models, avoid Multicullinearity
5) Account for Kurtosis and asymmetry
a) Use TGARCH
6) Conclusion
Topic:
Structured changes in Connecticut economy over the past 10 years. Analyze data from FRED