Examining the Causes of Inflation Robert Kelchen Student Research Conference April 20, 2006.

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Presentation transcript:

Examining the Causes of Inflation Robert Kelchen Student Research Conference April 20, 2006

Building the Model Data used: Time series from Q Q Total of 103 observations Data obtained from Federal Reserve and Bureau of Labor Statistics website

Variables Examined GDP=Gross Domestic Product ($bil) I=Prime interest rate M=M2 money supply ($bil) W=Employment cost index (1980=100) DEF=National debt ($bil) OIL=Price of a barrel of crude oil

Dummy Variables UN=Unemployment rate 0=Rate below seven percent 1=Rate above seven percent EXC=Trade-weighted exchange rate 0=Trade-weighted rate below 100 1=Trade-weighted rate above 100

Linear Model with Dummy Variables

Concerns: Coefficient for employment cost index is negative Coefficient for exchange rate dummy variable is negative Shows some collinearity among several of the variables

Partial Logarithmic Model with Dummy Variables

Concerns: Coefficient for employment cost index is still negative Coefficient for exchange rate dummy variable is negative Also shows some collinearity among several of the variables

Testing the Models Q CPI Inflation: 3.19% Linear Model Prediction: 7.79% Partial Log Model Prediction: 5.83% Look at exogenous variables and model parameters to explain the difference

Conclusion Although both models explain a fair amount of the regression, the partial logarithmic model is the better model. The partial logarithmic model consistently has less error in regression, especially in recent years. No model can predict inflation with perfect accuracy!