Essays on Estimation of Inflation Equation
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This dissertation improves upon the estimation of inflation equation, using the ad- ditional measures of distribution of price changes and the optimum choice of instru- mental variables. The measures of dispersion and skewness of the cross-sectional distribution of price changes have been used in empirical analysis of inflation. In the first essay, we find that independent kurtosis effect can have a significant role in the approximation of inflation rate in addition to the dispersion and skewness. The kurtosis measure can improve the approximation of inflation in terms of goodness of fit. The second essay complements the first essay. It is well known that classical measures of moments are sensitive to outliers. It examines the presence of outliers in relative price changes and consider several robust alternative measures of dispersion and skewness. We find the significant relationship between inflation and robust mea- sures of dispersion and skewness. In particular, medcouple as a measure of skewness is very useful in predicting inflation. The third essay estimates the Hybrid Phillips Curve using the optimal set of instrumental variables. Instrumental variables are usually selected from a large number of valid instruments on an ad hoc basis. It has been recognized in the literature that the estimates are sensitive to the choice of instrumental variables and to the choice of the measurement of inflation. This paper uses the L2-boosting method that selects the best instruments from a large number of valid weakly exogenous instruments. We find that boosted instruments produce more comparable estimates of parameters across different measures of inflation and a higher joint precision of the estimates. Instruments boosted from principal compo- nents tend to give a little better results than the instruments from observed variables, but no significant difference is found between the ordinary and generalized principal components.
Kim, Woong (2008). Essays on Estimation of Inflation Equation. Doctoral dissertation, Texas A&M University. Available electronically from