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Essays on Estimation of Inflation Equation

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
Date15 May 2009
CreatorsKim, Woong
ContributorsHwang, hae-shin
Source SetsTexas A and M University
Detected LanguageEnglish
TypeBook, Thesis, Electronic Dissertation, text
Formatelectronic, application/pdf, born digital

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