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|Title: ||Two essays in applied econometrics on duration analysis and model selection|
|Other Titles: ||Ying yong ji liang jing ji xue zhuan ti yan jiu : qi jian fen xi yu mo xing xuan ze|
應用計量經濟學專題研究 : 期間分析與模型選擇
|Authors: ||Guo, Yingwen (郭穎文)|
|Department: ||Department of Management Sciences|
|Degree: ||Master of Philosophy|
|Issue Date: ||2010|
|Publisher: ||City University of Hong Kong|
|Subjects: ||Interest rates -- Econometric models.|
|Notes: ||CityU Call Number: HB539 .G86 2010|
vii, 86 leaves 30 cm.
Thesis (M.Phil.)--City University of Hong Kong, 2010.
Includes bibliographical references (leaves 81-86)
|Abstract: ||The thesis consists of two essays in applied econometrics. Essay 1 adopts duration
analysis to investigate what factors affect the length of an "interest rate spell" - the
period during which the interest rate instrument remains unchanged under inflation
targeting. Nowadays, an increasing number of countries have transitioned to
inflation-targeting regime, and most of them have achieved stable economic growth
and low rates of inflation. Not surprisingly, inflation targeting has attracted growing
interest among economists in recent years. Shih and Giles (2009) first applied
duration analysis to model the length of an interest rate spell under inflation
targeting, and their analysis was directed to the experiences of Canada. This essay
extends Shih and Giles (2009) work through a cross-national analysis of eight
inflation-targeting countries (or areas). Both parametric and nonparametric methods
are employed for the analysis. The conclusion is consistent with that of Shih and
Giles (2009), that is, the length of an interest rate spell is affected by both the rate of
inflation and the rate of economic growth; the influence of exchange and
unemployment rates proved to be insignificant. Moreover, empirical results support
that inflation-targeting central banks usually design their monetary policies based on
the Taylor Rule.
Essay 2 compares the performances of four model selection criteria: Akaike’s
information criterion (AIC), the Schwarz Information criterion (SIC), the smallsample
bias corrected AIC (AICc) and the small-sample bias corrected SIC (SICc)
in a linear regression model with heteroskedasticitic or mutually dependent errors.
Monte Carlo simulation was used to conduct the analysis. AIC and SIC are widelyused
information criteria, but they have a tendency to overfitting in small samples.
The AICc and SICc can reduce this small-sample bias. Most literature compares the
model selection criteria in the situation when the error terms are identically and
independently distributed. Ohtani (2003) first examined their small-sample
performances in a linear regression model with first-order autocorrelated errors.
Stipulated by Ohtani (2003), this essay considers other types of error terms,
including multiplicative heteroskedasticity, the first-order moving average (MA (1))
and the first-order autoregressive conditional heteroskedasticity (ARCH (1)). It was
found that AIC and SIC tend to overfit in small samples, and AICc and SICc
outperform AIC and SIC respectively. As the sample size increases, AIC and SIC
have a decreasing tendency to overfitting and respectively converge to AICc and
SICc. In addition, SIC and SICc perform better than AIC and AICc respectively.|
|Online Catalog Link: ||http://lib.cityu.edu.hk/record=b3947601|
|Appears in Collections:||MS - Master of Philosophy |
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