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|Title: ||Real time data and exchange rate models|
|Other Titles: ||Shi shi shu ju zai hui lü mo xing zhong de ying yong|
|Authors: ||Song, Wei (宋偉)|
|Department: ||Department of Economics and Finance|
|Degree: ||Master of Philosophy|
|Issue Date: ||2010|
|Publisher: ||City University of Hong Kong|
|Subjects: ||Foreign exchange rates -- Data processing.|
|Notes: ||CityU Call Number: HG3851 .S66 2010|
117 leaves : ill. 30 cm.
Thesis (M.Phil.)--City University of Hong Kong, 2010.
Includes bibliographical references (leaves 70-80)
|Abstract: ||It is well known that macroeconomic data are revised from time to time. Recently more
and more researchers have noticed that data choice may affect empirical results since we
usually have more than one value for a particular economic variable. Considerable
results have been made in real time data studies.
The main purpose of this paper is to investigate how much data type would affect the in-sample-fit performance and out-of-sample forecast performance of flexible-price
monetary model of exchange rate determination.
In chapter two, related literatures on monetary model and real time data is reviewed.
Several East Asian countries are chosen to test the theoretical monetary model in
chapter three. The testing strategy is based on the MacDonald and Taylor (1993) paper.
Evidence from chapter three shows that the theoretical flexible-price monetary model
does not hold for any country which is in contrast with supportive results found by
previous literatures employing cointegration tests.
Chapter four, chapter five and chapter six try to find out how much data type affects in-sample-fit performance and out-of-sample forecast performance of a model respectively.
Results show that real time data generates more volatile fundamentals than current
vintage data does for all countries and regions. For error correction specification of the
monetary model, real-time-vintage data has the highest out-of-sample predictive power in terms of the three criterions. For first difference specification, current-vintage data
outperforms the other types of data in terms of the three criterions. We also find that
first difference specification can generate better out-of-sample forecasts than error
correction specification of the monetary model in general.
No previous literatures have worked on how data type affects in-sample-fit performance
of exchange rate models. Compare with papers identifying data choice matters for
exchange rate forecasts, this paper tests more model specifications, examines more data
type and uses most recent Clark-West statistical test to evaluate empirical performances.|
|Online Catalog Link: ||http://lib.cityu.edu.hk/record=b3947569|
|Appears in Collections:||EF - Master of Philosophy |
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