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Hierarchical Bayesian semiparametric...

Li, Ming.

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Hierarchical Bayesian semiparametric models for international inflation and interest rates.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Hierarchical Bayesian semiparametric models for international inflation and interest rates./
Author:	Li, Ming.
Description:	100 p.
Notes:	Chair: Peter J. Lenk.
Contained By:	Dissertation Abstracts International64-02B.
Subject:	Business Administration, General. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3079488

Hierarchical Bayesian semiparametric models for international inflation and interest rates.
Li, Ming.

Hierarchical Bayesian semiparametric models for international inflation and interest rates. - 100 p.

Chair: Peter J. Lenk.

Thesis (Ph.D.)--University of Michigan, 2003.

Given the importance of the inflation, nominal and interest rates on economy, volumes of papers have been focused on them for past several decades. However, the economic literature shows no consensus on the findings and controversies still remain.Subjects--Topical Terms:

1017457
Business Administration, General.

Hierarchical Bayesian semiparametric models for international inflation and interest rates.
LDR:03310nam 2200301 a 45 001 927402
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008 110425s2003 eng d
035 $a (UnM)AAI3079488
035 $a AAI3079488
040 $a UnM $c UnM
100 1 $a Li, Ming. $3 559294
245 1 0 $a Hierarchical Bayesian semiparametric models for international inflation and interest rates.
300 $a 100 p.
500 $a Chair: Peter J. Lenk.
500 $a Source: Dissertation Abstracts International, Volume: 64-02, Section: B, page: 0798.
502 $a Thesis (Ph.D.)--University of Michigan, 2003.
520 $a Given the importance of the inflation, nominal and interest rates on economy, volumes of papers have been focused on them for past several decades. However, the economic literature shows no consensus on the findings and controversies still remain.
520 $a This dissertation empirically investigates the relationship among inflation, nominal and real interest rates. The empirical model relaxes the assumption that real rates are constant and allows them to change over time. In addition, the model provides a framework for analyzing the relationship among multiple countries simultaneously. The major conclusions are: First, it improves estimation of the relationship between inflation and nominal interest rate by accounting for non-constant real rates. Nominal rates and inflation move together, and the degree of adjustment is about the same as predicted theoretically. Our results also provide additional supporting evidence to the existing literature for the United States. Second, this model detects the serial variations in the real rates and captures its movement. That is, the nonparametric function well captures the characteristic of the real rates movement for each country. Third, the model also detects serial substantial cross-sectional correlations for multiple countries.
520 $a One objective of the dissertation is to propose a global real rate index. A “global real rate” is not well defined, and the dissertation offers several interpretations. One general approach among three methods is by using Markowitz portfolio theory. Here, country-specific real rates are weighted according to their long-term mean return, volatility, and inter-correlations.
520 $a In summary, this research uses a multivariate, hierarchical Bayes, semiparametric regression model to investigate the relationship between inflation, nominal and real interest rates for multiple countries simultaneously. The model allows for time varying real interest rates for each country. The results show that there is some variation in the real rates over time and across countries, and in the last decade, real rates are declining for most countries. Three methods are provided to construct a global real rates index from three different perspectives. From an investor's point of view, the global real rate index can be treated as a “benchmark” when making multiple countries comparisons and investment allocations.
590 $a School code: 0127.
650 4 $a Business Administration, General. $3 1017457
650 4 $a Statistics. $3 517247
690 $a 0310
690 $a 0463
710 2 0 $a University of Michigan. $3 777416
773 0 $t Dissertation Abstracts International $g 64-02B.
790 $a 0127
790 1 0 $a Lenk, Peter J., $e advisor
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3079488