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Statistical Analysis for Sovereign R...

Li, Zhi.

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Statistical Analysis for Sovereign Rating Data.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical Analysis for Sovereign Rating Data./
Author:	Li, Zhi.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
Description:	109 p.
Notes:	Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Contained By:	Dissertations Abstracts International83-02B.
Subject:	Applied mathematics. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28540726
ISBN:	9798534654110

Statistical Analysis for Sovereign Rating Data.
Li, Zhi.

Statistical Analysis for Sovereign Rating Data. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 109 p.

Source: Dissertations Abstracts International, Volume: 83-02, Section: B.

Thesis (Ph.D.)--State University of New York at Stony Brook, 2021.

This item must not be sold to any third party vendors.

Being an assessment of a government's ability to liquidate its obligations and a measure of the economic, financial and political situations of an economy, sovereign credit rating becomes progressively important for governments and international financial market. As commonly used rating data, the rating assignments from international rating agencies are viewed as reference of sovereign rating level. Combining country's economic, financial and political data with corresponding rating data, we collect a full set of panel data for a universe of 67 countries, from least developed to developed, covering the period 1989-2016.Following typical statistical method, we use linear methods to analyze the relationship between economic, financial data and sovereign rating data. Then we push the analysis forward concentrating on individual-specific effect. We propose fixed effect approach based on least squares dummy variable (LSDV) model to provide a framework for the analysis and prediction of the sovereign panel data, and for random effect approach, we use linear mixed model for analysis. We apply the statistical method to simulation studies and empirical analysis of sovereign rating and economic panel data. Related conclusion includes the fixed and random effect of country-specific indicator, feedback effect of rating history.

ISBN: 9798534654110Subjects--Topical Terms:

2122814
Applied mathematics.
Subjects--Index Terms:

Liquidity

Statistical Analysis for Sovereign Rating Data.
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245 1 0 $a Statistical Analysis for Sovereign Rating Data.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 109 p.
500 $a Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
500 $a Advisor: Xing, Haipeng;Hu, Jiaqiao.
502 $a Thesis (Ph.D.)--State University of New York at Stony Brook, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a Being an assessment of a government's ability to liquidate its obligations and a measure of the economic, financial and political situations of an economy, sovereign credit rating becomes progressively important for governments and international financial market. As commonly used rating data, the rating assignments from international rating agencies are viewed as reference of sovereign rating level. Combining country's economic, financial and political data with corresponding rating data, we collect a full set of panel data for a universe of 67 countries, from least developed to developed, covering the period 1989-2016.Following typical statistical method, we use linear methods to analyze the relationship between economic, financial data and sovereign rating data. Then we push the analysis forward concentrating on individual-specific effect. We propose fixed effect approach based on least squares dummy variable (LSDV) model to provide a framework for the analysis and prediction of the sovereign panel data, and for random effect approach, we use linear mixed model for analysis. We apply the statistical method to simulation studies and empirical analysis of sovereign rating and economic panel data. Related conclusion includes the fixed and random effect of country-specific indicator, feedback effect of rating history.
590 $a School code: 0771.
650 4 $a Applied mathematics. $3 2122814
650 4 $a Statistics. $3 517247
650 4 $a Finance. $3 542899
650 4 $a Regression analysis. $3 529831
650 4 $a Trends. $3 3560051
650 4 $a Politics. $3 685427
650 4 $a Growth rate. $3 3562870
650 4 $a Statistical analysis. $3 3543751
650 4 $a Variables. $3 3548259
650 4 $a Ratings & rankings. $3 3562221
653 $a Liquidity
653 $a Sovereign credit rating
653 $a Fixed effect approach
653 $a Least squares dummy variable
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710 2 $a State University of New York at Stony Brook. $b Applied Mathematics and Statistics. $3 1684041
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792 $a 2021
793 $a English
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