Debt crisis, credit cycles and economic growth in Indonesia

Riznaldi Akbar

Research output: ThesisDoctoral Thesis

Abstract

This thesis is structured as a series of four papers. The first study adopts a Firth's penalized logistic regression model and the second study adopts an Artificial Neural Network for external debt crisis prediction in Indonesia.The results suggest that GOP growth, debt-to-GOP, exchange rate, foreign reserve, and export are major determinants for the debt crisis. The third study examines Indonesia's credit cycles and shows that Indonesia experienced more credit booms than busts. The fourth study investigates the relationship between local government debt and regional growth using an augmented growth model and suggests an inverted U-shaped relationship.
LanguageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • The University of Western Australia
Supervisors/Advisors
  • Wu, Yanrui, Supervisor
  • Li, Bei, Supervisor
Award date18 Feb 2018
DOIs
StateUnpublished - 2018

Fingerprint

Economic growth
Indonesia
Debt crisis
Credit cycle
Growth model
Local government
Inverted-U
Logistic regression model
Regional growth
Foreign reserves
Credit booms
External debt
Government debt
Debt
Artificial neural network
Prediction
Exchange rates

Cite this

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title = "Debt crisis, credit cycles and economic growth in Indonesia",
abstract = "This thesis is structured as a series of four papers. The first study adopts a Firth's penalized logistic regression model and the second study adopts an Artificial Neural Network for external debt crisis prediction in Indonesia.The results suggest that GOP growth, debt-to-GOP, exchange rate, foreign reserve, and export are major determinants for the debt crisis. The third study examines Indonesia's credit cycles and shows that Indonesia experienced more credit booms than busts. The fourth study investigates the relationship between local government debt and regional growth using an augmented growth model and suggests an inverted U-shaped relationship.",
keywords = "Debt crisis, Credit cycles, Economic growth, Indonesia",
author = "Riznaldi Akbar",
year = "2018",
doi = "10.4225/23/5a9f80ea377a5",
language = "English",
school = "The University of Western Australia",

}

Akbar, R 2018, 'Debt crisis, credit cycles and economic growth in Indonesia', Doctor of Philosophy, The University of Western Australia. DOI: 10.4225/23/5a9f80ea377a5

Debt crisis, credit cycles and economic growth in Indonesia. / Akbar, Riznaldi.

2018.

Research output: ThesisDoctoral Thesis

TY - THES

T1 - Debt crisis, credit cycles and economic growth in Indonesia

AU - Akbar,Riznaldi

PY - 2018

Y1 - 2018

N2 - This thesis is structured as a series of four papers. The first study adopts a Firth's penalized logistic regression model and the second study adopts an Artificial Neural Network for external debt crisis prediction in Indonesia.The results suggest that GOP growth, debt-to-GOP, exchange rate, foreign reserve, and export are major determinants for the debt crisis. The third study examines Indonesia's credit cycles and shows that Indonesia experienced more credit booms than busts. The fourth study investigates the relationship between local government debt and regional growth using an augmented growth model and suggests an inverted U-shaped relationship.

AB - This thesis is structured as a series of four papers. The first study adopts a Firth's penalized logistic regression model and the second study adopts an Artificial Neural Network for external debt crisis prediction in Indonesia.The results suggest that GOP growth, debt-to-GOP, exchange rate, foreign reserve, and export are major determinants for the debt crisis. The third study examines Indonesia's credit cycles and shows that Indonesia experienced more credit booms than busts. The fourth study investigates the relationship between local government debt and regional growth using an augmented growth model and suggests an inverted U-shaped relationship.

KW - Debt crisis

KW - Credit cycles

KW - Economic growth

KW - Indonesia

U2 - 10.4225/23/5a9f80ea377a5

DO - 10.4225/23/5a9f80ea377a5

M3 - Doctoral Thesis

ER -