Predictive Analysis of Fiscal Crises with Deep Learning Time Series Model
- Zhou Ming Matt
- Wang Man Cang
Abstract
Fiscal crisis can cause serious damage to the economy. Remarkably, there is limited study about when and how it occurs. With the social and economic data of more than 180 countries from 1970 to 2015, this paper constructs a fiscal crisis risk index system to explore the relationships between the crises and the indicators such as GDP growth rate, inflation rate, FDI, and foreign debt interests. Predictive analysis is performed based on the time series model of deep neural network to shed some light on policies and economic dynamics around the crises. We find that besides the inflation, fiscal crises in advanced economies are closely related to the net outflows of FDI and GDP p.c. while in developing countries the GDP growth rate and the net inflows of FDI are the key factors. Low-income developing countries are the heavy-hit targets with the net inflows of FDI, debt structure and interests as main contributors.
- Full Text: PDF
- DOI:10.5539/ijef.v11n5p21
Journal Metrics
Index
- Academic Journals Database
- ACNP
- ANVUR (Italian National Agency for the Evaluation of Universities and Research Institutes)
- Berkeley Library
- CNKI Scholar
- COPAC
- Copyright Clearance Center
- Directory of Research Journals Indexing
- DTU Library
- EBSCOhost
- EconBiz
- EconPapers
- Elektronische Zeitschriftenbibliothek (EZB)
- EuroPub Database
- Genamics JournalSeek
- GETIT@YALE (Yale University Library)
- Harvard Library
- Harvard Library E-Journals
- IBZ Online
- IDEAS
- JournalTOCs
- LOCKSS
- MIAR
- NewJour
- Norwegian Centre for Research Data (NSD)
- Open J-Gate
- PKP Open Archives Harvester
- Publons
- RePEc
- ROAD
- Scilit
- SHERPA/RoMEO
- SocioRePEc
- Standard Periodical Directory
- Technische Informationsbibliothek (TIB)
- The Keepers Registry
- UCR Library
- Ulrich's
- Universe Digital Library
- UoS Library
- ZBW-German National Library of Economics
- Zeitschriften Daten Bank (ZDB)
Contact
- Michael ZhangEditorial Assistant
- ijef@ccsenet.org