Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian case

This study aims to integrate short-term, medium-term, and long-term Composite Leading Indices (CLIs) to establish that interconnected CLIs offer enhanced predictive capabilities compared to individual CLIs. Specifically, it investigates the relationships among CLIs to forecast Indonesia's Manuf...

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Main Authors: Tirta Wisnu Permana, Gatot Yudoko, Eko Agus Prasetio
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Heliyon
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Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024175536
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author Tirta Wisnu Permana
Gatot Yudoko
Eko Agus Prasetio
author_facet Tirta Wisnu Permana
Gatot Yudoko
Eko Agus Prasetio
author_sort Tirta Wisnu Permana
collection DOAJ
description This study aims to integrate short-term, medium-term, and long-term Composite Leading Indices (CLIs) to establish that interconnected CLIs offer enhanced predictive capabilities compared to individual CLIs. Specifically, it investigates the relationships among CLIs to forecast Indonesia's Manufacturing Cycle (ManC) using Partial Least Squares-Structural Equation Modeling (PLS-SEM).Building on an extensive literature review, the study employs quarterly data spanning from Q1 2010 to Q2 2022, incorporating five constructs representing key economic sectors influencing the manufacturing cycle. The analysis includes two short-term CLIs: the Short Leading Economic Index (SLEI) and the International Trade Channel (ITC). The SLEI is composed of two indicators, the Manufacturing Purchasing Managers’ Index (PMI) and the Composite Stock Price Index from the Indonesia Stock Exchange, while the ITC comprises nine critical export-import CLIs.The Fiscal Cycle (FC) is a potential medium-term CLI, including Gross Domestic Product (GDP) per capita, manufacturing investment, oil prices, and the Consumer Price Index (CPI). Meanwhile, the monetary cycle (MC) comprises the Policy Interest and Real Effective Exchange Rates. This research effectively supports the application of PLS-SEM in forecasting the ManC in Indonesia.
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institution Kabale University
issn 2405-8440
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publishDate 2025-01-01
publisher Elsevier
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series Heliyon
spelling doaj-art-3a08caaed2de41bfbbadf9fa8c3d2e402025-01-17T04:51:31ZengElsevierHeliyon2405-84402025-01-01111e41522Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian caseTirta Wisnu Permana0Gatot Yudoko1Eko Agus Prasetio2Corresponding author.; School of Business and Management, Institute of Technology Bandung (ITB), Bandung, IndonesiaSchool of Business and Management, Institute of Technology Bandung (ITB), Bandung, IndonesiaSchool of Business and Management, Institute of Technology Bandung (ITB), Bandung, IndonesiaThis study aims to integrate short-term, medium-term, and long-term Composite Leading Indices (CLIs) to establish that interconnected CLIs offer enhanced predictive capabilities compared to individual CLIs. Specifically, it investigates the relationships among CLIs to forecast Indonesia's Manufacturing Cycle (ManC) using Partial Least Squares-Structural Equation Modeling (PLS-SEM).Building on an extensive literature review, the study employs quarterly data spanning from Q1 2010 to Q2 2022, incorporating five constructs representing key economic sectors influencing the manufacturing cycle. The analysis includes two short-term CLIs: the Short Leading Economic Index (SLEI) and the International Trade Channel (ITC). The SLEI is composed of two indicators, the Manufacturing Purchasing Managers’ Index (PMI) and the Composite Stock Price Index from the Indonesia Stock Exchange, while the ITC comprises nine critical export-import CLIs.The Fiscal Cycle (FC) is a potential medium-term CLI, including Gross Domestic Product (GDP) per capita, manufacturing investment, oil prices, and the Consumer Price Index (CPI). Meanwhile, the monetary cycle (MC) comprises the Policy Interest and Real Effective Exchange Rates. This research effectively supports the application of PLS-SEM in forecasting the ManC in Indonesia.http://www.sciencedirect.com/science/article/pii/S2405844024175536IndonesiaManufacturing cycleComposite leading indices (CLI)Time series dataPLS-SEM
spellingShingle Tirta Wisnu Permana
Gatot Yudoko
Eko Agus Prasetio
Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian case
Heliyon
Indonesia
Manufacturing cycle
Composite leading indices (CLI)
Time series data
PLS-SEM
title Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian case
title_full Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian case
title_fullStr Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian case
title_full_unstemmed Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian case
title_short Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian case
title_sort manufacturing cycle prediction using structural equation model toward industrial early warning system simulation the indonesian case
topic Indonesia
Manufacturing cycle
Composite leading indices (CLI)
Time series data
PLS-SEM
url http://www.sciencedirect.com/science/article/pii/S2405844024175536
work_keys_str_mv AT tirtawisnupermana manufacturingcyclepredictionusingstructuralequationmodeltowardindustrialearlywarningsystemsimulationtheindonesiancase
AT gatotyudoko manufacturingcyclepredictionusingstructuralequationmodeltowardindustrialearlywarningsystemsimulationtheindonesiancase
AT ekoagusprasetio manufacturingcyclepredictionusingstructuralequationmodeltowardindustrialearlywarningsystemsimulationtheindonesiancase