Output Gap Estimation in NTB Province with Modified Hodrick Prescott Filter
DOI:
https://doi.org/10.35590/jeb.v12i1.7917Abstract
- Purpose: This study aims to estimate the Output Gap in West Nusa Tenggara (NTB) Province using a Modified Hodrick Prescott (HP) Filter method by primary, secondary, and tertiary sectors.
- Design/methodology/approach: The study uses quarterly constant-price RGDP data from 2010Q1 to 2023Q3. The Potential RGDP is estimated using a modified HP Filter with an optimal lambda value derived by minimizing the Generalized Cross Validation (GCV). An algorithm developed in R-Statistics software was employed to automate lambda optimization and potential output computation.
- Findings: The optimal lambda values were found to be 343 for total RGDP, 271 for the primary sector, 4438 for the secondary sector, and 989 for the tertiary sector. Overheating was identified during 2015Q1–2016Q1 due to a surge in mining activity, while the COVID-19-induced recession was observed from 2020Q1 to 2022Q2. The primary sector was most vulnerable during overheating, the secondary sector remained stable, and the tertiary sector was most affected during the recession.
- Research limitations/implications: As a univariate method, the Modified HP Filter may not fully capture structural economic shifts, especially in the primary sector. Further research using multivariate approaches such as SVAR, Kalman Filters, or production functions is recommended.
- Practical implications: Sector-specific output gap estimation enables more targeted fiscal and monetary policy interventions. Policymakers can apply contractionary measures during overheating and expansionary actions during recession with greater precision based on sectoral sensitivity.
- Originality/value: This study provides a novel application of a modified HP Filter at a regional and sectoral level in Indonesia, offering a valuable analytical tool for regional economic monitoring and policy development.
- Paper type: Research paper
Keywords: Output Gap, NTB, Potential RGDP, R-Statistics.
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