Revisiting the Phillips Curve in Bangladesh

The current discussion retests the Phillips Curve in the environment of Bangladesh, a fast-moving developing economy, to dish out the dynamic interdependence between inflation and unemployment between 1990 and 2024. This paper combines the classical and contemporary theoretical models, the expectations augmented and New Keynesian Phillips Curve (NKPC), and employ strong econometric estimation procedures, e.g. autoregressive distributed lag (ARDL), vector error correction model (VECM), and Granger causality test. Results show that in the long run there is a statistically significant long-run trade-off. Expectation-based models are more strongly supported compared to use of traditional Phillips Curve formulation. The dynamics in the short run is dampened, and structural imbalances are especially heightened when external shocks abound, such as the global financial crisis and the COVID-19. The findings highlight that inflation in Bangladesh is excessively affected by variations in output than unemployment and there is therefore a need to have a forward looking inflation targeting and structural labour market adjustment. The policy recommendations focus on flexible monetary structure, more labor market policies and labored contingency plans to exogenous shocks. The findings give a detailed description of inflation-unemployment interactions and empirically supports more responsive policymaking in the realm of macroeconomics within Bangladesh.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-22
DOI
https://doi.org/10.5281/zenodo.16319088
Primary Topic
Unemployment and Economic Growth
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Revisiting the Phillips Curve in Bangladesh

Zenodo (CERN European Organization for Nuclear Research)
Unemployment and Economic Growth
article

Revisiting the Phillips Curve in Bangladesh

article en

Abstract

The current discussion retests the Phillips Curve in the environment of Bangladesh, a fast-moving developing economy, to dish out the dynamic interdependence between inflation and unemployment between 1990 and 2024. This paper combines the classical and contemporary theoretical models, the expectations augmented and New Keynesian Phillips Curve (NKPC), and employ strong econometric estimation procedures, e.g. autoregressive distributed lag (ARDL), vector error correction model (VECM), and Granger causality test. Results show that in the long run there is a statistically significant long-run trade-off. Expectation-based models are more strongly supported compared to use of traditional Phillips Curve formulation. The dynamics in the short run is dampened, and structural imbalances are especially heightened when external shocks abound, such as the global financial crisis and the COVID-19. The findings highlight that inflation in Bangladesh is excessively affected by variations in output than unemployment and there is therefore a need to have a forward looking inflation targeting and structural labour market adjustment. The policy recommendations focus on flexible monetary structure, more labor market policies and labored contingency plans to exogenous shocks. The findings give a detailed description of inflation-unemployment interactions and empirically supports more responsive policymaking in the realm of macroeconomics within Bangladesh.

Zenodo (CERN European Organization for Nuclear Research)
China West Normal University (CN)
Decent work and economic growth
Openalex Percentile: Top 51%
Unemployment and Economic Growth
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.