Construction of an Industry Cycle Indicator for Profitability Prediction Analysis of Aggregate Firms in Bangladesh

Maria Afreen (1)
(1) PhD (Financial Economics), Faculty of Economics and Business, University Malaysia Sarawak, Malaysia , Bangladesh


Purpose of this study: In the aggregate industrial sector, government intervention to influence demand within the economy is generally counterproductive, while the optimal policy is to concentrate on supply-side reforms that help the economy become efficient. The objective of this study was to construct a unique industry cycle indicator for Bangladeshi aggregate firms within this industrial sector. The specific objectives were to assemble a unique industry cycle indicator which recommends early signals of a firm’s industrial vulnerability, identify industry cycle indicator turning points and evaluate the predictive performance of the industry. The industry cycle indicator model demonstrates the macroeconomic fluctuations in the industrial sector.

Methodology: The industry cycle indicator was constructed following the approach of the Conference Board (2000). The result wasthen tested for robustness with a macro-stress test. Lagged independent variables were used in this study to allow early predictions by the ICI for the year in which the financial crisis happened.

Main Findings: The industry cycle indicator model underplays the role of aggregate industrial efficiency in influencing the economic cycle. By forecasting directional changes, this leading indicator allows policymakers to be made aware of revolutions in the financial industry and to undertake early precautionary steps to prevent vulnerability. Here, the constructed industry cycle indicator demonstrates a remarkable lead time of around 6 months for predictions and outperforms by the leading against the reference series.

Research Limitations/Implications: The industry cycle indicator model rejects the Keynesian approach and also rejects monetarism. It tends to be associated with neo-classical economics. The ICI generally assumes that shocks to productivity lead to economic fluctuations. In other words, a temporary fall in output is an inevitable consequence of a drop in productivity within the industrial sector. It also leads to adjustments to this new equilibrium and enables resources to discover more productive uses.

Novelty/Originality: This research demonstrates that enhanced knowledge of components of the macro-prudential policy framework combined with the existence of a certain degree of standardisation of the macro-prudential tools and indicators is essential. This can significantly develop the capability of the financial markets supervisory authorities to forecast systemic risk and to avoid or reduce the consequences of industrial crises. The present study reflects a situation for upcoming researchers who intend to study and develop their interests in this area.

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Maria Afreen (Primary Contact)
Author Biography

Maria Afreen, PhD (Financial Economics), Faculty of Economics and Business, University Malaysia Sarawak, Malaysia

Maria Afreen: Dr. Maria Afreen Completed her Ph.D. in "Financial Economics" from University Malaysia Sarawak, Malaysia in 2018 with a merit-based scholarship. She has expertise in data analysis in the areas of Volatility Forecasting & Macro-economic Modeling, Credit Risk Management, Constructing Risk Indicator & Filtering tools. She has a remarkable number of high impact factor indexed peer-reviewed journal publication records at the international level.

Afreen, M. (2020). Construction of an Industry Cycle Indicator for Profitability Prediction Analysis of Aggregate Firms in Bangladesh. Innovation Journal of Social Sciences and Economic Review, 2(4), 09–18.

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