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Predictive Insights: Using Macro and Micro Models for Wage Growth Forecast in Malaysia
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The Malaysian government has implemented the Progressive Wage Policy (PWP) to accelerate wage growth and address the low contribution of employee compensation (CE) to Gross Domestic Product The objective, as outlined in the Twelfth Malaysian Plan (RMKe-12), is to achieve a median wage of RM2,700 per month by 2025 and attain an annual productivity growth rate of 3.7% from 2021 to 2025[22]. In line with this policy, Social Security Organization (PERKESO), an organization under the Ministry of Human Resource, has taken proactive measures to analyze and model wage growth forecasting for the upcoming years. This paper aims to develop a forecasting model by examining the relationship between wages and various macroeconomic and microeconomic variables, including the unemployment rate. The methodology employs both Phillips Curve and Artificial Intelligence Model to predict wage increments, covering the period from 2016 to 2023. The approach ensures the development of a robust model supported by big data. This study establishes a predictive relationship within a stylistic framework of wage bargaining, indirectly fostering dynamic ecosystems between the prevailing economic conditions and employers' market trends in the Macro Model. The model considers the institutional structure of the current economic condition and employers' market trends, incorporating factors based on economic indicators and contributions. Additionally, a Machine Learning Gradient Boosting Regressor Model is utilized to predict the output from micro models. This enhances the overall reliability of the model. Significantly, the methodological innovation revolves around the integration of Macro and Micro Models, utilizing detailed data from job placements and monthly contributions spanning from 2020 to 2023 for the wage forecast framework. This distinct approach facilitates forecast development through model averaging techniques customized to maximize the accuracy of wage increase and estimated salary predictions.
Al-Kindi Center for Research and Development
Title: Predictive Insights: Using Macro and Micro Models for Wage Growth Forecast in Malaysia
Description:
The Malaysian government has implemented the Progressive Wage Policy (PWP) to accelerate wage growth and address the low contribution of employee compensation (CE) to Gross Domestic Product The objective, as outlined in the Twelfth Malaysian Plan (RMKe-12), is to achieve a median wage of RM2,700 per month by 2025 and attain an annual productivity growth rate of 3.
7% from 2021 to 2025[22].
In line with this policy, Social Security Organization (PERKESO), an organization under the Ministry of Human Resource, has taken proactive measures to analyze and model wage growth forecasting for the upcoming years.
This paper aims to develop a forecasting model by examining the relationship between wages and various macroeconomic and microeconomic variables, including the unemployment rate.
The methodology employs both Phillips Curve and Artificial Intelligence Model to predict wage increments, covering the period from 2016 to 2023.
The approach ensures the development of a robust model supported by big data.
This study establishes a predictive relationship within a stylistic framework of wage bargaining, indirectly fostering dynamic ecosystems between the prevailing economic conditions and employers' market trends in the Macro Model.
The model considers the institutional structure of the current economic condition and employers' market trends, incorporating factors based on economic indicators and contributions.
Additionally, a Machine Learning Gradient Boosting Regressor Model is utilized to predict the output from micro models.
This enhances the overall reliability of the model.
Significantly, the methodological innovation revolves around the integration of Macro and Micro Models, utilizing detailed data from job placements and monthly contributions spanning from 2020 to 2023 for the wage forecast framework.
This distinct approach facilitates forecast development through model averaging techniques customized to maximize the accuracy of wage increase and estimated salary predictions.
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