Malaysia’s Development Expenditure Effects on Gross Domestic Product by Using VECM Approach

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Nur Arina Bazilah Kamisan
Siti Mariam Norrulashikin
Kamaruzaman Mohamed
Nur Amirah Buliah
Zainuddin Ahmad

Abstract

The provision of public goods and services to citizens is a significant responsibility of the government. The products include schools, hospitals, roads, and other infrastructure. This investment is essential to stimulate economic growth, create job opportunities, and improve living standards. The effect of development spending on economic growth has been shown in a significant amount of existing literature. However, there are still various opinions on the impact level of development spending on economic growth. Therefore, the goal of our research is to investigate the link between Malaysia's Gross Domestic Product (GDP) and Development Expenditure (DE) based on the long-run and short-run vector error correction model (VECM) approach. The findings show that the long-term impact of GDP on development spending is positive, according to the results of the Johansen co-integration test. The long-run VECM also shows a positive correlation between GDP and government spending on development. Development spending and lag one GDP are negatively correlated. The short-run VECM shows a positive correlation between GDP and GDP lag. Unrestricted Vector Autoregressive (VAR) demonstrates that government spending on development has no discernible impact on GDP. According to the impulse response function (IRF) study, a GDP shock first has a negative effect on development spending before having a positive reaction. Although GDP might not be a strong indicator of DE in the near run, it becomes increasingly apparent over longer time frames, emphasizing the intricate relationship between macroeconomic factors and fiscal policy.

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How to Cite
Kamisan, N. A. B., Norrulashikin, S. M., Mohamed, K. ., Buliah, N. A. ., & Ahmad, Z. . (2024). Malaysia’s Development Expenditure Effects on Gross Domestic Product by Using VECM Approach. Journal of Statistical Modeling &Amp; Analytics (JOSMA), 6(2). Retrieved from http://mjs.um.edu.my/index.php/JOSMA/article/view/49884
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