Macroeconomic Variables and the Prediction of Financial Distress Companies in the Manufacturing Sector in Malaysia
Mohd Norfian Alifiah1, Muhammad Sohail Tahir2
1Mohd Norfian Alifiah, Universiti Teknologi Malaysia.
2Muhammad Sohail Tahir, Universiti Teknologi Malaysia.
Manuscript received on 28 April 2019 | Revised Manuscript received on 10 May 2019 | Manuscript Published on 17 May 2019 | PP: 403-410 | Volume-8 Issue-1S May 2019 | Retrieval Number: A10580581S19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This study attempts to predict financial distress companies in the manufacturing sector in Malaysia using PN4 and PN17 companies as the dependent variable and financial ratios and macroeconomic variables as the independent variables. Logit Analysis was used as the analysis procedure. This study found that the independent variables that can be used to predict financial distress companies in the manufacturing sector in Malaysia were total assets turnover ratio, current ratio, net income to total assets ratio and money supply (M2). The findings from the internal validation showed that the prediction model provided a more than 50% chance that the model is accurate. In addition, the findings from the external validation also showed that the model might be able to be used outside the time period that the model was estimated because the overall percentage accuracy were more than 50% for five years before distress. This study provides the prediction model of financial distress companies in the manufacturing sector in Malaysia and it also validate the findings internally and externally. Internal and external validations were seldom conducted in previous studies on the prediction of financial distress in Malaysia due to lack of data.
Keywords: Financial Distress; Macroeconomic Variables; Malaysia; Manufacturing Sector.
Scope of the Article: Manufacturing Processes