Research Reports

Korean construction companies face tough business environment. Korean economy is in a low growth phase, the SOC budget is declining, and the real estate market is subject to strong regulations. As the construction industry is highly sensitive to the domestic demand as well as to the political changes, the management conditions of construction companies are expected to become more difficult in the near future. The number of marginal firms will increase, and there will be greater needs of corporate restructuring. Under these circumstances, it is very necessary to predict the possibility of marginal enterprises to improve the efficiency of the corporate management and the competitiveness of the construction industry. This study proposes a forecasting model of construction marginal firms by using macroeconomic indices as well as financial variables of companies. Compared with the previous research, it enhance the reality and reliability of the model by using long time data of the whole construction companies, whose financial data is available. In addition, it provides detailed models according to the firm characteristics. This study analyzes the current state of the construction industry, analyzes the time series trend of financial ratios and macroeconomic indices, identifies determinants of marginal firms, and verifies the suitability of models. The model proposed by this study can be applied to policy authorities, creditor financial institutions, and construction companies. First, the model can be utilized as an early warning system that recognizes the point at which policy makers may worry about the possibility of a construction firms insolvency. The model will help the authorities search for the cause of the insolvency and find a direction to prevent the insolvent company. Second, in terms of creditor financial institutions, the model is expected to contribute to elaborating and systematizing the credit ratings. The model enables the systematic and future-oriented risk management, by complementing the existing credit ratings. Third, the results of this study can contribute to the development of effective strategies of firms to reduce potential business risks. Firms can measure the level of risks and analyze the risk factors through the model. After that, they can establish the optimal management strategy based on it.