تجزیه و تحلیل تجربی در سهم سرمایه گذاری ایمنی به رشد اقتصادی: مطالعه موردی صنعت معدن چین

Insufficient investment in safety is one of the most important reasons which lead to frequent accidents in Chinese mining industry. Safety input has long been regarded as a ‘sunk cost’, lacking output, and little attention from mining companies was focused on increasing safety input according to technical codes or technical requirements due to the narrow understanding on safety input. So, the empirical analysis on the contribution share of safety investment to economic growth is very important. In this paper, a new set of production safety indexes including six 1-level indexes for describing the safety level of mining production in China was constructed on the basis of Granger causality test. Meanwhile, a mining economic growth model was constructed on the basis of the new production safety indexes with co-integration theory and dynamic modeling system. The empirical results show that the production safety factor in the short term indeed drives the GDP growth in the mining industry although labor and capital input remain the major factors impacting mining economic growth, and its long term contribution share is 7.7%. Principal Component Analysis (PCA) of production safety indexes, shows that the safety level of mining production increased more than 21-fold during 1991–2009, and the investment in mining technology development capability, mining safety production environment and mechanized level of mining should be the direction to focus for improving the safety level of mining production.

Work-related injuries are unwelcome byproducts of economic activity. On average, there is a higher rate of occupational deaths in the mining industry than most other industries in China due to the hazardous nature of the work conditions. Insufficient safety input is the principal one in Chinese mining industries among various factors that could trigger accidents. Safety input is generally felt unnecessary or too costly to manufacturers and has long been regarded as a ‘sunk cost’, lacking output. Little attention from mining companies was focused on increasing safety input according to technical codes or technical requirements, which results from safety input penetrated into the production input, and investment in safety was in advance of its benefit. Generally, only when accidents happened, would a corporation recognize safety input problems. It is therefore intended that estimating contribution share of safety investment to economic growth (CSS) will be very important to understand the safety input and its role correctly. There have been studies that CSS can be mathematically designed by input–output approach, superposition method and product-function method (Luo, 2004, Lui and Shi, 2006 and Mou and Wang, 2006). In these studies, CSS was defined as the share of safety output in total output value, and safety output was generally divided into derogation part and increment part. The increment part has been included in GDP, but derogation part, including increase in value of GDP or decrease in work efficiency loss, improvement in the value of safety condition and safety credit and others, was too difficult to estimate, which exists only in theory but not in the productivity statistics. However, they cannot avoid using GDP. Their formula for common calculating CSS was presented as follows:A positive number (YD) was subtracted both in numerator and in denominator of Eq. (2). Therefore, the value of ES in Eq. (3) was reduced compared with that of Eq. (2). Therefore, this method in which safety output was split from GDP for calculating the value of safety was not accurate. The definition of CSS not only led to a one-sided safety output, but also limited the selection of safety input indexes. Safety output derived mainly from three aspects of safety input including level of safety technology, safety capital input and safety labor input in the past studies (Luo, 2004, Lui and Shi, 2006, Mou and Wang, 2006 and Tong and Ding, 2008). Here, technology level of safety was gained by national experts who worded out the percentage how much the level of safety technology took in the contribution share of scientific and technological progress over the whole country; capital input involved safety allowance from government, expenditure on labor protection and occupational disease; and labor input included the number of safety technologists and safety managers. They failed to take into account investment in production, organizational factors, work climate, etc. Accidents were only ascribed to specialty safety factors, and had nothing to do with production input (such as mechanized level of mining, and production management) on the basis of this safety input idea. However, we cannot draw a conclusion that those enterprises who invest abundantly in the above-mentioned professional safety factors and poorly in production will have a high safety level, while those enterprises who invest poorly in professional safety factors and abundantly in production will have a low safety level. In fact, it was difficult to differentiate safety input from production input (Chen, 2002). When backed up by abundant production input, safety input has been somewhat more effective and safety and productivity were improved in the mechanized system more so than the conventional system (Sari et al., 2004 and John, 1992). Safety level can be improved with the technology development in production field. The National Mining Association (State Administration of Work Safety, 2005) found that coal mine accidents had been significantly reduced by deployment and use of new technology according to proven practice for 30 years. The maximum safety level of a company can be determined by its organizational management system as current manufacturing strategies have been progressing toward collaborative manufacturing partnerships. Statistics show that over 80% of accidents resulted from unsatisfactory management (Denis and Camille, 2003 and Yu, 2007). As is mentioned above, the definition and research methods on CSS have some defects in past studies. However, the experiences in CSS have formed the foundation for the following successful studies. Thus, it is necessary to break down the narrow understanding on safety input, and understand the nature of accident and the influence factors of safety in order to resolve the shortfall of safety input problem. In this paper, a case study of the Chinese mining industry addresses a new set of production safety indexes that was constructed on the basis of the Granger causality test. A mining economic growth model was established on the basis of the new production safety indexes through adopting co-integration theory and dynamic construction model. The study provides a theoretical reference for understanding the safety input and the effect of safety input.

On the basis of an establishment of Chinese mining economic growth model with safety factor to measure the CSS since 1991, a new set of production safety indexes including six 1-level indexes for describing Chinese mining safety production level was constructed. The new indexes better describe the safety status of China’s mining production. It can be shown from the data features of the new indexes and the results of Granger causality test on the number of deaths in mining occupational accidents and production safety indexes. Along with co-integration theory and dynamic construction model, a mining economic growth model on the basis of the new production safety indexes simulates prime movement of China’s mining economic growth. We have made the following evaluation on the safety situation of mining industry in China according to the mining production safety indexes. (1) The safety level of China’s mining industry has made remarkable achievements since 1991. Overall, the safety level of China’s mining industry has been improved continuously, and the relative indexes of production safety have increased by more than 21-fold during 1991–2009. The benefit from increasing the level of the mining product safety indexes can be reflected in the existing number of deaths due to mining occupational accidents. The number of deaths in mining occupational accidents has dropped from 9189 people in 1991–4173 people in 2009. (2) The investment in safety in the mining industry should be adjusted. The PCA on six 1-level indexes of mining production safety indexes shows that the top three are level of mining technology development capability (X6), level of mining safety production environment (X5) and mechanized level of mining (X4). It indicates that investment in these areas should be the direction to focus for improving the safety level of mining production in the limited funds. Traditional safety input conception holds that only the investment in safety technology, protecting facilities and personnel of safety technology and safety management can ensure safety production. However, it has been proven that the number of deaths in mining occupational accidents is still ranked high compared it with other industries in China no matter how efforts are made in these areas. The reason is that these decisive factors for guaranteeing safety production are lacking of fundamental improvement, such as level of mining technology development capability, level of mining safety production environment and mechanized level of mining. The above hardware investments should be implemented in advance to ensure and promote the improvement of the safety level of production, but it is hard to accomplish, especially for small-and medium-sized mining enterprises, and this has some connection with the recoverable amount of materials reserves and the mining difficulty. Improvement of the production safety level in entire mining industry will be a long process, and it will increase with the overall economic development. (3) Insufficient investment in professional personnel and management personnel is at the forefront for making a difference in safety input to mining enterprises. The results of Granger causality test on six 1-level indexes of production safety indexes and the number of deaths in mining occupational accidents provide powerful evidence for passive investment in professional personnel and management personnel. Mining enterprises have to enhance the relevant investments with the high number of deaths due to mining occupational accidents. It shows that there is a relatively large shortage gap in professional and management personnel for quite a long time or there has been severe outward migration of professional and management talents in the mining industry. On the other hand, this also shows that there is a serious production safety situation in the mining industry (it is accused of frequent mining accidents from the outside aspect) forcing mining enterprises into an urgent need of professional and management personnel. Mining total investment in fixed assets per 10,000 yuan gross output value (X1), mechanized level of mining (X4), level of mining safety production environment (X5) and level of mining technology development capability (X6) through Granger causality test, confirm influences on the number of deaths due to mining occupational accidents, and confirm that some potential and essential safety factors should be taken into consideration when we estimate CSS. (4) The mining economic growth model shows that the coefficient values of safety factor and its inertias (lagged term) entered distinctly into the model, and safety factor surely accelerated the mining economic growth in short-term though the driving value is weaker than that of capital and labor, and its long-term contribution share is 7.7%. The accommodation coefficient of mining economic growth model is −5.092. A bigger effect means that system can rapidly adjust to a new equilibrium if capital inputs and labor inputs are changed by comparison. (5) CSS can reflect the scale and quality of capital services and labor services, and its value depends on the relationship of growth rate of safety and that of the economy. It is not true that the economy is more developed at some times or in some regions, the CSS is greater. Given the same production safety level conditions, the slower economic growth rate has the greater CSS, and the economic growth is faster, CSS is smaller. It is possible to turn up the frequently of fluctuation of CSS in some particular years due to the economic adjustment or the nature of a periods’ activity. In order to make different economic basis, the state and industry are comparable, estimating CSS should be combined with examining the level of production safety indexes. The length of time should be measured for medium-and long-term (such as 5 years), and the rolling 5-year industry average production safety indexes can be designated as an appropriate safety criterion at an acceptable risk level. The criterion can be used for estimating the safety input of corporations or enterprises as to whether or not they meet the requirement and can help to find out the potential problems in safety inputs. This work may establish a useful base for continuous improvement in the safety field.