Abstract:

Excessive producing capacity of coal industry is wasting resources, harmful to a green, efficient and safe energy system. Utilization rate of producing capacity is a key indicator to mark the excess of producing capacity, measuring it will be helpful to tell the excess degree of coal producing capacity and its developing trend, which provides references for authorities to make producing capacity policies and for coal producers to make market strategies. China ‘s coal resource is heterogeneously distributing with different burying geology, which determines its regional developing difference. The past measurements ignored its impacts on utilization rate of producing rate. This paper uses LCRMA to measure 2001 to 2017 utilization rate of coal producing capacity in China ‘s 24 provinces, classifies coal provinces into 4 groups, abundant type, moderate type, insufficient type and exhausted type in terms of the intrinsic variance of mining conditions, and applies spatial counting model to study their spatial evolution of utilization rate of producing capacity in these four groups. Utilization rate of coal producing capacity shows a rising-falling trend during the study period, average at 0.82, with excessive producing capacity varying with groups. Production in insufficient type and exhausted type is approaching the producing margin, suggesting a limited room to improve their utilization rate of producing capacity. Utilization rate of producing capacity in moderate type is average at 0.63, meaning an excessive producing capacity. Factors impacting utilization rate of producing capacity vary with groups. Economy works adversely, but positively on groups with abundant resources, advanced technologies and most large coal bases, indicating expanded producing capacity induced by economic growth ignores quality. Utilization rate of producing capacity is sensitive to changes of market demands, a growing demand is favorable for improving utilization rate of producing capacity. Spatialβconditional convergence exists in utilization rate of coal producing capacity, suggesting industrial migration helpful to spatially increase utilization rate of producing capacity, contributing to a diminishing regional difference. This paper presents suggestions on enhancing infrastructural construction and research inputs in western and new producing bases, accelerating quit and consolidation of lagging producing capacity in central, exerting the key “survival of fittest” role of market in coal producing capacity, actively directing human and management resources in insufficient and exhausted groups to abundant and moderate types so as to reach a quality development of coal industry.

Key words: coal industry, excessive producing capacity, utilization rate of producing capacity; spatial convergence, random marginalization, spatial counting model

摘要： 煤炭行业的产能过剩造成资源浪费，不利于绿色、高效、安全能源系统的发展。产能利用率是表征产能过剩程度的重要指标，对其客观科学测算有利于正确评判煤炭行业产能过剩的程度及其发展趋势，为有关部门产能政策制定和煤炭企业市场决策提供依据。我国煤炭资源分布的不均衡性以及埋藏地质差异决定了其开发利用的区域差异性，以往的测算方法忽略了此种差异对产能利用率的影响。本文采用潜类别随机边界法对我国24个产煤省2001—2017年煤炭行业产能利用率进行测算，基于开采条件的内生差异，将产煤省划分为丰富型、适度型、贫乏型和枯竭型4个群组，运用空间计量模型对各群组产能利用率的空间演变特征进行分析。研究结果表明：煤炭行业产能利用率在测算年度内呈现先上升后下降的趋势，平均水平为0.82；产能过剩情况在群组间存在较为明显的差异，贫乏型和枯竭型群组的生产已接近生产边界，产能利用率改善空间有限，适度型群组产能利用率的平均值为0.63，产能过剩较为严重；影响因素对各群组产能利用率的作用各异，总的来说，经济发展影响因素对煤炭产能利用率具有负向作用，但对资源丰富、技术先进、拥有多数大煤炭基地的丰富型群组具有正向作用，说明由经济增长而引发的扩张产能忽视了质量提升；产能利用率对市场需求的变化敏感，需求的增长有利于产能利用率的提升；煤炭行业产能利用率存在空间β条件收敛，说明产业转移有助于产能利用率的空间追赶，产能利用率总体水平提升，地区间差异缩小。由此可得，要实现煤炭产业的高质量发展，应加大西部和新兴生产基地的基础建设和科技投入，加速中部地区落后产能的退出和整合，发挥市场在煤炭产能优胜劣汰中的关键作用，积极引导贫乏型、枯竭型群组的人力和管理资源向丰富型、适度型群组转移。

关键词: 煤炭行业, 产能过剩, 产能利用率, 空间收敛, 随机边界法, 空间计量模型