印尼九大制造企业集群的技术效率及其影响因素:随机前沿分析

Theresya Jeini Astanto, S. Suyanto, Henrycus Winarto Santoso, Ruhul Salim
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引用次数: 1

摘要

目前的研究考察了印尼制造企业的技术效率低下及其关键决定因素。在以往研究主要集中于某一特定行业企业的基础上,本研究将企业划分为9个产业集群,并分别对其进行估计,在集群之间寻找各种结果。采用随机前沿分析(SFA)方法对5848家企业5年(共29240次观察)的低效率得分和关键决定因素进行了估计。数据期截止于2014年,原因是印尼中央统计局调查中制造业分类代码发生了重大变化。记录了五个值得注意的发现。首先,所有观察企业的平均效率得分为0.8815。其次,在所有企业和9个集群中的3个(ISIC 34、ISIC 35和ISIC 37)的样本中,企业规模对效率低下有负向影响。第三,无论是在所有企业样本中,还是在每九个产业集群样本中,外资所有权都对企业的技术效率低下产生负贡献。第四,出口导向对9个产业集群的企业有不同的影响,其中纸及纸制品行业(ISIC 34)和金属制品行业(ISIC 38)的负面影响显著。最后,在大多数产业集群中,进口强度对企业具有显著的负向影响。这些发现支持了在分析技术效率低下的关键决定因素的影响时,吸收能力和独特企业特征的重要性的论点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Technical Inefficiency in Nine Clusters of Indonesian Manufacturing Firms And its Determinants: Stochastic Frontier Analysis
The current study examines the technical inefficiency of Indonesian manufacturing firms and its key determinants. Extending the previous research that mainly focuses on firms in a specific industry, the current study groups firms into nine industrial clusters and estimates them separately to find a variety of results among the clusters. The stochastic frontier analysis (SFA) method is applied to estimate the inefficiency score and the key determinants of 5,848 firms for five years (29,240 total observations). Data period ended in 2014 due to the substantial change in the classification code of the manufacturing industry in the survey by the Indonesian Central Board of Statistics. Five notable findings are recorded. First, the average efficiency score of all observed firms is 0.8815. Second, firm size is found to have a negative effect on inefficiency in the sample of all firms and three out of nine clusters (ISIC 34, ISIC 35, and ISIC 37). Third, foreign ownership generates a negative contribution to firms’ technical inefficiency in both the sample of all firms and the sample of each nine industrial clusters. Fourth, export orientation has various effects on firms across nine industrial clusters, with a dominant significant negative impact in paper and paper product industry (ISIC 34) and metal product industry (ISIC 38). Finally, import intensity provides a significant negative impact on firms in most industrial clusters. These findings support the argument on the importance of absorption capacity and unique firm characteristics in analyzing the impact of key determinants of technical inefficiency.
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