Our paper investigates productivity, output growth and total factor productivity (TFP) growth using a novel single-index smooth-coefficient stochastic frontier approach and two firm-level datasets respectively from the high technology (high-tech) manufacturing and Knowledge Intensive Business Services (KIBS) sectors in Norway. The approach considers input productivity and technical inefficiency to be flexible functions of production environmental variables indexed with unknown parameters for more precise estimation of marginal effects of these variables on the frontier and inefficiency. Output growth is decomposed into technical change (TC), input-driven component (IDC) and efficiency change (EC), while TFP growth is decomposed into TC, scale component and EC. The primary objective is to (i) maximise output through the frontier and efficiency channels and (ii) enhance productivity growth through such channels as technical progress and efficiency improvement, specifically tailored for the manufacturing and services industries. The empirical results reveal substantial heterogeneity in technology across firms. Overall speaking, geographical industrial concentration, export intensity and urbanisation positively influence output in both sectors. Technical progress contributes to TFP growth in both sectors; however, TC is biased towards capital in the high-tech sector and driven by labour in the KIBS sector. In addition to TC, TFP growth in the high-tech and KIBS sectors also benefits from EC and IDC, respectively.

中文翻译：

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生产率和增长分解：一种新颖的单指数平滑系数随机前沿方法


本文使用一种新的单指数平滑系数随机前沿方法和两个公司级数据集分别来自挪威的高科技 （high-tech） 制造业和知识密集型商业服务 （KIBS） 部门，研究了生产率、产出增长和全要素生产率 （TFP） 增长。该方法认为投入生产率和技术低效率是用未知参数索引的生产环境变量的灵活函数，以便更精确地估计这些变量对前沿和低效率的边际影响。产出增长被分解为技术变化 （TC）、投入驱动成分 （IDC） 和效率变化 （EC），而 TFP 增长被分解为 TC、规模成分和 EC。主要目标是 （i） 通过前沿和效率渠道实现产出最大化，以及 （ii） 通过技术进步和效率提升等渠道提高生产力，特别是为制造业和服务业量身定制的渠道。实证结果表明，不同公司之间的技术存在很大的异质性。总体而言，工业的地理集中度、出口强度和城市化对这两个行业的产出都有积极影响。技术进步有助于这两个行业的 TFP 增长;然而，TC 偏向于高科技领域的资本，并由 KIBS 部门的劳动力驱动。除了 TC 之外，高科技和 KIBS 行业的 TFP 增长也分别受益于 EC 和 IDC。