IT服务业生产企业效率排名:以印度跨国公司为例

H. Vinod, P. M. Rao
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引用次数: 0

摘要

生产函数通常研究有资本和劳动投入的实物产品的产出。相反,我们使用2004年至2016年55家印度跨国公司的数据来评估服务生产。我们对柔性生产函数的估计产生了对汇集数据的规模弹性(SCE)和替代弹性(EOS)的估计。对31家数据相对完整的公司进行子集分析,得出了它们各自的SCE和EOS值,揭示了它们的异质性。根据SCE对31家公司进行分类,有助于命名规模高效(高SCE)和规模低效(低SCE)的跨国公司。同样,EOS对31家公司进行了分类,使我们能够列出对投入价格冲击有(或没有)抵抗力的公司。利用这些上市公司的股票市场数据,我们报告了SCE对排名靠前的公司的三个股票市场标准的价值。我们还研究了从市场标准到EOS和SCE的实证因果路径,表明SCE和EOS确实推动了暗示有效市场的股票市场指标。我们的汇总和详细结果与政府针对IT部门和公司治理问题的政策相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficiency Ranking of IT Service-Producing Firms: Case of Indian Multinationals
Production functions often study the output of physical products with capital and labor inputs. Instead, we use 2004 to 2016 data for 55 Indian multinational companies to assess the production of services. Our estimates of flexible production functions yield estimates of scale elasticity (SCE) and elasticity of substitution (EOS) for pooled data. A subset of 31 companies with relatively complete data yields their individual SCE and EOS values, revealing their heterogeneity. Sorting the 31 companies by their SCE help name scale-efficient (high SCE) and scale inefficient (low SCE) multinationals. Similarly, a listing of 31 companies sorted by EOS allows us to name companies that are (and are not) robust to input price shocks. Using stock market data on these publicly traded companies, we report the values of three stock market criteria for top ranking companies by SCE. We also study empirical causal paths from the market criteria to EOS and SCE, suggesting that SCE and EOS do drive stock market indicators implying efficient markets. Our pooled and detailed results are relevant for government policy toward the IT sector and corporate governance issues.
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