Firms' GitHub Copilot adoption and labor market outcomes for software engineers

IF 1 4区经济学 Q2 ECONOMICS

Contemporary Economic Policy Pub Date : 2026-10-14 Epub Date: 2026-04-22 DOI:10.1111/coep.70035

Matthew Baird, Mar Carpanelli, Brian Xu, Kevin Xu

引用次数: 0

Abstract

Using LinkedIn and GitHub data, this paper examines how firms' adoption of GitHub Copilot (GHC), a generative AI coding assistant, relates to software engineer (SWE) skills and labor outcomes. GHC adoption is associated with around a 3%–5% higher monthly probability of hiring SWEs, driven by entry-level hires. New hires exhibit around 5% more non-programming skills, with no decrease in coding skills. These findings are consistent with, for SWEs, GAI's productivity impacts and creation of new tasks outweighing potential displacement effects from automation of some SWE tasks.

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公司的GitHub副驾驶员采用软件工程师和劳动力市场的结果

利用LinkedIn和GitHub数据，本文研究了企业采用GitHub Copilot (GHC)（一种生成式人工智能编码助手）与软件工程师（SWE）技能和劳动成果之间的关系。采用GHC与每月聘用SWEs的可能性高出3%-5%有关，这是由入门级员工推动的。新员工的非编程技能高出5%左右，编码技能没有下降。这些发现与以下观点一致：对于SWE来说，GAI对生产率的影响和新任务的创造超过了某些SWE任务自动化带来的潜在替代效应。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Contemporary Economic Policy Multiple-

CiteScore

3.10

自引率

6.70%

发文量

期刊介绍： Contemporary Economic Policy publishes scholarly economic research and analysis on issues of vital concern to business, government, and other decision makers. Leading western scholars, including three Nobel laureates, are among CEP"s authors. The objectives are to communicate results of high quality economic analysis to policymakers, focus high quality research and analysis on current policy issues of widespread concern, increase knowledge among economists of features of the economy key to understanding the impact of policy, and to advance methods of policy analysis.