Unveiling the causal effects of China’s minimum living standard guarantee on household transportation expenditures: A causal forest analysis

IF 6.3 2区 工程技术 Q1 ECONOMICS
Zheng Wu , Yihua Zhang , Mingyu Zhang
{"title":"Unveiling the causal effects of China’s minimum living standard guarantee on household transportation expenditures: A causal forest analysis","authors":"Zheng Wu ,&nbsp;Yihua Zhang ,&nbsp;Mingyu Zhang","doi":"10.1016/j.tranpol.2024.09.021","DOIUrl":null,"url":null,"abstract":"<div><div>We investigate the causal effects of China’s Minimum Living Standard Guarantee (<em>MLSG</em>, also called <em>Dibao</em>) subsidy on household transportation expenditures. Utilizing data from the Chinese Social Survey, we employ a combination of the propensity score matching (<em>PSM</em>), causal forest (<em>CF</em>) and marginal treatment effect model (<em>MTE</em>) methodologies to rigorously estimate the subsidy’s effects. The <em>PSM</em> allows us to mitigate selection bias by matching <em>MLSG</em> recipients with comparable non-recipients. While the causal forest captures the heterogeneity of treatment effects across various household profiles. The result of <em>MTE</em> indicate that observable and essential heterogeneity are present to influence the effect of their subsidies, which present the consistent with <em>PSM</em> and <em>CF</em>. The causal mediation analysis indicates the mediating mechanism that <em>MLSG</em> impacts on household transportation expenditures, while also revealing significant variations among different regions. The study not only refines our understanding of the <em>MLSG</em>’s effects on household spending but also offers novel insights into applicational advancements by incorporating machine-learning techniques for policy evaluation. These results have important implications for policy formulation and refinement, particularly in the urban-rural differences.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"159 ","pages":"Pages 1-13"},"PeriodicalIF":6.3000,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transport Policy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967070X24002725","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0

Abstract

We investigate the causal effects of China’s Minimum Living Standard Guarantee (MLSG, also called Dibao) subsidy on household transportation expenditures. Utilizing data from the Chinese Social Survey, we employ a combination of the propensity score matching (PSM), causal forest (CF) and marginal treatment effect model (MTE) methodologies to rigorously estimate the subsidy’s effects. The PSM allows us to mitigate selection bias by matching MLSG recipients with comparable non-recipients. While the causal forest captures the heterogeneity of treatment effects across various household profiles. The result of MTE indicate that observable and essential heterogeneity are present to influence the effect of their subsidies, which present the consistent with PSM and CF. The causal mediation analysis indicates the mediating mechanism that MLSG impacts on household transportation expenditures, while also revealing significant variations among different regions. The study not only refines our understanding of the MLSG’s effects on household spending but also offers novel insights into applicational advancements by incorporating machine-learning techniques for policy evaluation. These results have important implications for policy formulation and refinement, particularly in the urban-rural differences.
揭示中国最低生活保障对家庭交通支出的因果效应:因果森林分析
我们研究了中国最低生活保障补贴对家庭交通支出的因果效应。利用中国社会调查的数据,我们综合运用倾向得分匹配法(PSM)、因果森林法(CF)和边际治疗效果模型法(MTE),对补贴效果进行了严格估算。倾向得分匹配法使我们能够将小额贷款担保基金的受助者与可比的非受助者进行匹配,从而减少选择偏差。而因果森林则捕捉了不同家庭情况下治疗效果的异质性。MTE 的结果表明,可观察到的基本异质性会影响其补贴效果,这与 PSM 和 CF 的结果一致。因果中介分析表明了多层次交通补贴对家庭交通支出影响的中介机制,同时也揭示了不同地区之间的显著差异。这项研究不仅完善了我们对 MLSG 对家庭支出影响的理解,而且通过将机器学习技术应用于政策评估,为应用的进步提供了新的见解。这些结果对政策的制定和完善具有重要意义,尤其是在城乡差异方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Transport Policy
Transport Policy Multiple-
CiteScore
12.10
自引率
10.30%
发文量
282
期刊介绍: Transport Policy is an international journal aimed at bridging the gap between theory and practice in transport. Its subject areas reflect the concerns of policymakers in government, industry, voluntary organisations and the public at large, providing independent, original and rigorous analysis to understand how policy decisions have been taken, monitor their effects, and suggest how they may be improved. The journal treats the transport sector comprehensively, and in the context of other sectors including energy, housing, industry and planning. All modes are covered: land, sea and air; road and rail; public and private; motorised and non-motorised; passenger and freight.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信