{"title":"An environmental Kuznets curve for global forests: An application of the mi-lasso estimator","authors":"","doi":"10.1016/j.forpol.2024.103304","DOIUrl":null,"url":null,"abstract":"<div><p>In this study, we employ a Moran's <span><math><mi>i</mi></math></span> based Lasso (Mi-Lasso) methodology to address the spatial dependence of an unspecified functional form, investigating the association between a country's economic growth and the rate of deforestation. Our aim is to explore the existence of a forestry environmental Kuznets curve (EKC). Our approach to handling spatial dependence overcomes limitations identified in existing EKC literature. We estimate a series of cross-sectional data models spanning the period from 1990 to 2020 for 146 countries. Our findings indicate a non-linear relationship, revealing a change peak rate of deforestation over time. Additionally, we observe that the income threshold at which the deforestation rate begins to decrease changes over time with differences observed between model specifications. Crucially, our results highlight that failing to account for spatial dependence leads to a significant absolute upward bias in ordinary least squares (OLS) estimates of income and worse model fit.</p></div>","PeriodicalId":12451,"journal":{"name":"Forest Policy and Economics","volume":null,"pages":null},"PeriodicalIF":4.0000,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1389934124001588/pdfft?md5=24ed1e5dd57b115acef4f70cc7711d1c&pid=1-s2.0-S1389934124001588-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forest Policy and Economics","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1389934124001588","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, we employ a Moran's based Lasso (Mi-Lasso) methodology to address the spatial dependence of an unspecified functional form, investigating the association between a country's economic growth and the rate of deforestation. Our aim is to explore the existence of a forestry environmental Kuznets curve (EKC). Our approach to handling spatial dependence overcomes limitations identified in existing EKC literature. We estimate a series of cross-sectional data models spanning the period from 1990 to 2020 for 146 countries. Our findings indicate a non-linear relationship, revealing a change peak rate of deforestation over time. Additionally, we observe that the income threshold at which the deforestation rate begins to decrease changes over time with differences observed between model specifications. Crucially, our results highlight that failing to account for spatial dependence leads to a significant absolute upward bias in ordinary least squares (OLS) estimates of income and worse model fit.
期刊介绍:
Forest Policy and Economics is a leading scientific journal that publishes peer-reviewed policy and economics research relating to forests, forested landscapes, forest-related industries, and other forest-relevant land uses. It also welcomes contributions from other social sciences and humanities perspectives that make clear theoretical, conceptual and methodological contributions to the existing state-of-the-art literature on forests and related land use systems. These disciplines include, but are not limited to, sociology, anthropology, human geography, history, jurisprudence, planning, development studies, and psychology research on forests. Forest Policy and Economics is global in scope and publishes multiple article types of high scientific standard. Acceptance for publication is subject to a double-blind peer-review process.