预测德克萨斯农村地区的公司创建:一个多模型机器学习方法来解决复杂的政策问题
Mark C Hand1,2, Vivek Shastry2, Varun Rai2
1University of Texas at Arlington, Arlington, Texas, United States of America.
PloS one
|June 23, 2023
概括
美国农村地区的企业家精神是由诸如多样性和移民等社会经济因素驱动的,而不仅仅是宽带接入. 这些发现为政策制定者提供了支持农村经济增长的指导.
科学领域:
- *农村创业和经济发展.
- * 应用机器学习用于社会经济分析.
- * 创建公司的比较研究.
背景情况:
- * 农村和城市地区面临着日益严重的政治和经济分裂.
- *创业是农村经济振兴,创造就业机会和恢复力的关键战略.
- * 有限的研究存在于特定在农村环境中的企业创建与城市环境相比.
研究的目的:
- * 确定美国农村地区创建公司的预测因素.
- * 解决创业研究中关于比较变量重要性方面的差距,重点关注城市/高科技企业,以及现代机器学习的应用.
- * 为决策者提供有关促进农村经济增长的见解.
主要方法:
- * 应用四种机器学习方法:子集选择,LASSO,随机森林和极端梯度增强.
- *分析了一套新的数据集,对2008-2018年德克萨斯州农村县进行了检查.
- *比较框架,以评估各种社会经济和行业特定因素的预测重要性.
主要成果:
- *社会经济因素,如年龄分布,种族多样性,社会资本和移民,比宽带接入或专利更能预测农村企业的增长.
- *行业实力 (石油,风力,医疗保健,老年人/儿童保健) 和当地银行数量也预测了稳定的增长.
- *农村企业增长的预测因素与城市地区的预测因素有很大不同.
结论:
- *农村创业是一个独特的现象,需要量身定制的战略和专注.
- * 机器学习模型有效地识别了农村企业创建的复杂,多因素驱动因素.
- * 调查结果为旨在刺激农村经济的政策制定者提供了实际指导.
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