分析乌拉圭1974-2010年财政激励对工业投资的影响，发现长期效应显著。
Machine Learning and Econometric Approaches to Fiscal Policies: Understanding Industrial Investment Dynamics in Uruguay (1974-2010)
- 结合计量经济与机器学习方法，研究财政激励的短期与长期作用。
- 财政激励显著推动长期工业增长，且需稳定宏观环境配合。
- 揭示汇率等因子与政策的非线性关系，适合政策制定者参考。
本文研究1974至2010年间乌拉圭财政激励对工业投资的影响。采用混合方法，融合计量模型与机器学习技术，分析财政优惠在短期与长期对工业投资的作用。结果表明，财政激励对长期工业增长具有显著影响，同时强调宏观经济稳定、公共投资及信贷可得性的重要性。机器学习模型进一步揭示了财政激励与其他宏观经济因素（如汇率）之间的非线性交互作用，凸显定制化财政政策的必要性。研究结果对新兴经济体具有重要政策启示：财政激励若与更广泛的经济改革协同，可有效促进工业发展。
原文摘要 · Abstract (English)
This paper examines the impact of fiscal incentives on industrial investment in Uruguay from 1974 to 2010. Using a mixed-method approach that combines econometric models with machine learning techniques, the study investigates both the short-term and long-term effects of fiscal benefits on industrial investment. The results confirm the significant role of fiscal incentives in driving long-term industrial growth, while also highlighting the importance of a stable macroeconomic environment, public investment, and access to credit. Machine learning models provide additional insights into nonlinear interactions between fiscal benefits and other macroeconomic factors, such as exchange rates, emphasizing the need for tailored fiscal policies. The findings have important policy implications, suggesting that fiscal incentives, when combined with broader economic reforms, can effectively promote industrial development in emerging economies.
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