英文标题：
《Understanding food inflation in India: A Machine Learning approach》
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作者：
Akash Malhotra, Mayank Maloo
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最新提交年份：
2017
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英文摘要：
Over the past decade, the stellar growth of Indian economy has been challenged by persistently high levels of inflation, particularly in food prices. The primary reason behind this stubborn food inflation is mismatch in supply-demand, as domestic agricultural production has failed to keep up with rising demand owing to a number of proximate factors. The relative significance of these factors in determining the change in food prices have been analysed using gradient boosted regression trees (BRT), a machine learning technique. The results from BRT indicates all predictor variables to be fairly significant in explaining the change in food prices, with MSP and farm wages being relatively more important than others. International food prices were found to have limited relevance in explaining the variation in domestic food prices. The challenge of ensuring food and nutritional security for growing Indian population with rising incomes needs to be addressed through resolute policy reforms.
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中文摘要：
在过去十年中，印度经济的强劲增长受到了持续高水平通货膨胀的挑战，尤其是食品价格。这种顽固的食品通胀背后的主要原因是供需不匹配，因为由于一些近因，国内农业生产无法跟上需求的增长。利用梯度增强回归树（BRT）这一机器学习技术，分析了这些因素在确定食品价格变化中的相对重要性。BRT的结果表明，所有预测变量在解释食品价格变化方面都相当重要，MSP和农场工资相对来说比其他变量更重要。国际食品价格在解释国内食品价格变化方面的相关性有限。需要通过果断的政策改革来应对确保收入不断增长的印度人口的粮食和营养安全的挑战。
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分类信息：

一级分类：Statistics 统计学
二级分类：Machine Learning 机器学习
分类描述：Covers machine learning papers (supervised, unsupervised, semi-supervised learning, graphical models, reinforcement learning, bandits, high dimensional inference, etc.) with a statistical or theoretical grounding
覆盖机器学习论文（监督，无监督，半监督学习，图形模型，强化学习，强盗，高维推理等）与统计或理论基础
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一级分类：Quantitative Finance 数量金融学
二级分类：Economics 经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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