Topic Classification of Central Bank Monetary Policy Statements: Evidence from Latent Dirichlet Allocation in Lesotho

M. Damane
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引用次数: 1

Abstract

Abstract This article develops a baseline on how to analyse the statements of monetary policy from Lesotho’s Central Bank using a method of topic classification that utilizes a machine learning algorithm known as Latent Dirichlet Allocation. To evaluate the changes in the policy distribution, the classification of topics is performed on a sample of policy statements spanning from February 2017 to January 2021. The three-topic Latent Dirichlet Allocation model extracted topics that remained prominent throughout the sample period and were most closely reflective of the functions of the Central Bank of Lesotho Monetary Policy Committee. The topics identified are: (i) International Monetary and Financial Market Conditions; (ii) Monetary Policy Committee and International Reserves; (iii) Regional and International Economic Policy Conditions. The three-topic Latent Dirichlet Allocation model was determined as the most appropriate model through which a consistent analysis of topic evolution in Central Bank of Lesotho Monetary Policy Statements can be performed.
中央银行货币政策声明的主题分类:来自莱索托潜在狄利克雷配置的证据
本文开发了一个关于如何使用主题分类方法分析莱索托中央银行货币政策声明的基线,该方法利用了一种称为潜在狄利克雷分配的机器学习算法。为了评估政策分布的变化,对2017年2月至2021年1月的政策声明样本进行主题分类。三主题潜狄利克雷分配模型提取了在整个样本期间仍然突出的主题,并且最能反映莱索托中央银行货币政策委员会的职能。确定的主题是:(i)国际货币和金融市场状况;货币政策委员会和国际储备;区域和国际经济政策条件。三主题潜狄利克雷配置模型被确定为最合适的模型,通过该模型可以对莱索托央行货币政策声明的主题演变进行一致性分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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