Abstract Employing Factor Augmented Vector Autoregression (FAVAR) model where factors are obtained using the principal component analysis (PCA) and the parameters of the model are estimated using Vector Autoregression framework, we analyse how changes in monetary policy variables impact inflation, output, money supply, and the financial sector in India. Our results for the period 2001:04 to 2016:03 show that the benchmark FAVAR model showed more reliable results than baseline VAR model. Benchmark FAVAR model shows the existence of weak ‘liquidity puzzle’ in India. The impulse responses from the FAVAR approach reveal that monetary policy is more efficient in explaining the variations in inflation rather than stimulating output indicating its effectiveness in attaining the objective of price stability.

中文翻译：

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印度针对通货膨胀目标的有效性测试：因子增强向量自回归（FAVAR）方法

摘要运用因子增强向量自回归（FAVAR）模型，其中使用主成分分析（PCA）获得因子，并使用向量自回归框架估算模型的参数，我们分析了货币政策变量的变化如何影响通货膨胀，产出，货币供应量，以及印度的金融部门。我们在2001：04到2016：03期间的结果表明，基准FAVAR模型比基线VAR模型显示出更可靠的结果。基准FAVAR模型表明印度存在弱的“流动性难题”。FAVAR方法的冲动反应表明，货币政策在解释通货膨胀的变化上比在刺激产出方面更有效，这表明货币政策在实现价格稳定目标方面是有效的。