Author Description

This Paper Applies State-of-the-art Deep Learning Techniques To Develop The First Sentiment Index Measuring Member Countries’ Reception Of Imf Policy Advice At The Time Of Article Iv Consultations. This Paper Finds That While Authorities Of Member Countries Largely Agree With Fund Advice, There Is Variation Across Country Size, External Openness, Policy Sectors And Their Assessed Riskiness, Political Systems, And Commodity Export Intensity. The Paper Also Looks At How Sentiment Changes During And After A Financial Arrangement Or Program With The Fund, As Well As When A Country Receives Imf Technical Assistance. The Results Shed Light On Key Aspects On Fund Surveillance While Redefining How The Imf Can View Its Relevance, Value Added, And Traction With Its Member Countries. Ghada Fayad, Chengyu Huang, Yoko Shibuya, Peng Zhao.