Narrow your search

Library

ULB (3)

National Bank of Belgium (2)

Vlaams Parlement (2)


Resource type

book (3)


Language

English (3)


Year
From To Submit

2023 (1)

2020 (2)

Listing 1 - 3 of 3
Sort by

Book
Improving the Short-term Forecast of World Trade During the Covid-19 Pandemic Using Swift Data on Letters of Credit
Authors: --- --- --- ---
Year: 2020 Publisher: Washington, D.C. : International Monetary Fund,

Loading...
Export citation

Choose an application

Bookmark

Abstract

An essential element of the work of the Fund is to monitor and forecast international trade. This paper uses SWIFT messages on letters of credit, together with crude oil prices and new export orders of manufacturing Purchasing Managers’ Index (PMI), to improve the short-term forecast of international trade. A horse race between linear regressions and machine-learning algorithms for the world and 40 large economies shows that forecasts based on linear regressions often outperform those based on machine-learning algorithms, confirming the linear relationship between trade and its financing through letters of credit.


Book
Improving the Short-term Forecast of World Trade During the Covid-19 Pandemic Using Swift Data on Letters of Credit
Authors: --- --- --- ---
ISBN: 1513562878 Year: 2020 Publisher: Washington, D.C. : International Monetary Fund,

Loading...
Export citation

Choose an application

Bookmark

Abstract

An essential element of the work of the Fund is to monitor and forecast international trade. This paper uses SWIFT messages on letters of credit, together with crude oil prices and new export orders of manufacturing Purchasing Managers’ Index (PMI), to improve the short-term forecast of international trade. A horse race between linear regressions and machine-learning algorithms for the world and 40 large economies shows that forecasts based on linear regressions often outperform those based on machine-learning algorithms, confirming the linear relationship between trade and its financing through letters of credit.


Book
Predicting the Law: Artificial Intelligence Findings from the IMF’s Central Bank Legislation Database
Authors: --- --- ---
ISBN: 9798400260162 Year: 2023 Publisher: Washington, D.C. : International Monetary Fund,

Loading...
Export citation

Choose an application

Bookmark

Abstract

Using the 2010, 2015, and 2020/2021 datasets of the IMF’s Central Bank Legislation Database (CBLD), we explore artificial intelligence (AI) and machine learning (ML) approaches to analyzing patterns in central bank legislation. Our findings highlight that: (i) a simple Naïve Bayes algorithm can link CBLD search categories with a significant and increasing level of accuracy to specific articles and phrases in articles in laws (i.e., predict search classification); (ii) specific patterns or themes emerge across central bank legislation (most notably, on central bank governance, central bank policy and operations, and central bank stakeholders and transparency); and (iii) other AI/ML approaches yield interesting results, meriting further research.

Listing 1 - 3 of 3
Sort by