This study addresses the challenge of sovereign external debt sustainability by employing a cointegration test, machine-learning classifiers, and explainable models. Focusing on 22 middle-income countries during the period 2000-2021, our study aims to provide accurate insights into debt...

Economic indicators provide important information for the evaluation of the state of the economy of a country and they are used for business cycle analysis. Timeliness of the indicators is of fundamental interest for analysts of government authorities, national banks, politicians or economic...

Accurate Gross Domestic Product (GDP) prediction is essential for economic planning and policy formulation. This paper evaluates the performance of three machine learning models-Random Forest Regression (RFR), XGBoost, and Prophet-in predicting Somalia's GDP. Historical economic data, including...

Market turnover levels and liquidity changes across various territories significantly influence currency prices, leading to continuous fluctuations. Consequently, traders and investors constantly seek strategies to mitigate exchange rate risks. This study aimed to measure and assess foreign...

I utilize latent Dirichlet allocation and dynamic topic model that are machine learning algorithms across a data set encompassing 25,990 financial accounting articles issued from 1956 to 2023 in 16 accounting journals, and impartially ascertain 20 research topics. The topics of mergers and...