... among variables. Additionally, the study reaffirms the central role of institutional quality and political stability in determining sovereign credit ratings, contributing to the expanding use of computational tools in economics, particularly for classification and forecasting tasks. Mathias Schneid...

...Amit Kumar; Manpreet Kaur; Anil Kumar Mittal Purpose The present paper aims to systematically map the research landscape of artificial neural networks ( ANNs ) in forex rate forecasting by particularly (1) uncovering significant research trends, key players, scientific collaborations, hot topics...

...Mohamad Ahmadian Purpose This study aims to investigate the impact of the COVID-19 pandemic on electronic payments and to predict future trends in this sector using advanced grey forecasting models. It seeks to fill the research gap in understanding how digital payment behaviors have evolved post...

...Edgardo Sica; Hazar Altınbaş; Gaetano Gabriele Marini Purpose Public debt forecasts represent a key policy issue. Many methodologies have been employed to predict debt sustainability, including dynamic stochastic general equilibrium models, the stock flow consistent method, the structural vector...

...Afees Salisu; Douglason Godwin Omotor Purpose This study forecasts the government expenditure components in Nigeria, including recurrent and capital expenditures for 2021 and 2022, based on data from 1981 to 2020. Design/methodology/approach The study employs statistical/econometric problems...

...Xiaojie Xu; Yun Zhang Purpose Chinese housing market has been growing fast during the past decade, and price-related forecasting has turned to be an important issue to various market participants, including the people, investors and policy makers. Here, the authors approach this issue...

... component allows their influence over the observable inflation to change over time. Out‐of‐sample forecasting exercises are used to test the model validity. Design/methodology/approach The model is written in state‐space form and estimation is carried out in one step via quasi‐maximum likelihood using...

...Hamid Baghestani; Bassam AbuAl‐Foul Purpose This study aims to both test the asymmetric information hypothesis and explore the factors influencing the one‐ through four‐quarter‐ahead Federal Reserve inflation forecasts for 1983‐2002. Design/methodology/approach Encompassing tests are used...

... based on quarterly data on real gross national product (GNP), consumption, investment and hours worked, for the South African economy, over the period of 1970:1 to 2000:4. Based on a recursive estimation using the Kalman filter algorithm, the out‐of‐sample forecasts from the hybrid model...

...Periklis Gogas; Apostolos Serletis Purpose This paper set out to use an autoregressive conditional heteroscedasticity (ARCH)‐type model to capture the time‐varying conditional variance of Alberta electricity prices. This is of major importance in forecasting, since ARCH‐type models allow...

... GNP quarterly data taking as reference the NBER and Romer’s business cycle datings. © MCB UP Limited 2001 Business cycles Economics USA Forecasting The reconstruction of the historical data of the US main economic indicators before the Second World War has allowed economic...

...Abul F.M. Shamsuddin; Richard A. Holmes Conducts both the cointegration test of the monetary theory of inflation and the Granger‐causality test between the variables in the system, and also develops univariate and multivariate time series models to forecast inflation rates. Quarterly time series...

...Ken Holden Analyses and checks the annual forecasts produced each autumn from four prominent UK economic modelling organizations. Compares these forecasts with those of three Bayesian vector‐autoregressive models. Examines the accuracy for each set of forecasts up to four years ahead...