Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Time series econometrics and forecasting constitute a dynamic research area that combines sophisticated statistical methodologies with economic theory to model, interpret and predict economic and ...

State & Local Government Review, Vol. 10, No. 3 (Sep., 1978), pp. 92-99 (8 pages) A quarterly econometric model, the Louisiana Revenue Projection Model, is developed and tested for forecasting state ...

Education and health services remained the strongest-performing category and are among the least vulnerable to recession, ...

Journal of Applied Econometrics, Vol. 17, No. 5, Special Issue: Modelling and Forecasting Financial Volatility (Sep. - Oct., 2002), pp. 601-616 (16 pages) Due to high and low volatility periods, time ...

Will the world still need economists in 2030? With skin in the game, we certainly hope so — but artificial intelligence is already transforming economic analysis. In our own work — and in a review of ...

Lawrence R. Klein was the father of modern economic forecasting, which melds economics with statistics in an attempt to predict the future. Mr. Klein, who died Sunday at age 93, was the recipient of ...

This paper develops an econometric panel data model that can be used both to identify the dynamic effects of disease transmission factors and to forecast disease spread. The empirical model is derived ...