India is the largest producer of cotton in the world. For proper planning and designing of policies related to cotton, robust forecast of future production is utmost necessary. In this study, an ...

Refer to Pankratz (1991) "Forecasting with Dynamic Regression Models," and Box and Jenkins (1976) "Time Series Analysis: Forecasting and Control" for more information on dynamic regression or transfer ...

Laura Liu, Hyungsik Roger Moon, Frank Schorfheide, FORECASTING WITH DYNAMIC PANEL DATA MODELS, Econometrica, Vol. 88, No. 1 (January 2020), pp. 171-201 ...

Learn how ARIMA models use time series data for accurate short-term forecasting. Discover its pros, cons, and essential tips ...

Using historical data and regression analysis has its limitations in business forecasting. For example, a significant correlation between the independent and dependent variable does not ...

Traditional forecasting models trained primarily on a company’s historical data were never best practice. Given the mass graduation from big data to smart data was already underway, demand ...

These platform enhancements reflect the market’s transition from static annual budgeting to dynamic, real-time financial forecasting and planning.

Scientists from the University of the Philippines Diliman have developed an artificial intelligence (AI) model to forecast rainfall from tropical cyclones.