Mustard price dynamics due to ban on blending: time series intervention model with nonlinear function

Intervention analysis is used to study structural changes in data resulting from external events. Traditional time series intervention models, viz. autoregressive integrated moving average model with exogenous variables (ARIMA-X) and artificial neural networks with exogenous variables (ANN-X), rely on linear intervention functions such as step or ramp functions, or their combinations. However, when intervention effects are nonlinear, growth models may offer a viable alternative. This study proposed a new algorithm for time series intervention analysis employing ARIMA and ANN models with a nonlinear intervention function. The Hoerl function has been introduced as a nonlinear intervention function. To demonstrate the effectiveness of the proposed model, monthly wholesale price data from three markets in Rajasthan, namely, Tonk, Alwar and Sriganganagar during January 2010 to May 2023 have been used. The analysis encompassed a comprehensive examination across all markets, revealing that the proposed models consistently outperformed the conventional ARIMA-X and ANN-X methodologies in terms of performance and accuracy