Forecasting in ation is fundamental to UK monetary policy, both for policy-makers and private agents. However, forecast failure is prevalent with naive devices often outperforming the dominant congruent in-sample model in forecasting competitions. This paper assesses evidence for UK annual and quarterly in ation using the theoretical framework developed by Clements and Hendry (1998, 1999) to ex...

Article history: Received 13 February 2016 Accepted 4 July 2016 Available online 5 August 2016 To compare the accuracy of different forecasting approaches an error measure is required. Many error measures have been proposed in the literature, however in practice there are some situations where different measures yield different decisions on forecasting approach selection and there is no agreeme...

Soil moisture monitoring and the characterization of the spatial and temporal variability of this hydrologic parameter at scales from small catchments to large river basins continues to receive much attention, reflecting its critical role in subsurface – land surface – atmosphere interactions and its importance to drought analysis, crop yield forecasting, irrigation planning, flood protection, ...

Earthquake forecasting is known to be a challenging research program for which no single prediction method can claim to be the best. At large, earthquake data when viewed as a time series over a long time, exhibits a complex pattern that is composed of a mix of statistical features. A single prediction algorithm often does not yield an optimal forecast by analyzing over a long series that is co...

The merits of the modelling philosophy of Box & Jenkins (1970) are illustrated with a summary of our recent work on seasonal river flow forecasting. Specifically, this work demonstrates that the principle of parsimony, which has been questioned by several authors recently, is helpful in selecting the best model for forecasting seasonal river flow. Our work also demonstrates the importance of mo...

This study is an endeavor to evaluate statistically predicts a weather-crop yield-forecasting model to generate early crop production estimates. The weather-crop yield-forecasting model was applied to estimate prospective production of Aus rice in Jessore and Rajshahi districts of Bangladesh. This model is the relationship between the crop yield and input weather parameters influencing the crop...

In the present study, bio-meteorological models for predicting olive-crop production in the southern Iberian Peninsula were developed. These covered a 16-year period: 1994-2009. The forecasting models were constructed using the partial least-squares regression method, taking the annual olive yield as the dependent variable, and both aerobiological and meteorological parameters as the independen...