Forecasting UK consumer price inflation using inflation forecasts

The inflation rate is a key economic indicator for which forecasters are constantly seeking to improve the accuracy of predictions, so as to enable better macroeconomic decision making. Presented in this paper is a novel approach which seeks to exploit auxiliary information contained within inflation forecasts for developing a new and improved forecast for inflation by modeling with Multivariate Singular Spectrum Analysis (MSSA). Unlike other forecast combination techniques, the key feature of the proposed approach is its use of forecasts, i.e. data into the future, within the modeling process and extracting auxiliary information for generating a new and improved forecast. We consider real data on consumer price inflation in UK, obtained via the Office for National Statistics. A variety of parametric and nonparametric models are then used to generate univariate forecasts of inflation. Thereafter, the best univariate forecast is considered as auxiliary information within the MSSA model alongside historical data for UK consumer price inflation, and a new multivariate forecast is generated. We find compelling evidence which shows the benefits of the proposed approach at generating more accurate medium to long term inflation forecasts for UK in relation to the competing models. Finally, through the discussion, we also consider Google Trends forecasts for inflation within the proposed framework.     

Forecasting the price of gold

This article seeks to evaluate the appropriateness of a variety of existing forecasting techniques (17 methods) at providing accurate and statistically significant forecasts for gold price. We report the results from the nine most competitive techniques. Special consideration is given to the ability of these techniques to provide forecasts which outperforms the random walk (RW) as we noticed that certain multivariate models (which included prices of silver, platinum, palladium and rhodium, besides gold) were also unable to outperform the RW in this case. Interestingly, the results show that none of the forecasting techniques are able to outperform the RW at horizons of 1 and 9 steps ahead, and on average, the exponential smoothing model is seen providing the best forecasts in terms of the lowest root mean squared error over the 24-month forecasting horizons. Moreover, we find that the univariate models used in this article are able to outperform the Bayesian autoregression and Bayesian vector autoregressive models, with exponential smoothing reporting statistically significant results in comparison with the former models, and classical autoregressive and the vector autoregressive models in most cases.     

Economic Roots of Political Conflict: The Case of Sri Lanka

The escalation of political conflicts in many developing countries and their impact on economic development have been topical issues in recent development literature. The overwhelming emphasis on ‘ethnic conflicts’ in the literature has, however, precluded analysts from looking at political conflicts beyond their ethnic dimension, in the wider context of the development process. In particular, because of the preoccupation with ethnic roots as the prime source of these conflicts, reverse causation, running from economic policy to political conflict, has been virtually ignored in the debate. The purpose of this paper is to fill this gap through an in‐depth case study of the ‘twin political conflict’ in Sri Lanka – the Tamil separatist war in the North and the Sinhala youth uprising in the South – with emphasis on its economic roots. The findings suggest that fundamental contradictions in the national development policy in the restrictive trade regime of Sri Lanka were at the heart of the country's twin political conflict.     

Ethical and moral considerations of airline management

Air transport is a relatively new industry. It has expanded rapidly and now is an exceptionally safe way to travel. But all may not be well. Despite all this achievement, the human face of commercial aviation has been somewhat tarnished by the very prolific growth of carriage by air, and the monotonous regularity with which it is executed. Aviation business management needs to go back to basics, where the formula “everyone needs to know and feel that he is needed; and everyone wants to be treated as an individual” has to be revisited in the face of modern exigencies experienced by the passenger. The issue is likely to gain in importance in the future as economic, political and social trends affect the types of people who wish to use air transport. Airline managers have to be aware of the need to identify passengers in need and offer tangible support and assistance. This article addresses issues relating to the human face of aviation management and looks at some of the proposals to improve current practices.