US inflation expectations and heterogeneous loss functions, 1968-2010

Recent literature has suggested that macroeconomic forecasters may have asymmetric loss functions, and that there may be heterogeneity across forecasters in the degree to which they weigh under- and over-predictions. Using an individual-level analysis that exploits the Survey of Professional Forecasters respondents’ histogram forecasts, we find little evidence of asymmetric loss for the inflation forecasters

Neural networks for identification of nonlinear systems under random piecewise polynomial disturbances

The problem of identification of a nonlinear dynamic system is considered. A two-layer neural network is used for the solution of the problem. Systems disturbed with unmeasurable noise are considered, although it is known that the disturbance is a random piecewise polynomial process. Absorption polynomials and nonquadratic loss functions are used to reduce the effect of this disturbance on the estimates of the optimal memory of the neural-network model.

Volatility forecasting for risk management

Recent research has suggested that forecast evaluation on the basis of standard statistical loss functions could prefer models which are sub-optimal when used in a practical setting. This paper explores a number of statistical models for predicting the daily volatility of several key UK financial time series. The out-of-sample forecasting performance of various linear and GARCH-type models of volatility are compared with forecasts derived from a multivariate approach. The forecasts are evaluated using traditional metrics, such as mean squared error, and also by how adequately they perform in a modern risk management setting. We find that the relative accuracies of the various methods are highly sensitive to the measure used to evaluate them. Such results have implications for any econometric time series forecasts which are subsequently employed in financial decisionmaking.

A model for exchange rates with crawling bands: an application to the Colombian peso

This paper builds upon previous research on currency bands, and provides a model for the Colombian peso. Stochastic differential equations are combined with information related to the Colombian currency band to estimate competing models of the behaviour of the Colombian peso within the limits of the currency band. The resulting moments of the density function for the simulated returns describe adequately most of the characteristics of the sample returns data. The factor included to account for the intra-marginal intervention performed to drive the rate towards the Central Parity accounts only for 6.5% of the daily change, which supports the argument that intervention, if performed by the Central Bank, it is not directed to push the currency towards the limits. Moreover, the credibility of the Colombian Central Bank, Banco de la República’s ability to defend the band seems low.

Production, hidden action, and the payment system

In this paper, we study a model economy that examines the optimal intraday rate. In Freeman’s (1996) paper, he shows that the efficient allocation can be implemented by adopting a policy in which the intraday rate is zero. We modify the production set and show that such a model economy can account for the non-uniform distribution of settlements within a day. In addition, by modifying both the consumption set and the production set, we show that the central bank may be able to implement the planner’s allocation with a positive intraday interest rate.

Commodity currency: an alternative route to currency union

Proposals have been made for a common currency for East Asia, but the countries preparing to participate need to be in a state of economic convergence. We show that at least six countries of East Asia already satisfy this condition. There also needs to be a mechanism by which the new currency relates to other reserve currencies. We demonstrate that a numéraire could be defined solely from the actual worldwide consumption of food and energy per capita, linked to fiat currencies via world market prices. We show that real resource prices are stable in real terms, and likely to remain so. Furthermore, the link from energy prices to food commodity prices is permanent, arising from energy inputs in agriculture, food processing and distribu-tion. Calibration of currency value using a yardstick such as our SI numéraire offers an unbiased measure of the con-sistently stable cost of subsistence in the face of volatile currency exchange rates. This has the advantage that the par-ticipating countries need only agree to currency governance based on a common standards institution, a much less on-erous form of agreement than would be required in the creation of a common central bank.

Accounting for the economic risk, caused by variation in disease severity, in fungicide dose decisions: exemplified for Mycosphaerella graminicola on winter wheat

A method is presented to calculate economic optimum fungicide doses accounting for the risk-aversion of growers responding to variability in disease severity between crops. Simple dose-response and disease-yield loss functions are used to estimate net disease-related costs (fungicide cost, plus disease-induced yield loss) as a function of dose and untreated severity. With fairly general assumptions about the shapes of the probability distribution of disease severity and the other functions involved, we show that a choice of fungicide dose which minimises net costs on average across seasons results in occasional large net costs caused by inadequate control in high disease seasons. This may be unacceptable to a grower with limited capital. A risk-averse grower can choose to reduce the size and frequency of such losses by applying a higher dose as insurance. For example, a grower may decide to accept ‘high loss’ years one year in ten or one year in twenty (i.e. specifying a proportion of years in which disease severity and net costs will be above a specified level). Our analysis shows that taking into account disease severity variation and risk-aversion will usually increase the dose applied by an economically rational grower. The analysis is illustrated with data on septoria tritici leaf blotch of wheat caused by Mycosphaerella graminicola. Observations from untreated field plots at sites across England over three years were used to estimate the probability distribution of disease severities at mid-grain filling. In the absence of a fully reliable disease forecasting scheme, reducing the frequency of ‘high loss’ years requires substantially higher doses to be applied to all crops. Disease resistant cultivars reduce both the optimal dose at all levels of risk and the disease-related costs at all doses.

Forecasting economic and financial time series with non-linear models

In this paper we discuss the current state-of-the-art in estimating, evaluating, and selecting among non-linear forecasting models for economic and financial time series. We review theoretical and empirical issues, including predictive density, interval and point evaluation and model selection, loss functions, data-mining, and aggregation. In addition, we argue that although the evidence in favor of constructing forecasts using non-linear models is rather sparse, there is reason to be optimistic. However, much remains to be done. Finally, we outline a variety of topics for future research, and discuss a number of areas which have received considerable attention in the recent literature, but where many questions remain.

The importance of the volatility risk premium for volatility forecasting

In this paper, we study the role of the volatility risk premium for the forecasting performance of implied volatility. We introduce a non-parametric and parsimonious approach to adjust the model-free implied volatility for the volatility risk premium and implement this methodology using more than 20 years of options and futures data on three major energy markets. Using regression models and statistical loss functions, we find compelling evidence to suggest that the risk premium adjusted implied volatility significantly outperforms other models, including its unadjusted counterpart. Our main finding holds for different choices of volatility estimators and competing time-series models, underlying the robustness of our results.

Translation practices in political institutions: a comparison of national, supranational, and non-governmental organisations

This paper explores the settings and practices of translation at three types of political institutions, i.e. national, supranational, and non-governmental organisations. The three institutions are the translation service of the German Foreign Office, the translation department of the European Central Bank, and translation provision by the non-governmental organisation Amnesty International. The three case studies describe the specific translation practices in place at these institutions and illustrate some characteristic translation strategies. In this way, we reflect on how different translation practices can impact on translation agency and how these practices in turn are influenced by the type of institution and its organisational structure. The article also aims to explore to which extent the characteristics of collectivity, anonymity and standardisation, and of institutional translation as self-translation are applicable to the institutions under discussion.

Balkanisation of banking damages international trade and UK GDP

Balkanisation is a way to describe the breakdown of cross-border banking, as nervous lenders retreat in particular from the more troubled parts of the Eurozone or at least try to isolate operations within national boundaries. It is increasing at the Bank level, however the senior policy makers consider this a negative trend – Mario Draghi, president of the European Central Bank, has talked of the need to “repair this financial fragmentation” and Mark Carney, head of global regulatory body the Financial Stability Board, [and now Governor of the Bank of England] has warned that deglobalising finance will hurt growth and jobs by “reducing financial capacity and systemic resilience”. In this article I would like to examine the impact of banking balkanisation on international trade and provide some initial thoughts about remedies for excessive risk in a banking non-balkanising world.

Do jumps matter for volatility forecasting? Evidence from energy markets

This paper characterizes the dynamics of jumps and analyzes their importance for volatility forecasting. Using high-frequency data on four prominent energy markets, we perform a model-free decomposition of realized variance into its continuous and discontinuous components. We find strong evidence of jumps in energy markets between 2007 and 2012. We then investigate the importance of jumps for volatility forecasting. To this end, we estimate and analyze the predictive ability of several Heterogenous Autoregressive (HAR) models that explicitly capture the dynamics of jumps. Conducting extensive in-sample and out-of-sample analyses, we establish that explicitly modeling jumps does not significantly improve forecast accuracy. Our results are broadly consistent across our four energy markets, forecasting horizons, and loss functions

Declining resilience of ecosystem functions under biodiversity loss

The composition of species communities is changing rapidly through drivers such as habitat loss and climate change, with potentially serious consequences for the resilience of ecosystem functions on which humans depend. To assess such changes in resilience, we analyse trends in the frequency of species in Great Britain that provide key ecosystem functions-specifically decomposition, carbon sequestration, pollination, pest control and cultural values. For 4,424 species over four decades, there have been significant net declines among animal species that provide pollination, pest control and cultural values. Groups providing decomposition and carbon sequestration remain relatively stable, as fewer species are in decline and these are offset by large numbers of new arrivals into Great Britain. While there is general concern about degradation of a wide range of ecosystem functions, our results suggest actions should focus on particular functions for which there is evidence of substantial erosion of their resilience.

Introducing improved cultivars: Understanding farmers' seed drying and storage practices in central Ghana

Improved upland rice cultivars introduced in Volta Region, Ghana, have been perceived to store poorly compared to farmers' traditional cultivars. A survey was conducted in 2003 in the Hohoc district of this region, where a participatory Varietal Selection programme had started in 1997, to gain insight into fanners' seed production and storage practices that are likely to affect seed quality in storage. Farmers rated keeping quality (p < 0.001), tolerance to storage pests (p < 0.001), seed quality (p < 0.001) and establishment of their local cultivars Kawomo, Viono and Wuwulili as much better than the improved cultivar IDSA 85. Initial seed moisture content ranged from 12.8 to 18% and germination from 0 to 82%. There was a significant relationship between seed moisture content and duration of drying prior to storage (p < 0.001) and storage method (p = 0.015). Germination loss in storage was rapid at high moisture content and slow at low moisture content. Between 60 and 80% of seeds germinated after six Months storage at 12.8% moisture content. The viability equation predicted accurately germination of farmer-saved seed stored under ambient temperature in Ghana. Except for the japonica rice cultivar WAB 126-18-HB, the traditional cultivars Kawomo, Viono and Wuwulili survived better in storage than improved cultivars. There is a need to improve seed quality of improved cultivars if farmers are to benefit from their higher yields and grain quality and to improve storage practices.

Study of the lactation curve in dairy cattle on farms in Central Mexico

Accurate knowledge of lactation curves has an important relevance to management and research of dairy production systems. A number of equations have been proposed to describe the lactation curve, the most widely applied being the gamma equation. The objective of this work was to compare and evaluate candidate functions for their predictive ability in describing lactation curves from central Mexican dairy cows reared under 2 contrasting management systems. Five equations were considered: Gaines ( exponential decay), Wood ( gamma equation), Rook ( Michaelis-Menten x exponential), and 2 more mechanistic ones (Dijkstra and Pollott). A database consisting of 701 and 1283 records of cows in small-scale and intensive systems, respectively, was used in the analysis. Before analysis, the database was divided into 6 groups representing first, second, and third and higher parity cows in both systems. In all cases except second and above parity cows in small-scale systems, all models improved on the Gaines equation. The Wood equation explained much of the variation, but its parameters do not have direct biological interpretation. Although the Rook equation fitted the data well, some of the parameter estimates were not significant. The Dijkstra equation consistently gave better predictions, and its parameters were usually statistically significant and lend themselves to physiological interpretation. As such, the differences between systems and parity could be explained due to variations in theoretical initial milk production at parturition, specific rates of secretory cell proliferation and death, and rate of decay, all of which are parameters in the model. The Pollott equation, although containing the most biology, was found to be over-parameterized and resulted in nonsignificant parameter estimates. For central Mexican dairy cows, the Dijkstra equation was the best option to use in describing the lactation curve.