Forecasting Seasonal UK Consumption Components

Periodic models for seasonal data allow the parameters of the model to vary across the different seasons. This paper uses the components of UK consumption to see whether the periodic autoregressive (PAR) model yields more accurate forecasts than non-periodic models, such as the airline model of Box and Jenkins (1970), and the autoregressive models that pre-test for (seasonal) unit roots. We analyze possible explanations for the relatively poor forecast performance of the periodic models that we find, notwithstanding the apparent support such models receive from the data in-sample.SEASONAL FLUCTUATIONS

Class of {varphi}X174 Mutants Relatively Deficient in Synthesis of Viral RNA

Nonpermissive cells infected with {varphi}X174 gene D amber mutants synthesized some sixfold less viral RNA than permissive cells. The decrease was unaffected by increasing the multiplicity of infection and was a consequence of an overall decrease in all viral RNA species. It is suggested that the gene D product may function in replicative form DNA unwinding to expose the template for transcription

The effect of a trapping procedure on the stress response of wild rainbow trout

Fish traps are a common research and management tool in which fish are subjected to procedures that elicit a stress response in other contexts. The effects of trapping on the stress response of sexually mature, wild rainbow trout Oncorhynchus mykiss were investigated during their upstream spawning migration by measuring concentrations of plasma cortisol, lactate, and glucose. Males had significantly lower basal plasma cortisol concentrations (6.1 ± 0.8 ng/mL [mean ± SE]) than females (21.4 ± 5.9 ng/mL). Similarly, the plasma cortisol response in males was significantly lower than that in females for all experiments. Fish working the barrier before entering the trap had increased concentrations of plasma cortisol. Confinement in the trap also induced a stress response. Plasma cortisol concentrations increased to 185.1 ± 40.9 ng/mL in males and 549.1 ± 60.1 ng/mL in females after confinement for 1 h. After processing, the magnitude of the stress response and the relative duration of recovery was less in fish that were confined longer in the trap. However, resting cortisol concentrations in females were not reached after 40 h of recovery in either group. Recovery to resting concentrations of plasma lactate occurred within 15 h after processing. In contrast, concentrations of plasma glucose remained significantly elevated at 40 h after processing. Postspawning fish had significantly lower plasma concentrations of cortisol, glucose, and lactate following application of an extreme stressor compared with prespawning fish. Based on the results of this study, we conclude that the trapping procedure induces a severe and prolonged stress response in wild rainbow trout

On SETAR non- linearity and forecasting

We consider the usefulness of the two-regime SETAR model for out-of-sample forecasting, and compare it with a linear AR model. A range of newly-developed forecast evaluation techniques are employed. Our simulation results show that time-series data need to exhibit a substantial degree of non-linearity before the SETAR model is favoured on some of these criteria. We find only weak evidence that a SETAR model of US GNP provides more accurate forecasts than a linear AR model.SETAR model;linear AR model;out-of-sample forecasting

Lumber Futures and Timberland Investment

Using 20 years of data, we derive a pricing model for timberland market values. We examine the relationship between lumber futures, capitalization rates, anticipated inflation, anticipated construction and timberland value. Using an ordinary least squares regression model and Johansen’s cointegration technique, we find that timberland market values have a long-run significant positive equilibrium relationship with lumber futures, and building permits. Capitalization rates have a significant negative relationship as expected. In the short run, unanticipated shocks in the independent variables provide a permanent change in timberland market values.

Resolving Architectural Mismatches of COTS Through Architectural Reconciliation

The integration of COTS components into a system under development entails architectural mismatches. These have been tackled, so far, at the component level, through component adaptation techniques, but they also must be tackled at an architectural level of abstraction. In this paper we propose an approach for resolving architectural mismatches, with the aid of architectural reconciliation. The approach consists of designing and subsequently reconciling two architectural models, one that is forward-engineered from the requirements and another that is reverse-engineered from the COTS-based implementation. The final reconciled model is optimally adapted both to the requirements and to the actual COTS-based implementation. The contribution of this paper lies in the application of architectural reconciliation in the context of COTS-based software development. Architectural modeling is based upon the UML 2.0 standard, while the reconciliation is performed by transforming the two models, with the help of architectural design decisions.

HACking at Non-linearity: Evidence from Stocks and Bonds

The implicit assumption of linearity is an important element in empirical finance. This study presents a hypothesis testing approach which examines the linear behaviour of the conditional mean between stock and bond returns. Conventional tests detect spurious non-linearity in the conditional mean caused by heteroskedasticity and/or autocorrelation. This study re-states these tests in a heteroskedasticity and autocorrelation consistent (HAC) framework and we find that stock and bond returns are indeed linear-in-the-mean in both univariate and bivariate settings. This study contends that previous research may have detected spurious non-linearity due to size distortions caused by heteroskedasticity and autocorrelation, rather than the presence of genuine non-linearity.linearity, nonlinear, heteroskedasticity-robust tests, autocorrelation-robust tests

Does Agricultural Liberalization Reduce Rural Welfare in Less Developed Countries? The Case of CAFTA

Conventional economic wisdom and findings from aggregate economy-wide models suggest that removing tariffs on agricultural imports is detrimental to rural welfare in less developed countries. This paper explores the rural welfare effects of own-country agricultural liberalization under CAFTA using a disaggregated rural economy-wide model that nests within it a series of micro agricultural household models. Our simulation findings suggest that CAFTA would reduce nominal incomes for nearly all rural household groups in El Salvador, Guatemala, Honduras and Nicaragua. However, compensating variations that take into account rural economy-wide adjustments to policy shocks are mostly negative, implying that current agricultural protection policies are disadvantageous for most rural household groups.International Relations/Trade,