Fluctuaciones cíclicas y raíces unitarias en la economia española, 1850-1990

En este artículo se analiza el grado de persistencia de las fluctuaciones cíclicas en la economía española. En concreto, se estudia si el PIB y el PIB por capita de esta economía presentan una raíz unitaria. Con el fin de evitar el sesgo a aceptar raíces unitarias cuando se producen cambios en la función de tendencia, como el originado por la Guerra Civil española (1936-1939), se han aplicado varios contrastes que tienen en cuenta los cambios en la función de tendencia. Los resultados obtenidos muestran que existe una importante evidencia en el sentido que el logaritmo del PIB presenta una raíz unitaria. La principal implicación de este resultado es que los shocks sobre el producto tienen efectos permanentes en el nivel del PIB de la economía española, aun cuando esta hipótesis es más difícil de aceptar por el PIB por capita vista la evidencia contradictoria encontrada a favor de la misma.

Coherent forecasting of multiple-decrement life tables: a test using Japanese cause of death data

Planners in public and private institutions would like coherent forecasts of the components of age-specic mortality, such as causes of death. This has been di cult toachieve because the relative values of the forecast components often fail to behave ina way that is coherent with historical experience. In addition, when the group forecasts are combined the result is often incompatible with an all-groups forecast. It hasbeen shown that cause-specic mortality forecasts are pessimistic when compared withall-cause forecasts (Wilmoth, 1995). This paper abandons the conventional approachof using log mortality rates and forecasts the density of deaths in the life table. Sincethese values obey a unit sum constraint for both conventional single-decrement life tables (only one absorbing state) and multiple-decrement tables (more than one absorbingstate), they are intrinsically relative rather than absolute values across decrements aswell as ages. Using the methods of Compositional Data Analysis pioneered by Aitchison(1986), death densities are transformed into the real space so that the full range of multivariate statistics can be applied, then back-transformed to positive values so that theunit sum constraint is honoured. The structure of the best-known, single-decrementmortality-rate forecasting model, devised by Lee and Carter (1992), is expressed incompositional form and the results from the two models are compared. The compositional model is extended to a multiple-decrement form and used to forecast mortalityby cause of death for Japan

Is the observed persistence spurious? A test for fractional integration versus short memory and structural breaks

Although it is commonly accepted that most macroeconomic variables are nonstationary, it is often difficult to identify the source of the non-stationarity. In particular, it is well-known that integrated and short memory models containing trending components that may display sudden changes in their parameters share some statistical properties that make their identification a hard task. The goal of this paper is to extend the classical testing framework for I(1) versus I(0)+ breaks by considering a a more general class of models under the null hypothesis: non-stationary fractionally integrated (FI) processes. A similar identification problem holds in this broader setting which is shown to be a relevant issue from both a statistical and an economic perspective. The proposed test is developed in the time domain and is very simple to compute. The asymptotic properties of the new technique are derived and it is shown by simulation that it is very well-behaved in finite samples. To illustrate the usefulness of the proposed technique, an application using inflation data is also provided.

Morphological and functional variability in the root system of Quercus ilex L. subject to confinement: consequences for afforestation

We examined root morphological and functional differences caused by restrictions imposed to vertical growth in the root system of holm oak (Quercus ilex L.) seedlings to assess the consequences of using nursery containers in the development of a confined root system for this species. Thus, root morphological, topological and functional parameters, including hydraulic conductance per leaf unit surface area (K $_{\rm RL})$, were investigated in one-year seedlings cultivated in three PVC tubes differing in length (20, 60 and 100 cm). Longer tubes showed greater projected root area, root volume, total and fine root lengths, specific root length (SRL) and K$_{\rm RL}$ values than did shorter tubes. On the other hand, the length of coarse roots (diameter > 4.5 mm) and the average root diameter were greater in shorter tubes. The strong positive correlation found between K$_{\rm RL}$ and SRL (r=+0.69; P<0.001) indicated that root thickness was inversely related to water flow through the root system. We concluded that root systems developed in longer tubes are more efficient for plant water uptake and, therefore, changes in root pattern produced in standard forest containers (i.e. about 20 cm length) may in fact prevent a proper establishment of the holm oak in the field, particularly in xeric environments.

Problems of the randomization test for AB designs

N = 1 designs imply repeated registrations of the behaviour of the same experimental unit and the measurements obtained are often few due to time limitations, while they are also likely to be sequentially dependent. The analytical techniques needed to enhance statistical and clinical decision making have to deal with these problems. Different procedures for analysing data from single-case AB designs are discussed, presenting their main features and revising the results reported by previous studies. Randomization tests represent one of the statistical methods that seemed to perform well in terms of controlling false alarm rates. In the experimental part of the study a new simulation approach is used to test the performance of randomization tests and the results suggest that the technique is not always robust against the violation of the independence assumption. Moreover, sensitivity proved to be generally unacceptably low for series lengths equal to 30 and 40. Considering the evidence available, there does not seem to be an optimal technique for single-case data analysis