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Long Time Series (long + time_series)
Selected AbstractsFlood events overrule fertiliser effects on biomass production and species richness in riverine grasslandsJOURNAL OF VEGETATION SCIENCE, Issue 5 2007Boudewijn Beltman Abstract Question: Do severe winter flood events lift the nutrient limitation of biomass production in a river floodplain? How does this affect plant species richness? How long do the effects last? Location: Floodplain grassland on calcareous sandy loam near river Rhine in The Netherlands. Methods: Plots were fertilised with four treatments (control, N, P, N+P) for 21 years; plant species composition, vegetation biomass and tissue nutrient concentrations were determined every year between 1985 and 2005. Results: Fertilisation with N generally increased biomass production and reduced species richness, but these effects varied over time. During the first four years of the experiment, biomass production appeared to be co-limited by N and P, while N fertilisation dramatically reduced plant species richness; these effects became weaker subsequently. Following two extreme winter floods in 1993,94 and 1994,95 and a drought in spring 1996, the effects of fertilisation disappeared between 1998 and 2001 and then appeared again. Flooding caused an overall reduction in species richness (from c. 24 to 15 species m -2) and an increase in biomass production, which were only partly reversed after ten years. Conclusions: Long time series are necessary to understand vegetation dynamics and nutrient limitation in river floodplains, since they are influenced by occasional flood and drought events, whose effects may persist for more than ten years. A future increase in flooding frequency might be detrimental to species richness in floodplain grasslands. [source] Capturing Government Policy on the Left,Right Scale: Evidence from the United Kingdom, 1956,2006POLITICAL STUDIES, Issue 4 2009Armèn Hakhverdian The left,right scheme is the most widely used and parsimonious representation of political competition. Yet, long time series of the left,right position of governments are sparse. Existing methods are of limited use in dynamic settings due to insufficient time points which hinders the proper specification of time-series regressions. This article analyses legislative speeches in order to construct an annual left,right policy variable for Britain from 1956 to 2006. Using a recently developed content analysis tool, known as Wordscores, it is shown that speeches yield valid and reliable estimates for the left,right position of British government policy. Long time series such as the one proposed in this article are vital to building dynamic macro-level models of politics. This measure is cross-validated with four independent sources: (1) it compares well to expert surveys; (2) a rightward trend is found in post-war British government policy; (3) Conservative governments are found to be more right wing in their policy outputs than Labour governments; (4) conventional accounts of British post-war politics support the pattern of government policy movement on the left,right scale. [source] Latent Separability: Grouping Goods without Weak SeparabilityECONOMETRICA, Issue 1 2000Richard Blundell This paper develops a new concept of separability with overlapping groups,latent separability. This is shown to provide a useful empirical and theoretical framework for investigating the grouping of goods and prices. It is a generalization of weak separability in which goods are allowed to enter more than one group and where the composition of groups is identified by the choice of group specific exclusive goods. Latent separability is shown to be equivalent to weak separability in latent rather than purchased goods and provides a relationship between separability and household production theory. For the popular class of linear, almost ideal and translog demand models and their generalizations, we provide a method for choosing the number of homothetic separable groups. A detailed method for exploring the composition of the separable groups is also presented. These methods are applied to a long time series of British individual household data on the consumption of twenty two nondurable and service goods. [source] Up-to-date cancer survival: Period analysis and beyondINTERNATIONAL JOURNAL OF CANCER, Issue 6 2009Hermann Brenner Abstract Since its introduction in 1996, period analysis has been shown to be useful for deriving more up-to-date cancer survival estimates, and the method is now increasingly used for that purpose in national and international cancer survival studies. However, period analysis, like other commonly employed methods, is just a special case from a broad class of design options in the analysis of cancer survival data. Here, we explore a broader range of design options, including 2 model-based approaches, for deriving up-to-date estimates of 5- and 10-year relative survival for patients diagnosed in the most recent 5-year interval for which data are available. The performance of the various designs is evaluated empirically for 20 common forms of cancer using more than 50-year long time series of data from the Finnish Cancer Registry. Period analysis as well as the 2 model-based approaches, one using a "cohort-type model" and another using a "period-type model", all performed better than traditional cohort or complete analysis. Compared with "standard period analysis", the cohort-type model further increased up-to-dateness of survival estimates, whereas the period-type model increased their precision. While our analysis confirms advantages of period analysis over traditional methods in terms of up-to-dateness of cancer survival data, further improvements are possible by flexible use of model-based approaches. © 2008 Wiley-Liss, Inc. [source] A synoptic-scale climate analysis of anomalous snow water equivalent over the Northern Great Plains of the USAINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 8 2003Andrew Grundstein Abstract The Northern Great Plains is a region where variations in seasonal snow accumulation can have a dramatic affect on regional hydrology. In the past, one of the problems in studying snow hydrology has been obtaining information of sufficiently high temporal and spatial resolution on the water content of the snowpack. This project used a hybrid climatology of snow water equivalent (SWE) that incorporated both model and observed data. This climatology has a long time series (49 years) and a high spatial resolution (1° × 1°) sufficient for use in a climatic analysis. The long and complete time series of SWE generated in this project allowed for a comprehensive analysis of the meteorological and climate forcing mechanisms that influence the amount of SWE. The five largest (high SWE) and five smallest SWE (low SWE) accumulations on 1 March were examined. High SWE years received greater snowfall and fewer accumulated melting degree days throughout the season. Large SWE accumulations at the end of the season, however, were not always associated with deep snowpacks early in the season. Also, all five high SWE years had above normal snowfall in February. Years with small or no SWE had below-average snowfall but greater than average accumulated melting degree days. A synoptic analysis examined both atmospheric circulation and air mass frequencies to assess impacts on ablation and snowfall. A distinct difference in the frequency of different air mass during high SWE versus low SWE years was evident. High SWE years were characterized by substantially greater intrusions of the coldest and driest air mass type (dry polar). Low SWE years, in contrast, had a greater frequency of more moderate air masses (dry moderate and moist moderate). In years with above average SWE, negative departures in November,December,January,February composite 700 hPa field were evident across the continental USA and indicate a greater frequency of troughing across the study area. Low SWE years were characterized by a ridging pattern that reduced the likelihood of precipitation and may have aided in the intrusion of more moderate air masses. Copyright © 2003 Royal Meteorological Society [source] Using the Lee,Carter Method to Forecast Mortality for Populations with Limited Data,INTERNATIONAL STATISTICAL REVIEW, Issue 1 2004Nan Li Summary The Lee,Carter method for modeling and forecasting mortality has been shown to work quite well given long time series of data. Here we consider how it can be used when there are few observations at uneven intervals. Assuming that the underlying model is correct and that the mortality index follows a random walk with drift, we find the method can be used with sparse data. The central forecast depends mainly on the first and last observation, and so can be generated with just two observations, preferably not too close in time. With three data points, uncertainty can also be estimated, although such estimates of uncertainty are themselves highly uncertain and improve with additional observations. We apply the methods to China and South Korea, which have 3 and 20 data points, respectively, at uneven intervals. Résumé La méthode Lee,Carter de modélisation et de prévision de la mortalité a prouvé son bon fonctionnement avec des séries de données existant sur une longue période. Nous envisageons ici son utilisation lorsqu'on ne dispose que de quelques observations à intervalles irréguliers. En supposant que le modèle sous-jacent est correct et que l'indice de mortalité suit une marche aléatoire avec dérive, nous trouvons que cette méthode peut êetre utilisée avec des données éparses. La prévision centrale dépend alors principalement de la première et de la dernière observation. Elle peut donc êetre générée à partir de deux observations seulement, de préférence pas trop proches dans le temps. Avec trois points, on peut aussi estimer l'aléa, bienqu'un tel estimateur de l'aléa soit lui-mêeme très aléatoire. Il s'améliore cependant lorsqu'on dispose d'observations supplémentaires. Nous appliquons notre méthode àla Chine et à la Corée du Sud, pour lesquelles nous avons respectivement 3 et 20 points àintervalles irréguliers. [source] Detecting year-of-birth mortality patterns with limited dataJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2008S. J. Richards Summary., Late life mortality patterns are of crucial interest to actuaries assessing risk of longevity, most obviously for annuities and defined benefit pension schemes. The stability of public finances is also affected, as the governments have very substantial risk of longevity in the form of state benefits and public sector pension schemes. One important explanatory variable for late life mortality patterns is year of birth. Previous work has demonstrated various techniques for detecting such patterns, but always with long time series of mortality rates. The paper describes two alternative ways to detect such patterns, even with missing population data or the absence of a time series. The paper finds support for the idea that different birth cohorts have different rates of aging. [source] Averaged Periodogram Spectral Estimation with Long-memory Conditional HeteroscedasticityJOURNAL OF TIME SERIES ANALYSIS, Issue 4 2001Marc Henry The empirical relevance of long-memory conditional heteroscedasticity has emerged in a variety of studies of long time series of high frequency financial measurements. A reassessment of the applicability of existing semiparametric frequency domain tools for the analysis of time dependence and long-run behaviour of time series is therefore warranted. To that end, in this paper the averaged periodogram statistic is analysed in the framework of a generalized linear process with long-memory conditional heteroscedastic innovations according to a model specification first proposed by Robinson (Testing for strong serial correlation and dynamic conditional heteroscedasticity in multiple regression. J. Economet. 47 (1991), 67,84). It is shown that the averaged periodogram estimate of the spectral density of a short-memory process remains asymptotically normal with unchanged asymptotic variance under mild moment conditions, and that for strongly dependent processes Robinson's averaged periodogram estimate of long memory (Semiparametric analysis of long memory time series. Ann. Stat. 22 (1994), 515,39) remains consistent. [source] Capturing Government Policy on the Left,Right Scale: Evidence from the United Kingdom, 1956,2006POLITICAL STUDIES, Issue 4 2009Armèn Hakhverdian The left,right scheme is the most widely used and parsimonious representation of political competition. Yet, long time series of the left,right position of governments are sparse. Existing methods are of limited use in dynamic settings due to insufficient time points which hinders the proper specification of time-series regressions. This article analyses legislative speeches in order to construct an annual left,right policy variable for Britain from 1956 to 2006. Using a recently developed content analysis tool, known as Wordscores, it is shown that speeches yield valid and reliable estimates for the left,right position of British government policy. Long time series such as the one proposed in this article are vital to building dynamic macro-level models of politics. This measure is cross-validated with four independent sources: (1) it compares well to expert surveys; (2) a rightward trend is found in post-war British government policy; (3) Conservative governments are found to be more right wing in their policy outputs than Labour governments; (4) conventional accounts of British post-war politics support the pattern of government policy movement on the left,right scale. [source] | |||||||||||||