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Background: Local policymakers require information about public health, housing and well-being at small geographical areas. A municipality can for example use this information to organize targeted activities with the aim of improving the well-being of their residents. Surveys are often used to gather data, but many neighborhoods can have only few or even zero respondents. In that case, estimating the status of the local population directly from survey responses is prone to be unreliable. Methods: Small Area Estimation (SAE) is a technique to provide estimates at small geographical levels with only few or even zero respondents. In classical individual-level SAE, a complex statistical regression model is fitted to the survey responses by using auxiliary administrative data for the population as predictors, the missing responses are then predicted and aggregated to the desired geographical level. In this paper we compare gradient boosted trees (XGBoost), a well-known machine learning technique, to a structured additive regression model (STAR) designed for the specific problem of estimating public health and well-being in the whole population of the Netherlands. Results: We compare the accuracy and performance of these models using out-of-sample predictions with five-fold Cross Validation (5CV). We do this for three data sets of different sample sizes and outcome types. Compared to the STAR model, gradient boosted trees are able to improve both the accuracy of the predictions and the total time taken to get these predictions. Even though the models appear quite similar in overall accuracy, the small area predictions at neighborhood level sometimes differ significantly. It may therefore make sense to pursue slightly more accurate models for better predictions into small areas. However, one of the biggest benefits is that XGBoost does not require prior knowledge or model specification. Data preparation and modelling is much easier, since the method automatically handles missing data, non-linear responses, interactions and accounts for spatial correlation structures. Conclusions: In this paper we provide new nationwide estimates of health, housing and well-being indicators at neighborhood level in the Netherlands, see 'Online materials'. We demonstrate that machine learning provides a good alternative to complex statistical regression modelling for small area estimation in terms of accuracy, robustness, speed and data preparation. These results can be used to make appropriate policy decisions at a local level and make recommendations about which estimation methods are beneficial in terms of accuracy, time and budget constraints. [ABSTRACT FROM AUTHOR]

Focuses on the estimation procedure for a fixed coefficients vintage model in the Netherlands. Use of the output and labor demand data for capacity variables; Confirmation of the structural unemployment; Overestimation of the life span of the oldest equipment.

This paper develops a simple dynamic oligopoly model and a quick estimation procedure for empirical applications. I develop a simple dynamic oligopoly model for empirical work. A unique feature of the model is that any Markov-perfect equilibrium that survives some intuitive refinements can be quickly computed from low-dimensional contraction mappings in seconds. After computation, it is easy to check the uniqueness of the refined equilibrium. These results facilitate fast estimation using a full-solution approach and produce reliable counterfactual analysis. Model estimation at its minimum only requires panel data on firm presence, yet it quantifies important market primitives, such as toughness of competition and entry costs. I provide a step-by-step illustration of the estimation approach by applying it to the Dutch retail grocery industry, in which chain stores slowly replace local stores. A counterfactual simulation computing equilibrium under a large number of different primitive values shows that relaxing restrictions on chain-store entry will not only quicken the destruction of local stores, but also hurt chain stores' profits. Data and the online appendix are available at https://doi.org/10.1287/mksc.2018.1117. [ABSTRACT FROM AUTHOR]

Copyright of Demography (Springer Nature) is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bouvier, C.; Balouin Y.; Castelle B., and Valentini N., 2020. Video depth inversion at a microtidal site exposed to prevailing low-energy short-period waves and episodic severe storms. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1021–1026. Coconut Creek (Florida), ISSN 0749-0208. Over the last decades, a wide range of depth inversion algorithms have been developed, which aim to infer local water depth from remotely-sensed wave parameters based on physical relations. Particularly, the depth inversion algorithm named cBathy (Holman, Plant, and Holland, 2013) showed good results for a range of wave conditions and environments but the method was only applied to beaches exposed to moderate or highly energetic wave climate, with wave peak period often larger than 8 s. This paper applies the cBathy algorithm for the very first time on a Mediterranean Sea beach, Sète, southeast France, a semidiurnal microtidal environment exposed to a moderate-energy modal wave climate and episodic severe storms. The objective of the paper is to assess the ability of the cBathy algorithm to estimate the nearshore bathymetry for waves with large energy spread in both direction and frequency. After a comparison between the remotely sensed bathymetry and a ground truth bathymetric survey, we use a non-linear, depth-averaged morphodynamic model, 2DBeach (Dubarbier et al., 2017), on remotely sensed bathymetries to determine the sensitivity of nearshore waves and horizontal circulations to the estimated morphology. The depth inversion technique estimates the nearshore bathymetry with good accuracy (RMSE = 0.39 m) for a beach area extending respectively 1600 m and 600 m in the longshore and cross-shore directions, respectively, suggesting the technical feasibility of coupling remotely-sensed bathymetry to 2DH numerical model, even at short-waves exposed Mediterranean beaches. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the perceptions of key participants in the Dutch Cost–Benefit Analysis (CBA) practice regarding substantive problems when appraising spatial-infrastructure projects with CBA. Two research methods were applied. Firstly, 86 key participants in the Dutch CBA practice were interviewed in-depth in order to obtain an overview and a ranking of perceived substantive problems with CBA in the Netherlands. Secondly, the people interviewed were also asked to fill in a written questionnaire in which they were asked to rank the substantive problems once again, in order to improve the validity of the ranking; 74 of the participants completed this questionnaire. The most important conclusions of this paper are, firstly, that key participants in the Dutch CBA practice consider ‘problems with the estimation of the non-monetized project effects’ as the most important substantive problem cluster and ‘problems with monetizing project effects’ as the second most important substantive problem cluster. Secondly, key participants in the Dutch CBA practice consider the ‘problem analysis’ in a CBA to be a very important substantive problem. Thirdly, there is, in a broad sense, consensus among the different groups in the Dutch CBA practice concerning their perception of the seriousness of problem clusters and the way they rank the problem clusters. Fourthly, a large part of the substantive problems mentioned by the key participants in the Dutch CBA practice are non-specific CBA problems. [Copyright &y& Elsevier]

This paper discusses the effects of the existence of natural and/or exogenously imposed thresholds in firm size distributions on estimations of the relation between firm size and the variance in firm growth rates. We argue that these estimations are upwardly biased whenever the threshold operates on the same proxy that is used to calculate the growth rates. We show the potential impact of the bias on simulated data, suggest a methodology to improve these estimations, and present an empirical analysis on Dutch firms. The only stable relation that emerges is the negative relationship between firm size and growth rate variance. [ABSTRACT FROM AUTHOR]

The study of time series models for count data has become a topic of special interest during the last years. However, while research on univariate time series for counts now flourishes, the literature on multivariate time series models for count data is notably more limited. In the present paper, a bivariate integer-valued autoregressive process of order 1 (BINAR(1)) is introduced. Emphasis is placed on models with bivariate Poisson and bivariate negative binomial innovations. We discuss properties of the BINAR(1) model and propose the method of conditional maximum likelihood for the estimation of its unknown parameters. Issues of diagnostics and forecasting are considered and predictions are produced by means of the conditional forecast distribution. Estimation uncertainty is accommodated by taking advantage of the asymptotic normality of maximum likelihood estimators and constructing appropriate confidence intervals for the fe-step-ahead conditional probability mass function. The proposed model is applied to a bivariate data series concerning daytime and nighttime road accidents in the Netherlands. [ABSTRACT FROM AUTHOR]

This paper's objective is to develop a method to estimate the total mortality among problem drug users. The total mortality is given by a base rate of mortality not related to drugs and the deaths that are directly and indirectly related to drugs. A fatal poisoning by drugs (overdose) is directly related to drugs, whereas a casualty due to a drug-related disease or a drug-related accident is indirectly related to drugs. As an example of a method to estimate the total mortality, the results from a cohort study among methadone patients in Amsterdam were projected on the whole population of problem drug users in The Netherlands. Due to differences between the problem drug users in Amsterdam and the rest of the country, adjustments were required. It was found that an initial estimation did not require adjustment for injection behavior and gender but did require adjustment for age and the percentage of HIV infection. In a first unadjusted estimation, the total number of deaths among problem drug users in The Netherlands in 2001 was estimated at 606 deaths. After adjustment for age, the estimated mortality decreased to 573 deaths, and after adjustment for HIV infection, this estimation again decreased to 479 deaths. From the ultimately estimated mortality, 11% was considered to be not related to drugs, 23% was attributed directly to drugs, and 66% was attributed indirectly to drugs. The number of direct deaths, as estimated by this method, falls in the same order of magnitude as the number extracted from the Causes of Death Statistics, when selecting cases according to the Drug-Related Deaths Standard as established by the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA). Further cross-validation with other measures will be needed to assess the accuracy of the method, the limitations of which are discussed with respect to stipulating directions for future research. [ABSTRACT FROM AUTHOR]

LOFAR is a low-frequency radio astronomical array currently under development in The Netherlands. It is designed to produce synthesis images of the most distant celestial objects yet observed. Due to high redshift levels, observations must be at unusually low frequencies (30-240 MHz), over large apertures (100 km), using thousands of antennas. At these frequencies, Earth's ionosphere acts as a random refractive sheet which over the large aperture induces source direction dependent gain and phase errors that must be estimated and calibrated out. Current radio astronomy "self-calibration" algorithms do not address direction dependence and will not work in the LOFAR environment. This paper presents a formal study of the parameter estimation problem for LOFAR calibration. A data model is proposed, and a Cramer-Rao lower bound (CRB) analysis is developed with a new general formulation to easily incorporate a variety of constraining signal models. It is shown that although the unconstrained direction dependent calibration problem is ambiguous, physically justifiable constraints can be applied in LOFAR to yield viable solutions. Use of a "compact core" of closely spaced array elements as part of the larger array is shown to significantly improve full array direction dependent calibration performance. Candidate algorithms are proposed and compared to the CRB. [ABSTRACT FROM AUTHOR]

This study compares state space models (estimated with the Kalman filter with a frequentist approach to hyperparameter estimation) with multilevel time series models (based on the hierarchical Bayesian framework). The application chosen is the Dutch Travel Survey featuring small sample sizes and discontinuities caused by the survey redesigns. Both modelling approaches deliver similar point and variance estimates. Slight differences in model-based variance estimates appear mostly in small-scaled domains and are due to neglecting uncertainty around the hyperparameter estimates in the state space models, and to a lesser extent to skewness in the posterior distributions of the parameters of interest. The results suggest that the reduction in design-based standard errors with the hierarchical Bayesian approach is over 50% at the provincial level, and over 30% at the national level. [ABSTRACT FROM AUTHOR]

The author comments on a study that examined the use of social contact data to improve estimation of transmission parameters for infectious respiratory disease. Researchers asked a random sample of people in Utrecht, Netherlands about the number of conversations they had with people of different age groups during a typical week before using the data on which to base their contact matrix analysis. The results of the study are said to indicate the effectiveness of using simple data in estimating contact structures in dynamic infectious disease models.

We study if labour market mismatch has increased in the Netherlands during the Great Recession. First, we estimate a so-called 'steady-state' Beveridge curve based on labour market flows. An outward shift of this curve implies decreasing matching efficiency. Second, we construct a mismatch index which enables us to calculate the contribution of sector mismatch to the increase in unemployment. Our analyses show little support for the hypothesis that mismatch is currently a significant problem for the Dutch labour market. At the aggregate level, the Beveridge curve has not shifted outwards. In addition, at most one-ninth of the Dutch unemployment rise can be attributed to sector mismatch, which is comparable to the contribution during the previous downturn. [ABSTRACT FROM AUTHOR]

Abstract: This paper uses the automobile market model Dynamo to assess the effects of replacing car purchase and road taxes with CO2-differentiated distance-based user charges in the Netherlands. The effects of this replacement on vehicle size and the composition of the car fleet are estimated, as are the effects on emissions and mileage. We conclude that distance-based charging schemes can reduce CO2 emissions and other traffic-related pollutants but can also have unintended impacts on the size, composition and environmental performance of the national car fleet (e.g., car ownership increases, fuel efficiency is reduced and emissions per kilometer driven increases). These unintended effects occur because households react more strongly to one-time fixed costs than to recurring variable costs and because car costs are reduced for households with relatively low car usage. Environmentally differentiated distance-based charges can reduce these effects, but only partially. [Copyright &y& Elsevier]

Abstract: Surface subsidence is in many cases an unwanted effect of subsurface exploitation. It can, however, also be used as a reservoir monitoring tool. The present paper reports a field study on the Roswinkel gas field, in which subsidence data were used to reduce the uncertainty about the reservoir architecture. The Roswinkel gas field in the northeast of the Netherlands was in production from 1980 to 2005. Located at about 2100m depth, it is a severely faulted anticlinal structure, constituting up to 30 reservoir compartments. As a result of its complexity there are large uncertainties about the fault transmissibilities and the strength of the connected aquifer. Consequently, it is possible there are undepleted compartments in the reservoir. Pressure depletion due to gas production causes the reservoir sandstones to compact, leading to surface subsidence. The gas production in Roswinkel has induced subsidence of approximately 17cm above the center of the field. The subsidence at any point on the surface is a result of compaction over a large area within the reservoir. We estimated the compaction in the reservoir using subsidence data in order to reduce the uncertainties about fault transmissibility and aquifer connection. The subsidence data had been obtained from leveling campaigns and satellite measurements (Persistent Scatterer InSAR). We used a previously developed Bayesian inversion method in which prior knowledge is combined with observations. The prior knowledge on the compaction and the associated uncertainties were generated by Monte Carlo simulations of the reservoir in which the fault transmissibilities and aquifer connectivity were varied. In the meantime, the geological reality was maintained and the production history was honored. The average prior compaction field was a relatively smooth field extending far into the aquifer and typically having an uncertainty of 40%. Our inversion results show a reservoir in which certain large faults divide the reservoir into compartments with different pressure histories. In addition, the aquifer activity appeared to be much weaker than the average prior knowledge suggested. The posterior uncertainty of the degree of compaction was reduced to about 10%. Our study demonstrates that a carefully executed inversion exercise can considerably reduce uncertainties, thus making it possible to identify possibly undepleted compartments in the reservoir. [Copyright &y& Elsevier]

Abstract: This paper presents a new method for assessing the risk of accidents associated with darkness. The method estimates the risk of accident associated with darkness in terms of an odds ratio, which is defined as follows: [(number of accidents in darkness in a given hour of the day)/(number of accidents in daylight in the same hour of the day)]/[(Number of accidents in a given comparison hour when the case hour is dark)/(Number of accidents in a given comparison hour when the case hour is in daylight)]. This estimate of the risk of accident associated with darkness does not require data on exposure, but relies on the count of accidents in the same pair of hours throughout the year. One of the hours is dark part of the year, but has daylight the rest of the year. The comparison hour, which has daylight the whole year, is used to control for seasonal variations. The aim of relying on the same pair of hours throughout the year is to minimise the influence of potentially confounding factors. Estimates of the risk of injury accidents associated with darkness are developed on the basis of accident data for Norway, Sweden and the Netherlands. It is found that the risk of an injury accident increases by nearly 30% in darkness in urban areas, by nearly 50% in rural areas, and by about 40% for urban and rural areas combined (adjusted estimate). [Copyright &y& Elsevier]

This paper investigates the relation between unobserved farm productivity and other production factors in a system of netput equations for specialised pig breeding farms in the Netherlands. In order to estimate the system, a Hausman-Taylor panel data estimator is developed for a system of equations with unbalanced panel data. Tests on the correlation between model variables and farm-effects are performed, yielding an insight into the sources of differences in total factor productivity and its components (e.g. managerial ability and scale economies). Results indicate that specialised pig breeding farms that are characterised by high total factor productivity have more buildings and machinery than farms with low total factor productivity. [ABSTRACT FROM AUTHOR]

An important task of auditors is to check whether recorded values are correct. From the number (or total) of the errors found in a sample, upper confidence limits for the fraction (or total) of the errors in the population are calculated by standard methods. Even auditors are human, however, and may make mistakes: errors may remain unnoticed. As administrative rules and regulations are becoming more and more complicated, this kind of auditors' mistakes tends to occur more frequently. Hence, there is an increasing need to check the auditing process itself. This can be achieved by checking a subsample of audited values a second time, now by an error-free supervisor. This paper investigates the consequences of the (possible) occurrence of errors in this subsample. A simple and analytically attractive model is presented for the number of errors found in this double inspection scheme. Maximum likelihood estimators are derived for the population fraction of errors and the probability of an error remaining unnoticed. Based on that, an exact upper confidence limit for the population fraction of errors is calculated, treating the probability of an unnoticed error as a nuisance parameter. Our method was originally developed during a recent Dutch case study: in a subsample of already audited values one additional error was found by the supervisor. It is shown that, as a consequence, the upper confidence limit is increased very sizeably. [ABSTRACT FROM AUTHOR]

The railway bridge at Dordrecht (Holland) can be raised to let big ships pass through. This takes place according to a fixed daily time schedule derived from the railway timetable. The waiting times of the ships depend on the number and the duration of these openings, the headway of the unraised bridge (changing on account of tidal effects), and the traffic supply. In this paper the dependence of the waiting times on the above-mentioned factors is quantified by means of a Monte Carlo simulation procedure. [ABSTRACT FROM AUTHOR]

This article deals with three models of complete systems of demand equations (Rotterdam model, AIDS and CBS model). After the models and the theoretical restrictions have been described the parameters are estimated subject to an increasing number of restrictions and using aggregate time series for the Netherlands on five commodity groups. As the initial results are not altogether satisfactory an attempt is made to improve the estimates by combining the time-series information with cross section data from the Dutch 1974/1975 budget survey. While the revised estimates of the income elasticities are more plausible than the initial ones, the reverse is true for the estimated price elasticities. [ABSTRACT FROM AUTHOR]

The article offers views concerning the hypothesis of Philip Hans Franses regarding the upward revisions of gross domestic product (GDP) growth rates in Netherlands. Using a Monte Carlo simulation technique, it indicates that 15% of the forecasting error of the Dutch official forecasts for GDP growth made by CPB Netherlands Bureau for Policy Analysis can be attributed to revisions of preliminary data published by Statistics Netherlands. Moreover, it relates that Franses' hypothesis is based on data collection process and the behavior of the statisticians who have to fill in the missing data.

Dependent interviewing (DI) uses respondent data from earlier waves in panel surveys to improve the data quality of change estimates. Apart from a positive effect on data quality through reducing overestimations of change, DI could also affect data quality negatively when it leads to satisficing and an overestimation of stability between waves. In this article, we experimentally test two frequently used DI designs under different levels of measurement error. Our data consist of income reports from a four-wave panel survey conducted in the Netherlands. The effects of our experiment on data quality are modeled with a quasi-simplex structure to enable the decomposition of variances into measurement errors and true change. Our main conclusion is that there is some risk of a negative effect on data quality for proactive DI but not for reactive DI. [ABSTRACT FROM AUTHOR]

ObjectiveReduction in the current high levels of meat and dairy consumption may contribute to environmental as well as human health. Since meat is a major source of Fe, effects on Fe intake need to be evaluated, especially in groups vulnerable to negative Fe status. In the present study we evaluated the effects of replacing meat and dairy foods with plant-based products on environmental sustainability (land requirement) and health (SFA and Fe intakes) in women.DesignData on land requirements were derived from existing calculation methods. Food composition data were derived from the Dutch Food Composition Table 2006. Data were linked to the food consumption of young Dutch women. Land requirements and nutrient intakes were evaluated at baseline and in two scenarios in which 30 % (Scenario_30 %) or 100 % (Scenario_100 %) of the dairy and meat consumption was randomly replaced by the same amount of plant-based dairy- and meat-replacing foods.SettingThe Netherlands.SubjectsThree hundred and ninety-eight young Dutch females.ResultsReplacement of meat and dairy by plant-based foods benefited the environment by decreasing land use. The intake of SFA decreased considerably compared with the baseline situation. On average, total Fe intake increased by 2·5 mg/d, although most of the Fe intake was from a less bioavailable source.ConclusionsReplacement of meat and dairy foods by plant-based foods reduced land use for consumption and SFA intake of young Dutch females and did not compromise total Fe intake. [ABSTRACT FROM PUBLISHER]

ABSTRACT The quality of ecotope maps of five districts of main water courses in the Netherlands was assessed on the basis of independent validation samples of field observations. The overall proportion of area correctly classified, and user's and producer's accuracy for each map unit were estimated. In four districts, the validation samples were selected purposively in the past. For the fifth district, a stratified two-stage probability sample was designed, such that the spatial pattern resembles that of the purposive samples. For the purposively sampled districts, measures of map quality were estimated following a model-based approach, using a model for the spatial variation of classification errors. For the randomly sampled district, measures of map quality were obtained following a design-based approach, using the inclusion probabilities of the sampling points. The overall proportions of area correctly classified vary from 61% to 76%. Both user's and producer's accuracies show large variation among the map units. Model-based predictions of producer's accuracies from two models differed strongly, indicating that with the model-based approach the validation results strongly depend on model assumptions. We demonstrate that stratified two-stage random sampling answers to the same practical and budgetary constraints as purposive sampling. Stratified two-stage sampling combined with a design-based estimation method results in model-free estimates of the overall proportion of area correctly classified, user's and producer's accuracies. This means that the inferential validity of the estimated overall proportion of area correctly classified and user's and producer's accuracies is rigorously established if a design-based approach is followed. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Secondary inorganic aerosol, most notably ammonium nitrate and ammonium sulphate, is an important contributor to ambient particulate mass and provides a means for long range transport of acidifying components. The modelling of the formation and fate of these components is challenging. Especially, the formation of the semi-volatile ammonium nitrate is strongly dependent on ambient conditions and the precursor concentrations. For the first time an hourly artefact free data set from the MARGA instrument is available for the period of a full year (1 August 2007 to 1 August 2008) at Cabauw, the Netherlands. This data set is used to verify the results of the LOTOS-EUROS model. The comparison showed that the model underestimates the SIA levels. Closer inspection revealed that base line values appear well estimated for ammonium and sulphate and that the underestimation predominantly takes place at the peak concentrations. For nitrate the variability towards high concentrations is much better captured, however, a systematic relative underestimation was found. The model is able to reproduce many features of the intra-day variability observed for SIA. Although the model captures the seasonal and average diurnal variation of the SIA components, the modelled variability for the nitrate precursor gas nitric acid is much too large. It was found that the thermodynamic equilibrium module produces a too stable ammonium nitrate in winter and during night time in summer, whereas during the daytime in summer it is too unstable. We recommend to improve the model by verification of the equilibrium module, inclusion of coarse mode nitrate and to address the processes concerning SIA formation combined with a detailed analysis of the data set at hand. The benefit of the hourly data with both particulate and gas phase concentrations is illustrated and a continuation of these measurements may prove to be very useful in future model evaluation and improvement studies. Based on our findings we propose to implement a monitoring strategy using three levels of detail within the Netherlands. [ABSTRACT FROM AUTHOR]

We have implemented six different inverse carbon flux estimation methods in a regional carbon dioxide (CO2) flux modeling system for the Netherlands. The system consists of the Regional Atmospheric Mesoscale Modeling System (RAMS) coupled to a simple carbon flux scheme which is run in a coupled fashion on relatively high resolution (10 km). Using an Ensemble Kalman filter approach we try to estimate spatiotemporal carbon exchange patterns from atmospheric CO2 mole fractions over the Netherlands for a two week period in spring 2008. The focus of this work is the different strategies that can be employed to turn first-guess fluxes into optimal ones, which is known as a fundamental design choice that can affect the outcome of an inversion significantly. Different state-of-the-art approaches with respect to the estimation of net ecosystem exchange (NEE) are compared quantitatively: (1) where NEE is scaled by one linear multiplication factor per land-use type, (2) where the same is done for photosynthesis (GPP) and respiration (R) separately with varying assumptions for the correlation structure, (3) where we solve for those same multiplication factors but now for each grid box, and (4) where we optimize physical parameters of the underlying biosphere model for each land-use type. The pattern to be retrieved in this pseudo-data experiment is different in nearly all aspects from the first-guess fluxes, including the structure of the underlying flux model, reflecting the difference between the modeled fluxes and the fluxes in the real world. This makes our study a stringent test of the performance of these methods, which are currently widely used in carbon cycle inverse studies. Our results show that all methods struggle to retrieve the spatiotemporal NEE distribution, and none of them succeeds in finding accurate domain averaged NEE with correct spatial and temporal behavior. The main cause is the difference between the structures of the first-guess and true CO2 flux models used. Most methods display overconfidence in their estimate as a result. A commonly used daytime-only sampling scheme in the transport model leads to compensating biases in separate GPP and R scaling factors that are readily visible in the nighttime mixing ratio predictions of these systems. Overall, we recommend that the estimate of NEE scaling factors should not be used in this regional setup, while estimating bias factors for GPP and R for every grid box works relatively well. The biosphere parameter inversion performs good compared to the other inversions at simultaneously producing space and time patterns of fluxes and CO2 mixing ratios, but non-linearity may significantly reduce the information content in the inversion if true parameter values are far from the prior estimate. Our results suggest that a carefully designed biosphere model parameter inversion or a pixel inversion of the respiration and GPP multiplication factors are from the tested inversions the most promising tools to optimize spatiotemporal patterns of NEE. [ABSTRACT FROM AUTHOR]

In-situ, quasi-continuous measurements of at- mospheric hydrogen (H2) have been performed since October 2007 at the Cabauw tall tower station in the Netherlands. Mole fractions of H2, CO and several greenhouse gases are determined simultaneously in air sampled successively at four heights, between 20 and 200m above ground level. 222Rn measurements are performed in air sampled at 20 and 200m. This H2dataset represents the first in-situ, quasi-continuous long-term measurement series of vertical profiles of H2in the lower continental boundary layer. Seasonal cycles are present at all heights in both H2 and CO, and their amplitude varies with the sampling height. The seasonality is evident in both the "baseline" values and in the short term (diurnal to synoptic time scales) variability, the latter being significantly larger during winter. The observed H2 short term signals and vertical gradients are in many cases well correlated to other species, especially to CO. On the other hand, H2 has at times a unique behaviour, due to its particular distribution of sources and sinks. Our estimation for the regional H2 soil uptake flux, using the radon tracer method, is (-1.89±0.26) x 10-5 g/(m² h), significantly smaller than other recent results from Europe. H2/CO ratios of the traffic emissions computed from our data, with an average of 0.54±0.07mol:mol, are larger and more variable than estimated in some of the previous studies in Europe. This difference can be explained by a different driving regime, due to the frequent traffic jams in the influence area of Cabauw. The H2/CO ratios of the large scale pollution events have an average of 0.36±0.05mol:mol; these ratios were observed to slightly increase with sampling height, possibly due to a stronger influence of soil uptake at the lower sampling heights. [ABSTRACT FROM AUTHOR]

Copyright of Geographical Analysis is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Raised bog peat deposits form important archives for reconstructing past changes in climate. Precise and reliable age models are of vital importance for interpreting such archives. We propose enhanced, Markov chain Monte Carlo based methods for obtaining age models from radiocarbon-dated peat cores, based on the assumption of piecewise linear accumulation. Included are automatic choice of sections, a measure of the goodness of fit and outlier downweighting. The approach is illustrated by using a peat core from the Netherlands. [ABSTRACT FROM AUTHOR]

Abstract--Sickness absenteeism figures show a relatively large amount of variation across firms and organizations, indicating substantial within-firm correlations between absenteeism records of individual workers. To study the role of firm-specific circumstances and workforce composition, we specify three-state, multicycle duration models of work, sickness, and job separation, with workplace-specific fixed effects to account for unobserved differences between firms. In the most flexible specification, these fixed effects are separate, nonparametric, baseline hazards for each firm and each type of transition. Alternative estimation methods are discussed and applied to individual absenteeism histories of primary-school teachers. [ABSTRACT FROM AUTHOR]

The Barro (1979) theory of public debt creation forms a starting-point for an analysis of postwar debt creation in the Netherlands. Empirically, the model appears not to apply to the entire 1953-80 estimation period. In the early 1970's a break in the Dutch public debt creation mechanism can be observed. This is consistent with events which actually started to occur at the beginning of this decade. Attention is paid to the interpretation of the theory in view of the empirical results, and their implications for Dutch public financing policy. [ABSTRACT FROM AUTHOR]