Modelling the time on unemployment insurance benefits

A duration model based on the time on Unemployment Insurance (UI) benefits instead of a model based on the time till re-employment is more relevant from a cost-benefit perspective. The contribution of this paper is to extend the standard (mixed) Proportional Hazard model to account for an upper bound on the duration. We use a modified mover-stayer model to this end and discuss the interpretation of the parameters. In an empirical application we compare the method with the standard analysis of unemployment duration. We also derive the expected UI-benefit costs implied by the model for some typical unemployed individuals.mover-stayer model;UI-benefits;maximum duration;mixed proportional hazard

Migration dynamics of immigrants: who leaves, who returns and how quick?

In this paper we analyze the demographic factors that influence the return and repeated migration of immigrants. Using longitudinal data from Statistics Netherlands we track migration histories of recent immigrants to The Netherlands and analyze which migrants will stay in the country, which migrants are more prone to leave and how quick they leave. In order to identify these migrants we apply a mover-stayer duration model on the time spent in the country. We also analyze the return from abroad to The Netherlands of these migrants. Results disclose differences among migrants by migration motive and by country of origin and lend support to our analytical framework. Combining the model for departure from the country and the model for returning to the country provides the long-run stay probability of a specific migrant. It also yields a framework for simulating the life-cycle migration dynamics. The major findings are: (1) labor migrants and students are more prone to leave and migrants who come for family reasons remain in the country more often, (2) migrants from the `guestworker' countries, Turkey and Morocco, will stay in the country more often thanmigrants from Western countries.migration dynamics;mover-stayer model;return migration

Modeling migration dynamics of immigrants: the case of the Netherlands

In this paper we analyze the demographic factors that influence the migration dynamics of recent immigrants to The Netherlands. We show how we can allow for both permanent and temporary migrants. Based on data from Statistics Netherlands we analyze both the departure and the return from abroad for recent non-Dutch immigrants to The Netherlands. Results disclose differences among migrants by migration motive and by country of origin and lend support to our analytical framework. Combining both models, for departure and returning, provides the probability that a specific migrant ends-up in The Netherlands. It also yields a framework for predicting the migration dynamics over the life-cycle. We can conclude that for a complete view of the migration dynamics it is important to allow for both permanent (stayers) migrants and temporary (movers) migrants and that return from abroad should not be neglected.migration dynamics;mover-stayer model;return migration

Unobserved Heterogeneity in Multiple-Spell Multiple-States Duration Models

In survival analysis a large literature using frailty models, or models with unobserved heterogeneity, exist. In the growing literate on multiple spell multiple states duration models, or multistate models, modeling this issue is only at its infant phase. Ignoring unobserved heteogeneity can, however, produce incorrect results. This paper presents how unobserved heterogeneity can be incorporated into multistate models, with an emphasis on semi-Markov multistate models with a mixed proportional hazard structure. First, the aspects of frailty modeling in univariate (proportional hazard, Cox) duration models are addressed and some important models with unobserved heterogeneity are discussed. Second, the domain is extended to modeling of parallel/clustered multivariate duration data with unobserved heterogeneity. The implications of choosing shared or correlated unobserved heterogeneity is highlighted. The relevant differences with recurrent events data is covered next. They include the choice of the time scale and risk set which both have important implications for the way unobserved heterogeneity influence the model. Multistate duration models can have both parallel and recurrent events. Incorporating unobserved heterogeneity in multistate models, therefore, brings all the previously addressed issues together. Although some estimation procedures are covered the emphasis is on conceptual issues. The importance of including unobserved heterogeneity in multistate duration models is illustrated with data on labour market and migration dynamics of recent immigrants to The Netherlands.multiple spell multiple state duration, mixed proportional hazard, multistate model, unobserved heterogeneity, frailty

A Simple GMM Estimator for the Semi-Parametric Mixed Proportional Hazard Model

Ridder and Woutersen (2003) have shown that under a weak condition on the baseline hazard there exist root-N consistent estimators of the parameters in a semiparametric Mixed Proportional Hazard model with a parametric baseline hazard and unspecified distribution of the unobserved heterogeneity. We extend the Linear Rank Estimator (LRE) of Tsiatis (1990) and Robins and Tsiatis (1991) to this class of models. The optimal LRE is a two-step estimator. We propose a simple first-step estimator that is close to optimal if there is no unobserved heterogeneity. The efficiency gain associated with the optimal LRE increases with the degree of unobserved heterogeneity.mixed proportional hazard, linear rank estimation, counting process

Econometric analysis of ship life cycles - are safety inspections effective?

Due to the shipping industry’s international legal framework and the existence of loopholes in the system, an estimated 5-10 percent of substandard ships exist which are more likely to have incidents with high economic cost. This article uses ship life cycles to provide insight into the effectiveness of inspections on prolonging ship lives. We account for fluctuations in the relevant economic environment and the (possible time-varying) ship particulars. We use a unique dataset containing information on the timing of accidents, inspections, ship particular changes of more than fifty thousand ships over a 29 year time period (1978-2007). The results of our duration analysis reveal that the shipping industry is a relative safe industry but there is a possible over-inspection of vessels. It also reveals the need to improve transparency related to class withdrawals and changes of classification of the vessel. Another interesting finding is that for the majority of ship types an increase in earnings decreases the incident rate. This is in contrast to the industry perception of the impact of earnings. The effect of inspections vary across ship types and the prevention of incidents with high economic costs can be improved by better coordination of inspections, data sharing and a decrease in the number of inspections . Further, more emphasis should be placed on the rectification and follow up of deficiencies.

Does rounding matter for payment efficiency?

Theory predicts that dismissing the 1 and 2 euro cent coins fromthe denominational range of the euro leads to more paymentefficiency. To examine whether this theory holds true in practice,we collected data for the Netherlands before and after September 12004, which marks the day that retail stores were allowed to roundall amounts at 5 euro cents. The data consist of wallet contentsfor three cross sections of individuals. We propose a multivariatePoisson- log Normal model to analyze these data. We find thatrounding leads to less 1 and 2 cent coins in wallets, but thatstill other coins are over or underrepresented, thereby suggestingthat the euro range does not yet lead to fully efficient paymentbehavior.cash payment;euro denomination;maximum simulated likelihood;multivariate poisson-log normal

Collaborative Engineering Environments. Two Examples of Process Improvement

Companies are recognising that innovative processes are determining factors in competitiveness. Two examples from projects in aircraft development describe the introduction of collaborative engineering environments as a way to improve engineering processes. A multi-disciplinary simulation environment integrates models from all disciplines involved in a common functional structure. Quick configuration for specific design problems and powerful feedback / visualisation capabilities enable engineering teams to concentrate on the integrated behaviour of the design. An engineering process management system allows engineering teams to work concurrently in tasks, following a defined flow of activities, applying tools on a shared database. Automated management of workspaces including data consistency enables engineering teams to concentrate on the design activities. The huge amount of experience in companies must be transformed for effective application in engineering processes. Compatible concepts, notations and implementation platforms make tangible knowledge like models and algorithms accessible. Computer-based design management makes knowledge on engineering processes and methods explicit