A covariate adjustment for zero-truncated approaches to estimating the size of hidden and elusive populations

In this paper we consider the estimation of population size from onesource capture–recapture data, that is, a list in which individuals can potentially be found repeatedly and where the question is how many individuals are missed by the list. As a typical example, we provide data from a drug user study in Bangkok from 2001 where the list consists of drug users who repeatedly contact treatment institutions. Drug users with 1, 2, 3, . . . contacts occur, but drug users with zero contacts are not present, requiring the size of this group to be estimated. Statistically, these data can be considered as stemming from a zero-truncated count distribution.We revisit an estimator for the population size suggested by Zelterman that is known to be robust under potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a locally truncated Poisson likelihood which is equivalent to a binomial likelihood. This result allows the extension of the Zelterman estimator by means of logistic regression to include observed heterogeneity in the form of covariates. We also review an estimator proposed by Chao and explain why we are not able to obtain similar results for this estimator. The Zelterman estimator is applied in two case studies, the first a drug user study from Bangkok, the second an illegal immigrant study in the Netherlands. Our results suggest the new estimator should be used, in particular, if substantial unobserved heterogeneity is present.

Mixture models for capture-recapture count data

The contribution investigates the problem of estimating the size of a population, also known as the missing cases problem. Suppose a registration system is targeting to identify all cases having a certain characteristic such as a specific disease (cancer, heart disease, ...), disease related condition (HIV, heroin use, ...) or a specific behavior (driving a car without license). Every case in such a registration system has a certain notification history in that it might have been identified several times (at least once) which can be understood as a particular capture-recapture situation. Typically, cases are left out which have never been listed at any occasion, and it is this frequency one wants to estimate. In this paper modelling is concentrating on the counting distribution, e.g. the distribution of the variable that counts how often a given case has been identified by the registration system. Besides very simple models like the binomial or Poisson distribution, finite (nonparametric) mixtures of these are considered providing rather flexible modelling tools. Estimation is done using maximum likelihood by means of the EM algorithm. A case study on heroin users in Bangkok in the year 2001 is completing the contribution.

Dynamic analysis of house price diffusion across Asian financial centres

The aim of this paper is to explore effects of macroeconomic variables on house prices and also, the lead-lag relationships of real estate markets to examine house price diffusion across Asian financial centres. The analysis is based on the Global Vector Auto-Regression (GVAR) model estimated using quarterly data for six Asian financial centres (Hong Kong, Tokyo, Seoul, Singapore, Taipei and Bangkok) from 1991Q1 to 2011Q2. The empirical results indicate that the global economic conditions play significant roles in shaping house price movements across Asian financial centres. In particular, a small open economy that heavily relies on international trade such as – Singapore and Tokyo - shows positive correlations between economy’s openness and house prices, consistent with the Balassa-Samuelson hypothesis in international trade. However, region-specific conditions do play important roles as determinants of house prices, partly due to restrictive housing policies and demand-supply imbalances, as found in Singapore and Bangkok.

Evaluating the interdependencies between managing business change, IT sourcing and IT governance

Organisations need the right business and IT capabilities in order to achieve future business success. It follows that the sourcing of these capabilities is an important decision. Yet, there is a lack of consensus on the approach to decid-ing where and how to source the core operational capabilities. Furthermore, de-veloping its dynamic capability enables an organisation to effectively manage change its operational capabilities. Recent research has proposed that analysing business capabilities is a key pre-requisite to defining its Information Technology (IT) solutions. This research builds on these findings by considering the interde-pendencies between the dynamic business change capability and the sourcing of IT capabilities. Further it examines the decision-making oversight of these areas as implemented through IT governance. There is a good understanding of the direct impact of IT sourcing decision on operational capabilities However, there is a lack of research on the indirect impact to the capability of managing business change. Through a review of prior research and initial pilot field research, a capability framework and three main propositions are proposed, each examining a two-way interdependency. This paper describes the development of the integrated capa-bility framework and the rationale for the propositions. These respectively cover managing business change, IT sourcing and IT governance. Firstly, the sourcing of IT affects both the operational capabilities and the capability to manage business change. Similarly a business change may result in new or revised operational ca-pabilities, which can influence the IT sourcing decision resulting in a two-way rela-tionship. Secondly, this IT sourcing is directed under IT governance, which pro-vides a decision-making framework for the organisation. At the same time, the IT sourcing can have an impact on the IT governance capability, for example by out-sourcing key capabilities; hence this is potentially again a two-way relationship. Finally, there is a postulated two-way relationship between IT governance and managing business change in that IT governance provides an oversight of manag-ing business change through portfolio management while IT governance is a key element of the business change capability. Given the nature and novelty of this framework, a philosophical paradigm of constructivism is preferred. To illustrate and explore the theoretical perspectives provided, this paper reports on the find-ings of a case study incorporating eight high-level interviews with senior execu-tives in a German bank with 2300 employees. The collected data also include or-ganisational charts, annual reports, project and activity portfolio and benchmark reports for the IT budget. Recommendations are made for practitioners. An understanding of the interdependencies can support professionals in improving business success through effectively managing business change. Additionally, they can be assisted to evaluate the impact of IT sourcing decisions on the organisa-tion’s operational and dynamic capabilities, using an appropriate IT governance framework.

International transmission mechanisms and contagion in housing markets

This paper explores international transmission mechanism and its role in contagion effect in the housing markets across six major Asian cities. The analysis is based on the identification of house price diffusion effects through a global vector autoregressive (GVAR) model estimated using quarterly data for six major Asian cities (Hong Kong, Tokyo, Seoul, Singapore, Taipei and Bangkok) from 1991Q1 to 2011Q2. The empirical results indicate that the open economies heavily relying on international trade such as Singapore, Japan (Tokyo), Taiwan (Taipei) and Thailand (Bangkok) show positive correlations between the economy's openness and house prices, which is consistent with the Balassa–Samuelson hypothesis. Interestingly, some region-specific conditions also appear to play important roles as determinants of house price movements, which may be driven by restrictive housing policies and demand–supply imbalances such as Singapore and Bangkok. These results are reasonably robust across several model specifications. The findings bear significant implications for formulation of investment strategy and public policies.