Wiegand, Gordon
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Imputation of Housing Rents for Owners Using Models With Heckman Correction
The direct income of owners and tenants of dwellings is not comparable since the owners have a hidden income from the investment in their dwelling. This hidden income is considered a part of the disposable income of owners. It may be predicted with the help of a linear model of the rent. Since such a model must be developed and estimated for tenants with observed market rents a selection bias may occur. The selection bias can be minimised through a Heckman correction. The paper applies the Heckman correction to data from the Swiss Statistics on Income and Living Conditions. The Heckman method is adapted to the survey context, the modeling process including the choice of covariates is explained and the effect of the prediction using the model is discussed.
e-Infrastructure adoption in the social sciences and humanities: cross-national evidence
This paper is a first attempt to describe and compare the adoption of e-Infrastructure across the UK, continental Europe, and the USA in the social sciences and humanities. A survey of early adopters identified three differences across these countries, each potentially affecting adoption: funding approaches, the technical configuration of projects, and research support. Our findings also suggest that the sustainable adoption of e-Infrastructure co-varies with the role of intrinsic and extrinsic motivations and the involvement of other people in the adoption decision.