Incentives (Version 2.0)

Incentives are all forms of monetary or non-monetary encouragement given to potential respondents (Singer, 2002; Singer & Ye, 2013). Non-monetary incentives include vouchers, lottery tickets, vouchers for contributions to charity, stamps, and objects. The monetary value of the incentives used in studies ranges from tiny amounts to several hundred euros in the case of medical studies. Moreover, incentives differ in terms of the way in which they are awarded: Pre-paid incentives are provided in advance, irrespective of whether the recipient participates in the overall gross sample. Conditional incentives are given to respondents after they have participated in the survey. This contribution provides an overview of the current state of theories and empirical findings on the impact on response rates, retention rates and sample quality of giving incentives to respondents

Detailed description of the implementation the multinomial logit model with fixed effects (femlogit)

Fixed effect models have become increasingly popular in the field of sociology. The possibility to control for unobserved heterogeneity makes these models a prime tool for causal analysis. As of today, fixed effects models have been derived and implemented for many statistical software packages for continuous, dichotomous and count-data dependent variables. Chamberlain (1980) derived the multinomial logistic regression with fixed effects. However, this model has not been implemented in any statistical software package, yet. Possible applications would be analyses of effects on employment status with special consideration of part-time or irregular employment, and analyses of the effects on voting behavior, that implicitly control for long-time party identification rather than having to measure it directly. This paper introduces an implementation of this model with the new command femlogit. I show its application with British election panel data and multi-level data about the effect of smoking on pre-term, full term, and post-term birth

Implementation of a multinomial logit model with fixed effects

Fixed-effect models have become increasingly popular in the field of sociology. The possibility of controlling for unobserved heterogeneity makes these models a prime tool for causal analysis. As of today, fixed-effects models have been derived and implemented for many statistical software packages for continuous, dichotomous, and count-data dependent variables, but there are still many important and popular statistical models, for which only population-average estimators are available, such as models for multinomial categorical dependent variables. In a seminal paper by Chamberlain (1980) such a model was derived. Possible applications would be analyses of effects on employment status with special consideration of part-time or irregular employment and analyses of the effects on voting behavior that impicitly control for longtime party identification rather than having to measure it directly. This model has not yet been implemented in any statistical software package. In this presentation, I show a first version of an ado-file, that closes this gap. The implementation draws on the native Stata multinomial logit and conditional logit model implementations. The actual ml evaluator utilizes Mata functions to implement the conditional likelihood function. To show the numerical stability and computational speed of the implementation, comparison results with the built-in clogit are shown, as well as some basic results with simulated data.

Operationalization of Employment Protection Legislation and Implications for Substantive Results: Example of Perceived Job Insecurity and Temporary Employment Risk

Almost all comparative research on the effects of employment protection legislation of regular employees (EPLR) is based on the index of the OECD. This study argues that this index is methodologically flawed and proposes a new EPLR index, following a theory-driven formative index construction approach. To demonstrate the implications using the OECD EPLR index versus the new index, we use two empirical applications: First, the effects of EPLR on perceived job insecurity, using multi-level models with data from the European Social Survey, the European Working Condition Survey, and the European Quality of Life Survey. Secondly the temporary employment risk for new hires, using multi-level models with data from the European Labour Force Survey. Whereas the results based on the OECD EPLR index significantly deviate from the hypotheses in the literature, the results using the new EPLR index is compliant with the hypotheses in the literature. This demonstrates higher criterion validity of the theory-driven new EPLR index and also calls for replications of previous research that is based on the index of the OECD

The European Union Statistics on Income and Living Conditions after 15 Years

This data brief describes the European Union Statistics on Income and Living Conditions (EU-SILC). Detailed data on income and taxes are collected, as well as information on material deprivation, labour, housing, childcare, health, access to and use of services, and education. Although primarily a social policy instrument that addresses the information needs of policymakers and is used for social monitoring at the European level, EU-SILC is also closely geared to the needs of researchers and provides an excellent database for evidence-based research on a wide variety of aspects of income, income poverty, material poverty, health, and well-being in Europe. EU-SILC is composed of national probability sample surveys and is conducted annually. The target population comprises private households. Observation units are households and all current household members. EU-SILC provides cross-sectional and longitudinal data. The data are composed of a fixed core module, and annually changing ad-hoc modules. Launched in 2003 and revised with effect from 2021, EU-SILC is currently implemented in all EU Member States and in 11 non-EU countries. During the revision process, many suggestions from the research community were incorporated

Why Panel Surveys (Version 2.0)

This contribution provides an overview of the advantages and disadvantages of panel surveys and of fundamental considerations when deciding for or against a panel design

Panel Conditioning: Michael Bergmann über Wirkungsmechanismen und Konsequenzen wiederholter Befragungen

Michael Bergmann: Panel Conditioning: Wirkungsmechanismen und Konsequenzen wiederholter Befragungen. Baden-Baden: Nomos 2015. 978384872016

Anwendung des genetischen Algorithmus zur Lösung des iterierten Freiwilligendilemmas

Anwendung des genetischen Algorithmus nach Robert Axelrod (1987) auf das iterierte Freiwilligendilemma nach Andreas Diekmann (1985

Incentives (Version 1.1)

Incentives bezeichnen alle Formen der monetären oder nichtmonetären Anreizgabe an potentielle Befragte (Singer, 2002; Singer & Ye, 2013). Als nichtmonetäre Incentives werden Gutscheine, Lose, Spendengutscheine, Briefmarken und Sachgegenstände verwendet. Der Geldwert der Incentives, die in Studien verwendet werden, reicht von Kleinstbeträgen bis zu mehreren 100€ bei medizinischen Studien. Incentives unterscheiden sich darüber hinaus in der Art der Vergabe: Pre-paid incentives werden vorab unabhängig von der Teilnahme an das gesamte Stichprobenbrutto gegeben. Conditional incentives werden nach der Teilnahme an die Befragten gegeben, die am Interview teilgenommen haben. Das Papier gibt einen Überblick über den aktuellen Stand der Theorien und empirischen Befunde zur Wirkung von der Vergabe von Anreizen (Incentives) an Befragte auf Response-Raten, Retention-Raten und die Stichprobenqualität