In research on sensitive questions in surveys, the item count technique (ICT) has gained increased attention in recent years as a means of counteracting the problem of misreporting, that is, the under- and over-reporting of socially undesirable and socially desirable behaviors or attitudes. The performance of ICT compared with conventional direct questioning (DQ) has been investigated in numerous experimental studies, yielding mixed evidence. This calls for a systematic review. For this purpose, the present article reports results from a comprehensive meta-analysis of experimental studies comparing ICT estimates of sensitive items to those obtained via DQ. In total, 89 research articles with 124 distinct samples and 303 effect estimates are analyzed. All studies rely on the “more (less) is better” assumption, meaning that higher (lower) estimates of negatively (positively) connoted traits or behaviors are considered more valid. The results show (1) a significantly positive pooled effect of ICT on the validity of survey responses compared with DQ; (2) a pronounced heterogeneity in study results, indicating uncertainty that ICT would work as intended in future studies; and (3) as meta-regression models indicate, the design and characteristics of studies, items, and ICT procedures affect the success of ICT. There is no evidence for an overestimation of the effect due to publication bias. Our conclusions are that ICT is generally a viable method for measuring sensitive topics in survey studies, but its reliability has to be improved to ensure a more stable performance.

Despite decades of debate on environmental justice, analyses of the causal mechanisms have often been restricted to spatially aggregate data and a single context. We thus still lack a detailed understanding of how and to what extent selective residential migration contributes to environmental inequality. We link geo-referenced longitudinal household-level data from the German Socio-Economic Panel (GSOEP) and the UK Household Longitudinal Study (UKHLS) to air pollution estimates, including nitrogen dioxide (NO2), particulate matter (PM2.5), and sulphur dioxide (SO2). In both countries, immigrant minorities are exposed to higher levels of air pollution around their place of residence. Given the initial disadvantage of immigrant minorities, we would expect them to experience larger improvements from relocations over time. However, we show that this is not the case using household fixed effects models conditioning on the initial pollution level. If a native household started in a similar situation as immigrants do, they would experience much higher relocation gains. This process is similar in Germany and England, but the general disadvantage as well as the differences in returns or residential mobility are stronger in England. We also show that immigrants’ lower average income is not the driving force behind their environmental disadvantage.

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