Using a large data set that links individual Current Population Survey (CPS) records to employer-reported administrative data, we document substantial discrepancies in basic measures of employment status that persist even after controlling for known definitional differences between the two data...

Globalisation presents significant statistical challenges, particularly for small and open economies in terms of measuring macroeconomic level and growth indicators and communicating the results in a meaningful way. In the aftermath of the so-called “Irish case”, Eurostat with its partners...

In the modern era everyone using web for analysis and analytics of large amount of data. In addition, most of the web pages did not contain semantic information until recently, raising difficulties for mechanical research. As a way to remedy these poor online characteristics, the Semantic Web...

Empirical researchers routinely encounter sample selection bias whereby 1) the regressor of interest is assumed to be exogenous, 2) the dependent variable is missing in a potentially non-random manner, 3) the dependent variable is characterized by an unbounded (or very large) support, and 4) it...

Despite established recommended standard definitions, measures, and methods by the UN Washington Group on Disability Statistics and the International Classification of Functioning, Disability and Health (ICF) to assess dimensions of disability, national censuses vary widely in the questions used...

Tracking human activity in real time and at fine spatial scale is particularly valuable during episodes such as the COVID-19 pandemic. In this paper, we discuss the suitability of smartphone data for quantifying movement and social contact. These data cover broad sections of the US population...

In this paper, we propose an approach for evaluating the trade-offs inherent in different approaches used to match Current Population Survey (CPS) respondents across various CPS surveys. Because there is some measurement error in both the variables used to identify individuals over time and in...

This article analyses the crucial role of user data for digital markets contestability and presents policy proposals devised to address growing concerns about the dominance of data-rich incumbents in digital markets. To this end, we discuss a data-driven theory of harm that would warrant ex-ante...

A central problem in applied empirical work is to separate out the patterns in the data that are due to poor production of the data, such as e.g. non-response and measurement errors, from the patterns attributable to the economic phenomena studied. This paper interprets this inference problem as...