In this paper we describe an alternative iterative approach for the estimation of linear regression models with high-dimensional fixed-effects such as large employer-employee data sets. This approach is computationally intensive but imposes minimum memory requirements. We also show that the...

Questions about monetary variables (such as income, wealth or savings) are key components of questionnaires on household finances. However, missing information on such sensitive topics is a well-known phenomenon which can seriously bias any inference based only on complete cases analysis. Many...

We describe identification assumptions underlying synthetic control studies and offer recommendations for key — and normally ad hoc — implementation decisions, focusing on model selection; model fit; cross-validation; and decision rules for inference. We outline how to implement a Synthetic...

To their credit, empirical legal scholars try to live up to the highest methodological standards from the social sciences. But these standards do not always match the legal research question. This paper focuses on normative legal argument based on empirical evidence. Whether there is a normative...

In this paper we describe an alternative iterative approach for the estimation of linear regression models with high-dimensional fixed-effects such as large employer-employee data sets. This approach is computationally intensive but imposes minimum memory requirements. We also show that the...

Abstract Staffing decisions typically account for a large portion of a retailer's operational costs. The effectiveness of these decisions has often been analyzed by relating staffing levels to revenues. However, such approach does not explicitly consider the mechanisms by which the staff can...

We evaluate how nonresponse affects conclusions drawn from survey data and consider how researchers can reliably test and correct for nonresponse bias. To do so, we examine a survey on labor market conditions during the COVID-19 pandemic that used randomly assigned financial incentives to...

This paper presents a regression procedure for inhomogeneous data characterized by varying variance, skewness and kurtosis or by an unequal amount of data over the estimation domain. The concept is based first on the estimation of the densities of an observed variable for given values of...