Understanding the trade-offs in improving the precision of agricultural measures through survey design is crucial. Yet, standard indicators used to determine program effectiveness may be flawed and at a differential rate for men and women. The authors use a household survey from Mozambique to...

This paper firstly aims to evaluate the incidence of measurement error affecting the main variables collected in surveys on consumption. The assessment is carried out on two Tanzania surveys which provide both diary and panel data. Diary data can be employed to obtain reliability coefficients...

Improving women's agency, namely their ability to define goals and act on them, is crucial for advancing gender equality and the empowerment of women. Yet, existing frameworks for women's agency measurement -- both disorganized and partial -- provide a fragmented understanding of the constraints...

This paper discusses the challenges associated with collecting time-use data in developing countries. The paper suggests potential solutions, concentrating on the two most common time-use methods used in development settings: stylized questions and time diaries. The paper identifies a...

We examine inferences about old age mortality that arise when researchers use survey data matched to death records. We show that even small rates of failure to match respondents can lead to substantial bias in the measurement of mortality rates at older ages. This type of measurement error is...

Social scientists have observed that socially desirable responding (SDR) often biases unincentivized surveys. During the 2016 presidential campaign, we conducted three list experiments to test the effect SDR has on polls of agreement with presidential candidates. We elicit a subject's agreement...

Since the late 90s, Regression Discontinuity (RD) designs have been widely used to estimate Local Average Treatment Effects (LATE). When the running variable is observed with continuous measurement error, identification fails. Assuming non-differential measurement error, we propose a consistent...

This paper proposes a simple maximum likelihood regression estimator that outperforms Least Squares in terms of efficiency and mean square error for a large number of skewed and/or heavy tailed error distributions

We introduce a novel framework to predict the relative accuracy of sell-side analysts' annual earnings forecasts out-of-sample. Prior studies only evaluate forecasts shortly before the corresponding earnings release. In contrast, our study is the first to provide long-term predictions which are...