We argue that measurement error in historical price data has led researchers to erroneously believe that there was little persistence of inflation during the 19th century. Using a statistical technique that accounts for these errors, we estimate the persistence of (a) US inflation and (b)...

Using longitudinal, nationally representative data from Australia, this study uncovers a previously undocumented pattern: in over half of cases where one household member reports weather-related home damage, their co-resident does not. This high rate of intra-household inconsistency is striking,...

This study introduces Members of the European Parliament to the different estimates of the level of error affecting EU expenditure in cohesion policy. It explains how the European Commission calculates the estimated 'risk at payment' and 'risk at closure', how the European Court of Auditors...

This study introduces Members of the European Parliament to the different estimates of the level of error affecting EU expenditure in cohesion policy. It explains how the European Commission calculates the estimated 'risk at payment' and 'risk at closure', how the European Court of Auditors...

We propose a methodology to construct tests for the null hypothesis that the pricing errors of a panel of asset returns are jointly equal to zero in a linear factor asset pric- ing model - that is, the null of "zero alpha". We consider, as a leading example, a model with observable, tradable...

Measurement errors in macroeconomic aggregates such as GDP have been widely lamented, particularly in low-income contexts. This study investigates the reliability of one component of national accounts, agricultural sector output. Focusing first on the case of Mozambique, we use a series of 12...

In this article, new ratio regression type estimators with imputation have been proposed as means to overcome the problem of missing data relating to a studied variable in a sample survey. It has been shown that the suggested estimators are more efficient than the mean method of imputation, the...

Given several studies (inputs) of some phenomenon of interest, each input presents an estimate of a key parameter with an associated estimated precision. The random-effects model used in meta-analysis estimates this parameter based on a decomposition of the error term into within-input noise and...

We assess the reliability of measured farm sizes (ownership holdings) in the Living Standard Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) in Ethiopia and Malawi based on three survey rounds (2012, 2014, 2016) in Ethiopia and four rounds (2010, 2013, 2016, 2019) in Malawi....

Accurate macroeconomic forecasts are essential for effective policy decisions, yet their precision depends on the accuracy of the underlying assumptions. This paper examines the extent to which assumption errors affect forecast accuracy, introducing the average squared assumption error (ASAE) as...

A propensity to guess randomly rather than to admit ignorance answering “Don’t know” is a plausible reason why frequent wrong answers are given to survey questions that aim to assess competence. We model this source of measurement error and assess its empirical relevance in two consecutive...

We develop a practical way of addressing the Errors-In-Variables (EIV) problem in the Generalized Method of Moments (GMM) framework. We focus on the settings in which the variability of the EIV is a fraction of that of the mismeasured variables, which is typical for empirical applications. For...

Probabilistic editing has been introduced to enable valid inference using established survey sampling theory in situations when some of the collected data points may have measurement errors and are therefore submitted to an editing process. To reduce the editing effort and avoid over-editing, in...

The availability of weather data from remotely sensed Earth observation data has reduced the cost of including weather variables in econometric models. Weather variables are common instrumental variables used to predict economic outcomes and serve as an input in modeling crop yields for rainfed...

We contribute new cross-national evidence about the nature of measurement errors in employment earnings, fitting the same error components model to harmonised earnings data for Austria and the UK. The model allows for measurement error in the administrative data and linkage error as well as...

This paper considers nonparametric identification and estimation of the regression function when a covariate is mismeasured. The measurement error need not be classical. Employing the small measurement error approximation, we establish nonparametric identification under weak and...

Women are less likely to correctly answer the “Big-3” financial literacy questions, and a substantial share of the gap reflects women’s lower confidence. In our experiment, women are more likely to choose “do not know” or refuse to answer financial literacy questions. If these options...

Process outputs of many production processes like chemical, food processing and pharmaceutical industry follow a stationary Gaussian process. Some amount of measurement error always present in the measured data due to inaccurate measuring processes. Throughout this paper, we discuss some...

Economic data are often contaminated by measurement errors and truncated by ranking. This paper shows that the classical measurement error model with independent and additive measurement errors is identified nonparametrically using only two order statistics of repeated measurements. The...

We present evidence on the extent of measurement error in German longitudinal earnings data. Qualitatively, we confirm the main result of the international literature: longitudinal earnings data are relatively reliable in a cross section but much less so in first differences. Quantitatively, in...

The most common sampling approach for cross-sectional household surveys in the developing world is a stratified two-stage design, where the first stage is usually a sample from a census-based area frame, and the second stage is a random sample of households from each of the areas selected in the...

This paper considers nonparametric identification and estimation of the regression function when a covariate is mismeasured. The measurement error need not be classical. Employing the small measurement error approximation, we establish nonparametric identification under weak and...

We develop a practical way of addressing the Errors-In-Variables (EIV) problem in the Generalized Method of Moments (GMM) framework. We focus on the settings in which the variability of the EIV is a fraction of that of the mismeasured variables, which is typical for empirical applications. For...

Time-use statistics are sensitive to measurement error, especially errors that might be introduced based on whether the informant is reporting on herself or reporting on others in the household. In this paper, we use the nationally representative time-use survey in India and propensity score...

Many studies of historical persistence find that modern outcomes strongly reflect characteristics of the same places in the distant past. However they rely on data that often exhibit extreme spatial trends and autocorrelation, suggesting that their unusually large t-statistics may be due to...