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 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)...

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...

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...

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...

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 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....

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,...

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...

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...

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 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...

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 novel methodology to quantify forecasts based on qualitative survey data. The methodology is generally applicable when quantitative information is available on the realization of the forecasted variable, for example from firm balance sheets. The method can be applied to a wide range...

The examination of the causal impact of health insurance coverage on healthcare utilisation is a critical endeavour in both academic research and policy formulation. However, this endeavour faces challenges, notably the endogenous selection into coverage and prevalent misreporting of coverage...

This paper demonstrates how the estimation of economic activities and inequality for the Indian economy based on nighttime lights data from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite outperforms those obtained using traditional Defense Meteorological Satellite Program...

The article presents a method for balancing Gross Domestic Product (GDP) when the measurements of its components are distorted by the existence of the shadow economy. Our proposal to measure GDP is based on a multiple ultrastructural model (MUM), where the explanatory variables are subject to...

Regularized regression methods have attracted much attention in the literature, mainly due to its application in high-dimensional variable selection problems. Most existing regularization methods assume that the predictors are directly observed and precisely measured. It is well known that in a...

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...

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...

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...

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...

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...