Using commuting data for Brisbane, Australia, we find that accounting for measurement error in travel times causes the magnitude of parameters in mode and location choice models to increase approximately three-fold and 30-40%, respectively. Errors appear to be somewhat systematic, with travel...

Measures based on self-assessments, which are increasingly important in empirical economic research, are plagued by measurement error. This paper presents the first attempt at measuring both revealed and self-reported reliability of individuals' answers on self-reports of latent characteristics....

We examine economic mobility in India while accounting for misclassification to better understand the welfare e§ects of the rise in inequality. To proceed, we extend recently developed methods on the partial identification of transition matrices. Allowing for modest misclassification, we find...

In this paper we systematically evaluate the impact of using the alternative methods conventionally used in the international literature on the measured incidence of educational mismatch and its earnings effects. We use a rich Australian longitudinal data set for a controlled group of full-time...

The incentivized risky investment game has become a popular tool in lab-in-the-field experiments for its simplicity and ease of comprehension compared to some of the more complex Multiple Choice List approaches that have been more commonly used in laboratory experiments. We use a field...

Measurement errors are often a large source of bias in survey data. Lack of knowledge of the determinants of such errors makes it difficult for data producers to reduce the extent of errors and for data users to assess the validity of analyses using the data. We study the determinants of...

In linear regression analysis, the estimator of the variance of the estimator of the regression coefficients should take into account the clustered nature of the data, if present, since using the standard textbook formula will in that case lead to a severe downward bias in the standard errors....

We capitalise on an opportunity in the UK Household Longitudinal Study, which asks respondents the same SAH question with identical wording two times. This is done once with a self-completion and once with an open interview mode within the same household interview over four waves. We estimate...

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 variance of the measurement errors is a fraction of that of the mismeasured variables, which is typical for empirical...

Studies on health insurance coverage often rely on measures self-reported by respondents, but the accuracy of such measures has not been thoroughly validated. This paper is the first to use linked Australian National Health Survey and administrative population tax data to explore the accuracy of...

In empirical studies, the data usually don't include all the variables of interest in an economic model. This paper shows the identification of unobserved variables in observations at the population level. When the observables are distinct in each observation, there exists a function mapping...

The economics of obesity literature implicitly assumes that measured anthropometrics are error-free and they are often treated as a gold standard when compared to self-reported data. We use factor mixture models to analyse and characterize measurement error in both self-reported and measured...

This paper proposes a minimum distance (MD) estimator to estimate panel regression models with measurement error. The model considered is more general than examined in the literature in that (i) measurement error can be non-classical in the sense that they are allowed to be correlated with the...

This paper investigates the estimation and inference of spatial panel data models in which the regression coefficient vector is a trending function. We use time differences to eliminate the individual effects and employ GMM estimations for regression coefficients with both linear and quadratic...

The mixed-demand model allows for very flexible specification of what should be considered endogenous and exogenous in demand system estimation. This paper introduces a revealed preference framework to analyze the mixed-demand model. The proposed methods can be used to test whether observed data...

In observational studies, confounding variables that affect both the exposure and an outcome of interest are a general concern. It is well known that failure to control for confounding variables adequately can worsen inference on an exposure's effect on outcome. In this paper, we explore how...

Short-time work (STW) in Germany allows for a lot of flexibility in actual usage. Ex ante, firms notify the Federal Employment Agency about the total number of employees eligible, and, up to the total granted, firms can flexibly choose how many employees actually use STW. In firm-level surveys,...

This paper reports on a randomized experiment conducted among Malawian agricultural households to study nonclassical measurement error in self-reported plot area and farmers' responses to new information (the objective plot area measure) that was provided to correct nonclassical measurement...

Although proxy variables are pervasive in empirical work, the quality of proxy variables---in terms of how closely they track underlying economic forces---is not known. We derive novel regression specifications to infer the severity of measurement error using a sample of 2,552 instrumental...

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation...

In this paper, a quantum error correction scheme combined with quantum feedback control is proposed, which can achieve the Heisenberg limit even if the Hamiltonian-Not-in-Lindblad-Span condition in the optimal error correction protocol is not satisfied. Compared with other error correction...

A vast firm productivity literature finds that otherwise similar firms differ widely in their productivity and that these differences persist through time, with important implications for the broader macroeconomy. These stylized facts derive largely from studies of manufacturing firms in wealthy...

There is growing concern that the increasing use of machine learning and artificial intelligence-based systems may exacerbate health disparities through discrimination. We provide a hierarchical definition of discrimination consisting of algorithmic discrimination arising from predictive scores...

This paper reports evidence on the error properties of survey reports of labor market variables such as earnings and work hours. Our primary data source is the PSID Validation Study, a two-wave panel survey of a sample of workers employed by a large firm which also allowed us access to its very...

We study the size and drivers of non-standard errors (Menkveld et al., 2021) in portfolio sorts across 14 common methodological decision nodes and 40 sorting variables. These non-standard errors range between 0.05 and 0.26 percent and are, on average, larger than standard errors. Supposedly...

The Schwartz–Smith two-factor model is commonly used for pricing of derivatives in commodity markets. For estimating and forecasting the term structures of futures prices, the logarithm of commodity spot price is represented as the sum of short- and long-term factors being the unobservable...

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...

We construct a peer effects model where mean expenditures of consumers in one's peer group affect utility through perceived consumption needs. We provide a novel method for obtaining identification in social interactions models like ours, using ordinary survey data, where very few members of...

AbstractAccurate forecasting is critical for an efficient fiscal policy framework since it impacts consumer sentiments, business confidence, domestic and international institutions. Forecasts will be evaluated for accuracy, bias and efficiency, using ME, MAE, RMSE, Theil’s U statistic and the...