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Heteroskedasticity and Autocorrelation of Errors
The regression model is a random model in the sense that an error term is included in the equation linking the dependent variable to the explanatory...
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Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors
Advanced efficiency measurement methods usually fall within Stochastic Frontier Analysis (SFA), Data Envelopment Analysis (DEA), or their...
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Measurement Error Models
This chapter discusses the use of instrumental variables for dealing with measurement error in regression covariates. Instruments are defined as...
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A model of errors in BMI based on self-reported and measured anthropometrics with evidence from Brazilian data
The economics of obesity literature implicitly assumes that measured anthropometrics are error-free and they are often treated as a gold standard...
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Impact of uncertainty on inflation forecast errors in Central and Eastern European countries
The question underlying the research problem addressed by this study concerns various factors, including uncertainty, that could affect forecast...
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Measurement error in longitudinal earnings data: evidence from Germany
We present evidence on the extent of measurement error in German longitudinal earnings data. Qualitatively, we confirm the main result of the...
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Which Capital Flow Surge Methods Are Better at Predicting Reversals and Sudden Stops?: Balancing Type 1 and Type 2 Errors
Capital flow surges have become a major source of concern as they have been often followed by disruptive reversals and sudden stops. We introduce...
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Cognitive/Emotional Errors and Financial Education
Behavioral Finance has already become the new theoretical financial paradigm. Based on other disciplines, such as psychology, sociology, and...
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Eco-efficiency, Circularity Measurement and Assessment
Before to measure eco-efficiency and sustainable impact, it needs to learn to understand systems. Circularity needs to be measured, since it is...
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Are Disaster Impact Estimates Distorted by Errors in Popular Night-Time Lights Data?
Satellite-detected night lights data are widely used to evaluate economic impacts of disasters. Growing evidence from elsewhere in applied economics...
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Measurement error and its impact on estimates of income dynamics
This paper examines whether reported income generates biases for studies on economic mobility and poverty dynamics. Using a linear measurement error...
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Partially Convex Production Technology and Efficiency Measurement
Economists tend to believe that production technology should exhibit increasing returns to scale first and then constant and finally decreasing...
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Density deconvolution with Laplace errors and unknown variance
We consider density deconvolution with zero-mean Laplace noise in the context of an error component regression model. We adapt the minimax...
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Effects of mixing modes on nonresponse and measurement error in an economic panel survey
Numerous panel surveys around the world use multiple modes of data collection to recruit and interview respondents. Previous studies have shown that...
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Endogeneity and Measurement Bias of the Indicator Variables in Hybrid Choice Models: A Monte Carlo Investigation
We investigate the problem of endogeneity and measurement bias arising from incorporating indicator variables (e.g., measures of attitudes) into...
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Hidden schooling: endogenous measurement error and bias in education and labor market experience
Since 1980, 25% of US students repeated a grade during their academic career. Despite this, few economists account for retention when measuring...
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The Climate Actions and Policies Measurement Framework: A Database to Monitor and Assess Countries’ Mitigation Action
There are major gaps in the measurement of the adoption and stringency of countries’ climate actions and policies, notably in a manner coherent...
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Intergenerational mobility measurement with latent transition matrices
We propose a multivariate approach for the estimation of intergenerational transition matrices. Our methodology is grounded on the assumption that...
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Inequality measurement with coarse data
Measuring inequality is a challenging task, particularly when data is collected in a coarse manner. This paper proposes a new approach to measuring...
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Supply Chain Sustainability and Supply Chain Resilience: A Performance Measurement Framework with Empirical Validation
Sustainability and resilience are both fundamental to ensure the long-term survival of supply chains. Considering that synergies and trade-offs...