High nonresponse rates have become a rule in survey sampling. In panel surveys there occur additional sample losses due to panel attrition, which are thought to worsen the bias resulting from initial nonresponse. However, under certain conditions an initial wave nonresponse bias may vanish in...

This paper conducts a comprehensive investigation of the "forecast combination puzzle" in the context of the heterogeneous autoregressive (HAR) model for volatility forecasting. The widely-used HAR model can be considered as a theoretically optimal combination of three random-walk forecasts...

While partial moments like semivariance, lower and upper partial moments have seen acceptance by both academics and investment professionals, there are some who consider these measures to be ad hoc measures of investment performance. This paper seeks to provide the academic foundation for the...

Accurate data on crime rates is essential for evaluating many social programs. However, in the United States, officials often impute crime rates to compensatefor the 20--40% of agencies that do not report crime statistics. I show that all commonly used methods underestimate crime. First, I show...

Machine learning is a growing method for causal inference. In machine learning settings, prediction errors are a commonly overlooked problem that can bias results and lead to arbitrarily incorrect parameter estimates. We consider a two-stage model where (1) machine learning is used to predict...

Problem definition. We present a continuous-time Bayesian model for managing inventory in a retail setting when inventory records are inaccurate. In our formulation, the inventory level and its record have separate dynamics. The former is driven by the demand and unobservable loss process while...

Products cannot be produced as perfect as nominal values due to errors in manufacturing and assembly processes. These complex errors eventually affect the function and performance of the finished products. This paper deals with how to minimize the overall errors when assembling each part which...

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....