Researchers interested in studying the frequency of events or behaviors among a population must rely on count data provided by sampled individuals. Often, this involves a decision between live event counting, such as a behavioral diary, and recalled aggregate counts. Diaries are generally more...

Meta-analysis upweights studies reporting lower standard errors and hence more precision. But in empirical practice, notably in observational research, precision is not given to the researcher. Precision must be estimated, and thus can be p-hacked to achieve statistical significance. Simulations...

The aim of this paper is to construct a forecasting model oriented on predicting basic macroeconomic variables, namely: the GDP growth rate, the unemployment rate, and the consumer price inflation. In order to select the set of the best regressors, Bayesian Averaging of Classical Estimators...

This paper reworks and expands on the results of existing simulation studies, investigating the performance of various robust estimators of scale for Tukey's three corner distributions. We focus attention on the popular biweight A-estimator, but also propose a new estimator based on the...

Objective: To estimate the treatment effect from participating in an asthma intervention that was part of the National Asthma Control Program.Study Setting: Data on children who participated in asthma case management (N=270) and eligible children who did not participate in case management...

Economic agents are aware to incur in a loss basing their decisions on their own extrapolations instead of sound statistical data, but the loss could be smaller than the one related to waiting for the dissemination of final data. A broad guidance in deciding when statistical offices should...

Purpose - Knowing financial and economic information beforehand benefits in planning and developing policies for every country especially for a developing country like Thailand and for other Asian countries. Unfortunately, missing data or non-response plays an essential role in many areas of...

Estimating covariance matrices using high-frequency data is crucial for market makers, investors in newly-issued securities, and risk managers. These estimations often handle the asynchrony of high-frequency trades by using returns for periods between when all instruments have traded (refresh...

The aim of this paper is to construct a forecasting model oriented on predicting basic macroeconomic variables, namely: the GDP growth rate, the unemployment rate, and the consumer price inflation. In order to select the set of the best regressors, Bayesian Averaging of Classical Estimators...