We demonstrate that all meta-analyses of partial correlations are biased, and yet hundreds of meta-analyses of partial correlation coefficients (PCC) are conducted each year widely across economics, business, education, psychology, and medical research. To address these biases, we offer a new...

This article presents a computationally efficient approach to sample from Gaussian state space models. The method is an instance of precision-based sampling methods that operate on the inverse variance-covariance matrix of the states (also known as precision). The novelty is to handle cases...

How to sample training/validation data is an important question for machine learning models, especially when the dataset is heterogeneous and skewed. In this paper, we propose a data sampling method that robustly selects training/validation data. We formulate the training/validation data...

Certificates are structured financial instruments that aim to provide investors with investment solutions tailored to their needs. Certificates can be modeled using a bond component and a derivative component, typically an options strategy. The pricing of certificates is typically performed...

Investors sometimes have strong convictions that a distinctive economic regime will prevail in the period ahead and therefore would like to form a portfolio that reflects the expected returns, standard deviations, and correlations of assets during such a regime. To do so, they typically isolate...

Many household panel surveys have experienced decreasing response rates and increasing risk of nonresponse bias in recent decades, but trends in response rates and nonresponse bias in business or establishment panel surveys are largely understudied. This article examines both panel response...

The properties of classical panel data estimators including fixed effect, first-differences, random effects, and generalized method of moments-instrumental variables estimators in both static as well as dynamic panel data models are investigated under sample selection. The correlation of the...

A crucial role belongs to export firms in the export-led growth model of Vietnam. The COVID-19 disease has posed a serious challenge to the Vietnamese economy, having negatively impacted its influential export sector. However, investigating this export sector encounters small sample issues...

Estimations of quadratic forms in the parameters of linear models exhibit small-sample bias. The direct computation for a bias correction is not feasible when the number of covariates is large. We propose a bootstrap method for correcting this bias that accommodates different assumptions on the...

In the context of high-frequency financial data it is often assumed that sampling times are exogenous. This entails that financial asset prices, sampled on a grid of trade instants, are independent from the sampling times. We derive statistical tests capable of determining whether or not, and to...

This study explores the benefits of incorporating fat-tailed innovations, asymmetric volatility response, and an extended information set into crude oil return modeling and forecasting. To this end, we utilize standard volatility models such as Generalized Autoregressive Conditional...

We study informational dissociations between decisions and decision confidence. We explore the consequences of a dual-system model: the decision system and confidence system have distinct goals, but share access to a source of noisy and costly information about a decision-relevant variable. The...

Under the advanced internal ratings-based (AIRB) approach, the banks are allowed to use their internally developed models for probability of default (PD), exposure at default (EAD) and loss given default (LGD) parameters. According to the Basel II Accord (2004), the potential over-optimism of...

We develop a distribution regression model under endogenous sample selection. This model is a semi-parametric generalization of the Heckman selection model. It accommodates much richer effects of the covariates on outcome distribution and patterns of heterogeneity in the selection process, and...

Evaluating the impact of policy interventions on respondents who are embedded in a social network is often challenging due to the presence of network interference within the treatment groups, as well as between treatment and non-treatment groups throughout the network. In this paper, we propose...

The quality of historical US census data is critical to the performance of linking algorithms. We use genealogical profiles to correct measurement errors in census names and ages. Our findings suggest that one in every two records has an error in name or age, and human capital is correlated with...

We investigate to what extent volunteer-based sampling of large-scale biobanks biases associations and estimate inverse probability (IP) weights to correct for such bias. Using the UK Biobank (UKB) as an example of a large-scale volunteer-based cohort, and population-representative data from the...

In this paper, a single acceptance sampling plan based on a truncated life test is proposed for a lifetime that follows the Zubair-Exponential (ZE) distribution. For some acceptance numbers, confidence levels, values of the ratio of the fixed experiment time to the particular mean lifetime, and...

This paper introduces a simulation algorithm for evaluating the log-likelihood function of a large supermodular binary-action game. Covered examples include (certain types of) peer effect, technology adoption, strategic network formation, and multi-market entry games. More generally, the...

Globally, unhealthy diets have a significant impact on people's risk of disease and mortality, so the German Ministry of Nutrition and Agriculture also focuses on healthier and balanced diets in its reduction and innovation strategy. By means of the NutriScore, the nudging principle is used to...

A new two-parameter model is proposed using the Kavya-Manoharan (KM) transformation family and Burr X (BX) distribution. The new model is called the Kavya-Manoharan-Burr X (KMBX) model. The statistical properties are obtained, involving the quantile (QU) function, moment (MOs), incomplete MOs,...

We use Markov chain Monte Carlo (MCMC) sampling to draw model coefficients to generate LGD distributions. We find that applying this Bayesian method on a sophisticated model that accounts for the bi-modal distribution of the LGDs, such as the zero-one-inflated beta (ZOIB) model, can generate LGD...

We derive the finite sample bias of the sample cross-covariance estimator based on a stationary vector-valued time series with an unknown mean. This result leads to a bias-corrected estimator of cross-covariances constructed from linear combinations of sample cross-covariances, which can in...