Frame of the research: Effective risk assessment is central to managerial decisionmaking in financial institutions, corporate finance, and strategic planning. Drawing from prior studies on default risk, this paper investigates how the predictive ability of financial indicators varies depending...

We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but also the most computationally demanding, involves...

Over the past years, machine learning emerged as a powerful tool for credit scoring, producing high-quality results compared to traditional statistical methods. However, literature shows that statistical methods are still being used because they still perform and can be interpretable compared to...

Dynamic social norms have been recognized as a promising approach to promote energy sufficiency. By highlighting trends and future shifts rather than current states, dynamic norms allow for a better focus on emerging norms that are not widely adopted. While existing studies predominantly examine...

The prediction of financial distress has emerged as a significant concern over a prolonged period spanning more than half a century. This subject has garnered considerable attention owing to the precise outcomes derived from its predictive models. The main objective of this study is to predict...

Logistic regression is a very popular binary classification technique in many industries, particularly in the financial service industry. It has been used to build credit scorecards, estimate the probability of default or churn, identify the next best product in marketing, and many more...

In the literature on Philippine public procurement, knowledge gaps exist in terms of coverage of period of reform implementation and scope of reform application. This study helps close these gaps by analyzing Philippine public procurement history up to the years of application of the 2016...

Climate-related disasters have increased over recent decades, with severe human and economic consequences. While research has examined their macroeconomic effects and impact on households' income and consumption patterns, little attention has been given to their impact on tax morale-taxpayers'...

Recent studies focus on machine learning (ML) algorithms for predicting employee churn (ECn) to save probable economic loss, technology leakage, and customer and knowledge transference. However, can human resource professionals rely on algorithms for prediction? Can they decide when the process...

The COVID-19 vaccination program in 2021 constituted a key public health policy measure to overcome the pandemic in Germany. However, research has identified substantial variations in vaccination uptake across social groups. Over the course of the COVID-19 pandemic, research has indicated that...

This paper studies a dynamic ordered logit model for panel data with fixed effects. The main contribution of the paper is to construct a set of valid moment conditions that are free of the fixed effects. The moment functions can be computed using four or more periods of data, and the paper...

This study aims to analyze the typology of regional inequality in Indonesia and the opportunity for regional inequality shifts due to changes in independent variables. The analysis method is carried out using the Williamson index and the Theil index. Furthermore, multinomial logit regression...

This study investigates the interplay between bank lending standards and credit scoring behavior of Turkish banks to SMEs. A Logistic Regression Model has been used by employing CBRT bank and firm-level micro data for the 2017Q1 - 2024Q2 period. First, one of the primary findings of the study...

This paper aims to understand the health effects of energy poverty in Germany using SOEP panel data from 2010 to 2020. Linear probability models and fixed effects ordered logit models reveal a consistently negative relationship of three expenditures based energy poverty indicators with general...

This study explores the relevance of education in reducing poverty in Egypt's rural and urban areas.The study applies the logistic model to Analyse Household Income Expenditure survey data.The results indicate that spending on education in urban regions is higher than in rural areas. Second, the...

This study reframes closure intention in small- and medium-sized enterprises (SMEs) as an ex ante diagnostic signal rather than a post-mortem symptom of failure. The survey evidence from 385 Ecuadorian SMEs was analyzed in two stages; confirmatory factor analysis validated the scales capturing...

Understanding the complex and multidimensional nature of poverty is essential for designing effective and targeted policy interventions in rural Ethiopia. This study examined the determinants of multidimensional poverty in Bilate River Basin in South Ethiopia, employing cross-sectional household...

Several studies have investigated the determinants of firms' capital structure choices. Though an intercorporate loan is an essential source of corporate debt, there are no studies that examine the determinants of firms' preference to use the intercorporate loan as a source of debt. This study...

Job satisfaction is an essential factor influencing employees as well as employers. This study aims to identify and compare overall job satisfaction determinants among young adults in Poland in two dimensions, i.e., economic and socio-demographic. The ordered logit model was built upon the data...

This paper aims to understand the health effects of energy poverty in Germany using SOEP panel data from 2010 to 2020. Linear probability models and fixed effects ordered logit models reveal a consistently negative relationship of three expendituresbased energy poverty indicators with general...

The spatial distribution of future renewable capacities is a key determinant for developing appropriate grid expansion plans. This is particularly relevant for onshore wind energy. Existing studies mostly extrapolate future installations based on existing capacities and available sites. As wind...

Climate-related disasters have increased over recent decades, with severe human and economic consequences. While research has examined their macroeconomic effects and impact on households' income and consumption patterns, little attention has been given to their impact on tax morale-taxpayers'...

This study addresses the quantification of credit risk in solidarity economy entities, proposing a new methodology to redefine the concept of a "default" in the frequent situations of extreme class imbalances. The objective is to develop and evaluate credit scoring models that enhance risk...

Using a discrete choice experiment (DCE), we analyze how social comparisons and financial information influence households' preferences and trade-offs among three sustainable electricity demand behaviors: conservation actions, efficiency investments, and purchasing a green power mix. Our results...

Logistic regression is widely used in complex data analysis. When predictors are at individual level and the response at aggregate level, logistic regression can be estimated using the Maximum Likelihood Estimation (MLE) method with the joint likelihood function formed by Poisson binomial...

Contemporary consumer society is deeply intertwined with the concepts of money and shopping, which are closely related yet often studied separately. Despite their interconnectedness, there is a notable gap in research that simultaneously addresses financial literacy as a tool for effective money...

According to the Federal Reserve of the United States, in the second quarter of 2024, American credit card debt reached USD 1.14 trillion, the highest balance ever recorded. In an age of high-interest, complex credit cards, how does financial literacy affect credit card debt repayment? Also, how...

This study investigates tax compliance patterns among individuals in Romania through a survey-based approach, aiming to comprehend factors influencing taxpayers' behavior, including perception towards taxation, ethics, evasion, and public awareness. The insights garnered can inform policy...

This study examines the importance of game elements of the first set in Wimbledon matches in deciding the match outcome. We propose a LASSO-induced logistic regression model based on first set data to identify the variables that impact the match outcome. Our findings indicate that winning...