Having highly educated workers can be beneficial for organizations in terms of innovation and problem-solving capabilities, however when underpaid and underemployed, overeducated workers may experience feelings of frustration and stagnation as they are unable to fully utilize their skills and...

Unmanned aircraft vehicles (UAV) are widely used for yield estimations in agricultural production. Many significant improvements have been made towards the usage of hyperspectral and thermal sensors. The practical application of these new techniques meanwhile has been limited by the cost of data...

Quantile crossing has been a challenge for quantile regression, leading to research in how to obtain monotonically increasing quantile estimates. While important contributions, these papers do not provide insight into how enforcing monotonicity influences the estimated coefficients. This paper...

Recognizing the profound influence of geopolitical risks and world uncertainty on financial investment behaviour, this study uses a comprehensive approach to assess the impact of rising geopolitical risk on sovereign debt holdings for a panel of 24 OECD economies from Q1 2004 to Q4 2023. To do...

Binned scatter plots are a powerful statistical tool for empirical work in the social, behavioral, and biomedical sciences. Available methods rely on a quantile-based partitioning estimator of the conditional mean regression function to primarily construct flexible yet interpretable...

The paper explores the impact of digital transformation (DT) on new business creation in the case of European Union member states over the period 2015-2020 by employing several econometric techniques such as Ordinary Least Squares (OLS) and quantile regression (QR). The results of OLS regression...

This study estimates value-at-risk (VaR) to measure foreign exchange risk in Indonesia's banking industry using quantile regression (QR) approach. Four large banks whose capital and assets were the biggest were observed, and their selection was based on their market share in the industry. To...

Having highly educated workers can be beneficial for organizations in terms of innovation and problem-solving capabilities, however when underpaid and underemployed, overeducated workers may experience feelings of frustration and stagnation as they are unable to fully utilize their skills and...

Carbon risk, a type of climate risk, is expected to have a crucial impact, especially on high-carbon-emitting, "polluting" firms as opposed to less carbon-intensive, "clean" ones. With a rising number of actions and policies being continuously proposed to mitigate these concerns and an...

There is growing concern that climate change poses a serious threat to the sustainability of the insurance business. Understanding whether climate warming is a cause for an increase in claims and losses, and how this cause-effect relationship will develop in the future, are two significant open...

This study delves into the intricate impact of board social networks and local economic development on abnormal earnings within the financial statements of listed companies in Vietnam. The unique focus lies in internal board linkages, differentiating it from external engagements with other...

Value at risk (VaR) and expected shortfall (ES) have emerged as standard measures for detecting the market risk of financial assets and play essential roles in investment decisions, external regulations, and risk capital allocation. However, existing VaR estimation approaches fail to accurately...

Most previous studies on the market efciency of cryptocurrencies consider time evolution but do not provide insights into the potential driving factors. This study addresses this limitation by examining the time-varying efciency of the two largest cryptocurrencies, Bitcoin and Ethereum, and the...

Accurate prediction of offshore wind power generation is essential for efficient power scheduling and grid integration. This study introduces an innovative hybrid forecasting approach to address variability in power output due to different climatic conditions and challenges in measuring offshore...

This study examines the effect of household interference on business returns and household economic welfare of Micro and Small Enterprises (MSEs). This study employs a quantile regression method involving 7,020 households as the sample. The data are taken from the Indonesian Family Life Survey...

The present study investigates the nexus between health performance dynamics and economic growth in 43 countries in sub-Saharan Africa for the period 2004-2018. Four health performance dynamics are used, notably: total life expectancy, male life expectancy, female life expectancy and risk of...

The COVID-19 shock hit firms hard, on average, but how did it hit in the distribution of firms, differently between the high-growth superstars and the firms that were already struggling to survive? This paper implements graphical techniques and quantile regression to analyse the effect of the...

We propose a novel empirical approach to inform monetary policymakers about the potential effects of policy action when facing trade-offs between financial and macroeconomic stability. We estimate a quantile vector autoregression (QVAR) for the euro area covering the real economy, monetary...

Using a data sample from all 27 EU Member States from 2009-2020, the present study quantifies the factors that can lead to an increase in the collection rate of waste from electrical and electronic equipment (EEE). The results underline the fact that an increase in the quality of road...

The use of the internet is growing rapidly and has become an engine for economic development. However, few studies have examined the impact of internet use on agricultural production, and the results are not yet conclusive. Employing a dataset of more than 2,000 observations in rural Vietnam,...

This paper focuses on the downside risks to the German residential real estate market. It applies the "at-risk" methodology to the German housing market. Quantile regressions reveal that different quantiles of the house price forecast distribution are heterogeneously affected by the same...

The objective of the article is to carry out a review of the subject of composite indicators, especially that related to the methodological process associated with their construction, detailing and discussing the various steps linked to said process, using the construction of the Competitive...

Recent work on the conditional mean model offers the possibility of addressing misreporting of participation in social programs, which is common and has increased in all major surveys. However, researchers who employ quantile regression continue to encounter challenges in terms of estimation and...

Modeling and predicting extreme movements in GDP is notoriously difficult, and the selection of appropriate covariates and/or possible forms of nonlinearities are key in obtaining precise forecasts. In this paper, our focus is on using large datasets in quantile regression models to forecast the...

Financial stability indicators can be grouped into financial stress indicators that reflect heightened spreads and market volatility, and financial vulnerability indicators that reflect credit and asset price imbalances. Based on a panel of euro area countries, we show that both types of...

This study examines the effect of household interference on business returns and household economic welfare of Micro and Small Enterprises (MSEs). This study employs a quantile regression method involving 7,020 households as the sample. The data are taken from the Indonesian Family Life Survey...

The COVID-19 shock hit firms hard, on average, but how did it hit in the distribution of firms, differently between the high-growth superstars and the firms that were already struggling to survive? This paper implements graphical techniques and quantile regression to analyse the effect of the...