Merton-type default risk and financial performance: the dynamic panel moderation of firm size

PurposeThe main purpose of this study is to evaluate the probability of default and examine the relationship between default risk and financial performance, with dynamic panel moderation of firm size.Design/methodology/approachThis study utilizes a total of 1,500 firm-year observations from 2013 to 2018 using dynamic panel data approach of generalized method of moments to test the relationship between default risk and financial performance with the moderation effect of the firm size.FindingsThis study establishes the findings that default risk significantly impacts the financial performance. The relationship between distance-to-default (DD) and financial performance is positive, which means the relationship of the independent and dependent variable is inverse. Moreover, this study finds that the firm size is a significant positive moderator between DD and financial performance.Practical implicationsThis study provides new and useful insight into the literature on the relationship between default risk and financial performance. The results of this study provide investors and businesses related to nonfinancial firms in the Pakistan Stock Exchange (PSX) with significant default risk's impact on performance. This study finds, on average, the default probability in KSE ALL indexed companies is 6.12%.Originality/valueThe evidence of the default risk and financial performance on samples of nonfinancial firms has been minimal; mainly, it has been limited to the banking sector. Moreover, the existing studies have only catered the direct effect of only. This study fills that gap and evaluates this relationship in nonfinancial firms. This study also helps in the evaluation of Merton model's performance in the nonfinancial firms.

Which food prices were more vulnerable to the COVID-19 blockade regulations in China? Comparison between perishable and storable vegetables

PurposeThis paper aims to investigate how differently the COVID-19 blockade regulations influence the prices of perishable and storable foods. The authors focus on the cases of the 2020 blockade at Hubei province and the 2021 blockade at Shijiazhuang city in China, and the authors examine how the blockade influenced the prices of Chinese cabbages (perishable) and potatoes (storable) within and around the blockade area.Design/methodology/approachThe paper employs the fixed effects model, the panel VAR (PVAR) model, and the spatial dynamic panel (SPD) model to estimate the impacts of the blockade on the food prices. It constructs the unique data set of 3-day average prices of Chinese cabbages and potatoes at main wholesale markets in China during the two urban blockade periods from January 1 to April 8 in 2020 and from January 1 to March 1 in 2021.FindingsThe results from the SPD models indicate that the price of Chinese cabbages was more vulnerable and increased by 7.1–9.8% due to the two blockades while the price of potatoes increased by 1.2–6.1%. The blockades also significantly influenced the prices in the areas adjacent to the blockade area. The SPD results demonstrate that the impacts of the blockades would be overestimated if the spatial dependence is not controlled for in the fixed effects model and the PVAR model.Research limitations/implicationsBecause the research focuses on the cases in China, the results may lack generalizability. Further research for other countries is encouraged.Originality/valueThis paper demonstrates the importance of considering food types and spatial dependence in examining the impact of the COVID-19 blockades on food prices.

The Employment in Innovative Enterprises in Europe

In this article we evaluate the determinants of the Employment in Innovative Enterprises in Europe. We use data from the European Innovation Scoreboard of the European Commission for 36 countries in the period 2000-2019 with Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel, WLS and Pooled OLS. We found that the “Employment in Innovative Enterprises in Europe” is positively associated with “Broadband Penetration in Europe”, “Foreign Controlled Enterprises Share of Value Added”, “Innovation Index”, “Medium and High-Tech Product Exports” and negatively associated to “Basic School Entrepreneurial Education and Training”, “International Co-Publications”, and “Marketing or Organizational Innovators”. Secondly, we perform a cluster analysis with the k-Means algorithm optimized with the Silhouette Coefficient and we found the presence of four different clusters. Finally, we perform a comparison among eight different machine learning algorithms to predict the level of “Employment in Innovative Enterprises” in Europe and we found that the Linear Regression is the best predictor.

The Effect of COVID-19 Pandemic on Corporate Dividend Policy in Indonesia: The Static and Dynamic Panel Data Approaches

This research examines the effect of the crisis due to the COVID-19 pandemic on dividend policy in Indonesia. The purposive sampling method was used to collect data from corporates listed on the IDX from 2014 to 2020 and analyzed using static and dynamic panel data approaches. The fixed-effect models (FEM) were selected for the static panel data regression. Meanwhile, the first difference-generalized method of moments (FD-GMM) and system-generalized method of moments (SYS-GMM) were used for determine the robustness of the estimated dynamic panel data. The results showed that the crisis due to the pandemic led to higher dividend distribution on SYS-GMM. Furthermore, companies maintained the dividend level as a positive signal for investors which lifted the sluggish trade condition in the capital market. Profitability and previous year dividends positively affect dividend policy robustly. Furthermore, the results showed that age affects dividend policy on FD-GMM. Financial leverage has a robust effect, and firm size has an effect on FD-GMM in different directions, while investment opportunity does not affect dividend policy. Statistically, the FEM selected that violates the best linear unbiased estimation was proven to form parameters that were not much different from the estimates produced by the dynamic model, both from the coefficient of influence direction and significance, and the omitted variable bias occurs as evidenced in the robust test with dynamic model was solved. This research is also used as a reference for considering investors’ investment decisions in the new normal condition. Therefore, dividend policy can be considered as a positive signal to investors with the ability to stock trading activities in the capital market.

Adolescent Suicides and Social Disparities

Suicides have been the second leading cause of deaths among adolescents in the United States in 2016. This paper aims to find qualitative and quantitative evidence of the relationship between socioeconomic inequalities and adolescent suicides. The suicide risk factors among all states are identified to form the pooled dynamic panel dataset from 1990 to 2016. To our knowledge, this paper is the first to find that social inequalities are significantly related to American adolescent suicides using the state-level dynamic panel data. Changes of unemployment rates have the consistent and significantly positive impacts on changes of adolescent suicides rates. Changes of Top 10% income index are uniformly positive to changes of adolescent suicide rates. Gini indices have inconsistently positive correspondence to adolescent suicide rates. Furthermore, high school graduation rates are insignificantly and negatively associated with adolescent suicide rates in the United States.