Bidirectional Associations Between Depressive and Anxiety Symptoms and Loneliness During the COVID-19 Pandemic: Dynamic Panel Models With Fixed Effects

Background: Understanding the direction and magnitude of mental health-loneliness associations across time is important to understand how best to prevent and treat mental health and loneliness. This study used weekly data collected over 8 weeks throughout the COVID-19 pandemic to expand previous findings and using dynamic panel models with fixed effects which account for all time-invariant confounding and reverse causation.Methods: Prospective data on a convenience and snowball sample from all 50 US states and the District of Colombia (n = 2,361 with ≥2 responses, 63.8% female; 76% retention rate) were collected weekly via online survey at nine consecutive timepoints (April 3–June 3, 2020). Anxiety and depressive symptoms and loneliness were assessed at each timepoint and participants reported the COVID-19 containment strategies they were following. Dynamic panel models with fixed effects examined bidirectional associations between anxiety and depressive symptoms and loneliness, and associations of COVID-19 containment strategies with these outcomes.Results: Depressive symptoms were associated with small increases in both anxiety symptoms (β = 0.065, 95% CI = 0.022–0.109; p = 0.004) and loneliness (β = 0.019, 0.008–0.030; p = 0.001) at the subsequent timepoint. Anxiety symptoms were associated with a small subsequent increase in loneliness (β = 0.014, 0.003–0.025; p = 0.015) but not depressive symptoms (β = 0.025, −0.020–0.070; p = 0.281). Loneliness was strongly associated with subsequent increases in both depressive (β = 0.309, 0.159–0.459; p < 0.001) and anxiety (β = 0.301, 0.165–0.436; p < 0.001) symptoms. Compared to social distancing, adhering to stay-at-home orders or quarantining were not associated with anxiety and depressive symptoms or loneliness (both p ≥ 0.095).Conclusions: High loneliness may be a key risk factor for the development of future anxiety or depressive symptoms, underscoring the need to combat or prevent loneliness both throughout and beyond the COVID-19 pandemic. COVID-19 containment strategies were not associated with mental health, indicating that other factors may explain previous reports of mental health deterioration throughout the pandemic.

Economic Cycle and Bank Liquidity Hoarding: Are They Procyclical or Countercyclical?

The paper empirically examines bank liquidity hoarding fluctuations over the economic cycle and provides further evidence on the heterogeneous cyclicality of bank liquidity hoarding across different banks in Vietnam for the period 2007–2019. Using both static panel models with the fixed-effects regression using corrected Driscoll-Kraay standard errors and dynamic panel models with the two-step system generalized method of moments estimator, we find that the liquidity hoarding of banks is procyclical. Concretely bank liquidity hoarding on- and off-balance sheets tends to increase during economic upturns and decrease during economic downturns. Our additional analysis yields a consistent pattern that financially weaker banks are more procyclical than their stronger counterparts. During booms and busts, the behaviour of hoarding liquidity is more pronounced for banks with smaller sizes, less capital, more risk, and less profit. This heterogeneity also contributes to understanding the core mechanism behind our main findings, further confirming the precautionary motive of bank liquidity hoarding.

Remittances and subjective well-being: A static versus dynamic panel approach to happiness

Using all five waves of the National Income Dynamics Study (NIDS) panel dataset, we examine the effect of domestic remittances on the static and dynamic subjective well-being (SWB) of recipient individuals in South Africa, by using a random effects ordered probit model that accounts for individual heterogeneity. Moreover, we check the robustness of our static model results by making use of an instrumental variable for migrants’ remittances. Two major empirical findings emerge from this paper: firstly, domestic remittances are consistently found to have a positive and statistically significant impact on the happiness of recipient individuals. Moreover, this finding persists in both the static and dynamic panel models. Secondly, the coefficient on lagged SWB (derived from the dynamic model) is found to be positive and statistically significant, confirming that SWB today is significantly influenced by SWB in the past.

Do Negative Emotions Matter? Paths From Victimization to Cyber and Traditional Bullying From a General Strain Theory Perspective

Drawing on theoretical propositions of general strain theory (GST), the current study aims to examine whether general victimization as a source of criminogenic strain predicts two different types of bullying, traditional and cyberbullying perpetrations, and whether negative emotionality, such as trait-based anger and depression, conditions the effects of general victimization on bullying. Using a Korean adolescent sample, we adopt cross-lagged dynamic panel models to investigate the longitudinal effects and interactions of strain and negative emotionality. The results indicate a significant influence of general victimization on both types of bullying perpetrations, as expected, while the conditioning effects of negative emotionality are found only for traditional bullying, which may reflect differences in the nature of the two different forms of bullying.

FDML versus GMM for Dynamic Panel Models with Roots Near Unity

This paper evaluates the first-differenced maximum likelihood (FDML) and the continuously updating system generalized method of moments (CU-GMM) estimators of dynamic panel models when the data is close to non-stationary. This case is far from trivial, as a high degree of persistence is the norm rather than the exception in economic panels, particularly in financial management. While the CU-GMM is shown to have lower bias and higher power, it suffers from severe size distortions, which are exacerbated when the data approaches non-stationarity.

Maturation as a Promoter of Change in Features of Psychopathy Between Adolescence and Emerging Adulthood

The relationship between psychopathy and negative behavioral, social, and health outcomes has lead to calls to identify factors that promote change in features of psychopathy. Given that maturation has important implications for changes in personality more broadly, it also may be informative of changes in specific personality traits associated with psychopathy. Rocque’s integrated maturation theory was used in the current study to guide the measurement of psychosocial, adult social role, and identity maturation domains among boys and girls from the Pathways to Desistance Study ( n = 1,354). Based on cross-lagged dynamic panel models, within-individual change in temperance (psychosocial maturation), work orientation and consideration of others (adult social role maturation), and moral disengagement (identity maturation) predicted within-individual change in features of psychopathy measured using the Youth Psychopathic Traits Inventory. Maturation may influence features of psychopathy directly or indirectly through changes in a person’s social environment. Understanding why features of psychopathy change is an important step for developing person-oriented intervention strategies.

Relationship between Energy Consumption and Economic Growth in European Countries: Evidence from Dynamic Panel Data Analysis

The aim of the article is to empirically verify the relationship between energy consumption and economic growth. The time scope of this study covers the period of 2008–2019. The scope of analyzed subjects covers 34 European countries, 27 of which are currently members of the European Union. European countries consume large amounts of energy, so it is worth investigating the effect of reducing energy consumption on the process of economic growth. For this purpose, dynamic panel models were used. The research methods included the use of dynamic panel models, taking into account the Arellano and Bond and Blundell and Bond estimators. The results made it possible to identify the relationship between energy consumption and economic growth. It was found that, in the short term, increases in production will result in a statistically significant increase in energy consumption. Importantly, in the long term, this impact is also statistically significant and positive. On the other hand, taking into account the second of the estimated models, it can be concluded that, in the short term, increases in energy consumption do not cause changes in the rate of economic growth. The verification of this relationship in the long term also does not confirm it. In summary, it can be stated that a one-way relationship (in the short and in the long term), directed from economic growth towards energy consumption, was identified.