Time-invariant Variables Research Articles

World Society, Cultural Diversity, and Gender Gap in Political Empowerment

Abstract This article studies the interactive effects of world society and cultural diversity on the gender gap in political empowerment. Focusing on the Women’s Share of Seats in National Parliaments (WSSNP) and the Gender Gap in Political Empowerment (GGPE) Index as two main outcome variables, the analyses use a growth curve approach to estimate nations’ trajectories of gender political inequality and explain them by time-invariant and time-varying independent variables. Overall, the results suggest that nations’ level of embeddedness in the world society, measured by the political globalization index of the KOF Swiss Economic Institute, closes the gender gap in political empowerment. Nevertheless, more culturally diverse societies, in terms of the level of religious fractionalization, are more susceptible to the equalizing impacts of globalization on the gender gap in political empowerment. Conversely, culturally homogenous nations appear to show some level of resistance to adopting the gender-equitable values prompted by world culture.

Does firm-level teamwork culture affect cash holdings?

PurposePrior literature on the cultural determinants of cash holdings focuses on time-invariant cultural variables measured at the geographical level. These measures of culture do not capture the firm-level variation in corporate culture. Using a validated time-variant measure of firm-level corporate culture, specifically teamwork, we examine the effect of teamwork on a firm's cash holdings.Design/methodology/approachIn this paper, we explore the effect of corporate teamwork culture on firms' cash holdings. Using sudden CEO turnover as an exogenous shock to a firm's teamwork culture, we find teamwork increases cash holdings. Also, we test and find two channels—financial constraint and agency—and two new labour-related channels—human capital quality and labour inefficiency—through which teamwork culture affects cash holdings. Our results are robust to endogeneity tests.FindingsWe find that teamwork increases the cash holdings of firms. We find that a firm with a high teamwork culture has higher cash holdings: an increase of one standard deviation in teamwork leads to a 14.6% rise in the mean cash holdings.Originality/valueTo our knowledge, our study is the first to introduce the firm-level teamwork cultural construct as a determinant of cash holdings.

Born to move? Birth order and emigration

This paper studies the interrelation between birth order and emigration adopting a family fixed-effects approach. We use register data on all persons in full-siblings groups born 1970–2002 in the entire Finnish-born population, and observe their first move abroad since age 18 in the period 1987–2020. The total number of siblings is 1,352,908, the total number of sibling groups 549,842, and the total number of first moves abroad 31,192. By comparing siblings in the same family, we effectively adjust for all time-invariant confounding from unobserved or unmeasured time-invariant variables. Emigration is found to be positively associated with birth order. The hazard of emigration for second-born siblings is 1.05 that of first borns, that of third borns 1.07, and that of fourth borns 1.11. The pattern is particularly marked for emigration to countries where there is free mobility, and the association is similar for both genders. Potential explanations to the birth order pattern may be variation in personality traits, risk-taking behaviours and aspirations between siblings, or differential allocation of resources and opportunities within families. The results highlight the importance of considering birth order within the context of family dynamics and individual mobility patterns, and they need to be extended to broader settings.

Quantifying reciprocal relationships between poverty and health: combining a causal loop diagram with longitudinal structural equation modelling.

This study takes on the challenge of quantifying a complex causal loop diagram describing how poverty and health affect each other, and does so using longitudinal data from The Netherlands. Furthermore, this paper elaborates on its methodological approach in order to facilitate replication and methodological advancement. After adapting a causal loop diagram that was built by stakeholders, a longitudinal structural equation modelling approach was used. A cross-lagged panel model with nine endogenous variables, of which two latent variables, and three time-invariant exogenous variables was constructed. With this model, directional effects are estimated in a Granger-causal manner, using data from 2015 to 2019. Both the direct effects (with a one-year lag) and total effects over multiple (up to eight) years were calculated. Five sensitivity analyses were conducted. Two of these focus on lower-income and lower-wealth individuals. The other three each added one exogenous variable: work status, level of education, and home ownership. The effects of income and financial wealth on health are present, but are relatively weak for the overall population. Sensitivity analyses show that these effects are stronger for those with lower incomes or wealth. Physical capability does seem to have strong positive effects on both income and financial wealth. There are a number of other results as well, as the estimated models are extensive. Many of the estimated effects only become substantial after several years. Income and financial wealth appear to have limited effects on the health of the overall population of The Netherlands. However, there are indications that these effects may be stronger for individuals who are closer to the poverty threshold. Since the estimated effects of physical capability on income and financial wealth are more substantial, a broad recommendation would be that including physical capability in efforts that are aimed at improving income and financial wealth could be useful and effective. The methodological approach described in this paper could also be applied to other research settings or topics.

Thrombocytopenia after sutureless and standard stented aortic valve replacement: a retrospective analysis of risk factors, clinical course, and early outcome

ObjectivesThrombocytopenia following Perceval aortic valve replacement has been described previously with variable outcome. Studies have lacked a robust analysis of platelet fluctuation and factors affecting it. We aimed to statistically describe the trend in thrombocyte variability as compared with conventional aortic valve replacement, and to assess predictors as well as impact on associated outcomes.MethodsOne hundred consecutive patients with first-time Perceval were retrospectively compared to 219 patients after Perimount Magna Ease valve replacement. The primary outcome was the serial thrombocyte count on day 0–6. Generalized estimating equations were used to analyse the data using fixed-effect models: for the effect of the post-operative day on platelet count, and random-effect models estimating both time-variant (platelets) and time in-variant variables (valve type, age, LV function, pre-op platelet level).ResultsPerceval patients were older (72 ± 1 vs 68 ± 1 years, p < 0.01) with higher NYHA status (3(2–3) vs 2(1–2), p < 0.001). Mean platelet count in the sutureless group was lowest on day 2 (91.9 ± 31.6 vs 121.7 ± 53.8 × 103 µl−1), and lower on day 4 (97.9 ± 44) and 6 (110.6 ± 61) compared to the conventional group (157.2 ± 60 and 181.7 ± 79) but did not result in a higher number of transfusions, bleeding or longer hospital stay (p > 0.05). Reduced platelet count was a strong predictor of red cell transfusion in the conventional (p = 0.016), but not in the sutureless group (p = 0.457). Age (Coef -1.025, 95%CI-1.649—-0.401, p < 0.001) and CPB-time (Coef 0.186, 95%CI-0.371—-0.001, p = 0.048) were predictors for lower platelet levels.ConclusionConsidering the older patient profile treated with Perceval, postoperative thrombocytopenia does not impact on outcome in terms of transfusions, complications or hospital stay.

Parallel processing modeling in longitudinal designs: An example predicting trajectories of distress and life satisfaction.

Parallel process modeling (PPM) can be used to analyze co-occurring relationships between health and psychological variables over time. A demonstration is provided using data obtained from the British Household Panel Survey (years 2005, 2006, 2007, and 2008), examining predictors of ongoing changes in their distress and life satisfaction of a subsample from the survey. In the 2005 survey, data were available from 7,970 participants based on the following demographic variables: gender, age, ever registered as disabled, and ever experienced any strokes (before or at 2005). Time-varying variables included distress and life satisfaction collected yearly from 2005 to 2008. Time-invariant variables included age (65 or older), gender, disability condition, and stroke survivor status. Steps of fitting the PPM are presented. Four distinct distress trajectory groups-chronic, recovery, delayed, and resilient-were identified from the PPM estimates. Resilient and recovery groups showed a positive trend in life satisfaction. The delayed distress and chronic groups had a slight decrease in satisfaction. The time-invariant covariates only significantly predicted baseline levels of distress and satisfaction (i.e., their intercepts). PPM is a relatively simple and powerful tool for simultaneously studying relations between multiple processes. A step-by-step approach on decomposing the significant predictive relation from the change of distress to the change of satisfaction is presented. Properly decomposing any significant growth factor regressed on another growth factor is necessary to fully comprehend the intricate relationships within the results. Practical implications and additional methodological information about fitting PPM are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Financial access and income inequality in Sub-Saharan Africa: Does ethnic fragmentation give new evidence?

There is a large body of work documenting the non-consensual effects of financial access on income inequality. Despite this extensive literature and the predominance of ethnic fragmentation in Sub Saharan Africa countries (SSA), little is known about its mediating effect on the above relation. This paper focuses on assessing the effect of ethnic fragmentation on financial access income inequality nexus. Based on Kripfganz and Schwarz's (2019) dynamic panel estimator of time-invariant variables in a sample of thirty-seven (37) SSA countries over the period of 1990–2019, it is observed that ethnic fragmentation hinders financial access to reduce inequality in SSA. The results remain stable following several sensitivity tests related to corruption, urbanization, financial literacy and socio-geographic factors. They are also robust to the use of alternative measures of financial access and to change estimation technique.

Real-time dual prediction of intradialytic hypotension and hypertension using an explainable deep learning model

Both intradialytic hypotension (IDH) and hypertension (IDHTN) are associated with poor outcomes in hemodialysis patients, but a model predicting dual outcomes in real-time has never been developed. Herein, we developed an explainable deep learning model with a sequence-to-sequence-based attention network to predict both of these events simultaneously. We retrieved 302,774 hemodialysis sessions from the electronic health records of 11,110 patients, and these sessions were split into training (70%), validation (10%), and test (20%) datasets through patient randomization. The outcomes were defined when nadir systolic blood pressure (BP) < 90 mmHg (termed IDH-1), a decrease in systolic BP ≥ 20 mmHg and/or a decrease in mean arterial pressure ≥ 10 mmHg (termed IDH-2), or an increase in systolic BP ≥ 10 mmHg (i.e., IDHTN) occurred within 1 h. We developed a temporal fusion transformer (TFT)-based model and compared its performance in the test dataset, including receiver operating characteristic curve (AUROC) and area under the precision-recall curves (AUPRC), with those of other machine learning models, such as recurrent neural network, light gradient boosting machine, random forest, and logistic regression. Among all models, the TFT-based model achieved the highest AUROCs of 0.953 (0.952–0.954), 0.892 (0.891–0.893), and 0.889 (0.888–0.890) in predicting IDH-1, IDH-2, and IDHTN, respectively. The AUPRCs in the TFT-based model for these outcomes were higher than the other models. The factors that contributed the most to the prediction were age and previous session, which were time-invariant variables, as well as systolic BP and elapsed time, which were time-varying variables. The present TFT-based model predicts both IDH and IDHTN in real time and offers explainable variable importance.

The impacts of working from home on individual health and well-being

Using a novel German linked employer–employee dataset, we provide unique evidence about the consequences of working from home (WfH) on individual health and well-being. During the recent pandemic, this locational flexibility measure has been used extensively to promote health by hampering the spread of the virus and to secure jobs. However, its direct theoretical ambiguous effects on health and well-being as characterized by different potential channels have barely been empirically investigated to date despite WfH’s increasing popularity in the years before the pandemic. To address concerns about selection into WfH in our dataset that is unaffected by the COVID-19 shock, our analysis relies on an identification strategy ruling out confounding effects by time-invariant unobservable variables. Moreover, we explain the remaining (intertemporal) variation in the individual WfH status by means of an instrumental variable strategy using variation in equipment with mobile devices among establishments. We find that subjective measures of individual health are partly affected by WfH, whereas no corresponding effect is present for an objective measure of individual health. In terms of individual well-being, we find that WfH leads to considerable improvement. By addressing the potential heterogeneity in our effect of interest, we find that men and middle-aged individuals particularly benefit from WfH.

Regional Financial Performance and Inclusive Economic Development: Empirical Evidence From Provinces in Indonesia

This study aims to analyze the relationship between regional financial performance and inclusive economic development in Indonesia using secondary data from 34 provinces in Indonesia from 2011-2021. The data sources for this study were collected from the National Development Planning Agency, Directorate General of Fiscal Balance, and Statistics Indonesia. This study uses panel data regression analysis with a fixed effect model because it can reduce bias compared to other panel data models, especially those caused by unobservable time-invariant variables. The results showed that regional financial performance, as measured by the fiscal decentralization ratio, fiscal independence ratio, capital expenditure ratio, and social assistance expenditure ratio, significantly influenced inclusive economic development in Indonesia. Fiscal decentralization and social assistance spending have a positive relationship with inclusive economic development. Meanwhile, fiscal independence and capital expenditure have a negative relationship with inclusive economic growth.

Entrepreneurial ecosystems and regional persistence of high growth firms: A ‘broken clock’ critique

The Entrepreneurial Ecosystems (EE) approach makes specific predictions regarding how EE inputs are converted into high-growth firms (HGFs) as an output. A simulation model draws out our hypothesis of regional persistence in HGF shares. Based on intuitions that EEs are persistent, we investigate whether regional HGF shares are persistent, using census data for 2 European countries taken separately (Croatia for 2004–2019, and Slovenia for 2007–2019). Overall, there is no clear persistence in regional HGF shares – regions with large HGF shares in one period are not necessarily likely to have large HGF shares in the following period. This is a puzzle for EE theory. In fact, there seems to be more persistence in industry-level HGF shares than for regional HGF shares. We formulate a ‘broken clock’ critique – just as a broken clock is correct twice a day, EE recommendations may sometimes be correct, but are fundamentally flawed as long as time-changing outputs (HGF shares) are predicted using time-invariant variables (such as local universities, institutions, investments in R&D and infrastructure).

A Linear Mixed Model Approach for Determining the Effect of Financial Inclusion on Bank Stability: Comparative Empirical Evidence for Islamic and Conventional Banks in Kuwait

Recently, financial inclusion and bank stability have gained attention among researchers, particularly since the 2008 global financial crisis. This study investigates how financial inclusion may have influenced bank stability given differences in banks’ structure based on operating principles (Islamic and conventional banks) during the period of 2003–2017, using Kuwait as a high-income economy case. The current paper assesses how bank stability responds to financial inclusion. This work adopts a Linear Mixed Model (LMM), which tracks variables over time while considering other time-invariant variables. The findings show that the adopted measures of financial inclusion, access and depth, are both significant and negatively related to bank stability. Furthermore, the results unveil a slight difference between the response of Islamic and conventional banks’ stability to the dimensions of financial inclusion. Additionally, the study concludes that the financial crisis had an inverse and significant impact on bank stability. However, the extent of the impact appears to have been greater on Islamic banks compared to their conventional counterparts. Based on this study, banking with more financial inclusion can improve stability if institutional quality in Kuwait is improved so that these banks can operate more efficiently.

Relative deprivation, inequality and the Covid-19 pandemic

There is a growing concern that inequalities are hindering health outcomes. This paper's primary objective is to investigate the role of relative deprivation and inequality in explaining the daily spread of the Covid-19 pandemic. For this purpose, we use secondary cross-sectional data across 119 (developed and developing) countries from January 2020 – to April 2021. For the empirical analysis, we use a recent dynamic panel data modelling approach that allows us to identify the role of time-invariant variables such as degree of globalisation, political freedom and income inequality on the dynamics of the pandemic and fatality rates across countries. We find that new cases per million and fatality rates are highly persistent processes. After controlling for time-varying mobility statistics from the Google mobility database and region-specific dummy variables, the two significant factors that explain the severity of Covid-19 spread in a country are per-capita Gross Domestic Product (GDP) and Yitzhaki's relative income deprivation index. Lagged value of new cases per million significantly explains cross-country variations in the daily case fatality rates. A higher proportion of the older population and pollution increased fatality rates while better medical infrastructure reduced it.

Socioeconomic factors in the age-graded effect of incarceration on depressive symptoms in early adulthood

Based on insights from the stress process and life-course paradigms, this study investigates the effect of incarceration on depressive symptoms during early adulthood (ages 18–40). We employed fixed-effects dynamic panel models that adjust for confounding effects due to unobserved time-invariant variables and reverse causality using data from the National Longitudinal Study of Adolescent to Adult Health (N = 11, 811). Our analysis shows that the effect of incarceration on depressive symptoms is greater when incarceration occurs after individuals have established a stable adult status (ages 32–40) as compared to incarceration that occurs at earlier stages of adulthood (ages 18–24 and ages 25–31). The age-graded effect of incarceration on depressive symptoms is partially attributable to time-varying effects of incarceration on socioeconomic factors, such as employment status and income. All these findings contribute to our understanding of the mental health consequences of incarceration.

Social anhedonia affects the trajectory of internet addiction in the college students: A latent growth curve analysis

Background/AimThere is growing awareness that anhedonia plays a critical role in the development of Internet Addictions (IA). However, anhedonia is a multidimensional construct and different aspects of anhedonia may exert different effects on IA. This study was designed to distinguish the effects of social anhedonia and physical anhedonia on the developmental trajectory of IA among college students. MethodsA total of 3577 Chinese college freshmen (Mage = 18.01, SD = 0.77; 65.4 % girls) participated in a 2-year, four waves longitudinal tracking study. The latent growth curve model (LGCM) was constructed to examine the impacts of different types of anhedonia on the developmental trajectories of IA. Gender was also added to the conditional LGCM as time-invariant variable. ResultsThe results of unconditional LGCM showed a U-shape developmental trajectory of IA. Social anhedonia significantly affected the intercept (β = 0.468, p < 0.001) and significantly affected the linear slope (β = −0.259, p < 0.05), but not the quadratic slope (β = 0.293, p > 0.05). Physical anhedonia was not significantly associated with intercept, linear slope and quadratic slope. There was no sex difference in both initial levels and change rate of IA. ConclusionsSocial anhedonia while not physical anhedonia has prediction effect on IA. College students with high levels of social anhedonia experienced high levels of IA at baseline, and performed a slower rate in downward trend of IA. The findings of the current study provide implications for prevention of IA in college students.

Import Determinants and Potential Markets of Pakistan: An Application of PPML Gravity Model

Abstract The present study examines import determinants of Pakistan with the top 28 trade partners from 2002 to 2018. To achieve this objective, the augmented gravity model of trade has been applied by incorporating both time-variant and time-invariant variables. In addition, the analysis quantifies the impact of free trade agreements (FTA) signed by Pakistan with China and other trade partners. The results show that along with income and distance, FTA, common language, and common border plays an essential role in imports of Pakistan with its main trade partners. In addition to identifying trade determinants, the impact of adherence to a particular trade agreement was also examined. The results indicate that FTA signed by Pakistan with China and other trade partners has created trade opportunities for participating countries, highlighting the importance of trade liberalization for the long-run development of the country.

SHORT-TERM COUPLED ASSOCIATION BETWEEN BLOOD PRESSURE AND COGNITIVE FUNCTIONING

Abstract An extensive body of research has investigated the association between cognition and blood pressure (BP). Limited research, however, has examined the association at the daily within-person level. No study has yet applied an intensive measurement design utilizing the convenience and objectivity of mobile devices for cognitive assessments and automated BP monitors. To address this gap in the literature, we recruited community-residing healthy adults (N=64; Mage=70.6, SD=3.5; 76.6% female), who recorded their BP and completed a battery of brief cognitive tasks twice daily for 14 days. Multi-level models estimated associations between systolic/diastolic BP (sBP/dBP) and cognitive functioning, adjusting for time-varying self-reported effort, stressors, and physical activity, as well as time-invariant variables (age, sex, education, and anti-hypertensive medication). At the interindividual level, results suggest that individuals with higher overall sBP and dBP relative to others performed worse on delayed-reproduction and visual short-term memory tasks. At the intraindividual level, on occasions when individuals had higher sBP compared to their personal average, they performed relatively worse on delayed-reproduction tasks. Mean sBP was also significant within these models, suggesting that this coupled relationship is stronger for individuals with higher sBP on average. Analyses did not indicate significant associations for working memory, reaction time, or cognitive interference assessments, which may have been due to relatively limited power for between-person analyses. Use of such digital health technology is critical for detecting the complex nature of and interplay between physiological and cognitive processes. Further, research based on intraindividual associations may contribute to strategies aiming to promote lifestyle modifications.

The impact of board gender diversity on the financing costs of microfinance institutions: a global evidence

Purpose Considering the existing evidence on the impact of female board members on the default risks of an organization, the purpose of this study is to investigate the effect of board gender diversity, alongside institutional characteristics and macroeconomic factors, on the financing costs of microfinance institutions (MFIs). Design methodology approach This study collected unbalanced panel data of 1,190 unique MFIs between 2010 and 2018 from the World Bank. The collected data, which covers a total of 95 developing and emerging countries, was thereafter analyzed using the pooled ordinary least squares and random effects model. To overcome endogeneity and omitted variable bias (e.g. time-invariant variables), the authors have also used the generalized method of moments and fixed effects model, respectively. Different proxies of board gender diversity and sub-sample analysis by regions were further undertaken to examine the robustness of the obtained results. Findings The findings of this study revealed that board gender diversity has a statistically significant negative effect on the financing costs of MFIs. This suggests that a gender-diverse board can generate cheaper funding for MFIs by minimizing their default risks through effective monitoring and strategic management. Furthermore, the negative impact of board gender diversity on financing costs appears to be more pronounced when there is a minimum of two female board members in the boardroom of MFIs. The results of this study remain consistent and valid regardless of alternate model specifications (e.g. sub-sample analysis, use of alternative proxies of board gender diversity and application of different estimators) and endogeneity issues. Ultimately, the findings in this study reiterate the importance of promoting and implementing gender diversity in the boardroom to minimize the financing costs of MFIs. Originality value This study investigated the relationship between board gender diversity and financing costs of MFIs by using relatively recent and global data. The minimum number of female board members required to significantly reduce the financing costs of MFIs was also identified.

Impact of regional trade agreements on bilateral trade flows: A Systemic Literature Review

This paper reviews the theoretical and empirical literature on the impact of regional trade agreements on trade. The empirical literature is arranged based on the econometricmethods used to estimate the gravity model. Advantages and disadvantages of each method were highlighted. Papers covering RTAs from Africa, Asia, the Americas, and Europe were reviewed to gain a more representative understanding. The covered empirical literature suggests that the Poisson Pseudo Maximum Likelihood (PPML) estimator is more reliable than OLS in estimating gravity models, as it can deal with zero trade flows. The Fixed Effects (FE) approach produces more consistent estimates than the Random Effects (RE) approach when quantifying the effects of RTAs. This is because it allows one to control for the unobserved time-invariant variables. Surprisingly, the covered literature suggests that a great majority of African RTAs generated trade, regardless of the method of estimation used. Journal of Economic Literature (JEL) codes: F13, F15

Simulation of the dynamic behavior of viscoelastic structures with random material parameters using time-separated stochastic mechanics

Modeling and simulation of materials with stochastic properties is typically computationally expensive, especially for nonlinear materials or dynamic simulations. Time-separated stochastic mechanics (TSM) is a technique to efficiently compute the stochastic characteristics of stress and reaction force of materials. It has successfully been used for viscoelastic materials with random homogenized Young’s modulus. The method is based on a decomposition of time-invariant random variables and time-dependent but deterministic variables for the strain response at the material point. In this work, the TSM is extended for the dynamic analysis of stochastic viscoelastic materials. It is showcased that the TSM can efficiently approximate the expectation and variance of the reaction force and the stress for the dynamic simulation of a viscoelastic nonlinear material. Furthermore, generalized equations of the TSM are presented that increase the accuracy and allow for accounting of larger fluctuations of the material parameters. Transient time-domain simulations are performed for different boundary value problems and compared to Monte Carlo simulations to demonstrate the accuracy and computational efficiency of the method.