Cross-sectional Time Series Research Articles

Varying effects of public pensions: Pension spending and old-age employment under different pension regimes

Socioeconomic consequences of pension reforms have often been discussed without careful consideration of institutional contexts, despite the fact that institutional designs of public pensions differ substantially across countries. This study argues that the outcomes of pension reforms vary depending on the institutional structure of public pensions, by showing that the associations between public pension spending and old-age employment rates of different socio-demographic groups vary across different institutional contexts. Using time-series cross-section data from 20 European countries and the United States from 1998 to 2019, the study examines how changes in public pension spending ‘per older person’, a comparable measure for the welfare state effort towards old-age income security, are associated with gender- and education-specific employment rates in old age. The study also explores how these associations differ under different pension regimes, constructed based on the degree to which financing and benefit structures exhibit redistributive orientations. The results reveal complex gender and educational gradients in the relationship between public pension spending and old-age employment. Female employment rates, especially among the low-educated, are more sensitive to changes in pension spending in the ‘Beveridgean’ regime that focuses on basic income security. In the Bismarckian regime characterized by earnings-related pensions, educational differences in the marginal effects on male employment rates are, in particular, larger. Future pension reforms balancing the goal of activation and social equity should therefore consider the longstanding institutional design of public pensions.

Firm Attributes and Corporate Financial Distress of Listed Manufacturing Firms at The Nigeria Exchange Group

This study investigated the effect of firm attributes on corporate financial distress of listed manufacturing firms in Nigeria. The specific objectives of this study was to investigate the relationship between six dimensions of firm characteristics (profitability, financial leverage, tangibility, liquidity, operating capacity and firms size) and corporate financial distress of manufacturing firms in Nigeria. Ex-post facto research design and a cross sectional time series secondary data covering the period of one hundred and fifty observations (2018-2022) was extracted from the audited financial statement of thrifty (30) manufacturing firms listed on the floor of Nigerian exchange group. The data collected was analysed using descriptive statistics, correlation analysis and Generalized Method of Moments (GMM) of regression analysis. The result from the regression analysis indicated that profitability does positively and significantly affect corporate financial distress; financial leverage does negatively and significantly affect corporate financial distress; tangibility does positively and insignificantly affect corporate financial distress; liquidity does positively and insignificantly affect corporate financial distress; firm size does positively and insignificantly affect corporate financial distress and operating capacity does positively and insignificantly affect corporate financial distress of listed manufacturing firms in Nigeria. Based on the findings, the study generally concluded that firm attributes impact on corporate financial distress of listed manufacturing firms in Nigeria. Hence, it was suggested that corporate managers need to determine and maintain the appropriate level of profitability to ensure smooth operation and continual survival of the organization in term of short run but should be careful in evaluating the long term profitability.

Các nhân tố ảnh hưởng đến công bố báo cáo bền vững của các doanh nghiệp phi tài chính niêm yết trên thị trường chứng khoán Việt Nam

A sustainability report is considered a tool that can help enterprises measure, disclose, explain, and commit responsibility for sustainable development to stakeholders. This article uses panels data, cross sectional data and time series data, figures out factors which affect the disclosure of the 253 non-financial enterprises listed on Vietnam stock market in the period 2020-2022. It also finds out 2 new ones called audited by BIG 4 and listing time apart from 4 factors: profitability, firm size, the frequency of the Audit committee, gender of leader; listing time is the only one to have a negative impact on the publication of this report. Research result is a base to consider improving legal regulations of the disclosure of sustainability reports, related parties to help stakeholders make the right decisions

Understanding the Impact of Demographic Factors and Education Policy on Enrollment Trends: A Study in China

This study addresses the complex interplay between demographic factors and educational enrollment trends in China, with a focus on understanding how population dynamics and education policies influence enrollment patterns. Utilizing a cross-sectional design and time series data from 2010 to 2020, the research examines the effects of population size, structure, distribution, and birth rate on enrollment trends, moderated by education policy assessments. The findings reveal significant correlations between demographic factors and enrollment trends. Specifically, as population size increases, enrollment tends to decrease, while decreasing birth rates are associated with increased enrollment. Urban areas show higher enrollment rates compared to rural areas, reflecting disparities in access to educational resources. However, the study finds mixed evidence regarding the influence of population average age on enrollment trends. Moreover, the research investigates the moderating effect of education policy assessments on demographic factors. While education policies have a positive moderation effect on population size and birth rate, the study suggests limited impact on the relationship between population average age and enrollment trends. This study provides valuable insights for educational planning and policy development, emphasizing the need for strategic adjustments to accommodate changing population dynamics and ensure continued access to quality education. Additionally, the predictive model developed in this study offers a practical tool for understanding enrollment patterns and guiding policy decisions in the educational sector. However, the study acknowledges limitations related to generalizability and the complexity of external factors influencing enrollment trends, highlighting avenues for future research to enhance the predictive model and deepen understanding of enrollment dynamics.

Allies and diffusion of state military cybercapacity

Understanding the diffusion of military capabilities is a central issue in international relations. Despite this, only a few works attempt to explain this phenomenon, focusing on threats. This article explains why threats alone cannot account for cybercapacity-development diffusion and introduces a more consistent explanation: the role of alliances. Allies with cybercapacity help partner-countries without cybercapacity start developing their own capacity to increase the alliance’s overall security by reducing mutual vulnerabilities in cyberspace. Partner-countries that lack cybercapacity are eager to accept this option because it is more favorable than developing cybercapacity on their own. Partner-countries may also start investing in cybersecurity to reduce the likelihood of being abandoned in other, conventional, domains. My new cross-sectional time-series dataset on indicators of a state’s cybercapacity-development initiation for 2000–18 provides robust empirical support for this argument and offers important implications for scholarship on arms, allies, and diffusion.

Government Expenditure and Economic Growth: A Cross-Country Analysis

This paper empirically analyses the relationship between Economic Growth measured in terms of GDP Growth and Government Expenditure, GDP and Population. It employs annual cross-section time series data of the concerned variable of 117 countries from 2001 to 2021. Random Effect model was used for the analysis. The pool-ability of data is tested by the Breusch and Pagan LM test which confirmed that Pooled OLS is not appropriate for the model. The Hausman Specification Test was then conducted for choosing between the Fixed Effect or Random Effect model. The Hausman Specification Test for the Model suggests the Random effect model is appropriate for the analysis of the data. Thus, Random effect regression is used to find the consequences of explanatory and the control variables on the dependent variable. Government Expenditure as an explanatory variable has a positive relationship with the Economic Growth, even in the case of controlling for Population and the Trade Openness. Both the control variable is depicted to have positive relationship with the Economic Growth.

Fiscal Moderating Effect for Sustaining the Upstream Petroleum Field Economics and Profitability: Inventory and Purchasing Performance

Introduction: The study literature's obvious limits with a complete fiscal term model for moderating variables are crucial to our investigation. In order to preserve petroleum field economics and profitability in Indonesia's petroleum business context, this study examines the relationship between material inventory performance, purchasing performance, and fiscal term moderating influence with an agglomeration approach. Theoretical Framework: Industry character strongly influences the inventory and purchasing performance relationship (Basu & Wang, 2011); Hofer et al., 2012); (Priniotakis & Argyropoulos, 2018). Despite circumstances and fiscal terms that were not adaptive to environmental dynamism (Acquah-Andoh et al., 2019), Production Sharing Contract (PSC) Contractors' upstream field economics deteriorated compared to the initial (Paramita, 2022). Financial term in fossil sector draws investors, ensuring fair economic performance and cost balance (Mardiana et al., 2019; Yun et al., 2020). Methodology: Cross-sectional time series data were collected over five years from 26 Production Sharing Contract (PSC) Contractors from Indonesia's upstream oil industry in the preliminary Plan of Development (POD) phase. Econometric analysis using multivariate structural equation modeling will test the model. Results and Discussions: The results showed that different financial performance agglomerations showed an inconsistent relationship between inventory performance, petroleum field economics, and profitability, but purchasing performance showed a positive relationship in any scheme, and fiscal terms significantly strengthened the relationship between variables. Conclusion: This study sheds light on whether fiscal term strengthening variables in the upstream petroleum company affect decision-making.

Surveillance of Infant Formula Shortages Using Special Supplemental Nutrition Program for Women, Infants, and Children Administrative Data

ObjectiveTo quantify self-reported difficulty accessing Special Supplemental Nutrition Program for Women, Infants, and Children (WIC)-issued infant formula among participants early in the coronavirus disease 2019 (COVID-19) pandemic, to determine if infant formula redemption was associated with self-reported difficulty accessing infant formula, and to quantify changes in formula redemption during the 2022–2023 US infant formula shortages. DesignA cross-sectional study and time series data. SettingFamilies participating in the WIC program in the Los Angeles metropolitan area from November 2019 to June 2023. ParticipantsFamilies with infants (aged 0–12 months) issued infant formula by WIC with a completed 2020 Los Angeles County WIC Survey (n = 1,897) or issued infant formula by a large WIC program in Southern California between November 2019 and June 2023 (n = 109,135). Main Outcome MeasuresIncidence of ≥ 30% reduction in infant formula redemption and interval-scaled infant formula redemption. AnalysisSpecial Supplemental Nutrition Program for Women, Infants, and Children formula redemption data were matched to 2020 Los Angeles County WIC Survey data to determine if self-reported difficulty accessing infant formula was associated with administrative infant formula redemption data using negative binomial regression and were used to quantify the prevalence and severity of incomplete formula redemption during 2020–2023 formula shortages using ordinal logistic regression (outcome: interval-scaled formula redemption). ResultsFew (13.0%) caregivers reported difficulty accessing the WIC-issued formula early in the COVID-19 pandemic. The 2.8% who reported an unresolved shortage early in the COVID-19 pandemic had 201% higher rates of ≥ 30% declines in formula redemption (incidence rate ratio [IRR], 3.01; 95% confidence interval, 1.57–5.79, P < 0.001) than those with no difficulties. Incomplete formula redemption odds were significantly elevated throughout the COVID-19 pandemic from March 2020 to January 2022 and increased further during the 2022–2023 infant formula shortages from February 2022 to June 2023, reaching 342% higher in October 2022 than February 2020 (odds ratio, 4.42; 95% confidence interval, 4.14–4.72; P < 0.001). Conclusions and ImplicationsSpecial Supplemental Nutrition Program for Women, Infants, and Children redemption data are an adequate proxy for population-level infant formula access issues among households with low income but are insufficiently sensitive for screening at a household level. US formula shortages (2020–2023) demonstrate the need for improved coordination between nutrition assistance programs, regulatory bodies, and commercial food systems, particularly during acute supply crises.

A practical utility-based but objective approach to model selection for regression in scientific applications

In many fields of science, various types of models are available to describe phenomena, observations and the results of experiments. In the last decades, given the enormous advances of information gathering technologies, also machine learning techniques have been systematically deployed to extract models from the large available databases. However, regardless of their origins, no universal criterion has been found so far to select the most appropriate model given the data. A unique solution is probably a chimera, particularly in applications involving complex systems. Consequently, in this work a utility-based approach is advocated. However, the solutions proposed are not purely subjective but all based on “objective” criteria, rooted in the properties of the data, to preserve generality and to allow comparative assessments of the results. Several methods have been developed and tested, to improve the discrimination capability of basic Bayesian and information theoretic criteria, with particular attention to the BIC (Bayesian Information Criterion) and AIC (Akaike Information Criterion) indicators. Both the quality of the fits and the evaluation of model complexity are aspects addressed by the advances proposed. The competitive advantages of the individual alternatives, for both cross sectional data and time series, are clearly identified, together with their most appropriate fields of application. The proposed improvements of the criteria allow selecting the right models more reliably, more efficiently in terms of data requirements and can be adjusted to very different circumstances and applications. Particular attention has been paid to ensure that the developed versions of the indicators are easy to implement in practice, in both confirmatory and exploratory settings. Extensive numerical tests have been performed to support the conceptual and theoretical considerations.

Infant feeding practices in three Latin American countries in three decades: what demographic, health, and economic factors are relevant?

Studies in Latin America have focused either on analyzing factors associated with exclusive breastfeeding (EBF) or infant formula (IF). Analyze the association between economic, sociodemographic, and health factors with EBF, mixed milk feeding (MixMF), and exclusive use of IF in three Latin American and Caribbean countries in the 1990s, 2000s, and 2010s. Cross-sectional time-series study using data from Demographic and Health Surveys between the 1990s and 2010s in Colombia (1995-2010), Haiti (1994-2017), and Peru (1996-2012) accounting for a sample of 12,775 infants under 6 months. Hierarchical logistic multilevel regression models were used to estimate the adjusted association between infant feeding outcomes (EBF, MixMF, exclusive use of IF) and contextual level DHS survey decade (1990s, 2000s and 2010s) and economic factors (Gross Domestic Product by purchasing power parity, female wage and salaried workers, labor force participation rate female) as well as individual level sociodemographic (maternal age, maternal education, number of children in the household, wealth index, mother living with a partner, area of residence, mother working outside of home), and health factors (breastfed in the first hour, C-section). Factors associated with EBF cessation were c-section (OR: 0.76; 95%CI: 0.64, 0.92), mothers working outside of the home (OR: 0.79; 95%CI: 0.69, 0.90), families in the highest income quintile (OR: 0.64; 95%CI: 0.49, 0.84), and female wage and salaried workers (OR: 0.92; 95%CI: 0.91, 0.94). MixMF was associated with women with higher education (OR: 1.54; 95%CI: 1.21, 1.97), mother working outside of the home (OR: 1.26; 95%CI: 1.10, 1.43), c-section (OR: 1.37; 95%CI: 1.15, 1.62), families in the highest income quintiles (OR: 2.77; 2.10, 3.65). and female wage and salaried workers (OR: 1.08;95% CI: 1.05, 1.09). Exclusive use of IF was associated with a mother working outside of the home (OR: 2.09; 95%CI: 1.41, 3.08), c-section (OR: 1.65; 95%CI: 1.09, 2.51), families in the highest income quintiles (OR: 12.08; 95% CI: 4.26, 34.28), the 2010s (OR: 3.81; 95%CI: 1.86, 7.79), and female wage and salaried workers (OR: 1.12; 95%CI: 1.07, 1.16). Factors related to women empowerment and gender equality jeopardized EBF and favored the exclusive use of IF in Latin America. Therefore, workplace interventions to promote, protect, and support breastfeeding practices are key to reducing exclusive use of IF.

Cross-sectional study of rapid tapering of opioid prescriptions following medical regulatory intervention in Alberta from 2013 to 2020

ObjectiveTo determine if inappropriate tapering/discontinuation of opioids to Alberta patients occurred from mid-2013–2020, as unintended consequences of prescribing guidelines, regulations and policies in response to the North American opioid crisis.DesignA...

POVERTY PANEL DATA MODELING IN SOUTH SUMATERA

Poverty is still a major problem on Sumatra's island, despite abundant natural resources potential, such as mining and plantation products. Sumatra Island consists of 10 provinces divided into three regions: Northern Sumatra, Central Sumatra, and Southern Sumatra. The island of Sumatra has the highest number of poor people in the Southern Sumatra region, which reaches 2.88 million people. Poverty is an integrated concept with five dimensions: poverty, powerlessness, vulnerability to emergencies, dependency, and alienation, both geographically and sociologically. One method that can be used to analyze poverty data problems is panel data regression analysis, which combines two data, namely cross-sectional data and time series data. It is expected to produce more in-depth and comprehensive information, both the interrelationships between the variables and their development within a certain period. The panel data was related to poverty and included 60 districts in the southern Sumatra region from 2018 to 2020. This study aimed to model poverty panel data in Southern Sumatra. Three estimation methods were used in the panel data regression, including the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM. The results of the model specification test show that the best model for estimating the percentage of poor people in the Southern Sumatra region is the Fixed Effect Model (FEM), with a value of R2 = 75.57%. The results of the significance test show that the variables that significantly influence the percentage of poverty in the Southern Sumatra region using the FEM model are the open unemployment rate (), life expectancy (), and the average length of schooling ().

Cheap on Punishment: Examining the Impact of Prison Population Racial Demographics on State-Level Corrections Spending

Research has explored the effects of various state-level characteristics, such as racial composition and economic conditions, on correctional budgetary decisions. However, researchers have yet to consider how the racial makeup of state prison populations themselves may impact subsequent corrections spending decisions. Drawing on work suggesting that people of color are simultaneously over-punished and neglected by criminal justice systems, and utilizing a time-series cross-section analysis of 50 states from 1979 through 2017, we explore differences in state budgetary allocations for correctional expenditures based on the racial demographics of prison populations. We find that the relationship between the Black-to-White incarceration ratio and spending on corrections is curvilinear: once a tipping point of Black-to-White incarceration is reached, spending on corrections decreases. This finding is especially pronounced in Southern and Midwestern states. Overall, our results provide a strong starting point for understanding the ways in which Black Americans are neglected in the incarceration setting.

Provision of evaluation and management visits by nurse practitioners and physician assistants in the USA from 2013 to 2019: cross-sectional time series study

ObjectiveTo examine the proportion of healthcare visits are delivered by nurse practitioners and physician assistants versus physicians and how this has changed over time and by clinical setting, diagnosis, and...

Factor price convergence in OECD economies: the case of three profit rates indicators

Abstract This paper examines profit rate (rates of return to capital) convergence in OECD economies in the periods of 1960-2016 and relevant sub-periods. It also performs comparison of profit rates convergence in selected developed and developing economies, using the data for 1973-2003 period. Economy-wide, productive economy and manufacturing rates are estimated and three convergence concepts are considered (beta, sigma, and stochastic convergence). We use a combination of cross-sectional and univariate time series models and density distribution analysis. For each profit rate measure, a strong evidence of beta convergence is provided. In contrast, sigma convergence is indicated only in the case of productive economy profit rate; while in other cases, sigma divergence or the absence of either convergence or divergence are likely. Stochastic convergence is present in a smaller number of economies and is confined to productive economy and manufacturing. The comparison of convergence dynamics in developed versus developing economies confirmed beta convergence in both groups and for their aggregate, but did not establish sigma convergence, given the significant diversity of economies and their different economic trajectories.

Environmental consequences of geopolitical crises: The case of economic sanctions and emissions

Geopolitical crises, and economic sanctions, in particular, have created considerable disturbance in natural resource markets. This study focuses on a significant consequence of this disturbance, namely how sanctions may derail targeted states from their low-carbon pathways. Increasing capital costs and difficulties in accessing technology force sanctioned states to move away from capital- and technology-intensive greener alternatives to employ more carbon-intensive (predominantly coal) generation modes in their primary energy supply. We also show that the recovery process from sanctions further increases coal use in these targeted states. Our econometric results from a global cross-sectional time-series dataset support our expectations. Our findings call for a deeper understanding of the challenges in achieving sustainable recovery in the aftermath of geopolitical crises. These results call for assessing carbon-footprint implications of specific foreign policy actions before these actions are carried out.

Determinant Factors Of Profitability Of Islamic Banks In 2017-2021 With Capital Adequacy Ratio As a Variable Intervening

This study aims to analyze the effect of Non Performing Financing (NPF) and Finance to Deposit Ratio (FDR) on Islamic bank profitability mediated by Capital Adequacy Ratio (CAR). This study uses secondary data in the form of panel data (pooled data), which is a combination of cross section data and time series data. The analysis technique uses path analysis. The results showed that FDR has no influence on CAR while NPF affects the CAR of Islamic banks. FDR and NPF directly have no influence on the ROA of Islamic banks. CAR variable is only able to be intervening between NPF and ROA while FDR variable indirectly through CAR variable has no significant effect on ROA of Islamic banks.

Gauging Bankruptcy using Altman’s Z-Score Empirical Investigation from the Pharmaceutical Sector

This study aims to construct timely responses to escape financial distress and further losses and prevent financial crises. The main focus of the research is to present the analysis of financial distress on the performance of the five firms listed on the Pakistan Stock Exchange under the Pharmaceutical sector within ten years. If financial distress is not identified in time and inappropriate measures are taken, insolvency (bankruptcy) is likely to occur. This study sought to test the validity of Altman’s Z-score and its effectiveness in identifying the financial distress on the performance of firms in the pharmaceutical sector. The sample size consists of cross-sectional time series annual data of five pharmaceutical companies listed on the Pakistan Stock Exchange (PSX). The data set has been tracked for ten years, from 2006 to 2016. The analytical model (Z-score) developed by Edward Altman is used in this study as the statistical technique. The results concluded that Abbot, Glaxo and Wyeth generally experienced stability and incline in the Z-Score values throughout the years. These companies have been fit into non-financial distress. On the other hand, Ferozsons and Highnoon have been in between a range of grey areas. The companies had a probability of experiencing the problems of financial distress. Consequently, companies have started to reach their peak and fit into non-financial distress.

Trends in Alcohol-Related Deaths by Sex in the US, 1999-2020

Alcohol consumption rates have been increasing among women in the US, which may affect mortality rates and sex gaps. Therefore, conducting a comprehensive assessment of sex differences in alcohol-related deaths is essential to inform targeted interventions and policies aimed at reducing the burden of alcohol-related harm among the population. To examine sex differences in the burden and trends of alcohol-related mortality in the US from 1999 to 2020. This cross-sectional time series study used Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research data on alcohol-related deaths from 1999 to 2020. Alcohol-related deaths were identified from the underlying cause of death files using International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, codes, including alcohol-related poisoning, liver disease, gastritis, cardiomyopathy, myopathy, polyneuropathy, and pseudo-Cushing syndrome, among others. Age-adjusted mortality rates (AAMRs) were analyzed by sex and substratified by race and ethnicity, age, and census region. Rate ratios and 95% CIs calculated by Taylor series were used to assess sex differences in mortality burden. Joinpoint regression was used to assess temporal trends. A total of 605 948 alcohol-attributed deaths were identified in the US from 1999 through 2020 (AAMR, 8.3 per 100 000 persons; 95% CI, 8.3-8.3 per 100 000 persons). The mortality burden was higher among male individuals than female individuals, with male individuals being 2.88 (95% CI, 2.86-2.89) times more likely to die compared with female individuals. However, temporal trends showed an increase in alcohol-related deaths for both male and female individuals in recent years, with higher rates of increase among female individuals relative to male individuals. The AAMR increased by 12.5% (95% CI, 6.4%-19.1%) per year among male individuals from 2018 to 2020 but increased by 14.7% (95% CI, 9.1%-20.5%) per year among female individuals during the same period. Trend differences were observed across subtypes of age, race and ethnicity, cause, and region. This study of alcohol-related mortality in the US suggests there has been a significantly higher rate of increase in deaths among female individuals in recent years. These findings underscore the need for further research to understand the specific factors associated with this trend. The development of targeted interventions and evidence-based treatments for alcohol use among female individuals becomes imperative in effectively addressing the increasing rates of alcohol-related deaths.

Does internet technology usage improve food production? Recent evidence from major rice-producing provinces of China

ICTs play an increasingly crucial role in ensuring food security and sustainable agricultural production, particularly in emerging economies. The majority of survey-based literature focuses on Internet use and farmers' income, technical efficiency of agricultural production, the economic well-being of smallholder farmers, and market information, respectively. The present study, on the other hand, investigates explicitly the long-term effects of Internet use on rice production using panel data from the main rice-producing provinces of China for the period 2011–2020. Other key factors of rice production included in this study are chemical fertilizer, sown area, power consumption, public spending, and labour force. Using the cross-sectional time-series FGLS approach to control endogeneity issues, the results show that Internet use improves rice production in the long run, while the remaining determinants (chemical fertilizer, sown area, power consumption, and public spending) stimulate rice production in the long run. The D-K-SE and MMQR approaches confirm the substantial impact of important factors of rice production. Policymakers should improve Internet access and encourage the use of modern techniques to increase rice output in China.