One major worry is the rise in unemployment and the decline in per capita income that often accompanies population growth. From this background, this study explores how population growth and investment trends are evolving in Nigeria in relations to various forms of investment public, private, household, and foreign and how they respond to population changes. Using Vector Auto Regression analysis, the study found that, in the short term, increases in population actually reduce foreign and public investments in Nigeria. However, while there seems to be a positive link between population growth and investment in the long run, there should caution approach to this conclusion with caution. Thus, it’s essential that policies are tailored specifically for Nigeria to create a supportive investment environment, especially given that the population is expected to double by 2036, potentially making up 20% of the world's population by 2050, according to the United Nations.

The economic impact of oil recovery and the strength of the Government of Nigeria as measured by the Institutional Quality Index with the impact of Oil Recovery has been examined by this study using a time series Vector Autoregressive Analysis. The findings show that oil recovery does not have a strong direct impact on the output of the Naira, while prior months and year’s OILREC (-1) and OILREC (-2) have small negative but insignificant coefficients (t=-0.79855 and - 0.72389). The OILREC_INSTQUAL (-1) and OILREC_INSTQUAL (-2) (the moderating terms) also have weak effects and are insignificant (t = -0.81896 and -0.94191) indicating that despite strong institutions, the economy has not been able to fully capitalize on the economic impact of oil recovery. Therefore, the findings of this study suggest that higher institutional strength will significantly increase the benefits of oil recovery on the economy of Nigeria.

Guided by steeling and hormesis models, this paper examined parenting adversity as a quadratic predictor of children's emotion knowledge and effortful control and, in turn, their internalizing and externalizing symptoms. Participants were 238 mothers, partners, and their preschool children (Mage = 4.38 years; 52% female). Multiple methods (i.e., observations, interviews, surveys, q-sorts) and informants (i.e., trained observers, experimenters, mothers, children, teachers) were used in a longitudinal design with three annual measurement occasions. Supporting the first link in the mediational cascade, lagged, autoregressive analyses indicated that a quadratic composite of parenting adversity derived from trained observer ratings of parenting at Wave 1 was a significant predictor of children's emotion knowledge and effortful control at Wave 2. In the second part of the proposed cascade, children's Wave 2 emotion knowledge predicted lower levels of their Wave 3 internalizing symptoms, while their Wave 2 effortful control predicted lower levels of their Wave 3 externalizing symptoms. Consistent with steeling effects, curvilinear findings in the first part of the cascade indicated that moderate levels of exposure to parenting adversity predicted the highest levels of children's subsequent emotion knowledge and effortful control. Children also exhibited substantially diminished emotion knowledge and effortful control as their exposure to family adversity increased from moderate to high levels.

While research has demonstrated the importance of parental autonomy support and psychological control for children’s adjustment, their implications of such parenting practices for children’s subjective feelings of autonomy remain less well understood. Focusing on American and Chinese adolescents, the current research examined the longitudinal associations between parenting and adolescents’ feelings of autonomy, with attention to adolescents’ endorsement of parent-oriented reasons for doing well in school as a possible underlying mechanism. At three time points over 1.5 years, American ( n = 332) and Hong Kong Chinese ( n = 235) adolescents reported on their parents’ use of autonomy-supportive and psychological controlling parenting practices, their reasons for doing well in school, and their feelings of autonomy. Autoregressive path analyses were conducted to examine longitudinal associations and test for indirect effects. Results revealed that, in both the American and Chinese samples, parental autonomy support predicted increases in adolescents’ feelings of autonomy, whereas psychological control predicted decreases. In the Chinese sample only, autonomy support also predicted a greater endorsement of parent-oriented reasons for doing well in school, which, in turn, was associated with reduced feelings of autonomy over time. Findings highlight both the universal and culture-specific pathways through which parenting practices shape adolescents’ autonomy development. While autonomy support fosters a sense of volition across cultures, its motivational significance may vary depending on cultural norms and the extent to which adolescents internalize parental expectations.

Saving is a crucial step towards investing. Several factors influence the decision to save, including religion, economic conditions, cultural attitudes and the interest rate on savings accounts. This study investigates low savings rates in West Africa and tries to find out whether higher interest rate would stimulate regional saving. The lack of empirical understanding of how interest rate affects saving behaviour challenges economic development. Using the lifecycle hypothesis, the study analysed savings as a function of a deposit interest rate, per capita income and the inflation rate through panel autoregressive distributed lag analysis. The findings show that deposit interest rate does not significantly impact savings in the region, in contrast to per capita income and inflation. The conclusion of the study is that the relationship between interest rates and savings is complex and influenced by multiple factors other than the deposit interest rate. The study suggests implementing policies that promote long-term investment strategies beyond relying on interest rates, which helps balance immediate investments with savings and encourages firms to set aside funds for future use.

ResumenIntroducción. El informe Lancet Countdown 2023 para Latinoamérica indica que el aumento de las temperaturas influye en la transmisión del virus del dengue. En la región Caribe de Colombia, se ha identificado una asociación significativa entre la incidencia de dengue y variables climáticas, como la temperatura, la humedad y la precipitación.Objetivo. Analizar la relación entre la tasa de incidencia de dengue y el índice oceánico de El Niño en los departamentos de la región Caribe colombiana entre el 2021 y el 2023.Materiales y métodos. Se llevó a cabo un estudio ecológico de serie de tiempo, utilizando modelos de regresión no lineal con desfase y modelos autorregresivos integrados de media móvil en los siete departamentos de la región Caribe. Para los análisis descriptivos y los modelos autorregresivos, se emplearon los programas JASP y RStudio. Para los análisis no lineales y con desfase, se usó el paquete dlnm de RStudio.Resultados. Se encontró una relación positiva y significativa entre el índice oceánico de El Niño y la tasa de incidencia de dengue en el 2023, año en el que se presentó el fenómeno de El Niño. Los departamentos de Bolívar, Cesar, Córdoba y Magdalena tuvieron correlaciones positivas. También, se observó una relación no lineal entre El Niño o La Niña y la incidencia de dengue, con un mayor impacto durante la fase de El Niño.Conclusiones. El índice oceánico de El Niño se presenta como un indicador climático útil para monitorear el aumento de casos de dengue en los departamentos analizados de la región Caribe colombiana.

The relevance of the study is due to both the high degree of importance of energy for the economic development of Russia and the insufficient use of econometric models in modern energy research. The purpose of the study is to develop and propose an econometric model of the country’s fuel and energy resources. In line with this objective, the research provides a detailed examination of the methodological framework and key stages involved in developing an econometric model using autoregressive analysis for the purpose of studying the Russian energy sector. This is both the scientific and applied, as well as the scientific and methodological significance of the presented publication. To achieve this goal, statistical materials from Rostat “Consumption of fuel and energy resources per person employed in the country’s economy” have been used since 2012. Econometric analysis and statistics are used as a methodology, in particular, an autoregressive analysis model is used. The methodological advantage of the autoregressive model is its flexibility when working with a wide range of different time series patterns. Data Science methods were used to develop the model in particular, cMLE (conditional maximum likelihood method). The autoregressive model itself is written in the high-level Python language. Pandas, Numpy, Statsmodels, Sklearn.metrics, and Matplotlib libraries and modules were used. The study describes in detail the main stages of building an autoregressive model: data selection, visualization and verification for stationarity, data separation into test and training samples, training of an autoregressive model, RMSE analysis. The data obtained are characterized by the absence of an obvious trend: there have been periods of a decrease in the consumption of fuel and energy resources per person employed in the country’s economy since 2012, as well as periods of an increase in the corresponding consumption in tons of conventional fuel. The study concludes that the autoregressive model is applicable to the analysis of the Russian energy sector. Although the time series of data is limited, the autoregressive model has high predictive characteristics. The “conservatism” of the autoregressive model towards underestimating the forecast values is emphasized. It is indicated that as new energy statistics accumulate, the autoregressive qualities of the model will improve.

The evolution of the global energy landscape has established liquefied natural gas (LNG) as a critical component of the worldwide energy mix. Nonetheless, instability in global LNG prices presents significant challenges, particularly for export dependent nations like Indonesia. This study rigorously quantifies the impact of LNG price volatility on Indonesia’s Balance of Payments (BOP) and subsequently proposes strategic policies to bolster national economic resilience. Utilizing a mixed-methods design, the research integrates advanced time-series econometric modeling specifically Vector Autoregression (VAR) and Impulse Response Function (IRF) analysis with a qualitative policy review spanning the period 2015–2024. Data include monthly LNG indices, BOP components, and macroeconomic controls, sourced from authoritative institutions such as the International Energy Agency (IEA, 2024), Bank Indonesia (2024), and the Ministry of Energy and Mineral Resources (2024). The empirical results demonstrate a significant, adverse effect of LNG price shocks on Indonesia's trade balance and overall current account, with these effects propagating and persisting over multiple quarters (Fauzi & Gunawan, 2023; Siregar et al., 2023). These findings underscore Indonesia’s high vulnerability to global commodity fluctuations and emphasize the urgent requirement for robust fiscal buffers and economic diversification strategies. Policy analysis reveals ongoing government efforts in energy subsidy reform and infrastructure investment but highlights continuing difficulties in reconciling energy security with overall macroeconomic stability (Robinson, 2023; UNCTAD, 2025). This comprehensive investigation contributes new empirical evidence and practical policy recommendations, establishing a valuable framework for managing LNG price shocks in Indonesia and analogous emerging markets.

Adolescents vary widely in how they engage with digital media, yet prior research often overlooks the heterogeneity and developmental dynamics underlying these behaviors. Using four waves of data collected between 2013 and 2021 from a nationally representative sample of U.S. adolescents (N = 14,798; ages 12-17 at baseline), we identified three media use trajectories via latent class growth analysis: low-increasing, moderate-stable, and high-stable. Internalizing and externalizing problems significantly predicted trajectory membership. To examine bidirectional associations between media use and psychological symptoms, we applied autoregressive latent trajectory cross-lagged panel models, which allowed for the modeling of within-person dynamics while accounting for interindividual change patterns. Results revealed several modest but significant bidirectional effects between media use and psychological problems over time. Specifically, higher media use predicted later increases in externalizing and internalizing symptoms, while earlier media use was also associated with short-term reductions in internalizing problems. Strong trait-level associations were observed across all three constructs, indicating that adolescents with consistently high media use also experienced persistent emotional and behavioral difficulties. These findings highlight the heterogeneous and dynamic nature of adolescent digital engagement and its mental health correlates. The results underscore the importance of person-centered and developmentally informed interventions that account for psychological vulnerability and sociodemographic context.

Does work improve mental health in later life? A 12-year longitudinal study across social group.

Purpose: This study examines how Indonesian corporations adjust their financing strategies in response to global financial market volatility and the implications of these adjustments on domestic financial stability. Methodology: The research applies Vector Autoregression (VAR) analysis to explore the dynamic relationships among capital flows, corporate external debt, exchange rates, bank lending to corporations, and non-performing loans. The Volatility Index (VIX) is employed as the primary measure of global financial uncertainty, serving as the main indicator of external shocks. Findings: Results show that corporations act as potential conduits for the transmission of global financial shocks to the Indonesian domestic economy. Periods of elevated global uncertainty are often associated with rupiah depreciation and reduced access to foreign funding for Indonesian firms. In such circumstances, corporations tend to adjust by shifting from foreign borrowing to domestic bank loans, which could, in turn, reallocate certain financial risks from firms to local banks. This observed pattern of financing substitution reflects the adaptive strategies employed by corporations in managing funding sources during episodes of global financial stress. Originality: This research offers valuable insights into the ways Indonesian corporations respond to global financial volatility, particularly through adjustments between foreign and domestic financing sources. The study adds to the existing body of knowledge by shedding light on potential risk transmission pathways from international markets to domestic banking systems via corporate financing behavior, thereby enhancing the understanding of macro-financial linkages in emerging economies. Keywords: Banking exposure; Capital inflows; Financing behaviour; Financial vulnerability; Macro-financial linkages.

The global economy frequently experiences cycles of rapid growth followed by abrupt crashes, challenging economists and analysts in forecasting and risk management. Crashes like the dot-com bubble crash and the 2008 global financial crisis caused huge disruptions to the world economy. These crashes have been found to display somewhat similar characteristics, like rapid price inflation and speculation, followed by collapse. In search of these underlying patterns, the Log-Periodic Power-Law (LPPL) model has emerged as a promising framework, capable of capturing self-reinforcing dynamics and log-periodic oscillations. However, while log-periodic structures have been tested in developed and stable markets, they lack validation in volatile and developing markets. This study investigates the applicability of the LPPL framework for modeling financial crashes in the Brazilian stock market, which serves as a representative case of a volatile market, particularly through the Bovespa Index (IBOVESPA). In this study, daily data spanning 1993 to 2025 is analyzed to model pre-crash oscillations and speculative bubbles for five major market crashes. In addition to the traditional LPPL model, autoregressive residual analysis is incorporated to account for market noise and improve predictive accuracy. The results demonstrate that the enhanced LPPL model effectively captures pre-crash oscillations and critical transitions, with low error metrics. Eigenstructure analysis of the Hessian matrices highlights stiff and sloppy parameters, emphasizing the pivotal role of critical time and frequency parameters. Overall, these findings validate LPPL-based nonlinear modeling as an effective approach for anticipating speculative bubbles and crash dynamics in complex financial systems.

ABSTRACT Merchandise trade openness can enhance sovereign solvency by ensuring a sustainable generation of foreign exchange earnings. Using Panel Vector Autoregressions on a panel dataset of 55 low- and middle-income countries from 2000 to 2019, the paper demonstrates that increasing merchandise trade openness decreases reliance on external public debts in low- and middle-income countries. The results indicate that these effects are short term. Our findings remain robust across various datasets and econometric models. These results highlight the significance of engaging in international trade activities to improve sovereign solvency and to manage external public debts in less developed economies.

Existential concerns, an unavoidable aspect of human existence, are one of the key elements influencing people’s quest for purpose in life. Individuals may experience inner turmoil and sorrow in this situation. However, hope may play a crucial part in mitigating this adverse circumstance, despite existential concerns, as it symbolizes the person’s ability to cultivate optimistic hopes and beliefs toward the future. In this regard, the current study intends to investigate the longitudinal mediation role of hope between existential concerns and inner peace. The literature has never examined the linkages between these concepts and their design in a longitudinal study. A significant gap in the research was addressed in the current study by combining these factors for the first time and employing a longitudinal mediation analysis, which also avoided the drawbacks of mediational analysis in cross-sectional studies. As a result, by autoregressive analysis of the cross-lagged panel model in a half-longitudinal form, the connections among existential concerns, hope, and inner peace ideas are investigated. In the relationship between existential concerns and inner peace, the analysis’s findings demonstrate the longitudinal mediation of hope. Existential concerns can be viewed as a normal state, yet they pose a threat to inner peace and necessitate optimism. If not, people may lose hope and experience inner turmoil as a result of existential concerns. Interventions with an existential viewpoint are therefore necessary to boost hope in this area.

Military dental providers often operate in environments with extreme temperature gradients. The purpose of this study was to analyze the effect of simulated storage in extreme cold conditions on 8 medications-4 local anesthetics (2% Lidocaine with 1:100,000 epinephrine, 0.5% Marcaine with 1:200,000 epinephrine, 4% Articaine with 1:100,000 epinephrine, 3% Polocaine), 2 pain medications (Acetaminophen 325 mg, Ibuprofen 800 mg), and 2 antibiotics (Amoxicillin 500 mg, Azithromycin 500 mg), who are commonly used by the military for dental treatment. Medications were subjected to simulated freeze-thaw (FT) conditions (MIL-STD-810H), using an environmental chamber to expose any tendency for degradation. The medications were cycled through 13 hours at -10 °C and 11 hours at 4 °C for 28 days, to simulate springtime FT conditions experienced by Kyiv, Ukraine. Samples were analyzed at 0, 7, 14, 21, and 28 days under both environmental stress and room temperature (RT) conditions. Liquid chromatography-mass spectrometry (LC-MS) was completed with electrospray ionization interface and triple quadrupole mass analyzer. Each medication was used as an internal standard (IS) for the other and response factors determined for each. All drugs and their respective IS were measured in multiple reaction monitoring in electrospray positive ionization. Room temperature data from each time point were compared to the respective environmentally stressed drug data using T-tests adjusted via Bonferroni's method (α = 0.01). Parametric first-order autoregressive moving-average repeated-measures analysis of variance using maximum likelihood was performed using the "MIXED" procedure in SAS v9.4 to determine if concentrations were affected by time and environmental stress (α = 0.05). Lidocaine, Polocaine, Acetaminophen, and Azithromycin concentrations were affected by time and environmental stressing. All other medication concentrations were affected by time but not by environmental stressing. Utilization and/or storage of commonly used local anesthetics, antibiotics, and pain medications in these climate conditions may experience concentration changes who may affect their efficacy in treating dental-related conditions.

ABSTRACT This analysis aims to illuminate the interconnectedness of markets such as oil, gold, silver, palladium, and platinum during the COVID‐19 pandemic, employing the quantile vector autoregressive (QVAR) and time‐varying parameter vector autoregression (TVP‐VAR) analysis. These methods are particularly suitable for understanding the evolving dynamics of markets during the pandemic, as they account for varying levels of connectedness and spillover effects among different market segments. Moreover, this study explores spillover effects and conditional volatility among precious metal and oil markets across three distinct regimes: peak, recovery, and the full duration of the pandemic. Results indicate prominent connectedness among markets in all three samples, validating markets' sensitivity toward economic catastrophe like pandemic. Crude oil and gold are dominant shock‐transmitters; conversely, silver, palladium, and platinum are prominently considered as shock‐receivers across the majority of the quantiles. Furthermore, the results will assist relevant stakeholders to include markets that are less vulnerable to unforeseen shocks or unanticipated events.

Impact of monetary policy on functional income distribution: A panel vector autoregressive analysis

China is a major trading partner of the European Union (EU), and the debate over China’s economic influence has gained prominence on both the political and media agendas in EU countries. Through time-series analysis, this study investigates reciprocal relationships between the European Parliament’s (EP) political agenda and the national media agenda regarding EU–China trade relations (2001–2020). The analysis is based on a sample of 538 speeches from the EP Plenary Debates and a total of 867 newspaper articles from the Netherlands and the United Kingdom (UK). Combined with a manual quantitative content analysis, this study also examines the salience of sub-issues in EU–China trade relations. Monthly-level vector autoregressive analyses yielded four major findings. First, a positive reciprocal relationship was observed between the EP’s political agenda and the national media agenda on EU–China trade relations, with mutual influences showing similar effect sizes. Second, it was especially the speeches by Far-Right Members of the European Parliament (MEPs) from the Netherlands and the UK that elicited more national media attention, and vice versa. Third, we found positive mutual influences not only between the national media agenda and the political agenda set by MEPs but also between the national media agenda and the political agenda set by EU representatives. Fourth, the geographical and social proximity of sub-issues in EU–China trade relations appears to moderate the politics-media dynamics. The findings contribute to existing scholarship by examining the function of multilevel structures (i.e., supranational vs. national) in agenda-setting research.

Traditional spatial autoregressive analysis usually assumes that the observed data are precise, but this assumption is often difficult to meet in practical applications. Spatial data, owing to its inherent spatial autocorrelation, as well as the differences in data collection methods at different locations, the complexity of the geographical environment, and other factors, often has greater uncertainty. To address this problem, this article introduces an uncertain spatial autoregressive approach. Assuming that the observed values are imprecise and described by uncertain variables, a minimization problem is then derived using the principle of least squares to estimate the values of the unknown parameters of the uncertain spatial autoregressive model. In addition, a method is provided to determine the predicted value and the confidence interval for the response variable in the newly introduced explanatory variables. Ultimately, to demonstrate the application of the uncertain spatial autoregressive model, two numerical examples are provided.

Many of the world's megafaunal species went extinct during the late Quaternary, leading to dramatic reductions in community and ecosystem functioning. While the nature and severity of the extinctions are well documented on global and continental scales, less is known about local‐scale impacts. We quantified the biomass and energy use of 292 pre‐extinction and 360 post‐extinction fossil assemblages from around the globe to determine effects on large mammal communities. Assemblage energy use was calculated from metabolic rates obtained for 562 individual species, and was compared to species richness along with indicators of taphonomy, archaeology, and biogeography, using three analytical methods: least‐squares orthogonalization regression, spatial autoregression, and linear mixed effects model analysis. Globally, total biomass and energy use are greatly reduced in post‐extinction assemblages. Human‐accumulated assemblages are further homogenised post‐extinction due to their high abundances of domesticated species. The presence of domesticates greatly altered the biomass and energy use of assemblages post‐extinction, producing strong energetic variation across continents that differs considerably to pre‐extinction patterns. This fundamental anthropogenic alteration of communities further exacerbated the impacts of Pleistocene extinctions, even in less severely impacted regions. The results show how human activities have altered mammalian communities for many thousands of years.