Lower Quantiles Research Articles

Quantile regressions as a tool to evaluate how an exposure shifts and reshapes the outcome distribution: A primer for epidemiologists.

Quantifying how an exposure affects the entire outcome distribution is often important, e.g., for outcomes such as blood pressure which have non-linear effects on long-term morbidity and mortality. Quantile regressions offer a powerful way of estimating an exposure's relationship with the outcome distribution but remain underused in epidemiology. We introduce quantile regressions with a focus on distinguishing estimators for quantiles of the conditional and unconditional outcome distributions. We also present an empirical example in which we fit mean and quantile regressions to investigate educational attainment's association with later-life systolic blood pressure (SBP). We use data on 8,875 US-born respondents aged 50+ years from the US Health and Retirement Study. More education was negatively associated with mean SBP. Conditional and unconditional quantile regressions both suggested a negative association between education and SBP at all levels of SBP, but the absolute magnitudes of these associations were higher at higher SBP quantiles relative to lower quantiles. In addition to showing that educational attainment shifted the SBP distribution left-wards, quantile regression results revealed that education may have reshaped the SBP distribution through larger protective associations in the right tail, thus benefiting those at highest risk of cardiovascular diseases.

Investigating the persistence degree of environmental patent: application of panel SPSM-quantile unit root test

ABSTRACT This article analyzes the degree of persistence of shocks to environmental patents in the OECD countries from 1980 to 2022 by applying the panel quantile unit root (PQUR) test and sequential panel selection (SPS) method. Our results indicate that most OECD countries reveal similar stochastic behaviours, where low and extreme (middle and moderate high) quantiles behave as unit root (stationary) processes. According to our findings, except for the US, the time series of environmental patents of other OECD countries behaved as a unit root process in 2022. Accordingly, the mandatory and incentive pro-green innovation policies have long-lasting effects on the development of the patents.

Decomposing socioeconomic inequality in household out of pocket health expenditures in Pakistan (2010-11–2018-19)

BackgroundThe increased socioeconomic inequality in catastrophic health expenditure (CHE) disproportionately affects disadvantaged populations, subjecting them to financial hardships, limiting their access to healthcare, and exacerbating their vulnerability to morbidity.ObjectivesThis study examines changes in socioeconomic inequality related to CHE and analyzes the contributing factors responsible for these changes in Pakistan between 2010-11 and 2018-19.MethodsThis paper extracted the data on out-of-pocket health expenditures from the National Health Accounts for 2009-10 and 2017-18. Sociodemographic information was gathered from the Household Integrated Economic Surveys of 2010-11 and 2018-19. CHE was calculated using budget share and the ability-to-pay approaches. To assess socioeconomic inequality in CHE in 2010-11 and 2018-19, both generalized and standard concentration indices were used, and Wagstaff inequality decomposition analysis was employed to explore the causes of socioeconomic inequality in each year. Further, an Oaxaca-type decomposition was applied to assess changes in socioeconomic inequality in CHE over time.ResultsThe concentration index reveals that socioeconomic inequality in CHE decreased in 2018-19 compared to 2010-11 in Pakistan. Despite the reduction in inequality, CHE was concentrated among the poor in Pakistan in 2010-11 and 2018-19. The inequality decomposition analysis revealed that wealth status was the main cause of inequality in CHE over time. The upper wealth quantiles indicated a positive contribution, whereas lower quantiles showed a negative contribution to inequality in CHE. Furthermore, urban residence contributed to pro-rich inequality, whereas employed household heads, private healthcare provider, and inpatient healthcare utilization contributed to pro-poor inequality. A noticeable decline in socioeconomic inequality in CHE was observed between 2010 and 2018. However, inequality remained predominantly concentrated among the lower socio-economic strata.ConclusionThese results underscore the need to improve the outreach of subsidized healthcare and expand social safety nets.

Fresh evidence from temperature effects on growth and economic policy uncertainty: A panel quantile approach

This paper provides fresh evidence of temperature effects on GDP per capita growth and economic policy uncertainty (epu). We apply the quantile via moments methodology (Machado and Santos Silva, 2019) in a sample of 31 countries for the period 1980–2021, the most current time frame of the work we reviewed. To the best of our knowledge, temperature effects on epu, in a panel quantile setting, have not been examined before. Our empirical results provide evidence in favor of asymmetric temperature impacts on both growth rates and epu. Specifically, according to our main findings: First, the impact of temperature on the growth rate of GDP per capita is quadratic, negative and increases, in absolute terms, as we move from the upper (flourishing economy) to the lower (bearish economy) quantiles. Second, hotter countries are more vulnerable to economic policy uncertainty, with the effect being more pronounced as uncertainty increases. Third, the temperature effect on GDP is higher than the political effect in weaker economies, while the political effect becomes of greater magnitude in stronger economies. Overall, our results indicate that an increase in temperature due to climate change poses important threats for the development prospects especially, but not exclusively, of the poorer countries that usually have both higher temperatures and face severe issues of economic policy uncertainty due to political instability and lack of basic economic infrastructure.

Connectedness between Sustainable Investment Indexes: The QVAR Approach

We studied the relationship between sustainable investment indexes and examine whether this relationship varies in bullish, bearish, and stable financial markets. To understand this issue more deeply, we analyzed the connectedness between three indexes—the Sustainable Impact investments, Paris-aligned stocks, and green bonds indexes—using the daily closing prices from 1 June 2017 to 15 April 2024, encompassing 1793 observations. We used a quantile vector autoregressive (QVAR) model to understand the dynamic relationship among the considered indices. The findings indicate that sustainable investments are strongly interconnected in both high and low quantiles, but this connection weakens significantly during periods of market stability. The Sustainable Impact investments and Paris-aligned stocks indexes are net transmitters of impacts to other sustainable alternatives, while the green bonds index is a net receiver. We also observed an increase in interconnectedness across all quantiles during the pandemic, the Russia–Ukraine military conflict, and changes in the European Union and the United States’ monetary policies.

Disentangled oil shocks and macroeconomic policy uncertainty in South Africa

This study examines the spillovers among oil shocks and macroeconomic policy uncertainty in South Africa between January 1990 to July 2022. The study arrives at some important findings.From the Diebold and Yılmaz (2012) connectedness analysis, which measures average connectedness, we find a moderate connection between oil shocks and macroeconomic policy uncertainty phenomena. Conversely, the connections among oil shocks and macroeconomic policy uncertainty are greatest at the low and upper quantiles. That is, when these phenomena are experiencing extreme values, the connectedness among them is formidable. Moreover, the study finds that over the period of assessment, macroeconomic policy uncertainty phenomena are net receivers at lower quantiles. Meanwhile, unlike financial policy uncertainty, economic policy uncertainty and political uncertainty become net transmitters at the middle and upper quantiles. On the other hand, the disaggregated oil shocks are net transmitters (receivers) at the low (median) quantiles. Interestingly, their receiver/transmitter roles are mixed at the upper quantile.Finally, using the Quantile-on-Quantile regression analysis, we find that oil shocks generally increase (reduce) macroeconomic policy uncertainty when this uncertainty is already low (high).

Quantile-based extended joint connectedness between trade policy uncertainty and Gulf Cooperation Council Islamic sectoral volatility

This study quantifies the shock transmission mechanism between the trade policy uncertainty (TPU) index and Sharia-compliant stock sectoral conditional volatility in the Gulf Cooperation Council (GCC) countries. We employ a comprehensive analysis that includes the time-domain extended joint and frequency-domain quantum vector autoregressive (QVAR) frameworks. The time-domain QVAR demonstrates that TPU causes the most substantial shocks to utility sector volatility. Investors in the GCC must strategically allocate their investment portfolios to the consumer services and energy industries, which are less vulnerable to the TPU shock. The results show that TPU shocks provide more error variances to the long-term and bullish conditional volatility (or higher quantiles) of the utility, real estate investment trust funds (REIT), healthcare, and industry sectors. Conversely, during bearish volatility conditions (lower quantiles), TPU shocks result in higher shocks in the conditional volatility of the utility, REIT, finance, and industrial sectors. Long-term investors should diversify their portfolios to mitigate risk in the utility, REIT, and industry sectors through strategic investments in consumer service sector. However, in the short term and during both bearish and bullish sectoral volatility, the consumer service and industry sectors are more vulnerable to TPU shocks. Regarding diversity, the REIT, energy, and financial sectors are the least affected by TPU shocks, offering a protective buffer in the short term and during periods of higher and lower GCC Islamic sectoral volatility.

Nghiên cứu tác động của chính sách an toàn vĩ mô tới khả năng sinh lời- Bằng chứng thực nghiệm tại các ngân hàng thương mại Việt Nam

This paper investigates the impact of macroprudential policies on the profitability of 27 Vietnamese commercial banks from 2014:Q3 to 2023:Q3. This paper uses panel data regression methods combined with tests to resolve the endogeneity issue, and robustness checks produce consistent research results. Accordingly, empirical results show that contractionary macroprudential policies have a positive impact on the profitability of Vietnamese commercial banks. The results from the quantile regression model indicate that contractionary macroprudential policies help commercial banks with low ROA quantiles improve profitability better than banks with high ROA quantiles. Based on that, this research forms several recommendations including: the banks should conduct appropriate strategies to align to macroprudential regulations; the State Bank of Vietnam is in charge of the banks in complying to these regulations.

Innovate, conserve, grow: A comprehensive analysis of technological innovation, energy utilization, and carbon emission in BRICS

AbstractThe aim of this study was to embark on a transformative exploration of the interplay between technological innovation, renewable energy, economic development, and carbon emissions in BRICS nations, unveiling novel insights that redefine sustainability paradigms and contribute to global environmental policymaking. This comprehensive study spans the years 1990–2022, meticulously examining the dynamics of economic indicators, energy consumption, renewable energy generation, and technological progress. The dataset's non‐normal distribution prompts the use of moment quantile regression, providing nuanced insights with consideration for diverse slopes and cross‐sectional dependencies. Validation through the “Dumitrescu‐Hurlin panel Causality Test” refines the findings, revealing the diminishing impact of technological innovation across quantiles. The study illuminates a compelling connection: heightened technological innovation correlates strongly with reduced carbon emissions, particularly evident at lower quantiles. This aligns seamlessly with existing research, emphasizing technology's transformative potential for sustainability. Conversely, a concerning positive association emerges between energy utilization and carbon emissions, highlighting the persistent environmental challenge posed by escalating energy use. Urgent strategic interventions are underscored to address the ecological consequences associated with rising energy consumption. The intricate relationship between renewable electricity production and carbon emissions unfolds, emphasizing renewables' pivotal role in mitigating environmental impact. This aligns with ongoing discussions regarding their indispensable contribution to sustainable development. The study underscores the strategic importance of prioritizing renewable power production in environmental sustainability initiatives. However, a disconcerting positive association surfaces between economic development and carbon emissions across all quantiles, revealing the environmental costs accompanying economic growth in BRICS nations. As economic development advances, carbon emissions escalate, presenting substantial sustainability challenges and emphasizing the imperative to balance progress with environmental conservation efforts. This contribution enriches the ongoing discourse on fostering sustainability within the BRICS nations and beyond, marking a significant stride toward a more environmentally conscious future.

Sustainable development through green transition in EU countries: New evidence from panel quantile regression

Sustainable development addresses global challenges by promoting practices that balance economic, social, and environmental considerations. Key factors include the shifting to green energy and the integrating of green technology in the sustainable development process. This study investigates the heterogenous effects of green technology development, green energy, R&D expenditures, FDI, economic growth, and urbanization on CO2 emissions in 25 European Union (EU) countries using panel quantile regression over the period 2000–2021. The results, based on panel quantile regression, indicate that green energy decreases CO2 emissions from the 10th to the 90th quantiles, while green technology development increases CO2 emissions at the lower quantiles (10th to 60th) and then turns negative. The robustness of the fixed effect model also confirms the findings of the study. Additionally, panel causality tests indicate no causal link between green technology development and CO2 emissions, but there is bidirectional causality between green energy and CO2 emissions. Therefore, the findings highlight that policymakers should thoroughly evaluate measures and strategies to encourage the development of green technologies and green energy sources to reduce high levels of CO2 emissions. One strategy is to provide financial aid and support technological advances to produce green energy at reduced costs.

Asymmetric effects of commodity and stock market on Chinese green market: Evidence from wavelet-based quantile-on-quantile approach

This study principally concentrates on evaluating the effects of Chinese commodity and stock market on the green market. The Maximum Overlap Discrete Wavelet Transform (MODWT) technique is utilized for decomposing time series into diverse frequency components. Following this, quantile-on-quantile regression (QQ) is implemented to meticulously demonstrates the dependency structure among the variables under diverse market conditions. Results demonstrate that energy has no short-term impact, while non-ferrous metals, palm oil, sugar, and stock impact the green market at high and low quantiles. Booming gold and declining stock negatively affect the green market. In the medium term, the influence of stocks and most commodities diminishes. Bullish coal and lead prices have a positive impact, while bearish zinc, corn, and palm oil prices have a negative impact. Crude oil does not significantly affect the green market. In the long term, both stock and commodities have a positive impact on the green market, particularly at extreme quantiles. When both markets decline, they negatively affect the green market. Finally, Granger causality test reveals a bi-directional linear and non-linear causality between commodity and stock markets and the green market across all time scales, enabling investors to predict green market returns based on commodity and stock returns.

Information communication technology, globalization, and energy poverty: Prospects for sustainable development in the N‐11 countries

AbstractEnergy poverty is a significant barrier to sustainable development, affecting millions of people worldwide. However, technology offers innovative solutions that can bridge the energy gap and promote access to reliable and affordable energy services. In this study, we analyze the impact of ICT and globalization on energy poverty in N‐11 countries from 1990 to 2021, utilizing education, financial development, and economic growth as control variables. Results explain that the impact of ICT on energy poverty in lower quantiles appears to be relatively weak and positive, suggesting that it may be of limited effectiveness in reducing energy poverty in the most vulnerable populations. At higher quantiles, however, the impact becomes increasingly hostile, which suggests that higher ICT levels may exacerbate energy poverty among those who are already experiencing it. Energy poverty tends to decrease as globalization increases, as evidenced by the statistically significant negative coefficients across all quantiles. At the 10th percentile (Q0.1), an increase of one unit in globalization is associated with a reduction of 0.898 in energy poverty. Similarly, at the 90th percentile (Q0.9), an increase of one unit in globalization increases to 0.050 in energy poverty. It is possible to optimize resource utilization, reduce costs, and increase energy access through regional energy cooperation frameworks, such as cross‐border electricity grids or gas pipelines. In order to promote sustainable energy practices among citizens, the government should prioritize investing in clean energy projects, promoting energy conservation, and raising awareness of the importance of sustainable energy practices.

Revisiting the interest rate-investment nexus in India: fresh perspective from non-parametric analysis

PurposeIt is generally believed that business spending on capital expenditure tends to decrease as interest rates rise, and vice versa, this is not always the case. The previous literature produces inconclusive results vis-à-vis the interest rate and investment nexus. This study analyzes the responsiveness of investment to changes in high and low levels of interest rates in India through a quantile-based, non-parametric method utilizing annual data from 1980 to 2022.Design/methodology/approachThis study uses Quantile-on-quantile (QQ) technique proposed by Sim and Zhou (2015) to examine the impact of interest rate quantiles on quantiles of investment. In addition, long-term association and the direction of causality are estimated through the Cho et al. (2015) test of quantile cointegration and the Jeong et al. (2012) Granger causality in quantile (GCQ) test, respectively.FindingsThe empirical evidence validates that the linkage between investments and interest rate is not consistently negative and varies from quantile to quantile. The study finds a negative impact at median quantiles and a positive impact at extreme higher quantiles. Conversely, the impact at lower quantiles is negligible, which is also observed from quantile cointegration, indicating the presence of a statistically significant association above the median quantiles. Additionally, the study finds one interesting finding that there exists unidirectional causality from investment to interest rates in India rather than other way around.Research limitations/implicationsThe study provides significant implications for policymakers as it suggests that during extreme economic conditions, the effectiveness of traditional monetary policy tools to boost capital formation is restricted. Policymakers may consider alternative measures to stimulate investment during these time periods. The study additionally posits that the neoclassical theory of investment may not be readily applicable in emerging economies in its unaltered state, mostly due to the lack of well-developed financial markets.Originality/valueThere is a limited literature available on non-linear linkage between interest rates and investment. The present study adds to the existing knowledge by investigating how investment responds differently to fluctuations in interest rates, while incorporating the complete distribution of both the variables.

Spatiotemporal Interaction Characteristics and Transition Mechanism of Carbon Intensity in China's Transportation Industry

This research was conducted using many spatial analysis approaches to dissect the spatiotemporal interactive characteristics of carbon emission intensity within the transportation sector from 2002 to 2020. An in-depth exploration of their transition mechanisms was conducted by nesting the obtained timewarp types with the panel quantile model. Finally, the geodetector model aligned with different transition mechanisms was employed to investigate and analyze the interaction effects among various factors influencing carbon intensity in the transportation sector. The results indicated that:① The carbon emission intensity of the transportation sector in 30 provinces and regions of China showed an overall downward trend with fluctuations, and the spatial clustering level was relatively stable. ② The spatiotemporal interactive features of ESTDA revealed that the relationship between the northwest region and its adjacent spatial units was unstable, with significant variations and fluctuations. In contrast, economically developed areas such as coastal cities in the eastern part had established mature transportation networks, resulting in a relatively stable local spatial pattern, though a few areas still exhibited spatiotemporal competitiveness. ③ The spatiotemporal transition of carbon intensity in the transportation sector could be categorized into four driving or constraining modes(the population economy urbanization constraint model, population economy urbanization facility constraint model, technology consumption industry-driven model, and technology industry regulation-driven model). Most provinces were influenced by the low quantile constraint and high quantile drive modes, with only a few affected by the high quantile constraint and low quantile drive modes, the majority of which were located in the northwest or southwest regions. ④ Further, we introduced the geographical detector model based on the identified mechanism of carbon emission intensity transition in the transportation sector, emphasizing the coordinated development of multiple factors and strengthening inter-regional collaborative governance.

Breaking barriers, cultivating sustainability: Discovering the trifecta influence of digitalization, natural resources, and globalization on eco-innovations across 27 European nations

In recent years, the convergence of digitalization, natural resources, and globalization has profoundly influenced eco-innovations in European economies, emphasizing their significance in achieving sustainable development goals (SDGs). Additionally, digitalization enables smart infrastructure and facilitates a circular economy. Furthermore, natural resources provide prospects for transitioning to renewable energy and improving resource efficiency, while globalization connects European economies to global networks, endorsing the exchange of information and best practices. This study examines the influence of digitalization, natural resources, and globalization on eco-innovations for the 27 European Union (EU-27) nations from 1990 to 2021. The estimated outcomes reveal that digitalization substantially encourages eco-innovations. After confirming the issues of cross-sectional dependence and slope heterogeneity, this study adopts the second-generation process to estimate consistent and robust outcomes. The findings from the method of moment quantile regression (MMQR) show that digitalization significantly increases eco-innovations across all quantiles. Regarding natural resources, the findings explore the asymmetric relationship, indicating that an increase in natural resources raises the level of eco-innovations in the lower and lower-middle quantiles but decreases it in the upper quantiles. This signifies the inefficient use of natural resources in EU-27 nations. Additionally, the findings report that the globalization process significantly reduces the pace of eco-innovations. The interaction between natural resources and digitalization reveals that it increases eco-innovations at lower quantiles but reduces them at higher quantiles. As for the interaction between natural resources and globalization, the findings indicate a positive association with eco-innovations in the lower and lower-middle quantiles but a negative association in higher quantiles. Based on the estimated evidences, this study suggests some feasible policy inferences to drive eco-innovations, mitigate ecological impacts, and pave the way for a greener and more resilient future in EU-27 nations.

The U-shaped relationship between corruption and international tourism demand: A gravity model approach

The tourism industry significantly contributes to a country’s economic growth and creates a positive image of the destination. This study assesses the impact of corruption on international tourism demand. It employs two-dimensional analyses using the gravity model and a pooled ordinary least square estimator to provide a unique recognition of international tourism demand. The study utilized a conditional quantile regression technique to analyze a dataset of 200 destination countries from 1995 to 2022. The empirical results demonstrate a mixed effect of corruption on international tourism demand. The analysis reveals a non-linear relationship between corruption and international tourism demand, with the inverted-U relationship being statistically significant only at the 50th–75th quantiles and not holding at the upper and lower quantiles. The research confirms that income has a positive impact on tourism across quantiles, but the impact is disproportionate. The sub-period of 2006–2022 experienced a significant decline in gross domestic product (GDP) due to the global financial crisis and its aftershocks, which severely impacted the attractiveness of destination countries for tourists. These valuable insights can inform national tourism policies and businesses.

Socioeconomic Inequalities in Catastrophic Health Expenditure in Sindh Province of Pakistan

This study aims to examines the socio-economic inequality in Catastrophic Health Expenditure(CHE) by using the data from the Household Integrated Economic Surveys. Catastrophic Health Expenditure(CHE) was computed using the ability-to-pay-approach. To assess socioeconomic inequality in CHE for the years 2018, both generalized and standard concentration Indices were used. The results of concentration index revealed that Catastrophic Health Expenditure(CHE) concentrated among the poor in Sindh. The inequality decomposition analysis reveals that wealth status was the main cause of the inequality. The upper wealth quantiles had larger contribution, while the lower quantiles showed smaller contribution to inequality in CHE. Further, employed head of the household, Educated head of household, private provision of healthcare, and inpatient access of healthcare were negative contributors to CHE inequality in Sindh.

From black to green: Quantifying the impact of economic growth, resource management, and green technologies on CO2 emissions

In an exploration of environmental concerns, this groundbreaking research delves into the relationship between GDP per capita, coal rents, forest rents, mineral rents, oil rents, natural gas rents, fossil fuels, renewables, environmental tax and environment-related technologies on CO2 emissions in 30 highly emitting countries from 1995 to 2021 using instrumental-variables regression Two-Stage least squares (IV-2SLS) regression and two-step system generalized method of moments (GMM) estimates. Our results indicate a significant positive relationship between economic growth and CO2 emissions across all quantiles, showcasing an EKC with diminishing marginal effects. Coal rents exhibit a statistically significant negative relationship with emissions, particularly in higher quantiles, and mineral rents show a negative association with CO2 emissions in lower and middle quantiles, reinforcing the idea of resource management in emissions reduction. Fossil fuels exert a considerable adverse impact on emissions, with a rising effect in progressive quantiles. Conversely, renewable energy significantly curtails CO2 emissions, with higher impacts in lower quantiles. Environmental tax also mitigates CO2 emissions. Environment-related technologies play a pivotal role in emission reduction, particularly in lower and middle quantiles, emphasizing the need for innovative solutions. These findings provide valuable insights for policymakers, highlighting the importance of tailoring interventions to different emission levels and leveraging diverse strategies for sustainable development.

Do China and USA differ in the interrelationship between green bond and ESG markets?

Studying the interrelationship between green bond markets and ESG stock markets is crucial for promoting sustainable development in the face of environmental concerns. This paper explores this interrelationship across a range of time scales and market conditions by conducting wavelet analysis, quantile Granger causality test, and quantile-on-quantile regression (QQR) analysis, using data from January 5, 2015 to December 31, 2021 with 1705 observations of each variable. The results show that the green bond markets and the ESG stock markets in USA present a strong correlation, especially in response to external events. Additionally, we observe quantile Granger causality form green bond markets to ESG stock markets in both China and USA at all time scales. The QQR results suggest that the impact of green bond markets on ESG stock markets is significant under extreme market conditions in both countries. When both markets are in the lower quantiles, green bond markets would positively impact ESG stock markets in the short-term, but the impact turns out to be negative as the time term extends. Furthermore, the results in China and USA demonstrate some differences. When green bonds market is in the higher quantiles, green bonds markets would negatively impact ESG stock markets in both countries in the short-term. However, unlike that in China, the impact of in USA becomes positive as the term is longer, implying significant differences between the influencing mechanisms of the markets in these two countries.

The impact of COVID-19 vaccines on China’s overall and sectoral stock returns: a quantile-based analysis

ABSTRACT This research analyzes the response of China’s stock market returns (overall and sector-specific) to COVID-19 vaccines. We examine these relationships using quantile-on-quantile (QQR) regression and causality-in-quantile (CQ) approaches. The empirical results show that the higher quantiles of COVID-19 vaccines propel the higher quantiles of the Shanghai stock returns (SSR). Simultaneously, the higher quantiles of COVID-19 vaccines negatively influence the lower quantiles of the Shanghai stock returns. On the sectoral level, consumer discretionary, basic materials, industrial, utilities, and telecommunication sectors exhibit similar trends to those observed in the Shanghai stock market. The study emphasizes that COVID-19 vaccines tend to increase Shanghai stock returns during bullish market condition, and this impact becomes adverse when the market showcases a bearish trend. These findings serve as insights for policymakers, investors, and other stakeholders.