Quantile Techniques Research Articles

Can digital government reduce the resource dependency? Evidence from method of moments quantile technique

The conventional thinking states that pervasive government corruption may turn resource plenty in resource-rich countries into a burden. These issues may surface, particularly when the public sector uses conventional procedures. Based on this, the research looks at how the public sector's digitalization might aid in resolving this issue. Specifically, economic growth, trade openness, economic complexity index, public sector size, and the impacts of digitalization are assessed in relation to their reliance on natural resources for 16 nations that are vulnerable to the “curse of the natural resource” Furthermore, the moderating influence of digitalization on the link between the growth of the public sector and the resource curse is investigated. In this case, the years 1995–2021 are investigated using the CS–ARDL methodology, and the robustness of the results is evaluated using the Moments Quantile Regression method. The CS-ARDL approach's findings indicate that trade openness, public sector size, and economic progress all correlate with increased resource reliance. However, as the economy becomes more complex and digitalized, resource dependency declines. Additionally, it is demonstrated that the interaction term parameter between digitalization and the growth of the public sector is negative, indicating that digitalization within the public sector has the potential to counteract the growing reliance of the sector on resources.

The Effects of IT and Financial Development on Economic Growth in BRICS-T Countries: Insights from the Solow Growth Model

The aim of the study is to examine the impact of IT and financial development on economic growth in BRICS-T countries for the period 1990-2022 using the panel quantile technique. For this purpose, IT technology and financial development variables were added to the basic Solow model. According to the findings, the impact of physical capital stock on economic growth is positive in all quantiles. The effect of population growth on economic growth is significant starting from 0.4 quantile and the negative effect increases as the quantile level increases. Information technology, which is the subject of the study, positively affects economic growth and this effect decreases as the quantile level increases. The variables we used to represent the level of financial development, financial institutions have a positive but statistically insignificant coefficient sign, while financial markets have a statistically significant but negative coefficient sign. This negative effect increases as the quantile level increases.

Does increased digital transformation promote a firm's financial performance? New insights from the quantile approach

When studying how digital transformation affects company performance, a phenomenon known as the "digitalization paradox" frequently emerges. In previous studies, however, an average estimate has often been used to assess the relationship between digital transformation and firm performance. Using a fixed-effects quantile technique, this study examines the heterogeneous effect of digital transformation on firm performance in Vietnam. The findings reveal a nuanced relationship, indicating that only high-performing companies gain from digital transformation while others do not. The extensive robustness tests in the empirical analysis support this result. It becomes clear that the mean approach may hide the genuine consequences of digital transformation on firm performance.

Corporate Governance and Cash Holdings among Non-Financial Companies Listed in the Nigerian Exchange Group

The exogenous shocks that necessitate firm deviation from a target cash holding vary across firms and institutional environments, hence the need for the study. This study examines the relationship between corporate governance (CG) and cash holdings among non-financial companies in the Nigerian Exchange Group between 2011 and 2020. The number of populations is 133 non-financial firms. As not all firms disclosed publicly comprehensive annual reports the number of final samples is 88 firms. Generalized Method of Moments (GMM) and the quantile techniques were adopted. With a speed of adjustment (SOA) of 0.75 and a time frame of one year, three months, and four days (1/0.749 = 1.34), the result reveals a partial dynamic adjustment to target cash holdings. The quantile estimation generally reveals low cash holdings and high SOA dynamics, and it is significant at 5% level. With exception of board gender diversity and institutional ownership, variables such as board independence, size, and chief executive officer equity ownership exhibit a significant inverse impact on cash holdings at a 5% level. Relying on the dynamic trade-off and agency theories, the results conform to a prior expectation. This study recommends that a manager should formulate strategic financial policy based on a firm’s specific SOA.

Modelling the connection between energy intensity, renewable energy, globalization, technological innovation and CO2 emissions: A Quantile–on–Quantile technique

As Nigeria progresses towards reaching net‐zero emissions by 2060, it is crucial to identify the factors responsible for environmental deterioration and those that enhance ecological well‐being. It is equally significant to emphasize that Nigeria's economy is heavily dependent on fossil fuels, which have proven unsustainable and environmentally unsafe. As a result, this research investigates the impact of energy intensity (EINT), renewable energy consumption (RENC), globalization (GLOX), technological innovation (TINV) and carbon dioxide emissions (CO2) in Nigeria from 1990Q1–2019Q4. The methods employed include Quantile–on–Quantile (QQ) and non–parametric causality. The QQ method reveals that EINT has both positive and negative impacts on CO2, varying in magnitude from 3 to −5. Higher quantiles of RENC tend to influence CO2 positively, whereas the lower quantile has a negative impact. Negative shocks of GLOX on CO2 have less impact, with a maximum magnitude of −1 at the upper quantile of CO2. In contrast, the positive shocks seem to have a stronger impact and vary in magnitude. TINV has negative shocks across all quantiles. In addition, a significant causality is observed in the upper, middle and lower quantiles. This study suggests that policymakers should implement policies encouraging investments in renewable energy and green technologies.

Análise das Tendências de Precipitação Extrema no Estado de Minas Gerais

Abstract The study of the behavior of intense precipitation is extremely important in the management of disasters triggered by these events that culminate in environmental, social and economic damage throughout Brazil. The main objective of this work was to identify the trends and behavior of intense precipitation events in the State of Minas Gerais. Daily precipitation data from 309 rainfall stations managed by the National Water and Basic Sanitation Agency (ANA) were analyzed, corresponding to the period between 1978 and 2017. The quantile technique was used as a confidence interval (95%) in the trend analysis. The Mann-Kendall Test and the Sen Estimator estimated the trends and their magnitudes, respectively. Of the 309 stations analyzed, 20 stations showed a statistically significant trend (at the 95% level) in the intensity of events, with 8 stations showing an increasing trend and 12 stations showing a decreasing trend, in the States of Minas Gerais. Summer recorded the highest rate of intense rainfall (≥ 50%) throughout the State. An increase in extreme rain events was observed in some points in the north of Minas (increase of 0.20 mm/day/year) and a reduction in the Triângulo Mineiro region and central strip of Minas Gerais (reduction of 0.1 mm /day/year).

Analysis of sustainable groundwater management policies for urban development

AbstractGroundwater is essential to human well‐being and sustains a variety of aquatic ecosystems in both urban and rural settings. Yet, it is commonly overlooked in these contexts. As a result, groundwater may be very important to the development and well‐being of many nations if it is properly evaluated and utilized. Although the possibility for sustainable groundwater resource development is still debated in the literature, these issues still lack quantitative understanding. In order to assess groundwater potential in two different urbanized regions of “Northern Kerala, Southern India,” this research uses the “Enhanced Fuzzy Analytic Hierarchy Process (E‐Fuzzy AHP) based Multi‐Criteria Decision Making (MCDM)‐Geospatial Framework employing Improved Particle Swarm Optimization (IPSO)”. The study area is a coastal region that is quickly becoming urbanized and relies on groundwater resources to meet its basic needs. By incorporating both spatial and non‐spatial data into the Geographic Information System (GIS) platform, a groundwater potential zone map with an accurate integer value was created, known as the “groundwater potential index (GWPI)”. The very excellent potential zone occupies 35% and 11%, respectively, of the “urban and peri‐urban zones,” according to the final groundwater potential map, which employed the quantile technique to split the research territory into four zones. The statistical effectiveness and dependability of results in the overall decision‐making phase were examined in the validation study using the data on mean water depth level, and it was found that the reliability was well within the tolerance threshold.

How do economic policy uncertainty, geopolitical risk, and natural resources rents affect economic complexity? Evidence from advanced and emerging market economies

Progressing to higher economic complexity is widely believed to be a vital economic growth strategy. While most studies examine factors that enhance the sophistication of an economy, there is limited knowledge about the obstacles to economic complexity evolution. This research aims to examine the new barriers to economic sophistication. We adopt an advanced panel quantile technique to a sample of 12 advanced economies and seven emerging market economies from 1997 to 2019. The empirical analysis shows that while economic policy uncertainty poses a threat to economic complexity evolution, interestingly, geopolitical risks bring about opportunities for upgrading economic sophistication. This study also validates the “Dutch disease” effect caused by natural resources rents in all the sampled countries. In addition, the impacts of economic policy uncertainty, geopolitical instability, and natural resources rents on economic complexity are found to be heterogeneous, not only across the quantiles of economic complexity but also between advanced and emerging market economies. Our findings provide insightful and adaptive implications for different country segments for accelerating economic sophistication.

Assessment of uncertainties in threshold doses for tissue reactions following acute external radiation exposure.

The study aimed to estimate threshold doses and their uncertainties for some human health effects after short-term high dose-rate radiation exposure by quantile technique and the effective dose threshold technique based on distribution functions. The relative uncertainty (U) of the threshold dose was estimated using the error propagation technique. The quantile technique provided statistically significant estimates of threshold doses for acute radiation syndrome onset (0.44±0.12Gy, U=143%) and lethality (1.84±0.44Gy, U=117%) but relative uncertainties were high. The effective threshold dose technique provided statistically significant and more precise threshold dose estimates for acute radiation syndrome onset (0.73±0.02Gy, U=18%) and lethality (6.83±0.08Gy, U=36%), as well as agranulocytosis (3.51±0.03Gy, U=16%) and vomiting onset in the prodromal period (1.54±0.02Gy, U=16%). Threshold doses estimated for the change in the peripheral blood neutrophil and leukocyte counts during the first days after short-term high dose-rate radiation exposure were not statistically significant.

Locally sparse quantile estimation for a partially functional interaction model

Functional data analysis has been extensively conducted. In this study, we consider a partially functional model, under which some covariates are scalars and have linear effects, while some other variables are functional and have unspecified nonlinear effects. Significantly advancing from the existing literature, we consider a model with interactions between the functional and scalar covariates. To accommodate long-tailed error distributions which are not uncommon in data analysis, we adopt the quantile technique for estimation. To achieve more interpretable estimation, and to accommodate many practical settings, we assume that the functional covariate effects are locally sparse (that is, there exist subregions on which the effects are exactly zero), which naturally leads to a variable/model selection problem. We propose respecting the “main effect, interaction” hierarchy, which postulates that if a subregion has a nonzero effect in an interaction term, then its effect has to be nonzero in the corresponding main functional effect. For estimation, identification of local sparsity, and respect of the hierarchy, we propose a penalization approach. An effective computational algorithm is developed, and the consistency properties are rigorously established under mild regularity conditions. Simulation shows the practical effectiveness of the proposed approach. The analysis of the Tecator data further demonstrates its practical applicability. Overall, this study can deliver a novel and practically useful model and a statistically and numerically satisfactory estimation approach.

ET Partitioning Assessment Using the TSEB Model and sUAS Information across California Central Valley Vineyards

Evapotranspiration (ET) is a crucial part of commercial grapevine production in California, and the partitioning of this quantity allows the separate assessment of soil and vine water and energy fluxes. This partitioning has an important role in agriculture since it is related to grapevine stress, yield quality, irrigation efficiency, and growth. Satellite remote sensing-based methods provide an opportunity for ET partitioning at a subfield scale. However, medium-resolution satellite imagery from platforms such as Landsat is often insufficient for precision agricultural management at the plant scale. Small, unmanned aerial systems (sUAS) such as the AggieAir platform from Utah State University enable ET estimation and its partitioning over vineyards via the two-source energy balance (TSEB) model. This study explores the assessment of ET and ET partitioning (i.e., soil water evaporation and plant transpiration), considering three different resistance models using ground-based information and aerial high-resolution imagery from the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). We developed a new method for temperature partitioning that incorporated a quantile technique separation (QTS) and high-resolution sUAS information. This new method, coupled with the TSEB model (called TSEB-2TQ), improved sensible heat flux (H) estimation, regarding the bias, with around 61% and 35% compared with the H from the TSEB-PT and TSEB-2T, respectively. Comparisons among ET partitioning estimates from three different methods (Modified Relaxed Eddy Accumulation—MREA; Flux Variance Similarity—FVS; and Conditional Eddy Covariance—CEC) based on EC flux tower data show that the transpiration estimates obtained from the FVS method are statistically different from the estimates from the MREA and the CEC methods, but the transpiration from the MREA and CEC methods are statistically the same. By using the transpiration from the CEC method to compare with the transpiration modeled by different TSEB models, the TSEB-2TQ shows better agreement with the transpiration obtained via the CEC method. Additionally, the transpiration estimation from TSEB-2TQ coupled with different resistance models resulted in insignificant differences. This comparison is one of the first for evaluating ET partitioning estimation from sUAS imagery based on eddy covariance-based partitioning methods.

Does corporate engagement in social responsibility affect firm innovation? The mediating role of digital transformation

The literature is divided on whether corporate social responsibility (CSR) has an impact on firm innovation. For the first time in the Vietnamese context, using a quantile technique with panel data, this study investigates the types of corporate social responsibility (CSR) and their effects on business innovation. In this article, external and internal forms of CSR are found to be interconnected, and their adoption results in supercharged innovative performance. This research also adds to our knowledge of how digital transformation affects CSR and corporate innovation, implying a favorable relationship between CSR, digital transformation, and firm innovation. This means that even if effective institutions are lacking, firms can still be innovative by adopting CSR practices and adapting to changes in the digital world.

Assessing the environmental sustainability corridor: linking oil consumption, hydro energy consumption, and ecological footprint in Turkey.

Climate change has been a topic of significant discourse and debate among scholars and policy makers for several decades. In recent decades, it has become a major problem for the entire human race. Therefore, the present research evaluates the impact of oil consumption, hydro energy use, population density, and economic growth on ecological footprint in Turkey for the period from 1965QI to 2018Q4. This paper uses the BDS test to assess the nonlinearity of the variables in the pre-estimation analysis. The results of the test reveal that non-linearity occurs in all of the variables used in this study. As a consequence, using traditional linear methodologies would produce erroneous results. Our research uses the quantile techniques (quantile cointegration, quantile causality, quantile-on-quantile regression), which are recently developed nonlinear estimate methodologies to assess these associations. The results from the study reveal that oil consumption, hydro energy use, population density, and economic growth contribute to environmental degradation in Turkey in majority of the quantiles. The Granger Causality in Quantiles result also gives credence to the results. The study proposes policy recommendation based on these results.

The impact of cryptocurrencies on China's carbon price variation during COVID-19: A quantile perspective

We aim to document the impact of cryptocurrencies on China's carbon price variation using some quantile techniques during COVID-19 with the daily data spanning from August 7, 2015 to April 30, 2021. In this paper, we show that cryptocurrencies have a very strong explanation power for carbon market with the non-parametric causality-in-quantiles method. In addition, cryptocurrencies can work as a good hedging candidate for carbon market at different investment horizons with the quantile coherency approach. Using hedging effectiveness measure, we further show that COVID-19 can reverse the optimal hedging ratios in our portfolio specification in cryptocurrencies‑carbon emission trading pairs while this pandemic does not have effects on the trading effectiveness. Finally, the heterogeneity and asymmetry features in the dynamic quantile-on-quantile effects are detected and the effects on carbon efficient index show relatively strong fluctuation while on carbon emission trading market are relatively strong in magnitude. Our empirical results conclude with many potential applications for policymakers and investors.

Understanding the Gold-Inflation Nexusi In Malaysia: Hedge and Safe Haven Perspectives

The main objective of this study is to examine the roles of gold as a hedge or a safe haven against inflation in Malaysia. We propose the standard and quantile techniques in the volatility models, with a time-varying conditional variance of regression residuals based on TGARCH specifications. We found that gold only plays a minor role as a hedge and safe haven against inflation since their returns do not evolve at the same pace as inflation. On the other hand, the rolling regression results reveal that shelter incidents against purchasing power loss only occasionally occur at different times and not consistently across holding periods. We conclude that gold does not have the ability to secure Malaysian investment during high inflationary periods and at all times. Thus, Malaysian investors should hold a well-diversified portfolio to earn sustainable returns and protection from purchasing power loss.

Corporate social responsibility, market rivalry and firm leverage: new evidence from a fixed-effect quantile regression approach

Previous research has employed conditional mean-focused regressions to examine the relationship between CSR and firm leverage in developed nations. By offering the first evidence in a developing country, this study employs a quantile technique to overcome the limitations of previous investigations. Our findings reveal that participation in corporate social responsibility activities has a negative and substantial influence on firm leverage at higher quantiles but no effect at lower quantiles. Our study shows that CSR spillovers on firm leverage take place through promoting employee benefits as well as improvements in the business environment.

Daily rainfall intensity and temporal trends in eastern Paraná state – Brazil

The present study aims to analyze the intensity of daily extreme rainfall and trends for precipitation in Castro, Curitiba and Paranaguá stations, located in the state of Paraná, Brazil. Historical series of rainfall registered by the Brazilian National Institute of Meteorology were used considering the period from 1976 to 2015. The Mann-Kendall and Pettitt statistical tests were applied to identify trends and ruptures in historical rainfall series. Other indicators of trends in rainfall and temperature were calculated using the RClimDex software, developed by the Canadian Meteorological System. The classification of cumulative daily rainfall in 24 h with the application of the quantile technique was defined as a standard for percentiles. The months of January, February and December presented greater occurrence frequency of rainfall equal to or greater than 95% and 99% of the quantiles for all locations. The comparative analysis showed that Paranaguá station has the largest accumulated values of rainfall in 24 h during the rainiest months, between September and April, while Castro and Curitiba stations recorded the highest daily totals between May and August. Increasing daily precipitation totals were identified in all quantile's classes with statistical significance only in Curitiba and Paranaguá station, which is attributed to greater urban densities and its direct impacts over daily rainfall totals. Significant trends for increased rainfall were observed, especially in Curitiba, a condition that is associated with the expressive and also significant increase in climate indicators of air temperature.

Avaliação de eventos extremos de precipitação, associados a desastres naturais

O estudo se baseou no levantamento estatístico de eventos extremos de precipitação (P) no Leste do Nordeste Brasileiro (LNEB), com destaque a cidade de Maceió/AL. Dados de Estações Meteorológicas Automáticas (EMA) do INMET, imagens de satélite e dados de hidroestimador disponibilizado pelo CPTEC/INPE foram usados no estudo. Os resultados obtidos via técnica dos quantis, categorizou as seguintes classes de P(mm): Dia Seco (DS) - P < 2,4mm, Chuva muito fraca (Cmf) - 2,4 ≤ P < 3,8mm, Chuva fraca (Cf) - 3,8 ≤ P < 7,6mm, Chuva Moderada (CM) - 7,6 ≤ P < 14,4mm, Chuva Forte (CF) - 14,4 ≤ P < 39,8mm, Chuva Muito Forte - (CMF) 39,8 ≤ P < 82,8mm e Chuva Extrema (CE) - P ³ 82,8mm. As categorias CMF e CE foram eficientes na associação entre extremos de precipitação e os desastres naturais a partir dos registros de decreto de Estado de Calamidade Pública (ECP). Tal padrão relacional apontou a possibilidade de ocorrência de desastres hidrometeorológicos para a cidade de Maceió/AL. No tocante a distribuição espacial da quantidade de casos de CMF e CE em Alagoas, os municípios com maiores ocorrências foram Japaratinga, Porto de Pedras e Maceió. Especificamente a cidade de Maceió/AL, a região R5 (Ipioca e Pescaria) e R2 foram as que mais se destacaram em comparação as demais regiões.Palavras-chave: MERGE, chuva urbana, quartis, desastres naturais. Evaluation of extreme precipitation events associated with natural disasters A B S T R A C TThe present study mainly aimed to make a statistical survey of extreme precipitation events for the eastern region of the Brazilian Northeast, more specifically for the city of Maceió/AL. For this purpose, punctual data from INMET Automatic Meteorological Stations were used, and spatial data using satellite images and hydro-estimator data provided by CPTEC/INPE. The main results were based on daily precipitation data and quantile technique, it generated the following R(mm) classes: Dry Day R < 2.4mm, Drizzle Rain 2.4 ≤ R < 3, 8mm, Showers 3.8 ≤ R < 7.6mm, Moderate Rain 7.6 ≤ R < 14.4mm, Heavy Rain 14.4 ≤ R < 39.8mm, Strong Rain 39.8 ≤ R < 82.8mm, Extreme Rain R ≥ 82.8mm. The method adopted for classifying extreme rainfall (Strong more Extreme) using quartiles proved to be efficient, made by the association between extreme precipitation events and natural disasters using the records of the State of Public Calamity (SPC) degree, that is, the indicators recognition of SPC and annual accumulated average precipitation, point to the possibility of occurrence of hydrometeorological disasters for the city of Maceió/AL. Regarding the spatial distribution of the number of cases of Strong and Extreme, for Alagoas the municipalities with the most recorded occurrences were Japaratinga, Porto de Pedras, Maceió, among others. For the city of Maceió/AL, the region R5 (Ipioca and Pescaria) and R2 were the ones that presented the most cases of rainfall ranging from very strong to extreme.Keywords: MERGE, urban rainfall, quantiles, natural disasters.

Does Gold Still Shelter Inflation, and, if so, When? Evidence From Four Countries

This study investigates gold as a hedge or a safe haven against inflation in four countries. We propose two standard and quantile techniques in the volatility models, with a time-varying conditional variance of regression residuals based on TGARCH specifications. Gold exhibits considerable evidence of a strong hedge in the US and China. Nevertheless, gold provides shelter at different times and not consistently across countries. With regards to be a safe haven, gold retains its status as a key investment in China. On the other hand, gold only plays a minor role in the UK and India. These findings indicate that gold can secure Chinese investment during the high inflationary periods, while gold is a profitable asset to hold over a long period of time in the US. In contrast, UK and Indian investors should hold a well-diversified portfolio for sustainable return and protection from purchasing power loss.

Stochastic Time-Varying Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot

In this paper, a stochastic model predictive control (MPC) is proposed for the wheeled mobile robot to track a reference trajectory within a finite task horizon. The wheeled mobile robot is supposed to subject to additive stochastic disturbance with known probability distribution. It is also supposed that the mobile robot is subject to soft probability constraints on states and control inputs. The nonlinear mobile robot model is linearized and discretized into a discrete linear time-varying model, such that the linear time-varying MPC can be applied to forecast and control its future behavior. In the proposed stochastic MPC, the cost function is designed to penalize its tracking error and energy consumption. Based on quantile techniques, a learning-based approach is applied to transform the probability constraints to deterministic constraints, and to calculate the terminal constraint to guarantee recursive feasibility. It is proved that, with the proposed stochastic MPC, the tracking error of the closed-loop system is asymptotically average bounded. A simulation example is provided to support the theoretical result.