90th Quantile Research Articles

URBAN EFFECTS ON LAND SURFACE TEMPERATURE IN DAVAO CITY, PHILIPPINES

Abstract. This study produced spatiotemporal hot and cold spot occurrence maps for Davao City for the period 1994-2019 using land surface temperature (LST) images. Urban heat is theorized to have been affected by some, if not all, of the following impact factors: air pollutant concentrations/particulate matter (PM10), vegetation “abundance” (using EVI), building “density” (NDBI), albedo, topography, and population density. A mobile traverse sampling was performed in the morning and afternoon of 15 April 2019 to measure PM10 in the city’s identified hot spots. The remaining factors were generated from imagery (i.e., Landsat 8, Synthetic Aperture Radar) and obtained from the Philippine Statistics Authority. These factors were analyzed against the LST which was obtained through Project GUHeat’s methodology. The relationships between the factors and LST were studied through multiple and quantile regression models (MRM & QRM). Results showed that variable PM10 does not have any significance in the MRM. Meanwhile, QRM were fitted to different quantile values, namely: 10th, 25th, 50th, 75th, and 90th. It is only at the 90th quantile where all the independent variables are good predictors for the LST. Albedo is the most important predictor for the LST at 10th quantile whereas Elev for the 25th quantile. However, when LST is at the 50th, 75th, and 90th quantiles NDBI is the most significant variable at predicting LST. Reliable spatiotemporal assessment and modelling of surface temperature are essential for urban planning and management to formulate sustainable strategies for the welfare of people and environment.

Effects of building types and materials on household electricity consumption in Indonesia

Air conditioning is one of the growing sources of electricity consumption in developing countries with tropical and sub-tropical climates. Vernacular design and the use of natural building materials are considered effective measures for mitigating the rapid growth in electricity demand, but such arguments and analyses have only been performed at small scales or through prototype studies of individual buildings. We seek to conduct a society-wide analysis by providing a national-scale macro analysis and discuss the social quantile effects of building types and materials on household electricity consumption. With data obtained from two waves of nationally representative household surveys, the Blinder-Oaxaca (BD) and the Firpo, Fortin and Lemieux (FFL) decomposition methods are used for the mean and quantile analyses, respectively. The mean analysis indicates that significant reductions in electricity consumption can be achieved by utilizing natural materials in both urban and rural regions. The FFL decomposition further affirms the use of natural materials in housing can mitigate the electricity consumption among urban occupants even at the 90th quantile. It is recommended that the merits of vernacular houses be emphasized in climate and energy policies, and further measures should be taken to promote vernacular architecture through design and planning guidelines.

Heterogeneous effects of energy efficiency and renewable energy on carbon emissions: Evidence from developing countries

Abstract The adoption of energy-efficient and clean energy resources is crucial in reducing greenhouse gas emissions. The study analyzes the heterogeneous effects of energy efficiency (EE), renewable energy (RE), and other variables on carbon emissions within the context of the environment Kuznets curve (EKC) hypothesis in 66 developing countries from 1990 to 2014. This study incorporates the role of EE in the construction of the EKC hypothesis, which has been neglected in the previous literature. By using panel ordinary least squares and fixed-effect panel quantile regression (PQR), we find that the impact of the decisive factors of CO 2 emissions are heterogeneous across different quantiles. Specifically, EE reduces CO 2 emissions across all quantiles, but the mitigation effect is strongest at the 90th quantile. RE reduces CO 2 emissions and shows a substantial effect at the 10th quantile. Nuclear energy consumption reduces CO 2 emissions but significantly influences carbon emissions only at the 50th quantile. GDP (Y) increases CO 2 emissions, but the escalating effect of Y increases at the upper quantiles. The squared of GDP ( Y 2 ) reduces CO 2 emissions and shows the strongest mitigation effect at the upper quantiles. The quantile coefficients of Y and Y 2 are significantly positive and negative, respectively, thereby verifying the existence of the EKC hypothesis in developing countries. In sum, EE and RE contribute to reducing carbon emissions in developing countries. These results also verify EE as an essential factor in the formation of the EKC hypothesis in developing countries and offer some important recommendations for designing and implementing appropriate economic and energy policies to achieve environment sustainability in these countries.

Effect of Prognostic Factors on Survival Time of Patients of Cardiovascular Disease using Quantile Regression

Background: The study of survival time after the first myocardial infarction among cardiovascular disease patients are quite important for medical practitioners, planners and for the patients. This study tries to study the survival patterns and their risk factors using relatively new and advanced model. Objective: The current paper conceived to accentuate the effect of prognostic factors on survival time of cardiovascular disease patients. using quantile regression technique. Methods: Quantile regression model has been used to model survival time, McNemar’s test for checking independence of linked attributes. Results: The results showed our perceived notion that different prognostic factors have a different effect on patients’ survival at varying locations of survival time. Like smoking has one effect at 10th quantile and quite different effect at 75th quantile of survival time after first myocardial infarction. McNemar test reveals that the initial status of hypertension has significant association with the current hypertension status of the patients, hypertensive patients are more likely to have heart failure which is in tandem with proven medical findings. Conclusion: Unlike most of the well-known survival models, quantile regression models the survival time directly instead of modelling some other functions like hazard function or death density function. Therefore, its interpretation is easy and informative.

Crime and social media

PurposeThe purpose of this paper is to complement the scant macroeconomic literature on the development outcomes of social media by examining the relationship between Facebook penetration and violent crime levels in a cross-section of 148 countries for the year 2012.Design/methodology/approachThe empirical evidence is based on ordinary least squares (OLS), Tobit and quantile regressions. In order to respond to policy concerns on the limited evidence on the consequences of social media in developing countries, the data set is disaggregated into regions and income levels. The decomposition by income levels included: low income, lower middle income, upper middle income and high income. The corresponding regions include: Europe and Central Asia, East Asia and the Pacific, Middle East and North Africa (MENA), Sub-Saharan Africa and Latin America.FindingsFrom OLS and Tobit regressions, there is a negative relationship between Facebook penetration and crime. However, quantile regressions reveal that the established negative relationship is noticeable exclusively in the 90th crime quantile. Further, when the data set is decomposed into regions and income levels, the negative relationship is evident in the MENA while a positive relationship is confirmed for Sub-Saharan Africa. Policy implications are discussed.Originality/valueStudies on the development outcomes of social media are sparse because of a lack of reliable macroeconomic data on social media. This study primarily complemented three existing studies that have leveraged on a newly available data set on Facebook.

797 High Thiopurine Methyltransferase Activity Does Not Affect Concentration of Azathioprine Metabolite 6-Thioguanine Nucleotide in Inflammatory Bowel Disease

INTRODUCTION: Azathioprine (AZA) is commonly used to treat inflammatory bowel disease (IBD). Thiopurine methyltransferase (TPMT) converts AZA to key active metabolite 6-thioguanine nucleotide (6-TGN). Low TPMT activity is associated with high 6-TGN and side effects. Conversely, low 6-TGN is associated with lack of clinical response and has been associated with high TPMT activity but has not been examined in an IBD population. The aim of this study was to identify the independent effect of normal to high TPMT activity on 6-TGN concentrations in an IBD population. METHODS: We performed a retrospective chart review of patients aged >18 with IBD treated with AZA and with documented TPMT activity and 6-TGN levels from 2010 to 2017. To account for different assays, TPMT activity was normalized against the established low-normal TPMT activity, with low activity defined as less than 1 and high activity defined as above the 75th quantile of TPMT activity in the cohort. Those with low TPMT were excluded. Linear regression was used to determine the effect of TPMT activity on 6-TGN accounting for potential confounders. Further assessment of the interaction between dose and TPMT activity on 6-TGN was measured through the Average Causal Mediation Effects (ACME). Statistics performed in R v3.6.0 using mediation package. This study was IRB approved. RESULTS: Dosing of AZA in mg/kg, TPMT activity, and 6-TGN concentration were documented in 63 patients, of which 10 had low TPMT activity and were subsequently excluded, leaving 53 patients for analysis. Overall 37% of the cohort had a therapeutic 6-TGN level of >240 pmol/8 × 108 RBC. No patient under 1mg/kg achieved a therapeutic 6-TGN level, whereas 50% of patients taking 2.5 mg/kg did. The median 6-TGN in the normal TPMT range was 191.5 (IQR: 78.8, 296.3) versus 201 (IQR: 45, 312) in the high group (P = 0.57). There was a weak positive correlation between dosing (mg/kg) and 6-TGN (R2 = 0.08), while no correlation was seen between TPMT and 6-TGN (R2 = 0.0). Linear regression to assess the effect of TPMT activity and dose on 6-TGN concentrations including potential confounders of sex, age, smoking status only identified dose (mg/kg) to have a significant effect on 6-TGN concentration (Table 1). CONCLUSION: There was no effect on 6-TGN as TPMT activity increased, although 6-TGN was positively affected by dose. Despite normal TPMT activity, therapeutic 6-TGN concentrations were only found in 50% of those dosed at 2.5 mg/kg.

Homicide and social media: Global empirical evidence

This study investigates the relationship between social media and homicide in a cross section of 148 countries for the year 2012. The empirical evidence is based on Ordinary Least Squares, Tobit and Quantile regressions. The findings from Ordinary Least Squares and Tobit regressions show a negative relationship between Facebook penetration and the homicide rate. The negative relationship is driven by the 75th quantile of the conditional distribution of the homicide rate. The negative nexus is also driven by upper middle income countries and “Europe and Central Asia”. Three main implications are apparent when the findings are compared and contrasted. First, established findings from OLS and Tobit regressions are driven by countries with above-median levels of homicide. Second, such above-median countries are largely associated with upper middle income countries and nations in “Europe and Central Asia”. Third, modelling the relationship between Facebook penetration and homicide at the conditional mean of homicide may be misleading unless it is contingent on initial levels of homicide and tailored differently across income levels and regions of the world.

The Role of Rural Infrastructure in Reducing Production Costs and Promoting Resource-Conserving Agriculture

The development of rural infrastructure plays an essential role in improving rural livelihoods and enhancing sustainable and environmentally friendly agricultural production. However, little is known about whether rural infrastructure enables the promotion of resource-conserving agriculture and reduces production costs. Understanding the relationship between rural infrastructure and production costs can provide significant information for policy-makers in their efforts to promote resource-saving agriculture that is beneficial to environmental performance. This study contributes to the literature by analyzing the heterogeneous effects of irrigation infrastructure and standard and substandard roads on agricultural production costs, using an unconditional quantile regression model and provincial data from China for the period 1995–2017. The empirical results show that the effects of rural infrastructure on production costs are mixed. In particular, irrigation infrastructure affects production costs positively in the lower quantiles, but it negatively affects production costs in the higher quantiles. In the higher 80th and 90th quantiles, standard and substandard roads affect production costs both negatively and significantly. Our findings suggest that improving rural infrastructure enables the promotion of resource-conserving agriculture and enhances environmental performance, especially for those paying high production costs.

Association of Access to Healthcare with Self-Assessed Health and Quality of Life among Old Adults with Chronic Disease in China: Urban Versus Rural Populations.

This study examined urban–rural differences in the association of access to healthcare with self-assessed health and quality of life (QOL) among old adults with chronic diseases (CDs) in China. The data of 5796 older adults (≥60) with self-reported CDs were collected from the Study on Global Ageing and Adult Health in China, including indicators of self-assessed health and QOL and information on access to healthcare. Associations of access to healthcare with self-assessed health and QOL at the 10th, 50th, and 90th conditional quantiles were determined after controlling individual and household factors, showing that urban patients who received healthcare within two weeks gave higher ratings on self-assessed health scores at the 10th and 50th quantiles. In rural areas, one-year and two-week access to healthcare was found to be associated with QOL scores at the 10th and 90th quantiles, respectively. Marginal effects of using needed health service decreased with a growth in QOL and self-assessed health scores in both urban and rural locations despite these effects being significant across the whole distribution. Overall, access to healthcare affects the self-assessed health and QOL of the elderly with CDs in China, especially in patients with poor health, though differently for urban and rural patients. Policy actions targeted at vulnerable and rural populations should give priority to reducing barriers to seeking health services.

The narrowing gender wage gap in South Korea

This paper investigates the Korean gender wage gap in 2003 and 2016 as well as its changes over time. Using data from the Economically Active Population Survey and unconditional quantile regressions, the wage gap is decomposed at selected quantiles across the wage distribution. The log wage gap forms an inverted-U shape across the distribution. Between 2003 and 2016, the log wage gap falls by 32%, 45%, 35% and 25% at the mean, 10th,50th and 90th quantiles. Reductions in structural and composition effects drive the fall at the bottom and middle of the distribution, while smaller reductions in structural effects result in the smaller fall at the top. Reductions in gender differences in tenure, regular worker status, education and occupations are associated with the fall in the wage gap over time. However, these variables continue to play important roles in the wage gap in 2016.

Socioeconomic inequalities in childhood-to-adulthood BMI tracking in three British birth cohorts

BackgroundBody mass index (BMI) tracks from childhood-to-adulthood, but the extent to which this relationship varies across the distribution and according to socio-economic position (SEP) is unknown. We aimed to address this using data from three British cohort studies.MethodsWe used data from: 1946 National Survey of Health and Development (NSHD, n = 2470); 1958 National Child Development Study (NCDS, n = 7747); 1970 British Cohort Study (BCS, n = 5323). BMI tracking between 11 and 42 years was estimated using quantile regression, with estimates reflecting correlation coefficients. SEP disparities in tracking were investigated using a derived SEP variable based on parental education reported in childhood. This SEP variable was then interacted with the 11-year BMI z-score.ResultsIn each cohort and sex, tracking was stronger at the upper end of the distribution of BMI at 42 years. For example, for men in the 1946 NSHD, the tracking estimate at the 10th quantile was 0.31 (0.20, 0.41), increasing to 0.71 (0.61, 0.82) at the 90th quantile. We observed no strong evidence of SEP inequalities in tracking in men in the 1946 and 1958 cohorts. In the 1970 cohort, however, we observed tentative evidence of stronger tracking in low SEP groups, particularly in women and at the higher end of the BMI distribution. For example, women in the 1970 cohort from low SEP backgrounds had tracking coefficients at the 50th, 70th, and 90th quantiles, which were 0.05 (−0.04; 0.15), 0.19 (0.06; 0.31), and 0.22 (0.02; 0.43) units higher, respectively, than children from high SEP groups.ConclusionTracking was consistently stronger at the higher quantiles of the BMI distribution. We observed suggestive evidence for a pattern of greater BMI tracking in lower (compared to higher) SEP groups in the more recently born cohort, particularly in women and at the higher end of the BMI distribution.

Energy intensity and its differences across China’s regions: Combining econometric and decomposition analysis

To achieve the energy intensity reduction targets set by the Chinese government policymakers need to understand the key drivers that contribute to regional variations in energy intensity. Understanding regional differences will contribute to the design of more effective energy policies. To facilitate this understanding we estimate a penalized panel quantile regression model that accounts for unobserved individual heterogeneity and distributional heterogeneity across the regions of China. The effects of economic growth, urbanization, foreign direct investment, energy structure, and industrialization, on energy intensity differ across quantiles. The effects of economic growth and foreign direct investment on energy intensity are negative and significant at every quantile. A 1% increase in foreign direct investment decreases energy intensity along the entire conditional distribution, ranging from 7.5% at 10th quantile to 3.7% at 90th quantile. The effects of urbanization and industrialization on energy intensity are positive and significant at every quantile. Moreover, a 1% increase in industrialization lifts energy intensity by 54% at 10th quantile and 33% per cent at 90th quantile. The results from a Shapley decomposition model further show that economic growth is the most prominent factor that contributes to energy intensity differences, following by industrialization, foreign direct investment and energy structure.

The Heterogeneous Effect of Prenatal Care on Birth Weight: Evidence from Mexico

Prenatal care has long been identified as an effective strategy to reduce the risk of low birth weight among infants; however, most studies ignore endogeneity and distributional effect of prenatal care on birth weight. Using the instrumental variable quantile regression method, we estimate the effect of prenatal care on birth weight at different quantiles of the birth weight distribution. We find that the effect of a prenatal visit on birth weight is heterogeneous across birth weight quantiles. Infants at the lower birthweight quantiles benefit more from prenatal care compared with infants at the higher birthweight quantiles. The marginal effect of prenatal care visit is 52 grams at the 10th quantiles versus 34 grams at the 90th quantiles. Targeted policies aimed at improving access to prenatal care for women at higher risk of giving birth to low birth infants may help improve the birth endowment of infants.

Diferenciais de rendimento entre os setores de serviços e da indústria no Brasil: uma análise de decomposição

Resumo Este trabalho teve por objetivo analisar o diferencial de rendimentos entre os setores de serviços e da indústria no Brasil com base nas PNADs para os anos de 2004, 2009 e 2014. No primeiro momento, procurou-se analisar o hiato salarial entre os setores citados através da decomposição proposta por Oaxaca e Blinder, seguindo a análise através do método de regressão RIF (Recentered Influence Function). Os resultados sugerem que na decomposição salarial pela média, o hiato salarial se mantém favorável aos trabalhadores do setor de serviços nos três anos analisados. No entanto, a decomposição por quantis indicou que o diferencial de renda entre os setores se mantém mais favorável para o setor de serviços entre 2004 e 2014 para os 75º e 90º quantis da distribuição, mas não nos quantis inferiores, favorecendo mais os trabalhadores da indústria.

Health care expenditure for delivery care between maternity waiting home users and nonusers in Ethiopia.

To compare the health care expenditures between maternity waiting home (MWH) users and nonusers in Ethiopia. A cross-sectional study was done in Ethiopia between December 2017 and June 2018. The study setting included eight health facilities in the Gurage zone of Ethiopia. Health expenditure for delivery care was the outcome variable that was then classified into out-of-pocket (OOP) payments, women's costs, total costs, and overall costs. Those health expenditures were then compared among MWH users and nonusers. OOP payments were further analyzed using quantile regression to explore associated factors. A total of 812 postpartum women were included in this study of whom half were MWH users. Significantly higher OOP payment, women's costs, total costs, and overall cost were found among MWH users compared with nonusers regardless of duration of MWH stay. The MWH users were more likely to have higher OOP payment compared with MWH nonusers in linear and quantile regressions for both unadjusted and adjusted analyses. Higher OOP payments were observed for longer distance traveled and cesarean section (CS) delivery women at the 75th and 90th quantiles of expenditure. Using public transportation was significantly associated with higher OOP payment in all quantile levels. Utilization of MWH incurred higher OOP payments, total costs, women's costs, and overall costs compared with MWH nonusers. Higher OOP payments for delivery care among MWH users were observed in all quantiles of expenditure.

The heterogeneous spatial impact of foreclosures on nearby property values

Foreclosures have negative impacts not just on homeowners, but also on neighboring properties. Due to the heterogeneous characteristics of the housing market, different neighborhoods can be impacted differently by foreclosures. This study focuses on the varying impacts of foreclosures on nearby property values across space. These results can provide insightful directions for decision makers to identify places in greatest need. A semi-parametric approach is applied to allow estimates varying over space. In Chicago, property values most impacted by foreclosures are in the south where the vacancy rate and crime occurrences are high and incomes are low. The spatial variation in impacts is wider for homes priced at the 10th quantile than at the 90th quantile. Moreover, the impacts are generally larger for home prices at the 10th quantile than at the 90th quantile, but the differences are not uniform across space.

Trends of extreme cold events in the central regions of Korea and their influence on the heating energy demand

In recent years, cold waves have come over the Northern Hemisphere, and South Korea has been experiencing extreme cold as well. A number of studies present the recent extreme cold over the Northern Hemisphere as being closely related to the loss of Arctic sea ice. If their assumptions are reasonable, and Arctic warming continues, extreme cold may occur more frequently in the near future. Extreme cold heavily influences the energy demand, and its impact is more severe on low-income people. We compare extreme cold trends from 1976 to 2015 in South Korea by investigating the trends in the winter daily minimum temperature. Quantile regression analysis is applied, and the 10th quantile temperature is taken as an extreme cold event.The results show that all 22 stations have increased tendencies of the winter daily minimum temperature being in the lower 10th quantile over the past 40 years. In contrast, 9 out of 22 stations have decreased tendencies over the last 10 years. Such extreme cold events changed energy consumption behavior. From 2009 to 2015, the peak power demand appeared in winter and not summer, and when an abnormal cold occurred in 2010 and 2013, January heating energy consumption was higher than the average (1997–2015). Energy policy-makers need to assume that worsening of extreme cold is possible in the mid-term and set up measures for it, such as emergency fuel cost support for low-income people. Measures should be taken to ensure that peak loads do not sharply rise in winter. There is a need for a policy that supports heating demand to be easily met by heat rather than electricity.

Examining the influencing factors of CO2 emissions at city level via panel quantile regression: evidence from 102 Chinese cities

ABSTRACTAscertaining the influencing factors of carbon dioxide emissions in Chinese cities is an important issue for policy-makers. This paper investigates the effect of several determinants on carbon emissions per capita in Chinese cities. Non-normally distributed and heterogeneous features of carbon emissions per capita in Chinese cities are considerably important. The empirical results demonstrate that GDP per capita has an increasingly positive impact on carbon emissions per capita due to the growth in household consumption. Urbanization has a slightly decreasing positive effect on carbon emissions per capita with a quantile increase resulting from continuous highway construction. Industrialization has a decreasing positive effect with carbon emission per capita quantile increases because of increasing energy efficiency and lower costs related to carbon reductions. The population has a decreasing negative effect on carbon emissions because of people’s increasing demand for environmental safety. The distributions of emissions per capita conditional on the 10th and 90th quantiles of independent variables also vary considerably. Specific policy implications are provided based on these results.

Relationship between the oil price volatility and sectoral stock markets in oil-exporting economies: Evidence from wavelet nonlinear denoised based quantile and Granger-causality analysis

This paper examines the extent of volatility between oil price and sectoral indices in the Gulf Cooperation Council (GCC) countries by using quantile regression analysis (QRA) for the return's series and denoised series over the period 2006–2017. Four sectors are found to offer diversification opportunities during a high market (i.e.,90th quantile). All the sectors are found interdependent of oil price volatility; however, the bank and insurance sectors are insusceptible to oil price volatility during the 10th, 25th and 75th quantiles. In addition, QRA results for wavelet nonlinear denoising with a soft-thresholding series indicate that all the sectors are interdependent of oil price volatility but that the aggregate market index, transport and telecommunication sectors are insensitive to oil price volatility during the 75th and 90th quantiles. This highlights the usefulness of denoising the financial returns series when applying regression tools. Moreover, the contagion and interdependence between the oil price and stock returns sectors are estimated by frequency domain causality.

Does income inequality facilitate carbon emission reduction in the US?

Abstrct Considering the short- and long-term impacts of income inequality on carbon emissions, as well as the heterogeneity of the emission distribution, this paper employs panel ARDL and quantile regression models to analyze the effect of income inequality on carbon emissions across US states. The findings suggest that higher income inequality increases US carbon emissions in the short term, whereas it promotes carbon reduction in the long term. Furthermore, we find that the absolute values for the coefficients on income inequality in the states from the 70th to the 90th quantiles are larger than those from the 10th to the 40th quantiles. This indicates that income inequality reduces more carbon emissions in states with higher per capita carbon emissions. The results provide important insights for policy makers to improve the quality of economic development and address climate change.