Literatura académica sobre el tema "Census-based socio-economic status index"

AIM: We investigate the evaluation of socio-economic status (SES) inequality on self-rated health (SRH) at women with breast cancer. STUDY DESIGN: Cross-sectional study METHODS: The current study conducted on all 270 breast cancer patients that were admitted to one of the hospitals of Arak University Medical Sciences (Arak, Iran from April to July 2018) by census (using non-random sampling (accessible sampling). SES was calculated by asset-based questionnaire and Principle Component Analysis (PCA) was performed to estimate the families' SES. Concentration Index (C) and Curve (CC) was used to measure SES inequality in SRH. The data were analysed with Stata software. RESULTS: The number of persons with good SRH by the level of SES was 165 (61.1%) and with poor SRH was 105 (38.9%). The number of persons with good SRH in comparison to same-aged people by level of SES was 135 (50%) and with poor SRH was 135 (50%). Concentration index of SRH in all level of SES was 0.061 (SE = 0.03). Also, Concentration index for SRH in comparison to same-aged people at different levels of SES was -0.044 (SE = 0.03). CONCLUSION: The results of this study showed that there is inequality in SRH in a patient with breast cancer of the richest level of SES.

Through an analysis based primarily on British census returns from 1851 to 1911, supplemented by other online genealogical resources, the evolving use of the terms ‘index’ and ‘indexer’ in occupational descriptions is charted. Initially, the majority of entries related to watch, clock and gas meter index makers. Towards the end of the nineteenth century, ‘index clerks’ and others involved in putting things into alphabetical order became more prominent, with the first appearance of an identifiable book indexer in the census returns dating from 1881. Supplementing the existing literature on well-known pioneers of the profession, such as Henry B. Wheatley, the census returns and other sources consulted offer fascinating glimpses into the socio-economic status, family background and everyday lives of ‘ordinary’ indexers in the late nineteenth and early twentieth centuries, the vast majority of whom were female and living in or near London.

Background: Health status is largely determined by socio-economic status. The general health of individuals at higher social hierarchy is better than people in lower levels. Likewise, people with higher socio-economic status have better oral health than lower socio-economic groups. There has not been much work regarding the influence of socio-economic status on the health conditions of children in developing countries, particularly in Iran. The aim of this study was to compare the oral and general health conditions of primary school children of three different socio-economic areas in the city of Shiraz, Iran.Methods: This cross-sectional study was conducted on 335, 8- to 11-year-old primary schoolchildren in Shiraz. The children were selected by a three-stage cluster sampling method from three socio-economically different areas. Tools and methods used by the United Kingdom’s Medical Research Council were used to obtain anthropometric variables as indicators of general health. The Decay, Missing, Filled Teeth (DMFT) Index for permanent teeth, dmft Index for primary teeth, the Modified Developmental Defects of Enamel (DDE) Index, the Gingival Index (GI) and the Debris Index-Simplified (DI-S) were used for oral health assessment. Results: Height (P<0.001), weight (P<0.001), and BMI (P=0.001) significantly increased as the socio-economic status of area increased. GI score (P<0.001), DI-S score (P<0.001), number of permanent teeth with DDE (P=0.008), and number of DDE lesions in permanent teeth (P=0.008) significantly decreased as the socio-economic status of area increased.Discussion: Findings of this study generally confirmed that social gradients exist in both general and oral health status of the primary schoolchildren of Shiraz. The influence of socio-economic status on health condition means children have different life chances based on their socio-economic conditions. These findings emphasize the significance of interventions for tackling socio-economic inequalities in order to improve the health status of children in lower socio-economic areas.

The property tax is the major source of own revenues for most city and county governments, yet economists have had very little definitive information to share with policymakers about the burden that it imposes on local citizens. This is because most previous studies of property taxes have used a Suits index analysis which does not allow for any independent variables other than income. We estimate a regression model using current income and various socio-demographic variables in order to take a more fine grained approach. We use data obtained from the Florida Department of Revenue from 326,976 single family homeowners in four northeast Florida counties geo-coded with the 2010 block group census data. We find that the property tax is regressive with respect to current income. With respect to demographic variables, we find that homeowners over the age of 65 pay a higher average tax rate based on their current incomes. African Americans pay a lower tax rate than other races based on their current income. When we combine income and demographic variables to predict the tax rate paid by a hypothetical low socio-economic status household versus a high socio-economic status household, we find that the high SES household pays a higher average tax rate. Thus, the demographic variables temper the regressivity of the property tax based on current income alone.

Disadvantaged communities tend to have poorer early childhood development outcomes. Access to safe, secure, and stable housing is a well-known social determinant of health but there is a need to examine key features of neighbourhood housing that reduce early childhood development inequities. The 2012 Australian Early Development Census (AEDC), a population-wide measure of early childhood development, and the Australian Bureau of Statistics Socio-economic Index for Areas Index of Relative Socio-economic Disadvantage were used to select fourteen disadvantaged local communities in five Australian states and territories based on those performing better (off-diagonal), or as expected (on-diagonal) on the AEDC relative to their socio-economic profile. Between 2015–2017, qualitative and quantitative housing data were collected in the local communities. In total, 87 interviews with stakeholders, 30 focus groups with local service providers and parents, and Australian Census dwelling information were analysed. A comparative case study approach was used to examine differences in housing characteristics (e.g., public housing, density, affordability, and tenure) between disadvantaged local communities performing ‘better than expected’ and ‘as expected’ on early childhood development. Perceived better housing affordability, objectively measured housing tenure (ownership) and perceived and objectively measured lower-density public housing were housing characteristics that emerged as points of difference for disadvantaged local communities where children had relatively better early childhood development outcomes. These characteristics are potential modifiable and policy sensitive housing levers for reducing early childhood development inequities.

♦BackgroundThe aim of the present study was to investigate the relationship between socio-economic status (SES) and peritoneal dialysis (PD)-related peritonitis.♦MethodsAssociations between area SES and peritonitis risk and outcomes were examined in all non-indigenous patients who received PD in Australia between 1 October 2003 and 31 December 2010 (peritonitis outcomes). SES was assessed by deciles of postcode-based Australian Socio-Economic Indexes for Areas (SEIFA), including Index of Relative Socio-economic Disadvantage (IRSD), Index of Relative Socio-economic Advantage and Disadvantage (IRSAD), Index of Economic Resources (IER) and Index of Education and Occupation (IEO).♦Results7,417 patients were included in the present study. Mixed-effects Poisson regression demonstrated that incident rate ratios for peritonitis were generally lower in the higher SEIFA-based deciles compared with the reference (decile 1), although the reductions were only statistically significant in some deciles (IRSAD deciles 2 and 4 – 9; IRSD deciles 4 – 6; IER deciles 4 and 6; IEO deciles 3 and 6). Mixed-effects logistic regression showed that lower probabilities of hospitalization were predicted by relatively higher SES, and lower probabilities of peritonitis-associated death were predicted by less SES disadvantage status and greater access to economic resources. No association was observed between SES and the risks of peritonitis cure, catheter removal and permanent hemodialysis (HD) transfer.♦ConclusionsIn Australia, where there is universal free healthcare, higher SES was associated with lower risks of peritonitis-associated hospitalization and death, and a lower risk of peritonitis in some categories.

AbstractObjective:The primary purpose of this study is to examine changes in socio-economic inequality in nutritional status (stunting and underweight) among children in Empowered Action Group (EAG) states.Design:The study is based on the most recent two wave’s cross-sectional data from the National Family Health Survey (NFHS) conducted in 2005–2006 (NFHS-3) and 2015–2016 (NFHS-4). The study used height-for-age (stunting) and weight-for-age (underweight) of children as anthropometric indicators.Setting:EAG states including Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Odisha, Rajasthan, Uttarakhand and Uttar Pradesh in India.Participants:The study includes a total of 11 858 (NFHS-3) and 92 630 (NFHS-4) children under 5 years of age.Result:The socio-economic inequality in stunting remained unchanged in all EAG states. At the same time, the inequality in underweight decreased during 2005–2016. On decomposing, the factors contributing to socio-economic inequality revealed that household wealth index, mother’s education and mother’s nutritional status were the largest contributors to stunting (47 %, 24 % and 8 %) and underweight (51 %, 21 % and 16 %), respectively, in 2015–2016.Conclusion:The study concluded the socio-economic inequality in underweight among children under 5 years of age increased over the years in EAG states in India. Altogether, household wealth index, mother’s education and mother’s nutritional status contributed to nearly 80 % to inequality in stunting and 90 % to inequality in underweight in 2015–2016. Hence, efforts should be made to minimise the socio-economic inequality in the nutritional status of children, particularly in EAG states in India.

Background: The mean population mood has been demonstrated to strongly correlate with the prevalence of depression in European populations. Mean population mood has, therefore, been proposed as both a metric to measure the impact of population-level interventions to prevent depression and a target for public health policy. Aim: To demonstrate the relationship between mean population mood and the prevalence of depression using Australian data in order to broaden the applicability of this finding to the Australian population. Methods: We used data from the Geelong Osteoporosis Study to assess the relationship between population mean mood and depression. Participants reported mood symptoms via questionnaire (the Hospital Anxiety and Depression Scale or General Health Questionnaire-12). Depression was diagnosed by semi-structured clinical interview ( Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Non-patient Edition). Stratification by age and socio-economic status was used to create subpopulation groups. Socio-economic status was measured using Index of Relative Socio-economic Advantage and Disadvantage quintiles, an area-based measure based on Australian census data and published by the Australian Bureau of Statistics. The mean subpopulation questionnaire scores and subpopulation prevalence of depression were then analysed using regression and predictive models. Results: Mean subpopulation questionnaire scores correlated well with the prevalence of depression across socio-economic status groups in women but not age groups. Questionnaire scores tended to underestimate the prevalence of depression in the young and overestimate it in the elderly. Conclusion: The mean population mood was demonstrated to correlate with the population prevalence of depression in Australia for women, but not for men. Due to the issues of questionnaire validity and sample size in the oldest age groups, the age analysis is unlikely to be a representative of population characteristics. Further work to identify population determinants of mean mood could potentially create policy targets to reduce the prevalence of depression.

Background.Previous studies have attempted to forecast the costs of mental health care, using clinical and individual variables; the inclusion of ecological measures could improve the knowledge of predictors of psychiatric service utilisation and costs to support clinical and strategic decision-making.Methods.Using a Psychiatric Case Register (PCR), all patients with an ICD-10 psychiatric diagnosis, who had at least one contact with community-based psychiatric services in the Verona Health District, Northern Italy, were included in the study (N = 4558). For each patient, one year's total cost of care was calculated by merging service contact data with unit cost estimates and clinical and socio-demographic variables were collected. A socio-economic status (SES) index was developed, as a proxy of deprivation, using census data. Multilevel multiple regression models, considering socio-demographic and clinical characteristics of patients as well as socioeconomic local characteristics, were estimated to predict costs.Results.The mean annual cost for all patients was 2,606.11 Euros; patients with an ongoing episode of care and with psychosis presented higher mean costs. Previous psychiatric history represented the most significant predictor of cost (36.99%R2increase) and diagnosis was also a significant predictor but explained only 4.96% of cost variance. Psychiatric costs were uniform throughout the Verona Health District and SES characteristics alone contributed towards less than 1% of the cost variance.Conclusions.For all patients of community-based psychiatric services, a comprehensive model, including both patients' individual characteristics and socioeconomic local status, was able to predict 43% of variance in costs of care.

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Introduzione: Studi precedenti condotti in un servizio psichiatrico community-based hanno evidenziato un’associazione inversa tra il SES e l’utilizzazione dei servizi per alcuni gruppi di pazienti. In generale, la letteratura evidenzia un’associazione tra status socio-economico (SES) e misure oggettive e soggettive di salute mentale ed emerge la necessità di una maggior comprensione dei fattori legati all’utilizzazione dei servizi psichiatrici al fine di migliorare l’allocazione delle risorse. Obiettivi: Lo scopo principale di questo studio è quello di valutare come l’utilizzazione di servizi psichiatrici community-based sul territorio italiano possa variare in base al SES dell’area di residenza, tenendo in considerazione anche la prossimità spaziale e le caratteristiche socio-demografiche e cliniche dei pazienti. Metodi: Sono stati inclusi nello studio tutti i pazienti (n 2.759) con diagnosi psichiatrica in base all’ICD-10 che presentavano almeno un contatto tra gennaio e giugno 2009 con tre Unità Operative (UO) Psichiatriche Italiane (Verona, Bollate-Milano, Avellino). I servizi delle UO sono state descritte utilizzando l’International Classification of Mental Health e l’European Service Mapping Schedule. Sono stati calcolati prevalenza ed incidenza trattata ed indicatori di utilizzazione specifici per l’attività di ricovero, di day-care, ambulatoriale e domiciliare, considerando per ciascun paziente tutti i contatti avuti in un periodo di sei mesi. E’ stato calcolato un indice di satus socio-economico a partire da nove variabili censuarie a livello di sezione di censimento (SC) (SC 336.788). Le caratteristiche socio demografiche e cliniche sono state raccolte utilizzando dei questionari e i dati estratti dai Sistemi Informativi; la prossimità spaziale tra il domicilio dei pazienti e la localizzazione delle sedi dei servizi è stata misurata lungo la rete stradale; l’area di residenza è stata descritta in termini di uso del suolo e disponibilità di servizi dedicati alla persona. Queste variabili sono state considerate in modelli di regressione multilevel con distribuzione di Poisson. Risultati: La prevalenza e l’incidenza trattata aumentava con un trend significativo spostandosi nelle sezioni di censimento più deprivate per Verona, ma non per gli altri centri e risultavano differenze tra le diverse categorie assistenziali community-based: emergeva un’associazione inversa tra l’indice SES e la prevalenza di day-care e ambulatoriale per Verona e per la prevalenza di ricoverati per Milano. In generale, il numero di contatti risultava maggiore per i pazienti che vivono in sezioni di censimento più affluenti e, considerando il campione totale, i modelli che consideravano tutte le variabili individuali ed ecologiche erano in grado di spiegare intorno al 20% della varianza spiegata, anche se emergevano differenze per le diverse tipologie assistenziali e tra le tre Unità Psichiatriche, che presentavano differenti caratteristiche e disponibilità di servizi. Conclusioni: Lo status socio-economico assieme ad altre caratteristiche socio-demografiche e cliniche dei pazienti possono essere utilizzate come misure utili per informare i pianificatori dei servizi sui bisogni locali e organizzare e valutare i servizi per la salute mentale. Ulteriori ricerche in quest’area saranno utili per chiarire quali interventi possono migliorare l’equità nell’accesso ai servizi e definire l’allocazione delle risorse economiche.
Introduction: Previous studies conducted in a community-based psychiatric service showed an inverse association between socio-economic status (SES) and services utilization for some group of patients. In general, literature reported evidence for an association between SES and both objective and subjective mental health outcomes and there is a need for a greater understanding of the factors related with psychiatric services utilization to improve allocation of economic resources. Objectives: The main aim of this study was to assess how the utilization of community-based psychiatric services in Italy varies according to the SES of the area of residence, adjusted for spatial proximity and patients’ socio-demographic and clinical characteristics. Methods: All patients with ICD-10 psychiatric diagnosis, who had at least one contact between January and June 2009 with one of three Italian Psychiatric Units (Verona, Bollate-Milan, Avellino) were included (2,759 pts.). Services were described by using the International Classification of Mental Health and the European Service Mapping Schedule. Treated prevalence and incidence and indicators of inpatient, day-care, outpatient and domiciliary service utilization were calculated by considering all contacts occurred for each patient in a period of six months. An ecological socio-economic status index was calculated from nine census variables at census block (CB) level (336,788 CBs). Patients’ clinical and socio-demographic characteristics were collected by using questionnaires and Information Systems data; spatial proximity between patients and facilities locations were measured along the street network; residential area characteristics was described by land characteristics and public services supply. These variables were considered in multilevel regression models with Poisson distribution. Results: General treated prevalence and incidence significantly increased in the more deprived census blocks in Verona, but not in the other centers and differences among category of community services resulted: an inverse association between SES and day care prevalence and outpatient prevalence in Verona and in-patient prevalence in Milan emerged. In general, number of contacts was greater for those living in more affluent CBs and considering the overall sample, the models which included all individual and ecological variables were able to explain around 20% of the variance in utilization; however differences resulted for inpatient, day care, outpatient and domiciliary services and among the three Italian Psychiatric Units, which presented different characteristics and supply of services. Conclusion: Socio-economic status conditions alongside other patients’ characteristics may be used as proxy measures to make planners aware of the local needs and to organize and evaluate mental health services. Further research in this area will help to clarify what interventions are required to improve equality access to mental health services and to refine allocation of economic resources.

AbstractGreater Cairo is a primate, monocentric metropolis with significant socio-economic disparities among its population and neighborhoods. This chapter examines the relationship between income inequality, the welfare regime, centralized governance, settlement type, housing policies, occupational status, and socio-economic segregation. Using data from the 1986, 1996, and 2006 censuses, we report the dissimilarity index to demonstrate the distribution of residents in the Greater Cairo Region by occupational status, we show patterns of socio-economic segregation based on the distribution of the population by categories of occupations across census tracts and employ the location quotient to compare the concentration of the top/bottom groups in each census tract relative to the city average. The results show that growing economic inequality does not necessarily result in greater socio-economic segregation. The results also suggest that social class contributes to residential clustering. While the poorer strata of the Greater Cairo Region were pushed to the periphery and the older urban core, affluent inhabitants were more likely to settle voluntarily in segregated enclaves to isolate themselves from the general population.

AbstractSocio-economic residential segregation is a common feature of almost all Argentinean cities, neatly divided into poor, middle-class, and affluent neighborhoods. At the end of the 1980s, and especially over the 1990s, the process of suburbanization for affluent and upper middle-class groups was consolidated as a generalized model. This study concentrates on the trends and the patterns of socio-economic segregation in Buenos Aires and focuses on two major dimensions of segregation: the spatial concentration patterns of a given social group in specific areas and the degree of social homogeneity within such areas. Socio-economic segregation is described using the highest level of education that a householder has completed as a proxy for socio-economic status. The indices of segregation and dissimilarity are used as the main measure to compare the level and changes of residential segregation but other metrics—such as location quotient index—are also used to estimate the degree of homogeneity or heterogeneity in neighboring areas. This study uses population and household census data from 1991, 2001, and 2010 provided by the National Institute of Statistics and Censuses (INDEC), and the data are presented at the spatial disaggregation level of block groups called ‘radios censales’.

AbstractChina’s rapid economic growth since the early 1980s has been accompanied by a substantial increase in economic inequality. Economic restructuring, rural–urban migration, globalization and marketization have jointly led to a transformation of the socio-spatial structure of large Chinese cities. Although a handful of studies have examined the level and pattern of socioeconomic segregation in a particular Chinese city using neighbourhood-level census data from the year 2000, little research has been done to investigate in-depth changes in the level and pattern of segregation using more up to date and more geographically detailed data. This chapter aims to examine the levels, patterns and drivers of socioeconomic segregation in Shanghai, China, using neighbourhood-level and subdistrict-level data from the 2000 and 2010 decennial population census. This chapter uses the dissimilarity index to measure the overall level of socioeconomic segregation by occupation and household registration (hukou) status. Based on a location quotient and neighbourhood composition, it also illustrates the change in the spatial pattern of segregation. The chapter ends with a discussion on the possible drivers of segregation and policy suggestions to combat segregation in large Chinese cities.

AbstractSocioeconomic segregation has become a common phenomenon, both in the Global North and Global South, and highly relates to income inequality. The merging of these two notions affects the geography of residential areas which are based on the socio-occupational composition. This chapter focuses on the Jakarta Metropolitan Area (JMA). Not only is Jakarta the largest metropolitan area in Southeast Asia, it is also one of the most dynamic. Batavia, the colonial capital of the former Dutch East Indies in the first half of the twentieth century, was a small urban area of approximately 150,000 residents. In the second half of the century, Batavia became Jakarta, a megacity of 31 million people and the capital of independent Indonesia was beset with most of the same urban problems experienced in twenty-first-century Southeast Asia, including poverty, income inequality, and socioeconomic segregation. This study aims to identify the correlation among income inequality, socioeconomic segregation, and other institutional and contextual factors which caused residential segregation in JMA. The analysis consists of two stages. First, we examine income inequality measured by the Gini Index as well as the occupational structure based on the International Standard Classification of Occupations (ISCO). Second, we investigate residential segregation by using the Dissimilarity Index as a result of socioeconomic intermixing in residential areas. The data in this study comes from multiple sources including Indonesia’s Central Bureau of Statistics, Indonesia’s National Socio-economic Survey (Susenas), Indonesia’s Economic Census, Jakarta’s Regional Bureau of Statistics, and policies related to the housing system and investment in the JMA. This study also produces maps of socioeconomic segregation patterns from several sources including Jakarta’s Geospatial Information Centre, Jakarta’s Spatial Plan Information System, and the Indonesian Poverty Map by the SMERU Research Institute.

AbstractMaterial deprivation is a key aspect of social exclusion, and the domain of economic exclusion, for the older population. In this chapter we utilised cross-sectional data from Wave 5 (2013) of the Survey of Health and Retirement in Europe (SHARE) and logistic regression analysis to assess the variation in material deprivation of the population aged 50+ across four geographic clusters of welfare regimes in Europe. We used the SHARE-based Material Deprivation Index (MDI) to assess the associations between material deprivation and socio-demographic factors (age, gender, education, economic activity status, household type, number of children, residential area, chronic diseases and limitations of daily activities, and origin). We observed a pronounced variation in material deprivation among the older population across welfare clusters, with high levels of MDI in the Eastern and Southern clusters. Living alone, having a large number of children, low education, activity limitations, and being of immigrant origin significantly increase the risk of material deprivation in older age in all clusters. The study also identified subgroups of older persons that have an increased risk of material deprivation in some but not all clusters, such as those aged 80+ and rural residents in the Southern and Eastern clusters.

AbstractOriginally, the concept of resilience refers to one’s capacity to cope with unexpected shocks and unpredictable situations. Originating from ecological theories, the approach has gained ground in social sciences. In the context of education, the concept has been applied to explain how disadvantaged students can overcome structural constraints and become educationally successful and socially mobile (Werner, E. E., Vulnerable but invincible: a longitudinal study of resilient children and youth. McGraw-Hill, New York, 1982; Masten A. S., American Psychologist 56: 227–238, 2001; Reid, R., Botterrill L. C., Australian Journal of Public Administration 72:31–40, 2013; Máté, D., Erdélyi Társadalom 13:43–55, 2015).This paper is based on the analysis of the Hungarian National Assessment of Basic Competences (NABC) database which has been conducted annually since 2001. We created a typology of school resilience based on the schools’ social and ethnic profile as well as their performance indicators. We defined those schools resilient which over perform others with similar social intake, and we also identified irresilient schools which underperform others with similar social intake. The school types were created by correlating the socio-economic status index (SES) and school performance.Since the NABC database provides us with data on the estimated rate of Roma students in each school, it is possible to take into account the schools’ ethnic intake in the analysis of resilience. We conducted statistical analyses to compare the performance of resilient and irresilient schools in the light of the ratio of Roma students. Finally, we seek answers to the question whether ethnic segregation correlates with school achievement in Hungary. We could identify some crucial institutional factors contributing to resilience (or school success) in the case of schools with relatively high proportion of Roma students.

AbstractOne of the main goals of urban planning is to reduce ‘urban inequalities’ between neighbourhoods to promote socio-spatial cohesion within the city. Cohesion is achieved by reducing the social and spatial distance of targeted areas compared to the city as a whole. This chapter aims to contribute to the study of this effect by analysing the social change in intervened neighbourhoods compared to change in all the non-intervened. The areas of five major Spanish cities (Madrid, Malaga, Sevilla, Valencia y Zaragoza), where URBAN initiatives were implemented, were analysed. This chapter presents the change in the neighbourhoods’ relative position—based on residents’ socio-economic status—within the city hierarchy. The difference was explored by comparing and analysing the census data for 1991 and 2001. Evidence suggests that intervened neighbourhoods improved their relative position within the city raking.

AbstractSince the 2000s, Lima city shows important changes in its socio-spatial structure, decreasing the long-established opposition between the centre and the periphery, developing a more complex arrangement. Sustained national economic growth has allowed better socio-economic conditions in different areas of the city. However, high inequality still remains in the ways of production of urban space, which affects residential segregation. To identify possible changes in the segregation patterns of Metropolitan Lima, this study focuses on the spatial patterns of occupational groups, examining their causes and relation with income inequality. The analysis is based on the 1993 and 2007 census data, measuring residential segregation by the Dissimilarity Index, comparing with the Diversity Index. The results confirm trends towards increased segregation between occupational groups. Top occupational groups are concentrated in central areas, expanding into adjacent districts. Bottom occupational groups are over-represented in distant neighbourhoods. In-between, a new, more mixed, transitional zone has emerged in upgraded formerly low-income neighbourhoods. Areas of lower occupational diversity coincide with extreme income values, forming spaces of greater segregation. In the metropolitan centre–periphery pattern, the centre has expanded, while the periphery has been shifted to outer peripheral rings.

AbstractIn urban environments, sustainable access to water resources depends on many factors, including climatic, social and economic conditions characterizing the surrounding environment. For urban areas in mountain environments these conditions are compounded by stressors resulting from climate change, such as drought, as well as physical remoteness, economic marginalization and poverty, phenomena which impose limits on access to water. Based on Sustainable Development Goals (SDGs) 1, 6 and 13, which were part of the 2030 Agenda for Sustainable Development adopted by UN member states in 2015, in this paper we assess the impact of urban drought on water security in the mountain city of Phuthaditjhaba, South Africa. World Meteorological Organization - Time Series (4.04) climate (precipitation and maximum temperature) data for Phuthaditjhaba were analysed for trends for the period between 1960 and 2019. Trends of Standardized Precipitation Index values and Maximum Temperatures were used to determine how climate change has affected Phuthaditjhaba’s sources of water supply, namely the Fika Patso and Metsimatsho dams. A sample of Landsat images from the same period was used to determine how the two water bodies have responded to the change over time. The results indicate that the two reservoirs have shrunk due to climate change induced drought, thus worsening water insecurity in the city. The results also indicate that mean annual stream discharge is projected to decrease by 39% for the 2016–2045 period. Lastly, based on government reports on water shortages in Phuthaditjhaba and other secondary sources, the results also indicate that though 90% of Phuthaditjhaba’s population has access to potable water, only 55% of the residents have access to reliable water supply. We conclude that without urgent government intervention the future of the livelihoods of the poor majority of Phuthaditjhaba’s residents will remain bleak due to dwindling water resources, making SDG 6, and those influenced by it, unattainable.

This study investigates the role of various socioeconomic determinants and vaccination rates in the spread of Covid-19 in a spatial setting in Turkey. For this aim, we employ the 41 sub-indicators of Life Index in Provinces data provided by the Turkish Statistical Institute which is obtained based on the Organization for Economic Cooperation and Development (OECD) Better Life Index approach. Our results indicate no global interactions in the transmission process of the disease among Turkish provinces. This means that the infection burden in the neighboring province does not significantly affect the infection burden of a given state. Yet, we show that vaccination rates and the median age of a neighboring province significantly affect the number of total cases in a given province. We find that as the vaccination rates of a neighboring province rise, the number of total cases in a given province also increases. This finding can be attributed to the “neighbor–reliant immunity” concept. It seems that people with vaccine hesitancy toward Covid-19 feel safer without a vaccine when their neighbors are mostly vaccinated. Last, people with a higher satisfaction rate with their health status are more likely to catch the disease due to underestimation of negative consequences.

In recent decades, remote sensing methods have often been used to estimate population density, especially using data on nighttime illumination. Information about the spatial distribution of the population is important for understanding the dynamics of cities and analyzing various socio-economic, environmental and political factors. In this work, we have formed layers of the nighttime light index, surface temperature and vegetation index according to the SNPP/VIIRS satellite system for the territory of the central and southern regions of the Krasnoyarsk krai. Using these data, we have calculated VTLPI (vegetation temperature light population index) for the year 2013. The obtained values of the VTLPI calculated for a number of settlements of the Krasnoyarsk krai were compared with the results of the population census conducted in 2010. In total, we used census data for 40 settlements. Analysis of the data showed that the relationship between the value of the VTLPI index and the population density in the Krasnoyarsk krai can be adequately fitted (R 2 = 0.65) using a linear function. In this case, the value of the root-meansquare error was 345, and the relative error was 0.09. Using the obtained model equation and the spatial distribution of the VTLPI index using GIS tools, the distribution of the population over the study area was estimated with a spatial resolution of 500 meters. According to the obtained model and the VTLPI index, the average urban population density in the study area exceeded 500 people/km2 . Comparison of the obtained data on the total population in the study area showed that the estimate based on the VTLPI index is about 21% higher than the actual census data.

Governments in economically free societies; aim to increase the level of sustainable growth and prosperity of the country while allowing labor, capital, and products to move freely. To determine the economic freedom of the countries, it publishes indices by various independent institutions, and thus, their position in comparison to other countries is determined. Especially ın order to determine the group structure among countries that are close to each other in terms of regions; In addition to revealing the status of the region in terms of economic freedom, it is beneficial in terms of acting with similar countries for plans and determining policies. In the index called the Economic Freedom Index published annually by the Heritage Foundation, a ranking including the countries that are members of the United Nations is made. This index value is measured through variables based on 12 quantitative and qualitative factors divided into four broad categories of economic freedom. In this study in which 2021 data was used, cluster analysis, one of the multivariate statistical analysis techniques, was preferred to group countries. Findings from the analysis showed that Eurasian countries were divided into 4 different clusters according to the economic freedom index. Among the countries, the most striking country was North Korea. In the formation of this situation. It can be thought that it is due to the state's adoption of an excessively interventionist policy in the economic policies of the country.

Pressure from land use patterns, climate change, and urbanisation on rivers is an important socio-ecological issue that requires management and biomonitoring. The ecologi-cal status of the Venta River at Kuldīga was assessed using bioindicators, specifically diatoms, which are widely used in monitoring of streams and rivers worldwide, especially in European countries. Ecological status was defined by calculating Specific Pollution Sensitivity Index (IPS). In addition, diatom diversity was determined in the studied part of the river. A total of six sam-pling sites were selected along a 10 km stretch of the river in the territory of Kuldīga. The aver-age distance between sampling sites was 1.5 km. A total of 118 taxa were identified in all samples. The highest species diversity (67 taxa) was observed in sample 2. Individual rarefaction was calculated if exactly 500 diatom valves were counted in all samples. The lowest species diversity was observed in samples 6 (45 taxa) and 6A (17 taxa). Samples 1 and 5 were the most similar in terms of species composition. This is probably because both sites have similar physical characteristics that include sandy beaches with a slow current. The most abundant diatoms were Cocconeis placentula Ehrenberg, Amphora pediculus (Kützing) Grunow, Nitzschia fossilis (Grunow) Grunow, Navicula capitatoradiata Germain ex Gasse, Navicula antonii Lange-Bertalot, Amphora libyca Ehrenberg, and Sellaphora nigri (De Notaris) Wetzel & Ector, which are commonly found in eutrophic waters. Diatom analysis suggests that the Venta might be at risk for eutrophication. For the most abundant diatom taxa, the suscep-tibility to pollution was assessed as III (medium), but there were also diatoms with IV and V (very sensitive to pollution). This shows that the Venta River in Kuldīga overall has low levels of pollution. All study sites were rated as having ‘good’ ecological status according to the IPS index (12.4-14.1 IPS).

Data on Health Literacy in the population of Latvia is limited. The aim of the study was to determine the Health Literacy impacting factors of inhabitants of Vidzeme Statistical region in Latvia (LV008). Respondent survey (n = 383), using a paper-and-pencil self-administered approach and telephone interviews, was conducted based the European Health Literacy Survey Questionnaire (HLS-EU-Q47). In order to ensure internal consistency and reliability, the authors used Cronbach’s α test (α = 0.965). The confirmatory factor analysis (CFA) allowed to determine that factor results differentiate between genders and there is a strong positive correlation (r = 0.945), that impacts results. Factors Access, Appraise and Apply explained each 30 % of the variance, and factors Understand explained 31 %. HL index division by gender indicated that 47.4 % of female respondents and 46.6 % of male respondents have “limited health literacy” (“inadequate” + “problematic”). The largest age group among respondents are 18-39-year old where there is lower level of education and lower income. However, cases have been observed when respondents even with higher education have “limited health literacy,” which indicates towards a need for further HL research in Latvia, because compared to HL of other member states, LV008 HL index is by 38.9 % larger than the EU average (47.6 %).

The paper is aimed at quantitative evaluation of the level of countries’ financial solvency based on the use of a multidimensional methodical toolkit for evaluating financial indicators of a country’s development, which results in the construction of the appropriate integral security indices. Unlike other methods to assess the level of security, the proposed approach makes it possible to determine not only the integrated level of a financial component of the economic security but also to calculate the quantitative thresholds of the financial indicators aggregated in the integral index (gold and currency reserves, external debt per capita, changes in the official local currency rate, budget deficit/surplus to GDP); going beyond the threshold values is a signal of the increased risk and lack of solvency. Comprehensive consideration of the financial indicators, taken from the official statictic databases or calculated basing on the official statictics, in the structure of the integral index helps quantify the level of a financial component in the system of ensuring countries’ economic security. The proposed approach is approbated in terms of the countries for which the level of a component of the financial solvency (critical, dangerous, unsatisfactory, safe, and optimal) has been calculated. From the practical viewpoint, the proposed toolkit makes it possible to identify actual and potential threats to the countries’ sustainable development. The obtained integral indices of security can be used as the variables in economic and mathematical models while evaluating the effect of security status on the global economic development and positions of certain countries, communities, and regions in the system of world economic relationships.

An essential aspect of deepening the level of economic integration between European economies is the reduction of mutual economic disparities, which is especially emphasized by the formation of the supranational monetary authority of the Euro-zone member states. However, fixing the currency for the euro and losing monetary sovereignty in the circumstances of a structurally heterogeneous system meant that the same monetary policy provoked different repercussions for member states. This research aims to point out the differences in the exchange rate transmission mechanism between the representatives of two groups of Euro-zone member states: the core of the EZ (Germany, Finland, Belgium, and France) and the periphery of the EZ (Greece, Spain, Portugal, Ireland), in the 1999M1-2021M1 time horizon. Empirical findings are based on estimates of the VAR model, i.e. derived impulse response functions in the circumstances of shock transmission (nominal effective exchange rate) to inflation (consumer price index). The results of the research indicate the asymmetry of the exchange rate transmission mechanism in terms of a more pronounced and longer degree of exposure of peripheral economies to shocks of the nominal exchange rate compared to the representatives of the core of the Euro-zone. Empirical findings confirm the asymmetry of the exchange rate transmission mechanism as one of the indicators of the weakness of the Euro-zone, given the inflationary diversity and the consequent anomalies of the monetary union with heterogeneous membership.

The last years are distinguished by increasing the awareness of companies towards sustainable business, going beyond their traditional role of providing goods and services at competitive prices to meet customer requirements. Thus, companies will have to consider the effects of their best practices on the environment and society, in order to contribute to the progress of society and the protection of the environment, the essence of sustainable development being the coexistence of economic and social relations and environmental protection by implementing economic, social and environmental objectives. We can see that every company that seeks to become sustainable must consider approaches based on sustainable business practices geared to meeting customer needs. For companies listed on the stock market, the index that stands next to each company is the one that shows the level of sustainability, through corporate sustainability, long-term value is created for shareholders, taking into account all social factors, those related to the environment, as well as economic ones. All these considerations have led to the establishment of the general objective of the paper, through which the authors aim to explain and present the importance of sustainability/sustainable development in energy companies in conjunction with the UN guidelines on business and human rights, which will address with priority to the Sustainable Development Goals (SDGs) for 2030.

The establishment and enlargement of the European Union have been partly motivated by catching up on higher living standards of living. This study examines whether developmental convergence can be demonstrated among the NUTS 2 regions of the Union. The existence of convergence among the EU is generally approached from an economic perspective by using macroeconomic indicators. Although these metrics are suitable for comparing the performance of Member States, they are less reflective of each country's social well-being. Several analyses, usually based on mortality indicators, have been conducted in an attempt to characterize convergence from a social point of view. However, these calculations are usually limited to country-level convergence analyses with diseases and causes of death in their focus. Thus, this study applies a complex measure, the Human Development Index (HDI), to examine convergence at a regional level. For this purpose, the regional HDI is calculated and the existence of absolute and conditional beta convergence is assessed. Our calculations confirm convergence among EU regions over the period between 2006 and 2017, but the analysis also reveals divergent trends and various national characteristics that will call into question the long-term sustainability of equalization.

The article considers the possibility of analyzing the dynamics of changes in the characteristics of time series obtained on the basis of recurrence plots. The possibility of using the studied indicators to determine the presence of critical phenomena in economic systems is considered. Based on the analysis of economic time series of different nature, the suitability of the studied characteristics for the identification of critical phenomena is assessed. The description of recurrence diagrams and characteristics of time series that can be obtained on their basis is given. An analysis of seven characteristics of time series, including the coefficient of self-similarity, the coefficient of predictability, entropy, laminarity, is carried out. For the entropy characteristic, several options for its calculation are considered, each of which allows the one to get its own information about the state of the economic system. The possibility of using the studied characteristics as precursors of critical phenomena in economic systems is analyzed. We have demonstrated that the entropy analysis of financial time series in phase space reveals the characteristic recurrent properties of complex systems. The recurrence entropy methodology has several advantages compared to the traditional recurrence entropy defined in the literature, namely, the correct evaluation of the chaoticity level of the signal, the weak dependence on parameters. The characteristics were studied on the basis of daily values of the Dow Jones index for the period from 1990 to 2019 and daily values of oil prices for the period from 1987 to 2019. The behavior of recurrence entropy during critical phenomena in the stock markets of the USA, Germany and France was studied separately. As a result of the study, it was determined that delay time measure, determinism and laminarity can be used as indicators of critical phenomena. It turned out that recurrence entropy, unlike other entropy indicators of complexity, is an indicator and an early precursor of crisis phenomena. The ways of further research are outlined.

The United States Army Corps of Engineers is tasked with maintaining waterborne transportation system elements. Understanding channel utilization by vessels informs decisions regarding operations, maintenance, and investments in those elements. Historically, investment decisions have been informed by safety, environmental considerations, and projected economic benefits of alleviating channel restrictions or shipping delays (usually derived from models). However, quantifying causes and impacts of shipping delays based on actual historical vessel location data and then identifying which causes could be ameliorated through investment has been out of reach until recently. In this study, Automatic Identification System vessel position reports were used to develop quantitative measures of transit and dwell-time reliabilities for commercial vessels calling at the Port of Baltimore, Maryland. This port has two deep-water approaches: Chesapeake Bay and the Chesapeake and Delaware Canal. Descriptive metrics were determined for each approach, including port cycle time, harbor stay hours, travel time inbound, and travel time outbound. Then, additional performance measures were calculated: baseline travel time, travel time index, and planning time index. The key finding of this study is that the majority of variability in port cycle time is due to the variability in harbor stay hours, not from channel conditions or channel restrictions.

Review question / Objective: P：Liver cirrhosis patients with risk factors associated with HE attack;HE patients caused by chronic liver diseases represented by cirrhosis. I: Rifaximin treatment. C: Other drugs or placebo. O：HE incidence; HE improvement; All-cause mortality; Blood ammonia level; PSE index; mental state; NCT-A; NCT-B; Adverse events. Condition being studied: Hepatic encephalopathy(HE) is a neuropsychiatric disorder syndrome based on metabolic disorders, which is caused by severe acute and chronic liver dysfunction or various abnormalities of portosystemic shunt (hereinafter referred to as portosystemic shunt). The research data shows that the prevalence of OHE in patients with cirrhosis is 10-14%, and the prevalence of HE in patients with decompensated cirrhosis is 16-21%. HE can lead to 60-80% of patients with liver cirrhosis with mild cognitive impairment, affecting their ability of daily life and quality of life. When OHE occurs, the one-year mortality rate of patients with liver cirrhosis is 64%, which brings a heavy economic burden to patients and public health resources. Therefore, the prevention and early management of HE is very important.

To reduce financial risk and N losses to the environment, fertilization methods are needed that improve NUE and increase the quality of wheat. In the literature, ample attention is given to grid-based and zone-based soil testing to determine the soil N available early in the growing season. Plus, information is available on in-season N topdressing applications as a means of improving GPC. However, the vast majority of research has focused on wheat that is grown under N limiting conditions in sub-humid regions and irrigated fields. Less attention has been given to wheat in dryland that is water limited. The objectives of this study were to: (1) determine accuracy in determining GPC of HRSW in Israel and SWWW in Oregon using on-combine optical sensors under field conditions; (2) develop a quantitative relationship between image spectral reflectance and effective crop physiological parameters; (3) develop an operational precision N management procedure that combines variable-rate N recommendations at planting as derived from maps of grain yield, GPC, and test weight; and at mid-season as derived from quantitative relationships, remote sensing, and the DSS; and (4) address the economic and technology-transfer aspects of producers’ needs. Results from the research suggest that optical sensing and the DSS can be used for estimating the N status of dryland wheat and deciding whether additional N is needed to improve GPC. Significant findings include: 1. In-line NIR reflectance spectroscopy can be used to rapidly and accurately (SEP <5.0 mg g⁻¹) measure GPC of a grain stream conveyed by an auger. 2. On-combine NIR spectroscopy can be used to accurately estimate (R² < 0.88) grain test weight across fields. 3. Precision N management based on N removal increases GPC, grain yield, and profitability in rainfed wheat. 4. Hyperspectral SI and partial least squares (PLS) models have excellent potential for estimation of biomass, and water and N contents of wheat. 5. A novel heading index can be used to monitor spike emergence of wheat with classification accuracy between 53 and 83%. 6. Index MCARI/MTVI2 promises to improve remote sensing of wheat N status where water- not soil N fertility, is the main driver of plant growth. Important features include: (a) computable from commercial aerospace imagery that include the red edge waveband, (b) sensitive to Chl and resistant to variation in crop biomass, and (c) accommodates variation in soil reflectance. Findings #1 and #2 above enable growers to further implement an efficient, low cost PNM approach using commercially available on-combine optical sensors. Finding #3 suggests that profit opportunities may exist from PNM based on information from on-combine sensing and aerospace remote sensing. Finding #4, with its emphasis on data retrieval and accuracy, enhances the potential usefulness of a DSS as a tool for field crop management. Finding #5 enables land managers to use a DSS to ascertain at mid-season whether a wheat crop should be harvested for grain or forage. Finding #6a expands potential commercial opportunities of MS imagery and thus has special importance to a majority of aerospace imaging firms specializing in the acquisition and utilization of these data. Finding #6b on index MCARI/MVTI2 has great potential to expand use of ground-based sensing and in-season N management to millions of hectares of land in semiarid environments where water- not N, is the main determinant of grain yield. Finding #6c demonstrates that MCARI/MTVI2 may alleviate the requirement of multiple N-rich reference strips to account for soil differences within farm fields. This simplicity will be less demanding of grower resources, promising substantially greater acceptance of sensing technologies for in-season N management.

Objectives: We seek to establish the basis for improving cotton productivity under arid conditions, by studying the water use efficiency - evaporative cooling interrelationship. Specifically, we will test the hypothesis that cotton productivity under arid conditions can be improved by combining high seasonal WUE with efficient evaporative cooling, evaluate whether high WUE and/or evaporative cooling are based on specific physiological factors such as diurnal flexibility in stomatal conductance, stomatal density, photosynthetic capacity, chlorophyll fluorescence, and plant water status. Genes influencing both WUE and evaporative cooling, as well as other parameters such as economic products (lint yield, quality, harvest index) of cotton will also be mapped, in order to evaluate influences of water relations on these parameters. Approach: Carbon isotope ratio will be used to evaluate WUE, accompanied by additional parameters to elucidate the relationship between WUE, evaporative cooling, and cotton productivity. A detailed RFLP map will be used to determine the number, location, and phenotypic effects of genes underlying genetic variation in WUE between cultivated cottons, as well as test associations of these genes with traits of economic importance such as harvest index, lint yield, and lint quality. Major Conclusions: Productivity and quality of cotton grown under well-watered versus water-limited conditions was shown to be partly accounted for by different quantitative trait loci (QTLs). Among a suite of physiological traits often found to differ between genotypes adapted to arid versus well-watered conditions, genetic mapping implicated only reduced plant osmotic potential in improved cotton productivity under arid conditions. Our findings clearly implicate OP as a major component of cotton adaptation to arid conditions. However, testing of further physiological hypotheses is clearly needed to account for additional QTL alleles conferring higher seed-cotton yield under arid conditions, such as three of the five we found. Near-isogenic lines being made for QTLs discovered herein will offer a powerful new tool useful toward identification of the underlying gene(s) by using fine-scale mapping approaches (Paterson et al 1990). Implications: Adaptation to both arid and favorable conditions can be combined into the same genotype. We have identified diagnostic DNA markers that are being applied to creation of such desirable genotypes. Simultaneous improvement of productivity (and/or quality) for both arid and irrigated conditions will require more extensive field testing and the manipulation of larger numbers of genes, reducing the expected rate of genetic gain These difficulties may be at least partly ameliorated by efficiencies gained through identification and use of diagnostic DNA markers. Genomic tools and approaches may expedite adaptation of crops to arid cultivation, help to test roles of additional physiological factors, and guide the isolation of the underlying genes that protect crop performance under arid conditions.

Floods are major water-related disasters that affect millions of people resulting in thousands of mortalities and billiondollar losses globally every year. Flood Early Warning Systems (FEWS) - one of the floods risk management measures - are currently operational in many countries. The UN Office for Disaster Risk Reduction recognises their importance and strongly advocates for an increase in their availability under the targets of the Sendai Framework for Disaster Risk Reduction, and Sustainable Development Goals (SDGs). However, despite widespread recognition of the importance of FEWS for disaster risk reduction (DRR), there’s a lack of information on their availability and status around the world, their benefits and costs, challenges and trends associated with their development. This report contributes to bridging these gaps by analyzing the responses to a comprehensive online survey with over 80 questions on various components of FEWS (risk knowledge, monitoring and forecasting, warning dissemination and communication, and response capabilities), investments into FEWS, their operational effectiveness, benefits, and challenges. FEWS were classified as technologically “basic”, “intermediate” and “advanced” depending on the existence and sophistication of FEWS` components such as hydrological data = collection systems, data transfer systems, flood forecasting methods, and early warning communication methods. The survey questionnaire was distributed to flood forecasting and warning centers around the globe; the primary focus was developing and least-developed countries (LDCs). The questionnaire is available here: https://inweh.unu.edu/questionnaireevaluation-of-flood-early-warning-systems/ and can be useful in its own right for similar studies at national or regional scales, in its current form or with case-specific modifications. Survey responses were received from 47 developing (including LDCs) and six developed countries. Additional information for some countries was extracted from available literature. Analysis of these data suggests the existence of an equal number of “intermediate” and “advanced” FEWS in surveyed river basins. While developing countries overall appear to progress well in FEWS implementation, LDCs are still lagging behind since most of them have “basic” FEWS. The difference between types of operational systems in developing and developed countries appear to be insignificant; presence of basic, intermediate or advanced FEWS depends on available investments for system developments and continuous financing for their operations, and there is evidence of more financial support — on the order of USD 100 million — to FEWS in developing countries thanks to international aid. However, training the staff and maintaining the FEWS for long-term operations are challenging. About 75% of responses indicate that river basins have inadequate hydrological network coverage and back-up equipment. Almost half of the responders indicated that their models are not advanced and accurate enough to produce reliable forecasts. Lack of technical expertise and limited skilled manpower to perform forecasts was cited by 50% of respondents. The primary reason for establishing FEWS, based on the survey, is to avoid property damage; minimizing causalities and agricultural losses appear to be secondary reasons. The range of the community benefited by FEWS varies, but 55% of FEWS operate in the range between 100,000 to 1 million of population. The number of flood disasters and their causalities has declined since the year 2000, while 50% of currently operating FEWS were established over the same period. This decline may be attributed to the combined DRR efforts, of which FEWS are an integral part. In lower-middle-income and low-income countries, economic losses due to flood disasters may be smaller in absolute terms, but they represent a higher percentage of such countries’ GDP. In high-income countries, higher flood-related losses accounted for a small percentage of their GDP. To improve global knowledge on FEWS status and implementation in the context of Sendai Framework and SDGs, the report’s recommendations include: i) coordinate global investments in FEWS development and standardise investment reporting; ii) establish an international hub to monitor the status of FEWS in collaboration with the national responsible agencies. This will support the sharing of FEWS-related information for accelerated global progress in DRR; iii) develop a comprehensive, index-based ranking system for FEWS according to their effectiveness in flood disaster mitigation. This will provide clear standards and a roadmap for improving FEWS’ effectiveness, and iv) improve coordination between institutions responsible for flood forecasting and those responsible for communicating warnings and community preparedness and awareness.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.