scholarly journals ANALISIS KERENTANAN PERIKANAN TANGKAP AKIBAT PERUBAHAN IKLIM PADA SKALA PROVINSI (Province Scaled Fisheries Vulnerability on Climate Change)

2018 ◽  
Vol 8 (2) ◽  
pp. 223
Author(s):  
Allasay Kitsash Addifisyuka Cintra ◽  
Isdradjad Setyobudiandi ◽  
Achmad Fahrudin
Keyword(s):  
Climate Change ◽  
Adaptive Capacity ◽  
Composite Index ◽  
High Sensitivity ◽  
Vulnerability Index ◽  
Medium Term ◽  
Short Term ◽  
High Exposure ◽  
Purposive Sampling

<p align="center"><strong><em>ABSTRACT</em></strong><strong></strong></p><p><em>Fisheries has significant roles for the Indonesian economy. Climate change influences Indonesian fisheries through a range of direct and indirect pathaway. A scientific based approach such as vulnerability is needed to determine the risks of climate change and adaptation strategies. Therefore, this study was conducted to analyze the vulnerability of fisheries to climate change on  province scaled in Indonesia. Vulnerability index (VI) is obtained with composite index of exposure (EI), sensitivity (SI) and adaptive capacity (ACI) of ten provinces representing the eastern and western parts of Indonesia by using purposive sampling method. Source of data for indices variables were using recorded datas from relevant institutions. The results showed that fisheries status of North Sulawesi (VI = 0,78), Central Sulawesi (VI = 0,72) and Gorontalo (VI = 0,61) were very vulnerable despite the composition of constituent vulnerability index was different. This difference determined the specific policies to be taken to each province to reduce vulnerability.</em> <em>Short term policies are taken to reduce the vulnerability of the most vulnerable areas on Sulawesi Utara, Sulawesi Tengah, and Gorontalo. Medium term policy is carried out in high sensitivity areas, namely Kepulauan Riau, Sulawesi Utara, and Kalimantan Timur and in low adaptive capacity areas such as Jambi, Gorontalo and Bangka Belitung. Long term policy is conducted for areas with high exposure such as Sulawesi Tengah, Sulawesi Utara and Kalimantan Timur.</em></p><p><strong><em>Keywords</em></strong><em>: Climate change, fisheries, vulnerability, province</em></p><p><em><br /></em></p><p align="center"><strong>ABSTRAK</strong><strong></strong></p>Perikanan tangkap memiliki peranan penting bagi perekonomian Indonesia. Adanya perubahan iklim akan berdampak merugikan secara langsung maupun tidak langsung pada perikanan tangkap Indonesia. Suatu pendekatan ilmiah diperlukan untuk menentukan risiko perubahan iklim dan strategi adaptasi perikanan tangkap, salah satunya adalah analisis kerentanan (<em>Vulnerability</em>). Oleh karena itu penelitian ini dilakukan untuk menganalisis kerentanan perikanan tangkap akibat perubahan iklim pada skala provinsi di Indonesia. Indeks kerentanan (VI) didapatkan dengan mengkompositkan indeks keterpaparan (EI), kepekaan (SI) dan kapasitas adaptif (ACI) dari sepuluh provinsi yang mewakili bagian timur dan barat Indonesia dengan metode <em>purposive sampling. </em>Sumber variabel penyusun indeks variabel menggunakaan rekaman data dari instansi terkait.  Hasil penelitian menunjukkan bahwa provinsi Sulawesi Utara (VI=0,78), Sulawesi Tengah (VI=0,72) dan Gorontalo (VI=0,61) berstatus sangat rentan walaupun komposisi penyusun indeks kerentanannya tidak sama. Perbedaan ini menentukan bahwa jenis kebijakan yang diambil menjadi spesifik pada tiap provinsi untuk mengurangi kerentanan. <em>Short term policy </em>diambil untuk mengurangi dapak di daerah yang paling rentan yaitu Sulawesi Utara, Sulawesi Tengah, dan Gorontalo. <em>Medium term policy </em>dilakukan pada daerah yang kepekaannya tinggi yaitu Kepulauan Riau, Sulawesi Utara, dan Kalimantan Timur dan kapasitas adaptifnya rendah yaitu Jambi, Gorontalo dan Bangka Belitung. <em>Long term policy </em>dilakukan untuk daerah yang keterpaparannya tinggi yaitu Sulawesi Tengah, Sulawesi Utara dan Kalimantan Timur.<p><strong>Kata kunci</strong>:<em> </em>perubahan iklim, perikanan tangkap, kerentanan, provinsi <strong></strong></p>

scholarly journals A Study of Multi-Scale Relationship Between Investor Sentiment and Stock Index Fluctuation Based on the Analysis of BEMD Spillover Index

2021 ◽  
Vol 9 (4) ◽  
pp. 399-420
Author(s):  
Weiguo Chen ◽  
Shufen Zhou ◽  
Yin Zhang ◽  
Yi Sun
Keyword(s):  
Stock Price ◽  
Composite Index ◽  
Investor Sentiment ◽  
Stock Index ◽  
Financial Industry ◽  
Medium Term ◽  
Short Term ◽  
Frequency Components ◽  
Original Scale

Abstract According to behavioral finance theory, investor sentiment generally exists in investors’ trading activities and influences financial market. In order to investigate the interaction between investor sentiment and stock market as well as financial industry, this study decomposed investor sentiment, stock price index and SWS index of financial industry into IMF components at different scales by using BEMD algorithm. Moreover, the fluctuation characteristics of time series at different time scales were extracted, and the IMF components were reconstructed into short-term high-frequency components, medium-term important event low-frequency components and long-term trend components. The short-term interaction between investor sentiment and Shanghai Composite Index, Shenzhen Component Index and financial industries represented by SWS index was investigated based on the spillover index. The time difference correlation coefficient was employed to determine the medium-term and long-term correlation among variables. Results demonstrate that investor sentiment has a strong correlation with Shanghai Composite Index, Shenzhen Component Index and different financial industries represented by SWS index at the original scale, and the change of investor sentiment is mainly influenced by external market information. The interaction between most markets at the short-term scale is weaker than that at the original scale. Investor sentiment is more significantly correlated with SWS Bond, SWS Diversified Finance and Shanghai Composite Index at the long-term scale than that at the medium-term scale.

scholarly journals Communities’ Livelihood Vulnerability to Climate Variability in Ethiopia

2019 ◽  
Vol 11 (22) ◽  
pp. 6302 ◽  
Author(s):  
Misganaw Teshager Abeje ◽  
Atsushi Tsunekawa ◽  
Nigussie Haregeweyn ◽  
Zerihun Nigussie ◽  
Enyew Adgo ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Adaptive Capacity ◽  
Policy Development ◽  
Composite Index ◽  
Household Survey ◽  
Kendall Test ◽  
Vulnerability Index ◽  
Relative Difference ◽  
Sustainable Livelihood

Ethiopia has experienced more than 10 major drought episodes since the 1970s. Evidence has shown that climate change exacerbates the situation and presents a daunting challenge to predominantly rain-fed agricultural livelihoods. The aim of this study was to analyze the extent and sources of smallholder famers’ livelihood vulnerability to climate change/variability in the Upper Blue Nile basin. We conducted a household survey (n = 391) across three distinct agroecological communities and a formative composite index of livelihood vulnerability (LVI) was constructed. The Mann–Kendall test and the standard precipitation index (SPI) were employed to analyze trends of rainfall, temperature, and drought prevalence for the period from 1982 to 2016. The communities across watersheds showed a relative difference in the overall livelihood vulnerability index. Aba Gerima (midland) was found to be more vulnerable, with a score of 0.37, while Guder (highland) had a relatively lower LVI with a 0.34 index score. Given similar exposure to climate variability and drought episodes, communities’ livelihood vulnerability was mainly attributed to their low adaptive capacity and higher sensitivity indicators. Adaptive capacity was largely constrained by a lack of participation in community-based organizations and a lack of income diversification. This study will have practical implications for policy development in heterogeneous agroecological regions for sustainable livelihood development and climate change adaptation programs.

scholarly journals STRATEGI USAHA BIRO PERJALANAN WISATA SUMATERA BARAT DALAM MENGHADAPI KRISIS PANDEMI COVID-19

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Rini Eka Sari ◽  
Novi Yanita ◽  
Sepri Neswardi
Keyword(s):  
Data Collection ◽  
Sampling Method ◽  
Swot Analysis ◽  
Research Data ◽  
Medium Term ◽  
Short Term ◽  
Purposive Sampling ◽  
Depth Interview ◽  
Tour Operator

The study is aimed to formulate the stategies of West Sumatera’s Tour Operator in facing the COVID-19 Pandemic crisis. The limitation of mobilization in travelling to break the chain of the spreading of COVID-19 Pandemic, has paralyzed the Tour operator business in all regions including in West Sumatera. The strategies are formulated using SWOT analysis (Strength, Weakness, Opportunity, Thread), by minimizing the weakness and thread and maximizing the strength and opportunity. Research data collection is conducted through in depth interview with some tour operator business stakeholders in West Sumatera, using purposive sampling method. Then, the data is analyzed descriptively, by noticing the strength, weakness, opportunity and thread factors of tour operator business in West Sumatera to formulate the strategies in facing the COVID-19 Pandemic crisis. The result reveals that there are several strategies conducted by tour operators in West Sumatera in the stage of short-term strategies, medium term strategies and long-term strategies to sustain the business.  

scholarly journals Climate change induced vulnerability and adaption for dengue incidence in Colombo and Kandy Districts: The first detailed investigation in Sri Lanka

2020 ◽  
Author(s):  
N.W.B.A.L. Udayanga ◽  
Nayana Gunathilaka ◽  
M.C.M. Iqbal ◽  
W. Abeyewickreme
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Sri Lanka ◽  
Adaptive Capacity ◽  
Medical Officer ◽  
High Sensitivity ◽  
Local Communities ◽  
Sensitivity Index ◽  
High Exposure ◽  
Municipal Council

Abstract Background: Assessing the vulnerability of an infectious disease such as dengue among endemic population is an important requirement to design proactive programmes in order to improve resilience capacity of vulnerable communities. Despite the significance in decision making process especially for rational resource allocation, recognition of actual burden of dengue, the vulnerability of dengue has been limitedly addressed in many countries including Sri Lanka, due to some in a holistic methodology.Methods: A total of 42 variables (entomological, epidemiological, meteorological parameters, landuse practices and socio-demographic data) of all the 38 Medical Officer of Health (MOH) areas in the districts of Colombo and Kandy were considered as candidate variables for composite index based vulnerability assessment. The Principal Component Analysis (PCA) was used in selecting and setting the weight for each indicator. Exposure, Sensitivity, Adaptive Capacity and Vulnerability of all the MOH areas for dengue incidence were calculated.Results: Out of 42 candidate variables, only 23 parameters (Exposure Index: 6 variables; Sensitivity Index: 11 variables; Adaptive Capacity Index: 6 variables) were selected as the indicators to assess climate change vulnerability to dengue. Colombo Municipal Council (CMC) MOH area denoted the highest values for exposure (0.89: exceptionally high exposure), sensitivity (0.86: exceptionally high sensitivity) in the district of Colombo, while Kandy Municipal Council (KMC) area reported the highest exposure (0.79: high exposure) and sensitivity (0.77: high sensitivity) in Kandy. Piliyandala MOH area denoted the highest level of adaptive capacity (0.66) in the district of Colombo followed by Menikhinna (0.68) in Kandy. The highest vulnerability (0.45: moderate vulnerability) to dengue was receded from CMC and the lowest indicated from Galaha MOH (0.15; very low vulnerability) in Kandy. Interestingly the Kandy Municipal Council MOH area had a notable vulnerability of 0.41 (moderate vulnerability), which remained the highest within Kandy.Conclusions: In general, vulnerability for dengue was relatively higher within the MOH areas of Colombo, than in Kandy, suggesting a higher degree of potential susceptibility to dengue within among local communities of Colombo. The VCE are recommended to consider the spatial variations in vulnerability of local communities to dengue for decision making, especially in allocation of limited financial, human and mechanical resources for dengue epidemic management.

scholarly journals Climate change induced vulnerability and adaption for dengue incidence in Colombo and Kandy Districts: The first detailed investigation in Sri Lanka

2020 ◽  
Author(s):  
N.W.B.A.L. Udayanga ◽  
Nayana Gunathilaka ◽  
M.C.M. Iqbal ◽  
W. Abeyewickreme
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Sri Lanka ◽  
Adaptive Capacity ◽  
Medical Officer ◽  
High Sensitivity ◽  
Local Communities ◽  
Sensitivity Index ◽  
High Exposure ◽  
Municipal Council

Abstract Background: Assessing the vulnerability of an infectious disease such as dengue among endemic population is an important requirement to design proactive programmes in order to improve resilience capacity of vulnerable communities. Despite the significance in decision making process especially for rational resource allocation, the recognition of actual burden of dengue and the vulnerability towards dengue, has been limitedly addressed in many countries including Sri Lanka, due to deficiencies in a holistic methodology. Methods: A total of 42 variables (entomological, epidemiological, meteorological parameters, land-use practices and socio-demographic data) of all the 38 Medical Officer of Health (MOH) areas in the districts of Colombo and Kandy were considered as candidate variables for a composite index based vulnerability assessment. The Principal Component Analysis (PCA) was used in selecting and setting the weight for each indicator. Exposure, Sensitivity, Adaptive Capacity and Vulnerability of all the MOH areas for dengue incidence were calculated. Results: Out of 42 candidate variables, only 23 parameters (Exposure Index: 6 variables; Sensitivity Index: 11 variables; Adaptive Capacity Index: 6 variables) were selected as indicators to assess climate change vulnerability to dengue. Colombo Municipal Council (CMC) MOH area denoted the highest values for exposure (0.89: exceptionally high exposure), sensitivity (0.86: exceptionally high sensitivity) in the district of Colombo, while Kandy Municipal Council (KMC) area reported the highest exposure (0.79: high exposure) and sensitivity (0.77: high sensitivity) in Kandy. Piliyandala MOH area denoted the highest level of adaptive capacity (0.66) in the district of Colombo followed by Menikhinna (0.68) in Kandy. The highest vulnerability (0.45: moderate vulnerability) to dengue was indicated from CMC and the lowest indicated from Galaha MOH (0.15; very low vulnerability) in Kandy. Interestingly the Kandy Municipal Council MOH area had a notable vulnerability of 0.41 (moderate vulnerability), which was the highest within Kandy. Conclusions: In general, vulnerability for dengue was relatively higher within the MOH areas of Colombo, than in Kandy, suggesting a higher degree of potential susceptibility to dengue within and among local communities of Colombo. The Vector Controlling Entities (VCE) are recommended to consider the spatial variations in vulnerability of local communities to dengue for decision making, especially in allocation of limited financial, human and mechanical resources for dengue epidemic management

Determinants of Anthropometric Failure Among Tribal Children Younger than 5 Years of Age in Palghar, Maharashtra, India

2021 ◽  
Vol 42 (1) ◽  
pp. 55-64
Author(s):  
Angeline Jeyakumar ◽  
Swapnil Godbharle ◽  
Bibek Raj Giri
Keyword(s):  
Odds Ratio ◽  
Composite Index ◽  
Z Score ◽  
Short Term ◽  
Cross Sectional Survey ◽  
Crude Odds Ratio ◽  
Cross Sectional ◽  
Independent Variables ◽  
Child Undernutrition

Background: Measuring undernutrition using composite index of anthropometric failure (CIAF) and identifying its determinants in tribal regions is essential to recognize the true burden of undernutrition in these settings. Objective: To determine anthropometric failure and its determinants among tribal children younger than 5 years in Palghar, Maharashtra, India. Methods: A cross-sectional survey employing CIAF was performed in children <5 years to estimate undernutrition in the tribal district of Palghar in Maharashtra, India. Anthropometric measurements, maternal and child characteristics were recorded from 577 mother–child pairs in 9 villages. Results: As per Z score, prevalence of stunting, wasting, and underweight were 48%, 13%, and 43%, respectively. According to CIAF, 66% of children had at least one manifestation of undernutrition and 40% had more than one manifestation of undernutrition. Odds of anthropometric failure were 1.5 times higher among children of mothers who were illiterate (adjusted odds ratio [AOR] =1.57, 95% CI: 1.0-2.3), children who had birth weight >2.5 kg had lesser odds (AOR: 0.63, 95% CI: 0.4-0.9) of anthropometric failure, and children who had initiated early breastfeeding had 1.5 times higher odds of anthropometric failure (crude odds ratio: 1.5, 95% CI: 1.0-2.1). However, when adjusted for other independent variables, the results were not significant. Conclusion: The alarming proportion of anthropometric failure among tribal children calls for urgent short-term interventions to correct undernutrition and long-term interventions to improve maternal literacy and awareness to prevent and manage child undernutrition.

scholarly journals Long-Term Data Traffic Forecasting for Network Dimensioning in LTE with Short Time Series

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1151
Author(s):  
Carolina Gijón ◽  
Matías Toril ◽  
Salvador Luna-Ramírez ◽  
María Luisa Marí-Altozano ◽  
José María Ruiz-Avilés
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Analysis ◽  
Data Traffic ◽  
Medium Term ◽  
Short Term ◽  
Traffic Forecasting ◽  
Series Analysis ◽  
Radio Planning

Network dimensioning is a critical task in current mobile networks, as any failure in this process leads to degraded user experience or unnecessary upgrades of network resources. For this purpose, radio planning tools often predict monthly busy-hour data traffic to detect capacity bottlenecks in advance. Supervised Learning (SL) arises as a promising solution to improve predictions obtained with legacy approaches. Previous works have shown that deep learning outperforms classical time series analysis when predicting data traffic in cellular networks in the short term (seconds/minutes) and medium term (hours/days) from long historical data series. However, long-term forecasting (several months horizon) performed in radio planning tools relies on short and noisy time series, thus requiring a separate analysis. In this work, we present the first study comparing SL and time series analysis approaches to predict monthly busy-hour data traffic on a cell basis in a live LTE network. To this end, an extensive dataset is collected, comprising data traffic per cell for a whole country during 30 months. The considered methods include Random Forest, different Neural Networks, Support Vector Regression, Seasonal Auto Regressive Integrated Moving Average and Additive Holt–Winters. Results show that SL models outperform time series approaches, while reducing data storage capacity requirements. More importantly, unlike in short-term and medium-term traffic forecasting, non-deep SL approaches are competitive with deep learning while being more computationally efficient.

scholarly journals Short- and Long-term Biologic Variability of Galectin-3 and Other Cardiac Biomarkers in Patients with Stable Heart Failure and Healthy Adults

2016 ◽  
Vol 62 (2) ◽  
pp. 360-366 ◽  
Author(s):  
Emily I Schindler ◽  
Jeffrey J Szymanski ◽  
Karl G Hock ◽  
Edward M Geltman ◽  
Mitchell G Scott
Keyword(s):  
Heart Failure ◽  
Troponin I ◽  
Prognostic Biomarker ◽  
High Sensitivity ◽  
Cardiac Biomarkers ◽  
Healthy Individuals ◽  
Short Term ◽  
Galectin 3 ◽  
Short And Long Term

Abstract BACKGROUND Galectin-3 (Gal-3) has been suggested as a prognostic biomarker in heart failure (HF) patients that may better reflect disease progression than traditional markers, including B-type natriuretic peptide (BNP) and cardiac troponins. To fully establish the utility of any biomarker in HF, its biologic variability must be characterized. METHODS To assess biologic variability, 59 patients were prospectively recruited, including 23 male and 16 female patients with stable HF and 10 male and 10 female healthy individuals. Gal-3, BNP, and high-sensitivity cardiac troponin I (hs-cTnI) were assayed at 5 time points within a 3-week period to assess short-term biologic variability. Long-term (3-month) biologic variability was assessed with samples collected at enrollment and after 4, 8, and 12 weeks. RESULTS Among healthy individuals, mean short-term biologic variability, expressed as intraindividual CV (CVI), was 4.5% for Gal-3, 29.0% for BNP, and 14.5% for hs-cTnI; long-term biologic variability was 5.5% for Gal-3, 34.7% for BNP, and 14.7% for hs-cTnI. In stable HF patients, mean short-term biologic variability was 7.1% for Gal-3, 22.5% for BNP, and 8.5% for hs-cTnI, and mean long-term biologic variability was 7.7% for Gal-3, 27.6% for BNP, and 9.6% for hs-cTnI. CONCLUSIONS The finding that Gal-3 has minimal intraindividual biological variability adds to its potential as a useful biomarker in HF patients.

Sampling estuarine copepods at different scales and resolutions: a study in Rio de la Plata

2018 ◽  
Vol 99 (5) ◽  
pp. 1059-1064 ◽  
Author(s):  
Sourav Paul ◽  
Danilo Calliari
Keyword(s):  
Sampling Effort ◽  
Rio De La Plata ◽  
Population Densities ◽  
Medium Term ◽  
Short Term ◽  
Río De La Plata ◽  
La Plata ◽  
Resource Limitations ◽  
Paracalanus Parvus

AbstractIn the Rio de la Plata salinity, temperature, chlorophyll a (chl a), and densities (ind. m−3) of the copepods Acartia tonsa and Paracalanus parvus were measured from January to November in 2003 by following a nested weekly and monthly design. Such sampling yielded two separate datasets: (i) Yearly Dataset (YD) which consists of data of one sampling effort per month for 11 consecutive months, and (ii) Seasonal Weekly Datasets (SWD) which consists of data of one sampling effort per week of any four consecutive weeks within each season. YD was assumed as a medium-term low-resolution (MTLR) dataset, and SWD as a short-term high-resolution (STHR) dataset. The hypothesis was, the SWD would always capture (shorter scales generally captures more noise in data) more detail variability of copepod populations (quantified through the regression relationships between temporal changes of salinity, temperature, chl a and copepod densities) than the YD. Analysis of both YD and SWD found that A. tonsa density was neither affected by seasonal cycles, nor temporal variability of salinity, temperature and chl a. Thus, compared to STHR sampling, MTLR sampling did not yield any further information of the variability of population densities of the perennial copepod A. tonsa. Analysis of SWD found that during summer and autumn the population densities of P. parvus had a significant positive relationship to salinity but their density was limited by higher chl a concentration; analysis of YD could not yield such detailed ecological information. That hints the effectiveness of STHR sampling over MTLR sampling in capturing details of the variability of population densities of a seasonal copepod species. Considering the institutional resource limitations (e.g. lack of long-term funding, manpower and infrastructure) and the present hypothesis under consideration, the authors suggest that a STHR sampling may provide useful complementary information to interpret results of longer-term natural changes occurring in estuaries.

scholarly journals Crédito consignado: segmentos e efeitos econômicos

2018 ◽  
Vol 17 (2) ◽  
pp. 783-810
Author(s):  
Angélica Pott de Medeiros ◽  
Giulia Xisto de Oliveira ◽  
Reisoli Bender Filho
Keyword(s):  
Economic Recession ◽  
High Sensitivity ◽  
Variance Decomposition ◽  
Economic Effects ◽  
Short Term ◽  
Macroeconomic Variables ◽  
The Public ◽  
Short And Long Term ◽  
Vector Estimation

Resumo: O cenário de instabilidade política, a recessão econômica e as mudanças nas regras de concessão de crédito pautaram o objetivo de examinar o relacionamento do crédito consignado, por segmento de concessão, com variáveis macroeconômicas, caso do consumo, da produção industrial e do produto agregado, na última década (2007-2017). Os resultados foram obtidos por meio da estimação do vetor de correção de erros, funções de impulso-resposta e decomposição da variância, possibilitando a análise das relações de curto e de longo prazo entre as séries temporais e indicaram que as diferentes modalidades do crédito consignado implicam efeitos distintos sobre as variáveis econômicas em curto prazo. O segmento de aposentados e pensionistas impacta positivamente ambas as variáveis analisadas, com destaque para os bens de consumo das famílias. Já a concessão ao setor privado, embora represente a menor parcela do crédito consignado concedido, mostrou elevada sensibilidade a alterações na oferta dessa modalidade de crédito, enquanto que o crédito ao setor público, de maior participação, apresentou efeitos reduzidos e de curta duração.Palavras-chave: Crédito consignado. Segmentos. Economia brasileira. Payroll loans: segments and economic effects Abstract: The environment of political instability, economic recession and changes in the rules of granting credit were guiders to aim to examine the payroll loans relationship, by concession segment, with macroeconomic variables, case of consumption, industrial production and aggregate product, in the last decade (2007-2017). The results obtained by error correction vector estimation, and functions of impulse-response and variance decomposition, making it possible to analyze the short- and long-term relationships between the time series and indicated that the different modalities of payroll loans imply different effects on economic short-term variables. With retirees and pensioners segment positively impact on both analyzed variables, highlighting the household consumption goods. The concession to the private sector, although it represents the smallest portion of payroll loans granted, it showed high sensitivity to the changes of this modality. About credit to the public sector, which has the biggest portion, it showed reduced and short-term effects.Keywords: Payroll loans. Segments. Brazilian economy.

Sign in / Sign up

Export Citation Format

Share Document