Cássio Nóbrega Besarria
(Cassio Nobrega Besarria)

Personal Details

First Name:	Cassio
Middle Name:	Nobrega
Last Name:	Besarria
Suffix:
RePEc Short-ID:	pbe1221
	https://sigaa.ufpb.br/sigaa/public/docente/portal.jsf?siape=1848107

Affiliation

Departamento de Economia
Centro de Ciências Socais Aplicadas
Universidade Federal da Paraíba

João Pessoa, Brazil
http://www.ccsa.ufpb.br/de/
RePEc:edi:ccufpbr (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Cássio Da Nóbrega Besarria & Jevuks Matheus De Araújo & Andréa Ferreira Da Silva & Éryka Fernanda Miranda Sobral & Thiago Geovane Pereira, 2018. "Effects Of Income Inequality On The Economic Growth Of Brazilian States: An Analysis Using The Cointegrated Panel Model," Anais do XLIV Encontro Nacional de Economia [Proceedings of the 44th Brazilian Economics Meeting] 81, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

   Cited by:

   1. Mdingi, Kholeka & Ho, Sin-Yu, 2023. "Income inequality and economic growth: An empirical investigation in South Africa," MPRA Paper 117733, University Library of Munich, Germany.

Articles

1. José Carlos Araújo Amarante & Cássio da Nóbrega Besarria & Helson Gomes de Souza & Otoniel Rodrigues dos Anjos Junior, 2021. "The relationship between economic growth, renewable and nonrenewable energy use and CO2 emissions: empirical evidences for Brazil," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 11(3), pages 411-431, June.

   Cited by:

   1. Robert Stefko & Beata Gavurova & Miroslav Kelemen & Martin Rigelsky & Viera Ivankova, 2021. "Relationships between Renewable Energy and the Prevalence of Morbidity in the Countries of the European Union: A Panel Regression Approach," IJERPH, MDPI, vol. 18(12), pages 1-18, June.

2. Diego Pitta de Jesus & Cássio da Nóbrega Besarria & Sinézio Fernandes Maia, 2020. "The macroeconomic effects of monetary policy shocks under fiscal constrained," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(4), pages 805-825, February.

   Cited by:

   1. Sumei Luo & Guangyou Zhou & Jinpeng Zhou, 2021. "The Impact of Electronic Money on Monetary Policy: Based on DSGE Model Simulations," Mathematics, MDPI, vol. 9(20), pages 1-26, October.
   2. Áydano Ribeiro Leite & Cássio da Bessaria Nobrega & André Luis Mota dos Santos & Fernando Fernandes Neto, 2022. "Regra do teto dos gastos públicos (PEC 55/241) e sustentabilidade da dívida pública no Brasil: Análise de cenários a partir de um modelo DSGE [Public spending celing rule (PEC 55/241) and public de," Estudios Economicos, Universidad Nacional del Sur, Departamento de Economia, vol. 39(79), pages 219-247, july-dece.

3. de Jesus, Diego Pitta & Lenin Souza Bezerra, Bruno Felipe & da Nóbrega Besarria, Cássio, 2020. "The non-linear relationship between oil prices and stock prices: Evidence from oil-importing and oil-exporting countries," Research in International Business and Finance, Elsevier, vol. 54(C).

   Cited by:

   1. Su, Zhi & Mo, Xuan & Yin, Libo, 2021. "Oil market uncertainty and excess returns on currency carry trade," Research in International Business and Finance, Elsevier, vol. 56(C).
   2. Martínez-Cañete, Ana R. & Márquez-de-la-Cruz, Elena & Pérez-Soba, Inés, 2022. "Non-linear cointegration between oil and stock prices: The role of interest rates," Research in International Business and Finance, Elsevier, vol. 59(C).
   3. Mensi, Walid & Lee, Yun-Jung & Vinh Vo, Xuan & Yoon, Seong-Min, 2021. "Does oil price variability affect the long memory and weak form efficiency of stock markets in top oil producers and oil Consumers? Evidence from an asymmetric MF-DFA approach," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
   4. Zhu, Huiming & Yu, Dongwei & Hau, Liya & Wu, Hao & Ye, Fangyu, 2022. "Time-frequency effect of crude oil and exchange rates on stock markets in BRICS countries: Evidence from wavelet quantile regression analysis," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
   5. Kruel, Maximiliano & Ceretta, Paulo Sergio, 2022. "Asymmetric influences on Latin American stock markets: A quantile approach," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
   6. Wang, Jun-Zhuo & Feng, Gen-Fu & Yin, Hua-Tang & Chang, Chun-Ping, 2023. "Toward sustainable development: Does the rising oil price stimulate innovation in climate change mitigation technologies?," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 569-583.
   7. Jingran Zhu & Qinghua Song & Dalia Streimikiene, 2020. "Multi-Time Scale Spillover Effect of International Oil Price Fluctuation on China’s Stock Markets," Energies, MDPI, vol. 13(18), pages 1-29, September.
   8. Asadi, Mehrad & Roubaud, David & Tiwari, Aviral Kumar, 2022. "Volatility spillovers amid crude oil, natural gas, coal, stock, and currency markets in the US and China based on time and frequency domain connectedness," Energy Economics, Elsevier, vol. 109(C).
   9. Zhang, Chuanguo & Mou, Xinjie & Ye, Shuping, 2022. "How do dynamic jumps in global crude oil prices impact China's industrial sector?," Energy, Elsevier, vol. 249(C).
   10. Raheem, Ibrahim D. & Bello, Ajide Kazeem & Agboola, Yusuf H., 2020. "A new insight into oil price-inflation nexus," Resources Policy, Elsevier, vol. 68(C).

4. Cássio da Nóbrega Besarria & Nelson Leitão Paes & Marcelo Eduardo Alves Silva, 2018. "Testing for bubbles in housing markets: some evidence for Brazil," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 11(5), pages 754-770, June.

   Cited by:

   1. Benjamas Jirasakuldech & Riza Emekter & Thuy Bui, 2023. "Non-linear structures, chaos, and bubbles in U.S. regional housing markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(1), pages 63-93, March.

5. de Oliveira, Felipe A. & Maia, Sinézio F. & de Jesus, Diego P. & Besarria, Cássio da N., 2018. "Which information matters to market risk spreading in Brazil? Volatility transmission modelling using MGARCH-BEKK, DCC, t-Copulas," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 83-100.

   Cited by:

   1. Camille Baulant & Nivine Albouz, 2021. "Has financial globalization since 1990 reduced income inequality: the role of rating announcements on the volatility and the returns of the Brazilian Financial Market [Les annonces de notation souv," Working Papers hal-03258994, HAL.
   2. Karel Janda & Ladislav Krištoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods and Outcomes," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 195-216, October.
   3. Shuping Li & Xinghua Liu & Chongren Wang, 2020. "The Influence of Internet Finance on the Sustainable Development of the Financial Ecosystem in China," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
   4. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
   5. Zhang, Weiping & Zhuang, Xintian & Lu, Yang & Wang, Jian, 2020. "Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework," International Review of Financial Analysis, Elsevier, vol. 71(C).
   6. Xu Zhang & Xian Yang & Jianping Li & Jun Hao, 2023. "Contemporaneous and noncontemporaneous idiosyncratic risk spillovers in commodity futures markets: A novel network topology approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 705-733, June.
   7. Hao Chen & Zhixin Liu & Yinpeng Zhang & You Wu, 2020. "The Linkages of Carbon Spot-Futures: Evidence from EU-ETS in the Third Phase," Sustainability, MDPI, vol. 12(6), pages 1-18, March.
   8. Oguzhan Ozcelebi & José A. Pérez‐Montiel, 2023. "Examination of the impacts of the immediate interest rate of the United States and the VIX on the Dow Jones Islamic Market Index," Bulletin of Economic Research, Wiley Blackwell, vol. 75(4), pages 1157-1180, October.
   9. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
   10. Jiang, Cuixia & Ding, Xiaoyi & Xu, Qifa & Tong, Yongbo, 2020. "A TVM-Copula-MIDAS-GARCH model with applications to VaR-based portfolio selection," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
   11. Aliyu, Shehu Usman Rano, 2020. "What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy?," MPRA Paper 110382, University Library of Munich, Germany, revised 06 Jun 2021.
   12. Cunha, Felipe Arias Fogliano de Souza & Meira, Erick & Orsato, Renato J. & Klotzle, Marcelo Cabus & Lucena, André F.P., 2021. "Do low-carbon investments in emerging economies pay off? Evidence from the Brazilian stock market," International Review of Financial Analysis, Elsevier, vol. 74(C).
   13. Pablo Urtubia & Alfonso Novales & Andrés Mora-Valencia, 2021. "Cross-Hedging Portfolios in Emerging Stock Markets: Evidence for the LATIBEX Index," Mathematics, MDPI, vol. 9(21), pages 1-19, October.

6. de Albuquerquemello, Vinícius Phillipe & de Medeiros, Rennan Kertlly & da Nóbrega Besarria, Cássio & Maia, Sinézio Fernandes, 2018. "Forecasting crude oil price: Does exist an optimal econometric model?," Energy, Elsevier, vol. 155(C), pages 578-591.

   Cited by:

   1. Carpio, Lucio Guido Tapia, 2019. "The effects of oil price volatility on ethanol, gasoline, and sugar price forecasts," Energy, Elsevier, vol. 181(C), pages 1012-1022.
   2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
   3. He, Huizi & Sun, Mei & Li, Xiuming & Mensah, Isaac Adjei, 2022. "A novel crude oil price trend prediction method: Machine learning classification algorithm based on multi-modal data features," Energy, Elsevier, vol. 244(PA).
   4. Drachal, Krzysztof, 2021. "Forecasting crude oil real prices with averaging time-varying VAR models," Resources Policy, Elsevier, vol. 74(C).
   5. Zuzanna Karolak, 2021. "Energy prices forecasting using nonlinear univariate models," Bank i Kredyt, Narodowy Bank Polski, vol. 52(6), pages 577-598.
   6. Meng, Fanyi & Liu, Li, 2019. "Analyzing the economic sources of oil price volatility: An out-of-sample perspective," Energy, Elsevier, vol. 177(C), pages 476-486.
   7. Manickavasagam, Jeevananthan & Visalakshmi, S. & Apergis, Nicholas, 2020. "A novel hybrid approach to forecast crude oil futures using intraday data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
   8. Butler, Sunil & Kokoszka, Piotr & Miao, Hong & Shang, Han Lin, 2021. "Neural network prediction of crude oil futures using B-splines," Energy Economics, Elsevier, vol. 94(C).
   9. Bouteska, Ahmed & Hajek, Petr & Fisher, Ben & Abedin, Mohammad Zoynul, 2023. "Nonlinearity in forecasting energy commodity prices: Evidence from a focused time-delayed neural network," Research in International Business and Finance, Elsevier, vol. 64(C).
   10. Canepa, Alessandra & Zanetti Chini, Emilio & Alqaralleh, Huthaifa, 2023. "Modelling and Forecasting Energy Market Cycles: A Generalized Smooth Transition Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202318, University of Turin.
   11. Long, Shaobo & Guo, Jiaqi, 2022. "Infectious disease equity market volatility, geopolitical risk, speculation, and commodity returns: Comparative analysis of five epidemic outbreaks," Research in International Business and Finance, Elsevier, vol. 62(C).
   12. Wu, Binrong & Wang, Lin & Wang, Sirui & Zeng, Yu-Rong, 2021. "Forecasting the U.S. oil markets based on social media information during the COVID-19 pandemic," Energy, Elsevier, vol. 226(C).
   13. Kertlly de Medeiros, Rennan & da Nóbrega Besarria, Cássio & Pitta de Jesus, Diego & Phillipe de Albuquerquemello, Vinicius, 2022. "Forecasting oil prices: New approaches," Energy, Elsevier, vol. 238(PC).
   14. Jiangwei Liu & Xiaohong Huang, 2021. "Forecasting Crude Oil Price Using Event Extraction," Papers 2111.09111, arXiv.org.
   15. Akdoğan, Kurmaş, 2020. "Fundamentals versus speculation in oil market: The role of asymmetries in price adjustment?," Resources Policy, Elsevier, vol. 67(C).
   16. Rubaszek Michal & Karolak Zuzanna & Kwas Marek & Uddin Gazi Salah, 2020. "The role of the threshold effect for the dynamics of futures and spot prices of energy commodities," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(5), pages 1-20, December.
   17. Asit Kumar Das & Debahuti Mishra & Kaberi Das & Pradeep Kumar Mallick & Sachin Kumar & Mikhail Zymbler & Hesham El-Sayed, 2022. "Prophesying the Short-Term Dynamics of the Crude Oil Future Price by Adopting the Survival of the Fittest Principle of Improved Grey Optimization and Extreme Learning Machine," Mathematics, MDPI, vol. 10(7), pages 1-33, March.
   18. Pavel Baboshkin & Mafura Uandykova, 2021. "Multi-source Model of Heterogeneous Data Analysis for Oil Price Forecasting," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 384-391.

More information

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-URE: Urban and Real Estate Economics (1) 2018-04-16

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