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Oscar Claveria

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. Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022. "“An application of deep learning for exchange rate forecasting”," AQR Working Papers 202201, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2022.

    Cited by:

    1. Sylvain Barthélémy & Virginie Gautier & Fabien Rondeau, 2024. "Early warning system for currency crises using long short‐term memory and gated recurrent unit neural networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1235-1262, August.

  2. Oscar Claveria & Ivana Lolic & Enric Monte & Salvador Torra & Petar Soric, 2020. "“Economic determinants of employment sentiment: A socio-demographic analysis for the euro area”," AQR Working Papers 2012001, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2020.

    Cited by:

    1. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.

  3. Oscar Claveria, 2018. "“A new metric of consensus for Likert scales”," AQR Working Papers 201810, University of Barcelona, Regional Quantitative Analysis Group, revised Oct 2018.

    Cited by:

    1. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    2. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    3. Oscar Claveria, 2020. "Measuring and assessing economic uncertainty," IREA Working Papers 202011, University of Barcelona, Research Institute of Applied Economics, revised Jul 2020.

  4. Oscar Claveria & Enric Monte & Salvador Torra, 2014. "“A multivariate neural network approach to tourism demand forecasting”," AQR Working Papers 201410, University of Barcelona, Regional Quantitative Analysis Group, revised May 2014.

    Cited by:

    1. Abdoulaye Camara & Wang Feixing & Liu Xiuqin, 2016. "Energy Consumption Forecasting Using Seasonal ARIMA with Artificial Neural Networks Models," International Journal of Business and Management, Canadian Center of Science and Education, vol. 11(5), pages 231-231, April.

  5. Oscar Claveria & Salvador Torra, 2013. "“Forecasting Business surveys indicators: neural networks vs. time series models”," AQR Working Papers 201312, University of Barcelona, Regional Quantitative Analysis Group, revised Nov 2013.

    Cited by:

    1. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.

  6. Oscar Claveria & Enric Monte & Salvador Torra, 2013. "“Tourism demand forecasting with different neural networks models”," AQR Working Papers 201313, University of Barcelona, Regional Quantitative Analysis Group, revised Nov 2013.

    Cited by:

    1. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    2. İhsan Erdem Kayral & Tuğba Sarı & Nisa Şansel Tandoğan Aktepe, 2023. "Forecasting the Tourist Arrival Volumes and Tourism Income with Combined ANN Architecture in the Post COVID-19 Period: The Case of Turkey," Sustainability, MDPI, vol. 15(22), pages 1-20, November.
    3. Rendell E. de Kort, 2017. "Forecasting tourism demand through search queries and machine learning," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Big Data, volume 44, Bank for International Settlements.
    4. Dr. Murat çuhadar & Iclal Cogurcu & Ceyda Kukrer, 2014. "Modelling and Forecasting Cruise Tourism Demand to Izmir by Different Artificial Neural Network Architectures," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(3), pages 12-28, March.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Regional Forecasting with Support Vector Regressions: The Case of Spain”," AQR Working Papers 201506, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2015.

  7. Claveria, Oscar & Datzira, Jordi, 2008. "Tourism Demand in Catalonia: Detecting External Economic Factors," MPRA Paper 25303, University Library of Munich, Germany, revised 12 Apr 2008.

    Cited by:

    1. Asgary, Ali & Rezvani, Mohammad Reza & Mehregan, Nader, 2011. "Local Residents’ Preferences for Second Home Tourism Development Policies: A Choice Experiment nalysis," MPRA Paper 29703, University Library of Munich, Germany.
    2. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Multiple-input multiple-output vs. single-input single-output neural network forecasting”," AQR Working Papers 201502, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2015.
    3. Biljana Petrevska, 2014. "Measuring Seasonal Concentration Of Tourism Demand: Comparative Study Of See Countries," Journal Articles, Center For Economic Analyses, pages 45-53, December.
    4. Brida, Juan Gabriel & Osti, Linda & Santifaller, Esther, 2011. "Second Homes and the Need for Policy Planning," MPRA Paper 29835, University Library of Munich, Germany.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Regional Forecasting with Support Vector Regressions: The Case of Spain”," AQR Working Papers 201506, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2015.

Articles

  1. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.

    Cited by:

    1. Oscar Claveria & Petar Soric, 2023. "“Income inequality and redistribution in Scandinavian countries”," AQR Working Papers 202306, University of Barcelona, Regional Quantitative Analysis Group, revised Oct 2023.
    2. Emiliano Alzate & Oscar Claveria, 2023. "A different look at the nexus between entrepreneurship and development using GEM data," IREA Working Papers 202318, University of Barcelona, Research Institute of Applied Economics, revised Nov 2023.

  2. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).

    Cited by:

    1. Kanavos, Panos & Vandoros, Sotiris, 2023. "Road traffic mortality and economic uncertainty: Evidence from the United States," Social Science & Medicine, Elsevier, vol. 326(C).
    2. Tao, Hung-Lin & Cheng, Hui-Pei, 2023. "Economic policy uncertainty and subjective health: A gender perspective," Social Science & Medicine, Elsevier, vol. 334(C).
    3. Lepori, Gabriele M. & Morgan, Sara & Assarian, Borna A. & Mishra, Tapas, 2024. "Economic activity and suicides: Causal evidence from macroeconomic shocks in England and Wales," Social Science & Medicine, Elsevier, vol. 342(C).
    4. Saito, Masashige & Watanabe, Ryota & Tamada, Yudai & Takeuchi, Kenji & Tani, Yukako & Kondo, Katsunori & Ojima, Toshiyuki, 2024. "Social disconnection and suicide mortality among Japanese older adults: A seven-year follow-up study," Social Science & Medicine, Elsevier, vol. 347(C).

  3. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.

    Cited by:

    1. Samuel Narh Dorhetso, 2024. "A review of fifty-six years of consumer economics research," SN Business & Economics, Springer, vol. 4(11), pages 1-27, November.
    2. Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
    3. Petar Soric & Oscar Claveria, 2021. "“Employment uncertainty a year after the irruption of the covid-19 pandemic”," AQR Working Papers 202104, University of Barcelona, Regional Quantitative Analysis Group, revised May 2021.
    4. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).
    5. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.

  4. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.

    Cited by:

    1. Oscar Claveria, 2020. "Business and consumer uncertainty in the face of the pandemic: A sector analysis in European countries," Papers 2012.02091, arXiv.org.
    2. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.

  5. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.

    Cited by:

    1. Sergey V. Arzhenovskiy, 2024. "Forecasting GDP Dynamics Based on the Bank of Russia’s Enterprise Monitoring Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 31-44, February.
    2. Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022. ""Density forecasts of inflation using Gaussian process regression models"," IREA Working Papers 202210, University of Barcelona, Research Institute of Applied Economics, revised Jul 2022.

  6. Oscar Claveria & Enric Monte & Salvador Torra, 2021. "Frequency domain analysis and filtering of business and consumer survey expectations," International Economics, CEPII research center, issue 166, pages 42-57.

    Cited by:

    1. Petar Soric & Oscar Claveria, 2021. "“Employment uncertainty a year after the irruption of the covid-19 pandemic”," AQR Working Papers 202104, University of Barcelona, Regional Quantitative Analysis Group, revised May 2021.
    2. Marcela De Castro-Valderrama & Santiago Forero-Alvarado & Nicolás Moreno-Arias & Sara Naranjo-Saldarriaga, 2021. "Unraveling the Exogenous Forces Behind Analysts’ Macroeconomic Forecasts," Borradores de Economia 1184, Banco de la Republica de Colombia.
    3. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.

  7. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.

    Cited by:

    1. Shouheng Tuo & Tianrui Chen & Hong He & Zengyu Feng & Yanling Zhu & Fan Liu & Chao Li, 2021. "A Regional Industrial Economic Forecasting Model Based on a Deep Convolutional Neural Network and Big Data," Sustainability, MDPI, vol. 13(22), pages 1-11, November.
    2. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    3. Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022. ""Density forecasts of inflation using Gaussian process regression models"," IREA Working Papers 202210, University of Barcelona, Research Institute of Applied Economics, revised Jul 2022.
    4. Petar Sorić & Ivana Lolić & Marija Logarušić, 2021. "On the behavioral antecedents of business cycle coherence in the euro area," EFZG Working Papers Series 2104, Faculty of Economics and Business, University of Zagreb.
    5. Petar Sorić & Ivana Lolić & Marija Logarušić, 2022. "Economic Sentiment and Aggregate Activity: A Tale of Two European Cycles," Journal of Common Market Studies, Wiley Blackwell, vol. 60(2), pages 445-462, March.
    6. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2021. "Frequency domain analysis and filtering of business and consumer survey expectations," International Economics, Elsevier, vol. 166(C), pages 42-57.
    7. Petar Sorić & Blanka Škrabić Perić & Marina Matošec, 2022. "Breaking new grounds: a fresh insight into the leading properties of business and consumer survey indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4511-4535, December.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.

  8. Pérez, Claudia & Claveria, Oscar, 2020. "Natural resources and human development: Evidence from mineral-dependent African countries using exploratory graphical analysis," Resources Policy, Elsevier, vol. 65(C).

    Cited by:

    1. Fu, Rong & Liu, Jianmei, 2023. "Revenue sources of natural resources rents and its impact on sustainable development: Evidence from global data," Resources Policy, Elsevier, vol. 80(C).
    2. Liang, Xuefang & Qianqian, Ding & Tanai, Breshna & Shinwari, Riazullah, 2023. "On the conflict of natural resources hypothesis in Pakistan," Resources Policy, Elsevier, vol. 85(PA).
    3. Geoffrey Omedo & Kariuki Muigua & Richard Mulwa & Robert Kibugi, 2024. "Comparing Environmental Financial Guarantee Schemes in Kenya and South Africa," Journal of Sustainable Development, Canadian Center of Science and Education, vol. 15(2), pages 1-1, July.
    4. Ampofo, Gideon Kwaku Minua & Cheng, Jinhua & Asante, Daniel Akwasi & Bosah, Philip, 2020. "Total natural resource rents, trade openness and economic growth in the top mineral-rich countries: New evidence from nonlinear and asymmetric analysis," Resources Policy, Elsevier, vol. 68(C).
    5. Chen, Yufeng & Khurshid, Adnan & Rauf, Abdur & Yang, Hanyao & Calin, Adrian Cantemir, 2023. "Natural resource endowment and human development: Contemporary role of governance," Resources Policy, Elsevier, vol. 81(C).
    6. Jonathan Mukiza Peter Kansheba & Mutaju Isack Marobhe, 2022. "Institutional quality and resource-based economic sustainability: the mediation effects of resource governance," SN Business & Economics, Springer, vol. 2(2), pages 1-24, February.
    7. Liu, Haiying & Saleem, Muhammad Mansoor & Al-Faryan, Mamdouh Abdulaziz Saleh & Khan, Irfan & Zafar, Muhammad Wasif, 2022. "Impact of governance and globalization on natural resources volatility: The role of financial development in the Middle East North Africa countries," Resources Policy, Elsevier, vol. 78(C).
    8. Tian, Guixian & Zhang, Zhuo, 2023. "Exploring the impact of natural Resource utilization on human capital development: A sustainable development perspective," Resources Policy, Elsevier, vol. 87(PA).
    9. Yin, Yikun & Liu, Haoyu, 2024. "Fin-tech indicators, mineral resources and green productivity: Role of human development and globalization in BRICS region," Resources Policy, Elsevier, vol. 89(C).
    10. Selahmi, Basma & Liu, Chunping, 2022. "Institutions and the Resource Curse in GCC countries," MPRA Paper 114924, University Library of Munich, Germany, revised 26 Aug 2022.
    11. Abiodun Adegboye & Olawale Daniel Akinyele, 2022. "Assessing the determinants of government spending efficiency in Africa," Future Business Journal, Springer, vol. 8(1), pages 1-17, December.
    12. Sun, Tong & Wang, Xuefang, 2023. "Adoption of financial inclusion in a world of depleting natural resources: The importance of information and communication technology in emerging economies," Resources Policy, Elsevier, vol. 85(PB).
    13. Mahmood Ahmad & Zahoor Ahmed & Xiyue Yang & Muhlis Can, 2023. "Natural Resources Depletion, Financial Risk, and Human Well-Being: What is the Role of Green Innovation and Economic Globalization?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 167(1), pages 269-288, June.
    14. Feng, Meihong & Zou, Donghang & Hafeez, Muhammad, 2024. "Mineral resource volatility and green growth: The role of technological development, environmental policy stringency, and trade openness," Resources Policy, Elsevier, vol. 89(C).
    15. Le Clech, Néstor A., 2024. "Policy market orientation, property rights, and corruption effects on the rent of non-renewable resources in Latin America and the Caribbean," Resources Policy, Elsevier, vol. 91(C).
    16. Suzanna Elmassah & Eslam A. Hassanein, 2022. "Can the Resource Curse for Well-Being Be Morphed into a Blessing? Investigating the Moderating Role of Environmental Quality, Governance, and Human Capital," Sustainability, MDPI, vol. 14(22), pages 1-21, November.
    17. Hussain, Muzzammil & Ye, ZhiWei & Usman, Muhammad & Mir, Ghulam Mustafa & Usman, Ahmad & Abbas Rizvi, Syed Kumail, 2020. "Re-investigation of the resource curse hypothesis: The role of political institutions and energy prices in BRIC countries," Resources Policy, Elsevier, vol. 69(C).
    18. Sun, Wei & Yao, Guohui, 2023. "Impact of mineral resource depletion on energy use: Role of energy extraction, CO2 intensity, and natural resource sustainability," Resources Policy, Elsevier, vol. 86(PB).
    19. Li, Kaixian & Wang, Dongyu & Xu, Tong & Zhang, Yuqi, 2024. "Financial development and resource-curse hypothesis: Moderating role of internal and external conflict in the MENA region," Resources Policy, Elsevier, vol. 90(C).
    20. Ibrahim A. Adekunle & Olukayode E. Maku & Tolulope O. Williams & Judith Gbagidi & Emmanuel O. Ajike, 2023. "Natural Resource Endowments and Growth Dynamics in Africa: Evidence from Panel Cointegrating Regression," Working Papers of the African Governance and Development Institute. 23/015, African Governance and Development Institute..
    21. van Krevel, Charan, 2021. "Does natural capital depletion hamper sustainable development? Panel data evidence," Resources Policy, Elsevier, vol. 72(C).
    22. Ekundayo Peter Mesagan & Xuan Vinh Vo, 2024. "The Importance of Economic Complexity in the Resource-Growth Discourse: Empirical Evidence from Africa," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 2772-2793, March.
    23. Sandu, Suwin & Yang, Muyi & Phoumin, Han & Aghdam, Reza Fathollahzadeh & Shi, Xunpeng, 2021. "Assessment of accessible, clean and efficient energy systems: A statistical analysis of composite energy performance indices," Applied Energy, Elsevier, vol. 304(C).
    24. Feng, Meihong & Zou, Donghang & Hafeez, Muhammad, 2024. "Mineral resource volatility and green growth: the role of technological development, environmental policy stringency, and trade openness," LSE Research Online Documents on Economics 121592, London School of Economics and Political Science, LSE Library.
    25. Anis Omri & Montassar Kahia, 2024. "Natural Resources Abundance and Human Well-Being: the Role of Institutional Quality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 173(3), pages 607-644, July.
    26. Liu, Haiying & Alharthi, Majed & Atil, Ahmed & Zafar, Muhammad Wasif & Khan, Irfan, 2022. "A non-linear analysis of the impacts of natural resources and education on environmental quality: Green energy and its role in the future," Resources Policy, Elsevier, vol. 79(C).
    27. Deng, Ming, 2022. "China economic performance and natural resources commodity prices volatility: Evidence from China in COVID-19," Resources Policy, Elsevier, vol. 75(C).
    28. Tang, Chang & Irfan, Muhammad & Razzaq, Asif & Dagar, Vishal, 2022. "Natural resources and financial development: Role of business regulations in testing the resource-curse hypothesis in ASEAN countries," Resources Policy, Elsevier, vol. 76(C).
    29. Liang, Huijun & Shi, Changkuan & Abid, Nabila & Yu, Yanliang, 2023. "Are digitalization and human development discarding the resource curse in emerging economies?," Resources Policy, Elsevier, vol. 85(PB).
    30. Mamoudou Camara, 2023. "Bauxite mining and economic growth in Guinea over the period 1986–2020: empirical evidence from ARDL and NARDL approaches," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(1), pages 157-179, January.
    31. Wang, Lu & Chang, Hsu-Ling & Sari, Arif & Sowah, James Karmoh & Cai, Xu-Yu, 2020. "Resources or development first: An interesting question for a developing country," Resources Policy, Elsevier, vol. 68(C).
    32. Rajkumar, G. & Saravanan, M. & Marimuthu, P., 2023. "Developing a numerical model to analyze the production process of PMEDM," Resources Policy, Elsevier, vol. 80(C).
    33. Zhu, Jia & Zhou, Pengfei & Shen, Yang, 2024. "Exploring the individual and combined effect of natural resource rents, fin-tech, and renewable energy on sustainable development: New insights from SSA countries," Resources Policy, Elsevier, vol. 91(C).
    34. Jiang, Wanxing & Gao, Han, 2023. "The nexus between natural resources and exports of goods and services in the OECD countries," Resources Policy, Elsevier, vol. 85(PA).
    35. GU, Jianqiang & Umar, Muhammad & Soran, Semih & Yue, Xiao-Guang, 2020. "Exacerbating effect of energy prices on resource curse: Can research and development be a mitigating factor?," Resources Policy, Elsevier, vol. 67(C).
    36. Long, Hai & Li, Wen-Wei & Otrakçı, Caner, 2023. "Sustaining environment through natural resource and human development: Revisiting EKC curve in China through BARDL," Resources Policy, Elsevier, vol. 85(PB).
    37. Cao, Yanyan & Xiang, Shihui, 2023. "Natural resources volatility and causal associations for BRICS countries: Evidence from Covid-19 data," Resources Policy, Elsevier, vol. 80(C).
    38. Tadadjeu, Sosson & Njangang, Henri & Ningaye, Paul & Nourou, Mohammadou, 2020. "Linking natural resource dependence and access to water and sanitation in African countries," Resources Policy, Elsevier, vol. 69(C).
    39. Baz, Khan & Xu, Deyi & Cheng, Jinhua & Zhu, Yongguang & Huaping, Sun & Ali, Hashmat & Abbas, Khizar & Ali, Imad, 2022. "Effect of mineral resource complexity and fossil fuel consumption on economic growth: A new study based on the product complexity index from emerging Asian economies," Energy, Elsevier, vol. 261(PB).
    40. Wen, Jun & Mughal, Nafeesa & Kashif, Maryam & Jain, Vipin & Ramos Meza, Carlos Samuel & Cong, Phan The, 2022. "Volatility in natural resources prices and economic performance: Evidence from BRICS economies," Resources Policy, Elsevier, vol. 75(C).
    41. Michael Asiedu & Ebenezer Nana Yeboah & David Owusu Boakye, 2021. "Natural Resources and the Economic Growth of West Africa Economies," Applied Economics and Finance, Redfame publishing, vol. 8(2), pages 20-32, March.
    42. Bakhsh, Satar & Zhang, Wei, 2023. "How does natural resource price volatility affect economic performance? A threshold effect of economic policy uncertainty," Resources Policy, Elsevier, vol. 82(C).
    43. Tabash, Mosab I. & Mesagan, Ekundayo Peter & Farooq, Umar, 2022. "Dynamic linkage between natural resources, economic complexity, and economic growth: Empirical evidence from Africa," Resources Policy, Elsevier, vol. 78(C).
    44. Issaka Dialga & Youmanli Ouoba, 2022. "How do extractive resources affect human development ? Evidence from a panel data analysis," Post-Print hal-04467781, HAL.
    45. Berna Dogan, . "Does FDI in agriculture promote food security in developing countries? The role of land governance," UNCTAD Transnational Corporations Journal, United Nations Conference on Trade and Development.
    46. Li, Yumei & Naqvi, Bushra & Caglar, Ersin & Chu, Chien-Chi, 2020. "N-11 countries: Are the new victims of resource-curse?," Resources Policy, Elsevier, vol. 67(C).
    47. Ahmad, Mahmood & Peng, Tao & Awan, Ashar & Ahmed, Zahoor, 2023. "Policy framework considering resource curse, renewable energy transition, and institutional issues: Fostering sustainable development and sustainable natural resource consumption practices," Resources Policy, Elsevier, vol. 86(PB).
    48. Li, Yurog & Cong, Zhenglong & Xie, Yufan & Wang, Yan & Wang, Hongmei, 2022. "The relationship between green finance, economic factors, geopolitical risk and natural resources commodity prices: Evidence from five most natural resources holding countries," Resources Policy, Elsevier, vol. 78(C).

  9. Claveria, Oscar, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 53(1), pages 1-3.

    Cited by:

    1. Emilia Tomczyk & Barbara Kowalczyk, 2023. "Consensus in Business Tendency Surveys: Comparison of Alternative Measures," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 4, pages 17-29.
    2. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    3. Petar Soric & Oscar Claveria, 2021. "“Employment uncertainty a year after the irruption of the covid-19 pandemic”," AQR Working Papers 202104, University of Barcelona, Regional Quantitative Analysis Group, revised May 2021.
    4. Lenka Mynaříková & Vít Pošta, 2023. "The Effect of Consumer Confidence and Subjective Well-being on Consumers’ Spending Behavior," Journal of Happiness Studies, Springer, vol. 24(2), pages 429-453, February.
    5. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    6. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "“Spectral analysis of business and consumer survey data”," AQR Working Papers 2012002, University of Barcelona, Regional Quantitative Analysis Group, revised May 2020.
    8. Wooi Chen Khoo & Kim Leng Yeah & Shun Yi Hong, 2022. "Modeling unemployment duration, determinants and insurance premium pricing of Malaysia: insights from an upper middle-income developing country," SN Business & Economics, Springer, vol. 2(8), pages 1-25, August.
    9. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    10. Petar Sorić & Blanka Škrabić Perić & Marina Matošec, 2022. "Breaking new grounds: a fresh insight into the leading properties of business and consumer survey indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4511-4535, December.
    11. António Bento Caleiro, 2021. "Learning to Classify the Consumer Confidence Indicator (in Portugal)," Economies, MDPI, vol. 9(3), pages 1-12, September.
    12. Aurelia Rybak & Aleksandra Rybak, 2021. "The Impact of the COVID-19 Pandemic on Gaseous and Solid Air Pollutants Concentrations and Emissions in the EU, with Particular Emphasis on Poland," Energies, MDPI, vol. 14(11), pages 1-25, June.
    13. Phi-Hung Nguyen & Jung-Fa Tsai & Ihsan Erdem Kayral & Ming-Hua Lin, 2021. "Unemployment Rates Forecasting with Grey-Based Models in the Post-COVID-19 Period: A Case Study from Vietnam," Sustainability, MDPI, vol. 13(14), pages 1-27, July.
    14. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.
    15. Gillmann, Niels & Kim, Alisa, 2021. "Quantification of Economic Uncertainty: a deep learning approach," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242421, Verein für Socialpolitik / German Economic Association.
    16. Oscar Claveria, 2020. "Measuring and assessing economic uncertainty," IREA Working Papers 202011, University of Barcelona, Research Institute of Applied Economics, revised Jul 2020.
    17. Periklis Gogas & Theophilos Papadimitriou & Emmanouil Sofianos, 2022. "Forecasting unemployment in the euro area with machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 551-566, April.
    18. Adriana AnaMaria Davidescu & Simona-Andreea Apostu & Liviu Adrian Stoica, 2021. "Socioeconomic Effects of COVID-19 Pandemic: Exploring Uncertainty in the Forecast of the Romanian Unemployment Rate for the Period 2020–2023," Sustainability, MDPI, vol. 13(13), pages 1-22, June.

  10. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.

    Cited by:

    1. David G. Blanchflower & Alex Bryson, 2021. "The Economics of Walking About and Predicting Unemployment," DoQSS Working Papers 21-24, Quantitative Social Science - UCL Social Research Institute, University College London.
    2. Silveira, Jaylson Jair da & Lima, Gilberto Tadeu, 2021. "Can workers’ increased pessimism about the labor market conditions raise unemployment?," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 125-134.
    3. Petar Soric & Oscar Claveria, 2021. "“Employment uncertainty a year after the irruption of the covid-19 pandemic”," AQR Working Papers 202104, University of Barcelona, Regional Quantitative Analysis Group, revised May 2021.
    4. Lenka Mynaříková & Vít Pošta, 2023. "The Effect of Consumer Confidence and Subjective Well-being on Consumers’ Spending Behavior," Journal of Happiness Studies, Springer, vol. 24(2), pages 429-453, February.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "“Spectral analysis of business and consumer survey data”," AQR Working Papers 2012002, University of Barcelona, Regional Quantitative Analysis Group, revised May 2020.
    6. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2021. "Frequency domain analysis and filtering of business and consumer survey expectations," International Economics, Elsevier, vol. 166(C), pages 42-57.
    7. Petar Soric & Mateo Zokalj & Marija Logarusic, 2020. "Economic determinants of Croatian consumer confidence: real estate prices vs. macroeconomy," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 18(2B), pages 240-257.
    8. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    9. Zaremba, Adam & Cakici, Nusret & Bianchi, Robert J. & Long, Huaigang, 2023. "Interest rate changes and the cross-section of global equity returns," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).

  11. Oscar Claveria, 2019. "A new consensus-based unemployment indicator," Applied Economics Letters, Taylor & Francis Journals, vol. 26(10), pages 812-817, June.

    Cited by:

    1. David G. Blanchflower & Alex Bryson, 2021. "The Economics of Walking About and Predicting Unemployment," DoQSS Working Papers 21-24, Quantitative Social Science - UCL Social Research Institute, University College London.
    2. Oscar Claveria, 2020. "Business and consumer uncertainty in the face of the pandemic: A sector analysis in European countries," Papers 2012.02091, arXiv.org.
    3. Petar Soric & Oscar Claveria, 2021. "“Employment uncertainty a year after the irruption of the covid-19 pandemic”," AQR Working Papers 202104, University of Barcelona, Regional Quantitative Analysis Group, revised May 2021.
    4. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    5. Oscar Claveria, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-10, December.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "“Spectral analysis of business and consumer survey data”," AQR Working Papers 2012002, University of Barcelona, Regional Quantitative Analysis Group, revised May 2020.
    7. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    8. Oscar Claveria, 2020. "Measuring and assessing economic uncertainty," IREA Working Papers 202011, University of Barcelona, Research Institute of Applied Economics, revised Jul 2020.
    9. Martin Kenyeres & Jozef Kenyeres, 2023. "Distributed Average Consensus Algorithms in d-Regular Bipartite Graphs: Comparative Study," Future Internet, MDPI, vol. 15(5), pages 1-24, May.
    10. Blanchflower, David G. & Bryson, Alex, 2023. "Labour Market Expectations and Unemployment in Europe," IZA Discussion Papers 15905, Institute of Labor Economics (IZA).

  12. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Economic Uncertainty: A Geometric Indicator of Discrepancy Among Experts’ Expectations," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 95-114, May.

    Cited by:

    1. Emilia Tomczyk & Barbara Kowalczyk, 2023. "Consensus in Business Tendency Surveys: Comparison of Alternative Measures," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 4, pages 17-29.
    2. Songul Tolan & Annarosa Pesole & Fernando Martinez-Plumed & Enrique Fernandez-Macias & José Hernandez-Orallo & Emilia Gomez, 2020. "Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks," JRC Working Papers on Labour, Education and Technology 2020-02, Joint Research Centre.
    3. Andreas Dibiasi, 2021. "Measuring Knightian uncertainty," Post-Print hal-03391638, HAL.
    4. Oscar Claveria, 2020. "Business and consumer uncertainty in the face of the pandemic: A sector analysis in European countries," Papers 2012.02091, arXiv.org.
    5. Petar Soric & Oscar Claveria, 2021. "“Employment uncertainty a year after the irruption of the covid-19 pandemic”," AQR Working Papers 202104, University of Barcelona, Regional Quantitative Analysis Group, revised May 2021.
    6. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    7. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    8. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).
    9. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    10. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.

  13. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.

    Cited by:

    1. David Alaminos & M. Belén Salas & Manuel A. Fernández-Gámez, 2022. "Quantum Computing and Deep Learning Methods for GDP Growth Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 803-829, February.
    2. David G. Blanchflower & Alex Bryson, 2021. "The Economics of Walking About and Predicting Unemployment," DoQSS Working Papers 21-24, Quantitative Social Science - UCL Social Research Institute, University College London.
    3. Christos Alexakis & Michael Dowling & Konstantinos Eleftheriou & Michael Polemis, 2021. "Textual Machine Learning: An Application to Computational Economics Research," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 369-385, January.
    4. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    5. Mustafa Ozguven & Chong Yan Gao & Mohamed Yacine Si Tayeb, 2021. "The Utilization of Autoregressive Forecasting Models in Strategic Management," International Journal of Science and Business, IJSAB International, vol. 5(7), pages 170-185.
    6. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "“Spectral analysis of business and consumer survey data”," AQR Working Papers 2012002, University of Barcelona, Regional Quantitative Analysis Group, revised May 2020.
    8. José A. Tenreiro Machado & Maria Eugénia Mata & António M. Lopes, 2020. "Fractional Dynamics and Pseudo-Phase Space of Country Economic Processes," Mathematics, MDPI, vol. 8(1), pages 1-17, January.
    9. Lucia Modugno, 2024. "Evaluating Qualitative Expectational Data on Investments from Business Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(1), pages 59-88, August.
    10. Rui Luan & Ping Xu, 2024. "Risk Prediction of the Development of the Digital Economy Industry Based on a Machine Learning Model in the Context of Rural Revitalization," Information Resources Management Journal (IRMJ), IGI Global, vol. 37(1), pages 1-21, January.
    11. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    12. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.
    13. Blanchflower, David G. & Bryson, Alex, 2023. "Labour Market Expectations and Unemployment in Europe," IZA Discussion Papers 15905, Institute of Labor Economics (IZA).

  14. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.

    Cited by:

    1. David G. Blanchflower & Alex Bryson, 2021. "The Economics of Walking About and Predicting Unemployment," DoQSS Working Papers 21-24, Quantitative Social Science - UCL Social Research Institute, University College London.
    2. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "“Spectral analysis of business and consumer survey data”," AQR Working Papers 2012002, University of Barcelona, Regional Quantitative Analysis Group, revised May 2020.
    4. Blanchflower, David G. & Bryson, Alex, 2023. "Labour Market Expectations and Unemployment in Europe," IZA Discussion Papers 15905, Institute of Labor Economics (IZA).

  15. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.

    Cited by:

    1. Raffaele Mattera & Michelangelo Misuraca & Maria Spano & Germana Scepi, 2023. "Mixed frequency composite indicators for measuring public sentiment in the EU," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2357-2382, June.
    2. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    3. Yelin Fu & Kong Xiangtianrui & Hao Luo & Lean Yu, 2020. "Constructing Composite Indicators with Collective Choice and Interval-Valued TOPSIS: The Case of Value Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(1), pages 117-135, November.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "“Spectral analysis of business and consumer survey data”," AQR Working Papers 2012002, University of Barcelona, Regional Quantitative Analysis Group, revised May 2020.
    5. Tianjiao Wang & Yelin Fu, 2020. "Constructing Composite Indicators with Individual Judgements and Best–Worst Method: An Illustration of Value Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(1), pages 1-14, May.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    7. Petar Sorić & Blanka Škrabić Perić & Marina Matošec, 2022. "Breaking new grounds: a fresh insight into the leading properties of business and consumer survey indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4511-4535, December.

  16. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Using survey data to forecast real activity with evolutionary algorithms. A cross-country analysis," Journal of Applied Economics, Universidad del CEMA, vol. 20, pages 329-349, November.

    Cited by:

    1. David G. Blanchflower & Alex Bryson, 2021. "The Economics of Walking About and Predicting Unemployment," DoQSS Working Papers 21-24, Quantitative Social Science - UCL Social Research Institute, University College London.
    2. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    3. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "“Spectral analysis of business and consumer survey data”," AQR Working Papers 2012002, University of Barcelona, Regional Quantitative Analysis Group, revised May 2020.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    6. Rui Luan & Ping Xu, 2024. "Risk Prediction of the Development of the Digital Economy Industry Based on a Machine Learning Model in the Context of Rural Revitalization," Information Resources Management Journal (IRMJ), IGI Global, vol. 37(1), pages 1-21, January.
    7. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.
    9. Blanchflower, David G. & Bryson, Alex, 2023. "Labour Market Expectations and Unemployment in Europe," IZA Discussion Papers 15905, Institute of Labor Economics (IZA).

  17. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Assessment of the effect of the financial crisis on agents’ expectations through symbolic regression," Applied Economics Letters, Taylor & Francis Journals, vol. 24(9), pages 648-652, May.

    Cited by:

    1. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    2. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.

  18. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.

    Cited by:

    1. Juan Gabriel Brida & Bibiana Lanzilotta & Lucía Rosich, 2019. "Common trends in producers’ expectations, the nonlinear linkage with Uruguayan GDP and its implications in economic growth forecasting," Documentos de Trabajo (working papers) 19-28, Instituto de Economía - IECON.
    2. Oscar Claveria, 2018. "“A new metric of consensus for Likert scales”," IREA Working Papers 201821, University of Barcelona, Research Institute of Applied Economics, revised Oct 2018.
    3. Raffaele Mattera & Michelangelo Misuraca & Maria Spano & Germana Scepi, 2023. "Mixed frequency composite indicators for measuring public sentiment in the EU," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2357-2382, June.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Economic Uncertainty: A Geometric Indicator of Discrepancy Among Experts’ Expectations," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 95-114, May.
    5. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "“Spectral analysis of business and consumer survey data”," AQR Working Papers 2012002, University of Barcelona, Regional Quantitative Analysis Group, revised May 2020.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    8. Petar Soric & Mateo Zokalj & Marija Logarusic, 2020. "Economic determinants of Croatian consumer confidence: real estate prices vs. macroeconomy," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 18(2B), pages 240-257.
    9. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," IREA Working Papers 201806, University of Barcelona, Research Institute of Applied Economics, revised Mar 2018.
    10. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    11. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
    12. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    13. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.

  19. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2016. "A self-organizing map analysis of survey-based agents׳ expectations before impending shocks for model selection: The case of the 2008 financial crisis," International Economics, Elsevier, vol. 146(C), pages 40-58.

    Cited by:

    1. Oscar Claveria, 2017. "“What really matters is the economic performance: Positioning tourist destinations by means of perceptual maps”," AQR Working Papers 201707, University of Barcelona, Regional Quantitative Analysis Group, revised Jul 2017.
    2. Hector M. Zarate-Solano & Daniel R. Zapata-Sanabria, 2017. "Clustering and forecasting inflation expectations using the World Economic Survey: the case of the 2014 oil price shock on inflation targeting countries," Borradores de Economia 993, Banco de la Republica de Colombia.
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    4. Hyun Hak Kim, 2022. "A dynamic analysis of household debt using a self-organizing map," Empirical Economics, Springer, vol. 62(6), pages 2893-2919, June.

  20. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 341-357, August.

    Cited by:

    1. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A regional perspective on the accuracy of machine learning forecasts of tourism demand based on data characteristics”," AQR Working Papers 201802, University of Barcelona, Regional Quantitative Analysis Group, revised Apr 2018.
    2. Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022. "“An application of deep learning for exchange rate forecasting”," AQR Working Papers 202201, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2022.
    3. Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022. ""Density forecasts of inflation using Gaussian process regression models"," IREA Working Papers 202210, University of Barcelona, Research Institute of Applied Economics, revised Jul 2022.
    4. Poonpong Suksawang & Sukonthip Suphachan & Kanokkarn Kaewnuch, 2018. "Electricity Consumption Forecasting in Thailand using Hybrid Model SARIMA and Gaussian Process with Combine Kernel Function Technique," International Journal of Energy Economics and Policy, Econjournals, vol. 8(4), pages 98-109.

  21. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Combination forecasts of tourism demand with machine learning models," Applied Economics Letters, Taylor & Francis Journals, vol. 23(6), pages 428-431, April.

    Cited by:

    1. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A regional perspective on the accuracy of machine learning forecasts of tourism demand based on data characteristics”," AQR Working Papers 201802, University of Barcelona, Regional Quantitative Analysis Group, revised Apr 2018.
    2. Seyed Farshid Ghorashi & Maziyar Bahri & Atousa Goodarzi, 2024. "Developing and comparing machine learning approaches for predicting insurance penetration rates based on each country," Letters in Spatial and Resource Sciences, Springer, vol. 17(1), pages 1-29, December.
    3. Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022. ""Density forecasts of inflation using Gaussian process regression models"," IREA Working Papers 202210, University of Barcelona, Research Institute of Applied Economics, revised Jul 2022.
    4. Anca-Gabriela Turtureanu & Rodica Pripoaie & Carmen-Mihaela Cretu & Carmen-Gabriela Sirbu & Emanuel Ştefan Marinescu & Laurentiu-Gabriel Talaghir & Florentina Chițu, 2022. "A Projection Approach of Tourist Circulation under Conditions of Uncertainty," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    5. Sule Birim & Ipek Kazancoglu & Sachin Kumar Mangla & Aysun Kahraman & Yigit Kazancoglu, 2024. "The derived demand for advertising expenses and implications on sustainability: a comparative study using deep learning and traditional machine learning methods," Annals of Operations Research, Springer, vol. 339(1), pages 131-161, August.
    6. Moreno-Izquierdo, Luis & Egorova, Galina & Peretó-Rovira, Alexandre & Más-Ferrando , Adrián, 2018. "Exploring the use of artificial intelligence in price maximisation in the tourism sector: its application in the case of Airbnb in the Valencian Community," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 42, pages 113-128.
    7. Chuan Zhang & Ao‐Yun Hu & Yu‐Xin Tian, 2023. "Daily tourism forecasting through a novel method based on principal component analysis, grey wolf optimizer, and extreme learning machine," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2121-2138, December.
    8. Bi, Jian-Wu & Li, Hui & Fan, Zhi-Ping, 2021. "Tourism demand forecasting with time series imaging: A deep learning model," Annals of Tourism Research, Elsevier, vol. 90(C).
    9. Xi Wu & Adam Blake, 2023. "Does the combination of models with different explanatory variables improve tourism demand forecasting performance?," Tourism Economics, , vol. 29(8), pages 2032-2056, December.
    10. Artemisa Zaragoza-Ibarra & Gerardo G. Alfaro-Calderón & Víctor G. Alfaro-García & Fernando Ornelas-Tellez & Rodrigo Gómez-Monge, 2021. "A machine learning model of national competitiveness with regional statistics of public expenditure," Computational and Mathematical Organization Theory, Springer, vol. 27(4), pages 451-468, December.
    11. Mr. Serhan Cevik, 2020. "Where Should We Go? Internet Searches and Tourist Arrivals," IMF Working Papers 2020/022, International Monetary Fund.
    12. Wai Kit Tsang & Dries F. Benoit, 2020. "Gaussian processes for daily demand prediction in tourism planning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 551-568, April.
    13. Bi, Jian-Wu & Liu, Yang & Li, Hui, 2020. "Daily tourism volume forecasting for tourist attractions," Annals of Tourism Research, Elsevier, vol. 83(C).
    14. Ling Tang & Chengyuan Zhang & Tingfei Li & Ling Li, 2021. "A novel BEMD-based method for forecasting tourist volume with search engine data," Tourism Economics, , vol. 27(5), pages 1015-1038, August.

  22. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies," Eastern European Economics, Taylor & Francis Journals, vol. 54(2), pages 171-189, March.

    Cited by:

    1. Juan Gabriel Brida & Bibiana Lanzilotta & Lucía Rosich, 2019. "Common trends in producers’ expectations, the nonlinear linkage with Uruguayan GDP and its implications in economic growth forecasting," Documentos de Trabajo (working papers) 19-28, Instituto de Economía - IECON.
    2. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    3. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    6. Petar Sorić & Ivana Lolić & Marina Matošec, 2020. "Some properties of inflation expectations in the euro area," Metroeconomica, Wiley Blackwell, vol. 71(1), pages 176-203, February.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
    9. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.

  23. Claveria, Oscar & Torra, Salvador, 2014. "Forecasting tourism demand to Catalonia: Neural networks vs. time series models," Economic Modelling, Elsevier, vol. 36(C), pages 220-228.

    Cited by:

    1. Reza Sanei & Farhad Hosseinzadeh lotfi & Mohammad Fallah & Farzad Movahedi Sobhani, 2022. "An Estimation of an Acceptable Efficiency Frontier Having an Optimum Resource Management Approach, with a Combination of the DEA-ANN-GA Technique (A Case Study of Branches of an Insurance Company)," Mathematics, MDPI, vol. 10(23), pages 1-21, November.
    2. Silva, Emmanuel Sirimal & Hassani, Hossein & Heravi, Saeed & Huang, Xu, 2019. "Forecasting tourism demand with denoised neural networks," Annals of Tourism Research, Elsevier, vol. 74(C), pages 134-154.
    3. Lingyu, Tang & Jun, Wang & Chunyu, Zhao, 2021. "Mode decomposition method integrating mode reconstruction, feature extraction, and ELM for tourist arrival forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    4. Marcos à lvarez-Díaz & Manuel González-Gómez & María Soledad Otero-Giráldez, 2019. "Estimating the economic impact of a political conflict on tourism: The case of the Catalan separatist challenge," Tourism Economics, , vol. 25(1), pages 34-50, February.
    5. Li, Hengyun & Hu, Mingming & Li, Gang, 2020. "Forecasting tourism demand with multisource big data," Annals of Tourism Research, Elsevier, vol. 83(C).
    6. Wanke, Peter & Barros, Carlos Pestana, 2016. "Efficiency drivers in Brazilian insurance: A two-stage DEA meta frontier-data mining approach," Economic Modelling, Elsevier, vol. 53(C), pages 8-22.
    7. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
    8. Andrea Saayman & Ilsé Botha, 2017. "Non-linear models for tourism demand forecasting," Tourism Economics, , vol. 23(3), pages 594-613, May.
    9. Binglei Xie & Yu Sun & Xiaolong Huang & Le Yu & Gangyan Xu, 2020. "Travel Characteristics Analysis and Passenger Flow Prediction of Intercity Shuttles in the Pearl River Delta on Holidays," Sustainability, MDPI, vol. 12(18), pages 1-23, September.
    10. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    11. Dr. Murat çuhadar & Iclal Cogurcu & Ceyda Kukrer, 2014. "Modelling and Forecasting Cruise Tourism Demand to Izmir by Different Artificial Neural Network Architectures," International Journal of Business and Social Research, LAR Center Press, vol. 4(3), pages 12-28, March.
    12. Oscar Claveria & Enric Monte & Salvador Torra, 2013. "“Tourism demand forecasting with different neural networks models”," AQR Working Papers 201313, University of Barcelona, Regional Quantitative Analysis Group, revised Nov 2013.
    13. Katerina Volchek & Anyu Liu & Haiyan Song & Dimitrios Buhalis, 2019. "Forecasting tourist arrivals at attractions: Search engine empowered methodologies," Tourism Economics, , vol. 25(3), pages 425-447, May.
    14. Oscar Claveria & Enric Monte & Salvador Torra, 2014. "“A multivariate neural network approach to tourism demand forecasting”," AQR Working Papers 201410, University of Barcelona, Regional Quantitative Analysis Group, revised May 2014.
    15. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A regional perspective on the accuracy of machine learning forecasts of tourism demand based on data characteristics”," AQR Working Papers 201802, University of Barcelona, Regional Quantitative Analysis Group, revised Apr 2018.
    16. El houssin Ouassou & Hafsa Taya, 2022. "Forecasting Regional Tourism Demand in Morocco from Traditional and AI-Based Methods to Ensemble Modeling," Forecasting, MDPI, vol. 4(2), pages 1-18, April.
    17. Marisol Valencia Cárdenas & Juan Gabriel Vanegas López & Juan Carlos Correa Morales & Jorge Aníbal Restrepo Morales, 2017. "Comparing forecasts for tourism dynamics in Medellín, Colombia," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 86, pages 199-230, Enero - J.
    18. Mathias Bärtl & Simone Krummaker, 2020. "Prediction of Claims in Export Credit Finance: A Comparison of Four Machine Learning Techniques," Risks, MDPI, vol. 8(1), pages 1-27, March.
    19. Jun, Wang & Yuyan, Luo & Lingyu, Tang & Peng, Ge, 2018. "Modeling a combined forecast algorithm based on sequence patterns and near characteristics: An application for tourism demand forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 108(C), pages 136-147.
    20. Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022. "“An application of deep learning for exchange rate forecasting”," AQR Working Papers 202201, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2022.
    21. Long Wen & Chang Liu & Haiyan Song, 2019. "Forecasting tourism demand using search query data: A hybrid modelling approach," Tourism Economics, , vol. 25(3), pages 309-329, May.
    22. Ahmad Nazrul Hakimi Ibrahim & Muhamad Nazri Borhan & Mohd Haniff Osman & Muhamad Razuhanafi Mat Yazid & Munzilah Md. Rohani, 2022. "The Influence of Service Quality on User’s Perceived Satisfaction with Light Rail Transit Service in Klang Valley, Malaysia," Mathematics, MDPI, vol. 10(13), pages 1-21, June.
    23. Yılmaz, Engin, 2015. "Forecasting tourist arrivals to Turkey," MPRA Paper 68616, University Library of Munich, Germany.
    24. Ogechi Adeola & Nathaniel Boso & Olaniyi Evans, 2018. "Drivers of international tourism demand in Africa," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 53(1), pages 25-36, January.
    25. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
    26. Jorge V Pérez-Rodríguez & María Santana-Gallego, 2020. "Modelling tourism receipts and associated risks, using long-range dependence models," Tourism Economics, , vol. 26(1), pages 70-96, February.
    27. Yi-Chung Hu, 2023. "Tourism combination forecasting using a dynamic weighting strategy with change-point analysis," Current Issues in Tourism, Taylor & Francis Journals, vol. 26(14), pages 2357-2374, July.
    28. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 341-357, August.
    29. Grabowski Daniel & Staszewska-Bystrova Anna & Winker Peter, 2017. "Generating prediction bands for path forecasts from SETAR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(5), pages 1-18, December.
    30. Kamel Jlassi, 2015. "Modelling and Forecasting of Tunisian Current Account: Aggregate versus Disaggregate Approach," IHEID Working Papers 13-2015, Economics Section, The Graduate Institute of International Studies.
    31. Hu, Yi-Chung, 2023. "Air passenger flow forecasting using nonadditive forecast combination with grey prediction," Journal of Air Transport Management, Elsevier, vol. 112(C).
    32. Valencia Cárdenas, Marisol & Vanegas López, Juan Gabriel & Correa Morales, Juan Carlos & Restrepo Morales, Jorge Aníbal, 2016. "Comparación de pronósticos para la dinámica del turismo en Medellín, Colombia," Revista Lecturas de Economía, Universidad de Antioquia, CIE, issue 86, pages 199-230, December.
    33. Moreno-Izquierdo, Luis & Egorova, Galina & Peretó-Rovira, Alexandre & Más-Ferrando , Adrián, 2018. "Exploring the use of artificial intelligence in price maximisation in the tourism sector: its application in the case of Airbnb in the Valencian Community," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 42, pages 113-128.
    34. Marcos Álvarez-Díaz & Manuel González-Gómez & María Soledad Otero-Giráldez, 2018. "Forecasting International Tourism Demand Using a Non-Linear Autoregressive Neural Network and Genetic Programming," Forecasting, MDPI, vol. 1(1), pages 1-17, September.
    35. Correa, Alexander, 2021. "Prediciendo la llegada de turistas a Colombia a partir de los criterios de Google Trends," Revista Lecturas de Economía, Universidad de Antioquia, CIE, issue No. 95, pages 105-134, July.
    36. Zhao, Shangwei & Xie, Tian & Ai, Xin & Yang, Guangren & Zhang, Xinyu, 2023. "Correcting sample selection bias with model averaging for consumer demand forecasting," Economic Modelling, Elsevier, vol. 123(C).
    37. Maela Madel L. Cahigas & Ardvin Kester S. Ong & Yogi Tri Prasetyo, 2023. "Super Typhoon Rai’s Impacts on Siargao Tourism: Deciphering Tourists’ Revisit Intentions through Machine-Learning Algorithms," Sustainability, MDPI, vol. 15(11), pages 1-29, May.
    38. Weiwei Zhang & Mingyan Wang, 2021. "An improved deep forest model for prediction of e-commerce consumers’ repurchase behavior," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-16, September.
    39. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Combination forecasts of tourism demand with machine learning models," Applied Economics Letters, Taylor & Francis Journals, vol. 23(6), pages 428-431, April.
    40. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting”," AQR Working Papers 201701, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2017.
    41. Haddad, S. & Benghanem, M. & Mellit, A. & Daffallah, K.O., 2015. "ANNs-based modeling and prediction of hourly flow rate of a photovoltaic water pumping system: Experimental validation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 635-643.
    42. Jean-François Verne, 2021. "Smooth Threshold Autoregressive models and Markov process: An application to the Lebanese GDP growth rate," International Econometric Review (IER), Econometric Research Association, vol. 13(3), pages 71-88, September.
    43. Han Liu & Ying Liu & Yonglian Wang & Changchun Pan, 2019. "Hot topics and emerging trends in tourism forecasting research: A scientometric review," Tourism Economics, , vol. 25(3), pages 448-468, May.
    44. Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
    45. Hassani, Hossein & Silva, Emmanuel Sirimal & Antonakakis, Nikolaos & Filis, George & Gupta, Rangan, 2017. "Forecasting accuracy evaluation of tourist arrivals," Annals of Tourism Research, Elsevier, vol. 63(C), pages 112-127.
    46. Chi-Wei Su & Xian-Li Meng & Ran Tao & Muhammad Umar, 2023. "Chinese consumer confidence: A catalyst for the outbound tourism expenditure?," Tourism Economics, , vol. 29(3), pages 696-717, May.
    47. Chen, Fu-Hsiang & Chi, Der-Jang & Wang, Yi-Cheng, 2015. "Detecting biotechnology industry's earnings management using Bayesian network, principal component analysis, back propagation neural network, and decision tree," Economic Modelling, Elsevier, vol. 46(C), pages 1-10.
    48. Dr. Murat çuhadar & Iclal Cogurcu & Ceyda Kukrer, 2014. "Modelling and Forecasting Cruise Tourism Demand to Izmir by Different Artificial Neural Network Architectures," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(3), pages 12-28, March.
    49. Hewamalage, Hansika & Bergmeir, Christoph & Bandara, Kasun, 2021. "Recurrent Neural Networks for Time Series Forecasting: Current status and future directions," International Journal of Forecasting, Elsevier, vol. 37(1), pages 388-427.
    50. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Regional Forecasting with Support Vector Regressions: The Case of Spain”," AQR Working Papers 201506, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2015.
    51. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.
    52. Tea Šestanović & Josip Arnerić, 2021. "Neural network structure identification in inflation forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 62-79, January.
    53. Ke Xu & Junli Zhang & Junhao Huang & Hongbo Tan & Xiuli Jing & Tianxiang Zheng, 2024. "Forecasting Visitor Arrivals at Tourist Attractions: A Time Series Framework with the N-BEATS for Sustainable Tourism," Sustainability, MDPI, vol. 16(18), pages 1-28, September.

  24. Claveria, Oscar & Pons, Ernest & Ramos, Raul, 2007. "Business and consumer expectations and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 47-69.

    Cited by:

    1. Dées, Stéphane & Soares Brinca, Pedro, 2011. "Consumer confidence as a predictor of consumption spending: evidence for the United States and the euro area," Working Paper Series 1349, European Central Bank.
    2. Lui, Silvia & Mitchell, James & Weale, Martin, 2011. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1128-1146, October.
    3. Juan Gabriel Brida & Bibiana Lanzilotta & Lucía Rosich, 2019. "Common trends in producers’ expectations, the nonlinear linkage with Uruguayan GDP and its implications in economic growth forecasting," Documentos de Trabajo (working papers) 19-28, Instituto de Economía - IECON.
    4. Tsuchiya, Yoichi, 2013. "Do corporate executives have accurate predictions for the economy? A directional analysis," Economic Modelling, Elsevier, vol. 30(C), pages 167-174.
    5. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
    6. Huber, Florian & Onorante, Luca & Pfarrhofer, Michael, 2024. "Forecasting euro area inflation using a huge panel of survey expectations," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1042-1054.
    7. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    8. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    9. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
    10. María Alejandra Hernández-Montes & Ramón Hernández-Ortega & Jonathan Alexander Muñoz-Martínez, 2022. "Aporte de las expectativas de empresarios al pronóstico de las variables macroeconómicas," Borradores de Economia 1202, Banco de la Republica de Colombia.
    11. Marta Necadova, 2019. "Changes in Economic Sentiment Indicators before and after Economic Crisis (Position of Visegrad Group and Germany in EU)," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 55-85.
    12. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    13. Robert Lehmann, 2015. "Survey-based indicators vs. hard data: What improves export forecasts in Europe?," ifo Working Paper Series 196, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    14. Knut Are Aastveit & Anne Sofie Jore & Francesco Ravazzolo, 2014. "Forecasting recessions in real time," Working Paper 2014/02, Norges Bank.
    15. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    16. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    17. Nikolay Robinzonov & Klaus Wohlrabe, 2010. "Freedom of Choice in Macroeconomic Forecasting ," CESifo Economic Studies, CESifo Group, vol. 56(2), pages 192-220, June.
    18. Juhro, Solikin M. & Iyke, Bernard Njindan, 2020. "Consumer confidence and consumption expenditure in Indonesia," Economic Modelling, Elsevier, vol. 89(C), pages 367-377.
    19. José R. Maria & Sara Serra, . "Previsão do Investimento em Portugal com Base em Indicadores Qualitativos e Quantitativos," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    20. Maria Rita Ippoliti & Fabiana Sartor & Luigi Martone, 2021. "Trade surveys: qualitative and quantitative indicators," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 75(4), pages 75-85, October-D.
    21. Nikolay Robinzonov & Gerhard Tutz & Torsten Hothorn, 2012. "Boosting techniques for nonlinear time series models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 99-122, January.
    22. Sudeshna Ghosh, 2021. "Consumer Confidence and Consumer Spending in Brazil: A Nonlinear Autoregressive Distributed Lag Model Analysis," Arthaniti: Journal of Economic Theory and Practice, , vol. 20(1), pages 53-85, June.
    23. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    24. Tiziana Cesaroni & Stefano Iezzi, 2015. "The Predictive Content of Business Survey Indicators: evidence from SIGE," Working Papers LuissLab 15118, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    25. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    26. Oscar Claveria, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-10, December.
    27. Claudia Foroni & Francesco Ravazzolo & Luca Rossini, 2020. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Papers 2007.13566, arXiv.org, revised Dec 2022.
    28. Ciaran Driver, 2019. "Trade liberalization and South African manufacturing: Looking back with data," WIDER Working Paper Series wp-2019-30, World Institute for Development Economic Research (UNU-WIDER).
    29. Inna S. Lola & Anton Manukov, 2020. "Forecasting Employment In Small Businesses In Russia: The Relevance Of Business Tendency Surveys," HSE Working papers WP BRP 113/STI/2020, National Research University Higher School of Economics.
    30. Gabriel Caldas Montes & André Almeida, 2017. "Corruption and business confidence: a panel data analysis," Economics Bulletin, AccessEcon, vol. 37(4), pages 2692-2702.
    31. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "“Spectral analysis of business and consumer survey data”," AQR Working Papers 2012002, University of Barcelona, Regional Quantitative Analysis Group, revised May 2020.
    32. R. Lehmann & K. Wohlrabe, 2017. "Experts, firms, consumers or even hard data? Forecasting employment in Germany," Applied Economics Letters, Taylor & Francis Journals, vol. 24(4), pages 279-283, February.
    33. G. Bruno & L. Crosilla & P. Margani, 2019. "Inspecting the Relationship Between Business Confidence and Industrial Production: Evidence on Italian Survey Data," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 15(1), pages 1-24, April.
    34. Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2022. "A babel of web-searches: Googling unemployment during the pandemic," Labour Economics, Elsevier, vol. 74(C).
    35. Claveria, Oscar & Datzira, Jordi, 2008. "Tourism Demand in Catalonia: Detecting External Economic Factors," MPRA Paper 25303, University Library of Munich, Germany, revised 12 Apr 2008.
    36. Euler Pereira G. de Mello & Francisco Marcos R. Figueiredo, 2014. "Assessing the Short-term Forecasting Power of Confidence Indices," Working Papers Series 371, Central Bank of Brazil, Research Department.
    37. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    38. Petar Sorić & Ivana Lolić & Marija Logarušić, 2022. "Economic Sentiment and Aggregate Activity: A Tale of Two European Cycles," Journal of Common Market Studies, Wiley Blackwell, vol. 60(2), pages 445-462, March.
    39. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," AQR Working Papers 201801, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2018.
    40. Christos Papamichael & Nicoletta Pashourtidou, 2016. "The Role of Survey Data in the Construction of Short-term GDP Growth Forecasts," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 10(2), pages 77-109, December.
    41. Yuan-Ming Lee & Kuan-Min Wang, 2012. "Searching for a better proxy for business cycles: with supports using US data," Applied Economics, Taylor & Francis Journals, vol. 44(11), pages 1433-1442, April.
    42. Klein, Lawrence R. & Özmucur, Süleyman, 2010. "The use of consumer and business surveys in forecasting," Economic Modelling, Elsevier, vol. 27(6), pages 1453-1462, November.
    43. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
    44. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    45. Martinsen, Kjetil & Ravazzolo, Francesco & Wulfsberg, Fredrik, 2014. "Forecasting macroeconomic variables using disaggregate survey data," International Journal of Forecasting, Elsevier, vol. 30(1), pages 65-77.
    46. Klaus Abberger & Klaus Wohlrabe, 2006. "Einige Prognoseeigenschaften des ifo Geschäftsklimas - Ein Überblick über die neuere wissenschaftliche Literatur," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(22), pages 19-26, November.
    47. Pablo Castellanos García & Indalecio Pérez Díaz del Río & Jose Manuel Sanchez-Santos, 2014. "The role of confidence in the evolution of the Spanish economy: empirical evidence from an ARDL model," European Journal of Government and Economics, Europa Grande, vol. 3(2), pages 148-161, December.
    48. Knut Are Aastveit & Andr K. Anundsen & Eyo I. Herstad, 2017. "Residential investment and recession predictability," Working Papers No 8/2017, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    49. José R. Maria & Sara Serra, 2008. "Forecasting investment: A fishing contest using survey data," Working Papers w200818, Banco de Portugal, Economics and Research Department.
    50. Klaus Abberger & Gebhard Flaig & Wolfgang Nierhaus, 2007. "ifo Konjunkturumfragen und Konjunkturanalyse : ausgewählte methodische Aufsätze aus dem ifo Schnelldienst," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 33, September.
    51. Mohd Haniff, NorAzza & Masih, Mansur, 2016. "Does consumer sentiment predict consumer spending in Malaysia? an autoregressive distributed lag (ARDL) approach," MPRA Paper 69769, University Library of Munich, Germany.
    52. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    53. André Filipe Guedes Almeida & Gabriel Caldas Montes, 2020. "Effects of crime and violence on business confidence: evidence from Rio de Janeiro," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(7), pages 1669-1688, May.
    54. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.
    55. Gillmann, Niels & Kim, Alisa, 2021. "Quantification of Economic Uncertainty: a deep learning approach," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242421, Verein für Socialpolitik / German Economic Association.
    56. Nicoletta Pashourtidou & Andreas Tsiaklis, 2011. "An Analysis of Firms’ Expectations about Activity and Employment," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 5(1), pages 71-85, June.
    57. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    58. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
    59. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    60. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.
    61. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    62. Helder Ferreira Mendonça & André Filipe Guedes Almeida, 2019. "Importance of credibility for business confidence: evidence from an emerging economy," Empirical Economics, Springer, vol. 57(6), pages 1979-1996, December.

  25. O Claveria & E Pons & J Surinach, 2006. "Quantification of Expectations. Are They Useful for Forecasting Inflation?," Economic Issues Journal Articles, Economic Issues, vol. 11(2), pages 19-38, September.

    Cited by:

    1. Werner Hölzl & Gerhard Schwarz, 2014. "Der WIFO-Konjunkturtest: Methodik und Prognoseeigenschaften," WIFO Monatsberichte (monthly reports), WIFO, vol. 87(12), pages 835-850, December.
    2. Oscar Claveria & Salvador Torra, 2013. "“Forecasting Business surveys indicators: neural networks vs. time series models”," IREA Working Papers 201320, University of Barcelona, Research Institute of Applied Economics, revised Nov 2013.
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    4. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    5. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    6. Petar Soric & Mateo Zokalj & Marija Logarusic, 2020. "Economic determinants of Croatian consumer confidence: real estate prices vs. macroeconomy," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 18(2B), pages 240-257.
    7. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "A new approach for the quantification of qualitative measures of economic expectations," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2685-2706, November.
    9. Santiago Pinto & Pierre-Daniel G. Sarte & Robert Sharp, 2015. "Learning About Consumer Uncertainty from Qualitative Surveys: As Uncertain As Ever," Working Paper 15-9, Federal Reserve Bank of Richmond.
    10. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.

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