Bibliografie tematiche / Economic forecasting

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Letteratura scientifica selezionata sul tema "Economic forecasting"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 25 luglio 2025

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Articoli di riviste sul tema "Economic forecasting"

1

Clark, Mary E. "Economic Forecasting." Science 246, no. 4926 (1989): 10. http://dx.doi.org/10.1126/science.246.4926.10.b.

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Lieberman, Bernhardt. "Economic Forecasting." Science 246, no. 4926 (1989): 10. http://dx.doi.org/10.1126/science.246.4926.10.a.

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CLARK, M. E. "Economic Forecasting." Science 246, no. 4926 (1989): 10. http://dx.doi.org/10.1126/science.246.4926.10-a.

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4

Vogelsang, Timothy J. "Economic Forecasting." Journal of the American Statistical Association 96, no. 453 (2001): 339–55. http://dx.doi.org/10.1198/jasa.2001.s386.

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5

Elliott, Graham, and Allan Timmermann. "Economic Forecasting." Journal of Economic Literature 46, no. 1 (2008): 3–56. http://dx.doi.org/10.1257/jel.46.1.3.

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Forecasts guide decisions in all areas of economics and finance and their value can only be understood in relation to, and in the context of, such decisions. We discuss the central role of the loss function in helping determine the forecaster's objectives. Decision theory provides a framework for both the construction and evaluation of forecasts. This framework allows an understanding of the challenges that arise from the explosion in the sheer volume of predictor variables under consideration and the forecaster's ability to entertain an endless array of forecasting models and time-varying spe
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6

Суворов, Anatoliy Suvorov, Ивантер, Viktor Ivantyer, Сутягин, and Valyeriy Sutyagin. "The Main Objectives and Principles of Socio-Economic Forecasting." Administration 3, no. 1 (2015): 8–17. http://dx.doi.org/10.12737/8785.

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The methodological foundations of socio-economic forecasting are considered in this paper. The forecasting’s
 definition is given; the forecasting’s role and place in national economy regulation are considered. Forecasts
 types’ classification and the forecasting’s basic principles have been presented. Forecasting models’
 structure and classification, as well as socio-economic forecasts’ elements and development stages have
 been considered.
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Clements, Michael P., and David F. Hendry. "Forecasting economic processes." International Journal of Forecasting 14, no. 1 (1998): 111–31. http://dx.doi.org/10.1016/s0169-2070(97)00057-5.

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Bradley, M. E. "Forecasting Oilfield Economic Performance." Journal of Petroleum Technology 46, no. 11 (1994): 965–71. http://dx.doi.org/10.2118/26054-pa.

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9

Hall, Stephen G., K. Holden, D. A. Peel, and J. L. Thompson. "Economic Forecasting: An Introduction." Economica 59, no. 233 (1992): 132. http://dx.doi.org/10.2307/2555081.

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10

Swanson, Norman R., Michael P. Clements, and David F. Hendry. "Forecasting Economic Time Series." Journal of the American Statistical Association 95, no. 450 (2000): 687. http://dx.doi.org/10.2307/2669429.

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Tesi sul tema "Economic forecasting"

1

Odendahl, Florens. "Essays in economic forecasting." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/664016.

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This thesis consists of three chapters on forecasting techniques in economics. In chapter 1, I use copulas to estimate multivariate density forecasts based on univariate densities from survey data. Survey-based predictions are often competitive to time series models in their forecasting performance but have a univariate focus and my estimation strategy exploits the information in the surveys’ marginal densities. I subsequently demonstrate the importance of the multivariate aspect for forecasters. In chapter 2, we propose novel tests for forecast rationality, which are robust under the presence
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Souza, André B. M. "Essays in economic forecasting." Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/672997.

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This dissertation consists of two independent chapters on economic and financial forecasting. The first chapter introduces a nonlinear forecasting framework that combines forecasts of the sign and absolute value of a time series into conditional mean forecasts. In contrast to linear models, the proposed framework allows different predictors to separately impact the sign and absolute value of the target series. An empirical application using the FRED-MD dataset shows that forecasts from the proposed model substantially outperform linear forecasts for series that exhibit persistent volati
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Acar, Emmanuel. "Economic evaluation of financial forecasting." Thesis, City University London, 1993. http://openaccess.city.ac.uk/8256/.

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This thesis examines the economic evaluation of forecasting strategies based on past prices, bringing together academics and practitioners techniques Forecasting methods based on past prices are convex and path-dependent dynamic strategies Therefore, they must be able to profitably exploit positive serial dependences in financial prices The most important measure of financial forecasting ability is the rate of return achieved by the predictor The expected return of forecasting strategies is first investigated by applying stochastic modelling Then, the presence of serial dependences in financia
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Bezsmertna, Julia. "Modern methods of economic forecasting." Thesis, Київський національний університет технологій та дизайну, 2019. https://er.knutd.edu.ua/handle/123456789/14350.

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Sippl-Swezey, Nicolas. "Heterogeneous gain forecasting using historic asset information." Oberlin College Honors Theses / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1354304083.

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Marsilli, Clément. "Mixed-Frequency Modeling and Economic Forecasting." Thesis, Besançon, 2014. http://www.theses.fr/2014BESA2023/document.

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La prévision macroéconomique à court terme est un exercice aussi complexe qu’essentiel pour la définition de la politique économique et monétaire. Les crises financières récentes ainsi que les récessions qu’ont endurées et qu’endurent aujourd’hui encore, en ce début d’année 2014, nombre de pays parmi les plus riches, témoignent de la difficulté d’anticiper les fluctuations économiques, même à des horizons proches. Les recherches effectuées dans le cadre de la thèse de doctorat qui est présentée dans ce manuscrit se sont attachées à étudier, analyser et développer des modélisations pour la prév
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Franklin, Jesse C. "Forecasting the Inland Empire's Economic Recovery." Scholarship @ Claremont, 2010. http://scholarship.claremont.edu/cmc_theses/42.

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The Inland Empire -Riverside and San Bernardino Counties - was one of the hardest hit areas in all of the United States during the Great Recession. Home prices have declined over 50%, significantly more than the 25% decline in the surrounding Los Angeles County, and housing starts have declined to over 90% from 2005. The Inland Empire has one of the highest unemployment rates in the US at 14.8%. This paper attempts to forecast the recovery for the Inland Empire. Employing univariate forecasts along with VAR(12) forecasts, focusing on housing starts and unemployment rates as the underlying vari
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Thomas, M. C. "Techno-economic forecasting for packaging materials." Thesis, Swansea University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.639223.

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Forecasting packaging material demand is crucial to effective future planning by capital intensive material manufacturers. Yet several considerations introduce great uncertainty over the future packaging mix. Foremost is a highly heterogeneous and dynamic end-use marketplace subject to multitudinous technological, economic, consumer and legislative change-forces. These act at all levels upon a diverse and complex supply chain that suffers data paucity and, hence, opacity of cause and effect. A wide range of future-oriented decision technologies was examined to meet these challenges. None promi
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Hackworth, J. F. "Forecasting the ownership growth of consumer durables." Thesis, Cranfield University, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.371830.

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Betz, Gregor Tetens Holm. "Prediction or prophecy? the boundaries of economic foreknowledge and their socio-political consequences /." Wiesbaden : Deutscher Universitäts-Verlag, 2006. http://site.ebrary.com/id/10231757.

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Libri sul tema "Economic forecasting"

1

Molnar, Alan T. Economic forecasting. Nova Science Publishers, 2010.

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2

Carnot, Nicolas, Vincent Koen, and Bruno Tissot. Economic Forecasting. Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815.

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Molnar, Alan T. Economic forecasting. Nova Science Publishers, 2009.

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4

W, Abelson P., and Joyeux Roselyne 1951-, eds. Economic forecasting. Allen & Unwin, 2000.

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5

Vincent, Koen, and Tissot Bruno, eds. Economic forecasting. Palgrave Macmillan, 2005.

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T, Molnar Alan, ed. Economic forecasting. Nova Science Publishers, 2009.

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7

C, Mills T., ed. Economic forecasting. Elgar, 1999.

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8

Cooper, Mary H., Helen B. Shaffer, and John M. Berry. Economic Forecasting. CQ Press, 1986. http://dx.doi.org/10.4135/cqresrre1986121900.

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Carnot, Nicolas, Vincent Koen, and Bruno Tissot. Economic Forecasting and Policy. Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230306448.

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D, Peel, and Thompson John L, eds. Economic forecasting: An introduction. Cambridge University Press, 1990.

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Capitoli di libri sul tema "Economic forecasting"

1

Carnot, Nicolas, Vincent Koen, and Bruno Tissot. "Sectoral Forecasting." In Economic Forecasting. Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_10.

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Gujarati, Damodar. "Economic Forecasting." In Econometrics. Macmillan Education UK, 2015. http://dx.doi.org/10.1007/978-1-137-37502-5_16.

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Carnot, Nicolas, Vincent Koen, and Bruno Tissot. "First Principles." In Economic Forecasting. Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_1.

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Carnot, Nicolas, Vincent Koen, and Bruno Tissot. "Accuracy." In Economic Forecasting. Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_11.

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Carnot, Nicolas, Vincent Koen, and Bruno Tissot. "Using the Forecasts." In Economic Forecasting. Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_12.

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Carnot, Nicolas, Vincent Koen, and Bruno Tissot. "Communication Challenges." In Economic Forecasting. Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_13.

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Carnot, Nicolas, Vincent Koen, and Bruno Tissot. "A Tour of the Forecasting Institutions." In Economic Forecasting. Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_14.

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Carnot, Nicolas, Vincent Koen, and Bruno Tissot. "Epilogue." In Economic Forecasting. Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_15.

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Carnot, Nicolas, Vincent Koen, and Bruno Tissot. "The Data." In Economic Forecasting. Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_2.

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Carnot, Nicolas, Vincent Koen, and Bruno Tissot. "Incoming News and Near-Term Forecasting." In Economic Forecasting. Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_3.

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Atti di convegni sul tema "Economic forecasting"

1

Mengov, George, Iliyan Nenov, Kaloyan Ganev, and Ralitsa Simeonova-Ganeva. "Neurocomputational Forecasting of Economic Shocks." In 2024 IEEE 12th International Conference on Intelligent Systems (IS). IEEE, 2024. http://dx.doi.org/10.1109/is61756.2024.10705270.

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Gupta, Arhaan, Kirana Kumar, V. Asha, and S. Naveen Kumar. "Machine Learning in Economic Forecasting: A Comprehensive Review." In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2024. https://doi.org/10.1109/ic3i61595.2024.10828960.

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Fang, Niuxiao. "Economic Growth Simulation and Forecasting Based on Neural Network." In 2024 3rd International Conference for Advancement in Technology (ICONAT). IEEE, 2024. https://doi.org/10.1109/iconat61936.2024.10775011.

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Ahammad, Md Saymon, Sadia Akter Sinthia, Mahjabeen Hossain, Md Mustak Ahmed, Md Nurul Afsar Ikram, and Nur-A.-All Asif. "Machine Learning for GDP Forecasting: Enhancing Economic Projections in Bangladesh." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725136.

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Chen, Jiaxian, Zijia He, Peng Zhang, Sixi Peng, and Zhuotong Gu. "Regional Economic Forecasting Model and Demonstration Based on Deep Residual Network." In 2024 IEEE 6th International Conference on Power, Intelligent Computing and Systems (ICPICS). IEEE, 2024. https://doi.org/10.1109/icpics62053.2024.10797168.

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Tripathi, Ankit, Arpit Tripathi, Oldřich Trenz, and Pawan Kumar Mishra. "COMPARATIVE ANALYSIS OF SELECTED TIME SERIES FORECASTING APPROACHES FOR INDIAN MARKETS." In 26th Annual International Conference Economic Competitiveness and Sustainability 2024. Mendel University in Brno, 2024. http://dx.doi.org/10.11118/978-80-7509-990-7-0167.

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Montante, Carmin, and Clemente Hernandez-Rodriguez. "Evaluation of Economic Interventions in Economic Blocks during an Economic and Sanitary Crisis." In International conference on Time Series and Forecasting. MDPI, 2024. http://dx.doi.org/10.3390/engproc2024068055.

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Shiryaev, Mihail. "FORECASTING MODELS OF ECONOMIC DYNAMICS." In 4th International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM2017. Stef92 Technology, 2017. http://dx.doi.org/10.5593/sgemsocial2017/14/s04.046.

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Waller, Ephraim Nii Kpakpo, Pamela Delali Adablah, and Quist-Aphetsi Kester. "Markov Chain: Forecasting Economic Variables." In 2019 International Conference on Computing, Computational Modelling and Applications (ICCMA). IEEE, 2019. http://dx.doi.org/10.1109/iccma.2019.00026.

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Shnaider, E., P. Hurtado, and M. Schneider. "Expert systems for economic/business forecasting." In the 1993 ACM/SIGAPP symposium. ACM Press, 1993. http://dx.doi.org/10.1145/162754.165215.

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Rapporti di organizzazioni sul tema "Economic forecasting"

1

Snowberg, Erik, Justin Wolfers, and Eric Zitzewitz. Prediction Markets for Economic Forecasting. National Bureau of Economic Research, 2012. http://dx.doi.org/10.3386/w18222.

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Higgins, Patrick, Tao Zha, and Karen Zhong. Forecasting China's Economic Growth and Inflation. National Bureau of Economic Research, 2016. http://dx.doi.org/10.3386/w22402.

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Zarnowitz, Victor. The Record and Improvability of Economic Forecasting. National Bureau of Economic Research, 1986. http://dx.doi.org/10.3386/w2099.

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Ponce-Parra, Montserrat. Improvements for the Iowa Economic Forecasting Model. Iowa State University, 2022. http://dx.doi.org/10.31274/cc-20240624-884.

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Giacomini, Raffaella. Economic theory and forecasting: lessons from the literature. Cemmap, 2014. http://dx.doi.org/10.1920/wp.cem.2014.4114.

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Nenov, Iliyan, George Mengov, Kaloyan Ganev, and Ralitsa Simeonova-Ganeva. Neurocomputational Economic Forecasting with a Handful of Data. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2021. http://dx.doi.org/10.7546/crabs.2021.10.11.

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Baluga, Anthony, and Masato Nakane. Maldives Macroeconomic Forecasting:. Asian Development Bank, 2020. http://dx.doi.org/10.22617/wps200431-2.

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This study aims to build an efficient small-scale macroeconomic forecasting tool for Maldives. Due to significant limitations in data availability, empirical economic modeling for the country can be problematic. To address data constraints and circumvent the “curse of dimensionality,” Bayesian vector autoregression estimations are utilized comprising of component-disaggregated domestic sectoral production, price, and tourism variables. Results demonstrate how this methodology is appropriate for economic modeling in Maldives. With the appropriate level of shrinkage, Bayesian vector autoregressi
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Cooper, Daniel H., Giovanni P. Olivei, and Hannah Rhodenhiser. Forecasting U.S. Economic Activity with a Small Information Set. Federal Reserve Bank of Boston, 2025. https://doi.org/10.29412/res.wp.2025.04.

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Dolmas, Sheila, Evan F. Koenig, and Jeremy M. Piger. The Use and Abuse of 'Real-Time' Data in Economic Forecasting. Federal Reserve Bank of St. Louis, 2001. http://dx.doi.org/10.20955/wp.2001.015.

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Galeano-Ramírez, Franky Juliano, Nicolás Martínez-Cortés, Carlos D. Rojas-Martínez, and Margaret Guerrero. Nowcasting Colombian Economic Activity: DFM and Factor-MIDAS approaches. Banco de la República, 2021. http://dx.doi.org/10.32468/be.1168.

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Economic policy decision-making requires constantly assessing the state of economic activity. However, this is not an easy task: official figures have significant lags, and the timely information is usually partial and has different frequencies. This paper applies two types of short-term forecasting methodologies (Factor-MIDAS and DFM) for Colombian economic activity involving information with mixed frequencies. We present a heuristic process to select relevant variables, and we evaluate the proposed models' fits by comparing them with traditional forecasting methodologies. Overall, DFM and Fa
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