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Artykuły w czasopismach na temat "Macroeconomics – Forecasting"
Chatziantoniou, Ioannis, Stavros Degiannakis, Bruno Eeckels i George Filis. "Forecasting tourist arrivals using origin country macroeconomics". Applied Economics 48, nr 27 (29.12.2015): 2571–85. http://dx.doi.org/10.1080/00036846.2015.1125434.
Pełny tekst źródłaMaldonado, Isabel, i Carlos Pinho. "Yield curve dynamics with macroeconomic factors in Iberian economies". Global Journal of Business, Economics and Management: Current Issues 10, nr 3 (26.11.2020): 193–203. http://dx.doi.org/10.18844/gjbem.v10i3.4691.
Pełny tekst źródłaDiebold, F. X., i Kenneth D. West. "Forecasting and empirical methods in finance and macroeconomics". Journal of Econometrics 105, nr 1 (listopad 2001): 1–3. http://dx.doi.org/10.1016/s0304-4076(01)00067-7.
Pełny tekst źródłaLi, Cao. "Macroeconomic Short-Term High-Precision Combined Forecasting Algorithm Based on Grey Model". Security and Communication Networks 2021 (16.09.2021): 1–9. http://dx.doi.org/10.1155/2021/7026064.
Pełny tekst źródłaKurovskiy, Gleb. "Using Textual Information to Predict In Macroeconomics". Moscow University Economics Bulletin 2019, nr 6 (30.12.2019): 39–58. http://dx.doi.org/10.38050/01300105201965.
Pełny tekst źródłaSyamsudin, Moch. "Pengujian Kembali Volatilitas Kebijakan Trilemma Terhadap Variabel Makroekonomi di Indonesia". Jurnal Ekonomi Akuntansi dan Manajemen 20, nr 1 (8.04.2021): 1. http://dx.doi.org/10.19184/jeam.v20i1.18880.
Pełny tekst źródłaAhmadi, Ahmadi, i R. Adisetiawan. "Multivariate Time Series in Macroeconomics". Eksis: Jurnal Ilmiah Ekonomi dan Bisnis 11, nr 2 (23.11.2020): 151. http://dx.doi.org/10.33087/eksis.v11i2.209.
Pełny tekst źródłaFischer, Charles C. "On the Design and Use of Forecasting Experiments in Teaching Macroeconomics". Simulation & Gaming 22, nr 1 (marzec 1991): 75–82. http://dx.doi.org/10.1177/1046878191221006.
Pełny tekst źródłaBritton, Andrew. "Seasonal Patterns in the British Economy". National Institute Economic Review 117 (sierpień 1986): 33–42. http://dx.doi.org/10.1177/002795018611700105.
Pełny tekst źródłaDiebold, Francis X., i Kenneth D. West. "Symposium on Forecasting and Empirical Methods in Macroeconomics and Finance: Editors' Introduction". International Economic Review 39, nr 4 (listopad 1998): 811. http://dx.doi.org/10.2307/2527339.
Pełny tekst źródłaRozprawy doktorskie na temat "Macroeconomics – Forecasting"
Heidari, Hassan Economics Australian School of Business UNSW. "Essays on macoroeconomics and macroeconomic forecasting". Awarded by:University of New South Wales. School of Economics, 2006. http://handle.unsw.edu.au/1959.4/22800.
Pełny tekst źródłaLiu, Dandan. "Essays on macroeconomics and forecasting". Texas A&M University, 2005. http://hdl.handle.net/1969.1/4271.
Pełny tekst źródłaDe, Antonio Liedo David. "Structural models for macroeconomics and forecasting". Doctoral thesis, Universite Libre de Bruxelles, 2010. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210142.
Pełny tekst źródłacentral debates in empirical macroeconomic modeling.
Chapter 1, entitled “A Model for Real-Time Data Assessment with an Application to GDP Growth Rates”, provides a model for the data
revisions of macroeconomic variables that distinguishes between rational expectation updates and noise corrections. Thus, the model encompasses the two polar views regarding the publication process of statistical agencies: noise versus news. Most of the studies previous studies that analyze data revisions are based
on the classical noise and news regression approach introduced by Mankiew, Runkle and Shapiro (1984). The problem is that the statistical tests available do not formulate both extreme hypotheses as collectively exhaustive, as recognized by Aruoba (2008). That is, it would be possible to reject or accept both of them simultaneously. In turn, the model for the
DPP presented here allows for the simultaneous presence of both noise and news. While the “regression approach” followed by Faust et al. (2005), along the lines of Mankiew et al. (1984), identifies noise in the preliminary
figures, it is not possible for them to quantify it, as done by our model.
The second and third chapters acknowledge the possibility that macroeconomic data is measured with errors, but the approach followed to model the missmeasurement is extremely stylized and does not capture the complexity of the revision process that we describe in the first chapter.
Chapter 2, entitled “Revisiting the Success of the RBC model”, proposes the use of dynamic factor models as an alternative to the VAR based tools for the empirical validation of dynamic stochastic general equilibrium (DSGE) theories. Along the lines of Giannone et al. (2006), we use the state-space parameterisation of the factor models proposed by Forni et al. (2007) as a competitive benchmark that is able to capture weak statistical restrictions that DSGE models impose on the data. Our empirical illustration compares the out-of-sample forecasting performance of a simple RBC model augmented with a serially correlated noise component against several specifications belonging to classes of dynamic factor and VAR models. Although the performance of the RBC model is comparable
to that of the reduced form models, a formal test of predictive accuracy reveals that the weak restrictions are more useful at forecasting than the strong behavioral assumptions imposed by the microfoundations in the model economy.
The last chapter, “What are Shocks Capturing in DSGE modeling”, contributes to current debates on the use and interpretation of larger DSGE
models. Recent tendency in academic work and at central banks is to develop and estimate large DSGE models for policy analysis and forecasting. These models typically have many shocks (e.g. Smets and Wouters, 2003 and Adolfson, Laseen, Linde and Villani, 2005). On the other hand, empirical studies point out that few large shocks are sufficient to capture the covariance structure of macro data (Giannone, Reichlin and
Sala, 2005, Uhlig, 2004). In this Chapter, we propose to reconcile both views by considering an alternative DSGE estimation approach which
models explicitly the statistical agency along the lines of Sargent (1989). This enables us to distinguish whether the exogenous shocks in DSGE
modeling are structural or instead serve the purpose of fitting the data in presence of misspecification and measurement problems. When applied to the original Smets and Wouters (2007) model, we find that the explanatory power of the structural shocks decreases at high frequencies. This allows us to back out a smoother measure of the natural output gap than that
resulting from the original specification.
Doctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished
Schwarzmüller, Tim [Verfasser]. "Essays in Macroeconomics and Forecasting / Tim Schwarzmüller". Kiel : Universitätsbibliothek Kiel, 2016. http://d-nb.info/1102204021/34.
Pełny tekst źródłaBrinca, Pedro Soares. "Essays in Quantitative Macroeconomics". Doctoral thesis, Stockholms universitet, Nationalekonomiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-92861.
Pełny tekst źródłaGalimberti, Jaqueson Kingeski. "Adaptive learning for applied macroeconomics". Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/adaptive-learning-for-applied-macroeconomics(cde517d7-d552-4a53-a442-c584262c3a8f).html.
Pełny tekst źródłaArora, Siddharth. "Time series forecasting with applications in macroeconomics and energy". Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:c763b735-e4fa-4466-9c1f-c3f6daf04a67.
Pełny tekst źródłaWard, Felix [Verfasser]. "Essays in International Macroeconomics and Financial Crisis Forecasting / Felix Ward". Bonn : Universitäts- und Landesbibliothek Bonn, 2018. http://d-nb.info/1167856899/34.
Pełny tekst źródłaXue, Jiangbo. "A structural forecasting model for the Chinese macroeconomy /". View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?ECON%202009%20XUE.
Pełny tekst źródłaRicci, Lorenzo. "Essays on tail risk in macroeconomics and finance: measurement and forecasting". Doctoral thesis, Universite Libre de Bruxelles, 2017. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/242122.
Pełny tekst źródłaDoctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished
Książki na temat "Macroeconomics – Forecasting"
Inc, NetLibrary, red. Macroeconomic forecasting: A sociological appraisal. London: Routledge, 2002.
Znajdź pełny tekst źródłaChipika, Jesimen. Macroeconomic modeling and forecasting manual. Harare, Zimbabwe: Macroeconomic and Financial Management Institute of Eastern and Southern Africa, 2012.
Znajdź pełny tekst źródłaEconomic fluctuations and forecasting. New York: HarperCollins College Publishers, 1996.
Znajdź pełny tekst źródłaSiviero, Stefano. Macroeconomic forecasting: Debunking a few old wives' tales. [Roma]: Banca d'Italia, 2001.
Znajdź pełny tekst źródłaMacro-economic forecasting: A sociological appraisal. London: Routledge, 1999.
Znajdź pełny tekst źródłaBoivin, Jean. Are more data always better for factor analysis? Cambridge, Mass: National Bureau of Economic Research, 2003.
Znajdź pełny tekst źródłaVlatko, Ćurković, Škegro Borislav, Ekonomski institut Zagreb, Samoupravna interesna zajednica znanosti SR Hrvatske., Republički zavod za društveno planiranje SR Hrvatske. i Znanstvene osnove dugoročnog društveno-ekonomskog razvoja Hrvatske., red. Globalna analiza i projekcija dinamike i strukture razvoja. Zagreb: Samoupravna interesna zajednica znanosti Hrvatske, 1990.
Znajdź pełny tekst źródłaLamont, Owen A. Macroeconomic forecasts and microeconomic forecasters. Cambridge, MA: National Bureau of Economic Research, 1995.
Znajdź pełny tekst źródłaBackus, David. Cracking the conundrum. Cambridge, Mass: National Bureau of Economic Research, 2007.
Znajdź pełny tekst źródłaBackus, David. Cracking the conundrum. Cambridge, MA: National Bureau of Economic Research, 2007.
Znajdź pełny tekst źródłaCzęści książek na temat "Macroeconomics – Forecasting"
Holden, K. "Macroeconomic Forecasting". W Current Issues in Macroeconomics, 163–81. London: Palgrave Macmillan UK, 1989. http://dx.doi.org/10.1007/978-1-349-20286-7_8.
Pełny tekst źródłaWard, Benjamin. "Macroeconomics: Theorem-Seeking, Forecasting Failure". W Dionysian Economics, 53–65. New York: Palgrave Macmillan US, 2016. http://dx.doi.org/10.1057/9781137597366_7.
Pełny tekst źródłaGandolfo, Giancarlo, Pier Carlo Padoan i Giuseppe de Arcangelis. "The Theory of Exchange Rate Determination, and Exchange Rate Forecasting". W Open-Economy Macroeconomics, 332–52. London: Palgrave Macmillan UK, 1993. http://dx.doi.org/10.1007/978-1-349-12884-6_18.
Pełny tekst źródłaOzaki, Tohru, i Valerie H. Ozaki. "Statistical Identification of Nonlinear Dynamics in Macroeconomics Using Nonlinear Time Series Models". W Statistical Analysis and Forecasting of Economic Structural Change, 345–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-662-02571-0_22.
Pełny tekst źródłaBuckmann, Marcus, Andreas Joseph i Helena Robertson. "Opening the Black Box: Machine Learning Interpretability and Inference Tools with an Application to Economic Forecasting". W Data Science for Economics and Finance, 43–63. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66891-4_3.
Pełny tekst źródłaCarnot, Nicolas, Vincent Koen i Bruno Tissot. "Macroeconomic Models". W Economic Forecasting, 133–54. London: Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230005815_6.
Pełny tekst źródłaWatson, Mark W. "Macroeconomic Forecasting". W The New Palgrave Dictionary of Economics, 1–3. London: Palgrave Macmillan UK, 2008. http://dx.doi.org/10.1057/978-1-349-95121-5_2434-1.
Pełny tekst źródłaWatson, Mark W. "Macroeconomic Forecasting". W The New Palgrave Dictionary of Economics, 8094–96. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_2434.
Pełny tekst źródłaCohen, Gerald D. "Macroeconomic Theory and Forecasting". W The Palgrave Handbook of Government Budget Forecasting, 11–36. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18195-6_2.
Pełny tekst źródłaBassetti, Federico, Roberto Casarin i Francesco Ravazzolo. "Density Forecasting". W Macroeconomic Forecasting in the Era of Big Data, 465–94. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31150-6_15.
Pełny tekst źródłaStreszczenia konferencji na temat "Macroeconomics – Forecasting"
Nguyen, Hien T., i Duc Trung Nguyen. "Transfer Learning for Macroeconomic Forecasting". W 2020 7th NAFOSTED Conference on Information and Computer Science (NICS). IEEE, 2020. http://dx.doi.org/10.1109/nics51282.2020.9335848.
Pełny tekst źródłaCook, Thomas R., i Aaron Smalter Hall. "Macroeconomic Indicator Forecasting with Deep Neural Networks". W CARMA 2018 - 2nd International Conference on Advanced Research Methods and Analytics. Valencia: Universitat Politècnica València, 2018. http://dx.doi.org/10.4995/carma2018.2018.8571.
Pełny tekst źródłaPlevokaitė, Jurgita, i Raimonda Martinkutė-Kaulienė. "Estimation of Investment Perspectives in the Baltic Stock Market". W Contemporary Issues in Business, Management and Education. VGTU Technika, 2015. http://dx.doi.org/10.3846/cibme.2015.01.
Pełny tekst źródłaYu-Ge Xu, Fei Luo i Zhi-Ming Chen. "Macroeconomic forecasting algorithm based on novel adaptive neural network". W 2008 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2008. http://dx.doi.org/10.1109/icwapr.2008.4635784.
Pełny tekst źródłaKaraganis, Anastasios, i Vasiliki Vlachostergiou. "Forecasting the Greek office price index using macroeconomic leading indicators". W 24th Annual European Real Estate Society Conference. European Real Estate Society, 2017. http://dx.doi.org/10.15396/eres2017_311.
Pełny tekst źródłaTurner, David. "The use of models in macroeconomic forecasting at the OECD". W Conference on Global Economic Modeling. WORLD SCIENTIFIC, 2018. http://dx.doi.org/10.1142/9789813220447_0003.
Pełny tekst źródłaMehrotra, Anupam, i Alka Munjal. "Leveraging Technology in Central Banking: Macroeconomic Forecasting & Managing Volatility". W 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). IEEE, 2021. http://dx.doi.org/10.1109/iccike51210.2021.9410771.
Pełny tekst źródłaWaduge, Nisal, i Upeksha Ganegoda. "Forecasting Stock Price of a Company Considering Macroeconomic Effect from News Events". W 2018 3rd International Conference on Information Technology Research (ICITR). IEEE, 2018. http://dx.doi.org/10.1109/icitr.2018.8736133.
Pełny tekst źródłaTarasov, A. N. "ON THE COMPOSITION OF CONCEPTS IN COGNITIVE MODELS OF RURAL DEVELOPMENT". W STATE AND DEVELOPMENT PROSPECTS OF AGRIBUSINESS Volume 2. DSTU-Print, 2020. http://dx.doi.org/10.23947/interagro.2020.2.200-202.
Pełny tekst źródłaAbounoori, Esmaiel, i Afsaneh Ghasemi Tazehabadi. "Forecasting Stock Price Using Macroeconomic Variables: A Hybrid ARDL, ARIMA and Artificial Neural Network". W 2009 International Conference on Information and Financial Engineering, ICIFE. IEEE, 2009. http://dx.doi.org/10.1109/icife.2009.23.
Pełny tekst źródłaRaporty organizacyjne na temat "Macroeconomics – Forecasting"
Baluga, Anthony, i Masato Nakane. Maldives Macroeconomic Forecasting:. Asian Development Bank, grudzień 2020. http://dx.doi.org/10.22617/wps200431-2.
Pełny tekst źródłaDiebold, Francis. The Past, Present, and Future of Macroeconomic Forecasting. Cambridge, MA: National Bureau of Economic Research, listopad 1997. http://dx.doi.org/10.3386/w6290.
Pełny tekst źródłaOwyang, Michael T., i Ana B. Galvão. Forecasting Low Frequency Macroeconomic Events with High Frequency Data. Federal Reserve Bank of St. Louis, 2020. http://dx.doi.org/10.20955/wp.2020.028.
Pełny tekst źródłaNg, Serena, i Jonathan Wright. Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling. Cambridge, MA: National Bureau of Economic Research, wrzesień 2013. http://dx.doi.org/10.3386/w19469.
Pełny tekst źródłaStock, James, i Mark Watson. A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series. Cambridge, MA: National Bureau of Economic Research, czerwiec 1998. http://dx.doi.org/10.3386/w6607.
Pełny tekst źródłaMonetary Policy Report - January 2021. Banco de la República de Colombia, marzec 2021. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr1.-2021.
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