Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2018

• Gulay Emrah, 2018, "Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition," Scientific Annals of Economics and Business, Sciendo, volume 65, issue 2, pages 159-169, June, DOI: 10.2478/saeb-2018-0010.
• Ginanneschi Marco & Piu Pietro, 2018, "The Role of e-Commerce in the Success of Low-cost Carriers," Scientific Annals of Economics and Business, Sciendo, volume 65, issue 4, pages 407-425, December, DOI: 10.2478/saeb-2018-0029.
• Husáková Martina, 2018, "Use of the Multi-Agent Paradigm in Sustainable Tourism," Czech Journal of Tourism, Sciendo, volume 7, issue 1, pages 5-24, June, DOI: 10.1515/cjot-2018-0001.
• Zekić-Sušac Marijana & Scitovski Rudolf & Has Adela, 2018, "Cluster analysis and artificial neural networks in predicting energy efficiency of public buildings as a cost-saving approach," Croatian Review of Economic, Business and Social Statistics, Sciendo, volume 4, issue 2, pages 57-66, November, DOI: 10.2478/crebss-2018-0013.
• Siekelova Anna & Kliestik Tomas & Adamko Peter, 2018, "Predictive Ability of Chosen Bankruptcy Models: A Case Study of Slovak Republic," Economics and Culture, Sciendo, volume 15, issue 1, pages 105-114, June, DOI: 10.2478/jec-2018-0012.
• Zawada Marcin & Szajt Marek, 2018, "Application of Statistical and Econometric Tools in The Analysis of Air Pollution Level on The Example of Czestochowa," Folia Oeconomica Stetinensia, Sciendo, volume 18, issue 2, pages 144-158, December, DOI: 10.2478/foli-2018-0024.
• Kaczmarczyk Paweł, 2018, "Neural Network Application to Support Regression Model in Forecasting Single-Sectional Demand for Telecommunications Services," Folia Oeconomica Stetinensia, Sciendo, volume 18, issue 2, pages 159-177, December, DOI: 10.2478/foli-2018-0025.
• Simionescu Mihaela, 2018, "The Impact of European Economic Integration on Migration in the European Union," HOLISTICA – Journal of Business and Public Administration, Sciendo, volume 9, issue 1, pages 23-34, May, DOI: 10.1515/hjbpa-2018-0002.
• Ene Andreea Bianca, 2018, "Distance Education in Romanian Higher Education," HOLISTICA – Journal of Business and Public Administration, Sciendo, volume 9, issue 1, pages 65-70, May, DOI: 10.1515/hjbpa-2018-0005.
• Devjak Srečko, 2018, "Modeling of Cash Flows from Nonperforming Loans in a Commercial Bank," Naše gospodarstvo/Our economy, Sciendo, volume 64, issue 4, pages 3-9, December, DOI: 10.2478/ngoe-2018-0018.
• Weigand Roland & Wanger Susanne & Zapf Ines, 2018, "Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany," Journal of Official Statistics, Sciendo, volume 34, issue 1, pages 265-301, March, DOI: 10.1515/jos-2018-0012.
• Simionescu Mihaela, 2018, "What Drives Economic Growth in Some CEE Countries?," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, volume 28, issue 1, pages 46-56, March, DOI: 10.2478/sues-2018-0004.
• Florea Nicoleta Valentina & Tănăsescu Dorina Antoneta & Duică Anişoara, 2018, "Enabling Customer-Centricity and Relationship Management using Net Promoter Score," Valahian Journal of Economic Studies, Sciendo, volume 9, issue 2, pages 115-126, November, DOI: 10.2478/vjes-2018-0023.
• Shehu U.R. Aliyu & Nafiu B. Abdulsalam & Sani Bawa, 2018, "Testing For Financial Spillovers In Calm And Turbulent Periods," West African Journal of Monetary and Economic Integration, West African Monetary Institute, volume 18, issue 2, pages 1-27, December.
• Martin Feldkircher & Florian Huber & Gregor Kastner, 2018, "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Papers, Vienna University of Economics and Business, Department of Economics, number wuwp260, Jan.
• Feldkircher, Martin & Kastner, Gregor & Huber, Florian, 2018, "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Department of Economics Working Paper Series, WU Vienna University of Economics and Business, number 260, Jan.
• Joseph P. Byrne & Dimitris Korobilis & Pinho J. Ribeiro, 2018, "On The Sources Of Uncertainty In Exchange Rate Predictability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, volume 59, issue 1, pages 329-357, February, DOI: 10.1111/iere.12271.
• John M. Maheu & Yong Song, 2018, "An efficient Bayesian approach to multiple structural change in multivariate time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 33, issue 2, pages 251-270, March, DOI: 10.1002/jae.2606.
• Carlos Díaz, 2018, "Extracting information shocks from the Bank of England inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., volume 37, issue 3, pages 316-326, April, DOI: 10.1002/for.2501.
• Ricardo Crisóstomo & Lorena Couso, 2018, "Financial density forecasts: A comprehensive comparison of risk‐neutral and historical schemes," Journal of Forecasting, John Wiley & Sons, Ltd., volume 37, issue 5, pages 589-603, August, DOI: 10.1002/for.2521.
• Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018, "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., volume 37, issue 7, pages 705-719, November, DOI: 10.1002/for.2539.
• Marek Jarociński & Michele Lenza, 2018, "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, volume 50, issue 6, pages 1189-1224, September, DOI: 10.1111/jmcb.12496.
• Bartosz Uniejewski & Rafal Weron, 2018, "Efficient forecasting of electricity spot prices with expert and LASSO models," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/02, Jun.
• Katarzyna Hubicka & Grzegorz Marcjasz & Rafal Weron, 2018, "A note on averaging day-ahead electricity price forecasts across calibration windows," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/03, Jul.
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2018, "Probabilistic electricity price forecasting with NARX networks: Combine point or probabilistic forecasts?," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/05, Jul.
• Grzegorz Marcjasz & Tomasz Serafin & Rafal Weron, 2018, "Selection of calibration windows for day-ahead electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/06, Aug.
• Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2018, "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/07, Aug.
• Rafal Weron & Florian Ziel, 2018, "Electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/18/08, Sep.
• Benchimol, Jonathan & Bounader, Lahcen, 2018, "Optimal monetary policy under bounded rationality," Bank of Finland Research Discussion Papers, Bank of Finland, number 9/2018.
• Granziera, Eleonora & Sekhposyan, Tatevik, 2018, "Predicting relative forecasting performance: An empirical investigation," Bank of Finland Research Discussion Papers, Bank of Finland, number 23/2018.
• Foroni, Claudia & Marcellino, Massimiliano & Stevanović, Dalibor, 2018, "Mixed frequency models with MA components," Discussion Papers, Deutsche Bundesbank, number 02/2018.
• Breitung, Jörg & Knüppel, Malte, 2018, "How far can we forecast? Statistical tests of the predictive content," Discussion Papers, Deutsche Bundesbank, number 07/2018.
• Kurz-Kim, Jeong-Ryeol, 2018, "A note on the predictive power of survey data in nowcasting euro area GDP," Discussion Papers, Deutsche Bundesbank, number 10/2018.
• Gerke, Rafael & Giesen, Sebastian & Kienzler, Daniel, 2018, "Uncertainty about QE effects when an interest rate peg is anticipated," Discussion Papers, Deutsche Bundesbank, number 12/2018.
• Pinkwart, Nicolas, 2018, "Short-term forecasting economic activity in Germany: A supply and demand side system of bridge equations," Discussion Papers, Deutsche Bundesbank, number 36/2018.
• Götz, Thomas B. & Hauzenberger, Klemens, 2018, "Large mixed-frequency VARs with a parsimonious time-varying parameter structure," Discussion Papers, Deutsche Bundesbank, number 40/2018.
• Ollech, Daniel, 2018, "Seasonal adjustment of daily time series," Discussion Papers, Deutsche Bundesbank, number 41/2018.
• Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018, "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers, Deutsche Bundesbank, number 48/2018.
• Knüppel, Malte & Schultefrankenfeld, Guido, 2018, "Assessing the uncertainty in central banks' inflation outlooks," Discussion Papers, Deutsche Bundesbank, number 56/2018.
• Jang, Tae-Seok & Sacht, Stephen, 2018, "Forecast heuristics, consumer expectations, and new-Keynesian macroeconomics: A horse race," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2018-09.
• Jang, Tae-Seok & Sacht, Stephen, 2018, "Macroeconomic dynamics under bounded rationality: On the impact of consumers' forecast heuristics," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2018-10.
• Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018, "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2018-11.
• Kašćelan, Ljiljana & Lazović, Vujica & Đuričković, Tamara & Rondović Biljana, 2018, "Analysis of the Diffusion of E-services in Public Sector Using the Decision Tree Method," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2018), Split, Croatia, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Split, Croatia, 6-8 September 2018".
• Opiła, Janusz, 2018, "Visualization in a Knowledge Transfer Process," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2018), Split, Croatia, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Split, Croatia, 6-8 September 2018".
• Jackson, Emerson Abraham & Sillah, Abdulai & Tamuke, Edmund, 2018, "Modelling Monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins Methodology," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 7, issue 1, pages 51-56, DOI: 10.18483/ijSci.1479.
• Heinisch, Katja & Lindner, Axel, 2018, "For how long do IMF forecasts of world economic growth stay up-to-date?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, issue Latest ar, pages 1-6, DOI: 10.1080/13504851.2018.1459035.
• Kholodilin, Konstantin A. & Michelsen, Claus & Ulbricht, Dirk, 2018, "Speculative price bubbles in urban housing markets," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 55, issue 4, pages 1957-1983.
• Dockery, Everton & Efentakis, Miltiadis & Al-Faryan, Mamdouh Abdulaziz Saleh, 2018, "Are range based models good enough? Evidence from seven stock markets," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 8, issue 2, pages 7-40, DOI: 10.22495/rgcv8i2p1.
• Havranek, Tomas & Zeynalov, Ayaz, 2018, "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 187420.
• Jahn, Malte, 2018, "Artificial neural network regression models: Predicting GDP growth," HWWI Research Papers, Hamburg Institute of International Economics (HWWI), number 185.
• Coupé, Tom, 2018, "Replicating "Predicting the present with Google trends" by Hyunyoung Choi and Hal Varian (The Economic Record, 2012)," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), volume 12, pages 1-8, DOI: 10.5018/economics-ejournal.ja.2018-.
• Chernozhukov, Victor & Härdle, Wolfgang Karl & Huang, Chen & Wang, Weining, 2018, "LASSO-Driven Inference in Time and Space," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2018-021.
• Chen, Ying & Han, Qian & Niu, Linlin, 2018, "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2018-046.
• Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2018, "Cryptocurrencies, Metcalfe's law and LPPL models," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2018-056.
• Holtemöller, Oliver & Schult, Christoph, 2018, "Expectation formation, financial frictions, and forecasting performance of dynamic stochastic general equilibrium models," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 15/2018.
• Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Wieschemeyer, Matthias & Zeddies, Götz, 2018, "Mittelfristprojektion des IWH: Wirtschaftsentwicklung und Öffentliche Finanzen 2018 bis 2025," Konjunktur aktuell, Halle Institute for Economic Research (IWH), volume 6, issue 4, pages 105-114.
• Duarte, Pablo & Süßmuth, Bernd, 2018, "Implementing an approximate dynamic factor model to nowcast GDP using sensitivity analysis," Working Papers, University of Leipzig, Faculty of Economics and Management Science, number 152.
• Wei-Bin Zhang, 2018, "A Growth Theory Based on Walrasian General Equilibrium, Solow-Uzawa Growth, and Heckscher-Ohlin Trade Theories," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 16, issue 3-B, pages 452-464.
• Berislav Žmuk & Ksenija Dumièiæ & Irena Paliæ, 2018, "Forecasting Labour Productivity in the European Union Member States: Is Labour Productivity Changing as Expected?," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 16, issue 3-B, pages 504-523.

2017

• Mikael Collan & Jyrki Savolainen & Pasi Luukka, 2017, "Investigating the effect of price process selection on the value of a metal mining asset portfolio," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, volume 30, issue 2, pages 107-115, July, DOI: 10.1007/s13563-017-0102-2.
• Iñaki Bildosola & Pilar Gonzalez & Paz Moral, 2017, "An approach for modelling and forecasting research activity related to an emerging technology," Scientometrics, Springer;Akadémiai Kiadó, volume 112, issue 1, pages 557-572, July, DOI: 10.1007/s11192-017-2381-3.
• Wali Ullah, 2017, "Term structure forecasting in affine framework with time-varying volatility," Statistical Methods & Applications, Springer;Società Italiana di Statistica, volume 26, issue 3, pages 453-483, August, DOI: 10.1007/s10260-017-0378-y.
• Bogdan Batrinca & Christian W. Hesse & Philip C. Treleaven, 2017, "Developing a Volume Forecasting Model," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 7, issue 1, pages 1-1.
• Bing Li, 2017, "Network Evolution of the Chinese Stock Market: A Study based on the CSI 300 Index," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 7, issue 3, pages 1-5.
• Petrus Strydom, 2017, "Macro economic cycle effect on mortgage and personal loan default rates," Journal of Applied Finance & Banking, SCIENPRESS Ltd, volume 7, issue 6, pages 1-1.
• Brian Stacey, 2017, "A Standardized Treatment of Binary Similarity Measures with an Introduction to k-Vector Percentage Normalized Similarity," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, volume 6, issue 1, pages 1-3.
• Brownlees, Christian & Engle, Robert F., 2017, "SRISK: a conditional capital shortfall measure of systemic risk," ESRB Working Paper Series, European Systemic Risk Board, number 37, Mar.
• Andrea BUCCI, 2017, "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, volume 8, issue 2, pages 94-138.
• Anthony Mouraud, 2017, "Innovative time series forecasting: auto regressive moving average vs deep networks," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, volume 4, issue 3, pages 282-293, March, DOI: 10.9770/jesi.2017.4.3S(4).
• Rahul Deb & Mallesh M. Pai & Maher Said, 2017, "Evaluating Strategic Forecasters," Working Papers, New York University, Leonard N. Stern School of Business, Department of Economics, number 17-02.
• Christopher G. Gibbs & Andrey L. Vasnev, 2017, "Conditionally Optimal Weights and Forward-Looking Approaches to Combining Forecasts," Discussion Papers, School of Economics, The University of New South Wales, number 2017-10, Feb.
• Rachida Ouysse, 2017, "Constrained principal components estimation of large approximate factor models," Discussion Papers, School of Economics, The University of New South Wales, number 2017-12, Apr.
• R. Lehmann & K. Wohlrabe, 2017, "Experts, firms, consumers or even hard data? Forecasting employment in Germany," Applied Economics Letters, Taylor & Francis Journals, volume 24, issue 4, pages 279-283, February, DOI: 10.1080/13504851.2016.1184219.
• Jari Hännikäinen, 2017, "The shadow rate as a predictor of real activity and inflation: evidence from a data-rich environment," Applied Economics Letters, Taylor & Francis Journals, volume 24, issue 8, pages 527-535, May, DOI: 10.1080/13504851.2016.1208347.
• Colin O’hare & Youwei Li, 2017, "Modelling mortality: are we heading in the right direction?," Applied Economics, Taylor & Francis Journals, volume 49, issue 2, pages 170-187, January, DOI: 10.1080/00036846.2016.1192278.
• Stavros Degiannakis & George Filis & George Palaiodimos, 2017, "Investments and uncertainty revisited: the case of the US economy," Applied Economics, Taylor & Francis Journals, volume 49, issue 45, pages 4521-4529, September, DOI: 10.1080/00036846.2017.1284995.
• Mardi Dungey & Jan P.A.M. Jacobs & Jing Tian, 2017, "Forecasting output gaps in the G-7 countries: the role of correlated innovations and structural breaks," Applied Economics, Taylor & Francis Journals, volume 49, issue 45, pages 4554-4566, September, DOI: 10.1080/00036846.2017.1284998.
• Philip Hans Franses & Rianne Legerstee & Richard Paap, 2017, "Estimating loss functions of experts," Applied Economics, Taylor & Francis Journals, volume 49, issue 4, pages 386-396, January, DOI: 10.1080/00036846.2016.1197373.
• Colin O’hare & Youwei Li, 2017, "Models of mortality rates – analysing the residuals," Applied Economics, Taylor & Francis Journals, volume 49, issue 52, pages 5309-5323, November, DOI: 10.1080/00036846.2017.1305092.
• Francis X. Diebold & Minchul Shin, 2017, "Assessing point forecast accuracy by stochastic error distance," Econometric Reviews, Taylor & Francis Journals, volume 36, issue 6-9, pages 588-598, October, DOI: 10.1080/07474938.2017.1307247.
• Manabu Asai & Michael McAleer, 2017, "The impact of jumps and leverage in forecasting covolatility," Econometric Reviews, Taylor & Francis Journals, volume 36, issue 6-9, pages 638-650, October, DOI: 10.1080/07474938.2017.1307326.
• Sotirios Bersimis & Stavros Degiannakis & Dimitrios Georgakellos, 2017, "Real-time monitoring of carbon monoxide using value-at-risk measure and control charting," Journal of Applied Statistics, Taylor & Francis Journals, volume 44, issue 1, pages 89-108, January, DOI: 10.1080/02664763.2016.1161738.
• Daniele Bianchi & Massimo Guidolin & Francesco Ravazzolo, 2017, "Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 1, pages 110-129, January, DOI: 10.1080/07350015.2015.1061436.
• Joshua C. C. Chan, 2017, "The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 1, pages 17-28, January, DOI: 10.1080/07350015.2015.1052459.
• Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017, "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 2, pages 162-182, April, DOI: 10.1080/07350015.2015.1123636.
• Davide Pettenuzzo & Allan Timmermann, 2017, "Forecasting Macroeconomic Variables Under Model Instability," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 2, pages 183-201, April, DOI: 10.1080/07350015.2015.1051183.
• Michael P. Clements, 2017, "Assessing Macro Uncertainty in Real-Time When Data Are Subject To Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 3, pages 420-433, July, DOI: 10.1080/07350015.2015.1081596.
• Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017, "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 35, issue 3, pages 470-485, July, DOI: 10.1080/07350015.2015.1087856.
• Christian Menden & Christian R. Proaño, 2017, "Dissecting the financial cycle with dynamic factor models," Quantitative Finance, Taylor & Francis Journals, volume 17, issue 12, pages 1965-1994, December, DOI: 10.1080/14697688.2017.1357971.
• G. Demos & D. Sornette, 2017, "Birth or burst of financial bubbles: which one is easier to diagnose?," Quantitative Finance, Taylor & Francis Journals, volume 17, issue 5, pages 657-675, May, DOI: 10.1080/14697688.2016.1231417.
• V. Filimonov & G. Demos & D. Sornette, 2017, "Modified profile likelihood inference and interval forecast of the burst of financial bubbles," Quantitative Finance, Taylor & Francis Journals, volume 17, issue 8, pages 1167-1186, August, DOI: 10.1080/14697688.2016.1276298.
• Goodwin, Thomas & Tian, Jing, 2017, "A state space approach to evaluate multi-horizon forecasts," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2017-15.
• Kurmas Akdogan, 2017, "Mean-Reversion in Unprocessed Food Prices," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 1703.
• Ferhat Camlica & Didem Gunes & Etkin Ozen, 2017, "A Financial Connectedness Analysis for Turkey," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 1719.
• Manabu Asai & Michael McAleer, 2017, "Forecasting the Volatility of Nikkei 225 Futures," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 17-017/III, Jan.
• Tom Boot & Andreas Pick, 2017, "A near optimal test for structural breaks when forecasting under square error loss," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 17-039/III, Apr.
• León, C. & Moreno, José Fernando & Cely, Jorge, 2017, "Whose Balance Sheet is this? Neural Networks for Banks' Pattern Recognition," Discussion Paper, Tilburg University, Center for Economic Research, number 2017-009.
• León, C. & Moreno, José Fernando & Cely, Jorge, 2017, "Whose Balance Sheet is this? Neural Networks for Banks' Pattern Recognition," Other publications TiSEM, Tilburg University, School of Economics and Management, number 75d8648e-9855-4c5c-9aa9-0.
• Steven Lehrer & Tian Xie, 2017, "Box Office Buzz: Does Social Media Data Steal the Show from Model Uncertainty When Forecasting for Hollywood?," The Review of Economics and Statistics, MIT Press, volume 99, issue 5, pages 749-755, December.
• Gianni Amisano & John Geweke, 2017, "Prediction Using Several Macroeconomic Models," The Review of Economics and Statistics, MIT Press, volume 99, issue 5, pages 912-925, December.
• Manabu Asai & Michael McAleer, 2017, "Forecasting the volatility of Nikkei 225 futures," Documentos de Trabajo del ICAE, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, number 2017-07, Jan.
• Roberta Cardani & Alessia Paccagnini & Stelios D. Bekiros, 2017, "The Effectiveness of Forward Guidance in an Estimated DSGE Model for the Euro Area: the Role of Expectations," Working Papers, School of Economics, University College Dublin, number 201701, Jan.
• Michael Spagat & Neil Johnson & Stijn van Weezel, 2017, "David Versus Goliath: Fundamental Patterns and Predictions in Modern Wars and Terrorist Campaigns," Working Papers, School of Economics, University College Dublin, number 201721, Oct.
• Anton Grui & Roman Lysenko, 2017, "Nowcasting Ukraine's GDP Using a Factor-Augmented VAR (FAVAR) Model," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 242, pages 5-13, DOI: 10.26531/vnbu2017.242.005.
• Teresa de J. Vargas Vega & Zeus S. Hernández Veleros & Eleazar Villegas González, 2017, "Economic growth and financial development: Evidence from three countries in North America," Economía, Instituto de Investigaciones Económicas y Sociales (IIES). Facultad de Ciencias Económicas y Sociales. Universidad de Los Andes. Mérida, Venezuela, volume 42, issue 43, pages 11-50, January-j.
• Lorenzo Ricci, 2017, "Essays on tail risk in macroeconomics and finance: measurement and forecasting," ULB Institutional Repository, ULB -- Universite Libre de Bruxelles, number 2013/242122, Feb.
• Beutner, Eric & Heinemann, Alexander & Smeekes, Stephan, 2017, "A Justification of Conditional Confidence Intervals," Research Memorandum, Maastricht University, Graduate School of Business and Economics (GSBE), number 023, Oct, DOI: 10.26481/umagsb.2017023.
• A. Ason Okoruwa, 2017, "Regression Analysis of Property Productivity Index and Value," The Valuation Journal, The National Association of Authorized Romanian Valuers, volume 12, issue 1, pages 58-93.
• Chlebus Marcin, 2017, "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Central European Economic Journal, Sciendo, volume 3, issue 50, pages 01-25, December, DOI: 10.1515/ceej-2017-0014.
• Popescu Mioara, 2017, "Modelling prediction of unemployment statistics using web technologies," HOLISTICA – Journal of Business and Public Administration, Sciendo, volume 8, issue 3, pages 55-60, December, DOI: 10.1515/hjbpa-2017-0023.
• Gurgul Henryk & Machno Artur, 2017, "Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades," Statistics in Transition New Series, Statistics Poland, volume 18, issue 1, pages 91-114, March, DOI: 10.21307/stattrans-2016-059.
• Mateusz Buczyński & Marcin Chlebus, 2017, "Is CAViaR model really so good in Value at Risk forecasting? Evidence from evaluation of a quality of Value-at-Risk forecasts obtained based on the: GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH(," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2017-29.
• Mckenzie,David J. & Sansone,Dario & Mckenzie,David J. & Sansone,Dario, 2017, "Man vs. machine in predicting successful entrepreneurs : evidence from a business plan competition in Nigeria," Policy Research Working Paper Series, The World Bank, number 8271, Dec.
• Christian Glocker & Philipp Wegmüller, 2017, "Business Cycle Dating and Forecasting with Real-time Swiss GDP Data," WIFO Working Papers, WIFO, number 542, Oct.
• Florian Huber & Thomas Zörner, 2017, "Threshold cointegration and adaptive shrinkage," Department of Economics Working Papers, Vienna University of Economics and Business, Department of Economics, number wuwp250, Jun.
• Huber, Florian & Zörner, Thomas, 2017, "Threshold cointegration and adaptive shrinkage," Department of Economics Working Paper Series, WU Vienna University of Economics and Business, number 250, Jun.
• Bruno Lanz & Simon Dietz & Timothy Swanson, 2017, "Global Population Growth, Technology, And Malthusian Constraints: A Quantitative Growth Theoretic Perspective," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, volume 58, issue 3, pages 973-1006, August, DOI: 10.1111/iere.12242.
• Anders Warne & Günter Coenen & Kai Christoffel, 2017, "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 1, pages 103-119, January.
• Erik Kole & Dick Dijk, 2017, "How to Identify and Forecast Bull and Bear Markets?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 1, pages 120-139, January.
• Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2017, "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 2, pages 275-295, March, DOI: 10.1002/jae.2510.
• Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2017, "Euromind‐ D : A Density Estimate of Monthly Gross Domestic Product for the Euro Area," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 3, pages 683-703, April.
• Knut Are Aastveit & Claudia Foroni & Francesco Ravazzolo, 2017, "Density Forecasts With Midas Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 4, pages 783-801, June.
• Knut Are Aastveit & Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2017, "Have Standard VARS Remained Stable Since the Crisis?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 5, pages 931-951, August.
• Jack Fosten, 2017, "Model selection with estimated factors and idiosyncratic components," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 32, issue 6, pages 1087-1106, September.
• Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017, "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 2, pages 109-121, March.
• Dirk Ulbricht & Konstantin A. Kholodilin & Tobias Thomas, 2017, "Do Media Data Help to Predict German Industrial Production?," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 5, pages 483-496, August.
• Kirstin Hubrich & Frauke Skudelny, 2017, "Forecast Combination for Euro Area Inflation: A Cure in Times of Crisis?," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 5, pages 515-540, August.
• Rangan Gupta & Eric Olson & Mark E. Wohar, 2017, "Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 6, pages 640-650, September.
• Michael K Andersson & Ted Aranki & André Reslow, 2017, "Adjusting for information content when comparing forecast performance," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 7, pages 784-794, November.
• Manabu Asai & Michael McAleer, 2017, "Forecasting the volatility of Nikkei 225 futures," Journal of Futures Markets, John Wiley & Sons, Ltd., volume 37, issue 11, pages 1141-1152, November.
• Edward S. Knotek & Saeed Zaman, 2017, "Nowcasting U.S. Headline and Core Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, volume 49, issue 5, pages 931-968, August, DOI: 10.1111/jmcb.12401.
• Hasenzagl, Thomas & Pellegrino, Filippo & Reichlin, Lucrezia & Ricco, Giovanni, 2017, "A Model of the Fed’s View on Inflation," The Warwick Economics Research Paper Series (TWERPS), University of Warwick, Department of Economics, number 1145.
• Bartosz Uniejewski & Rafal Weron & Florian Ziel, 2017, "Variance stabilizing transformations for electricity spot price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/17/01, Feb.
• Bartosz Uniejewski & Grzegorz Marcjasz & Rafal Weron, 2017, "On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/17/02, May.
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2017, "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Neural network models," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/17/03, Jul.
• Dreher, Sandra & Eichfelder, Sebastian & Noth, Felix, 2017, "Predicting earnings and cash flows: The information content of losses and tax loss carryforwards," arqus Discussion Papers in Quantitative Tax Research, arqus - Arbeitskreis Quantitative Steuerlehre, number 224.
• Menden, Christian & Proaño, Christian R., 2017, "Dissecting the financial cycle with dynamic factor models," BERG Working Paper Series, Bamberg University, Bamberg Economic Research Group, number 126.
• Itkonen, Juha & Juvonen, Petteri, 2017, "Nowcasting the Finnish economy with a large Bayesian vector autoregressive model," BoF Economics Review, Bank of Finland, number 6/2017.
• Funke, Michael & Loermann, Julius & Tsang, Andrew, 2017, "The information content in the offshore Renminbi foreign-exchange option market: Analytics and implied USD/CNH densities," BOFIT Discussion Papers, Bank of Finland Institute for Emerging Economies (BOFIT), number 15/2017.
• Mikosch, Heiner & Solanko, Laura, 2017, "Should one follow movements in the oil price or in money supply? Forecasting quarterly GDP growth in Russia with higher-frequency indicators," BOFIT Discussion Papers, Bank of Finland Institute for Emerging Economies (BOFIT), number 19/2017.
• Bettendorf, Timo & Bursian, Dirk, 2017, "Chow-Lin x N: How adding a panel dimension can improve accuracy," Discussion Papers, Deutsche Bundesbank, number 12/2017.
• Götz, Thomas B. & Knetsch, Thomas A., 2017, "Google data in bridge equation models for German GDP," Discussion Papers, Deutsche Bundesbank, number 18/2017.
• Mokinski, Frieder, 2017, "A severity function approach to scenario selection," Discussion Papers, Deutsche Bundesbank, number 34/2017.
• Jang, Tae-Seok & Sacht, Stephen, 2017, "Modeling consumer confidence and its role for expectation formation: A horse race," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2017-04.
• Simionescu, Mihaela, 2017, "The Influence of Brexit on the Foreign Direct Investment Projects and Inflows in the United Kingdom," GLO Discussion Paper Series, Global Labor Organization (GLO), number 68.
• Simionescu, Mihaela, 2017, "Prediction intervals for inflation and unemployment rate in Romania. A Bayesian approach," GLO Discussion Paper Series, Global Labor Organization (GLO), number 82.
• Doll, Jens & Rosenthal, Beatrice & Volkenand, Jonas & Hamella, Sandra, 2017, "Nowcasting des deutschen BIP," Weidener Diskussionspapiere, University of Applied Sciences Amberg-Weiden (OTH), number 59.
• Coupé, Tom, 2017, "Replicating "Predicting the present with Google trends" by Hyunyoung Choi and Hal Varian (The Economic Record, 2012)," Economics Discussion Papers, Kiel Institute for the World Economy (IfW Kiel), number 2017-76.
• Dreher, Sandra & Eichfelder, Sebastian & Noth, Felix, 2017, "Predicting earnings and cash flows: The information content of losses and tax loss carryforwards," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 30/2017.
• Heinisch, Katja & Scheufele, Rolf, 2017, "Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 5/2017.
• Bershadskyy, Dmitri & Brautzsch, Hans-Ulrich & Drygalla, Andrej & Heinisch, Katja & Holtemöller, Oliver & Lindner, Axel & Wieschemeyer, Matthias & Zeddies, Götz, 2017, "Die mittelfristige wirtschaftliche Entwicklung in Deutschland für die Jahre 2017 bis 2022 und finanzpolitische Optionen einer neuen Bundesregierung," Konjunktur aktuell, Halle Institute for Economic Research (IWH), volume 5, issue 5, pages 138-145.
• Deschermeier, Philipp, 2017, "Bevölkerungsentwicklung in den deutschen Bundesländern bis 2035
  [Regional population development in Germany to 2035]," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, volume 44, issue 3, pages 63-80, DOI: 10.2373/1864-810X.17-03-04.
• Haskamp, Ulrich, 2017, "Forecasting exchange rates: The time-varying relationship between exchange rates and Taylor rule fundamentals," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 704, DOI: 10.4419/86788818.
• Haskamp, Ulrich, 2017, "Improving the forecasts of European regional banks' profitability with machine learning algorithms," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 705, DOI: 10.4419/86788819.
• Prüser, Jan, 2017, "Forecasting US inflation using Markov dimension switching," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 710, DOI: 10.4419/86788828.
• Roesel, Felix, 2017, "The causal effect of wrong-hand drive vehicles on road safety," CEPIE Working Papers, Technische Universität Dresden, Center of Public and International Economics (CEPIE), number 15/17.
• Conrad, Christian, 2017, "When does information on forecast variance improve the performance of a combined forecast?," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking, Verein für Socialpolitik / German Economic Association, number 168200.
• Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017, "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking, Verein für Socialpolitik / German Economic Association, number 168206.
• Knüppel, Malte & Krüger, Fabian, 2017, "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking, Verein für Socialpolitik / German Economic Association, number 168294.
• Ksenija Dumicic & Berislav Zmuk & Anita Ceh Casni, 2017, "Evaluating forecasting models for unemployment rates by gender in selected european countries," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 15, issue 1, pages 16-35.
• Mihály Ormos & Dusán Timotity, 2017, "Expected downside risk and asset prices: characteristics of emerging and developed European markets," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, volume 44, issue 3, pages 529-546, August, DOI: 10.1007/s10663-016-9329-3.
• Francesca Rondina, 2017, "An Econometric Learning Approach to Approximate Expectations in Empirical Macro Models," International Advances in Economic Research, Springer;International Atlantic Economic Society, volume 23, issue 4, pages 437-438, November, DOI: 10.1007/s11294-017-9662-8.
• Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2017, "On exchange-rate movements and gold-price fluctuations: evidence for gold-producing countries from a nonparametric causality-in-quantiles test," International Economics and Economic Policy, Springer, volume 14, issue 4, pages 691-700, October, DOI: 10.1007/s10368-016-0357-z.
• Esteban Fernández-Vázquez & Blanca Moreno, 2017, "Entropy Econometrics for combining regional economic forecasts: A Data-Weighted Prior Estimator," Journal of Geographical Systems, Springer, volume 19, issue 4, pages 349-370, October, DOI: 10.1007/s10109-017-0259-9.
• Rangan Gupta & Anandamayee Majumdar & Mark E. Wohar, 2017, "The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence From a Quantile Predictive Regression Approach," Open Economies Review, Springer, volume 28, issue 1, pages 47-59, February, DOI: 10.1007/s11079-016-9408-x.
• Niels D. Gilbert & Jasper F.M. Jong, 2017, "Do European fiscal rules induce a bias in fiscal forecasts? Evidence from the Stability and Growth Pact," Public Choice, Springer, volume 170, issue 1, pages 1-32, January, DOI: 10.1007/s11127-016-0372-1.
• Jing Xu & Michelle Hallack & Miguel Vazquez, 2017, "Applying a third party access model for China’s gas pipeline network: an independent pipeline operator and congestion rent transfer," Journal of Regulatory Economics, Springer, volume 51, issue 1, pages 72-97, February, DOI: 10.1007/s11149-017-9316-z.
• Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017, "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, volume 49, issue 4, pages 949-971, November, DOI: 10.1007/s11156-016-0613-x.
• Chulwoo Han & Frank C. Park & Jangkoo Kang, 2017, "A geometric treatment of time-varying volatilities," Review of Quantitative Finance and Accounting, Springer, volume 49, issue 4, pages 1121-1141, November, DOI: 10.1007/s11156-017-0618-0.
• Byeongdeuk Jang & Young Se Kim, 2017, "Driving Forces of Inflation Expectations," Korean Economic Review, Korean Economic Association, volume 33, pages 207-237.
• Mihaela Simionescu, 2017, "The Impact Of Immigrants On The UK Economy," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, volume 9, issue 2, pages 31-46, June.
• Mirel-Daniel Simionescu, 2017, "Determinants of Foreign Direct Investments in Bulgaria and Romania in the Context of Recent Economic Crisis," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, volume 3, issue 1, pages 68-72, March.
• Iulian Lolea, 2017, "Where did the GARCH Models Perform Best in Terms of Volatility Forecasting? Equity vs. Commodities Markets," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, volume 3, issue 3, pages 79-86, September.
• Ayse Kabukcuoglu & Enrique Martínez-García & Mehmet Ali Soytas, 2017, "Exploring the Nexus between Inflation and Globalization under Inflation Targeting through the Lens of New Zealand’s Experience," Koç University-TUSIAD Economic Research Forum Working Papers, Koc University-TUSIAD Economic Research Forum, number 1709, Apr.
• Florian Chatagny & Christian Stettler, 2017, "Fiscal Fore casting in a Federal Country: Does Space Matter?," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, volume 11, issue 4, pages 51-60, December, DOI: 10.3929/ethz-a-005427569.
• Virág, Miklós & Nyitrai, Tamás, 2017, "Magyar vállalkozások felszámolásának előrejelzése pénzügyi mutatóik idősorai alapján
  [Predicting the liquidation of Hungarian firms using a time series of their financial ratios]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), volume 0, issue 3, pages 305-324, DOI: 10.18414/KSZ.2017.3.305.
• Ouael EL JEBARI & Abdelati HAKMAOUI, 2017, "Modeling persistence of volatility in the Moroccan exchange market using a fractionally integrated EGARCH," Turkish Economic Review, KSP Journals, volume 4, issue 4, pages 388-399, December.
• Ron W. NIELSEN, 2017, "Application of differential equations in projecting growth trajectories," Journal of Economics Bibliography, KSP Journals, volume 4, issue 3, pages 203-221, September.
• Evzen Kocenda & Karen Poghosyan, 2017, "Export sophistication: A dynamic panel data approach," KIER Working Papers, Kyoto University, Institute of Economic Research, number 980 Classification-C52; C, Nov.
• 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, DOI: 10.17533/udea.le.n86a08.
• Anh Dinh Minh Nguyen, 2017, "U.K. Monetary Policy under Inflation Targeting," Bank of Lithuania Working Paper Series, Bank of Lithuania, number 41, Mar.
• Michael McAleer & Xiao-Guang Yue, 2017, "Prediction of Gas Concentration Based on the Opposite Degree Algorithm," Journal of Reviews on Global Economics, Lifescience Global, volume 6, pages 154-162.
• Aumnad Phdungsilp, 2017, "Projections of Energy Use and Carbon Emissions for Bangkok,Thailand," Journal of Reviews on Global Economics, Lifescience Global, volume 6, pages 248-257.
• Narongdech Keeratipranon & Phatcharasak Phawanaphinyo, 2017, "Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution," Journal of Reviews on Global Economics, Lifescience Global, volume 6, pages 269-278.
• Lehmann, Robert & Wohlrabe, Klaus, 2017, "Boosting and regional economic forecasting: the case of Germany," Munich Reprints in Economics, University of Munich, Department of Economics, number 49919.
• Magdalena Petrovska & Gani Ramadani & Nikola Naumovski & Biljana Jovanovic, 2017, "Forecasting Macedonian Inflation: Evaluation of different models for short-term forecasting," Working Papers, National Bank of the Republic of North Macedonia, number 2017-06.
• Mohammad Reza Farzanegan & Mai Hassan, 2017, "The impact of economic globalization on the shadow economy in Egypt," MAGKS Papers on Economics, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung), number 201718.
• Radim Farana & Ivo Formánek & Cyril Klimeš & Bogdan Walek, 2017, "System Modelling and Decision Making System Based on Fuzzy Expert System," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, volume 3, issue 2, pages 118-122, DOI: 10.11118/ejobsat.v3i2.103.
• Aleksandra Hałka & Jacek Kotłowski, 2017, "Global or Domestic? Which Shocks Drive Inflation in European Small Open Economies?," Emerging Markets Finance and Trade, Taylor & Francis Journals, volume 53, issue 8, pages 1812-1835, August, DOI: 10.1080/1540496X.2016.1193001.
• Christoph Anders & Max Groneck, 2017, "The Optimal Portfolio of PAYG Benefits and Funded Pensions in Germany," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, volume 73, issue 3, pages 255-291, September, DOI: 10.1628/001522117X14915570953903.