Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2016

• Angus Deaton & Nancy Cartwright, 2016, "Understanding and Misunderstanding Randomized Controlled Trials," Working Papers, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies., number august_25.pdf, Aug.
• Damian Stelmasiak & Grzegorz Szafrański, 2016, "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, volume 8, issue 1, pages 21-42, March.
• Cláudia Duarte, 2016, "A Mixed Frequency Approach to Forecast Private Consumption with ATM/POS Data," Working Papers, Banco de Portugal, Economics and Research Department, number w201601.
• António Rua, 2016, "A wavelet-based multivariate multiscale approach for forecasting," Working Papers, Banco de Portugal, Economics and Research Department, number w201612.
• Graham Elliott & Allan Timmermann, 2016, "Economic Forecasting," Economics Books, Princeton University Press, number 10740, edition 1, December.
• David Magaña Lemus, 2016, "Assessment of Price Risk on Agricultural Inventory Credit under Sparse Data Conditions," Economia y Sociedad., Universidad Michoacana de San Nicolas de Hidalgo, Facultad de Economia, issue 34, pages 106-118, Enero-Jun.
• Fernanda Fuentes & Rodrigo Herrera & Adam Clements, 2016, "Modelling Extreme Risks in Commodities and Commodity Currencies," NCER Working Paper Series, National Centre for Econometric Research, number 115, Nov.
• Alain Kabundi & Elmarie Nel & Franz Ruch, 2016, "Nowcasting Real GDP growth in South Africa," Working Papers, South African Reserve Bank, number 7068, Feb.
• Michael Clements, 2016, "Are Macroeconomic Density Forecasts Informative?," ICMA Centre Discussion Papers in Finance, Henley Business School, University of Reading, number icma-dp2016-02, Apr.
• Steffen Heinig & Anupam Nanda & Sotiris Tsolacos, 2016, "Which Sentiment Indicators Matter? An Analysis of the European Commercial Real Estate Market," ICMA Centre Discussion Papers in Finance, Henley Business School, University of Reading, number icma-dp2016-04, Jun.
• Michael Clements, 2016, "Are Macro-Forecasters Essentially The Same? An Analysis of Disagreement, Accuracy and Efficiency," ICMA Centre Discussion Papers in Finance, Henley Business School, University of Reading, number icma-dp2016-08, Oct.
• Marc Giannoni & Christina Patterson & Marco Del Negro, 2016, "The Forward Guidance Puzzle," 2016 Meeting Papers, Society for Economic Dynamics, number 143.
• Mihaela Simionescu, 2016, "The relation between economic growth and foreign direct investment during the economic crisis in the European Union," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, volume 34, issue 1, pages 187-213.
• Nataša Erjavec & Petar Soriæ & Mirjana Èižmešija, 2016, "Predicting the probability of recession in Croatia: Is economic sentiment the missing link?," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, volume 34, issue 2, pages 555-579.
• Tuhkuri, Joonas, 2016, "ETLAnow: A Model for Forecasting with Big Data – Forecasting Unemployment with Google Searches in Europe," ETLA Reports, The Research Institute of the Finnish Economy, number 54, May.
• Widgrén, Joona, 2016, "Predicting Housing Prices with Google Searches in Finland," ETLA Reports, The Research Institute of the Finnish Economy, number 63, Dec.
• Tuhkuri, Joonas, 2016, "Forecasting Unemployment with Google Searches," ETLA Working Papers, The Research Institute of the Finnish Economy, number 35, Mar.
• Marina Lifshits, 2016, "Forecasting of the global migration situation based on the analysis of net migration in the countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 41, pages 96-122.
• Boris Demeshev & Oxana Malakhovskaya, 2016, "BVAR mapping," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 43, pages 118-141.
• Dean Fantazzini & Erik Nigmatullin & Vera Sukhanovskaya & Sergey Ivliev, 2016, "Everything you always wanted to know about bitcoin modelling but were afraid to ask. I," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), volume 44, pages 5-24.
• Monzur Hossain & Mohammad Yunus, 2016, "Estimates of Per Capita Consumption of Food Grains in Bangladesh," Bangladesh Development Studies, Bangladesh Institute of Development Studies (BIDS), volume 39, issue 1-2, pages 103-116.
• Recep Akdağ, 2016, "Urban Water Demand Forecasting and Comparative Analysis by Artificial Neural Networks, Support Vector Machines and Box-Jenkins Methods," Business and Economics Research Journal, Bursa Uludag University, Faculty of Economics and Administrative Sciences, volume 7, issue 1, pages 123-138.
• Georges Dionne & Xiaozhou Zhou, 2016, "The Dynamics of Ex-ante Weighted Spread: An Empirical Analysis," Working Papers, HEC Montreal, Canada Research Chair in Risk Management, number 16-4, Nov.
• William Barnett & Marcelle Chauvet & Danilo Leiva-Leon & Liting Su, 2016, "Nowcasting Nominal GDP with the Credit-Card Augmented Divisia Monetary," Studies in Applied Economics, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise, number 59, Aug.
• William Barnett & Liting Su, 2016, "Risk Adjustment of the Credit-Card Augmented Divisia Monetary Aggregates," Studies in Applied Economics, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise, number 67, Oct.
• Sora Chon, 2016, "A Predictive System for International Trade Growth," Working Papers, Korea Institute for International Economic Policy, number 16-3, Aug.
• Hossein Asgharpur & Ali Rezazadeh, 2016, "Determining the Stock Optimal Portfolio using Value at Risk," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, volume 2, issue 4, pages 93-118.
• Odette Virginia Delfín Ortega & Plinio Hernánez Barriga & Noemí Ramírez Sepúlveda, 2016, "La Evasión Fiscal del IVA en México 2004-2013," Revista Nicolaita de Estudios Económicos, Universidad Michoacana de San Nicolás de Hidalgo, Instituto de Investigaciones Económicas y Empresariales, volume 0, issue 2, pages 61-80.
• Eugen Scarlat, 2016, "Connectivity - Based Clustering of GDP Time Series," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 1, pages 23-38, March.
• Dorina Lazar & Anuta Buiga & Adela Deaconu, 2016, "Common Stochastic Trends in European Mortality Levels: Testing and Consequences for Modeling Longevity Risk in Insurance," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 2, pages 152-168, June.
• Mihaela SIMIONESCU, 2016, "Investiţiile Străine Directe Şi Criza Economică Recentă," Institute for Economic Forecasting Conference Proceedings, Institute for Economic Forecasting, number 161106, Nov.
• Mihaela Simionescu, 2016, "The Real GDP Rate in European Union. A Panel Data Approach," Working Papers of Institute for Economic Forecasting, Institute for Economic Forecasting, number 161001, Oct.
• Mihaela Simionescu, 2016, "Foreign Direct Investment and Sustainable Development. A Regional Approach for Romania," Working Papers of Macroeconomic Modelling Seminar, Institute for Economic Forecasting, number 162702, Nov.
• Gheorghe Savoiu & Emilia Gogu & Alexandru Ionescu, 2016, "Model Estimates Of Gross Domestic Product In Relation to Export And Import Of Fuels, Focused on the Elasticity and Determination Of Directly and Indirectly Associated Rates," Romanian Statistical Review, Romanian Statistical Review, volume 64, issue 1, pages 21-40, March.
• Davide De Gaetano, 2016, "Forecast Combinations For Realized Volatility In Presence Of Structural Breaks," Departmental Working Papers of Economics - University 'Roma Tre', Department of Economics - University Roma Tre, number 0208, Jun.
• Loretta Mastroeni & Pierluigi Vellucci, 2016, "“Butterfly Effect" vs Chaos in Energy Futures Markets," Departmental Working Papers of Economics - University 'Roma Tre', Department of Economics - University Roma Tre, number 0209, Oct.
• Martyna Marczak & Tommaso Proietti & Stefano Grassi, 2016, "A Data–Cleaning Augmented Kalman Filter for Robust Estimation of State Space Models," CEIS Research Paper, Tor Vergata University, CEIS, number 374, Mar, revised 31 Mar 2016.
• Murat Midilic, 2016, "Estimation Of Star-Garch Models With Iteratively Weighted Least Squares," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium, Ghent University, Faculty of Economics and Business Administration, number 16/918, Jan.
• Ulyana Dzyuma-Zaremba, 2016, "Gant Development S.A. – the effectiveness of bankruptcy prediction models in case of sudden bankruptcy. Case study," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, volume 11, issue 3, pages 45-57, February.
• Paramita Mukherjee & Malabika Roy, 2016, "What Drives the Stock Market Return in India? An Exploration with Dynamic Factor Model," Journal of Emerging Market Finance, Institute for Financial Management and Research, volume 15, issue 1, pages 119-145, April, DOI: 10.1177/0972652715623681.
• Francesco Bartolucci & Fulvia Pennoni & Giorgio Vittadini, 2016, "Causal Latent Markov Model for the Comparison of Multiple Treatments in Observational Longitudinal Studies," Journal of Educational and Behavioral Statistics, , volume 41, issue 2, pages 146-179, April, DOI: 10.3102/1076998615622234.
• Эдер Л. В. & Немов В. Ю. & Филимонова И. В., 2016, "Перспективы энергопотребления на транспорте: методические подходы и результаты прогнозирования. Prospects for Transport Energy Consumption: Methodological Approaches and Results of Forecasting," Мир экономики и управления // Вестник НГУ. Cерия: Cоциально-экономические науки, Socionet;Новосибирский государственный университет, volume 16, issue 1, pages 25-38.
• Соколова Г. Е., 2016, "Имитационная модель газового комплекса. A simulation model of the gas complex," Мир экономики и управления // Вестник НГУ. Cерия: Cоциально-экономические науки, Socionet;Новосибирский государственный университет, volume 16, issue 2, pages 57-69.
• Dilip Kumar, 2016, "Estimating and forecasting value-at-risk using the unbiased extreme value volatility estimator," Proceedings of Economics and Finance Conferences, International Institute of Social and Economic Sciences, number 3205528, Mar.
• Mihaela Simionescu, 2016, "Determinats Of Unemployment Rate In Romanian Counties. A Panel Var Approach," Journal of Academic Research in Economics, Spiru Haret University, Faculty of Accounting and Financial Management Constanta, volume 8, issue 1 (March), pages 136-145.
• Mihaela Simionescu, 2016, "The Impact of BREXIT on the Foreign Direct Investment in the United Kingdom," Bulgarian Economic Papers, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, number bep-2016-07, Jul, revised Jul 2016.
• Boyan Lomev & Nikolay Netov, 2016, "Bulgarian stock market and market risk forecasting under long memory in returns," Yearbook of the Faculty of Economics and Business Administration, Sofia University, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria, volume 13, issue 1, pages 185-200, September.
• Sandra Hanslin Grossmann & Rolf Scheufele, 2016, "Foreign PMIs: A reliable indicator for exports?," Working Papers, Swiss National Bank, number 2016-01.
• Pinar Yesin, 2016, "Exchange Rate Predictability and State-of-the-Art Models," Working Papers, Swiss National Bank, number 2016-02.
• Christian Hepenstrick & Massimiliano Marcellino, 2016, "Forecasting with Large Unbalanced Datasets: The Mixed-Frequency Three-Pass Regression Filter," Working Papers, Swiss National Bank, number 2016-04.
• Duo Qin & Qingchao Wang, 2016, "Predictive Macro-Impacts of PLS-based Financial Conditions Indices: An Application to the USA," Working Papers, Department of Economics, SOAS University of London, UK, number 201, Oct.
• Daniel Ambach & Robert Garthoff, 2016, "Vorhersagen der Windgeschwindigkeit und Windenergie in Deutschland," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, volume 10, issue 1, pages 15-36, February, DOI: 10.1007/s11943-016-0177-1.
• Hiroshi Mori & Toshio Inaba & John Dyck, 2016, "Accounting for structural changes in demand for foods in the presence of age and cohort effects: the case of fresh fish in Japan," Evolutionary and Institutional Economics Review, Springer, volume 13, issue 2, pages 363-379, December, DOI: 10.1007/s40844-016-0056-z.
• Zouheir Mighri & Faysal Mansouri, 2016, "Asymmetric price transmission within the Argentinean stock market: an asymmetric threshold cointegration approach," Empirical Economics, Springer, volume 51, issue 3, pages 1115-1149, November, DOI: 10.1007/s00181-015-1029-5.
• Ali Babikir & Henry Mwambi, 2016, "Evaluating the combined forecasts of the dynamic factor model and the artificial neural network model using linear and nonlinear combining methods," Empirical Economics, Springer, volume 51, issue 4, pages 1541-1556, December, DOI: 10.1007/s00181-015-1049-1.
• Christian Pierdzioch & Marian Risse & Sebastian Rohloff, 2016, "Fluctuations of the real exchange rate, real interest rates, and the dynamics of the price of gold in a small open economy," Empirical Economics, Springer, volume 51, issue 4, pages 1481-1499, December, DOI: 10.1007/s00181-015-1053-5.
• Jacques Peeperkorn & Yudhvir Seetharam, 2016, "A learning-augmented approach to pricing risk in South Africa," Eurasian Business Review, Springer;Eurasia Business and Economics Society, volume 6, issue 1, pages 117-139, April, DOI: 10.1007/s40821-015-0038-9.
• Alfonso Arpaia & Aron Kiss & Balazs Palvolgyi & Alessandro Turrini, 2016, "Labour mobility and labour market adjustment in the EU," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), volume 5, issue 1, pages 1-21, December, DOI: 10.1186/s40176-016-0069-8.
• Michal Franta & David Havrlant & Marek Rusnák, 2016, "Forecasting Czech GDP Using Mixed-Frequency Data Models," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 12, issue 2, pages 165-185, December, DOI: 10.1007/s41549-016-0008-z.
• Kaushik Bhattacharya & Sunny Kumar Singh, 2016, "Impact of Payment Technology on Seasonality of Currency in Circulation: Evidence from the USA and India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 14, issue 1, pages 117-136, June, DOI: 10.1007/s40953-015-0024-1.
• Han Hwa Goh & Kim Leng Tan & Chia Ying Khor & Sew Lai Ng, 2016, "Volatility and Market Risk of Rubber Price in Malaysia: Pre- and Post-Global Financial Crisis," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 14, issue 2, pages 323-344, December, DOI: 10.1007/s40953-016-0037-4.
• Juan Jose Echavarria & Mauricio Villamizar-Villegas, 2016, "Great expectations? evidence from Colombia’s exchange rate survey," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), volume 25, issue 1, pages 1-27, December, DOI: 10.1007/s40503-016-0033-2.
• Marco Stampini & Marcos Robles & Mayra Sáenz & Pablo Ibarrarán & Nadin Medellín, 2016, "Poverty, vulnerability, and the middle class in Latin America," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), volume 25, issue 1, pages 1-44, December, DOI: 10.1007/s40503-016-0034-1.
• Lina M. Cortés & Andrés Mora-Valencia & Javier Perote, 2016, "The productivity of top researchers: a semi-nonparametric approach," Scientometrics, Springer;Akadémiai Kiadó, volume 109, issue 2, pages 891-915, November, DOI: 10.1007/s11192-016-2072-5.
• 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, volume 7, issue 3, pages 341-357, August, DOI: 10.1007/s13209-016-0144-7.
• Gong Cheng & Javier Diaz-Cassou & Aitor Erce, 2016, "The Macroeconomic Effects of Official Debt Restructuring: Evidence from the Paris Club," Working Papers, European Stability Mechanism, number 21, Dec, revised 24 Apr 2017.
• Pinar Yesin, 2016, "Exchange Rate Predictability and State-of-the-Art Models," Working Papers, Swiss National Bank, Study Center Gerzensee, number 16.03, Mar.
• Pascal Bührig & Klaus Wohlrabe, 2016, "Forecasting revisions of German industrial production," Applied Economics Letters, Taylor & Francis Journals, volume 23, issue 15, pages 1062-1064, October, DOI: 10.1080/13504851.2015.1133890.
• R. Lehmann & K. Wohlrabe, 2016, "Looking into the black box of boosting: the case of Germany," Applied Economics Letters, Taylor & Francis Journals, volume 23, issue 17, pages 1229-1233, November, DOI: 10.1080/13504851.2016.1148246.
• Jari H�nnik�inen, 2016, "The mortgage spread as a predictor of real-time economic activity," Applied Economics Letters, Taylor & Francis Journals, volume 23, issue 2, pages 112-116, February, DOI: 10.1080/13504851.2015.1054064.
• Carlos A. Medel & Pablo M. Pincheira, 2016, "The out-of-sample performance of an exact median-unbiased estimator for the near-unity AR(1) model," Applied Economics Letters, Taylor & Francis Journals, volume 23, issue 2, pages 126-131, February, DOI: 10.1080/13504851.2015.1057890.
• David Iselin & Boriss Siliverstovs, 2016, "Using newspapers for tracking the business cycle: a comparative study for Germany and Switzerland," Applied Economics, Taylor & Francis Journals, volume 48, issue 12, pages 1103-1118, March, DOI: 10.1080/00036846.2015.1093085.
• Ioannis Chatziantoniou & Stavros Degiannakis & Bruno Eeckels & George Filis, 2016, "Forecasting tourist arrivals using origin country macroeconomics," Applied Economics, Taylor & Francis Journals, volume 48, issue 27, pages 2571-2585, June, DOI: 10.1080/00036846.2015.1125434.
• Stelios Bekiros & Rangan Gupta & Clement Kyei, 2016, "A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices," Applied Economics, Taylor & Francis Journals, volume 48, issue 31, pages 2895-2898, July, DOI: 10.1080/00036846.2015.1130793.
• Nikolaos Antonakakis & Vassilios Babalos & Clement Kyei, 2016, "Predictability of sustainable investments and the role of uncertainty: evidence from a non-parametric causality-in-quantiles test," Applied Economics, Taylor & Francis Journals, volume 48, issue 48, pages 4655-4665, October, DOI: 10.1080/00036846.2016.1161724.
• Francesco Audrino & Fulvio Corsi & Kameliya Filipova, 2016, "Bond Risk Premia Forecasting: A Simple Approach for Extracting Macroeconomic Information from a Panel of Indicators," Econometric Reviews, Taylor & Francis Journals, volume 35, issue 2, pages 232-256, February, DOI: 10.1080/07474938.2013.833809.
• Álvaro Cartea & Dimitrios Karyampas, 2016, "The Relationship between the Volatility of Returns and the Number of Jumps in Financial Markets," Econometric Reviews, Taylor & Francis Journals, volume 35, issue 6, pages 929-950, June, DOI: 10.1080/07474938.2014.976529.
• Anders Bredahl Kock & Timo Teräsvirta, 2016, "Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques," Econometric Reviews, Taylor & Francis Journals, volume 35, issue 8-10, pages 1753-1779, December, DOI: 10.1080/07474938.2015.1035163.
• Stavros Degiannakis & Alexandra Livada, 2016, "Evaluation of realized volatility predictions from models with leptokurtically and asymmetrically distributed forecast errors," Journal of Applied Statistics, Taylor & Francis Journals, volume 43, issue 5, pages 871-892, April, DOI: 10.1080/02664763.2015.1079306.
• Marine Carrasco & Barbara Rossi, 2016, "In-Sample Inference and Forecasting in Misspecified Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 34, issue 3, pages 313-338, July, DOI: 10.1080/07350015.2016.1186029.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016, "Common Drifting Volatility in Large Bayesian VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 34, issue 3, pages 375-390, July, DOI: 10.1080/07350015.2015.1040116.
• Laura Coroneo & Domenico Giannone & Michele Modugno, 2016, "Unspanned Macroeconomic Factors in the Yield Curve," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 34, issue 3, pages 472-485, July, DOI: 10.1080/07350015.2015.1052456.
• Jari Hännikäinen, 2016, "When does the yield curve contain predictive power? Evidence from a data-rich environment," Working Papers, Tampere University, Faculty of Management and Business, Economics, number 1603, Apr.
• Hännikäinen Jari, 2016, "The shadow rate as a predictor of real activity and inflation: Evidence from a data-rich environment," Working Papers, Tampere University, Faculty of Management and Business, Economics, number 1606, Jun.
• Jari Hännikäinen, 2016, "Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks," Working Papers, Tampere University, Faculty of Management and Business, Economics, number 1692, Nov.
• Dungey, Mardi & Jacobs, Jan P.A.M. & Tian, Jing, 2016, "Forecasting output gaps in the G-7 countries: The role of correlated Innovations and structural breaks," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2016-04.
• Bahar Sen Dogan & Murat Midilic, 2016, "Forecasting Turkish Real GDP Growth in a Data Rich Environment," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 1611.
• Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2016, "Dynamic Predictive Density Combinations for Large Data Sets in Economics and Finance," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 15-084/III, Mar, revised 03 Jul 2017.
• Xiao-Guang Yue & Rui Gao & Michael McAleer, 2016, "Prediction of Gas Concentration based on the Opposite Degree Algorithm," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 16-027/III, Apr.
• Andre Lucas & Anne Opschoor & Julia Schaumburg, 2016, "Accounting for Missing Values in Score-Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 16-067/IV, Aug.
• Tom Boot & Didier Nibbering, 2016, "Forecasting Using Random Subspace Methods," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 16-073/III, Sep, revised 11 Aug 2017.
• Triepels, Ron & Daniels, Hennie, 2016, "A Comparison of Three Models to Predict Liquidity Flows between Banks Based on Daily Payments Transactions," Discussion Paper, Tilburg University, Center for Economic Research, number 2016-037.
• Herman Stekler & Yongchen Zhao, 2016, "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Working Papers, Towson University, Department of Economics, number 2016-15, Sep, revised Sep 2016.
• Siem Jan Koopman & André Lucas & Marcel Scharth, 2016, "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," The Review of Economics and Statistics, MIT Press, volume 98, issue 1, pages 97-110, March.
• Graham Elliott & Dalia Ghanem & Fabian Krüger, 2016, "Forecasting Conditional Probabilities of Binary Outcomes under Misspecification," The Review of Economics and Statistics, MIT Press, volume 98, issue 4, pages 742-755, October.
• Rochelle M. Edge & Jeremy B. Rudd, 2016, "Real-Time Properties of the Federal Reserve's Output Gap," The Review of Economics and Statistics, MIT Press, volume 98, issue 4, pages 785-791, October.
• Anil Alpman, 2016, "Implementing Rubin's alternative multiple-imputation method for statistical matching in Stata," Stata Journal, StataCorp LLC, volume 16, issue 3, pages 717-739, September.
• Mihaela Simionescu & Irina Dragan, 2016, "The Evaluation Of Quarterly Forecast Intervals For Inflation Rate In Romania," Economic Review: Journal of Economics and Business, University of Tuzla, Faculty of Economics, volume 14, issue 1, pages 80-89, May.
• Xiao-Guang Yue & Rui Gao & Michael McAleer, 2016, "Prediction of Gas Concentration Based on the Opposite Degree Algorithm," Documentos de Trabajo del ICAE, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, number 2016-05, Apr.
• Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2016, "Volatility transmission between stock and exchange-rate markets: A connectedness analysis," Working Papers del Instituto Complutense de Estudios Internacionales, Universidad Complutense de Madrid, Instituto Complutense de Estudios Internacionales, number 1604.
• Christiane Baumeister & Lutz Kilian, 2016, "Understanding the Decline in the Price of Oil since June 2014," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, volume 3, issue 1, pages 131-158, DOI: 10.1086/684160.
• Elena Andreou, 2016, "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics, University of Cyprus Department of Economics, number 03-2016, Apr.
• Nikola Radivojevic & Milena Cvjetkovic & Saša Stepanov, 2016, "The new hybrid value at risk approach based on the extreme value theory," Estudios de Economia, University of Chile, Department of Economics, volume 43, issue 1 Year 20, pages 29-52, June.
• Jack Fosten, 2016, "Forecast evaluation with factor-augmented models," University of East Anglia School of Economics Working Paper Series, School of Economics, University of East Anglia, Norwich, UK., number 2016-05, Jan.
• Daniela Bragoli & Jack Fosten, 2016, "Nowcasting Indian GDP," University of East Anglia School of Economics Working Paper Series, School of Economics, University of East Anglia, Norwich, UK., number 2016-06, Jun.
• Jack Fosten, 2016, "Model selection with factors and variables," University of East Anglia School of Economics Working Paper Series, School of Economics, University of East Anglia, Norwich, UK., number 2016-07, Mar.
• Francis Bismans & Igor N. Litvine, 2016, "Forecasting with Neural Networks Models," Working Papers of BETA, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg, number 2016-28.
• Smeekes, Stephan & Wijler, Etiënne, 2016, "Macroeconomic Forecasting Using Penalized Regression Methods," Research Memorandum, Maastricht University, Graduate School of Business and Economics (GSBE), number 039, Jan, DOI: 10.26481/umagsb.2016039.
• Marine Carrasco & Barbara Rossi, 2016, "In-sample inference and forecasting in misspecified factor models," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1530, Apr.
• Barbara Rossi & Tatevik Sekhposyan & Matthieu Soupre, 2016, "Understanding the sources of macroeconomic uncertainty," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1531, May, revised Dec 2018.
• Galina Gagarina & Nikita Moiseev & Alla Ryzhakova & Gleb Ryzhakov, 2016, "Estimation And Forecast Of Regional Competitiveness Level," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, volume 1, issue 4, pages 1040-1049.
• EMAMVERDI, Ghodratollah & KARIMI, Mohammad Sharif & KHAKIE, Sima & KARIMI, Mojtaba, 2016, "Forecasting The Total Index Of Tehran Stock Exchange," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", volume 20, issue 1, pages 54-68.
• GHERBOVET, Sergiu, 2016, "Prospects For Triggering The Crisis And Related Investment Opportunities," Journal of Financial and Monetary Economics, Centre of Financial and Monetary Research "Victor Slavescu", volume 3, issue 1, pages 238-244, October.
• Goodness C. Aye & Frederick W. Deale & Rangan Gupta, 2016, "Does Debt Ceiling and Government Shutdown Help in Forecasting the US Equity Risk Premium?," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, volume 63, issue 3, pages 273-291.
• Wiśniewski Jerzy Witold, 2016, "Empirical Econometric Model of an Enterprise," Folia Oeconomica Stetinensia, Sciendo, volume 16, issue 1, pages 232-247, December, DOI: 10.1515/foli-2016-0015.
• Kaczmarczyk Paweł, 2016, "Integrated Model of Demand for Telephone Services in Terms of Microeconometrics," Folia Oeconomica Stetinensia, Sciendo, volume 16, issue 2, pages 72-83, December, DOI: 10.1515/foli-2016-0026.
• Kostetska Iryna, 2016, "Improving of Business Planning Using the Method of Fuzzy Numbers," Journal of Management and Business Administration. Central Europe, Sciendo, volume 24, issue 3, pages 47-61, September, DOI: 10.7206/jmba.ce.2450-7814.175.
• Marcin Chlebus, 2016, "One-Day Prediction of State of Turbulence for Portfolio. Models for Binary Dependent Variable," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2016-01.
• Marcin Chlebus, 2016, "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2016-06.
• Florian Huber & Martin Feldkircher, 2016, "Adaptive shrinkage in Bayesian vector autoregressive models," Department of Economics Working Papers, Vienna University of Economics and Business, Department of Economics, number wuwp221, Mar.
• Feldkircher, Martin & Huber, Florian, 2016, "Adaptive Shrinkage in Bayesian Vector Autoregressive Models," Department of Economics Working Paper Series, WU Vienna University of Economics and Business, number 221, Mar.
• Chu‐An Liu & Biing‐Shen Kuo, 2016, "Model averaging in predictive regressions," Econometrics Journal, Royal Economic Society, volume 19, issue 2, pages 203-231, June.
• Raffaella Giacomini & Barbara Rossi, 2016, "Model Comparisons In Unstable Environments," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, volume 57, issue 2, pages 369-392, May, DOI: 10.1111/iere.12161.
• Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016, "Bayesian Graphical Models for STructural Vector Autoregressive Processes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 31, issue 2, pages 357-386, March.
• Barbara Rossi & Tatevik Sekhposyan, 2016, "Forecast Rationality Tests in the Presence of Instabilities, with Applications to Federal Reserve and Survey Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 31, issue 3, pages 507-532, April.
• Tim Bollerslev & Andrew J. Patton & Wenjing Wang, 2016, "Daily House Price Indices: Construction, Modeling, and Longer‐run Predictions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 31, issue 6, pages 1005-1025, September.
• George Athanasopoulos & Donald S. Poskitt & Farshid Vahid & Wenying Yao, 2016, "Determination of Long‐run and Short‐run Dynamics in EC‐VARMA Models via Canonical Correlations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 31, issue 6, pages 1100-1119, September.
• Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2016, "Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 31, issue 7, pages 1254-1275, November.
• Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. Van Dijk, 2016, "Interconnections Between Eurozone and us Booms and Busts Using a Bayesian Panel Markov‐Switching VAR Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 31, issue 7, pages 1352-1370, November.
• David A. Bessler & Shahriar Kibriya & Junyi Chen & Edwin Price, 2016, "On Forecasting Conflict in the Sudan: 2009–2012," Journal of Forecasting, John Wiley & Sons, Ltd., volume 35, issue 2, pages 179-188, March.
• Kavita Sirichand & Stephen G. Hall, 2016, "Decision‐Based Forecast Evaluation of UK Interest Rate Predictability," Journal of Forecasting, John Wiley & Sons, Ltd., volume 35, issue 2, pages 93-112, March.
• Andre Jungmittag, 2016, "Combination of Forecasts across Estimation Windows: An Application to Air Travel Demand," Journal of Forecasting, John Wiley & Sons, Ltd., volume 35, issue 4, pages 373-380, July.
• Alessandro Girardi & Christian Gayer & Andreas Reuter, 2016, "The Role of Survey Data in Nowcasting Euro Area GDP Growth," Journal of Forecasting, John Wiley & Sons, Ltd., volume 35, issue 5, pages 400-418, August.
• Bangzhu Zhu & Xuetao Shi & Julien Chevallier & Ping Wang & Yi‐Ming Wei, 2016, "An Adaptive Multiscale Ensemble Learning Paradigm for Nonstationary and Nonlinear Energy Price Time Series Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., volume 35, issue 7, pages 633-651, November.
• Tim Oliver Berg, 2016, "Multivariate Forecasting with BVARs and DSGE Models," Journal of Forecasting, John Wiley & Sons, Ltd., volume 35, issue 8, pages 718-740, December.
• Mark Rempel, 2016, "Improving Overnight Loan Identification in Payments Systems," Journal of Money, Credit and Banking, Blackwell Publishing, volume 48, issue 2-3, pages 549-564, March, DOI: 10.1111/jmcb.12309.
• Jakub Nowotarski & Rafal Weron, 2016, "To combine or not to combine? Recent trends in electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/16/01, Jan.
• Jakub Nowotarski & Rafal Weron, 2016, "On the importance of the long-term seasonal component in day-ahead electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/16/05, Mar.
• Bartosz Uniejewski & Jakub Nowotarski & Rafal Weron, 2016, "Automated variable selection and shrinkage for day-ahead electricity price forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/16/06, Jul.
• Jakub Nowotarski & Rafal Weron, 2016, "Recent advances in electricity price forecasting: A review of probabilistic forecasting," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/16/07, Sep.
• Florian Ziel & Rafal Weron, 2016, "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate models," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/16/08, Oct.
• Pawel Maryniak & Stefan Trueck & Rafal Weron, 2016, "Carbon pricing, forward risk premiums and pass-through rates in Australian electricity futures markets," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/16/10, Nov.
• Han, Xing & Li, Youwei, 2016, "Can Investor Sentiment Be a Momentum Time-Series Predictor? Evidence from China," RIEI Working Papers, Xi'an Jiaotong-Liverpool University, Research Institute for Economic Integration, number 2016-07, Jul, revised 12 Jan 2017.
• Donal Smith, 2016, "The International Impact of Financial Shocks: A Global VAR and Connectedness Measures Approach," Discussion Papers, Department of Economics, University of York, number 16/07, May.
• Oinonen, Sami & Paloviita, Maritta, 2016, "How informative are aggregated inflation expectations? Evidence from the ECB Survey of Professional Forecasters," Bank of Finland Research Discussion Papers, Bank of Finland, number 15/2016.
• Kilponen, Juha & Orjasniemi, Seppo & Ripatti, Antti & Verona, Fabio, 2016, "The Aino 2.0 model," Bank of Finland Research Discussion Papers, Bank of Finland, number 16/2016.
• Abbassi, Puriya & Brownlees, Christian & Hans, Christina & Podlich, Natalia, 2016, "Credit risk interconnectedness: What does the market really know?," Discussion Papers, Deutsche Bundesbank, number 09/2016.
• Abbate, Angela & Marcellino, Massimiliano, 2016, "Point, interval and density forecasts of exchange rates with time-varying parameter models," Discussion Papers, Deutsche Bundesbank, number 19/2016.
• Knüppel, Malte & Vladu, Andreea L., 2016, "Approximating fixed-horizon forecasts using fixed-event forecasts," Discussion Papers, Deutsche Bundesbank, number 28/2016.
• Kurz-Kim, Jeong-Ryeol, 2016, "Macroeconomic now- and forecasting based on the factor error correction model using targeted mixed frequency indicators," Discussion Papers, Deutsche Bundesbank, number 47/2016.
• Meinen, Philipp & Röhe, Oke, 2016, "On measuring uncertainty and its impact on investment: Cross-country evidence from the euro area," Discussion Papers, Deutsche Bundesbank, number 48/2016.
• Ćorić, Ivica, 2016, "Comparison of Multivariate Statistical Analysis and Machine Learning Methods in Retailing: Research Framework Proposition," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2016), Rovinj, Croatia, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 8-9 September 2016".
• Pirschel, Inske, 2016, "Forecasting euro area recessions in real-time," Kiel Working Papers, Kiel Institute for the World Economy, number 2020.
• Brautzsch, Hans-Ulrich & Heinisch, Katja & Holtemöller, Oliver & Loose, Brigitte & Wieschemeyer, Matthias & Zeddies, Götz, 2016, "Die mittelfristige wirtschaftliche Entwicklung in Deutschland für die Jahre 2016 bis 2021," Konjunktur aktuell, Halle Institute for Economic Research (IWH), volume 4, issue 4, pages 155-158.
• Deschermeier, Philipp, 2016, "Die Großstädte im Wachstumsmodus: Stochastische Bevölkerungsprognosen für Berlin, München und Frankfurt am Main bis 2035," IW-Reports, Institut der deutschen Wirtschaft (IW) / German Economic Institute, number 39/2016.
• Deschermeier, Philipp, 2016, "Einfluss der Zuwanderung auf die demografische Entwicklung in Deutschland," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, volume 43, issue 2, pages 21-38, DOI: 10.2373/1864-810X.16-02-03.
• Hanck, Christoph & Prüser, Jan, 2016, "House prices and interest rates: Bayesian evidence from Germany," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 620, DOI: 10.4419/86788722.
• Zharova, Alona & Mihoci, Andrija & Härdle, Wolfgang Karl, 2016, "Academic ranking scales in economics: Prediction and imputation," SFB 649 Discussion Papers, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk, number 2016-020.
• Chen, Ying & Chua, Wee Song & Härdle, Wolfgang Karl, 2016, "Forecasting limit order book liquidity supply-demand curves with functional AutoRegressive dynamics," SFB 649 Discussion Papers, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk, number 2016-025.
• Zieba, Maciej & Härdle, Wolfgang Karl, 2016, "Beta-boosted ensemble for big credit scoring data," SFB 649 Discussion Papers, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk, number 2016-052.
• Winker, Peter & Lütkepohl, Helmut & Staszewska-Bystrova, Anna, 2016, "Calculating Joint Bands for Impulse Response Functions using Highest Density Regions," VfS Annual Conference 2016 (Augsburg): Demographic Change, Verein für Socialpolitik / German Economic Association, number 145537.
• Dovern, Jonas & Manner, Hans, 2016, "Robust Evaluation of Multivariate Density Forecasts," VfS Annual Conference 2016 (Augsburg): Demographic Change, Verein für Socialpolitik / German Economic Association, number 145547.
• Bätje, Fabian & Menkhoff, Lukas, 2016, "Predicting the equity premium via its components," VfS Annual Conference 2016 (Augsburg): Demographic Change, Verein für Socialpolitik / German Economic Association, number 145789.
• Heinisch, Katja, 2016, "A real-time analysis on the importance of hard and soft data for nowcasting German GDP," VfS Annual Conference 2016 (Augsburg): Demographic Change, Verein für Socialpolitik / German Economic Association, number 145864.
• Hartmann, Matthias & Dovern, Jonas, 2016, "Forecast Performance, Disagreement, and Heterogeneous Signal-to-Noise Ratios," VfS Annual Conference 2016 (Augsburg): Demographic Change, Verein für Socialpolitik / German Economic Association, number 145925.
• Niels Haldrup & Oskar Knapik & Tommaso Proietti, 2016, "A generalized exponential time series regression model for electricity prices," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2016-08, Mar.
• Andrew J.G. Cairns & Malene Kallestrup-Lamb & Carsten P.T. Rosenskjold & David Blake & Kevin Dowd, 2016, "Modelling Socio-Economic Differences in the Mortality of Danish Males Using a New Affluence Index," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2016-14, May.
• Robinson Kruse & Christian Leschinski & Michael Will, 2016, "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2016-17, May.
• Lasse Bork & Stig V. Møller & Thomas Q. Pedersen, 2016, "A New Index of Housing Sentiment," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2016-32, Nov.
• Simplice A. Asongu & Jacinta C. Nwachukwu, 2016, "Is the Threat of Foreign Aid Withdrawal an Effective Deterrent to Political Oppression? Evidence from 53 African Countries," Research Africa Network Working Papers, Research Africa Network (RAN), number 16/020, Jan.
• Luis Uzeda, 2016, "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," ANU Working Papers in Economics and Econometrics, Australian National University, College of Business and Economics, School of Economics, number 2016-632, Mar.
• Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016, "Do We Need High Frequency Data to Forecast Variances?," Annals of Economics and Statistics, GENES, issue 123-124, pages 135-174, DOI: 10.15609/annaeconstat2009.123-124.0.
• Peter Diamond & Kashin Konstantin & Gary King & Samir Soneji, 2016, "Correspondence: Scoring Social Security Proposals," Journal of Economic Perspectives, American Economic Association, volume 30, issue 2, pages 245-246, Spring.
• Diana Ioncica & Maria Ioncica & Eva-Cristina Petrescu, 2016, "The Environment, Tourist Transport and the Sustainable Development of Tourism," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, volume 18, issue S10, pages 898-898, November.
• Simplice Asongu & Jacinta C. Nwachukwu, 2016, "Is the Threat of Foreign Aid Withdrawal an Effective Deterrent to Political Oppression? Evidence from 53 African Countries," Working Papers of the African Governance and Development Institute., African Governance and Development Institute., number 16/020, Jan.
• MacDonald, Stephen & Ash, Mark, 2016, "Detecting the Sources of Information Rigidity: Analyzing Forecast Bias and Smoothing in USDA’s Soybean Forecasts," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts, Agricultural and Applied Economics Association, number 235349, DOI: 10.22004/ag.econ.235349.
• Pena-Levano, Luis M & Foster, Kenneth, 2016, "Efficiency gains in commodity forecasting using disaggregated levels versus more aggregated predictions," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts, Agricultural and Applied Economics Association, number 235792, DOI: 10.22004/ag.econ.235792.
• Huang, Wei & Hagerman, Amy & Bessler, David A., 2016, "The Impact of Highly Pathogenic Avian Influenza on Table Egg Prices," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, volume 31, issue 2, pages 1-7, DOI: 10.22004/ag.econ.236294.
• Jo, Jisung & Lusk, Jayson L., 2016, "Predicting Food Prices using Data from Consumer Surveys and Search," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas, Southern Agricultural Economics Association, number 230028, DOI: 10.22004/ag.econ.230028.
• George C?ru?a?u & Alexandru Pîrjan, 2016, "A Seasonal And Monthly Approach For Predicting The Delivered Energy Quantity In A Photovoltaic Power Plant In Romania," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, volume 1, issue 44, pages 198-207.
• Gordon Rausser & David A. Bessler, 2016, "Information Recovery and Causality: A Tribute to George Judge," Annual Review of Resource Economics, Annual Reviews, volume 8, issue 1, pages 7-23, October.
• Jozef Barunik & Lukas Vacha, 2016, "Do co-jumps impact correlations in currency markets?," Papers, arXiv.org, number 1602.05489, Feb, revised Oct 2017.
• Vladimir Filimonov & Guilherme Demos & Didier Sornette, 2016, "Modified Profile Likelihood Inference and Interval Forecast of the Burst of Financial Bubbles," Papers, arXiv.org, number 1602.08258, Feb.
• Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016, "Copula--based Specification of vector MEMs," Papers, arXiv.org, number 1604.01338, Apr.
• Mihaly Ormos & Dusan Timotity, 2016, "Unravelling the Asymmetric Volatility Puzzle: A Novel Explanation of Volatility Through Anchoring," Papers, arXiv.org, number 1606.03597, Jun.