Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2018

• Seika Akemura & Daizo Kojima, 2018, "Japan’s Long-Term Care Cost Projections: Comparison with the European Commission Ageing Report," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, volume 14, issue 4, pages 541-562, July.
• Dominique Guégan & Matteo Iacopini, 2018, "Nonparameteric forecasting of multivariate probability density functions," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 18012, Mar.
• Jørgen Vitting Andersen & Philippe de Peretti, 2018, "New method to detect convergence in simple multi-period market games with infinite large strategy spaces," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 18038, Dec.
• David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Brendan P.M. McCabe, 2018, "Approximate Bayesian forecasting," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 2/18.
• GONÇALVES, Sílvia & PERRON, Benoit, 2018, "Bootstrapping factor models with cross sectional dependence," Cahiers de recherche, Universite de Montreal, Departement de sciences economiques, number 2018-07.
• Sílvia GONÇALVES & Benoit PERRON, 2018, "Bootstrapping Factor Models With Cross Sectional Dependence," Cahiers de recherche, Centre interuniversitaire de recherche en économie quantitative, CIREQ, number 10-2018.
• Eric Ghysels & Leonardo Iania & Jonas Striaukas, 2018, "Quantile-based Inflation Risk Models," Working Paper Research, National Bank of Belgium, number 349, Oct.
• Witold Orzeszko, 2018, "Prognozowanie indeksu WIG za pomocą jądrowych estymatorów funkcji regresji," Bank i Kredyt, Narodowy Bank Polski, volume 49, issue 3, pages 253-288.
• Atsushi Inoue & Barbara Rossi, 2018, "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Chapters, National Bureau of Economic Research, Inc, "NBER International Seminar on Macroeconomics 2018".
• Patrick Bajari & Victor Chernozhukov & Ali Hortaçsu & Junichi Suzuki, 2018, "The Impact of Big Data on Firm Performance: An Empirical Investigation," NBER Working Papers, National Bureau of Economic Research, Inc, number 24334, Feb.
• Steven F. Lehrer & Tian Xie, 2018, "The Bigger Picture: Combining Econometrics with Analytics Improve Forecasts of Movie Success," NBER Working Papers, National Bureau of Economic Research, Inc, number 24755, Jun.
• Ş. Pelin Akyol & Kala Krishna & Jinwen Wang, 2018, "Taking PISA Seriously: How Accurate are Low Stakes Exams?," NBER Working Papers, National Bureau of Economic Research, Inc, number 24930, Aug.
• Francis X. Diebold & Minchul Shin, 2018, "Machine Learning for Regularized Survey Forecast Combination: Partially-Egalitarian Lasso and its Derivatives," NBER Working Papers, National Bureau of Economic Research, Inc, number 24967, Aug.
• Atsushi Inoue & Barbara Rossi, 2018, "The Effects of Conventional and Unconventional Monetary Policy on Exchange Rates," NBER Working Papers, National Bureau of Economic Research, Inc, number 25021, Sep.
• Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2018, "Forecasting with Dynamic Panel Data Models," NBER Working Papers, National Bureau of Economic Research, Inc, number 25102, Sep.
• Soumya Bhadury & Sanjib Pohit & Robert C. M. Beyer, 2018, "A new approach to nowcast Indian Gross Value Added," NCAER Working Papers, National Council of Applied Economic Research, number 115, Jun.
• Erika Vanessa Alves da Silva & Nathália da Silva Oliveira & Roberto Tatiwa Ferreira & Cristiano da Costa da Silva, 2018, "Média móvel e a Curva de Phillips: previsões para a taxa de inflação em uma amostra de países desenvolvidos e em desenvolvimento [Moving Average and the Phillips Curve: forecasts for the inflation rat," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), volume 28, issue 2, pages 499-521, May-Augus.
• Chakraborty, Lekha & Sinha, Darshy, 2018, "Has Fiscal Rule changed the Fiscal Marksmanship of Union Government?," Working Papers, National Institute of Public Finance and Policy, number 18/234, Jun.
• Clément Bortoli & Stéphanie Combes & Thomas Renault, 2018, "Nowcasting GDP Growth by Reading the Newspapers," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 17-33, DOI: https://doi.org/10.24187/ecostat.20.
• François Robin, 2018, "Use of Google Trends Data in Banque de France Monthly Retail Trade Surveys," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 35-63, DOI: https://doi.org/10.24187/ecostat.20.
• Pete Richardson, 2018, "Nowcasting and the Use of Big Data in Short-Term Macroeconomic Forecasting: A Critical Review," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 65-87, DOI: https://doi.org/10.24187/ecostat.20.
• Gary Koop & Stuart McIntyre & James Mitchell, 2018, "UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers, Economic Statistics Centre of Excellence (ESCoE), number ESCoE DP-2018-07, Jun.
• George Kapetanios & Fotis Papailias, 2018, "Big Data & Macroeconomic Nowcasting: Methodological Review," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers, Economic Statistics Centre of Excellence (ESCoE), number ESCoE DP-2018-12, Jul.
• Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2018, "Regional Output Growth in the United Kingdom: More Timely and Higher Frequency Estimates, 1970-2017," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers, Economic Statistics Centre of Excellence (ESCoE), number ESCoE DP-2018-14, Nov.
• Anthony Garratt & Shaun P. Vahey & Ynuyi Zhang, 2018, "Real-time Forecast Combinations for the Oil Price," National Institute of Economic and Social Research (NIESR) Discussion Papers, National Institute of Economic and Social Research, number 494, Oct.
• Aleksandra Riedl & Julia Wörz, 2018, "A simple approach to nowcasting GDP growth in CESEE economies," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/18, pages 56-74.
• Tommaso Proietti & Alessandro Giovannelli, 2018, "A Durbin–Levinson regularized estimator of high-dimensional autocovariance matrices," Biometrika, Biometrika Trust, volume 105, issue 4, pages 783-795.
• Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018, "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Oxford University Press, volume 16, issue 1, pages 1-33.
• Piotr Kokoszka & Hong Miao & Matthew Reimherr & Bahaeddine Taoufik, 2018, "Dynamic Functional Regression with Application to the Cross-section of Returns," Journal of Financial Econometrics, Oxford University Press, volume 16, issue 3, pages 461-485.
• Martin M Andreasen & Jesús Fernández-Villaverde & Juan F Rubio-Ramírez, 2018, "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications," The Review of Economic Studies, Review of Economic Studies Ltd, volume 85, issue 1, pages 1-49.
• Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018, "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, volume 31, issue 7, pages 2729-2773.
• Vintu Denis & Negotei Ioana-Alina, 2018, "Analysis of Financial Stability: The Construction of a New Composite Financial Stability Index for Euro Area," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 1, pages 264-270, July.
• El Jebari, Ouael & Hakmaoui, Abdelati, 2018, "GARCH Family Models vs EWMA: Which is the Best Model to Forecast Volatility of the Moroccan Stock Exchange Market? || Modelos de la familia GARCH vs EWMA: ¿cuál es el mejor modelo para pronosticar la ," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, volume 26, issue 1, pages 237-249, Diciembre.
• Max Schreder, 2018, "Volatility forecasting in practice: exploratory evidence from European hedge funds," Journal of Asset Management, Palgrave Macmillan, volume 19, issue 4, pages 245-258, July, DOI: 10.1057/s41260-018-0082-y.
• Emilio Zanetti Chini, 2018, "Forecaster’s utility and forecasts coherence," DEM Working Papers Series, University of Pavia, Department of Economics and Management, number 145, Jan.
• Santiago Javier Fucci & Martín Grandes, 2018, "Inflación y crecimiento a largo plazo: malas predicciones, ¿buenos modelos?," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, volume 41, issue 82, pages 83-123.
• Jaka Sriyana, 2018, "Inflationary effects of fiscal and monetary policies in Indonesia," Business and Economic Horizons (BEH), Prague Development Center, volume 14, issue 3, pages 674-688, June, DOI: 10.15208/beh.2018.47.
• Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018, "On the Comparison of Interval Forecasts," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 18-013, Aug, revised 02 Aug 2018.
• Francis X. Diebold & Minchul Shin, 2018, "Machine Learning for Regularized Survey Forecast Combination: Partially Egalitarian Lasso and its Derivatives," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 18-014, Aug, revised 17 Aug 2018.
• Marcin Chlebus, 2018, "One-day-ahead forecast of state of turbulence based on today's economic situation," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, volume 13, issue 3, pages 357-389, September, DOI: 10.24136/eq.2018.018.
• Miskolczi, Panna, 2018, "Comparison of Risk Calculation Based on Historical Simulation and the Copula Function," Public Finance Quarterly, Corvinus University of Budapest, volume 63, issue 1, pages 80-95.
• Malik, Afia, 2018, "Fuel Demand in Pakistan's TRansport Sector," MPRA Paper, University Library of Munich, Germany, number 103455, Jun.
• Vîntu, Denis & Negotei, Ioana-Alina, 2018, "Analysis of Financial Stability: The Construction of a New Composite Financial Stability Index for Euro Area," MPRA Paper, University Library of Munich, Germany, number 107625, Jun, revised 15 Apr 2018.
• Bespalova, Olga, 2018, "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper, University Library of Munich, Germany, number 117706, Mar.
• Maheu, John M & Yang, Qiao & Song, Yong, 2018, "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper, University Library of Munich, Germany, number 83779.
• Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018, "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper, University Library of Munich, Germany, number 83893, Jan.
• GRITLI, Mohamed Ilyes, 2018, "Quel avenir du dinar tunisien face à l'euro ? Prévision avec le modèle ARIMA
  [What future of the Tunisian dinar against the euro? Prediction with the ARIMA model]," MPRA Paper, University Library of Munich, Germany, number 83937, Jan.
• Ghouse, Ghulam & Khan, Saud Ahmed & Rehman, Atiq Ur, 2018, "ARDL model as a remedy for spurious regression: problems, performance and prospectus," MPRA Paper, University Library of Munich, Germany, number 83973, Jan.
• Maheu, John M & Song, Yong & Yang, Qiao, 2018, "Oil Price Shocks and Economic Growth: The Volatility Link," MPRA Paper, University Library of Munich, Germany, number 83999, Jan.
• Sabaj, Ernil & Kahveci, Mustafa, 2018, "Forecasting tax revenues in an emerging economy: The case of Albania," MPRA Paper, University Library of Munich, Germany, number 84404, Feb.
• Corradini, Riccardo, 2018, "A set of state space models at an high disaggregation level to forecast Italian Industrial Production," MPRA Paper, University Library of Munich, Germany, number 84558, Feb, revised 12 Feb 2018.
• Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2018, "Does a financial accelerator improve forecasts during financial crises?: Evidence from Japan with Prediction Pool Methods," MPRA Paper, University Library of Munich, Germany, number 85523, Mar.
• Lee, David, 2018, "Pricing Financial Derivatives Subject to Counterparty Risk and Credit Value Adjustment," MPRA Paper, University Library of Munich, Germany, number 85575, Mar.
• Jackson, Emerson Abraham, 2018, "Comparison between Static and Dynamic Forecast in Autoregressive Integrated Moving Average for Seasonally Adjusted Headline Consumer Price Index," MPRA Paper, University Library of Munich, Germany, number 86180, Jan, revised 12 Apr 2018.
• Check, Adam J. & Nolan, Anna K. & Schipper, Tyler C., 2018, "Forecasting GDP: Do Revisions Matter?," MPRA Paper, University Library of Munich, Germany, number 86194, Apr.
• Fingleton, Bernard, 2018, "Exploring Brexit with dynamic spatial panel models : some possible outcomes for employment across the EU regions," MPRA Paper, University Library of Munich, Germany, number 86553, May.
• Raputsoane, Leroi, 2018, "Quantifying economic recovery from the recent global financial crisis," MPRA Paper, University Library of Munich, Germany, number 87410, Jun.
• Brkic, Sabina & Hodzic, Migdat & Dzanic, Enis, 2018, "Soft Data Modeling via Type 2 Fuzzy Distributions for Corporate Credit Risk Assessment in Commercial Banking," MPRA Paper, University Library of Munich, Germany, number 87652, Jun.
• Koop, Gary & Korobilis, Dimitris, 2018, "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper, University Library of Munich, Germany, number 87972, Jul.
• Spelta, Alessandro & Pecora, Nicolò & Flori, Andrea & Pammolli, Fabio, 2018, "Transition drivers and crisis signaling in stock markets," MPRA Paper, University Library of Munich, Germany, number 88127, Jul.
• Kapur, Muneesh, 2018, "Macroeconomic Policies and Transmission Dynamics in India," MPRA Paper, University Library of Munich, Germany, number 88566, Aug.
• Cobb, Marcus P A, 2018, "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper, University Library of Munich, Germany, number 88593, Aug.
• Nyoni, Thabani, 2018, "Modeling and Forecasting Naira / USD Exchange Rate In Nigeria: a Box - Jenkins ARIMA approach," MPRA Paper, University Library of Munich, Germany, number 88622, Aug, revised 19 Aug 2018.
• Pincheira, Pablo & Hardy, Nicolas, 2018, "The predictive relationship between exchange rate expectations and base metal prices," MPRA Paper, University Library of Munich, Germany, number 89423, Oct.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2018, "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," MPRA Paper, University Library of Munich, Germany, number 89449, Oct.
• Asante Gyamerah, Samuel & Ngare, Philip & Ikpe, Dennis, 2018, "A Levy Regime-Switching Temperature Dynamics Model for Weather Derivatives," MPRA Paper, University Library of Munich, Germany, number 89680, May, revised 10 Jul 2018.
• bailek, Alexandra, 2018, "Economic Impact Analysis of Hospital Readmission Rate and Service Quality Using Machine Learning," MPRA Paper, University Library of Munich, Germany, number 89875, Oct.
• Havranek, Tomas & Zeynalov, Ayaz, 2018, "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper, University Library of Munich, Germany, number 90205, Nov.
• Pincheira, Pablo & Neumann, Federico, 2018, "Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile," MPRA Paper, University Library of Munich, Germany, number 90432, Dec.
• Nyoni, Thabani & Nathaniel, Solomon Prince, 2018, "Modeling rates of inflation in Nigeria: an application of ARMA, ARIMA and GARCH models," MPRA Paper, University Library of Munich, Germany, number 91351, Nov.
• Aliyu, Shehu Usman Rano & Aminu, Abubakar Wambai, 2018, "Economic regimes and stock market performance in Nigeria: Evidence from regime switching model," MPRA Paper, University Library of Munich, Germany, number 91430, Jul, revised 03 Oct 2018.
• Spiliotis, Evangelos & Petropoulos, Fotios & Kourentzes, Nikolaos & Assimakopoulos, Vassilios, 2018, "Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption," MPRA Paper, University Library of Munich, Germany, number 91762, Jul.
• Gerlach, Richard & Naimoli, Antonio & Storti, Giuseppe, 2018, "Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting," MPRA Paper, University Library of Munich, Germany, number 94289, Jan.
• Fries, Sébastien, 2018, "Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds," MPRA Paper, University Library of Munich, Germany, number 97353, May, revised Nov 2019.
• Rangan Gupta & Christian Pierdzioch & Andrew J. Vivian & Mark E. Wohar, 2018, "The Predictive Value of Inequality Measures for Stock Returns: An Analysis of Long-Span UK Data Using Quantile Random Forests," Working Papers, University of Pretoria, Department of Economics, number 201809, Feb.
• Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2018, "Is There a Role for Uncertainty in Forecasting Output Growth in OECD Countries? Evidence from a Time Varying Parameter-Panel Vector Autoregressive Model," Working Papers, University of Pretoria, Department of Economics, number 201823, Mar.
• Goodness Aye, 2018, "Causality between Economic Policy Uncertainty and Real Housing Returns in Emerging Economies: A Cross-Sample Validation Approach," Working Papers, University of Pretoria, Department of Economics, number 201827, May.
• Rangan Gupta, 2018, "Manager Sentiment and Stock Market Volatility," Working Papers, University of Pretoria, Department of Economics, number 201853, Aug.
• Rangan Gupta & Chi Keung Marco Lau & Wendy Nyakabawo, 2018, "Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment," Working Papers, University of Pretoria, Department of Economics, number 201866, Oct.
• Christian Pierdzioch & Rangan Gupta & Hossein Hassani & Emmanuel Silva, 2018, "Forecasting Changes of Economic Inequality: A Boosting Approach," Working Papers, University of Pretoria, Department of Economics, number 201868, Oct.
• Hossein Hassani & Mohammad Reza Yeganegi & Juncal Cunado & Rangan Gupta, 2018, "Forecasting Interest Rate Volatility of the United Kingdom: Evidence from over 150 Years of Data," Working Papers, University of Pretoria, Department of Economics, number 201873, Nov.
• Milan Bašta, 2018, "Time series forecasting with a prior wavelet-based denoising step," Acta Oeconomica Pragensia, Prague University of Economics and Business, volume 2018, issue 1, pages 5-24, DOI: 10.18267/j.aop.592.
• Michal Kováč, 2018, "Approaches to stress testing for regulatory purposes by institutions using the IRBA method
  [Konstrukce stres testu pro regulatorní účely modelem VEC]," Český finanční a účetní časopis, Prague University of Economics and Business, volume 2018, issue 2, pages 43-59, DOI: 10.18267/j.cfuc.512.
• Michal Kováč, 2018, "Comparison of stress testing models for regulatory purposes by institutions using the IRBA method
  [Porovnání stres test modelů pro regulatorní účely institucí využívajících IRBA metodu]," Český finanční a účetní časopis, Prague University of Economics and Business, volume 2018, issue 3, pages 41-56, DOI: 10.18267/j.cfuc.516.
• Madalina Ecaterina Popescu & Victor Dragotă, 2018, "What Do Post-Communist Countries Have in Common When Predicting Financial Distress?," Prague Economic Papers, Prague University of Economics and Business, volume 2018, issue 6, pages 637-653, DOI: 10.18267/j.pep.664.
• Matúš Mihalovič, 2018, "Využitie skóringových modelov pri predikcii defaultu ekonomických subjektov v Slovenskej republike
  [Applicability of Scoring Models in Firms' Default Prediction. The Case of Slovakia]," Politická ekonomie, Prague University of Economics and Business, volume 2018, issue 6, pages 689-708, DOI: 10.18267/j.polek.1226.
• Daniel Kosiorowski & Dominik Mielczarek & Jerzy P. Rydlewski, 2018, "Forecasting of a Hierarchical Functional Time Series on Example of Macromodel for the Day and Night Air Pollution in Silesia Region - A Critical Overview," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, volume 10, issue 1, pages 53-73, March.
• Alasdair Brown & James Reade & Leighton Vaughan Williams, 2018, "Prediction Markets and Poll Releases: When Are Prices Most Informative?," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2018-02, Mar.
• Anttonen, Jetro, 2018, "Nowcasting the Unemployment Rate in the EU with Seasonal BVAR and Google Search Data," ETLA Working Papers, The Research Institute of the Finnish Economy, number 62, Nov.
• Alain-Philippe Fortin & Jean-Guy Simonato & Georges Dionne, 2018, "Forecasting Expected Shortfall: Should we use a Multivariate Model for Stock Market Factors?," Working Papers, HEC Montreal, Canada Research Chair in Risk Management, number 18-4, Jun.
• Amedeo AMATO, 2018, "Some International Financial Contributions: Empirical Results and Policy Implications," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, volume 71, issue 2, pages 1-1.
• Imad A. Moosa & John Vaz, 2018, "Direct and Indirect Forecasting of Cross Exchange Rates," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, volume 71, issue 2, pages 173-190.
• Yesuf M. Awel, 2018, "Forecasting GDP Growth: Application of Autoregressive Integrated Moving Average Model," Empirical Economic Review, Department of Economics and Statistics, Dr Hassan Murad School of Management, University of Management and Technology, Lahore, volume 1, issue 2, pages 1-16.
• Sabbah Gueddoudj, 2018, "Financial Variables as Predictive Indicators of the Luxembourg GDP Growth," Empirical Economic Review, Department of Economics and Statistics, Dr Hassan Murad School of Management, University of Management and Technology, Lahore, volume 1, issue 2, pages 49-62.
• Behnoosh Sadat Aghayan & Javid Bahrami & Esfandiar Jahangard, 2018, "Forecasting Iran's Economy Inflation with DSGE-VAR Model (Theory and Technique)," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, volume 5, issue 2, pages 149-176.
• Wali ULLAH & Khadija Malik BARI, 2018, "The Term Structure of Government Bond Yields in an Emerging Market," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 3, pages 5-28, September.
• Mircea BAHNA & Cosmin-Octavian CEPOI & Bogdan Andrei DUMITRESCU & Virgil DAMIAN, 2018, "Estimating the Price Impact of Market Orders on the Bucharest Stock Exchange," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 4, pages 120-133, December.
• Sinelnikova-Muryleva, Elena V. (Синельникова-Мурылева, Елена) & Gorshkova, Taisija G. (Горшкова, Таисия) & Makeeva, Natalja V. (Макеева, Наталья), 2018, "Default forecasting in the Russian banking sector
  [Прогнозирование Дефолтов В Российском Банковском Секторе]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, volume 2, pages 8-27, April.
• Angelica BĂCESCU-CĂRBUNARU, 2018, "Global Demographic Pressures and Management of Natural Resources – Foresights about the Future of Mankind," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, volume 19, issue 1, pages 40-53, March.
• Luca Brugnolini, 2018, "About Local Projection Impulse Response Function Reliability," CEIS Research Paper, Tor Vergata University, CEIS, number 440, Jun, revised 09 Jun 2018.
• Sumana Chaudhuri & Shovan Ray & Ganesh-Kumar, 2018, "Integrated Model of Computable General Equilibrium and Social Cost Benefit Analysis of an Indian Oil Refinery: Future Projections and Macroeconomic Effects," Journal of Infrastructure Development, India Development Foundation, volume 10, issue 1-2, pages 96-125, June, DOI: 10.1177/0974930618813749.
• Thomas Conefrey & Gerard O'Reilly & Graeme Walsh, 2018, "Modelling External Shocks in a Small Open Economy: The Case of Ireland," National Institute Economic Review, National Institute of Economic and Social Research, volume 244, issue 1, pages 56-63, May.
• Shahzad Ahmad & Waqas Ahmed & Ehsan Choudhri & Farooq Pasha & Abdullah Tahir, 2018, "A Model for Forecasting and Policy Analysis in Pakistan: The Role of Government and External Sectors," SBP Working Paper Series, State Bank of Pakistan, Research Department, number 95, Feb.
• Fida Hussain & Kalim Hayder & Muhammad Rehman, 2018, "Nowcasting LSM Growth in Pakistan," SBP Working Paper Series, State Bank of Pakistan, Research Department, number 98, May.
• Krzysztof Echaust, 2018, "Conditional VaR using GARCH-EVT approach with optimal tail selection," Proceedings of Economics and Finance Conferences, International Institute of Social and Economic Sciences, number 6910151, Oct.
• Michal Mares & Martin Slany, 2018, "Early Warning Indicator of financial crises for V4 Countries," Proceedings of Economics and Finance Conferences, International Institute of Social and Economic Sciences, number 6910382, Oct.
• Łukasz Lipiński & Michał Bernardelli, 2018, "Anonimowość w Internecie – identyfikacja płci użytkowników na podstawie historii odwiedzanych stron internetowych," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 53, pages 147-162.
• Bo Feng & Mark Partridge & Mark Rembert, 2018, "The Perils of Modelling How Migration Responds to Climate Change," Advances in Spatial Science, Springer, chapter 0, in: Roger R. Stough & Karima Kourtit & Peter Nijkamp & Uwe Blien, "Modelling Aging and Migration Effects on Spatial Labor Markets", DOI: 10.1007/978-3-319-68563-2_4.
• A. M. Angulo & J. Mur & F. J. Trívez, 2018, "Measuring resilience to economic shocks: an application to Spain," The Annals of Regional Science, Springer;Western Regional Science Association, volume 60, issue 2, pages 349-373, March, DOI: 10.1007/s00168-017-0815-8.
• Masato Yamazaki & Atsushi Koike & Yoshinori Sone, 2018, "A Heuristic Approach to the Estimation of Key Parameters for a Monthly, Recursive, Dynamic CGE Model," Economics of Disasters and Climate Change, Springer, volume 2, issue 3, pages 283-301, October, DOI: 10.1007/s41885-018-0027-4.
• Wen-Hsien Liu & Shu-Shih Weng, 2018, "On predicting the semiconductor industry cycle: a Bayesian model averaging approach," Empirical Economics, Springer, volume 54, issue 2, pages 673-703, March, DOI: 10.1007/s00181-016-1198-x.
• Fabio Bacchini & Maria Elena Bontempi & Roberto Golinelli & Cecilia Jona-Lasinio, 2018, "Short- and long-run heterogeneous investment dynamics," Empirical Economics, Springer, volume 54, issue 2, pages 343-378, March, DOI: 10.1007/s00181-016-1211-4.
• Katja Heinisch & Rolf Scheufele, 2018, "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, volume 54, issue 2, pages 705-745, March, DOI: 10.1007/s00181-016-1218-x.
• Sami Ben Jabeur & Youssef Fahmi, 2018, "Forecasting financial distress for French firms: a comparative study," Empirical Economics, Springer, volume 54, issue 3, pages 1173-1186, May, DOI: 10.1007/s00181-017-1246-1.
• Angelos T. Vouldis & Dimitrios P. Louzis, 2018, "Leading indicators of non-performing loans in Greece: the information content of macro-, micro- and bank-specific variables," Empirical Economics, Springer, volume 54, issue 3, pages 1187-1214, May, DOI: 10.1007/s00181-017-1247-0.
• Inske Pirschel & Maik H. Wolters, 2018, "Forecasting with large datasets: compressing information before, during or after the estimation?," Empirical Economics, Springer, volume 55, issue 2, pages 573-596, September, DOI: 10.1007/s00181-017-1286-6.
• Matteo Luciani & Madhavi Pundit & Arief Ramayandi & Giovanni Veronese, 2018, "Nowcasting Indonesia," Empirical Economics, Springer, volume 55, issue 2, pages 597-619, September, DOI: 10.1007/s00181-017-1288-4.
• Konstantin A. Kholodilin & Claus Michelsen & Dirk Ulbricht, 2018, "Speculative price bubbles in urban housing markets," Empirical Economics, Springer, volume 55, issue 4, pages 1957-1983, December, DOI: 10.1007/s00181-017-1347-x.
• C. Orsenigo & C. Vercellis, 2018, "Anthropogenic influence on global warming for effective cost-benefit analysis: a machine learning perspective," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, volume 45, issue 3, pages 425-442, September, DOI: 10.1007/s40812-018-0092-2.
• Manhal Ali & Reza Salehnejad & Mohaimen Mansur, 2018, "Hospital heterogeneity: what drives the quality of health care," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), volume 19, issue 3, pages 385-408, April, DOI: 10.1007/s10198-017-0891-9.
• Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018, "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 14, issue 1, pages 1-46, April, DOI: 10.1007/s41549-017-0022-9.
• Fritz Breuss, 2018, "Would DSGE Models Have Predicted the Great Recession in Austria?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 14, issue 1, pages 105-126, April, DOI: 10.1007/s41549-018-0025-1.
• Pablo Duarte & Bernd Süssmuth, 2018, "Implementing an Approximate Dynamic Factor Model to Nowcast GDP Using Sensitivity Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 14, issue 1, pages 127-141, April, DOI: 10.1007/s41549-018-0026-0.
• Alain Galli, 2018, "Which Indicators Matter? Analyzing the Swiss Business Cycle Using a Large-Scale Mixed-Frequency Dynamic Factor Model," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 14, issue 2, pages 179-218, November, DOI: 10.1007/s41549-018-0030-4.
• KhasadYahu ZarBabal & Jocelyn Evans, 2018, "Does wall street affect main street? examining potential spillovers from investor stock market sentiment to personal consumption expenditures," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 42, issue 2, pages 293-314, April, DOI: 10.1007/s12197-017-9394-x.
• Vugar Ahmadov & Salman Huseynov & Shaig Adigozalov & Fuad Mammadov & Vugar Rahimov, 2018, "Forecasting inflation in post-oil boom years: A case for regime switches?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, volume 42, issue 2, pages 369-385, April, DOI: 10.1007/s12197-017-9410-1.
• Muhammad Aamir Khan & Naseeb Zada & Kakali Mukhopadhyay, 2018, "Economic implications of the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) on Pakistan: a CGE approach," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), volume 7, issue 1, pages 1-20, December, DOI: 10.1186/s40008-017-0103-x.
• M. L. Bertotti & G. Modanese, 2018, "Mathematical models describing the effects of different tax evasion behaviors," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, volume 13, issue 2, pages 351-363, July, DOI: 10.1007/s11403-016-0185-9.
• David Court & Benjamin Gillen & Jordi McKenzie & Charles R. Plott, 2018, "Two information aggregation mechanisms for predicting the opening weekend box office revenues of films: Boxoffice Prophecy and Guess of Guesses," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), volume 65, issue 1, pages 25-54, January, DOI: 10.1007/s00199-017-1036-1.
• Bo Carlsson & Gunnar Eliasson & Karolin Sjöö, 2018, "The Swedish industrial support program of the 1970s revisited," Journal of Evolutionary Economics, Springer, volume 28, issue 4, pages 805-835, September, DOI: 10.1007/s00191-018-0581-5.
• Sangeeta Das & Dipankor Coondoo, 2018, "Is PMI Useful in Quarterly GDP Growth Forecasts for India? An Exploratory Note," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 16, issue 1, pages 199-207, December, DOI: 10.1007/s40953-017-0116-1.
• Dilip Kumar, 2018, "Modeling and Forecasting Unbiased Extreme Value Volatility Estimator in Presence of Leverage Effect," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 16, issue 2, pages 313-335, June, DOI: 10.1007/s40953-017-0085-4.
• Zouheir Mighri, 2018, "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), volume 16, issue 2, pages 427-473, June, DOI: 10.1007/s40953-017-0088-1.
• Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018, "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, volume 46, issue C, pages 111-129, DOI: 10.1016/j.jempfin.2017.12.008.
• Sander, Magnus, 2018, "Market timing over the business cycle," Journal of Empirical Finance, Elsevier, volume 46, issue C, pages 130-145, DOI: 10.1016/j.jempfin.2017.12.002.
• Chen, Ying & Han, Qian & Niu, Linlin, 2018, "Forecasting the term structure of option implied volatility: The power of an adaptive method," Journal of Empirical Finance, Elsevier, volume 49, issue C, pages 157-177, DOI: 10.1016/j.jempfin.2018.09.006.
• Zhu, Bangzhu & Ye, Shunxin & Wang, Ping & He, Kaijian & Zhang, Tao & Wei, Yi-Ming, 2018, "A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting," Energy Economics, Elsevier, volume 70, issue C, pages 143-157, DOI: 10.1016/j.eneco.2017.12.030.
• Wang, Delu & Wang, Yadong & Song, Xuefeng & Liu, Yun, 2018, "Coal overcapacity in China: Multiscale analysis and prediction," Energy Economics, Elsevier, volume 70, issue C, pages 244-257, DOI: 10.1016/j.eneco.2018.01.004.
• Salisu, Afees A. & Ademuyiwa, Idris & Isah, Kazeem O., 2018, "Revisiting the forecasting accuracy of Phillips curve: The role of oil price," Energy Economics, Elsevier, volume 70, issue C, pages 334-356, DOI: 10.1016/j.eneco.2018.01.018.
• Özmen, Ayşe & Yılmaz, Yavuz & Weber, Gerhard-Wilhelm, 2018, "Natural gas consumption forecast with MARS and CMARS models for residential users," Energy Economics, Elsevier, volume 70, issue C, pages 357-381, DOI: 10.1016/j.eneco.2018.01.022.
• Ziel, Florian & Weron, Rafał, 2018, "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Energy Economics, Elsevier, volume 70, issue C, pages 396-420, DOI: 10.1016/j.eneco.2017.12.016.
• Zhang, Yaojie & Ma, Feng & Shi, Benshan & Huang, Dengshi, 2018, "Forecasting the prices of crude oil: An iterated combination approach," Energy Economics, Elsevier, volume 70, issue C, pages 472-483, DOI: 10.1016/j.eneco.2018.01.027.
• Presno, María José & Landajo, Manuel & Fernández González, Paula, 2018, "Stochastic convergence in per capita CO2 emissions. An approach from nonlinear stationarity analysis," Energy Economics, Elsevier, volume 70, issue C, pages 563-581, DOI: 10.1016/j.eneco.2015.10.001.
• Chai, Jian & Xing, Li-Min & Zhou, Xiao-Yang & Zhang, Zhe George & Li, Jie-Xun, 2018, "Forecasting the WTI crude oil price by a hybrid-refined method," Energy Economics, Elsevier, volume 71, issue C, pages 114-127, DOI: 10.1016/j.eneco.2018.02.004.
• Wang, Minggang & Tian, Lixin & Zhou, Peng, 2018, "A novel approach for oil price forecasting based on data fluctuation network," Energy Economics, Elsevier, volume 71, issue C, pages 201-212, DOI: 10.1016/j.eneco.2018.02.021.
• Sephton, Peter & Mann, Janelle, 2018, "Gold and crude oil prices after the great moderation," Energy Economics, Elsevier, volume 71, issue C, pages 273-281, DOI: 10.1016/j.eneco.2018.02.022.
• Pan, Zhiyuan & Wang, Qing & Wang, Yudong & Yang, Li, 2018, "Forecasting U.S. real GDP using oil prices: A time-varying parameter MIDAS model," Energy Economics, Elsevier, volume 72, issue C, pages 177-187, DOI: 10.1016/j.eneco.2018.04.008.
• Liu, Jing & Ma, Feng & Yang, Ke & Zhang, Yaojie, 2018, "Forecasting the oil futures price volatility: Large jumps and small jumps," Energy Economics, Elsevier, volume 72, issue C, pages 321-330, DOI: 10.1016/j.eneco.2018.04.023.
• Cheng, Fangzheng & Fan, Tijun & Fan, Dandan & Li, Shanling, 2018, "The prediction of oil price turning points with log-periodic power law and multi-population genetic algorithm," Energy Economics, Elsevier, volume 72, issue C, pages 341-355, DOI: 10.1016/j.eneco.2018.03.038.
• Hahn, Warren J. & DiLellio, James A. & Dyer, James S., 2018, "Risk premia in commodity price forecasts and their impact on valuation," Energy Economics, Elsevier, volume 72, issue C, pages 393-403, DOI: 10.1016/j.eneco.2018.04.018.
• Uddin, Gazi Salah & Rahman, Md Lutfur & Shahzad, Syed Jawad Hussain & Rehman, Mobeen Ur, 2018, "Supply and demand driven oil price changes and their non-linear impact on precious metal returns: A Markov regime switching approach," Energy Economics, Elsevier, volume 73, issue C, pages 108-121, DOI: 10.1016/j.eneco.2018.05.024.
• Jiao, Lei & Liao, Yin & Zhou, Qing, 2018, "Predicting carbon market risk using information from macroeconomic fundamentals," Energy Economics, Elsevier, volume 73, issue C, pages 212-227, DOI: 10.1016/j.eneco.2018.05.008.
• Drachal, Krzysztof, 2018, "Comparison between Bayesian and information-theoretic model averaging: Fossil fuels prices example," Energy Economics, Elsevier, volume 74, issue C, pages 208-251, DOI: 10.1016/j.eneco.2018.04.043.
• Gong, Xu & Lin, Boqiang, 2018, "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, volume 74, issue C, pages 370-386, DOI: 10.1016/j.eneco.2018.06.005.
• Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018, "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, volume 74, issue C, pages 628-643, DOI: 10.1016/j.eneco.2018.07.009.
• Smith, Michael Stanley & Shively, Thomas S., 2018, "Econometric modeling of regional electricity spot prices in the Australian market," Energy Economics, Elsevier, volume 74, issue C, pages 886-903, DOI: 10.1016/j.eneco.2018.07.013.
• Liu, Li & Wang, Yudong & Yang, Li, 2018, "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, volume 75, issue C, pages 193-205, DOI: 10.1016/j.eneco.2018.08.010.
• Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018, "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, volume 75, issue C, pages 400-409, DOI: 10.1016/j.eneco.2018.09.006.
• Poblete-Cazenave, Miguel & Pachauri, Shonali, 2018, "A structural model of cooking fuel choices in developing countries," Energy Economics, Elsevier, volume 75, issue C, pages 449-463, DOI: 10.1016/j.eneco.2018.09.003.
• Prakash Ranjan, Ravi & Bhattachharyya, Malay, 2018, "Does investor attention to energy stocks exhibit power law?," Energy Economics, Elsevier, volume 75, issue C, pages 573-582, DOI: 10.1016/j.eneco.2018.09.005.
• Funk, Christoph, 2018, "Forecasting the real price of oil - Time-variation and forecast combination," Energy Economics, Elsevier, volume 76, issue C, pages 288-302, DOI: 10.1016/j.eneco.2018.04.016.
• Degiannakis, Stavros & Filis, George, 2018, "Forecasting oil prices: High-frequency financial data are indeed useful," Energy Economics, Elsevier, volume 76, issue C, pages 388-402, DOI: 10.1016/j.eneco.2018.10.026.
• Zhang, Jin & Li, Pujiang & Zhao, Guochang, 2018, "Is power generation really the gold measure of the Chinese economy? A conceptual and empirical assessment," Energy Policy, Elsevier, volume 121, issue C, pages 211-216, DOI: 10.1016/j.enpol.2018.06.030.
• Lyócsa, Štefan & Molnár, Peter, 2018, "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, volume 155, issue C, pages 462-473, DOI: 10.1016/j.energy.2018.04.194.
• de Albuquerquemello, Vinícius Phillipe & de Medeiros, Rennan Kertlly & da Nóbrega Besarria, Cássio & Maia, Sinézio Fernandes, 2018, "Forecasting crude oil price: Does exist an optimal econometric model?," Energy, Elsevier, volume 155, issue C, pages 578-591, DOI: 10.1016/j.energy.2018.04.187.
• Elamin, Niematallah & Fukushige, Mototsugu, 2018, "Modeling and forecasting hourly electricity demand by SARIMAX with interactions," Energy, Elsevier, volume 165, issue PB, pages 257-268, DOI: 10.1016/j.energy.2018.09.157.
• Antonakakis, Nikolaos & Chang, Tsangyao & Cunado, Juncal & Gupta, Rangan, 2018, "The relationship between commodity markets and commodity mutual funds: A wavelet-based analysis," Finance Research Letters, Elsevier, volume 24, issue C, pages 1-9, DOI: 10.1016/j.frl.2017.03.005.
• Gupta, Rangan & Mwamba, John W. Muteba & Wohar, Mark E., 2018, "The role of partisan conflict in forecasting the U.S. equity premium: A nonparametric approach," Finance Research Letters, Elsevier, volume 25, issue C, pages 131-136, DOI: 10.1016/j.frl.2017.10.023.
• Ping, Yuan & Li, Rui, 2018, "Forecasting realized volatility based on the truncated two-scales realized volatility estimator (TTSRV): Evidence from China's stock market," Finance Research Letters, Elsevier, volume 25, issue C, pages 222-229, DOI: 10.1016/j.frl.2017.10.028.
• van der Merwe, C.J. & Heyman, D. & de Wet, T., 2018, "Approximating risk-free curves in sparse data environments," Finance Research Letters, Elsevier, volume 26, issue C, pages 112-118, DOI: 10.1016/j.frl.2017.12.016.
• Kim, Donghan & Kim, Jun Sik & Seo, Sung Won, 2018, "What options to trade and when: Evidence from seasoned equity offerings," Journal of Financial Markets, Elsevier, volume 37, issue C, pages 70-96, DOI: 10.1016/j.finmar.2016.09.006.
• Barunik, Jozef & Vacha, Lukas, 2018, "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, volume 37, issue C, pages 97-119, DOI: 10.1016/j.finmar.2017.11.004.
• Lin, Qi, 2018, "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, volume 38, issue C, pages 103-123, DOI: 10.1016/j.finmar.2017.09.003.
• Baltas, Nick & Karyampas, Dimitrios, 2018, "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, volume 38, issue C, pages 83-102, DOI: 10.1016/j.finmar.2017.11.002.
• Papanikolaou, Nikolaos I., 2018, "To be bailed out or to be left to fail? A dynamic competing risks hazard analysis," Journal of Financial Stability, Elsevier, volume 34, issue C, pages 61-85, DOI: 10.1016/j.jfs.2017.11.005.
• Kupiec, Paul H., 2018, "On the accuracy of alternative approaches for calibrating bank stress test models," Journal of Financial Stability, Elsevier, volume 38, issue C, pages 132-146, DOI: 10.1016/j.jfs.2018.08.001.
• Jåstad, Eirik Ogner & Mustapha, Walid Fayez & Bolkesjø, Torjus Folsland & Trømborg, Erik & Solberg, Birger, 2018, "Modelling of uncertainty in the economic development of the Norwegian forest sector," Journal of Forest Economics, Elsevier, volume 32, issue C, pages 106-115, DOI: 10.1016/j.jfe.2018.04.005.
• Bruszas, Sandy & Kaschützke, Barbara & Maurer, Raimond & Siegelin, Ivonne, 2018, "Unisex pricing of German participating life annuities—Boon or bane for customer and insurance company?," Insurance: Mathematics and Economics, Elsevier, volume 78, issue C, pages 230-245, DOI: 10.1016/j.insmatheco.2017.09.012.
• Börger, Matthias & Schupp, Johannes, 2018, "Modeling trend processes in parametric mortality models," Insurance: Mathematics and Economics, Elsevier, volume 78, issue C, pages 369-380, DOI: 10.1016/j.insmatheco.2017.09.024.
• Doan, Bao & Papageorgiou, Nicolas & Reeves, Jonathan J. & Sherris, Michael, 2018, "Portfolio management with targeted constant market volatility," Insurance: Mathematics and Economics, Elsevier, volume 83, issue C, pages 134-147, DOI: 10.1016/j.insmatheco.2018.09.010.
• Franses, Philip Hans & Janssens, Eva, 2018, "Inflation in Africa, 1960–2015," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 57, issue C, pages 261-292, DOI: 10.1016/j.intfin.2018.09.005.
• Knüppel, Malte, 2018, "Forecast-error-based estimation of forecast uncertainty when the horizon is increased," International Journal of Forecasting, Elsevier, volume 34, issue 1, pages 105-116, DOI: 10.1016/j.ijforecast.2017.08.006.
• Clements, Michael P., 2018, "Are macroeconomic density forecasts informative?," International Journal of Forecasting, Elsevier, volume 34, issue 2, pages 181-198, DOI: 10.1016/j.ijforecast.2017.10.004.
• Smeekes, Stephan & Wijler, Etienne, 2018, "Macroeconomic forecasting using penalized regression methods," International Journal of Forecasting, Elsevier, volume 34, issue 3, pages 408-430, DOI: 10.1016/j.ijforecast.2018.01.001.
• Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018, "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, volume 34, issue 4, pages 774-787, DOI: 10.1016/j.ijforecast.2018.06.004.
• Berge, Travis J., 2018, "Understanding survey-based inflation expectations," International Journal of Forecasting, Elsevier, volume 34, issue 4, pages 788-801, DOI: 10.1016/j.ijforecast.2018.07.003.
• Herrera, R. & Clements, A.E., 2018, "Point process models for extreme returns: Harnessing implied volatility," Journal of Banking & Finance, Elsevier, volume 88, issue C, pages 161-175, DOI: 10.1016/j.jbankfin.2017.12.001.
• Grigoli, Francesco & Mansilla, Mario & Saldías, Martín, 2018, "Macro-financial linkages and heterogeneous non-performing loans projections: An application to Ecuador," Journal of Banking & Finance, Elsevier, volume 97, issue C, pages 130-141, DOI: 10.1016/j.jbankfin.2018.09.023.
• Badarinza, Cristian & Ramadorai, Tarun, 2018, "Home away from home? Foreign demand and London house prices," Journal of Financial Economics, Elsevier, volume 130, issue 3, pages 532-555, DOI: 10.1016/j.jfineco.2018.07.010.
• Foroni, Claudia & Ravazzolo, Francesco & Sadaba, Barbara, 2018, "Assessing the predictive ability of sovereign default risk on exchange rate returns," Journal of International Money and Finance, Elsevier, volume 81, issue C, pages 242-264, DOI: 10.1016/j.jimonfin.2017.12.001.
• Amat, Christophe & Michalski, Tomasz & Stoltz, Gilles, 2018, "Fundamentals and exchange rate forecastability with simple machine learning methods," Journal of International Money and Finance, Elsevier, volume 88, issue C, pages 1-24, DOI: 10.1016/j.jimonfin.2018.06.003.
• Ismailov, Adilzhan & Rossi, Barbara, 2018, "Uncertainty and deviations from uncovered interest rate parity," Journal of International Money and Finance, Elsevier, volume 88, issue C, pages 242-259, DOI: 10.1016/j.jimonfin.2017.07.012.
• Proaño, Christian R. & Tarassow, Artur, 2018, "Evaluating the predicting power of ordered probit models for multiple business cycle phases in the U.S. and Japan," Journal of the Japanese and International Economies, Elsevier, volume 50, issue C, pages 60-71, DOI: 10.1016/j.jjie.2018.08.002.
• Debnath, Deepayan & Babu, Suresh & Ghosh, Parijat & Helmar, Michael, 2018, "The impact of India’s food security policy on domestic and international rice market," Journal of Policy Modeling, Elsevier, volume 40, issue 2, pages 265-283, DOI: 10.1016/j.jpolmod.2017.08.006.
• Chen, Junyi & Kibriya, Shahriar & Bessler, David & Price, Edwin, 2018, "The relationship between conflict events and commodity prices in Sudan," Journal of Policy Modeling, Elsevier, volume 40, issue 4, pages 663-684, DOI: 10.1016/j.jpolmod.2018.01.014.