Research classified by Journal of Economic Literature (JEL) codes

1. Forecasting

2017

• Roesel, Felix, 2017, "The causal effect of wrong-hand drive vehicles on road safety," CEPIE Working Papers, Technische Universität Dresden, Center of Public and International Economics (CEPIE), number 15/17.
• Conrad, Christian, 2017, "When does information on forecast variance improve the performance of a combined forecast?," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking, Verein für Socialpolitik / German Economic Association, number 168200.
• Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017, "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking, Verein für Socialpolitik / German Economic Association, number 168206.
• Knüppel, Malte & Krüger, Fabian, 2017, "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking, Verein für Socialpolitik / German Economic Association, number 168294.
• Ksenija Dumicic & Berislav Zmuk & Anita Ceh Casni, 2017, "Evaluating forecasting models for unemployment rates by gender in selected european countries," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 15, issue 1, pages 16-35.
• Christian Menden & Christian R. Proaño, 2017, "Dissecting the financial cycle with dynamic factor models," IMK Working Paper, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute, number 183-2017.
• Christian R. Proaño & Artur Tarassow, 2017, "Evaluating the predicting power of ordered probit models for multiple business cycle phases in the U.S. and Japan," IMK Working Paper, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute, number 188-2017.
• Thorsten Simon & Peter Fabsic & Georg J. Mayr & Nikolaus Umlauf & Achim Zeileis, 2017, "Probabilistic forecasting of thunderstorms in the Eastern Alps," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2017-25, Dec.
• José A. Álvarez-Jareño & Elena Badal-Valero & José Manuel Pavía, 2017, "Using machine learning for financial fraud detection in the accounts of companies investigated for money laundering," Working Papers, Economics Department, Universitat Jaume I, Castellón (Spain), number 2017/07.
• Dr. Sudeshna Ghosh, 2017, "Forecasting Exports of Tea from India : Application of Arima Model," Journal of Commerce and Trade, Society for Advanced Management Studies, volume 12, issue 2, pages 116-129, October.
• Bernard Njindan Iyke & Sin-Yu Ho, 2017, "Monetary uncertainty and the demand for money in Ghana," Journal of Developing Areas, Tennessee State University, College of Business, volume 51, issue 4, pages 1-15, October-D.
• Fizzah Malik & Fangjun Wang & Muhammad Akram Naseem, 2017, "Econometric estimation of banking stocks," Journal of Developing Areas, Tennessee State University, College of Business, volume 51, issue 4, pages 207-237, October-D.
• Jose Cuesta & Gabriel Lara Ibarra, 2017, "Comparing Cross-Survey Micro Imputation and Macro Projection Techniques: Poverty in Post Revolution Tunisia," Journal of Income Distribution, Ad libros publications inc., volume 25, issue 1, pages 1-30, March.
• Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017, "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, volume 237, issue 1, pages 29-62, February, DOI: 10.1515/jbnst-2016-1002.
• William A. Barnett & Liting Su, 2017, "Financial Firm Production Of Inside Monetary And Credit Card Services: An Aggregation Theoretic Approach1," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 201707, Oct, revised Oct 2017.
• Mihály Ormos & Dusán Timotity, 2017, "Expected downside risk and asset prices: characteristics of emerging and developed European markets," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, volume 44, issue 3, pages 529-546, August, DOI: 10.1007/s10663-016-9329-3.
• Francesca Rondina, 2017, "An Econometric Learning Approach to Approximate Expectations in Empirical Macro Models," International Advances in Economic Research, Springer;International Atlantic Economic Society, volume 23, issue 4, pages 437-438, November, DOI: 10.1007/s11294-017-9662-8.
• Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2017, "On exchange-rate movements and gold-price fluctuations: evidence for gold-producing countries from a nonparametric causality-in-quantiles test," International Economics and Economic Policy, Springer, volume 14, issue 4, pages 691-700, October, DOI: 10.1007/s10368-016-0357-z.
• Esteban Fernández-Vázquez & Blanca Moreno, 2017, "Entropy Econometrics for combining regional economic forecasts: A Data-Weighted Prior Estimator," Journal of Geographical Systems, Springer, volume 19, issue 4, pages 349-370, October, DOI: 10.1007/s10109-017-0259-9.
• Rangan Gupta & Anandamayee Majumdar & Mark E. Wohar, 2017, "The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence From a Quantile Predictive Regression Approach," Open Economies Review, Springer, volume 28, issue 1, pages 47-59, February, DOI: 10.1007/s11079-016-9408-x.
• Niels D. Gilbert & Jasper F.M. Jong, 2017, "Do European fiscal rules induce a bias in fiscal forecasts? Evidence from the Stability and Growth Pact," Public Choice, Springer, volume 170, issue 1, pages 1-32, January, DOI: 10.1007/s11127-016-0372-1.
• Jing Xu & Michelle Hallack & Miguel Vazquez, 2017, "Applying a third party access model for China’s gas pipeline network: an independent pipeline operator and congestion rent transfer," Journal of Regulatory Economics, Springer, volume 51, issue 1, pages 72-97, February, DOI: 10.1007/s11149-017-9316-z.
• Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017, "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, volume 49, issue 4, pages 949-971, November, DOI: 10.1007/s11156-016-0613-x.
• Chulwoo Han & Frank C. Park & Jangkoo Kang, 2017, "A geometric treatment of time-varying volatilities," Review of Quantitative Finance and Accounting, Springer, volume 49, issue 4, pages 1121-1141, November, DOI: 10.1007/s11156-017-0618-0.
• Byeongdeuk Jang & Young Se Kim, 2017, "Driving Forces of Inflation Expectations," Korean Economic Review, Korean Economic Association, volume 33, pages 207-237.
• Mihaela Simionescu, 2017, "The Impact Of Immigrants On The UK Economy," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, volume 9, issue 2, pages 31-46, June.
• Mirel-Daniel Simionescu, 2017, "Determinants of Foreign Direct Investments in Bulgaria and Romania in the Context of Recent Economic Crisis," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, volume 3, issue 1, pages 68-72, March.
• Iulian Lolea, 2017, "Where did the GARCH Models Perform Best in Terms of Volatility Forecasting? Equity vs. Commodities Markets," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, volume 3, issue 3, pages 79-86, September.
• Ayse Kabukcuoglu & Enrique Martínez-García & Mehmet Ali Soytas, 2017, "Exploring the Nexus between Inflation and Globalization under Inflation Targeting through the Lens of New Zealand’s Experience," Koç University-TUSIAD Economic Research Forum Working Papers, Koc University-TUSIAD Economic Research Forum, number 1709, Apr.
• Florian Chatagny & Christian Stettler, 2017, "Fiscal Fore casting in a Federal Country: Does Space Matter?," KOF Analysen, KOF Swiss Economic Institute, ETH Zurich, volume 11, issue 4, pages 51-60, December, DOI: 10.3929/ethz-a-005427569.
• Virág, Miklós & Nyitrai, Tamás, 2017, "Magyar vállalkozások felszámolásának előrejelzése pénzügyi mutatóik idősorai alapján
  [Predicting the liquidation of Hungarian firms using a time series of their financial ratios]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), volume 0, issue 3, pages 305-324, DOI: 10.18414/KSZ.2017.3.305.
• Ouael EL JEBARI & Abdelati HAKMAOUI, 2017, "Modeling persistence of volatility in the Moroccan exchange market using a fractionally integrated EGARCH," Turkish Economic Review, KSP Journals, volume 4, issue 4, pages 388-399, December.
• Ron W. NIELSEN, 2017, "Application of differential equations in projecting growth trajectories," Journal of Economics Bibliography, KSP Journals, volume 4, issue 3, pages 203-221, September.
• Evzen Kocenda & Karen Poghosyan, 2017, "Export sophistication: A dynamic panel data approach," KIER Working Papers, Kyoto University, Institute of Economic Research, number 980 Classification-C52; C, Nov.
• Marisol Valencia Cárdenas & Juan Gabriel Vanegas López & Juan Carlos Correa Morales & Jorge Aníbal Restrepo Morales, 2017, "Comparing forecasts for tourism dynamics in Medellín, Colombia," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 86, pages 199-230, Enero - J, DOI: 10.17533/udea.le.n86a08.
• Anh Dinh Minh Nguyen, 2017, "U.K. Monetary Policy under Inflation Targeting," Bank of Lithuania Working Paper Series, Bank of Lithuania, number 41, Mar.
• Michael McAleer & Xiao-Guang Yue, 2017, "Prediction of Gas Concentration Based on the Opposite Degree Algorithm," Journal of Reviews on Global Economics, Lifescience Global, volume 6, pages 154-162.
• Aumnad Phdungsilp, 2017, "Projections of Energy Use and Carbon Emissions for Bangkok,Thailand," Journal of Reviews on Global Economics, Lifescience Global, volume 6, pages 248-257.
• Narongdech Keeratipranon & Phatcharasak Phawanaphinyo, 2017, "Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution," Journal of Reviews on Global Economics, Lifescience Global, volume 6, pages 269-278.
• Lehmann, Robert & Wohlrabe, Klaus, 2017, "Boosting and regional economic forecasting: the case of Germany," Munich Reprints in Economics, University of Munich, Department of Economics, number 49919.
• Magdalena Petrovska & Gani Ramadani & Nikola Naumovski & Biljana Jovanovic, 2017, "Forecasting Macedonian Inflation: Evaluation of different models for short-term forecasting," Working Papers, National Bank of the Republic of North Macedonia, number 2017-06.
• Mohammad Reza Farzanegan & Mai Hassan, 2017, "The impact of economic globalization on the shadow economy in Egypt," MAGKS Papers on Economics, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung), number 201718.
• Radim Farana & Ivo Formánek & Cyril Klimeš & Bogdan Walek, 2017, "System Modelling and Decision Making System Based on Fuzzy Expert System," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, volume 3, issue 2, pages 118-122, DOI: 10.11118/ejobsat.v3i2.103.
• Aleksandra Hałka & Jacek Kotłowski, 2017, "Global or Domestic? Which Shocks Drive Inflation in European Small Open Economies?," Emerging Markets Finance and Trade, Taylor & Francis Journals, volume 53, issue 8, pages 1812-1835, August, DOI: 10.1080/1540496X.2016.1193001.
• Christoph Anders & Max Groneck, 2017, "The Optimal Portfolio of PAYG Benefits and Funded Pensions in Germany," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, volume 73, issue 3, pages 255-291, September, DOI: 10.1628/001522117X14915570953903.
• Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017, "The contribution of jumps to forecasting the density of returns," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17006, Jan, DOI: 10.1016/j.jedc.2020.103853.
• Armagan Tuna Aktuna-Gunes & Okay Gunes, 2017, "Time Use Elasticity of Substitution Estimates Conditional on Working Time Available," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17016, Feb.
• Antoine Kornprobst, 2017, "Winning Investment Strategies Based on Financial Crisis Indicators," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17039, Sep, DOI: 10.48550/arXiv.1709.02701.
• Jørgen Vitting Andersen & Philippe de Peretti, 2017, "New method to detect convergence in simple multi-period market games," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17058, Dec.
• David T. Frazier & Gael M. Martin & Christian P. Robert & Judith Rousseau, 2017, "Asymptotic properties of approximate Bayesian computation," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 12/17.
• Nithi Sopitpongstorn & Param Silvapulle & Jiti Gao, 2017, "Local logit regression for recovery rate," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 19/17.
• Bin Jiang & George Athanasopoulos & Rob J Hyndman & Anastasios Panagiotelis & Farshid Vahid, 2017, "Macroeconomic forecasting for Australia using a large number of predictors," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 2/17.
• Souhaib Ben Taieb & James W. Taylor & Rob J. Hyndman, 2017, "Coherent Probabilistic Forecasts for Hierarchical Time Series," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 3/17.
• David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017, "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 9/17.
• Raïsa Basselier & David de Antonio Liedo & Geert Langenus,, 2017, "Nowcasting real economic activity in the euro area : Assessing the impact of qualitative surveys," Working Paper Research, National Bank of Belgium, number 331, Dec.
• Alessia Paccagnini, 2017, "Forecasting with FAVAR: macroeconomic versus financial factors," NBP Working Papers, Narodowy Bank Polski, number 256.
• Karol Szafranek, 2017, "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers, Narodowy Bank Polski, number 262.
• Hunt Allcott & Matthew Gentzkow, 2017, "Social Media and Fake News in the 2016 Election," NBER Working Papers, National Bureau of Economic Research, Inc, number 23089, Jan.
• Ulrich K. Müller & Mark W. Watson, 2017, "Long-Run Covariability," NBER Working Papers, National Bureau of Economic Research, Inc, number 23186, Feb.
• Jonathan M.V. Davis & Sara B. Heller, 2017, "Rethinking the Benefits of Youth Employment Programs: The Heterogeneous Effects of Summer Jobs," NBER Working Papers, National Bureau of Economic Research, Inc, number 23443, May.
• Andrés F. Barrientos & Alexander Bolton & Tom Balmat & Jerome P. Reiter & John M. de Figueiredo & Ashwin Machanavajjhala & Yan Chen & Charles Kneifel & Mark DeLong, 2017, "A Framework for Sharing Confidential Research Data, Applied to Investigating Differential Pay by Race in the U. S. Government," NBER Working Papers, National Bureau of Economic Research, Inc, number 23534, Jun.
• Yuriy Gorodnichenko & Byoungchan Lee, 2017, "A Note on Variance Decomposition with Local Projections," NBER Working Papers, National Bureau of Economic Research, Inc, number 23998, Nov.
• Hom Nath Gaire, 2017, "Forecasting NEPSE Index: An ARIMA And GARCH Approach," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, volume 29, issue 1, pages 53-68, April.
• Evgenia Vasileva, 2017, "Creating of Something from Nothing. Methodic. (Applying the Principles of Chaos and Complex Systems in a Learning Environment)," Research Papers of UNWE, University of National and World Economy, Sofia, Bulgaria, issue 2, pages 169-186, August, DOI: 10.37075/RP.2017.2.06.
• Maria Chiara Cavalleri & Yvan Guillemette, 2017, "A revised approach to trend employment projections in long-term scenarios," OECD Economics Department Working Papers, OECD Publishing, number 1384, May, DOI: 10.1787/075f0153-en.
• Yvan Guillemette & Alexandre Kopoin & David Turner & Andrea De Mauro, 2017, "A revised approach to productivity convergence in long-term scenarios," OECD Economics Department Working Papers, OECD Publishing, number 1385, May, DOI: 10.1787/0b8947e3-en.
• Alberto Marino & David Morgan & Luca Lorenzoni & Chris James, 2017, "Future trends in health care expenditure: A modelling framework for cross-country forecasts," OECD Health Working Papers, OECD Publishing, number 95, Jun, DOI: 10.1787/247995bb-en.
• Niematallah Elamin & Mototsugu Fukushige, 2017, "Integrating judgment in statistical demand forecasting: An approach to confront uncertainty," Discussion Papers in Economics and Business, Osaka University, Graduate School of Economics, number 17-20, Jul.
• Niematallah Elamin & Mototsugu Fukushige, 2017, "Modeling and Forecasting Hourly Electricity Demand by SARIMAX with Interactions," Discussion Papers in Economics and Business, Osaka University, Graduate School of Economics, number 17-28, Sep.
• Robert A. Cord, 2017, "The London and Cambridge Economic Service: history and contributions," Cambridge Journal of Economics, Cambridge Political Economy Society, volume 41, issue 1, pages 307-326.
• João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017, "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, volume 15, issue 2, pages 247-285.
• Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017, "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, volume 15, issue 4, pages 649-677.
• Michael S. O’Doherty & N. E. Savin & Ashish Tiwari, 2017, "Hedge Fund Replication: A Model Combination Approach," Review of Finance, European Finance Association, volume 21, issue 4, pages 1767-1804.
• Frank J. Fabozzi & Ahmet K. Karagozoglu & Na Wang, 2017, "Effects of Spot Market Short-Sale Constraints on Index Futures Trading," Review of Finance, European Finance Association, volume 21, issue 5, pages 1975-2005.
• Christian Brownlees & Robert F. Engle, 2017, "SRISK: A Conditional Capital Shortfall Measure of Systemic Risk," The Review of Financial Studies, Society for Financial Studies, volume 30, issue 1, pages 48-79.
• Aivaz Kamer Ainur & Jugănaru Mariana & Jugănaru Ion Dănut, 2017, "The Seasonality in the Number of Overnight Stays by Residents in Romania and Bulgaria and Its Ranking in Connection to the EU Average Level," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 2, pages 355-360, December.
• Jugănaru Ion DănuÈ› & Aivaz Kamer Ainur & Jugănaru Mariana, 2017, "Comparative Assessments of the Seasonality in "The Total Number of Overnight Stays" in Romania, Bulgaria and the European Union," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 2, pages 95-100, December.
• Simionescu, Mihaela, 2017, "Forecast Intervals for US/EURO Foreign Exchange Rate || Intervalos de pronóstico para los tipos de cambio US/EURO," 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 23, issue 1, pages 257-271, Junio.
• Alonso, Julio César & Rivera, Andrés Felipe, 2017, "Pronosticando la inflación mensual en Colombia un paso hacia delante: una aproximación "de abajo hacia arriba" || Forecasting the Colombian Monthly Inflation One Step Ahead: A "Bottom to Top" Approach," 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 23, issue 1, pages 98-118, Junio.
• Caro, Norma Patricia & Arias, Ver—nica & Ortiz, Pablo, 2017, "Predicci—n de fracaso en empresas latinoamericanas utilizando el mŽtodo del vecino más cercano para predecir efectos aleatorios en modelos mixtos || Prediction of Failure in Latin-American Companies Using the Nearest-Neighbor Method to Predict Random," 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 24, issue 1, pages 5-24, Diciembre.
• Erdely, Arturo, 2017, "Value at Risk and the Diversification Dogma || Valor en riesgo y el dogma de la diversificación," 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 24, issue 1, pages 209-219, Diciembre.
• Rania Jammazi & Duc Khuong Nguyen, 2017, "Estimating and forecasting portfolio’s Value-at-Risk with wavelet-based extreme value theory: Evidence from crude oil prices and US exchange rates," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, volume 68, issue 11, pages 1352-1362, November, DOI: 10.1057/s41274-016-0133-z.
• Miguel Ataurima Arellano & Erika Collantes & Gabriel Rodriguez, 2017, "Empirical Modeling of Latin American Stock and Forex Markets Returns and Volatility using Markov-Switching GARCH Models," Documentos de Trabajo / Working Papers, Departamento de Economía - Pontificia Universidad Católica del Perú, number 2017-436.
• Laura Liu, 2017, "Density Forecasts in Panel Models: A semiparametric Bayesian Perspective," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 17-006, Apr, revised 28 Apr 2017.
• Francis X. Diebold & Minchul Shin, 2017, "Beating the Simple Average: Egalitarian LASSO for Combining Economic Forecasts," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 17-017, Aug, revised 20 Aug 2017.
• Blazej Mazur, 2017, "Probabilistic predictive analysis of business cycle fluctuations in Polish economy," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, volume 12, issue 3, pages 435-452, September, DOI: 10.24136/eq.v12i3.23.
• Tomasz Berent & Boguslaw Blawat & Marek Dietl & Przemyslaw Krzyk & Radoslaw Rejman, 2017, "Firm's default — new methodological approach and preliminary evidence from Poland," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, volume 12, issue 4, pages 753-773, December, DOI: 10.24136/eq.v12i4.39.
• Tomasz Berent & Boguslaw Blawat & Marek Dietl & Radoslaw Rejman, 2017, "Firms’ Default – from Prediction Accuracy to Informational Capacity of Predictors," Working Papers, Institute of Economic Research, number 158/2017, May, revised May 2017.
• Blazej Mazur, 2017, "Density Forecasts of Polish Industrial Production: a Probabilistic Perspective on Business Cycle Fluctuations," Working Papers, Institute of Economic Research, number 75/2017, May, revised May 2017.
• Nuhu Isah & Abdul Talib Bon, 2017, "Application of Markov Model in Crude Oil Price Forecasting," Traektoriâ Nauki = Path of Science, Altezoro, s.r.o. & Dialog, volume 3, issue 8(25), pages 1007-1012, August, DOI: 10.22178/pos.25-3.
• Ganna Gridina, 2017, "Фінансовий Лізинг: Проблеми Та Перспективи Розвитку В Україні
  [Financial Leasing: Problems and Prospects of Development in Ukraine]," Traektoriâ Nauki = Path of Science, Altezoro, s.r.o. & Dialog, volume 3, issue 9(26), pages 3019-3025, September, DOI: 10.22178/pos.26-2.
• Doojav, Gan-Ochir & Luvsannyam, Davaajargal, 2017, "Forecasting inflation in Mongolia: A dynamic model averaging approach," MPRA Paper, University Library of Munich, Germany, number 102602.
• Fajar, Muhammad & Hartini, Sri, 2017, "Inflation forecasting by hybrid singular spectrum analysis – multilayer perceptrons neural network method, case of Indonesia," MPRA Paper, University Library of Munich, Germany, number 105100, Oct, revised 11 May 2018.
• Ngomba Bodi, Francis Ghislain & Bikai, Landry, 2017, "Prévisions de l’inflation et de la croissance en zone CEMAC
  [Inflation and real growth forecasts in CEMAC zone]," MPRA Paper, University Library of Munich, Germany, number 116433, Dec.
• Coble, David & Pincheira, Pablo, 2017, "Nowcasting Building Permits with Google Trends," MPRA Paper, University Library of Munich, Germany, number 76514, Feb.
• Cobb, Marcus P A, 2017, "Joint Forecast Combination of Macroeconomic Aggregates and Their Components," MPRA Paper, University Library of Munich, Germany, number 76556, Feb.
• Cobb, Marcus P A, 2017, "Aggregate Density Forecasting from Disaggregate Components Using Large VARs," MPRA Paper, University Library of Munich, Germany, number 76849, Feb.
• Pincheira, Pablo, 2017, "A Power Booster Factor for Out-of-Sample Tests of Predictability," MPRA Paper, University Library of Munich, Germany, number 77027, Feb.
• Tóth, Peter, 2017, "Nowcasting Slovak GDP by a Small Dynamic Factor Model," MPRA Paper, University Library of Munich, Germany, number 77245, Feb.
• BLINOV, Sergey, 2017, "Использование Взаимосвязи Между Ввп И Денежной Массой Для Экономического Прогнозирования
  [Economic Forecasting Based on the Relationship between GDP and Real Money Supply]," MPRA Paper, University Library of Munich, Germany, number 77475, Mar.
• Degiannakis, Stavros & Filis, George, 2017, "Forecasting oil prices," MPRA Paper, University Library of Munich, Germany, number 77531, Mar.
• Medel, Carlos A., 2017, "Forecasting Chilean Inflation with the Hybrid New Keynesian Phillips Curve: Globalisation, Combination, and Accuracy," MPRA Paper, University Library of Munich, Germany, number 78439, Apr.
• BLINOV, Sergey, 2017, "Economic Forecasting Based on the Relationship between GDP and Real Money Supply," MPRA Paper, University Library of Munich, Germany, number 78717, Apr.
• Maheu, John M & Song, Yong, 2017, "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper, University Library of Munich, Germany, number 79211, May.
• Pyzhov, Vladislav & Pyzhov, Stanislav, 2017, "Comparison of methods of data mining techniques for the predictive accuracy," MPRA Paper, University Library of Munich, Germany, number 79326, May.
• Polman, Fabian M. & Krijgsman, Cees & Dajani, Karma & Hemminga, Marcus A., 2017, "Modelling a Dutch Pension Fund’s Capital Requirement for Longevity Risk," MPRA Paper, University Library of Munich, Germany, number 79438, May.
• Davis, Brent, 2017, "“Negative Political Advertising: It’s All in the Timing”," MPRA Paper, University Library of Munich, Germany, number 79449, May.
• Bhatt, Vipul & Kishor, Kundan & Marfatia, Hardik, 2017, "Estimating excess sensitivity and habit persistence in consumption using Greenbook forecast as an instrument," MPRA Paper, University Library of Munich, Germany, number 79748, Jun.
• Yang, Bill Huajian, 2017, "Smoothing Algorithms by Constrained Maximum Likelihood," MPRA Paper, University Library of Munich, Germany, number 79911, Jun.
• Yang, Bill Huajian, 2017, "Forward Ordinal Probability Models for Point-in-Time Probability of Default Term Structure," MPRA Paper, University Library of Munich, Germany, number 79934, Sep.
• Bisio, Laura & Moauro, Filippo, 2017, "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper, University Library of Munich, Germany, number 80211, Jul, revised 14 Jul 2017.
• Lindblad, Annika, 2017, "Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility," MPRA Paper, University Library of Munich, Germany, number 80266, Jul.
• Kuusela, Annika & Hännikäinen, Jari, 2017, "What do the shadow rates tell us about future inflation?," MPRA Paper, University Library of Munich, Germany, number 80542, Aug.
• Yang, Bill Huajian, 2017, "Point-in-Time PD Term Structure Models with Loan Credit Quality as a Component," MPRA Paper, University Library of Munich, Germany, number 80641, Aug.
• Nelimarkka, Jaakko, 2017, "Evidence on News Shocks under Information Deficiency," MPRA Paper, University Library of Munich, Germany, number 80850, Aug.
• Fries, Sébastien & Zakoian, Jean-Michel, 2017, "Mixed Causal-Noncausal AR Processes and the Modelling of Explosive Bubbles," MPRA Paper, University Library of Munich, Germany, number 81345, Sep.
• Cobb, Marcus P A, 2017, "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper, University Library of Munich, Germany, number 81585, Sep.
• Raihan, Tasneem, 2017, "Performance of Markov-Switching GARCH Model Forecasting Inflation Uncertainty," MPRA Paper, University Library of Munich, Germany, number 82343, Oct.
• Svetunkov, Ivan & Boylan, John Edward, 2017, "Multiplicative state-space models for intermittent time series," MPRA Paper, University Library of Munich, Germany, number 82487, Nov.
• Hegadekatti, Kartik & S G, Yatish, 2017, "The Programmable Economy: Envisaging an Entire Planned Economic System as a Single Computer through Blockchain Networks," MPRA Paper, University Library of Munich, Germany, number 82831, Mar, revised 16 May 2017.
• Hassett, Kevin & Zhong, Weifeng, 2017, "On the Observational Implications of Knightian Uncertainty," MPRA Paper, University Library of Munich, Germany, number 82998, Oct.
• Brkic, Sabina & Hodzic, Migdat & Dzanic, Enis, 2017, "Fuzzy Logic Model of Soft Data Analysis for Corporate Client Credit Risk Assessment in Commercial Banking," MPRA Paper, University Library of Munich, Germany, number 83028, Nov, revised Nov 2017.
• Bucci, Andrea, 2017, "Forecasting realized volatility: a review," MPRA Paper, University Library of Munich, Germany, number 83232, Dec.
• Zeynalov, Ayaz, 2017, "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper, University Library of Munich, Germany, number 83268, Dec.
• Graefe, Andreas & Armstrong, J. Scott & Jones, Randall J. & Cuzan, Alfred G., 2017, "Assessing the 2016 U.S. Presidential Election Popular Vote Forecasts," MPRA Paper, University Library of Munich, Germany, number 83282, Feb.
• Lee, Seohyun, 2017, "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper, University Library of Munich, Germany, number 83617, Jul.
• Chhorn, Theara & Chaiboonsri, Chukiat, 2017, "Modelling and Forecasting Tourist Arrivals to Cambodia: An Application of ARIMA-GARCH Approach," MPRA Paper, University Library of Munich, Germany, number 83942, Dec, revised 27 Dec 2017.
• Tonnerre, Antoine, 2017, "Merger Simulations in the American Airline Industry," MPRA Paper, University Library of Munich, Germany, number 84395, Oct.
• Nguyen, Duc Khuong & Walther, Thomas, 2017, "Modeling and forecasting commodity market volatility with long-term economic and financial variables," MPRA Paper, University Library of Munich, Germany, number 84464, May, revised Jan 2018.
• Li, Longqing, 2017, "A Comparative Study of GARCH and EVT Model in Modeling Value-at-Risk," MPRA Paper, University Library of Munich, Germany, number 85645, Feb.
• MacDonald, Stephen & Ash, Mark & Cooke, Bryce, 2017, "The Evolution of Inefficiency in USDA’s Forecasts of U.S. and World Soybean Markets," MPRA Paper, University Library of Munich, Germany, number 87545, Sep.
• Degiannakis, Stavros & Filis, George, 2017, "Forecasting oil price realized volatility using information channels from other asset classes," MPRA Paper, University Library of Munich, Germany, number 96276.
• Christina Christou & Rangan Gupta & Fredj Jawadi, 2017, "Does Inequality Help in Forecasting Equity Premium in a Panel of G7 Countries?," Working Papers, University of Pretoria, Department of Economics, number 201720, Mar.
• Christian Pierdzioch & Rangan Gupta, 2017, "Uncertainty and Forecasts of U.S. Recessions," Working Papers, University of Pretoria, Department of Economics, number 201732, May.
• Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017, "Are Multifractal Processes Suited to Forecasting Electricity Price Volatility? Evidence from Australian Intraday Data," Working Papers, University of Pretoria, Department of Economics, number 201739, May.
• Steven F. Koch, 2017, "Does the Equivalence Scale Matter? Equivalence and Out-of-Pocket Payments," Working Papers, University of Pretoria, Department of Economics, number 201746, Jun.
• Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2017, "The Role of Economic Uncertainty in Forecasting Exchange Rate Returns and Realized Volatility: Evidence from Quantile Predictive Regressions," Working Papers, University of Pretoria, Department of Economics, number 201774, Oct.
• Milan Fičura, 2017, "Forecasting Stock Market Realized Variance with Echo State Neural Networks," European Financial and Accounting Journal, Prague University of Economics and Business, volume 2017, issue 3, pages 145-155, DOI: 10.18267/j.efaj.193.
• Nikola Radivojevic & Jelena Jovovic, 2017, "Examining of Determinants of Non-Performing Loans," Prague Economic Papers, Prague University of Economics and Business, volume 2017, issue 3, pages 300-316, DOI: 10.18267/j.pep.615.
• Martina Miskolczi & Jitka Langhamrová, 2017, "Využití metody vícestavové demografie při analýze trhu práce
  [Utilization of Multistate Demography Method at the Labour Market Analysis]," Politická ekonomie, Prague University of Economics and Business, volume 2017, issue 1, pages 82-95, DOI: 10.18267/j.polek.1128.
• Jan Vlachý, 2017, "Analýza daňových systémů středoevropských zemí pomocí statistické simulace
  [An Analysis of Central European Tax Systems Using Statistical Simulation]," Politická ekonomie, Prague University of Economics and Business, volume 2017, issue 4, pages 410-423, DOI: 10.18267/j.polek.1152.
• Angus Deaton & Nancy Cartwright, 2017, "Understanding and misunderstanding randomized controlled trials," Working Papers, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing., number 2017-10, Oct.
• Antoine A. Djogbenou, 2017, "Model Selection In Factor-augmented Regressions With Estimated Factors," Working Paper, Economics Department, Queen's University, number 1391, Oct.
• David Reifschneider & Peter Tulip, 2017, "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors: The Federal Reserve's Approach," RBA Research Discussion Papers, Reserve Bank of Australia, number rdp2017-01, Feb.
• Alain Kabundi & Asi Mbelu, 2017, "Estimating a timevarying financial conditions index for South Africa," Working Papers, South African Reserve Bank, number 8008, Sep.
• Michael P Clements & Ana Beatriz Galvao, 2017, "Data Revisions and Real-time Probabilistic Forecasting of Macroeconomic Variables," ICMA Centre Discussion Papers in Finance, Henley Business School, University of Reading, number icma-dp2017-01, Jan.
• Emese Lazar & Ning Zhang, 2017, "Model Risk of Expected Shortfall," ICMA Centre Discussion Papers in Finance, Henley Business School, University of Reading, number icma-dp2017-10, Nov.
• Piergiorgio Alessandri & Haroon Mumtaz, 2017, "Online Appendix to "Financial conditions and density forecasts for US output and inflation"," Online Appendices, Review of Economic Dynamics, number 14-103.
• Piergiorgio Alessandri & Haroon Mumtaz, 2017, "Code and data files for "Financial conditions and density forecasts for US output and inflation"," Computer Codes, Review of Economic Dynamics, number 14-103, revised .
• Piergiorgio Alessandri & Haroon Mumtaz, 2017, "Financial conditions and density forecasts for US output and inflation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, volume 24, pages 66-78, March, DOI: 10.1016/j.red.2017.01.003.
• Nina Boyarchenko & Domenico Giannone & Tobias Adrian, 2017, "Vulnerable Growth," 2017 Meeting Papers, Society for Economic Dynamics, number 1317.
• Simon M. Potter & Giorgio Topa & Wilbert van den Klaauv, 2017, "The Advantages of Probabilistic Survey Questions," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, volume 9, issue 1, pages 1-32, June.
• Gustavo Rodriguez & Jorge Davalos, 2017, "El Potencial de Comercio del Acuerdo Trans-Pacifico para el Peru, un enfoque Gravitacional," Revista Internacional de Gestión del Conocimiento y la Tecnología (GECONTEC), Revista Internacional de Gestión del Conocimiento y la Tecnología (GECONTEC), volume 5, issue 2, pages 93-107, October, DOI: 10.5281/zenodo.7507073.
• Fornaro, Paolo & Luomaranta, Henri & Saarinen, Lauri, 2017, "Nowcasting Finnish Turnover Indexes Using Firm-Level Data," ETLA Working Papers, The Research Institute of the Finnish Economy, number 46, Jan.
• Elettra Agliardi & Thomas Alexopoulos & Christian Cech, 2017, "On the relationship between GHGs and Global Temperature Anomalies: Multi-level rolling analysis and Copula calibration," Working Paper series, Rimini Centre for Economic Analysis, number 17-05, Feb.
• Siddhartha Vadlamudi, 2017, "Stock Market Prediction using Machine Learning: A Systematic Literature Review," American Journal of Trade and Policy, Asian Business Consortium, volume 4, issue 3, pages 123-128.
• Sebastian Fossati, 2017, "Testing for State-Dependent Predictive Ability," Working Papers, University of Alberta, Department of Economics, number 2017-09, Sep.
• Dean Fantazzini & Erik Nigmatullin & Vera Sukhanovskaya & Sergey Ivliev, 2017, "Everything you always wanted to know about bitcoin modelling but were afraid to ask. Part 2," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), volume 45, pages 5-28.
• Artem Aganin, 2017, "Forecast comparison of volatility models on Russian stock market," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), volume 48, pages 63-84.
• Valerii Makarov & Albert Bakhtizin & Elena Sushko & Alina Ageeva, 2017, "Simulation of the socio-economic system of the Eurasian continent using the agent-based models," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), volume 48, pages 122-139.
• Mehdi Behrad-Amin & Gholamreza Zamanian & Marziyeh Esfandiari, 2017, "The Impact of Oil Shocks on Foreign Trade in Iran: The Role of Inflation Targeting Policy," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, volume 4, issue 1, pages 1-28.
• Emilian DOBRESCU, 2017, "Modelling an Emergent Economy and Parameter Instability Problem," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 2, pages 5-28, June.
• Emrah ALTUN & Morad ALIZADEH & Gamze OZEL & Hüseyin TATLIDIL & Najmieh MAKSAYI, 2017, "Forecasting Value-At-Risk With Two-Step Method: Garch-Exponentiated Odd Log-Logistic Normal Model," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 4, pages 97-115, December.
• Akaev, Askar A. (Акаев, Аскар) & Sarygulov, Askar I. (Сарыгулов, Аскар) & Sokolov, Valentin N. (Соколов, Валентин), 2017, "On the Possibility of Dynamic Optimization of Output by Changing the Level of Income Inequality
  [О Динамической Оптимизации Роста Ввп Путем Изменения Уровня Неравенства Доходов]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, volume 6, pages 8-23, December.
• Randall W. Jackson, 2017, "Technical Document for Computing Coal Dependent Employment Estimates," Working Papers, Regional Research Institute, West Virginia University, number Technical Document 2017-0, Apr.
• Madalina-Gabriela ANGHEL & Ana CARP & Marian SFETCU & Stefan Gabriel DUMBRAVA, 2017, "Econometric Model For Analyzing The Influence Of Factors On Final Consumption," Romanian Statistical Review Supplement, Romanian Statistical Review, volume 65, issue 10, pages 123-131, October.
• Madalina-Gabriela ANGHEL & Constantin ANGHELACHE & Georgiana NITA & Gyorgy BODO, 2017, "The Main Concepts Of The Eqcm Model And Data-Based Dvar Systems," Romanian Statistical Review Supplement, Romanian Statistical Review, volume 65, issue 7, pages 132-140, July.
• Constantin ANGHELACHE & Madalina-Gabriela ANGHEL & Zoica NICOLA & Radu STOICA, 2017, "Correction Of Equilibrum And Autoregressive Models Used In The Macroeconomic Forecast," Romanian Statistical Review Supplement, Romanian Statistical Review, volume 65, issue 7, pages 92-104, July.
• Julia Mortera & A. Philip Dawid, 2017, "A Note on Prediction Markets," Departmental Working Papers of Economics - University 'Roma Tre', Department of Economics - University Roma Tre, number 0215, Feb.
• Loretta Mastroeni & Pierluigi Vellucci, 2017, "“Chaos” In Energy And Commodity Markets: A Controversial Matter," Departmental Working Papers of Economics - University 'Roma Tre', Department of Economics - University Roma Tre, number 0218, May.
• Davide De Gaetano, 2017, "Forecasting With Garch Models Under Structural Breaks: An Approach Based On Combinations Across Estimation Windows," Departmental Working Papers of Economics - University 'Roma Tre', Department of Economics - University Roma Tre, number 0219, May.
• Vincenzo Atella & Federico Belotti & Ludovico Carrino & Andrea Piano Mortari, 2017, "The future of Long Term Care in Europe. An investigation using a dynamic microsimulation model," CEIS Research Paper, Tor Vergata University, CEIS, number 405, May, revised 08 May 2017.
• Tommaso Proietti & Alessandro Giovannelli, 2017, "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CEIS Research Paper, Tor Vergata University, CEIS, number 410, Jul, revised 19 Jul 2017.
• Tommaso Proietti & Niels Haldrup & Oskar Knapik, 2017, "Spikes and Memory in (Nord Pool) Electricity Price Spot Prices," CEIS Research Paper, Tor Vergata University, CEIS, number 422, Dec, revised 18 Dec 2017.
• Qing Zhou & Robert Faff, 2017, "The complementary role of cross-sectional and time-series information in forecasting stock returns," Australian Journal of Management, Australian School of Business, volume 42, issue 1, pages 113-139, February, DOI: 10.1177/0312896215575888.
• Aviral Kumar Tiwari & Phouphet Kyophilavong, 2017, "Exchange Rates and International Reserves in India," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, volume 18, issue 1, pages 76-93, March, DOI: 10.1177/1391561416684237.
• Santos, André Alves Portela & Ferreira, Alexandre R., 2017, "On the choice of covariance specifications for portfolio selection problems," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, volume 37, issue 1, May.
• Fida Hussain & Asif Mahmood, 2017, "Predicting Output Growth and Inflation in Pakistan: The Role of Yield Spread," SBP Research Bulletin, State Bank of Pakistan, Research Department, volume 13, pages 53-76.
• Fida Hussain & Asif Mahmood, 2017, "Predicting Inflation and Output in Pakistan: The Role of Yield Spread," SBP Working Paper Series, State Bank of Pakistan, Research Department, number 93, Oct.
• Witold Orzeszko, 2017, "Nonparametric prediction of nonlinear time series. A Monte Carlo study," Proceedings of International Academic Conferences, International Institute of Social and Economic Sciences, number 5107220, May.
• Jiri Prochazka & Matej Camaj, 2017, "Modelling the number of road accidents of uninsured drivers and their severity," Proceedings of International Academic Conferences, International Institute of Social and Economic Sciences, number 5408040, Jul.
• Taku Yamamoto & Hiroaki Chigira, 2017, "Forecasting Mortality: Some Recent Developments," Proceedings of International Academic Conferences, International Institute of Social and Economic Sciences, number 5808110, Oct.
• Michał Chojnowski & Piotr Dybka, 2017, "Is Exchange Rate Moody? Forecasting Exchange Rate with Google Trends Data," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, volume 2, issue 1, pages 1-21, June, DOI: 10.33119/ERFIN.2017.2.1.1.
• Giovanni De Luca & Giampiero M. Gallo & Danilo Carità, 2017, "Evaluating Combined Forecasts for Realized Volatility Using Asymmetric Loss Functions," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, volume 2, issue 2, pages 99-111, December, DOI: 10.33119/ERFIN.2017.2.2.3.
• Waldemar Florczak, 2017, "Wpływ starzejącego się społeczeństwa na długookresowy wzrost gospodarczy Polski do roku 2050," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 5, pages 73-104.
• Mihaela Simionescu, 2017, "Bayesian Forecast Intervals for Inflation and Unemployment Rate in Romania," 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-2017-06, May, revised May 2017.