Research classified by Journal of Economic Literature (JEL) codes

1. Nowcasting
2. Bayesian Vector autoregressions (BVARs)
3. Dynamic Factor Models

2018

• Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018, "Econometrics and Machine Learning," Post-Print, HAL, number hal-02163979, DOI: 10.24187/ecostat.2018.505d.1970.
• Guillaume Chevillon & Alain Hecq & Sébastien Laurent, 2018, "Generating Univariate Fractional Integration within a Large VAR(1)," Working Papers, HAL, number halshs-01944588, Dec.
• Baum, Christopher F & Lööf, Hans & Perez, Luis & Stephan, Andreas, 2018, "Offshoring and Innovation Capabilities: Evidence from Swedish Manufacturing," Working Paper Series in Economics and Institutions of Innovation, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies, number 469, Jun.
• Trapp, Andrew C. & Teytelboym, Alexander & Martinello, Alessandro & Andersson, Tommy & Ahani, Narges, 2018, "Placement Optimization in Refugee Resettlement," Working Papers, Lund University, Department of Economics, number 2018:23, Oct, revised 20 Mar 2020.
• Ilya Kuzminov & Pavel Bakhtin & Elena Khabirova & Maxim Kotsemir & Alina Lavrynenko, 2018, "Mapping the Radical Innovations in Food Industry: A Text Mining Study," HSE Working papers, National Research University Higher School of Economics, number WP BRP 80/STI/2018.
• Ilya Kuzminov & Pavel Bakhtin & Elena Khabirova & Irina V. Loginova, 2018, "Detecting and Validating Global Technology Trends Using Quantitative and Expert-Based Foresight Techniques," HSE Working papers, National Research University Higher School of Economics, number WP BRP 82/STI/2018.
• Ilya Kuzminov & Irina Loginova & Elena Khabirova, 2018, "Stress Scenario Development: Global Challenges For The Russian Agricultural Sector," HSE Working papers, National Research University Higher School of Economics, number WP BRP 88/STI/2018.
• Michael Vogt & Oliver Linton, 2018, "Multiscale clustering of nonparametric regression curves," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP08/18, Jan.
• Koen Jochmans & Martin Weidner, 2018, "Fixed-effect regressions on network data," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP44/18, Jul.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018, "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201806, Mar, revised Mar 2018.
• Montserrat Guillen & Ana M. Pérez-Marín & Mercedes Ayuso & Jens Perch Nielsen, 2018, "“Exposure to risk increases the excess of zero accident claims frequency in automobile insurance”," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201810, May, revised May 2018.
• Susana Santos & Tanya Araújo, 2018, "The network of inter-industry flows in a SAM framework," Working Papers REM, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa, number 2018/40, May.
• Headey, Bruce & Wagner, Gert G., 2018, "Alternative Values-Based 'Recipes' for Life Satisfaction: German Results with an Australian Replication," IZA Discussion Papers, IZA Network @ LISER, number 11818, Sep.
• Dynarski, Susan & Jacob, Brian A. & Kreisman, Daniel, 2018, "How Important Are Fixed Effects and Time Trends in Estimating Returns to Schooling? Evidence from a Replication of Jacobson, Lalonde and Sullivan, 2005," IZA Discussion Papers, IZA Network @ LISER, number 11935, Nov.
• Jonathan Hersh & Matthew Harding, 2018, "Big Data in economics," IZA World of Labor, LISER, pages 451-451, September.
• Kevin Momanyi, 2018, "A Structural Model of The Demand For Telecare," 2018 Papers, Job Market Papers, number pmo1170, Jul.
• James Lo, 2018, "Dynamic ideal point estimation for the European Parliament, 1980–2009," Public Choice, Springer, volume 176, issue 1, pages 229-246, July, DOI: 10.1007/s11127-018-0551-3.
• Maurizio Daniele & Winfried Pohlmeier & Aygul Zagidullina, 2018, "Sparse Approximate Factor Estimation for High-Dimensional Covariance Matrices," Working Paper Series of the Department of Economics, University of Konstanz, Department of Economics, University of Konstanz, number 2018-07, Oct.
• Dominik Bertsche & Ralf Brüggemann & Christian Kascha, 2018, "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz, Department of Economics, University of Konstanz, number 2018-08, Dec.
• Matthias Weber & Jonas Striaukas & Martin Schumacher & Harald Binder, 2018, "Network constrained covariate coefficient and connection sign estimation," Bank of Lithuania Discussion Paper Series, Bank of Lithuania, number 8, Jun.
• Ian Borg & Germano Ruisi, 2018, "Forecasting using Bayesian VARs: A Benchmark for STREAM," CBM Working Papers, Central Bank of Malta, number WP/04/2018.
• Priyanga Dilini Talagala & Rob J Hyndman & Kate Smith-Miles & Sevvandi Kandanaarachchi & Mario A Munoz, 2018, "Anomaly detection in streaming nonstationary temporal data," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 4/18.
• Dominic Coey & Bradley Larsen & Kane Sweeney & Caio Waisman, 2018, "The Simple Empirics of Optimal Online Auctions," NBER Working Papers, National Bureau of Economic Research, Inc, number 24698, Jun.
• 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.
• Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018, "Empirical Asset Pricing via Machine Learning," NBER Working Papers, National Bureau of Economic Research, Inc, number 25398, Dec.
• Benjamin Sakarovitch & Marie-Pierre de Bellefon & Pauline Givord & Maarten Vanhoof, 2018, "Estimating the Residential Population from Mobile Phone Data, an Initial Exploration," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 109-132, DOI: https://doi.org/10.24187/ecostat.20.
• Lorie Dudoignon & Fabienne Le Sager & Aurélie Vanheuverzwyn, 2018, "Big Data and Audience Measurement: A Marriage of Convenience?," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 133-146, DOI: https://doi.org/10.24187/ecostat.20.
• Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018, "Econometrics and Machine Learning," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 147-169, DOI: https://doi.org/10.24187/ecostat.20.
• 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.
• Paul Labonne & Martin Weale, 2018, "Temporal disaggregation of overlapping noisy quarterly data using state space models: Estimation of monthly business sector output from Value Added Tax data in the UK," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers, Economic Statistics Centre of Excellence (ESCoE), number ESCoE DP-2018-18, Dec.
• 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.
• Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018, "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, volume 133, issue 1, pages 237-293.
• Oprea Simona Vasilica & Bâra Adela & Elefterescu LuminiÈ›a, 2018, "Decision Support System Design for Photovoltaic Systems Operation and Maintenance by using Big Data Technologies," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 1, pages 104-110, July.
• Bâra Adela & Oprea Simona Vasilica & PreoÈ›escu Dan, 2018, "Data Management for Photovoltaic Power Plants Operation and Maintenance," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 1, pages 70-75, July.
• David Troncoso-Ponce, 2018, "Estimation of competing risks duration models with unobserved heterogeneity using hsmlogit," Working Papers, Universidad Pablo de Olavide, Department of Economics, number 18.03, Feb.
• Garanasvili, Antanina & Kazimierczak, Michal & Lazaridis, George, 2018, "The Use of Intellectual Property Right Bundles by Firms in Copyright Intensive Industries," MPRA Paper, University Library of Munich, Germany, number 109493, revised 2021.
• Tierney, Heather L.R. & Kim, Jiyoon (June) & Nazarov, Zafar, 2018, "The Effects of Temporal Aggregation on Search Engine Data," MPRA Paper, University Library of Munich, Germany, number 84474, Jan.
• Chakraborty, Lekha S & Singh, Yadawendra, 2018, "Fiscal Policy, as the “Employer of Last Resort”: Impact of Direct fiscal transfer (MGNREGA) on Labour Force Participation Rates in India," MPRA Paper, University Library of Munich, Germany, number 85225.
• Verstappen, Ksenia, 2018, "Economics of big data: review of best papers for January 2018," MPRA Paper, University Library of Munich, Germany, number 85520, Feb.
• 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.
• Ogunlesi, Ayodeji, 2018, "Agricultural Productivity, Fiscal and Trade Policies Nexus in Sub-Saharan Africa: A Panel Structural Vector Error Correction Model Analysis," MPRA Paper, University Library of Munich, Germany, number 90202, Oct.
• Aleksandra Halka & Grzegorz Szafranski, 2018, "What Common Factors are Driving Inflation in CEE Countries?," Prague Economic Papers, Prague University of Economics and Business, volume 2018, issue 2, pages 131-148, DOI: 10.18267/j.pep.640.
• Jan Hanousek & Štěpán Jurajda, 2018, "Názvy společností a jejich vliv na výkonnost firem
  [Corporate Names and Performance]," Politická ekonomie, Prague University of Economics and Business, volume 2018, issue 6, pages 671-688, DOI: 10.18267/j.polek.1218.
• Chantawit Tantasith & Nasha Ananchotikul & Chatlada Chotanakarn & Vorada Limjaroenrat & Runchana Pongsaparn, 2018, "The Impact of LTV policy on Bank Lending: Evidence from Disaggregate Housing Loan Data," PIER Discussion Papers, Puey Ungphakorn Institute for Economic Research, number 90, Jul.
• 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.
• Abdessamad SAIDI & Sara BENAZZI & Jawad EL OTHMANI, 2018, "Capital humain au Maroc: Evaluation fondée sur le revenu de la vie entière," Document de travail, Bank Al-Maghrib, Département de la Recherche, number 2018-1, May.
• Jean-François Angers & Denise Desjardins & Georges Dionne & François Guertin, 2018, "Modelling and Estimating Individual and Firm Effects with Count Panel Data," Working Papers, HEC Montreal, Canada Research Chair in Risk Management, number 15-2, Jan.
• Jin-Myon Lee & Kayoung Park, 2018, "Utilization and Development of Big Data for Official Statistics," Industrial Economic Review, Korea Institute for Industrial Economics and Trade, number 18-1, Feb.
• 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.
• 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.
• Philipp Otto & Wolfgang Schmid, 2018, "Spatiotemporal analysis of German real-estate prices," The Annals of Regional Science, Springer;Western Regional Science Association, volume 60, issue 1, pages 41-72, January, DOI: 10.1007/s00168-016-0789-y.
• Milena Stróżyna & Gerd Eiden & Witold Abramowicz & Dominik Filipiak & Jacek Małyszko & Krzysztof Węcel, 2018, "A framework for the quality-based selection and retrieval of open data - a use case from the maritime domain," Electronic Markets, Springer;IIM University of St. Gallen, volume 28, issue 2, pages 219-233, May, DOI: 10.1007/s12525-017-0277-y.
• 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.
• Grégoire Lagasnerie & Anne-Sophie Aguadé & Pierre Denis & Anne Fagot-Campagna & Christelle Gastaldi-Menager, 2018, "The economic burden of diabetes to French national health insurance: a new cost-of-illness method based on a combined medicalized and incremental approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), volume 19, issue 2, pages 189-201, March, DOI: 10.1007/s10198-017-0873-y.
• Valerie Moran & Rowena Jacobs, 2018, "Investigating the relationship between costs and outcomes for English mental health providers: a bi-variate multi-level regression analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), volume 19, issue 5, pages 709-718, June, DOI: 10.1007/s10198-017-0915-5.
• Gordon H. Dash & Nina Kajiji & Domenic Vonella, 2018, "The role of supervised learning in the decision process to fair trade US municipal debt," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, volume 6, issue 1, pages 139-168, June, DOI: 10.1007/s40070-018-0079-2.
• 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.
• 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.
• Tanya Araújo & Elsa Fontainha, 2018, "Are scientific memes inherited differently from gendered authorship?," Scientometrics, Springer;Akadémiai Kiadó, volume 117, issue 2, pages 953-972, November, DOI: 10.1007/s11192-018-2903-7.
• Nicolaas Johannes Odendaal & Monique Reid, 2018, "Media based sentiment indices as an alternative measure of consumer confidence," Working Papers, Stellenbosch University, Department of Economics, number 17/2018.
• Jochen Lüdering, 2018, "Standing and ‘survival’ in the adult film industry," Applied Economics, Taylor & Francis Journals, volume 50, issue 16, pages 1812-1823, April, DOI: 10.1080/00036846.2017.1374542.
• Mahmut Gunay, 2018, "Forecasting industrial production and inflation in Turkey with factor models," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, volume 18, issue 4, pages 149-161.
• Mahmut Gunay, 2018, "Forecasting Industrial Production and Inflation in Turkey with Factor Models," Working Papers, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, number 1805.
• Marta Banbura & Andries van Vlodrop, 2018, "Forecasting with Bayesian Vector Autoregressions with Time Variation in the Mean," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 18-025/IV, Mar.
• Andries C. van Vlodrop & Andre (A.) Lucas, 2018, "Estimation Risk and Shrinkage in Vast-Dimensional Fundamental Factor Models," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 18-099/III, Dec.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2018, "Measuring Uncertainty and Its Impact on the Economy," The Review of Economics and Statistics, MIT Press, volume 100, issue 5, pages 799-815, December.
• Giacomo Caterini, 2018, "Classifying Firms with Text Mining," DEM Working Papers, Department of Economics and Management, number 2018/09.
• Tae-Hwy Lee & Jianghao Chu & Aman Ullah, 2018, "Variable Selection in Sparse Semiparametric Single Index Models," Working Papers, University of California at Riverside, Department of Economics, number 201908, Sep.
• Tae-Hwy Lee & Yundong Tu, 2018, "Forecasting Using Supervised Factor Models," Working Papers, University of California at Riverside, Department of Economics, number 201909, Dec.
• Oleksandr Faryna & Oleksandr Talavera & Tetiana Yukhymenko, 2018, "What Drives the Difference between Online and Official Price Indexes?," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 243, pages 21-32, DOI: 10.26531/vnbu2018.243.021.
• Aslanidis, Nektarios, & Christiansen, Charlotte & Cipollini, Andrea & Bons -- Models matemàtics, 2018, "Predicting Bond Betas using Macro-Finance Variables," Working Papers, Universitat Rovira i Virgili, Department of Economics, number 2072/306546.
• Mengheng Li & Marcel Scharth, 2018, "Leverage, asymmetry and heavy tails in the high-dimensional factor stochastic volatility model," Working Paper Series, Economics Discipline Group, UTS Business School, University of Technology, Sydney, number 49, Aug.
• Peter Martey Addo & Dominique Guegan & Bertrand Hassani, 2018, "Credit Risk Analysis using Machine and Deep learning models," Working Papers, Department of Economics, University of Venice "Ca' Foscari", number 2018:08.
• Brito Rui Pedro & Sebastião Helder & Godinho Pedro, 2018, "On the Gains of Using High Frequency Data in Portfolio Selection," Scientific Annals of Economics and Business, Sciendo, volume 65, issue 4, pages 365-383, December, DOI: 10.2478/saeb-2018-0030.
• Zekić-Sušac Marijana & Scitovski Rudolf & Has Adela, 2018, "Cluster analysis and artificial neural networks in predicting energy efficiency of public buildings as a cost-saving approach," Croatian Review of Economic, Business and Social Statistics, Sciendo, volume 4, issue 2, pages 57-66, November, DOI: 10.2478/crebss-2018-0013.
• Oliver Reiter & Robert Stehrer, 2018, "Trade Policies and Integration of the Western Balkans," wiiw Working Papers, The Vienna Institute for International Economic Studies, wiiw, number 148, May.
• A. Chudik & G. Kapetanios & M. Hashem Pesaran, 2018, "A One Covariate at a Time, Multiple Testing Approach to Variable Selection in High‐Dimensional Linear Regression Models," Econometrica, Econometric Society, volume 86, issue 4, pages 1479-1512, July, DOI: 10.3982/ECTA14176.
• Susan Dynarski & Brian Jacob & Daniel Kreisman, 2018, "How important are fixed effects and time trends in estimating returns to schooling? Evidence from a replication of Jacobson, Lalonde, and Sullivan, 2005," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 33, issue 7, pages 1098-1108, November, DOI: 10.1002/jae.2653.
• Oscar Claveria & Enric Monte & Salvador Torra, 2018, "Tracking economic growth by evolving expectations via genetic programming: A two-step approach," Working Papers, Xarxa de Referència en Economia Aplicada (XREAP), number XREAP2018-4, Oct, revised Oct 2018.
• Jia Chen & Degui Li & Oliver Linton, 2018, "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Discussion Papers, Department of Economics, University of York, number 18/14, Oct.
• Bailliu, Jeannine & Han, Xinfen & Kruger, Mark & Liu, Yu-Hsien & Thanabalasingam, Sri, 2018, "Can media and text analytics provide insights into labour market conditions in China?," BOFIT Discussion Papers, Bank of Finland Institute for Emerging Economies (BOFIT), number 9/2018.
• Schaefer, Maximilian & Sapi, Geza & Lorincz, Szabolcs, 2018, "The effect of big data on recommendation quality: The example of internet search," DICE Discussion Papers, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE), number 284.
• Hausmann, Ricardo & Hinz, Julian & Yildirim, Muhammed A., 2018, "Measuring Venezuelan emigration with Twitter," Kiel Working Papers, Kiel Institute for the World Economy, number 2106.
• Daniel, Volker & Neubert, Magnus & Orban, Agnes, 2018, "Fictional expectations and the global media in the Greek debt crisis: A topic modeling approach," Working Papers, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin, number 4, DOI: 10.18452/18967.
• Klos, Jonas & Krieger, Tim & Stöwhase, Sven, 2018, "A New Measure of Intra-generational Redistribution within PAYG Pension Schemes and its Application to German Micro-data," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy, Verein für Socialpolitik / German Economic Association, number 181580.
• Kaufmann, Sylvia & Beyeler, Simon, 2018, "Factor augmented VAR revisited - A sparse dynamic factor model approach," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy, Verein für Socialpolitik / German Economic Association, number 181602.
• Simon Jäger & Benjamin Schoefer & Josef Zweimüller, 2018, "Marginal jobs and job surplus: a test of the efficiency of separations," ECON - Working Papers, Department of Economics - University of Zurich, number 314, Dec.

2017

• Tommaso Proietti & Alessandro Giovannelli, 2017, "A Durbin-Levinson Regularized Estimator of High Dimensional Autocovariance Matrices," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2017-20, May.
• Martin M. Andreasen & Jens H.E. Christensen & Glenn D. Rudebusch, 2017, "Term Structure Analysis with Big Data," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2017-31, Sep.
• Hyeongwoo Kim & Kyunghwan Ko, 2017, "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series, Department of Economics, Auburn University, number auwp2017-03, May.
• Christian Gouriéroux & Alain Monfort & Eric Renault, 2017, "Consistent Pseudo-Maximum Likelihood Estimators," Annals of Economics and Statistics, GENES, issue 125-126, pages 187-218.
• Luis Alejandro Lopez-Agudo & John Jerrim & Oscar David Marcenaro Gutierrez & Nikki Shure, 2017, "To weight or not to weight?: the case of PISA data," Investigaciones de Economía de la Educación volume 12, Asociación de Economía de la Educación, chapter 13, in: Juan Cándido Gómez Gallego & María Concepción Pérez Cárceles & Laura Nieto Torrejón, "Investigaciones de Economía de la Educación 12".
• Sorin Manole & Laura Panoiu & Adriana Paunescu, 2017, "Impact of Migration upon a Receiving Country’s Economic Development," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, volume 19, issue 46, pages 670-670, August.
• Djogbenou, Antoine A., 2017, "Model Selection in Factor-Augmented Regressions with Estimated Factors," Queen's Economics Department Working Papers, Queen's University - Department of Economics, number 274717, Oct, DOI: 10.22004/ag.econ.274717.
• T. Tony Cai & Wenguang Sun, 2017, "Large-Scale Global and Simultaneous Inference: Estimation and Testing in Very High Dimensions," Annual Review of Economics, Annual Reviews, volume 9, issue 1, pages 411-439, September, DOI: 10.1146/annurev-economics-063016-10.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017, "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 201706, May, revised May 2017.
• Massimo Franchi & Paolo Paruolo, 2017, "Cointegration in functional autoregressive processes," Papers, arXiv.org, number 1712.07522, Dec, revised Oct 2018.
• Danut-Octavian SIMION & Emilia VASILE, 2017, "Applications For Businesses That Uses Relational Databases:," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 45, issue 1, pages 61-72, March.
• Danut-Octavian SIMION, 2017, "Evaluation Of The Economic Activity Through Experts Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 46, issue 2, pages 63-75, June.
• Nelu BURCEA & Danut-Octavian SIMION, 2017, "The Management Of Software Products Through Economic Information Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 47, issue 3, pages 111-124, Supplemen.
• Emilia VASILE & Danut-Octavian SIMION, 2017, "Representation Of Knowledge And Algorithms For Economic Systems," Internal Auditing and Risk Management, Athenaeum University of Bucharest, volume 48, issue 4, pages 7-20, December.
• Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017, "Optimal data collection for randomized control trials," CeMMAP working papers, Institute for Fiscal Studies, number 15/17, Mar, DOI: 10.1920/wp.cem.2017.1517.
• Koen Jochmans & Martin Weidner, 2017, "Fixed-effect regressions on network data," CeMMAP working papers, Institute for Fiscal Studies, number 26/17, May, DOI: 10.1920/wp.cem.2017.2617.
• Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017, "Optimal data collection for randomized control trials," CeMMAP working papers, Institute for Fiscal Studies, number 45/17, Oct, DOI: 10.1920/wp.cem.2017.4517.
• Le-Yu Chen & Sokbae (Simon) Lee, 2017, "Best subset binary prediction," CeMMAP working papers, Institute for Fiscal Studies, number 50/17, Nov, DOI: 10.1920/wp.cem.2017.5017.
• Lidiya Guryanova & Tamara Klebanova & Tetiana Trunova, 2017, "Modeling the Financial Strategy of the Enterprise in an Unstable Environment," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 91-109.
• Carlos Casanova & Alvaro Ortiz & Tomasa Rodrigo & Le Xia & Joaquín Iglesias, 2017, "Tracking chinese vulnerability in real time using Big Data," Working Papers, BBVA Bank, Economic Research Department, number 17/13, May.
• George Kapetanios & Massimiliano Marcellino & Fabrizio Venditti, 2017, "Large time-varying parameter VARs: a non-parametric approach," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1122, Jun.
• Dario Sansone, 2017, "Now You See Me: High School Dropout and Machine Learning," 2017 Stata Conference, Stata Users Group, number 5, Aug.
• Chiranjit Chakraborty & Andreas Joseph, 2017, "Machine learning at central banks," Bank of England working papers, Bank of England, number 674, Sep.
• David Bholat & James Brookes & Chris Cai & Katy Grundy & Jakob Lund, 2017, "Sending firm messages: text mining letters from PRA supervisors to banks and building societies they regulate," Bank of England working papers, Bank of England, number 688, Oct.
• Hyeongwoo Kim & Kyunghwan Ko, 2017, "Improving Forecast Accuracy of Financial Vulnerability: Partial Least Squares Factor Model Approach," Working Papers, Economic Research Institute, Bank of Korea, number 2017-14, May.
• Berg Tim Oliver, 2017, "Forecast accuracy of a BVAR under alternative specifications of the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 21, issue 2, pages 1-29, April, DOI: 10.1515/snde-2015-0084.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017, "Using survey data to forecast real activity with evolutionary algorithms. A cross-country analysis," Journal of Applied Economics, Universidad del CEMA, volume 20, pages 329-349, November.
• Matthew Bursnall & Vahé Nafilyan & Stefan Speckesser, 2017, "An analysis of the duration and achievement of apprenticeships in England," CVER Briefing Notes, Centre for Vocational Education Research, number 004, Sep.
• Sophie Hedges & Vahé Nafilyan & Stefan Speckesser & Augustin de Coulon, 2017, "Young people in low level vocational education: characteristics, trajectories and labour market outcomes," CVER Research Papers, Centre for Vocational Education Research, number 004, Mar.
• Vahé Nafilyan & Stefan Speckesser, 2017, "The longer the better? The impact of the 2012 apprenticeship reform in England on achievement and other outcomes," CVER Research Papers, Centre for Vocational Education Research, number 006, Sep.
• Peter Grajzl & Peter Murrell, 2017, "Toward Understanding 17th Century English Culture: A Structural Topic Model of Francis Bacon's Ideas," CESifo Working Paper Series, CESifo, number 6443.
• Dalibor Stevanovic & Rachidi Kotchoni & Maxime Leroux, 2017, "Forecasting economic activity in data-rich environment," CIRANO Working Papers, CIRANO, number 2017s-05, Jan.
• Ariadne M. Checo & Salomé Pradel & Francisco A. Ramírez, 2017, "The Effects of USA Monetary Policy on Central America and the Dominican Republic," Investigación Conjunta-Joint Research, Centro de Estudios Monetarios Latinoamericanos, CEMLA, chapter 7, in: Ángel Estrada García & Alberto Ortiz Bolaños, "International Spillovers of Monetary Policy".
• Ángel Estrada García & Alberto Ortiz Bolaños (ed.), 2017, "International Spillovers of Monetary Policy," Investigación Conjunta-Joint Research, Centro de Estudios Monetarios Latinoamericanos, CEMLA, number 3, edition 1, ISBN: ARRAY(0x72c15560), December.
• Alvaro J. Riascos & Mauricio Romero & Natalia Serna, 2017, "Risk Adjustment Revisited using Machine Learning Techniques," Documentos CEDE, Universidad de los Andes, Facultad de Economía, CEDE, number 15601, Mar.
• Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017, "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 12256, Aug.
• Christian Gouriéroux & Alain Monfort & Eric Renault, 2017, "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers, Center for Research in Economics and Statistics, number 2017-10, Jan.
• Max Nathan & Anna Rosso, 2017, "Innovative events," Development Working Papers, Centro Studi Luca d'Agliano, University of Milano, number 429, Oct, revised 08 Apr 2019.
• Alvarez Iturri, Silvana Valeria, 2017, "Pricing the quality of an innovative idea," IC3JM - Estudios = Working Papers, Instituto Mixto Carlos III - Juan March de Ciencias Sociales (IC3JM), number 24183, Feb.
• Benjamin David, 2017, "Model economic phenomena with CART and Random Forest algorithms," EconomiX Working Papers, University of Paris Nanterre, EconomiX, number 2017-46.
• Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017, "Forecasting economic activity in data-rich environment," EconomiX Working Papers, University of Paris Nanterre, EconomiX, number 2017-5.
• Ciccarelli, Matteo & García, Juan Angel & Montes-Galdón, Carlos, 2017, "Unconventional monetary policy and the anchoring of inflation expectations," Working Paper Series, European Central Bank, number 1995, Jan.
• Osbat, Chiara & Benkovskis, Konstantins & Bluhm, Benjamin & Bobeica, Elena & Zeugner, Stefan, 2017, "What drives export market shares? It depends! An empirical analysis using Bayesian Model Averaging," Working Paper Series, European Central Bank, number 2090, Jul.
• Md. Shakib Hossain & Md. Ziaur Rahman, 2017, "Does Governance Facilitate Foreign Direct Investment in Developing Countries?," International Journal of Economics and Financial Issues, Econjournals, volume 7, issue 1, pages 164-177.
• Bee, Marco & Riccaboni, Massimo & Trapin, Luca, 2017, "An extreme value analysis of the last century crises across industries in the U.S. economy," Journal of Economic Dynamics and Control, Elsevier, volume 81, issue C, pages 65-78, DOI: 10.1016/j.jedc.2017.01.012.
• Wongboonsin, Kua & Phiromswad, Piyachart, 2017, "Searching for empirical linkages between demographic structure and economic growth," Economic Modelling, Elsevier, volume 60, issue C, pages 364-379, DOI: 10.1016/j.econmod.2016.09.023.
• Liu, Jing & Wei, Yu & Ma, Feng & Wahab, M.I.M., 2017, "Forecasting the realized range-based volatility using dynamic model averaging approach," Economic Modelling, Elsevier, volume 61, issue C, pages 12-26, DOI: 10.1016/j.econmod.2016.11.020.
• Ma, Feng & Liu, Jing & Huang, Dengshi & Chen, Wang, 2017, "Forecasting the oil futures price volatility: A new approach," Economic Modelling, Elsevier, volume 64, issue C, pages 560-566, DOI: 10.1016/j.econmod.2017.04.020.
• Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro-Gutierrez, Oscar D. & Shure, Nikki, 2017, "What happens when econometrics and psychometrics collide? An example using the PISA data," Economics of Education Review, Elsevier, volume 61, issue C, pages 51-58, DOI: 10.1016/j.econedurev.2017.09.007.
• Fosten, Jack, 2017, "Confidence intervals in regressions with estimated factors and idiosyncratic components," Economics Letters, Elsevier, volume 157, issue C, pages 71-74, DOI: 10.1016/j.econlet.2017.05.034.
• Gagliardini, Patrick & Gouriéroux, Christian, 2017, "Double instrumental variable estimation of interaction models with big data," Journal of Econometrics, Elsevier, volume 201, issue 2, pages 176-197, DOI: 10.1016/j.jeconom.2017.08.002.
• Aït-Sahalia, Yacine & Xiu, Dacheng, 2017, "Using principal component analysis to estimate a high dimensional factor model with high-frequency data," Journal of Econometrics, Elsevier, volume 201, issue 2, pages 384-399, DOI: 10.1016/j.jeconom.2017.08.015.
• Shang, Han Lin, 2017, "Functional time series forecasting with dynamic updating: An application to intraday particulate matter concentration," Econometrics and Statistics, Elsevier, volume 1, issue C, pages 184-200, DOI: 10.1016/j.ecosta.2016.08.004.
• Gupta, Rangan & Wohar, Mark, 2017, "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, volume 62, issue C, pages 181-186, DOI: 10.1016/j.eneco.2017.01.001.
• Bjørnland, Hilde C. & Ravazzolo, Francesco & Thorsrud, Leif Anders, 2017, "Forecasting GDP with global components: This time is different," International Journal of Forecasting, Elsevier, volume 33, issue 1, pages 153-173, DOI: 10.1016/j.ijforecast.2016.02.004.
• Kang, Yanfei & Hyndman, Rob J. & Smith-Miles, Kate, 2017, "Visualising forecasting algorithm performance using time series instance spaces," International Journal of Forecasting, Elsevier, volume 33, issue 2, pages 345-358, DOI: 10.1016/j.ijforecast.2016.09.004.
• Hännikäinen, Jari, 2017, "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, volume 33, issue 4, pages 1044-1064, DOI: 10.1016/j.ijforecast.2017.05.006.
• Davis, Morris A. & Oliner, Stephen D. & Pinto, Edward J. & Bokka, Sankar, 2017, "Residential land values in the Washington, DC metro area: New insights from big data," Regional Science and Urban Economics, Elsevier, volume 66, issue C, pages 224-246, DOI: 10.1016/j.regsciurbeco.2017.06.006.
• Timur Behlul & Anastasios Panagiotelis & George Athanasopoulos & Rob J Hyndman & Farshid Vahid, 2017, "The Australian Macro Database: An Online Resource for Macroeconomic Research in Australia," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2017-15, Feb.
• Hilde C. Bjornland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2017, "Do Central Banks Respond Timely to Developments in the Global Economy?," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2017-20, Mar.
• Michal Antoszewski, 2017, "Panel estimation of sectoral substitution elasticities for CES production functions," EcoMod2017, EcoMod, number 10160, Jul.
• Nathalie Picard & Kamel Gadouche, 2017, "L’accès aux données très détaillées pour la recherche scientifique," Thema Working Papers, THEMA (Théorie Economique, Modélisation et Applications), CY Cergy-Paris University, ESSEC and CNRS, number 2017-06.
• Yolanda F. Rebollo-Sanz, 2017, "Decomposing the structure of wages into firm and worker effects," International Journal of Manpower, Emerald Group Publishing Limited, volume 38, issue 5, pages 765-787, August, DOI: 10.1108/IJM-04-2016-0082.
• Korobilis, D, 2017, "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers, University of Essex, Essex Business School, number 19565, May.
• Matej Nevrla, 2017, "Systemic Risk in the European Financial and Energy Sector: Dynamic Factor Copula Approach," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2017/11, May, revised May 2017.
• Michelle L. Barnes & Giovanni P. Olivei, 2017, "Financial variables and macroeconomic forecast errors," Working Papers, Federal Reserve Bank of Boston, number 17-17, Oct.
• Martin M. Andreasen & Jens H. E. Christensen & Glenn D. Rudebusch, 2017, "Term Structure Analysis with Big Data," Working Paper Series, Federal Reserve Bank of San Francisco, number 2017-21, Sep.
• Alessandro Barbarino & Efstathia Bura, 2017, "A Unified Framework for Dimension Reduction in Forecasting," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2017-004, Jan, DOI: 10.17016/FEDS.2017.004.
• Matteo Barigozzi & Matteo Luciani, 2017, "Common Factors, Trends, and Cycles in Large Datasets," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2017-111, Nov, DOI: 10.17016/FEDS.2017.111.
• Marlene Amstad & Simon M. Potter & Robert W. Rich, 2017, "The New York Fed Staff Underlying Inflation Gauge (UIG)," Economic Policy Review, Federal Reserve Bank of New York, issue 23-2, pages 1-32.
• Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2017, "Macroeconomic nowcasting and forecasting with big data," Staff Reports, Federal Reserve Bank of New York, number 830, Nov.
• Bige KÜÇÜKEFE, Dündar Murat DEMİRÖZ, 2017, "FAVAR (Factor-Augmented Vector Autoregression) Modeli Literatür Taraması," Fiscaoeconomia, Tubitak Ulakbim JournalPark (Dergipark), issue 2.
• Rossella Bardazzi & Leonardo Ghezzi, 2017, "International competitiveness and investment: simulations with a bilateral trade model," Working Papers - Economics, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, number wp2017_01.rdf.
• Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2017, "On the gains of using high frequency data and higher moments in Portfolio Selection," CeBER Working Papers, Centre for Business and Economics Research (CeBER), University of Coimbra, number 2017-02, Feb.
• Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017, "Forecasting economic activity in data-rich environment," Working Papers, HAL, number hal-04141668.
• Alexander N. Bogin & William M. Doerner, 2017, "Property Renovations and Their Impact on House Price Index Construction," FHFA Staff Working Papers, Federal Housing Finance Agency, number 17-02, Mar, DOI: 10.1080/10835547.2019.12091526.
• Leonid Gokhberg & Ilya Kuzminov & Pavel Bakhtin & Elena Tochilina & Alexander Chulok & Anton Timofeev & Alina Lavrinenko, 2017, "Big-Data-Augmented Approach to Emerging Technologies Identification: Case of Agriculture and Food Sector," HSE Working papers, National Research University Higher School of Economics, number WP BRP 76/STI/2017.
• Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017, "Optimal data collection for randomized control trials," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP15/17, Mar.
• Koen Jochmans & Martin Weidner, 2017, "Fixed-effect regressions on network data," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP26/17, May.
• Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017, "Optimal data collection for randomized control trials," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP45/17, Oct.
• Le-Yu Chen & Sokbae (Simon) Lee, 2017, "Best subset binary prediction," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP50/17, Nov.
• Oscar Claveria & Enric Monte & Salvador Torra, 2017, "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201711, May, revised May 2017.
• Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro Gutierrez, Oscar & Shure, Nikki, 2017, "What Happens When Econometrics and Psychometrics Collide? An Example Using the PISA Data," IZA Discussion Papers, IZA Network @ LISER, number 10847, Jun.
• Simon Freyaldenhoven, 2017, "A Generalized Factor Model with Local Factors," 2017 Papers, Job Market Papers, number pfr361, Nov.
• David Wuepper & Marc Patry, 2017, "The World Heritage list: Which sites promote the brand? A big data spatial econometrics approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, volume 41, issue 1, pages 1-21, February, DOI: 10.1007/s10824-016-9266-9.
• 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.
• Ralf Brüggemann & Christian Kascha, 2017, "Directed Graphs and Variable Selection in Large Vector Autoregressive Models," Working Paper Series of the Department of Economics, University of Konstanz, Department of Economics, University of Konstanz, number 2017-06, Aug.
• Jaqueson K Galimberti, 2017, "Forecasting GDP growth from the outer space," KOF Working papers, KOF Swiss Economic Institute, ETH Zurich, number 17-427, Feb, DOI: 10.3929/ethz-a-010852413.
• 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.
• Konstantins Benkovskis & Benjamin Bluhm & Elena Bobeica & Chiara Osbat & Stefan Zeugner, 2017, "What drives export market shares? It depends! An empirical analysis using Bayesian Model Averaging," Working Papers, Latvijas Banka, number 2017/02, Aug.
• Martin Schumann & Thomas A. Severini & Gautam Tripathi, 2017, "Integrated Likelihood Based Inference for Nonlinear Panel Data Models with Unobserved Effects," DEM Discussion Paper Series, Department of Economics at the University of Luxembourg, number 17-01.
• Martin Boyer & Philippe De Donder & Claude Fluet & Marie-Louise Leroux & Pierre-Carl Michaud, 2017, "Long-term Care Insurance: Knowledge Barriers, Risk Perception and Adverse Selection," Cahiers de recherche, Chaire de recherche Industrielle Alliance sur les enjeux économiques des changements démographiques, number 1701.
• Damien Échevin & Qing Li & Marc-André Morin, 2017, "Hospital Readmission is Highly Predictable from Deep Learning," Cahiers de recherche, Chaire de recherche Industrielle Alliance sur les enjeux économiques des changements démographiques, number 1705.
• Gabriele, Mazzolini & Laura, Pagani & Alessandro, Santoro, 2017, "The deterrence effect of real-world operational tax audits," Working Papers, University of Milano-Bicocca, Department of Economics, number 359, Feb, revised 03 Feb 2017.
• Carlo, Fiorio & Alessandro, Santoro, 2017, "Evidence-based threat-of-audit letters: do taxpayers respond strategically in a complex environment?," Working Papers, University of Milano-Bicocca, Department of Economics, number 372, Sep, revised 26 Sep 2017.
• François Gardes, 2017, "Angus Deaton, prix à la mémoire d'Alfred Nobel 2015 : un maître de l'économie appliquée," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17025, May.
• Dominique Guegan & Bertrand Hassani, 2017, "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17034, Jul.
• Dominique Guegan & Bertrand Hassani, 2017, "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17034r, Jul, revised Sep 2017.
• Okay Gunes, 2017, "Hedonic Recommendations: An Econometric Application on Big Data," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 17061, Dec.
• Timur Behlul & Anastasios Panagiotelis & George Athanasopoulos & Rob J Hyndman & Farshid Vahid, 2017, "The Australian Macro Database: An online resource for macroeconomic research in Australia," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 1/17.
• 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.