Research classified by Journal of Economic Literature (JEL) codes

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

2020

• Nélida Díaz Sobrino & Corinna Ghirelli & Samuel Hurtado & Javier J. Pérez & Alberto Urtasun, 2020, "The narrative about the economy as a shadow forecast: an analysis using Banco de España quarterly reports," Working Papers, Banco de España, number 2042, Dec.
• Bradley Shapiro & Günter J. Hitsch & Anna Tuchman, 2020, "Generalizable and Robust TV Advertising Effects," Working Papers, Becker Friedman Institute for Research In Economics, number 2020-111.
• Caroline Jardet & Baptiste Meunier, 2020, "Nowcasting World GDP Growth with High-Frequency Data," Working papers, Banque de France, number 788.
• Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020, "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Discussion Papers, Department of Economics, University of Birmingham, number 20-03, Feb.
• Daniel Levy & Tamir Mayer & Alon Raviv, 2020, "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers, Bar-Ilan University, Department of Economics, number 2020-01, Jan.
• Filipp Ulyankin, 2020, "Forecasting Russian Macroeconomic Indicators Based on Information from News and Search Queries," Russian Journal of Money and Finance, Bank of Russia, volume 79, issue 4, pages 75-97, December, DOI: 10.31477/rjmf.202004.75.
• Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020, "Taming the Factor Zoo: A Test of New Factors," Journal of Finance, American Finance Association, volume 75, issue 3, pages 1327-1370, June, DOI: 10.1111/jofi.12883.
• Hilde C. Bj⊘rnland & Leif Anders Thorsrud & Sepideh Khayati Zahiri, 2020, "Do Central Banks Respond Timely to Developments in the Global Economy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, volume 82, issue 2, pages 285-310, April, DOI: 10.1111/obes.12335.
• Jaqueson K. Galimberti, 2020, "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, volume 82, issue 4, pages 697-722, August, DOI: 10.1111/obes.12361.
• Hanjo Odendaal & Monique Reid & Johann F. Kirsten, 2020, "Media‐Based Sentiment Indices as an Alternative Measure of Consumer Confidence," South African Journal of Economics, Economic Society of South Africa, volume 88, issue 4, pages 409-434, December, DOI: 10.1111/saje.12261.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020, "News media vs. FRED-MD for macroeconomic forecasting," Working Paper, Norges Bank, number 2020/14, Oct.
• Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2020, "Making text count: economic forecasting using newspaper text," Bank of England working papers, Bank of England, number 865, May.
• Hyeongwoo Kim & Soohyon Kim, 2020, "Common Factor Augmented Forecasting Models for the US Dollar-Korean Won Exchange Rate," Working Papers, Economic Research Institute, Bank of Korea, number 2020-5, Feb.
• Andreas Gulyas & Krzysztof Pytka, 2020, "Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach," CRC TR 224 Discussion Paper Series, University of Bonn and University of Mannheim, Germany, number crctr224_2020_131v2, May.
• Cristea, R. G., 2020, "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 20108, Nov.
• Ahmed, R. & Pesaran, M. H., 2020, "Regional Heterogeneity and U.S. Presidential Elections," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2092, Oct.
• Markus Heinrich & Magnus Reif, 2020, "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series, CESifo, number 8054.
• Jonas Klos & Tim Krieger & Sven Stöwhase, 2020, "Measuring Intra-Generational Redistribution in PAYG Pension Schemes," CESifo Working Paper Series, CESifo, number 8200.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020, "Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks," CESifo Working Paper Series, CESifo, number 8475.
• Rashad Ahmed & M. Hashem Pesaran, 2020, "Regional Heterogeneity and U.S. Presidential Elections," CESifo Working Paper Series, CESifo, number 8615.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020, "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series, CESifo, number 8639.
• Michael Allan Ribers & Hannes Ullrich, 2020, "Machine Predictions and Human Decisions with Variation in Payoffs and Skill," CESifo Working Paper Series, CESifo, number 8702.
• Magnus Reif, 2020, "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
• Roberto Molinari & Gaetan Bakalli & Stéphane Guerrier & Cesare Miglioli & Samuel Orso & O. Scaillet, 2020, "Swag: A Wrapper Method for Sparse Learning," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 20-49, Jun.
• David Ardia & Laurent Barras & Patrick Gagliardini & Olivier Scaillet, 2020, "Is it Alpha or Beta? Decomposing Hedge Fund Returns When Models are Misspecified," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 20-82, Sep, revised May 2023.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2020, "Macroeconomic Data Transformations Matter," CIRANO Working Papers, CIRANO, number 2020s-42, Aug.
• Kevin Moran & Dalibor Stevanovic & Adam Abdel Kader Touré, 2020, "Macroeconomic Uncertainty and the COVID-19 Pandemic: Measure and Impacts on the Canadian Economy," CIRANO Working Papers, CIRANO, number 2020s-47, Sep.
• Giglio, Stefano & Feng, Guanhao & Xiu, Dacheng, 2020, "Taming the Factor Zoo: A Test of New Factors," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 14266, Jan.
• Mark Trede & Michael Zimmermann, 2020, "Regional labour migration - Stylized facts for Germany," CQE Working Papers, Center for Quantitative Economics (CQE), University of Muenster, number 9320, Sep.
• Franchi, Massimo & Paruolo, Paolo, 2020, "Cointegration In Functional Autoregressive Processes," Econometric Theory, Cambridge University Press, volume 36, issue 5, pages 803-839, October.
• Antonia Grohmann & Steffen Herbold & Friederike Lenel, 2020, "Repayment under Flexible Loan Contracts: Evidence from Tanzania," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1884.
• Michael Allan Ribers & Hannes Ullrich, 2020, "Machine Predictions and Human Decisions with Variation in Payoffs and Skills," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1911.
• Laurent Ferrara & Anna Simoni, 2020, "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," EconomiX Working Papers, University of Paris Nanterre, EconomiX, number 2020-11.
• Hansen, Stephen & McMahon, Michael & Tong, Matthew, 2020, "The long-run information effect of central bank communication," Working Paper Series, European Central Bank, number 2363, Jan.
• Arrigoni, Simone & Bobasu, Alina & Venditti, Fabrizio, 2020, "The simpler the better: measuring financial conditions for monetary policy and financial stability," Working Paper Series, European Central Bank, number 2451, Aug.
• Ferrari Minesso, Massimo & Pagliari, Maria Sole & Kurcz, Frederik, 2020, "Do words hurt more than actions? The impact of trade tensions on financial markets," Working Paper Series, European Central Bank, number 2490, Nov.
• Schönheit, David & Weinhold, Richard & Dierstein, Constantin, 2020, "The impact of different strategies for generation shift keys (GSKs) on the flow-based market coupling domain: A model-based analysis of Central Western Europe," Applied Energy, Elsevier, volume 258, issue C, DOI: 10.1016/j.apenergy.2019.114067.
• Milusheva, Sveta, 2020, "Managing the spread of disease with mobile phone data," Journal of Development Economics, Elsevier, volume 147, issue C, DOI: 10.1016/j.jdeveco.2020.102559.
• Schnaubelt, Matthias & Fischer, Thomas G. & Krauss, Christopher, 2020, "Separating the signal from the noise – Financial machine learning for Twitter," Journal of Economic Dynamics and Control, Elsevier, volume 114, issue C, DOI: 10.1016/j.jedc.2020.103895.
• Pham, Manh Cuong & Anderson, Heather Margot & Duong, Huu Nhan & Lajbcygier, Paul, 2020, "The effects of trade size and market depth on immediate price impact in a limit order book market," Journal of Economic Dynamics and Control, Elsevier, volume 120, issue C, DOI: 10.1016/j.jedc.2020.103992.
• Kim, Hyeongwoo & Ko, Kyunghwan, 2020, "Improving forecast accuracy of financial vulnerability: PLS factor model approach," Economic Modelling, Elsevier, volume 88, issue C, pages 341-355, DOI: 10.1016/j.econmod.2019.09.046.
• Arata, Linda & Fabrizi, Enrico & Sckokai, Paolo, 2020, "A worldwide analysis of trend in crop yields and yield variability: Evidence from FAO data," Economic Modelling, Elsevier, volume 90, issue C, pages 190-208, DOI: 10.1016/j.econmod.2020.05.006.
• Álvarez de Toledo, Pablo & Núñez, Fernando & Usabiaga, Carlos, 2020, "Matching in segmented labor markets: An analytical proposal based on high-dimensional contingency tables," Economic Modelling, Elsevier, volume 93, issue C, pages 175-186, DOI: 10.1016/j.econmod.2020.07.019.
• Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020, "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, volume 93, issue C, pages 576-585, DOI: 10.1016/j.econmod.2020.09.015.
• Sant’Anna, Leonardo Riegel & Caldeira, João Frois & Filomena, Tiago Pascoal, 2020, "Lasso-based index tracking and statistical arbitrage long-short strategies," The North American Journal of Economics and Finance, Elsevier, volume 51, issue C, DOI: 10.1016/j.najef.2019.101055.
• Gupta, Rangan & Sun, Xiaojin, 2020, "Forecasting economic policy uncertainty of BRIC countries using Bayesian VARs," Economics Letters, Elsevier, volume 186, issue C, DOI: 10.1016/j.econlet.2019.108677.
• Wei, Jie & Chen, Hui, 2020, "Determining the number of factors in approximate factor models by twice K-fold cross validation," Economics Letters, Elsevier, volume 191, issue C, DOI: 10.1016/j.econlet.2020.109149.
• Wei, Jie & Zhang, Yonghui, 2020, "A time-varying diffusion index forecasting model," Economics Letters, Elsevier, volume 193, issue C, DOI: 10.1016/j.econlet.2020.109337.
• Fan, Yanqin & Han, Fang & Li, Wei & Zhou, Xiao-Hua, 2020, "On rank estimators in increasing dimensions," Journal of Econometrics, Elsevier, volume 214, issue 2, pages 379-412, DOI: 10.1016/j.jeconom.2019.08.003.
• Cai, T. Tony & Hu, Jianchang & Li, Yingying & Zheng, Xinghua, 2020, "High-dimensional minimum variance portfolio estimation based on high-frequency data," Journal of Econometrics, Elsevier, volume 214, issue 2, pages 482-494, DOI: 10.1016/j.jeconom.2019.04.039.
• Li, Z. Merrick & Laeven, Roger J.A. & Vellekoop, Michel H., 2020, "Dependent microstructure noise and integrated volatility estimation from high-frequency data," Journal of Econometrics, Elsevier, volume 215, issue 2, pages 536-558, DOI: 10.1016/j.jeconom.2019.10.004.
• Zhu, Xuening & Huang, Danyang & Pan, Rui & Wang, Hansheng, 2020, "Multivariate spatial autoregressive model for large scale social networks," Journal of Econometrics, Elsevier, volume 215, issue 2, pages 591-606, DOI: 10.1016/j.jeconom.2018.11.018.
• Huang, Danyang & Wang, Feifei & Zhu, Xuening & Wang, Hansheng, 2020, "Two-mode network autoregressive model for large-scale networks," Journal of Econometrics, Elsevier, volume 216, issue 1, pages 203-219, DOI: 10.1016/j.jeconom.2020.01.014.
• Chan, N.H. & Cheung, Simon K.C. & Wong, Samuel P.S., 2020, "Inference for the degree distributions of preferential attachment networks with zero-degree nodes," Journal of Econometrics, Elsevier, volume 216, issue 1, pages 220-234, DOI: 10.1016/j.jeconom.2020.01.015.
• Vogt, Michael & Linton, Oliver, 2020, "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, volume 216, issue 1, pages 305-325, DOI: 10.1016/j.jeconom.2020.01.020.
• Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020, "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, volume 216, issue 1, pages 86-105, DOI: 10.1016/j.jeconom.2020.01.007.
• Hafner, Christian M. & Linton, Oliver B. & Tang, Haihan, 2020, "Estimation of a multiplicative correlation structure in the large dimensional case," Journal of Econometrics, Elsevier, volume 217, issue 2, pages 431-470, DOI: 10.1016/j.jeconom.2019.12.012.
• Galbraith, John W. & Zinde-Walsh, Victoria, 2020, "Simple and reliable estimators of coefficients of interest in a model with high-dimensional confounding effects," Journal of Econometrics, Elsevier, volume 218, issue 2, pages 609-632, DOI: 10.1016/j.jeconom.2020.04.031.
• Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020, "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, volume 219, issue 1, pages 171-200, DOI: 10.1016/j.jeconom.2020.04.043.
• Nevrla, Matěj, 2020, "Systemic risk in European financial and energy sectors: Dynamic factor copula approach," Economic Systems, Elsevier, volume 44, issue 4, DOI: 10.1016/j.ecosys.2020.100820.
• Reschenhofer, Erhard & Mangat, Manveer Kaur & Stark, Thomas, 2020, "Volatility forecasts, proxies and loss functions," Journal of Empirical Finance, Elsevier, volume 59, issue C, pages 133-153, DOI: 10.1016/j.jempfin.2020.09.006.
• Evangelista, Rui & Ramalho, Esmeralda A. & Andrade e Silva, João, 2020, "On the use of hedonic regression models to measure the effect of energy efficiency on residential property transaction prices: Evidence for Portugal and selected data issues," Energy Economics, Elsevier, volume 86, issue C, DOI: 10.1016/j.eneco.2020.104699.
• Cepni, Oguzhan & Gul, Selcuk & Gupta, Rangan, 2020, "Local currency bond risk premia of emerging markets: The role of local and global factors," Finance Research Letters, Elsevier, volume 33, issue C, DOI: 10.1016/j.frl.2019.05.001.
• Batagelj, Vladimir & Maltseva, Daria, 2020, "Temporal bibliographic networks," Journal of Informetrics, Elsevier, volume 14, issue 1, DOI: 10.1016/j.joi.2020.101006.
• Hüttner, Amelie & Scherer, Matthias & Gräler, Benedikt, 2020, "Geostatistical modeling of dependent credit spreads: Estimation of large covariance matrices and imputation of missing data," Journal of Banking & Finance, Elsevier, volume 118, issue C, DOI: 10.1016/j.jbankfin.2020.105897.
• DePaula, Guilherme, 2020, "The distributional effect of climate change on agriculture: Evidence from a Ricardian quantile analysis of Brazilian census data," Journal of Environmental Economics and Management, Elsevier, volume 104, issue C, DOI: 10.1016/j.jeem.2020.102378.
• Kala, Kaveri & Bolia, Nomesh B. & Sushil,, 2020, "Waste management communication policy for effective citizen awareness," Journal of Policy Modeling, Elsevier, volume 42, issue 3, pages 661-678, DOI: 10.1016/j.jpolmod.2020.01.012.
• Samaratunge, Ramanie & Kumara, Ajantha Sisira & Abeysekera, Lakmal, 2020, "Breaking the Perverse Health-debt Cycle in Sri Lanka: Policy Options," Journal of Policy Modeling, Elsevier, volume 42, issue 3, pages 728-745, DOI: 10.1016/j.jpolmod.2020.01.003.
• Indaco, Agustín, 2020, "From twitter to GDP: Estimating economic activity from social media," Regional Science and Urban Economics, Elsevier, volume 85, issue C, DOI: 10.1016/j.regsciurbeco.2020.103591.
• Chen, Wang & Ma, Feng & Wei, Yu & Liu, Jing, 2020, "Forecasting oil price volatility using high-frequency data: New evidence," International Review of Economics & Finance, Elsevier, volume 66, issue C, pages 1-12, DOI: 10.1016/j.iref.2019.10.014.
• Joshua C.C. Chan & Xuewen Yu, 2020, "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2020-108, Dec.
• Tino Berger & James Morley & Benjamin Wong, 2020, "Nowcasting the Output Gap," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2020-78, Aug.
• Bo Zhang & Bao H. Nguyen, 2020, "Real-Time Forecasting of the Australian Macroeconomy Using Flexible Bayesian VARs," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2020-91, Oct.
• Yan Li & Lian Luo & Chao Liang & Feng Ma, 2020, "The role of model bias in predicting volatility: evidence from the US equity markets," China Finance Review International, Emerald Group Publishing Limited, volume 13, issue 1, pages 140-155, October, DOI: 10.1108/CFRI-04-2020-0037.
• Nguyen Khanh Doanh & Linh Tuan Truong & Yoon Heo, 2020, "Impact of institutional and cultural distances on ASEAN's trade efficiency," Journal of Economic Studies, Emerald Group Publishing Limited, volume 49, issue 1, pages 77-94, December, DOI: 10.1108/JES-07-2020-0343.
• Luisa Mendonça & Alan De Genaro, 2020, "Detection and analysis of occurrences of spoofing in the Brazilian capital market," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, volume 28, issue 3, pages 369-408, March, DOI: 10.1108/JFRC-07-2019-0092.
• Barbora Malinska, 2020, "Time-Varying Pricing of Risk in Sovereign Bond Futures Returns," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2020/7, Mar, revised Mar 2020.
• Chiara Castelli & Angela Parenti, 2020, "Commuting in Europe: An Inter-regional Analysis on its Determinants and Spatial Effects," Working Papers, Fondazione Eni Enrico Mattei, number 2020.19, Nov.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2020, "Measuring Uncertainty and Its Effects in the COVID-19 Era," Working Papers, Federal Reserve Bank of Cleveland, number 20-32R, Oct, revised 05 Jan 2022, DOI: 10.26509/frbc-wp-202032r.
• Alexander Chudik & M. Hashem Pesaran & Mahrad Sharifvaghefi, 2020, "Variable Selection in High Dimensional Linear Regressions with Parameter Instability," Globalization Institute Working Papers, Federal Reserve Bank of Dallas, number 394, Aug, revised 05 Aug 2024, DOI: 10.24149/gwp394r3.
• Hie Joo Ahn & Matteo Luciani, 2020, "Common and Idiosyncratic Inflation," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2020-024r1, Mar, revised 01 Aug 2024, DOI: 10.17016/FEDS.2020.024r1.
• Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher J. Kurz, 2020, "Tracking Labor Market Developments during the COVID-19 Pandemic: A Preliminary Assessment," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2020-030, Apr, DOI: 10.17016/FEDS.2020.030.
• Leland D. Crane & Ryan A. Decker & Aaron Flaaen & Adrian Hamins-Puertolas & Christopher J. Kurz, 2020, "Business Exit During the COVID-19 Pandemic: Non-Traditional Measures in Historical Context," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2020-089r1, Oct, revised 15 Apr 2021, DOI: 10.17016/FEDS.2020.089r1.
• Michael T. Kiley, 2020, "Financial Conditions and Economic Activity: Insights from Machine Learning," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2020-095, Nov, DOI: 10.17016/FEDS.2020.095.
• Matteo Luciani, 2020, "Common and Idiosyncratic Inflation," FEDS Notes, Board of Governors of the Federal Reserve System (U.S.), number 2020-03-05, Mar, DOI: 10.17016/2380-7172.2508.
• Feras A. Batarseh & Munisamy Gopinath & Anderson Monken, 2020, "Artificial Intelligence Methods for Evaluating Global Trade Flows," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.), number 1296, Aug, DOI: 10.17016/IFDP.2020.1296.
• Scott A. Brave & R. Andrew Butters & Michael Fogarty, 2020, "The perils of working with Big Data and a SMALL framework you can use to avoid them," Working Paper Series, Federal Reserve Bank of Chicago, number WP-2020-35, Dec, revised 02 Mar 2020, DOI: 10.21033/wp-2020-35.
• Yifei Lyu & Jun Nie & Shu-Kuei X. Yang, 2020, "Forecasting U.S. Economic Growth in Downturns Using Cross-Country Data," Research Working Paper, Federal Reserve Bank of Kansas City, number RWP 20-09, Aug, DOI: 10.18651/RWP2020-09.
• Jan J. J. Groen & Michael Nattinger, 2020, "Alternative Indicators for Chinese Economic Activity Using Sparse PLS Regression," Economic Policy Review, Federal Reserve Bank of New York, volume 26, issue 4, pages 39-68, October.
• Dean Croushore & Stephanie M. Wilshusen, 2020, "Forecasting Consumption Spending Using Credit Bureau Data," Working Papers, Federal Reserve Bank of Philadelphia, number 20-22, Jun, DOI: 10.21799/frbp.wp.2020.22.
• Simon Freyaldenhoven, 2020, "Identification Through Sparsity in Factor Models," Working Papers, Federal Reserve Bank of Philadelphia, number 20-25, Jun, DOI: 10.21799/frbp.wp.2020.25.
• Leonardo BARGIGLI & Giulio CIFARELLI, 2020, "Structural Interdependence of Price and Demand in a Model of the Foreign Exchange Market with Heterogeneous Speculators: Evidence from High-frequency Data," Working Papers - Economics, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, number wp2020_04.rdf.
• Leonardo Bargigli & Giulio Cifarelli, 2020, "Endogenous and Exogenous Volatility in the Foreign Exchange Market," Working Papers - Economics, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, number wp2020_17.rdf.
• Jérôme Dugast & Thierry Foucault, 2020, "Equilibrium Data Mining and Data Abundance," Post-Print, HAL, number hal-02933315, Aug.
• Jérome Dugast & Thierry Foucault, 2020, "Equilibrium Data Mining and Data Abundance," Post-Print, HAL, number hal-02933316, May.
• Christoph Breunig & Enno Mammen & Anna Simoni, 2020, "Ill-posed estimation in high-dimensional models with instrumental variables," Post-Print, HAL, number hal-03089879, Nov, DOI: 10.1016/j.jeconom.2020.04.043.
• Catherine Doz & Peter Fuleky, 2020, "Dynamic Factor Models," Post-Print, HAL, number halshs-02491811, Nov, DOI: 10.1007/978-3-030-31150-6_2.
• Catherine Doz & Peter Fuleky, 2020, "Dynamic Factor Models," PSE-Ecole d'économie de Paris (Postprint), HAL, number halshs-02491811, Nov, DOI: 10.1007/978-3-030-31150-6_2.
• Daniel Levy & Tamir Mayer & Alon Raviv, 2020, "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," Working Papers, HAL, number hal-02488796, Feb.
• Jérôme Dugast & Thierry Foucault, 2020, "Equilibrium Data Mining and Data Abundance," Working Papers, HAL, number hal-03053967, Dec.
• Laurent Ferrara & Anna Simoni, 2020, "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Working Papers, HAL, number hal-04159714.
• Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020, "Modeling Joint Lives within Families," Working Papers, HAL, number halshs-02871927, Jun.
• Sami Diaf & Jörg Döpke & Ulrich Fritsche & Ida Rockenbach, 2020, "Sharks and minnows in a shoal of words: Measuring latent ideological positions of German economic research institutes based on text mining techniques," Macroeconomics and Finance Series, University of Hamburg, Department of Socioeconomics, number 202001, Aug.
• von Essen, Emma & Jansson, Joakim, 2020, "Misogynistic and Xenophobic Hate Language Online: A Matter of Anonymity," Working Paper Series, Research Institute of Industrial Economics, number 1350, Aug.
• Alfelt, Gustav & Bodnar, Taras & Javed, Farrukh & Tyrcha, Joanna, 2020, "Singular conditional autoregressive Wishart model for realized covariance matrices," Working Papers, Örebro University, School of Business, number 2021:1, Oct.
• von Essen, Emma & Jansson, Joakim, 2020, "Misogynistic and xenophobic hate language online: a matter of anonymity," Working Paper Series, Stockholm University, Swedish Institute for Social Research, number 7/2020, Aug.
• Dauth, Wolfgang & Eppelsheimer, Johann, 2020, "Preparing the sample of integrated labour market biographies (SIAB) for scientific analysis," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], volume 54, issue , pages 1-010, DOI: 10.1186/s12651-020-00275-9.
• Falco J. Bargagli-Dtoffi & Massimo Riccaboni & Armando Rungi, 2020, "Machine Learning for Zombie Hunting. Firms Failures and Financial Constraints," Working Papers, IMT School for Advanced Studies Lucca, number 01/2020, Jun, revised Jun 2020.
• Daisuke Miyakawa & Kohei Shintani, 2020, "Disagreement between Human and Machine Predictions," IMES Discussion Paper Series, Institute for Monetary and Economic Studies, Bank of Japan, number 20-E-11, Aug.
• Shree Saha & Sudha Narayanan, 2020, "A Simplified measure of nutritional empowerment using machine learning to abbreviate the Women's Empowerment in Nutrition Index (WENI)," Indira Gandhi Institute of Development Research, Mumbai Working Papers, Indira Gandhi Institute of Development Research, Mumbai, India, number 2020-031, Oct.
• Oscar Claveria & Ivana Lolic & Enric Monte & Petar Soric, 2020, "Economic determinants of employment sentiment: A socio-demographic analysis for the euro area," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202001, Jan, revised Jan 2020.
• Pacheco, Gail & Plum, Alexander T. & Sloane, Peter J., 2020, "Not Much Bounce in the Springboard: On the Mobility of Low Pay Workers," IZA Discussion Papers, IZA Network @ LISER, number 12896, Jan.
• Nicodemo, Catia & Satorra, Albert, 2020, "Exploratory Data Analysis on Large Data Sets: The Example of Salary Variation in Spanish Social Security Data," IZA Discussion Papers, IZA Network @ LISER, number 13459, Jul.
• Biewen, Martin & Kugler, Philipp, 2020, "Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)," IZA Discussion Papers, IZA Network @ LISER, number 13613, Aug.
• Shen, Kailing & Taska, Bledi, 2020, "Measuring the Impacts of COVID-19 on Job Postings in Australia Using a Reweighting-Estimation-Transformation Approach," IZA Discussion Papers, IZA Network @ LISER, number 13640, Aug.
• Nicodemo, Catia & Barzin, Samira & Lasserson, Daniel S. & Moscone, Francesco & Redding, Stuart & Shaikh, Mujaheed & Cavalli, Nicolò, 2020, "Measuring Geographical Disparities in England at the Time of COVID-19: Results Using a Composite Indicator of Population Vulnerability," IZA Discussion Papers, IZA Network @ LISER, number 13757, Sep.
• Philip Hans Franses & Thomas Wiemann, 2020, "Intertemporal Similarity of Economic Time Series: An Application of Dynamic Time Warping," Computational Economics, Springer;Society for Computational Economics, volume 56, issue 1, pages 59-75, June, DOI: 10.1007/s10614-020-09986-0.
• Rezwanul Hasan Rana & Khorshed Alam & Jeff Gow, 2020, "Health expenditure and gross domestic product: causality analysis by income level," International Journal of Health Economics and Management, Springer, volume 20, issue 1, pages 55-77, March, DOI: 10.1007/s10754-019-09270-1.
• Lu Jinks & Thomas J. Kniesner & John Leeth & Anthony T. Lo Sasso, 2020, "Opting out of workers’ compensation: Non-subscription in Texas and its effects," Journal of Risk and Uncertainty, Springer, volume 60, issue 1, pages 53-76, February, DOI: 10.1007/s11166-020-09320-x.
• Martin Obschonka & Neil Lee & Andrés Rodríguez-Pose & Johannes C. Eichstaedt & Tobias Ebert, 2020, "Big data methods, social media, and the psychology of entrepreneurial regions: capturing cross-county personality traits and their impact on entrepreneurship in the USA," Small Business Economics, Springer, volume 55, issue 3, pages 567-588, October, DOI: 10.1007/s11187-019-00204-2.
• Jens Prüfer & Patricia Prüfer, 2020, "Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands," Small Business Economics, Springer, volume 55, issue 3, pages 651-672, October, DOI: 10.1007/s11187-019-00208-y.
• Jermain C. Kaminski & Christian Hopp, 2020, "Predicting outcomes in crowdfunding campaigns with textual, visual, and linguistic signals," Small Business Economics, Springer, volume 55, issue 3, pages 627-649, October, DOI: 10.1007/s11187-019-00218-w.
• Alessandro Giovannelli & Daniele Massacci & Stefano Soccorsi, 2020, "Forecasting Stock Returns with Large Dimensional Factor Models," Working Papers, Lancaster University Management School, Economics Department, number 305661169.
• Marco Delogu & Raffaelle Lagravinese & Dimitri Paolini & Giuliano Resce, 2020, "Predicting dropout from higher education: Evidence from Italy," DEM Discussion Paper Series, Department of Economics at the University of Luxembourg, number 22-06.
• Andrea Bastianin & Matteo Manera, 2020, "A test of time reversibility based on Lmoments with an application to the business cycles of the G7 economies," Working Papers, University of Milano-Bicocca, Department of Economics, number 445, Jun, revised Jun 2020.
• Guowei Cui & Vasilis Sarafidis & Takashi Yamagata, 2020, "IV Estimation of Spatial Dynamic Panels with Interactive Effects: Large Sample Theory and an Application on Bank Attitude," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 11/20.
• Yi He & Sombut Jaidee & Jiti Gao, 2020, "Most Powerful Test against High Dimensional Free Alternatives," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 13/20.
• George Athanasopoulos & Nikolaos Kourentzes, 2020, "On the Evaluation of Hierarchical Forecasts," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 2/20.
• Leland Bybee & Bryan T. Kelly & Asaf Manela & Dacheng Xiu, 2020, "The Structure of Economic News," NBER Working Papers, National Bureau of Economic Research, Inc, number 26648, Jan.
• Evan M. Munro & Serena Ng, 2020, "Latent Dirichlet Analysis of Categorical Survey Expectations," NBER Working Papers, National Bureau of Economic Research, Inc, number 27182, May.
• Ammar Farooq & Adriana D. Kugler & Umberto Muratori, 2020, "Do Unemployment Insurance Benefits Improve Match and Employer Quality? Evidence from Recent U.S. Recessions," NBER Working Papers, National Bureau of Economic Research, Inc, number 27574, Jul.
• Bradley Shapiro & Günter J. Hitsch & Anna Tuchman, 2020, "Generalizable and Robust TV Advertising Effects," NBER Working Papers, National Bureau of Economic Research, Inc, number 27684, Aug.
• Marshall Burke & Anne Driscoll & David Lobell & Stefano Ermon, 2020, "Using Satellite Imagery to Understand and Promote Sustainable Development," NBER Working Papers, National Bureau of Economic Research, Inc, number 27879, Oct.
• Bryan S. Graham, 2020, "Sparse Network Asymptotics for Logistic Regression under Possible Misspecification," NBER Working Papers, National Bureau of Economic Research, Inc, number 27962, Oct.
• L. Galiana & B. Sakarovitch & F. Sémécurbe & Z. Smoreda, 2020, "Residential segregation, daytime segregation and spatial frictions : an analysis from mobile phone data," Documents de Travail de l'Insee - INSEE Working Papers, Institut National de la Statistique et des Etudes Economiques, number g2020-12.
• Paula Adamczyk & Ben Westmore, 2020, "Unpicking Portugal’s export performance: A microdata analysis," OECD Economics Department Working Papers, OECD Publishing, number 1618, Sep, DOI: 10.1787/71df6aa3-en.
• Nicolas Woloszko, 2020, "Tracking activity in real time with Google Trends," OECD Economics Department Working Papers, OECD Publishing, number 1634, Dec, DOI: 10.1787/6b9c7518-en.
• Al-Kasawnih Akad, 2020, "Money-Laundering Practices, Estimation, Regulation, and Commercial and Financial Cross-Border Flows," Revista OEconomica, Romanian Society for Economic Science, Revista OEconomica, issue 03-4.
• Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020, "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, volume 23, issue 1, pages 1-31.
• Elena Andreou & Patrick Gagliardini & Eric Ghysels & Mirco Rubin, 2020, "Mixed-Frequency Macro–Finance Factor Models: Theory and Applications," Journal of Financial Econometrics, Oxford University Press, volume 18, issue 3, pages 585-628.
• Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020, "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, volume 33, issue 5, pages 2223-2273.
• Kailing Shen & Bledi Taska, 2020, "Measuring the impacts of COVID-19 on job postings in Australia using a reweighting-estimation-transformation approach," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, volume 23, issue 2, pages 153-171.
• Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020, "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series, University of Pavia, Department of Economics and Management, number 181, Feb.
• Daniel Felix Ahelegbey & Paolo Giudici, 2020, "Market Risk, Connectedness and Turbulence: A Comparison of 21st Century Financial Crises," DEM Working Papers Series, University of Pavia, Department of Economics and Management, number 188, May.
• Daniel Felix Ahelegbey & Paolo Giudici, 2020, "NetVIX - A Network Volatility Index of Financial Markets," DEM Working Papers Series, University of Pavia, Department of Economics and Management, number 192, Sep.
• Daniel Felix Ahelegbey, 2020, "A Statistical Measure of Global Equity Market Risk," DEM Working Papers Series, University of Pavia, Department of Economics and Management, number 194, Nov.
• Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2020, "Modeling Turning Points In Global Equity Market," DEM Working Papers Series, University of Pavia, Department of Economics and Management, number 195, Nov.
• Roberto S. Mariano & Suleyman Ozmucur, 2020, "Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)Abstract: We study how the separation of time and risk preferences relates to a behavioral property that generalizes ," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 20-029, Aug.
• igescu, iulia, 2020, "Describing Location Shifts with One Class Support Vector Machines," MPRA Paper, University Library of Munich, Germany, number 100984, Feb.
• Glocker, Christian & Kaniovski, Serguei, 2020, "Structural modeling and forecasting using a cluster of dynamic factor models," MPRA Paper, University Library of Munich, Germany, number 101874, Jul.
• Van, Germinal, 2020, "The Effect of Economic Sectors on the National Income of West African Economies from 2010 to 2019: A Multiple Regression Analysis," MPRA Paper, University Library of Munich, Germany, number 102417, Aug.
• Gomez-Ruano, Gerardo, 2020, "Data Science: A Primer for Economists," MPRA Paper, University Library of Munich, Germany, number 102928.
• Pinto, Claudio, 2020, "Fuzzy DEA models for sports data analysis: The evaluation of the relative performances of professional (virtual) football teams," MPRA Paper, University Library of Munich, Germany, number 103129, Sep.
• Tamara, Novian & Dwi Muchisha, Nadya & Andriansyah, Andriansyah & Soleh, Agus M, 2020, "Nowcasting Indonesia’s GDP Growth Using Machine Learning Algorithms," MPRA Paper, University Library of Munich, Germany, number 105235, Jun.
• van der Plaat, Mark, 2020, "Loan sales and the tyranny of tistance in U.S. residential mortgage lending," MPRA Paper, University Library of Munich, Germany, number 107519, Sep, revised 20 Apr 2021.
• Maiorova, Ksenia & Fokin, Nikita, 2020, "Наукастинг Темпов Роста Стоимостных Объемов Экспорта И Импорта По Товарным Группам
  [Nowcasting the growth rates of the export and import by commodity groups]," MPRA Paper, University Library of Munich, Germany, number 109557, Jun.
• Fernandez, Julian, 2020, "Exchange Rate Uncertainty and the Interest Rate Parity," MPRA Paper, University Library of Munich, Germany, number 116010, revised 2022.
• Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020, "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," MPRA Paper, University Library of Munich, Germany, number 98785, Feb.
• Omoshoro-Jones, Oyeyinka Sunday & Bonga-Bonga, Lumengo, 2020, "Intra-regional spillovers from Nigeria and South Africa to the rest of Africa: New evidence from a FAVAR model," MPRA Paper, University Library of Munich, Germany, number 99514, Apr.
• Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020, "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers, University of Pretoria, Department of Economics, number 202058, Jun.
• Markus Brunnermeier & Rohit Lamba & Carlos Segura-Rodriguez, 2020, "Inverse Selection," Working Papers, Princeton University. Economics Department., number 2020-50, Apr.
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• Damian Przekop, 2020, "Feature Engineering for Anti-Fraud Models Based on Anomaly Detection," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, volume 12, issue 3, pages 301-316, September.
• António Rua & Carlos Melo Gouveia & Nuno Lourenço, 2020, "Forecasting tourism with targeted predictors in a data-rich environment," Working Papers, Banco de Portugal, Economics and Research Department, number w202005.
• Castellares, Renzo & Cornejo, Gerson, 2020, "A Leading Indicator for Employment using Big Data," Working Papers, Banco Central de Reserva del Perú, number 2020-009, Jun.
• Coronado, Hilary & Lahura, Erick & Vega, Marco, 2020, "¿Qué tan rígidos son los precios en línea? Evidencia para Perú usando Big Data," Working Papers, Banco Central de Reserva del Perú, number 2020-018, Dec.
• Oleksandr Faryna & Tho Pham & Oleksandr Talavera & Andriy Tsapin, 2020, "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2020-02, Mar.
• Michael P. Clements, 2020, "Individual Forecaster Perceptions of the Persistence of Shocks to GDP," ICMA Centre Discussion Papers in Finance, Henley Business School, University of Reading, number icma-dp2020-02, Jan.
• Fornaro, Paolo, 2020, "Nowcasting Industrial Production Using Uncoventional Data Sources," ETLA Working Papers, The Research Institute of the Finnish Economy, number 80, Jun.
• Minsung Kang, 2020, "Big Data and Policy Directions for Korean Service Firms," Industrial Economic Review, Korea Institute for Industrial Economics and Trade, number 20-11, Aug.
• Marianna Brunetti & Roberta De Luca, 2020, "Pre-selection in Cointegration-based Pairs Trading," CEIS Research Paper, Tor Vergata University, CEIS, number 500, Jun, revised 10 Mar 2021.
• Francesca Di Iorio & Stefano Fachin, 2020, "Forecasting mortality rates and life expectancy in the year of Covid-19," DSS Empirical Economics and Econometrics Working Papers Series, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome, number 2020/1, Nov.
• Neeti Mathur & Himanshu Mathur, 2020, "Application of GARCH Models For Volatility Modelling of Stock Market Returns: Evidences From BSE India," Proceedings of Business and Management Conferences, International Institute of Social and Economic Sciences, number 10112533, Feb.
• Sandra Figueiredo & André Soares & Neuza Vieira & Miguel Devezas, 2020, "A psycholinguistic analysis of world leaders? discourses concerning the COVID-19 context: authenticity and emotional tone," International Journal of Social Sciences, International Institute of Social and Economic Sciences, volume 9, issue 2, pages 66-69, September.
• Tomasz Piotr Kostyra & Michał Rubaszek, 2020, "Forecasting the Yield Curve for Poland," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, volume 5, issue 2, pages 103-117, December, DOI: 10.2478/erfin-2020-0006.
• Sinem Güler KANGALLI-UYAR, 2020, "The Matrix Exponential Spatial Specification Approach for Big Datasets: The Analysis of Istanbul Office Market," Sosyoekonomi Journal, Sosyoekonomi Society, issue 28(43).
• Fernando Moraes & Rodrigo De-Losso, 2020, "Risk Factor Centrality and the Cross-Section of Expected Returns," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2020_17, Sep.
• Fernando Moraes & Rodrigo De-Losso, 2020, "Risk Factors’ CPDAG Roots and the Cross-Section of Expected Returns," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2020_18, Sep.
• Sabine Zinn & Ariane Würbach & Hans Walter Steinhauer & Angelina Hammon, 2020, "Attrition and selectivity of the NEPS starting cohorts: an overview of the past 8 years
  [Ausfall und Selektivitäten in den NEPS Startkohorten: ein Überblick über die letzten 8 Jahre]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, volume 14, issue 2, pages 163-206, July, DOI: 10.1007/s11943-020-00268-7.
• Arianna Agosto & Paolo Giudici, 2020, "COVID-19 contagion and digital finance," Digital Finance, Springer, volume 2, issue 1, pages 159-167, September, DOI: 10.1007/s42521-020-00021-3.
• Larisa Adamyan & Kirill Efimov & Cathy Y. Chen & Wolfgang K. Härdle, 2020, "Adaptive weights clustering of research papers," Digital Finance, Springer, volume 2, issue 3, pages 169-187, December, DOI: 10.1007/s42521-020-00017-z.
• Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020, "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, volume 58, issue 1, pages 139-167, January, DOI: 10.1007/s00181-019-01788-0.
• Paolo Fornaro & Henri Luomaranta, 2020, "Nowcasting Finnish real economic activity: a machine learning approach," Empirical Economics, Springer, volume 58, issue 1, pages 55-71, January, DOI: 10.1007/s00181-019-01809-y.
• K. Benkovskis & B. Bluhm & E. Bobeica & C. Osbat & S. Zeugner, 2020, "What drives export market shares? It depends! An empirical analysis using Bayesian model averaging," Empirical Economics, Springer, volume 59, issue 2, pages 817-869, August, DOI: 10.1007/s00181-019-01727-z.
• Maximo Camacho & Angela Caro & German Lopez-Buenache, 2020, "The two-speed Europe in business cycle synchronization," Empirical Economics, Springer, volume 59, issue 3, pages 1069-1084, September, DOI: 10.1007/s00181-019-01730-4.
• Yaohao Peng & Lucas Ferreira Mation, 2020, "The Challenge of Pairing Big Datasets: Probabilistic Record Linkage Methods and Diagnosis of Their Empirical Viability," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 16, issue 1, pages 35-57, April, DOI: 10.1007/s41549-020-00043-1.
• Yongchen Zhao, 2020, "Predicting U.S. Business Cycle Turning Points Using Real-Time Diffusion Indexes Based on a Large Data Set," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 16, issue 2, pages 77-97, November, DOI: 10.1007/s41549-020-00046-y.
• Wolfgang Dauth & Johann Eppelsheimer, 2020, "Preparing the sample of integrated labour market biographies (SIAB) for scientific analysis: a guide," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), volume 54, issue 1, pages 1-14, December, DOI: 10.1186/s12651-020-00275-9.