Research classified by Journal of Economic Literature (JEL) codes

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

2020

• 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.
• Baris Yalin Uzunlu & Syed Muzammil Hussain, 2020, "Employing Machine Learning Algorithms to build Trading Strategies with higher than Risk-Free Returns," International Econometric Review (IER), Economic Research Association, volume 12, issue 2, pages 112-138, September.
• 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 & Marzio Galeotti & Matteo Manera, 2014, "Forecasting the oil-gasoline price relationship: should we care about the Rockets and the Feathers?," Working Papers, University of Milano-Bicocca, Department of Economics, number 269, Mar, revised Mar 2014.
• 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.
• Mark Braverman & Sylvain Chassang, 2020, "Data-Driven Incentive Alignment in Capitation Schemes," Working Papers, Princeton University. Economics Department., number 2020-60, Mar.
• 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.
• Vladimir Batagelj, 2020, "On fractional approach to analysis of linked networks," Scientometrics, Springer;Akadémiai Kiadó, volume 123, issue 2, pages 621-633, May, DOI: 10.1007/s11192-020-03383-y.
• Andrea Bastianin, 2020, "Robust measures of skewness and kurtosis for macroeconomic and financial time series," Applied Economics, Taylor & Francis Journals, volume 52, issue 7, pages 637-670, February, DOI: 10.1080/00036846.2019.1640862.
• Jean Boivin & Marc P. Giannoni & Dalibor Stevanović, 2020, "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, volume 38, issue 2, pages 272-284, April, DOI: 10.1080/07350015.2018.1497507.
• Zhang, Bo & Nguyen, Bao H., 2020, "Real-time forecasting of the Australian macroeconomy using Bayesian VARs," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2020-12.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020, "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LLC, volume 20, issue 1, pages 176-235, March, DOI: 10.1177/1536867X20909697.
• Laura Zieger & John Jerrim & Jake Anders & Nikki Shure, 2020, "Conditioning: How background variables can influence PISA scores," CEPEO Working Paper Series, UCL Centre for Education Policy and Equalising Opportunities, number 20-09, Apr, revised Apr 2020.
• Fiona Burlig & Christopher Knittel & David Rapson & Mar Reguant & Catherine Wolfram, 2020, "Machine Learning from Schools about Energy Efficiency," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, volume 7, issue 6, pages 1181-1217, DOI: 10.1086/710606.
• Tae-Hwy Lee & Ekaterina Seregina, 2020, "Learning from Forecast Errors: A New Approach to Forecast Combination," Working Papers, University of California at Riverside, Department of Economics, number 202024, Sep.
• Tae-Hwy Lee & Ekaterina Seregina, 2020, "Optimal Portfolio Using Factor Graphical Lasso," Working Papers, University of California at Riverside, Department of Economics, number 202025, Sep.
• Schubert, Torben & Jäger, Angela & Türkeli, Serdar & Visentin, Fabiana, 2020, "Addressing the productivity paradox with big data: A literature review and adaptation of the CDM econometric model," MERIT Working Papers, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT), number 2020-050, Nov.
• Jonas Striaukas & Martin Schumacher & Harald Binder & Matthias Weber, 2020, "Network-Constrained Covariate Coefficient and Connection Sign Estimation," Working Papers on Finance, University of St. Gallen, School of Finance, number 2001, Jan.
• Arnerić Josip, 2020, "Realized density estimation using intraday prices," Croatian Review of Economic, Business and Social Statistics, Paradigm, volume 6, issue 1, pages 1-9, May, DOI: 10.2478/crebss-2020-0001.
• Wójcik Filip & Górnik Michał, 2020, "Improvement of E-Commerce Recommendation Systems with Deep Hybrid Collaborative Filtering with Content: A Case Study," Econometrics. Advances in Applied Data Analysis, Paradigm, volume 24, issue 3, pages 37-50, September, DOI: 10.15611/eada.2020.3.03.
• Urbańczyk Dominika M., 2020, "Competing Risks Models for an Enterprises Duration on the Market," Folia Oeconomica Stetinensia, Paradigm, volume 20, issue 1, pages 456-473, June, DOI: 10.2478/foli-2020-0027.
• Szkutnik Tomasz, 2020, "Identification of Outliers in High Density Areas with the Use of a Quantile Regression Model," Folia Oeconomica Stetinensia, Paradigm, volume 20, issue 2, pages 375-391, December, DOI: 10.2478/foli-2020-0054.
• Gružauskas Valentas & Kriščiūnas Andrius & Čalnerytė Dalia & Navickas Valentinas, 2020, "Analytical Method for Correction Coefficient Determination for Applying Comparative Method for Real Estate Valuation," Real Estate Management and Valuation, Sciendo, volume 28, issue 2, pages 52-62, June, DOI: 10.1515/remav-2020-0015.
• Marek Stelmach & Marcin Chlebus, 2020, "Novel multilayer stacking framework with weighted ensemble approach for multiclass credit scoring problem application," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2020-08.
• Christian Glocker & Serguei Kaniovski, 2020, "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers, WIFO, number 614, Oct.
• Stefan Jestl & Emanuel List, 2020, "Distributional National Accounts (DINA) for Austria, 2004-2016," wiiw Working Papers, The Vienna Institute for International Economic Studies, wiiw, number 175, Feb.
• Stefan Ederer & Stefan Humer & Stefan Jestl & Emanuel List, 2020, "Distributional National Accounts (DINA) with Household Survey Data: Methodology and Results for European Countries," wiiw Working Papers, The Vienna Institute for International Economic Studies, wiiw, number 180, May.
• Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2020, "Assessing international commonality in macroeconomic uncertainty and its effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 35, issue 3, pages 273-293, April, DOI: 10.1002/jae.2750.
• Antoine A. Djogbenou, 2020, "Comovements in the real activity of developed and emerging economies: A test of global versus specific international factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., volume 35, issue 3, pages 344-370, April, DOI: 10.1002/jae.2749.
• Benedikt Maas, 2020, "Short‐term forecasting of the US unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., volume 39, issue 3, pages 394-411, April, DOI: 10.1002/for.2630.
• Oguzhan Cepni & Rangan Gupta & I. Ethem Güney & M. Yilmaz, 2020, "Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages," Journal of Forecasting, John Wiley & Sons, Ltd., volume 39, issue 6, pages 966-985, September, DOI: 10.1002/for.2669.
• 牛霖琳 & 夏红玉 & 许秀, 2020, "中国地方债务的省级风险度量和网络外溢风险," Working Papers, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University, number 2020-11-12, Nov.
• Raddant, Matthias & Takahashi, Hiroshi, 2020, "Corporate boards, interorganizational ties and profitability: The case of Japan," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics, number 2020-02.
• Vrigazova, Borislava, 2020, "Tenfold Bootstrap as Resampling Method in Classification Problems," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020".
• Isaak, Andrew Jay & Selasinsky, Constantin von, 2020, "It's all in the (Sub-)title? Expanding Signal Evaluation in Crowdfunding Research," EconStor Conference Papers, ZBW - Leibniz Information Centre for Economics, number 338889.
• Zinn, Sabine & Würbach, Ariane & Steinhauer, Hans Walter, 2020, "Attrition and Selectivity of the NEPS Starting Cohorts: An Overview of the Past 8 Years," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, volume 14, pages 163-206, DOI: 10.1007/s11943-020-00268-7.
• Levy, Daniel & Mayer, Tamir & Raviv, Alon, 2020, "Academic Scholarship in Light of the 2008 Financial Crisis: Textual Analysis of NBER Working Papers," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 214194.
• Martínez-Hernández, Catalina, 2020, "Disentangling the effects of multidimensional monetary policy on inflation and inflation expectations in the euro area," Discussion Papers, Free University Berlin, School of Business & Economics, number 2020/18, DOI: 10.17169/refubium-28493.
• Faryna, Oleksandr & Pham, Tho & Talavera, Oleksandr & Tsapin, Andriy, 2020, "Wage Setting and Unemployment: Evidence from Online Job Vacancy Data," GLO Discussion Paper Series, Global Labor Organization (GLO), number 503.
• Greyling, Talita & Rossouw, Stephanie & Adhikari, Tamanna, 2020, "Happiness-lost: Did Governments make the right decisions to combat Covid-19?," GLO Discussion Paper Series, Global Labor Organization (GLO), number 556.
• Rossouw, Stephanie & Greyling, Talita & Adhikari, Tamanna & Morrison, Phillip S., 2020, "Markov switching models for happiness during a pandemic: The New-Zealand experience," GLO Discussion Paper Series, Global Labor Organization (GLO), number 573.