Research classified by Journal of Economic Literature (JEL) codes

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Top JEL
/ C: Mathematical and Quantitative Methods
/ / C1: Econometric and Statistical Methods and Methodology: General
/ / / C11: Bayesian Analysis: General

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This JEL code is mentioned in the following RePEc Biblio entries:

1. Bayesian Vector autoregressions (BVARs)

2019

• Agnieszka Borowska & Lennart Hoogerheide & Siem Jan Koopman & Herman K. van Dijk, 2019, "Partially Censored Posterior for robust and efficient risk evaluation," Working Paper, Norges Bank, number 2019/12, Aug.
• Hilde C. Bjørnland & Julia Zhulanova, 2019, "The shale oil boom and the U.S. economy: Spillovers and time-varying effects," Working Paper, Norges Bank, number 2019/14, Aug.
• Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2019, "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School, number No 01/2019, Jan.
• Vegard H. Larsen & Leif Anders Thorsrud & Julia Zhulanova, 2019, "News-driven inflation expectations and information rigidities," Working Papers, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School, number No 03/2019, Apr.
• Marko Melolinna & Máté Tóth, 2019, "Trend and cycle shocks in Bayesian unobserved components models for UK productivity," Bank of England working papers, Bank of England, number 826, Sep.
• Otrok Christopher & Pourpourides Panayiotis M., 2019, "On the cyclicality of real wages and wage differentials," The B.E. Journal of Macroeconomics, De Gruyter, volume 19, issue 1, pages 1-18, January, DOI: 10.1515/bejm-2017-0047.
• Mariolis Theodore & Konstantakis Konstantinos N. & Michaelides Panayotis G. & Tsionas Efthymios G., 2019, "A non-linear Keynesian Goodwin-type endogenous model of the cycle: Bayesian evidence for the USA," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 23, issue 1, pages 1-16, February, DOI: 10.1515/snde-2016-0137.
• Chan Joshua C.C. & Fry-McKibbin Renée A. & Hsiao Cody Yu-Ling, 2019, "A regime switching skew-normal model of contagion," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, volume 23, issue 1, pages 1-24, February, DOI: 10.1515/snde-2017-0001.
• Chiara Limongi Concetto & Francesco Ravazzolo, 2019, "Optimism in Financial Markets: Stock Market Returns and Investor Sentiments," BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen, number BEMPS56, Jan.
• Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019, "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen, number BEMPS59, Feb.
• Zhou, W. & O’Neill, E. & Moncaster, A. & Reiner, D. & Guthrie, P., 2019, "Applying Bayesian Model Averaging to Characterise Urban Residential Stock Turnover Dynamics," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 1986, Oct.
• Jim Malley & Ulrich Woitek, 2019, "Estimated human capital externalities in an endogenous growth framework," CESifo Working Paper Series, CESifo, number 7603.
• Domenico Delli Gatti & Jakob Grazzini, 2019, "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series, CESifo, number 7894.
• Ian Martin & Stefan Nagel, 2019, "Market Efficiency in the Age of Big Data," CESifo Working Paper Series, CESifo, number 8015.
• Laurent Barras & O. Scaillet & Russ Wermers, 2019, "Reassessing False Discoveries in Mutual Fund Performance: Skill, Luck, or Lack of Power? A Reply," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-61, Aug.
• Paola Andrea Vaca González, 2019, "Cálculo y evaluación del riesgo operativo en entidades de salud a partir del enfoque de redes bayesianas," Ensayos de Economía, Universidad Nacional de Colombia Sede Medellín, number 18302, Jul, DOI: 10.15446/ede.v29n55.78411.
• Bianchi, Francesco & Kung, Howard & Tirskikh, Mikhail, 2019, "The Origins and Effects of Macroeconomic Uncertainty," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13450, Jan.
• Koenig, Michael & Hsieh, Chih-Sheng & Liu, Xiaodong, 2019, "A Structural Model for the Coevolution of Networks and Behavior," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13911, Aug.
• Marcellino, Massimiliano & Clark, Todd & Carriero, Andrea, 2019, "Assessing International Commonality in Macroeconomic Uncertainty and Its Effects," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13970, Aug.
• Lawson, Jeremy & Watt, Abigail & Martinez, Carolina & Fu, Rong, 2019, "Chinese Financial Conditions and their Spillovers to the Global Economy and Markets," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 14065, Oct.
• Martin, Ian & Nagel, Stefan, 2019, "Market Efficiency in the Age of Big Data," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 14235, Dec.
• T. Philipp Dybowski & Bernd Kempa, 2019, "The ECB’s monetary pillar after the financial crisis," CQE Working Papers, Center for Quantitative Economics (CQE), University of Muenster, number 8519, Jul.
• Gehrke, Britta, 2019, "Fiscal Rules And Unemployment," Macroeconomic Dynamics, Cambridge University Press, volume 23, issue 8, pages 3293-3326, December.
• Martin Bruns & Michele Piffer, 2019, "Bayesian Structural VAR Models: A New Approach for Prior Beliefs on Impulse Responses," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1796.
• Kanngiesser, Derrick & Martin, Reiner & Moccero, Diego & Maurin, Laurent, 2019, "The macroeconomic impact of changes in economic bank capital buffers," Macroprudential Bulletin, European Central Bank, volume 8.
• Attinasi, Maria Grazia & Berardini, Francesco & Palazzo, Alessandra Anna, 2019, "Do public wages in the euro area explain private wage developments? An empirical investigation," Working Paper Series, European Central Bank, number 2231, Jan.
• Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019, "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series, European Central Bank, number 2250, Mar.
• Brand, Claus & Mazelis, Falk, 2019, "Taylor-rule consistent estimates of the natural rate of interest," Working Paper Series, European Central Bank, number 2257, Mar.
• Amisano, Gianni & Tristani, Oreste, 2019, "Uncertainty shocks, monetary policy and long-term interest rates," Working Paper Series, European Central Bank, number 2279, May.
• Huber, Florian & Koop, Gary & Onorante, Luca, 2019, "Inducing sparsity and shrinkage in time-varying parameter models," Working Paper Series, European Central Bank, number 2325, Nov.
• García, Juan Angel & Poon, Aubrey, 2019, "Inflation trends in Asia: implications for central banks," Working Paper Series, European Central Bank, number 2338, Dec.
• Kutlu, Levent & Sickles, Robin & Tsionas, Mike G., 2019, "Heterogeneous Decision-Making and Market Power," Working Papers, Rice University, Department of Economics, number 19-008, Sep.
• Chin-Sheng Huang & Yi-Sheng Liu, 2019, "Machine Learning on Stock Price Movement Forecast: The Sample of the Taiwan Stock Exchange," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 2, pages 189-201.
• Chia-Cheng Chen & Yisheng Liu & Ting-Hsin Hsu, 2019, "An Analysis on Investment Performance of Machine Learning: An Empirical Examination on Taiwan Stock Market," International Journal of Economics and Financial Issues, Econjournals, volume 9, issue 4, pages 1-10.
• Mariam Camarero & Laura Montolio & Cecilio Tamarit, 2019, "Determinants of German outward FDI: variable selection using Bayesian statistical," Working Papers, Department of Applied Economics II, Universidad de Valencia, number 1906, Sep.
• Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2019, "Searching The Us Fdi Determinants In The Eu: Is There A Euro Effect?," Working Papers, Department of Applied Economics II, Universidad de Valencia, number 1916, Nov.
• Kapetanios, George & Masolo, Riccardo M. & Petrova, Katerina & Waldron, Matthew, 2019, "A time-varying parameter structural model of the UK economy," Journal of Economic Dynamics and Control, Elsevier, volume 106, issue C, pages 1-1, DOI: 10.1016/j.jedc.2019.05.012.
• Yong, Chen & Dingming, Liu, 2019, "How does government spending news affect interest rates? Evidence from the United States," Journal of Economic Dynamics and Control, Elsevier, volume 108, issue C, DOI: 10.1016/j.jedc.2019.103747.
• Fasolo, Angelo Marsiglia, 2019, "Monetary policy volatility shocks in Brazil," Economic Modelling, Elsevier, volume 81, issue C, pages 348-360, DOI: 10.1016/j.econmod.2019.06.012.
• Camarero, Mariam & Montolio, Laura & Tamarit, Cecilio, 2019, "What drives German foreign direct investment? New evidence using Bayesian statistical techniques," Economic Modelling, Elsevier, volume 83, issue C, pages 326-345, DOI: 10.1016/j.econmod.2019.08.017.
• Chaim, Pedro & Laurini, Márcio P., 2019, "Nonlinear dependence in cryptocurrency markets," The North American Journal of Economics and Finance, Elsevier, volume 48, issue C, pages 32-47, DOI: 10.1016/j.najef.2019.01.015.
• Tetlow, Robert, 2019, "The monetary policy response to uncertain inflation persistence," Economics Letters, Elsevier, volume 175, issue C, pages 5-8, DOI: 10.1016/j.econlet.2018.10.034.
• Wang, Bin, 2019, "Measuring the natural rate of interest of China: A time varying perspective," Economics Letters, Elsevier, volume 176, issue C, pages 117-120, DOI: 10.1016/j.econlet.2019.01.011.
• Casarin, Roberto & Costola, Michele, 2019, "Structural changes in large economic datasets: A nonparametric homogeneity test," Economics Letters, Elsevier, volume 176, issue C, pages 55-59, DOI: 10.1016/j.econlet.2018.12.020.
• Cheng, Tingting & Gao, Jiti & Yan, Yayi, 2019, "Regime switching panel data models with interactive fixed effects," Economics Letters, Elsevier, volume 177, issue C, pages 47-51, DOI: 10.1016/j.econlet.2019.01.024.
• Evgenidis, Anastasios & Salachas, Evangelos, 2019, "Unconventional monetary policy and the credit channel in the euro area," Economics Letters, Elsevier, volume 185, issue C, DOI: 10.1016/j.econlet.2019.108695.
• Sun, Yutec & Ishihara, Masakazu, 2019, "A computationally efficient fixed point approach to dynamic structural demand estimation," Journal of Econometrics, Elsevier, volume 208, issue 2, pages 563-584, DOI: 10.1016/j.jeconom.2018.09.021.
• Fulop, Andras & Li, Junye, 2019, "Bayesian estimation of dynamic asset pricing models with informative observations," Journal of Econometrics, Elsevier, volume 209, issue 1, pages 114-138, DOI: 10.1016/j.jeconom.2018.11.014.
• Jarociński, Marek & Marcet, Albert, 2019, "Priors about observables in vector autoregressions," Journal of Econometrics, Elsevier, volume 209, issue 2, pages 238-255, DOI: 10.1016/j.jeconom.2018.12.023.
• Kaufmann, Sylvia & Schumacher, Christian, 2019, "Bayesian estimation of sparse dynamic factor models with order-independent and ex-post mode identification," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 116-134, DOI: 10.1016/j.jeconom.2018.11.008.
• Koop, Gary & Korobilis, Dimitris & Pettenuzzo, Davide, 2019, "Bayesian compressed vector autoregressions," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 135-154, DOI: 10.1016/j.jeconom.2018.11.009.
• McAlinn, Kenichiro & West, Mike, 2019, "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 155-169, DOI: 10.1016/j.jeconom.2018.11.010.
• Baştürk, N. & Borowska, A. & Grassi, S. & Hoogerheide, L. & van Dijk, H.K., 2019, "Forecast density combinations of dynamic models and data driven portfolio strategies," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 170-186, DOI: 10.1016/j.jeconom.2018.11.011.
• Fisher, Mark & Jensen, Mark J., 2019, "Bayesian inference and prediction of a multiple-change-point panel model with nonparametric priors," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 187-202, DOI: 10.1016/j.jeconom.2018.11.012.
• Herbst, Edward & Schorfheide, Frank, 2019, "Tempered particle filtering," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 26-44, DOI: 10.1016/j.jeconom.2018.11.003.
• Geweke, John & Durham, Garland, 2019, "Sequentially adaptive Bayesian learning algorithms for inference and optimization," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 4-25, DOI: 10.1016/j.jeconom.2018.11.002.
• Dellaportas, Petros & Tsionas, Mike G., 2019, "Importance sampling from posterior distributions using copula-like approximations," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 45-57, DOI: 10.1016/j.jeconom.2018.11.004.
• Bianchi, Daniele & Billio, Monica & Casarin, Roberto & Guidolin, Massimo, 2019, "Modeling systemic risk with Markov Switching Graphical SUR models," Journal of Econometrics, Elsevier, volume 210, issue 1, pages 58-74, DOI: 10.1016/j.jeconom.2018.11.005.
• Isakov, Leah & Lo, Andrew W. & Montazerhodjat, Vahid, 2019, "Is the FDA too conservative or too aggressive?: A Bayesian decision analysis of clinical trial design," Journal of Econometrics, Elsevier, volume 211, issue 1, pages 117-136, DOI: 10.1016/j.jeconom.2018.12.009.
• Liao, Yuan & Simoni, Anna, 2019, "Bayesian inference for partially identified smooth convex models," Journal of Econometrics, Elsevier, volume 211, issue 2, pages 338-360, DOI: 10.1016/j.jeconom.2019.03.001.
• Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019, "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, volume 212, issue 1, pages 137-154, DOI: 10.1016/j.jeconom.2019.04.024.
• Hautsch, Nikolaus & Voigt, Stefan, 2019, "Large-scale portfolio allocation under transaction costs and model uncertainty," Journal of Econometrics, Elsevier, volume 212, issue 1, pages 221-240, DOI: 10.1016/j.jeconom.2019.04.028.
• Korobilis, Dimitris & Pettenuzzo, Davide, 2019, "Adaptive hierarchical priors for high-dimensional vector autoregressions," Journal of Econometrics, Elsevier, volume 212, issue 1, pages 241-271, DOI: 10.1016/j.jeconom.2019.04.029.
• Petrova, Katerina, 2019, "A quasi-Bayesian local likelihood approach to time varying parameter VAR models," Journal of Econometrics, Elsevier, volume 212, issue 1, pages 286-306, DOI: 10.1016/j.jeconom.2019.04.031.
• Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019, "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, volume 212, issue 1, pages 323-344, DOI: 10.1016/j.jeconom.2019.04.033.
• Pesaran, M. Hashem & Smith, Ron P., 2019, "A Bayesian analysis of linear regression models with highly collinear regressors," Econometrics and Statistics, Elsevier, volume 11, issue C, pages 1-21, DOI: 10.1016/j.ecosta.2018.10.001.
• Caruso, Alberto & Reichlin, Lucrezia & Ricco, Giovanni, 2019, "Financial and fiscal interaction in the Euro Area crisis: This time was different," European Economic Review, Elsevier, volume 119, issue C, pages 333-355, DOI: 10.1016/j.euroecorev.2019.08.002.
• Best, Gabriela & Hur, Joonyoung, 2019, "Bad luck, bad policy, and learning? A Markov-switching approach to understanding postwar U.S. macroeconomic dynamics," European Economic Review, Elsevier, volume 119, issue C, pages 55-78, DOI: 10.1016/j.euroecorev.2019.06.006.
• Yang, Qiao, 2019, "Stock returns and real growth: A Bayesian nonparametric approach," Journal of Empirical Finance, Elsevier, volume 53, issue C, pages 53-69, DOI: 10.1016/j.jempfin.2019.06.005.
• Müller, Gernot & Seibert, Armin, 2019, "Bayesian estimation of stable CARMA spot models for electricity prices," Energy Economics, Elsevier, volume 78, issue C, pages 267-277, DOI: 10.1016/j.eneco.2018.10.016.
• Chen, Liyuan & Zerilli, Paola & Baum, Christopher F., 2019, "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Energy Economics, Elsevier, volume 79, issue C, pages 111-129, DOI: 10.1016/j.eneco.2018.03.032.
• Ghoddusi, Hamed & Creamer, Germán G. & Rafizadeh, Nima, 2019, "Machine learning in energy economics and finance: A review," Energy Economics, Elsevier, volume 81, issue C, pages 709-727, DOI: 10.1016/j.eneco.2019.05.006.
• Fontana, Magda & Iori, Martina & Nava, Consuelo Rubina, 2019, "Switching behavior in the Italian electricity retail market: Logistic and mixed effect Bayesian estimations of consumer choice," Energy Policy, Elsevier, volume 129, issue C, pages 339-351, DOI: 10.1016/j.enpol.2019.01.060.
• Zhang, Tong & Shi, Xunpeng & Zhang, Dayong & Xiao, Junji, 2019, "Socio-economic development and electricity access in developing economies: A long-run model averaging approach," Energy Policy, Elsevier, volume 132, issue C, pages 223-231, DOI: 10.1016/j.enpol.2019.05.031.
• Li, Zhuo & Panza, Laura & Song, Yong, 2019, "The evolution of ottoman–European market linkages, 1469–1914: Evidence from dynamic factor models," Explorations in Economic History, Elsevier, volume 71, issue C, pages 112-134, DOI: 10.1016/j.eeh.2018.10.002.
• Skintzi, Vasiliki D., 2019, "Determinants of stock-bond market comovement in the Eurozone under model uncertainty," International Review of Financial Analysis, Elsevier, volume 61, issue C, pages 20-28, DOI: 10.1016/j.irfa.2018.12.005.
• Matkovskyy, Roman & Jalan, Akanksha, 2019, "From financial markets to Bitcoin markets: A fresh look at the contagion effect," Finance Research Letters, Elsevier, volume 31, issue C, pages 93-97, DOI: 10.1016/j.frl.2019.04.007.
• Bezemer, Dirk & Zhang, Lu, 2019, "Credit composition and the severity of post-crisis recessions," Journal of Financial Stability, Elsevier, volume 42, issue C, pages 52-66, DOI: 10.1016/j.jfs.2019.05.010.
• Kavaler, Itay & Smorodinsky, Rann, 2019, "On comparison of experts," Games and Economic Behavior, Elsevier, volume 118, issue C, pages 94-109, DOI: 10.1016/j.geb.2019.08.005.
• Buncic, Daniel & Stern, Cord, 2019, "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, volume 63, issue C, DOI: 10.1016/j.intfin.2019.101138.
• Frazier, David T. & Maneesoonthorn, Worapree & Martin, Gael M. & McCabe, Brendan P.M., 2019, "Approximate Bayesian forecasting," International Journal of Forecasting, Elsevier, volume 35, issue 2, pages 521-539, DOI: 10.1016/j.ijforecast.2018.08.003.
• McAdam, Peter & Warne, Anders, 2019, "Euro area real-time density forecasting with financial or labor market frictions," International Journal of Forecasting, Elsevier, volume 35, issue 2, pages 580-600, DOI: 10.1016/j.ijforecast.2018.10.013.
• Knotek, Edward S. & Zaman, Saeed, 2019, "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, volume 35, issue 4, pages 1708-1724, DOI: 10.1016/j.ijforecast.2018.10.012.
• Cai, Michael & Del Negro, Marco & Giannoni, Marc P. & Gupta, Abhi & Li, Pearl & Moszkowski, Erica, 2019, "DSGE forecasts of the lost recovery," International Journal of Forecasting, Elsevier, volume 35, issue 4, pages 1770-1789, DOI: 10.1016/j.ijforecast.2018.12.001.
• Spruk, Rok & Kovac, Mitja, 2019, "Replicating and extending Martin-Quinn scores," International Review of Law and Economics, Elsevier, volume 60, issue C, DOI: 10.1016/j.irle.2019.105861.
• Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019, "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, volume 102, issue C, pages 43-58, DOI: 10.1016/j.jbankfin.2019.03.009.
• Kang, Woo-Young & Poshakwale, Sunil, 2019, "A new approach to optimal capital allocation for RORAC maximization in banks," Journal of Banking & Finance, Elsevier, volume 106, issue C, pages 153-165, DOI: 10.1016/j.jbankfin.2019.06.006.
• Byrne, Joseph P. & Cao, Shuo & Korobilis, Dimitris, 2019, "Decomposing global yield curve co-movement," Journal of Banking & Finance, Elsevier, volume 106, issue C, pages 500-513, DOI: 10.1016/j.jbankfin.2019.07.018.
• Sapci, Ayse & Miles, Bradley, 2019, "Bank size, returns to scale, and cost efficiency," Journal of Economics and Business, Elsevier, volume 105, issue C, DOI: 10.1016/j.jeconbus.2019.04.003.
• Bergholt, Drago & Larsen, Vegard H. & Seneca, Martin, 2019, "Business cycles in an oil economy," Journal of International Money and Finance, Elsevier, volume 96, issue C, pages 283-303, DOI: 10.1016/j.jimonfin.2017.07.005.
• Crespo Cuaresma, Jesus & von Schweinitz, Gregor & Wendt, Katharina, 2019, "On the empirics of reserve requirements and economic growth," Journal of Macroeconomics, Elsevier, volume 60, issue C, pages 253-274, DOI: 10.1016/j.jmacro.2019.03.004.
• Cardani, Roberta & Paccagnini, Alessia & Villa, Stefania, 2019, "Forecasting with instabilities: An application to DSGE models with financial frictions," Journal of Macroeconomics, Elsevier, volume 61, issue C, pages 1-1, DOI: 10.1016/j.jmacro.2019.103133.
• Akbar, Muhammad & Iqbal, Farhan & Noor, Farzana, 2019, "Bayesian analysis of dynamic linkages among gold price, stock prices, exchange rate and interest rate in Pakistan," Resources Policy, Elsevier, volume 62, issue C, pages 154-164, DOI: 10.1016/j.resourpol.2019.03.003.
• Ivo da Rocha Lima Filho, Roberto, 2019, "Does PPI lead CPI IN Brazil?," International Journal of Production Economics, Elsevier, volume 214, issue C, pages 73-79, DOI: 10.1016/j.ijpe.2019.03.007.
• Baltagi, Badi H. & Egger, Peter H. & Kesina, Michaela, 2019, "Contagious exporting and foreign ownership: Evidence from firms in Shanghai using a Bayesian spatial bivariate probit model," Regional Science and Urban Economics, Elsevier, volume 76, issue C, pages 125-146, DOI: 10.1016/j.regsciurbeco.2018.04.003.
• Li, Jianan & Han, Xiaoyi, 2019, "Bayesian Lassos for spatial durbin error model with smoothness prior: Application to detect spillovers of China's treaty ports," Regional Science and Urban Economics, Elsevier, volume 77, issue C, pages 38-74, DOI: 10.1016/j.regsciurbeco.2019.01.009.
• Brancaccio, Emiliano & Giammetti, Raffaele & Lopreite, Milena & Puliga, Michelangelo, 2019, "Monetary policy, crisis and capital centralization in corporate ownership and control networks: A B-Var analysis," Structural Change and Economic Dynamics, Elsevier, volume 51, issue C, pages 55-66, DOI: 10.1016/j.strueco.2019.08.005.
• John Kenny, 2019, "Robust Bayesian Inference," Journal of Economics and Econometrics, Economics and Econometrics Society, volume 62, issue 1, pages 15-29.
• Cliff Severin & Katie Sierminski, 2019, "Variational Bayesian Methods and Frequentist Consistency," Journal of Economics and Econometrics, Economics and Econometrics Society, volume 62, issue 2, pages 1-18.
• Douglas MacLean, 2019, "Meta-Analysis of Diagnostic Tests," Journal of Economics and Econometrics, Economics and Econometrics Society, volume 62, issue 2, pages 41-55.
• Stephen Madsen, 2019, "Bayesian Uncertainty Directed Designs," Journal of Economics and Econometrics, Economics and Econometrics Society, volume 62, issue 2, pages 56-72.
• Deborah Gefang & Gary Koop & Aubrey Poon, 2019, "Variational Bayesian Inference in Large Vector Autoregressions with Hierarchical Shrinkage," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2019-08, Jan.
• Qazi Haque, 2019, "Monetary Policy, Inflation Target and the Great Moderation: An Empirical Investigation," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2019-44, Jun.
• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019, "An Automated Prior Robustness Analysis in Bayesian Model Comparison," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2019-45, Jun.
• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019, "Efficient Selection of Hyperparameters in Large Bayesian VARs Using Automatic Differentiation," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2019-46, Jun.
• Joshua C. C. Chan, 2019, "Asymmetric Conjugate Priors for Large Bayesian VARs," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2019-51, Jul.
• Hilde C. Bjornland & Julia Zhulanova, 2019, "The Shale Oil Boom and the US Economy: Spillovers and Time-Varying Effects," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2019-59, Aug.
• Joshua C. C. Chan, 2019, "Minnesota-Type Adaptive Hierarchical Priors for Large Bayesian VARs," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2019-61, Aug.
• Joshua C.C. Chan, 2019, "Large Hybrid Time-Varying Parameter VARs," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2019-77, Oct.
• Qazi Haque & Leandro M. Magnusson & Kazuki Tomioka, 2019, "Empirical Evidence on the Dynamics of Investment Under Uncertainty in the US," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2019-87, Dec.
• Mariolis, Theodore & Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Tsionas, Efthymios G., 2019, "A non-linear Keynesian Goodwin-type endogenous model of the cycle: Bayesian evidence for the USA," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 100229, Feb.
• Sariev, Eduard & Germano, Guido, 2020, "Bayesian regularized artificial neural networks for the estimation of the probability of default," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 101029, Feb.
• Maynou, Laia & Coll-de-Tuero, Gabriel & Saez, Marc, 2019, "The effects of copayment in primary health care: evidence from a natural experiment," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 101303, Nov.
• Md. Nazmul Ahsan & Jean-Marie Dufour, 2019, "A Simple Efficient Moment-based Estimator for the Stochastic Volatility Model," Advances in Econometrics, Emerald Group Publishing Limited, "Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A", DOI: 10.1108/S0731-90532019000040A008.
• Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2019, "How Sensitive Are VAR Forecasts to Prior Hyperparameters? An Automated Sensitivity Analysis," Advances in Econometrics, Emerald Group Publishing Limited, "Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A", DOI: 10.1108/S0731-90532019000040A010.
• Theodore F. Figinski & Alicia Lloro & Phillip Li, 2019, "New Evidence on the Effect of Compulsory Schooling Laws☆," Advances in Econometrics, Emerald Group Publishing Limited, "Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A", DOI: 10.1108/S0731-90532019000040A013.
• Eri Nakamura & Takuya Urakami & Kazuhiko Kakamu, 2019, "A Bayesian Stochastic Frontier Model with Endogenous Regressors: An Application to the Effect of Division of Labor in Japanese Water Supply Organizations," Advances in Econometrics, Emerald Group Publishing Limited, "Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B", DOI: 10.1108/S0731-90532019000040B003.
• Justin L. Tobias & Joshua C. C. Chan, 2019, "An Alternate Parameterization for Bayesian Nonparametric/Semiparametric Regression," Advances in Econometrics, Emerald Group Publishing Limited, "Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B", DOI: 10.1108/S0731-90532019000040B004.
• Rolando Gonzales & Andrea Rojas-Hosse, 2019, "Inflation shocks and income inequality," African Journal of Economic and Management Studies, Emerald Group Publishing Limited, volume 10, issue 2, pages 226-240, April, DOI: 10.1108/AJEMS-10-2018-0299.
• Donglian Ma & Hisashi Tanizaki, 2019, "Fat-tailed stochastic volatility model and the stock market returns in China," China Finance Review International, Emerald Group Publishing Limited, volume 11, issue 2, pages 170-184, June, DOI: 10.1108/CFRI-03-2018-0028.
• Khee Giap Tan & Nguyen Trieu Duong Luu & Sangiita Yoong Wei Cher, 2019, "Understanding growth slowdown dynamics in India’s sub-national economies," International Journal of Social Economics, Emerald Group Publishing Limited, volume 46, issue 3, pages 429-453, January, DOI: 10.1108/IJSE-09-2017-0418.
• Tobias Brünner, 2019, "Price formation in call auctions with insider information," Studies in Economics and Finance, Emerald Group Publishing Limited, volume 36, issue 3, pages 408-426, July, DOI: 10.1108/SEF-02-2018-0066.
• Wei Zhou & Eoghan O'Neill & Alice Moncaster & David M Reiner & Peter Guthrie, 2019, "Applying Bayesian Model Averaging to Characterise Urban Residential Stock Turnover Dynamics," Working Papers, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge, number EPRG1933, Sep.
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• Albert Caruso & Lucrezia Reichlin & Giovanni Ricco, 2019, "Financial and fiscal interaction in the euro area crisis : this time was different," Documents de Travail de l'OFCE, Observatoire Francais des Conjonctures Economiques (OFCE), number 2019-11, Jul.
• Mark Fisher & Mark J. Jensen & Paula A. Tkac, 2019, "Bayesian Nonparametric Learning of How Skill Is Distributed across the Mutual Fund Industry," FRB Atlanta Working Paper, Federal Reserve Bank of Atlanta, number 2019-3, Mar, DOI: 10.29338/wp2019-03.
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• Yasuo Hirose & Takushi Kurozumi & Willem Van Zandweghe, 2019, "Monetary Policy and Macroeconomic Stability Revisited," Working Papers, Federal Reserve Bank of Cleveland, number 19-14, Jun, DOI: 10.26509/frbc-wp-201914.
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• Gianni Amisano & Oreste Tristani, 2019, "Uncertainty Shocks, Monetary Policy and Long-Term Interest Rates," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2019-024, Apr, DOI: 10.17016/FEDS.2019.024.
• Padma Sharma, 2019, "Risk-Shifting, Regulation, and Government Assistance," Research Working Paper, Federal Reserve Bank of Kansas City, number RWP 19-10, Nov, DOI: 10.18651/RWP2019-10.
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• Emanuela Ciapanna & Marco Taboga, 2019, "Bayesian Analysis of Coefficient Instability in Dynamic Regressions," Econometrics, MDPI, volume 7, issue 3, pages 1-32, June.
• Chiara Limongi Concetto & Francesco Ravazzolo, 2019, "Optimism in Financial Markets: Stock Market Returns and Investor Sentiments," JRFM, MDPI, volume 12, issue 2, pages 1-14, May.
• Marcin Błażejowski & Jacek Kwiatkowski & Jakub Gazda, 2019, "Sources of Economic Growth: A Global Perspective," Sustainability, MDPI, volume 11, issue 1, pages 1-14, January.
• Valentin Jouvanceau, 2019, "New Evidence on the Effects of Quantitative Easing," Working Papers, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon, number 1912.
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• Alberto Caruso & Lucrezia Reichlin & Giovanni Ricco, 2019, "Financial and fiscal interaction in the Euro Area crisis: This time was different," Sciences Po Economics Publications (main), HAL, number hal-03403613, Oct, DOI: 10.1016/j.euroecorev.2019.08.002.
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• Carlo Pizzinelli & Konstantinos Theodoridis & Francesco Zanetti, 2019, "State Dependence in Labor Market Fluctuations: Evidence, Theory, and Policy Implications," IMES Discussion Paper Series, Institute for Monetary and Economic Studies, Bank of Japan, number 19-E-03, Feb.
• Gustavo Cabrera González, 2019, "Modeling and Projection of the Mexican Exchange Rate (Peso/Dollar): a Bayesian Approach for Model Selection," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 14, issue 2, pages 203-219, Abril-Jun.
• Miguel Antonio Alba Suárez & Wilmer Pineda-Ríos & Javier Deaza Chaves, 2019, "Análisis comparativo de las metodologías de estimación semiparamétricas y vía cópulas del Valor en Riesgo (VaR) en el mercado accionario colombiano," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 14, issue 2, pages 279-307, Abril-Jun.
• Beatriz Mota Aragón & José Antonio Núñez Mora, 2019, "Estimación de la distribución multivariada de los rendimientos de los tipos de cambio contra el dólar de las criptomonedas Bitcoin, Ripple y Ether," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, volume 14, issue 3, pages 447-457, Julio - S.
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• Nima Nonejad, 2019, "Modeling Persistence and Parameter Instability in Historical Crude Oil Price Data Using a Gibbs Sampling Approach," Computational Economics, Springer;Society for Computational Economics, volume 53, issue 4, pages 1687-1710, April, DOI: 10.1007/s10614-018-9835-4.
• Enrique Martínez-García, 2019, "Good Policies or Good Luck? New Insights on Globalization and the International Monetary Policy Transmission Mechanism," Computational Economics, Springer;Society for Computational Economics, volume 54, issue 1, pages 419-454, June, DOI: 10.1007/s10614-017-9746-9.
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• I. G. Ukpong & K. G. Balcombe & I. M. Fraser & F. J. Areal, 2019, "Preferences for Mitigation of the Negative Impacts of the Oil and Gas Industry in the Niger Delta Region of Nigeria," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, volume 74, issue 2, pages 811-843, October, DOI: 10.1007/s10640-019-00349-4.
• Markus Glatt & Roy Brouwer & Ivana Logar, 2019, "Combining Risk Attitudes in a Lottery Game and Flood Risk Protection Decisions in a Discrete Choice Experiment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, volume 74, issue 4, pages 1533-1562, December, DOI: 10.1007/s10640-019-00379-y.
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