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Laura Liu

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.

    Mentioned in:

    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health > Measurement

Working papers

  1. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.

    Cited by:

    1. Senay Sokullu & Irene Botosaru & Chris Muris, 2022. "Time-Varying Linear Transformation Models with Fixed Effects and Endogeneity for Short Panels," Bristol Economics Discussion Papers 22/756, School of Economics, University of Bristol, UK.

  2. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2021. "Forecasting with a Panel Tobit Model," Papers 2110.14117, arXiv.org, revised Jul 2022.

    Cited by:

    1. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    2. Chen, Mo & Xue, Wei-Xian & Zhao, Xin-Xin & Chang, Chun-Ping & Liu, Xiaoxia, 2024. "The impact of economic sanctions on the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 163-174.
    3. Timothy B. Armstrong & Michal Kolesár & Mikkel Plagborg-Møller, 2022. "Robust Empirical Bayes Confidence Intervals," Working Papers 2022-27, Princeton University. Economics Department..
    4. Hyeongwoo Kim & Jisoo Son, 2023. "What Charge-Off Rates Are Predictable by Macroeconomic Latent Factors?," Auburn Economics Working Paper Series auwp2023-06, Department of Economics, Auburn University.
    5. Antonio Pacifico, 2023. "Obesity and labour market outcomes in Italy: a dynamic panel data evidence with correlated random effects," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(4), pages 557-574, June.
    6. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
    7. Xin Sheng & Rangan Gupta & Qiang Ji, 2020. "Forecasting Charge-Off Rates with a Panel Tobit Model: The Role of Uncertainty," Working Papers 202092, University of Pretoria, Department of Economics.
    8. Bykhovskaya, Anna & Duffy, James A., 2024. "The local to unity dynamic Tobit model," Journal of Econometrics, Elsevier, vol. 241(2).
    9. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    10. Anna Bykhovskaya & James A. Duffy, 2022. "The Local to Unity Dynamic Tobit Model," Papers 2210.02599, arXiv.org, revised May 2024.
    11. Zuoxiang Zhao & Hongjun Sun & Ding Han & Qiuyun Zhao, 2023. "Development strategy, technological progress, and regional environmental performance: empirical evidence from China," Economic Change and Restructuring, Springer, vol. 56(5), pages 3701-3732, October.
    12. Brezigar-Masten, Arjana & Masten, Igor & Volk, Matjaž, 2021. "Modelin-g credit risk with a Tobit model of days past due," Journal of Banking & Finance, Elsevier, vol. 122(C).
    13. Timmermann, Allan & Zhu, Yinchu, 2019. "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers 13746, C.E.P.R. Discussion Papers.
    14. James A. Duffy & Sophocles Mavroeidis & Sam Wycherley, 2022. "Cointegration with Occasionally Binding Constraints," Papers 2211.09604, arXiv.org, revised Jul 2023.
    15. Qu, Ritong & Timmermann, Allan & Zhu, Yinchu, 2023. "Comparing forecasting performance in cross-sections," Journal of Econometrics, Elsevier, vol. 237(2).

  3. Laura Liu & Mikkel Plagborg-M{o}ller, 2021. "Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro Data," Papers 2101.04771, arXiv.org, revised Jun 2022.

    Cited by:

    1. Matteo Barigozzi & Filippo Pellegrino, 2023. "Multidimensional dynamic factor models," Papers 2301.12499, arXiv.org.
    2. Langot, François & Malmberg, Selma & Tripier, Fabien & Hairault, Jean-Olivier, 2023. "The Macroeconomic and Redistributive Effects of Shielding Consumers from Rising Energy Prices: the French Experiment," CEPREMAP Working Papers (Docweb) 2305, CEPREMAP.

  4. Schorfheide, Frank & Liu, Laura & Moon, Hyungsik Roger, 2020. "Panel Forecasts of Country-Level Covid-19 Infectionsliu," CEPR Discussion Papers 14790, C.E.P.R. Discussion Papers.

    Cited by:

    1. Guenette,Justin Damien & Yamazaki,Takefumi, 2021. "Projecting the Economic Consequences of the COVID-19 Pandemic," Policy Research Working Paper Series 9589, The World Bank.

  5. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Panel Forecasts of Country-Level Covid-19 Infections," NBER Working Papers 27248, National Bureau of Economic Research, Inc.

    Cited by:

    1. Cem Cakmakli & Yasin Simsek, 2023. "Bridging the Covid-19 Data and the Epidemiological Model using Time-Varying Parameter SIRD Model," Papers 2301.13692, arXiv.org.
    2. Yothin Jinjarak & Rashad Ahmed & Sameer Nair-Desai & Weining Xin & Joshua Aizenman, 2020. "Accounting for Global COVID-19 Diffusion Patterns, January-April 2020," NBER Working Papers 27185, National Bureau of Economic Research, Inc.
    3. Hwang, Eunju, 2022. "Prediction intervals of the COVID-19 cases by HAR models with growth rates and vaccination rates in top eight affected countries: Bootstrap improvement," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    4. Chaohua Dong & Jiti Gao & Oliver Linton & Bin Peng, 2020. "On the Time Trend of COVID-19: A Panel Data Study," Papers 2006.11060, arXiv.org, revised Jun 2020.
    5. Yanqing Yang & Xingcheng Xu & Jinfeng Ge & Yan Xu, 2024. "Machine Learning for Economic Forecasting: An Application to China's GDP Growth," Papers 2407.03595, arXiv.org.
    6. Sokbae (Simon) Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2020. "Sparse HP filter: Finding kinks in the COVID-19 contact rate," CeMMAP working papers CWP32/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Hartl, Tobias, 2021. "Monitoring the pandemic: A fractional filter for the COVID-19 contact rate," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242380, Verein für Socialpolitik / German Economic Association.
    8. Zubarev, Andrei & Kirillova, Maria, 2022. "Modeling COVID-19 spread in the Russian Federation using global VAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 117-138.
    9. Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2023. "How to go viral: A COVID-19 model with endogenously time-varying parameters," Journal of Econometrics, Elsevier, vol. 232(1), pages 70-86.
    10. Julliard, Christian & Shi, Ran & Yuan, Kathy, 2020. "The spread of COVID-19 in London: network effects and optimal lockdowns," LSE Research Online Documents on Economics 118864, London School of Economics and Political Science, LSE Library.
    11. Li, S. & Linton, O., 2020. "When will the Covid-19 pandemic peak?," Cambridge Working Papers in Economics 2025, Faculty of Economics, University of Cambridge.
    12. Christian Aleman & Christopher Busch & Alexander Ludwig & Raul Santaeulalia-Llopis, 2022. "A Stage-Based Identification of Policy Effects," PIER Working Paper Archive 22-026, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    13. Difang Huang & Ying Liang & Boyao Wu & Yanyi Ye, 2024. "Estimating the Impact of Social Distance Policy in Mitigating COVID-19 Spread with Factor-Based Imputation Approach," Papers 2405.12180, arXiv.org.
    14. Fernández-Villaverde, Jesús & Jones, Charles I., 2022. "Estimating and simulating a SIRD Model of COVID-19 for many countries, states, and cities," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    15. Sen, Anindya & Baker, John David & Zhang, Qihuang & Agarwal, Rishav Raj & Lam, Jean-Paul, 2023. "Do more stringent policies reduce daily COVID-19 case counts? Evidence from Canadian provinces," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 225-242.
    16. Leonardo Martins & Marcelo C. Medeiros, 2021. "The Impacts of Mobility on Covid-19 Dynamics: Using Soft and Hard Data," Papers 2110.00597, arXiv.org.
    17. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
    18. Guenette,Justin Damien & Yamazaki,Takefumi, 2021. "Projecting the Economic Consequences of the COVID-19 Pandemic," Policy Research Working Paper Series 9589, The World Bank.
    19. Otilia Boldea & Adriana Cornea-Madeira & João Madeira, 2023. "Disentangling the effect of measures, variants, and vaccines on SARS-CoV-2 infections in England: a dynamic intensity model," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 444-466.
    20. Tobias Hartl, 2021. "Monitoring the pandemic: A fractional filter for the COVID-19 contact rate," Papers 2102.10067, arXiv.org.

  6. Laura Liu & Christian Matthes & Katerina Petrova, 2018. "Monetary Policy across Space and Time," Working Paper 18-14, Federal Reserve Bank of Richmond.

    Cited by:

    1. Goodhead, Robert, 2024. "The economic impact of yield curve compression: Evidence from euro area forward guidance and unconventional monetary policy," European Economic Review, Elsevier, vol. 164(C).
    2. Lei, Jian, 2021. "Curve momentum in currency markets," Finance Research Letters, Elsevier, vol. 42(C).
    3. Zakipour-Saber, Shayan, 2019. "Forecasting in the euro area: The role of the US long rate," Economic Letters 5/EL/19, Central Bank of Ireland.
    4. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan, 2019. "International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression," International Review of Financial Analysis, Elsevier, vol. 65(C).

  7. Laura Liu, 2018. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," Papers 1805.04178, arXiv.org, revised Oct 2021.

    Cited by:

    1. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    2. Federico Bassetti & Roberto Casarin & Marco Del Negro, 2022. "A Bayesian Approach to Inference on Probabilistic Surveys," Staff Reports 1025, Federal Reserve Bank of New York.
    3. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
    4. Boyuan Zhang, 2020. "Forecasting with Bayesian Grouped Random Effects in Panel Data," Papers 2007.02435, arXiv.org, revised Oct 2020.
    5. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.

  8. Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2017. "Commodity Connectedness," NBER Working Papers 23685, National Bureau of Economic Research, Inc.

    Cited by:

    1. Juncal Cunado & David Gabauer & Rangan Gupta, 2021. "Realized Volatility Spillovers between Energy and Metal Markets: A Time-Varying Connectedness Approach," Working Papers 202180, University of Pretoria, Department of Economics.
    2. Bastianin, Andrea & Casoli, Chiara & Galeotti, Marzio, 2023. "The connectedness of Energy Transition Metals," FEEM Working Papers 336984, Fondazione Eni Enrico Mattei (FEEM).
    3. Scarcioffolo, Alexandre Ribeiro & Etienne, Xiaoli L., 2019. "How connected are the U.S. regional natural gas markets in the post-deregulation era? Evidence from time-varying connectedness analysis," Journal of Commodity Markets, Elsevier, vol. 15(C), pages 1-1.
    4. Costola, Michele & Lorusso, Marco, 2021. "Spillovers among Energy Commodities and the Russian Stock Market," MPRA Paper 108990, University Library of Munich, Germany.
    5. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    6. Cagli, Efe Caglar, 2023. "The volatility spillover between battery metals and future mobility stocks: Evidence from the time-varying frequency connectedness approach," Resources Policy, Elsevier, vol. 86(PA).
    7. Gong, Xu & Xu, Jun & Liu, Tangyong & Zhou, Zicheng, 2022. "Dynamic volatility connectedness between industrial metal markets," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    8. Kyriazis, Nikolaos & Corbet, Shaen, 2024. "Evaluating the dynamic connectedness of financial assets and bank indices during black-swan events: A Quantile-VAR approach," Energy Economics, Elsevier, vol. 131(C).
    9. Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2019. "Crisis transmission: visualizing vulnerability," Working Papers 2019-07, University of Tasmania, Tasmanian School of Business and Economics.
    10. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
    11. Liang, Chao & Ma, Feng & Li, Ziyang & Li, Yan, 2020. "Which types of commodity price information are more useful for predicting US stock market volatility?," Economic Modelling, Elsevier, vol. 93(C), pages 642-650.
    12. shah, Adil Ahmad & Bhanja, Niyati & Dar, Arif Billah, 2023. "Do gold and the US dollar diversify global sectoral risk? Evidence from connectedness and dynamic conditional correlation measures," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    13. Abid, Ilyes & Benkraiem, Ramzi & Mzoughi, Hela & Urom, Christian, 2024. "From black gold to financial fallout: Analyzing extreme risk spillovers in oil-exporting nations," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    14. An, Sufang & Gao, Xiangyun & An, Haizhong & Liu, Siyao & Sun, Qingru & Jia, Nanfei, 2020. "Dynamic volatility spillovers among bulk mineral commodities: A network method," Resources Policy, Elsevier, vol. 66(C).
    15. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    16. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    17. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
    18. Cao, Yan & Cheng, Sheng & Li, Xinran, 2023. "How economic policy uncertainty affects asymmetric spillovers in food and oil prices: Evidence from wavelet analysis," Resources Policy, Elsevier, vol. 86(PB).
    19. Pagnottoni, Paolo & Spelta, Alessandro, 2023. "The motifs of risk transmission in multivariate time series: Application to commodity prices," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    20. Thiem, Christopher, 2018. "Cross-category, trans-Pacific spillovers of policy uncertainty and financial market volatility," Ruhr Economic Papers 782, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    21. Najaf Iqbal & Elie Bouri & Guangrui Liu & Ashish Kumar, 2024. "Volatility spillovers during normal and high volatility states and their driving factors: A cross‐country and cross‐asset analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 975-995, January.
    22. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    23. Ma, Yan-Ran & Ji, Qiang & Wu, Fei & Pan, Jiaofeng, 2021. "Financialization, idiosyncratic information and commodity co-movements," Energy Economics, Elsevier, vol. 94(C).
    24. Choi, Insu & Kim, Woo Chang, 2024. "Practical forecasting of risk boundaries for industrial metals and critical minerals via statistical machine learning techniques," International Review of Financial Analysis, Elsevier, vol. 94(C).
    25. Jonas Krampe & Luca Margaritella, 2024. "Global bank network connectedness revisited: What is common, idiosyncratic and when?," Papers 2402.02482, arXiv.org.
    26. Akyildirim, Erdinc & Cepni, Oguzhan & Pham, Linh & Uddin, Gazi Salah, 2022. "How connected is the agricultural commodity market to the news-based investor sentiment?," Energy Economics, Elsevier, vol. 113(C).
    27. Thiem, Christopher, 2018. "Cross-category spillovers of economic policy uncertainty," Ruhr Economic Papers 744, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    28. Lucey, Brian M. & Vigne, Samuel A. & Ballester, Laura & Barbopoulos, Leonidas & Brzeszczynski, Janusz & Carchano, Oscar & Dimic, Nebojsa & Fernandez, Viviana & Gogolin, Fabian & González-Urteaga, Ana , 2018. "Future directions in international financial integration research - A crowdsourced perspective," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 35-49.
    29. Escribano, Ana & Koczar, Monika W. & Jareño, Francisco & Esparcia, Carlos, 2023. "Shock transmission between crude oil prices and stock markets," Resources Policy, Elsevier, vol. 83(C).
    30. Shah, Adil Ahmad & Dar, Arif Billah, 2021. "Exploring diversification opportunities across commodities and financial markets: Evidence from time-frequency based spillovers," Resources Policy, Elsevier, vol. 74(C).
    31. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    32. Lukas Boeckelmann & Arthur Stalla-Bourdillon, 2021. "Structural Estimation of Time-Varying Spillovers:an Application to International Credit Risk Transmission," Working Papers hal-03338209, HAL.
    33. Liu, Pan & Power, Gabriel J. & Vedenov, Dmitry, 2021. "Fair-weather Friends? Sector-specific volatility connectedness and transmission," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 712-736.
    34. Shakya, Shishir & Li, Bingxin & Etienne, Xiaoli, 2022. "Shale revolution, oil and gas prices, and drilling activities in the United States," Energy Economics, Elsevier, vol. 108(C).
    35. Morelli, Giacomo, 2023. "Stochastic ordering of systemic risk in commodity markets," Energy Economics, Elsevier, vol. 117(C).
    36. Chen, Huayi & Shi, Huai-Long & Zhou, Wei-Xing, 2024. "Carbon volatility connectedness and the role of external uncertainties: Evidence from China," Journal of Commodity Markets, Elsevier, vol. 33(C).
    37. Fan, Zaifeng & Jump, Jeff & Tse, Yiuman & Yu, Linda, 2023. "Volatility in US dairy futures markets," Journal of Commodity Markets, Elsevier, vol. 29(C).
    38. I. Abid & R. Benkraiem & H. Mzoughi & C. Urom, 2024. "From black gold to financial fallout: Analyzing extreme risk spillovers in oil-exporting nations," Post-Print hal-04681726, HAL.
    39. Apergis, Nicholas, 2023. "Realized higher-order moments spillovers across cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    40. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    41. Pagnottoni, Paolo, 2023. "Superhighways and roads of multivariate time series shock transmission: Application to cryptocurrency, carbon emission and energy prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    42. Shah, Adil Ahmad & Dar, Arif Billah, 2022. "Asymmetric, time and frequency-based spillover transmission in financial and commodity markets," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    43. Libo Yin & Hong Cao, 2024. "Financialization of commodity markets: New evidence from temporal and spatial domains," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1357-1382, August.
    44. Cui, Jinxin & Maghyereh, Aktham, 2023. "Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict," International Review of Financial Analysis, Elsevier, vol. 86(C).
    45. Agyei, Samuel Kwaku & Umar, Zaghum & Bossman, Ahmed & Teplova, Tamara, 2023. "Dynamic connectedness between global commodity sectors, news sentiment, and sub-Saharan African equities," Emerging Markets Review, Elsevier, vol. 56(C).
    46. Wang, Xiaoyang, 2022. "Efficient markets are more connected: An entropy-based analysis of the energy, industrial metal and financial markets," Energy Economics, Elsevier, vol. 111(C).
    47. Balli, Faruk & Balli, Hatice Ozer & Dang, Tam Hoang Nhat & Gabauer, David, 2023. "Contemporaneous and lagged R2 decomposed connectedness approach: New evidence from the energy futures market," Finance Research Letters, Elsevier, vol. 57(C).
    48. Ogbuabor, Jonathan E. & Anthony-Orji, Onyinye I. & Manasseh, Charles O. & Orji, Anthony, 2020. "Measuring the dynamics of COMESA output connectedness with the global economy," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).

  9. Laura Liu, 2017. "Density Forecasts in Panel Models: A semiparametric Bayesian Perspective," PIER Working Paper Archive 17-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 28 Apr 2017.

    Cited by:

    1. Mikkel Plagborg-Moller & Gita Gopinath & Emine Boz, 2017. "Global Trade and the Dollar," 2017 Meeting Papers 1041, Society for Economic Dynamics.

  10. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2017. "Forecasting with Dynamic Panel Data Models," Papers 1709.10193, arXiv.org.

    Cited by:

    1. Mihaela Simionescu & Javier Cifuentes-Faura, 2022. "Forecasting National and Regional Youth Unemployment in Spain Using Google Trends," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1187-1216, December.
    2. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2019. "Forecasting with a Panel Tobit Model," CAEPR Working Papers 2019-005, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    3. Hyungsik Roger Moon & Frank Schorfheide & Boyuan Zhang, 2023. "Bayesian Estimation of Panel Models under Potentially Sparse Heterogeneity," PIER Working Paper Archive 23-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    4. Andrew Y Chen & Tom Zimmermann & Jeffrey Pontiff, 2020. "Publication Bias and the Cross-Section of Stock Returns," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(2), pages 249-289.
    5. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2017. "Forecasting with Dynamic Panel Data Models," Papers 1709.10193, arXiv.org.
    6. Seoyoung Yu & Donghyun Kim, 2021. "Changes in Regional Economic Resilience after the 2008 Global Economic Crisis: The Case of Korea," Sustainability, MDPI, vol. 13(20), pages 1-14, October.
    7. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    8. Antonio Pacifico, 2023. "Obesity and labour market outcomes in Italy: a dynamic panel data evidence with correlated random effects," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(4), pages 557-574, June.
    9. Randal Verbrugge & Alan Dorfman & William Johnson & Fred Marsh III & Robert Poole & Owen Shoemaker, 2017. "Determinants of Differential Rent Changes: Mean Reversion versus the Usual Suspects," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 45(3), pages 591-627, July.
    10. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
    11. Raffaella Giacomini & Sokbae Lee & Silvia Sarpietro, 2023. "A Robust Method for Microforecasting and Estimation of Random Effects," Working Paper Series WP 2023-26, Federal Reserve Bank of Chicago.
    12. Lin, Jilei & Eck, Daniel J., 2021. "Minimizing post-shock forecasting error through aggregation of outside information," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1710-1727.
    13. Yugang He, 2024. "E-commerce and foreign direct investment: pioneering a new era of trade strategies," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    14. Pengyu Chen & Yiannis Karavias & Elias Tzavalis, 2022. "Panel unit-root tests with structural breaks," Stata Journal, StataCorp LP, vol. 22(3), pages 664-678, September.
    15. Laura Liu, 2017. "Density Forecasts in Panel Models: A semiparametric Bayesian Perspective," PIER Working Paper Archive 17-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 28 Apr 2017.
    16. Andrew Y. Chen, 2022. "Do t-Statistic Hurdles Need to be Raised?," Papers 2204.10275, arXiv.org, revised Apr 2024.
    17. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Robust Forecasting," Papers 2011.03153, arXiv.org, revised Dec 2020.
    18. Laura Liu, 2020. "Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective," CAEPR Working Papers 2020-003, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    19. Chinco, Alex & Neuhierl, Andreas & Weber, Michael, 2021. "Estimating the anomaly base rate," Journal of Financial Economics, Elsevier, vol. 140(1), pages 101-126.
    20. Timmermann, Allan & Zhu, Yinchu, 2019. "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers 13746, C.E.P.R. Discussion Papers.
    21. Fabio Canova, 2024. "Should we trust cross‐sectional multiplier estimates?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 589-606, June.
    22. Oguzhan Cepni & Riza Demirer & Rangan Gupta & Ahmet Sensoy, 2020. "Interest Rate Uncertainty and the Predictability of Bank Revenues," Working Papers 202040, University of Pretoria, Department of Economics.
    23. Qu, Ritong & Timmermann, Allan & Zhu, Yinchu, 2023. "Comparing forecasting performance in cross-sections," Journal of Econometrics, Elsevier, vol. 237(2).
    24. Greenaway-McGrevy, Ryan, 2022. "Forecast combination for VARs in large N and T panels," International Journal of Forecasting, Elsevier, vol. 38(1), pages 142-164.
    25. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    26. Andrew Y. Chen & Mihail Velikov, 2020. "Zeroing in on the Expected Returns of Anomalies," Finance and Economics Discussion Series 2020-039, Board of Governors of the Federal Reserve System (U.S.).

  11. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2015. "Estimating Global Bank Network Connectedness," Koç University-TUSIAD Economic Research Forum Working Papers 1512, Koc University-TUSIAD Economic Research Forum.

    Cited by:

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    262. Chen, Yan & Wang, Gang-Jin & Zhu, You & Xie, Chi & Uddin, Gazi Salah, 2023. "Quantile connectedness and the determinants between FinTech and traditional financial institutions: Evidence from China," Global Finance Journal, Elsevier, vol. 58(C).
    263. Sasan Barak & Navid Parvini, 2023. "Transfer‐entropy‐based dynamic feature selection for evaluating Bitcoin price drivers," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(12), pages 1695-1726, December.
    264. Jian Yang & Zheng Li & Hong Miao, 2021. "Volatility spillovers in commodity futures markets: A network approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 1959-1987, December.
    265. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
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Articles

  1. Evans, D.L. & Falagán, N. & Hardman, C.A. & Kourmpetli, S. & Liu, L. & Mead, B.R. & Davies, J.A.C., 2022. "Ecosystem service delivery by urban agriculture and green infrastructure – a systematic review," Ecosystem Services, Elsevier, vol. 54(C).

    Cited by:

    1. Mariana Oliveira & Remo Santagata & Serena Kaiser & Yanxin Liu & Chiara Vassillo & Patrizia Ghisellini & Gengyuan Liu & Sergio Ulgiati, 2022. "Socioeconomic and Environmental Benefits of Expanding Urban Green Areas: A Joint Application of i-Tree and LCA Approaches," Land, MDPI, vol. 11(12), pages 1-16, November.
    2. Weiyao Yang & Wanglin Yan & Lihua Chen & Haichen Wei & Shuang Gan, 2024. "Developing a TOD assessment model based on node–place–ecology for suburban areas of metropolitan cities: A case in Odawara," Environment and Planning B, , vol. 51(4), pages 839-853, May.
    3. Goździewicz-Biechońska, Justyna & Brzezińska-Rawa, Anna, 2022. "Protecting ecosystem services of urban agriculture against land-use change using market-based instruments. A Polish perspective," Land Use Policy, Elsevier, vol. 120(C).
    4. Nazmul Haque, Md. & Sharifi, Ayyoob, 2024. "Justice in access to urban ecosystem services: A critical review of the literature," Ecosystem Services, Elsevier, vol. 67(C).
    5. Giulio Senes & Chiara Parretta & Natalia Fumagalli & Patrizia Tassinari & Daniele Torreggiani, 2023. "Soft Mobility Network for the Enhancement and Discovery of the Rural Landscape: Definition of a Masterplan for Alto Ferrarese (Italy)," Land, MDPI, vol. 12(3), pages 1-24, February.
    6. Silvio Caputo & Victoria Schoen & Chris Blythe, 2023. "Productivity and Efficiency of Community Gardens: Case Studies from the UK," Land, MDPI, vol. 12(1), pages 1-19, January.
    7. Nápoles-Vértiz, Sonia & Caro-Borrero, Angela, 2024. "Conceptual diversity and application of ecosystem services and disservices: A systematic review," Ecosystem Services, Elsevier, vol. 67(C).

  2. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
    See citations under working paper version above.
  3. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Forecasting With Dynamic Panel Data Models," Econometrica, Econometric Society, vol. 88(1), pages 171-201, January.
    See citations under working paper version above.
  4. Laura Liu & Christian Matthes & Katerina Petrova & Jessica Sackett Romero, 2019. "Monetary Policy across Space and Time," Richmond Fed Economic Brief, Federal Reserve Bank of Richmond, issue August.
    See citations under working paper version above.
  5. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    See citations under working paper version above.

Chapters

  1. Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Commodity Connectedness," Central Banking, Analysis, and Economic Policies Book Series, in: Enrique G. Mendoza & Ernesto Pastén & Diego Saravia (ed.),Monetary Policy and Global Spillovers: Mechanisms, Effects and Policy Measures, edition 1, volume 25, chapter 4, pages 097-136, Central Bank of Chile.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
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