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Andrea Coppola

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First Name:Andrea
Middle Name:
Last Name:Coppola
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RePEc Short-ID:pco357
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Affiliation

International Bank for Reconstruction & Development (IBRD)
World Bank Group

Washington, District of Columbia (United States)
http://www.worldbank.org/html/extdr/backgrd/ibrd/
RePEc:edi:ibrdwus (more details at EDIRC)

Research output

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Jump to: Working papers Articles

Working papers

  1. Coppola,Andrea & Lagerborg,Andresa & Mustafaoglu,Zafer, 2016. "Estimating an equilibrium exchange rate for the Argentine Peso," Policy Research Working Paper Series 7682, The World Bank.
  2. Seabold,Skipper & Rutherford,Alex & De Backer,Olivia & Coppola,Andrea, 2015. "The pulse of public opinion : using Twitter data to analyze public perception of reform in El Salvador," Policy Research Working Paper Series 7399, The World Bank.
  3. Klemens,Ben & Coppola,Andrea & Shron,Max, 2015. "Estimating local poverty measures using satellite images : a pilot application to Central America," Policy Research Working Paper Series 7329, The World Bank.
  4. Seabold,Skipper & Coppola,Andrea, 2015. "Nowcasting prices using Google trends : an application to Central America," Policy Research Working Paper Series 7398, The World Bank.
  5. Coppola, Andrea & Fernholz, Fernando & Glenday, Graham, 2014. "Estimating the economic opportunity cost of capital for public investment projects : an empirical analysis of the Mexican case," Policy Research Working Paper Series 6816, The World Bank.
  6. Andrea Coppola & Alessandro Girardi & Gustavo Piga, 2012. "Overcrowding Versus Liquidity in the Euro Sovereign Bond Markets," CEIS Research Paper 222, Tor Vergata University, CEIS, revised 20 Feb 2012.
  7. Coppola, Andrea & Calvo-Gonzalez, Oscar, 2011. "Higher wages, lower pay : public vs. private sector compensation in Peru," Policy Research Working Paper Series 5858, The World Bank.
  8. Andrea Coppola, 2007. "Forecasting Oil Price Movements: Exploiting the Information in the Future Market," CEIS Research Paper 100, Tor Vergata University, CEIS.
  9. Andrea Coppola & Gustavo Piga, "undated". "Watering the Garden of Government Securities:Measuring the "Bunching" Effect in Euro Sovereign Bond Markets," Working Papers wp2008-5, Department of the Treasury, Ministry of the Economy and of Finance.

Articles

  1. Andrea Coppola & Alessandro Girardi & Gustavo Piga, 2013. "Overcrowding Versus Liquidity In The Euro Sovereign Bond Markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 18(4), pages 307-318, October.
  2. Andrea Coppola, 2008. "Forecasting oil price movements: Exploiting the information in the futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(1), pages 34-56, January.

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.

Working papers

  1. Seabold,Skipper & Rutherford,Alex & De Backer,Olivia & Coppola,Andrea, 2015. "The pulse of public opinion : using Twitter data to analyze public perception of reform in El Salvador," Policy Research Working Paper Series 7399, The World Bank.

    Cited by:

    1. Resce, Giuliano & Maynard, Diana, 2018. "What matters most to people around the world? Retrieving Better Life Index priorities on Twitter," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 61-75.

  2. Klemens,Ben & Coppola,Andrea & Shron,Max, 2015. "Estimating local poverty measures using satellite images : a pilot application to Central America," Policy Research Working Paper Series 7329, The World Bank.

    Cited by:

    1. Paul Minard, 2020. "Is China’s regional inequality ethnic inequality?," Letters in Spatial and Resource Sciences, Springer, vol. 13(3), pages 297-314, December.
    2. Francis Rathinam & Sayak Khatua & Zeba Siddiqui & Manya Malik & Pallavi Duggal & Samantha Watson & Xavier Vollenweider, 2021. "Using big data for evaluating development outcomes: A systematic map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
    3. Paul Minard, 2020. "Institutions and China's comparative development," Papers 2001.02804, arXiv.org.
    4. Mitnik, Oscar A. & Sanchez, Raul & Yañez, Patricia, 2018. "Bright Investments: Measuring the Impact of Transport Infrastructure Using Luminosity Data in Haiti," IDB Publications (Working Papers) 28, Inter-American Development Bank.
    5. Thomas Ferreira, 2018. "Using satellite data to track socio-economic outcomes: a case study of Namibia," Working Papers 12/2018, Stellenbosch University, Department of Economics.

  3. Seabold,Skipper & Coppola,Andrea, 2015. "Nowcasting prices using Google trends : an application to Central America," Policy Research Working Paper Series 7398, The World Bank.

    Cited by:

    1. Chi, Tsung-Li & Liu, Hung-Tsen & Chang, Chia-Chien, 2023. "Hedging performance using google Trends–Evidence from the indian forex options market," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 107-123.
    2. Jain, Anshul & Biswal, Pratap Chandra, 2019. "Does internet search interest for gold move the gold spot, stock and exchange rate markets? A study from India," Resources Policy, Elsevier, vol. 61(C), pages 501-507.
    3. Petrova, Diana & Trunin, Pavel, 2020. "Revealing the mood of economic agents based on search queries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 71-87.
    4. Götz, Thomas B. & Knetsch, Thomas A., 2019. "Google data in bridge equation models for German GDP," International Journal of Forecasting, Elsevier, vol. 35(1), pages 45-66.
    5. Svatopluk Kapounek & Evžen Kocenda & Zuzana Kucerová, 2021. "Selective Attention in Exchange Rate Forecasting," CESifo Working Paper Series 8901, CESifo.
    6. Bulut Levent & Dogan Can, 2018. "Google Trends and Structural Exchange Rate Models for Turkish Lira–US Dollar Exchange Rate," Review of Middle East Economics and Finance, De Gruyter, vol. 14(2), pages 1-12, August.
    7. Bantis, Evripidis & Clements, Michael P. & Urquhart, Andrew, 2023. "Forecasting GDP growth rates in the United States and Brazil using Google Trends," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1909-1924.
    8. Jouchi Nakajima & Hiroaki Yamagata & Tatsushi Okuda & Shinnosuke Katsuki & Takeshi Shinohara, 2021. "Extracting Firms' Short-Term Inflation Expectations from the Economy Watchers Survey Using Text Analysis," Bank of Japan Working Paper Series 21-E-12, Bank of Japan.
    9. Voraprapa Nakavachara & Nuarpear Lekfuangfu, 2017. "Predicting the Present Revisited: The Case of Thailand," PIER Discussion Papers 70, Puey Ungphakorn Institute for Economic Research.
    10. Andree,Bo Pieter Johannes, 2021. "Estimating Food Price Inflation from Partial Surveys," Policy Research Working Paper Series 9886, The World Bank.

  4. Coppola, Andrea & Fernholz, Fernando & Glenday, Graham, 2014. "Estimating the economic opportunity cost of capital for public investment projects : an empirical analysis of the Mexican case," Policy Research Working Paper Series 6816, The World Bank.

    Cited by:

    1. Szekeres, Szabolcs, 2023. "The simple answer to the Social Discount Rate question," MPRA Paper 117843, University Library of Munich, Germany.
    2. Abdallah Othman & Glenn P. Jenkins, 2019. "Estimation of the Rate of Return to Capital in the East African Community Countries (EAC)," Development Discussion Papers 2019-11, JDI Executive Programs.
    3. Szekeres, Szabolcs, 2024. "Resolving the Discounting Dilemma," MPRA Paper 120014, University Library of Munich, Germany.

  5. Andrea Coppola & Alessandro Girardi & Gustavo Piga, 2012. "Overcrowding Versus Liquidity in the Euro Sovereign Bond Markets," CEIS Research Paper 222, Tor Vergata University, CEIS, revised 20 Feb 2012.

    Cited by:

    1. Gómez-Puig, Marta & Pieterse-Bloem, Mary & Sosvilla-Rivero, Simón, 2023. "Dynamic connectedness between credit and liquidity risks in euro area sovereign debt markets," Journal of Multinational Financial Management, Elsevier, vol. 68(C).
    2. Buis, Boyd & Pieterse-Bloem, Mary & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2020. "Expected issuance fees and market liquidity," Journal of Financial Markets, Elsevier, vol. 48(C).

  6. Coppola, Andrea & Calvo-Gonzalez, Oscar, 2011. "Higher wages, lower pay : public vs. private sector compensation in Peru," Policy Research Working Paper Series 5858, The World Bank.

    Cited by:

    1. Gindling,T. H. & Hasnain,Zahid & Newhouse,David Locke & Shi,Rong, 2019. "Are Public Sector Workers in Developing Countries Overpaid ? Evidence from a New Global Data Set," Policy Research Working Paper Series 8754, The World Bank.
    2. Juan Manuel del Pozo Segura, 2017. "Has the Gender Wage Gap been Reduced during the 'Peruvian Growth Miracle?' A Distributional Approach," Documentos de Trabajo / Working Papers 2017-442, Departamento de Economía - Pontificia Universidad Católica del Perú.

  7. Andrea Coppola, 2007. "Forecasting Oil Price Movements: Exploiting the Information in the Future Market," CEIS Research Paper 100, Tor Vergata University, CEIS.

    Cited by:

    1. Isabel Figuerola‐Ferretti & Alejandro Rodríguez & Eduardo Schwartz, 2021. "Oil price analysts' forecasts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1351-1374, September.
    2. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
    3. Prat, Georges & Uctum, Remzi, 2011. "Modelling oil price expectations: Evidence from survey data," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(3), pages 236-247, June.
    4. Wang, Yudong & Liu, Li & Diao, Xundi & Wu, Chongfeng, 2015. "Forecasting the real prices of crude oil under economic and statistical constraints," Energy Economics, Elsevier, vol. 51(C), pages 599-608.
    5. Wen, Chufu & Zhu, Haoyang & Dai, Zhifeng, 2023. "Forecasting commodity prices returns: The role of partial least squares approach," Energy Economics, Elsevier, vol. 125(C).
    6. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
    7. Celso Brunetti, Bahattin Buyuksahin, Michel A. Robe, and Kirsten R. Soneson, 2013. "OPEC "Fair Price" Pronouncements and the Market Price of Crude Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    8. Nicholas Apergis, 2023. "Forecasting energy prices: Quantile‐based risk models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 17-33, January.
    9. Krzysztof Drachal, 2018. "Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework," Energies, MDPI, vol. 11(5), pages 1-24, May.
    10. Di Zhu & Yinghong Wang & Fenglin Zhang, 2022. "Energy Price Prediction Integrated with Singular Spectrum Analysis and Long Short-Term Memory Network against the Background of Carbon Neutrality," Energies, MDPI, vol. 15(21), pages 1-20, October.
    11. Chatziantoniou, Ioannis & Degiannakis, Stavros & Filis, George, 2019. "Futures-based forecasts: How useful are they for oil price volatility forecasting?," Energy Economics, Elsevier, vol. 81(C), pages 639-649.
    12. Degiannakis, Stavros & Filis, George & Arora, Vipin, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," MPRA Paper 96270, University Library of Munich, Germany.
    13. Guglielmo Caporale & Davide Ciferri & Alessandro Girardi, 2010. "Time-varying spot and futures oil price dynamics," Quaderni del Dipartimento di Economia, Finanza e Statistica 75/2010, Università di Perugia, Dipartimento Economia.
    14. Georges Prat & Remzi Uctum, 2009. "Modelling oil price expectations: evidence from survey data," Working Papers hal-04140866, HAL.
    15. Ziliang Yu & Jian Yang & Robert I. Webb, 2023. "Price discovery in China's crude oil futures markets: An emerging Asian benchmark?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(3), pages 297-324, March.
    16. Clostermann, Jörg & Keis, Nikolaus & Seitz, Franz, 2010. "Short-term oil models before and during the financial market crisis," Arbeitsberichte – Working Papers 18, Technische Hochschule Ingolstadt (THI).
    17. Kertlly de Medeiros, Rennan & da Nóbrega Besarria, Cássio & Pitta de Jesus, Diego & Phillipe de Albuquerquemello, Vinicius, 2022. "Forecasting oil prices: New approaches," Energy, Elsevier, vol. 238(PC).
    18. Phan, Dinh Hoang Bach & Narayan, Paresh Kumar & Gong, Qiang, 2021. "Terrorist attacks and oil prices: Hypothesis and empirical evidence," International Review of Financial Analysis, Elsevier, vol. 74(C).
    19. Mustanen, Dmitri & Maaitah, Ahmad & Mishra, Tapas & Parhi, Mamata, 2022. "The power of investors’ optimism and pessimism in oil market forecasting," Energy Economics, Elsevier, vol. 114(C).
    20. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
    21. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil prices," MPRA Paper 77531, University Library of Munich, Germany.
    22. Hao, Xianfeng & Zhao, Yuyang & Wang, Yudong, 2020. "Forecasting the real prices of crude oil using robust regression models with regularization constraints," Energy Economics, Elsevier, vol. 86(C).
    23. Ramos & Pablo Negri & Martín Breitkopf & María Laura Ojeda, 2021. "From International to Regional Commodity Price Pass-through Using Self-Driven Recurrent Networks," Asociación Argentina de Economía Política: Working Papers 4513, Asociación Argentina de Economía Política.
    24. Bekiroglu, Korkut & Duru, Okan & Gulay, Emrah & Su, Rong & Lagoa, Constantino, 2018. "Predictive analytics of crude oil prices by utilizing the intelligent model search engine," Applied Energy, Elsevier, vol. 228(C), pages 2387-2397.
    25. Rubaszek Michal & Karolak Zuzanna & Kwas Marek & Uddin Gazi Salah, 2020. "The role of the threshold effect for the dynamics of futures and spot prices of energy commodities," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(5), pages 1-20, December.
    26. Degiannakis, Stavros & Filis, George, 2018. "Forecasting oil prices: High-frequency financial data are indeed useful," Energy Economics, Elsevier, vol. 76(C), pages 388-402.
    27. Lin, Ling & Jiang, Yong & Xiao, Helu & Zhou, Zhongbao, 2020. "Crude oil price forecasting based on a novel hybrid long memory GARCH-M and wavelet analysis model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 543(C).
    28. Paraschiv, Florentina & Mudry, Pierre-Antoine & Andries, Alin Marius, 2015. "Stress-testing for portfolios of commodity futures," Economic Modelling, Elsevier, vol. 50(C), pages 9-18.
    29. Jiaying Peng & Zhenghui Li & Benjamin M. Drakeford, 2020. "Dynamic Characteristics of Crude Oil Price Fluctuation—From the Perspective of Crude Oil Price Influence Mechanism," Energies, MDPI, vol. 13(17), pages 1-19, August.
    30. Vansteenkiste, Isabel, 2011. "What is driving oil futures prices? Fundamentals versus speculation," Working Paper Series 1371, European Central Bank.
    31. Konstantinidi, Eirini & Skiadopoulos, George, 2011. "Are VIX futures prices predictable? An empirical investigation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 543-560, April.
    32. Michael T. Chng, 2010. "Comparing Different Economic Linkages Among Commodity Futures," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(9‐10), pages 1348-1389, November.
    33. E. Mamatzakis, 2014. "Revealing asymmetries in the loss function of WTI oil futures market," Empirical Economics, Springer, vol. 47(2), pages 411-426, September.
    34. Liu, Jing & Ma, Feng & Tang, Yingkai & Zhang, Yaojie, 2019. "Geopolitical risk and oil volatility: A new insight," Energy Economics, Elsevier, vol. 84(C).
    35. Dbouk, Wassim & Jamali, Ibrahim, 2018. "Predicting daily oil prices: Linear and non-linear models," Research in International Business and Finance, Elsevier, vol. 46(C), pages 149-165.
    36. Arash Sioofy Khoojine & Mahboubeh Shadabfar & Yousef Edrisi Tabriz, 2022. "A Mutual Information-Based Network Autoregressive Model for Crude Oil Price Forecasting Using Open-High-Low-Close Prices," Mathematics, MDPI, vol. 10(17), pages 1-20, September.
    37. Cortazar, Gonzalo & Ortega, Hector & Valencia, Consuelo, 2021. "How good are analyst forecasts of oil prices?," Energy Economics, Elsevier, vol. 102(C).
    38. Cheng, Fangzheng & Li, Tian & Wei, Yi-ming & Fan, Tijun, 2019. "The VEC-NAR model for short-term forecasting of oil prices," Energy Economics, Elsevier, vol. 78(C), pages 656-667.
    39. Marek Kwas & Michał Rubaszek, 2021. "Forecasting Commodity Prices: Looking for a Benchmark," Forecasting, MDPI, vol. 3(2), pages 1-13, June.
    40. Nademi, Arash & Nademi, Younes, 2018. "Forecasting crude oil prices by a semiparametric Markov switching model: OPEC, WTI, and Brent cases," Energy Economics, Elsevier, vol. 74(C), pages 757-766.
    41. Liu, Li & Wang, Yudong & Yang, Li, 2018. "Predictability of crude oil prices: An investor perspective," Energy Economics, Elsevier, vol. 75(C), pages 193-205.
    42. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).

Articles

  1. Andrea Coppola & Alessandro Girardi & Gustavo Piga, 2013. "Overcrowding Versus Liquidity In The Euro Sovereign Bond Markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 18(4), pages 307-318, October.
    See citations under working paper version above.
  2. Andrea Coppola, 2008. "Forecasting oil price movements: Exploiting the information in the futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(1), pages 34-56, January.
    See citations under working paper version above.Sorry, no citations of articles recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 7 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-FOR: Forecasting (2) 2007-07-13 2015-08-30
  2. NEP-GER: German Papers (2) 2015-08-30 2015-08-30
  3. NEP-DEV: Development (1) 2015-06-27
  4. NEP-EEC: European Economics (1) 2012-02-27
  5. NEP-ENE: Energy Economics (1) 2007-07-13
  6. NEP-ICT: Information and Communication Technologies (1) 2015-08-30
  7. NEP-LAB: Labour Economics (1) 2011-11-01
  8. NEP-LMA: Labor Markets - Supply, Demand, and Wages (1) 2011-11-01
  9. NEP-MKT: Marketing (1) 2015-08-30
  10. NEP-PBE: Public Economics (1) 2014-03-30
  11. NEP-PPM: Project, Program and Portfolio Management (1) 2014-03-30

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