IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v86y2023ipas0301420723009625.html
   My bibliography  Save this article

“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone

Author

Listed:
  • Hardy, Nicolás
  • Ferreira, Tiago
  • Quinteros, Maria J.
  • Magner, Nicolás S.

Abstract

This paper presents robust evidence indicating that the tone of financial reports from the US mining industry firms can predict certain mining commodity returns. We assess this predictive ability with different tests, including evaluations of mean squared prediction errors, correlations, mean directional accuracy, and trading strategies. We compared our results with several benchmarks proposed in the literature, including the random walk, outperforming most statistically and economically. Our findings are related to the literature on firms' strategic disclosure choices, suggesting that firms may strategically tailor their disclosure decisions to influence investor expectations regarding future performance. Additionally, we conduct a series of placebo tests, revealing significant outcomes: (1) the tone of financial reports from other industries does not exhibit predictive power for mining industry commodity returns, (2) this predictive ability is not overshadowed when controlling for uncertainty measures, such as VIX, OVX, realized volatility and Google Trends commodity price searches, and (3) the tone of the mining industry's financial report does not predict returns for unrelated mining commodities. To our knowledge, our work is the first paper to employ financial report tone through text mining of nearly 60,000 financial reports to forecast commodity returns. Our findings substantially contribute to the commodity forecasting literature, offering valuable insights for portfolio managers and professionals seeking to enhance their forecasting capabilities.

Suggested Citation

  • Hardy, Nicolás & Ferreira, Tiago & Quinteros, Maria J. & Magner, Nicolás S., 2023. "“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone," Resources Policy, Elsevier, vol. 86(PA).
  • Handle: RePEc:eee:jrpoli:v:86:y:2023:i:pa:s0301420723009625
    DOI: 10.1016/j.resourpol.2023.104251
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420723009625
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.resourpol.2023.104251?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Trevor A. Reeve & Robert J. Vigfusson, 2011. "Evaluating the forecasting performance of commodity futures prices," International Finance Discussion Papers 1025, Board of Governors of the Federal Reserve System (U.S.).
    3. Barbara Rossi & Atsushi Inoue, 2012. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 432-453, April.
    4. Cheung, Yin-Wong & Chinn, Menzie D. & Pascual, Antonio Garcia & Zhang, Yi, 2019. "Exchange rate prediction redux: New models, new data, new currencies," Journal of International Money and Finance, Elsevier, vol. 95(C), pages 332-362.
    5. Jan J. J. Groen & Paolo A. Pesenti, 2011. "Commodity Prices, Commodity Currencies, and Global Economic Developments," NBER Chapters, in: Commodity Prices and Markets, pages 15-42, National Bureau of Economic Research, Inc.
    6. Skinner, Dj, 1994. "Why Firms Voluntarily Disclose Bad-News," Journal of Accounting Research, Wiley Blackwell, vol. 32(1), pages 38-60.
    7. Kalok Chan & Yiuman Tse & Michael Williams, 2011. "The Relationship between Commodity Prices and Currency Exchange Rates: Evidence from the Futures Markets," NBER Chapters, in: Commodity Prices and Markets, pages 47-71, National Bureau of Economic Research, Inc.
    8. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
    9. Menzie D. Chinn & Olivier Coibion, 2014. "The Predictive Content of Commodity Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(7), pages 607-636, July.
    10. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2020. "A random walk through the trees: Forecasting copper prices using decision learning methods," Resources Policy, Elsevier, vol. 69(C).
    11. Priyank Gandhi & Tim Loughran & Bill McDonald, 2019. "Using Annual Report Sentiment as a Proxy for Financial Distress in U.S. Banks," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 20(4), pages 424-436, October.
    12. Richard Meese & Kenneth Rogoff, 1983. "The Out-of-Sample Failure of Empirical Exchange Rate Models: Sampling Error or Misspecification?," NBER Chapters, in: Exchange Rates and International Macroeconomics, pages 67-112, National Bureau of Economic Research, Inc.
    13. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    14. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    15. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507, Elsevier.
    16. Hong, Harrison & Yogo, Motohiro, 2012. "What does futures market interest tell us about the macroeconomy and asset prices?," Journal of Financial Economics, Elsevier, vol. 105(3), pages 473-490.
    17. Fernandez, Viviana, 2017. "Rare-earth elements market: A historical and financial perspective," Resources Policy, Elsevier, vol. 53(C), pages 26-45.
    18. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    19. Pincheira, Pablo & Hardy, Nicolás, 2021. "Forecasting aluminum prices with commodity currencies," Resources Policy, Elsevier, vol. 73(C).
    20. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    21. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1145-1194.
    22. Meng Gao & Jiekun Huang & Itay Goldstein, 2020. "Informing the Market: The Effect of Modern Information Technologies on Information Production," The Review of Financial Studies, Society for Financial Studies, vol. 33(4), pages 1367-1411.
    23. Meng Gao & Jiekun Huang & Itay GoldsteinEditor, 2020. "Informing the Market: The Effect of Modern Information Technologies on Information Production," Review of Finance, European Finance Association, vol. 33(4), pages 1367-1411.
    24. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    25. Graham, John R. & Harvey, Campbell R. & Rajgopal, Shiva, 2005. "The economic implications of corporate financial reporting," Journal of Accounting and Economics, Elsevier, vol. 40(1-3), pages 3-73, December.
    26. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    27. Barbara Rossi, 2012. "The Changing Relationship Between Commodity Prices and Equity Prices in Commodity Exporting Countries," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 60(4), pages 533-569, December.
    28. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-565, October.
    29. Pincheira Brown, Pablo & Hardy, Nicolás, 2019. "Forecasting base metal prices with the Chilean exchange rate," Resources Policy, Elsevier, vol. 62(C), pages 256-281.
    30. Tim Loughran & Bill McDonald, 2017. "The Use of EDGAR Filings by Investors," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 18(2), pages 231-248, April.
    31. Alwathnani, Abdulaziz M. & Dubofsky, David A. & Al-Zoubi, Haitham A., 2017. "Under-or-overreaction: Market responses to announcements of earnings surprises," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 160-171.
    32. Chevapatrakul, Thanaset & Mascia, Danilo V., 2019. "Detecting overreaction in the Bitcoin market: A quantile autoregression approach," Finance Research Letters, Elsevier, vol. 30(C), pages 371-377.
    33. Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 369-404.
    34. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    35. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    36. Rubaszek, Michał & Karolak, Zuzanna & Kwas, Marek, 2020. "Mean-reversion, non-linearities and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 65(C).
    37. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    38. Borgards, Oliver & Czudaj, Robert L. & Hoang, Thi Hong Van, 2021. "Price overreactions in the commodity futures market: An intraday analysis of the Covid-19 pandemic impact," Resources Policy, Elsevier, vol. 71(C).
    39. Graham Elliott & Allan Timmermann, 2016. "Economic Forecasting," Economics Books, Princeton University Press, edition 1, number 10740.
    40. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    41. Pablo Pincheira Brown & Nicolás Hardy, 2024. "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1835-1858, September.
    42. Minna Martikainen & Antti Miihkinen & Luke Watson, 2022. "Board characteristics and negative disclosure tone," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 45(1), pages 100-129, December.
    43. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
    44. Peter R. Hansen & Asger Lunde & James M. Nason, 2011. "The Model Confidence Set," Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
    45. Marek Kwas & Michał Rubaszek, 2021. "Forecasting Commodity Prices: Looking for a Benchmark," Forecasting, MDPI, vol. 3(2), pages 1-13, June.
    46. Thomas A. Knetsch, 2007. "Forecasting the price of crude oil via convenience yield predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 527-549.
    47. Kearney, Colm & Liu, Sha, 2014. "Textual sentiment in finance: A survey of methods and models," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 171-185.
    48. 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.
    49. Pablo Pincheira-Brown & Nicolás Hardy & Cristobal Henrriquez & Ignacio Tapia & Andrea Bentancor, 2023. "Forecasting Base Metal Prices with an International Stock Index," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 73(3), pages 277-302, October.
    50. Kerstin Lopatta & Mario Albert Gloger & Reemda Jaeschke, 2017. "Can Language Predict Bankruptcy? The Explanatory Power of Tone in 10‐K Filings," Accounting Perspectives, John Wiley & Sons, vol. 16(4), pages 315-343, December.
    51. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    52. Peter R. Locke & P. C. Venkatesh, 1997. "Futures market transaction costs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 17(2), pages 229-245, April.
    53. Yu, Lean & Zhao, Yaqing & Tang, Ling & Yang, Zebin, 2019. "Online big data-driven oil consumption forecasting with Google trends," International Journal of Forecasting, Elsevier, vol. 35(1), pages 213-223.
    54. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    55. West, Kenneth D. & Wong, Ka-Fu, 2014. "A factor model for co-movements of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 289-309.
    56. Anatolyev, Stanislav & Gerko, Alexander, 2005. "A Trading Approach to Testing for Predictability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 455-461, October.
    57. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    58. Bowman, Robert G. & Iverson, David, 1998. "Short-run overreaction in the New Zealand stock market," Pacific-Basin Finance Journal, Elsevier, vol. 6(5), pages 475-491, November.
    59. Belasen, Ariel R. & Demirer, Rıza, 2019. "Commodity-currencies or currency-commodities: Evidence from causality tests," Resources Policy, Elsevier, vol. 60(C), pages 162-168.
    60. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    61. Barbara Rossi, 2012. "The changing relationship between commodity prices and equity prices in commodity exporting," Economics Working Papers 1405, Department of Economics and Business, Universitat Pompeu Fabra.
    62. Ankit Jain & Hariom Manchiraju & Shyam V. Sunder, 2023. "Institutional ownership and the informativeness of disclosure tone," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 50(1-2), pages 61-90, January.
    63. Gargano, Antonio & Timmermann, Allan, 2014. "Forecasting commodity price indexes using macroeconomic and financial predictors," International Journal of Forecasting, Elsevier, vol. 30(3), pages 825-843.
    64. Pincheira, Pablo & Hardy, Nicolás & Muñoz, Felipe, 2021. ""Go wild for a while!": A new asymptotically Normal test for forecast evaluation in nested models," MPRA Paper 105368, University Library of Munich, Germany.
    65. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
    66. Feng Li, 2010. "The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 48(5), pages 1049-1102, December.
    67. Ciner, Cetin, 2017. "Predicting white metal prices by a commodity sensitive exchange rate," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 309-315.
    68. Pincheira-Brown, Pablo & Bentancor, Andrea & Hardy, Nicolás & Jarsun, Nabil, 2022. "Forecasting fuel prices with the Chilean exchange rate: Going beyond the commodity currency hypothesis," Energy Economics, Elsevier, vol. 106(C).
    69. Pablo Pincheira & Nicolas Hardy & Andrea Bentancor, 2022. "A Simple Out-of-Sample Test of Predictability against the Random Walk Benchmark," Mathematics, MDPI, vol. 10(2), pages 1-20, January.
    70. Amor Aniss Benmoussa & Reinhard Ellwanger & Stephen Snudden, 2020. "The New Benchmark for Forecasts of the Real Price of Crude Oil," Staff Working Papers 20-39, Bank of Canada.
    71. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    72. Rubaszek, Michał & Uddin, Gazi Salah, 2020. "The role of underground storage in the dynamics of the US natural gas market: A threshold model analysis," Energy Economics, Elsevier, vol. 87(C).
    73. Zhang, Yaojie & Wei, Yu & Zhang, Yi & Jin, Daxiang, 2019. "Forecasting oil price volatility: Forecast combination versus shrinkage method," Energy Economics, Elsevier, vol. 80(C), pages 423-433.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pincheira, Pablo & Hardy, Nicolás, 2021. "Forecasting aluminum prices with commodity currencies," Resources Policy, Elsevier, vol. 73(C).
    2. Pincheira-Brown, Pablo & Bentancor, Andrea & Hardy, Nicolás & Jarsun, Nabil, 2022. "Forecasting fuel prices with the Chilean exchange rate: Going beyond the commodity currency hypothesis," Energy Economics, Elsevier, vol. 106(C).
    3. Nicolas S. Magner & Nicolás Hardy & Tiago Ferreira & Jaime F. Lavin, 2023. "“Agree to Disagree”: Forecasting Stock Market Implied Volatility Using Financial Report Tone Disagreement Analysis," Mathematics, MDPI, vol. 11(7), pages 1-16, March.
    4. Nicolás Magner & Nicolás Hardy, 2022. "Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle," Mathematics, MDPI, vol. 10(13), pages 1-27, July.
    5. Pincheira Brown, Pablo & Hardy, Nicolás, 2019. "Forecasting base metal prices with the Chilean exchange rate," Resources Policy, Elsevier, vol. 62(C), pages 256-281.
    6. Pablo Pincheira-Brown & Nicolás Hardy & Cristobal Henrriquez & Ignacio Tapia & Andrea Bentancor, 2023. "Forecasting Base Metal Prices with an International Stock Index," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 73(3), pages 277-302, October.
    7. Pincheira, Pablo & Hardy, Nicolas, 2018. "Forecasting Base Metal Prices with Commodity Currencies," MPRA Paper 83564, University Library of Munich, Germany.
    8. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    9. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    10. Pablo Pincheira & Nicolás Hardy & Felipe Muñoz, 2021. "“Go Wild for a While!”: A New Test for Forecast Evaluation in Nested Models," Mathematics, MDPI, vol. 9(18), pages 1-28, September.
    11. Pincheira, Pablo & Hardy, Nicolas, 2018. "The predictive relationship between exchange rate expectations and base metal prices," MPRA Paper 89423, University Library of Munich, Germany.
    12. Clark, Todd & McCracken, Michael, 2013. "Advances in Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201, Elsevier.
    13. Pincheira, Pablo & Jarsun, Nabil, 2020. "Summary of the Paper Entitled: Forecasting Fuel Prices with the Chilean Exchange Rate," MPRA Paper 105056, University Library of Munich, Germany.
    14. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    15. Marek Kwas & Michał Rubaszek, 2021. "Forecasting Commodity Prices: Looking for a Benchmark," Forecasting, MDPI, vol. 3(2), pages 1-13, June.
    16. Pincheira-Brown, Pablo & Neumann, Federico, 2020. "Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile," Finance Research Letters, Elsevier, vol. 37(C).
    17. Pablo Pincheira Brown & Nicolás Hardy, 2024. "Correlation‐based tests of predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1835-1858, September.
    18. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    19. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    20. Pablo Pincheira Brown & Nicolás Hardy, 2023. "Forecasting base metal prices with exchange rate expectations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2341-2362, December.

    More about this item

    Keywords

    Forecasting; Text-mining; Sentiment analysis; Commodities; Base metals; Time-series models; Out-of-sample comparison; Base metal equity securities; Qualitative disclosure; Linguistic tone;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • L74 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Construction
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:86:y:2023:i:pa:s0301420723009625. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.