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References

  • Adämmer, Philipp, and Rainer A Schüssler, 2020, Forecasting the equity premium: Mind the news!, Review of Finance 24, 1313–1355.
  • Altug, Sumru, and Cem Çakmaklı, 2016, Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey, International Journal of Forecasting 32, 138–153.
  • Andre, Peter, Ingar Haaland, Chrisotpher Roth, and Johannes Wohlfart, 2021a, Inflation narratives, CEPR Discussion Paper No. DP16758 .
  • Andre, Peter, Ingar Haaland, Christopher Roth, and Johannes Wohlfart, 2021b, Narratives about the macroeconomy, CEPR Discussion Paper No. DP17350 .
  • Ang, Andrew, Geert Bekaert, and Min Wei, 2007, Do macro variables, asset markets, or surveys forecast inflation better?, Journal of Monetary Economics 54, 1163–1212.
  • Armantier, Olivier, Scott Nelson, Giorgio Topa, Wilbert Van der Klaauw, and Basit Zafar, 2016, The price is right: Updating inflation expectations in a randomized price information experiment, Review of Economics and Statistics 98, 503–523.
  • Atkeson, Andrew, Lee E Ohanian, et al., 2001, Are phillips curves useful for forecasting inflation?, Federal Reserve Bank of Minneapolis Quarterly Review 25, 2–11.
  • Babii, Andrii, Eric Ghysels, and Jonas Striaukas, 2021, Machine learning time series regressions with an application to nowcasting, Journal of Business and Economic Statistics 1–23.
  • Baker, Scott R., Nicholas Bloom, and Steven J. Davis, 2016, Measuring economic policy uncertainty, Quarterly Journal of Economics 131, 1593–1636.
  • Bali, Turan G, Amit Goyal, Dashan Huang, Fuwei Jiang, and Quan Wen, 2020, Different strokes: Return predictability across stocks and bonds with machine learning and big data, Georgetown McDonough School of Business Research Paper 20–110.
  • Berge, Travis J., 2018, Understanding survey-based inflation expectations, International Journal of Forecasting 34, 788–801.
  • Bernanke, Ben S., and Michael Woodford, 1997, Inflation forecasts and monetary policy, Journal of Money, Credit and Banking 29.
  • Bertsch, Christoph, Isaiah Hull, and Xin Zhang, 2021, Narrative fragmentation and the business cycle, Economics Letters 201, 109783.
  • Bianchi, Daniele, Matthias Büchner, Andrea Tamoni, and Stijn Van Nieuwerburgh, 2021, Bond risk premiums with machine learning, Review of Financial Studies 34, 1046–1089.
  • Bils, Mark, and Peter J Klenow, 2004, Some evidence on the importance of sticky prices, Journal of political economy 112, 947–985.
  • Blei, David M, Andrew Y Ng, and Michael I Jordan, 2003, Latent dirichlet allocation, Journal of Machine Learning Research 3, 993–1022.
  • Bolhuis, Marijn A, Judd NL Cramer, and Lawrence H Summers, 2022a, The coming rise in residential inflation, Review of Finance .
  • Bolhuis, Marijn A, Judd NL Cramer, and Lawrence H Summers, 2022b, Comparing past and present inflation, Review of Finance .
  • Breiman, Leo, 2001, Random forests, Machine learning 45, 5–32.
  • Burke, Marshall, Solomon M Hsiang, and Edward Miguel, 2015, Global non-linear effect of temperature on economic production, Nature 527, 235–239.
  • Bursztyn, Leonardo, Aakaash Rao, Christopher Roth, David Yanagizawa-Drott, et al., forthcoming, Opinions as facts, Review of Economic Studies .
  • Bybee, Leland, Bryan T Kelly, Asaf Manela, and Dacheng Xiu, 2021, Business news and business cycles, Technical report, National Bureau of Economic Research.
  • Carlstrom, Charles T, Timothy S Fuerst, and Matthias Paustian, 2009, Inflation persistence, monetary policy, and the great moderation, Journal of Money, Credit and Banking 41, 767–786.
  • Claeskens, Gerda, Jan R Magnus, Andrey L Vasnev, and Wendun Wang, 2016, The forecast combination puzzle: A simple theoretical explanation, International Journal of Forecasting 32, 754–762.
  • Clark, Todd, and Michael McCracken, 2013, Advances in forecast evaluation, Handbook of Economic Forecasting 2, 1107–1201.
  • Clark, Todd E, and Michael W McCracken, 2015, Nested forecast model comparisons: a new approach to testing equal accuracy, Journal of Econometrics 186, 160–177.
  • Clark, Todd E, and Kenneth D West, 2007, Approximately normal tests for equal predictive accuracy in nested models, Journal of Econometrics 138, 291–311.
  • Coibion, Olivier, and Yuriy Gorodnichenko, 2012, What can survey forecasts tell us about information rigidities?, Journal of Political Economy 120, 116–159.
  • Coibion, Olivier, and Yuriy Gorodnichenko, 2015a, Information rigidity and the expectations formation process: A simple framework and new facts, American Economic Review 105, 2644–78.
  • Coibion, Olivier, and Yuriy Gorodnichenko, 2015b, Is the phillips curve alive and well after all? inflation expectations and the missing disinflation, American Economic Journal: Macroeconomics 7, 197–232.
  • Coibion, Olivier, Yuriy Gorodnichenko, and Rupal Kamdar, 2018, The formation of expectations, inflation, and the phillips curve, Journal of Economic Literature 56, 1447–1491.
  • Coibion, Olivier, Yuriy Gorodnichenko, and Michael Weber, 2022, Monetary policy communications and their effects on household inflation expectations, Journal of Political Economy 130, 000–000.
  • D’Agostino, Antonello, and Paolo Surico, 2012, A century of inflation forecasts, Review of Economics and Statistics 94, 1097–1106.
  • Diebold, Francis X., 2015, Comparing predictive accuracy, twenty years later: A personal perspective on the use and abuse of Diebold–Mariano tests, Journal of Business and Economic Statistics 33, 1–1.
  • Diebold, Francis X, and Roberto S Mariano, 1995, Comparing predictive accuracy., Journal of Business and Economic Statistics 13, 253–63.
  • Diebold, Francis X, and Minchul Shin, 2019, Machine learning for regularized survey forecast combination: Partially-egalitarian lasso and its derivatives, International Journal of Forecasting 35, 1679–1691.
  • Faust, Jon, and Jonathan H Wright, 2013, Forecasting inflation, in Handbook of Economic Forecasting, volume 2, 2–56 (Elsevier).
  • Forni, Mario, Marc Hallin, Marco Lippi, and Lucrezia Reichlin, 2003, Do financial variables help forecasting inflation and real activity in the euro area?, Journal of Monetary Economics 50, 1243–1255.
  • Giacomini, Raffaella, and Halbert White, 2006, Tests of conditional predictive ability, Econometrica 74, 1545–1578.
  • Gospodinov, Nikolay, and Serena Ng, 2013, Commodity prices, convenience yields, and inflation, Review of Economics and Statistics 95, 206–219.
  • Goulet Coulombe, Philippe, Maxime Leroux, Dalibor Stevanovic, and Stéphane Surprenant, 2022, How is machine learning useful for macroeconomic forecasting?, Journal of Applied Econometrics 37, 920–964.
  • Groen, Jan J. J., Richard Paap, and Francesco Ravazzolo, 2013, Real-time inflation forecasting in a changing world, Journal of Business and Economic Statistics 31, 29–44.
  • Gu, Shihao, Bryan Kelly, and Dacheng Xiu, 2020, Empirical asset pricing via machine learning, Review of Financial Studies 33, 2223–2273.
  • Hansen, Peter R, Asger Lunde, and James M Nason, 2011, The model confidence set, Econometrica 79, 453–497.
  • Hooker, Mark A, 2002, Are oil shocks inflationary? asymmetric and nonlinear specifications versus changes in regime, Journal of Money, Credit and Banking 540–561.
  • Huang, Dashan, Fuwei Jiang, Kunpeng Li, Guoshi Tong, and Guofu Zhou, 2022, Scaled pca: A new approach to dimension reduction, Management Science 68, 1678–1695.
  • Huang, Dashan, Fuwei Jiang, Kunpeng Li, Guoshi Tong, and Guofu Zhou, 2023, Are bond returns predictable with real-time macro data?, Journal of Econometrics 237, 105438.
  • Huang, Dashan, Fuwei Jiang, Jun Tu, and Guofu Zhou, 2015, Investor sentiment aligned: A powerful predictor of stock returns, Review of Financial Studies 28, 791–837.
  • Ibarra, Raul, 2012, Do disaggregated cpi data improve the accuracy of inflation forecasts?, Economic Modelling 29, 1305–1313.
  • Jiang, Fuwei, Joshua Lee, Xiumin Martin, and Guofu Zhou, 2019, Manager sentiment and stock returns, Journal of Financial Economics 132, 126–149.
  • Jiang, Fuwei, Kunpeng Li, Lingchao Meng, and Bowen Xue, 2022, Measuring real-time economic condition with economic narratives, Available at SSRN 4254796 .
  • Kellenberg, Derek K, and Ahmed Mushfiq Mobarak, 2008, Does rising income increase or decrease damage risk from natural disasters?, Journal of Urban Economics 63, 788–802.
  • Kelly, Bryan, and Seth Pruitt, 2013, Market expectations in the cross-section of present values, Journal of Finance 68, 1721–1756.
  • Larsen, Vegard H, Leif Anders Thorsrud, and Julia Zhulanova, 2021, News-driven inflation expectations and information rigidities, Journal of Monetary Economics 117, 507–520.
  • Leippold, Markus, Qian Wang, and Wenyu Zhou, 2022, Machine learning in the chinese stock market, Journal of Financial Economics 145, 64–82.
  • Levy, Ro’ee, 2021, Social media, news consumption, and polarization: Evidence from a field experiment, American Economic Review 111, 831–70.
  • Lucas, Robert E, and Thomas J Sargent, 1979, After keynesian macroeconomics, Federal Reserve Bank of Minneapolis Quarterly Review 3, 1–16.
  • Lucas Jr, Robert E, 1972, Expectations and the neutrality of money, Journal of Economic Theory 4, 103–124.
  • Manela, Asaf, and Alan Moreira, 2017, News implied volatility and disaster concerns, Journal of Financial Economics 123, 137–162.
  • McCracken, Michael W, and Serena Ng, 2016, Fred-md: A monthly database for macroeconomic research, Journal of Business and Economic Statistics 34, 574–589.
  • Medeiros, Marcelo C, Gabriel FR Vasconcelos, Álvaro Veiga, and Eduardo Zilberman, 2021, Forecasting inflation in a data-rich environment: the benefits of machine learning methods, Journal of Business and Economic Statistics 39, 98–119.
  • Mehra, Yash P, 2002, Survey measures of expected inflation: revisiting the issues of predictive content and rationality, FRB Richmond Economic Quarterly 88, 17–36.
  • Mullainathan, Sendhil, and Andrei Shleifer, 2005, The market for news, American Economic Review 95, 1031–1053.
  • Muth, John F, 1961, Rational expectations and the theory of price movements, Econometrica 315–335.
  • Odendahl, Florens, Barbara Rossi, and Tatevik Sekhposyan, 2022, Evaluating forecast performance with state dependence, Journal of Econometrics .
  • Pedemonte, Mathieu, 2019, Fireside chats: Communication and consumers’ expectations in the great depression, Review of Economics and Statistics 1–46.
  • Phillips, Alban W, 1958, The relation between unemployment and the rate of change of money wage rates in the united kingdom, 1861-1957, Economica 25, 283–299.
  • Rapach, David E, Jack K Strauss, and Guofu Zhou, 2010, Out-of-sample equity premium prediction: Combination forecasts and links to the real economy, Review of Financial Studies 23, 821–862.
  • Ryngaert, Jane M, 2022, Inflation disasters and consumption, Journal of Monetary Economics .
  • Schmitt-Grohé, Stephanie, and Martín Uribe, 2022, What do long data tell us about the inflation hike post covid-19 pandemic?, Working Paper 30357, National Bureau of Economic Research.
  • Shiller, Robert J., 2017, Narrative economics, American Economic Review 107, 967–1004.
  • Stock, James H, and Mark W Watson, 1999, Forecasting inflation, Journal of Monetary Economics 44, 293–335.
  • Stock, James H, and Mark W Watson, 2002, Forecasting using principal components from a large number of predictors, Journal of American Statistical Association 97, 1167–1179.
  • Stock, James H, and Mark W Watson, 2003, Forecasting output and inflation: The role of asset prices, Journal of Economic Literature 41, 788–829.
  • Stock, James H, and Mark W Watson, 2007, Why has us inflation become harder to forecast?, Journal of Money, Credit and Banking 39, 3–33.
  • Stock, James H, and Mark W Watson, 2016, Core inflation and trend inflation, Review of Economics and Statistics 98, 770–784.
  • Stockton, David J, and James E Glassman, 1987, An evaluation of the forecast performance of alternative models of inflation, Review of Economics and Statistics 108–117.
  • Stulz, Rene M, 1986, Asset pricing and expected inflation, The Journal of Finance 41, 209–223.
  • Svensson, Lars EO, and Michael Woodford, 2004, Implementing optimal policy through inflation-forecast targeting, in The Inflation-Targeting Debate, 19–92 (University of Chicago Press).
  • Tetlock, Paul C., 2007, Giving content to investor sentiment: The role of media in the stock market, Journal of Finance 62, 1139–1168.
  • Thomas, Lloyd B, 1999, Survey measures of expected us inflation, Journal of Economic Perspectives 13, 125–144.
  • Thorsrud, Leif Anders, 2020, Words are the new numbers: A newsy coincident index of the business cycle, Journal of Business and Economic Statistics 38, 393–409.
  • Tibshirani, Robert, 1996, Regression shrinkage and selection via the lasso, Journal of Royal Statistical Society: Series B (Methodological) 58, 267–288.
  • Verbrugge, Randal J., and Saeed Zaman, 2021, Whose inflation expectations best predict inflation?, Economic Commentary (Federal Reserve Bank of Cleveland) 1–7.
  • Welch, Ivo, and Amit Goyal, 2008, A comprehensive look at the empirical performance of equity premium prediction, Review of Financial Studies 21, 1455–1508.
  • Wold, Herman, 1966, Estimation of principal components and related models by iterative least squares, Multivariate Analysis 391–420.
  • Zheng, Tingguo, Xinyue Fan, Wei Jin, and Kuangnan Fang, 2023, Words or numbers? macroeconomic nowcasting with textual and macroeconomic data, International Journal of Forecasting .
  • Zou, Hui, and Trevor Hastie, 2005, Regularization and variable selection via the elastic net, Journal of Royal Statistical Society: series B (Statistical Methodology) 67, 301–320.

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