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Not all Surprises Matter: Attention and Monetary Transmission

Author

Listed:
  • David de Villiers

Abstract

This paper combines high-frequency monetary policy surprises with weekly Google search data in South Africa (2010–2026) to evaluate how central bank communication drives credit-related information acquisition. Using variation in shock magnitudes and pre-existing attention states, the results show that transmission is highly non-linear. Small policy surprises generate little measurable behavioural response, whereas large, salient shocks trigger significant credit search activity. Moreover, this behavioural response is highly conditional, heavily amplifying when baseline public attention is already elevated. This behavioural channel is concentrated within forward-looking formal credit searches, while distress-related and informal credit searches exhibit no systematic response to policy innovations. Ultimately, findings support the view that rational inattention operates as a selective filter on monetary policy transmission, suggesting that strategic central bank communication must actively navigate the public's shifting capacity to process policy surprises.

Suggested Citation

  • David de Villiers, 2026. "Not all Surprises Matter: Attention and Monetary Transmission," ERSA Working Paper Series 335, Economic Research Southern Africa.
    • Handle: RePEc:rza:ersawp:335
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    File URL: https://ersawps.org/index.php/working-paper-series/article/view/335/218
    File Function: First version, 2026
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    2. Zhang, Han & Zhao, Qing & Kuuluvainen, Jari & Wang, Changhai & Li, Shiping, 2015. "Determinants of China's lumber import: A bounds test for cointegration with monthly data," Journal of Forest Economics, Elsevier, vol. 21(4), pages 269-282.
    3. Clements, Kenneth W. & Gao, Grace, 2015. "The Rotterdam demand model half a century on," Economic Modelling, Elsevier, vol. 49(C), pages 91-103.
    4. Irfan, Muhammad & Cameron, Michael P. & Hassan, Gazi, 2018. "Household energy elasticities and policy implications for Pakistan," Energy Policy, Elsevier, vol. 113(C), pages 633-642.
    5. Libo Xu & Apostolos Serletis, 2022. "The Demand for Assets: Evidence from the Markov Switching Normalized Quadratic Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(4), pages 989-1025, June.
    6. Yangchuan Wang & Olga Isengildina Massa & Shamar L. Stewart, 2024. "Time‐varying reaction of U.S. meat demand to animal disease outbreaks," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 46(3), pages 983-1009, September.
    7. Atasoy, Filiz Guneysu & Zhang, Daowei, 2025. "Analyzing European Union wood pellet's import demand through the application of the almost ideal demand system and Rotterdam model," Renewable Energy, Elsevier, vol. 241(C).

    More about this item

    Keywords

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    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • E71 - Macroeconomics and Monetary Economics - - Macro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on the Macro Economy

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