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Noisy Information, Distance and Law of One Price Dynamics Across US Cities

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  • Mario J. Crucini
  • Mototsugu Shintani
  • Takayuki Tsuruga

Abstract

Using micro price data across US cities, we provide evidence that both the volatility and persistence of deviations from the law of one price (LOP) are positively correlated with the distance between cities. A standard, two-city, equilibrium model with time- varying technology under homogeneous information can predict the relationship between the volatility and distance but not between the persistence and distance. To account for the latter fact, we augment the standard model with noisy signals about the state of nominal aggregate demand that are asymmetric across cities. We further establish that the interaction of imperfect information and sticky prices improves the fi t of the model.

Suggested Citation

  • Mario J. Crucini & Mototsugu Shintani & Takayuki Tsuruga, 2010. "Noisy Information, Distance and Law of One Price Dynamics Across US Cities," Discussion papers e-11-005, Graduate School of Economics Project Center, Kyoto University, revised Jan 2012.
  • Handle: RePEc:kue:dpaper:e-11-005
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    Cited by:

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    2. José‐María Montero & Tiziana Laureti & Román Mínguez & Gema Fernández‐Avilés, 2020. "A Stochastic Model with Penalized Coefficients for Spatial Price Comparisons: An Application to Regional Price Indexes in Italy," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(3), pages 512-533, September.
    3. Okui, Ryo & Yanagi, Takahide, 2019. "Panel data analysis with heterogeneous dynamics," Journal of Econometrics, Elsevier, vol. 212(2), pages 451-475.
    4. Craig Benedict & Mario J. Crucini & Anthony Landry, 2020. "On What States Do Prices Depend? Answers From Ecuador," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(8), pages 1909-1935, December.
    5. Choi, Chi-Young & Choi, Horag, 2016. "The role of two frictions in geographic price dispersion: When market friction meets nominal rigidity," Journal of International Money and Finance, Elsevier, vol. 63(C), pages 1-27.
    6. Tatsushi Okuda & Tomohiro Tsuruga & Francesco Zanetti, 2021. "Imperfect information, heterogeneous demand shocks, and inflation dynamics," CAMA Working Papers 2021-29, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Ryo Okui & Takahide Yanagi, 2020. "Kernel estimation for panel data with heterogeneous dynamics [Econometric tools for analyzing market outcomes]," Econometrics Journal, Royal Economic Society, vol. 23(1), pages 156-175.
    8. Lee, Yoon-Jin & Okui, Ryo & Shintani, Mototsugu, 2018. "Asymptotic inference for dynamic panel estimators of infinite order autoregressive processes," Journal of Econometrics, Elsevier, vol. 204(2), pages 147-158.
    9. Malloy Brandon, 2018. "The Supply Network and Price Dispersion in the Canadian Gasoline Market," Review of Network Economics, De Gruyter, vol. 17(2), pages 75-107, June.
    10. Choi, Chi-Young & Choi, Horag, 2014. "Does distance reflect more than transport costs?," Economics Letters, Elsevier, vol. 125(1), pages 82-86.
    11. Chi‐Young Choi & Anthony Murphy & Jyh‐Lin Wu, 2017. "Segmentation of consumer markets in the US: What do intercity price differences tell us?," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(3), pages 738-777, August.
    12. TAKECHI Kazutaka, 2016. "Daily Gravity," Discussion papers 16095, Research Institute of Economy, Trade and Industry (RIETI).
    13. Yoon J. Jo & Misaki Matsumura & David E. Weinstein, 2019. "The Impact of E-Commerce on Relative Prices and Consumer Welfare," NBER Working Papers 26506, National Bureau of Economic Research, Inc.
    14. David Fielding & Christopher Hajzler & James Macgee, 2015. "Distance, Language, Religion, and the Law of One Price: Evidence from Canada and Nigeria," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(5), pages 1007-1029, August.
    15. Guo, Zi-Yi, 2017. "Information heterogeneity, housing dynamics and the business cycle," EconStor Preprints 168561, ZBW - Leibniz Information Centre for Economics.
    16. Guo, Zi-Yi, 2017. "Information heterogeneity, housing dynamics and the business cycle," Economics Discussion Papers 2017-17, Kiel Institute for the World Economy (IfW).
    17. Ryo Kato & Tatsushi Okuda & Takayuki Tsuruga, 2020. "Sectoral inflation persistence, market concentration and imperfect common knowledge," ISER Discussion Paper 1082, Institute of Social and Economic Research, Osaka University.

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    More about this item

    Keywords

    Real exchange rates; Law of one price; Relative prices; Trade cost;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General

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