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Price Dynamics with Customer Markets. (2014). Trachter, Nicholas ; Pozzi, Andrea ; Paciello, Luigi.
In: Working Paper.
RePEc:fip:fedrwp:14-17.

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  1. Influence of Price Level and Perceived Price Dispersion on Consumer Information Search Behaviour: Moderating Effect of Durables and Consumables. (2021). Chi, Maomao ; Dan, Qianyi ; Li, Weiqing ; Wang, Weijun.
    In: Sustainability.
    RePEc:gam:jsusta:v:13:y:2021:i:4:p:2105-:d:500212.

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  2. Customer Capital, Markup Cyclicality, and Amplification. (2019). Hong, Sung Ki.
    In: Working Papers.
    RePEc:fip:fedlwp:2017-033.

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  3. Customer relationship and sales. (2016). Shi, Shouyong.
    In: Journal of Economic Theory.
    RePEc:eee:jetheo:v:166:y:2016:i:c:p:483-516.

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References

References cited by this document

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  2. As explained in Eichenbaum et al. (2011), this only allows us to recover an average price for goods that were on promotion. In fact the same good will be sold to loyalty card carrying customers at the promotional price and at full price to customers who do not have or use a loyalty card. Without information on the fraction of these two types of customers it is not possible to recover the two prices separately. Furthermore, since prices are constructed based on information on sales, missing values can originate even in this case if no unit of a specific item is sold in a given store in a week. This is, however, an unfrequent circumstance and involves only rarely purchased UPCs, which are unlikely to represent important shares of the basket for any of the households in the sample. For the analysis, we only retain UPCs with at most two nonconsecutive missing price observations and impute price for the missing observation interpolating the prices of the contiguous weeks.
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  3. B Data sources and variables construction B.1 Data and selection of the sample The empirical evidence presented in Section 4 is based on two data sources provided by a large supermarket chain that operates over 1500 stores across the United States. This implies that we can observe our agents behavior only when they shop with the chain; on the other hand, cash register data contain significantly less measurement error than databases relying on home scanning (Einav et al. (2010)).
    Paper not yet in RePEc: Add citation now
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  29. Steindl, J. (1965). Random processes and the growth of firms: A study of the Pareto law, Griffin London.
    Paper not yet in RePEc: Add citation now
  30. The main data source contains information on grocery purchases at the chain between June 2004 and June 2006 for a panel of over 11,000 households. For each grocery trip made by a household, we observe date and store where the trip occurred, the collection of all the UPCs purchased with quantity and price paid. The data include information on the presence and size of price discounts but do not generally report redemption of manufacturer coupons. Data are collected through usage of the loyalty card; purchases made without using the card are not recorded. However, the chain ensures that the loyalty card has a high penetration by keeping to a minimum the effort needed to register for one. Furthermore, nearly all promotional discount are tied to ownership of a loyalty card, which provides a strong incentive to use it.
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Cocites

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  3. Price dispersion and the border effect. (2020). Chahrour, Ryan ; Stevens, Luminita.
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  4. Price Dispersion and the Border Effect. (2019). Stevens, Luminita ; Chahrour, Ryan.
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  7. Price Dynamics with Customer Markets. (2017). Trachter, Nicholas ; Pozzi, Andrea ; Paciello, Luigi.
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  8. Retailers and Consumers: The Pass-through of Import Price Changes. (2017). Birg, Laura ; Boddin, Dominik ; Berner, Eike.
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  9. Retailers and Consumers: The pass-through of import price changes. (2016). Boddin, Dominik ; Birg, Laura ; Berner, Eike.
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  10. Constant versus Variable Markups: Implications for the Law of One Price. (2016). YILMAZKUDAY, HAKAN.
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  19. Pricing to Market as a Revelator of Policy-Induced Market Power. (2014). Rais, Daniel .
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