During the coronavirus disease‐2019 pandemic, online grocery shopping experienced a never seen popularity in many countries. To study how the globally active online grocer Amazon Fresh reacted to this extraordinary demand increase, we analyzed a large dataset of daily price quotes for over 19,000 products for the customer location, Los Angeles. We found that contrary to the US consumer food price index, the overall price level at Amazon Fresh did not increase during the pandemic, but even slightly decreased for several product groups. Amazon seems to follow its low‐price strategy also in the grocery sector, even in times of high demand. However, during the lockdown phase, there were more price increases for certain highly demanded product groups such as frozen and prepared foods. Moreover, fewer prices were communicated as promotional prices. Because this change did not influence the general price level, we conclude that such promotional prices are used more as a marketing tool than as a price‐setting instrument.

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Purpose The purpose of this paper is to discuss web scraping as a method for extracting large amounts of data from online sources. The author wants to raise awareness of the method’s potential in the field of food price research, hoping to enable fellow researchers to apply this method. Design/methodology/approach The author explains the technical procedure of web scraping, reviews the existing literature, and identifies areas of application and limitations for food price research. Findings The author finds that web scraping is a promising method to collect customised, high-frequency data in real time, overcoming several limitations of currently used food price data sources. With today’s applications mostly focussing on (online) consumer prices, the scope of applications for web scraping broadens as more and more price data are published online. Research limitations/implications To better deal with the technical and legal challenges of web scraping and to exploit its scalability, joint data collection projects in the field of agricultural and food economics should be considered. Originality/value In agricultural and food economics, web scraping as a data collection technique has received little attention. This is one of the first articles to address this topic with particular focus on food price analysis.

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Switzerland applies seasonal tariff rate quotas (TRQs) for the import of many fruits and vegetables during the domestic harvest season. We examine how this system affects the relationship between Italian and Swiss tomato prices and test for physical market integration and spatial equilibrium conditions over time. We use detailed, transaction-based data on trade flows and trade costs and estimate an extended parity bounds model, following Barrett and Li (2002). We confirm that in the summer season, when TRQs are in place, markets are inefficient. While quota holders receive positive rents, the marginal rents for importers without quota shares are negative. This inhibits trade flows above the in-quota import quantity allowed by TRQs. Hence, despite leading to inefficiencies and creating rents for importers, seasonal TRQs are effective in protecting domestic production against competing imports.