Transport costs are considered relevant in assessing deviations from the law of one price. Arbitrage opportunities decrease as the cost of moving goods from one market to the other increases. We measure transport costs using two variables. As a proxy of transport costs two variables are considered: distance (in km) and travel times (in driving hours). Travel times are likely to capture relevant information beyond distance. For example, it would include time‐spent at border controls, which, in fact, can be a substantial amount of travel time.<sup>18</sup> Figure 34 and Figure 35 plot the relationship between both distance and travel times in retail markets for wheat. Figure 40 Figure 41 show the same relationship for wholesale.

Two indicators of nominal rigidities are considered: the speed of adjustment to shocks and a measure of price stickiness, proxying for menu costs (see next subsection for details on this variable). The speed of adjustment reflects how fast domestic shocks in Delhi are transmitted to other cities. If prices between a given state and Delhi do not respond to shocks at the same speed, we can expect higher differences in the law of one price. Price stickiness is measured as the probability that prices remain unchanged in consecutive months. We compute price stickiness for all commodities and states as the number of months where price differences were lower than 1 percent over the total number of months. High price stickiness indicates that prices are unlikely to change, due to, for example, high menu costs. In retail markets, price stickiness is on average 42 percent, which means that in every period there is a probability of 58 percent that prices change. We plot both measures against deviations from the law of one price for wheat in Figure 36 and Figure 37 for retail, and in Figure 42 and Figure 43 for wholesale.

Wireless phone penetration proxies for information frictions. Information frictions may also lead to failure of the law of one price. When pricing information is not shared across markets or is only available to a few agents in the market, agents might miss out on arbitrage opportunities. In recent years, both the private and public sectors have introduced several initiatives to increase access to information for different players in the market. Many of these initiatives consist of provision of information through, for example, mobile phones or online platforms. Therefore, state‐level data on the penetration of wireless cellular networks act as a good proxy for how well information flows. Lower cellular coverage is expected to be associated with larger deviations from the law of one price. Figure 38 and Figure 44 plot the correlation between the measure of information frictions and deviation from the law of one price for retail and wholesale, respectively.

A key feature of the India’s agricultural market is the APMC act. A dummy variable was constructed that takes the value of 1 if the act has been repealed or reformed and 0 otherwise (See Data Appendix for sources of information to construct this variable). On average, we do not observe that the presence of the APMC act is correlated with larger departures from the law of one price (Table 24 and Table 25 in the Appendix). One possible explanation is that the variable may be capturing state‐specific characteristics that cannot be fully controlled for in a cross‐sectional setting. States reformed the APMC act at different times – for example, some may have reformed toward the end of the period considered, but deviations from the law of one price are calculated on average for a relatively long period of time.<sup>19</sup>

> 18 World Bank (2016), for example, reports a study commissioned by the Ministry of Transport and Highways in the context of the Logistics Efficiency Enhancement Program (LEEP) logistics efficiency enhancement showing that 5 to 10 percent of travel time in India is spent on document verification.

> 19 Even though no clear relationship can be assessed between adherence to the APMC act and the extent of departures from the law of one price, it is worth mentioning that some of APMC marketing rules have a number of implications for market outcomes and the risk of anticompetitive behavior. Nyman (2017) argues that, first, restrictive licensing requirements for commission agents (CAs), for example, and the previous monopoly of the APMC marketing channel increase the risk of anticompetitive outcomes for farm‐gate prices. Restricting entry among CAs at the village level compounds issues raised by the reliance of farmers on CAs for information on prevailing wholesale prices and the importance of long‐term relationships between CAs and farmers / wholesalers in order to ensure reliability in the face of incomplete contracts. Several factors

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