# Section 5: Conclusions

This paper examined patterns of market integration for food commodities in India. First, it tested the extent of domestic spatial market integration for retail and wholesale markets for the periods 2006‐ 2014 and 2008‐2015, respectively, and looked at patterns of price transmission of shocks from international sources. Second, it measured vertical integration from wholesale to retail markets, and tested for asymmetric speed of adjustment to shocks. Third, it examined the determinants of spatial integration.

The results reveal that food markets in India are imperfectly integrated across space, with the law of one price being systematically rejected. To be sure, price signals are geographically transmitted both in retail and wholesale markets, but substantial heterogeneities by states and by products prevail. The case of red onions in Akluj and Pandharpur is not an exception, but rather a rule: Substantial price differences exist for narrowly defined products. In 90 percent of the cases, the price difference paid in any given city with respect to Delhi for a given product ranges from ‐28 percent to +28 percent. with substantial heterogeneities by states and by products.

There is substantial co‐movement between wholesale and retail prices, although integration is still imperfect in all commodities but one: rice, for which perfect vertical integration cannot be rejected. Also, retail prices adjust faster when wholesale prices rise than when wholesale prices fall. The analysis of determinants of spatial integration reveals that prior to GST implementation, the mere act of crossing a state border increased prices, that unexploited gains from arbitrage persisted after considering the effects of transport costs, and that information frictions and menu costs reduced market integration.

The results this paper unveils present some policy implications. First, distance and travel times explain part of the incompleteness of market integration documented in this paper, adding to the price premium that consumers in remote regions pay for food products. This suggests that investing in hard infrastructure will reduce spatial price differences. Indeed, the results reported here suggest that 10 percent price differences in wholesale markets are associated with travel times of about 24 hours that are roughly equivalent to 1,000km. Relatedly, enhancing logistics efficiency through increased competition will also help. While part of the effect captured through the travel times and distance variables relate to hard infrastructure, another part relates to how efficient logistics services are in India. Travel times could also increase, for example, because of inadequate maintenance of vehicles, or due to coordination problems at different stages of the logistics supply chain, or de jure and de facto requirements that arbitrarily increase travel times.<sup>23</sup> Encouraging competition in the transport and logistics sectors through the reduction of barriers to entry, for example, by issuing national‐level only trucking permits, could help reduce transport and logistics costs and stimulate quality upgrading in the sector, thus reducing the economic costs of distance.

Second, information frictions also play a role in spatial price dispersion, after controlling for distance. Indeed, estimates suggest that in wholesale markets, information frictions explain more of the departures from the law of one price than the transport costs related variables, with a 1‐percentage point increase in cellular penetration being associated with up to an 11‐percentage point reduction in

> 23 An example of de facto requirements that arbitrarily increase travel times is cited in World Bank (2016). The report argues that local trade unions may, for example, require cargo owners to have their goods transited to a local warehouse before dispatch to the destination market, reducing the efficiency of the domestic supply chain. An example of de jure requirements that reduce logistics efficiency is the excess burden of obtaining a national or multi‐state trucking permit, compared to a single state one.

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