1986, Goodwin and Piggott, 2001, Rashid, 2004 and Van Campenhout, 2007). For Indonesia, Varela et al (2012), and for Bangladesh, Goletti et al (1995) test the role of transport costs, and distance respectively, explaining a significant portion of the variation of market integration and price differences.

Transport costs, integration and welfare. Going one step further, and assuming a direct link between transport costs and market integration, Donaldson (2010) estimates the welfare benefits of improved connectivity (associated with increased integration). Using colonial data on India, he finds that the benefits of building the railroads in India were threefold. First, because of better infrastructure, price gaps between regions have decreased. Second, trade has been promoted (nationally and internationally). Third, real income has increased because of lower prices. In a recent contribution Allen and Atkin (2016), using data on Indian highways, show that transport improvements result in farmers being able to allocate their land to less volatile crops, avoiding the increased volatility in earnings that they would have otherwise faced, thus amplifying the gains from trade.

Information and the digital dividend. Jensen (2007) argues that, when information is limited or costly, agents are unable to engage in arbitrage, and excess price dispersion arises. The author uses micro‐ level survey data on prices obtained by south Indian fishermen, combined with data on the fishermen and wholesalers’ adoption of mobile phone technologies. He finds that mobile phone adoption is associated with the elimination of waste and near‐perfect adherence to the law of one price. As a result, both consumer and producer welfare increased.

Nominal rigidities. Crucini et al (2010) look at the role of price stickiness in explaining persistent deviations of the law of one price. To that effect, they build a model with nominal rigidities and transport costs that explains how pricing to market, transport costs and price stickiness lead to failures of the law of one price. In their model, deviation from the law of one price is negatively related with price stickiness and positively related with transport costs. This happens because productivity shocks are not transmitted in the case of full price stickiness. Similarly, Hickey & Jacks (2011) look at nominal rigidities in Canada. They find that price dispersion tends to be higher whenever inflation is persistent because it puts pressure on menu costs and stimulates lower price stickiness.

Government interventions. Ismet et al (1998) focus on the effects of government intervention on rice market integration in Indonesia. They find that procurement policies by Bulog, Indonesia’s rice policy agency contributed to market integration. For the case of India, Sekhar (2012) examines spatial integration for selected commodity markets in India, revealing an interesting pattern: commodity markets that do not face restrictions to trade, either inter‐state or inter‐region (gram and to a lower extent edible oils), appear well‐integrated, while those in which inter‐state movement restrictions prevailed (such as rice) do not show integration at a national level.

# _Our approach_

We focus on six factors that may explain departures from long run market integration and its heterogeneous patterns across commodities and states. These include transport costs; price adjustment dynamics (measured as the time it takes for shocks to be corrected), information frictions, the regulatory framework, commodity specific characteristics, state level production and regional consumption preferences. These factors have been identified in the empirical literature as potential drivers of market integration and price transmission as outlined in the previous subsection.

We take the case of wheat flour to illustrate bivariate correlations for all our explanatory variables. We choose wheat flour because it is a commodity that is present in both the wholesale (as wheat) and the retail database (as wheat flour). By fixing one commodity, we are able to visualize the data and give a first grasp of the correlation of each of the covariates and the dependent variable.

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