resumed in May 2005. However, in the course of time the lack of railway services will lead to adjustments like the use of alternative modes of transport, increased local cultivation of food, and shifts in consumption to local substitutes. The speed of adjustment will depend on the availability of cheap alternative modes of transport, supply response of local production, and the resilience of demand to shift to other food. These adjustments are likely to have taken place as domestic trade did not recover after rail transport operations were resumed (see figure 2 and appendix figures A2 and A3). The CEAR operational strategy favoring international freight may also play a role.

On the basis of data on passenger and freight transport by rail we have assumed in the estimations that the period in which the railway is effectively not operational is at least two years and at most three years. The minimum of two years is further motivated by the limited availability of price data around 2003 (see appendix, figure A2). The maximum of three years is motivated by the fading out of the impact (see estimation section) and is determined empirically, using a grid procedure (see supplemental appendix).

# _Selecting Maximum Trading Distance and Sample Period_

In the estimations we first employ a basic specification that is uniform across crops with respect to maximum trading distance (100 km), sample period (48 months before and 36 months after collapse), and cutoff distance to rail (20 km). All estimations include season-market dummies, a time trend for each market, month dummies, and market-pair dummies. Higher order lags of the dependent variable are included if statistically significant at acceptable levels of accuracy. This strategy made us include a number of lagged dependent variables, which varied by crop. In all estimations the coefficients of lagged dependent variables are positive, decreasing in size with the order of the lag, and statistically significant. Estimations with a specification that is uniform across crops are fine for maize but are not convincing for other crops (see supplemental appendix). We need to relax to assumption of a uniform maximum trading distance and sample period/period before and after bridge collapse to allow for heterogeneity between crops. We determine appropriate values of the maximum trading distance and the relevant period before and after the date of the collapse empirically, using a simple grid procedure: we estimate with a maximum trading distance varying from 70 km to 300 km (with a 10 km step), and with 24 to 48 months before and 24 to 36 months after January 2003. We use this procedure in order to find, simultaneously, the appropriate maximum trading distance and relevant period but also to assess the robustness of the estimations. Selected output of this exercise is reported in the supplemental appendix.

On the basis of the tables and the underlying estimations reported in the supplemental appendix, we observe for all four commodities sets of estimations with statistically significant ATEs with the required negative sign around a specific combination of maximum trading distance and sample period. The regularity of these estimation outcomes—both across commodities and for each individual commodity across combinations—offers comfort in and credibility of the estimations. For all commodities we see impacts disintegrate if the period without railway services is extended to the year 2006 (not shown, available from the author on request): apparently the period effectively without railway services (i.e., the period with effectively higher dispersion of agricultural market prices) is limited to the years 2003, 2004, and 2005, which is consistent with the fact that railway services resumed operations in May 2005. In fact, this motivated us to include estimations that exactly matched this period (January 2003 to April 2005), which further improved estimations in the case of beans, groundnuts, and, especially, maize. Also, with a maximum trading distance of 70 km or less, and with only two full years of observations before and after the bridge collapse (January 2003), the estimations tend to generate spurious outcomes. Next, the impact in the case of rice becomes significant with a maximum trading distance of 140–180 km and for groundnuts with a maximum trading distance of 200–300 km, opposed to around 100 km for maize and beans. The larger trading distance is possibly the result of the uneven spread of rice cultivation compared to the other commodities. Also good storability (of rice and groundnuts) will make trade over longer distances easier.

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