Kenya over the last century to show path dependence of economic activity and local increasing returns. Trade theory-based work looks at the impact of infrastructure on trade volumes, goods and labor markets, trade costs, and responsiveness to shocks (e.g., Michaels 2008, Feyrer 2009, Donaldson 2010, Burgess and Donaldson 2012, Atkin and Donaldson 2012, Allen and Atkin 2015). Donaldson (2010) exploits, in his extensive study on colonial Indian railways (1861-1930), the roll-out of the railroad network and finds, on the basis of a general equilibrium trade model, that railroads reduce trade costs, reduce price dispersion between regions, increase trade volumes and welfare, and decrease income volatility. Burgess and Donaldson (2012) use the same identification strategy and find that railroads in India made prices and income less responsive to shocks.

A different strand of the literature is directed toward the impact of infrastructure in contemporaneous developing countries and makes use of data with a shorter time dimension and a smaller space dimension, often micro-survey data (e.g., Yamauchi et al. 2011, Casaburi et al. 2013, Asher and Novosad <u>2016). Using (quality) improvements in road quality jointly with Indonesian</u> household panel and village census data (1995–2007), Yamauchi et al. (2011) claim that the increase on household income growth and non-agricultural labor supply due to improved connectivity supports complementarity between education and quality of local roads. Casaburi et al. <u>(2013) employs a</u> genuine experimental design in rural road rehabilitation in Sierra Leone to estimate the impact on transport costs and market prices and test alternative models of price formation. They find price reductions in rice and cassava, larger for cassava and for locations remote from urban centers, and smaller in markets located in production areas. Part of the research on developing countries particularly considers the impact of transport and trading infrastructure on transaction costs, trade margins, commodity prices, household income, welfare, and supply response (Minten and Kyle 1999, Jacoby <u>2000,</u> Jacoby and Minten <u>2008,</u> Goyal <u>2010,</u> Zant <u>2016). A key motivation for this research is the</u> impact of high transaction costs on low input, low productivity, and low growth agriculture, and thereby on welfare of rural households. Studying food prices in Zaire, both across regions and between products, Minten and Kyle (1999) show that transportation costs explain differences in food prices between producer regions and urban Kinshasa, and that road quality is the key determinant of transportation costs. Inspired by the difficulty of experimental designs in infrastructure, Jacoby (2000) and Jacoby and Minten (2008) take the reverse route and use the economic impact of transport costs on various economic variables and economic behavior (wages, value of agricultural land, household income, migration), in the absence of road infrastructure, in order to measure the potential gains of putting road infrastructure in place. Empirical application to Nepal data supports a substantial benefit to the poor which is, however, not large enough to reduce income equality (Jacoby 2000). Madagascar household data suggest large gains in income from improved infrastructure for remote households, but gains are small relative to the improved non-farm earning opportunities in town (Jacoby and Minten <u>2008). Focusing on marketing infrastructure in the soy market in Madhya Pradesh, Goyal (2010) finds</u> increased soybean prices, decreased price dispersion, and increased area under soy cultivation, due to the introduction of a direct marketing channel by a major private company. Zant (2016) also finds a positive supply response of tobacco growers in Malawi due to improved market access caused by the introduction of a new auction floor.

In this study, we provide empirical evidence of the impact of rail transport services on dispersion of market prices of agricultural commodities. The estimation strategy is similar to the one used in Aker (2010), and the topic is closely related to literature that explains the impact of trade costs on prices (e.g., Minten and Kyle 1999). The remainder of the paper is organized as follows. In section II, we briefly characterize the Malawi economy, present details on Malawi rail infrastructure and rail freight, and document the collapse of domestic rail freight since January 2003. In section III, we explain the methodology underlying the empirical estimation and the identification strategy. In section IV we present and discuss estimations, and in section V we give a summary and conclusion.

3