Following the price shocks in 2007-08, governments within many African economies started to intervene more regularly in agricultural markets. It has been argued that these government actions, which include discretionary trade controls, potentially contribute to exacerbating the food crisis (Tschirley and Jayne, 2010). This concern has prompted many researchers to examine the impact of trade controls on the efficiency and the degree of price transmission between markets within countries and across neighboring economies in Africa using a variety of statistical approaches. Davids, Meyer, and Westhoff (2017) use an autoregressive distributed lag model (ARDL) to look at price transmission between maize markets in Zambia, Zimbabwe, and South Africa. They find that under open trade policies, efficient price transmission occurs between the Zambia and Zimbabwe markets. However, this relationship breaks down during the period when Zambian export bans were in place. Ihle, von Cramon-Taubadel and Zorya (2009) arrive at similar conclusions using a Markov-switching vector autoregressive (MS-VAR) model to examine the maize price transmission between Kenya and Tanzania. The MS-VAR approach allows for a data-driven approach to detect the presence of different regimes in the price movements. Their MS-VAR model suggests the existence of two regimes defined by the high and low levels of the mean price margins between Kenya and Tanzania. They find that the occurrence of many of the high-margin episodes corresponds well with periods of export bans in Tanzania.

The role of informal maize trade across national borders in influencing the outcomes of export bans is further explored in Porteous (2017). This study uses a fixed-effects approach to estimate the impact of export bans on the price gaps between pairs of cross-border markets across five countries. The results indicate that the export bans have no significant effect on the price gaps suggesting that export controls are imperfectly enforced, and informal trade is likely to grow when such policies are in place. However, the study also finds suggestive evidence that the bans lead to higher prices and increased volatility in the imposing country, leading to increased instability in the domestic market.

Specifically, in the case of Malawi, Edelman, and Baluch (2016), in a descriptive study, note that export bans tend to limit access to food and artificially raise the cost of food for consumers. They are also likely to divert food from markets where there is high demand and send mixed signals to farmers as they make planting decisions ( _ibid._ ). It was further reported that export bans also tend to misdirect agricultural investments and encourage hoarding resulting in distorting the markets. Simulation models examining the economy-wide effects of Malawi’s long-term maize export ban and oilseed export levy from 2012-2017 found that these policies benefited the urban non-poor in the short-run, while poor farmers’ incomes and maize consumption levels declined in the longer run. The oilseed export levy also failed to achieve its longrun objectives (Aragie, Pauw and Pernechele, 2018).

The overall evidence from both CGE based studies as well price transmission analysis seems to suggest that export controls may not often be the right policy response to stabilize domestic food markets in Africa. Unpredictability in the announcement of such policies and imperfect enforcement may result in inefficient market outcomes in the short-run. Results from model-based studies also indicate that households engaged in the agricultural sector are likely to experience welfare losses in the aggregate. However, previous work in this area within the SSA context has usually ignored the potential spillover effects of trade policies within neighboring countries. This study builds upon and adds to previous work in several ways by using price transmission analysis methods in conjunction with spatially disaggregated price data from market locations across Malawi as well as within the neighboring countries.

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