variable strategy, however clever, has dispelled doubts about reverse causation or omittedvariable bias, both likely to be present at the level of aggregation at which these studies are cast. Impact evaluations, for all their own limitations, are less vulnerable to these identification issues, because they rely, for identification, on outcome differences between treatment and control groups _in the same context_ , instead of variations in policy choices or aid flows across countries.

# **3.1 Evaluating aid for trade**

The literature on the impact of AfT is fairly limited, in part because AfT projects are not always distinguishable from other aid projects. As in the rest of the aid effectiveness literature, the results are ambiguous (Rajan and Subramanian, 2008). Regarding the cross-country allocation of AfT, Gamberoni and Newfarmer (2009) find that, after controlling for absorption capacity (related, for example, to governance), more AfT is directed towards countries with a higher demand for AFT as measured by indicators of ―underperformance‖ in trade.<sup>8</sup> On impact, one strand of the literature explores whether AfT positively affects exports from the donor country to the recipient country given that, up to the early 1990s, over half of all bilateral aid was at least partially tied to donor exports. Using a gravity equation, Wagner (2003) shows that this form of trade was indeed boosted; but Osei, Morrissey, and Lloyd (2004), using a gravity equation in first differences for a panel of four European donors and 26 African recipients, found an unstable and insignificant impact of aid on exports from donor to recipient. Recently, Nelson and Juhasz Silva (2008) use a more conventional gravity equation including bilateral aid flows as a regressor (instrumented by their one-year lagged value), and find a significant although small impact on trade flows from donor to recipient.

From a development perspective, only a few of the recent studies focus on the more relevant question of whether aid raises the export capacity of recipient countries. Cali and te Velde (2011) regress trading costs and the value of exports on lagged AfT disbursements and control variables, using data from the OECD's Creditor Reporting System that separately identifies aid to trade facilitation and infrastructure from aid to productive capacity.<sup>9</sup> Using a large panel of developing countries, the authors address the possibility of endogeneity and measurement errors in AfT flows by instrumenting those with the Freedom House’s index of civil liberties. The message that emerges across their various specifications is that aid to trade facilitation and infrastructure seems to have a significant effect in reducing trade costs and in increasing export values, while

> 8 Underperformance in trade is captured by multiple indicators. Countries that underperform in trade can be those in the lower two quintiles of performance measured along five dimensions: (a) those experiencing relatively slow growth of exports of goods and services, (b) those losing global market share, (c) those suffering deterioration in competitiveness in existing markets, (d) those exporting slow-growing products or to slow-growing markets, and/or (e) those over-reliant on only a few exports. Also, countries that underperform in trade are those that under-trade with bilateral partners, controlling for market size and distance, those with low levels scores on the World Bank logistics performance index for transport or for customs, and on an indicator of peak tariffs.

> 9 Trading costs are measured by the trading across borders indicators of the Doing Business database.

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