the Syrian export basket has indeed become less concentrated although Syria does not appear to have diversified into higher value production. In this section, we seek to better understand why diversification has occurred in some sectors, while not in others. More specifically, we try to offer insight into the the question of how sectoral characteristics and government policy aimed at trade liberalization may affect the process of export diversification in the economy.

The analysis presents inference from simple linear regressions of export diversification measures on trade policy and outcome variables. It is important to notice that, in the absence of an obvious instrument, we are unable to fully control for potential endogeneity in the relationships examined. Indeed, as mentioned in previous sections, one may also be reasonably skeptical of the claim that trade liberalization as a political decision was entirely independent of structural change in the Syrian economy; the long term decline of the oil sector could also speak in favor of this argument. A word of caution is therefore in order when interpreting the results. Our preference is to interpret the estimated coefficients as partial (conditional) correlations, rather than causal relationships.

The regressions results are reported in Table 8.<sup>20</sup> We focus on diversification in a given 2-digit HS sector, using the corresponding 6-digit lines. We construct the dependent variable in the regressions as the percentage change, between 2002 and 2007, of one of three diversification measures: (a) the number of 6-digit products exported; (b) the Herfindahl index based on 6-digit lines; and (c) the share of the largest 6-digit line between 2002 and 2007.<sup>21</sup> These measures are analogous to change in product, Herfindahl, and product share indices commonly employed in cross-country analyses of export diversification.

It is important to note that a factor associated positively with export diversification would be expected to carry a positive sign in regressions with the first measure (specifi– – cations _D1 D3_ ) and a negative sign in the latter two measures (specifications _D4 D9_ ), given the nature of the indicators used as a dependent variable in the regressions. We include as controls the (natural logarithm) of the initial (year 2002) values of sector-specific density as given by (10), RCA as given by (5), PRODY as given by (6), trade volume, and the tariff rate. While we also experimented with taking changes in the variables as regressors, we consider the use of the initial values of each respective variable as a more accurate representation of the sector’s diversification potential throughout the period. This approach also has the added advantage of alleviating endogeneity concerns. That

> 20We also considered a cruder approach, with Probit regressions where the dependent variable was whether a sector became more diversified or not. The results obtained were qualitatively similar, and are available upon request.

> 21Utilizing the 6-digit HS to calculate diversification indicators at the 2-digit HS level allows us to maximize the level of disaggregation while still recovering sensible indicators at the aggregated level, since the number of exported 6-digit lines in any given 4-digit line is generally very small.

23