highly significant. We could not use nominal or real effective exchange rates (either from IFS or WDI sources) due to missing observations for four of the sample countries considered in the second analysis; (ii) To capture the potential effects of macroeconomic policy on manufacturing production and export, we consider inflation and real interest rates. _Inflation_ was considered due to its potential negative effect associated with economic imbalances and distortions, as well as being a symptom of economic mismanagement. _Real interest rates_ were incorporated as a proxy for average productivity of capital, expecting that lower interest rates would boost investments, increase productive capacity, and exports. Neither inflation nor real interest rates entered significantly in the regressions.

(iii) As a proxy of industry concentration, we have used _economic density_ (US$/sq m), which is highly significant in all the regressions. Real GDP per capita, as a proxy for the level of development and income level of the country was tried but was mostly insignificant.

(iv) _Infrastructure_ has important consequences for an economy‟s export performance by lowering the transaction costs, facilitating diversification and giving rise to forces for agglomeration<sup>19</sup> . To evaluate the effect of infrastructure on exports, we considered a number of variables, including rail carrying capacity (tones), roads paved (km), electricity generated (gigawatts) and telephone mainlines per 1,000 people. Due to data constraints, telephone mainlines per 1,000 people was used in our analysis; however, it did not enter significantly.

(v) For the sectoral analysis, we have incorporated a variable to capture sector specific human capital contributions. Roberts and Tybout (1997b) find that the average wage is a better proxy for human capital than the skill ratio because it reflects variations in the quality of employees across firms. So we use the sectoral average wage, computed as total remuneration divided by total employment (data sourced from the UNIDO ISIC database). We expect this variable to affect positively export performance.

(vi) In this first analysis we have not accounted for the effects of trade liberalization as the tariff reductions related to the GATT membership affected all the considered manufacturing sectors. We use a proxy for trade liberalization in our second analysis, which we will discuss in the next section.

39. In addition, to test the sensitivity of the model to the selection of different deflators when adjusting the nominal automotive exports series, two sources have been used, which do not alter the results: (a) each country‟s export price index (2000=100) and (b) the US wholesale price index (2000=100), both obtained from the WDI.

40. We formulate specification (2) below by expanding specification (1) and incorporating dummies for each sector, year, and the interaction between the two, together with the vector of other sector-specific and time changing control variables. The dummies aim to control for the effect of exogenous shocks that affect exports in all sectors equally ( year fixed effects), and also for those sector specific

> 19 Elbadawi, 1999; Collier, 2002; Redding and Venables, 2004; Mayer, 2003

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