duction of bound tariffs by the WTO meant that the Ghanaian government could not raise applied tariffs above the established ceiling. Hence, even though the government did adjust tariffs slightly upwards – as it can be seen in fig. 1 – tariff rates generally stayed below the 1991 levels on average for the remainder of the period under consideration.

Most importantly, the introduction of bound tariffs meant that whichever adjustments the government made, tariff rates could not exceed the upper limit. WTO accession, therefore, reduced uncertainty about Ghana’s trade policy and strengthened the commitment of Ghana toward trade liberalization. Handley (2014) presents a model and empirical evidence showing that the binding tariffs commitment introduced by the WTO reduced trade policy uncertainty. This can be observed in fig. 1, where there were fewer variations in tariff rates after 1996 compared with the pre-WTO period and tariff rates appear to converge to similar levels across sectors. Additionally, tariffs rate in the post-WTO era generally stayed below 25 percent demonstrating the effect of the bound tariffs absent from the pre-WTO era of trade liberalizations. Therefore, the two phases of Ghana’s trade liberalization policy – tariff reductions and restructuring enforced under the SAP, followed by the WTO entry that reduced trade policy uncertainty – will be taking into account in evaluating the impact of trade policy on market power in Section 5.

# **2.2 Data**

As part of the SAP, the World Bank launched the Regional Project on Enterprise Development (RPED) with the aim of collecting manufacturing firm-level survey data in many African countries, including Ghana. The dataset was jointly collected by the Centre for the Study of African Economies (CSAE) at the University of Oxford, the University of Ghana, and the Ghana Statistical Service between 1992 and 2003. The first survey involved an original sample of 200 firms randomly drawn from the 1987 Ghana manufacturing census. The sampled firms were broadly representative of the entire national economy across size distribution and the four major industries: food processing, textiles and garments, wood and furniture, and metals and machinery.

To maintain the representative nature of the sample, new firms were resampled from the census database to enter the survey in subsequent waves in order to make up for firms that dropped out of the survey. The final dataset used in this article is an unbalanced panel, containing 262 individual firms with 1,955 total observations. The primary dataset contains information on output and inputs necessary to estimate production function, as well as other firm-level characteristics. In addition to the primary dataset, S ̈oderbom and Teal (2004) computed physical capital from the investment flows information and firmspecific output and input prices, which were used to deflate monetary values. Both the primary data, the derived physical capital, and firm-specific prices data were made freely available by CSAE at the University of Oxford.

The long time span of the dataset, which includes the two episodes of trade liberalization (1991 and 1995), represents an advantage for this study. On the other hand, a common 6