~~~~~~~~- 11 -

-

of auctions data to draw some empirical regulaities: (i) to account for the behavior of the auction rate _L terwm_ of the impact of various fudamentls, as well as policy intvention, policy credibility and uncruinty; (ii) to atempt to link particular data characteristics to different outcomes, regarding the auction objectives (e.g. exchange rate unification); and (iii) to inform a futher and more rigorous analysis on testing theoretical propositions firom auction theory (Aron and Elbadawi, 1994b). The analysis of this section is centered around three broad methodological issues. First, basic summry statistics for each country will be analyzed for the overall auction period as well as for the episodes identified in section 2 above. Second, the distributional properties of the auction variables will be studied, focusing on the extent to which innovations from these variables exhibit departures from nonnormality. Third, the section condudes with a discussion of stationarity issue of individual auction or data series.

# 3.1 Standard Descriptive Statistics.

Table 2 provides basic summary statistics of auction data from Ghana, Nigeria, Uganda and Zmbia, on prices, price spreads, foreign exchange quani,ties1<sup>number of bids and bureaux or</sup> black/auction prema. The results broadly corroborate the analysis of the typology of auction designs and policies in the four countries. A summary of the evidence follows.

Auction prices (auction rate, maxmum and minimum bids) have been fairly stable in Ghana and Uganda, while in contrast they have been rather volatile in Nigeria and Zambia. For example, the range of auction rates (in terms of domestic currency per US$) was 970-1042 in Uganda and 317395 in Ghana (in the second auction regime),'3 compared to a range of _3-5_ for Nigeria and 5-25 for Zambia (also see Figure 1). Stability of auction prices has improved around a depreciating tend in Ghana as the auction progressed from a retail to a wholesale, auction while volatiit increased in Zambia with the change from competitive to Dutch pricing. In Nigeria, however, auction rae volatiity has declined, pehaps due to the stabilizig effect of the steady foreign exchange supply. The average max-min bid spread for example declined in Ghana and Nigeria, in contrast to Zambia. Except for Nigeria, for which the foreign exchange supply has been between US$50120 million, foreign exchange supplies have been rather volatilel<sup>4</sup> ranging from minima of USS (million) 2.60, 0.33 and 0.85, to ma xima of USS (million) 20.80, 3.48 and 18.48, in Zambia, Uganda and Ghana, rspectively. in all of the four countries foreign exchange supply has been almost always less than demand, but the evolution of this ratio over time has been yet another dcractrstc of the foreign exchange auction seting Ghana and Ugmada apart from Nigeria and Zambia. The supply demand ratio in Ghana increased from an average of 0.85 during the retail auction to an average of 0.87 during the wholesale, while the ratio remained quite high at an average rate of 090 in Uganda. On the other 13 In fact the auction rate was quite volaLi in Ghan during the fist rtail auction. where the maximum sct was 314.0O relave to a minimum of only 128.00.

4"The level non-sftionarisy of the variable involved, especially the aucion prics. imis options for the use of standard devation or coefficient of varanon as measues of volatilty. For te kvel vanbles in Tabk 2. the volatiliy measure _i-s_ the diflfrenee betwen. the aveage minimum ad _mamum_ viabes.