 equation (1), using the available data on CLEC lines, we found the coefficient of the FCost variable to be negative as expected, and the absolute values of these two regression coef- ficients in equation (1) were not significantly different. The resulting esti- mates of the direct elasticity of substitution in equation (2) are generally statistically significant and between 0.4 and 1.4, depending on the year and the source of the CLEC lines data. These estimates suggest that whole- sale UNE rates have a substantial effect on the incentive for entrants to invest in their own facilities. 23 The Determinants of the Level of CLEC Entry Given the short history of local competition, there is not a wealth of evidence on what influences local entry. Even the few empirical studies published on the subject shed little light on the determinants of successful entry because most of the local entrants examined were failures. In gen- eral, entry appears to correlate with market size and density, surely a rea- sonable result.24 Entrants have tended to target business customers more than residential customers for obvious reasons: regulated business rates are much higher than residential rates. Even if they are not using their own network facilities, entrants will be attracted to the larger, urban mar- kets because of the economies of density in marketing their services. Entry is also correlated with population or employment in the local market.25 Interestingly, many entrants avoid the largest markets because of the dif- ficulty in competing with the first movers in this arena, the CAPs. 26 Entrants fall into several types: some are national, others local or regional. Many of the latter are privately owned firms about which little public financial information is available. Some serve business customers exclusively, others both businesses and residences. Some target a particular group of small to medium businesses. Because entry conditions have been greatly eased by providing entrants access to incumbents' facilities, a major prob