t's implementation. If the UNE rate is lower than construction cost per line, CLECs would obviously want to lease lines rather than build them. On the other hand, if the UNE rate exceeds construction costs, CLECs would be motivated to build their own facilities, all other things being equal. To determine the effect of UNE rates on the use of unbundled loops, I and two colleagues undertook an econometric analysis of the choice of net- work design in 2000-01 and 2002. 19 First, we estimated the direct elastic- ity of substitution between UNEs and the CLECs' own loops from a cross section of state data: log(F)-log(U)i=a+b*log(UPrice;)+ d*log(FCost;) + Ui, where i is a geographic (state) index, F = CLEC-facilities-based lines, U = UNE lines, Uprice = statewide average UNE loop rate, Fcost = statewide average of FCC ARMIS data on embedded costs per line or FCC estimates from the Hybrid Cost Proxy Model (HCPM), and U = random distur- bance term. We expected that the absolute value of the estimate of b would not be significantly different from d. If the estimates passed this empirical test, we could then estimate equation (2), to obtain an estimate of the direct elasticity of substitution, b: log(Fi) - log(Ui) = b*[log(UPrice;) - log(FCost:)] + li. For the monthly UNE price per line, we used the average UNE loop rate as determined in proceedings supervised by each state's Public Utili- ties Commission (PUC) and published by the National Regulatory Research Institute (NRRI). 20 To estimate the cost of building loops, we used two alternatives: the embedded cost per loop from the FCC's ARMIS data and the FCC's HCPM model. We calculated the number of CLEC facilities-based lines and the number of UNE lines from two sources as well: the E911 database and the FCC's Local Competition Local Competition under the 1996 Act reports. Thus our model focuses on a CLEC's incentive to lease UNE loops in relation to investing in its own facilities-based network, a decision that most CLECs face.21 In a least-squares regression estimate of