This paper presents three estimators for genetic distance based on the coancestry coefficient, θ, which measures the genetic divergence between populations due to drift. The estimators are derived from multilocus, multiallelic data and are compared through simulations. The weighted ratio estimator of θ, denoted as θ_W, performs better than the unweighted average or least squares estimator in simulations of monoecious populations. Jackknifing over loci provides satisfactory variance estimates for the distance values. In the drift model, where mutation is excluded, the weighted estimator of D (where D = -ln(1 - θ)) appears to be a better measure of genetic distance than other methods. The coancestry coefficient, θ, is the probability that two randomly chosen genes from the same locus in a population are identical by descent. It is a natural measure of genetic distance and increases monotonically with divergence time. For short-term evolution, θ is approximately linear with time, and D is approximately equal to t/(2N). The paper discusses various methods for estimating θ, including Cockerham's analysis of variance, and compares different estimators for θ and D. The weighted ratio estimator of θ is found to be unbiased and performs well in simulations. The paper also compares other genetic distance measures, such as those proposed by Balakrishnan and Sanghvi, CAVALLI-SFORZA and BODMER, and LATTER. These measures are evaluated under the pure drift model, and their performance is compared with the weighted estimator of D. The paper concludes that the weighted estimator of D is the most appropriate for the drift model, as it provides accurate estimates of genetic distance and is less affected by initial allele frequencies. The jackknife method is used to estimate the variance of the distance estimators, and it provides good estimates of variance for populations that have diverged over many generations. The paper also discusses the limitations of other distance measures, such as NEI's distance, which is affected by initial allele frequencies. The study highlights the importance of using appropriate estimators for genetic distance in short-term evolution and the role of the coancestry coefficient in this context.This paper presents three estimators for genetic distance based on the coancestry coefficient, θ, which measures the genetic divergence between populations due to drift. The estimators are derived from multilocus, multiallelic data and are compared through simulations. The weighted ratio estimator of θ, denoted as θ_W, performs better than the unweighted average or least squares estimator in simulations of monoecious populations. Jackknifing over loci provides satisfactory variance estimates for the distance values. In the drift model, where mutation is excluded, the weighted estimator of D (where D = -ln(1 - θ)) appears to be a better measure of genetic distance than other methods. The coancestry coefficient, θ, is the probability that two randomly chosen genes from the same locus in a population are identical by descent. It is a natural measure of genetic distance and increases monotonically with divergence time. For short-term evolution, θ is approximately linear with time, and D is approximately equal to t/(2N). The paper discusses various methods for estimating θ, including Cockerham's analysis of variance, and compares different estimators for θ and D. The weighted ratio estimator of θ is found to be unbiased and performs well in simulations. The paper also compares other genetic distance measures, such as those proposed by Balakrishnan and Sanghvi, CAVALLI-SFORZA and BODMER, and LATTER. These measures are evaluated under the pure drift model, and their performance is compared with the weighted estimator of D. The paper concludes that the weighted estimator of D is the most appropriate for the drift model, as it provides accurate estimates of genetic distance and is less affected by initial allele frequencies. The jackknife method is used to estimate the variance of the distance estimators, and it provides good estimates of variance for populations that have diverged over many generations. The paper also discusses the limitations of other distance measures, such as NEI's distance, which is affected by initial allele frequencies. The study highlights the importance of using appropriate estimators for genetic distance in short-term evolution and the role of the coancestry coefficient in this context.