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Wireless links are often unreliable and prone to transmission error, particularly when network users are mobile. These can degrade the performance in wireless networks, particularly for applications with tight quality-of-service requirements. A common remedy to this problem is channel coding. However, this per-link solution can compromise the link data rate, leading to an undesired end-to-end performance. In this paper, we show that this shortcoming can be mitigated if the end-to-end transmission rates and channel code rates are properly selected over multiple routing paths. We formulate a joint channel coding and end-to-end data rate allocation problem in multipath wireless networks with max-min fairness as the objective function. Our goal is to maximize the minimum throughput available among the network users. To cope with the fast and frequent changes in dynamic environments that are typical for vehicular networks, we address both adaptive and nonadaptive channel coding scenarios. Unlike similar formulations in single-path routing networks, in the multipath routing case, we face an optimization problem that is nonconvex and usually difficult to solve. We tackle the nonconvexity by using function approximation and iterative techniques from signomial programming. Simulation results confirm that by using channel coding jointly with multipath routing, we can significantly improve the end-to-end network performance compared with the case when only one of them is used in the network. Nonadaptive channel coding is also shown to achieve a high degree of optimality with much less complexity.