AI 中文总结
该研究将并行估计框架与前门调整结合，分析东京165次市议会选举数据，发现候选集规模通过竞选手册页数渠道影响投票，新增一名候选人可使首页对获胜概率的效应提高0.322个百分点。
AI 中文摘要
我们研究处理分配随机但调节变量非随机时的因果调节问题。我们将并行估计框架与前门调整相结合，以识别平均中介处理调节效应。我们将该方法应用于1987-2023年东京的165次市议会选举，其中竞选手册的立场通过抽签分配，手册总页数由候选集规模和固定市政规则机械决定。新增一名候选人会通过页数渠道使首页对获胜概率的效应提高0.322个百分点，占其基线幅度的8.0%，而尾页效应未显著提高。
英文摘要
We study causal moderation when treatment assignment is randomized but the moderator is not. We combine the parallel estimation framework with front-door adjustment to identify an average mediated treatment moderation effect. We apply this approach to 165 municipal assembly elections in Tokyo (1987-2023), where pamphlet positions are assigned by lottery and total pamphlet pages are mechanically determined by candidate set size and fixed municipal rules. One additional candidate increases the front-page effect on winning probability by 0.322 percentage points through the page-count channel, 8.0% of its baseline magnitude, while the back-page effect does not increase significantly.
Comments27 pages, 7 figures, 6 tables. JEL Classification: C18, C21, D72, D83
