The Comparative Statics of Sorting
研究带货币转移的配对匹配模型中排序增强的一般理论，用正象限依赖偏序概括极端情况，证明排序随匹配协同性增加而增强，可用于推导经济学经典论文和新应用中的排序预测。
We create a general and tractable theory of increasing sorting in pairwise matching models with monetary transfers. The positive quadrant dependence partial order subsumes Becker (1973) as the extreme cases with most and least sorting and implies increasing regression coefficients. Our theory turns on synergy—the cross-partial difference or derivative of match production. This reflects basic economic forces: diminishing returns, technological convexity, insurance, and learning dynamics. We prove sorting increases if match synergy globally increases, and is cross-sectionally monotone or single crossing. We use our results to derive sorting predictions in major economics sorting papers and in new applications.