Research co-production model – full set of parameter estimates.

We implemented the estimation using STATA 13 including year fixed-effects and robust standard errors; see Eq (3) for the model specification. The dependent variable in each model is the research co-production Jij,t between institutions i and j in year t calculated for publications in the 21-year period 2000-2020. We incorporate the alignment with a 1-year lag, ⋅ , to account for inter-annual variation in research area profiles ; note that research area profiles are calculated using mono-university (denoted by M) publications of institution i, whereas Jij,t are calculated for co-produced publications. Below each point estimate is the associated p-value. See S3 Fig. for the corresponding descriptive statistics and covariance matrix. See Fig 5C for a plot of the interaction coefficients included in model (8) to identify the temporal trend associated with institutional homophily. See Fig 5D for a plot of the interaction coefficients generated by model (8) to identify the temporal trend associated with institutional prestige involving two premier universities (Premij = 2).本研究采用STATA 13完成所有估计工作，模型设置包含年份固定效应与稳健标准误；模型设定详见式(3)。各模型的因变量为2000-2020年（共21年）时段内，机构i与机构j在t年的学术合作产出$J_{i,j,t}$，该变量基于双方合作发表的论文计算得出。我们纳入滞后1期的匹配项，以控制研究领域分布的年度间波动；需注意，研究领域分布基于机构i的单机构发表论文（记为M）计算得到，而$J_{i,j,t}$则基于合作产出论文计算。各点估计值下方均标注了对应的p值。相关描述性统计量与协方差矩阵详见补充材料图S3。用于识别机构同质性相关时间趋势的模型(8)交互系数分布图，详见图5C。用于识别涉及两所顶尖高校（$Prem_{i,j}=2$）的院校声望相关时间趋势的模型(8)交互系数分布图，详见图5D。