This dissertation consists of three essays in the field of spatial econometrics. Incorpo- rating spatial interaction effects into the model can improve the explanatory power of econometric models. Additionally, employing spatial econometrics is an effective strategy for addressing the spatial dependence of variables, which could introduce endogeneity. In Chapter 1, the impact of P M2.5 on sleeplessness in Chinese cities is examined using novel Weibo data and spatial econometric models. Despite no direct effect of PM2.5 on sleeplessness, a significant negative impact is observed in adjacent cities during severe pollution in winter, indicating spatial spillover effects. Chapter 2 investigates the Real-Time Air Pollution Monitoring Policy’s influence on corporate responsibility in China, revealing spatial spillover effects of the policy. While no direct treatment effect of the policy on CSR or CER scores within treated cities is found, a significant indirect treatment effect of the policy on untreated neighboring cities is noted, possibly due to supply chain alterations. Chapter 3 investigates the impact of the minimum wage on employment in Chinese cities, while accounting for endogeneity arising from spatial heterogeneity, and spatial dependencies among variables. The findings indicate a notable positive direct effect and a considerable negative indirect effect of the minimum wage on employment rates.