The paper presents a spatial approach to the analysis of the phenomenon of contagion, i.e. the so-called? spillovers, in the analysis of the financial markets. The spatial spillover effects realized in the form of indirect impacts of a given explanatory variable in a specific spatial location on the explained variable in all other locations are discussed. In the context of identifying the relationships between Treasury bond yields in the world, these effects should be interpreted as information on the extent to which changes in the level of bond yields issued by countries from a given area are caused by a change in a specific explanatory variable in the i-th country. The dynamic spatial models for pooled time series and cross-sectional data (TSCS) together with dynamic spatial panel models as a tools of determining these effects were considered. The models of government bond yield issued by forty selected countries from different regions of the world in the period of 2008–2017 were estimated and verified. The yield to maturity (YTM) was used as the dependent variable in the models. Among the explanatory variables which were included in our models there are: the inflation rate, the level of integration of government bond markets measured by β convergence, the VIX index reflecting the anxiety in the global financial market, and two binary variables regarding positive and negative changes in the rating of bonds issued by the i-th country, respectively. Indirect effects have been determined in relation to the selected spatially lagged variable, namely the inflation rate measured in the neighboring regions.