@article{Magrini_2019, title={Distributed-lag Linear Structural Equation Models in R: the dlsem Package}, volume={48}, url={https://ajs.or.at/index.php/ajs/article/view/777}, DOI={10.17713/ajs.v48i2.777}, abstractNote={<p>In this paper, an extension of linear Markovian structural causal models is introduced,<br>called distributed-lag linear structural equation models (DLSEMs),<br>where each factor of the joint probability distribution is a<br>distributed-lag linear regression with constrained lag shapes.<br>DLSEMs account for temporal delays in the dependence relationships<br>among the variables and allow to assess dynamic causal effects.<br>As such, they represent a suitable methodology to investigate the effect<br>of an external impulse on a multidimensional system through time.<br>In this paper, we present the dlsem package for R<br>implementing inference functionalities for DLSEMs.<br>The use of the package is illustrated through an example on simulated data<br>and a real-world application aiming at assessing the impact of agricultural<br>research expenditure on multiple dimensions in Europe.</p>}, number={2}, journal={Austrian Journal of Statistics}, author={Magrini, Alessandro}, year={2019}, month={Jan.}, pages={14–42} }