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Deflections are commonly measured in the static structural system identification of structures. Comparatively less attention has been paid to the possibility of measuring rotations for structural system identification purposes, despite the many advantages of using inclinometers, such as a high resolution and being reference free. Although some work using rotations can be found in the literature, this paper, for the very first time, proposes a statistical analysis that justifies the theoretical advantage of measuring rotations. The analytical expressions for the target parameters are obtained via static structural system identification using the constrained observability method first. Combined with the inverse distribution theory, the probability density function of the estimations of the target parameters can be obtained. Comparative studies on a simply supported bridge and a frame structure demonstrate the advantage of measuring rotations regarding the unbiasedness and the extent of variation in the estimations. To achieve robust parameter estimations, four strategies to use redundant rotations are proposed and compared. Numerical verifications on a bridge structure and a high-rise building have shown promising results., This work was partially funded by the Scientific Research Fund of the Institute of Engineering Mechanics, China Earthquake Administration (grant no. 2019 EEEVL0401), National Natural Science Foundation of China (grant nos. 51878484), Spanish Ministry of Economy and Competitiveness and the FEDER fund through the projects BIA2013-47290-R and BIA2017-86811-C2-1-R directed by José Turmo and BIA2017-86811-C2-2-R, and the Natural Science Foundation of Shenzhen (grant no. JCYJ20190806143618723). The authors are also indebted to the Secretaria d’Universitats i Recerca de la Generalitat de Catalunya for the funding provided through Agaur (2017 SGR 1481). Part of this work was carried out through a collaborative agreement between Tongji University (China) and the Technical University of Catalonia, UPC. This included an exchange of faculty financed by the Chinese government. The financial support from the Chinese High-End Foreign Experts program (GDW20143100115) is greatly appreciated. Funding for this research has been provided to Jun Lei by the Chinese Scholarship Council through its program No. 201506260116 and by the Spanish Ministry of Economy and Competitiveness through its program BES-2014-07022 for his PhD stays., Peer Reviewed