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In this paper, I consider opportunities and limitations of modelling the political dynamics with the time-series instruments. Using the examples of the president Putin’s approval rating and readiness to join the collective actions with economic demands I demonstrate the analytical potential of autoregressive integrated moving average model (ARIMA), autoregressive distributed lag model (ADL), and error correction model (ECM). Modelling the political dynamics faces a string of analytical dilemmas. This paper aims at identifying the basic choices in application of the statistical instruments to dynamic processes and helping the other researchers to navigate through them. While it is hard to account in a single paper for all the developments in the discipline, which has been substantially advanced substantially and technically i the last three decades, this text also aims at stimulating the discussion on the opportunities and limitations when applied to Russian politics.

In this paper, I explore how Russians attribute the responsibility for handling the economic crisis among multiple political institutions. Previous research established the link between the crisis and electoral results for the ruling party and other regime players, but did not address the question of the responsibility burden's distribution between branches and levels of public authorities in Russia. Using the results of representative survey and a novel instrument - comparative responsibility attribution index, which allows to assess the intensity of responsibility and the ordering of the institutions simultaneously - I demonstrate that Russians singles out the president as a chief responsibly for handling the crisis. Moreover, there exists a tight consensus about his role and place among other institutions. The federal government, the Sate Duma, and the governors follow his lead with the ruling party and mayors judged as the least responsible. Using spectral decomposition, I also show that Russian voters when it comes to getting out of the crisis also distinguish between the federal and subnational authorities. Finally, the individual-level analysis reveals that gender, age, political preferences, and crisis impact, but its significance caries across target institutions. The study contributes to the growing scholarship on responsibility attribution under autocracies and the ways the voters navigate the institutional complexities of modern polities.