This dissertation investigates the consequences of fractional dynamics for political modeling. Using Monte Carlo analyses, Chapters II and III investigate the threats to statistical inference posed by including fractionally integrated variables in bivariate and multivariate regressions. Fractional differencing is the most appropriate tool to guard against spurious regressions and other threats to inference. Using fractional differencing, multivariate models of British politics are developed in Chapter IV to compare competing theories regarding which subjective measure of economic evaluations best predicts support levels for the governing party; egocentric measures outperform sociotropic measures. The concept of fractional cointegration is discussed and the value of fractionally integrated error correction mechanisms are both discussed and demonstrated in models of Conservative party support. In Chapter V models of presidential approval in the United States are reconfigured in light of the possibilities of fractionally integrated variables. In both the British and American case accounting for the fractional character of all variables allows the development of more accurate multivariate models.

Central planners and citizens, conservatives and reformers, 19th-century liberal statisticians and today's advocates of sustainable development all draw on statistics for the elaboration and communication of political visions. Yet, this striking phenomenon has so far largely escaped the attention of political philosophers in the English-speaking world. As politics has come to be informed and shaped by statistics, there is a need to scrutinize omnipresent statistical accounts for their political vision. Taking as its political vision the idea of society as a fair system of co-operation, this thesis offers a series of essays towards a political philosophy of statistics. To this end, the thesis retrieves the statistical macro-scopic point of view in the vision of co-operation as spelled out by John Rawls and contrasts this uptake of statistics with the one in Martin Heidegger's phenomenology of everydayness. The goal is to make explicit the implicit role of statistics in the philosophical reflection of these thinkers. This thesis then argues for the place of statistics in a system of co-operation in terms of accountability institutions. It also engages the contemporary political issue of sustainable development, which has seen the rapid development and use of statistics. It argues that the Index for Sustainable Development is not a measure of sustainable development, but rather a debunking index. As such, it is a stepping stone for more systematic accounts, such as the eco-space proposal. For these proposals to make a positive contribution to sustainable development, they must be situated within a vision of large-scale political society.

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