Suchergebnisse

Researched analysis, using the full range of conceptual & analytical tools developed by various disciplines, can be contrasted with quick analysis, a different approach. Quick analysis was developed in a basic course in analytical methods to give students a grasp of the essentials of analytical thinking. It involves thinking about a problem, decomposing it into components, simplifying by discarding nonessential factors, specifying elements with data sources or judgment, & rethinking all these steps on the basis of sensitivity consideration. The methods of quick analysis in approaching such problems are those appropriate to busy decisionmakers, thus introducing decision analysis & a decision-oriented perspective. A dynamically iterative approach is used, aiming to teach essentials rather than techniques, & to build up student confidence for real decision situations. Failure to convey these essentials makes analysis more sophisticated but may also render it meaningless. W. H. Stoddard.

The paper explores various measures of institutional quality in Russian regions, and compares those measures to each other. Such analysis leads to the conclusion that Russian regional institutions are essentially multidimensional, and therefore comparisons of Russian regions in terms of their overall institutional quality could be problematic. New institutional indexes are derived from Russian enterprise surveys held under the BEEPS project of the European Bank of Reconstruction and Development. Such indexes yield a typology of Russian regions in terms of efficacy of regional administrations' control over economy and bureaucracy in their regions. Dynamics of regional institutional indexes is investigated against the backdrop of Russia-wide institutional trends.

Re-analyzing a study of Garrett & Mitchell ('Globalization, government spending & taxation in the OECD', European Journal of Political Research 39(2) (2001): 145 177), this article addresses four potential sources of problems in panel data analyses with a lagged dependent variable & period & unit dummies (the de facto Beck-Katz standard). These are: absorption of cross-sectional variance by unit dummies, absorption of time-series variance by the lagged dependent variable & period dummies, mis-specification of the lag structure, & neglect of parameter slope heterogeneity. Based on this discussion, we suggest substantial changes of the estimation approach & the estimated model. Employing our preferred methodological stance, we demonstrate that Garrett & Mitchell's findings are not robust. Instead, we show that partisan politics & socioeconomic factors such as aging & unemployment as expected by theorists have a strong impact on the time-series & cross-sectional variance in government spending. 4 Tables, 2 Figures, 1 Appendix, 23 References. Adapted from the source document.

For several years, the social sciences experience an almost Copernican revolution: range and scope of social science data are increasing rapidly, research on computer-based methods for classification and analysis of existing large data volumes experiencing an interdisciplinary boom. The very much lamented lack of information about individual behavior or institutions has become - at least in part - abundantly wrong (King 2011). For this, a bit simplistic, but impressive example: The data collected as part of the German Election Study and the ALLBUS since 1949 can be easily put together on a gigabyte of storage. About the social media platform Twitter, which increasingly becoming the focus of scientific interest, will, over the rule of thumb, about four gigabytes of data generate - per hour. This illustrates not necessarily the rapid increase in political science relevant data - about the content some arbitrarily collated Tweet Collection for political science research let themselves worthy of debate - but probably the enormous potential of new data sources, as well as the extraordinary technical challenges are faced with the researchers, might study the social behavior on the World Wide Web. Adapted from the source document.

Interpersonal phenomena such as attachment, conflict, person perception, helping, and influence have traditionally been studied by examining individuals in isolation, which falls short of capturing their truly interpersonal nature. This book offers state-of-the-art solutions to this age-old problem by presenting methodological and data-analytic approaches useful in investigating processes that take place among dyads: couples, coworkers, or parent-child, teacher-student, or doctor-patient pairs, to name just a few. Rich examples from psychology and across the behavioral and social sciences help

In recent years, large sets of national surveys with shared content have increasingly been used for cross-national opinion research. But scholars have not yet settled on the most flexible and efficient models for utilizing such data. We present a two-step strategy for such analysis that takes advantage of the fact that in such datasets each "cluster" (i.e., country sample) is large enough to sustain separate analysis of its internal variances and covariances. We illustrate the method by examining a puzzle of comparative electoral behavior—why does turnout decline rather than increase with the number of parties competing in an election (Blais and Dobryzynska 1998, for example)? This discussion demonstrates the ease with which a two-step strategy incorporates confounding variables operating at different levels of analysis. Technical appendices demonstrate that the two-step strategy does not lose efficiency of estimation as compared with a pooling strategy.