Types and levels of comparative analysis in political science презентация

Types and levels of comparative analysis in political science

Plan Types of comparative analysis: "case-study" comparison, regional comparison, global comparison. Comparison of the most similar systems (Most Similar Systems Design, MSSD). Comparison of the most different systems (Most Different Systems Design, MDSD). Levels of variables in comparative political science: aggregative, behavioral, role or socio-structural, cultural-structural. 

Case Study A case study may be understood as the intensive study of a single case for the purpose of understanding a larger class of cases (a population). Case study research may incorporate several cases. However, at a certain point it will no longer be possible to investigate those cases intensively. At the point where the emphasis of a study shifts from the individual case to a sample of cases we shall say that a study is cross‐case.

Case Study

Regional Comparison Area Studies Cross-Regional Comparisons

Global Comparison Freedom House

Comparing Many Cases (large-n comparisons) Comparison of many countries, usually based on statistical analyses of strictly comparable evidence about them Can be used to: develop or test broad generalisations across a wide variety of different conditions; identify unexpected or deviant cases that are exceptions to the general rule; Min for a large-n study: 20-30 countries

Comparing Many Cases (large-n comparisons) Information about countries must be both quantified and standardized; Large-n comparisons are often called statistical comparisons because information is analysed with statistical techniques; Large-n comparisons are best carried out on large, standardised data-sets.

Comparing Few Cases (small-n comparisons) Comparison of a few countries, usually based on systematic, in-depth analysis and detailed knowledge of them Allows to understand the complexity of relations Average number of countries: 5-6

Comparing Few Cases (small-n comparisons) Small-n studies can include qualitative evidence and methods; The small-n approach can be characterised as heuristic; Small-n studies can handle a mass of country-specific information of a qualitative nature without any need to standardise

Quotes of the great The simplest and most obvious modes of singling out from among the circumstances which precede or follow a phenomenon, those with which it is really connected by an invariable law, are two in number. One is, by comparing together different instances in which the phenomenon occurs. The other is by comparing instances in which the phenomenon does occur, with instances in other respects similar in which it does not. These two methods may be respectively denominated, the Method of Agreement, and the Method of Difference. John Stuart Mill. A System of Logic.

Method of Agreement If a phenomenon occurs in two or more situations then the explanation for the phenomenon must lie in the common features of those situations.

Method of Difference If two or more situations are similar, but the phenomenon exists in only one of them, its cause must be related to the different features of its situation

Most Similar Systems Design (MSSD) Deals with too few cases to allow the use of statistics (should be at least 2 cases) Can manipulate experimental variables only indirectly through the careful selection/sampling of cases The number of common characteristics sought is as few as possible Problem of “many variables, small N’s” (small-n/large-V problem)

With each additional explanatory variable (V) the number of cases (n) required for comparisons grows exponentially. Therefore, only a few explanatory variables are often too many for the relatively small number of cases available, in which case an empirical test is not possible.

Most Different Systems Design (MDSD) Belongs to the category of statistical analysis Falsification as a goal Searches for independent variables within each system which are related in an identical way to the dependent variable in all systems

Levels of variables in comparative political science Aggregative Behavioral Role or socio-structural (so-called "background") Cultural-structural

Role or socio-structural (so-called "background") variables Social structural variables claim explanatory power for the physical things people do to each other

Cultural-structural variables Cultural structural variables claim explanatory power for the psychical things (thoughts and feelings) that people communicate to each other. Consensus (accompanying functionalism), complementarity (accompanying exchange), and dissensus (accompanying conflict).