Comparative is a need to integrate findings of various

Comparative
politics relies on breadth to generate variables and create typologies. The aim
of comparative research is to formulate rules and to apply them to similar
cases. Therefore, exploring multiple cases in a breadth study is imperative to
generalise and fulfill the requirements of the hypothesis. Hypotheses are key
in comparative politics, especially when considering the interaction of
different variables. Consequently, it is imperative that various results from
different studies are considered. Scientists must study, from alternative
perspectives, political systems, which should formulate and test similar
hypotheses. Wieviroka (1992:163) argues that to avoid starting again from
scratch, earlier findings have to be borne in mind. Therefore, when conducting
a study, there must be a basic knowledge of political systems as most political
scientists usually adopt the typical comparative politics methods; the method
of difference and the method of agreement. These make sure that variables
representing the differences and similarities can be identified to give the
study good foundations. For example, there are broad consensuses over
approaches used in comparative politics such as institutionalism, pluralism,
corporatism, behaviourism, cultural perspectives and policy analyses. This
emphasises that there is a need to integrate findings of various studies to
gain a better understanding of how institutions influence the individual’s
choice. Various approaches have aided comparative politics in its ability to
create a complex picture of political systems and the factors that contribute
to the structuring of the state. These breadth analyses then provide further
foundations for typologies and classifications. For example, Amorim Neto &
Cox’s “Electoral Institutions, Cleavage Structures, and the Number of Parties”
conducts a large-N study to analyse if there is a correlation (and if so, how
far it goes) between the different measures of electoral system permissiveness,
the number of effective parties and ethnic fragmentation. The data collected
was from 54 elections around the world, including both presidential and
parliamentary elections. From this, Neto and Cox were able to deduce that the
effective number of parties are dependent on the diversity of the state and the
types of electoral systems. The benefit therefore of conducting a large-N
analysis is that statistical controls can be used. Statistical control
(SC) refers to the ‘technique of separating out the effect of one particular
independent variable from the effects of the remaining variables on the
dependant variable in a multivariate analysis’ (Gujarati, 2003). Using SC can
aid political scientists in ruling out rival explanations for why outcomes are
produced. Within this, it is easier to identify ‘outliers’ and then make
generalisations as their theory is tested over a larger sample and in turn
becomes much more representative. One of the main problems with this type of
study is that it is often expensive and time consuming, as Collier (1993) notes
that there is a problem with “collecting adequate information in a sufficient amount of time”. However,
this is a necessity to gather evidence and draw comparisons, which is what
comparative politics is founded upon.