The was superior nature of presidential rule.

The idea that brings both thelarge-N design and case studies together is the practice of small-N studies. Small-N analysis examines a small number of cases in depth, which are allselectively handpicked. One of the main strengths of these types of studies arethat they are “ specified, complex models that are sensitive to variations bytime and place.” (Coppedge, 1999). “ Perils of Presidentialism” (Linz, 1990) isan example of small-N analysis.

Linz considers the consequence thatpresidential and parliamentary government types have on states’ democraticability. Linz’s research was carried out through selected cases (countries)from Western Europe (e. g. Italy, Spain and France), Latin America (such asChile, Argentina and Brazil) and North America. His hypothesis was based onproving if the nature of parliamentary rule was superior nature of presidentialrule. Small-N analysis enabled him to intentionally select case studies thathad alike characteristics to aide specific hypothesis testing. TheComparative Method (Collier, 1993) argues that small-N designs such asLinz’s enable the intensive analysis of a few cases with less energyexpenditure, financial resources and time. This means that analysis can be morerigorous in small-N studies, unlike statistical analysis in large-N studies.

Small-Nstudies also save time and resources, as collecting mass data can be extremelydifficult due to the size of the study. A benefit of utilising small-N insteadof large-N is that the studies can be operationalised at a lower level andconsequently the results are likely to be valid as the concepts chosen arebeing accurately measured. Small-N scientists are critical of the case studymethod as they believe that patterns must come from theory or observation whichis “ validated by intimate knowledge of the detail, nuance, and history of thesmall number of cases” (Paul et al.

2013). However, once the number of casesexpands, analysts can no longer “ hold all the cases in their head” and theinformation is too large to be compared holistically and qualitatively withoutexpecting a margin of error. Lijphart argues that this is because small-Nanalyses can focus on “ comparable cases” that are matched on many variablesthat are not central to the study. This means that they can effectively’control’ these variables. They can then choose countries, which differ interms of key variables that are the focus of the study, which allows a morereliable assessment of their influence. Yet, small-N analysis has variousweaknesses, which make it inferior to its large-N counterpart. Goggin (1986)comments on the nature of small-N analysis, as there are many variables yet asmall number of cases.

Therefore, it is more efficient to study more countriesand consequently conduct a large-N study instead. Kerlinger (1973) argues thatthe ideal research design must answer the research question, introduce theelement of control for extraneous independent variables and permit theinvestigator to generalize from their findings. Small-N studies are incapableof fulfilling these criteria. However, Prezworski et.

al in Democracy and Development (2000) studies 150 countries over 40 years toachieve a similar objective to Linz. Conversely, unlike Linz’s analysis, thisstudy complies with Kerlinger’s ideal research design as it allowsgeneralisation due to the increased scale of the project and randomisation of casestudies which conveys the superiority of large-N analysis.