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Voting is an intriguing process that goes down to an individual decision and in case where there are many voters concerned, its very hard to analyze the voting patterns generally without first taking into some account some factors and then dissecting the whole population (Bernard, Paul & William, 1986).
Two basic approaches towards this analysis can be identified which could help in sorting out the mysteries behind the voting and the reasons that motivates or influences the choice of a voter. In order to come up with these two methods, the variance of the results has to be checked which will affect the analysis of data and the inference of data. There is the micro level (sometimes referred as the individual level) analysis and the aggregate level (also known as macro level) analysis. In the aggregate approach, one concentrates mostly on masses or the national level where data is pulled together. For instance if you are looking at factors that influencing the voters like the common pledges by the campaigning candidates for example un employment and the voting patterns.
The data to be collected will be based on the national statistics at a known election for a specific candidate and the current unemployment that specific time. In the whole process two aspects are compared that are continuous. One has to kook at the voting in a state and its relationship to unemployment in that state and then involves other states which then help the researcher in unearthing the underlying reasons between the two variables. This may give a conclusion like whenever unemployment rises before subsequent elections, the more the probabilities of an incumbent not appealing the election. To be able to look at the motivating factors behind the national voting factors, we have to rely on the micro level analysis of the person. This now calls the researcher for testing hypothesis of individual voters and ascertaining whether they hold. The aim of the researcher in comparing different continuous variables at different times also establishes the kind of data he/ is available to use. In the above example for determining the connection involving voting and unemployment, we were interested in country wide figures and the effects on the candidates. To test this nationwide across the states of US in different times, several observations and data would be pooled together. This constitutes comparative analysis and but also the observations are across different times (Jocelyn, 2002).
At the individual point analysis, the individual voter is analyzed using a cross sectional mode. In this case it’s not a must that time variation may be considered but in some cases it is retained. A time frame can be taken in which a researcher wishes to analyze the extend of individual motivation influence on the voting process at that particular time. This can be carried out through cross sectional examination of time phases and then pool then results together. This would be a case of getting respondents at different times in different regions. As it’s the case in aggregate analysis, the type data of use depends on particular answers being sought. A researcher would therefore acknowledge the data type and how it allows for it’s usage in checking the hypothesis. If you look at unemployment, regardless of time or national issue, it has to include time analysis (Bernard, Paul & William, 1986).
In conclusion, aggregated model tries to account for concrete vote during election which explains why it is the most popular method for election prediction as opposed to micro approach which puts more emphasis on the reasons of individual voting decisions (Jocelyn, 2002).
Reference
Bernard, B., Paul, F.L., & William, N. (1986).Voting. New York: Mid way Publications.
Jocelyn, A. J. (2002). Voters & Voting. London: sage Publications.
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