Micro Econometrics Exam Case Solution
Because changes in the distribution of other factors can easily change the magnitude of the effect, the consistency of intersection relationships does not need to be considered a causal “model”. On the contrary, if one expects a similar distribution in a group of people from other causal factors, one should especially expect that uncontrolled disturbers will be consistent in the distribution of the population. , thus causing a similar degree of confusion at the correlation level; Therefore, even if the distribution of all other factors in the population is consistent, the consistency (homogeneity) of the degree of association itself cannot provide logical support for causation(Morgan, 1999).
These counterfactual conclusions provide a logical basis for the previous maintenance of the consistency model:
A related problem is the reason for determining consistency. Requiring the same risk ratio to occur in a wide variety of situations requires homogeneity, which is obviously very burdensome.
In other words, the consistency criterion can be used as a general qualitative rather than a quantitative criterion and can therefore only be used on the assumption that P is a causal relationship or a preventive effect P is negligible (usually reasonable). The same argument underlines the argument that a better meta-analysis is about finding the source of systematic differences in research results, not about the practice of estimating fictitious common effects.
A typical example is the analysis of the effect of treatment on rain in agricultural research that secretly transports a fertilizer from a treated field to an adjacent untreated field. In addition to simple intervention, SUTVA can be damaged in other situations, especially if the “macro effect” of the treatment changes the underlying outcome. Consider the situation of large-scale vocational training programs in cities where competition in the labor market is fierce. As the number of graduates of the program increases, the salaries that employers are willing to pay to graduates of the program decrease. When these complex effects exist, the immense simplicity of the counterfactual structure disappears.
The equation for this will be(Greenland, 2002)
- When some groups receive specific treatment and other groups do not receive specific treatment, the difference in difference (DiD) method is used. DiD is obtained by specifically obtaining two differences between group means. The first difference is the difference between the averages of the outcome variables for each group between the two periods. In the hypothetical example, the first difference corresponds only to the change in the average test score of each group between the beginning and the end of the school year.
The second difference is the difference between the differences calculated for the two groups in the first step (hence the DiD method is sometimes referred to as the “double difference” strategy). The second difference measures how the two sets of results change, which are interpreted as the causal relationship of the cause variables. Therefore, in our example, comparing the improvement in the test average of the two classes during the school year, we determine the effect of the afternoon class on student learning(Population Health Methods, 2019)……………………….
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