The paper “ Patents, Technological Spillovers at the Firm Level, Business and Default Cycles for Credit Risk” is an inspiring variant of the assignment on macro & microeconomics. The use of statistical tests in econometrics is not a straightforward concept therefore not resulting in a clear-cut interpretation. This is mostly applicable in areas where test statistics are used not only for checking the adequacy of a certain model but also to model construction. In solving econometric problems, less reliance should be placed on the indices of model adequacy that are used to develop the model; and on the other hand, the emphasis should be placed on the performance of models over other sets of data and against rival models.
One of the used methods by econometricians in solving economic and financial problems is the Maximum Likelihood Estimation Method. Maximum Likelihood Estimation is a fully parametric estimation. That is the likelihood function=the joint density of the observed random variable. It involves the process of finding the value of one or more parameters in relation to a given statistic which makes maximizes the known likelihood distribution.
An economic or financial problem can take different distributions hence different methods are applied to solve them. For instance, an economic or financial problem characterized by normal distribution can be solved as shown below: For a normal distribution 1 (2) so (3) and (4) giving (5) Similarly, (6) Gives Where; the standard deviation for maximum likelihood is the same for the sample. b) The t-test and similar non-parametric methods are only used to ascertain the difference between the two groups. However, where three or more groups are concerned, then ANOVA takes control. If ANOVA testing indicates a difference within groups, then the main area of interest is knowing the specific groups that exhibit the difference.
Considering a three study groups X, Y, and Z with different means, is X different from Y, X different from Z, Z different from Y? One of the several post hoc tests can be of help in determining the significant difference between the groups. It is worth noting that if the samples are paired then repeated-measures one-way ANOVA/Friedman’ s test is used while unpaired samples utilize one-way ANOVA or Kruskal-Wallis test.
Cincera, M. (1997) “Patents, R&D and Technological Spillovers at the Firm Level: Some evidence from Econometric Count Models for Panel Data” Journal of Applied Econometrics
Koopman, S. J. and Lucas, A. (2005) “Business and Default Cycles for Credit Risk” Journal of applied Econometrics.
Terza, J. V, (2002) “Alcohol Abuse and Employment: A Second Look” Journal of Applied Econometrics