Heuristic model selection for leading indicators in Russia and Germany

Abstract

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New Methods in Exploring Old Topics: Case Studying Brittle Diabetes in the Family Context

“…In order to alleviate this shortcoming of low adjusted R 2 values in the standard vector autoregressive modeling approach, we developed a computer code implementing a statistical procedure recently published in parts in Savin and Winker [ 25 ] and Winker [ 26 , 27 ], referred to as the optimized multivariate lag selection process, which allows (contrary to previous practice) excluding such explanatory variables (lags) from the VAR model which add little to its goodness of fit (estimated representativeness of reality) while nonetheless reducing its explanatory power (adjusted R 2 ). This “admittance of holes” to the lag structure (equations organizing the explanatory variables) allows us to now present an entirely new model exhibiting more detailed dynamics with a smaller number of parameters, for the data in this case resulting in about tenfold increase of the adjusted R 2 value.…”

“…Given the large number of explanatory variables (the more lags, the more variables) and the limited number of observations, only a very limited number of lags (past days) could be considered while adjusted R 2 would still be low, if we were to follow the standard modeling approach [ 22 , 23 ]. The novel contribution is to maximize the informational content of the model by minimizing an information criterion [ 25 – 27 ].…”

“…To resolve this dilemma, we drew on Winker [ 26 , 27 ] and Savin and Winker [ 25 ] engaging in optimized multivariate lag structure analysis. Given the huge discrete search space of all possible lag structures, for example, for a maximum lag length of seven, heuristic optimization algorithms are used to this end.…”

“…Given the huge discrete search space of all possible lag structures, for example, for a maximum lag length of seven, heuristic optimization algorithms are used to this end. For this process, a computer code was developed using Matlab R2011b with an interface to EViews 7.1, which implements a Genetic Algorithm for the search of an optimized lag structure making use of information criteria (BIC) as in the standard selection procedure (see for more details [ 25 ]). By providing an approximation to the minimum of the information criterion, the resulting model exhibits an optimized tradeoff between a good fit to the multivariate dynamics of the data and model parsimony.…”

The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators

“…Some authors analyzed the sentiment of economics or consumers on a country level, while others focused on a regional level. Savin and Winker (2011) analyzed Germany and Russia's cases, and pointed to the specifics of tendencies in different countries. Bhattacharyay et al (2009) studied early-warning indicators impacting economic and financial risks in Kazakhstan.…”