Ridge Type Shrinkage Estimation of Seemingly Unrelated Regressions And Analytics of Economic and Financial Data from "Fragile Five" Countries


YÜZBAŞI B., Ahmed S. E.

JOURNAL OF RISK AND FINANCIAL MANAGEMENT, cilt.13, sa.6, 2020 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 13 Sayı: 6
  • Basım Tarihi: 2020
  • Doi Numarası: 10.3390/jrfm13060131
  • Dergi Adı: JOURNAL OF RISK AND FINANCIAL MANAGEMENT
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI)
  • Anahtar Kelimeler: shrinkage estimator, seemingly unrelated regression model, multicollinearity, ridge regression, SPECIFICATION, TESTS, PARAMETERS, SELECTION
  • İnönü Üniversitesi Adresli: Evet

Özet

In this paper, we suggest improved estimation strategies based on preliminarily test and shrinkage principles in a seemingly unrelated regression model when explanatory variables are affected by multicollinearity. To that end, we split the vector regression coefficient of each equation into two parts: one includes the coefficient vector for the main effects, and the other is a vector for nuisance effects, which could be close to zero. Therefore, two competing models per equation of the system regression model are obtained: one includes all the regression of coefficients (full model); the other (sub model) includes only the coefficients of the main effects based on the auxiliary information. The preliminarily test estimation improves the estimation procedure if there is evidence that the vector of nuisance parameters does not provide a useful contribution to the model. The shrinkage estimation method shrinks the full model estimator in the direction of the sub-model estimator. We conduct a Monte Carlo simulation study in order to examine the relative performance of the suggested estimation strategies. More importantly, we apply our methodology based on the preliminarily test and the shrinkage estimations to analyse economic data by investigating the relationship between foreign direct investment and several economic variables in the "Fragile Five" countries between 1983 and 2018.