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    Identification of common factors in panel data growth model
    (Elsevier Science Sa, 2018) Deniz, Pinar; Stengos, Thanasis; Yazgan, M. Ege
    Cross sectional dependence may lead to inconsistent and inefficient estimators and as such misleading inferences when standard panel data techniques such as fixed/random effects are employed. Pesaran (2006) suggests incorporating cross sectional averages in panel data models as approximates of unobserved common factor(s) to deal with cross sectional dependence. In the context of a standard panel growth model we investigate whether these unobserved common factors can be identified and we find that institutional variables and life expectancy are able to adequately identify them. (C) 2018 Elsevier B.V. All rights reserved.
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    Revisiting the link between output growth and volatility: panel GARCH analysis
    (Physica-Verlag Gmbh & Co, 2021) Deniz, Pinar; Stengos, Thanasis; Yazgan, M. Ege
    This paper explores the link between output growth and volatility using several macroeconomic variables for a panel of countries for the period of 1971-2014. Using an augmented panel GARCH-M model, we allow for the first time in the literature for independent variables to be part of the conditional equations. The paper is also novel in terms of encompassing an extensive number of countries and country groups. The relationship between output growth and volatility is observed to vary between different country groups. Empirical findings regarding the effect of exogeneous variables suggest that trade openness contributes to economic growth and institutional quality lowers economic volatility.