This dissertation advances the literature on the cross-country differential real impact of the 2008-2009 Global Financial Crisis (GFC), and explains the apparent "Advanced Economies (AE) Nature" of the crisis. The literature's AE Nature result finds higher levels of pre-crisis income (logged per capita GDP) correlating with worse GFC-outcomes; but it does not address why this is so. Dependent variables (DVs) here measure GFC outcomes as the depth and duration of the peak-to-trough contraction in seasonally adjusted quarterly real GDP within 2007-2010. Following an introduction, Chapter 2 shows that the linear income relationships on both DVs represent spurious results, better characterized by a step-function between better performing lower-middle-income countries (LMICs) and similarly worse-off upper-middle-income and high-income countries (UMICs and HICs). Chapter 3 then undertakes a step-wise regression specification search on a broad set of pre-crisis independent variables (IVs), excluding those directly related to income. The search process addresses methodological issues found in the literature, including omitted variable bias, contingent significances, outlier influence, multicollinearity, and heteroscedasticity. IVs considered expand on those tested in the literature, newly adding measures for 2003-2007 "boom-period" growth for most indicators. Six IVs explain 75 per cent of depth DV variation: credit boom; manufacturing share of exports; FDI assets boom; food, fuels and mining share of exports boom; government expenditures boom; and an exchange rate regime dummy. Two IVs explain 46 per cent of duration DV variation: foreign debt liabilities; and bank assets boom. The models explain-away the AE Nature, in both LMIC-difference and linear-income forms. The depth model also explains an emerging Europe difference identified in the literature. However, several extreme outliers on the raw depth DV remain poorly-explained, including Ukraine and the Baltics. Chapter 4 undertakes comparative case studies on Ukraine and Latvia, paired with Romania and Belarus, respectively, as otherwise similar cases that are well-explained by the regression model. The analysis identifies factors helping explain Ukraine and Latvia's extreme contractions, primarily reflecting their different experiences-of and responses-to balance of payments crises.