|Keywords:||Economics; Economic Distress; Inter-industry Linkages; Power Law; Sector Rotation Strategy; Southern European Debt Crisis|
|Full text PDF:||http://www.escholarship.org/uc/item/79d8t54p|
This dissertation studies financial crises and sector-based analysis. Chapter 1 studies the balance of payments crisis in the euro area periphery countries preceded by significant private capital inflows from 1999 to 2007. With a detailed empirical investigation, I find that these capital inflows in the form of debt mainly financed the nontradable sector and the industries with weak forward linkages to the tradable sector. The model economy explains that domestic misallocation of the capital inflows in terms of inter-industry linkages can trigger the debt repayment problem which was experienced by PIIGS (Portugal, Italy, Ireland, Greece, and Spain). More precisely, it shows that the debt infows under the protection of implicit bailout-guarantee cannot be repaid in the case when they primarily nance the nontradable sector with weak forward linkage to the tradable sector. Chapter 2, which is co-authored with Aaron Tornell and Hyo Sang Kim, looks at the size distribution of economic distress (ED) events over the recent period of globalization (1970 - 2014) and the long historical period (1830 - 2013). We find that there exists a remarkable relation between the magnitude of economic distress events and the frequency with which they occur. We document that there is a threshold below which the size of ED events follows an exponential distribution, while a Pareto distribution (a power-law) applies for ED events larger than the threshold. To explain the empirical results, we present a wildre model in which the dynamics of an individual ED event is determined by the interaction of two opposing forces: (i) the natural stochastic growth of the ED, which is proportional to the size of the damage that has already occurred; and (ii) a policy that attempts to extinguish the economic distress. We then derive the steady-state cross-sectional distribution of the final size of the ED events. Chapter 3 studies a sector rotation strategy. I introduce a sector rotation model that generates forecasts of sector performance combining 4 factors which include price momentum, market sentiment, macroeconomic factors, and earnings expectations. The backtest results show that all 4 factors and the sector rotation model outperform its benchmark (Equal-Weight Basket). Moreover, macro factor as a single factor generates the highest risk-adjusted returns.