DOI: 10.25549/usctheses-c127-671225
title: Essays on Financial Shocks and Crises

description: A shock that affects the financial system, such that it impairs access to financing for firms and individuals, can have substantial financial and real effects at both the micro and macro level. The recent global financial crisis has shown that a systemic banking crisis can have a particularly severe impact on the flow of credit, which in turn can deleteriously impact investment, employment, and other aspects of the economy. This dissertation first examines a more micro level picture of how an aggregate shock can manifest as a financial shock that induces firms to substantially change their financing choices, though in different ways depending on the firms’ characteristics. Then we turn to the macro level and examine which macroeconomic variables may indicate that a country is at a greater risk of experiencing a financial crisis in the near future. ❧ Specifically, in chapter 2 we examine a sample of publicly listed high-tech firms over the period 1996 to 2004, which captures the episode commonly referred to as the Dot-Com boom and bust. This episode was exemplified by a rapid increase in market valuations for many IT related firms from 1996 to 2000 and a subsequent crash that saw the NASDAQ index, which is heavily weighted towards IT firms, drop 77% from peak (March 2000) to trough (September 2002). An exploration of the data reveals a number of interesting patterns, particularly in regards to significant differences in firm financing, R&D, and other choices firms make, when we looked at statistics for groups of firms classified according to different characteristics. For example, classifying firms by their financing behavior, as debt or equity issuers, in each year of the sample, we find that the average R&D to sales ratio is higher for firms that are equity issuers in a greater number of years in the sample, while the opposite pattern (as expected) holds for firms classified as debt issuers in a majority of the years studied. We find similar patterns for variables such as firms’ average liquid and fixed assets shares. When classifying firms according to different criteria we observe a number of other interesting patterns as well. The most striking is the heterogeneity of the financing behavior for high and low growth firms, as defined by their Tobin’s Q value at the peak of the market, both before and during the stock market crash. While the pre-crisis patterns can be explained by existing theories of firms facing differential financial frictions due to informational/contractual problems, the divergent financing choices during the crash is difficult to reconcile with these explanations of the pre-crisis patterns. ❧ Chapter 3 of the dissertation presents a model that can consistently explain the heterogeneity in financing patterns for high and low growth firms that we observe in Chapter 2. We model the relation between a firm’s growth opportunities and its financing policy. Financially constrained firms have an incentive to maintain reserve borrowing capacity when expected future investment opportunities are high. These strategic savings allow firms to respond optimally to new opportunities when there are frictions on equity financing. The incentive for saving decreases as the cost of borrowing declines, thus shifts in monetary policy can have a stronger impact on the financing of high growth firms. We show that, based on differences in growth opportunities alone, the model can explain differences in the financing and performance of high and low growth IT firms during the Dot-Com boom and its subsequent bust. ❧ The final chapter contributes to the empirical literature that studies the incidence of financial crises and tries to determine which macro indicators contribute to and/or predict the increasing likelihood of such crises. One issue in the empirical literature is that it seems difficult to find macroeconomic indicators (at annual frequency available across a broad set of countries) that are consistently significant, particularly as predictors of an increased likelihood of crises. The lack of robust results in such studies may stem from the fact that they treat all financial crises similarly (e.g. all crisis episodes are assigned a value of 1 for the dependent variable in a probit regression model). We hypothesize that there may be differences in the significance of macro variables prior to a crisis when one differentiates between crises based on their severity. Given this hypothesis, we first combine a number of financial and currency crisis episodes identified in previous studies and then categorize these episodes as either limited or severe crises. Then, employing a multinomial logit regression model, we test a number of macro variables identified in previous empirical studies or suggested by the theoretical literature to assess their significance as predictors of financial crises with differing severity. We find that for limited crises, which are almost 44% of the crisis episodes, there are relatively few consistently significant macro variables that indicate an increased or decreased risk of a limited crisis. However, for severe crises, we find that across numerous regression specifications a number of the macro variables suggested by earlier empirical and theoretical studies are robustly significant indicators of an increased risk of a severe financial crisis. These results support the hypothesis that there are differences in the predictive power of macro variables to indicate an increase in the likelihood of a crisis when the crises are differentiated according to severity. The results also suggest that the failure to differentiate crisis episodes based on their severity probably contributes to the lack of robustness of the results reported in some of the empirical studies looking at this issue.