This thesis examines the effects of fiscal consolidation on banking sector stability for 53 randomly selected developing and developed countries for the period 1960 to 2017. This thesis includes two parts. The first part investigates a causal link between public debt and primary surplus to estimate the vulnerability of a country to fiscal crisis. We estimate vulnerability through three debt methods: Bohn’s approach, a screening process and a threshold regression. The threshold model estimates a unique level of debt to gross domestic product (GDP) for every country, beyond which the economy may slip into fiscal crisis—called a vulnerable economy. Further, we offer a reconciliation of a debt approach with investment approach, analysed through financial net worth, to distinguish vulnerable from non-vulnerable economies. Using these debt and investment approaches, we propose a fiscal vulnerability selection procedure (Figure 5.2, Chapter 5). Applying this procedure, we find 26 economies vulnerable to fiscal crisis, with threshold ranges from a minimum of 21.16 per cent to a maximum of 84.06 per cent of public debt to GDP, respectively, for France and Belgium. These results are in contrast to the findings of Reinhart and Rogoff (2010), which considered 90 per cent of debt to GDP a criterion of vulnerability to fiscal crisis. Further, we observe some economies where the debt approach suggests those economies to be vulnerable, in contrast with the investment approach. The first part provides the basis (by distinguishing countries into vulnerable and non-vulnerable to fiscal crisis) for the second part of thesis, which investigates the effects of fiscal consolidation on financial sector stability.In the second part, we analyse the effects of fiscal consolidation on the financial sector stability for all countries and also for the subsamples of vulnerable and non-vulnerable economies. We use the conservative definition of fiscal consolidation (Ardagna, 2009) and carefully identify consolidation episodes for each country. In our panel analysis, we use bank-level capital adequacy ratios (Tier-1 and Tier-2) for each country by employing Bankscope data for the period from 1960 to 2017. We estimate both fixed-effects panel data models and the generalised method of moments proposed by Arellano and Bond (1991) through Roodman (2009) collapse to analyse the role of fiscal consolidation in banking sector stability. This enables two-dimensional analyses covering both the panel settings, where the number of countries and banks may affect estimations. We find that financial stability (Tier-1 ratio) improves by 0.36 percentage points as a result of one episode of fiscal consolidation across all countries included in the sample. The results follow by improvement of 0.58 percentage points in the subsample of vulnerable economies; however, non-vulnerable economies appear neutral in response to fiscal consolidation. Further, we conduct a country-wise empirical analysis to observe whether the country-specific settings may add some additional value to the panel analysis. For this purpose, we conduct aggregated and disaggregated analysis using data from 1960 to 2017. For aggregate analysis, we use risk-weighted regulatory capital, Z-scores and stock market capitalisation. The results of aggregated analysis reveal that standard capital adequacy ratios improve significantly in the vulnerable economies, compared with the non-vulnerable economies. For disaggregated analysis, we use the bank-wise Bankscope data on different banking variables. The results reveal that Indonesia, South Korea, New Zealand and Germany—as non-vulnerable economies—have also responded to fiscal consolidation. More interestingly, we find that strict fiscal consolidation may allow banks to compromise with their capital adequacy ratio; however, this seems true only for New Zealand and Germany. Therefore, we may infer that fiscal consolidation helps generate financial stability, particularly in economies vulnerable to fiscal crisis.
|Date of Award||13 Oct 2018|
|Supervisor||Arthur Goldsmith (Supervisor), Gulasekaran Rajaguru (Supervisor) & Safdar Khan (Supervisor)|