The relationship between fiscal vulnerability and macro-fiscal risk indicators: An empirical examination for selected countries

The ability of government to perform its functions in a timely and effective manner is directly linked to the existence of sound public finance. For this reason, the concepts of fiscal sustainability, fiscal vulnerability and fiscal risk have come to the fore in the relevant literature and in the international arena. Fiscal sustainability refers to the government's ability to pay its debts and meet its spending commitments in the long-run; fiscal vulnerability refers to the resilience of public finances to shocks, and fiscal risk refers to any phenomenon that may increase fiscal vulnerability and threaten fiscal sustainability by putting pressure on public finances. Therefore, measuring fiscal vulnerability and identifying, measuring, monitoring and managing fiscal risks are of great importance for ensuring fiscal sustainability. This study aims to identify and analyse indicators that may pose problems for fiscal sustainability, by examining the relationship between fiscal vulnerability and macro-fiscal risk indicators. The study uses the debt stock and debt structure indicators that are generally accepted in the literature to measure fiscal vulnerability. In addition, the study focuses on macro-fiscal risk indicators, taking into account the fact that fiscal risks can arise from various factors in different specialization areas and that there is a need for a lot of data on these risks. Accordingly, this study calculates a fiscal vulnerability index based on quarterly debt stock and debt structure data for the 2012-2023 period and a total of twenty-one countries, of which sixteen belong to the high-income group and five to the upper-middle-income group, and analyses the relationship between this index and selected macro-fiscal risk indicators, such as growth rate, current account balance/GDP ratio, consumer price index growth rate, unemployment rate, exchange rate and house price index growth rate, using panel data analysis.