António R. Antunes

Corruption, credit market imperfections, and economic development

This paper studies the role of credit market imperfections and corruption on the process of economic development. We address the question of how much of the differences in output per capita across countries can be attributed to differences in credit market policies and corruption. In order to accomplish that, we construct and solve numerically a general equilibrium model with heterogeneous agents, contractual imperfections and occupational choices. The quantitative exercises suggest that a country in which debt contracts are not enforced and corruption corresponds to 10% of output will be roughly 1/3 to 1/2 as rich as the United States. Though this is an important effect, it is a small fraction of the huge differences in income per capita across countries.

Comparing Different Early Warning Systems: Results from a Horse Race Competition Among Members of the Macro-Prudential Research Network

Over the recent decades researchers in academia and central banks have developed early warning systems (EWS) designed to warn policy makers of potential future economic and financial crises. These EWS are based on diverse approaches and empirical models. In this paper we compare the performance of nine distinct models for predicting banking crises resulting from the work of the Macroprudential Research Network (MaRs) initiated by the European System of Central Banks. In order to ensure comparability, all models use the same database of crises created by MaRs and comparable sets of potential early warning indicators. We evaluate the models’ relative usefulness by comparing the ratios of false alarms and missed crises and discuss implications for pratical use and future research. We find that multivariate models, in their many appearances, have great potential added value over simple signalling models. One of the main policy recommendations coming from this exercise is that policy makers can benefit from taking a broad methodological approach when they develop models to set macro-prudential instruments.

Forecasting Banking Crises with Dynamic Panel Probit Models

Banking crises are rare events, however when they occur they often have dramatic consequences. The aim of this paper is to contribute to the toolkit of early warning models available to policy makers by exploring the dynamics and non-linearities embedded in a panel dataset covering several countries over three decades. The in-sample and out-of-sample forecast performance of several dynamic probit models is evaluated, with the objective of developing a common vulnerability indicator with early warning properties. The results obtained evidence that adding dynamic and non-linear components to the models substantially improves the ability to forecast banking crises.

Towards a Systemic Risk Indicator Based on Contingent Claim Analysis

Traditionally, the literature in systemic risk focuses on financial institutions and on their relations. The financial crisis that began in the United States in 2007 and, particularly, the subsequent European sovereign debt crisis have shown that there are many more channels of contagion apart from the ones that link risks within the banking system. As these channels propagate shocks, understanding them better can help to defect the mechanics behind systemic risk. This type of analysis is, nevertheless, confronted with several data gaps and limitations, which flow-of-funds statistics tries to overcome.