Sustainability vs credibility of fiscal consolidation: A principal components factor analysis for the Euro Zone

The purpose of this paper is to explain why some countries in the eurozone between 2010 and 2012 experienced a dramatic vicious circle between hard austerity plans and rising default risk premia. Were such plans too small, and hence non-credible, or too large, and hence non-sustainable? These questions have prompted theoretical and empirical investigations in the line of the so-called “self-fulfilling beliefs”, where beliefs of unsustainability of fiscal adjustments, and hence default on debt, feed higher risk premia which indeed make fiscal adjustments less sustainable.

Detecting the sustainability factor in the evolution of spreads is uneasy because it is largely non-observable and may be proxied by different variables. In this paper, the authors present the results of a dynamic principal components factor analysis (PCFA) applied to a panel data set of the 11 major EZ countries from 2000 to 2013, consisting of each country’s spread of long-term interest rate over Germany as dependent variable, and an array of leading fiscal and macroeconomic indicators of solvency fiscal effort and its sustainability.

The authors have been able to identify the role of these indicators that combine themselves as significant latent variables in boosting spreads. Moreover, the large joint deterioration of these variables is identifiably located between 2009 and 2012 and particularly for the group of countries under most severe default risk (with Italy and France as borderline cases). The authors also find evidence that the announcement of the European Central Bank Outright Monetary Transactions program has improved the sustainability assessment of sovereign debts.

Dynamic PCFA is a rather unusual technique with respect to standard econometric tests of models, which is particularly well-suited to reduce the number of variables in a data set by extracting meaningful linear combinations from the observed variables that may concur to explain a given phenomenon (the dependent variable). These combinations, called “common factors”, can be interpreted as latent, non-observable variables.