Catherine Bruneau

Forecasting inflation using economic indicators: the case of France

In order to provide short-run forecasts of headline and core HICP inflation for France, we assess the forecasting performance of a large set of economic indicators, individually and jointly, as well as using dynamic factor models. We run out-of-sample forecasts implementing the Stock and Watson (1999) methodology. We find that, according to usual statistical criteria, the combination of several indicators-in particular those derived from surveys-provides better results than factor models, even after pre-selection of the variables included in the panel. However, factors included in VAR models exhibit more stable forecasting performance over time. Results for the HICP excluding unprocessed food and energy are very encouraging. Moreover, we show that the aggregation of forecasts on subcomponents exhibits the best performance for projecting total inflation and that it is robust to data snooping. Copyright

Fiscal Policy in the Transition to Monetary Union: A Structural VAR Model

In order to assess the effect of fiscal rules in Stage Three of EMU for France and Germany, Bayoumi and Eichengreens (1992) structural VAR analysis is extended by including the general government financial surplus and conditioning by external variables. This allows a distinction between fiscal and monetary shocks. During the period 1972.1-1995.4, monetary policy has a significant effect on prices in both countries. On the other hand, fiscal shocks, whose effect on the deficit provides a measure of the structural deficit , only contribute to a significant part of the dynamics of output in Germany. For that period, they appear to have little effect in France. In addition, fiscal shocks are uncorrelated between the two countries, although it is difficult to conclude that it reflects purely idiosyncratic shocks rather than a different policy-mix.

Forecasting Inflation in the Euro Area

In order to provide medium run forecasts of headline and core HICP inflation for the euro area, we assess the usefulness of dynamic factor models. We use Stock and Watsons (1999) out-of-sample methodology for models estimated over the 1988:1-2002:3 period, with balanced and unbalanced panels. We provide evidence that factors alone or combined with indicators help improve upon the simple Autoregressive (AR) model for forecasting HICP core inflation as well total inflation, if one refers to the usual criterion of Relative MSE together with its standard deviation. However, regarding total HICP we do not produce forecasts that are totally satisfactory in the sense of being capable of recognizing the 1999-2000 upturn in inflation in a timely manner. But, from that point of view, the construction of a synthetic core indicator helps achieve significantly better forecasts over a 12-month horizon than the AR model for total inflation for the final part of the sample. We also show that the results are rather robust to potential data-snooping.

Inflation and the Markup in the Euro Area

The paper implements a consistent empirical strategy in order to investigate the behaviour of the markup over the cycle and its contribution to inflation movements. We model the price series as I(2) components and use polynomial cointegration in order to recover a long-run price schedule. We do not reject statistically the reduction of the I(2) framework to an I(1) model as from the mid 1980s. We observe that the markup in fairly counter-cyclical and has a permanent effect on inflation through an error-correcting mechanism. Structural and forecasting equations exhibiting good performance are therefore estimated.

Nonlinear Cointegration Relationships between Non-Life Insurance Premiums and Financial Markets

The aim of this article is to study the adjustment dynamics of the non-life insurance premium (NLIP) and test its dependence to the financial markets in five countries (Canada, France, Japan, the United Kingdom, and the United States). First, we justify the linkage between the insurance and the financial markets by the underwriting cycle theory and financial models of insurance pricing. Second, we examine the relationship between the NLIP, the interest rate, and the stock price using the recent developments of nonlinear econometrics. We use threshold cointegration models: the switching transition error correction models (STECM). We show that STECM perform better than a linear error correction model (LECM) to reproduce the NLIP dynamics. Our empirical results show that the adjustment of the NLIP in France, Japan, and the United States is rather discontinuous, asymmetrical, and nonlinear. Moreover, we suggest a strong evidence of significant linkages between insurance and financial markets, show two regimes for the NLIP, and find that the NLIP adjustment toward equilibrium is time varying with a convergence speed that varies according to the insurance disequilibrium size.

Convergence in Household Credit Demand Across Euro Area Countries: Evidence from Panel Data

This article contributes to the literature on the convergence of financial systems in the euro area by estimating household credit demand in individual countries. Using the ARDL framework advocated notably by Pesaran et al. (1999), the article provides evidence on the convergence of long-run credit demand determinants (interest rates, investment and house prices) in the largest euro area countries, while short run-dynamics remain heterogenous across countries. The article also demonstrates that the equation uncovers demand rather than supply behaviour.

Cyclicity in the French Property–Liability Insurance Industry: New Findings Over the Recent Period

This paper reinvestigates the presence and the causes of the underwriting cycle in the French property-liability insurance industry as displayed by the combined ratio for the 1963-2008 period. The question is still a timely issue if we refer to regulation issues and the recent proposals in the Sovency framework to take into account the fluctuations of the profitability in specifying the solvency capital requirement. In the literature, two approaches are traditionally adopted to investigate the underwriting cycle : the first one refers to an endogeneous characterization of the cyclical properties from an AR(2) model. The second one claims that the cycle in the property-liability insurance has exogeneous sources related to the financial markets and the general economy. In this article, we reconcile the two approaches by using a smooth transition regression (STR) model. This model shows that the AR(2) model is relevant in a first regime where the capacity constraint is binding. In contrast, the fluctuations in the combined ratio are positively influenced by the lagged stock market return in a second regime where the capacity is not constrained, as for the most recent period. Moreover, we find that the current capacity is related to the lagged inflation rate in the latter case. These results confirm the idea that the European rules regarding the solvency capital requirement for insurance companies should take into account the state of the economy and the financial markets.

Measuring co-movements in the Euro area using a nonstationary factor model

This article investigates to what extent business cycles co-move in the four largest euro area economies, using a large-scale database of nonstationary series for the euro area over the 1980:Q1 to 2003:Q4 period. We apply the methodology proposed by Bai (2004) and Bai and Ng (2004) to construct a coincident indicator of the euro area business cycle, based on the first common factor estimated from a dynamic factor analysis on the level of the variables. The indicator appears to be significantly close, from a statistical point of view, to the level of the euro area GDP in the most recent period. We also show that national developments are increasingly correlated to the indicator at the business cycle frequencies. We finally suggest a decomposition of GDP growth along the different stationary and nonstationary factors.

Liquidity and Equity Short term fragility: Stress-tests for the European banking system

This paper investigates the impact of extreme shocks on stock and bond markets on listed European banks. The originality of our approach consists in dealing jointly with stock and bond markets and taking into account their interdependencies in case of extreme events by using a specific CVRF (CVine Risk Factor) model which combines copulas and a factorial structure. Moreover, contrary to what is generally done in the literature, we do not focus only on the responses of the stock returns but we also examine the response of the balance sheets of the banks and particularly of their short term assets in order to assess their fragility in terms of liquidity. Our main findings are the following: 1) the nature of the banks fragility has changed: today, the interest rate risk should be the first concern before the equity risk, as the banks have extensively increased their exposition to bond market due to flight-to-quality reactions and to large investments in governments bonds after the rescue operations the banks have benefited; 2) in case of a surge in the interest rate and in the links between stock and bond returns, the portfolios of the biggest banks in Europe would experience very severe shortfalls for both equity and liquidity buffers. Accordingly regulators should monitor the evolution of dependencies between assets and should pay utmost attention to the positive links between stock and bond returns.