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New evidences regarding the tax-spending nexus in Romania through wavelet analysis

Mardi | 2017-01-31
Salle des Thèses de 16h00 à 17h20

Mihai MUTASCU

The paper investigates the causality between government revenues and government expenditures in the case of Romania, for the period 1991m1-2015m5, by following the wavelet approach. The study offers detailed information of this connection, for different sub-periods of time and frequencies, emphasizing the lead-lag nexus between variables under cyclical and anti-cyclical shocks. The main findings show that the treasury goals should be controlled by using the individual taxation techniques under structural reforms. Separately, when the economic crisis arises, the expenditure adjustment is a more appropriate fiscal instrument. On medium and long terms, the taxation system of individuals is recommended to be used as control for budgetary deficits during crisis. At the same time, on medium term, the government expenditures represent also a suitable policy choice.

The new impact curve: A variational approach

Mardi | 2017-01-17
16h00-17h20 en sully05

clément GOULET – Matthieu GARCIN

In this paper, we propose an innovative methodology for modelling the news impact curve. The news impact curve provides a non-linear relation between past returns and current volatility and thus enables to forecast volatility. Our news impact curve is the solution of a dynamic optimization problem based on variational calculus. Consequently, it is a non-parametric and smooth curve. To our knowledge, this is the first time that such a method is used for volatility modelling. Applications on simulated heteroskedastic processes as well as on financial data show a better accuracy in estimation and forecast for this approach than for standard parametric (symmetric or asymmetric ARCH) or non-parametric (Kernel-ARCH) econometric techniques.

Pitfalls in Systemic-Risk Scoring

Mardi | 2017-01-10
16h00-17h20 sully 05

Christophe HURLIN – Sylvain BENOIT – Christophe PERIGNON

We identify two main shortcomings in the systemic-risk scoring methodology currently used to identify and regulate Systemically Important Financial Institutions (SIFIs). Using newly-disclosed regulatory data for 119 US and international banks, we show that the economic magnitude of the resulting bias turns out to be important. The banks that benefit the most from the bias are custodian banks and (non-) Eurozone banks when the Euro weakens (strengthens). We then propose and implement a modified methodology that corrects for these shortcomings and leads to different conclusions about the banks that contribute the most to the risk of the system.