Forecasting inflation and tracking monetary policy in the euro area: does national information help?

The ECB objective of price stability is given a quantitative content as a year-on-year growth rate in the euro area HICP close but below 2% over the medium term. While this objective is referred to area-wide price developments, in anticipating monetary policy moves, market analysts pay considerable attention to national data. In this paper we use the Generalized Dynamic Factor Model to derive a set of core inflation indicators that, combining national with area-wide data, allow us to answer two related questions: whether country-specific data are actually relevant to the future path of area-wide inflation once the information contained in area-wide data has been exploited, and whether it is useful, in order to track ECB monetary policy decisions, to factor in national and not only area-wide statistics. In both cases, our findings suggest that, when area-wide information is properly taken into account, there is little to be gained by considering national idiosyncratic developments.Forecast, Dynamic factor model, inflation, monetary policy

Forecasting economic activity with higher frequency targeted predictors

In this paper we explore the performance of bridge and factor models in forecasting quarterly aggregates in the very short-term subject to a pre-selection of monthly indicators. Starting from a large information set, we select a subset of targeted predictors using data reduction techniques as in Bai and Ng (2008). We then compare a Diffusion Index forecasting model as in Stock and Watson (2002), with a Bridge model specified with an automated General-To-Specific routine. We apply these techniques to forecasting Italian GDP growth and its main components from the demand side and find that Bridge models outperform naive forecasts and compare favorably against factor models. Results for France, Germany, Spain and the euro area confirm these findings.short-term GDP forecast, factor models, bridge models, General To Specific

Forecasting inflation and tracking monetary policy in the euro area: does national information help?

The ECB objective is set in terms of year on year growth rate of the Euro area HICP. Nonetheless, a good deal of attention is given to national data by market analysts when they try to anticipate monetary policy moves. In this paper we use the Generalized Dynamic Factor model to develop a set of core inflation indicators that, combining national data with area wide information, allow us to answer two related questions. The first is whether country specific data actually bear any relevance for the future path of area wide price growth, over and above that already contained in area wide data. The second is whether in order to track ECB monetary policy decisions it is useful to take into account national information and not only area wide statistics. In both cases our findings point to the conclusion that, once area wide information is properly taken into account, there is little to be gained from considering national idiosyncratic developments. JEL Classification: C25, E37, E52dynamic factor model, forecasting, inflation, monetary policy, Taylor rule

Down the non-linear road from oil to consumer energy prices: no much asymmetry along the way

In the past decade changes in oil prices have played a significant role in shaping inflation dynamics in the US and in the euro area, largely through their direct effect on fuels prices, reviving the controversy over whether the prices of petroleum products respond more promptly to positive than to negative oil price shocks. This paper provides fresh evidence on this issue for the US, the euro area and the four largest euro area countries (Germany, France, Italy and Spain), both for petrol and diesel prices. Inference is based on the dynamic response of downstream prices to upstream shocks, rather than on tests on the regression slopes as in the majority of existing studies, taking into account the non-linearity of the impulse response function in models with asymmetric adjustment, so far ignored in this literature. The empirical analysis shows that fuels prices respond very promptly to oil price shocks, with some heterogeneity across countries, and that no systematic evidence of asymmetries emerges. This result is robust across periods of high and low oil price volatility and holds both for standard and large shocks.energy, oil prices, asymmetry, inflation

Inflation convergence and divergence within the European Monetary Union

We study the convergence properties of inflation rates among the countries of the European Monetary Union over the period 1980-2004. Given the Maastricht agreements and the adoption of the single currency, the sample can be naturally split into two parts, before and after the birth of the euro. We study convergence in the first sub-sample by means of univariate and multivariate unit root tests on inflation differentials, arguing that the power of the tests is considerably increased if the Dickey-Fuller regressions are run without an intercept term. Overall, we are able to accept the convergence hypothesis over the period 1980-1997. We then investigate whether the second sub-sample is characterized by stable inflation rates across the European countries. Using stationarity tests on inflation differentials, we find evidence of diverging behaviour. In particular, we can statistically detect two separate clusters, or or convergence clubs: a lower inflation group that comprises Germany, France, Belgium, Austria, Finland and a higher inflation one with Spain, Netherlands, Greece, Portugal and Ireland. Italy appears to form a cluster of its own, standing in between the other two. JEL Classification: C12, C22, C32, E31Absolute Convergence, inflation differentials, stability, Unit Root Tests

Essays on Models with Time-Varying Parameters for Forecasting and Policy Analysis

PhD, 174ppThe aim of this thesis is the development and the application of econometric models with time-varying parameters in a policy environment. The popularity of these methods has run in parallel with advances in computing power, which has made feasible estimation methods that until the late ‘90s would have been unfeasible. Bayesian methods, in particular, benefitted from these technological advances, as sampling from complicated posterior distributions of the model parameters became less and less time-consuming. Building on the seminal work by Carter and Kohn (1994) and Jacquier, Polson, and Rossi (1994), bayesian algorithms for estimating Vector Autoregressions (VARs) with drifting coefficients and volatility were independently derived by Cogley and Sargent (2005) and Primiceri (2005). Despite their increased popularity, bayesian methods still suffer from some limitations, from both a theoretical and a practical viewpoint. First, they typically assume that parameters evolve as independent driftless random walks. It is therefore unclear whether the output that one obtains from these estimators is accurate when the model parameters are generated by a different stochastic process. Second, some computational limitations remain as only a limited number of time series can be jointly modeled in this environment. These shortcomings have prompted a new line of research that uses non-parametric methods to estimate random time-varying coefficients models. Giraitis, Kapetanios, and Yates (2014) develop kernel estimators for autoregressive models with random time-varying coefficients and derive the conditions under which such estimators consistently recover the true path of the model coefficients. The method has been suitably adapted by Giraitis, Kapetanios, and Yates (2012) to a multivariate context. In this thesis I make use of both bayesian and non-parametric methods, adapting them (and in some cases extending them) to answer some of the research questions that, as a Central Bank economist, I have been tackling in the past five years. The variety of empirical exercises proposed throughout the work testifies the wide range of applicability of these models, be it in the area of macroeconomic forecasting (both at short and long horizons) or in the investigation of structural change in the relationship among macroeconomic variables. The first chapter develops a mixed frequency dynamic factor model in which the disturbances of both the latent common factor and of the idiosyncratic components have time varying stochastic volatility. The model is used to investigate business cycle dynamics in the euro area, and to perform point and density forecast. The main result is that introducing stochastic volatility in the model contributes to an improvement in both point and density forecast accuracy. Chapter 2 introduces a nonparametric estimation method for a large Vector Autoregression (VAR) with time-varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information sets as large as those typically handled by factor models and Factor Augmented VARs (FAVAR). When applied to the problem of forecasting key macroeconomic variables, the method outperforms constant parameter benchmarks and large Bayesian VARs with time-varying parameters. The tool is also used for structural analysis to study the time-varying effects of oil price innovations on sectorial U.S. industrial output. Chapter 3 uses a bayesian VAR to provide novel evidence on changes in the relationship between the real price of oil and real exports in the euro area. By combining robust predictions on the sign of the impulse responses obtained from a theoretical model with restrictions on the slope of the oil demand and oil supply curves, oil supply and foreign productivity shocks are identified. The main finding is that from the 1980s onwards the relationship between oil prices and euro area exports has become less negative conditional on oil supply shortfalls and more positive conditional on foreign productivity shocks. A general equilibrium model is used to shed some light on the plausible reasons for these changes. Chapter 4 investigates the failure of conventional constant parameter models in anticipating the sharp fall in inflation in the euro area in 2013- 2014. This forecasting failure can be partly attributed to a break in the elasticity of inflation to the output gap. Using structural break tests and non-parametric time varying parameter models this study shows that this elasticity has indeed increased substantially after 2013. Two structural interpretations of this finding are offered. The first is that the increase in the cyclicality of inflation has stemmed from lower nominal rigidities or weaker strategic complementarity in price setting. A second possibility is that real time output gap estimates are understating the amount of spare capacity in the economy. I estimate that, in order to reconcile the observed fall in inflation with the historical correlation between consumer prices and the business cycle, the output gap should be wider by around one third.School of Economics and Finance Queen Mary, University of London

Strategic interactions and price dynamics in the global oil market

En un marco teórico simplificado, modelizamos las interacciones estratégicas entre los productores de la OPEP y los no pertenecientes a la OPEP y sus implicaciones para el mercado global de petróleo. Dependiendo de las condiciones del mercado, la OPEP puede considerar óptimo actuar como monopolista en la curva de demanda residual, variar su oferta en tándem con los no miembros de la OPEP, o compensar los cambios en la oferta de los productores fuera de la OPEP. Evaluamos las implicaciones del modelo a través de un modelo autorregresivo estructural (SVAR) que distingue entre producción de los países no pertenecientes a la OPEP y producción de la OPEP, y permite que la OPEP responda a aumentos de la oferta de los países no-OPEP. Esto se hace ya sea aumentando la producción (Market Share Targeting) o reduciéndola (Price Targeting). Comprobamos que los shocks de Price Targeting absorben la mitad de las fluctuaciones de los precios del petróleo, que no han sido explicadas por modelos más sencillos (que no incorporan las interacciones estratégicas entre OPEP y no-OPEP). Los shocks de Price Targeting, ignorados por estudios anteriores, explican alrededor del 10 % de las fluctuaciones de los precios del petróleo y son especialmente relevantes durante el auge de los precios de las materias primas en la década de 2000. Confirmamos que la caída de los precios del petróleo a finales de 2014 fue provocada por un intento de la OPEP de recuperar cuotas de mercado. También encontramos que la elasticidad de la oferta de la OPEP es tres veces mayor que la de los productores no pertenecientes a la OPEP.In a simplied theoretical framework, we model the strategic interactions between OPEC and non-OPEC producers and the implications for the global oil market. Depending on market conditions, OPEC may find it optimal to act either as a monopolist on the residual demand curve, to move supply in-tandem with non-OPEC, or to offset changes in non-OPEC supply. We evaluate the implications of the model through a Structural Vector Auto Regression (VAR) that separates non-OPEC and OPEC production and allows OPEC to respond to supply increases in non-OPEC countries. This is done by either increasing production (Market Share Targeting) or by reducing it (Price Targeting). We find that Price Targeting shocks absorb half of the fluctuations in oil prices, which have left unexplained by a simpler model (where strategic interactions are not taken into account). Price Targeting shocks, ignored by previous studies, explain around 10 percent of oil price fluctuations and are particularly relevant in the commodity price boom of the 2000s. We confirm that the fall in oil prices at the end of 2014 was triggered by an attempt of OPEC to re-gain market shares. We also find the OPEC elasticity of supply three times as high as that of non-OPEC producers

ICSBP Is Essential for the Development of Mouse Type I Interferon-producing Cells and for the Generation and Activation of CD8α+ Dendritic Cells

Interferon (IFN) consensus sequence-binding protein (ICSBP) is a transcription factor playing a critical role in the regulation of lineage commitment, especially in myeloid cell differentiation. In this study, we have characterized the phenotype and activation pattern of subsets of dendritic cells (DCs) in ICSBP−/− mice. Remarkably, the recently identified mouse IFN-producing cells (mIPCs) were absent in all lymphoid organs from ICSBP−/− mice, as revealed by lack of CD11clowB220+Ly6C+CD11b− cells. In parallel, CD11c+ cells isolated from ICSBP−/− spleens were unable to produce type I IFNs in response to viral stimulation. ICSBP−/− mice also displayed a marked reduction of the DC subset expressing the CD8α marker (CD8α+ DCs) in spleen, lymph nodes, and thymus. Moreover, ICSBP−/− CD8α+ DCs exhibited a markedly impaired phenotype when compared with WT DCs. They expressed very low levels of costimulatory molecules (intercellular adhesion molecule [ICAM]-1, CD40, CD80, CD86) and of the T cell area-homing chemokine receptor CCR7, whereas they showed higher levels of CCR2 and CCR6, as revealed by reverse transcription PCR. In addition, these cells were unable to undergo full phenotypic activation upon in vitro culture in presence of maturation stimuli such as lipopolysaccharide or poly (I:C), which paralleled with lack of Toll-like receptor (TLR)3 mRNA expression. Finally, cytokine expression pattern was also altered in ICSBP−/− DCs, as they did not express interleukin (IL)-12p40 or IL-15, but they displayed detectable IL-4 mRNA levels. On the whole, these results indicate that ICSBP is a crucial factor in the regulation of two possibly linked processes: (a) the development and activity of mIPCs, whose lack in ICSBP−/− mice may explain their high susceptibility to virus infections; (b) the generation and activation of CD8α+ DCs, whose impairment in ICSBP−/− mice can be responsible for the defective generation of a Th1 type of immune response

Antioxidant and α-glucosidase inhibitory activity of Achillea tenorii

Context: There is a need for the discovery of novel natural remedies to prevent and treat metabolic disorders such as hyperglycemia, type II non-insulin-dependent diabetes mellitus, and obesity. Several Achillea species have been utilized for centuries all around the world and are generally considered effective as hypoglycemic. Objective: Considering the ethnobotanical uses of Achillea genus, we evaluated the in vitro inhibitory activity of Achillea tenorii Grande (Asteraceae) extract on a-glucosidase, which is a valuable target to prevent and treat metabolic disorders. We also tested its antioxidant activity. Moreover, the phytochemical profile was discussed from a chemotaxonomic point of view. Materials and methods: In vitro a-glucosidase inhibition of crude ethanolic extract obtained from the aerial parts was assayed as well as the in vitro antioxidant activity (ABTS, DPPH, and FRAP-FZ tests) was measured. The extract was characterized from a phytochemical point of view by means of spectroscopic analysis. Results: The extract results endowed with a-glucosidase inhibitory activity (IC50 32 mg/mL) with a particular mechanism of action definable as un-competitive, which differed from the mechanism observed for the best-known a-glucosidase inhibitor (acarbose and miglitol). In addition, a considerable antioxidant potential has been found for A. tenorii extract, which resulted mainly constituted by phenolic compounds such as caffeoylquinic acids and flavonoids. Discussion and conclusions: These results suggest the potential of A. tenorii as a possible natural remedy to prevent and treat metabolic disorders of carbohydrates

The benefits and costs of adjusting bank capitalisation: evidence from Euro Area countries

El artículo propone un marco para evaluar el impacto de los colchones de capital a nivel de todo el sistema y a nivel bancario. La evaluación se basa en un modelo FAVAR (Factor-Augmented Vector Autoregression) que relaciona los ajustes bancarios individuales con la dinámica macroeconómica. El modelo FAVAR se estima individualmente para once economías de la zona del euro y se identifican impactos estructurales, lo que permite diagnosticar las principales vulnerabilidades de los sistemas bancarios nacionales y al mismo tiempo estimar los costes económicos a corto plazo del aumento de capital de los bancos. Sobre esta base, se realiza una evaluación completa de la relación coste-beneficio de un incremento en los colchones de capital. Los beneficios están relacionados con un aumento en la capacidad de resistencia de los bancos a perturbaciones adversas. Una mayor capitalización permite a los bancos hacer frente a impactos negativos y modera la reducción del crédito a economía real que se produce en circunstancias adversas. Los costes se relacionan con pérdidas transitorias de crédito y producción que son evaluadas tanto a nivel agregado como bancario. Se obtiene que un aumento en los ratios de capital tienen un impacto muy diferente en la actividad crediticia y económica, dependiendo de la forma en que los bancos se ajustan, es decir, bien a través de cambios en los activos o en capital.The paper proposes a framework for assessing the impact of system-wide and bank-level capital buffers. The assessment rests on a factor-augmented vector autoregression (FAVAR) model that relates individual bank adjustments to macroeconomic dynamics. We estimate FAVAR models individually for eleven euro area economies and identify structural shocks, which allow us to diagnose key vulnerabilities of national banking systems and estimate short-run economic costs of increasing banks’ capitalisation. On this basis, we run a fullyfledged cost-benefit assessment of an increase in capital buffers. The benefits are related to an increase in bank resilience to adverse shocks. Higher capitalisation allows banks to withstand negative shocks and moderates the reduction of credit to the real economy that ensues in adverse circumstances. The costs relate to transitory credit and output losses that are assessed both on an aggregate and bank level. An increase in capital ratios is shown to have a sharply different impact on credit and economic activity depending on the way banks adjust, i.e. via changes in assets or equity