Forecasting inflation: An art as well as a science!

In this study we build two forecasting models to predict inflation for the Netherlands and for the euro area. Inflation is the yearly change of the Harmonised Index of Consumer Prices (HICP). The models provide point forecasts and prediction intervals for both the components of the HICP and the aggregated HICP-index itself. Both models are small-scale linear time series models allowing for long run equilibrium relationships between HICP components and other variables, notably the hourly wage rate and the import or producer prices. The model for the Netherlands is used to generate the Dutch inflation projections over a horizon of 11-15 months ahead for the eurosystem’s Narrow Inflation Projection Exercise (NIPE). The recursive forecast errors for several forecast horizons are evaluated for all models, and are found to outperform a naive forecast and optimal AR models. Moreover, the same result holds for the Dutch NIPE projections, which have been provided quarterly since 1999. The direct and aggregation methods to predict total HICP inflation perform about equally goodmodel selection, time series models, aggregation

MOSES: Model of Swedish Economic Studies

MOSES is an aggregate econometric model for Sweden, estimated on quarterly data, and intended for short-term forecasting and policy simulations. After a presentation of qualitative model properties, the econometric methodology is summarized. The model properties, within sample simulations, and examples of dynamic simulation (model forecasts) for the period 2009q2-2012q4 are presented. We address practical issues relating to operational use and maintenance of a macro model of this type. The detailed econometric equations are reported in an appendix.

Human Antibody Responses against Virulence Factors of Staphylococcus aureus during Infection

_Staphylococcus aureus_ is an infamous bacterial pathogen which can produce a wide array of virulence factors, enabling it to cause many different infections with significant morbidity and mortality in humans. The ability of _S. aureus_ to form biofilm and its rising resistance against antibiotics further complicate treatment of many infections. Therefore, alternative treatment strategies, such as vaccination, are receiving great scientific and clinical interest. However, despite the many different virulence factors that have been targeted by vaccines and their promising effects in animal models, so far all clinical trials failed to demonstrate any favourable effect in humans. Thus, there remains a need for more insights into the presence of _S. aureus_ virulence factors and their ability to induce an antibody response during infection in humans. The general aim of this thesis was twofold; to provide further insights into the presence of a wide range of well-characterized virulence factors of _S. aureus_ during growth in _in vitro_ and _ex vivo_ infection models, mimicking the _in vivo_ situation during different infection in humans, and to further characterize the human antibody response during these different infections. The high-throughput, bead-based Luminex assay was used together with confirmation by additional techniques such as RT-PCR and mass-spectrometry throughout this thesis to achieve these aims. Data concerning _in vitro_ presence of -and _in vivo_ antibody responses against _S. aureus_ virulence factors are compared and, together, can help in identifying potential targets for novel vaccination strategies

On wage formation, wage flexibility and wage coordination : A focus on the nominal wage impact of productivity in Germany, Greece, Ireland, Portugal, Spain and the United States

This paper discusses the endeavours of policy makers to come to some degree of wage coordination among EU countries, aiming at aligning wage growth with labour productivity growth at the national levels. In this context, we analyse the wage and productivity developments in Germany, the European Union’s periphery countries Greece, Ireland, Portugal, and Spain along with the US for the period 1980-2010. Apart from the contribution of productivity to wages, we take into account the contributions of prices, unemployment, replacement rates and taxes by means of an econometrically estimated non-linear wage equation resulting from a wage bargaining model. We further study the downward rigidities of wages in depth. The findings show that in past times of low productivity, price inflation and reductions in unemployment put significant upward pressure on wage growth, also in the low inflationary period of the 2000s. Greece, Ireland, Portugal and Spain are far from aligning wage growth with productivity growth. German productivity is a major German wage determinant, but surely not the only one. To steer wages, policy makers can effectively use the replacement rate

Short-term forecasting of GDP using large monthly datasets - a pseudo real-time forecast evaluation exercise

This paper evaluates different models for the short-term forecasting of real GDP growth in ten selected European countries and the euro area as a whole. Purely quarterly models are compared with models designed to exploit early releases of monthly indicators for the nowcast and forecast of quarterly GDP growth. Amongst the latter, we consider small bridge equations and forecast equations in which the bridging between monthly and quarterly data is achieved through a regression on factors extracted from large monthly datasets. The forecasting exercise is performed in a simulated real-time context, which takes account of publication lags in the individual series. In general, we find that models that exploit monthly information outperform models that use purely quarterly data and, amongst the former, factor models perform best. JEL Classification: E37, C53.Bridge models, Dynamic factor models, real-time data flow.

Short-term forecasting of GDP using large monthly datasets: a pseudo real-time forecast evaluation exercise.

This paper evaluates different models for the short-term forecasting of real GDP growth in ten selected European countries and the euro area as a whole. Purely quarterly models are compared with models designed to exploit early releases of monthly indicators for the nowcast and forecast of quarterly GDP growth. Amongst the latter, we consider small bridge equations and forecast equations in which the bridging between monthly and quarterly data is achieved through a regression on factors extracted from large monthly datasets. The forecasting exercise is performed in a simulated real-time context, which takes account of publication lags in the individual series. In general, we find that models that exploit monthly information outperform models that use purely quarterly data and, amongst the former, factor models perform best.Bridge models ; Dynamic factor models ; real-time data flow.

Short-Term Forecasting of GDP Using Large Monthly Datasets: A Pseudo Real-Time Forecast Evaluation Exercise

This paper evaluates different models for the short-term forecasting of real GDP growth in ten selected European countries and the euro area as a whole. Purely quarterly models are compared with models designed to exploit early releases of monthly indicators for the nowcast and forecast of quarterly GDP growth. Amongst the latter, we consider small bridge equations and forecast equations in which the bridging between monthly and quarterly data is achieved through a regression on factors extracted from large monthly datasets. The forecasting exercise is performed in a simulated real-time context, which takes account of publication lags in the individual series. In general, we find that models that exploit monthly information outperform models that use purely quarterly data and, amongst the former, factor models perform best.Bridge models, Dynamic factor models, real-time data flow model