Discretionary monetary policy and the zero lower bound on nominal interest rates

Ignoring the existence of the zero lower bound on nominal interest rates one considerably understates the value of monetary commitment in New Keynesian models. A stochastic forward-looking model with an occasionally binding lower bound, calibrated to the U.S. economy, suggests that low values for the natural rate of interest lead to sizeable output losses and deflation under discretionary monetary policy. The fall in output and deflation are much larger than in the case with policy commitment and do not show up at all if the model abstracts from the existence of the lower bound. The welfare losses of discretionary policy increase even further when inflation is partly determined by lagged inflation in the Phillips curve. These results emerge because private sector expectations and the discretionary policy response to these expectations reinforce each other and cause the lower bound to be reached much earlier than under commitment.     

The impact of monetary policy on asset prices

Estimating the response of asset prices to changes in monetary policy is complicated by the endogeneity of policy decisions and the fact that both interest rates and asset prices react to numerous other variables. This paper develops a new estimator that is based on the heteroskedasticity that exists in high-frequency data. We show that the response of asset prices to changes in monetary policy can be identified based on the increase in the variance of policy shocks that occurs on days of FOMC meetings and of the Chairman's semi-annual monetary policy testimony to Congress. The identification approach employed requires a much weaker set of assumptions than needed under the “event-study” approach that is typically used in this context. The results indicate that an increase in short-term interest rates results in a decline in stock prices and in an upward shift in the yield curve that becomes smaller at longer maturities. The findings also suggest that the event-study estimates contain biases that make the estimated effects on stock prices appear too small and those on Treasury yields too large.     

Multidimensional principal–agent value for money in healthcare project financing

Value for money (VfM) is a key parameter for the public sector in the choice between a public–private partnership (PPP) and traditional procurement, especially for healthcare infrastructure. This paper investigates the differences in what VfM means to the public and private sectors.     

Regionality revisited: An examination of the direction of spread of currency crises

What determines the direction of spread of currency crises? We examine data on waves of currency crises in 1992, 1994, 1997, and 1998 to evaluate several hypotheses on the determinants of contagion. We simultaneously consider trade competition, financial links, and institutional similarity to the “ground zero” country as potential drivers of contagion. To overcome data limitations and account for model uncertainty, we utilize Bayesian methodologies hitherto unused in the empirical literature on contagion. In particular, we use the Bayesian averaging of binary models that allows us to take into account the uncertainty regarding the appropriate set of regressors.We find that institutional similarity to the ground zero country plays an important role in determining the direction of contagion in all the emerging market currency crises in our dataset. We thus provide persuasive evidence in favour of the “wake-up call” hypothesis for financial contagion. Trade and financial links may also play a role in determining the direction of contagion, but their importance varies amongst the crisis periods.     

Forecasting monthly industrial production in real-time: from single equations to factor-based models

The aim of this paper is to analyze the performance of alternative forecasting methods to predict the index of industrial production in Italy from 1 to 3 months ahead. We use twelve different models, from simple ARIMA to dynamic factor models exploiting the timely information of up to 110 short-term indicators, both qualitative and quantitative. This allows to assess the relevance for the forecasting practice of alternative combinations of types of data (real-time and latest available), estimation methods and periods. Out-of-sample predictive ability tests stress the relevance of more indicators in disaggregate models over sample periods covering a complete business cycle (about 7 years in Italy). Our findings downgrade the emphasis on both the estimation method and data revision issues. In line with the classical “average puzzle”, the use of simple averages of alternative forecasts often improves the predictive ability of their single components, mainly over short horizons. Finally, selected indicators and factor-based models always perform significantly better than ARIMA models, suggesting that the short-run indicator signal always dominates the noise component. On this regard, selected indicators models can further increase the amount of signal extracted to improve up to 30–40% the short-run predictive ability of factor-based models and to forecast-encompass them.     

Sectoral shifts, diversification and regional unemployment: evidence from local labour systems in Italy

Using Local Labour Systems (LLSs) data, this work aims at assessing the effects of sectoral shifts and industry specialization patterns on regional unemployment in Italy over the years 2004–2008. Italy represents an interesting case study because of the high degree of spatial heterogeneity in local labour market performance and the well-known North–South divide. Furthermore, the presence of strongly specialized LLSs (Industrial Districts, IDs) allows us to test whether IDs perform better than highly diversified urban areas thanks to the effect of agglomeration economies, or viceversa. Building on a semiparametric spatial auto-regressive framework, our empirical investigation documents that sectoral shifts and the degree of specialization exert a negative role on unemployment dynamics. By contrast, highly diversified areas turn out to be characterized by better labour market performances.