The curse of low expectations

We examine how a remedial education programme for primary school‐age children affects parental expectations about their children's future. Using original survey data we collected in Serbia, we investigate whether expectations on labour market prospects and educational attainment change as a consequence of exposure to the Roma Teaching Assistant programme. Our results show that parents of pupils in treated schools expect higher returns to education for their children and are more likely to expect them to achieve a secondary level of education. We also investigate the possible mechanisms in place due to the characteristics of the programme: remedial education and role model.     

Special Interest Groups and Trade Policy in the EU

The aim of this work is to employ theoretical and empirical analysis on the role of special interest groups in the determination of the EU trade policy. We build a two-stage game model of trade policy formation in a multisector-multicountry framework. We obtain the level of protection as a function of industry characteristics, in addition to political and economic factors at member state and European levels. The model is then tested by 2SLS estimation using data for 15 countries and 41 sectors. The econometric output suggests empirical support to model’s predictions as it highlights an important role for both national and European groups in trade policy making.      

Drivers for the voluntary adoption of consolidated financial statements in local governments

ABSTRACT

This paper investigates consolidated financial statements (CFS), which have been implemented by several countries. In Italy, CFS implementation was preceded by a testing period in which local governments could participate on a voluntary basis. This paper explains why this was a useful preliminary step to implementing CFS: the local governments that took part in the testing period were able to enhance their knowledge of the topic while improving their employees’ skills.     

NOMINAL AND REAL WAGE RIGIDITIES IN NEW KEYNESIAN MODELS: A CRITICAL SURVEY

Abstract The labour market is receiving increasing attention in the New Keynesian literature. In this paper, I critically survey this literature in order to highlight the role played by wage rigidities in the explanation of fluctuations caused by technology shocks. To this aim, I present a dynamic stochastic general equilibrium model with sticky prices, nominal wage rigidities and hiring costs. The comparison between this model and that of Blanchard and Gali highlights the non‐trivial differences which exist in the way nominal wage and real wage rigidities drive the economy's dynamics. My conclusion is that models incorporating nominal wage rigidities and some degree of price stickiness provide a better account of macroeconomic dynamics than models with real wage rigidities.     

CREDIT MARKETS AND HOUSING CHOICES

This paper analyses how individual characteristics and credit market conditions interact and determine homeownership. The impact of the lifetime profile of resources on homeownership is larger when credit market imperfections are more severe. We combine data from the Bank of Italy's Survey on Household Income and Wealth with information on regional differences in interest rate spreads. We find that an increase in current resources by 10,000 euros increases the probability of homeownership by five (two) percentage points under the least (most) favourable credit market conditions.     

Economic activity and recession probabilities: information content and predictive power of the term spread in Italy

The aim of the present article is to examine the information content of the Italian term spread as for real economic growth rates and recession probabilities and to test its predictive power in forecasting regime probabilities. To this end the relationship between the term spread and economic growth rates is modelled as a nonlinear one and specifically the Logistic Smooth Transition model is used, while a probit model is implemented to forecast recession probabilities. Specific to this article is the use of the OECD business cycle chronology, which was never used before to this end for the Italian case. Overall evidence supports the informative content of the spread in Italy over the whole period (1984–2005) although results are more satisfactory as from 1992. In particular, recession forecasts are generally better than those obtained with other chronologies previously adopted for the Italian case (ISAE and ECRI).     

Sustainable supply chain management in tourism

Sustainable supply chain management (SSCM) encapsulates the trend to use purchasing policies and practices to facilitate sustainable development at the tourist destination. Most research has focused on environmental aspects of manufacturing, while other aspects of sustainability or the challenges for the service sector are largely ignored. Yet SSCM is particularly important for tour operators, as the product depends on the activities of suppliers, such as accommodation, transport and activities. Therefore, tour operators' contribution to sustainable tourism will be more effective through the definition and implementation of policies that acknowledge responsibility for the impacts of suppliers. Exploratory research of SSCM practices amongst tour operators generated a wide range of examples of good practice across the whole supply chain, and recommendations are made for more widespread engagement. Copyright © 2006 John Wiley & Sons, Ltd and ERP Environment.     

Forecasting economic time series using targeted predictors

This paper studies two refinements to the method of factor forecasting. First, we consider the method of quadratic principal components that allows the link function between the predictors and the factors to be non-linear. Second, the factors used in the forecasting equation are estimated in a way to take into account that the goal is to forecast a specific series. This is accomplished by applying the method of principal components to ‘targeted predictors’ selected using hard and soft thresholding rules. Our three main findings can be summarized as follows. First, we find improvements at all forecast horizons over the current diffusion index forecasts by estimating the factors using fewer but informative predictors. Allowing for non-linearity often leads to additional gains. Second, forecasting the volatile one month ahead inflation warrants a high degree of targeting to screen out the noisy predictors. A handful of variables, notably relating to housing starts and interest rates, are found to have systematic predictive power for inflation at all horizons. Third, the targeted predictors selected by both soft and hard thresholding changes with the forecast horizon and the sample period. Holding the set of predictors fixed as is the current practice of factor forecasting is unnecessarily restrictive.     

Boosting diffusion indices

In forecasting and regression analysis, it is often necessary to select predictors from a large feasible set. When the predictors have no natural ordering, an exhaustive evaluation of all possible combinations of the predictors can be computationally costly. This paper considers ‘boosting’ as a methodology of selecting the predictors in factor‐augmented autoregressions. As some of the predictors are being estimated, we propose a stopping rule for boosting to prevent the model from being overfitted with estimated predictors. We also consider two ways of handling lags of variables: a componentwise approach and a block‐wise approach. The best forecasting method will necessarily depend on the data‐generating process. Simulations show that for each data type there is one form of boosting that performs quite well. When applied to four key economic variables, some form of boosting is found to outperform the standard factor‐augmented forecasts and is far superior to an autoregressive forecast. Copyright © 2009 John Wiley & Sons, Ltd.