Working papers results
In this paper we evaluate the relative performance of linear, non-linear and time-varying models for about 500 macroeconomic variables for the countries in the Euro area, using real-time forecasting methodology. It turns out that linear models work well for about 35% of the series under analysis, time-varying models for another 35% and on-linear models for the remaining 30% of the series. The gains in forecasting accuracy from the choice of the best model can be substantial, in particular for longer forecast horizons.These results emerge from a detailed is aggregated analysis, while they are hidden when an average loss function is used. To explore in more detail the issue of parameter instability, we then apply a battery of tests, detecting non-constancy in about 20-30% of the time series. For these variables the forecasting performance of the time-varying and non-linear models further improves, with larger gains for a larger fraction of the series. Finally, we evaluate whether non-linear models perform better for three key macroeconomic variables: industrial production, inflation and unemployment. It turns out that this is often the case. Hence, overall, our results indicate that there is a substantial amount of instability and non-linearity in the EMU, and suggest that it can be worth going beyond linear models for several EMU macroeconomic variables.
Index tracking requires to build a portfolio of stocks (a replica) whose behavior is as close as possible to that of a given stock index. Typically, much fewer stocks should appear in the replica than in the index, and there should be no low frequency (persistent) components in the tracking error. Unfortunately, the latter property is not satisfied by many commonly used methods for index tracking. These are based on the in-sample minimization of a loss function, but do not take into account the dynamic properties of the index components. Instead, we represent the index components with a dynamic factor model, and develop a procedure that, in a first step, builds a replica that is driven by the same persistent factors as the index. In a second step, it is also possible to refine the replica so that it minimizes a loss function, as in the traditional approach. Both Monte Carlo simulations and an application to the EuroStoxx50 index provide substantial support for our approach.
This paper studies the structure and time consistency of optimal monetary policy from a public finance perspective in an economy where agents di.er in preference for liquidity and holdings of nominal assets. I find that the presence of redistributional e.ects breaks the link between time consistency and high inflation which characterizes representative agent models of optimal fiscal and monetary policy. For a large class of economies, optimal monetary policy is time consistent. I relate these findings to key historical episodes of inflation and deflation.
This paper presents firm level evidence on the change of non-manual wage premia and employment shares in Italian manufacturing during the nineties. We find that the relative stability of aggregate wage premia and employment shares hides offsetting disaggregate forces. First, while technical progress raises the relative demand for skilled labor within firms, demand changes associated with exports reduce the relative demand for skills. Second, within the class of non-manual workers, wage premia and employment shares of executives rise substantially, whereas those of clerks fall in a similar proportion. We also find that the export status of firms plays a key role in explaining labor market dynamics, as exporters account for most of both demand-related and technology-related shifts. Overall, our results for Italy question the general validity of the conventional view that emphasizes the role of labor market institutions, as opposed to trade and technology, in determining wage and employment dynamics in continental Europe.
Time series models are often adopted for forecasting because of their simplicity and good performance. The number of parameters in these models increases quickly with the number of variables modelled, so that usually only univariate or small-scale multivariate models are considered. Yet, data are now readily available for a very large number of macroeconomic variables that are potentially useful when forecasting. Hence, in this paper we construct a large macroeconomic data-set for the UK, with about 80 variables, model it using a dynamic factor model, and compare the resulting forecasts with those from a set of standard time series models. We find that just six factors are sufficient to explain 50% of the variability of all the variables in the data set. Moreover, these factors, which can be considered as the main driving forces of the economy, are related to key variables such as interest rates, monetary aggregates, prices, housing and labour market variables, and stock prices. Finally, the factor-based forecasts are shown to improve upon standard benchmarks for prices, real aggregates, and financial variables, at virtually no additional modelling or computational costs.
This paper studies within-family decision making regarding investment in income protection for surviving spouses using a simple and tractable Nash-bargaining model. A change in US pension law (the Retirement Equity Act of 1984) is used as an instrument to derive predictions from the bargaining model and to contrast these with the predictions of the classical single-utility-function model of the household. This law change gave spouses of married pension-plan participants the right to survivor benefits unless they explicitly waived this right. The classical view of household behavior predicts that this would have had no effect on choices, while the bargaining model predicts an increase in spousal survivor protection. In the empirical part of the paper, the predictions of the classical model regarding the amount of life-insurance protection and the likelihood of a pensioner selecting survivor benefits are rejected in favor of the predictions of the Nash-bargaining model. The paper thus provides evidence for the need to take the existence of multiple decision makers into account when studying household behavior.