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Comunicació presentada al 6th Workshop on Distributed and Multi-Agent Planning (DMAP 2018), celebrat durant la 28th International Conference on Automated Planning and Scheduling, els dies 24 a 29 de juny de 2018 a Delft, Països Baixos., In this work we present a novel approach to solving concurrent multiagent planning problems in which several agents act in parallel. Our approach relies on a compilation from concurrent multiagent planning to classical planning, allowing us to use an off-the-shelf classical planner to solve the original multiagent problem. The solution can be directly interpreted as a concurrent plan that satisfies a given set of concurrency constraints, while avoiding the exponential blowup associated with concurrent actions. Theoretically, we show that the compilation is sound and complete. Empirically, we show that our compilation can solve challenging multiagent planning problems that require concurrent actions., This work has been supported by the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502).

This paper proposes a framework to implement regression-based tests of predictive ability in unstable environments, including, in particular, forecast unbiasedness and efficiency tests, commonly referred to as tests of forecast rationality. Our framework is general: it can be applied to model-based forecasts obtained either with recursive or rolling window estimation schemes, as well as to forecasts that are model-free. The proposed tests provide more evidence against forecast rationality than previously found in the Federal Reserve's Greenbook forecasts as well as survey-based private forecasts. It confirms, however, that the Federal Reserve has additional information about current and future states of the economy relative to market participants.

While forecasting is a common practice in academia, government and business alike, practitioners are often left wondering how to choose the sample for estimating forecasting models. When we forecast inflation in 2018, for example, should we use the last 30 years of data or the last 10 years of data? There is strong evidence of structural changes in economic time series, and the forecasting performance is often quite sensitive to the choice of such window size. In this paper, we develop a novel method for selecting the estimation window size for forecasting. Specifically, we propose to choose the optimal window size that minimizes the forecaster's quadratic loss function, and we prove the asymptotic validity of our approach. Our Monte Carlo experiments show that our method performs quite well under various types of structural changes. When applied to forecasting US real output growth and inflation, the proposed method tends to improve upon conventional methods, especially for output growth.

The goal of this paper is to develop formal tests to evaluate the relative in-sample per- formance of two competing, misspecified, non-nested models in the presence of possible data instability. Compared to previous approaches to model selection, which are based on measures of global performance, we focus on the local relative performance of the models. We propose three tests that are based on different measures of local performance and that correspond to different null and alternative hypotheses. The empirical application provides insights into the time variation in the performance of a representative DSGE model of the European economy relative to that of VARs.

This paper studies empirical facts regarding the effects of unexpected changes in aggregate macroeconomic fiscal policies on consumers that differ depending on individual characteristics. We use data from the Consumption Expenditure Survey to estimate individual-level responses and multipliers for government spending. We find that unexpected fiscal shocks have substantially different effects on consumers depending on their income and age levels: the wealthiest individuals tend to behave according to predictions of standard RBC models, whereas the poorest ones behave according to standard IS-LM (non- Ricardian) models, most likely due to credit constraints. Furthermore, government spending policy shocks tend to decrease consumption inequality.

In this paper we propose an empirical method for detecting and identifying misspecification in structural economic models. Our approach formalizes the common practice of adding "shocks" in the model, and identifies potential misspecification via forecast error variance decomposition and marginal likelihood analyses. The simulation results based on a small-scale DSGE model demonstrate that our method can correctly identify the source of misspecification. Our empirical results show that state-of-the-art medium-scale New Keynesian DSGE models remain misspecified, pointing to asset and labor markets as the sources of the misspecification.

In the capital asset pricing model (CAPM), estimating beta consistently is important to obtain a consistent estimate of the price of risk. However, it is often found that the estimate of beta is sensitive to the choice of portfolios used in the estimation. This paper provides a new test to evaluate whether the choice of portfolios in typical asset price regressions is valid, in the sense that the portfolios satisfy two conditions: (i) the way the portfolios are formed are exogenous; and (ii) the choice of the group of assets to include in the portfolios provides enough information to identify the parameters of interest. Thus, checking the validity of the portfolio choice is an important pre-requisite to ensure consistent estimates of the parameters of the model. We illustrate the performance of the test in small samples via Monte Carlo simulations.The proposed test is also applicable to group and pseudo panel data models.

This paper explores the relationship between the economic turmoil generated by the Great Recession and the increase of secessionism in different regions of Western countries. Some authors have stressed that the Great Recession triggered profound changes in political attitudes and preferences and, in the context of a conflict between the centre and the periphery, fuelled secessionism as a radical shift of the institutional setup. Nevertheless, other researchers have remarked that a deep recession may make voters more accommodating with the status quo and more reluctant to take radical stances. Our paper aims at contributing to this debate by analyzing the case of Catalonia. We use the variation of economic variables and data from surveys and electoral outcomes at the level of municipalities to explore the relationship between the deterioration of the economic situation (that is, the local variation in the intensity of the crisis) and the increase of preferences for secession among the Catalan population. The findings from the analysis of our empirical models do not support the hypothesis that the heterogeneous effects of the Great Recession had any significant impact on political preferences at the level of municipality in Catalonia. These findings contribute to our understanding of the effects of hard economic times on people s attitudes and behaviour.