1,721,024 research outputs found
Bootstrap lag selection in DSGE models with expectations correction
Full text linkA well known feature of DSGE models is that their dynamic structure is generally not consistent with agents’ forecasts when the latter are computed from ‘unrestricted’ models. The expectations correction approach tries to combine the structural form of DSGE models with the best fitting statistical model for the data, taken the lag structure from dynamically more involved state space models. In doing so, the selection of the lag structure of the state space specification is of key importance in this framework. The problem of lag selection in state space models is quite an open issue and bootstrap techniques are shown to be very useful in small samples. To evaluate the empirical performances of our approach, a Monte Carlo simulation study and an empirical illustration based on U.S. quarterly data are provided
Misspecification and Expectations Correction in New Keynesian DSGE Models
Full text linkAbstract: This paper focuses on the dynamic misspecification that characterizes the class
of small-scale New-Keynesian models and provides a `natural' remedy for the typical difficulties
these models have in accounting for the rich contemporaneous and dynamic correlation structure
of the data, generally faced with ad hoc shock specifications. We suggest using the `best fitting'
statistical model for the data as a device through which it is possible to adapt the econometric
specification of the New-Keynesian model. The statistical model may feature an autocorrelation
structure that is more involved than the autocorrelation structure implied by the structural
model's reduced form solution under rational expectations, and it is treated as the actual agents'
expectations generating mechanism. A pseudo-structural form is built from the baseline system
of Euler equations by forcing the state vector of the system to have the same dimension as the
state vector characterizing the statistical model. We provide an empirical illustration based on
U.S. quarterly data and a small-scale monetary New Keynesian model
Weighted Elo rating for tennis match predictions
Full text linkOriginally applied to tennis by the data journalists of FiveThirtyEight.com, the Elo rating method estimates the strength of each player based on her/his career as well as the outcome of the last match played. Together with the regression-based, point-based and paired-comparison approaches, the Elo rating is a popular method to predict the probability of winning tennis matches. Notwithstanding its widely recognized merits in terms of ease of reproducibility and good performance, the Elo method does not completely take into account the current form of each player and their recent performances. This paper proposes a new version of the Elo rating method, labelled Weighted Elo (WElo), where the standard Elo updating is additionally weighted according to the scoreline of the players' last match. The proposed method considers not only if a player has won (lost) a match, but also how the victory (defeat) was achieved. In the empirical application, the forecasting performance of the WElo method is evaluated and compared against the most popular forecasting methods in tennis, using a sample of over 60,000 men's and women's professional matches. Overall, the WElo method outperforms all these competing methods. Moreover, it provides meaningfully profitable opportunities, according to a simple betting strategy
Is Time an Illusion? A Bootstrap Likelihood Ratio Approach to Testing Shock Transmission Delays in DSGE Models
No full textDeveloping a composite indicator of resident well-being: the case of the Romagna area
No full textThere is a growing literature on the assessment of quality of life conditions
and well-being in geographically and/or politically divided areas.. The paper proposes a
new measure of well-being based on residents‟ satisfaction with specific life domains,
leisure activities and satisfaction with life as a whole. The well-being index is
constructed using a Weighted Sum Model, where the weights are calculated by DEA
Is Time an Illusion? A Bootstrap Likelihood Ratio Test for Shock Transmission Delays in DSGE Models
Full text linkSeveral business cycle models exhibit a recursive timing structure, which enforces delayed propagation of exogenous shocks driving short-run dynamics. We propose a bootstrap-based empirical strategy to test for the relevance of timing restrictions and ensuing shock transmission delays in DSGE environments. In the presence of strong identification, we document how likelihood-based tests in bootstrap-resamples can be used to empirically assess short-run restrictions placed by informational structures on a given model's equilibrium representation, thereby enhancing coherence between theory and measurement. We evaluate the size properties of our procedure in short time series by conducting a number of numerical experiments on a popular New Keynesian model of the monetary transmission mechanism. An empirical application to U.S. data from the Great Moderation period allows us to revisit and qualify previous findings in the field by lending support to the conventional (unrestricted) timing protocol, whereby inflation and output gap do respond on impact to monetary policy innovations
Exogenous uncertainty and the identification of Structural Vector Autoregressions with external instruments
Full text linkWe provide necessary and sufficient conditions for the identification of Structural Vector Autoregressions (SVARs) with external instruments, considering the case in which r instruments are used to identify g structural shocks of interest, r>=g>=1. Novel frequentist estimation methods are discussed by considering both a partial shocks identification strategy, where only g structural shocks are of interest and are instrumented, and in a full shocks identification strategy, where despite g structural shocks are instrumented, all n structural shocks of the system can be identified under certain conditions. The suggested approach is applied to empirically investigate whether financial and macroeconomic uncertainty can be approximated as exogenous drivers of U.S. real economic activity, or rather as endogenous responses to first moment shocks, or both. We analyze whether the dynamic causal effects of non-uncertainty shocks on macroeconomic and financial uncertainty are signicant in the period after the Global Financial Crisis
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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