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This paper investigates the differences between parameters estimated using real-time and those estimated with revised data. The models used are New Keynesian DSGE models of the Czech, Polish, Hungarian, Swiss, and Swedish small open economies in interaction with the euro area. The paper also offers an analysis of data revisions of GDP growth and inflation and trend revisions of interest rates.
Data revisions are found to be unbiased and not autocorrelated in all countries. Inflation is usually measured more accurately in real-time than GDP growth, but this is not the case in the euro area. The results of the core analysis suggest that there are significant differences between parameter estimates using real-time data and those estimated using revised data. The model parameters that are most prone to significant differences between real-time and revised estimations are habit in consumption and persistence of domestic supply, of demand, and of world-wide technology shocks. The impulse response analysis suggests that the model behavior based on real-time and revised data is different.
Alberto Prieto, José Manuel Díaz-Cao, Pablo Díaz, Ana Pérez-Creo, Gonzalo López-Lorenzo, Luis Ángel Quintela, Ceferino López, Patrocinio Morrondo, Pablo Díez-Baños and Gonzalo Fernández
The objective of this study was to assess the implementation of a three-year Mycobacterium avium subsp. paratuberculosis monitoring programme using pooled faecal culture in small and mediumsized dairy herds to classify them as infected or non-infected and apply proper hygiene and biosecurity measures. Over a three-year period, 35 dairy herds were analysed annually by faecal culture of ten pooled samples. In addition, proper hygiene and biosecurity protocols were implemented in the farms after the first testing round. Considering a herd as infected with at least one culture positive in any of the three years, the accumulated percentage of infected herds was 25.7%, 40% and 45.7%, for each year respectively. Assuming that all infected herds had been detected at the end of the study, the percentage of infected herds detected each year was 56.25% and 87.5% for the first and second year, respectively. Using frequentist and Bayesian approaches, the estimated individual prevalence revealed a downward trend from 3.30-3.65% in the first year to 1.66-1.86% in the third year. The results of this study indicate that pooled faecal culture allowed for proper classification of the herds and can be a useful tool for monitoring dairy herds against paratuberculosis. In addition, statistical analysis of pooled faecal culture results can be used to evaluate the evolution of individual prevalence in the population and therefore the function of the implemented control programmes.
We present a new-Keynesian model for small open economy, with price rigidities stemming from a Calvo pricing scheme (1983), monopolistic banking system, financial dollarization of the economy and monetary and fiscal policy governed by rules. We estimate the model on Serbian data and propose various model extensions that could be used for monetary and fiscal policy analysis. We consider 6 combinations of monetary and fiscal policy regimes, inflation targeting and currency peg on one hand, and discretionary cyclically neutral fiscal policy and fiscal rules, on the other. The model with inflation targeting and discretionary fiscal policy fits the data best.
Structural Differences and Asymmetric Shocks between the Czech Economy and the Euro Area 12
The goal of this paper is to determine whether there exist asymmetric shocks and structural differences between the Czech economy and the Euro Area 12. A New Keynesian DSGE model of a small open economy is used for this purpose. Asymmetric shocks and structural differences are examined in two ways. At first, I examine asymmetry of shocks and sources of structural differences, using model comparison based on the Bayes factor. I do not find substantial evidence in favor of heterogeneity in household preferences. I find slight differences in price and wage formation and substantial difference in interest rate smoothing. However, the main differences are in timing, persistence and volatility of structural shocks. I also investigate impact of structural differences and differences in persistence and volatility of structural shocks on the behavior of both economies, using analysis of impulse-response functions. I find no substantial differences in responses of the main variables to preference shocks. On the other hand, I find much larger volatility and persistence of domestic technology shocks. This contributes to the fact that responses of domestic variables to technology shocks are much larger, and display more gradual and hump-shaped pattern than responses of foreign variables. I also find that responses of foreign variables to labour supply shocks are much more gradual and sluggish than responses of domestic variables. As regards monetary shocks, I find that there is almost no response of foreign inflation to foreign monetary shock while response of domestic inflation to domestic monetary shock displays substantial decline followed by gradual recovery. Responses of foreign variables to cost-push shocks are larger and more volatile than responses of domestic variables.
The Bayesian theorem is the most used instrument for stochastic inferencing in nonlinear dynamic systems and also the fundament of measurement uncertainty evaluation in the GUM. Many powerful algorithms have been derived and applied to numerous problems. The most widely used algorithms are the broad family of Kalman filters (KFs), the grid-based filters and the more recent particle filters (PFs). Over the last 15 years, especially PFs are increasingly the subject of researches and engineering applications such as dynamic coordinate measurements, estimating signals from noisy measurements and measurement uncertainty evaluation. This is rooted in their ability to handle arbitrary nonlinear and/or non-Gaussian systems as well as in their easy coding. They are sampling-based sequential Monte-Carlo methods, which generate a set of samples to compute an approximation of the Bayesian posterior probability density function. Thus, the PF faces the problem of high computational burden, since it converges to the true posterior when number of particles NP→∞. In order to solve these computational problems a highly parallelized C++ library, called Parallel Bayesian Toolbox (PBT), for implementing Bayes filters (BFs) was developed and released as open-source software, for the first time.
In this paper the PBT is presented, analyzed and verified with respect to efficiency and performance applied to dynamic coordinate measurements of a photogrammetric coordinate measuring machine (CMM) and their online measurement uncertainty evaluation.
An individual tree model with additive direct and competition effects is introduced to account for competitive effects in forest genetics evaluation. The mixed linear model includes fixed effects as well as direct and competition breeding values plus permanent environmental effects. Competition effects, either additive or environmental, are identified in the phenotype of a competitor tree by means of ‘intensity of competition’ elements (IC), which are non-zero elements of the incidence matrix of the additive competition effects. The ICs are inverse function of the distance and the number of competing individuals, either row-column wise or diagonally. The ICs allow standardization of the variance of competition effects in the phenotypic variance of any individual tree, so that the model accounts for unequal number of neighbors. Expressions are obtained for the bias in estimating additive variance using the covariance between half-sibs, when ignoring competition effects for row-plot designs and for single-tree plot designs. A data set of loblolly pines on growth at breast height is used to estimate the additive variances of direct and competition effects, the covariance between both effects, and the variance of permanent environmental effects using a Bayesian method via Gibbs sampling and Restricted Maximum Likelihood procedures (REML) via the Expectation- Maximization (EM) algorithm. No problem of convergence was detected with the model and ICs used when compared to what has been reported in the animal breeding literature for such models. Posterior means (standard error) of the estimated parameters were σ̂2Ad = 12.553 (1.447), σ̂2Ac = 1.259 (0.259), σ̂AdAc = -3.126 (0.492), σ̂2 p = 1.186 (0.289), and σ̂2e = 5.819 (1.07). Leaving permanent environmental competition effects out of the model may bias the predictions of direct breeding values. Results suggest that selection for increasing direct growth while keeping a low level of competition is feasible.
We evaluate the forecasting performance of four competing models for short-term macroeconomic forecasting: the traditional VAR, small scale Bayesian VAR, Factor Augmented VAR and Bayesian Factor Augmented VAR models. Using Armenian quarterly actual macroeconomic time series from 1996Q1 – 2014Q4, we estimate parameters of four competing models. Based on the out-of-sample recursive forecast evaluations and using root mean squared error (RMSE) criterion we conclude that small scale Bayesian VAR and Bayesian Factor Augmented VAR models are more suitable for short-term forecasting than traditional unrestricted VAR model.