A steady-state approach to trend/cycle decomposition of regime-switching processes

In this paper, we present a new approach to trend/cycle decomposition under the assumption that the trend is the permanent component and the cycle is the transitory component of an integrated time series. The permanent component is defined as the steady-state level of the series, a definition that has exploitable forecasting implications useful for identification. We operationalize the steady-state approach for regime-switching processes and we use generated data from such processes to demonstrate the advantages of the steady-state approach over alternative approaches to trend/cycle decomposition. We then apply the steady-state approach to estimate the trend and cycle of U.S. real GDP implied by a regime-switching forecasting model. Our findings portray a very different picture of the business cycle than implied by more traditional methods.Time-series analysis ; Business cycles

Nonlinearity and the permanent effects of recessions

This paper presents a new nonlinear time series model that captures a post-recession “bounce-back” in the level of aggregate output. While a number of studies have examined this type of business cycle asymmetry using recession-based dummy variables and threshold models, we relate the “bounce-back” effect to an endogenously estimated unobservable Markov-switching state variable. When the model is applied to U.S. real GDP, we find that the Markov-switching regimes are closely related to NBER-dated recessions and expansions. Also, the Markov-switching form of nonlinearity is statistically significant and the “bounce-back” effect is large, implying that the permanent effects of recessions are small. Meanwhile, having accounted for the “bounce-back” effect, we find little or no remaining serial correlation in the data, suggesting that our model is sufficient to capture the defining features of U.S. business cycle dynamics. When the model is applied to other countries, we find larger permanent effects of recessions.Business cycles ; Recessions

Reproducing Business Cycle Features: How Important Is Nonlinearity Versus Multivariate Information?

In this paper, we consider the ability of time-series models to generate simulated data that display the same business cycle features found in U.S. real GDP. Our analysis of a range of popular time-series models allows us to investigate the extent to which multivariate information can account for the apparent univariate evidence of nonlinear dynamics in GDP. We find that certain nonlinear specifications yield an improvement over linear models in reproducing business cycle features, even when multivariate information inherent in the unemployment rate, inflation, interest rates, and the components of GDP is taken into account.

Inflation in the G7: mind the gap(s)?

We investigate the importance of trend inflation and the real-activity gap for explaining observed inflation variation in G7 countries since 1960. Our results are based on a bivariate unobserved-components model of inflation and unemployment in which inflation is decomposed into a stochastic trend and transitory component. As in recent implementations of the New Keynesian Phillips Curve, it is the transitory component of inflation, or “inflation gap”, that is driven by the real-activity gap, which we measure as the deviation of unemployment from its natural rate. Even when allowing for changes in the contributions of trend inflation and the inflation gap, we find that both are important determinants of inflation variation at business cycle horizons for all G7 countries throughout much of the past 50 years. Also, the real-activity gap explains a large fraction of the variation in the inflation gap for each country, both historically and in recent years. Taken together, the results suggest the New Keynesian Phillips Curve, once augmented to include trend inflation, is an empirically relevant model for the G7 countries. We also provide new estimates of trend inflation for the G7 that incorporate information in the real-activity gap for identification and, through formal model comparisons, new statistical evidence regarding structural breaks in the variability of trend inflation and the inflation gap.Inflation (Finance) ; Phillips curve

A Bayesian approach to counterfactual analysis of structural change

In this paper, we develop a Bayesian approach to counterfactual analysis of structural change. Contrary to previous analysis based on classical point estimates, this approach provides a straightforward measure of estimation uncertainty for the counterfactual quantity of interest. We apply the Bayesian counterfactual analysis to examine the sources of the volatility reduction in U.S. real GDP growth in the 1980s. Using Blanchard and Quah’s (1989) structural VAR model of output growth and the unemployment rate, we find strong statistical support for the idea that a counterfactual change in the size of structural shocks alone, with no corresponding change in propagation, would have produced the same overall volatility reduction that actually occurred. Looking deeper, we find evidence that a counterfactual change in the size of aggregate supply shocks alone would have generated a larger volatility reduction than a counterfactual change in the size of aggregate demand shocks alone. We show that these results are consistent with a standard monetary VAR, for which counterfactual analysis also suggests the importance of shocks in generating the volatility reduction, but with the counterfactual change in monetary shocks alone generating a small reduction in volatility.Monetary policy ; Econometrics

Hard limits on the postselectability of optical graph states

Coherent control of large entangled graph states enables a wide variety of quantum information processing tasks, including error-corrected quantum computation. The linear optical approach offers excellent control and coherence, but today most photon sources and entangling gates---required for the construction of large graph states---are probabilistic and rely on postselection. In this work, we provide proofs and heuristics to aid experimental design using postselection. We derive a fundamental limitation on the generation of photonic qubit states using postselected entangling gates: experiments which contain a cycle of postselected gates cannot be postselected. Further, we analyse experiments that use photons from postselected photon pair sources, and lower bound the number of classes of graph state entanglement that are accessible in the non-degenerate case---graph state entanglement classes that contain a tree are are always accessible. Numerical investigation up to 9-qubits shows that the proportion of graph states that are accessible using postselection diminishes rapidly. We provide tables showing which classes are accessible for a variety of up to nine qubit resource states and sources. We also use our methods to evaluate near-term multi-photon experiments, and provide our algorithms for doing so.Comment: Our manuscript comprises 4843 words, 6 figures, 1 table, 47 references, and a supplementary material of 1741 words, 2 figures, 1 table, and a Mathematica code listin

Modelling of building interiors with mobile phone sensor data

Creating as-built plans of building interiors is a challenging task. In this paper we present a semi-automatic modelling system for creating residential building interior plans and their integration with existing map data to produce building models. Taking a set of imprecise measurements made with an interactive mobile phone room mapping application, the system performs spatial adjustments in accordance with soft and hard constraints imposed on the building plan geometry. The approach uses an optimisation model that exploits a high accuracy building outline, such as can be found in topographic map data, and the building topology to improve the quality of interior measurements and generate a standardised output. We test our system on building plans of five residential homes. Our evaluation shows that the approach enables construction of accurate interior plans from imprecise measurements. The experiments report an average accuracy of 0.24 m, close to the 0.20 m recommended by the CityGML LoD4 specificatio

Predictive analytics for enhancing travel time estimation in navigation apps of Apple, Google, and Microsoft

The explosive growth of the location-enabled devices coupled with the increasing use of Internet services has led to an increasing awareness of the importance and usage of geospatial information in many applications. The mobile navigation apps (often called “Maps”), use a variety of available data sources to calculate and predict the travel time for different modes. This paper evaluates the pedestrian mode of Maps apps in three major smartphone operating systems (Android, iOS and Windows Phone). We will demonstrate that the Maps apps on iOS, Android and Windows Phone in pedestrian mode, predict travel time without learning from the individual’s movement profile. Then, we will exemplify that those apps suffer from a specific data quality issue (the absence of information about location and type of pedestrian crossings). Finally, we will illustrate learning from movement profile of individuals using predictive analytics models to improve the accuracy of travel time estimation for each user (personalization)

Evaluation of subjective preferences regarding indoor maps: comparison of schematic maps and floor plans

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.In this study, we investigate subjective preferences regarding floor plans and schematic maps in the use of a map in an indoor environment. To achieve this, we performed a qualitative experiment with a random user sample; the survey was carried out remotely. The survey was conducted in Portuguese and English, and users were asked to answer questions, using two different maps:a floor plan and a schematic map. In the sequence, users were asked questions about their preferences regarding map use in an indoor environment. Users also answered questions about the positive and negative aspects of using a schematic map in an indoor environment. The initial results do not indicate a preference for one kind of map, but show that users found the symbology adopted in the schematic map easier to understand

Preliminary Observations on New Images of the Elysium Frozen Sea Deposits from HRSC Mars Express

Abstract not available