Common business and housing market cycles in the Euro area from a multivariate decomposition.

The 2007 sub-prime crisis in the United States, prolonged by a severe economic recession spread over many countries around the world, has led many economic researchers to focus on the recent fluctuations in housing prices and their relationships with macroeconomics and monetary policies. The existence of common housing cycles among the countries of the euro zone could lead the European Central Bank to integrate more specifically the evolution of such asset prices in its assessment. In this paper, we implement a multivariate unobserved component model on housing market variables in order to assess the common euro area housing cycle and to evaluate its relationship with the economic cycle. Among the general class of multivariate unobserved component models, we implement the band-pass filter based on the trend plus cycle decomposition model and we allow the existence of two cycles of different periods. The dataset consists of gross domestic product and real house prices series for four main euro area countries (Germany, France, Italy and Spain). Empirical results show a strong relationship for business cycles in France, Italy and Spain. Moreover, French and Spanish house prices cycles appear to be strongly related, while the German one possesses its own dynamics. Finally, we find that GDP and house prices cycles are related in the medium-term for fluctuations between 4 and 8 years, while the housing market contributes to the long-term economic growth only in Spain and Germany.House prices, Business cycles, Euro area, Unobserved components model.

Missing observations in observation-driven time series models

We argue that existing methods for the treatment of missing observations in time-varying parameter observation-driven models lead to inconsistent inference. We provide a formal proof of this inconsistency for a Gaussian model with time-varying mean. A Monte Carlo simulation study supports this theoretical result and illustrates how the inconsistency problem extends to score-driven and, more generally, to observation-driven models, which include well-known models for conditional volatility. To overcome the problem of inconsistent inference, we propose a novel estimation procedure based on indirect inference. This easy-to-implement method delivers consistent inference. The asymptotic properties of the new method are formally derived. Our proposed estimation procedure shows a promising performance in a Monte Carlo simulation exercise as well as in an empirical study concerning the measurement of conditional volatility from financial returns data

Realized wishart-garch:A score-driven multi-Asset volatility model

We propose a novel multivariate GARCH model that incorporates realized measures for the covariance matrix of returns. The joint formulation of a multivariate dynamic model for outer-products of returns, realized variances, and realized covariances leads to a feasible approach for analysis and forecasting. The updating of the covariance matrix relies on the score function of the joint likelihood function based on Gaussian and Wishart densities. The dynamic model is parsimonious while the analysis relies on straightforward computations. In a Monte Carlo study, we show that parameters are estimated accurately for different small sample sizes. We illustrate the model with an empirical in-sample and out-of-sample analysis for a portfolio of 15 U.S. financial assets

Consistency of the Shannon entropy in quantum experiments

The consistency of the Shannon entropy, when applied to outcomes of quantum experiments, is analysed. It is shown that the Shannon entropy is fully consistent and its properties are never violated in quantum settings, but attention must be paid to logical and experimental contexts. This last remark is shown to apply regardless of the quantum or classical nature of the experiments.Comment: 12 pages, LaTeX2e/REVTeX4. V5: slightly different than the published versio

The potential of water markets to allocate water between industry, agriculture, and public water utilities as an adaptation mechanism to climate change

One of the climate change scenarios that have been developed for the Netherlands predicts hotter and drier summers and a substantial drop in river discharge. This might lead to water scarcity with detrimental economic and environmental effects. Among the possible adaptation responses to climate change-induced water scarcity, the re-allocation of water resources among competing uses should also be considered. In this paper, we extend and apply a computable general equilibrium (CGE) model to assess the potential of water markets (water allocation according to its shadow price) to guide the allocation of scarce water across agriculture, manufacturing, and public water supply. We develop four scenarios in which the scope of water markets is increased from industry-specific to economy-wide. The results show that the agricultural sector bears nearly all of the losses from a new water-scarce climate, while the manufacturing sectors are able to mitigate their losses to a large extent by technical measures. Extending the scope of water markets unambiguously increases economic output and results in a re-allocation of water to the manufacturing sector from the agricultural sector and from public water services. If, perhaps for political reasons, public water services are excluded from water trading, water is re-allocated from agriculture to manufacturing. Depending on which sectors are included, the construction of a water market can have negative or positive effects on a sector’s output, and although the implementation of water markets may be positive for overall economic output and can hence assist adaptation, the effect on vulnerable or societally sensitive economic sectors, such as public water, should be taken into account when implementing such a market

SPEXOR passive spinal exoskeleton decreases metabolic cost during symmetric repetitive lifting

PURPOSE: Besides mechanical loading of the back, physiological strain is an important risk factor for low-back pain. Recently a passive exoskeleton (SPEXOR) has been developed to reduce loading on the low back. We aimed to assess the effect of this device on metabolic cost of repetitive lifting. To explain potential effects, we assessed kinematics, mechanical joint work, and back muscle activity. METHODS: We recruited ten male employees, working in the luggage handling department of an airline company and having ample experience with lifting tasks at work. Metabolic cost, kinematics, mechanical joint work and muscle activity were measured during a 5-min repetitive lifting task. Participants had to lift and lower a box of 10 kg from ankle height with and without the exoskeleton. RESULTS: Metabolic cost was significantly reduced by 18% when wearing the exoskeleton. Kinematics did not change significantly, while muscle activity decreased by up to 16%. The exoskeleton took over 18-25% of joint work at the hip and L5S1 joints. However, due to large variation in individual responses, we did not find a significant reduction of joint work around the individual joints. CONCLUSION: Wearing the SPEXOR exoskeleton decreased metabolic cost and might, therefore, reduce fatigue development and contribute to prevention of low-back pain during repetitive lifting tasks. Reduced metabolic cost can be explained by the exoskeleton substituting part of muscle work at the hip and L5S1 joints and consequently decreasing required back muscle activity