The importance of common cyclical features in VAR analysis: a Monte-Carlo study

Despite the commonly held belief that aggregate data display short-run comovement, there has been little discussion about the econometric consequences of this feature of the data. We use exhaustive Monte-Carlo simulations to investigate the importance of restrictions implied by common-cyclical features for estimates and forecasts based on vector autoregressive models. First, we show that the ìbestî empirical model developed without common cycle restrictions need not nest the ìbestî model developed with those restrictions. This is due to possible differences in the lag-lengths chosen by model selection criteria for the two alternative models. Second, we show that the costs of ignoring common cyclical features in vector autoregressive modelling can be high, both in terms of forecast accuracy and efficient estimation of variance decomposition coefficients. Third, we find that the Hannan-Quinn criterion performs best among model selection criteria in simultaneously selecting the lag-length and rank of vector autoregressions.

A Common-feature approach for testing present-value restrictions with financial data

It is well known that cointegration between the level of two variables (labeled Yt and yt in this paper) is a necessary condition to assess the empirical validity of a present-value model (PV and PVM, respectively, hereafter) linking them. The work on cointegration has been so prevalent that it is often overlooked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. The basis of this result is the use of rational expectations in forecasting future values of variables in the PVM. If this condition fails, the present-value equation will not be valid, since it will contain an additional term capturing the (non-zero) conditional expected value of future error terms. Our article has a few novel contributions, but two stand out. First, in testing for PVMs, we advise to split the restrictions implied by PV relationships into orthogonality conditions (or reduced rank restrictions) before additional tests on the value of parameters. We show that PV relationships entail a weak-form common feature relationship as in Hecq, Palm, and Urbain (2006) and in Athanasopoulos, Guillén, Issler and Vahid (2011) and also a polynomial serial-correlation common feature relationship as in Cubadda and Hecq (2001), which represent restrictions on dynamic models which allow several tests for the existence of PV relationships to be used. Because these relationships occur mostly with nancial data, we propose tests based on generalized method of moment (GMM) estimates, where it is straightforward to propose robust tests in the presence of heteroskedasticity. We also propose a robust Wald test developed to investigate the presence of reduced rank models. Their performance is evaluated in a Monte-Carlo exercise. Second, in the context of asset pricing, we propose applying a permanent-transitory (PT) decomposition based on Beveridge and Nelson (1981), which focus on extracting the long-run component of asset prices, a key concept in modern nancial theory as discussed in Alvarez and Jermann (2005), Hansen and Scheinkman (2009), and Nieuwerburgh, Lustig, Verdelhan (2010). Here again we can exploit the results developed in the common cycle literature to easily extract permament and transitory components under both long and also short-run restrictions. The techniques discussed herein are applied to long span annual data on long- and short-term interest rates and on price and dividend for the U.S. economy. In both applications we do not reject the existence of a common cyclical feature vector linking these two series. Extracting the long-run component shows the usefulness of our approach and highlights the presence of asset-pricing bubbles.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.

Ciclos de la producción industrial en Colombia: extracción del ciclo del sector y de sus ramas de actividad

En este documento empleamos el filtro de Butterworth para analizar la producción industrial total y por ramas de actividad mediante la extracción de señales en las frecuencias bajas y altas. En las frecuencias bajas la tendencia de la producción al interior del sector exhibe una dinámica que difiere fuertemente entre actividades. En las frecuencias altas, la mayoría de las ramas industriales presentan una mayor sensibilidad al ciclo común del sector que a los ciclos particulares o idiosincráticos, evidenciando una sincronización en la respuesta de la producción frente a choques exógenos.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We compare the performance of our index with other currently popular coincident indices of economic activity.

Previsão de preços de ativos usando restrições do modelo de valor presente

Motivados pelo debate envolvendo modelos estruturais e na forma reduzida, propomos nesse artigo uma abordagem empírica com o objetivo de ver se a imposição de restrições estruturais melhoram o poder de previsibilade vis-a-vis modelos irrestritos ou parcialmente restritos. Para respondermos nossa pergunta, realizamos previsões utilizando dados agregados de preços e dividendos de ações dos EUA. Nesse intuito, exploramos as restrições de cointegração, de ciclo comum em sua forma fraca e sobre os parâmetros do VECM impostas pelo modelo de Valor Presente. Utilizamos o teste de igualdade condicional de habilidade de previsão de Giacomini e White (2006) para comparar as previsões feitas por esse modelo com outros menos restritos. No geral, encontramos que os modelos com restrições parciais apresentaram os melhores resultados, enquanto o modelo totalmente restrito de VP não obteve o mesmo sucesso.

Continuous measurements at Schwingbachtal Studienlandschaft in the growing seasons 2013-2014

The recent development of in-situ monitoring devices, such as UV-spectrometers, makes the study of short-term stream chemistry variation relevant, especially the study of diurnal cycles, which are not yet fully understood. Our study is based on high-frequency data from an agricultural catchment (Studienlandschaft Schwingbachtal, Germany). We propose a novel approach, i.e. the combination of cluster analysis and Linear Discriminant Analysis, to mine from these data nitrate behavior patterns. As a result, we observe a seasonality of nitrate diurnal cycles, that differs from the most common cycle seasonality described in the literature, i.e. pre-dawn peaks in spring. Our cycles appear in summer and the maximum and minimum shift to a later time in late summer/autumn. This is observed both for water- and energy-limited years, thus potentially stressing the role of evapotranspiration. This concluding hypothesis on the role of evapotranspiration on nitrate stream concentration, which was obtained through data mining, broadens the perspective on the diurnal cycling of stream nitrate concentrations.

Direction Finding Estimators of Cyclostationary Signals in Array Processing for Microwave Power Transmission

A solar power satellite is paid attention to as a clean, inexhaustible large- scale base-load power supply. The following technology related to beam control is used: A pilot signal is sent from the power receiving site and after direction of arrival estimation the beam is directed back to the earth by same direction. A novel direction-finding algorithm based on linear prediction technique for exploiting cyclostationary statistical information (spatial and temporal) is explored. Many modulated communication signals exhibit a cyclostationarity (or periodic correlation) property, corresponding to the underlying periodicity arising from carrier frequencies or baud rates. The problem was solved by using both cyclic second-order statistics and cyclic higher-order statistics. By evaluating the corresponding cyclic statistics of the received data at certain cycle frequencies, we can extract the cyclic correlations of only signals with the same cycle frequency and null out the cyclic correlations of stationary additive noise and all other co-channel interferences with different cycle frequencies. Thus, the signal detection capability can be significantly improved. The proposed algorithms employ cyclic higher-order statistics of the array output and suppress additive Gaussian noise of unknown spectral content, even when the noise shares common cycle frequencies with the non-Gaussian signals of interest. The proposed method completely exploits temporal information (multiple lag ), and also can correctly estimate direction of arrival of desired signals by suppressing undesired signals. Our approach was generalized over direction of arrival estimation of cyclostationary coherent signals. In this paper, we propose a new approach for exploiting cyclostationarity that seems to be more advanced in comparison with the other existing direction finding algorithms.

Comparison between common traffic lights and three types of traffic lights with visual cycle a safety and capacity analysis

The objective of this paper is compare the common traffic lights (CTL) to three different types of traffic lights with countdown displays (SCD) and assess their effects on road safety and capacity. This comparison is required because the results found in the literature are divergent among countries and cities, and one of the SCD analyzed in our study is different from the SCD used worldwide. An observational before-after study was conducted to evaluate the safety and capacity in a period of one year before and one year after the implementation of the SCD in three Brazilian cities. The results indicate that the SCD models 1 and 3 had around 35%±14% reduction in the total number of accidents; the model 2, does not have significant reduction. In order to perform the capacity analysis a framework for data collection and an adaptation for estimation of initial lost time in each phase were developed. Considering the capacity analysis there was a reduction around 11% in the lost time in SCD model 1, 7% in SCD model 2 and 3% in SCD model 3. However the implications of this on capacity are trifle due to a small increase in the average headways for all SCD models compare to CTL.

Spatial and Temporal Analyses of Expansion and Cell Cycle in Sunflower Leaves1 : A Common Pattern of Development for All Zones of a Leaf and Different Leaves of a Plant

We have investigated the spatial distributions of expansion and cell cycle in sunflower (Helianthus annuus L.) leaves located at two positions on the stem, from leaf initiation to the end of expansion. Relative expansion rate (RER) was analyzed by following the deformation of a grid drawn on the lamina; relative division rate (RDR) and flow-cytometry data were obtained in four zones perpendicular to the midrib. Calculations for determining in situ durations of the cell cycle and of S-G2-M in the epidermis are proposed. Area and cell number of a given leaf zone increased exponentially during the first two-thirds of the development duration. RER and RDR were constant and similar in all zones of a leaf and in all studied leaves during this period. Reduction in RER occurred afterward with a tip-to-base gradient and lagged behind that of RDR by 4 to 5 d in all zones. After a long period of constancy, cell-cycle duration increased rapidly and simultaneously within a leaf zone, with cells blocked in the G0-G1 phase of the cycle. Cells that began their cycle after the end of the period with exponential increase in cell number could not finish it, suggesting that they abruptly lost their competence to cross a critical step of the cycle. Differences in area and in cell number among zones of a leaf and among leaves of a plant essentially depended on the timing of two events, cessation of exponential expansion and of exponential division.

Common multiples of complete graphs and a 4-cycle

A graph G is a common multiple of two graphs H-1 and H-2 if there exists a decomposition of G into edge-disjoint copies of H-1 and also a decomposition of G into edge-disjoint copies of H-2. In this paper, we consider the case where H-1 is the 4-cycle C-4 and H-2 is the complete graph with n vertices K-n. We determine, for all positive integers n, the set of integers q for which there exists a common multiple of C-4 and K-n having precisely q edges. (C) 2003 Elsevier B.V. All rights reserved.

Screening The Life Cycle Of Schistosoma Mansoni Using High-resolution Mass Spectrometry.

Schistosomiasis is a common tropical disease caused by Schistosoma species Schistosomiasis' pathogenesis is known to vary according to the worms' strain. Moreover, high parasitical virulence is directly related to eggs release and granulomatous inflammation in the host's organs. This virulence might be influenced by different classes of molecules, such as lipids. Therefore, better understanding of the metabolic profile of these organisms is necessary, especially for an increased potential of unraveling strain virulence mechanisms and resistance to existing treatments. In this report, direct-infusion electrospray high-resolution mass spectrometry (ESI(+)-HRMS) along with the lipidomic platform were employed to rapidly characterize and differentiate two Brazilian S. mansoni strains (BH and SE) in three stages of their life cycle: eggs, miracidia and cercariae, with samples from experimental animals (Swiss/SPF mice). Furthermore, urine samples of the infected and uninfected mice were analyzed to assess the possibility of direct diagnosis. All samples were differentiated using multivariate data analysis, PCA, which helped electing markers from distinct lipid classes; phospholipids, diacylglycerols and triacylglycerols, for example, clearly presented different intensities in some stages and strains, as well as in urine samples. This indicates that biochemical characterization of S. mansoni may help narrowing-down the investigation of new therapeutic targets according to strain composition and aggressiveness of disease. Interestingly, lipid profile of infected mice urine varies when compared to control samples, indicating that direct diagnosis of schistosomiasis from urine may be feasible.