Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. A Monte Carlo study explores the finite sample performance of this procedure and evaluates the forecasting accuracy of models selected by this procedure. Two empirical applications confirm the usefulness of the model selection procedure proposed here for forecasting.

Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

It is well known that cointegration between the level of two variables (e.g. prices and dividends) is a necessary condition to assess the empirical validity of a present-value model (PVM) linking them. The work on cointegration,namelyon long-run co-movements, has been so prevalent that it is often over-looked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. This amounts to investigate whether short-run co-movememts steming from common cyclical feature restrictions are also present in such a system. In this paper we test for the presence of such co-movement on long- and short-term interest rates and on price and dividend for the U.S. economy. We focuss on the potential improvement in forecasting accuracies when imposing those two types of restrictions coming from economic theory.

Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions

This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up-dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities, the second includes the level of real price and dividend for the S&P composite index, and the third includes the logarithmic transformation of prices and dividends. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to them. Moreover, imposing short-run restrictions produce forecast winners 70% of the time for target variables of PVMs and 63.33% of the time when all variables in the system are considered.

Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

Using a sequence of nested multivariate models that are VAR-based, we discuss different layers of restrictions imposed by present-value models (PVM hereafter) on the VAR in levels for series that are subject to present-value restrictions. Our focus is novel - we are interested in the short-run restrictions entailed by PVMs (Vahid and Engle, 1993, 1997) and their implications for forecasting. Using a well-known database, kept by Robert Shiller, we implement a forecasting competition that imposes different layers of PVM restrictions. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to the unrestricted VAR. Moreover, imposing short-run restrictions produces forecast winners 70% of the time for the target variables of PVMs and 63.33% of the time when all variables in the system are considered.

Does mixed frequency vector error correction model add relevant information to exchange misalignment calculus? Evidence for United States

Real exchange rate is an important macroeconomic price in the economy and a ects economic activity, interest rates, domestic prices, trade and investiments ows among other variables. Methodologies have been developed in empirical exchange rate misalignment studies to evaluate whether a real e ective exchange is overvalued or undervalued. There is a vast body of literature on the determinants of long-term real exchange rates and on empirical strategies to implement the equilibrium norms obtained from theoretical models. This study seeks to contribute to this literature by showing that it is possible to calculate the misalignment from a mixed ointegrated vector error correction framework. An empirical exercise using United States' real exchange rate data is performed. The results suggest that the model with mixed frequency data is preferred to the models with same frequency variables

Automatic model selection for forecasting brazilian stock returns

This study aims to contribute on the forecasting literature in stock return for emerging markets. We use Autometrics to select relevant predictors among macroeconomic, microeconomic and technical variables. We develop predictive models for the Brazilian market premium, measured as the excess return over Selic interest rate, Itaú SA, Itaú-Unibanco and Bradesco stock returns. We nd that for the market premium, an ADL with error correction is able to outperform the benchmarks in terms of economic performance. For individual stock returns, there is a trade o between statistical properties and out-of-sample performance of the model.

Automatic model selection for forecasting Brazilian stock returns

This study aims to contribute on the forecasting literature in stock return for emerging markets. We use Autometrics to select relevant predictors among macroeconomic, microeconomic and technical variables. We develop predictive models for the Brazilian market premium, measured as the excess return over Selic interest rate, Itaú SA, Itaú-Unibanco and Bradesco stock returns. We find that for the market premium, an ADL with error correction is able to outperform the benchmarks in terms of economic performance. For individual stock returns, there is a trade o between statistical properties and out-of-sample performance of the model.

Testicular traits as selection criteria for young Nellore bulls

The objective of this study was to evaluate the possible use of biometric testicular traits as selection criteria for young Nellore bulls using Bayesian inference to estimate heritability coefficients and genetic correlations. Multitrait analysis was performed including 17,211 records of scrotal circumference obtained during andrological assessment (SCAND) and 15,313 records of testicular volume and shape. In addition, 50,809 records of scrotal circumference at 18 mo (SC18), used as an anchor trait, were analyzed. The (co) variance components and breeding values were estimated by Gibbs sampling using the Gibbs2F90 program under an animal model that included contemporary groups as fixed effects, age of the animal as a linear covariate, and direct additive genetic effects as random effects. Heritabilities of 0.42, 0.43, 0.31, 0.20, 0.04, 0.16, 0.15, and 0.10 were obtained for SC18, SCAND, testicular volume, testicular shape, minor defects, major defects, total defects, and satisfactory andrological evaluation, respectively. The genetic correlations between SC18 and the other traits were 0.84 (SCAND), 0.75 (testicular shape), 0.44 (testicular volume), -0.23 (minor defects), -0.16 (major defects), -0.24 (total defects), and 0.56 (satisfactory andrological evaluation). Genetic correlations of 0.94 and 0.52 were obtained between SCAND and testicular volume and shape, respectively, and of 0.52 between testicular volume and testicular shape. In addition to favorable genetic parameter estimates, SC18 was found to be the most advantageous testicular trait due to its easy measurement before andrological assessment of the animals, even though the utilization of biometric testicular traits as selection criteria was also found to be possible. In conclusion, SC18 and biometric testicular traits can be adopted as a selection criterion to improve the fertility of young Nellore bulls.

Evaluation of an average numerator relationship matrix model and a Bayesian hierarchical model for growth traits in Nellore cattle with uncertain paternity

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Selection for higher body weight in Nelore cattle is effective in achieving an increase of longissimus muscle area without reducing subcutaneous fat thickness

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Molecular Identification and Characterization of Ileal and Cecal Fungus Communities in Broilers Given Probiotics, Specific Essential Oil Blends, and Under Mixed Eimeria Infection

Broiler digestive tract fungal communities have gained far less scrutiny than that given corresponding bacterial communities. Attention given poultry-associated fungi have focused primarily on feed-associated toxin-producers, yeast, and yeast products. The current project focused on the use of pyrosequencing and denaturing gradient gel electrophoresis (DGGE) to identify and monitor broiler digestive fungal communities. Eight different treatments were included. Four controls were an Uninfected-Unmedicated Control, an Unmedicated-Infected Control, the antibiotic bacitracin methylene disalicylate plus the ionophore monensin as Positive Control, and the ionophore monensin alone as a Negative Control. Four treatments were two probiotics (BC-30 and Calsporin) and two specific essential oil blends (Crina Poultry Plus and Crina Poultry AF). All chickens except the Unmedicated-Uninfected Control were given, at 15 days of age, a standard oral Eimeria inoculum of sporulated oocysts. Ileal and cecal digesta were collected at pre-Eimeria infection at 14 days of age and at 7 days post-Eimeria infection at 22 days of age. Extracted cecal DNA was analyzed by pyrosequencing to examine the impact of diet supplements and Eimeria infection on individual constituents in the fungal community, while DGGE was used to compare more qualitative changes in ileal and cecal communities. Pyrosequencing identified three phyla, seven classes, eight orders, 13 families, 17 genera, and 23 fungal species. Ileal and cecal DGGE patterns showed fungal communities were clustered mainly into pre- and post-infection patterns. Post-infection Unmedicated-Uninfected patterns were clustered with pre-infection groups demonstrating a strong effect of Eimeria infection on digestive fungal populations. These combined techniques offered added versatility towards unraveling the effects of enteropathogen infection and performance enhancing feed additives on broiler digestive microflora.

Algoritmos evolutivos dedicados à reconfiguração de redes radiais de distribuição sob demandas fixas e variáveis: estudo dos operadores genéticos e parâmetros de controle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Clinical and radiographic changes around dental implants inserted in different levels in relation to the crestal bone, under different restoration protocols, in the dog model

Background: The aim of the present study was to evaluate clinical and radiographic changes that occur around dental implants inserted in different levels in relation to crestal bone under different restoration protocols.Methods: Thirty-six implants were inserted in the edentulous mandible of six mongrel dogs. Each implant was assigned to an experimental group according to the distance from the top of the implant to the crestal bone: Bone Level (at crestal bone level), Minus 1 (1 mm below crestal bone), or Minus 2 (2 mm below crestal bone). Each hemimandible was submitted to a restoration protocol: conventional (prosthesis was installed 120 days after implant placement, including 30 days with healing cap) or immediate (prosthesis was installed 24 hours after implant placement). Fixed partial prostheses were installed bilaterally in the same day. After 90 days, clinical and radiographic parameters were evaluated.Results: As long as the implants were inserted in more apical positions, the first bone-to-implant contact (fBIC) was positioned more apically (P<0.05). However, the apical positioning of the implants did not influence the ridge loss or the position of the soft tissue margin (PSTM) (P>0.05). In addition, in immediately restored sites, the PSTM was located significantly more coronally than that in conventionally restored sites (P=0.02).Conclusions: Despite the more apical positioning of the fBIC, the height of the peri-implant soft tissues and ridge was not jeopardized. Moreover, the immediate restoration protocol was beneficial to the maintenance of the PSTM. Further studies are suggested to evaluate the significance of these results in longer healing periods.

Selection of thermophilic and thermotolerant fungi for the production of cellulases and xylanases under solid-state fermentation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)