Business cycle measurement with some theory

A method to evaluate cyclical models not requiring knowledge of the DGP and the exact specificationof the aggregate decision rules is proposed. We derive robust restrictions in a class of models; use someto identify structural shocks in the data and others to evaluate the class or contrast sub-models. Theapproach has good properties, even in small samples, and when the class of models is misspecified. Themethod is used to sort out the relevance of a certain friction (the presence of rule-of-thumb consumers)in a standard class of models.

Back to square one: Identification issues in DSGE models

We investigate identifiability issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model impulse responses. We show that observational equivalence, partial and weak identification problems are widespread, that they lead to biased estimates, unreliable t-statistics and may induce investigators to select false models. We examine whether different objective functions affect identification and study how small samples interact with parameters and shock identification. We provide diagnostics and tests to detect identification failures and apply them to a state-of-the-art model.

How much structure in empirical models?

This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways but solved only if DSGEs are completely reparametrized or respecified. The potential misspecification of the structural relationships give Bayesian methods an hedge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecificationof the structural relationships but must firmly tie SVARs to the class of DSGE models which could have have generated the data.

A scaled difference chi-square test statistic for moment structure analysis

A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are available in standard computer software. Often, however, the interest is not on the overall fit of a model, but on a test of the restrictions that a null model say ${\cal M}_0$ implies on a less restricted one ${\cal M}_1$. If $T_0$ and $T_1$ denote the goodness-of-fit test statistics associated to ${\cal M}_0$ and ${\cal M}_1$, respectively, then typically the difference $T_d = T_0 - T_1$ is used as a chi-square test statistic with degrees of freedom equal to the difference on the number of independent parameters estimated under the models ${\cal M}_0$ and ${\cal M}_1$. As in the case of the goodness-of-fit test, it is of interest to scale the statistic $T_d$ in order to improve its chi-square approximation in realistic, i.e., nonasymptotic and nonnormal, applications. In a recent paper, Satorra (1999) shows that the difference between two Satorra-Bentler scaled test statistics for overall model fit does not yield the correct SB scaled difference test statistic. Satorra developed an expression that permits scaling the difference test statistic, but his formula has some practical limitations, since it requires heavy computations that are notavailable in standard computer software. The purpose of the present paper is to provide an easy way to compute the scaled difference chi-square statistic from the scaled goodness-of-fit test statistics of models ${\cal M}_0$ and ${\cal M}_1$. A Monte Carlo study is provided to illustrate the performance of the competing statistics.

Analysis of dyes in illicit pills (amphetamine and derivatives)

The determination of dyes present in illicit pills is shown to be useful and easy-to-get information in strategic and tactical drug intelligence. An analytical strategy including solid-phase extraction (SPE) thin-layer chromatography (TLC) and capillary zone electrophoresis equipped with a diode array detector (CZE-DAD) was developed to identify and quantify 14 hydrosoluble, acidic, synthetic food dyes allowed in the European Community. Indeed, these may be the most susceptible dyes to be found in illicit pills through their availability and easiness of use. The results show (1) that this analytical method is well adapted to small samples such as illicit pills, (2) that most dyes actually found belong to hydrosoluble, acidic, synthetic food dyes allowed in the European Community, and (3) that this evidence turns out to be important in drug intelligence and may be assessed into a Bayesian framework.

Subgroup-specific structural variation across 1,000 medulloblastoma genomes.

Medulloblastoma, the most common malignant paediatric brain tumour, is currently treated with nonspecific cytotoxic therapies including surgery, whole-brain radiation, and aggressive chemotherapy. As medulloblastoma exhibits marked intertumoural heterogeneity, with at least four distinct molecular variants, previous attempts to identify targets for therapy have been underpowered because of small samples sizes. Here we report somatic copy number aberrations (SCNAs) in 1,087 unique medulloblastomas. SCNAs are common in medulloblastoma, and are predominantly subgroup-enriched. The most common region of focal copy number gain is a tandem duplication of SNCAIP, a gene associated with Parkinson's disease, which is exquisitely restricted to Group 4α. Recurrent translocations of PVT1, including PVT1-MYC and PVT1-NDRG1, that arise through chromothripsis are restricted to Group 3. Numerous targetable SCNAs, including recurrent events targeting TGF-β signalling in Group 3, and NF-κB signalling in Group 4, suggest future avenues for rational, targeted therapy.

Insulation System in an Integrated Motor Compressor

A high-speed and high-voltage solid-rotor induction machine provides beneficial features for natural gas compressor technology. The mechanical robustness of the machine enables its use in an integrated motor-compressor. The technology uses a centrifugal compressor, which is mounted on the same shaft with the high-speed electrical machine driving it. No gearbox is needed as the speed is determined by the frequency converter. The cooling is provided by the process gas, which flows through the motor and is capable of transferring the heat away from the motor. The technology has been used in the compressors in the natural gas supply chain in the central Europe. New areas of application include natural gas compressors working at the wellheads of the subsea gas reservoir. A key challenge for the design of such a motor is the resistance of the stator insulation to the raw natural gas from the well. The gas contains water and heavy hydrocarbon compounds and it is far harsher than the sales gas in the natural gas supply network. The objective of this doctoral thesis is to discuss the resistance of the insulation to the raw natural gas and the phenomena degrading the insulation. The presence of partial discharges is analyzed in this doctoral dissertation. The breakdown voltage of the gas is measured as a function of pressure and gap distance. The partial discharge activity is measured on small samples representing the windings of the machine. The electrical field behavior is also modeled by finite element methods. Based on the measurements it has been concluded that the discharges are expected to disappear at gas pressures above 4 – 5 bar. The disappearance of discharges is caused by the breakdown strength of the gas, which increases as the pressure increases. Based on the finite element analysis, the physical length of a discharge seen in the PD measurements at atmospheric pressure was approximated to be 40 – 120 m. The chemical aging of the insulation when exposed to raw natural gas is discussed based on a vast set of experimental tests with the gas mixture representing the real gas mixture at the wellhead. The mixture was created by mixing dry hydrocarbon gas, heavy hydrocarbon compounds, monoethylene glycol, and water. The mixture was chosen to be more aggressive by increasing the amount of liquid substances. Furthermore, the temperature and pressure were increased, which resulted in accelerated test conditions. The time required to detect severe degradation was thus decreased. The test program included a comparison of materials, an analysis of the e ects of di erent compounds in the gas mixture, namely water and heavy hydrocarbons, on the aging, an analysis of the e ects of temperature and exposure duration, and also an analysis on the e ect of sudden pressure changes on the degradation of the insulating materials. It was found in the tests that an insulation consisting of mica, glass, and epoxy resin can tolerate the raw natural gas, but it experiences some degradation. The key material in the composite insulation is the resin, which largely defines the performance of the insulation system. The degradation of the insulation is mostly determined by the amount of gas mixture di used into it. The di usion was seen to follow Fick’s second law, but the coe cients were not accurately defined. The di usion was not sensitive to temperature, but it was dependent upon the thermodynamic state of the gas mixture, in other words, the amounts of liquid components in the gas. The weight increase observed was mostly related to heavy hydrocarbon compounds, which act as plasticizers in the epoxy resin. The di usion of these compounds is determined by the crosslink density of the resin. Water causes slight changes in the chemical structure, but these changes do not significantly contribute to the aging phenomena. Sudden changes in pressure can lead to severe damages in the insulation, because the motion of the di used gas is able to create internal cracks in the insulation. Therefore, the di usion only reduces the mechanical strength of the insulation, but the ultimate breakdown can potentially be caused by a sudden drop in the pressure of the process gas.

Tabular cusum control charts of chemical variables applied to the control of surface water quality

The aim of this study was to evaluate the application possibility of tabular CUSUM control charts in the quality control of chemical variables in surface water. It was performed bibliographic and field research to collect water samples from 2003 to 2009, totaling 30 samples, some monthly and others semi-annual in order to observe the variables that regulate water quality. It was found that these charts may be applied to control the quality of river water; showing to be effective in the perception of changes during the process, especially for small samples (n=1) which there is no repetition as in this research. It was also concluded that the Mandurim River does not presents significant levels of pollution.

Explorations and comparisons of actual, ideal, and ought forgiveness definitions : a Q-methodological study /

Numerous definitions of forgiveness have been proposed in the literature (e.g.. North, 1987; Enright, Freedman & Rique, 1998), most ofwhich are based on religious or philosophical notions, rather than on empirical evidence. Definitions employed by researchers have typically set very high standards for forgiveness. This research was designed to investigate the possibility that these definitions describe an ideal of forgiveness and may not reflect laypersons' beliefe and experiences. Using Higgins' Self-Discrepancy Theory as a fiamework, three types of forgiveness beliefs were investigated: actual, ideal, and ought Q-methodology (which permits intensive study ofphenomena in small samples) was employed to examine and compare participants' beliefs about forgiveness across these domains. Thirty participants (20 women), 25 to 78 years of age, were recruited firom the community. They were asked to sort a set of66 statements about forgiveness according to their level of agreement with each statement This process was repeated three times, with the goal of modelling participants' actual experiences, their ideals, and how they believed forgiveness ought to be. Three perspectives on forgiveness emerged across the domains: forgiveness as motivated by religious beliefs, reconciliation-focussed forgiveness, and conflicted forgiveness. These perspectives indicated that, for many participants, the definitions presented in the literature may coincide with their beliefs about how forgiveness would ideally be and should be, as well as with their experiences of forgiveness; however, a large number of participants' experiences of, and beliefs about, forgiveness do not conform to the standards set out in the literature, and to exclude these participants' experiences and beliefs would mean overlooking what forgiveness means to a large portion of people. Results of this study indicate that researchers need to keep an open mind about what forgiveness may mean to their participants.

Behavioural, mensural, and ecological correlates of polygyny in the eastern meadowlark (Sturnella magna)

During 1982 and 1983 I studied male attributes and attributes of the territory of male Eastern Meadowlarks (Sturnella magna) in order to determine whether there was a correlation between any of the attributes investigated and the number of females attracted by a male. Seventeen males, nine of which were polygynous and eight monogamous, were studied in 1982 and sixteen males.of which .. seven were polygynous and nine ~onogamous, were studied in 1983. The study was conducted in Short Hills Park, 10 km southwest of St. Catharines, Ontario and was designed to compare two hypotheses: the "sexy son" hypothesis (Weatherhead and Robertson,1977) and the polygyny threshold model (Verner and Willson,1966, Orians, 1969). Male attributes investigated were male size and song behaviour. Six measures of male size were taken: weight, flattened and natural wing chord length, culmen length, bill depth and length of the tarsometatarsus. In 1983 song repertoire size and song versatility measures were investigated. Attributes of the territory studied were: territory size, density of plant stems, percentage plant cover and measures of vegetation structure. In 1983 Arthropods were collected from each territory and sorted according to taxonomic group and size. During 1983, territory attributes were sampled twice, once early and once later in the nesting season. Analysis of data involved univariate comparisons between monogamous and polygynous males using T-tests and multivariate comparisons were made using discriminant function analysis (DFA) and principle components analysis (PCA).No correlations were found between the number of females attracted with, .ny measure of male size or with me, .sures of song versatili or size of song repertoire. Also no correlation was found between terri size and the number of females nesting on a terri . Some attributes of the male's terri id distinguish between monog,mous and po s males of thistudy. Analysis of Arthropod numbers showed that e~ .eran counts were significantly great~r on polygynous territories, a1 the total numb~rs of Arthropods collected showed no s fico .nt differences between territories of monogamous and po males. DFA chose ear teran and Hymenopteran counts as multivariate discriminators; both variables we' e more vegetation revealed that there were no univariate differences between the two groups of males fOT 1982 stem densities, but ~ spp. and Solidago spp. were chosen DFA as multivariate discriminators. The total number of plant stems and of Vicia spp. stems were s ficantly the early 1983 ing on monogamous territories for however DFA found no multivariate discriminators" Variables concerned with the overall aspects of vegetation structure showed significant differences between territories of monogamous and polygynous males. DFA of the 1982 sampling of vegetation structure showed significantly greater mat depth and vegetation height on polygynous territories, a finding which was not supported, however, by peA. For the early 1983 sampling period, plant height was greater on polygynous territories. Multivariate analysis identified greater green cover on polygynous territories, greater ground cover on monogamous territories, and greater depth of mat material on monogamous territories as discriminators between territories of monogamous and polygynous males. A DFA on the major variables of the study showed no significant difference between the territories of monogamous and polygynous male Meadowlarks. Of the correlations found, some were for non-prey Arthr~ods, for cover plants with very small samples sizes, or for variables which were greater for monogamous males during one sampling period and polygynous males during the next. While multivariate discriminators were found, peA showed no grouping of monogamous or polygynous males according to any of the variables investigated. On the basis of the univariate and multivariate analysis of major variables, I concluded that there were no correlations between the number of females attracted with male attributes and no unambiguous correlation with attributes of the territory. My study does not unequivocally support either the "sexy son" or the polygyny threshold hypothesis.

Estimating the Tobit Model with Serial Correlation: an Operational Approach

Several Authors Have Discussed Recently the Limited Dependent Variable Regression Model with Serial Correlation Between Residuals. the Pseudo-Maximum Likelihood Estimators Obtained by Ignoring Serial Correlation Altogether, Have Been Shown to Be Consistent. We Present Alternative Pseudo-Maximum Likelihood Estimators Which Are Obtained by Ignoring Serial Correlation Only Selectively. Monte Carlo Experiments on a Model with First Order Serial Correlation Suggest That Our Alternative Estimators Have Substantially Lower Mean-Squared Errors in Medium Size and Small Samples, Especially When the Serial Correlation Coefficient Is High. the Same Experiments Also Suggest That the True Level of the Confidence Intervals Established with Our Estimators by Assuming Asymptotic Normality, Is Somewhat Lower Than the Intended Level. Although the Paper Focuses on Models with Only First Order Serial Correlation, the Generalization of the Proposed Approach to Serial Correlation of Higher Order Is Also Discussed Briefly.

Sampling Interval and estimated Betas : Implications for the Presence of Transitory Components in Stock Prices

We provide a theoretical framework to explain the empirical finding that the estimated betas are sensitive to the sampling interval even when using continuously compounded returns. We suppose that stock prices have both permanent and transitory components. The permanent component is a standard geometric Brownian motion while the transitory component is a stationary Ornstein-Uhlenbeck process. The discrete time representation of the beta depends on the sampling interval and two components labelled \"permanent and transitory betas\". We show that if no transitory component is present in stock prices, then no sampling interval effect occurs. However, the presence of a transitory component implies that the beta is an increasing (decreasing) function of the sampling interval for more (less) risky assets. In our framework, assets are labelled risky if their \"permanent beta\" is greater than their \"transitory beta\" and vice versa for less risky assets. Simulations show that our theoretical results provide good approximations for the means and standard deviations of estimated betas in small samples. Our results can be perceived as indirect evidence for the presence of a transitory component in stock prices, as proposed by Fama and French (1988) and Poterba and Summers (1988).

Bootstrapping Autoregressions with Conditional Heteroskedasticity of Unknown Form

Conditional heteroskedasticity is an important feature of many macroeconomic and financial time series. Standard residual-based bootstrap procedures for dynamic regression models treat the regression error as i.i.d. These procedures are invalid in the presence of conditional heteroskedasticity. We establish the asymptotic validity of three easy-to-implement alternative bootstrap proposals for stationary autoregressive processes with m.d.s. errors subject to possible conditional heteroskedasticity of unknown form. These proposals are the fixed-design wild bootstrap, the recursive-design wild bootstrap and the pairwise bootstrap. In a simulation study all three procedures tend to be more accurate in small samples than the conventional large-sample approximation based on robust standard errors. In contrast, standard residual-based bootstrap methods for models with i.i.d. errors may be very inaccurate if the i.i.d. assumption is violated. We conclude that in many empirical applications the proposed robust bootstrap procedures should routinely replace conventional bootstrap procedures for autoregressions based on the i.i.d. error assumption.

Methods to Estimate Dynamic Stochastic General Equilibrium Models

This paper employs the one-sector Real Business Cycle model as a testing ground for four different procedures to estimate Dynamic Stochastic General Equilibrium (DSGE) models. The procedures are: 1 ) Maximum Likelihood, with and without measurement errors and incorporating Bayesian priors, 2) Generalized Method of Moments, 3) Simulated Method of Moments, and 4) Indirect Inference. Monte Carlo analysis indicates that all procedures deliver reasonably good estimates under the null hypothesis. However, there are substantial differences in statistical and computational efficiency in the small samples currently available to estimate DSGE models. GMM and SMM appear to be more robust to misspecification than the alternative procedures. The implications of the stochastic singularity of DSGE models for each estimation method are fully discussed.

Lesser Scaup Population Dynamics: What Can Be Learned from Available Data?

Populations of Lesser Scaup (Aythya affinis) have declined markedly in North America since the early 1980s. When considering alternatives for achieving population recovery, it would be useful to understand how the rate of population growth is functionally related to the underlying vital rates and which vital rates affect population growth rate the most if changed (which need not be those that influenced historical population declines). To establish a more quantitative basis for learning about life history and population dynamics of Lesser Scaup, we summarized published and unpublished estimates of vital rates recorded between 1934 and 2005, and developed matrix life-cycle models with these data for females breeding in the boreal forest, prairie-parklands, and both regions combined. We then used perturbation analysis to evaluate the effect of changes in a variety of vital-rate statistics on finite population growth rate and abundance. Similar to Greater Scaup (Aythya marila), our modeled population growth rate for Lesser Scaup was most sensitive to unit and proportional change in adult female survival during the breeding and non-breeding seasons, but much less so to changes in fecundity parameters. Interestingly, population growth rate was also highly sensitive to unit and proportional changes in the mean of nesting success, duckling survival, and juvenile survival. Given the small samples of data for key aspects of the Lesser Scaup life cycle, we recommend additional research on vital rates that demonstrate a strong effect on population growth and size (e.g., adult survival probabilities). Our life-cycle models should be tested and regularly updated in the future to simultaneously guide science and management of Lesser Scaup populations in an adaptive context.