101 resultados para conditional


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This analysis was stimulated by the real data analysis problem of householdexpenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that tryto add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spendingexcluding alcohol/tobacco similar for teetotal and non-teetotal households?In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than onecomponent, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durableswithin the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small.While this analysis is based on around economic data, the ideas carry over tomany other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

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Són quatre els objectius d’aquesta recerca: (1) determinar la taxa de reincidència administrativa dels sotmesos a formes substitutives a la presó; (2) descriure les relacions significatives entre determinades variables individuals i d’historial delictiu i la seva reincidència; (3) comparar taxes de reincidència entre penats que compleixen treballs en benefici de la comunitat (TBC) i suspensions de condemna amb imposició de regles de conducta; (4) comparar les taxes de reincidència de persones amb mesures alternatives amb les de reincidència penitenciària. Per reincidència administrativa s’entén entrar a presó o complir una nova mesura penal alternativa per un nou delicte durant el període de seguiment. Per assolir els objectius, han estat estudiades 329 persones que, al llarg de l’any 2000, van finalitzar, com a mínim, un TBC o una obligació imposada en el marc de la suspensió de la pena. El seguiment ha estat conclòs els 30 de juny de 2005. Els resultats indiquen que: (1) la taxa de reincidència administrativa dels sotmesos a MPA és inferior a la taxa de reincidència penitenciària; (2) no hi ha diferències rellevants pel que fa a la reincidència administrativa entre els homes i les dones estudiades, tampoc entre estrangers i espanyols; (3) presenten una major taxa de reincidència els que tenen antecedents de qualsevol tipus, i encara una taxa major els que tenen antecedents penitenciaris.

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There are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) in the current energy market framework. Environmental policy issues have become more and more important for fossil-fuelled power plants and they have to be considered in their management, giving rise to emission limitations. This work allows to investigate the influence of both the allowances and emission reduction plan, and the incorporation of the derivatives medium-term commitments in the optimal generation bidding strategy to the day-ahead electricity market. Two different technologies have been considered: the coal thermal units, high-emission technology, and the combined cycle gas turbine units, low-emission technology. The Iberian Electricity Market and the Spanish National Emissions and Allocation Plans are the framework to deal with the environmental issues in the day-ahead market bidding strategies. To address emission limitations, some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), have been extended. This study offers to electricity generation utilities a mathematical model to determinate the individual optimal generation bid to the wholesale electricity market, for each one of their generation units that maximizes the long-run profits of the utility abiding by the Iberian Electricity Market rules, the environmental restrictions set by the EU Emission Trading Scheme, as well as the restrictions set by the Spanish National Emissions Reduction Plan. The economic implications for a GenCo of including the environmental restrictions of these National Plans are analyzed and the most remarkable results will be presented.

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This paper proposes an empirical framework to study the effects of a policy regime change defined as an unpredictable and permanent change in the policy parameters. In particular I show how to make conditional forecast and perform impulse response functions and counterfactual analysis. As an application, the effects of changes in fiscal policy rules in the US are investigated. I find that discretionary fiscal policy has become more countercyclical over the last decades. In absence of such a change, surplus would have been higher, debt lower and output gap more volatile but only until mid 80s. An increase in the degree of counter-cyclicality of fiscal policy has a positive effect on output gap in periods where the level of debt-to-GDP ratio is low and a zero or negative effect when the ratio is high. This explains why a more countercylical stance of the systematic fiscal policy taking place in 2008:II is predicted to be rather ineffective for recovering from the crisis.

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One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By anessential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur inmany compositional situations, such as household budget patterns, time budgets,palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful insuch situations. From consideration of such examples it seems sensible to build up amodel in two stages, the first determining where the zeros will occur and the secondhow the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

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Report for the scientific sojourn carried out at the University of Aarhus, Denmark, from 2010 to 2012. Reprogramming of cellular metabolism is a key process during tumorigenesis. This metabolic adaptation is required in order to sustain the energetic and anabolic demands of highly proliferative cancer cells. Despite known for decades (Warburg effect), the precise molecular mechanisms regulating this switch remained unexplored. We have identify SIRT6 as a novel tumor suppressor that regulates aerobic glycolysis in cancer cells. Importantly, loss of this sirtuin in non-transformed cells leads to tumor formation without activation of known oncogenes, indicating that SIRT6 functions as a first-hit tumor suppressor. Furthermore, transformed SIRT6-deficient cells display increased glycolysis and tumor growth in vivo, suggesting that SIRT6 plays a role in both establishment and maintenance of cancer. We provide data demonstrating that the glycolytic switch towards aerobic glycolysis is the main driving force for tumorigenesis in SIRT6-deficient cells, since inhibition of glycolysis in these cells abrogates their tumorigenic potential. By using a conditional SIRT6-targeted allele, we show that deletion of SIRT6 in vivo increases the number, size and aggressiveness of tumors, thereby confirming a role of SIRT6 as a tumor suppressor in vivo. In addition, we describe a new role for SIRT6 as a regulator of ribosome biogenesis by co-repressing MYC transcriptional activity. Therefore, by repressing glycolysis and ribosomal gene expression, SIRT6 inhibits tumor establishment and progression. Further validating these data, SIRT6 is selectively downregulated in several human cancers, and expression levels of SIRT6 predict both prognosis and tumor-free survival rates, highlighting SIRT6 as a critical modulator of cancer metabolism. Our results provide a potential Achilles’ hill to tackle cancer metabolism.

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Background: Few studies have used longitudinal ultrasound measurements to assess the effect of traffic-related air pollution on fetal growth.Objective: We examined the relationship between exposure to nitrogen dioxide (NO2) and aromatic hydrocarbons [benzene, toluene, ethylbenzene, m/p-xylene, and o-xylene (BTEX)] on fetal growth assessed by 1,692 ultrasound measurements among 562 pregnant women from the Sabadell cohort of the Spanish INMA (Environment and Childhood) study.Methods: We used temporally adjusted land-use regression models to estimate exposures to NO2 and BTEX. We fitted mixed-effects models to estimate longitudinal growth curves for femur length (FL), head circumference (HC), abdominal circumference (AC), biparietal diameter (BPD), and estimated fetal weight (EFW). Unconditional and conditional SD scores were calculated at 12, 20, and 32 weeks of gestation. Sensitivity analyses were performed considering time–activity patterns during pregnancy.Results: Exposure to BTEX from early pregnancy was negatively associated with growth in BPD during weeks 20–32. None of the other fetal growth parameters were associated with exposure to air pollution during pregnancy. When considering only women who spent 2 hr/day in nonresidential outdoor locations, effect estimates were stronger and statistically significant for the association between NO2 and growth in HC during weeks 12–20 and growth in AC, BPD, and EFW during weeks 20–32.Conclusions: Our results lend some support to an effect of exposure to traffic-related air pollutants from early pregnancy on fetal growth during mid-pregnancy.

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The intensity of parental investments in child care time is expected to vary across families with different norms and time-constraints. Additionally, it should also differ across countries, since the abilities of parents to harmonize family and work vary by national context. In our opinion, however, this question remains inconclusive for two main reasons: 1) only some countries have been studied from a comparative approach; 2) previous studies have not paid enough attention to the analysis of how the conditional effects of education and employment affect parental investments.In this paper we used nationally representative time-use data from Denmark, Flanders, Spain and the United Kingdom (N=4,031) to explore how employment and education predict variations in child care time. IN Britain and Spain employment has a strong negative effect on fathers’ child care, but a weaker one in Flanders and particularly in Denmark. In contrast, maternal employment has a strong negative impact in all four countries. Education increases child care time significantly only among Spanish mothers and fathers, as well as British mothers. Nonetheless, we find that college-educated mothers under similar time-constraints increase substantially their expected child care time in Britain, Flanders and Spain; for fathers we find a more mixed picture. Routine child care activities are more sensitive to both maternal and paternal employment than interactive child care activities. Finally, we observe that working a public sector job generally increases a total time allocated to parental care, controlling for several demographic and socioeconomic variables.

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We analyze second birth decisions within the theoretical framework of joint household decision making, comparing two countires that represent the international extremes in terms of women's career behaviour, Denmark and Spain. Using all 8 ECHP panels we apply discrete time estimations of the likelihood of a second birth and show that in Spain, fertility behaviour continues to conform to the classic "Becker model" while in Denmark we identify a radically new behavioral pattern according to which career-women's fertility is conditional of their partners' contribution to care for the children.

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Can rules be used to shield public resources from political interference? The Brazilian constitution and national tax code stipulate that revenue sharing transfers to municipal governments be determined by the size of counties in terms of estimated population. In this paper I document that the population estimates which went into the transfer allocation formula for the year 1991 were manipulated, resulting in significant transfer differentials over the entire 1990's. I test whether conditional on county characteristics that might account for the manipulation, center-local party alignment, party popularity and the extent of interparty fragmentation at the county level are correlated with estimated populations in 1991. Results suggest that revenue sharing transfers were targeted at right-wing national deputies in electorally fragmented counties as well as aligned local executives.

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This paper estimates the effect of judicial institutions on governance at the local level in Brazil. Our estimation strategy exploits a unique institutional feature of state judiciary branches which assigns prosecutors and judges to the most populous among contiguous counties forming a judiciary district. As a result of this assignment mechanism there are counties with nearly identical populations, some with and some without local judicial presence, which we exploit to impute counterfactual outcomes. Conditional on observable county characteristics, offenses per civil servant are about 35% lower in counties that have a local seat of the state judiciary. The lower incidence of infractions stems mostly from fewer violations of financial management regulations by local administrators, fewer instances of problems in project execution and project managment, fewer cases of non-existent or ineffective civil society oversight and fewer cases of improper handling of remittances to local residents.

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This paper breaks new ground toward contractual and institutional innovation in models of homeownership, equity building, and mortgage enforcement. Inspired by recent developments in the affordable housing sector and in other types of public financing schemes, this paper suggests extending institutional and financial strategies such as timeand place-based division of property rights, conditional subsidies, and credit mediation to alleviate the systemic risks of mortgage foreclosure. Alongside a for-profit shared equity scheme that would be led by local governments, we also outline a private market shared equity model, one of bootstrapping home buying with purchase options.

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We discuss some practical issues related to the use of the Parameterized Expectations Approach (PEA) for solving non-linear stochastic dynamic models with rational expectations. This approach has been applied in models of macroeconomics, financial economics, economic growth, contracttheory, etc. It turns out to be a convenient algorithm, especially when there is a large number of state variables and stochastic shocks in the conditional expectations. We discuss some practical issues having to do with the application of the algorithm, and we discuss a Fortran program for implementing the algorithm that is available through the internet.We discuss these issues in a battery of six examples.

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The spectacular failure of top-rated structured finance products has broughtrenewed attention to the conflicts of interest of Credit Rating Agencies (CRAs). We modelboth the CRA conflict of understating credit risk to attract more business, and the issuerconflict of purchasing only the most favorable ratings (issuer shopping), and examine theeffectiveness of a number of proposed regulatory solutions of CRAs. We find that CRAs aremore prone to inflate ratings when there is a larger fraction of naive investors in the marketwho take ratings at face value, or when CRA expected reputation costs are lower. To theextent that in booms the fraction of naive investors is higher, and the reputation risk forCRAs of getting caught understating credit risk is lower, our model predicts that CRAs aremore likely to understate credit risk in booms than in recessions. We also show that, due toissuer shopping, competition among CRAs in a duopoly is less efficient (conditional on thesame equilibrium CRA rating policy) than having a monopoly CRA, in terms of both totalex-ante surplus and investor surplus. Allowing tranching decreases total surplus further.We argue that regulatory intervention requiring upfront payments for rating services (beforeCRAs propose a rating to the issuer) combined with mandatory disclosure of any ratingproduced by CRAs can substantially mitigate the con.icts of interest of both CRAs andissuers.

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We compare two methods for visualising contingency tables and developa method called the ratio map which combines the good properties of both.The first is a biplot based on the logratio approach to compositional dataanalysis. This approach is founded on the principle of subcompositionalcoherence, which assures that results are invariant to considering subsetsof the composition. The second approach, correspondence analysis, isbased on the chi-square approach to contingency table analysis. Acornerstone of correspondence analysis is the principle of distributionalequivalence, which assures invariance in the results when rows or columnswith identical conditional proportions are merged. Both methods may bedescribed as singular value decompositions of appropriately transformedmatrices. Correspondence analysis includes a weighting of the rows andcolumns proportional to the margins of the table. If this idea of row andcolumn weights is introduced into the logratio biplot, we obtain a methodwhich obeys both principles of subcompositional coherence and distributionalequivalence.