Determinants of reelection in Portuguese municipal elections

This Work Project investigates the determinants of reelection using data on the 278 Portuguese mainland municipalities for the period 1976-2009. We implement a logit fixed effect model to control for the municipalities’ unobserved characteristics that remain constant over time. Political variables, such as the vote share of the incumbent’s party in previous election, the number of mayor’s consecutive mandates and abstention rate, are found to be relevant in explaining incumbent’s reelection. Moreover, as to the mayor’s individual characteristics, age and education contribute to explain reelection prospects. We also provide weak evidence that a higher degree of fiscal autonomy increases political turnover and that the good economic prospects of the municipality positively affect reelection. Finally, the residents’ level of education and the size of the municipal population have an explanatory power on mayor’s reelection. We perform several robustness checks to confirm these results.

Correcting the fixed-effect estimator for endogenous switching

In this paper, we propose a two-step estimator for panel data models in which a binary covariate is endogenous. In the first stage, a random-effects probit model is estimated, having the endogenous variable as the left-hand side variable. Correction terms are then constructed and included in the main regression.

Credit default swap (CDS) prediction model & trading strategy

This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.

Designs and model effects definitions in the initial stage of a plant breeding program

The objective of this work was to compare the relative efficiency of initial selection and genetic parameter estimation, using augmented blocks design (ABD), augmented blocks twice replicated design (DABD) and group of randomised block design experiments with common treatments (ERBCT), by simulations, considering fixed effect model and mixed model with regular treatment effects as random. For the simulations, eight different conditions (scenarios) were considered. From the 600 simulations in each scenario, the mean percentage selection coincidence, the Pearsons´s correlation estimates between adjusted means for the fixed effects model, and the heritability estimates for the mixed model were evaluated. DABD and ERBCT were very similar in their comparisons and slightly superior to ABD. Considering the initial stages of selection in a plant breeding program, ABD is a good alternative for selecting superior genotypes, although none of the designs had been effective to estimate heritability in all the different scenarios evaluated.

A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

Supplementary tests of Masonboro Inlet fixed-bed model : hydraulic model investigation /

"General investigation of tidal inlets; a program of research conducted jointly by U.S. Army Coastal Engineering Research Center, Fort Belvoir, Virginia [and] U.S. Army Engineer Waterways Experiment Station, Vicksburg, Mississippi."

Statnote 30 : The one-way analysis of variance (ANOVA):fixed effects model

In Statnote 9, we described a one-way analysis of variance (ANOVA) ‘random effects’ model in which the objective was to estimate the degree of variation of a particular measurement and to compare different sources of variation in space and time. The illustrative scenario involved the role of computer keyboards in a University communal computer laboratory as a possible source of microbial contamination of the hands. The study estimated the aerobic colony count of ten selected keyboards with samples taken from two keys per keyboard determined at 9am and 5pm. This type of design is often referred to as a ‘nested’ or ‘hierarchical’ design and the ANOVA estimated the degree of variation: (1) between keyboards, (2) between keys within a keyboard, and (3) between sample times within a key. An alternative to this design is a 'fixed effects' model in which the objective is not to measure sources of variation per se but to estimate differences between specific groups or treatments, which are regarded as 'fixed' or discrete effects. This statnote describes two scenarios utilizing this type of analysis: (1) measuring the degree of bacterial contamination on 2p coins collected from three types of business property, viz., a butcher’s shop, a sandwich shop, and a newsagent and (2) the effectiveness of drugs in the treatment of a fungal eye infection.

Financial distress, financial constraint and investment decision: Evidence from Brazil

This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.

The treatment of tardive dyskinesia: A systematic review and meta-analysis

This systematic review aimed to collate randomized controlled trials (RCTs) of various interventions used to treat tardive dyskinesia (TD) and, where appropriate, to combine the data for mete-analysis, Clinical trials were identified by electronic searches, handsearches and contact with principal investigators. Data were extracted independently by two reviewers, for outcomes related to improvement, deterioration, side-effects and drop out rates. Data were pooled using the Mantel-Haenzel Odds Ratio (fixed effect model). For treatments that had significant effects, the number needed to treat (NNT) was calculated. From 296 controlled clinical trials, data were extracted from 47 trials. For most interventions, we could identify no RCT-derived evidence of efficacy. A meta-analysis showed that baclofen, deanol and diazepam were no more effective than a placebo. Single RCTs demonstrated a lack of evidence of any effect for bromocriptine, ceruletide, clonidine, estrogen, gamma linolenic acid, hydergine, lecithin, lithium, progabide, seligiline and tetrahydroisoxazolopyridinol. The meta-analysis found that five interventions were effective: L-dopa, oxypertine, sodium valproate, tiapride and vitamin E; neuroleptic reduction was marginally significant. Data from single RCTs revealed that insulin, alpha methyl dopa and reserpine were more effective than a placebo. There was a significantly increased risk of adverse events associated with baclofen, deanol, L-dopa, oxypertine and reserpine. Metaanalysis of the impact of placebo (n=485) showed that 37.3% of participants showed an improvement. Interpretation of this systematic review requires caution as the individual trials identified tended to have small sample sizes. For many compounds, data from only one trial were available, and where meta-analyses were possible, these were based on a small number of trials. Despite these concerns, the review facilitated the interpretation of the large and diverse range of treatments used for TD. Clinical recommendations for the treatment of TD are made, based on the availability of RCT-derived evidence, the strength of that evidence and the presence of adverse effects. (C) 1999 Elsevier Science B.V. All rights reserved.

Fiscal policy and reelection in Brazilian municipalities

This paper uses a new panel of more than 2,000 Brazilian municipalities over 13 years to analyze the influence of public expenditures on the probability of mayors` reelection. We examine Brazilian municipal elections from 1988 to 2000 using a logit fixed-effects model. The results suggest that mayors who spend more during their terms of office increase the probability of their own reelection or of a successor of the same political party. In particular, higher capital spending over the years preceding elections and current expenditures in election years are beneficial to Brazilian incumbent mayors.

The determinants of trade credit: a study of portuguese industrial companies

Despite the relevance of trade credit as a source of business financing, the topic is far from being considered exhausted, especially because there is no general and integrated theory explaining the causes and consequences of trade credit.Our research aims to contribute towards the literature that studies the determinants for granting and receiving trade credit. In this sequence, the present study seeks to empirically test some theories about the reasons why companies grant and receive commercial credit. For this purpose we apply a fixed effect model to a panel of 11 040 Portuguese industrial companies, of which 360 are large companies and the majority 10 680 are Small and Medium Enterprises (SME) for the period between 2003 and 2009. We conclude that large companies (with greater access to credit market) serve as financial intermediaries to their clients with less access to finance. In addition, it was observed that the supplier companies use trade credit as a legal means of price discrimination. Finally, financially constrained enterprises, especially in times of financial crisis, use commercial credit as an alternative source of funding, endorsing the hypothesis of substitution between trade credit and bank credit.