Pedro Macedo's research while affiliated with University of Aveiro and other places
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Publications (30)
The connection between Earth’s global temperature and carbon dioxide (CO2) emissions is one of the highest challenges in climate change science since there is some controversy about the real impact of CO2 emissions on the increase of global temperature. This work contributes to the existing literature by analyzing the relationship between CO2 emiss...
In a high tax burden environment related to electricity prices in Portugal, it is needed to establish fiscal and economic-political measures to lower the electrical price weight imposed on both households and non-households. The most effective way is to first be aware of its determinants. This paper contributes to the existent literature by analyzi...
This study examines the nexus between energy intensity (EI), gross domestic product (GDP) and carbon emissions from electricity generation (CEEG) in Iran, where energy intensity has been increasing during the last decades. Iran holds one of the world’s largest fossil fuel reserves and its electricity sector is highly dependent on natural gas. In re...
Using a unique or common measure of energy poverty is very limited for the true clas�sifcation of a household being in energy poverty. Thus, this study proposes a compos�ite indicator, whose weights will be determined from the estimation of two relationships using a robust and stable methodology based on information theory. This work considers two...
A variable selection procedure in regression analysis using a normalized entropy measure was firstly proposed in 1996, by Amos Golan, George Judge and Douglas Miller, in the book Maximum Entropy Econometrics – Robust Estimation with Limited Data. To the best of the authors’ knowledge, the idea has not been explored in the literature since then, des...
The analysis of big data, namely in inhomogeneous large-scale data under the regression analysis context, is a research topic with growing interest in recent years, where bagging and magging are two well-known aggregation procedures. As this kind of data may be recorded in different time regimes or may be taken from multiple sources, inhomogeneitie...
The maximum entropy bootstrap for time series is a technique that creates a large number of replicates, as elements of an ensemble, for inference purposes, which satisfies the ergodic and the central limit theorems. As an alternative to the use of traditional techniques, this work proposes generalized maximum entropy for the estimation of parameter...
The maximum entropy bootstrap for time series is applied in this study to investigate the nexus between carbon emissions from electricity generation and the gross domestic product, using a bivariate framework for eight Middle Eastern countries between 1995 and 2017. The sample under study includes oil-producing countries such as Bahrain, Iran, Iraq...
The objective of this paper is to analyse the retail banking behaviour in Portugal (2008–2010, 2011–2013 and 2014–2016), by taking into account the financial and economic assistance programme (FEAP) – monitored by the European Commission, the European Central Bank and the International Monetary Fund – that Portugal went through and that started in...
In linear regression models where there are no relationships between the dependent variable and each of the potential explanatory variables-a usual scenario in real-world problems-some of them can be identified as relevant by standard statistical procedures. This incorrect identification is usually known as Freedman’s paradox. To avoid this disturb...
Cities and living standards contribute intensively to air pollution, an environmental risk factor which causes diseases. Recently, in developed countries, the majority of cities has grown rapidly and has experienced increasing environmental problems. In this article we analyze the effect of urban air pollution considering the available data for the...
It was already in the fifties of the last century that the relationship between information theory, statistics and maximum entropy was established, following the works of Kullback, Leibler, Lindley and Jaynes. However, the applications were restricted to very specific domains and it was not until recently that the convergence between information pr...
The literature on incentive-based regulation in the electricity sector indicates that the size of this sector in a country constrains the choice of frontier methods as well as the model specification itself to measure economic efficiency of regulated firms. The aim of this study is to propose a stochastic frontier approach with maximum entropy esti...
This study aims to estimate the agricultural economic-environmental efficiency (Eco-efficiency) for European countries. Eco-efficiency is obtained by Data Envelopment Analysis and Stochastic Frontier Analysis using a Generalized Maximum Entropy approach. Agriculture Gross Value Added (GVA) is considered as the desirable output and Greenhouse Gas (G...
This article intends to compute agriculture technical efficiency scores of 27 European countries during the period 2005–2012, using both data envelopment analysis (DEA) and stochastic frontier analysis (SFA) with a generalized cross-entropy (GCE) approach, for comparison purposes. Afterwards, by using the scores as dependent variable, we apply quan...
Car safety is an essential feature of marketing strategies for automobile companies. In this work, a statistical analysis on crash tests is conducted based on data available from European New Car Assessment Programme (Euro NCAP). The research work developed in this chapter presents a statistical analysis of the information produced by Euro NCAP, us...
The main purpose of this study is to present an alternative benchmarking approach that can be used by national regulators of utilities. It is widely known that the lack of sizeable data sets limits the choice of the benchmarking method and the specification of the model to set price controls within incentive-based regulation. Ill-posed frontier mod...
This study involves several theories, namely: the theory of reasoned action, the technology acceptance model, the theory of planned behavior and the internet banking acceptance model. It aims to understand the relationships between the virtual atmosphere and emotional states, how the individual characteristics (social identity, altruism and telepre...
In this paper, the Ridge-GME parameter estimator, which combines Ridge Regression and Generalized Maximum Entropy, is improved in order to eliminate the subjectivity in the analysis of the ridge trace. A serious concern with the visual inspection of the ridge trace to define the supports for the parameters in the Ridge-GME parameter estimator is th...
This study aims to evaluate the resource and environment efficiency problem of European countries. We specify a new stochastic frontier model where Gross Domestic Product (GDP) is considered as the desirable output and Greenhouse Gases (GHG) emissions as the undesirable output. Capital, Labour, Fossil fuels and Renewable Energy consumption are rega...
It is well-known that under fairly conditions linear regression becomes a powerful statistical tool. In practice, however, some of these conditions are usually not satisfied and regression models become ill-posed, implying that the application of traditional estimation methods may lead to non-unique or highly unstable solutions. Addressing this iss...
Although the theory of state-contingent production is well-established, the empirical implementation of this approach is still in an infancy stage. The possibility of finding a large number of states of nature, few observations per state and models affected by collinearity have led some researchers to claim the urgent need to develop robust estimat...
Este livro de exercícios resolvidos dirige-se a todos os que necessitam de melhorar o seu desempenho em estatística elementar, isto é, a todos os estudantes de graduação/pós-graduação que procuram melhorar o seu desempenho académico, bem como a todos aqueles que, na sua vida profissional, são confrontados com a necessidade de saber aplicar técnicas...
In this article, a new method to estimate the ridge parameter, based on the ridge trace and an analytical method borrowed from maximum entropy, is presented. The performance of the new estimator is illustrated through a Monte Carlo simulation study and an empirical application to the well-known Portland cement data set.
In this article, a general class of estimators for the linear regression model affected by outliers and collinearity is introduced and studied in some detail. This class of estimators combines the theory of light, maximum entropy, and robust regression techniques. Our theoretical findings are illustrated through a Monte Carlo simulation study.
In this paper, an empirical application of the generalized maximum entropy estimator in a stochastic production frontier model with a translog specification is discussed to investigate technical efficiency in a wine region of Portugal. The empirical results indicate technical progress over the time period of the sample and an increasing technical i...
Citations
... The excessive use of fossil fuels has caused a significant increase in the emission of CO 2 greenhouse gases, which has seriously damaged the carbon cycle balance in nature [68][69][70]. However, CO 2 itself is a carbon resource, which can be used as a raw material for the preparation of carbon-based compounds. ...
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... Thus, the maximum entropy bootstrap, by not imposing parametric restrictions, allows for greater freedom in statistical modeling and inference through the replications of the original time series and the subsequent construction of confidence intervals for the model parameters. A recent proposal to improve the estimation of parameters is discussed in [40]. Moreover, since the inference is based on the analysis of confidence intervals, the use and possible misinterpretations of p-values are avoided, following recent recommendations from the statistical community (e.g., [41]). ...
... This is a solemn commitment by China to address climate change. Reducing energy intensity is an effective way to control carbon emissions (Zeinab et al., 2022). Energy intensity is the energy consumption ratio to output, reflecting the combined energy-use efficiency of different regions and industries. ...
... On the other hand, there are studies by Altinay and Karagol who, using the Granger Hsiao method for the 1950-2000 period in Turkey, did not find a causal relationship between energy consumption and GDP. Thus, the conclusions from the research differ depending on the methodology used by the researchers and the periods adopted [16]. ...
... Finally, this special section on innovation also includes an article on competitive dynamics in which Rosário et al. (2021) analyzed the Portuguese retail banking industry in three different time periods: 2008-2010; 2011-2013; and 2014-2016. The novelty of their approach is that they took into account the financial and economic assistance program (FEAP), which is monitored by the European Commission, the European Central Bank, and the International Monetary Fund, because of the difficult economic situation that Portugal underwent in 2011. ...
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... The information index, defined as 1 − S(p) , is a measure of uncertainty reduction and it is used in this work to establish the weights of each variable. It is important to note that no kind of judgment (including possible cut-off values; how irrelevant a variable is to justify its elimination from the model?) is used in this work to make a variable selection with normalized entropy; e.g., Macedo (2020). The novelty here is that the measure is used to define weights from the information content of different models and different variables, without any exclusion of models or variables. ...
... This is because the concept of eco-efficiency favors more realistic policy measures that can limit domestic economic activity to a lesser extent and lead to higher levels of sustainability (Kuosmanen and Kortelainen 2005). The existing methods for measuring eco-efficiency mainly use the data envelopment analysis (DEA) method (Moutinho et al. 2020) as it solves the problem of inconsistent units of various resource consumption and pollution emissions in the eco-environmental impact item of eco-efficiency measurement indexes. In this study, a three-stage DEA model is used to measure urban eco-efficiency. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/367788939071489-1464699124559_Q64/Victor-Moutinho.jpg)
... The translog functional form, which is the most common form for technology is used for estimation of the Cobb-Douglas production function. Recent examples of estimation with translog forms can be seen in Berger et al. (2009), Vu and Turnell (2010), Pessarossi and Weill (2015), and Silva et al. (2019). Taking natural logs of the production function yields the translog form to be estimated: ...
... The research theme of foreign scholars has rarely been CLUE, but they have contributed by measuring the efficiency in the process of multi-scale and multi-regional agricultural production. The relevant research results mainly cover the calculations of agricultural or crop production efficiency [48][49][50][51][52][53][54][55] and the identification of influencing factors [56][57][58][59][60]. In terms of methods, the DEA, SFA, and other mathematical models have mostly been used to calculate the CLUE, but spatial autocorrelation analysis has rarely been used to explore the spatial differentiation features of CLUE [61,62]. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/273621293727744-1442247808056_Q64/Margarita-Robaina.jpg)
... Richterová et al. evaluated the AEE in V4 regions through DEA-Malmquist analysis [16]. Moutinho et al. adopted the DEA and generalized maximum entropy approach to estimate the AEE in Europe [17]. Silva et al. combined the DEA methodology with double bootstrap and truncated regression (DEA-BTR) to estimate the AEE in the municipalities of the Amazon biome [18]. ...
