Ivette Luna- PhD in Electrical Eng.
- Professor (Full) at State University of Campinas (UNICAMP)
Ivette Luna
- PhD in Electrical Eng.
- Professor (Full) at State University of Campinas (UNICAMP)
Associate professor at the University of Campinas
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91
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Introduction
Ivette Luna received her M.Sc. and PhD degree in Electrical Engineering from the State University of Campinas (UNICAMP), Brazil, in 2003 and 2007, respectively. She is currently at the Institute of Economics-UNICAMP and is member of the Industrial Economics and Technology Center (NEIT) and the Agricultural Economics and Environment Center (NEA). The applied research that develops is based on dynamic simulation and models, SNA and quantitative methods within an evolutionary theoretical framework. Recently, special attention is given to Latin American issues and Economic Development.
Current institution
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Position
- Quantitative methods for Economists
Position
- Social Network Analysis
Position
- Statistics and introduction to econometrics
Publications
Publications (91)
During the 2000s and 2010s, the growth in sugar and ethanol production stimulated the expansion of sugarcane in new regions of Brazil, reducing the concentration in the state of São Paulo. This paper aims to investigate whether the rise in sugarcane production in peripheral areas has led to the growth of knowledge capabilities. In order to consider...
O artigo tem como objetivo precípuo analisar a associação entre complexidade econômica – mensurada pelo Índice de Complexidade Econômica – e desigualdade de renda – mensurada pelo Índice de Gini na América Latina. Para tanto, foi utilizado como recorte temporal o século XXI (2001 – 2017), período em que houve queda brusca de desigualdade de renda n...
In this work we analyse occupational profiles in the Brazilian workforce through data analysis. To achieve that, we implement NMF clustering over data provided by the Brazilian Ministry of Economy. Additionally, we make use of the data on probability of automation of occupations published in the work of Frey and Osborne, originally developed in the...
The study analyzes the growth and development opportunities for cities in the Brazilian state of São Paulo, considering economic complexity. Our hypothesis is that the structural heterogeneity in Brazil, and in São Paulo, creates regional inequality. Therefore, cities have different development trajectories depending on their current economic capac...
Public procurement is a key policy tool for promoting more sustainable agri-food systems. In Brazil, the National School Feeding Program (PNAE) has played an important role in integrating family farmers into institutional markets, yet various factors affect their participation. This study investigates the most important factors influencing family f...
Resumo A ciência global tem passado por transformações impulsionadas por inovações, colaborações internacionais e o uso crescente de ferramentas digitais. No Brasil, espera-se que essas mudanças sejam evidenciadas por meio de indicadores que captam as tendências da atividade científica nacional. Este trabalho analisa a produção científica na grande...
The purpose of this work is to investigate the factors influencing the adoption of price risk management tools by coffee farmers. The study also explores the risk perceptions of coffee farmers towards the severity degree of risk events. Results are based on primary data obtained from a sample of 385 coffee farmers. Findings indicated that the three...
Linear models are widely used to perform time series forecasting. The Autoregressive models stand out, due to their simplicity in the parameters adjustment based on close-form solution. The Autoregressive and Moving Average models (ARMA) and Infinite Impulse Response filters (IIR) are also good alternatives, since they are recurrent structures. How...
A pesquisa analisa as desigualdades de gênero na indústria de transformação paulista, visando entender o papel da mulher nesse setor de atuação, frente às inovações trazidas pela Indústria 4.0. Com os dados da RAIS do estado de São Paulo para os anos de 2003 e 2017, foi possível analisar que a participação feminina no mercado de trabalho paulista c...
This paper examines the collaboration dynamic among areas of knowledge and countries from 1975 to 2017 within the bioenergy field and from a complex network approach, as a driver for the evolution of technological frontiers and emerging paradigms, seeking opportunities for a transition to low carbon economies. The results provide detailed informati...
O nível de complexidade econômica é a mensuração da capacidade de uma economia em produzir bens com um maior (ou menor) nível de conhecimento embarcado. Assim, sob a ótica da complexidade econômica, este estudo discorre sobre as oportunidades de crescimento e desenvolvimento das cidades do estado de São Paulo. Nossa hipótese principal é que a heter...
A importância da indústria na economia pode ser representada através de seus efeitos multiplicadores de renda, emprego, inovação e difusão tecnológica. Nesse contexto, o trabalho possui como contribuição e objetivo sintetizar o debate acerca da desindustrialização brasileira sob a ótica do emprego e analisar de maneira exploratória a evolução da es...
Time series forecasting problems are often addressed using linear techniques, especially the autoregressive (AR) models, due to their simplicity combined with good performances. It is possible to generalize a linear predictor by allowing infinite impulse response (IIR) through the addition of feedback loops, as occurs in the autoregressive and movi...
RESUMO: problemas cíclicos atingem esporadicamente as atividades produtivas em todo mundo. A indústria automobilística brasileira, setor de atividade relevante na economia do país, passou por problemas na demanda durante a crise econômica de 2008 e nos anos que a seguiram. Uma série de medidas protetivas foi tomada, dentre elas: a redução do Impost...
The forecasting of monthly seasonal streamflow time series is an important issue for countries where hydroelectric plants contribute significantly to electric power generation. The main step in the planning of the electric sector’s operation is to predict such series to anticipate behaviors and issues. In general, several proposals of the literatur...
RESUMO: O trabalho propõe-se a investigar as nuances da inserção feminina na indústria de transformação paulista, realizando uma análise comparativa entre os anos de 2003 e 2017, à luz das mudanças produtivas trazidas pela indústria 4.0, com destaque para a hipótese da polarização do emprego. Para isso, são explorados os conceitos base de transvers...
This paper seeks to analyze the dynamic and determinants of high technology exports (HTE) toLatin America and the Caribbean, which is carried out on the basis of previousworks from the academic literature. To do so, it is used both explanatory SocialNetwork Analysis and the Panel Data modeling, both for the years 2005 to 2015,with data available fr...
This paper aims to analyze preliminary results that quantify and qualify specialization anddiversification for Brazilian states on the light of regional economics. Forthis purpose, it was used RAIS (Annual Relation of Social Information,developed by MTE – Ministry of Labor) and input-output tables. We used the Losindex as proxy for specialization a...
Foot-and mouth disease (FMD) is an animal disease that generates many economic impacts and sanctions on the international market. In 2018, Brazil, the world's largest beef exporter, had the recognition by World Organization for Animal Health (OIE) as a country free of FMD with vaccination and proposed to withdraw FMD vaccination throughout the coun...
This thesis aims to study the relationship between the diversification of the productive structure (related and unrelated variety) and the quality of the labor market of the Brazilian states from 2012 to 2019. This is a theoretical contribution to the debate by considering a qualitative approach to labor market analysis and it allows to fill in a g...
Resumo Este artigo tem como objetivo apresentar a atualidade do estudo dos recursos comuns no Brasil, expondo como o tema evoluiu, tanto na teoria quanto na prática. Primeiramente, faz-se uma revisão teórica sobre o tema, de modo a apresentar ao leitor as proposições acadêmicas mais recentes na área. Em seguida, expõe-se o conceito de “recursos com...
This paper investigates the statistical properties and patterns of Brazilian manufacturing firms related to size, productivity, growth, and their seemingly ubiquitous heterogeneity. Using microdata from the Brazilian Industrial Survey from 1996 to 2013, we conducted exercises using panel and crosssectional data at different levels of aggregation. O...
cyclical problems sporadically affect productive activities around the world. Brazilian car industry, a sector of relevant activity in the economy of the country, experienced problems in demand during the economic crisis of 2008 and in the following years. A set of protective measures were taken, among them: the reduction of the Industrialized Prod...
This paper aims to analyze the regional inequalities of bioethanol production, focusing on learning and knowledge creation. The papers have two central assumptions: first, learning is the key resource in modern capitalism; second, it is unevenly distributed in the space. For capturing this phenomenon in bioethanol production, we divided the Center-...
The digitization of economies and automation are processes of uncertain net effects on
occupational structures. Based on the researchs conducted by Frey and Osborne (2013) and the OECD (2016), this work presents scenarios about the potential impact of these productive transformations on the Brazilian occupational structure. The preliminary results...
O artigo tem como ponto de partida um diálogo com análises que discutem o movimento da fronteira do setor sucroenergético e sua influência no desenvolvimento urbano e regional no interior do território nacional. O argumento é que, apesar da maior dispersão da atividade produtiva, novas desigualdades persistem nesse setor, devido aos centros de deci...
This work discusses the direct relation between linear tools to solve forecasting tasks: Autoregressive (AR) and Autoregressive and Moving Average (ARMA) models, from Box & Jenkins methodology, and the Finite and Impulse response linear adaptive filters. The aforementioned filters are commonly used in channel equalization, but they also can be used...
Feedforward neural networks are those in which the input signal follows only one direction: from the input layer to the output layer, passing through all the hidden layers, in contrast with recurrent architectures. The main examples of this class are the Multilayer Perceptron (MLP) and the Radial Basis Function network (RBF). Recently, other model...
A pesquisa propõe a realização do mapeamento e análise da dinâmica de inovação das empresas brasileiras vis-à-vis às empresas portuguesas e alemãs. A pesquisa visa o estudo dos parâmetros da inovação a partir do questionamento sobre as diferenças apontadas sobretudo na pesquisa de Inovação Tecnológica (PINTEC), pesquisa realizada pelo Instituto Bra...
This work performs an extensive investigation about the application of unorganized machines – extreme learning machines and echo state networks – to predict monthly seasonal streamflow series, associated to three important Brazilian hydroelectric plants, for many forecasting horizons. The aforementioned models are neural network architectures which...
This paper presents the evaluation of a daily inflow forecasting model using a tool that facilitates the analysis of mathematical models for hydroelectric plants. The model is based on a Fuzzy Inference System. An offline version of the Expectation Maximization algorithm is employed to adjust the model parameters. The tool integrates different infl...
Echo state networks can be safely regarded as promising tools in time series forecasting because they are recurrent networks which have a simple and efficient training process based on a linear regression. The recurrent character of an ESN comes from a dynamic reservoir that corresponds to a hidden layer with feedback loops which remains untrained,...
O crescimento da produtividade é um dos fatores fundamentais para o crescimento econômico, estando associado diretamente ao progresso material e ao aumento dos padrões de vida da população. Justamente por isso, a compreensão das trans-formações da produtividade é um tema relevante para as ciências econômicas, já aparecendo como uma questão importan...
In hydroelectric systems, water inflow is important to coordinate a cascade and define the energy price. This
paper presents a method for managing inflow forecasting studies with a specific module for advanced assessment.
The main goal is to provide a structure that facilitates the analysis of water inflow prediction models. A
case study has been a...
O presente trabalho tem como objetivo apresentar a equação de Price e sua aplicação para a economia brasileira, tendo como embasamento teórico a abordagem neo-schumpeteriana da concorrência, dinâmica e inovação, assim como a concepção do darwinismo generalizado. Um modelo inspirado na equação de Price é utilizado para decompor a variação da produti...
mercado, o Value-at-Risk. Por meio do estudo de três métodos diferentes de cálculo, o método de Simulação Histórica (MSH), o método de Médias Móveis (EQMA) e o método de Suavizamento Exponencial (EWMA), o trabalho busca aplicar estes modelos em uma carteira fictícia composta pelas maiores empresas presentes no Índice Bovespa (IBOVESPA). Com os resu...
Este projeto visa à utilização das ferramentas metodológicas típicas da análise de redes sociais (SNA) no estudo de redes de patentes geradas usando as palavras-chave associadas ao Programa de Bioenergia da Fundação de Amparo à Pesquisa do Estado de São Paulo (BIOEN). As redes de co-citações de patentes a serem analisadas serão extraídas da base de...
Este trabalho apresenta um estudo comparativo de métodos de medida de risco de
mercado, o Value-at-Risk. Por meio do estudo de três métodos diferentes de cálculo, o método de
Simulação Histórica (MSH), o método de Médias Móveis (EQMA) e o método de Suavizamento
Exponencial (EWMA), o trabalho busca aplicar estes modelos em uma carteira fictícia comp...
Time series modelling is a subject of in-
terest to several fields of knowledge. The challenge of
dealing with this type of data is to develop computatio-
nal instrumentals able to handle with different features
related to non-stationarity as well as uncertainty pre-
sent in most of real processes. In that context, dynamic
fuzzy systems have shown...
Resumo—Este trabalho propõe o desenvolvimento de mecanismos de inferência fuzzy por meio de modelos de nuvem. Modelos de nuvem consideram a existência de estocasticidade e imprecisão nos dados observados. A utilização de nuvens para a representação de conceitos qualitativos via funções de pertinência fuzzy, permi-tirá o processamento não somente da...
Significant increasing in derivatives trading over the world markets has led to an interesting debate about futures contracts influences on spot prices. In this context, this paper aims to evaluate, during the subprime crisis, the influence of IBOVESPA futures price volatility on the spot price indices as follows: IBOVESPA, FGV-100, IBrX-50, IGC, S...
This paper suggests an adaptive fuzzy rule based system applied as a financial time series model for volatility forecasting. The model is based on
Takagi-Sugeno fuzzy systems, and it is built in two phases. In the first phase, the model uses the Subtractive Clustering algorithm to determine
group structures in a reduced data set for initialization...
Resumo—A previsão de vazões médias mensai e uma variável fundamental para o planejamento e programa ao e o despacho centralizado das usinas do Sistema Interligado Nacional (SIN). Durante o ultimos anos, diferentes propostas baseadas em modelos de séries temporais e outras em modelos baseados na inteligência computacional têm sido propostos para a c...
This paper introduces an adaptive fuzzy rule-based system applied as a financial time series model for volatility forecasting. The model is based on Takagi–Sugeno fuzzy systems and is built in two phases: In the first, the model uses the subtractive clustering algorithm to determine initial group structures in a reduced data set. In the second phas...
Inflow data plays an important role in water and energy resources planning and management. In general,
due to the limited availability of historical inflow data,
synthetic streamflow time series have been widely used
for several applications such as mid- and long-term hydropower scheduling and the identification of hydrological processes. This pape...
This paper presents a data-driven approach applied to the long term prediction of daily time series in the Neural Forecasting Competition. The proposal comprises the use of adaptive fuzzy rule-based systems in a top-down modeling framework. Therefore, daily samples are aggregated to build weekly time series, and consequently, model optimization is...
This paper presents the application of a methodology for daily reservoir inflow forecasting in Brazilian hydroelectric plants. The methodology is based on Fuzzy Inference Systems (FIS) and the technique used for adjusting of the model parameters is an offline version of the Expectation Maximization (EM) algorithm. In order to automate the applicati...
Significant increasing in derivatives trading over the world markets has led to an interesting debate about futures contracts influences on spot prices. In this context, this paper analyses, during the subprime crisis period, the influence of IBOVESPA futures price volatility on the spot price indexes as follows: IBOVESPA, FGV-100, IBrX-50, IGC, SMLL...
A modelling strategy based on the application of fuzzy inference system is shown to provide a powerful and efficient method
for the identification of non-linear and linear economic relationships. The procedure is particularly suitable for the estimation
of ill-defined systems in which there is considerable uncertainty about the nature and range of...
Forecasting stock index has received much attention in the literature of finance due its complexity and its importance in the formulation of investment strategies. Low performance forecasts of linear techniques against simple models, such as random walk model, has encouraged the application of non-linear time series models. In this context, neural...
This study presents a prediction system based on evolving fuzzy models and a bottom-up approach for daily streamflow forecasting. Prediction models are based on adaptive Takagi-Sugeno fuzzy inference systems. These models make use of a sequential learning approach for updating their own structure and parameters over time according to changes or var...
This paper proposes an operational policy for long-term hydropower scheduling based on deterministic nonlinear optimization and annual inflow forecasting models using an open-loop feedback control framework. The optimization model precisely represents hydropower generation by taking into consideration water head as a nonlinear function of storage,...
This paper suggests a constructive fuzzy system modeling for time series prediction. The model proposed is based on Takagi-Sugeno system and it comprises two phases. First, a fuzzy rule base structure is initialized and adjusted via the expectation maximization optimization technique (EM). In the second phase the initial system is modified and the...
This paper suggests a new algorithm for generating Takagi-Sugeno fuzzy systems applied for time series prediction. The model proposed comprises two phases. First, the model structure is initialized in a constructive offline fashion, via an expectation maximization algorithm (EM). In the second phase the system is modified dynamically, via adding an...
This paper suggests and compares two approaches for building a fuzzy-rule based system for time series modeling and forecasting. The first one is based on a constructive offline learning (C-FSM). The second one, is based on an adaptive online learning process (A-FSM). Both models have its general architecture based on a fuzzy rule based system, and...
This paper suggests an online algorithm for generating Takagi-Sugeno fuzzy systems applied for time series pre-diction. The model proposed is built in two phases. First, the model structure is initialized via a constructive offline adjustment, considering only two initial fuzzy rules. In the second phase, the system is modified dynamically, applyin...
In this work, an algorithm for identifying time series models is proposed. The strategy is based on Partial Mutual Information Criterion (PMI), which considers not only linear but also non-linear relations between variables under study. For calculating the PMI criterion, it is necessary to approximate marginal and joint probability densities, as we...
In this work, an algorithm for identifying time series models is proposed. The strategy is based on Partial Mutual Information Criterion (PMI), which considers not only linear but also non-linear relations between variables under study. For calculating the PMI criterion, it is necessary to approximate marginal and joint probability densities, as we...
In this paper, a strategy for mod-elling temporal time series is pro-posed. This approach is based on the Partial Mutual Information Cri-terion, which is evaluated for select-ing relevant inputs for a time se-ries model. This criterion does not only consider input-output relations but also stored information each in-put provides. The methodology is...
Planning of hydroelectric systems is a complex and difficult task once it involves non-linear production characteristics and depends on numerous variables. A key variable is the streamflow. Streamflow values covering the entire planning period must be accurately forecasted because they strongly influence energy production. This paper suggests an ap...
Questions
Questions (3)
Does anyone know about some hypothesis test to identify if a times series is (or can be considered) linear or non-linear?
Does cointegration between two variables imply causality (Granger sense)?
