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Efeitos de choques globais na economia brasileira: uma análise a partir do GVARZanetta Neto, Ary Cera 05 August 2014 (has links)
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Previous issue date: 2014-08-05 / O objetivo deste estudo é avaliar a propagação de choques econômicos de alguns países sobre o crescimento econômico brasileiro, com principal destaque para China, Estados Unidos da América (EUA) e Argentina, que são os principais parceiros comerciais do Brasil. O aumento do comércio com a China tornou o Brasil muito mais vulnerável a choques no PIB chinês e menos vulnerável, do que no passado recente, a choques no PIB americano, enquanto que a influência da Argentina manteve-se estável. Foi aplicada a metodologia Vetor Autorregressivo Global (Global Var – GVAR), introduzida por Pesaran, Schuermann e Weiner (2004), Garratt, Lee, Pesaran e Shin (2006) e Dées, Di Mauro, Pesaran e Smith (2007), para analisar os canais de comércio e a transmissão de choques entre o resto do mundo e o Brasil. Usando dados trimestrais a partir de 1990 até o final de 2013, foi possível constatar que o aumento da relevância da economia Chinesa na balança comercial Brasileira exerce pressão sobre o crescimento econômico do Brasil. Em suma, a China tornou-se mais relevante para o crescimento econômico do Brasil do que os EUA e a Argentina. / The objective of this study is to evaluate the impact of variations in the Gross Domestic Product (GDP) of countries and economic blocks over Brazilian economic growth, with emphasis on China, United States of America (USA) and Argentina, which are the main commercial partners of Brazil. The increase in trading with China has made Brazil more vulnerable to shocks in Chinese GDP and less vulnerable, than in the recent past, to shocks in American GDP, and stability in the case of Argentina. It has been applied the methodology Global Vector Autorregressive (Global Var – GVAR), introduced, explained and expanded by Pesaran, Schuermann and Weiner (2004), Garratt, Lee, Pesaran and Shin (2006) and Dées, Di Mauro, Pesaran and Smith (2007) to analyze the trading channels and the transmission of shocks between the rest of the world and Brazil (specially with China, USA and Argentina). Using a sample from the first quarter of 1990 to the third quarter of 2013 it is possible to see that the increase of relevance of the Chinese economy on the Brazil trade balance increased the relevance of the Chinese economy over the Brazilian economy. Therefore, the conclusions of this work indicate a considerable vulnerability of the Brazilian economy to the Chinese economic cycle and, in a lower degree than in the past, to the American and Argentinian economies.
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Análise dos impactos da linha Finem na produção industrial brasileira por meio de vetores autoregressivosMalafaia, Karla de Alvarenga Charles 29 January 2013 (has links)
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Previous issue date: 2013-01-29 / Este trabalho se propõe a testar e quantificar a importância do investimento de longo prazo, captado pela série de desembolsos da linha BNDES Finem, na produção industrial brasileira. Através dos modelos de causalidade de Granger e Função resposta ao impulso, podemos verificar as respostas acumuladas ao longo de três anos da linha Finem a choques positivos de um desvio padrão nas variáveis inflação, produção industrial, spread, e, da mesma forma um choque na variável Finem com resposta nas variáveis acima descritas. Além disso, é possível identificar a importância do BNDES como um ator anticíclico em períodos de crise como na economia brasileira. Como resultado, encontramos que apesar dos desembolsos Finem não Granger causarem a produção industrial brasileira, se testadas em conjunto com dados de inflação e a diferença entre a Selic e a TJLP rejeita-se a hipótese nula de não causalidade a 1% de significância. Já os testes de funções de resposta ao impulso indicam que a taxa de crescimento da produção industrial tem resposta positiva a um choque de desvio padrão nos desembolsos de Finem. Contudo, se testada em conjunto um choque no Finem apesar de impactar positivamente a produção industrial acaba pressionando a inflação. / This work is to test and quantify the importance of a long-term investment captured by the series of disbursements of BNDES Finem line in brazilian industrial production. Through Granger causality and impulse-response function, it was possible to check the Finem line accumulated answers along three years to positive shocks of a standard deviation on the variables inflation, industrial production, spread, and a shock on Finem variable with answer on the previous described variables. Furthermore, it's possible to identify the BNDES's importance as a countercyclical tool in crisis period as in brazilian economy. As a result, we found that despite causing the brazilian industrial production, if the no Granger Finem's disbursements are tested with inflation data and the difference between Selic and TJLP, the null hypothesis of no causality at 1% of significance is rejected. Yet, the tests of impulse-response function indicate that the industrial production growth rate has positive answer to a shock of standard deviation on Finem's disbursements. However, despite impacting the industrial production positevely, it pressures the inflation if it's tested with a shock on Finem.
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Korea's export performance: three empirical essaysKang, Shin-jae January 1900 (has links)
Doctor of Philosophy / Department of Economics / Wayne Nafziger / This dissertation constructs three empirical essays. The first essay illustrates the causality on the relationship between output (GDP) growth and exports. By using the Modified Wald (MWald) test we observe unidirectional causality from exports to GDP. More specifically, for the robustness we use a Vector Error Correction Model (VECM) model and the Generalized Impulse Response Function Analysis (GIRA). The VECM and the GIRA yield bidirectional causality between exports and GDP, which weakly supports the unidirectional result of the to MWald test. Meanwhile, we confirm that there is structure break by using the structural break test. These results are plausible and consistent with the expectations of our study for the Export Led Growth Hypothesis (ELGH). However, compared with previous studies on the ELGH for Korea, our results are different. Other studies show a bidirectional causality relationship but this study only has unidirectional causality. These differences may be caused from different observation data, various variables, and use of different econometric methodologies. Also, model selection and omitting variables can also significantly change the results of causality testing.
The second essay investigates a degree of competition between Korea's and China's exports in the U.S. market by using the substitute elasticity on a simple demand model. The market share of Korean exports has been decreasing while that of China's has been increasing. The results of this study are as follows. First, we find that Korea has a dominant market share of only goods group code 27 in commodity groups over that of China, otherwise having China's dominant market shares over those of Korea for other export sections by using historical trade data. Second, most estimates of substitute elasticity between both countries' exports in the U.S. market are small (inelastic). However, 61 (apparel articles and accessories, knit or crochet), 62 (apparel articles and accessories, not knit etc) and 85 (electric machinery etc, sound equipments, TV equipment, parts) commodity groups' substitute elasticities are large (elastic) and are competitive in the U.S. market compared with those of China. A small value of the elasticity of substitution may be due to an identification problem for a simple standard model as well as measurement errors in prices as a unit value in this study. So, in order to avoid problems such as these, we may need to use appropriate instrumental or proxy variables in the simple standard model, which highly correlate with the independent (unit price) variables and are uncorrelated with measurement error terms. In practice, it is not easy to find good instrumental variables.
The final essay evaluates the roles of price and income as important factors that affect Korea's exports by using the most recent monthly data. By using the Autoregressive Distributed Lag (ARDL) bounds testing approach we find the long-run relationship of variables and estimate the long-run price and income elasticities. However, the estimates of these long-run elasticities are statistically insignificant. This may be due to some misspecifications or measurement errors in our model. Meanwhile, due to the existence of the long-run relationship between variables, we construct the Error Correction Model (ECM) in order to observe the short-run dynamics of the elasticities. Specifically, we add a dummy variable into our export demand model to achieve more efficient estimations since the dummy variable reflects a shock in Korea's export; Korea's economic crisis in 1997. In contrast to the long-run elasticity, we find that the short-run elasticities' estimates are more statistically significant. When we use the structure break test to check the structural stability of Korea's export demand, we find that there is no structural break point of 1997. Therefore, a shock of Korea's economic crisis in 1997 might not significantly affect Korea's export demand in a given sample. However, the Information Technology (IT) bubble of the world economy in 2001 and the entry of Korea into the OECD had triggered an increase in Korea's export demand due to existing structural break points of both events. In addition, we find that income elasticities are larger than price elasticities in the short run. This implies that income has more of an impact than that of price for the export demand model in the short run. This also implies that the change of Korea's exports in the short run is more sensitive to changes in foreign income (industrial production) compared with that of price (exchange rate). An interesting result, thus, is that Korea's exports in the short run may have higher export performance on income than that of price (exchange rate). This might be a consequence of the dependence of an increase in foreign income in recent years. In recent years, developing countries have greatly increased their economic growth compared with that of developed countries and Korea's exports have increased into these developing countries. Thus, we confirm that an increase in Korea's exports is mainly affected by income compared with price, specifically in the short run by using recent data.
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Škálování arteriální vstupní funkce v DCE-MRI / Scaling of arterial input function in DCE-MRIHoleček, Tomáš January 2015 (has links)
Perfusion magnetic resonance imaging is modern diagnostic method used mainly in oncology. In this method, contrast agent is injected to the subject and then is continuously monitored the progress of its concentration in the affected area in time. Correct determination of the arterial input function (AIF) is very important for perfusion analysis. One possibility is to model AIF by multichannel blind deconvolution but the estimated AIF is necessary to be scaled. This master´s thesis is focused on description of scaling methods and their influence on perfussion parameters in dependence on used model of AIF in different tissues.
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Oil Price and the Stock Market: A Structural VAR Model Identified with an External InstrumentPerez, Tomas Rene 28 July 2020 (has links)
No description available.
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Correction of Radial Sampling Trajectories by Modeling Nominal Gradient Waveforms and Convolving with Gradient Impulse Response Function / Korrektion av radiella samplingstrajektorier genom modellering av nominella gradientvågformer och faltning med gradientimpulsresponsfunktionKim, Max, Belbaisi, Adham January 2019 (has links)
There are several reasons for using non-Cartesian k-space sampling methods in Magnetic Resonance Imaging (MRI). Such a method is radial sampling, which includes the advantage of continuous coverage of the k-space center which results in higher robustness to motion. On the other hand, radial imaging does have some limitations that must be considered. The method is more sensitive to gradient imperfections, such as eddy currents and gradient delays, resulting in inconsistencies between the nominal and actual gradient waveforms. This leads to distortions in the sampling trajectory, also called trajectory errors, yielding reconstructed images with artifacts caused by the gradient imperfections. The aim of this project was therefore to implement a method that takes these errors into account and perform a correction of the trajectory errors to yield images with reduced artifacts. Various methods have been proposed for correction of the gradient errors, some more effective than others. The method implemented in this project was based on the gradient impulse response function (GIRF) which characterizes the gradient system responses. When GIRF was acquired, the actual gradient waveforms played-out during the imaging measurement could be predicted by first modeling the nominal gradient waveforms and then performing a convolution with the corresponding GIRF for each gradient axis. The imaging experiments involved measurements on two different resolution phantoms and in-vivo measurements to note possible differences in correction performance. The used pulse sequences for imaging were FLASH and bSSFP. The results showed that the applied method using GIRF did reduce the artifacts caused by gradient imperfections in the reconstructed images taken with the FLASH sequence. On the other hand, the results for the bSSFP sequence were not as successful due to incomplete modeling of the gradient waveforms. The conclusion to be drawn is that the GIRF-correction does adequately compensate for the trajectory errors when using a radial sampling trajectory for the FLASH sequence and hence yield images with almost eliminated artifacts. A suggestion for future work would be to further investigate the bSSFP sequence modeling to obtain better bSSFP-images. / Det finns flera anledningar till att använda icke-Kartesiska k-space samplingsmetoder i magnetisk resonanstomografi. En sådan metod är radiell sampling, som har fördelen att kontinuerligt samla in mätdata från mittpunkten av k-space, vilket resulterar i lägre rörelsekänslighet under bildtagningstillfället. Radiell sampling har dock begränsningar som måste tas i beaktande, som gradient imperfektioner och gradientfördröjningar. Dessa leder till förvrängningar i samplingspositioneringen i k-space, även känt som trajektoriefel, vilket ger upphov till artefakter vid bildrekonstruktion. Syftet med projektet är att korrigera för dessa trajektoriefel så att den rekonstruerade bilden innehåller färre artefakter. Olika metoder har föreslagits för korrektion av gradientfel. Metoden som användes i detta projekt baseras på gradient impulsresponsfunktionen (GIRF), som karaktäriserar gradient systemet. För att estimera de verkliga samplingspositionerna i k-space beräknades de förvrängda gradientvågformerna efter varje mätning. Detta gjordes genom att först modellera de nominella gradientvågformerna och därefter utföra en faltning med GIRF. De utförda experimenten under projektets gång bestod av bildtagning av två fantomer och ett antal in-vivo mätningar för att identifiera eventuella skillnader i de rekonstruerade bilderna. Pulssekvenserna som användes under projektet var FLASH och bSSFP. Resultaten visade att GIRF-korrektionen reducerade artefakter orsakade av gradient imperfektioner i de rekonstruerade bilderna tagna med FLASH-sekvensen. Erhållna resultat med bSSFP-sekvensen var å andra sidan inte lika lyckade på grund av inkomplett modellering av gradientvågformerna. Slutsatsen som kan dras är att GIRF-korrektionen kompenserar för trajektoriefel i radiell sampling för FLASH-sekvensen och ger rekonstruerade bilder där artefakterna nästan eliminerats. Ett förslag för framtida arbeten är att vidare undersöka modelleringen av bSSFP-sekvensen för att erhålla bättre bilder.
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Identificação de danos estruturais utilizando dados no domínio do tempo provenientes de ensaios de vibração / Structural damage identification using time domain data from vibration testsLuciano dos Santos Rangel 17 February 2014 (has links)
Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / O presente trabalho aborda o problema de identificação de danos em uma estrutura
a partir de sua resposta impulsiva. No modelo adotado, a integridade estrutural
é continuamente descrita por um parâmetro de coesão. Sendo assim, o Modelo de
Elementos Finitos (MEF) é utilizado para discretizar tanto o campo de deslocamentos,
quanto o campo de coesão. O problema de identificação de danos é, então, definido
como um problema de otimização, cujo objetivo é minimizar, em relação a um vetor de
parâmetros nodais de coesão, um funcional definido a partir da diferença entre a resposta
impulsiva experimental e a correspondente resposta prevista por um MEF da estrutura.
A identificação de danos estruturais baseadas no domínio do tempo apresenta
como vantagens a aplicabilidade em sistemas lineares e/ou com elevados níveis de
amortecimento, além de apresentar uma elevada sensibilidade à presença de pequenos
danos. Estudos numéricos foram realizados considerando-se um modelo de viga
de Euler-Bernoulli simplesmente apoiada. Para a determinação do posicionamento
ótimo do sensor de deslocamento e do número de pontos da resposta impulsiva, a serem
utilizados no processo de identificação de danos, foi considerado o Projeto Ótimo
de Experimentos. A posição do sensor e o número de pontos foram determinados segundo
o critério D-ótimo. Outros critérios complementares foram também analisados.
Uma análise da sensibilidade foi realizada com o intuito de identificar as regiões da estrutura
onde a resposta é mais sensível à presença de um dano em um estágio inicial.
Para a resolução do problema inverso de identificação de danos foram considerados
os métodos de otimização Evolução Diferencial e Levenberg-Marquardt. Simulações
numéricas, considerando-se dados corrompidos com ruído aditivo, foram realizadas
com o intuito de avaliar a potencialidade da metodologia de identificação de danos,
assim como a influência da posição do sensor e do número de dados considerados
no processo de identificação. Com os resultados obtidos, percebe-se que o Projeto
Ótimo de Experimentos é de fundamental importância para a identificação de danos. / The present work deals with the damage identification problem in mechanical
structures from their impulse response. In the adopted model, the structural integrity
is continually described by a cohesion parameter and the finite element model
(FEM) is used to spatially discretize both the displacement and cohesion fields. The
damage identification problem is then posed as an optimization one, whose objective
is to minimize, with respect to the vector of nodal cohesion parameters, a functional
based on the difference between the experimentally obtained impulse response and
the corresponding one predicted by an FEM of the structure. The damage identification
problem built on the time domain presents some advantages, as the applicability
in linear systems with high levels of damping an/or closed spaced modes, and in nonlinear
systems. Besides, the time domain approaches present high sensitivities to the
presence of small damages. Numerical studies were carried out considering a simply
supported Euler-Bernoulli beam. Optimal experiment design techniques were considered
with the aim at determining the optimal position of the displacement sensor and
also the number of points of the impulse response to be considered in the identification
process. The Differential Evolution optimization method and the Levenberg-Marquardt
method were considered to solve the inverse problem of damage identification. Numerical
analysis were carried out in order to assess the influence, on the identification
results, of noise in the synthetic experimental data, of the sensor position, and of the
number of points retained in the impulse response. The presented results shown the
potentiality of the proposed damage identification approach and also the importance
of the optimal experiment design for the quality of the identification. al importance for
the identification of damage.
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Identificação de danos estruturais utilizando dados no domínio do tempo provenientes de ensaios de vibração / Structural damage identification using time domain data from vibration testsLuciano dos Santos Rangel 17 February 2014 (has links)
Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / O presente trabalho aborda o problema de identificação de danos em uma estrutura
a partir de sua resposta impulsiva. No modelo adotado, a integridade estrutural
é continuamente descrita por um parâmetro de coesão. Sendo assim, o Modelo de
Elementos Finitos (MEF) é utilizado para discretizar tanto o campo de deslocamentos,
quanto o campo de coesão. O problema de identificação de danos é, então, definido
como um problema de otimização, cujo objetivo é minimizar, em relação a um vetor de
parâmetros nodais de coesão, um funcional definido a partir da diferença entre a resposta
impulsiva experimental e a correspondente resposta prevista por um MEF da estrutura.
A identificação de danos estruturais baseadas no domínio do tempo apresenta
como vantagens a aplicabilidade em sistemas lineares e/ou com elevados níveis de
amortecimento, além de apresentar uma elevada sensibilidade à presença de pequenos
danos. Estudos numéricos foram realizados considerando-se um modelo de viga
de Euler-Bernoulli simplesmente apoiada. Para a determinação do posicionamento
ótimo do sensor de deslocamento e do número de pontos da resposta impulsiva, a serem
utilizados no processo de identificação de danos, foi considerado o Projeto Ótimo
de Experimentos. A posição do sensor e o número de pontos foram determinados segundo
o critério D-ótimo. Outros critérios complementares foram também analisados.
Uma análise da sensibilidade foi realizada com o intuito de identificar as regiões da estrutura
onde a resposta é mais sensível à presença de um dano em um estágio inicial.
Para a resolução do problema inverso de identificação de danos foram considerados
os métodos de otimização Evolução Diferencial e Levenberg-Marquardt. Simulações
numéricas, considerando-se dados corrompidos com ruído aditivo, foram realizadas
com o intuito de avaliar a potencialidade da metodologia de identificação de danos,
assim como a influência da posição do sensor e do número de dados considerados
no processo de identificação. Com os resultados obtidos, percebe-se que o Projeto
Ótimo de Experimentos é de fundamental importância para a identificação de danos. / The present work deals with the damage identification problem in mechanical
structures from their impulse response. In the adopted model, the structural integrity
is continually described by a cohesion parameter and the finite element model
(FEM) is used to spatially discretize both the displacement and cohesion fields. The
damage identification problem is then posed as an optimization one, whose objective
is to minimize, with respect to the vector of nodal cohesion parameters, a functional
based on the difference between the experimentally obtained impulse response and
the corresponding one predicted by an FEM of the structure. The damage identification
problem built on the time domain presents some advantages, as the applicability
in linear systems with high levels of damping an/or closed spaced modes, and in nonlinear
systems. Besides, the time domain approaches present high sensitivities to the
presence of small damages. Numerical studies were carried out considering a simply
supported Euler-Bernoulli beam. Optimal experiment design techniques were considered
with the aim at determining the optimal position of the displacement sensor and
also the number of points of the impulse response to be considered in the identification
process. The Differential Evolution optimization method and the Levenberg-Marquardt
method were considered to solve the inverse problem of damage identification. Numerical
analysis were carried out in order to assess the influence, on the identification
results, of noise in the synthetic experimental data, of the sensor position, and of the
number of points retained in the impulse response. The presented results shown the
potentiality of the proposed damage identification approach and also the importance
of the optimal experiment design for the quality of the identification. al importance for
the identification of damage.
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Essays on tail risk in macroeconomics and finance: measurement and forecastingRicci, Lorenzo 13 February 2017 (has links)
This thesis is composed of three chapters that propose some novel approaches on tail risk for financial market and forecasting in finance and macroeconomics. The first part of this dissertation focuses on financial market correlations and introduces a simple measure of tail correlation, TailCoR, while the second contribution addresses the issue of identification of non- normal structural shocks in Vector Autoregression which is common on finance. The third part belongs to the vast literature on predictions of economic growth; the problem is tackled using a Bayesian Dynamic Factor model to predict Norwegian GDP.Chapter I: TailCoRThe first chapter introduces a simple measure of tail correlation, TailCoR, which disentangles linear and non linear correlation. The aim is to capture all features of financial market co- movement when extreme events (i.e. financial crises) occur. Indeed, tail correlations may arise because asset prices are either linearly correlated (i.e. the Pearson correlations are different from zero) or non-linearly correlated, meaning that asset prices are dependent at the tail of the distribution.Since it is based on quantiles, TailCoR has three main advantages: i) it is not based on asymptotic arguments, ii) it is very general as it applies with no specific distributional assumption, and iii) it is simple to use. We show that TailCoR also disentangles easily between linear and non-linear correlations. The measure has been successfully tested on simulated data. Several extensions, useful for practitioners, are presented like downside and upside tail correlations.In our empirical analysis, we apply this measure to eight major US banks for the period 2003-2012. For comparison purposes, we compute the upper and lower exceedance correlations and the parametric and non-parametric tail dependence coefficients. On the overall sample, results show that both the linear and non-linear contributions are relevant. The results suggest that co-movement increases during the financial crisis because of both the linear and non- linear correlations. Furthermore, the increase of TailCoR at the end of 2012 is mostly driven by the non-linearity, reflecting the risks of tail events and their spillovers associated with the European sovereign debt crisis. Chapter II: On the identification of non-normal shocks in structural VARThe second chapter deals with the structural interpretation of the VAR using the statistical properties of the innovation terms. In general, financial markets are characterized by non- normal shocks. Under non-Gaussianity, we introduce a methodology based on the reduction of tail dependency to identify the non-normal structural shocks.Borrowing from statistics, the methodology can be summarized in two main steps: i) decor- relate the estimated residuals and ii) the uncorrelated residuals are rotated in order to get a vector of independent shocks using a tail dependency matrix. We do not label the shocks a priori, but post-estimate on the basis of economic judgement.Furthermore, we show how our approach allows to identify all the shocks using a Monte Carlo study. In some cases, the method can turn out to be more significant when the amount of tail events are relevant. Therefore, the frequency of the series and the degree of non-normality are relevant to achieve accurate identification.Finally, we apply our method to two different VAR, all estimated on US data: i) a monthly trivariate model which studies the effects of oil market shocks, and finally ii) a VAR that focuses on the interaction between monetary policy and the stock market. In the first case, we validate the results obtained in the economic literature. In the second case, we cannot confirm the validity of an identification scheme based on combination of short and long run restrictions which is used in part of the empirical literature.Chapter III :Nowcasting NorwayThe third chapter consists in predictions of Norwegian Mainland GDP. Policy institutions have to decide to set their policies without knowledge of the current economic conditions. We estimate a Bayesian dynamic factor model (BDFM) on a panel of macroeconomic variables (all followed by market operators) from 1990 until 2011.First, the BDFM is an extension to the Bayesian framework of the dynamic factor model (DFM). The difference is that, compared with a DFM, there is more dynamics in the BDFM introduced in order to accommodate the dynamic heterogeneity of different variables. How- ever, in order to introduce more dynamics, the BDFM requires to estimate a large number of parameters, which can easily lead to volatile predictions due to estimation uncertainty. This is why the model is estimated with Bayesian methods, which, by shrinking the factor model toward a simple naive prior model, are able to limit estimation uncertainty.The second aspect is the use of a small dataset. A common feature of the literature on DFM is the use of large datasets. However, there is a literature that has shown how, for the purpose of forecasting, DFMs can be estimated on a small number of appropriately selected variables.Finally, through a pseudo real-time exercise, we show that the BDFM performs well both in terms of point forecast, and in terms of density forecasts. Results indicate that our model outperforms standard univariate benchmark models, that it performs as well as the Bloomberg Survey, and that it outperforms the predictions published by the Norges Bank in its monetary policy report. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished
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Detecting and Measuring Corruption and Inefficiency in Infrastructure Projects Using Machine Learning and Data AnalyticsSeyedali Ghahari (11182092) 19 February 2022 (has links)
Corruption is a social evil that resonates far and deep in societies,
eroding trust in governance, weakening the rule of law, impairing economic
development, and exacerbating poverty, social tension, and inequality. It is
a multidimensional and complex societal malady that occurs in various forms and
contexts. As such, any effort to combat corruption must be accompanied by a
thorough examination of the attributes that might play a key role in
exacerbating or mitigating corrupt environments. This dissertation identifies a number of attributes that
influence corruption, using machine learning techniques, neural network
analysis, and time series causal relationship analysis and aggregated data from
113 countries from 2007 to 2017. The results suggest that improvements in
technological readiness, human development index, and e-governance index have
the most profound impacts on corruption reduction. This dissertation discusses
corruption at each phase of infrastructure systems development and engineering
ethics that serve as a foundation for corruption mitigation. The dissertation then applies novel analytical
efficiency measurement methods to measure infrastructure inefficiencies, and to rank
infrastructure administrative jurisdictions at the state level. An efficiency frontier is
developed using optimization and the highest performing jurisdictions are
identified. The dissertation’s framework could serve as a
starting point for governmental and non-governmental oversight agencies to
study forms and contexts of corruption and inefficiencies, and to propose
influential methods for reducing the instances. Moreover, the framework can help
oversight agencies to promote the overall accountability of infrastructure
agencies by establishing a clearer connection between infrastructure investment
and performance, and by carrying out comparative assessments of infrastructure
performance across the jurisdictions under their oversight or supervision.
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