A Note on Proxy Variables and Instrument Variable Regression

This is a note about proxy variables and instruments for identification of structural parameters in regression models. We have experienced that in the econometric textbooks these two issues are treated separately, although in practice these two concepts are very often combined. Usually, proxy variables are inserted in instrument variable regressions with the motivation they are exogenous. Implicitly meaning they are exogenous in a reduced form model and not in a structural model. Actually if these variables are exogenous they should be redundant in the structural model, e.g. IQ as a proxy for ability. Valid proxies reduce unexplained variation and increases the efficiency of the estimator of the structural parameter of interest. This is especially important in situations when the instrument is weak. With a simple example we demonstrate what is required of a proxy and an instrument when they are combined. It turns out that when a researcher has a valid instrument the requirements on the proxy variable is weaker than if no such instrument exists

Final report on heat pump developments in WP 4 - MacSheep Deliverable 4.4 : MacSheep -New Materials and Control for a next generation of compact combined Solar and heat pump systems with boosted energetic and exergetic performance

FP7- MacSheep

Predictive models for chronic renal disease using decision trees, naïve bayes and case-based methods

Data mining can be used in healthcare industry to “mine” clinical data to discover hidden information for intelligent and affective decision making. Discovery of hidden patterns and relationships often goes intact, yet advanced data mining techniques can be helpful as remedy to this scenario. This thesis mainly deals with Intelligent Prediction of Chronic Renal Disease (IPCRD). Data covers blood, urine test, and external symptoms applied to predict chronic renal disease. Data from the database is initially transformed to Weka (3.6) and Chi-Square method is used for features section. After normalizing data, three classifiers were applied and efficiency of output is evaluated. Mainly, three classifiers are analyzed: Decision Tree, Naïve Bayes, K-Nearest Neighbour algorithm. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. Efficiency of Decision Tree and KNN was almost same but Naïve Bayes proved a comparative edge over others. Further sensitivity and specificity tests are used as statistical measures to examine the performance of a binary classification. Sensitivity (also called recall rate in some fields) measures the proportion of actual positives which are correctly identified while Specificity measures the proportion of negatives which are correctly identified. CRISP-DM methodology is applied to build the mining models. It consists of six major phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.

Campus Life: In Perkins Arboretum there are birds of all feathers, trees that tell a story, and even romance (especially if you're a frog)

To the uninitiated, Perkins Arboretum is the edge of campus. For those familiar with its flora and fauna, the arboretum is a wondrous classroom and refuge.

Retenção de clientes na renegociação de créditos inadimplentes: um estudo em uma grande instituição financeira brasileira

Este trabalho analisa, sob uma perspectiva quantitativa, a retenção de clientes durante o processo de renegociação de créditos inadimplentes. O foco principal é entender quais são as variáveis que explicam a retenção destes clientes e, portanto, aprimorar o processo de cobrança de uma instituição financeira no Brasil. O tema se torna relevante à medida em que vários fatores tornam a competitividade mais difícil no ambiente de crédito no país: a concentração bancária vivida na última década, o aumento da oferta de crédito nos últimos anos, a redução dos spreads bancários, e por fim a crise econômica global que afeta em especial o setor financeiro. A pesquisa procura investigar quais variáveis melhor explicam o fenômeno da retenção. Para tanto, foram segregados clientes projetados como rentáveis pela cadeia de Markov. Em seguida, testou-se a aderência de variáveis cadastrais e contratuais à variável-resposta retenção, por duas metodologias: o algoritmo CHAID da árvore de decisão e o método stepwise da regressão logística. Os resultados indicam que o método CHAID selecionou 7 e o stepwise 8 variáveis, sendo algumas de natureza cadastral e outras que vêm do próprio contrato de renegociação. Dado que as condições do contrato influenciam a retenção e portanto o valor do cliente, sugere-se que o processo de oferta incorpore operacionalmente a noção de retenção na atividade da cobrança.

Electoral rules, political competition and fiscal spending: regression discontinuity evidence from brazilian municipalities

We exploit a discontinuity in Brazilian municipal election rules to investigate whether political competition has a causal impact on policy choices. In municipalities with less than 200,000 voters mayors are elected with a plurality of the vote. In municipalities with more than 200,000 voters a run-off election takes place among the top two candidates if neither achieves a majority of the votes. At a first stage, we show that the possibility of runoff increases political competition. At a second stage, we use the discontinuity as a source of exogenous variation to infer causality from political competition to fiscal policy. Our second stage results suggest that political competition induces more investment and less current spending, particularly personnel expenses. Furthermore, the impact of political competition is larger when incumbents can run for reelection, suggesting incentives matter insofar as incumbents can themselves remain in office.

Operações booleanas entre objetos delimitados por surfels usando constrained BSP-trees

As áreas de visualização e modelagem baseados em pontos têm sido pesquisadas ativamente na computação gráfica. Pontos com atributos (por exemplo, normais) são geralmente chamados de surfels e existem vários algoritmos para a manipulação e visualização eficiente deles. Um ponto chave para a eficiência de muitos métodos é o uso de estruturas de particionamento do espaço. Geralmente octrees e KD-trees, por utilizarem cortes alinhados com os eixos são preferidas em vez das BSP-trees, mais genéricas. Neste trabalho, apresenta-se uma estrutura chamada Constrained BSP-tree (CBSP-tree), que pode ser vista como uma estrutura intermediárias entre KD-trees e BSP-trees. A CBSP-tree se caracteriza por permitir cortes arbitrários desde que seja satisfeito um critério de validade dos cortes. Esse critério pode ser redefinido de acordo com a aplicação. Isso permite uma aproximação melhor de regões curvas. Apresentam-se algoritmos para construir CBSP-trees, valendo-se da flexibilidade que a estrutura oferece, e para realizar operações booleanas usando uma nova classificação de interior/exterior.

Wald tests for IV regression with weak instruments

This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).