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Authors
Advisor(s)
Abstract(s)
Esta dissertação analiza técnicas de correção do efeito do enviesamento que pode ocorrer no caso dos dados utilizados apresentarem valores em falta. Tais técnicas serão aplicadas a um modelo económico para caracterização da margem líquida de juros (MLJ) bancária, utilizando dados provinientes 15 países que pertencem ao sistema bancário da União Europeia (UE15).
As variáveis que caracterizam os bancos são observados entre de 2004 e 2010. E são escolhidas seguindo Valverde et al. (2007). Adicionalmente aos regressores são acrescentadas algumas variáveis macroeconómicas. A seleção proviniente da falta de alguns valores para os regressores é tratada através da ponderação probabilistica inversa. Os ponderadores são aplicados a estimadores GMM para um modelo de dados de painel dinámico.
This thesis discusses techniques to correct for the potentially biasing effects of missing data. We apply the techniques on an economic model that explains the Net Interest margin (NIM) of banks, using data from 15 countries that are part of the European Union (EU15) banking system. The variables that describe banks cover the period 2004 and 2010. We use the variables that were also used in Carbó-Valverde and Fernndez (2007). In addition, also macroeconomic variables are used as regressors. The selection that occurs as a consequence of missing values in these regressor variables is dealt with by means of Inverse Probability Weighting (IPW) techniques. The weights are applied to a GMM estimator for a dynamic panel data model that would have been consistent in the absence of missing data.
This thesis discusses techniques to correct for the potentially biasing effects of missing data. We apply the techniques on an economic model that explains the Net Interest margin (NIM) of banks, using data from 15 countries that are part of the European Union (EU15) banking system. The variables that describe banks cover the period 2004 and 2010. We use the variables that were also used in Carbó-Valverde and Fernndez (2007). In addition, also macroeconomic variables are used as regressors. The selection that occurs as a consequence of missing values in these regressor variables is dealt with by means of Inverse Probability Weighting (IPW) techniques. The weights are applied to a GMM estimator for a dynamic panel data model that would have been consistent in the absence of missing data.
Description
Mestrado em Econometria Aplicada e Previsão
Keywords
GMM IPW A margem líquida financeira A seleção na amostra MGM WIP Net interest margin Sample selection
Pedagogical Context
Citation
Afonso, Lutcy Menezes (2015). "Correcting for attrition in panel data using inverse probability weighting : an application to the european bank system". Dissertação de Mestrado, Universidade de Lisboa. Instituto Superior de Economia e Gestão.
Publisher
Instituto Superior de Economia e Gestão