Ricardo A. Pasquini
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March 20, 2011 by admin 0
Coding Notes, Uncategorized

Using loops to run (and export) many regressions / Usando loops para correr (y exportar) múltiples regresiones

español The use of  loops becomes essential when needing to perform repetitive calculations. Looping has many advantages, for example, when needing to do corrections in all the calculations specifications. So here are some interesting features that you would like to do when implementing a loop to run many regressions, and export their outputs: Choose the appropriate method for the regression according to the type of dependent variable. For instance,  you might want to estimate the model using OLS (regress) when the dependent variable is continuous and or a probit or a logit model when it is discrete (a dummy variable). Progressively add explanatory variables to the model and export all the output in a single table. This can be done using outreg2 ‘s  replace and append options, but if you want instead to write a single command line inside a loop you will have to make the appropriate changes. So assume that you want to estimate a number of econometric models that are quite similar in terms of the explanatory variables that are incorporated, but differ between them in terms of the dependent variables, for example : Model 1: outcome1=b1*x1+b2*x2+b3*X3+b4*X4+e Model 2: outcome2=b1*x1+b2*x2+b3*X3+b4*X4+e In addition you also want to progressively add sets of explanatory variables. So for instance you…

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AMM apps bienes publicos causal inference classification conda COVID-19 criptomonedas cryptocurrencies defi econometrics economía de mercados Ethereum Exportar resultados Export output Financial inclusion financiamiento cuadrático fraud geopandas Geospatial analysis Gitcoin h3 hexagons Households Finance Indebtedness Jupyter Loops machinelearning Mercado de Alquileres MongoDB negocios precision proyectos ingeniería public goods pymongo python quadratic funding recall Regression roc-curve scalability Stata Tablas Tables ubuntu