Ramon Antonio, Rosales Alvarez and Jorge Andres, Perdomo Calvo and Carlos Andres, Morales Torrado and Jaime Alejandro, Urrego Mondragon (2009): Fundamentos de econometría intermedia: Teoría y aplicaciones. Published in: Apuntes de Clase CEDE , Vol. 1, No. 2010 (January 2010): pp. 1-414.
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Abstract
Econometrics is the area of statistics concerned in analyzing economic data, for both economic and business applications. This document, introduces the intermediate concepts of this area, for students already familiarized with basic econometric theory. In particular, topics concerning endogenity, simultaneous equation models, time series and panel data, are discussed. One special contribution of these class notes is that both theory and applications, using Stata® statistical software package, are developed.
Item Type: | MPRA Paper |
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Original Title: | Fundamentos de econometría intermedia: Teoría y aplicaciones |
English Title: | Intermediate economics: Theory and applications |
Language: | Spanish |
Keywords: | Econometrics; Cross-Sectional Models; Simultaneous Equation Models; Discrete Regression and Qualitative Choice Models; Time Series Models; Models with Panel Data; Undergraduate Economics Education; Handbooks |
Subjects: | A - General Economics and Teaching > A2 - Economic Education and Teaching of Economics > A23 - Graduate C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C35 - Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C25 - Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions ; Probabilities C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C33 - Panel Data Models ; Spatio-temporal Models C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C23 - Panel Data Models ; Spatio-temporal Models C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C30 - General C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C31 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions ; Social Interaction Models C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics |
Item ID: | 37183 |
Depositing User: | Jorge Andres Perdomo Calvo |
Date Deposited: | 08 Mar 2012 15:50 |
Last Modified: | 26 Sep 2019 11:41 |
References: | Alonso, J; Contera, M; y Orozco, B. (2006). Sector Público y Déficit Fiscal. Apuntes de economía, Universidad ICESI. Arellano, M. (2003) Panel data econometrics. Oxford University Press. Baltagi, B. H. (2005) Econometric analysis of panel data. Ed 3. J. Wiley & Sons. Banco Mundial. World Development Indicators. Banco de la República. Índice de precios al consumidor. Bernal, R. (2008). The informal labor in Colombia: Indentification and characterization. Facultad de Economía, Universidad de Los Andes. Breusch, T., y Pagan, A. (1980)The LM test and its applications to model specification in econometrics. Review of Economic Studies, 47. Cameron, A. C. y Trivedi, P. (2009) Microeconometrics: Methods and applications. Cambridge. Catalán, H. Teoría de la cointegración. UNAM. Davidson, R. y Mackinnon, J. (1999). Foundations of econometrics. Draft. Davidson, R. y Mackinnon, J. (2004). Econometric theory and methods. Oxford University Press. Dougherty, C. (2007) Introduction to econometrics. 3ed. Oxford University Press Edwards, S. (1983)The short-run relation between inflation and growth in Latin America. Working paper N° 1065. NBER. Enders, W. (2004). Applied econometric time series. Ed 2. New York: John Wiley & Sons Gourieroux, C. (2000). Econometrics of qualitative dependent variables. Cambridge University Press. Granger, C. (1993) Forecasting in business and economics. Ed. 2. Elsevier Science. Granger, C. (2004) Análisis de series temporales, cointegración y aplicaciones. Revista Asturiana de Economía. Greene, W. (2000) Econometric analysis. Prentice-Hall Greene, William. (2003). Econometric analysis. Ed. 5. Pearson Prentice-Hall Gujarati, Damodar. (2003). Econometría. Ed. 4. Mc Graw Hill. Hanke, J. y Wichern, D. (2006) Pronósticos en los negocios. Ed 8. Prentice Hall. Hausman, J. y Taylor, W. (1981) Panel data and unobservable individual effects. Econometric Society Hill, Griffiths y Judge (1993) Learning and practicing econometrics. Ed. 1. New York: John Wiley Hill, Griffiths y Judge (2001) Undergraduate econometrics. Ed. 2. New York: John Wiley Hsiao, C. (2002). Analysis of panel data. Econometric society monographs. Cambridge. Johnston, J. y Dinardo, J. (1997) Econometrics methods. McGraw Hill Juan, A; Kizys, R; y Manzanedo, L. Modelos de ecuaciones simultáneas. Universitat Obertura de Catalunya. Judge, G, Hill, C, Griffiths, W, Lütketpohl, H, Lee, T. (1985) The theory and practice of econometrics. New York: John Wiley. Judge, G, Hill, C, Griffiths, W, Lütketpohl, H, Lee, T. (1988) Introduction to the theory and practice of econometrics. 2nd Sub edition New York: John Wiley & Sons. Krugman, P y Obstfeld, M. (2006). Economía internacional: Teoría y política. Pearson. Addison Wesley. Maddala, G. S. (1983). Limited-dependet and qualitative variables in econometrics. Cambridge University. Mahía, R. (2006) Breve apunte sobre la estimación de modelos multiecuacionales. Makridakis, S. y Wheelwright, S. C. (1978) Forecasting methods and applications. Ed 2. New York: John Wiley & Sons Montalvo, F. (2003) Cálculo diferencial e integral en varias variables. Universidad de Extremadura. Montenegro, A. (2007) Series de tiempo. Ed. 1. Pontificia Universidad Javeriana. Muñoz, J. y Kikut, A. (1994) El Filtro de Hodrick y Prescott: Una técnica para la extracción de la tendencia de una serie. Banco Central de Costa Rica. Oczkowski, E. (2003) Two-stage least squares (2SLS) and structural equation models (SEM) Charles Sturt University. Pena, B. El uso de retardos en los modelos econométricos uniecuacionales: Modelos autorregresivos y modelos con retardos escalonados. Instituto Nacional de Estadística de España. Perron, B, y Roger moon, H. (2006) Seemingly unrelated regressions. Pindyck, R. y Rubinfeld, D. (1981). Econometric models and econometric forecasts. Mc Graw Hill. Prada, T. (2004) Incorporación del fondo de estabilización de precios del azúcar en Colombia. Ilades-Georgetown University, School of Economics and Bussines. Pulido, A. (1987). Modelos econométricos. Ed. 1. Pirámide. Rodríguez, C, Sánchez, F y Armenta, A. (2007). Hacia una mejor educación rural: Impacto de un programa de intervención a las escuelas en Colombia. Universidad de los Andes: Documento CEDE 2007-13. Sánchez, F., Fazio, A. y López, M. (2008). Land conflict, property rights, and the rise of the export economy in Colombia, 1850-1925. Universidad de los Andes: Documento CEDE 2008-16. Shiskin, J. (1978). Seasonal adjustment of sensitive indicators. Keynote address US department of label. Vásquez, J. C. (2005). Análisis empírico del fondo de estabilización de precios del azúcar en Colombia. Memoria de grado maestría. Facultad Economía, Universidad de los Andes. Wooldridge, J. (2002). Econometric analysis of cross section and panel data. MIT Press. Wooldrige, J. (2009) Introductory econometrics. Ed. 4 Australia: South-Western/Cengage learning. Mundlak, Y. (1978) On the pooling of time series and cross section data. Econometric Society. Zellner, A. (1962) An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American Statistical Association, 57. Zellner, A., y Theil, H. (1962) Three-stage least squares: Simultaneous estimation of simultaneous equations. Econometrica N° 30. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/37183 |