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14.385 Nonlinear Econometric Analysis (MIT) 14.385 Nonlinear Econometric Analysis (MIT)

Description

This course presents micro-econometric models, including large sample theory for estimation and hypothesis testing, generalized method of moments (GMM), estimation of censored and truncated specifications, quantile regression, structural estimation, nonparametric and semiparametric estimation, treatment effects, panel data, bootstrapping, simulation methods, and Bayesian methods. The methods are illustrated with economic applications. This course presents micro-econometric models, including large sample theory for estimation and hypothesis testing, generalized method of moments (GMM), estimation of censored and truncated specifications, quantile regression, structural estimation, nonparametric and semiparametric estimation, treatment effects, panel data, bootstrapping, simulation methods, and Bayesian methods. The methods are illustrated with economic applications.Subjects

nonlinear | nonlinear | econometric | econometric | analysis | analysis | generalized method of moments | generalized method of moments | GMM | GMM | maximum likelihood estimation | maximum likelihood estimation | MLE | MLE | minimum distance | minimum distance | extremum | extremum | large sample theory | large sample theory | asymptotic theory | asymptotic theory | discrete choice | discrete choice | censoring | censoring | sample selection | sample selection | bootstrap | bootstrap | subsampling | subsampling | finite-sample methods | finite-sample methods | quantile regression | quantile regression | QR | QR | distributional methods | distributional methods | Bayesian methods | Bayesian methods | quasi-Bayesian methods | quasi-Bayesian methods | bounds | bounds | partial identification | partial identification | weak instruments | weak instruments | many instruments | many instruments | instrumental variables | instrumental variables | nonparametric estimation | nonparametric estimation | semiparametric estimation | semiparametric estimation | treatment effects | treatment effects | nonlinear models | nonlinear models | panel data | panel data | economic modeling | economic modelingLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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A 10 year old cat being investigated for weight loss, being held for a jugular blood sample.Subjects

svmsvet | cat | blood | sample | a0009 | catrestraint | cats | feline | felines | bloodsample | jugularsample | jugularbloodsample | catbloodsample | catbloods | catblood | felinebloodsampleLicense

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A 10 year old cat being investigated for weight loss, being held for a jugular blood sample.Subjects

svmsvet | cat | blood | sample | a0009 | catrestraint | cats | feline | felines | bloodsample | jugularsample | jugularbloodsample | catbloodsample | catbloods | catblood | felinebloodsampleLicense

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Overview of probability and non-probability sampling techniques in quantitative research.Subjects

confidence intervals | sampling error | snowball sampling | quota sampling | convenience sampling | stratification | cluster/ multi-stage random sample | stratified random sample | systematic sample | simple random sample | non-probability sample | ukoer | learning from woerk | lfwoer | uopcpdrm | work-based learning | wbl | continuous professional development | cpd | probability sample | Social studies | L000License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Site sourced from

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A 10 year old cat being investigated for weight loss, being held for a jugular blood sample.Subjects

svmsvet | cat | blood | sample | a0009 | jugular | bloodsample | catbloodsample | catbloodsampling | bloodsampling | jugularbloodsample | felinebloodsample | felineblood | catblood | catbloods | felinebloods | feline | catsLicense

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A 10 year old cat being investigated for weight loss, being held for a jugular blood sample.Subjects

svmsvet | cat | blood | sample | a0009 | jugular | bloodsample | catbloodsample | catbloodsampling | bloodsampling | jugularbloodsample | felinebloodsample | felineblood | catblood | catbloods | felinebloods | feline | catsLicense

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See all metadata14.381 Statistical Method in Economics (MIT) 14.381 Statistical Method in Economics (MIT)

Description

This course is divided into two sections, Part I and Part II. Part I provides an introduction to statistical theory and can be found by visiting 14.381 Fall 2013. Part II, found here, prepares students for the remainder of the econometrics sequence. The emphasis of the course is to understand the basic principles of statistical theory. A brief review of probability will be given; however, this material is assumed knowledge. The course also covers basic regression analysis. Topics covered include probability, random samples, asymptotic methods, point estimation, evaluation of estimators, Cramer-Rao theorem, hypothesis tests, Neyman Pearson lemma, Likelihood Ratio test, interval estimation, best linear predictor, best linear approximation, conditional expectation function, buil This course is divided into two sections, Part I and Part II. Part I provides an introduction to statistical theory and can be found by visiting 14.381 Fall 2013. Part II, found here, prepares students for the remainder of the econometrics sequence. The emphasis of the course is to understand the basic principles of statistical theory. A brief review of probability will be given; however, this material is assumed knowledge. The course also covers basic regression analysis. Topics covered include probability, random samples, asymptotic methods, point estimation, evaluation of estimators, Cramer-Rao theorem, hypothesis tests, Neyman Pearson lemma, Likelihood Ratio test, interval estimation, best linear predictor, best linear approximation, conditional expectation function, builSubjects

statistical theory | statistical theory | econometrics | econometrics | regression analysis | regression analysis | probability | probability | random samples | random samples | asymptotic methods | asymptotic methods | point estimation | point estimation | evaluation of estimators | evaluation of estimators | Cramer-Rao theorem | Cramer-Rao theorem | hypothesis tests | hypothesis tests | Neyman Pearson lemma | Neyman Pearson lemma | Likelihood Ratio test | Likelihood Ratio test | interval estimation | interval estimation | best linear predictor | best linear predictor | best linear approximation | best linear approximation | conditional expectation function | conditional expectation function | building functional forms | building functional forms | regression algebra | regression algebra | Gauss-Markov optimality | Gauss-Markov optimality | finite-sample inference | finite-sample inference | consistency | consistency | asymptotic normality | asymptotic normality | heteroscedasticity | heteroscedasticity | autocorrelation | autocorrelationLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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A 10 year old cat being investigated for weight loss, being prepped for a jugular blood sample.Subjects

svmsvet | cat | blood | sample | a0009 | cats | bloodsample | catrestraint | bloodsamplerestraint | catbloodsample | catbloodsLicense

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A 10 year old cat being investigated for weight loss, being prepped for a jugular blood sample.Subjects

svmsvet | cat | blood | sample | a0009 | cats | bloodsample | catrestraint | bloodsamplerestraint | catbloodsample | catbloodsLicense

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Overview of key sampling terminology.Subjects

non probability sample | probability sample | non sampling error | non response | sampling error | sampling variability | sampling bias | representative sample | sampling units | sampling frame | target population | population | sample | ukoer | learning from woerk | lfwoer | uopcpdrm | work-based learning | wbl | continuous professional development | cpd | census | Social studies | L000License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/Site sourced from

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See all metadata14.385 Nonlinear Econometric Analysis (MIT)

Description

This course presents micro-econometric models, including large sample theory for estimation and hypothesis testing, generalized method of moments (GMM), estimation of censored and truncated specifications, quantile regression, structural estimation, nonparametric and semiparametric estimation, treatment effects, panel data, bootstrapping, simulation methods, and Bayesian methods. The methods are illustrated with economic applications.Subjects

nonlinear | econometric | analysis | generalized method of moments | GMM | maximum likelihood estimation | MLE | minimum distance | extremum | large sample theory | asymptotic theory | discrete choice | censoring | sample selection | bootstrap | subsampling | finite-sample methods | quantile regression | QR | distributional methods | Bayesian methods | quasi-Bayesian methods | bounds | partial identification | weak instruments | many instruments | instrumental variables | nonparametric estimation | semiparametric estimation | treatment effects | nonlinear models | panel data | economic modelingLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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Two nurses take a blood sample from a cat to make a blood glucose curveSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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Two nurses take a blood sample from a cat to make a blood glucose curveSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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Two nurses take a blood sample from a cat to make a blood glucose curveSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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Two nurses take a blood sample from a cat to make a blood glucose curveSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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A cat after having a blood sample takenSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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A vet and a nurse take a blood sample from a cat for a blood glucose curveSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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A vet and a nurse take a blood sample from a cat for a blood glucose curveSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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Two nurses take a blood sample from a cat to make a blood glucose curveSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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Two nurses take a blood sample from a cat to make a blood glucose curveSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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A cat after having a blood sample takenSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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A vet and a nurse take a blood sample from a cat for a blood glucose curveSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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A vet and a nurse take a blood sample from a cat for a blood glucose curveSubjects

svmsvet | diabetes | cat | cats | feline | felines | diabetic | diabetemellitus | catdiabetes | diabeticcat | diabetescheck | catdiabeticcheck | catdiabetescheck | bloodglucose | bloodglucosecurve | catbloodglucose | diabeticmonitoring | catdiabeticmonitoring | felinediabetesmellitus | felinediabetes | diabetesmonitoring | b0002 | blood | bloods | bloodsample | bloodsampling | catbloods | catbloodsample | cephalicbloodsampleLicense

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See all metadata14.381 Statistical Method in Economics (MIT)

Description

?This course is divided into two sections, Part I and Part II. Part I provides an introduction to statistical theory and can be found by visiting 14.381 Fall 2013. Part II, found here, prepares students for the remainder of the econometrics sequence. The emphasis of the course is to understand the basic principles of statistical theory. A brief review of probability will be given; however, this material is assumed knowledge. The course also covers basic regression analysis. Topics covered include probability, random samples, asymptotic methods, point estimation, evaluation of estimators, Cramer-Rao theorem, hypothesis tests, Neyman Pearson lemma, Likelihood Ratio test, interval estimation, best linear predictor, best linear approximation, conditional expectation function, builSubjects

statistical theory | econometrics | regression analysis | probability | random samples | asymptotic methods | point estimation | evaluation of estimators | Cramer-Rao theorem | hypothesis tests | Neyman Pearson lemma | Likelihood Ratio test | interval estimation | best linear predictor | best linear approximation | conditional expectation function | building functional forms | regression algebra | Gauss-Markov optimality | finite-sample inference | consistency | asymptotic normality | heteroscedasticity | autocorrelationLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata14.381 Statistical Method in Economics (MIT) 14.381 Statistical Method in Economics (MIT)

Description

This course is divided into two sections, Part I and Part II. Part I, found here, provides an introduction to statistical theory. A brief review of probability will be given mainly as background material, however, it is assumed to be known. Topics include normal distribution, limit theorems, Bayesian concepts, and testing, among others. Part II prepares students for the remainder of the econometrics sequence and and can be found by visiting 14.381 Fall 2006. This course is divided into two sections, Part I and Part II. Part I, found here, provides an introduction to statistical theory. A brief review of probability will be given mainly as background material, however, it is assumed to be known. Topics include normal distribution, limit theorems, Bayesian concepts, and testing, among others. Part II prepares students for the remainder of the econometrics sequence and and can be found by visiting 14.381 Fall 2006.Subjects

economics | economics | statistics | statistics | sample | sample | population | population | convergence | convergence | limits | limits | method | method | testing | testing | confidence sets | confidence sets | Bayesian | BayesianLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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