经济学课程

第1周主题：Course Introduction and Math Review course introduction, Matrix algebra, review of elementary probability and statistics 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Course Introduction and Math Review course introduction, Matrix algebra, review of elementary probability and statistics”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第2周主题：Review of Multiple Regression and M-estimation Review matrix treatment of multiple regression; Gauss-Markov Theorem and assumptions; conditional prediction; loss function; M-estimation; causal vs. non causal relations; examples. | Tutorial 1 Review and practice the materials covered in Lecture 1. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Review of Multiple Regression and M-estimation Review matrix treatment of multiple regression; Gauss-Markov Theorem and assumptions; conditional prediction; loss function; M-estimation; causal vs. non causal relations; examples. | Tutorial 1 Review and practice the materials covered in Lecture 1.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第3周主题：Maximum Likelihood Estimation Basic likelihood concepts; score functions; computation of MLE; large sample properties; examples from univariate and regression models; likelihood-based inference. | Tutorial 2 Review and practice the materials covered in Lecture 2. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Maximum Likelihood Estimation Basic likelihood concepts; score functions; computation of MLE; large sample properties; examples from univariate and regression models; likelihood-based inference. | Tutorial 2 Review and practice the materials covered in Lecture 2.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第4周主题：GMM Basics and Extensions Simultaneous equations framework. Essential GMM Motivation; the Analogy Principle; causal parameters; simultaneous equations; IV estimation; GMM extensions; large sample properties | Tutorial 3 Review and practice the materials covered in Lecture 3. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“GMM Basics and Extensions Simultaneous equations framework. Essential GMM Motivation; the Analogy Principle; causal parameters; simultaneous equations; IV estimation; GMM extensions; large sample properties | Tutorial 3 Review and practice the materials covered in Lecture 3.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第5周主题：Linear Panel Data Models A Advantages of panel data; basics of linear panel models; pooled, random effects and fixed effect models; target parameters and estimation by GLS; applications. | Tutorial 4 Review and practice the materials covered in Lecture 4. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Linear Panel Data Models A Advantages of panel data; basics of linear panel models; pooled, random effects and fixed effect models; target parameters and estimation by GLS; applications. | Tutorial 4 Review and practice the materials covered in Lecture 4.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第6周主题：Linear Panel Data Models B Extensions of basic models; types of exogeneity; endogenous regressors; dynamic models; GMM methods; application to MABEL data. Friday, April 3rd, is Good Friday, a public holiday, so there will be no classroom lectures or consultation sessions that day. A recorded lecture will be uploaded to Ultra for students to access. Students who typically attend tutorials on this day are encouraged to 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Linear Panel Data Models B Extensions of basic models; types of exogeneity; endogenous regressors; dynamic models; GMM methods; application to MABEL data. Friday, April 3rd, is Good Friday, a public holiday, so there will be no classroom lectures or consultation sessions that day. A recorded lecture will be uploaded to Ultra for students to access. Students who typically attend tutorials on this day are encouraged to”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第7周主题：Simulation-based Estimation and Inference Computer-intensive methods for estimation and inference; simulation-based MLE and GMM; bootstrap standard errors; applications to panel models. | Tutorial 6 Review and practice the materials covered in Lecture 6. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Simulation-based Estimation and Inference Computer-intensive methods for estimation and inference; simulation-based MLE and GMM; bootstrap standard errors; applications to panel models. | Tutorial 6 Review and practice the materials covered in Lecture 6.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第8周主题：Quantile Regression Conditional quantiles (CQ); semiparametric models; marginal quantiles; MAD and CQ estimation; advantages of non separable heterogeneous responses; treatment effects. 18 April is a public holiday. No class, tutorial, or consultation session will be held that day. | Tutorial 7 Review and practice the materials covered in Lecture 7. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Quantile Regression Conditional quantiles (CQ); semiparametric models; marginal quantiles; MAD and CQ estimation; advantages of non separable heterogeneous responses; treatment effects. 18 April is a public holiday. No class, tutorial, or consultation session will be held that day. | Tutorial 7 Review and practice the materials covered in Lecture 7.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第9周主题：Hypothesis Tests Key concepts related to hypothesis tests, Wald, criterion-based, and score tests. | Tutorial 8 Review and practice the materials covered in Lecture 8. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Hypothesis Tests Key concepts related to hypothesis tests, Wald, criterion-based, and score tests. | Tutorial 8 Review and practice the materials covered in Lecture 8.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第10周主题：Non-parametric and Flexible Parametric Methods A Kernel density and regression; mixture models; kernel regression; mixture of normals; inference on mixture models 5 May is a public holiday. No class, tutorial, or consultation session will be held that day. | Tutorial 9 Review and practice the materials covered in Lecture 9. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Non-parametric and Flexible Parametric Methods A Kernel density and regression; mixture models; kernel regression; mixture of normals; inference on mixture models 5 May is a public holiday. No class, tutorial, or consultation session will be held that day. | Tutorial 9 Review and practice the materials covered in Lecture 9.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第11周主题：Non-parametric and Flexible Parametric Methods B Kernel density and kernel regression; mixture of normals; inference on mixture models; relationship to semiparametric models; random effects and mixed models. | Tutorial 10 Review and practice the materials covered in Lecture 10. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Non-parametric and Flexible Parametric Methods B Kernel density and kernel regression; mixture of normals; inference on mixture models; relationship to semiparametric models; random effects and mixed models. | Tutorial 10 Review and practice the materials covered in Lecture 10.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第12周主题：Big Data and Machine Learning High dimensional regression; Ridge regression; LASSO; penalty variable selection; LASSO IV; double/debiased machine learning. | Tutorial 11 Review and practice the materials covered in Lecture 11. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Big Data and Machine Learning High dimensional regression; Ridge regression; LASSO; penalty variable selection; LASSO IV; double/debiased machine learning. | Tutorial 11 Review and practice the materials covered in Lecture 11.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。

第13周主题：Review Lecture Review lecture | Tutorial 12 Review and practice the materials covered in Lecture 12. 本周先完成 Lecture/Reading 的概念梳理，再用 tutorial 或题目验证理解，重点是把概念转成可解释的步骤。 学习重点：围绕“Review Lecture Review lecture | Tutorial 12 Review and practice the materials covered in Lecture 12.”识别关键术语、方法边界和常见误区，输出一页结构化笔记（定义、方法、例题、易错点）。 实操建议：至少完成 2-3 个与本周主题直接相关的练习，并记录每题的假设与推导过程，避免只记结论。 交付与复盘：对照 ECON7320 的 assessment 要求检查本周产出，保留可复用模板用于后续周和考前复盘。