Variables:
DIST_CODE:
DISTRICT CODE;
READ_SCR:
AVG READING SCORE;
MATH_SCR:
AVG MATH SCORE;
COUNTY :
COUNTY;
DISTRICT:
DISTRICT;
GR_SPAN:
GRADE SPAN OF DISTRICT;
应用计量经济学
Instructor: Fred Engst (阳和平) (or just Fred)
Best way to contact me is by email: engst.uibe@, or engst@
应用计量经济学
第一课
Econometrics in the News
e.g. the weight records of all the students here for each day and fofication of data type:
Q: the data in the published 2012 Statistical Abstract of China is typically of what kind?
＋ 制造业 1745.2 2192.0 3866.6 4492.7 5251.6 6587.2 7278.0 7717.4
＋ 其他） 881.6 994.2 2607.8 3018.6 3602.7 4624.6 5486.3 5933.4
A) Cross Section B) Time Series Sure
The “ Art ” of Econometrics
The Art of Econometrics
A general approach to variable selection and model specification: (回归变量的选择)
Specify a “base” or “benchmark” model.(基准设 定)
Student-teacher ratio (STR) = no. of students in the district divided by no. full-time equivalent teachers
Q: What kind of data is this?
Initial look at the data:
(You should already know how to interpret this table)
Is there a relationship?
Scatterplot of test score v. student-teacher ratio
Do districts with smaller classes have higher test scores? What does this figure show?
C) Panel D) Not
What kind of data is this?
收入 张三 李四 。。。 2000年 23145 43251 2001年 25389 46239 。。。 2009年 30125 52395
王麻子 65234 67341
70128
A) Cross Section B) Time Series C) Panel D) Not Sure
home learning environment
(家庭环境)
parent’s education level…
(家长教育水平)
Variables actually in the California class size data set: (我们实际得到的)
ENRL_TOT :
TOTAL ENROLLMENT;
TEACHERS:
NUMBER OF TEACHERS;
COMPUTER:
NUMBER OF COMPUTERS;
TESTSCR:
AVG TEST SCORE (= (READ_SCR+MATH_SCR)/2 );
COMP_STU:
COMPUTERS PER STUDENT ( = COMPUTER/ENRL_TOT);
Specify a range of plausible alternative models, which include additional candidate variables.
Does a candidate variable change the coefficient of
interest (1)? (改变因子集对基准设定的影响)
图为淮河以北预期寿命下降5年。
The Purpose of Econometrics
从数据中找规律性的关系
Types of data:
To correctly identify the types of data, we need to understand the difference between entity and variable, in which each entity has infinite variables.
A True Panel vs.
A Pooled Cross Section
Often loosely use the term panel data to refer to any data set that has both a crosssectional dimension and a time-series dimension
这份研究 发现，长 期暴露于 污染空气 中，总悬 浮颗粒物 （TSP） 每上升 100微克/ 立方米， 平均预期 寿命将缩 短3年。
图为淮河以北TSP上升247.5微克/立方米
按照北 方地区 总悬浮 颗粒物 的水平， 这意味 着中国 北方5 亿居民 因严重 的空气 污染平 均每人 失去5 年寿命， 污染的 代价巨 大。
A) Cross Section
平均劳动报酬 39,684 27,628 16,456 18,106 18,382 19,365 16,393 15,894 37,585 23,657 27,570 17,610 19,424 15,370 19,135
B) Time Series C) Panel
D) Not Sure
What kind of data is this?
年
GDP
1978 3645.2
1980 4545.6
1985 9016.0
1986 10275.2
1987 12058.6
1988 15042.8
1989 16992.3
1990 18667.8
＝（养殖业 1018.4 1359.4 2541.6 2763.9 3204.3 3831.0 4228.0 5017.0
Cross-sectional data (截面数据)
e.g. recordings of every student’s weight for today
Time series (时间序列)
e.g. the weight record of a person over a year.
Panel data (面板数据)—the combination of cross-section and time series
Variables we would like to see in the California data set: (我们希望得到的变量)
School characteristics: (学校因素)
student-teacher ratio
(学生-教师比)
teacher quality
(教师质量)
食堂伙食评价 学生1 学生2 。。。 学生98
2000
3
9
7
学生A 学生B 学生C 。。。
2001 。。。
8
。。。 学生甲
5 学生乙
7 学生丙
学生丁
2009
5
9
3
6
学生105 6
。。。
学生79 2
A) Cross Section B) Time Series C) Panel D) Not Sure
The Purpose of Econometrics Types of Data The "Art" of Econometrics（计量的艺术性）
Econometrics in the News
清华经管学院李宏彬等在《美国科学院院刊》(2013年7月8 日)发表论文阐释空气污染对预期寿命的影响
computers (non-teaching resources) per student (教学设备)
measures of curriculum design… (教材质量)
Student characteristics:(学生因素)
English proficiency
(英语程度)
availability of extracurricular enrichment (课外活动)
Q: What kind of data is the published stock market activities?
What kind of data is this?
地区 北京 天津 河北 山西 内蒙古 辽宁 吉林 黑龙江 上海 江苏 浙江 安徽 福建 江西 山东
年均人数（万） 514 195 501 366 243 498 266 497 333 679 611 338 427 283 898
研究者收集了1981年到2000年间、淮河南北90座城市每日 总悬浮颗粒物浓度的数据，并通过中国疾病监控系统的数 据，计算出1991年到2000年上述城市的各年龄段死亡率、 预期寿命和死于心肺疾病的数量。