1、Chapter 1,The Nature of Econometrics and Economic Data,Wooldridge: Introductory Econometrics: A Modern Approach, 5e Instructed by professor Yuan, Huiping,Chapter 1 The Nature of Econometrics and Economic Data,1.1 What Is Econometrics?,1.2 Steps in Empirical Economic Analysis,1.3 The Structure of Eco

2、nomic Data,1.4 Causality and Ceteris Paribus in Econometric Analysis,The End,Appendix A: Basic Mathematical Tools,Chapter 1 The Nature of Econometrics and Economic Data,What is econometrics? Econometrics = use of statistical methods to analyze economic data Econometricians typically analyze nonexper

3、imental data Typical goals of econometric analysis Estimating relationships between economic variables Testing economic theories and hypotheses Forecasting economic variables Evaluating and implementing government and business policy,Chapter,End,1.1 What Is Econometrics?,Steps in econometric analysi

4、s 1) Economic model (this step is often skipped) 2) Econometric model Economic models Maybe micro- or macromodels Often use optimizing behaviour, equilibrium modeling, Establish relationships between economic variables Examples: demand equations, pricing equations, ,Chapter 1 The Nature of Econometr

5、ics and Economic Data,Chapter,End,1.2 Steps in Empirical Economic Analysis (1/5),Economic model of crime (Becker (1968) Derives equation for criminal activity based on utility maximization Functional form of relationship not specified Equation could have been postulated without economic modeling,Hou

6、rs spent in criminal activities,Wage“ of cri- minal activities,Wage for legal employment,Other income,Probability of getting caught,Probability of conviction if caught,Expected sentence,Age,Chapter 1 The Nature of Econometrics and Economic Data,Chapter,End,1.2 Steps in Empirical Economic Analysis (2

7、/5),Model of job training and worker productivity What is effect of additional training on worker productivity? Formal economic theory not really needed to derive equation: Other factors may be relevant, but these are the most important (?),Hourly wage,Years of formal education,Years of work- force

8、experience,Weeks spent in job training,Chapter 1 The Nature of Econometrics and Economic Data,Chapter,End,1.2 Steps in Empirical Economic Analysis (3/5),Econometric model of criminal activity The functional form has to be specified Variables may have to be approximated by other quantities,Measure of

9、 cri- minal activity,Wage for legal employment,Other income,Frequency of prior arrests,Frequency of conviction,Average sentence length after conviction,Age,Unobserved deter- minants of criminal activity,e.g. moral character, wage in criminal activity, family background ,Chapter 1 The Nature of Econo

10、metrics and Economic Data,Chapter,End,1.2 Steps in Empirical Economic Analysis (4/5),Econometric model of job training and worker productivity Most of econometrics deals with the specification of the error Econometric models may be used for hypothesis testing For example, the parameter represents ef

11、fect of training on wage How large is this effect? Is it different from zero?,Hourly wage,Years of formal education,Years of work- force experience,Weeks spent in job training,Unobserved deter- minants of the wage,e.g. innate ability, quality of education, family background ,Chapter 1 The Nature of

12、Econometrics and Economic Data,Chapter,End,1.2 Steps in Empirical Economic Analysis (5/5),Different kinds of economic data sets Cross-sectional data Time series data Pooled cross sections Panel/Longitudinal data Econometric methods depend on the nature of the data used Use of inappropriate methods m

13、ay lead to misleading results,Chapter 1 The Nature of Econometrics and Economic Data,Chapter,End,1.3 The Structure of Economic Data (1/10),Cross-sectional data sets Sample of individuals, households, firms, cities, states, countries, or other units of interest at a given point of time/in a given per

14、iod Cross-sectional observations are more or less independent For example, pure random sampling from a population Sometimes pure random sampling is violated, e.g. units refuse to respond in surveys, or if sampling is characterized by clustering Cross-sectional data typically encountered in applied m

15、icroeconomics,Chapter 1 The Nature of Econometrics and Economic Data,Chapter,End,1.3 The Structure of Economic Data (2/10),Observation number,Hourly wage,Indicator variables (1=yes, 0=no),Cross-sectional data set on wages and other characteristics,Chapter 1 The Nature of Econometrics and Economic Da

16、ta,Chapter,End,1.3 The Structure of Economic Data (3/10),Cross-sectional data on growth rates and country characteristics,Adult secondary education rates,Government consumtion as percentage of GDP,Growth rate of real per capita GDP,Chapter 1 The Nature of Econometrics and Economic Data,Chapter,End,1

17、.3 The Structure of Economic Data (4/10),Time series data Observations of a variable or several variables over time For example, stock prices, money supply, consumer price index, gross domestic product, annual homicide rates, automobile sales, Time series observations are typically serially correlat

18、ed Ordering of observations conveys important information Data frequency: daily, weekly, monthly, quarterly, annually, Typical features of time series: trends and seasonality Typical applications: applied macroeconomics and finance,Chapter 1 The Nature of Econometrics and Economic Data,Chapter,End,1

19、.3 The Structure of Economic Data (5/10),Time series data on minimum wages and related variables,Unemployment rate,Average coverage rate,Average minimum wage for given year,Gross national product,Chapter 1 The Nature of Econometrics and Economic Data,Chapter,End,1.3 The Structure of Economic Data (6

20、/10),Pooled cross sections Two or more cross sections are combined in one data set Cross sections are drawn independently of each other Pooled cross sections often used to evaluate policy changes Example: Evaluate effect of change in property taxes on house prices Random sample of house prices for t

21、he year 1993 A new random sample of house prices for the year 1995 Compare before/after (1993: before reform, 1995: after reform),Chapter 1 The Nature of Econometrics and Economic Data,Chapter,End,1.3 The Structure of Economic Data (7/10),Pooled cross sections on housing prices,Number of bathrooms,S

22、ize of house in square feet,Property tax,Before reform,After reform,Chapter 1 The Nature of Econometrics and Economic Data,Chapter,End,1.3 The Structure of Economic Data (8/10),Panel or longitudinal data The same cross-sectional units are followed over time Panel data have a cross-sectional and a ti

23、me series dimension Panel data can be used to account for time-invariant unobservables Panel data can be used to model lagged responses Example: City crime statistics; each city is observed in two years Time-invariant unobserved city characteristics may be modeled Effect of police on crime rates may

24、 exhibit time lag,Chapter 1 The Nature of Econometrics and Economic Data,Chapter,End,1.3 The Structure of Economic Data (9/10),Two-year panel data on city crime statistics,Each city has two time series observations,Number of police in 1986,Number of police in 1990,Chapter 1 The Nature of Econometric

25、s and Economic Data,Chapter,End,1.3 The Structure of Economic Data (10/10),Causality and the notion of ceteris paribus Most economic questions are ceteris paribus questions It is important to define which causal effect one is interested in It is useful to describe how an experiment would have to be

26、designed to infer the causal effect in question,Definition of causal effect of on :,How does variable change if variable is changed but all other relevant factors are held constant“,Chapter,End,1.4 Causality and Ceteris Paribus in Econometric Analysis (1/6),Chapter 1 The Nature of Econometrics and E

27、conomic Data,Causal effect of fertilizer on crop yield By how much will the production of soybeans increase if one increases the amount of fertilizer applied to the ground“ Implicit assumption: all other factors that influence crop yield such as quality of land, rainfall, presence of parasites etc.

28、are held fixed Experiment: Choose several one-acre plots of land; randomly assign different amounts of fertilizer to the different plots; compare yields Experiment works because amount of fertilizer applied is unrelated to other factors influencing crop yields,Chapter,End,1.4 Causality and Ceteris P

29、aribus in Econometric Analysis (2/6),Chapter 1 The Nature of Econometrics and Economic Data,Measuring the return to education If a person is chosen from the population and given another year of education, by how much will his or her wage increase? “ Implicit assumption: all other factors that influe

30、nce wages such as experience, family background, intelligence etc. are held fixed Experiment: Choose a group of people; randomly assign different amounts of eduction to them (infeasable!); compare wage outcomes Problem without random assignment: amount of education is related to other factors that i

31、nfluence wages (e.g. intelligence),Chapter,End,1.4 Causality and Ceteris Paribus in Econometric Analysis (3/6),Chapter 1 The Nature of Econometrics and Economic Data,Effect of law enforcement on city crime level If a city is randomly chosen and given ten additional police officers, by how much would

32、 its crime rate fall? “ Alternatively: If two cities are the same in all respects, except that city A has ten more police officers, by how much would the two cities crime rates differ?“ Experiment: Randomly assign number of police officers to a large number of cities In reality, number of police off

33、icers will be determined by crime rate (simultaneous determination of crime and number of police),Chapter,End,1.4 Causality and Ceteris Paribus in Econometric Analysis (4/6),Chapter 1 The Nature of Econometrics and Economic Data,Effect of the minimum wage on unemployment By how much (if at all) will

34、 unemployment increase if the minimum wage is increased by a certain amount (holding other things fixed)? “ Experiment: Government randomly chooses minimum wage each year and observes unemployment outcomes Experiment will work because level of minimum wage is unrelated to other factors determining unemployment In