Econ 140 Lecture 11 Empirical Relationships Lecture 1

Econ 140 Lecture 12 Today’s Plan Syllabus & housekeeping issues Course overview –What is econometrics? –Two econometric examples/ Examples from the textbook.

Econ 140 Lecture 13 Teaching Team Professor: Andrew K. G. Hildreth 593 Evans Hall (510) Office Hours: Monday 2-3 pm & Wednesday 10-11am Assistant: Judi Chan, (510) GSIs: Tanguy Brachet: Office Hours: location and time to be advised. Sections 104 & 106. Heather Royer: Office Hours: location and time to be advised. Sections 101 & 107. Kristy Piccinini: Office Hours: location and time to be advised. Sections 103 & 105.

Econ 140 Lecture 14 Syllabus Textbook: Stock, J. and Watson, M., Introduction to Econometrics, Addison-Wesley, Grading & ‘Harsh but Fair rules’. Final Exam: Lecture Etiquette Econometrics is a ‘doing’ or active learning subject. –Use of EXCEL. Available in all labs: times in the TMF –STATA: Anyone taking Econ195A. GSI’s - have homes to go to. When the going gets tough….

Econ 140 Lecture 15 Course Website emlab.berkeley.edu/users/hildreth/e140_f02/e140.html What you’ll find at the website: –My picture (not a good one!) –Excel files –Lecture notes –Problem Sets (& Solutions) –Midterms (after the tests) & Solutions –Supplemental handouts Also - faculty page has previous course plus other stuff. Just alter: “e140_f02/” to “e140_sp02/” and so on.

Econ 140 Lecture 16 What is Econometrics? Broadly defined: the study of economics using statistical methods Founding members of the econometric society described it: “..as the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference.” --Samuelson, P., Koopmans, T. & Stone, R. Report of the Evaluative Committee for Econometrica, Econometrica, 1954, p. 142

Econ 140 Lecture 17 Why Econometrics? When we read the newspaper or see announcements of economic statistics or predictions, how are the statistics and predictions derived? Some uses: –Returns from investing in 1 more year of school –2000 Florida election –Macroeconomic indicators (Phillips Curve) –Production function estimates

Econ 140 Lecture 18 Takeaways Econometrics is a doing subject! It is an art that must be learned through practice - working out problems algebraically, using economic data, building models using computer software No one exact way to present a statistical argument Course objective: providing you with knowledge of econometrics in theory and application Vocational uses –consultancy –business planning –politics or public policy –lawyers, circuit court judge, Supreme Court judge

Econ 140 Lecture 19 Returns to Education Examining relationship between years of education and earnings using Gary S. Becker’s 1964 theory on human capital Comparing the cost and future returns of an additional year of schooling –Future earnings are function of schooling given by: W=f (s) where s = given # years of schooling –But there’s a simultaneity problem: do you earn more because you have more schooling or do you pursue more schooling to earn higher wages?

Econ 140 Lecture 110 Returns to Education (2) Test the relationship using cross-section data from Current Population Surveys (CPS) for CA males in 1979 and 1995 You can use the 1995 data to graph gross weekly earnings vs. years of schooling, but it’s impossible to see any relationships between earnings and years of schooling The same goes for the 1979 data - it’s a mess! To highlight an array in EXCEL, hold CTRL+SHIFT and press the down arrow

Econ 140 Lecture 111 Returns to Education (3) Use conditional means to get a better approximation of the earnings and education relationship Conditional mean: the mean value of a variable Y given the value of another variable X –General formula: –In our case: W i = gross weekly earnings S = years of schooling

Econ 140 Lecture 112 Returns to Education (4) Using conditional means, you can compare the mean gross weekly earnings associated with different years of schooling - the graph is less messy There may be problems with our analysis ! –definitions of schooling changed –boundary set for top coding changed: in 1979, it was $999. In 1995 it was $1923 –Macro and microeconomic factors

Econ 140 Lecture 113 Chasing Butterflies What happened in Palm Beach, Florida during the 2000 election? Can we test the assertion that the butterfly ballot confused voters and caused them to accidentally vote for Buchanan rather than Gore? If Palm Beach County hadn’t used the butterfly ballot, can we show that Gore would have won Florida? The course website has Excel datasets of voting outcomes in Broward County, Palm Beach County, and Florida.

Econ 140 Lecture 114 Chasing Butterflies (2) Broward County is similar to Palm Beach in size and demographics, but the butterfly ballot was unique to Palm Beach Graphing the number of votes for Buchanan against those for Gore in Broward County, we see that he received less than 10 votes in any of the voting precincts Looking at the same graph for Palm Beach, we see that Buchanan received many more votes there than he did in Broward County.

Econ 140 Lecture 115 Chasing Butterflies (3) We can also look at the number of votes for a party vs. the number of registered voters for that party We see a similar upward trend for Democrats and Republicans However, for the Reform voters Palm Beach is an extreme outlier - for the other 66 counties, there were less than 1,000 Reform votes cast. Palm Beach County had 3,407 Reform votes cast!

Econ 140 Lecture 116 Chasing Butterflies (4) You can use a confidence interval to test whether the Palm Beach observation is statistically different from the others –Regress the number of Reform votes on the number of registered Reform voters by county, not including Palm Beach –We find the coefficients are highly statistically significant 95% confidence interval means that there is a 5% chance that an observation will lay outside that interval by error. Notice that Palm Beach doesn’t lie in that interval. What degree of confidence do we need to include Palm Beach in the confidence interval?

Econ 140 Lecture 117 Wrap up An overview of what’s to come An introduction to economic data and the idea of empirical relationships between two measured variables. –Example: years of education and gross earnings –Votes cast in Florida and ‘Butterfly Ballot’. Problems inherent in using economic data to test empirical relationships Conditional mean function