1. Economic Tools 1. Graphs: review basics –A. Plotting points. –B. Computing slope. 2. Micro approach –A. Choices –B. Constraints –C. Maximization (best choice) –D. Comparative statics 3. Functions –A. Utility function –B. Household production fn 4. Totals and marginals 5. Supply & demand 6. Empirical methods –A. Regression analysis –B. Natural experiments

2. Micro Approach Choices: –have a goal (maximize something); –chooser has info and is rational; –choice has limits (budget constraint); –constrained maximization. Variables: –Endogenous (dependent); –Exogenous (independent). Theory: Posits relationship between dependent variable and independent variable(s). Functional form: X* = F(Z). Marginal decision-making. Best choice (solution): x*

3. Comparative Statics From earlier: X* = F(Z). Theory:  X*/  Z  0. If Z , this causes  X*. Relate to Law of Demand: –Simple: D = F(P); –Full version: D = F(price of X, other P, Preferences) Microeconomics: –Economic actors choose endogenous variables to maximize something. –Best choice: satisfies above total condition and a marginal condition. –Theory predicts how best choice changes when exog variables change. –Predictions: comparative static results; use to assess theory.

4. Functions Functions: convenient way to show what depends on what. –Demand function. –Could write as: D(P). Utility function: –U = U(X,Y). –X & Y are two goods; –Ordinal utility; –utility theory a theory of choice; –rational choice model. Household production function: –G = G(T,Z). –G: amount of HH goods produced. –T: first input: time. –Z: amount of all other inputs. –Like firm prod fn: Q = Q(K.L).

5. How Make Best Choice Ex.: With 2 goods X & Y. 1. Maximize total utility. 2. Equate utility on the margin –Marginal decision-making. –On the margin: as  X and  Y, utility from that last extra X is equal to utility from that last given up Y; –So:  U/  X =  U/  Y. 3. See graphically.

6. Supply and Demand Law of Demand –Qd = F(P; other P; Y; Pref) –Negative slope. Law of Supply –Qs = F(P; input prices; techn.) –Positive slope. Equilibrium –Occurs naturally. –Excess supply –Excess demand Change in ceteris paribus factor –Shift demand curve. –Shift supply curve.

7. Empirical Methods: Regression Methods: –Testing predictions of a specific theory. –Ex: Law of D:  P of X   D for X; qualitative prediction; quantitative prediction. Regression Analysis: statistical technique for estimating relationship between two or more variables. –One dependent variable and one or more independent variables. –Example: prediction from Law of D. –Write as regression equation: –Qd =  +  P +   Qd/  P =  ; (1/  is slope of D curve)  is value of Qd when P = 0; (intercept).  is random error term: See picture.

8. More on Regression Multiple regression: adds in more independent variables (usually these are ceteris paribus factors). Book calls these more Xs. Want to add in as many relevant Xs as we can (so now have  1,  2, etc.) Qd =  +  1P +  2Y +  3Pref +  –Where Y is income. If leave out an important X, then the estimated values of  and  are “bad.”

9. More on Regression Types of variables: –Continuous –Dummy: yes/no. –Natural logs: ln(wage) so  on education is a percentage returns to education. Sampling error: to what group do the results relate? R-squared: what percent of variation across individuals in dependent variable is explained by the regression?

10. Experiments Scientific experiment: testing effectiveness of a new drug. –uses double-blind random assignment. (individuals assigned to get real drug or a placebo and doctor/individual do not know which it is). –Current real experiment in labor economics: temp work for welfare-to- work population. Natural experiment: –Useful because economists usually cannot conduct real experiments. –when something like real experiment occurs in real world. –Mariel boatlift of 1980: impact of immigration on local labor markets.