Lecture by: Jacinto Fabiosa Fall 2005 Methodology in Economics

2 Modeling Modeling – simplified (abstract) representation of relationships of agents and variables that exist in reality. –Structure of model Identify economic agents and objective Identify decision variables and given variables Specify relations of variables –Outcomes Decision rules Equilibrium conditions

3 Modeling Determined in the model – values they take are determined in the model (e.g., quantity demanded) –Endogenous variables –Decision variables –Dependent variables Given or assumed in the model – values they take are given or assumed (e.g., income of households) –Exogenous variables –Independent variables

4 Modeling Representation of relationships of variables in a model –Table form presentation of data –Graphical form –Functional form Individual equations or systems Specific functional forms (e.g., linear, quadratic, logarithmic, exponential) Specific parameters

5 Tables of Related Variables Table A.1 Advertising and Sales at Len & Harry’s

6 Graphs of Related Variables

7 Graphs - Curves

8 Slopes and Intercepts

9 Shifts in the Graphs

10 Shifts in Lines and Curves

11 Solving Equations Y = X If X = 4, solve for Y Y = (4) = Y = 52 If Y = 64, solve for X 64 = X 3X = 64 – 40 = 24 X = 24/3 X = 8

12 Solving Equations Equation 1Qd = 500 – 50P Equation 2Qs = P Solve for Qd, Qs, and P Equate the two equations, i.e., Qd=Qs 500 – 50P = P 1 equation 1 unknown, solve for P = 50P + 25P 75P = 450 P = 450/75 P = 6 Substitute P=6 in either equation 1 or 2 Qd = 500 – 50(6) = = 200 Qs = (6) = = 200

13 Applied Modeling Process Specification – edogenous-exogenous variables and their functional form Estimation of parameters Validation –Theoretical consistency of estimates Signs Magnitudes –Statistical properties of estimates Fit Significance –Forecasting performance of model