CHAPTER 6: EXTENSIONS OF THE TWO-VARIABLE LINEAR REGRESSION MODEL ECONOMETRICS I CHAPTER 6: EXTENSIONS OF THE TWO-VARIABLE LINEAR REGRESSION MODEL Textbook: Damodar N. Gujarati (2004) Basic Econometrics, 4th edition, The McGraw-Hill Companies

6.1 REGRESSION THROUGH THE ORIGIN

6.1 REGRESSION THROUGH THE ORIGIN

6.1 REGRESSION THROUGH THE ORIGIN

6.1 REGRESSION THROUGH THE ORIGIN

6.1 REGRESSION THROUGH THE ORIGIN

6.1 REGRESSION THROUGH THE ORIGIN

6.1 REGRESSION THROUGH THE ORIGIN Homework: Calculate , , and raw r2, and draw the estimated regression line. Y X 14 4 22 6 24 7 60 10 5 3

6.2 SCALING AND UNITS OF MEASUREMENT To grasp the ideas developed in this section, consider the data given in Table 6.2, which refers to U.S. gross private domestic investment (GPDI) and gross domestic product (GDP), in billions as well as millions of (chained) 1992 dollars.

6.2 SCALING AND UNITS OF MEASUREMENT

6.2 SCALING AND UNITS OF MEASUREMENT

6.2 SCALING AND UNITS OF MEASUREMENT

6.2 SCALING AND UNITS OF MEASUREMENT

6.2 SCALING AND UNITS OF MEASUREMENT

6.4 FUNCTIONAL FORMS OF REGRESSION MODELS

6.5 HOW TO MEASURE ELASTICITY: THE LOG-LINEAR MODEL

6.5 HOW TO MEASURE ELASTICITY: THE LOG-LINEAR MODEL

6.5 HOW TO MEASURE ELASTICITY: THE LOG-LINEAR MODEL

6.6 SEMILOG MODELS LOG–LIN MODEL Compound interest formula:

LOG–LIN MODEL

LIN-LOG MODEL

LIN-LOG MODEL

6.7 RECIPROCAL MODELS

6.7 RECIPROCAL MODELS

6.7 RECIPROCAL MODELS

THE SLOPE AND ELASTICITY COEFFICIENTS OF THE VARIOUS MODELS