## Figure

(Continued )

16See Chandan Mukherjee, Howard White, and Marc Wuyts, Econometrics and Data Analysis for Developing Countries, Routledge, London, 1998, p. 158. This quote is attributed to H. Working, "Statistical Laws of Family Expenditure," Journal of the American Statistical Association, vol. 38, 1943, pp. 43-56.

CHAPTER SIX: EXTENSIONS OF THE TWO-VARIABLE LINEAR REGRESSION MODEL 183

AN ILLUSTRATIVE EXAMPLE (Continued)

Interpreted in the manner described earlier, the slope coefficient of about 257 means that an increase in the total food expenditure of 1 percent, on average, leads to about 2.57 rupees increase in the expenditure on food of the 55 families included in the sample. (Note: We have divided the estimated slope coefficient by 100.)

Before proceeding further, note that if you want to compute the elasticity coefficient for the log—lin or lin—log models, you can do so from the definition of the elasticity coefficient given before, namely,

Elasticity = d^Y

As a matter of fact, once the functional form of a model is known, one can compute elasticities by applying the preceding definition. (Table 6.6, given later, summarizes the elasticity coefficients for the various models.)

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