The demand function for good X is ππ₯ π = π β πππ₯ + ππ + π . Where ππ₯ is the price of good X and M is income . Least squares regression reveals that Γ’ = 8.27, bΛ = 2.14, cΛ = 0.36, πΓ’ = 5.32, ππΛ = 0.41, and ππΛ = 0.22. The R-squared is 0.35. a. Compute the t-statistic for each of the estimated coefficients. (4mks) b. Determine which (if any) of the estimated coefficients are statistically different from zero. (4mks) c. Explain, in plain words, what the R-square in this regression indicates. (
"Qxd=a-bPx+cm+e"
Fitting in the estimated coefficients
"Qxd=8.27-2.14Px+0.36M+e"
"ta=\\frac{a}{da}=\\frac{8.27}{5.32}=1.55"
"tb=\\frac{b}{db}=\\frac{2.14}{0.41}=5.22"
"tc=\\frac{c}{dc}=\\frac{0.36}{0.22}=1.64"
Where ta, tb and tc represents the t test values for a, b and c respectively.
- Only the estimated coefficients of b is statistically different from zero. This is because it's t-value (5.22) is greater than the table t-value= 2.776.
- The R-square 0.35 explains 35% of the total valuation of demand for good X in relation to price and income. The remaining 65% is attributed to the error term and other factors affecting demand.
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