Explore BrainMass
Share

Explore BrainMass

    Regression analysis

    This content was COPIED from BrainMass.com - View the original, and get the already-completed solution here!

    Suppose you have cross-section data on income (y) and electricity consumption (x) for three regions and you have regressed ln x on an intercept and ln y for each region and for the full sample, obtaining the following results:

    Estimated Intercept Std Error. Slope Std. Error SSE n
    Region A 0.02 0.008 1.10 0.05 48 92
    Region B 0.01 0.003 0.90 0.1 35 82
    Region C 0.015 0.001 0.85 0.08 17 32
    All regions0.03 0.0015 0.88 0.05 112 206

    a. Test (at the 5% level) that this equation is the same for all regions.

    b. Assuming that these equations are the same (regardless of your answer to (a)), test (at the 5% level) that the common income elasticity is 1.

    c. Suppose you know that the intercepts are definitely different for all three regions. Explain what you would do to answer parts (a) and (b) given this knowledge (i.e. outline any changes in estimation and inference relative to your previous answers).

    © BrainMass Inc. brainmass.com October 10, 2019, 4:27 am ad1c9bdddf
    https://brainmass.com/statistics/regression-analysis/regression-difference-testing-econometrics-461179

    Solution Preview

    Please see the answers

    Regression / Difference Testing (ECONOMETRICS)
    Suppose you have cross-section data on income (y) and electricity consumption (x) for three regions and you have regressed ln x on an intercept and ln y for each region and for the full sample, obtaining the following results:

    Estimated Intercept Std Error. Slope Std. Error SSE n
    Region A 0.02 0.008 1.10 0.05 48 92
    Region B 0.01 0.003 0.90 0.1 35 82
    Region C 0.015 0.001 0.85 0.08 17 32
    All regions 0.03 0.0015 0.88 0.05 112 206

    a) Test (at the 5% level) that this equation is the same for all regions.
    Here t test can be used to test whether the intercept and ...

    Solution Summary

    Step by step method for computing regression model s given in the answer.

    $2.19