This dataset contains a time series of 30 monthly observations on ice cream consumption. The spreadsheet contains a simple time trend, per-capita consumption of ice cream (Q), price per 473 ml container (P), index of income (I), and temperature in degrees Fahrenheit (F; this was from a U.S. city). (a) estimate a model where consumption is a function of price, income and temperature using Excel. Fully report your results. Which of your independent variables exert a statistically significant impact on the dependent variable? Given what you have learned about economic theory so far in your academic career, do any of the results in terms of statistical significance surprise you? Why or why not? (b) plot the least-squar
This dataset contains a time series of 30 monthly observations on ice cream consumption. The spreadsheet contains a simple time trend, per-capita consumption of ice cream (Q), price per 473 ml container (P), index of income (I), and temperature in degrees Fahrenheit (F; this was from a U.S. city).
(a) estimate a model where consumption is a
(b) plot the least-squares residuals against time. Is there evidence of autocorrelation in your residuals? Why or why not?
(c) test formally for autocorrelation using the bounds test and the LM test. Be sure to do all parts of the hypothesis tests.
(d) use GLS to re-estimate the model. Fully report your results. Has the statistical significance of any of your independent variables changed? Why do you think this is?
(e) re-test for autocorrelation using the bounds test and the LM test. What do you find, and what do you think it means?
Dataset:
| t | Q | P | I | F |
| 1 | 0.386 | 0.27 | 78 | 41 |
| 2 | 0.374 | 0.282 | 79 | 56 |
| 3 | 0.393 | 0.277 | 81 | 63 |
| 4 | 0.425 | 0.28 | 80 | 68 |
| 5 | 0.406 | 0.272 | 76 | 69 |
| 6 | 0.344 | 0.262 | 78 | 65 |
| 7 | 0.327 | 0.275 | 82 | 61 |
| 8 | 0.288 | 0.267 | 79 | 47 |
| 9 | 0.269 | 0.265 | 76 | 32 |
| 10 | 0.256 | 0.277 | 79 | 24 |
| 11 | 0.286 | 0.282 | 82 | 28 |
| 12 | 0.298 | 0.27 | 85 | 26 |
| 13 | 0.329 | 0.272 | 86 | 32 |
| 14 | 0.318 | 0.287 | 83 | 40 |
| 15 | 0.381 | 0.277 | 84 | 55 |
| 16 | 0.381 | 0.287 | 82 | 63 |
| 17 | 0.47 | 0.28 | 80 | 72 |
| 18 | 0.443 | 0.277 | 78 | 72 |
| 19 | 0.386 | 0.277 | 84 | 67 |
| 20 | 0.342 | 0.277 | 86 | 60 |
| 21 | 0.319 | 0.292 | 85 | 44 |
| 22 | 0.307 | 0.287 | 87 | 40 |
| 23 | 0.284 | 0.277 | 94 | 32 |
| 24 | 0.326 | 0.285 | 92 | 27 |
| 25 | 0.309 | 0.282 | 95 | 28 |
| 26 | 0.359 | 0.265 | 96 | 33 |
| 27 | 0.376 | 0.265 | 94 | 41 |
| 28 | 0.416 | 0.265 | 96 | 52 |
| 29 | 0.437 | 0.268 | 91 | 64 |
| 30 | 0.548 | 0.26 | 90 | 71 |
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