3. Use the data in House_price.xls: price = house price, $1000s lotsize = size o

Question

3. Use the data in House_price.xls: price = house price, $1000s lotsize = size of lot in square feet sqrft = size of house in square feet bdrms = number of bedrooms price = 0 + 1*lotsize + 2*sqrft + 3*bdrms

a. Apply the White test for heteroskedasticity to the above model (you can use the STATA command for this). Write down the chi-square statistic and the p-value. What do you conclude? (4 points) Now generate the natural log of several of the variables using the following commands: gen lnprice = ln(price) gen lnlotsize = ln(lotsize) gen lnsqrft = ln (sqrft) *Note: We are not taking the natural log of bdrms* Our new model will be: lnprice = 0 + 1*lnlotsize + 2*lnsqrft + 3*bdrms

b. Apply the White test for heteroskedasticity to this new model. Write down the chi-square statistic and the p-value. What do you conclude? (4 points)

4. What explanation might there be for the results that you saw in a and b above? (Hint: How would taking the natural log of variables tend to affect the White test results?) (2 points)

price bdrms lotsize sqrft 300 4 6126 2438 370 3 9903 2076 191 3 5200 1374 195 3 4600 1448 373 4 6095 2514 466.275 5 8566 2754 332.5 3 9000 2067 315 3 6210 1731 206 3 6000 1767 240 3 2892 1890 285 4 6000 2336 300 5 7047 2634 405 3 12237 3375 212 3 6460 1899 265 3 6519 2312 227.4 4 3597 1760 240 4 5922 2000 285 3 7123 1774 268 3 5642 1376 310 4 8602 1835 266 3 5494 2048 270 3 7800 2124 225 3 6003 1768 150 4 5218 1732 247 3 9425 1440 275 3 6114 1932 230 3 6710 1932 343 3 8577 2106 477.5 7 8400 3529 350 4 9773 2051 230 4 4806 1573 335 4 15086 2829 251 3 5763 1630 235 4 6383 1840 361 4 9000 2066 190 4 3500 1702 360 4 10892 2750 575 5 15634 3880 209.001 4 6400 1854 225 2 8880 1421 246 3 6314 1662 713.5 5 28231 3331 248 4 7050 1656 230 3 5305 1171 375 5 6637 2293 265 3 7834 1764 313 3 1000 2768 417.5 4 8112 3733 253 3 5850 1536 315 4 6660 1638 264 3 6637 1972 255 2 15267 1478 210 3 5146 1408 180 3 6017 1812 250 3 8410 1722 250 4 5625 1780 209 4 5600 1674 258 4 6525 1850 289 3 6060 1925 316 4 5539 2343 225 3 7566 1567 266 4 5484 1664 310 6 5348 1386 471.25 5 15834 2617 335 4 8022 2321 495 4 11966 2638 279.5 4 8460 1915 380 4 15105 2589 325 4 10859 2709 220 3 6300 1587 215 3 11554 1694 240 3 6000 1536 725 5 31000 3662 230 3 4054 1736 306 2 20700 2205 425 3 5525 1502 318 4 92681 1696 330 3 8178 2186 246 4 5944 1928 225 3 18838 1294 111 4 4315 1535 268.125 3 5167 1980 244 4 7893 2090 295 3 6056 1837 236 3 5828 1715 202.5 3 6341 1574 219 2 6362 1185 242 4 4950 1774

Explanation / Answer

3. Use the data in House_price.xls: price = house price, $1000s lotsize = size o

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