ECON10005 Lecture Notes - Lecture 12: Nonlinear Regression, Random Variable, Dependent And Independent Variables
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The data for this assignment comes from household surveys carried out on a small island in Eastern Indonisa. The island, Selayar Island, is located in South Sulawesi, has two main industries: fishing and agriculture. We will be focusing of fishing activities occurring nearshore. Nearshore fishing takes place over coral reef, seagrass, and mangrove habitat. The most common fishing gear include spear guns, pole and lines, and nets. The boats used for fishing range from small canoes to small boats. The data was collected using a randomn sampling technique, and includes 152 fishing households.
Each fishing household was allowed to describe up to 6 different types of fishing trips. Researchers collected information on the âaverge tripâ. A subset of the data has been provided, in a .csv file named: âPS3_NearshoreFishing.csvâ.
Description of variables:
HouseholdID: Unique identification number used to protect the identity of respondents
Poor: Indicates poor and non-poor households, as defined by the Indonesian National Poverty Line ($0.83 per capita per day).
Poor = 1 if household income is less than the INPL
= 0 if household income is more than the INPL
Quantity: The quantity of average harvest during one trip, in 10,000 Rp (currency)
For example, if average trip harvest is 2 kg of Grouper, and Grouper price is 20,000 Rp/kg, then Quantity of the trip is 40
Hours: The number of person hours spent fishing per trip, in hours.
For example, if average trip includes 3 fishermen, and each fishermen spends 3 hours fishing, then Hours of the trip is 9 person hours.
Capital: The value of capital used up during the average trip, in 10,000 Rp.
You can think of this like depreciation of all gear and boats used during a trip
Part 1:
(Model 1)
log(Quantityi)= b0 + b1log(Capitali) + b2log(Hoursi) + ei
1. Estimate the basic production model and report regression results. Include coefficients, standard errors, and t-statics. (Note: You will have to create new variables for estimation)
2. Based on your results, what is the marginal reurns to hours spent fishing? Be careful to interpret coefficient on log-transformed variables correctly.
3. Does the estimated production function have constant returns to scale, decreasing returns to scale, or increasing returns to scale? How do you know?
4. Using single hypothesis tests, which coefficients are significantly different than zero at a 5% significiance level?
5. Use Whiteâs Test to test for heteroskedasticity. Report results and evaluate the results.
Help with the following problems that deal with the program stata and with econometrics.
Below is the data needed.
| HouseholdID | Poor | Quantity | Hours | Capital |
| 125465 | 0 | 25.4 | 8 | 0.796489877 |
| 130552 | 0 | 28.6 | 6 | 1.174603175 |
| 130552 | 0 | 9.1 | 4 | 2.222222222 |
| 127524 | 0 | 5 | 1 | 0.36544481 |
| 130538 | 1 | 10 | 6 | 2.008032129 |
| 130558 | 1 | 18.75 | 28 | 14.17848124 |
| 130462 | 1 | 14.4 | 2 | 0.487684729 |
| 126466 | 0 | 14.1 | 6 | 4.619435291 |
| 127474 | 1 | 13 | 3 | 0.367063492 |
| 127498 | 1 | 6 | 3 | 0.568124297 |
| 127471 | 0 | 12 | 5 | 0.115421137 |
| 127493 | 1 | 2.1 | 8 | 0.123444444 |
| 130561 | 0 | 39.6 | 3 | 0.289115646 |
| 130562 | 0 | 8 | 6 | 1.554278416 |
| 127532 | 1 | 41.7 | 6 | 0.738153469 |
| 127532 | 1 | 62.9 | 6 | 4.832562392 |
| 127495 | 0 | 7.65 | 3.5 | 0.116631206 |
| 127495 | 0 | 11.6 | 4 | 0.148772937 |
| 130524 | 1 | 2.95 | 10 | 0.706882255 |
| 130524 | 1 | 2.95 | 10 | 0.706882255 |
| 130564 | 0 | 14 | 14 | 1.495345632 |
| 127505 | 0 | 21.6 | 4 | 1.252053872 |
| 135460 | 1 | 21.5 | 4 | 0.757665094 |
| 131482 | 0 | 42.5 | 10 | 1.959625576 |
| 130560 | 0 | 15.3 | 4 | 0.697751323 |
| 128510 | 0 | 6 | 3 | 0.002311604 |
| 128510 | 0 | 4 | 2.5 | 0.416666667 |
| 128480 | 1 | 3.9 | 10 | 1.237449199 |
| 128480 | 1 | 4.4 | 10 | 1.237449199 |
| 128480 | 1 | 3.5 | 6 | 0.722079449 |
| 132456 | 0 | 8.5 | 5 | 0.177372685 |
| 132456 | 0 | 16.25 | 3 | 0.106423611 |
| 135486 | 0 | 21.5 | 11 | 3.665322581 |
| 135486 | 0 | 52.5 | 6 | 0.836021505 |
| 134524 | 0 | 33 | 7 | 1.242139722 |
| 135488 | 0 | 19.8 | 5 | 1.217105263 |
| 134460 | 0 | 84.4 | 3 | 3.824833703 |
| 131479 | 0 | 4 | 4.5 | 0.061111111 |
| 131465 | 0 | 8.5 | 1.5 | 0.39040198 |
| 128491 | 0 | 3.8 | 6 | 2.53815261 |
| 141514 | 1 | 1.4 | 6 | 0.946825397 |
| 134484 | 0 | 151.2 | 7 | 0.552428601 |
| 134484 | 0 | 71.2 | 6 | 0.479205754 |
| 141459 | 0 | 6.7 | 4 | 1.955605159 |
| 128473 | 0 | 70.7 | 5.5 | 0.553802416 |
| 128475 | 0 | 14.5 | 4 | 0.807217474 |
| 135520 | 0 | 2.5 | 4 | 1.041666667 |
| 135512 | 0 | 13.1 | 1 | 5.561594203 |
| 135512 | 0 | 3.3 | 2 | 0.650164062 |
| 134513 | 0 | 16.4 | 1 | 3.680053548 |
| 135469 | 1 | 18 | 13 | 1.979166667 |
| 132520 | 1 | 5.0625 | 2 | 0.395197395 |
| 134523 | 1 | 32.2 | 7 | 0.684749501 |
| 134497 | 0 | 10.76 | 5 | 3.18869165 |
| 129478 | 0 | 45.5 | 5.5 | 2.511574074 |
| 141461 | 0 | 25.6 | 2.5 | 4.849261849 |
| 141461 | 0 | 36.6 | 2.5 | 0.599912165 |
| 134503 | 0 | 30.6 | 8 | 1.214055483 |
| 128506 | 0 | 13.8 | 4 | 9.222222222 |
| 128506 | 0 | 19 | 4 | 9.222222222 |
| 130563 | 0 | 183.5 | 4 | 27.46449975 |
| 129488 | 0 | 215.1 | 1134 | 168.6111111 |
| 128487 | 0 | 4.5 | 1 | 0.000559284 |
| 129461 | 0 | 244 | 360 | 35.33333333 |
| 128496 | 0 | 1150 | 504 | 475.7380952 |
| 173468 | 0 | 2455 | 3366 | 1729.189322 |
| 134499 | 0 | 199 | 4 | 1.204772678 |
| 129466 | 0 | 4.5 | 3 | 2.773530545 |
| 145508 | 1 | 15 | 4 | 0.01460387 |
| 145508 | 1 | 15 | 4 | 0.01460387 |
| 134488 | 0 | 175 | 7 | 2.463414634 |
| 129484 | 0 | 275.1 | 2592 | 201.2685185 |
| 129484 | 0 | 175.1 | 1134 | 167.9891975 |
| 141467 | 0 | 16.5 | 2.5 | 0.270061728 |
| 141457 | 0 | 8.1 | 3 | 0.12021137 |
| 141457 | 0 | 24.1 | 4 | 0.499612792 |
| 135475 | 0 | 4.75 | 11 | 0.229402703 |
| 129498 | 0 | 616 | 830 | 362.7 |
| 134522 | 0 | 86.9 | 3 | 1.51324121 |
| 128477 | 0 | 9.4 | 5 | 1.626364087 |
| 141468 | 0 | 91.7 | 0.5 | 0.983115468 |
| 135489 | 1 | 18 | 8 | 3.206349206 |
| 134510 | 0 | 644.2 | 210 | 175.3837719 |
| 128457 | 0 | 3.5 | 2 | 0.509259259 |
| 134462 | 0 | 84.6 | 6 | 2.877641939 |
| 141509 | 1 | 23.2 | 2 | 2.640595716 |
| 129463 | 0 | 331 | 384 | 47.38180577 |
| 135514 | 1 | 18.6 | 2 | 8.338907469 |
| 135514 | 1 | 36.6 | 1 | 2.719893807 |
| 129485 | 0 | 4 | 7 | 0.833333333 |
| 129485 | 0 | 71.5 | 80 | 5.716746662 |
| 132529 | 1 | 7.8 | 3 | 1.024350649 |
| 132529 | 1 | 3.5 | 2 | 1.794733045 |
| 132529 | 1 | 1.5 | 3 | 0.861688312 |
| 145478 | 1 | 10.1 | 6 | 0.125 |
| 139510 | 1 | 12.5 | 10 | 6.041666667 |
| 134470 | 0 | 112 | 6 | 2.621527778 |
| 134496 | 0 | 279.7 | 4 | 4.799723021 |
| 134495 | 0 | 69 | 6 | 0.693735987 |
| 141460 | 0 | 60 | 2 | 1.272727273 |
| 135509 | 0 | 132.6 | 5 | 1.686077644 |
| 135506 | 0 | 10.5 | 3 | 0.295375197 |
| 134514 | 0 | 147.55 | 4 | 0.369502642 |
| 134514 | 0 | 147.55 | 4 | 0.369502642 |
| 134474 | 0 | 234.8 | 6 | 1.269918699 |
| 133503 | 0 | 6 | 3 | 1.095290252 |
| 133503 | 0 | 5.6 | 3 | 0.111111111 |
| 128460 | 0 | 15.5 | 5 | 0.306275676 |
| 128460 | 0 | 11.5 | 4 | 0.312922038 |
| 129501 | 0 | 500.5 | 483 | 74.36528749 |
| 129479 | 1 | 91 | 85 | 10.75104488 |
| 123490 | 1 | 15.75 | 5 | 1.35 |
| 123463 | 0 | 35.5 | 6 | 0.5 |
| 125465 | 0 | 18.5 | 6 | 0.568024685 |
| 127468 | 0 | 5.5 | 3.5 | 0.111111111 |
| 130552 | 0 | 13.1 | 2 | 1.166666667 |
| 130514 | 0 | 6.5 | 4 | 0.680555556 |
| 127524 | 0 | 14.5 | 5 | 2.532393505 |
| 130558 | 1 | 28 | 32 | 14.18542569 |
| 130516 | 0 | 3.5 | 4 | 0.208333333 |
| 130462 | 1 | 6.8 | 3 | 0.674055829 |
| 126466 | 0 | 12.6 | 2 | 4.592549518 |
| 127485 | 0 | 4.2 | 12 | 2.191666667 |
| 127485 | 0 | 10.2 | 6 | 1.186111111 |
| 130457 | 0 | 15 | 8 | 7.291666667 |
| 127474 | 1 | 10.5 | 3 | 0.724206349 |
| 127498 | 1 | 4.25 | 3 | 0.053412073 |
| 127498 | 1 | 3.5 | 3 | 0.053412073 |
| 127471 | 0 | 17.1 | 8 | 4.690142913 |
| 127471 | 0 | 12.3 | 4 | 2.311659648 |
| 127471 | 0 | 2.5 | 2 | 1.666666667 |
| 127493 | 1 | 2.1 | 8 | 0.123444444 |
| 130561 | 0 | 38.7 | 3 | 0.289115646 |
| 130561 | 0 | 16.5 | 3 | 11.33333333 |
| 127478 | 0 | 119.5 | 10 | 3.857877016 |
| 127478 | 0 | 30.5 | 6 | 2.170875421 |
| 127532 | 1 | 42.7 | 6 | 0.622768853 |
| 127532 | 1 | 38.7 | 6 | 6.971699297 |
| 127467 | 0 | 4.5 | 4 | 0.499600497 |
| 127467 | 0 | 9.1 | 3.5 | 0.366892361 |
| 127495 | 0 | 3.1 | 3.5 | 0.110797872 |
| 127495 | 0 | 9.9 | 3 | 0.114859845 |
| 130524 | 1 | 2.45 | 10 | 0.706882255 |
| 130524 | 1 | 2.45 | 10 | 0.706882255 |
| 130564 | 0 | 3814 | 3332 | 854.4818928 |
| 127505 | 0 | 14.5 | 3.5 | 2.491380471 |
| 135460 | 1 | 10 | 4 | 0.757665094 |
| 135460 | 1 | 20 | 14 | 0.484052111 |
| 131482 | 0 | 23.6 | 5 | 0.360957057 |
| 131482 | 0 | 67.9 | 6 | 0.416712483 |
| 130560 | 0 | 14 | 3 | 0.922110297 |
| 128510 | 0 | 504.6 | 1440 | 228.8873478 |
| 128510 | 0 | 6.3 | 2.5 | 0.416666667 |
| 128480 | 1 | 3.5 | 8 | 0.928789147 |
| 128480 | 1 | 49 | 70 | 33.6678911 |
| 132456 | 0 | 14.5 | 5 | 0.474991733 |
| 132456 | 0 | 8.75 | 5 | 0.177372685 |
| 132531 | 0 | 1.75 | 7 | 0.333333333 |
| 134524 | 0 | 33 | 7 | 1.116770991 |
| 134524 | 0 | 17 | 8 | 1.318727966 |
| 132513 | 0 | 1.5625 | 5 | 0.083333333 |
| 133494 | 0 | 2.875 | 2.5 | 0.5 |
| 135488 | 0 | 19.8 | 5 | 1.217105263 |
| 134460 | 0 | 40.8 | 3 | 3.824833703 |
| 128509 | 0 | 4216 | 2880 | 975.4285714 |
| 131479 | 0 | 2.35 | 4.5 | 0.42333225 |
| 131465 | 0 | 73 | 11.5 | 3.398356695 |
| 128491 | 0 | 6.4 | 3 | 1.871485944 |
| 141514 | 1 | 7.75 | 6 | 0.946825397 |
| 134484 | 0 | 91.7 | 7 | 0.962685011 |
| 134484 | 0 | 141.2 | 6 | 0.479205754 |
| 141459 | 0 | 12.2 | 4 | 1.955605159 |
| 128473 | 0 | 31.8 | 11 | 5.15297619 |
| 128481 | 0 | 852 | 810 | 49.09259259 |
| 128475 | 0 | 15.4 | 4 | 0.807217474 |
| 140461 | 1 | 4.7 | 5 | 1.183343855 |
| 128476 | 0 | 47 | 14 | 1.406476684 |
| 144544 | 0 | 21.2 | 2 | 0.866714015 |
| 135496 | 0 | 157.5 | 5 | 2.321399233 |
| 135496 | 0 | 59.8 | 5 | 2.003217415 |
| 134513 | 0 | 15.4 | 1 | 3.680053548 |
| 134523 | 1 | 28 | 40 | 3.667270345 |
| 144562 | 0 | 18.5 | 3 | 3.87254902 |
| 144562 | 0 | 11.4 | 3 | 2.086834734 |
| 134497 | 0 | 16.4 | 4 | 2.740795529 |
| 141461 | 0 | 34.1 | 2.5 | 4.849261849 |
| 141461 | 0 | 91.1 | 10 | 2.327184892 |
| 134503 | 0 | 29.6 | 8 | 1.214055483 |
| 128506 | 0 | 1271 | 1152 | 801 |
| 135497 | 0 | 0.75 | 1 | 0.221153846 |
| 141495 | 0 | 29 | 5 | 1.555555556 |
| 130563 | 0 | 252.5 | 8 | 36.62834591 |
| 141505 | 0 | 0.8 | 3 | 0.488855699 |
| 141505 | 0 | 0.8 | 3 | 0.513748468 |
| 133497 | 0 | 10 | 3 | 0.011904762 |
| 129488 | 0 | 210.5 | 1134 | 168.6111111 |
| 129461 | 0 | 722 | 720 | 70.66666667 |
| 128496 | 0 | 1150 | 504 | 475.7380952 |
| 173468 | 0 | 2882.5 | 1600 | 786.019471 |
| 145508 | 1 | 18.5 | 5 | 0.018254838 |
| 145508 | 1 | 16.65 | 5 | 0.018254838 |
| 134488 | 0 | 35 | 7 | 2.463414634 |
| 129484 | 0 | 371 | 2430 | 188.7268519 |
| 141467 | 0 | 25.65 | 2 | 1.158035714 |
| 141467 | 0 | 12.15 | 6.5 | 2.02808642 |
| 141457 | 0 | 19.8 | 3 | 0.167764213 |
| 141457 | 0 | 14.1 | 2 | 0.267971028 |
| 135475 | 0 | 5.75 | 10.5 | 0.22358875 |
| 129498 | 0 | 1068 | 830 | 362.7 |
| 134522 | 0 | 42.4 | 4 | 1.889213987 |
| 128477 | 0 | 7.6 | 6 | 1.919229497 |
| 144504 | 0 | 20.4 | 6 | 1.648461358 |
| 141468 | 0 | 35.65 | 0.5 | 0.983115468 |
| 135489 | 1 | 17.8 | 8 | 3.206349206 |
| 134510 | 0 | 384.7 | 90 | 75.16447368 |
| 128457 | 0 | 10 | 2 | 0.509259259 |
| 134462 | 0 | 114.6 | 7 | 2.918652438 |
| 141509 | 1 | 7.9 | 2 | 5.150635877 |
| 131485 | 0 | 6.75 | 8 | 2.973157134 |
| 131485 | 0 | 6.5 | 9 | 3.271105631 |
| 129463 | 0 | 1977.4 | 1848 | 224.9850657 |
| 135514 | 1 | 121.2 | 10 | 7.021349862 |
| 129485 | 0 | 1815 | 1296 | 80.22182224 |
| 132529 | 1 | 2.35 | 2.5 | 2.223124098 |
| 132529 | 1 | 7.6 | 2 | 1.875901876 |
| 132529 | 1 | 8.5 | 7 | 1.577705628 |
| 135502 | 0 | 31.2 | 4 | 0.320555556 |
| 132508 | 0 | 3.125 | 2.5 | 0.083333333 |
| 133479 | 0 | 26.7 | 2 | 4.126984127 |
| 134470 | 0 | 96 | 6 | 0.520833333 |
| 134496 | 0 | 114.8 | 7 | 2.416368587 |
| 134495 | 0 | 43 | 9 | 0.63703001 |
| 141460 | 0 | 23 | 2 | 1.272727273 |
| 132498 | 0 | 8 | 2 | 5.555555556 |
| 129497 | 0 | 2206 | 2880 | 955.3703704 |
| 129497 | 0 | 9.1 | 1.5 | 3.888888889 |
| 135509 | 0 | 2.6 | 5 | 0.942994199 |
| 135506 | 0 | 23.75 | 3 | 0.318339994 |
| 134514 | 0 | 37.55 | 7 | 0.596927834 |
| 134514 | 0 | 37.55 | 5 | 0.445311039 |
| 134474 | 0 | 114.75 | 6 | 1.269918699 |
| 133503 | 0 | 9 | 4 | 1.460387003 |
| 133503 | 0 | 6 | 3 | 0.111111111 |
| 128460 | 0 | 13.5 | 5 | 0.306275676 |
| 144502 | 0 | 6 | 3 | 0.644824673 |
| 129501 | 0 | 1280.2 | 672 | 123.9083139 |
| 129479 | 1 | 112 | 833 | 100.6137228 |
| 129511 | 0 | 231 | 60 | 0.02 |
Question 1
Which of the following approaches to understanding and predicting consumer behavior depends primarily on the knowledge and experience of a firm's employees and its suppliers?
| Test marketing and price experiments | ||
| Analysis of historical data. | ||
| Direct consumer surveys. | ||
| Expert opinion. |
Question 2
In which of the following situations would reliance on expert opinion as a basis for a managerial decision be most preferred?
| When the product being marketed is relatively new. | ||
| When the level of economic activity can have a significant effect on the demand for the firm's output. | ||
| When the product can be packaged with a variety of price and quality combinations. | ||
| When the business in question serves as a supplier of inputs to other businesses, especially in multi-product situations where other strategies may be prohibitively expensive. |
Question 3
The approach to analyzing consumer behavior that asks consumers to rank and choose among different product attributes to reveal their relative valuation of different characteristics is called:
| conjoint analysis. | ||
| contingent valuation. | ||
| the hedonic estimation technique. | ||
| a direct consumer survey. |
Question 4
All of the following are limitations of direct consumer surveys except:
| the possibility of response biases because survey respondents may not want to reveal their true preferences. | ||
| the possibility that the type of questions asked may unintentionally bias the respondent's answers. | ||
| the likelihood that respondents will deliberately and systematically mislead interviewers. | ||
| the possibility that consumers' responses may not reflect their actual behavior in the market place. |
Question 5
Which of the following approaches to understanding and predicting consumer behavior does not actually solicit any information from potential customers?
| Expert opinion. | ||
| Test marketing. | ||
| Analysis of historical data. | ||
| Conjoint analysis. |
Question 6
Data collected on a sample of individuals with different characteristics at a specific point in time are called:
| panel data. | ||
| cross-section data. | ||
| time series data. | ||
| none of the above. |
Question 7
Which of the following approaches to understanding and predicting consumer behavior provides the most insight into how consumers can be expected to respond in an actual market setting?
| Test marketing. | ||
| Conjoint analysis. | ||
| Expert opinion. | ||
| Analysis of historical data. |
Question 8
An approach to analyzing consumer behavior in which consumer reaction to different prices is analyzed in a laboratory situation or a test market is called:
| non-price experiments. | ||
| focus groups. | ||
| price experiments. | ||
| none of the above. |
Question 9
Data collected on the same observation unit at a number of points in time are called:
| panel data. | ||
| time series data. | ||
| cross-section data. | ||
| none of the above. |
Question 10
A measure of how much the coefficient would vary in regressions based on different samples is called:
| F-statistic. | ||
| standard error of the estimated coefficient. | ||
| t-statistic. | ||
| partial F-statistic. |
Question 11
The test statistic used to test the hypothesis of whether a regression coefficient is significantly different from zero, holding all other independent variables constant, is called a(n):
| t-test. | ||
| F-test. | ||
| multicollinearity test. | ||
| autocorrelation test. |
Question 12
Regression analysis that analyzes the relationship between one dependent variable and several independent variables is called:
| cluster analysis. | ||
| correlation analysis. | ||
| multiple regression analysis. | ||
| simple regression analysis. |
Question 13
The ratio of the regression coefficient to its standard error is called:
| F-statistic. | ||
| t-statistic. | ||
| coefficient of determination. | ||
| partial F-statistic. |
Question 14
The coefficient of determination will range between what values?
| -1 and +1 | ||
| 0 and 1 | ||
| -3 and +3 | ||
| none of the above |
Question 15
The range of values in which we can be confident that the true regression coefficient lies within a given degree of probability is called a:
| confidence interval. | ||
| logistic regression. | ||
| prediction interval. | ||
| none of the above. |
Question 16
The estimated regression equation is Y = 10 + 2.5X, if X =0 than the predicted value of Y is equal to
| 2.5 | ||
| 7.5 | ||
| 12.5 | ||
| 10 |
