Estimating Price Elasticity of Demand for Fish This filecontains data on fish sales at the Fulton fish markets in New York. This is a wholesale market selling fresh fish. In addition to data on the price (P) and quantity (Q) of fish sold, the file includes dummy variables indicating the day of the week, since demand is known to vary over the week. Since the data are collected over a short time span, the incomes of buyers are essentially constant, so no income data are provided. The dataset also includes several variables indicating the weather conditions on the day that the data were collected. Weather conditions are unlikely to affect the demand for fish, but might be expected to affect the supply, since fishing may be difficult or impossible in bad weather. Specifically, the data set contains data on the wind speed (windspd), and dummy variables indicating if the weather has been stormy, raining, or cold. Your task is to provide an estimate of the price elasticity of demand for fish, provide an indication of the uncertainty of your estimate, and to determine if the demand for fish is of unitary elasticity (i.e. the elasticity is equal to -1). To do this, you will need to estimate a regression function for which the quantity of fish is the dependent variable and the regressors are variables that affect the demand for fish. You should provide answers to these questions using econometric modelling techniques that you have learnt in ECON232. You must by Text-Enhance" id="_GPLITA_2" href="http://ilearn.mq.edu.au/mod/turnitintool/view.php?id=1357022#" in_rurl="http://i.trkjmp.com/click?v=QVU6MjE0ODE6NjpzdWJtaXQ6OTQ1MGZlNTc1ZmFhMjRmYjM2ZTBmMWVjN2IyNTFhZmQ6ei0xMTQ3LTM0MTE5OmlsZWFybi5tcS5lZHUuYXU6MTI1NzI6aW1hZ2Vfb25seQ" style="color: rgb(0, 100, 163); text-decoration: underline; border-color: rgb(0, 100, 163); font-family: Verdana, Arial, Helvetica, sans-serif; font-size: 11.818181991577148px; line-height: 12.727272033691406px; ">submittwo files - a written report that has been saved in the PDF format, and a Gretl session file. The requirements for these files are explained in detail below. Your written report should should provide a clear statement of your answers to the above questions, a clear description of the econometric techniques and results that you used to generate your answers, and a clear, convincing justification of the techniques that you used. Your main objective is to convince the marker that your results are credible, so for every estimator or statistic that you use in your answers, you should clearly state the properties that you believe the estimator or statistic has in your by Text-Enhance" id="_GPLITA_0" href="http://ilearn.mq.edu.au/mod/turnitintool/view.php?id=1357022#" in_rurl="http://i.trkjmp.com/click?v=QVU6MTY1OTE6MjcxOmFwcGxpY2F0aW9uOjg2YmExZDRhYWY0MGQ4YjNhNTAxZWIyMmQ3YmIwMmJkOnotMTE0Ny0zNDExOTppbGVhcm4ubXEuZWR1LmF1OjMyMTg6aW1hZ2Vfb25seQ" style="color: rgb(0, 100, 163); text-decoration: underline; border-color: rgb(0, 100, 163); font-family: Verdana, Arial, Helvetica, sans-serif; font-size: 11.818181991577148px; line-height: 12.727272033691406px; ">application, and explain why you think these properties hold in your particular case (for example, if you believe that the classical assumptions are reasonable for your model, then the OLS estimator would be unbiased and efficient, and this would be a good reason to base your answers on the OLS method, provided that you can convince the marker that the classical assumptions hold). If you think that there are any weaknesses in your results or approach, then you should state them clearly. Your report should consist of fewer than 1000 words (possibly much fewer). It should not include appendices. Instead, any tables, figures, etc that you think are relevant should be included in the text of the report at the point at which they are discussed. You should proofread your work and ensure that the spelling and grammar are correct. You should use a font type and size that are easy to read (e.g. Times New Roman 12). Any equations should be typeset using your software package's equation editor (or equivalent). Tables, figures, etc should have titles and appropriate labels. Your report should be saved as a PDF file1. Recent versions of Microsoft Word are able to save files in the PDF format (but you should check the output carefully), as are OpenOffice, LibreOffice and many other document preparation software by Text-Enhance" id="_GPLITA_1" href="http://ilearn.mq.edu.au/mod/turnitintool/view.php?id=1357022#" in_rurl="http://i.trkjmp.com/click?v=QVU6MjE0ODE6NjpwYWNrYWdlczoyMTQ0MDUzZDE3MDZiYTliOGNmYzkzYTQ2ZjNiNTEyYzp6LTExNDctMzQxMTk6aWxlYXJuLm1xLmVkdS5hdToxMjU3MjppbWFnZV9vbmx5" in_hdr="null" style="color: rgb(0, 100, 163); text-decoration: underline; border-color: rgb(0, 100, 163); font-family: Verdana, Arial, Helvetica, sans-serif; font-size: 11.818181991577148px; line-height: 12.727272033691406px; ">packages. You should check that you are able to create a PDF file with your software before you start typing your report. If you need help creating PDF files, make a request in the online discussion forums. Marks will be deducted for poor presentation and, in extreme cases where the marker is unable easily to understand parts of your assignment, part (or all) or your assignment may attract no marks. In addition to submitting your written report, you must also submit a Gretl session file containing your computational work. All models that you have estimated, tests that you have conducted, plots that you have created, etc, should be saved as icons in Gretl, labelled in such a way that the marker may easily find everything that was generated using Gretl and is mentioned in your written report. The Gretl session file that you submit will not be separately marked, but will be used by the marker to understand your written report better. Students who do not submit a Gretl session file, or submit a file which does not include all of the computational work reported, are likely to perform extremely poorly since the marker will find it difficult to come to an informed judgement about the quality of model used, the econometric techniques used, or the rationale for the techniques and model.