Economics 411 Spring 2015 Final project :
I will attach the database.please see the attachments.—————————————————————————————————————————————————
Forecasting is very much a learning-by-doing discipline. It should come as no surprise that your final project asks you to undertake a forecast. The variable I want you to forecast is employment in North Dakota. You can find this variable in the seasonality data file available in blackboard. I want you to forecast this value out to May 2016. This will not be a sink or swim exercise however. You are able to ask me questions along the way. This includes both substantive, technical questions as well as clarification questions. I also encourage you to talk with other classmates as needed, though be clear: everyone needs to turn in their own work, in their own words. You are not given any other variables. It is up to you to decide what to include and how to include it into your forecast model. Now it is natural to want to know how your grade will be determined. There are four parts to the assignment and each are listed below with their respective weight in the final grade. A more complete rubric will be made available to you in a week, but I wanted to give you the guidelines now. The first aspect evaluated for your grade is data. What variables do you bring into the model? Does it appear to be a complete model? Do you perform any necessary manipulations to the data to execute your forecast? These are the types of things you need to worry about and it makes up 15% of the overall score. The next part of your grade is technique. Does the technique employed match the data as well as the forecast objective? This presents you with the age–old question of executing a simple forecast well or a more complicated forecast not as well. There will be a degree of difficulty consideration here for you, but you still need to achieve results. This is worth 25% of your grade. The next evaluation criterion is the forecast result. Does your output make sense? Is there a serious problem with your forecast? This is one of the key evaluation criteria for all forecasts and is worth 30% of your final grade. The last criterion is the written explanation. Are you able to write in a way that explains what you did, and what you found? Are your explanations technically correct? This is another key element of successful forecasting.
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