Review the forecasting case study urban planning

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Reference no: EM131290181

FORECASTING CASE STUDY

Review "Forecasting Case Study: Urban Planning" for this topic's case study, in which you will serve as an urban planner forecasting economic growth and decline for a specific industry in your city.

Students must access the "County Business Patterns" webpage (https://www.census.gov/econ/cbp/index.html) for this assignment. Students will use this U.S. Census Industry data portal to access data for a zip code with which you are familiar. This can be the zip code of your personal residence, location of employer (corporate, regional, or local office), undergraduate educational institution, hometown, etc.

In addition to the forecasting model and data, prepare a 500-750-word report to your city manager. Explain your approach and the rationale for why this is the best model. Evaluate the data and conclude your report with a recommendation about either expanding the industry in your area or allocating resources elsewhere.

Use an Excel spreadsheet file for the calculations and explanations. Cells should contain the formulas (i.e., if a formula was used to calculate the entry in that cell). Students are highly encouraged to use the "Forecasting Template" Excel resource to complete this assignment.

Mac users can use StatPlus:mac LE, free of charge, from AnalystSoft.

Prepare the assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

Please refer to the directions in the Student Success Center.

https://www.census.gov/programs-surveys/cbp/data/tables.html (Correct access to "County Business Patterns" webpage)

Forecasting Case Study: Urban Planning

Important Note: Students must access the "County Business Patterns" Topic Material for this assignment. Students will use this U.S. Census Industry data portal to access data for a zip code with which you are familiar. This can be the zip code of your personal residence, location of employer (corporate, regional, or local office), undergraduate educational institution, hometown, etc.

Scenario

You have recently been hired as an urban planner for your local government. You have been tasked with determining economic growth and decline patterns in your area. As an urban planner, you will ultimately be responsible for determining patterns and forecasting for all industries within your area. However, the city manager has asked that you prioritize one of the 10 industries below. Business proposals have been submitted and the city manager would like to have use forecasting data to make an informed decision about whether to approve industry expansion or to allocate resources elsewhere.

Industries

• Construction
• Manufacturing
• Transportation and Warehousing
• Information
• Finance and Insurance
• Real Estate and Rental and Leasing
• Professional, Scientific, and Technical Services
• Management of Companies and Enterprises
• Administrative and Support and Waste Management and Remediation Services
• Health Care and Social Assistance

Forecasting

Access the "County Business Patterns" page on the United States Census Bureauwebsite and enter your city's zip code. Using one of the industries above, access the data for the last 5 years that are available on website. Determine patterns of economic growth or decline during this time period, and develop the most optimal forecasting model for the next 2 years. Note that you will need to set up these two forecast calculations.

Clearly justify why your selected model is the best one. Specifically explain what forecast error is and how you used it to ascertain the most optimal forecasting model. Assume that you are presenting your findings to senior management and that senior management has minimal knowledge of forecasting techniques and how forecast error is calculated.

Attachment:- Forecasting_Template.xlsx

Reference no: EM131290181

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