Evaluate the performance of the forecasting methods

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Reference no: EM132179183

Business Forecasting Assignment -

Case Problem: Natural Gas Consumption

A project has been done to develop a model to forecast natural gas consumption for the residential sector in the Washington, DC, metropolitan area. The level of natural gas consumption is influenced by a variety of factors, including local weather, the state of the national and the local economies, the purchasing power of the dollar (because at least some of the natural gas is imported), and the prices for other commodities. The following varuables have been identified and recorded on a quarterly basis (the data cover the period 1997Q1 through 2007Q4, with all data measured quarterly):

GASCONS: consumption of natural gas in DC metro area (million cubic feet)

AVETEMP: average temperature for the period in the DC metro area

GDP: annualized percentage change in GDP

UNEMP: percentage unemployment in the DC metro area

GAS_PRICE: price of natural gas ($/100 cubic feet)

DOLLAR: value index for the U.S dollar relative to a basket of international currencies

OIL_PRICE: price of crude oil ($/barrel)

RESERVES: reserves of natural gas (million cubic feet)

FUTURE: price of futures contract on natural gas ($/100 cubic feet)

Data for this case can be found in file Natural_Gas.xlsx.

Managerial Report

Generate forecasts for gas consumption. Include the following in your report:

1. Use the methods of descriptive analytics to learn about these data (include time series plot for gas consumption, descriptive statistics report, and correlation analysis). Discuss your findings.

2. Run a multiple regression analysis by including all independent variables in your model given the seasonality pattern in your time series. Interpret the results.

3. Adapt a backward selection approach to select the key independent variables for your model. Explain your approach.

4. Check multicollinearity issues for the selected variables. Interpret the results.

5. Finalize your model and develop the forecasting function.

6. Use a purely seasonal exponential smoothing method to generate forecasts for gas consumption (smoothing constant is 0.3 ).

7. Evaluate the performance of the forecasting methods you used. Interpret your results.

8. Select the method for forecasting and generate forecasts for year 2008. Discuss your results.

Attachment:- Assignment Files.rar

Reference no: EM132179183

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