Question

Develop a forecast for both unemployment rates for January (Boston) and February (United States) 2023. You must test at least three different forecasting methods (no more than two iterations of a same method (e.g. you can do 3 month and 6 month Moving Average, but you must test at least one other method). Pick the one you think is the best, and explain why you picked it. Provide the forecast unemployment rate for March for U.S. and January for Boston. Does the forecast "make sense" to you?

Answer 1

To develop a forecast for unemployment rates, we can use methods like Moving Average, Exponential Smoothing, and ARIMA. The best method can be determined by comparing forecasted values with actual values. The forecasted unemployment rate can then be obtained for future months, but the exact values depend on the specific data and chosen method.

Step-by-step explanation:

To develop a forecast for the unemployment rates in January (Boston) and February (United States) 2023, we can use three different forecasting methods. One method we can use is the Moving Average method, where we take the average of the unemployment rates for the previous months. Another method is the Exponential Smoothing method, where we assign weights to the previous data points based on their significance. Finally, we can use the ARIMA method, which takes into account the seasonal and trend components of the data.

After testing these three methods, we can determine which one is the best by comparing the forecasted values with the actual values for the past months. We can analyze the accuracy of the forecasts using metrics such as Mean Absolute Error (MAE) or Root Mean Square Error (RMSE). Based on the results, we can select the method that provides the most accurate and consistent forecasts.