Personal Income for Residents of Luzerne, Essay Example

This data pattern demonstrates that the personal income for residents of Luzerne, PA has steadily increased from 1969 to 2012 and this pattern is generally smooth. A moderate alpha, of approximately 0.5 would work best for this particular SES model because the trend is positive and the Pearson’s correlation coefficient is close to 1.0 (approximately 0.99). The moving average (MA) model would be the most appropriate model to use with this particular data set because this model is essentially a linear regression of the series values against occasional small disturbances in an otherwise smooth trend. In this situation, the trend is very close to a perfect positive relationship, so the mathematical model used should be based on this observation.

The actual data plotted above was more precise than the forecasted data, although the statistical models closely reflected the general trend of the information that was presented. Ultimately, the MA model gave better results than the SES due to the linear nature of the data. Among the SES models, the SES defaulthad the best prediction, although the SES 0.9 prediction was similar. The SES default had the best alpha because it had the smallest mean absolute error. Although I predicted that the MA model would be most appropriate to use above due to the data received, generating the models to produce a MAPE score indicated that the SES model is ideal to use in this situation. The lowest MAPE score for the MA model was 11.89 for MA 2 and the highest MAPE score for the MA model was 20.73 for the MA default. In these situations, the alpha is not ideal compared to the SES model.

The ACF chart demonstrates that there is a positive trend in personal income over time (see below). This indicates that using a SES or MA model would be the most appropriate methods to study this data because they are the best reflectors of linear positive data. In some cases, it may be useful to use a mixed model in which both SES and MA represent the data. However, in this particular situation, either can be used. The first part of this project indicated the SES default model would be the most appropriate to use for this purpose, so this model is recommended overall.

According to the trend identified by the NBER income per capita time series graph, the per capita personal income in my assigned county, Luzerne, PA, follows the business cycle. Both of these trend are generally positive between 1969 and 2012. The most apparent similarity is between the years of 2007 and 2009. In both the chart that summarizes the per capita personal income for Luzerne, PA residents and  the chart that summarizes the per capita personal income using the NBER data, this two year period marks significantly slower growth. Although this trend is still positive, this line has a lesser slope compared to the years surrounding it. Thus, this marks a period of recession, which was felt locally by residents of Luzerne, PA and nationally as well.One of the more striking examples of a period of economic growth occurs between 1987 and 1989. These two years indicate a period of economic growth which is the case according to both the data retrieved from Luzerne, PA residents and from NBER.

After fully considering both per capita income charts produced using Luzerne county data and NBER information, it was determined that January 1980, July 1981, July 1990, and March 2001 also mark the beginning of periods of recession. While one would expect a decrease in times of recession, it is essential to consider that the continuous positive trend reflects an increase in inflation rather than in per capita income. Therefore, both charts show a positive trend between year and per capita income, and the overall trend is close to a Pearson’s correlation coefficient of 1, but the greater slopes indicate periods of greater economic wealth and thus higher per capita income while the smaller slopes indicate periods of economic turmoil and thus lower per capita income.

In conclusion, the per capita personal income in my assigned county, Luzerne, PA, followed the business cycle. It decreased during recessions and increased during expansions, as marked by data trend observations starting at January 1980, July 1981, July 1990, March 2001, and December 2007. In this situation, it is clear that Luzerne, PA residents are reflective of the overall population of the country. It is likely that in some cases, county data will not match national data if the particular county is not representative of the country as a whole. However, in this case, we can expect that residents of Luzerne, PA have a similar job and salary distribution as individuals do across the country. This exhibition of defined lower, middle, and upper classes indicate that the economic trends of Luzerne, PA may be more predictable than trends in other counties. Since Luzerne, PA reflects the recession and growth trends of the NBER data, it is possible that it could be used as a model to measure the growth of the nation.