This master thesis addresses the forecast accuracy of individual inflation forecasts from the Survey of Professional Forecasters. Based on a variety of accuracy statistics, there are five main findings to report of. First, I find that some individuals are able to accurately predict inflation over time, and that forecasters on average have improved their accuracy over time. Second, forecasting accuracy becomes worse during recessions compared to the average accuracy in the respective decades but accuracy have improved in newer recessions compared to old ones. Nonetheless, some individuals are able to outperform the mean and a random walk model. Third, I find no difference in accuracy among industries, but I find evidence for biased forecasts for the three and four quarter horizon. Fourth, I find evidence for bias in roughly one-third of the individuals for all forecasting horizons. These results improve slightly when only data from the last two decades are being analysed. Fifth, the majority of individuals perform significantly worse than a random walk model regardless of used time span. I also find several problems with the database. These includes: missing values for the one-yearahead forecast, irregularities in forecasters’ response, reallocation of used ID’s, changing base year and inconsistencies in individuals’ forecasts.