{'fraction_non_alphanumeric': 0.029389017788089715, 'fraction_numerical': 0.004640371229698376, 'mean_word_length': 4.802690582959642, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Education and Synthetic Work-Life Earnings Estimates. American Community Survey Reports. ACS-14.

The relationship between education and earnings is a long-analyzed topic of study. Generally, there is a strong belief that achievement of higher levels of education is a well established path to better jobs and better earnings.1 This report provides one view of the economic value of educational attainment by producing an estimate of the amount of money a person might earn over the course of their working life, given their level of education. These estimates are “synthetic,” that is, they are not the actual dollars people earned over the complete working life of the person (which would require us to have retrospective earnings data for the 40 years of their work-life). Instead, they are estimated using data from a one point-in-time cross-sectional survey. Median annual earnings estimates are computed for the point in time of the survey for all ages (5-year age groups are used), education, gender, and race/ ethnicity groups. The age group-specific medians are then summed across the category of interest (say, Black females with a Master’s degree) to construct expected lifetime earnings of that group if all earnings patterns observed in the cross section were to remain unchanged.