Immigrants from China vs Immigrants from Moldova Community Comparison

The statistical analysis conducted on geographies consisting of 122,048,457 people shows a mild negative correlation between the proportion of Immigrants from Moldova within Immigrant from China communities in the United States with a correlation coefficient (R) of -0.370. On average, for every 1% (one percent) increase in Immigrants from China within a typical geography, there is a decrease of 0.002% in Immigrants from Moldova. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Immigrants from China corresponds to a decrease of 1.8 Immigrants from Moldova.

When considering income, the most significant differences between Immigrants from China and Immigrants from Moldova communities in the United States are seen in householder income ages 25 - 44 years ($119,756 compared to $101,091, a difference of 18.5%), median household income ($105,335 compared to $91,446, a difference of 15.2%), and per capita income ($54,264 compared to $47,489, a difference of 14.3%). Conversely, both communities are more comparable in terms of wage/income gap (26.7% compared to 26.2%, a difference of 1.9%), householder income under 25 years ($57,931 compared to $56,168, a difference of 3.1%), and householder income over 65 years ($69,174 compared to $62,939, a difference of 9.9%).

When considering poverty, the most significant differences between Immigrants from China and Immigrants from Moldova communities in the United States are seen in receiving food stamps (9.6% compared to 10.9%, a difference of 14.0%), female poverty among 18-24 year olds (20.2% compared to 17.9%, a difference of 12.9%), and seniors poverty over the age of 75 (13.2% compared to 11.9%, a difference of 10.9%). Conversely, both communities are more comparable in terms of single mother poverty (26.1% compared to 26.2%, a difference of 0.56%), family poverty (7.8% compared to 7.7%, a difference of 1.8%), and single father poverty (14.9% compared to 15.2%, a difference of 1.8%).

When considering unemployment, the most significant differences between Immigrants from China and Immigrants from Moldova communities in the United States are seen in unemployment among ages 60 to 64 years (5.1% compared to 4.6%, a difference of 10.7%), unemployment among ages 55 to 59 years (5.0% compared to 4.5%, a difference of 9.8%), and unemployment among ages 45 to 54 years (4.5% compared to 4.1%, a difference of 9.3%). Conversely, both communities are more comparable in terms of unemployment among ages 35 to 44 years (4.4% compared to 4.4%, a difference of 0.40%), unemployment among ages 30 to 34 years (5.1% compared to 5.1%, a difference of 0.48%), and unemployment among women with children under 18 years (4.9% compared to 5.0%, a difference of 1.9%).

When considering labor participation, the most significant differences between Immigrants from China and Immigrants from Moldova communities in the United States are seen in in labor force | age 16-19 (31.1% compared to 37.7%, a difference of 21.0%), in labor force | age 20-24 (71.1% compared to 76.6%, a difference of 7.8%), and in labor force | age > 16 (65.4% compared to 66.1%, a difference of 1.2%). Conversely, both communities are more comparable in terms of in labor force | age 30-34 (85.4% compared to 85.3%, a difference of 0.14%), in labor force | age 35-44 (84.7% compared to 85.0%, a difference of 0.40%), and in labor force | age 45-54 (83.2% compared to 83.7%, a difference of 0.59%).

When considering family structure, the most significant differences between Immigrants from China and Immigrants from Moldova communities in the United States are seen in divorced or separated (10.0% compared to 12.1%, a difference of 20.1%), single father households (1.8% compared to 2.1%, a difference of 15.6%), and single mother households (5.1% compared to 5.6%, a difference of 11.6%). Conversely, both communities are more comparable in terms of family households (64.7% compared to 64.4%, a difference of 0.41%), family households with children (27.4% compared to 27.6%, a difference of 0.74%), and married-couple households (48.4% compared to 48.0%, a difference of 0.94%).

When considering vehicle availability, the most significant differences between Immigrants from China and Immigrants from Moldova communities in the United States are seen in no vehicles in household (15.2% compared to 9.8%, a difference of 54.6%), 2 or more vehicles in household (51.5% compared to 56.1%, a difference of 9.0%), and 1 or more vehicles in household (84.9% compared to 90.2%, a difference of 6.3%). Conversely, both communities are more comparable in terms of 4 or more vehicles in household (6.0% compared to 6.0%, a difference of 1.2%), 3 or more vehicles in household (18.2% compared to 19.1%, a difference of 4.7%), and 1 or more vehicles in household (84.9% compared to 90.2%, a difference of 6.3%).

When considering education level, the most significant differences between Immigrants from China and Immigrants from Moldova communities in the United States are seen in doctorate degree (3.1% compared to 2.0%, a difference of 58.2%), professional degree (6.7% compared to 4.9%, a difference of 38.1%), and no schooling completed (2.6% compared to 2.0%, a difference of 28.0%). Conversely, both communities are more comparable in terms of nursery school (97.5% compared to 98.0%, a difference of 0.58%), kindergarten (97.4% compared to 98.0%, a difference of 0.58%), and 1st grade (97.4% compared to 98.0%, a difference of 0.59%).

When considering disability, the most significant differences between Immigrants from China and Immigrants from Moldova communities in the United States are seen in disability age 35 to 64 (8.7% compared to 10.6%, a difference of 21.6%), disability age 18 to 34 (5.4% compared to 6.5%, a difference of 20.0%), and disability age under 5 (0.96% compared to 1.1%, a difference of 18.9%). Conversely, both communities are more comparable in terms of cognitive disability (16.9% compared to 16.7%, a difference of 1.3%), disability age over 75 (46.3% compared to 47.4%, a difference of 2.5%), and self-care disability (2.3% compared to 2.6%, a difference of 9.9%).