Data for discussing the probability of improving one's economic situation across 741 Metropolitan Statistical Areas in the US.
Format
An object of class spec_tbl_df (inherits from tbl_df, tbl, data.frame) with 741 rows and 43 columns.
Source
This data set was based on the paper "Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States" (Raj Chetty, Nathaniel Hendren, Patrick Kline, Emmanuel Saez, QJE 2014), and its replication files. Both the paper and the data sets are available from https://opportunityinsights.org.
Details
The variables are:
| Variable | Description |
| Mobility | The probability that a child born in 1980–1982 into the lowest quintile (20%) of household income will be in the top quintile at age 30. Individuals are assigned to the community they grew up in, not the one they were in as adults. |
| Population | in 2000. |
| Urban | Is the community primarily urban or rural? |
| Black | percentage of individuals who marked black (and nothing else) on census forms. |
| Racial Segregation | a measure of residential segregation by race. |
| Income Segregation | Similarly but for income. |
| Segregation of poverty | Specifically a measure of residential segregation for those in the bottom quarter of the national income distribution. |
| Segregation of affluence | Residential segregation for those in the top quarter. |
| Commute | Fraction of workers with a commute of less than 15 minutes. |
| Mean income | Average income per capita in 2000. |
| Gini | A measure of income inequality, which would be 0 if all incomes were perfectly equal, and tends towards 100 as all the income is concentrated among the richest individuals (see Wikipedia, s.v. "Gini coefficient"). |
| Share 1% | Share of the total income of a community going to its richest 1%. |
| Gini bottom 99% | Gini coefficient among the lower 99% of that community. |
| Fraction middle class | Fraction of parents whose income is between the national 25th and 75th percentiles. |
| Local tax rate | Fraction of all income going to local taxes. |
| Local government spending | per capita. |
| Progressivity | Measure of how much state income tax rates increase with income. |
| EITC | Measure of how much the state contributed to the Earned Income Tax Credit (a sort of negative income tax for very low-paid wage earners). |
| School expenditures | Average spending per pupil in public schools. |
| Student/teacher ratio | Number of students in public schools divided by number of teachers. |
| Test scores | Residuals from a linear regression of mean math and English test scores on household income per capita. |
| High school dropout rate | Residuals from a linear regression of the dropout rate on per-capita income. |
| Colleges per capita | |
| College tuition | in-state, for full-time students |
| College graduation rate | Again, residuals from a linear regression of the actual graduation rate on household income per capita. |
| Labor force participation | Fraction of adults in the workforce. |
| Manufacturing | Fraction of workers in manufacturing. |
| Chinese imports | Growth rate in imports from China per worker between 1990 and 2000. |
| Teenage labor | fraction of those age 14–16 who were in the labor force. |
| Migration in | Migration into the community from elsewhere, as a fraction of 2000 population. |
| Migration out | Ditto for migration into other communities. |
| Foreign | fraction of residents born outside the US. |
| Social capital | Index combining voter turnout, participation in the census, and participation in community organizations. |
| Religious | Share of the population claiming to belong to an organized religious body. |
| Violent crime | Arrests per person per year for violent crimes. |
| Single motherhood | Number of single female households with children divided by the total number of households with children. |
| Divorced | Fraction of adults who are divorced. |
| Married | Ditto. |
| Longitude | Geographic coordinate for the center of the community |
| Latitude | Ditto |
| ID | A numerical code, identifying the community. |
| Name | the name of principal city or town. |
| State | the state of the principal city or town of the community. |
Examples
mobility
#> # A tibble: 741 × 43
#> ID Name Mobility State Population Urban Black Seg_racial Seg_income
#> <dbl> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 100 Johnson Ci… 0.0622 TN 576081 1 0.021 0.09 0.035
#> 2 200 Morristown 0.0537 TN 227816 1 0.02 0.093 0.026
#> 3 301 Middlesbor… 0.0726 TN 66708 0 0.015 0.064 0.024
#> 4 302 Knoxville 0.0563 TN 727600 1 0.056 0.21 0.092
#> 5 401 Winston-Sa… 0.0448 NC 493180 1 0.174 0.262 0.072
#> 6 402 Martinsvil… 0.0518 VA 92753 0 0.224 0.137 0.024
#> 7 500 Greensboro 0.0474 NC 1055133 1 0.218 0.22 0.068
#> 8 601 North Wilk… 0.0517 NC 90016 0 0.032 0.114 0.012
#> 9 602 Galax 0.0796 VA 64676 0 0.029 0.131 0.005
#> 10 700 Spartanburg 0.0431 SC 354533 1 0.207 0.139 0.045
#> # ℹ 731 more rows
#> # ℹ 34 more variables: Seg_poverty <dbl>, Seg_affluence <dbl>, Commute <dbl>,
#> # Income <dbl>, Gini <dbl>, Share01 <dbl>, Gini_99 <dbl>, Middle_class <dbl>,
#> # Local_tax_rate <dbl>, Local_gov_spending <dbl>, Progressivity <dbl>,
#> # EITC <dbl>, School_spending <dbl>, Student_teacher_ratio <dbl>,
#> # Test_scores <dbl>, HS_dropout <dbl>, Colleges <dbl>, Tuition <dbl>,
#> # Graduation <dbl>, Labor_force_participation <dbl>, Manufacturing <dbl>, …