Figure 1: Relationship between real income per capita and real
consumption per capita in 2015
Notes: The
graph plots the relationship between personal income per capita and
consumption per capita in 2015. Both series have been deflated to
account for state-specific differences in cost of living by means of
Regional Price Parities reported by the BEA, deflated by the national
Personal Consumption Expenditures price index, and normalized by the
corresponding values in Connecticut. Source: BEA.
Figure 1 is a scatterplot showing the relationship between personal income per capita and consumption per capita in 2015 for every state of the United States in 2015. Both series have been deflated to account for state-specific differences in cost of living by means of Regional Price Parities, deflated by the national Personal Consumption Expenditures price index, and normalized by the corresponding values in Connecticut. Each dot represents a state and is labeled with the state that it represents. The vertical axis is the level of real consumption per capita normalized to the Connecticut level. Therefore, any value lower than 1 on the vertical axis represents a state that has a lower level of consumption per capita than Connecticut, while any value higher than 1 represents a state with a higher level of consumption per capita than Connecticut. The horizontal axis is the level of real income per capita normalized to the Connecticut level. Because Connecticut is the state with the highest real per capita income level, the maximum value on the horizontal axis is 1. The graph shows a positive correlation between the levels of real consumption per capita and real income per capita, which we calculate to be equal to 0.78. This shows that richer states tend to have higher consumption than poorer states.
Figure 2: Relationship between real income per capita and life
expectancy at birth in 2015
Notes: The graph
plots the relationship between personal income per capita and life
expectancy at birth in 2015. Income per capita has been deflated to
account for state-specific differences in cost of living by means of
Regional Price Parities reported by the BEA, deflated by the national
Personal Consumption Expenditures price index, and normalized by the
value in Connecticut. Sources: BEA and CDC.
Figure 2 is a scatterplot showing the relationship between life expectancy at birth and the normalized levels of real income per capita for every state of the United States in 2015. Income per capita has been deflated to account for state-specific differences in cost of living by means of Regional Price Parities, deflated by the national Personal Consumption Expenditures price index, and normalized by the value in Connecticut. Each dot represents a state and is labeled with the state that it represents. The vertical axis is the level of life expectancy at birth, measured in years of life. The horizontal axis is the level of real income per capita normalized to the Connecticut level. Because Connecticut is the state with the highest real per capita income level, the maximum value on the horizontal axis is 1. The graph shows a positive correlation between life expectancy at birth and real income per capita, which suggests that life expectancy at birth tends to be higher in richer states than in poorer states. Life expectancy is also geographically concentrated, with states in the South having particularly low life expectancy compared to the other regions.
Figure 3: Relationship between real income per capita and annual hours
worked per capita in 2015
Notes: The graph
plots the relationship between personal income per capita and annual
hours worked per capita in 2015. Income per capita has been deflated to
account for state-specific differences in cost of living by means of
Regional Price Parities reported by the BEA, deflated by the national
Personal Consumption Expenditures price index, and normalized by the
value in Connecticut. Sources: BEA and CPS.
Figure 3 is a scatterplot showing the relationship between annual hours worked per capita and the normalized levels of real income per capita for every state of the United States in 2015. Income per capita has been deflated to account for state-specific differences in cost of living by means of Regional Price Parities, deflated by the national Personal Consumption Expenditures price index, and normalized by the value in Connecticut. Each dot represents a state and is labeled with the state that it represents. The vertical axis is the level of annuals worked per capita. The horizontal axis is the level of income per capita normalized to the Connecticut level. Because Connecticut is the state with the highest real per capita income level, the maximum value on the horizontal axis is 1. The graph shows a positive correlation between annual hours worked and real income per capita, which suggests that residents of richer states tend to work more hours annually than residents in poorer states.
Figure 4: Relationship between real income per capita and college
attainment in 2015
Notes: The graph plots the
relationship between personal income per capita and college attainment
in 2015, where the latter is given by the percentage of 25 year-olds
with at least a bachelor’s degree or a minimum of four years of college.
Income per capita has been deflated to account for state-specific
differences in cost of living by means of Regional Price Parities
reported by the BEA, deflated by the national Personal Consumption
Expenditures price index, and normalized by the value in Connecticut.
Sources: BEA and CPS.
Figure 4 is a scatterplot showing the relationship between college attainment and the normalized levels of real income per capita for every state of the United States in 2015. Income per capita has been deflated to account for state-specific differences in cost of living by means of Regional Price Parities, deflated by the national Personal Consumption Expenditures price index, and normalized by the value in Connecticut. Each dot represents a state and is labeled with the state that it represents. The vertical axis is the level of college attainment, measured as the percentage of 25-to-29 year-olds with at least a bachelor’s degree or a minimum of 4 years of college. The horizontal axis is the level of real income per capita normalized to the Connecticut level. Because Connecticut is the state with the highest real per capita income level, the maximum value on the horizontal axis is 1. The graph shows a positive correlation between college attainment and real income per capita, which suggests that college attainment tends to be higher in richer states than in poorer states. A notable exception is Wyoming, which displays a particularly low level of college attainment compared to its level of real per capita income.
Figure 5: Relationship between real income per capita and income
inequality in 2015
Notes: The graph plots the
relationship between personal income per capita and the GINI coefficient
of household income in 2015. Income per capita has been deflated to
account for state-specific differences in cost of living by means of
Regional Price Parities reported by the BEA, deflated by the national
Personal Consumption Expenditures price index, and normalized by the
value in Connecticut. Sources: ACS and BEA.
Figure 5 is a scatterplot showing the relationship between inequality and the normalized levels of real income per capita for every state of the United States in 2015. Income per capita has been deflated to account for state-specific differences in cost of living by means of Regional Price Parities, deflated by the national Personal Consumption Expenditures price index, and normalized by the value in Connecticut. Each dot represents a state and is labeled with the state that it represents. The vertical axis is the level of inequality, measured as the GINI coefficient of household income. The horizontal axis is the level of real income per capita normalized to the Connecticut level. Because Connecticut is the state with the highest real per capita income level, the maximum value on the horizontal axis is 1. The graph shows that inequality does not vary systematically with real income, and, in fact, inequality varies considerably across states with similar real per capita income levels.
Figure 6: Relationship between real income per capita and welfare in
2015
Notes: The graph plots the relationship
between real income per capita and welfare across the states in 2015,
where the latter is derived as in Equation (7). We
quantify the welfare differences across states by computing how much
consumption would have to change in all ages in the state with the
highest real personal income per capita, Connecticut, to make an unborn
individual behind the veil of ignorance indifferent between living her
entire life in Connecticut compared with any other state. Both welfare
and real per-capita income have been normalized by the corresponding
value in Connecticut. The dotted line depicts the 45-degree line. The
population-weighted correlation between real per-capita income and
welfare is 0.75.
Figure 6 is a scatterplot showing the relationship between the normalized levels of welfare and real income per capita for every state of the United States in 2015. Income per capita has been deflated to account for state-specific differences in cost of living by means of Regional Price Parities, deflated by the national Personal Consumption Expenditures price index, and normalized by the value in Connecticut. Each dot represents a state and is labeled with the state that it represents. The vertical axis is the level of welfare normalized to the Connecticut level. Therefore, any value lower than 1 on the vertical axis represents a state that has a lower level of welfare than Connecticut, while any value higher than 1 represents a state with a higher level of welfare than Connecticut. The horizontal axis is the level of real income per capita normalized to the Connecticut level. Because Connecticut is the state with the highest real per capita income level, the maximum value on the horizontal axis is 1. There is a dashed line that intercepts the vertical axis at 0.5 and connects it to the (1,1) coordinates. This dashed line corresponds to the 45-degree line. This means that any point above the dashed line corresponds to a state that has higher living standards than their income would suggest. Contrarily, any point below the dashed line corresponds to a state that has lower living standards than their income would suggest. The graph shows a positive correlation between the levels of welfare and real income per capita, which we calculate to be equal to 0.75. This shows that richer states tend to have higher living standards than poorer states. However, deviations between the two measures are often large. For instance, Minnesota has 15.4 percent lower real income per capita than Connecticut, but welfare in Minnesota is 2.9 percent higher than in Connecticut.
Figure 7: Relationship between growth in real income per capita and
growth in welfare between 1999 and 2015
Notes:
The graph plots the relationship between real per-capita income growth
and welfare growth between 1999 and 2015, where the latter is derived as
in Equation (13). We quantify
each state’s annual welfare growth rate by computing how much
consumption would have to change in all ages in state \(s\) in 2015 to make an unborn individual
behind the veil of ignorance indifferent between being born in state
\(s\) in 2015 compared with being born
in that same state in 1999. The dotted line depicts the 45-degree line.
The population-weighted correlation between real per-capita income
growth and welfare growth is 0.42.
Title: “Relationship Between Growth in Real Income per Capita and Growth in Welfare Between 1999 and 2015” Figure 7 is a scatterplot showing the relationship between the annual growth in real income capita to the corresponding annual growth in welfare in every state of the United States between 1999 and 2015. Each dot represents a state and is labeled with the state that it represents. The vertical axis is the annual growth in welfare as a percentage. The horizontal axis is the annual growth in real income per capita as a percentage. There is a dashed line that intercepts the vertical axis at 0.5 and connects it to the (4,4) coordinates. This dashed line corresponds to the 45-degree line. This means that any point above the dashed line corresponds to a state that has experienced a higher annual growth in welfare than its annual growth in real income per capita would suggest. Contrarily, any point below the dashed line corresponds to a state that experienced a lower growth in welfare than its growth in real income per capita would suggest. The graph shows that there is no relationship between the growth of real income per capita and the growth in welfare. In particular, richer (poorer) states do not generally have higher (lower) growth in welfare than their growth in real income per capita. The graph also shows that welfare has risen more rapidly than real per-capita income in all states except for Oklahoma.
Figure 8: Relationship between ranking of welfare in 1999 and annual
growth rate of welfare between 1999 and 2015
Notes: The graph plots the relationship between each
state’s welfare ranking in 1999 and annual welfare growth rate between
1999 and 2015. States have been ordered in descending order from the
state with the highest to the lowest welfare ranking in
1999.
Figure 8 is a scatterplot showing the relationship between the ranking of states according to their welfare level in 1999 and their annual growth rate in welfare between 1999 and 2015, as calculated by the authors. Each dot represents a state and is labeled with the state that it represents. The vertical axis is the annualized growth rate in welfare between 1999 and 2015 as a percentage. The horizontal axis is the ranking of states according to their welfare level in 1999 in descending order. Therefore, since there are 50 states, the horizontal axis is between 1 and 50, where the state corresponding to the value of 1, Minnesota, is the state that had the highest value of welfare in 1999, while the state corresponding to the value of 50, Mississippi, is the state that had the lowest value of welfare in 1999. The graph shows that there is no systematic relationship between the ranking of a state in 1999 and the growth rate in welfare that that same state experienced between 1999 and 2015. Therefore, this graph shows that states that were at the bottom of the 1999 welfare ranking have not growth faster than states at the top, suggesting that states are not converging toward similar welfare levels.
Figure 9: Benchmark model vs. model with endogenous migration
Notes: The graph plots each state’s welfare
level relative to Connecticut in the benchmark model (horizontal axis)
and the model with endogenous migration (vertical axis). The dotted line
depicts the 45-degree line.
Figure 9 is a scatterplot showing the relationship between the level of welfare of every state in the benchmark model and the corresponding level of welfare in every state based on a model with endogenous migration, as calculated by the authors. Each dot represents a state and is labeled with the state that it represents. The vertical axis is the level of welfare normalized to the Connecticut level where welfare was calculated based on a model with endogenous migration. The horizontal axis is the level of welfare normalized to the Connecticut level where welfare was calculated based on the benchmark model without migration. For both welfare measures, any value lower than 1 on either axis represents a state that has a lower level of welfare than Connecticut, while any value higher than 1 represents a state with a higher level of welfare than Connecticut. There is a dashed line that intercepts the vertical axis at 0.5 and connects it to the (1.1,1.1) coordinates. This dashed line corresponds to the 45-degree line. This means that any point above the dashed line corresponds to a state that has higher living standards when accounting for endogenous migration than the model without migration would suggest. Contrarily, any point below the dashed line corresponds to a state that has lower living standards when accounting for endogenous migration than the model without migration would suggest. The graph shows a highly positive correlation between the levels of welfare based on the model with endogenous migration and the model without migration. This shows that migration patterns do not affect our results.
Figure A1: Percentage of each state’s residents that were also born in
that state: Data vs. model with endogenous migration
Notes: The graph plots the percentage of residents in a
given state that were also born in that state in the data and in the
model with endogenous migration analyzed in Section 5.4.
Source: Census.
This is a bar chart displaying data for all U.S. states and territories, arranged alphabetically by state abbreviation on the x-axis from AK to WY. The y-axis measures percent of residents in state x that are born in state x, ranging from 0 to 90. Two variables are plotted for each state: "Data" represented by black bars and "Model" represented by red bars. The chart shows considerable variation across states in the percentage of residents who were born in their current state of residence. Most states display values between approximately 55 and 75 percent, with both Data and Model bars generally tracking closely together. Notable patterns include one particularly high spike reaching approximately 82 percent (appearing around the TX position), while some states show lower percentages in the 45-60 percent range. The final states in the series (WV and WY) show a declining pattern, with values dropping to approximately 45-55 percent. Throughout the chart, the black Data bars and red Model bars remain closely aligned for nearly all states, suggesting strong correspondence between observed data and model predictions.