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EVAN MCKAY, Harvard College '19

Felony Disenfranchisement as Backlash: Florida’s History of African American Voting Rights

THURJ Volume 12 | Issue 1


Around five million people in the United States are unable to register to vote due to a prior felony record. Felony disenfranchisement has been used to cull the electorate since its introduction, though initially, it was a narrow policy mostly related to anti-corruption and fraud. Since then, it was expanded to counter gains in voting eligibility to low income. Its reach grew through the criminalization of African Americans following the Civil War. Since the passage of the Voting Rights Act in 1965, felony disenfranchisement ballooned alongside mass incarceration to become the principal barrier to voting eligibility in the United States. The recent expansion of voting eligibility in Florida confronts a history of injustice, particularly against African Americans. At the same time, Amendment 4 is incomplete in its continued exclusion of people who were convicted of murder or sex crimes, those who are unable to pay fines and fees, and those who are currently incarcerated, on parole, or on probation.


In 1959, 23-year-old Wallace McDonald fell asleep on a bench waiting for a bus to come — he awoke to being arrested for vagrancy. Forty-one years later, this incident prevented him from voting in Florida during the contentious 2000 presidential election. Wallace is a victim of felony disenfranchisement, the legal exclusion of people with prior felony records from voting or registering to vote. Florida had been the strictest state in the nation with voting eligibility for people with criminal histories; however, this is currently changing due to a citizen ballot initiative, Amendment 4, which passed with 65% support in the 2018 election. Amendment 4, which will enable Wallace and other people with prior criminal histories to vote after finishing their sentences, is only the most recent chapter in felony disenfranchisement’s history as a tool to cull the electorate of undesirable voters and to disempower African Americans.

Disenfranchisement due to prior criminal history has grown dramatically as strict policies on voting eligibility for returning citizens combine with mass incarceration and the War on Drugs that have both increased the number of people with felony records. As of 2016, approximately 6.1 million people in the United Statescannot vote because of a prior felony conviction — up from 1.17 million in 1976, 3.34 million in 1996, and 5.85 million in 2010. Although felony disenfranchisement has indirect effects beyond politics, the impact on the political landscape is dramatic: according to legal scholar Pamela Karlan, “Felony disenfranchisement has decimated the potential black electorate.” Although policies have changed over time, today a majority of states disenfranchise people in prison, on parole, and on probation, and a minority disenfranchise people after their sentences are over, usually for life.




We analyze the income profiles of Asian immigrants from China, India, the Philippines, Korea, Vietnam, and Japan. In our classification, "immigrants" encompass individuals who are born in any of the six Asian countries, irrespective of whether they later became naturalized citizens in the U.S. On the other hand, we designate "natives" as white males born in any of the 50 U.S. states.

Our dataset comprises all available decennial census data spanning from 1970 to 2000, as well as the pooled 2009-2011 and 2019-2021 American Community Surveys (ACS). The ACS is currently the largest available survey that includes information on race/ethnicity and socioeconomic characteristics. For simplicity, we refer to the pooled 2009-2011 and 2019-2021 ACS survey data as 2010 and 2020 censuses, respectively. 

As is customary in labor force studies, we limit our native and immigrant sample to male adults of working age (18 to 65). We also restrict our immigrant sample exclusively to males who immigrated to the U.S. after turning 18 to ensure the tracking of cohorts across censuses is unaffected by subsequent waves of immigrants who arrive as children. This accounts for the possibility that immigrant children likely assimilate faster than their adult counterparts due to their integration into the American education system.

Regression Equations

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We estimate the following regression model in each of the census cross-sections from 1970 to 2020 and for each country of origin.

The dependent variable is the logarithm of the total pre-tax wage and salary income earned by a worker i in cross-section t and in cohort c compared to natives. The regressors include the worker’s age introduced as a third-degree polynomial,      . 

       are the fixed effects of a specific cohort in a given cross-section. We also control for education, which represents the observable differences in skills between Asian immigrants and natives. Finally, the regression model includes a fixed effect for the immigrant cohort that arrived on or before 1949 so that the earliest cohort starts at 1950.

Main Results

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Tables 1-6 display regression coefficients for all six Asian countries. In contrast to Borjas’s (2015) findings, where he observed that immigrants of all races and ethnicities in more recent cohorts had relatively lower entry wages compared to earlier cohorts, our study reveals a different trend among Asian immigrant cohorts. Specifically, we find that more recent Asian immigrant cohorts tend to experience either improved or similar levels of initial wage disadvantage upon entry compared to older cohorts for all six Asian countries.

For example, when we control for age and education, Chinese immigrants who arrived in 1965 and 1975 earned approximately 70% less than natives during their first decade in the U.S. However, Chinese immigrants who arrived in 2005 earned around 50% less than natives, and this wage gap was further reduced to approximately 30% for the latest wave of Chinese immigrants arriving in 2015. This indicates an improvement in the initial wage disadvantage over time. Similarly, Indian immigrants experienced an initial wage disadvantage of around 50-60% compared to natives for the 1965 and 1975 cohorts, but this gap diminished with each subsequent cohort and eventually closed entirely by 2020. On the other hand, Filipino immigrants exhibited a relatively stable pattern, starting with the 1965 and 1975 cohorts earning around 50-60% less than natives upon arrival, and this wage disadvantage persisted in successive cohorts, plateauing at around 48-53% in 2005 and 2015. In contrast, Korean immigrants from the 1975 to 2005 cohorts had a wage gap of approximately 60% relative to natives, which reduced to around 40% in 2015, indicating a modest level of improvement relative to earlier cohorts. These examples either contradict Borjas's findings on lower entry wages for immigrants overall or demonstrate no significant changes in the long-term trend of entry wages for specific Asian countries.

Next, we define the rate of economic assimilation as the pace at which the wage gap between migrants and natives narrows over time. In contrast to Borjas’s (2015) findings on the slowdown of assimilation rates in successive cohorts over time for immigrants of all origins (referred to as “cohort effects”), we find no substantial evidence of this collective assimilation pattern in successive cohorts for all six Asian countries.
For instance, when examining Korean and Japanese immigrants, we observe that the wage differential relative to natives for the 1950-1975 cohorts closed within their first decade upon arrival in the U.S., but it did not close as rapidly for subsequent cohorts within the first decade. Similarly, all Indian cohorts experienced rapid assimilation, with the wage gap closing for each cohort within their first five or ten years in the U.S. In contrast, Chinese immigrants experienced slower rates of assimilation, as seen in the 1950 and 1960 cohorts, where their wages were, on average, at a disadvantage of around 25.7% and 38.9%, respectively, compared to their native counterparts. This wage gap closed, as demonstrated in the 1990 and 2000 censuses, respectively, after 40 years of their residence in the U.S. Likewise, Vietnamese cohorts generally experienced much slower assimilation, with the wage gap closing for each cohort after 40 years of residency in the U.S.

While the analyses above focus on the rate of assimilation over time between different countries, Figures 1-6 show the rate of assimilation between cohorts within a single country across time. We have normalized the wages for each cohort so that the logarithm of the wage at the time of entry is 0, thereby capturing the cohort effects and allowing us to visualize how cohorts evolve over time. 

When examining the graphs for Indian, Filipino, Korean, Vietnamese, and Japanese immigrants, a general trend emerges where older cohorts tend to exhibit a higher rate of assimilation. However, in contrast, the graph for Chinese immigrants reveals that more recent cohorts experience a greater rate of assimilation.
In summary, immigrant cohorts from each Asian country display unique and divergent trends, indicating the absence of any clear, uniform pattern. This finding contradicts the "model minority" myth that suggests a consistent pattern of success among Asian immigrant cohorts.


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From our data, we observe that recent cohorts of Asian immigrants tend to have either higher or similar relative wages upon entry compared to older cohorts across all six Asian countries. Additionally, there is no consistent pattern in the rates of assimilation among cohorts within these six Asian countries, which challenges the prevailing "model minority" myth.

One possible explanation for the wage disparity between immigrants and native populations lies in the differing skill compositions of these groups. These skill-based distinctions are observable through factors such as education, while unobservable skill-based differences may be attributed to labor market discrimination, language barriers, and other factors. Another facet of unobservable skill differences, often referred to as omitted variable bias, may stem from the fact that educational qualifications earned in foreign countries may not seamlessly translate into the U.S. context. This could be due to cultural disparities in the workplace or additional licensing requirements in the U.S., potentially hindering immigrants from securing jobs that match their qualifications compared to their U.S. native counterparts.


This paper utilizes data drawn from the 1970–2000 decennial U.S. censuses and pooled 2009-2011 and 2019-2021 ACS data to document and investigate the long-run trends in Asian immigrant earnings spanning several decades, disaggregated by country of origin. One of the central findings of this paper is that, on average, more recent cohorts of Asian American immigrants tend to experience either higher or similar levels of entry wages compared to natives. Furthermore, the long-term trends in the data question the validity of the "model minority" myth, which assumes that all Asian American descendants uniformly outperform U.S. natives, as we observe very distinct paths in the economic assimilation of various Asian groups.

However, this study has a notable limitation, namely, we assumed that immigrants from earlier censuses continue to be present in successive censuses in order to track cohorts over time. In reality, individuals may retire, pass away, or simply return to their home countries, which is more likely for those who may have faced unfavorable job prospects in the U.S. This could lead to an underestimation of the true economic progress within a cohort. Therefore, it is imperative to replicate these findings using longitudinal samples rather than relying solely on the repeated cross-sectional data available in census records. While tracking individual immigrants across several decades may be logistically challenging, it would enhance the validity of our results.

Furthermore, it is essential to account for inflation when assessing earnings growth to obtain a comprehensive understanding of assimilation within a cohort. Macroeconomic conditions can also introduce biases into estimates of aging and cohort effects. Events like the Cold War, the Dot Com Bubble, or the 2008 Great Financial Crisis, may disproportionately impact specific groups of immigrants. It is probable that the variation in how these groups are impacted before and after a certain event is similar, and our cross-sectional methodology effectively captures this effect. However, in future research, we can evaluate whether all groups are equally affected by measuring their correlation with macro events. 
Finally, our study samples are restricted to Asian immigrants from the six major countries of origin, which means that smaller Asian countries are not included in our analysis. A more comprehensive analysis is required to precisely gauge the impact of these factors on the wage assimilation patterns over time for all Asian immigrant groups.


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