Abstract
Recent studies have examined the effect of political conflict and domestic terrorism on economic and political outcomes. This paper uses the rise in mass violence between 1870 and 1940 as an historical experiment for determining the impact of ethnic and political violence on economic activity, namely patenting. I find that violent acts account for more than 1,100 missing patents compared to 726 actual patents among African American inventors over this period. Valuable patents decline in response to major riots and segregation laws. Absence of the rule of law covaries with declines in patent productivity for white and black inventors, but this decline is significant only for African American inventors. Patenting responds positively to declines in violence. These findings imply that ethnic and political conflict may affect the level, direction, and quality of invention and economic growth over time.
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Notes
Using data on major British firms, Bloom and Van Reenen (2002) show that higher uncertainty in the market for patents reduces productivity because of delayed investment.
Economists and other scholars are increasingly interested in this period of conflict. Loewen (2005) finds all-white “sundown towns” emerged and were established using subtle intimidation and outright violence in nearly every state after 1890. Jaspin (2007) investigates sudden and dramatic shifts in racial composition in many U.S. counties. Using county-level census data between 1864 and 1923 and current census data, he finds that violent episodes of “racial cleansing” occurred throughout the United States and resulted in all-white or nearly all-white counties that have persisted. Norrell (2009) presents a new history of segregation in America with an emphasis on hate-related violence and the African American leader Booker T. Washington. Interest among policymakers and the popular press has also increased. Allen et al. (2000) chronicle the history of lynching through photographs and postcards, and their exhibit at the New York Historical Society and at other venues has received much attention (Smith 2000). In the last decade, a number of newspapers, such as the Waco Tribune-Herald (2006), have issued apologies for their role in fomenting riots and lynchings through “lynch journalism” during this period.
Although negative effects of race riots during this period were disproportionately concentrated among African Americans, there were also negative spillovers reported for whites. O’Dell (2001) analyzes claims against the city for property damage and other data related to the Tulsa riot in 1921 and identifies whites who incurred riot-related losses due to theft from businesses and losses associated with real-estate transactions in black neighborhoods. Martial law was imposed on the entire city of Tulsa following the riot, which would have affected all city residents. Mixon and Kuhn (2005) cite several newspaper accounts reporting the death of a white woman who had a heart attack at the sight of the mob near her home during the Atlanta riot in 1906.
There is some debate in the literature about whether the motives for lynching were relatively more political or economic. See Darity and Price (2003) for an extensive discussion of this debate.
Although there are no reports of lynchings of inventors in the biographical data collected, there is anecdotal evidence that arsonists and firebombers more often targeted African American inventors, particularly those who manufactured their inventions. For example, Haber (1970) includes an account of two fire bombings at the home of Percy Julian, a black chemist. The direct and indirect effects of arson and fire bombing are likely equivalent to those of riots (through property destruction) and lynching (personal security threats and the rule of law).
Historical American Lynching (HAL) Data Collection Project data on lynchings are often used in empirical studies. These data are based on and nearly identical to the Tolnay and Beck (1995) data. Because the data Tolnay and Beck (1995) used are limited geographically and temporally (1882–1930), the lynching series used here combines the Tolnay and Beck (1995) data for selected southern states and lynching data collected by Tuskegee Institute (2004) and Ginzburg (1962) for non-southern states. Both black and white lynchings, especially in northern states, are undercounted. Data on white lynchings report victims who are of all racial groups other than black, including those of Chinese and Mexican descent.
In 1892, Ida B. Wells (later Wells-Barnett), an early civil rights and anti-lynching activist who helped found the NAACP, published the Red Record, which contained the first systematic data on lynchings in the United States, and in 1895. Southern Horrors: Lynch Law in All Its Phases, both of which were nationally and internationally circulated. See Wells-Barnett (1892, 1895). By the early 1900s, regional and national, including congressional, debates on lynching were also receiving attention across the United States and beyond.
This is a negative externality cited in apologies for lynching by both U.S. Houses of Congress in 2008 and 2009.
It is anticipated that data on passage of segregation laws may understate the extent of racial segregation and isolation and their effect on property-rights enforcement. Supreme Court rulings and local, including residential, segregation laws are excluded from the data. For example, using census data, Cutler et al. (1999) develop indices of segregation and isolation from 1890 to 1990 and consider the importance of residential segregation in explaining the variation in segregation over time. Legislation related to miscegenation and employment is included in the “other” category in Table 1. As well, policies, customs, and practices will not necessarily be fully captured by state legislation.
Specifically, he argues, “Once previous customs became lodged in the statute books, it was imperative that any breaches be swiftly punished as examples to others of how the new order would be implemented....To forestall lynch mobs, courts often speeded the conviction and execution of black defendants, distorting whatever semblance of constitutional protection remained for them” (256-57).
See Jaspin (2007), p. 8. Data on racial cleansings were unavailable and, hence, are beyond the scope of the current paper.
See Thomson (2009) for a rich discussion of the importance of social ties and networks for invention and patenting in the nineteenth century.
Loewen (2013) notes that there were also entire towns, including three in Illinois, which barred African Americans during the day.
Suing a white person was one of the offenses reported for victims in the HAL lynching data set. Also, anecdotal evidence suggests that abrogation of intellectual property rights was not unusual. A letter in the Carter G. Woodson Papers contains testimony from the son of an African American inventor whose patent rights were illegally assumed by a firm when his father was temporarily sent on assignment abroad. However, to my knowledge, no systematic evidence of such abrogation exists. Similarly, there is anecdotal evidence concerning greater rejection rates of patents received from applicants suspected of being African American. There is only one instance of this behavior in the literature, and a comparison of a sample of similar patents obtained by white and African American inventors shows that the time between patent application and grant for the two groups was not significantly different, 1.4 years in each case. The implication is that patent examiners did not treat patent applications from the two groups of inventors differently once the decision to grant the patent was made. Application rejection rates would need to be analyzed to examine Patent-Office behavior more fully, which is beyond the scope of the current paper.
For example, Foner (1978) reports that Joseph H. Dickinson, a prolific inventor of musical and mechanical instruments, could only display his inventions and view other exhibits at the Centennial Exposition in Philadelphia in 1876 in the “Negro building.” As a result, there were extra costs associated with marketing his inventions.
Throughout the paper, I use the terms “patent” and “utility patent” interchangeably. A utility patent is issued for any new and useful process, machine, manufacture, composition of matter, or any new and useful improvement thereof. From 1995, utility patents are effective for 20 years from the date of application. Utility patents constitute more than 95 % of all patents granted to African Americans. Although it is standard to use patents as a proxy for innovation and inventive activity, this measure has limitations as, for instance, not all inventions are patentable or patented. However, direct measurement of invention is not generally possible and, in particular, not available, given the limitation of historical data needed for this study.
The 1843 patent of Norbert Rillieux was the only patent record Baker observed with the term “colored” next to the name of the patentee. It was the earliest patent he identified with an African American named as the patentee, but subsequent research would show that an 1821 patent obtained by Thomas Jennings was the earliest known to have been obtained by an African American. See the data appendix, Appendix I, for an explanation of approaches for identifying African American inventors, including the Baker surveys.
The easily identifiable names were based on the post-slavery practice of adopting the names of American presidents as first and middle names. The inventors using this convention were Andrew Jackson Beard, George Washington Carver, and George Washington Murray.
Biographical data, including patentee education, training, and property-ownership status, are only available and have been collected for a group of 26 prolific inventors before 1930. This group is the subject of Cook (2011). Application data were not recorded for patents obtained between 1870 and 1873. Technological classes created by Hall et al. (2001) are designed as an alternative to the USPTO technical classification to capture broad technological categories of innovation. Patents collected are matched to broad one-digit categories and more specific two-digit subcategories. Citations, a typical measure of quality of invention, are only publicly available from 1975. Patents granted between 1870 and 1930 and cited from 1975 will be rare, because older inventions will have been incorporated into newer inventions. Therefore, I do not use citations in the present analysis.
To determine the number of patents granted to white inventors, I subtracted the patents obtained by black inventors from total patents granted. Any nonblack patent-holders will therefore be included among white inventors. Although the precise ethnic composition of patent-holders is unknown, it is reasonable to assume that the majority of nonblack patent-holders are white.
The average is two per patentee from 1821 to 2004. The Hall et al. (2001) sample is drawn between 1963 and 1999. During the same period, the average for African American patentees is 6.2, and the median is 2.
Lewis Latimer was a member of Thomas Edison’s research team, the “Edison Pioneers.” Granville T. Woods, who obtained 45 patents mainly related to electricity and transportation, was asked by Edison to join Edison’s Pioneers but declined and preferred to invent alone or with his brother.
This was likely more broadly observed than just among inventors. There is anecdotal and empirical evidence during the period of heightened racial tension that race may have been endogenized, if physically possible. See Jaspin (2007) for an account of blacks who left counties owing to “racial cleansing,” who migrated to different counties, and who appeared in subsequent census years as white.
Other potential explanatory variables, such as wage differentials and quality of schooling, are also not available for the entire period or for all regions. Margo (1990) uses earnings data for blacks and whites from 1900 to 1940 in the South. State school-quality data as used in Card and Krueger (1992) are available from 1919. Rates of illiteracy are available throughout the period of interest and are included in the estimation. Other potential indicators, such as socioeconomic status, are highly correlated with race in the period 1870–1940 and would be dropped because of multicollinearity in estimation.
In this paper, I use the term “natural experiment” in reference to the orthogonality of violent events to patenting, because traditional models of patent activity do not include measures related to violence. For example, seminal work by Griliches (1957) and related subsequent work relate patent activity to demand and R&D spending. Factors like violence and rule of law are not included in these traditional models. The term is also used interchangeably with “historical experiment.”
The year 1921 was also determined statistically to be the break year. The Chow F-statistic for the year 1921 was computed, and the Quandt Likelihood Ratio statistic, or maximal Chow statistic, was also computed to confirm that the maximum Chow F-statistic was selected from a range of potential break years 8 years before and after 1921, 1913–1929.
Data from Google Books Search/Ngram are from April 2012, when more than 20 million books had been scanned.
In estimation, formal inclusion of specific determinants of the knowledge production function used by these and similar researchers will not be possible in this study. For example, Griliches (1957) and Kortum (1997) posit a relation between patenting and R&D expenditure. Many studying the modern era test this relation. Using R&D spending data would be outside the scope of this research, because the National Science Foundation did not collect such data until 1940, which is the last year of the period under review in this paper.
In estimation, the Wilson Administration’s segregation of the civil service in 1913 is considered a state law affecting Washington, DC, although its effects were likely more geographically extensive. It is the only federal law included among the segregation laws used in this analysis.
Statistical identification of a structural break in 1900 (and in 1921 below) is the result of estimating time-specific effects across all years in the sample, including adjacent years. These breaks are the most significant in the period of study.
Zivot and Andrews (1992) and Perron (1989, 1990) tests are used to determine the presence of a unit root with a structural break and intercept (optimal lag lengths from minimized AIC scores). As Eq. (1) implies, all regressors should be first-differenced, as well. However, there are many zeroes in the segregation-law and riot series, and they are essentially count variables, which should not be differenced. I report estimated coefficients for these variables for the estimated level coefficients.
I use the unemployment and industrial-production series alternately in estimation because of the high degree of correlation between them. Estimates obtained using each series are nearly identical, and only those using the industrial-production series are presented in Table 6. See Driscoll and Kraay (1998) for an explanation of Driscoll-Kraay standard errors.
Given the inherent noisiness of historical data, the significance levels attained should be considered a strict lower bound on the true values in all regressions. We may expect a negative effect from the interaction of riots and lynchings on patenting by African Americans because of the magnified sense of insecurity among African Americans and because of the occasional close proximity of these two events (see Table 1). Although these results are not reported, I added the interaction term \(riot_{t} *lynch_{it}\) to the models estimated, and reported results are robust to inclusion of this additional control.
Another approach for the baseline regression is to instrument for riots. I use three instruments that are correlated with riots and inventive activity but are uncorrelated with other regressors: the unemployment rate from Lebergott (1964), changes in industrial production from the Miron–Romer index of industrial production, and fraction of the population living in the South (see data appendix for descriptions of data used as instruments). Although the instruments are valid, they are weak, as were other instruments tried, such as weather patterns, and this approach does not change the fundamental results.
In addition to the aforementioned Southern Railway example, deaths of whites, and other quantified ways in which whites were affected by riots, they were also affected in broader ways. The Tulsa Riot of 1921 was targeted at African Americans, but the declaration of martial law to quell the violence would have affected all residents of, workers in, and economic activity in the city. Many white families had black domestic servants, and, according to historical accounts, e.g., Ellsworth (2001), they were accosted to turn over black workers so they could be taken to detention centers like the other 6,000 arrested. From a more contemporary example, although the riots in Los Angeles in 1992 occurred mainly in predominantly black neighborhoods, the entire city was affected by the curfew, the reassignment of police officers to riot-related duty, the investigation of the police department, the negative national and international publicity brought to the city, and so on. Matheson and Baade (2004) estimate that the entire city of Los Angeles lost $3.8 billion in taxable sales and $125 million in direct sales tax revenue losses.
Similar to Brown v. Board of Education in 1954, Plessy and other Supreme Court rulings are implemented with a lag as legislatures, courts, and other entities determine appropriate mechanisms for compliance. Barth (1968) and Shapiro (1971) contain rich discussions of Supreme Court decisions and their implementation.
Fouché (2003) recounts in detail the deterioration of the professional inventive career of Shelby Davidson, an African American inventor and official in charge of technology design, maintenance, and procurement at the U.S. Postal Office Division in Washington, D.C. Like other African Americans in the Treasury and Post Office Departments, he was removed from his supervisory position following President Wilson’s segregation of the civil service in 1913. He resigned from government service and inventive activity after this event (see pp. 173–176).
Kusmer (1976) reports that, like those in many northern cities, nearly all black-owned firms in Cleveland lost their white clients. As seen in many industrial cities in the North adopting segregationist laws and practices, between 1890 and 1910, the percentage of black residents who owned property in Cleveland fell from 14.8 to 10.9 %. Kusmer also finds that, by 1930, the percentage of African Americans who were property owners in Cleveland had not recovered its 1890 level. Consistent with the evidence from patent data, Higgs (1982, 1984) and Margo (1984) also find patterns of rapid increases in black wealth, as measured by property ownership in southern states, from the 1880s to the mid-1890s and a marked decline beginning around 1896. Unlike black property accumulation during this period, which resumed rapid growth between 1900 and 1905, entrepreneurial and economic activity did not recover quickly. Because these white consumers were wealthier than the black consumers to whom black firms were newly confined and because access to white suppliers was now limited or eliminated altogether, many black-owned firms faced rising cost, falling revenue, and bankruptcy.
Anti-lynching legislation, including the Dyer Anti-Lynching Bill of 1921, was introduced and passed several times in the House of Representatives but rejected by the Senate in the 1920s and 1930s.
Selection of the random-effects estimator is based on Hausman and robust Hausman tests to compare the random- and fixed-effects estimators, as suggested in Hausman (1978), Wooldridge (2002), Baltagi (2008), Cameron and Trivedi (2005), and Greene (2011). From these tests, we fail to reject the null hypothesis that the preferred model is the random-effects model, which suggests that the differences in the random- and fixed-effects coefficients are systematic. The random-effects model is consistent and is the more efficient of the two, which is anticipated since the random-effects estimator uses information from both the within and between estimators, rather than just the within estimator like the fixed-effects estimator, and is consistent with the findings of Taylor (1980).
Tests of the panel data find no evidence of a unit root. Therefore, these data are in levels and not first-differenced. See Maddala and Wu (1999) for unit-root tests in panel data.
The Mid-Atlantic region dummy is the one excluded in estimation. See data appendix for information on construction of the newspaper series. Because systematic data on schooling are not systematically available for the period and states of interest, I use illiteracy rates, which are correlated with schooling variables, in estimation. Illiteracy rates are available for census years only, and the illiteracy rate assigned a specific year is that of the closest census year. A patent is assigned an industry participation rate based on the technological category of the patent, and the value is determined by the closest year available to the grant year. I include a control for prolific inventors in estimation when data on assigned patents are used (Table 8).
This finding is also robust to inclusion of the number of new black-owned banks and new black newspapers in state \(s\) and year \(t\) in estimation.
Assignment of patent rights to a firm or individual at the time the patent is issued is the best available information on value in the patent data. Nonetheless, it is a crude measure of economic value, because patents could be assigned after the patent is granted and assignment could be a noisy indicator of an innovation’s economic value.
A broader indicator of economic activity may be patenting in the “miscellaneous” category, which includes widely varied patents and consists of 44 % of patents by African Americans during the period. Being in a high-lynching state depresses expected miscellaneous patent counts by 29–55 %. This result is significant at all levels of significance.
The estimated coefficient on riots becomes positive and significant when controlling for firms per capita. Although it is not significant at conventional levels, it does suggest that states where manufacturing firms are more concentrated are also states in which mechanical patents and riots also occur.
There are no records of application dates for patents applied for between 1870 and 1873, which diminishes the useable sample size to 714 patents. In fact, two samples are drawn for white inventors. In the first sample, patents of white inventors are matched only by application year to allow variation in other dimensions, such as technology and state or region, which may be exploited in estimation. A second sample, which I do not use in estimation, is drawn by selecting matching patents on state, technology, and application year. The second sample cannot exploit the variation present in the first sample but, as I mentioned, is used to test whether the times between patent application and grant are similar between white and black inventors when controlling for these characteristics, which is what is found.
The random-effects specification using panel data does not work in the placebo experiment. The Tuskegee data report lynchings of whites for each state between 1882 and 1968. Data by state and year are unavailable, and there is insufficient variation in average lynchings per year for estimation. The Ginzburg (1962) and Tolnay and Beck (1995) state data allowed me to minimize this problem in the black series. More important, measurement error was more pronounced for white than for black lynchings. For example, immigrants from Mexico, China, and other countries are recorded as “white” among victims of lynching. Carrigan and Webb (2003) find that mobs lynched nearly 600 Mexicans between 1848 and 1928, which would represent almost half of all white lynchings recorded in the Tuskegee data. The motives for these lynchings would be more heterogeneous than if they were in fact white Americans. Because detailed data were not available on white lynchings outside the South, there was no means of systematically separating whites from nonwhites in the white lynching data. To the extent data are available, they are incomplete with respect to ethnic and temporal coverage, such as the lynchings of people of Mexican origin in the United States from 1848 to 1928 examined in Carrigan and Webb (2003). Variation in lynchings by state-year cannot be exploited in the panel framework. However, these errors are less pronounced when data are aggregated by year or by state, and a negative binomial specification is used for both samples, given overdispersion in the white sample. Because of omitted variables and an overcount of actual white lynchings, the estimated coefficient on lynchings for whites will be biased upward in these (and all) regressions. Finally, measurement error is also problematic in the black sample, as lynchings, especially in northern states, are underreported, and this biases estimated coefficients on lynchings among blacks toward zero in all regressions.
The notation follows Long and Freese (2006). Data on industry participation are not available for whites and are therefore excluded in these regressions
These results are consistent with a second counterfactual exercise presented in Appendix III. In this case, parameter estimates from estimation of Eq. (3) in in the black subsample are used in the white (non-placebo) subsample. As can be seen in Fig. f4, patent output over the period 1882–1940 would have been significantly lower and more volatile for white inventors. This estimation does not fully account for preexisting differences between the two groups. Nonetheless, the results are suggestive that economic activity would be substantially higher and more stable absent hate-related violence.
The case of Dr. Percy Julian, the developer of cortisone and the first African American to head a major industrial research laboratory (Glidden Industries), is more direct. Julian began his patenting career at the end of the 1930s. During his tenure at Glidden, his home in a predominantly white neighborhood in Oak Park, Illinois, was firebombed twice. Such violence was likely extraordinary in industrial research circles.
See Mowery and Rosenberg (1998) for a comprehensive discussion of the development of R&D activities within firms during the twentieth century.
Anecdotal and historical evidence suggest that several inventors were extended jobs as inventors in industrial laboratories as a result of phone interviews, such as Lloyd Hall, but were not allowed to take the positions once their race was known.
Other hypotheses related to the causes of lynching have been advanced and tested. Blalock (1967) argues that lynching of blacks was a response to rising political competition between blacks and whites. Inference is difficult, Tolnay et al. (1989) find, because parameter estimates in these models are sensitive to outliers and model misspecification, among other problems. Recently, research has focused on preservation of social norms as an explanation for lynching, e.g., Carden (2006, 2009), Feimster (2009), Markovitz (2004), and Wood (2011). Still other evidence suggests that the origins of lynching are economic. “Whitecapping,” or the organized efforts of nightriders using violence to drive blacks from their land, was a common practice in the Deep South. See Holmes (1980), Whayne (1996), and Winbush (2003) for an elaboration of the practice of “whitecapping” and the “whitecapping” hypothesis.
This sum includes 84 thefts and robberies, which may or may not have had an economic motive. These data were also reviewed, along with the data and literature on riots, for political motives. Only 0.4 % of lynchings and five of 27 riots during this period could be traced to an explicit and documented political motive, such as voting. Because lynchings were extralegal killings, it is difficult to know the underlying relation between offenses recorded and actual offenses.
See Data Appendix for a description of the construction of the newspaper series.
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Acknowledgments
I am grateful to George Akerlof, Jeff Biddle, Barry Eichengreen, Stan Engerman, Milton Friedman, Galina Hale, Chang Tai Hsieh, Thomas Jeitschko, Michael Kremer, Steve Levitt, Trevon Logan, Petra Moser, Paul Romer, Ken Sokoloff, Michèle Tertilt, and Tim Vogelsang for helpful comments on earlier versions of this paper, to Ken Arrow, Sandy Darity, Crystal Feimster, Naomi Lamoreaux, Jeff Wooldridge, and Gavin Wright for helpful conversations, and to Stewart Tolnay and E.M. Beck for use of their data. I would like to thank seminar participants at Michigan State University; the University of Michigan; Harvard University; NBER; the University of California, Berkeley, Davis, and Riverside; Stanford University; and Yale University, and a number of entrepreneurs, patentees, and patent attorneys for helpful conversations. Two anonymous referees provided useful comments. I am grateful to Priyanka Bakaya, Jeff Brown, Chaleampong Kongcharoen, Serah Makka, Ging Cee Ng, and Christopher Tan for able research assistance and to reference librarians and staff at the Carter G. Woodson Collection at the Library of Congress, the Harvard University Office for Technology and Trademark Licensing, the Moorland-Spingarn Research Center at Howard University, and the Western Reserve Historical Society for their expert assistance. I conducted much of this research while at the Hoover Institution at Stanford University, and its generosity is acknowledged. All mistakes are my own.
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Appendices
Appendix I: Data
1.1 Data sources
Data on patents obtained by African Americans between 1870 and 1940 come from the author’s data set, which extends the Baker (1913/1969, 1917, 1921) data set. Total patent data are from the U.S. Patent and Trademark Office database. Patents held by white inventors are derived by subtracting patents obtained by black inventors from the total. Data on lynchings by race of victim per year per state in southern states are from Beck and Tolnay (1995). Data on lynchings in other states are from the Tuskegee Institute data set and are averages for the period 1882 to 1930; annual data are not available by state. Data for blacks and whites after 1930 are from the Tuskegee data set. I find that the Tuskegee data underestimate lynchings among blacks and whites in nonsouthern states. Data from Ginzburg (1988) were added for blacks in nonsouthern states. Data on major riots and segregation laws are from the U.S. House of Representatives Select Committee (1979), Library of Congress (2004), Higgs (2007), “The History of Jim Crow” (www.jimcrowhistory.org), and the Final Report of the Oklahoma Commission to Study the Tulsa Race Riot of 1921 (2001). Aggregate and state illiteracy data are extracted from Integrated Public Use Microdata Series (2004), approximately 50,000 individuals over 10 years old, and from the University of Virginia Library (2004), full sample, individuals over 10 years old. Data on aggregate illiteracy rates in 1890 are taken from Collins and Margo (2003). These data are derived from the population of 10- to 69-year-olds using the full count. Population data are extracted from Gibson and Jung (2002). Regions do not conform exactly to census divisions: Delaware and Maryland are considered Mid-Atlantic states in this paper and are considered South Atlantic states by the U.S. Census Bureau. Data on black-owned banks are from Ammons (1996). Industry and occupation data are from Margo (1990). The industry-participation variable is available only for 1910 and 1940 and is only for the South. Patents obtained up to and including 1900 are assigned industry-segregation values for 1900, and patents obtained after 1900 are assigned values for 1910. Technological categories are taken from NBER-Hall et al. (2001). Economic peak and trough data are from the NBER Business Cycle Dating Committee (2007). As many years of abnormal economic activity are controlled for in estimation as possible. Data on unemployment rates are taken from Lebergott (1964) and are available from 1890 to 1940. Data on industrial production are taken from the Miron and Romer (1990) aggregate index of industrial production, which has 13 components. Data on African American newspapers founded in a given year were collected from the University of Georgia (2007), Harvard University (2007), and the Library of Congress (2007). Firm data for each state are collected from U.S. Census Bureau’s Census of Manufactures (1883; 1895; 1933; 1942).
1.2 Variable definitions
Variable | Definition |
|---|---|
Lynchings | Lynchings per million in a given year |
Riots | Major riot in a given year |
Segregation laws | Laws promoting segregation between races passed in a given year and not overturned within 3 years |
Newspaper | Newspaper established for or by African Americans in a given year |
Illiteracy rate | Person can neither read nor write; over 14 male population, by race |
Bank | African American banks founded in state by a given year |
Great inventor | Prolific inventor as defined in Cook (2011) |
Population, south | Proportion of U.S. population living in the South, by race |
Industry participation rate | Proportion of employment in given industry, southern blacks only, 1900 |
Industrial production | Miron–Romer index of industrial production |
Unemployment | Annual national rate |
Appendix II: Identifying African American Inventors in Patent Data
As I mentioned, it is very difficult to identify the race of a patentee because patent records did not record it, with only one exception since 1790. The first systematic attempt to identify African American patentees was an effort by the Patent Office, which undertook surveys in 1900 and 1913. The objective of the surveys was to locate African American patentees whose achievements would be featured in the 1900 Paris World’s Fair and to commemorate scientific achievements by African Americans in the 50 years following the end of the Civil War. Directed by one of the lead examiners, Henry E. Baker, surveys were sent to 9,000 of the approximately 12,000 patent attorneys and agents. Responses to the survey were collected and analyzed by Baker and published in several formats (Baker 1913/1969, 1917, 1921). A subset of the original responses were donated to Carter G. Woodson, a noted historian, and, in turn, donated by him to the Library of Congress. The Baker data extend from 1834 to 1917. The investigation in this paper required that the data be extended to 1940. A first strategy to extend the data set was to include patents obtained in 1913 and beyond by inventors already in the data set. These data were collected using the European Patent Office (EPO) search engine, which is searchable by name from 1920. Google Patent Search, which can also conduct historical searches, became available after 2004, when these data were originally collected. Google Patent Search misses some historical patents, and the EPO search is more reliable. One strategy for identifying additional black inventors would be to match patentees from USPTO data to Census data. This method should work for inventors who lived and patented in the same place. However, this procedure fails, because African Americans during this period did not patent where most African Americans live, as Table 2 shows. Before 1940, most African American inventors obtained patents in northern states rather than in southern states. Unlike today, specific addresses were not reported by the Patent Office, just the city or town in which the inventor resided or from which he or she applied for a patent. It is difficult to find a unique first- and last-name match using census data, because of the proximity of first and last names of African American inventors to those of other inventors, especially inventors of British origin. Eight patentees were identified as African American using this method. Only with significant additional biographical data does this method work, and these data are available for few inventors in the data set. And if additional biographical data were introduced, the selection problem would be of greater concern, because biographical information is available for only the most famous and prolific inventors. Another strategy would be to match common names given to African Americans to patent data. A three-pronged strategy in the spirit of Fryer and Levitt (2004) and Bertrand and Mullainathan (2004) was executed but was unsuccessful in identifying black patentees. This mechanism is described below. A second-best method would be to match known black inventors to names in the patent data. This method was significantly more successful in producing matches. The second method and its limitations are described in the text. An index of black names for the period 1870 to 1940 was constructed from census data in two ways. The first strategy answered the question: conditional on being black, which names are most likely to be observed? Random samples of black (“Negro”), “mulatto”, and “colored” heads of households from the 1870, 1900, and 1920 censuses were drawn for the District of Columbia, Georgia, Michigan, and New York. From these samples, frequencies were calculated for first and last names separately. There were 14 first names and 11 last names that appeared more frequently than the median frequency and were included in the index. The second strategy answered the question: conditional on observing a certain name, what is the likelihood that the person is black? First and last names of blacks (“Negroes”) and whites were extracted from the 5% IPUMS sample of the 1870 census. Unlike the above samples, names were not restricted to heads of households. From these samples, frequencies were calculated for first and last names separately and by race for names occurring at least 80 times. Among blacks, there were 27 first names and 20 last names that appeared more frequently than the median frequency for whites or were a larger share of the total names than the black share of the total population and were included in the index. A third approach was an extension of the second approach and answered the question: conditional on having a name widely adopted by African Americans following the end of slavery, what is the probability that the person is black? This strategy was intended to take advantage of a well-known practice among African Americans of adopting the first and last names of presidents, e.g., George Washington, or famous people in the black community, e.g., Booker T. Washington, as first and middle names. The entire 1900 census was used and also was not restricted to heads of households. These approaches yielded largely similar results from which I constructed an index of “black names.” Results were nearly identical with respect to surnames. Yet the composite index was unable to predict matches in the 1880 census sample of the 690 individuals identifying their occupation as “inventor.” I was able to predict a small number of black inventors but, with the exception of George Washington Carver and George Washington Murray, not ones that could be matched to a patent. The index significantly underpredicted matches to black inventors and overpredicted matches to white inventors in New England, particularly those born in England, as was the case with the first census-based approach. Additional location and biographical data would have been required to obtain unique first- and last-name matches. In general, these methods are more suitable for the current rather than historical period. This highlights a problem associated with occupation identification and reporting among inventors. Many identify themselves as machinists or artisans or engineers rather than inventors, irrespective of race. Thomas Edison, among other “great inventors” who are alive and active as inventors, does not appear in the 1880 sample. The final strategy to extend the Baker data set was to construct a broad-based data set of African American inventors, i.e., potential patentees, and to match the resulting data to patent data. Among the historical and contemporary sources used to create a pool of potential patentees were searches of historical newspapers, including obituaries, e.g., from the Ohio Historical Society Newspaper online database and newspaperarchive.com; correspondence from Carter G. Woodson, Henry E. Baker, and patent survey participants (Library of Congress); the Garrett Morgan Papers; historical and contemporary directories of African American medical doctors, scientists, and engineers, e.g., academic journals, including the Journal of Economic History and the Journal of Negro History; historical and contemporary biographies of African American inventors and general biographies, e.g., Great Negroes Past and Present; and programs of exhibitors in the African American sections or exhibitions of historical fairs, including the “Exhibit of American Negroes” at the 1900 Paris World’s Fair, the 1904 “Great Negro Fair” in Raleigh, North Carolina, and the 1933 Chicago World’s Fair “Negro Day.” Newspaper and obituary searches and programs of exhibitions allowed the identification of lesser known inventors. A complete list of sources appears in a companion paper. Not all inventors and others in the pool of potential patentees were matched to patent records and were dropped from the data set. Others were dropped if there was not a unique first- and last-name match, e.g., James Young in the patent data. Ultimately, while second best, this process provides a more systematic and less ad hoc means of recovering black patentees to extend the data set. This summary is adapted from Cook (2011).
Appendix III: Estimating the Effect on Productivity Using Black Parameters
Let us consider a second counterfactual exercise. How much lower would inventive activity in the U.S. have been if all inventors operated under violence-related conditions? We can address this question by taking parameter estimates from estimation of equation 3 in the black subsample and using them in the white subsample. As can be seen in Figure 4, patent output over the period 1882 to 1940 would have been nearly 1% per year, or 40% over the period, lower and would have displayed significantly more volatility for white inventors, who constitute the overwhelming majority of inventors at that time. Like Abadie and Gardeazabal (2003), I find that volatility seems to increase in the presence of greater violence. Of course, the comparison using black parameters with the white sample should be interpreted with caution, because it not only reflects the evolution of violence but also pre-violence differences in determinants related to patent or economic activity. There is an imperfect mapping between technological progress and patent activity, and there are other factors that would change in the white subsample, e.g., illiteracy rates. Nonetheless, the results are suggestive that the rate of technical change in the U.S. may have been substantially lower in the absence of the rule of law affecting both races. Further, concomitant improvements in living standards may have increased much more slowly.
Predicted White Patent Activity Using African American Estimates
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Cook, L.D. Violence and economic activity: evidence from African American patents, 1870–1940. J Econ Growth 19, 221–257 (2014). https://doi.org/10.1007/s10887-014-9102-z
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DOI: https://doi.org/10.1007/s10887-014-9102-z