Version 1.11 

For additional work on given name popularity, see the Given Name Frequency Project

 

 

Long-Term Trends in Personal Given Name Frequencies in the UK

 

 

Douglas A. Galbi

Senior Economist

Federal Communications Commission[1]

 

July 20, 2002

 

 

 

 

 

 

Abstract

 

 

The frequency distribution of personal given names offers important evidence about the information economy.  This paper presents data on the popularity of the most frequent personal given names (first names) in the UK over the past millennium.  The popularity of a name is its frequency relative to the total name instances sampled.  The data show that the popularity distribution of names, like the popularity of other symbols and artifacts associated with the information economy, can be helpfully viewed as a power law.  Moreover, the data on name popularity suggest that historically distinctive changes in the information economy occurred in conjunction with the Industrial Revolution.  

 


 

 

The frequency of personal given names provides important historical evidence about the information economy. The information economy consists of the production and use of symbols.  Names are an important type of symbol. Choosing a "good name" for a person involves assessing the social valuation of a name.  The frequency distribution of names thus provides evidence about the social valuation of different symbols.  The frequency distribution of names also indicates the number of persons who share the experience of being called by the same symbol in the course of their daily lives.   More abstractly, the frequency distribution of personal names, graphed as the logarithm of name popularity against the logarithm of name popularity rank, looks similar to other frequency or popularity distributions where persons and organizations are free to create and choose among many collections of symbols instantiated and used in a similar way.  Thus naming appears to be representative of more general patterns of behavior in the information economy.

 

This paper shows that, since early in the nineteenth century, the frequency distribution of personal given names in the UK has evolved differently than it did over the previous eight centuries.  Simple indicators of this change are the trend in the popularity (frequency relative to the total number of names in the sample) of the most frequent names.   The popularity of the most frequent name, the three most frequent names, and the ten most frequent names show no trend from circa 1300 to 1800.  Since then all these measures have dropped dramatically.   This latter development reflects a "flattening" in the name frequency distribution, viewed as a graph of the logarithm of name popularity against the logarithm of name popularity rank.   This change in the evolution of the name frequency distribution early in the nineteenth century may indicate a more general change in the information economy about that time.

 

 

I.  Popularity of the Most Frequent Personal Given Names

 

This section provides data on the popularity of the most frequency personal given names in the UK over the past millennium.  Measuring name frequencies in actual samples requires attention to name definition and standardization.  Given names can include multiple names and name variants, as well as abbreviations, non-standard spellings, and mistakes in recording (e.g.William, Bill, Wm., and Williamus). Unlike sampling variability, coding variability does not fall with sample size.  Throughout the analysis in this paper, names have been truncated to the shorter of either the first eight letters of the given name or the letters preceding the first period, space, hyphen, or other non-alphabetic character (e.g. Wm. and Williamus would be truncated to Wm and William, respectively).  These shortened names have then been standardized through a name coding available on the Internet for public inspection, use, and improvement on an open source basis (e.g. Bill is standardized to William).[2]  This procedure attempts to identify feasibly and consistently names with common communicative properties.[3]  Experience with different name samples suggests that this procedure can reduce coding variability to less that half a percentage point for the popularity of a single name and less than three percentage points for total popularity of the top ten names (Galbi 2001, Sec. I.B. and Appendix B).

 

Over the past two hundred years, the popularity of the most frequent personal given names in the UK has steadily declined.  Table 1 shows popularity statistics for the most frequent names. The data in this table come from Census records, birth records, and doctor registrations, collected from different sources documented in detail in Galbi (2001).  In the UK from 1800 to 1994, the popularity of the most frequent female and male names fell from 23.9% and 21.5% to 3.4% and 4.2%, respectively.  The popularity of the ten most frequent names for females and males fell from 82.0% and 84.7% to 23.8% and 28.4%, respectively. 

 

Table 1

Popularity of UK Personal Given Names: 1800 to 1994

 

 

 

 

Females

Males

Birth

Top Name

Top 3

Top 10

Top Name

Top 3

Top 10

Year

Name

Pop.

Pop.

Pop.

Name

Pop.

Pop.

Pop.

1800

Mary

23.9%

53.2%

82.0%

John

21.5%

51.5%

84.7%

1810

Mary

22.2%

50.7%

79.4%

John

19.0%

47.0%

81.4%

1820

Mary

20.4%

47.7%

76.5%

John

17.8%

44.9%

80.4%

1830

Mary

19.6%

45.4%

75.8%

John

16.4%

42.3%

78.2%

1840

Mary

18.7%

43.2%

75.0%

William

15.4%

40.3%

76.0%

1850

Mary

18.0%

41.0%

72.1%

William

15.2%

38.7%

73.8%

1860

Mary

16.3%

37.0%

68.3%

William

14.5%

36.2%

69.8%

1870

Mary

13.3%

31.5%

61.1%

William

13.1%

31.7%

63.5%

1880

Mary

10.6%

25.4%

53.8%

William

11.7%

28.5%

58.9%

 

 

 

 

 

 

 

 

 

1900

Elizabet

7.2%

16.2%

38.5%

William

9.0%

22.9%

50.9%

1925

Mary

6.7%

16.8%

38.7%

John

7.3%

17.6%

38.0%

 

 

 

 

 

 

 

 

 

1944

Margaret

4.5%

12.6%

31.7%

John

8.3%

20.7%

39.9%

1954

Susan

6.1%

13.2%

32.5%

David

6.3%

17.4%

37.8%

1964

Susan

3.6%

10.3%

28.6%

Paul

5.6%

15.9%

39.4%

1974

Sarah

4.9%

12.3%

28.0%

Mark

4.6%

12.5%

33.1%

1984

Sarah

4.1%

11.0%

27.3%

James

4.3%

11.8%

32.3%

1994

Emily

3.4%

8.6%

23.8%

James

4.2%

11.0%

28.4%

Note: Based on Galbi (2001), Table 3, p 15 and underlying data.  See Appendix D of that paper for sources and details of analysis..

 

Prior to the beginning of the nineteenth century, the popularity of the most frequent personal given names in England was higher and more stable.  Tables 2 and 3 provide evidence on name popularity from late in the eleventh century through early in the nineteenth century.  The data in Table 2 come from a wide variety of sources, with individual source numbers given after the location (e.g. " 1)" and keyed to a list of sources in Galbi (2001).  The data in Table 3 comes from parish records, with the set of parishes represented changing over time.  From 1300 to 1800, popularities of 20%, 50%, and 80% seem to be roughly representative figures for the top name, top three names, and top ten names for both females and males.   As Table 1 shows, the corresponding figures for the late twentieth century are much lower – about 4%, 10%, and 25%.  It is important to recognize that, while top name popularities show no overall trend from 1300 to 1800, the names that made up the most popular names did change.  The causes of changes in individual names is an empirical issue left for other scholars.

 


Table 2

Popularity of Personal Given Names in England before 1825

 

 

Females

Males

 

Year, Location

Top Name

 

Pop.

Top 3

Pop.

Top 10 Pop.

Sample

Size

Top Name

 

Pop.

Top 3

Pop.

Top 10 Pop.

Sample

Size

1080, Winchester 1)

 

 

 

 

 

Robert

6.6%

18.0%

35%

228

1120, Winchester 1)

 

 

 

 

 

William

6.6%

15.8%

30%

912

1180, Winchester 1)

 

 

 

 

 

William

10.2%

29.2%

57%

383

 

 

 

 

 

 

 

 

 

 

 

1200, Essex 2)

Alice

11.3%

27.4%

56%

c. 1400

William

12.4%

30.5%

61%

c. 4000

1210, South 3)

Matilda

16.2%

39.9%

70%

173

William

14.4%

32.7%

65%

877

1270, Rutland 4)

Alice

19.4%

51.0%

84%

206

William

15.2%

35.6%

76%

1627

1300, Lincoln 5)

Alice

17.1%

42.4%

75%

1213

John

22.7%

52.2%

79%

9390

 

 

 

 

 

 

 

 

 

 

 

1260, London 6)

 

 

 

 

 

John

17.6%

39.7%

69%

814

1290, London 6)

 

 

 

 

 

John

23.3%

44.8%

73%

1852

1510, London 7)

 

 

 

 

 

John

24.4%

49.4%

74%

427

1610, London 7)

 

 

 

 

 

John

21.0%

43.8%

72%

463

1825, London 8)

Mary

19.2%

43.9%

73%

63809

William

16.3%

39.2%

80%

48275

 

 

 

 

 

 

 

 

 

 

 

1350, Manchester 9c)

 

 

 

 

 

John

22.7%

47.4%

92%

717

1610, Manchester 10)

 

 

 

 

 

John

18.6%

37.6%

77%

1298

1805, Manchester 11)

Mary

25.8%

48.2%

84%

1866

John

21.7%

48.7%

81%

1935

 

 

 

 

 

 

 

 

 

 

 

1350, Yorkshire 9d)

Alice

22.4%

50.4%

86%

1794

John

33.5%

66.8%

93%

1665

1620, Yorkshire 12)

Ann

24.0%

54.7%

88%

342

John

16.2%

47.1%

86%

427

1670, Yorkshire 12)

Ann

21.5%

59.2%

79%

228

William

18.7%

47.4%

78%

283

1720, Yorkshire 12)

Mary

25.7%

57.4%

87%

413

John

25.5%

57.8%

86%

377

1770, Yorkshire 12)

Mary

22.8%

45.9%

84%

381

John

25.6%

55.7%

86%

433

1825, Yorkshire 8)

Mary

20.1%

45.8%

81%

99299

John

18.8%

44.2%

79%

91111

 

Females

Males

 

Year, Location

Top Name

 

Pop.

Top 3

Pop.

Top 10 Pop.

Sample

Size

Top Name

 

Pop.

Top 3

Pop.

Top 10 Pop.

Sample

Size

1350, North/Cumbria 9a)

 

 

 

 

 

John

34.5%

64.6%

89%

328

1530, North/Cumbria 13)

Jane

16.0%

44.8%

84%

852

John

23.1%

46.1%

74%

870

1550, North/Cumbria 13)

Margaret

15.6%

45.1%

86%

1491

John

21.7%

44.4%

75%

1515

1580, North/Cumbria 13)

Margaret

16.8%

44.9%

84%

3750

John

18.0%

39.4%

71%

3765

1610, North/Cumbria 13)

Elizabet

15.8%

43.8%

84%

4000

John

18.2%

42.4%

74%

4044

1640, North/Cumbria 13)

Elizabet

16.6%

46.0%

87%

2888

John

19.7%

46.7%

75%

2914

1670, North/Cumbria 13)

Elizabet

16.5%

45.1%

86%

3813

John

19.6%

46.7%

75%

3834

1700, North/Cumbria 13)

Ann

16.4%

47.1%

86%

3064

John

21.1%

49.5%

77%

3070

1730, North/Cumbria 13)

Ann

18.1%

50.0%

87%

2038

John

21.6%

49.9%

80%

2038

1760, North/Cumbria 13)

Ann

18.8%

52.1%

89%

2830

John

23.2%

51.4%

81%

2830

1790, North/Cumbria 13)

Mary

19.4%

50.8%

89%

2139

John

23.4%

52.9%

83%

2141

1825, North/Cumbria 8)

Mary

20.3%

46.7%

88%

24857

John

21.8%

49.9%

85%

21966

 

 

 

 

 

 

 

 

 

 

 

1350, Hereford 9b)

Alice

21.9%

47.2%

84%

576

John

34.8%

58.9%

89%

2066

1700, Hereford 14)

 

 

 

 

 

John

20.3%

49.9%

78%

931

1825, Hereford 8)

Mary

21.7%

56.1%

85%

6832

John

18.9%

51.1%

90%

6350

 

 

 

 

 

 

 

 

 

 

 

1280, East Anglia 15)

 

 

 

 

 

John

22.3%

47.1%

74%

391

1400, East Anglia 15)

 

 

 

 

 

John

36.1%

63.3%

 

90%

590

 

 

 

 

 

 

 

 

 

 

 

1385, soldiers 19)

 

 

 

 

 

John

28.1%

58.3%

84%

829

1550, sailors 16)

 

 

 

 

 

John

21.4%

40.8%

70%

583

1560, Canterbury 17)

Elizabet

13.6%

33.6%

74%

661

John

20.3%

46.9%

75%

5986

1560, Gloucester 18)

Joan

18.7%

45.5%

88%

c. 4000

John

21.4%

52.5%

80%

c. 4000

Note:  Adapted from Galbi (2001) Table 5 p. 20.  The source identifier is the number following the location (or group descriptor, such as "soldiers")>  For details and sources, see ibid p. 41-43, and Appendix D.


 

 

Table 3

Personal Given Names in England:

1570 to 1700

 

 

Popularity of

Top 3 Names

Birth Years

Females

Males

1570-1579

41.0%

48.5%

1580-1589

36.2%

47.3%

1590-1599

41.1%

50.6%

1600-1609

38.2%

48.8%

1610-1619

38.8%

49.9%

1620-1629

41.3%

49.3%

1630-1639

45.1%

48.5%

1640-1649

46.7%

49.3%

1650-1659

50.1%

49.0%

1660-1669

47.5%

48.0%

1670-1679

50.3%

50.3%

1680-1689

51.7%

49.2%

1690-1700

52.1%

51.2%

Source:  Smith-Banister (1997) Table 7.8, p. 150.  Figures for “mean” across English regions are given above.  Sample sizes and weighting not reported.

 

 

Significant changes prior to 1800 seemed to have a relatively small effect on the pattern of name popularity.  The Norman Conquest of England in 1066 brought about an almost complete change in given names.  Within a few generations, most persons used given names brought by the invaders.  By about 1250, pre-Conquest names had essentially died out.[4]  The influx of new names and the shift to them must have decreased the popularity of the most popular names until the new naming practices were well established throughout society.   Yet only about a hundred years after the Conquest the popularity of the most popular male names in Winchester had risen to a level closer to that in 1300 and 1800 than that in the late twentieth century.   The information economy of the twelfth century supported an astonishing capacity for dissemination of information (new names) and creation of social information (the pattern of popular names).  The relatively high name popularity prior to 1800 was not simply an artifact of inertia created by naming norms or underdevelopment of the information economy. 

 

II.  A Better View of Changes over the Past Two Hundred Years

 

Changes in the popularity of the most frequent name, most frequent three names, and most frequent ten names are part of a larger order of change that can be easily recognized graphically.  Scholars analyzing personal given names have recognized that graphs of name frequencies have a characteristic shape (Eschel, 2001; Tucker, 2001, 2002; Galbi, 2001).   The graph of the logarithm of name popularity against the logarithm of name popularity rank is the same as a similar graph using name frequencies, except that the left axis is labeled in more easily understood units.[5]  The graph typically is nearly a straight line.  This type of empirical regularity is called a power law.  It describes the relative frequency or popularity of names.  Hence a power law describes a relationship between the popularity of the most frequent name, the three most frequent names, and the ten most frequent names

 

Over the past two hundred years, the change in the popularity of the most frequent names has been associated with a flattening of the power law that best describes the name popularity distribution.  Charts 1 and 2 show these graphs for names of females and males born in the UK in 1819-30 and in 1994.   In both cases the slope of a line approximating the graph has become less negative.  This means that the relative name popularities have become more equal.  This change can be interpreted as a reduction in the magnitude of information encoded in the name distribution and an increase in the extent of personalization in naming (Galbi 2001, Sec. II.B). 

 

Popularity Distribution of

UK Female Names

 

 

 

 

 

 

Popularity Distribution of

UK Male Names

 

 

Empirical regularities such as those in Charts 1 and 2 are in fact prevalent in the information economy.  Where persons and organizations are free to create and choose among many collections of symbols instantiated and used in a similar way, the relative popularity of the symbolic artifacts typically follows a power law.  Thus the circulation of magazines of similar type has followed power laws throughout the twentieth century.  The total box office receipts of movies follow a power law.  The popularity of musical groups, as measured by “gold records,” follows a power law (Chung and Cox, 1994).  The popularity of Internet web sites, measured in users or page views, also follows a power law (Adamic and Huberman, 2000).  Insights into the evolution of such power laws over time from study of names might contribute to more general insights into personal preferences, media diversity, information industry structure, and other aspects of the information economy.

 

 

III. Understanding the Changes

 

Although recent work on personal given names in England has emphasized name-sharing practices for understanding the frequency distribution of given names (Smith-Bannister, 1997), name-sharing practices have little direct relationship to the frequency distribution of names.  Naming a significant share of children after parents, or after godparents, are equally consistent with a high or low popularity of the most frequent names.  Similarly, having names freely chosen, i.e. chosen in absence of norms giving high value to the name of a person in a specific social position in relation to the person to be named, could produce high or low popularity of the most frequent names.  The most that can be said for name-sharing is that a norm of naming after parents creates additional inertia in name popularity.  Name popularity and its long-term evolution depend on factors other than name-sharing.  The evolution of the name frequency distribution over time is a complicated dynamic system.  Such systems can, in some circumstances, be highly sensitive to a particular factor, while in other circumstances, be totally unaffected by that factor.  Moreover, boundary conditions, such as a small share of naming done in violation of prevailing norms, can determine the over-all state of the system.[6]

 

Analysis of long-term trends in personal given names in the UK suggests that significant changes in the information economy occurred in conjunction with the broad social and economic changes called the Industrial Revolution.  The Industrial Revolution is associated with more rapid growth in population.  The population of England in 1800 was about 50% greater than in 1300, while its population in 2000 was about six times greater than in 1800.  The Industrial Revolution is also associated with much more rapid growth in income: real economic income per person probably increased by about a factor of four from 1300 to 1800, and by about a factor of 100 from 1800 to 2000.[7]  But populations of much different sizes show similar naming patterns (Eshel (2001), Galbi (2001) Table 4), and it is not clear how the level of income itself would effect naming.  The Industrial Revolution also produced major changes in social networks and the social context of personal activity.  These changes probably drove changes in the information economy.

 

Whether information and communication technologies have created or will create a “new economy” is an important public policy issue.  These technologies enable persons to interact in new ways that may be as significant as the changes associated with the Industrial Revolution.  Consider, for example, the creation of knowledge about aggregate patterns of personal given names.  Large compilations of name frequencies can be easily shared on the Internet.  I have benefited from such sharing of information in writing this paper, and I have made much more extensive data on name frequencies than can be reported in this paper freely available on the Internet.[8]  If other scholars use the Internet in similar ways, this sub-field of onomastics could develop much more rapidly than it has in the past.  The same might be true of many other areas of activity.  Analyzing the popularity distribution of personal given names thus offers a particularly rich means for understanding changes in the information economy.

 


 

References

 

Adamic, Lada A. and Bernardo A. Huberman. 2000.  “The Nature of Markets in the World Wide Web.” Quarterly Journal of Electronic Commerce 1: 5-12 [online at

http://www.parc.xerox.com/istl/groups/iea/abstracts/ECommerce/webmarkets.html].

 

Chung, Kee H. and Raymond A.K. Cox. 1994.  “A Stochastic Model of Superstardom: An Application of the Yule Distribution.” The Review of Economics and Statistics 76: 771-75.

Clark, Cecily. 1992. “Onomastics.”  Ed. Richard M. Hogg.  The Cambridge History of the English Language, Vol. II, 1066-1476.  Cambridge: Cambridge University Press.

 

Eshel, Amram. 2001. “On the Frequency Distribution of First Names.”  Names 49: 55-60.

 

Gabaix, Xavier. 1999. “Zipf’s Law for Cities: An Explanation.” Quarterly Journal of Economics 114: 739-67.

 

Galbi, Douglas A. 2001.  “A New Account of Personalization and Effective Communication.” Manuscript online at http://www.galbithink.org and http://www.ssrn.com.

 

Mayhew, N.J. 1995. “Population, money supply, and the velocity of circulation in England, 1300-1700.” Economic History Review XLVIII: 238-57.

 

Smith-Bannister, Scott.  1997. Names and naming patterns in England, 1538-1700.                     Oxford: Oxford University Press.

 

Snooks, Graeme Donald. 1995. “The dynamic role of the market in the Anglo-Norman economy and beyond, 1086-1300.”  A Commercialising Economy: England 1086 to c.1300.  Eds. Richard H. Britnell and Bruce M.S. Campbell. Manchester and New York: Manchester University Press.

 

Tucker, D.K. 2001.  “Distribution of Forenames, Surnames, and Forename-Surname Pairs in the United States.” Names 49: 69-96.

 

Tucker, D.K. 2001, "Distribution of Forenames, Surnames, and Forename-Surname Pairs in the United States.” Names 50: 105-132.


 

 

Appendix – Personal Given Names Over Time

 

The table below shows the ten most popular given male names about London over time.  The years given are approximate birth years.  The average year of birth was estimated relative to the date of the compilation and the probable ages of the persons in the compilation.  The data come from a variety of sources, which have used different (and often not explicit described) approaches to standardizing and grouping names. 

 

 

Top Ten Most Popular Names in London

 

Rank

Name

Year

c. 1120

Name

Year

c. 1260

Name

Year

c. 1510

1

Willelm

6.6%

John

17.6%

John

24.4%

2

Robert

5.0%

William

14.4%

Thomas

13.3%

3

Ricard

4.2%

Robert

7.7%

William

11.7%

4

Radulf

3.6%

Richard

7.0%

Richard

7.3%

5

Roger

3.2%

Thomas

5.3%

Robert

5.6%

6

Herbert

2.2%

Walter

4.4%

Ralph

3.3%

7

Hugo

1.8%

Henry

4.1%

Edward

3.0%

8

Johannes

1.3%

Adam

3.1%

George

2.1%

9

Anschetill

1.1%

Roger

2.9%

James

1.9%

10

Drogo

1.1%

Stephen

2.3%

Edmund

1.6%

 

Sample Size

912

Sample Size

814

Sample Size

427

 

 

Rank

Name

Year

c. 1610

Name

Year

c. 1825

Name

Year

c. 1994

1

John

21.0%

William

16.3%

Jack

3.2%

2

William

11.4%

John

13.5%

James

3.1%

3

Thomas

11.4%

George

9.4%

Daniel

2.2%

4

Richard

5.2%

James

8.6%

Thomas

2.2%

5

Samuel

5.0%

Thomas

8.6%

Michael

1.6%

6

Henry

4.8%

Henry

7.6%

Alexander

1.5%

7

Edward

4.5%

Charles

5.8%

Matthew

1.4%

8

James

3.5%

Joseph

3.7%

Luke

1.3%

9

Joseph

2.6%

Edward

3.5%

Samuel

1.3%

10

Robert

2.4%

Robert

3.1%

George

1.3%

 

Sample Size

463

Sample Size

48275

Sample Size

51097

 

 

The list for 1120 was compiled from the Winton Doomesday book for the year 1148.  The list is given in Barlow et al. (1976), Table 8, p. 187.  No details are provided regarding any name standardization done. 

 

The list for 1260 was compiled from the London Subsidy Rolls of 1292.  The list is given in Ekwall (1951) p. 35.  Variants included under the given name heading are as follows: John (Jon), Walter (Water), and Henry (Hanry, Hary, Herri). 

 

The list for 1510 was compiled from baptismal names in five London parishes, 1540-1549.  The parishes are: St. Peter’s upon Cornhill; St. De’nis Backchurch; Christ Church Newgate; Kensington; St. Antholin, Budge Row.  All baptismal names, as recorded in Harleian Society Publications, were included in the compilation.  The list is given in Stewart (1948), Table 1, p. 110.  The source notes: “I have tried to ignore mere variations of spelling, but to count separately the different forms of  the same name, such as Henry and Harry, Augustine and Austin. … Spellings have been normalized to conform with those of the King James Bible, or with modern usage for non-Biblical names.”  See Stewart (1948), footnote pp. 109-10.

 

The list for 1610 was compiled on the same basis as the 1510 list, but for the years 1640-1649.  See Stewart (1948) Table 2, p. 112.

 

The 1825 list is from persons born between 1819 and 1830 in London, and still alive and recorded in the U.K. Census of 1881.   The complete Census of 1881 is available from the Genealogical Society of Utah (1997).  Names given in the Census were standardized using GINAP v. 1.0 name standardization.

 

The list for 1994 includes all males born in Greater London in 1994 who registered with the National Health Service Central Register. See Merry (1995), Table 21.  The source lists the top 50 names. From that compilation, the list given above groups Jamie with James and Jake with Jack. 

 

Scholars interested in additional name lists should consult Smith-Bannister (1997), Appendix C. That appendix lists, at decade intervals, the fifty most popular male and female names in forty English parishes from 1538-49 to 1690-1700.  Unfortunately, the frequency of specific names are not given, nor are sample sizes.  The weights given to individual parishes in each decade sample apparently change, but details are not given.

 

 

Additional References

 

Barlow, Frank, Martin Biddle, Olof von Feilitzen, and D.J. Keene, with contributions from T.J. Brown, H.M. Nixon, and Francis Wormald, Winchester in the Early Middle Ages: An Edition and Discussion of the Winton Doomesday (Oxford: Clarendon Press, 1976) Table 8, p. 187

 

Ekwall, Eilert, ed., Two early London subsidy rolls, with introd., commentaries, and indices (Lund: C.W.K. Gleerup, 1951) pp. 34-37.

 

Genealogical Society of Utah, Federation of Family History Societies [GSU-FFHS], 1881 Census for England and Wales, the Channel Islands and the Isle of Man [computer file, SN: 3643] (Colchester, Essex: The Data Archive [distributor], 29 July 1997).

 

Merry, Emma, with support from Kay Callaghan and Chris Cotton, First Names: The definitive guide to popular names in England and Wales 1944-1994 and in the regions 1994 (London: HMSO, 1995).

 

Stewart, George R., Men’s Names in Plymouth and Massachusetts in the Seventeenth Century (Berkeley and Los Angeles: University of California Press, 1948) Tables 1 and 2, pp. 110, 112, compiled from London parish records (source 7).

 

 

 



[1] The opinions and conclusions expressed in this paper are those of the author.  They do not necessarily reflect the views of the Federal Communications Commission, its Commissioners, or any staff other than the author.  Author’s address: [email protected]; FCC, 445 12’th St. SW, Washington, DC 20554, USA.

[2] See the GINAP webpage.  The principle for coding is to group together names that either sound the same, have the same public meaning, or changed only in the recording process (spelling errors, recording errors, etc.).

[3] Note that name standardization helps to control for changes in names used as a person grows older, e.g. a correlation between nicknames or informal names and age.  Thus name standardization is particularly important in analyzing time trends when the data come from naming cohorts constructed by age.  That is the case for this paper’s data on nineteenth century names.

[4] Clark (1992) pp. 552, 558-562. There is no evidence that Norman clergy or royal officials compelled the English to adopt Norman names.

[5] This is true because log(a/b)=log(a)-log(b).  The logarithm of name frequency differs from the logarithm of name popularity only by an additive factor.  Name popularity rank and name frequency rank are of course identical.

[6] Gabaix (1999) shows that, when the appearance rate for new cities is not too high, it has no effect on the slope of the power law describing city sizes.  If the appearance rate for new cities rises above a certain threshold, than the slope depends on the appearance rate.  Cities can be analogized to name types. 

[7] For population and income statistics for 1700 and earlier, see Mayhew (1995) Table I, and Snooks (1995), Table 3.5.  For current population statistics, see UK National Statistics, Key Population and Vital Statistics, online at http://www.statistics.gov.uk/statbase/Product.asp?vlnk=539&More=N .  The large changes in the structure of the economy over the past two hundred years make estimating changes in per capita income subject to significant uncertainty.  The figure of 100 is my estimate based on my knowledge of the economic history literature.

[8] See AGNAMES names frequency webpage.