Industrial Revolution began in 1689 or 1649?

Abstract

Acemoglu and Robinson (2012) say that the Industrial Revolution began in England following the English Bill of Rights of 1689. Maddison Project data suggest that it began close to 40 years earlier when the English chopped the head off of King Charles I for abuse of power as discussed in this brief note,.

Introduction

The MaddisonData package for R includes a ggplotPath function that makes it easy to plot Maddison project data for any country or group of countries plus a getMaddisonSources function that makes it easy to get the citations required for publication of such a plot. We illustrate that here applied to England / Great Britain / the United Kingdom, whose 3-letter ISO code is GBR. We select that, because it suggests that the Industrial Revolution began in England close to 1649, when the English chopped the head off their King Charles I for abuse of power, 40 years earlier than the English Bill of Rights, which Acemoglu and Robinson (2012) claim started the Industrial Revolution

World leader in `GDPpc` by year

Let’s compute the world leader in gdppc for each year in MaddisonData.

library(MaddisonData)

Leaders0 <- MaddisonData::MaddisonLeaders()
Leaders00 <- table(Leaders0$ISO)
MaddisonData::MaddisonCountries[names(Leaders00), 1:2]

##     ISO              country
## ARE ARE United Arab Emirates
## AUS AUS            Australia
## BEL BEL              Belgium
## CHE CHE          Switzerland
## CHN CHN                China
## ESP ESP                Spain
## FRA FRA               France
## GBR GBR       United Kingdom
## IRQ IRQ                 Iraq
## ITA ITA                Italy
## KWT KWT               Kuwait
## LUX LUX           Luxembourg
## NLD NLD          Netherlands
## NOR NOR               Norway
## NZL NZL          New Zealand
## QAT QAT                Qatar
## SWE SWE               Sweden
## USA USA        United States

Let’s redo this without countries like ARE, KWT, and QAT that seem NOT to have been technology leaders.

Leaders1 <- MaddisonData::MaddisonLeaders(c('ARE', 'KWT', 'QAT'))
Leaders10 <- table(Leaders1$ISO)
MaddisonData::MaddisonCountries[names(Leaders10), 1:2]

##     ISO        country
## AUS AUS      Australia
## BEL BEL        Belgium
## CHE CHE    Switzerland
## CHN CHN          China
## ESP ESP          Spain
## FRA FRA         France
## GBR GBR United Kingdom
## IRQ IRQ           Iraq
## ITA ITA          Italy
## LUX LUX     Luxembourg
## NLD NLD    Netherlands
## NOR NOR         Norway
## NZL NZL    New Zealand
## SWE SWE         Sweden
## USA USA  United States

Let’s plot.

Plot

#library(MaddisonData)

Leaders10d <- subset(MaddisonData, ISO %in% names(Leaders10))
plotLeaders1 <- MaddisonData::ggplotPath(y='gdppc', group='ISO', 
                        data=Leaders10d, scaley=1000)

plotLeaders1

plotLeaders1 + ggplot2::xlim(1200, 2022)

## Warning: Removed 13 rows containing missing values or values outside the scale range
## (`geom_path()`).

MaddisonSources for all 15 leaders?

MadSources15 <- MaddisonData::getMaddisonSources(names(Leaders10))
head(MadSources15)

## # A tibble: 6 × 3
##   ISO   years      source                                                       
##   <chr> <chr>      <chr>                                                        
## 1 ""    2008-      GDP pc:    Total Economy Database (TED) of the Conference Bo…
## 2 ""    1990-      population:Total Economy Database (TED) of the Conference Bo…
## 3 "BEL" 1          Scheidel, W. and Friesen, S. J., ‘The size of the economy an…
## 4 "BEL" 1500- 1846 Buyst, E. (2011), “Towards Estimates of Long Term Growth in …
## 5 "CHE" 1          Scheidel, W. and Friesen, S. J., ‘The size of the economy an…
## 6 "CHE" 1850-2011  Stohr, Christian (2016), Trading Gains: new estimates of Swi…

How long was each country the leader?

plot(yearEnd-yearBegin+1~yearBegin, Leaders1, log='y', las=1)

Leaders1$dYrs0 <- with(Leaders1, yearEnd-yearBegin+1)
Leaders1$dYrs1 <- c(tail(Leaders1$yearBegin, -1) - head(Leaders1$yearEnd, -1),
                    NA)
Leaders1

##    yearBegin yearEnd    gdppc0    gdppc1 ISO dy0 dy1 dYrs0 dYrs1
## 1          1       1  1407.000  1407.000 ITA   0 729     1   729
## 2        730    1000  1466.000  1307.000 IRQ 270  90   271    90
## 3       1090    1150  1221.711  1180.959 CHN  60 102    61   102
## 4       1252    1275  1320.000  1304.000 GBR  23   1    24     1
## 5       1276    1277  1366.393  1417.405 FRA   1   1     2     1
## 6       1278    1296  1346.637  1422.398 ESP  18   1    19     1
## 7       1297    1297  1375.486  1375.486 FRA   0   1     1     1
## 8       1298    1301  1368.422  1352.596 ESP   3   1     4     1
## 9       1302    1303  1608.395  1506.408 FRA   1   1     2     1
## 10      1304    1304  1463.000  1463.000 SWE   0   1     1     1
## 11      1305    1307  1475.734  1512.613 ESP   2   1     3     1
## 12      1308    1310  1580.197  1548.042 FRA   2   1     3     1
## 13      1311    1316  1446.525  1384.888 ESP   5   1     6     1
## 14      1317    1319  1478.000  1451.000 SWE   2   1     3     1
## 15      1320    1324  1394.176  1321.890 ESP   4   1     5     1
## 16      1325    1331  1433.000  1486.000 SWE   6   1     7     1
## 17      1332    1334  1536.290  1568.650 ESP   2   1     3     1
## 18      1335    1336  1611.267  1502.946 FRA   1   1     2     1
## 19      1337    1340  1479.107  1588.135 ESP   3   1     4     1
## 20      1341    1341  1749.107  1749.107 FRA   0   1     1     1
## 21      1342    1343  1690.944  1612.788 ESP   1   1     2     1
## 22      1344    1344  1566.623  1566.623 FRA   0   1     1     1
## 23      1345    1348  1625.028  1480.181 ESP   3   1     4     1
## 24      1349    1356  1459.893  1742.424 NLD   7   1     8     1
## 25      1357    1357  2087.454  2087.454 FRA   0   1     1     1
## 26      1358    1361  1744.207  1780.749 NLD   3   1     4     1
## 27      1362    1363  2006.937  1751.124 FRA   1   1     2     1
## 28      1364    1364  1726.381  1726.381 NLD   0   1     1     1
## 29      1365    1366  1946.410  1787.717 FRA   1   1     2     1
## 30      1367    1371  1901.961  1942.959 NLD   4   1     5     1
## 31      1372    1372  2092.925  2092.925 FRA   0   1     1     1
## 32      1373    1373  1926.916  1926.916 NLD   0   1     1     1
## 33      1374    1374  1797.091  1797.091 FRA   0   1     1     1
## 34      1375    1450  1903.743  2201.426 NLD  75   1    76     1
## 35      1451    1451  2529.992  2529.992 ITA   0   1     1     1
## 36      1452    1467  2276.292  2292.335 NLD  15   1    16     1
## 37      1468    1468  2263.000  2263.000 SWE   0   1     1     1
## 38      1469    1499  2278.075  2360.071 NLD  30   1    31     1
## 39      1500    1500  2338.000  2338.000 BEL   0   1     1     1
## 40      1501    1501  2549.070  2549.070 ITA   0   1     1     1
## 41      1502    1508  2329.768  2461.676 NLD   6   1     7     1
## 42      1509    1509  2570.000  2570.000 SWE   0   1     1     1
## 43      1510    1807  2439.394  3862.745 NLD 297   1   298     1
## 44      1808    1852  3250.000  4626.000 GBR  44   1    45     1
## 45      1853    1853  4798.000  4798.000 AUS   0   1     1     1
## 46      1854    1872  4909.000  5769.000 GBR  18   1    19     1
## 47      1873    1874  6107.000  6126.000 NZL   1   1     2     1
## 48      1875    1881  6596.000  7101.000 AUS   6   1     7     1
## 49      1882    1882  6557.846  6557.846 USA   0   1     1     1
## 50      1883    1891  7133.000  7438.000 AUS   8   1     9     1
## 51      1892    1893  7324.063  6834.250 USA   1   1     2     1
## 52      1894    1894  6851.000  6851.000 GBR   0   1     1     1
## 53      1895    1895  7159.506  7159.506 USA   0   1     1     1
## 54      1896    1896  7211.000  7211.000 GBR   0   1     1     1
## 55      1897    1897  7406.342  7406.342 USA   0   1     1     1
## 56      1898    1898  7500.000  7500.000 GBR   0   1     1     1
## 57      1899    1930  7959.150 10694.982 USA  31   1    32     1
## 58      1931    1934 10055.485  9997.376 CHE   3   1     4     1
## 59      1935    1970  9680.839 23958.000 USA  35   1    36     1
## 60      1971    1971 24486.978 24486.978 CHE   0   1     1     1
## 61      1972    1990 25414.000 36982.000 USA  18   1    19     1
## 62      1991    1995 39198.299 40838.565 LUX   4   1     5     1
## 63      1996    2022 43133.143 88366.219 NOR  26  NA    27    NA

tail(Leaders1)

##    yearBegin yearEnd    gdppc0    gdppc1 ISO dy0 dy1 dYrs0 dYrs1
## 58      1931    1934 10055.485  9997.376 CHE   3   1     4     1
## 59      1935    1970  9680.839 23958.000 USA  35   1    36     1
## 60      1971    1971 24486.978 24486.978 CHE   0   1     1     1
## 61      1972    1990 25414.000 36982.000 USA  18   1    19     1
## 62      1991    1995 39198.299 40838.565 LUX   4   1     5     1
## 63      1996    2022 43133.143 88366.219 NOR  26  NA    27    NA

MadDat1600 <- subset(MaddisonData::MaddisonData, year>1600)
Leaders1600 <- MaddisonData::MaddisonLeaders(c('ARE', 'KWT', 'QAT'), 
                               data=MadDat1600)

table(Leaders1600$ISO)

## 
## AUS CHE GBR LUX NLD NOR NZL USA 
##   3   2   5   1   1   1   1   7

Leaders1600d <- subset(MaddisonData, ISO %in% names(table(Leaders1600$ISO)))
plotLeaders1600 <- MaddisonData::ggplotPath(y='gdppc', group='ISO', 
                        data=Leaders1600d, scaley=1000)
  
plotLeaders1600 + ggplot2::xlim(1601, 2022)

## Warning: Removed 604 rows containing missing values or values outside the scale range
## (`geom_path()`).

Are the three lines before 1800 NLD, GBR, and USA?

NLD_GBR_USAd <- subset(MaddisonData, ISO %in% c("NLD", 'GBR', 'USA'))

NLD_GBR_USA <- ggplotPath(y='gdppc', group='ISO', 
                        data=NLD_GBR_USAd, scaley=1000)

NLD_GBR_USA + ggplot2::xlim(1301, 2022)

## Warning: Removed 50 rows containing missing values or values outside the scale range
## (`geom_path()`).

NLD_GBR_USA + ggplot2::xlim(1601, 2022)

## Warning: Removed 603 rows containing missing values or values outside the scale range
## (`geom_path()`).

The first two observations in these data are for 1000 and 1252. The two biggest events in that period are the Norman Conquest and the Magna Carta. Dates are conveniently given in the Wikipedia article on “Timeline of English history”.

UKevents1 <- matrix(c(
  "1066-10-14", "Norman Conquest", 
  '1215-06-16', 'Magna Carta' 
), ncol=2)

Let’s zoom in on 1250 to 1350.

GBRgdppc + ggplot2::coord_cartesian(xlim=c(1250, 1350), ylim=c(0.9, 2))

GDPpc declines from 1252 to around 1290 then rebounds until around 1300, when it mostly stops growing until around 1349, the year after the Black Death arrived in England.

UKevents2 <- rbind(UKevents1, 
  c("1348-06", "Black Death") )

GBR <- subset(MaddisonData, (ISO == 'GBR') & (1347<year) & (year<1451))
(GBRpop <- 
    
    
    plotMaddison('GBR', 'pop'))



head(GBRpop@data)

The first three years for which the Maddison project has data on population are 1, 1000, and 1500. The Wikipedia article on the Black Death quotes Geoffrey the Baker as having written in 1350, “The seventh year after it began, it came to England … . [It] so wasted the people that scarce the tenth person of any sort was left alive.” Clearly, no such population crash appears in these data.

GBRgdppc + ggplot2::coord_cartesian(xlim=c(1300, 1700), ylim=c(0.98, 2.7))

GDPpc grew until around 1390 and then was mostly flat until 1649.

GBRgdppc + ggplot2::coord_cartesian(xlim=c(1380, 1400), ylim=c(1.5, 2))

I don’t know what happened around 1390. Richard II ruled from 1377 to 1399. The British economy was stagnant until close to the time that King Charles I was beheaded 1649-01-30.

Let’s zoom on on various parts of this history.

GBRgdppc + ggplot2::coord_cartesian(xlim=c(1640, 1700), ylim=c(1.5, 3)) 
GBRgdppc + ggplot2::coord_cartesian(xlim=c(1640, 1730), ylim=c(1.5, 3)) 
GBRgdppc + ggplot2::coord_cartesian(xlim=c(1640, 1920), ylim=c(1.5, 9)) 
GBRgdppc + ggplot2::coord_cartesian(xlim=c(1900, 2022), ylim=c(6, 40)) 
GBRgdppc + ggplot2::coord_cartesian(xlim=c(2000, 2022), ylim=c(30, 40))

UKevents3 <- rbind(UKevents2, 
  c("1377-06-21", "King Richard II"), 
  c('1399-09-40', 'King Henry IV'), 
  c('1413-03-21', 'King Henry V'), 
  c('1422-09-01', 'King Henry VI'), 
  c('1461-03-04', 'King Edward IV'), 
  c('1483-04-09', 'King Edward V'), 
  c('1483-06-26', 'King Richard III'), 
  c('1485-08-22', 'House of Tudor'), 
  c('1603-03-24', 'King James I'), 
  c('1625-03-27', 'King Charles I'), 
  c('1649-02-14', 'Lord Protector Oliver Cromwell'), 
  c('1658-09-03', 'Lord Protector Richard Cromwell'), 
  c('1660-05-29', 'King Charles II'), 
  c('1685-02-06', 'King James II'), 
  c('1689-01-01', 'William and Mary'), 
  c('1702-03-01', 'Queene Ann'), 
  c('1714-08-01', 'King George I'), 
  c('1722-06-22', 'King George II'), 
  c('1760-10-25', 'King George III'), 
  c('1820-01-29', 'King George IV'), 
  c('1830-06-29', 'King William IV'), 
  c('1837-06-20', 'Queen Victoria'), 
  c('1901-01-22', 'King Edward VII'), 
  c('1910-05-06', 'King George V'), 
  c('1936-01-20', 'King Edward VIII'), 
  c('1936-12-11', 'King George VI'), 
  c('1952-02-06', 'Queen Elizabeth II'), 
  c('1997-05-02', 'PM Tony Blair'), 
  c('2007-06-27', 'PM Gordon Brown'), 
  c('2010-05-11', 'PM David Cameron'),
  c('2016-07-13', 'PM Theresa May'), 
  c('2019-07-22', 'PM Boris Johnson'), 
  c('2022-09-06', 'PM Liz Truss') 
  )

Maddison sources

Let’s get the sources that the Maddison Project says we should cite if we want to publish a plot like this:

(GBRsources <- MaddisonData::getMaddisonSources('GBR'))
# the print method for a tibble does not print all; 
# convert to a data.frame: 
as.data.frame(GBRsources)

Before we publish a plot like this we want to annotate it with major events, especially transitions in head of state …

Bibliography

Acemoglu and Robinson (2012) Why Nations Fail (Crown)

Broadberry, S.N., B. Campbell, A. Klein, M. Overton and B. van Leeuwen (2015), British Economic Growth 1270-1870 (Cambridge: Cambridge University Press) for England 1252-1700 and for Great Britain 1700-1870.

Conference Board: Total Economy Database (TED) for GDP pc since 2008 and population since 1990.

Scheidel, W. and Friesen, S. J., ‘The size of the economy and the distribution of income in the Roman Empire’, Journal of Roman Studies, 99 (2009, pp. 61–91) for the population at year 1.

Industrial Revolution began in 1689 or 1649?

Spencer Graves

2025-11-20

Abstract

Introduction

World leader in `GDPpc` by year

Plot

Maddison sources

Bibliography

Industrial Revolution began in 1689 or 1649?

Spencer Graves

2025-11-20

Abstract

Introduction

World leader in GDPpc by year

Plot

Maddison sources

Bibliography

World leader in `GDPpc` by year