The story of two transitions: Unified Growth Theory and the European growth
experience, 1300-1870
Alexandra M. de Pleijt and Jan Luiten van Zanden
Utrecht University
E-mail corresponding author: A.M.dePleijt@uu.nl
Abstract:
This paper sets out the firstly establish the ‘stylized facts’ about the transition from an economy
dominated by Malthusian forces to one characterized by ‘modern economic growth’, as it occurred in
Western Europe between 1300 and 1850. Thanks to the new research in the evolution of population,
GDP and its components, we can present a much clearer picture about patterns of long-term economic
growth in North-Western Europe, in particular England and Holland. This new research has not been
used in recent contributions to ‘unified growth theory’, which we consider a missed opportunity. We
will try to explain these ‘stylized facts’ testing various insights from ‘unified growth theory’, in
particular about the links between demographic change, human capital formation, and economic
growth.
1. Introduction
We aim at integrating new empirical results into debate on transition to modern growth
regime. To be written.
2. The stylized facts of European economic growth, 1300-1850
All ‘facts’ are interpretations, so if we want to establish the ‘stylized facts’ about European
economic growth in the centuries before the Industrial Revolution, we have to be careful
which period and territorial entity we focus on. Can we explain the Industrial Revolution by
looking at growth in the 18th century only, or is a much longer time-span required? What is
the relevant entity we should look at: is growth indeed a sub-national/regional phenomenon,
or is the ‘nation’ state the appropriate unit of analysis, or is growth not limited by ‘national’
borders? As we will demonstrate in this section, these are relevant issues for deciding what
the stylized facts are.
Let’s begin with the issue: where is economic growth located? The concept of the
‘Little Divergence’ is relevant here: a substantial body of evidence – starting with the real
wage estimates by Allen (2001), and including the new generation of GDP estimates already
introduced – points to the fact that there was a divergence in levels of economic performance
within Europe between 1500 and 1800. North-Western Europe – basically the Low Countries
and England – showed more or less stable real wages (after the increase in real wages in the
14th century following the Black Death), whereas real wages in Eastern and Southern Europe
declined sharply in the long run. In terms of GDP per capita there is a similar divergence
between the North-Sea area and the rest of the continent: in the latter real incomes stagnate or
even decline somewhat, whereas Holland and England show a lot of progress: they are
substantially richer in 1750 than in 1500 (Broadberry et.al.; Prados de la Escosura; Bolt and
van Zanden 2013). This is mirrored in patterns of urbanization (rising in the North Sea area,
stabilizing in the rest of Europe), in the development of political institutions (parliaments
decline almost everywhere, except for England and the Netherlands) (Van Zanden, Buringh
and Bosker 2012), and in indices linked to human capital formation (such as book production
and consumption) (Baten and Van Zanden 2008). So growth seems to be an international
1990 GK dollars
phenomenon, originating in the region bordering the North Sea: the Low Countries and
England formed the core of this wider region, but parts of Belgium, Northern France, NorthWest Germany, and Scotland, were probably also participating in it (but we do not have
detailed statistics and estimates to test this, and it may be that the region experienced long
term growth was also changing over time – for example, Scotland maybe only joined in the
17th or even 18th century). This was a strongly integrated region, in which, for example, in the
late Middle Ages, England supplied the wool for the textile industries of the Low Countries,
the main source of employment of the large Flemish cities. In the 14th-15th centuries Flanders
formed the urban core of this economic system – and England its ‘periphery’. In the 16th
century Brabant (and in particular Antwerp) took over the role of being the core. After 1585
the urban center moved to Holland, a switch that resulted in the Dutch ‘Golden Age’ of the
17th century. After about 1650 London gradually replaced Amsterdam as the central hub in
the commercial network of North-Western Europe, and he urban core switched to England, as
a result of which the Netherlands in the 18th century started to specialize on livestock products
for the British market – confirming its role as ‘new’ periphery. Our working hypothesis (to be
further tested below) is therefore that growth was a regional phenomenon, not (really) limited
by international boundaries, and concentrated in the North western part of Europe, or more
specifically, in the North Sea region.
The next question concerns the beginning and the periodization of the process of
economic growth in this region. Here we suggest a division into three periods: before the
Black Death (‘classic Malthusian economy’), between 1347 and 1820 (slow but consistent
growth), and after about 1820 (rapid, post-Industrial Revolution growth). This is based on the
recent work on estimating GDP in the long run mentioned in the introduction. Figure 1
presents the big picture: estimates of GDP per capita of England (annual estimates, 12701700), Great Britain (annual, 1700-1870), Holland (annual, 1347-1807), the Netherlands
(annual, 1807-1870) and Belgium (point estimates, 1500-1850).
GB
England
NL
Holland
Belgium
Figure 1. Per capita GDP growth in England, Holland and Belgium, 1270-1870
Sources: Broadberry et.al.2012; Van Zanden and Van Leeuwen 2012; Buyst 2011.
2
For the period before 1347 we only have detailed estimates for England, starting in
1252 (Figure 2). This series shows no growth before 1348; the trend is indeed slightly
negative, mainly due to serious crises in the 1280s and the 1310s. Population growth seems to
matter a lot: the population grows from 4.2 million in 1250 to 4.8 million in 1290, when GDP
per capita registers a declining trend; after the crisis of the 1280s, the population starts to fall
(to about 4.6 million in 1340), which results in a stabilization of real income (albeit with huge
fluctuations, such as the ‘Great Famine’ of the 1320s. In short, this economy shows distinct
Malthusian features, with a decline of real GDP during the (last stage of the) great Medieval
boom (1080-1280) during which the population increased a lot, and stability after the 1280s
because also population growth came to a halt. The level of GDP per capita is, however,
much above subsistence levels, especially at the start of this century; during the 1250s the
English GDP per head of 800-850 dollars is between at least twice and almost thrice the
subsistence level (of 300-350 dollars), and quite high by international standards – only the
more wealthy ancient economies reached similar levels, if we are to believe recent estimates
of pre-1000 GDP. The earliest estimates for Holland (in 1347) also point to similar high GDP
(almost 900 dollar).
950
5.000
900
4.800
850
4.600
800
4.400
750
700
4.200
650
4.000
600
3.800
550
500
1252
3.600
1262
1272
1282
1292
1302
GDP per capita (left-hand)
1312
1322
1332
1342
Population (right-hand)
Figure 2. English per capita GDP and population growth, 1252-1347
Sources: Broadberry et.al. 2012
The starting point is therefore an already relatively prosperous pre-industrial economy,
which however showed certain Malthusian traits. The flat trend between 1250 and 1347 is
broken by a large decline of the population after 1347, resulting in a sudden increase in real
per capita GDP – both in England and in Holland. From the Malthusian perspective this is
what is to be expected, so it seems to confirm the Malthusian character of the Late Medieval
Economy. In other parts of the world (Spain, Egypt), the collapse of population did not have
similar positive effect on real incomes – so it is not inevitable that the Black Death has such a
result and it probably tells us something about the quality of institutions in the North Sea area:
a large exogenous shock such as the Black Death did not result in collapse of the economy (as
appears to have happened in Egypt), but in a sudden increase in real incomes and real wages.
One could argue that this is a typical ‘Malthusian’ response, but it is also exactly what one
3
would expect to happen in a market economy: one factor of production – human labour –
suddenly because much more scarce, as a result of which its remuneration increases. What is
even more important, is that after this exogenous shock real incomes did not return anymore
to the pre-shock level, but remained much (20-40%) higher than before, and, especially in the
case of Holland, began to show a consistent rate of growth (of about 0.19% per year), which
resulted in a doubling of GDP per capita in the next 250 years (not taking into account the
effect of the 1347/48 shock). The English growth experience was somewhat different:
between 1400 and 1600 real incomes fluctuated around a plateau of about 1000 dollars
(against 700-800 dollars before 1347), and only in the second half of the 17th century growth
really took off. We know less about growth in Belgium, but the few point estimates that have
been made (by Erik Buyst) suggest that it followed a third pattern: its level was quite high at
the start of the 16th century, there was some per capita growth until the 1560s or 1570s, but
the late 16th and 17th centuries saw a decline of GDP per capita, due to the loss of industrial
and tertiary activities to the Northern Netherlands (Figure 1). The decline of Belgium and the
rise of the Netherlands were part of the same process, in which the urban center of the North
Sea area moved from Antwerp to Amsterdam. The next change in the urban system, from
Amsterdam to London, began in earnest after about 1670, and had similar consequences
(England again began to grow, Holland stagnated at a high level).
The main point about growth in this second phase – beginning in 1347 and ending in
the early 19th century – is related to this. Superficially, each country knew its separate growth
cycles, characterized by period of rapid growth followed by (and/or preceded by) long periods
of stagnation. Flanders boomed in the late Middle Ages, but declined after about 1560;
Holland had its most spectacular growth spurt during its Golden Age (1585-1670), but
stagnated in the 18th century; conversely, English real incomes did not increase between 1400
and 1600, but rose rapidly after 1650. Scholars have concluded from this that growth was
sporadic, intermittent, non-consistent – that growth spurts were always followed by stagnation
and/or decline. Perhaps Jack Goldstone’s concept of periodic ‘efflorescences’ best captures
this idea. But what seems a reasonable picture of growth before 1800 if one looks at
individual regions within the wider North Sea region, is perhaps plain wrong when looked at
the region as a whole. Figure 3 attempts to do this by merging the two (England and Holland)
or three (also including Flanders – but only after 1500) into one index of real GDP per capita
of the North Sea region as a whole. What then appears is a remarkable stable path of
economic growth, in which stagnation in one part of the region (in England between 1400 and
1600, or Holland after 1670) is compensated for by growth in the rest of the region (in
Flanders and Holland when England stagnates, and in England when Holland’s growth
decelerates). But the region as a whole grows at a stable rate of 0.18 percent per year, almost
without real interruption, between 1347 and 1820 (after which growth accelerates). The
phases of growth and stagnation within certain sub-regions are linked to changes in the
international division of labour: when a certain sub-region (Flanders first, followed by
Holland, and finally England) manages to attract the high-value added activities in industry
and services, and develops into the urban core of the North Sea, its growth accelerates.
Similarly, when regions lose their edge in manufacturing or international trade and shipping,
they stagnate – or even see their GDP per capita decline (as happened in Flanders after 1560).
But these shifts within the larger regional unit of the North Sea region can to some extent be
separated from the process of economic transformation that is happening in the region as a
whole, which lead to a consistent growth of GDP per capita from the 1350s to the 1820s (as
Figure 3 shows).
4
10.000
y = 921,03e0,0017x
R² = 0,8737
1.000
100
England and Holland
Three countries
Exponentieel (England and Holland)
Figure 3. Economic growth in the North Sea area, 1348-1820
Sources: see Figure 1.
What is more, as indicated already, the relation between per capita GDP and
population levels is also changing in time. This link is given in Figures 4 (England 12521870), 5 (Holland: 1348-1870) and 6 (the North Sea region as a whole: 1348-1870), which
present, on the vertical axis, the log of GDP per capita, and on the horizontal axis, the
population. In a Malthusian regime one expects a negative link between the two, which is
evident in Figure 5 between 1252 and 1400. The escape from the Malthusian regime is in both
cases very clear: there is a negative relation between levels of per capita GDP and population
growth prior to 1400, whereas this disappears in England and the North Sea region, and
becomes positive in the case of Holland. In England the shift towards a positive relation
becomes visible after the 1650s – exactly when the centre of economic activity shifted from
Holland to England. Our findings contradict research that used real wages as an indicator of
income levels (e.g. Clark and Mills 2010, Nicolini 2007). Clark and Mills do, however, date
the escape from the Malthusian confines at about 1650, but they found a negative relation
before 1650. We conclude that the Malthusian link disappears in the 14th century, and that in
particular when the North Sea region is seen as a whole, consistent growth began in the same
period.
5
Figure 4. Per capita GDP and population: England, 1252 – 1870.
Sources: Broadberry et al 2012.
Figure 5. Per capita GDP and population: Holland, 1348 – 1870.
6
Sources: van Zanden and van Leeuwen 2012.
Figure 6. Per capita GDP and population: North Sea region, 1348 – 1870
Sources: see figure 4 and 5 above.
3. Human capital formation North Sea region, 1300-1807/1900
In other papers we have explained how it was possible to estimate the long-term evolution of
educational attainment in Holland (Van Zanden and Van Leeuwen 2012), and England (De
Pleijt 2013). To summarize the latter paper: thanks to research carried out by Stone (1964,
1969), Cressy (1980), Stephens (1987), Moran (1985), and others that considered the
development of English schooling and literacy, it is possible to quantify human capital
formation: primary education (based on literacy rates) and secondary schooling (grammar and
university enrolment) are combined and adjusted to population levels and rates of life
expectancy to estimate annual education levels of men, women and the total population
between 1300 and 1900.
Combining the evidence offers a bridge between the different views with some
interesting findings as shown in figure 7 and 8. Increases in average years of education were
gradual: the basis of elementary schooling was led in the late 14th century, which paved the
way for an ‘educational revolution’ in higher education after the 1530s (Stone 1964). Average
English men spend about 2 years in education at the end of the 17th century. The ‘revolution’
was followed by a severe ‘depression’ that started in the 18th century. Many secondary
schools disappeared and strong population growth reduced average years of higher education
(it fell from 1 year in 1700 to 0.2 years by the 1870s). Women were not admitted to formal
secondary schooling, but their basic skills increased remarkable after 1700, such that it
alleviated for an overall decline in education levels during the Industrial Revolution.
7
Figure 7. Growth in human capital formation, England: 1307-1900.
Source: De Pleijt 2013.
Figure 8. Growth in primary and secondary schooling, England: 1307-1850.
Notes and Source: De Pleijt 2013. Women were not admitted to formal secondary schooling. Series capturing the
average years of education of women is therefore solely based on the development of literacy.
The English economy displayed substantial dynamism and growth before the
Industrial Revolution, which makes it appealing to examine the relationship between human
8
capital formation and economic growth more in-depth. To test this relationship, it was first of
all necessary to run the Quandt-Andrews unknown breakpoint test (Quandt 1960, Andrews
1993), since the relation may change over time. The obtained regression results for per capita
GDP show a break around 1808 (QLR statistic of 5.46), whereas the results for average years
of education report on two breaks at about 1563/64 and 1806-1811 (QLR statistic of
respectively 3.91 and 3.93).1 We thus identified two breakpoints, such that the regressions
should be performed for each sub-period: i.e. 1307-1563, 1565-1806 and 1811-1900. Both
breakpoints can be explained as growth starts to accelerate around 1810 and average years of
education starts to grow exponentially due to increases in the attendance of elementary
schooling (see figure 8). The break of the 1560s might be attributed to the growth of
secondary schooling that occurs between 1530 and 1600, which causes a sharp increase in the
average years of schooling of men as is shown in figure 8. Secondly, as depicted in figure 7
and 1, human capital formation and real per capita GDP exhibit an upward trend. This
evolution of time-series is in line with the possibility that our variables are non-stationary and
co-integrated, an observation that is confirmed by several tests (the appendix to this paper
reports on the results of the augmented Dickey-Fuller tests and Johansen tests for cointegration).
We estimated single equation Error Correction Models (ECMs) as proposed by
Bardsen (1989) to explore the relationship between per capita income (lnYt) and human
capital formation (lnEt):
∆lnYt =  + 0∆lnEt - 1(lnYt-1 - 2 lnEt-1),
where  is the intercept, 0 captures the short run effect of human capital formation on
economic growth, 2 estimates the long term effect that is dispersed across future time periods
at a rate equal to 1.
Regression
Dep. Var.
Sub-period
1
∆lnYt
1307-1563
2
∆lnYt
1565-1806
3
∆lnYt
1811-1900
∆lnEt
0.0928
(0.4247)
-0.1783***
(0.0437)
0.1189***
(0.0052)
1.2697***
(0.3129)
0.1216
(0.2550)
-0.2988***
(0.0478)
0.9537***
(0.0165)
2.1165***
(0.3376)
-0.0379
(0.4107)
-0.3707***
(0.0951)
0.6906***
(0.0072)
2.6514***
(0.6823)
255
0.0920
241
0.1578
89
0.2164
lnYt-1
lnEt-1

N
R2
Table 1. Per capita GDP growth England, 1307-1900
Notes: Robust standard error in parentheses. *** Coefficient is significant at the 0.01 level, ** at the 0.05 level,
* at the 0.10 level. Standard error of the long run multiplier is calculated according to the transformation
proposed by Bewley (1979).
The short run effects are insignificant in all sub-periods, indicating that there is no
direct effect of human capital formation on per capita GDP growth. There are, however, long
1
The critical level used in the Quandt-Andrews unknown breakpoint tests is 3.66.
9
run effects (estimated by lnEt-1) of which the magnitude increases between 1307-1563 and
1565-1806, whilst the rate at which it is dispersed over future time periods increases (given by
lnYt-1).2 Our results also indicate that the long effect becomes somewhat weaker when growth
starts to accelerate after 1811. We applied Granger causality tests, since interest lies in the
direction of causality as well. Table 2 reports on the results. Our findings confirm that human
capital contributed to early modern growth in the period 1307-1806, whereas an endogenous
system is found in the last sub-period (1811-1900).
P-value
1307-1563
- Education causes growth
- Growth causes education
Yes
No
0.000
0.594
1565-1806
- Education causes growth
- Growth causes education
Yes
No
0.000
0.980
1811-1900
- Education causes growth
- Growth causes education
Yes
Yes
0.000
0.000
Table 2. Granger causality test England, 1307-1900
Notes: Lag-order determined with the Schwarz’s Bayesian information criterion (SBIC) and the Hannan and
Quinn information criterion (HQIC).
As clear from figures 7 and 8, it is possible to differentiate between levels of education
as we have series covering average years of primary schooling (EducPrim) and average years
of secondary and tertiary schooling (EducHigh). A further distinction can be made according
to gender (women and men), although it should be stressed that the series of women is solely
based on the development of literacy (women were not admitted to formal secondary
schooling before the late 19th century) such that it only measures reading and writing abilities.
Several Quandt-Andrews unknown breakpoint tests have been conducted that indicate a
structural break in the dataset of women around 1418 (QLR statistic of 5.168) and 1810
(4.561), whereas the breakpoints in the series capturing primary skills of men are similar to
those reported above – i.e. 1563/64 (QLR statistic of 3.704) and 1810 (QLR statistic of
5.234). With respect to average years of higher education, we find two different breakpoints:
1562/73 (probably caused by the sharp increases in grammar schooling) and 1700 (decay of
higher education) (QLR statistics of respectively 4.721 and 17.01). The variables are again
non-stationary and co-integrated (results reported in the appendix), which makes it necessary
to estimate our regressions with single equation ECMs of which the results are given in tables
3 (women) and 4 (men).
Regression
Dep. Var.
Sub-period
Proxy
4
∆lnYt
1418-1806
Women
5
∆lnYt
1811-1900
Women
∆lnYt
1565-1806
Women
∆lnEt
0.1044
(0.1721)
-0.0926***
(0.0226)
0.1012
(0.2109)
-0.2262**
(0.0810)
-0.0129
(0.1628)
-0.2091***
(0.0406)
lnYt-1
2
6
Our results remain equal when we standardize the coefficients.
10
lnEt-1

N
R2
0.1862***
(0.0030)
0.6888***
(0.1691)
0.5805***
(0.0065)
1.6688***
(0.5973)
0.4021***
(0.0073)
1.5845***
(0.3069)
387
0.0476
89
0.1498
241
0.1108
Table 3. Per capita GDP growth England, 1307-1900
Notes: Robust standard error in parentheses. *** Coefficient is significant at the 0.01 level, ** at the 0.05 level,
* at the 0.10 level. Standard error of the long run multiplier is calculated according to the transformation
proposed by Bewley (1979).
Regression
Dep. Var.
Sub-period
Proxy
7
∆lnYt
1307-1563
MenPrim
8
∆lnYt
1565-1806
MenPrim
9
∆lnYt
1811-1900
MenPrim
10
∆lnYt
1307-1562
MenHigh
11
∆lnYt
1564-1699
MenHigh
∆lnEt
-0.1245
(0.3084)
-0.1621**
(0.0413)
0.1157***
(0.0053)
1.1554***
(0.2975)
0.0876
(0.1816)
-0.2596***
(0.0444)
0.6889***
(0.0123)
1.8761***
(0.3201)
-0.1152
(0.4350)
-0.3623***
(0.0803)
0.7569***
(0.0079)
2.5543***
(0.5681)
-0.0153
(0.2843)
-0.2030***
(0.0470)
0.1247***
(0.0048)
1.4498***
(0.3381)
0.9416
(0.6488)
-0.4476***
(0.0707)
1.7179***
(0.0962)
3.2617***
(0.5138)
255
0.0827
241
0.1324
89
0.2174
254
0.1021
134
0.2430
lnYt-1
lnEt-1

N
R2
Table 4. Per capita GDP growth England, 1307-1900
Notes: Robust standard error in parentheses. *** Coefficient is significant at the 0.01 level, ** at the 0.05 level,
* at the 0.10 level. Standard error of the long run multiplier is calculated according to the transformation
proposed by Bewley (1979).
Equation 6 is added to table 3 to capture the sub-period 1565-1806. There is no
breakpoint in the series of women around 1564, but this makes it possible to compare the
regression results with that of men (equations 7 – 9). For all measures of human capital and
sub-periods, there are no short run effects. Long run effects are significant and increase in
magnitude over time, whilst the effect of human capital formation of women is slightly below
that of men as shown in equations 5 and 6 of table 3 and equations 7-9 of Table 4. The
obtained results indicate a stronger long-term effect of advanced skills on per capita GDP than
do basic skills when differentiation between average years of primary education (MenPrim)
and higher education (MenHigh) (equation 11). Interestingly, the long-run impact of higher
education disappears after 1700 due to the movement away from secondary schooling, which
points to a process of deskilling during the first phase of the industrial revolution that is
mentioned in the literature (Mitch 1992 and Mokyr 2001).
Granger causality tests for the sub-periods and different indicators of human capital
formation are given in Table 5. The results are equivalent to those reported above: education
granger causes per capita income – it does not work in the opposite direction before 1811; the
process becomes endogenous after 1811, confirming established views.
P-value
Women
1418-1806
11
- Education causes growth
- Growth causes education
1811-1900
- Education causes growth
- Growth causes education
MenPrim 1307-1563
- Education causes growth
- Growth causes education
1565-1806
- Education causes growth
- Growth causes education
1811-1900
- Education causes growth
- Growth causes education
MenHigh 1307-1562
- Education causes growth
- Growth causes education
1354-1699
- Education causes growth
- Growth causes education
Yes
No
0.000
0.581
Yes
Yes
0.000
0.002
Yes
No
0.001
0.251
Yes
No
0.000
0.379
Yes
Yes
0.000
0.011
Yes
No
0.000
0.327
Yes
No
0.000
0.572
Table 5. Granger causality test England, 1307-1900
Notes: Lag-order determined with the Schwarz’s Bayesian information criterion (SBIC) and the Hannan and
Quinn information criterion (HQIC).
Figure 9 depicts the growth in human capital for Holland and the North Sea region.
The human capital series of Holland only goes back to the 1560s (and we are working on
further refining the results and projecting the series back into the Middle Ages). For Holland
and the North Sea region it is therefore only possible to perform regressions for the subperiod 1564-1807). No structural breaks were found in this GDP series (see also Van Zanden
and Van Leeuwen 2012), although our test results show that our variables are non-stationary
and co-integrated (results reported in the appendix). We therefore estimated ECMs of which
the results are shown in table 3.
12
Figure 9. Growth in human capital formation, Holland and North Sea region: 1565-1806.
Notes and Source: De Pleijt 2013. Women were not admitted to formal secondary schooling. Average years of
education of women are therefore solely based on the development of literacy.
Regression
Dep. Var.
Sub-period
Region
12
∆lnYt
1565-1806
Holland
13
∆lnYt
1565-1806
North Sea
∆lnEt
-2.5083*
(1.2941)
-0.3778***
(0.0582)
0.1931***
(0.0212)
2.1923***
(0.4495)
0.1555
(0.2249)
-0.3990***
(0.0594)
0.7131***
(0.0121)
2.8835***
(0.4284)
243
0.1923
243
0.2104
lnYt-1
lnEt-1

N
R2
Table 6. Error Correction Models for per capita GDP growth Holland and the North Sea
area, 1565-1806
Notes: Robust standard error in parentheses. *** Coefficient is significant at the 0.01 level, ** at the 0.05 level,
* at the 0.10 level. Standard error of the long run multiplier is calculated according to the transformation
proposed by Bewley (1979).
Our regression results report again on a long run effect of human capital formation on
growth, but the coefficient is much smaller than in the English case (Table 3). Finally we
tested for Granger causality for Holland and the North Sea region. In Holland we find that
education causes growth and growth causes education; this pattern of endogenous growth may
be linked to Holland as being ‘the first modern economy’ (Vries and van der Woude 1997).
13
The North Sea region as a whole only shows education causing growth (as in the English
case) (Table 4).
P-value
Holland:
- Education causes growth
- Growth causes education
Yes
Yes
0.000
0.000
North Sea:
- Education causes growth
- Growth causes education
Yes
No
0.000
0.296
Table 7. Granger causality test Holland and North Sea region, 1564-1807
Notes: Lag-order determined with the Schwarz’s Bayesian information criterion (SBIC) and the Hannan and
Quinn information criterion (HQIC).
Our regression results on long-term per capita income growth and human capital
formation contradict the earlier conclusion of Mitch (1993), Allen (2003) and Mokyr (2001)
that points towards an insignificant relationship between education and early modern growth.
These studies focus on literacy rates as a proxy of human capital formation that suffers from
the disadvantage of measuring only very basic skills (reading and writing abilities), where
these analyses overlooked the growth in (higher) education before 1750. The regression
results reported in this section are similar to recent studies that use estimates for more
advanced skills, as these find a positive relation between development and human capital
formation (book production and consumption: Baten and van Zanden 2008; secondary
schooling: Boucekkine et al 2007). We furthermore find that basic skills affected preindustrial growth, which opposes the study of Goldin and Katz (1998) as they find that basic
skills such as reading and writing abilities were irrelevant before the 20th century. A second
finding is that progressive skills, as measured by average years of higher education,
contributed even more to economic growth than basic skills, although there is a clear
movement away from higher education on the eve of the Industrial Revolution (setting in after
1700): literacy rates of men stagnated and there was a remarkable decline in average years of
higher education. It was not until the late 19th century that English education levels started to
rise again, which, against the view of Unified Growth Theory, was mainly the result of
government polices implemented in the mid-19th century. A third finding, aligned with
Modern Growth Theory (e.g. Lucas 1989, Romer 1990, Galor and Moav 2002), is that growth
becomes endogenous during the second Industrial Revolution since our Granger causality
tests suggests that education contributed to technological progress, whereas per capita GDP
growth fostered further growth in human capital formation. In contradiction to these theories,
however, and as stressed above, our results show that human capital formation already
contributed to the process of development long before the second Industrial Revolution.
4. Conclusion
This paper considered the ‘stylized facts’ about patterns of long-term economic growth in the
North Sea region between 1300 and 1900, thereby focussing on demographic change, human
capital and economic growth. The evidence presented in this paper suggests that Holland and
England managed to escape the Malthusian confines long before the epoch of Modern
Growth. The negative relationship between population levels and per capita GDP disappears
after the Black Death, and is transformed in a positive link, in particular in Holland and the
North Sea area as a whole. In explaining the transition from a Malthusian economy to modern
growth we therefore have to focus on two transformations: the late Middle Ages, and the early
14
19th century. The first break saw the emergence of sustained by slow growth in a small part of
Western Europe (England, Holland and Flanders), the second break – the ‘traditional’
Industrial Revolution – saw the transition towards rapid growth in a much larger (and rapidly
expanding) part of the Continent.
We have studied the links between these various regimes of growth and human capital
formation. Several regression analyses have been performed that measure the magnitude of
human capital formation (as measured by average years of education) on economic growth in
the North Sea region. With respect to England, it was required to divide our analysis in three
sub-periods (i.e. 1307-1563, 1565-1806 and 1811-1900) since the relation between human
capital formation and growth changes over time. The obtained regression results show that
there was a long run effect of human capital formation on growth that increases in magnitude
between 1307 and 1811. This is an important result: education did already matter for growth
before the Industrial Revolution (contra: Mokyr and Allen), and we cannot explain the
continuous growth that occurred in this region since the 14th century without taking this effect
into account. In Holland we already see the emergence of endogenous growth (which is a
feature of the post 1810 period). For England and the North Sea region as a whole it was only
possible to estimate the relationship for the sub-period 1565-1806, of which our regression
analysis indicate a long run effect of human capital formation on economic growth. Our
evidence suggests that growth was endogenous in Holland between 1565 and 1806 but not in
the region as a whole.
APPENDIX
In order to examine the time-series properties of the data, we performed several augmented
Dickey-Fuller and Johansen tests for co-integration. The results of these tests are reported in
this section.
lnYt
lnEt
∆lnYt
∆lnEt
1307-1563
-2.254
(-3.430)
0.338
(-3.430)
-10.074
(-3.430)
-6.886
(-3.430)
1565-1806
-0.667
(-3.431)
-3.035
(-3.431)
-11.711
(-3.431)
-10.091
(-3.431)
1811-1900
1.024
(-3.461)
-0.887
(-3.461)
-8.417
(-3.461)
-4.925
(-3.461)
Table 8. Dickey-Fuller test results equations 1-3 (England)
Notes: Critical values (at 5% level) between parentheses. Lag-order determined with the Schwarz’s Bayesian
information criterion (SBIC) and the Hannan and Quinn information criterion (HQIC).
Trace statistic
1307-1563
15.66
1565-1806
41.68
1811-1900
33.55
Table 9. Johansen tests for co-integration, equations 1-3 (England)
Notes: Critical value is 15.41. Lag-order determined with the Schwarz’s Bayesian information criterion (SBIC)
and the Hannan and Quinn information criterion (HQIC).
lnYt
lnEt
∆lnYt
∆lnEt
15
Women:
1418-1806
1564-1806
-2.593
(-3.425)
-
1811-1900
-
MenPrim:
1307-1563
-
1564-1806
-
1811-1900
-
MenHigh:
1307-1562
1564-1699
-2.214
(-3.430)
-3.377
(-3.445)
-2.018
(-3.425)
-3.179
(-3.431)
0.194
(-3.461)
-15.847
(-3.425)
0.317
(-3.430)
-2.333
(-3.431)
-0.262
(-3.461)
-
-1.093
(-3.430)
-0.942
(-3.445)
-9.890
(-3.430)
-15.255
(-3.445)
-
-
-11.447
(-3.425)
-10.701
(-3.431)
-7.562
(-3.461)
-4.668
(-3.430)
-8.920
(-3.431)
-9.241
(-3.461)
-5.957
(-3.430)
-12.268
(-3.445)
Table 10. Dickey-Fuller test results equations 4-11 (England)
Notes: Critical values (at 5% level) between parentheses. Lag-order determined with the Schwarz’s Bayesian
information criterion (SBIC) and the Hannan and Quinn information criterion (HQIC). Test results of per capita
income only reported when sub-period under consideration deviates from those given in table 8.
Trace statistic
Women
1418-1806
1564-1806
1811-1900
19.07
28.95
23.56
MenPrim
1307-1563
1565-1806
1811-1900
21.33
35.88
28.33
MenHigh
1307-1562
1564-1699
29.24
35.38
Table 11. Johansen tests for co-integration, equations 4-11 (England)
Notes: Critical value is 15.41. Lag-order determined with the Schwarz’s Bayesian information criterion (SBIC)
and the Hannan and Quinn information criterion (HQIC).
lnYt
lnEt
∆lnYt
∆lnEt
Holland
-3.368
(-3.431)
-1.252
(-3.431)
-9.503
(-3.431)
-5.809
(-3.431)
North Sea
-2.449
(-3.431)
-2.001
(-3.431)
-10.413
(-3.431)
-9.614
(-3.431)
Table 12. Dickey-Fuller test results equations 12 and 13 (Holland and North Sea region)
16
Notes: Critical values (at 5% level) between parentheses. Lag-order determined with the Schwarz’s Bayesian
information criterion (SBIC) and the Hannan and Quinn information criterion (HQIC).
Trace statistic
Holland
37.08
North Sea
57.51
Table 13. Johansen tests for co-integration, equations 12 and 13 (Holland and North Sea
region)
Notes: Critical value is 15.41. Lag-order determined with the Schwarz’s Bayesian information criterion (SBIC)
and the Hannan and Quinn information criterion (HQIC).
17