Early Starts, Reversals and Catch-up in The Process of Economic Development Areendam Chanda...

Early Starts, Reversals and Catch-up in The Process of

Economic Development

Areendam ChandaLouisiana State University

Louis PuttermanBrown University

We begin with two possibly conflicting observations.

Observation 1

• Levels of income and recent rates of growth are positively correlated with “early development” (Diamond, 1998; Hibbs and Olsson, 2004a,b; Burkett,Humblet and Putterman, 1998; Bockstette, Chanda and Putterman, 2001)

Observation 2

• Rates of growth between 1500 and recent times are negatively correlated with early development (level of urbanization in 1500) – Acemoglu, Johnson and Robinson 2002 “Reversal of Fortune”

The two observations appear to be conflicting because urbanization goes hand-in-hand with other indicators of early development (population density, early agricultural transition, long-term presence of states).

What we do in the paper

• We provide the following simple reconciliation of the two observations:

1. Level of development in 1500 was positively predicted by early development.

2. Rate of growth from 1500 to 1960 was negatively predicted by early development.

3. Rate of growth from 1960 to 1998 is positively predicted by early development.

in other words

• The AJR “reversal” in colonized countries is real, but

• It applies to the era of European expansion and not to the post-World War II era (except as a remnant)

• The Diamond/Hibbs-Olsson/et al. observation holds for most of the time since the agricultural revolution.

implication

• The AJR arguments about institutions introduced in the colonial era do not seem to hold for explaining differences in growth rates from 1960 to present, the main period studied by modern growth and development economists. (This is not to take a position about institutions versus geography in general.)

Early development:concept and measurement

• Early development or early starts are indicated by

1. early transition from hunting and gathering to agriculture

2. early appearance of villages, dense populations, and eventually states

3. increases in specialization, development of technology, organizational complexity etc.

measures we use

• Agyears = years since transition to agriculture, based on Hibbs-Olsson estimates (and Diamond)

• Statehist = proportion of years since 1 CE that country had a super-tribal polity (i.e., a state), downweighted if colonial, geographically restricted, or if multiple competing states (Bockstette, Chanda, Putterman)

• We mainly use statehist1500, which covers only the years 1 to 1500 CE.

• We check some correlations for other measures, for example statehist50 (statehist 1000) covers only state status during 1 to 50 CE (1 to 1000 CE)

agyears – statehist correlation AGYEARS S50 S500 S1000 S1500 Sample: All Countries (n=90) AGYEARS 1.00 STATEHIST50 0.49 1.00

STATEHIST500 0.57 0.94 1.00

STATEHIST1000 0.68 0.83 0.93 1.00 STATEHIST1500 0.73 0.72 0.82 0.94 1.00 Sample: Colonized Countries (n=64) AGYEARS 1.00 STATEHIST50 0.48 1.00 STATEHIST500 0.53 0.98 1.00 STATEHIST1000 0.62 0.90 0.94 1.00 STATEHIST1500 0.66 0.76 0.82 0.93 1.00

Does early developmentraise income?

• Possibly early development does not raise ordinary people’s incomes - - “Malthusian growth”

• Available estimates nonetheless suggest that areas further ahead in population density, urbanization, and state presence as of 1500 had somewhat higher incomes.

Overview of Analysis

• First, demonstrate that incomes in 1500 are positively predicted by early starts.

• Second, demonstrate that growth from 1500 to 1960 in non-European countries is negatively predicted by early starts.

• Third, demonstrate that growth from 1960 to 1998 in non-European countries is positively predicted by early starts.

Estimating income in 1500

We use urbanization 1500 from Bairoch (1988) and AJR (2002). The data for population densities are calculated by using population numbers from Maddison (2001) and land area numbers from FAO Statistics. Regressions 1 and 2 are alternately used to estimate income of 1500. ***- denotes significance at 1%, **- at 5% and *- at 10%.

1 2 Constant 6.133***

(0.062) 6.132***

(0.05) Urbanization in 1500

0.024*** (0.006)

0.016*** (0.005)

Log Population Density in 1500

0.058*** (0.015)

R-Square 0.38 0.55 Observations 32 32

Income 1500 predicted by early start

Explaining (predicted) GDP per capita in 1500 1 2 3 4 5 6 Dependent Variable Predicted Log GDP pc 1500

(urbanization only) Predicted Log GDP pc 1500

(urbn + popden) Constant 6.227***

(0.018) 6.059*** (0.08)

6.18*** (0.08)

6.146*** (0.028)

5.798*** (0.099)

5.96*** (0.096)

STATEHIST 1500

0.243*** (0.045)

0.206*** (0.05)

0.392*** (0.058)

0.265*** (0.075)

AGYEARS 0.034*** (0.01)

0.007 (0.011)

0.064*** (0.012)

0.03** (0.013)

Observations 61 55 53 61 55 52 R- Square 0.29 0.16 0.27 0.46 0.36 0.47

0 0.20 0.40 0.60 0.80 1 300

400

500

600

700

800

900

1000

1100

1200

CAN AUS USA NZL MEX

FIN GRC JPN

IND

CHN PRT NOR DEU

SWE ESP AUT GBR FRA DNK CHE NLD

BEL

ITA

URY

ARG BRA HKG GUY VEN PRY CHL

SGP JAM DOM HTI PNG PHL COL MYS

BOL HND NIC CRI SLV GTM PAN PER DZA IDN ECU MMR TUN LKA KOR TUR EGY PAK BGD MAR

Note that this is the first formal direct test of the core hypothesis in Diamond (1998) on a large sample of countries.

Documenting the reversalof fortune (1500 – 1960)Dependent variable: Log GDP p.c. 1960

1 2 3 4 Urbanization 1500

-.044** (0.023)

Log Population Density 1500

-0.223*** (0.044)

Log GDP pc 1500 (urbanization only)

-1.83** (0.953)

Log GDP pc 1500 (urbn +popden)

-2.549*** (0.588)

R-Square 0.10 0.21 0.10 0.34

Observations 37 73 37 37

Documenting the reversalof fortune (1500 – 1960)Dependent variable: Log GDP p.c. 1960

STATEHIST 1500

-0.672*** (0.232)

-1.05*** (0.255)

AGYEARS -0.014 (0.037)

-0.26*** (0.045)

R-Square 0.09 0.001 0.26 0.51

Observations 65 59 36 31

Notes: Last two columns restrict sample to countries for which we also have estimated 1500 GDP numbers. Constant included but suppressed

Robustness checks

• Test for convergence• Add various combinations of (a)

landlocked, (b) latitude, (c) colonizing power (France, Spain), (d) years colonized.

• Substitute PWT for Maddison estimate of 1960 GDP p.c.

• Substitute growth rate 1500 – 1960 for log GDP p.c. 1960 and test for convergence.

Sample: AJR sample of colonized countries, excluding Hong Kong, Singapore and Western Offshoots

1 2 3 4 5 6 7 8 Log GDP pc 1500 (urbn +popden)

-1.81** (0.68)

-1.25** (0.54)

-2.00** (0.85)

-2.1*** (0.51)

-0.006*** (0.001)

STATEHIST 1500

-0.48* (0.27)

-0.40 (0.35)

-0.81*** (0.25)

0.20 (0.27)

-0.38* (0.18)

-.44 (0.18) **

-0.001* (0.0006)

AGYEARS -0.20*** (0.05)

LANDLOCK -0.42 (0.27)

-0.63*** (0.14)

-.33** (0.14)

LATITUDE (Absolute Value)

0.001 (0.008)

.013** (0.007)

0.014** (0.006)

French Colony 0.20 (0.22)

0.23 (0.15)

0.34** (0.15)

Spanish Colony

0.72*** (0.18)

0.93*** (0.17)

0.40* (0.22)

Years Colonized

.0006 (.0005)

.0006 (.0006)

-.001 (.0007) **

R-Square 0.38 0.59 0.41 0.26 0.61 0.48 0.57 0.38 Observations 36 31 36 64 36 65 66 36

Notes: Columns 1-6 use Maddison’s estimates of Log Real GDP pc in 1960 as the dependent variable. Column 7 uses the PWT estimate of the log of real GDP pc in 1960 as the dependent variable. Column 8 uses growth rate as the dependent variable. Constant included in all regressions but suppressed. ***- denotes significance at 1%, **- at 5% and *- at 10%.

Documenting “catch-up” 1960-98Dependent Variable: Log GDP per Capita 1998

Sample: AJR sample of colonized countries, excluding Hong Kong, Singapore and Western Offshoots

1 2 3 4 5 6 7 Urbanization in 1500

-0.03 (0.02)

0.004 (0.014)

Log GDP pc 1500 (urbn +popden

0.22 (0.53)

Log GDP pc 1960

0.837*** (0.102)

0.86*** (0.11)

0.94*** (0.11)

1.22*** (0.15)

1.01*** (0.11)

1.05*** (0.13)

STATEHIST 1500

0.41* (0.24)

0.55*** (0.20)

AGYEARS 0.16*** (.06)

0.15*** (0.03)

R-Square 0.05 0.68 0.68 0.71 0.78 0.63 0.68 Observations 37 37 37 36 31 65 59 Note: Constant included in all regressions but suppressed. ***- denotes significance at 1%, **- at 5% and *- at 10%.

0 0.20 0.40 0.60 0.80 1-0.04

-0.02

0

0.02

0.04

0.06

0.08

AFG

AGO

ARG

JAM

ZMB

ZAFBEN

BGD BOL

BRA

BWA

CAF

HND

CHL

SWZ

CIVCMR

COG

COL

CPV

CRI

VEN

PHL

DOM

DZA

ECU

EGY

URY

UGA

TUN

GAB

TTO

GHA

GMB

TGO

GTM

GUY MAR

HTI

IDN

IND

PNG

PRY

MLISLV

PER

ZWEKEN

PAN

LKAPAK

MDG

MEX

MYS

MMR

MOZ

MRTNGA

NIC

NER

SEN

NPL

RWA

KOR

MUSISR

CHN

IRN

THA

JOR

TUR

SYR

Dependent Variable: Log GDP per Capita 1998++ Sample: AJR sample of colonized countries, excluding

Hong Kong, Singapore and Western Offshoots 1 2 3 4 5 6 7+ 8++ Log GDP pc 1960 0.94***

(0.13) 0.95*** (0.10)

0.99*** (0.14)

0.92*** (0.13)

0.74*** (0.11)

0.74*** (0.15)

0.61*** (0.12)

-0.001 (0.003)

STATEHIST1500 0.43* (0.22)

0.48** (0.23)

0.47* (0.25)

0.57*** (0.19)

0.43** (0.21)

0.50** (0.20)

0.30# (0.18)

0.01* (0.006)

LANDLOCK -.15 (0.18)

-.08 (.18)

-0.19 (0.16)

LATITUDE (Absolute Value)

-.002 (.006)

.009 (.006)

0.003 (0.006)

French Colony -0.33 (0.20)

-0.35** (0.15)

-0.19 (0.16)

Spanish Colony -0.21 (0.17)

0.16 (0.18)

0.10 (0.16)

Years Colonized .0004 (.0007)

-.00002 (0.0007)

-0.0003 (0.0006)

Log(Investment) 1960- 2000

0.38** (0.17)

0.35** (0.14)

0.50*** (0.13)

Population Growth (1960-2000)

1.07 (12.36)

1.98** (0.83)

-15.52 (16.04)

Secondary Enrollment Ratio 1960

0.80 (0.80)

3.53 (11.90)

0.64 (1.07)

R-Square 0.71 0.65 0.75 0.65 0.75 0.76 0.77 0.17 Observations 36 64 36 65 32 56 59 36 Notes: Columns 1-6 use Maddison’s estimates of Log Real GDP pc in 1998 as the dependent variable. + :Column 7 uses the PWT estimate of the log of real GDP pc in 1995 as the dependent variable. ++: Column 8 uses growth rate as the dependent variable. Constant included in all regressions but suppressed. ***- denotes significance at 1%, **- at 5% and *- at 10%. #: the p-value is 0.11

Conclusion

• We’ve demonstrated that early starts are positively correlated with (a) income in 1500, and (b) growth during 1960-98.

• We’ve reconfirmed the “reversal of fortune” for 1500-1960 using “early start” indicators, but found a “reversal of the reversal” underway after 1960.

• The effects of colonially imposed

institutions seem to have worn off some time after 1960.

• Modern growth is more related to “social capability” built up over two millennia than to differences in colonial institutions.

• Hibbs & Olsson and Bockstette, Chanda and Putterman find that early development (agriculture or states) predicts current quality of institutions, some other institutional measures.

• Perhaps the biggest long-term colonial impact is that from large-scale population movements, which may have transferred old social capabilities with them—something to be explored in future research. (This may help to explain Hall & Jones and La Porta, Lopez-de-Silanes, Shelifer and Vishny).