Institutions and the Allocation of Talent

Higher School of Economics, Moscow

Timur Natkhov, Leonid Polishchuk

Motivation: Selection of Subject Areas by Russian University Applicants

Health

Agriculture

Science

Education

Humanities & Social Sciencies

Law & Public Administration

Engineering

Economics & Management

3%

4%

7%

10%

10%

13%

17%

30%

Most Able Applicants Choose Law

32.5 37.5 42.5 47.5 52.5 57.5 62.5 67.5 72.5 77.5 82.5 87.5 92.5 97.5

Law

32.5 37.5 42.5 47.5 52.5 57.5 62.5 67.5 72.5 77.5 82.5 87.5 92.5 97.5

Aviation and space technologies

Unified State Test Results

Institutions affect returns to human capital in various economic activities and hence occupational choice

Strong institutions reward productive economic activities and create incentives for value-creating Schumpeterian entrepreneurship

Weak institutions reward rent-seeking which draws talents and entrepreneurial energy away from wealth creation towards redistribution

Economic development

Allocation of talent Institutions

Hypotheses

Antecedents: William Baumol (1990)

Institutions affect allocation of talent between productive and unproductive activities«Entrepreneurs are always with us and always play some substantial role. How they act at a given time and place depends heavily on the rules of the game – the reward structure in the economy – that happen to prevail»

Ancient Rome Medieval China Dark Ages in Europe Later Middle Ages

Economic growth is driven by energy and innovations produced by a relatively small group of most talented individuals

Hence the choice by such individuals between production and rent-seeking is critically important for economic development

Excessive enrollment of best and brightest in law at the expense of sciences and engineering adversely related to growth rates

Antecedents: K.Murphy, A.Shleifer, R.Vishny (1991)

Empirical strategy

• (Un)productive activities – share of young talents in country i pursuing education which equips for (un) productive activities

• Institutional quality – quality of institutions in country i• X – control variables • e – random error

Coefficient reflects the impact of institutions on the allocation of talent

Regression model

 

Data UNESCO database on graduates by 28 fields of study in

100 countries1. Law2. Science3. Engineering

Governance Matters Indicators by the World Bank1. Rule of Law2. Control for Corruption

Control variables

Institutions and students’ choices

Sample average

Rule of Law

above median

Rule of Law

below median

Law, % 6.2 4.2 8.3

Sciences, % 8.3 9.7 6.8

Difference between shares of law and science students, % -2.1 -5.5 1.4

Quality of institutions and enrollment in law schools Share of Law graduates Rule of Law -0.530*** -0.589*** -0.578*** -0.581*** -0.563*** -0.466***

Log GDP per capita 0.218 0.218 0.207 0.232 0.0571 0.157

School Tertiary, % -0.335 -0.422 -0.433 -0.366 -0.0516 -0.581

Services, % GDP 0.777 0.837 0.776 1.500 1.466

Log Oil reserves 0.00545 -2.57e-05 0.0626** 0.0542

Ethnic Fractionalization 0.285 0.327 0.286

Log Populaion -0.219*** -0.357***

Gini coefficient 0.925

Trade to GDP ratio -0.526**

Constant -1.707 -2.123 -2.072 -2.379 1.947 3.726 Observations 95 95 95 95 95 81R-squared 0.165 0.171 0.171 0.175 0.230 0.322

Lawlessness increases the appeal of legal profession

BLR

LBN

RUS

PAN

ALB

GEO

ARG

GTM

MKD

HND

UKR

SLV

ECU

VEN

MEX

HKG

BRA

BGRKEN

HRVIRQ

KHM

TUR

ROMAZE

CYP

LVA

LAO

SVK

IRNGRC

ITA

KOR

LUX

DZA

ARM

BEL

IDN

GUY

URY

PHL

NAM

LTU

BRN

BOL

EST

POLBWA

KGZCZE

CRI

SVN

SAU

BGD

PRTIRL

COMFRA

JOR

ESPHUN

BDI

MAR

ETH

CHE

THA

USAMYS

SWETZA

NLD

UGA

GBRLSO

FIN

ERI

AUT

MWI

ISL

GHA

AUSNZL

DNK

NER

CHL

CANNOR

-2-1

01

2S

hare

of L

aw G

radu

ates

, res

idua

ls

-1.5 -1 -.5 0 .5 1 1.5Rule of Law index, residuals

coef = -.466, (robust) se = .119, t = -3.92

Quality of institutions and enrollment in sciences Share of Science graduates Rule of Law 0.257**

*0.205* 0.258** 0.258** 0.252*

*0.262*

*Log GDP per capita 0.194 0.194 0.134 0.137 0.191 0.250School Tertiary, % -1.261** -1.339** -1.395** -1.386** -1.482*** -1.179**Services, % GDP   0.700 1.020 1.012 0.789 0.235Log Oil reserves     0.0289 0.0281 0.00887 -0.0119Ethnic Fractionalization       0.0378 0.0249 0.493Log Populaion         0.0674 0.114**Gini coefficient           -0.0210Trade to GDP ratio           0.289Constant -0.240*** -1.487 -1.861 -1.594 -1.635 -2.964*            Observations 95 95 95 95 95 81R-squared 0.199 0.208 0.223 0.223 0.233 0.339

Rule of Law increases the appeal of sciences

BLR PAN

GEO

ALB

RUS

ARG

HNDCOL

GTM

MKD

UKR

ECU

HKG

SWZ

AGO

VENKEN

BGR

HRV

BRA

MEXCYP

KHM

LVA

ROMTUR

GRC

CMR

LAO

SVK

IRQ

KOR

AZE

ITA

BELARM

URY

GUY

IRN

EST

NAM

LTU

DZA

CRI

PHL

BWAKGZ

SVN

POL

BGD

PRT

CZE

BOLIDN

COM

JOR

IRL

BRN

FRA

BDI

HUN

ESP

CHE

ETHMLT

SWE

MOZ

TZA

USA

THA

MRT

NLDLSO

MYSERI

FIN

GBR

UGA

MDG

MWIISL

AUTGHA

DNK

NZL

AUS

NERCHL

NOR

CAN

-1.5

-1-.5

0.5

11.

5S

hare

of S

cien

ce G

radu

ates

, res

idua

ls

-1.5 -1 -.5 0 .5 1 1.5Rule of Law index, residuals

coef = .326, (robust) se = .092, t = 3.55

Law vs. Sciences and quality of institutions Difference between Shares of Law and Science

Rule of Law -0.552***Government Effectiveness -0.387**Control for Corruption -0.383***Private Property Protection -0.294**

Log GDP per capita -0.116 -0.188 -0.228 -0.339*School Tertiary, % 1.152** 1.153** 1.140** 1.013Services, % GDP 0.298 0.0628 0.218 0.101Log Oil reserves 0.0318 0.0440 0.0520* 0.0589**Ethnic Fractionalization 0.182 0.236 0.144 0.0169Log Populaion -0.190*** -0.179** -0.208*** -0.219*** Observations 95 95 95 83R-squared 0.310 0.246 0.266 0.301

Net attractiveness of law and the quality of institutions

BLR

PAN

RUS

GEO

ALB

ARG

GTM

HND

SLV

UKR

MKDECU

HKG

AGO

VEN

KEN

BGR

BRA

MEX

HRVKHM

CYP

ROM

LVA

TUR

CMR

GRC

LAO

SVK

IRQKOR

ITA

AZE

BEL

ARM

IRN

URY

GUY

DZA

EST

NAMLTU

PHL

KGZ

CRI

POL

SVNIDN

BWABGD

BOL

CZE

PRT

JOR

BRNIRL

FRA

COM

BDI

ESP

HUN

ETH

CHE

MOZ

SWE

USA

TZA

THA

NLD

MYS

LSO

FIN

ERI

UGA

GBR

MDG

MWI

AUT

ISL

GHANZL

DNKAUS

NERCHL

CAN

NOR

-2-1

01

2D

iffer

ence

bet

wee

n La

w a

nd S

cien

ce g

radu

ates

, res

idua

ls

-1.5 -1 -.5 0 .5 1 1.5Rule of Law index, residuals

coef = -.537, (robust) se = .110, t = -4.9

Robustness checks Difference between Shares of Law and Science Without OECD

and High Income Countries

Without Low Income

Countries

Full Sample with dummy for Asia

Full Sample with dummy for

Africa

Rule of Law -0.697*** -0.488*** -0.636*** -0.631***Log GDP per capita 0.0930 -0.368 0.00175 -0.0149School Tertiary, % 0.307 1.210** 0.995* 1.354**Services, % GDP 0.680 0.804 -0.613 0.397Log Oil reserves 0.0577 0.0360 0.0153 0.0301Ethnic Fractionalization 0.435 0.00826 -0.0105 0.115Log Populaion -0.288*** -0.198** -0.133* -0.187***Asia -0.777***Africa 0.421

constant 3.129 5.729** 6.363** 1.945

Observations 61 81 95 95R-squared 0.29 0.36 0.41 0.32

Institutions and settlers mortality (Acemoglu, Johnson, Robinson 2001)

AUS

NZL

HKG

USA

ZAF

CAN

MLT

MYS

SGP

ETHGUY

PAK

IND

TUNEGY

ARG

CHL

LKA

BOL

BRA

COL

ECU

GTM

MEX

PER

URY

BGD

DZA

CRI

SLVHND

MARPRYVEN

BHSTTO

SDN

DOM

HTI

JAM

VNM

KEN

NIC

PANSEN

IDN

ZAR

COG

AGO

BFA

CMR

GAB

TZA

UGA

NER

GIN

SLE

MDG

CIV

GHA

TGO

GMB

NGA

MLI

-4-2

02

4P

rivat

e P

rope

rty P

rote

ctio

n

-2 0 2 4Log Settler Mortality

coef = -.607 se = .126, t = -4.8

2SLS for former colonies with settlers mortality as instrument Difference between Shares of Law and

Science

Government Effectiveness -1.526**

Private Property Protection -0.931***

Government Effectiveness Private Property Protection

Settler Mortality

-0.246*** -0.403***

Full set of controls

Observations 35 35R-squared 0.70 0.77First Stage F-statistics 9.3 13.3

The case of transition economies

Share of Law Graduates

Share of Science Graduates

Difference

Rule of Law -0.735** 0.571*** -0.912***

Log GDP per capita -0.286 0.320** -0.432**

School Tertiary, % 0.399 -1.477*** 1.421***

Services, % GDP 3.992* -1.845** 3.946***

Constant 4.181 -4.827* 6.363**

Observations 20 20 20R-squared 0.601 0.735 0.833

Successful reforms increase relative attractiveness of sciences over law

BLR

MKD

ALB

GEORUS

UKR

ARM

BGRSVK

LVA

SVN

HRV

ROM

POL

EST

LTUCZE

AZEHUN

KGZ

-1-.5

0.5

1D

iffer

ence

bet

wee

n La

w a

nd S

cien

ce g

radu

ates

, res

idua

ls

-1 -.5 0 .5 1Rule of Law index, residuals

coef = -.912, (robust) se = .148, t = -6.16

Enrollment trends: The tale of two neighbors

2001 2002 2003 2004 2005 2006 2007 20080%1%2%3%4%5%6%7%8%9%

Poland

2001 2002 2003 2004 2005 2006 2007 2008

Ukraine

sciencelaw

Conclusions

Inefficient state, lack of the rule of law and poor protection of property rights increase the relative attractiveness law and public administration as areas of study for university students

Strong institutions increase the relative attractiveness of sciences and engineering as career choices for young people

Allocation of talent is a transmission mechanism between institutions and growth

Institutions, Human Capital, and the Allocation Talent

According to the model, more talented individuals are more sensitive to the quality of institutions

With weak institutions, the share of law students among more gifted young people should be higher, then for the whole cohort

With strong institutions, the share of science students among more gifted young people should be higher, then for the whole cohort

Consistency check: legal origins

Legal origins have strong impact on contemporary institutions:

Property rights protection (La Porta, Shleifer, et al., 1997)

Contract enforcement (La Porta, Shleifer, et al., 1998) Quality of governance (La Porta, Shleifer, et al., 1999) Control of corruption (La Porta, Shleifer, et al., 1999)

2SLS model

(𝑈𝑛 )𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑒 𝐴𝑐𝑡𝑖𝑣𝑖𝑡𝑖𝑒𝑠𝑖=𝛽0+𝛽1 𝐼𝑛𝑠𝑡𝑖𝑡𝑢𝑡𝑖𝑜𝑛𝑎𝑙𝑄𝑢𝑎𝑙𝑖𝑡𝑦 𝑖+𝛽2𝑋 𝑖+𝜀𝑖

Estimation results Difference between Shares of Law and Science

Rule of Law -1.544***Government Effectiveness -1.781**Control for Corruption -1.750**Private Property Protection -0.740***

Rule of Law Government Effectiveness

Control for Corruption

Private Property Protection

English Legal Origin

0.430*** 0.373*** 0.379*** 1.024***

Full set of controls

Observations 95 95 95 83R-squared 0.732 0.773 0.679 0.610First Stage F-statistics 33.97 42.23 26.34 16.77

Direct and indirect impact of legal origins

Legal origins are NOT valid instruments: they directly affect the legal profession

Common law system is more lawyers-intensive than the civil law one due to differences in administration of justice (adversarial vs. inquisitorial approaches)

However the indirect effect of legal origins (trough the quality of institutions) on the popularity of legal profession prevails over the direct one

Human capital, institutions, and allocation of talent

Data: quality of education indexes PISA and TIMMS for 60 countries

Rule of Law below the median

Rule of Law above the median

High Human Capital Index 7.33% 4.24%

Low Human Capital Index 2.88% 3.20%

Strong human capital and weak institutions

TZA

MWI

KEN

UGAHND

VEN

PHL

BRAMEX

IDN

ARG

LBN

IRN

MKD

ARM

ROM

RUS-.0

50

.05

Sha

re o

f Law

Gra

duat

es

-.2 -.1 0 .1 .2Human Capital Quality Index (Altinok, Murseli 2007)

coef = .246, se = .055, t = 4.5

Institutions and economic growth

2 3 4 5 6 7 8 9 105

6

7

8

9

10

11

R² = 0.611322109192881

Property rights protection index

Log

GD

P pe

r ca

pita

Institutions are pivotal for development

Allocation of talent as a missing link between institutions and growth

Average GDP per capita growth in 2000-2009

Rule of Law in 1998 0.759*** 0.673** 1.672** 0.601

Share of Law graduates -0.136 -1.418***

Share of Science graduates 0.124 0.019***

Full set of controls

Observations 94 94 20 20R-squared 0.17 0.18 0.62 0.78

Single-country analysis – quality of institutions and preference to law in Russian regions

MAG

KAM

KIR

SAK

KOS

IVA

ADY

TVE

OSE

KBRALT

KCRNGR

YEV

TYV

PRIOMS

VLGKAL

KLU

ZABCHE

DAG

ING

TUL

KYA

SMO

VLA

MUR

CU

YARPER

LIPRYA

BEL

KR

MO

VGGMEPSKAST

NIZ

KGNSVE

SAM

ORL

KGD

BA

BUR

KO

ARK

KK

TAM

KHA

SAR

TOM

UD

PNZ

KRS

ULY

BRY

VOR

NVS

AMU

TA

KEM

IRK

STA

ORE

RAL

SAHROS

-40

-20

020

40Ра

зниц

а до

лей

юри

стов

и и

нжен

еров

-2 -1 0 1 2Индкекс качества инвестиционного климата

coef = -7.10, se = 1.75, t = -4.05

Dream Employers for Russian youths

Gazprombank

Russian Railroads, JSC

LukOil

Sberbank

Rosneft (Oil company)

Police

President administration

Gazprom

0% 5% 10% 15% 20% 25%

7%

7%

9%

10%

10%

11%

12%

22%

Dream Employers for European Youths

Ernst & Young

PricewaterhouseCoopers

Coca-Cola Company

Boston Consulting Group

McKinsey & Co

L'Oreal

Google

Apple

Lawyers crowd out scientists and engineers

41.77 48.87 53.04 56.51 59.83 63.15 66.53 70.17 74.64 83.050%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Engineering

Law & Public administra-tion

Social sciences & Humanities

Economics & Man-agement

Health

Agriculture

Science

A model

Selection of activity

Equilibrium

Impact of institutions on the allocation of effort

Higher talents are more sensitive to institutions

Strong institutions: А > 0

Weak institutions: А < 0

Rent-seeking

Production

w

θ

w

θ

Production

Rent-seeking