determinants of economic growth of russian regions o. lugovoy, i. mazayev the institute for the...

Determinants of Economic Growth of Russian Regions

O. Lugovoy, I. MazayevThe Institute for the Economy in Transition

In collaboration with:V. Dashkeyev, D. Fomchenko (IET)E. Polyakov (The World Bank)

Seminar at WLU in WaterlooNovember 23, 2006

A. HechtWilfred Laurier University

Addressed questions:

• What are the fundamental causes of regional disparities?

• Why do growth rates differ across Russian regions?

• Is there an income convergence?

I. Differences in Income and Growth Rates

‘Deep’ Determinants

D. Rodrik’s proximate and deep determinants

Source: D. Rodrik, ‘Search of Prosperity’, p. 5, Figure 1.3

“Fundamental Causes” in income differences

(according to D. Acemoglu, S. Johnson, J. Robinson, 2005)

• Economic institutions

• Geography

• Culture

“Proximate” determinants (endogenous)

• Capital deepening (K)• Human capital accumulation (L, H)• Productivity (A)• Natural resources (R)

Benchmark production function:

Y = A·K ·(H·L)1- ·(1+R)y = a+r+·k+(1- )·h

“Deep” determinants of regional growth

• Physical geography: temperature, permafrost, distribution of natural resource deposits

• Economic geography (Infrastructure and trade) access to seaports, railway infrastructure, innovation diffusion, agglomeration)

• Institutions (indexes of corruption and trust, financial ratings and proxy variables)

Distribution of per capita income in 2004.

Legend

29019 - 4521647696 - 6162162679 - 9508396749 - 120564

130038 - 172770265130 - 265131573898 - 573898N o D ata

Annual per capita grp growth rate (average 1998 - 2004),%

Legend

-1.0 - 2.02.0 - 2 .82.8 - 3 .83.8 - 4 .8

4.8 - 5 .95.9 - 7 .27.2 - 8 .3N o D ata

N et M igration R ate (1998-2004 average)

Legend

-30 - -10-10 - -3-3 - -1-1 - 1

1 - 33 - 1010 - 30N o D ata

Population grow th betw een 1926 and 1989 census, %

Legend

0 - 100100 - 200200 - 400400 - 700

700 - 15001500 - 50005000 - 5815N o D ata

R egions w ith seaports

Postgraduate students per 10 000 inhabitants

Legend

0 - 33 - 44 - 66 - 8

8 - 1221 - 2230 - 37N o D ata

Simultaneous equations model

y = y(k, h, r)dy = y(dk, m, h, r)m = m(y, Geo, Infr, Inst, …)dk = k(y, Geo, Infr, Inst, …)

Geo – GeographyInfr – InfrastructureInst - Institutions

Econometric techniques

• Panel data set: 77 regions, 8 years (1997-2004)

• Mundlak specification for ‘between’ and ‘within’ estimates

• 3SLS & FIML for estimation of simultaneous equation model (SEM)

Mundlak specification for the one-factor lineal regression model

Mundlak specification:

ititit xaay 10

itiitit xaxaay *110

itiiitit xxxay *110

or

within(Fixed Effect)

between(BE)

Regions with higher income (GRP p.c.) are characterized

by: • Relatively higher level of per capita investment;• Higher share of raw materials in industrial output

(including fuel, ferrous, non-ferrous and timber industries);

• Higher share of economically active population; • Higher share of the employed in economically active

population;• Increase in share of the employed in economically

active population;• Higher number of postgraduate students (per 10 th.);• Higher agglomeration (population in the largest city).

The faster growing regions are characterized by:

• Relatively higher level of per capita investment;

• Increase in per capita investment;• Increase in the share of raw

materials’ industries in industrial output;

• Availability of a seaport;• Lower per capita output level

(conditional convergence).

The larger migrants’ balance is observed at:

• Relatively wealthy regions (per capita output, mean over the period);

• Regions with the smaller population growth rates during the soviet period (early developed regions or “home” regions);

• Regions with relatively warmer climate (average January temperature);

• Regions with more developed infrastructure (railway passengers);

• Regions with higher agglomeration (population in the largest city).

• Unemployment level (official data) tends to be statistically insignificant.

The larger per capita investment is observed in:

• Regions with higher per capita output, (mean over the period);

• Regions with relatively warmer climate (average January temperature) on the one side, and regions with permafrost on the other (probably those with field development of natural resources and/or higher costs of investment);

• Regions with higher per capita fuel industry output;• Regions with increase in per capita fuel industry output;• Regions with more developed infrastructure (per capita

phones in1995);• Regions with higher per capita investment during the

period 1997-2004 are characterized with less corruption figures concerning small-scale business in 2005.

The larger per capita investment is observed in:

• “Better” programs of regional development (CEFIR est.)

• Less legislative risk.

• S&P rating (dummy variable).

Basic conclusions

• Proximate determinants matter for income level and growth

• Geography matters for proximate factors accumulation: cause to migration flows and capital accumulation

• Infrastructure, trade, agglomeration matter for physical and human capital accumulation.

• There are some statistical evidence of relationship between some institutions measures and ‘proximate’ determinants but the problem of endogenity remains.