Bear Traps on Russias Road to Modernization Clifford G. Gaddy, - - PowerPoint PPT Presentation

Bear Traps

• n Russia’s Road to Modernization

Clifford G. Gaddy, Brookings Institution (Washington, DC) Barry W. Ickes, Penn State University and New Economic School (Moscow)

Two Themes:

• 1. Danger of misdiagnosis of economic

problems.

• 2. Myths about what produces growth.

• 1. Danger of Misdiagnosis
• The inputs (physical capital, labor, human

capital) into Russia’s production function are all mismeasured.

• They are assigned inflated values because of

failure to take into account that they are handicapped by nature and by legacies.

• Mismeasurement (inflation of value) of inputs

 wrong analysis of causes of low output  wrong policies to increase growth.

• 2. Myths about What Produces Growth

Especially on human capital side.

Findings:

• The loss to the Russian economy from

handicapped capital” is very large.

• For physical capital inputs alone, handicaps may

be causing Russia to underperform by as much as 30% compared to most-advantaged competitors.

• Human capital and labor handicaps add even

more.

• Russia performs as well as it does only thanks

to oil.

Policy Conclusions:

• 1. Remove existing handicaps to capital; avoid

adding more in future.

• 2. Concentrate even more on oil and gas — a

“Resource Track” policy instead of false “Modernization.”

Bear Traps Table of Contents Introduction

• 1. Historical Prelude
• 2. Investment [physical capital]
• 3. Economics of Location
• 4. Market-impeding Federalism
• 5. Human Capital
• 6. Conclusion

Introduction - 1

• Modernization is more than just having

new capital.

• If the location, structure, and production

and supply chains are not appropriate, then merely replacing the depleted, out-

• f-date capital with physically new capital

is not true modernization.

Introduction - 2

• “Scrapping problem” — choice between

(1) replace old machines with new ones

• r (2) scrap entire technology/approach,

start fresh.

• (1) produces short-term results, but

dooms to long-term failure. (2) is costly in short term, better in long term.

Introduction - 3

“Making mistakes and correcting mistakes”

• The Soviet economy made very large

mistakes and allowed them to persist for too long.

• Free market economy makes many

mistakes (because tests more). But corrects quickly.

• Harsh process, disruptive. Risky. Cannot be
• verly afraid of chaos and instability.

• 1. Historical Prelude

Russia’s transition:

• No write down of value of assets inherited.

So old assets kept, with illusory value. Everyone complicit in maintaining pretense.

• Subsidies. Virtual Economy.
• Needed to maintain location, structure,

chains.

• 2. Investment (physical capital)
• Illusory value of assets = inflated value.

Handicapped by location, historical legacy, production relationships.

• τ-factor (tau-factor) = discount. Gap between

actual and measured value.

• Why is this important? Because we misjudge

the cause of poor performance. You think you have lots of capital. When performance fails to live up to expectations, blame low productivity due to “institutional” failures, Rule of Law, corruption, etc.

• And fail to remove handicaps.

• 3. Economics of Location

[=”Siberian Curse”]

Not only cold; also distance (remoteness).

Should Russia then focus its resources on modernizing its transport network? In the typical country with such an inadequate network, the returns to such investment would be high. But it is important to think about the problem more carefully in the case of Russia. While improvements in transportation infrastructure will have cost-reducing effects, they will do nothing to eliminate the burden of a highly dispersed population and the lack of empty space. Building a transportation network to minimize the costs of the current spatial location is a bear trap. Even a cost minimizing, efficient transportation system cannot eliminate the burden of running an economy that is spatially misallocated. In fact, it would likely deepen the problem in the long term. Such a system would still be needlessly high-cost relative to its competitors abroad. A policy of this sort ignores the

• pportunity cost of the cities. If the cities should not be there, building more

roads to them makes things worse. It is not a sunk cost. If it were, it could just be written off as a mistake. But expanding the transport infrastructure to connect cities over vast distances reinforces the original mistake and creates even more costs in future. Even more wasteful than the “Bridge to Nowhere” is a “Bridge to Somewhere that Should Not Exist.” Rather than spending money to build more and better roads to connect non-economic locations, policy should be directed at phasing out those locations, making them less important. Resources could instead be used to better link cities and people that are more rationally located.

• 4. Federalism — “Lights On”
• Normally, federalism is good. Competition,

check on predation by central government. Assumption is that each region can be winner, can grow. But efficiency ≠ growth everywhere. Some regions should shrink.

• But Russia’s federalism allows all to fight

against shrinkage.

• Moreover, winner regions do not want losers

to reform! Reform causes externalities for

• winners. So winners (Moscow) supports

policies to keep population in place. Cheapest way? Keep factories going at minimal level, “keep the lights on.”

• 5. Human Capital

Population size. The population is shrinking, to a greater extent and for a longer time than almost any other country’s today. Age structure. The working age population is collapsing. The number of young and old people each productive worker will have to support (the “dependency ratio”) is going to rise sharply.

• Fertility. Birth rates are down.
• Mortality. Death rates are up. Not only are they much higher than those of the

rest of the world, but they have grown worse over recent decades.

• Health. The overall health of the population in all age groups is poor.
• Education. The stock of skills is in question. The education system appears to be

performing poorly despite high levels of education per worker.

• 5. Human Capital

Ask, how affect growth? Population size — NO Health — NO Education — YES (but measure correctly) Location — YES!

• 6. Conclusion
• “War on Moscow”  centralized “Lights

On”

• Our proposal: “Resource Track” —

embrace natural resources sectors, especially oil and gas.

• Make it national priority, higher even than

military defense sector.

US Russia Roads Comparison

From 1960 to 1990, Russia expanded its road network more than five-fold. But that was from a very low base, and even at the end of the period, total road mileage in Russia was still only 18 percent of that in the United States. Adjusted for Russia’s larger size, Russia’s coverage was only 10 percent of the US. Moreover, these statistics do not account for quality of the roads or even the width (number of lanes) of the roads. Most of Russia's roads are 1- or 2-lane roads; of the total of nearly 800,000 km of roads, only 4,300 km are roads with four or more lanes. That is around 1.2 percent of the US total of such highways. [US highway data from the US Bureau of Transportation Statistics, “National Transportation Statistics, 2010” available at http://www.bts.gov.] In fact, Russia’s total of highways of 4 or more lanes is barely half of what the state of North Carolina has. [NC data from North Carolina Department of Transportation, "2010 Highway and Road Mileage Report", p. 13, http://www.ncdot.gov/travel/statemapping/]

Quantities Land area Population Roads Vehicles Rail lines (km2 millions) (millions) (km millions) (millions) (km '000s) 1 Russia 16.4 142 0.937 37 84.2 2 China 9.3 1325 3.770 49 60.8 3 USA 9.1 304 4.169 158 227.1 4 Canada 9.1 33 1.440 20 57.2 5 Brazil 8.5 192 40 29.8 6 Australia 7.7 21 0.821 15 9.7 Densities Population/ Area Roads/ Area Roads/ Population Vehicles/ Population Vehicles/ Roads Rail lines/ Area (persons per km2) (km per km2) (km per 1000) (per 1000) (per km) km per km2 '000s 1 Russia 8.7 57 6.6 264 40 5.1 2 China 142.0 404 2.8 37 13 6.5 3 USA 33.2 456 13.7 521 38 24.8 4 Canada 3.7 158 43.2 605 14 6.3 5 Brazil 22.6 209 3.5 6 Australia 2.8 107 38.2 687 18 1.3

City Location 2010 Population (000s) January temperature (degrees centigrade) Percent

• f cold

Novosibirsk Siberia 1,474

• 19

4.9% Omsk Siberia 1,154

• 19

3.8% Yakutsk Siberia 270

• 43

3.4% Yekaterinburg Urals 1,350

• 16

2.9% Khabarovsk Far East 578

• 22

2.6% Ulan-Ude Siberia 404

• 27

2.6% Krasnoyarsk Siberia 974

• 17

2.5% Irkutsk Siberia 587

• 21

2.4% Norilsk Siberia 175

• 35

2.3% Chita Siberia 324

• 27

2.1% Chelyabinsk Urals 1,130

• 15

2.0% Barnaul Siberia 612

• 18

1.8% Perm Urals 992

• 15

1.8% Tomsk Siberia 523

• 19

1.7% Samara Volga 1,165

• 14

1.6% Novokuznetsk Siberia 548

• 18

1.6% Kemerovo Siberia 533

• 18

1.6% Ufa Volga 1,062

• 14

1.5% Komsomolsk Far East 264

• 24

1.4% Kazan Volga 1,144

• 13

1.3% Tyumen Siberia 582

• 16

1.3% Bratsk Siberia 246

• 23

1.2% Blagoveshchensk Far East 214

• 24

1.1% Source: Authors’ calculations.

City Location Population (000s) January

• temp. (oC)

Percent of Cold Novosibirsk Siberia 1,474

• 19

4.9% Omsk Siberia 1,154

• 19

3.8% Yakutsk Siberia 270

• 43

3.4% Yekaterinburg Urals 1,350

• 16

2.9% Khabarovsk Far East 578

• 22

2.6% Ulan-Ude Siberia 404

• 27

2.6% Krasnoyarsk Siberia 974

• 17

2.5% Irkutsk Siberia 587

• 21

2.4% Norilsk Siberia 175

• 35

2.3% Chita Siberia 324

• 27

2.1% Chelyabinsk Urals 1,130

• 15

2.0% Barnaul Siberia 612

• 18

1.8% Perm Urals 992

• 15

1.8% Tomsk Siberia 523

• 19

1.7% Samara Volga 1,165

• 14

1.6% Novokuznetsk Siberia 548

• 18

1.6% Kemerovo Siberia 533

• 18

1.6% Ufa Volga 1,062

• 14

1.5% Komsomolsk Far East 264

• 24

1.4% Kazan Volga 1,144

• 13

1.3% Tyumen Siberia 582

• 16

1.3% Bratsk Siberia 246

• 23

1.2% Blagoveshchensk Far East 214

• 24

1.1% Source: Authors’ calculations