Ersa Workshop

Infrastructure and Growth – Theory, Empirical Evidence and Policy Lessons

Cape Town, 29 – 31 May 2006

Infrastructural Investment in Long-run Economic Growth: South Africa 1875-2001

J. Fedderke (UCT), P. Perkins (Wits),

J. Luiz (Wits)

1. Introduction

Renewed interest amongst South African policy-makers in economic infrastructural investment following an extended period of decline (from mid-1970s to 2002) The decline coincided with poor economic growth

in SA In the literature, the empirical evidence on the

infrastructure – growth relationship is relatively mixed

This paper provides a long-run, time-series investigation of the infrastructure – growth relationship in SA

2. The Role of Infrastructure in Economic Development

Labour-intensive Cobb-Douglas production function, from Barro model (1990):

y = Agk1- (0 < < 1)

where

y = output

A (> 0) = level of technology

g = government spending on productive services (e.g. infrastructure)

k = private capital

Marginal product of g:

Marginal product of k:

As g/y rises, g/k rises:

As g/y rises, y/k rises but y/g falls

1

g

kA

g

y

k

gA

k

y1

1/1

y

gA

k

g

Maximize utility:

where

Then steady state growth is given by:

0)( dtecuU t

1

1)(

1ccu

111

k

gA

y

g

k

k

g

g

y

y

c

c

The impact on of raising g/y depends on whether y/g is greater or less than 1:

When y/g > 1, d/d(g/y) > 0 When y/g = 1, d/d(g/y) = 0 When y/g < 1, d/d(g/y) < 0 The core rationale for infrastructural investment that emerges is that it raises the marginal product of other capital… …which in turn raises the rate of economic

growth, but within limits

1

1

/ g

y

k

gA

ygd

d

Author Nature of study Variations Elasticity Findings

Aschauer(1989)

Cobb-Douglas, OLS, United States (national), 1949-1985.

Non-military public capital

0.39 There is a strong, positive relationship between public capital (particularly core infrastructure) and productivity.

Core infrastructure (transport, power, water)

0.24

Hospitals 0.06

Educational buildings -0.01

Conservation & development structures

0.02

Baffes and Shah (1998)

Translog specification of a flexible production function, OLS, public- sector infrastructure, 21 countries from 4 regions, 1965-1984.

Africa (4 countries) 0.03The elasticities for labour, private capital and human capital are higher in all regions (compared with infrastructure), with the exception of labour in Latin America (0.15).

Asia (8 countries) 0.01

Europe / Middle East(5 countries)

0.04

Latin America(4 countries)

0.15

Author Nature of study Variations Elasticity Findings

Easterly and Rebelo (1993)

Cross-sectional pooled regression with decade averages, using 36 countries in the 1960s, 108 countries in the 1970s, and 119 countries in the 1990s. † These coefficients are not elasticities. The explanatory variables are expressed as investment/GDP ratios, so the effect of a one percentage point change in the ratio on annual GDP per capita growth is given by the coefficient/100.

Total consolidated public investment

-0.004 to0.04 †

Results for transport and communication support Aschauer’s (1989) finding that infrastructure spending has supernormal returns, and suggest that causality runs from infrastructure to economic growth. More work is needed to investigate the surprisingly high coefficients and the direction of causality.

General government investment

0.388 to0.453 †

Public enterprises investment

-0.13 to‑0.001 †

Transport & communication

0.588 to0.661 †

Transport & communication (IV)

2 †

General government investment (IV)

0.7 †

Author Nature of study Variations Elasticity Findings

Garcia-Milà, McGuire and Porter (1996)

Cobb-Douglas, 48 American states, 1970-1983, first differences with fixed state effects.

Highways -0.058 The elasticities are insignificant, confirming the results of Holtz-Eakin (1994).

Water & sewers -0.029

Other public capital

-0.022

Holtz-Eakin(1994)

Cobb-Douglas, state and local government capital for 48 American states, 1969-1986.

No state specific effects

0.203The elasticity of private output or productivity with respect to state and local government capital is close to zero.

Fixed state effects‑0.0517 to

‑0.0557

Long differences -0.115

GLS0.0077 to

0.0212

IV -0.0218

Lau and Sin (1997)

VAR system, multivariate stochastic cointegration method, U.S., non-military public capital,1925-89.

– 0.11

The elasticity of 0.39 reported by Aschauer (1989) is implausibly high. They find a positive but substantially lower elasticity.

Author Nature of study Variations Elasticity Findings

Munnell (1990a, 1990b, 1992)

Cobb-Douglas, presumably OLS (not specified), United States.

National, 1949-1987

0.34Public capital has a substantial positive impact on output, particularly at national level.

48 states, 1970-1986

0.15

Pereira (2000)

Impulse-response functions associated with estimated VAR models, United States, 1956-1997.

Aggregate public investment

0.0425

Public investment has a significant impact on economic growth in the United States. It also crowds in private investment and private employment.

Highways & streets

0.0055

Power & transport 0.0210

Water and sewerage

0.0086

Hospital, educational and other buildings

0.0173

Conservation & development structures & civilian equipment

0.0049

3. Estimation of the Structural Model

The Barro model and descriptive evidence suggest the following framework as a basis for empirical investigation [equation numbers correspond with those in the paper]:

• y = y(k, g) [6’]

• k = k(y, g) [7’]

• gi = g(y, gj), i ≠ j [8]

Employ standard VECM model

in which:

Stationarity characteristics of the data: standard augmented Dickey-Fuller test statistics

All variables found to be I(1), except for total capital stock and public-sectorinfrastructural capital stock: both I(2)

t1ktiti

1k

1it zzz

'1 :)r(H

Parsimonious specification of [6’] – [8]:

[9]

Possibility of multiple relationships between different forms of infrastructure, which may render identification of the system difficult Choice of public infrastructure, roads and electricity rests on PSS-F tests and prior literature

12 15

21 23

31 34

1 0 0

1 0 0

0 1 0

LNYPC

LNYPC DLNKPC

DLNKPC DLNIFPC

DLNIFPC LNTORD

LNELEC

Eskom’s generating capacity: uncomfortably close to winter peak demand Canning et al. (growth); Pereira (growth & inv.)

15

20

25

30

35

40

1993 1996 1999 2002 2005

Meg

awat

ts (

000)

Peak demand on Eskom integrated system Eskom net max capacity

?

Maximal Eigenvalue and Trace Statistics

Null Alternative Maximal

Eigenvalue

Trace

r =0 r =1 55.99*

(33.64)

122.62*

(70.49)

r ≤ 1 r =2 36.26*

(27.42)

66.62*

(48.88)

r ≤ 2 r =3 17.18

(21.12)

30.36**

(31.54)

r ≤ 3 r =4 9.44

(14.88)

13.19

(17.86)

* denotes rejection of null at the 5% level

** denotes rejection of null at the 10% level

Figures in parentheses report 5% critical values

Imputed elasticities (of output, capital investment and public infrastructural investment) at variable mean values

Variable CV1

(LNYPC)

CV2

(DLNKPC)

CV3

(DLNIFPC)

LNYPC - 2.44 3.93

DLNKPC 0.06 - -

DLNIFPC - 1.37 -

LNTORD - - 87.72

LNELEC 0.20 - -

Replace LNTORD with LNRLIN, LNRCOA, LNRPAS, LNRFRT, LNPARD, LNPASV, LNGDSV, LNPORT, LNFTEL, LNRGDS, LNRCAP

CV1: • Elasticity of output wrt capital investment:

0.03 – 0.09 (prev 0.06), except for LNRGDS (0.15)

• Elasticity of output wrt electricity: 0.07 – 0.24 (prev 0.2), except for LNRGDS and LNRCAP (both negative)

CV2: • Elasticity of capital investment wrt output:

2.03 – 6.70 (prev 2.44), except for LNRGDS (11) and LNRCAP (11.2)

• Elasticity of capital investment wrt public infrastructural investment: 0.68 – 1.54 (prev 1.37), except for LNRGDS and LNRCAP (both negative)

CV3:• Elasticity of public infrastructural investment wrt

output: 2.73 – 24.77 (prev 3.93)• Elasticity of public infrastructure wrt gj: all negative (prev 87.72 for total roads)

Considering the fragility of the previous results, we estimate a more parsimonious system:

[10]

Trace statistic indicates r = 2

12 14

21 23

1 0

1 0

LNYPC

LNYPC DLNKPC

DLNKPC DLNIFPC

LNELEC

Results reasonably close to initial results:• CV1: 0.06 (DLNKPC) and 0.20 (LNELEC) • CV2: 2.44 (LNYPC) and 1.37 (DLNIFPC)

Variable CV1

(LNYPC)

CV2

(DLNKPC)

LNYPC - 4.20

DLNKPC 0.05 -

DLNIFPC - 1.38

LNELEC 0.16 -

Imputed elasticities (of output and capital investment) at variable mean values

An obvious concern with [10] is that the results may be sensitive to the inclusion of additional regressors

Consequently, we test this by including property rights and political instability:

[11]

11 12

21 22

31 32 12 13 14 15 16

41 42 21 23 24 25 26

51 52

61 62

1

1

LNYPC

DLNKPC

LNYPC DLNIFPC

DLNKPC LNELEC

LNPROP

LNINST

Two alternative specifications of [11]:

1. Exclusion of property rights

α51 = α52 = 0 = β15 = β25

2. Same identification structure with weak exogeneity restrictions

β15 = β16 = β24 = 0

α31 = α32 = α41 = α51 = 0

Imputed elasticities at variable mean values

Specification 1 Specification 2

Variable CV1 (LNYPC)

CV2 (DLNKPC)

CV1 (LNYPC)

CV2 (DLNKPC)

LNYPC - 2.90 - 6.25

DLNKPC 0.03 - 0.04 -

DLNIFPC - 0.98 - 1.34

LNELEC 0.52 - 0.39 -

LNPROP - - - 1.68

LNINST - -0.17 - -0.16

4. Main findings

Investment in infrastructure appears to have led economic growth in South Africa The impact of infrastructure is direct and indirect, the latter occurring by raising the marginal productivity of other capital This result is robust both to the use of a parsimonious growth model and to a fuller specification incorporating institutional determinants of economic development There is weak evidence of feedback from output to infrastructure; this is not robust

Empirical studies using US data: wide range of estimates for the elasticity of output with

respect to public capital or some type of public infrastructure Aschauer (1989): 0.39; supported by Munnell (1990): 0.15-0.34 (smaller at state level) Holtz-Eakin (1994): elasticities ≈ 0; supported by

Garcia-Milà et al. (1996) Lau & Sin (1997): 0.11; Pereira (2000): 0.04 Econometric methodologies have generated much controversy

SA’s economic infrastructure has developed in phases, in some cases closely linked to

the development of the mining industry

0

50

100

150

200

1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Inde

x (2

000

= 100

)

Railway lines Goods stock (rail) Paved roads

Electricity Phone lines, incl. mobile