Is infrastructure capital productive ? a dynamic heterogeneous approach

TLDR: In this paper, a long-run aggregate production function relating GDP to human capital, physical capital, and a synthetic measure of infrastructure given by the first principal component of infrastructure endowments in transport, power, and telecommunications is presented.

Abstract: This paper offers an empirical evaluation of the output contribution of infrastructure. Drawing from a large data set on infrastructure stocks covering 88 countries and spanning the years 1960-2000, and using a panel time-series approach, the paper estimates a long-run aggregate production function relating GDP to human capital, physical capital, and a synthetic measure of infrastructure given by the first principal component of infrastructure endowments in transport, power, and telecommunications. Tests of the cointegration rank allowing it to vary across countries reveal a common rank with a single cointegrating vector, which is taken to represent the long-run production function. Estimation of its parameters is performed using the pooled mean group estimator, which allows for unrestricted short-run parameter heterogeneity across countries while imposing the (testable) restriction of long-run parameter homogeneity. The long-run elasticity of output with respect to the synthetic infrastructure index ranges between 0.07 and 0.10. The estimates are highly significant, both statistically and economically, and robust to alternative dynamic specifications and infrastructure measures. There is little evidence of long-run parameter heterogeneity across countries, whether heterogeneity is unconditional, or conditional on their level of development, population size, or infrastructure endowments.

Figures

Table 2. Panel Unit Root and Cointegration Tests

Table 5 Additional Homogeneity Tests

Table 3 Estimation of the Production Function Alternative Dynamic Specifications

Full text

IS INFRASTRUCTURE CAPITAL
PRODUCTIVE? A DYNAMIC
HETEROGENEOUS APPROACH
César Calderón, Enrique Moral-Benito
and Luis Servén
Documentos de Trabajo
N.º 1103
2011

IS INFRASTRUCTURE CAPITAL PRODUCTIVE? A DYNAMIC
HETEROGENEOUS APPROACH

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ISSN: 0213-2710
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IS INFR
A
STRUCTURE CAPITAL PRODUCTIVE? A DYNAMIC
HETEROGENEOUS APPROACH
(*)
César Calderón
THE WORLD BANK
Enrique Moral-Benito
BANCO DE ESPAÑA
Luis Servén
THE WORLD BANK
(*) We are grateful to Nicola Limodio and Stéphane Straub for useful comments and suggestions. We also than
k
participants at the Toulouse conference on ‘Infrastructure Economics and Development’, the Australian National
University conference on ‘The Economics of Infrastructure’, the IMF conference on ‘Investment Scaling-up in Low-
Income Countries’, the 2010 Symposium of Economic Analysis, and seminars at Brookings and the Bank of Spain.
However, any remaining errors are ours only. Rei Odawara and Junko Sekine provided excellent research assistance.
This work was partly supported by the Knowledge for Change Program as well as the Government of Japan through the
Consultancy Trust Fund Program (CTF) of the World Bank.
T
he views expressed in this paper are only ours and do not
necessarily reflect those of the Bank of Spain or the Eurosystem, The World Bank, its Executive Directors, or the
countries they represent.
Documentos de Trabajo. N.º 1103
2011

A
bstract
This paper offers an evaluation of the output contribution of infrastructure. Drawing from
a large data set of infrastructure stocks covering 88 countries and spanning the years
1960-2000, and using a panel time-series approach, the paper estimates a long-run
aggregate production function relating GDP to human capital, physical capital, and a
synthetic measure of infrastructure given by the first principal component of infrastructure
endowments in transport, power and telecommunications. Tests of the cointegration rank
allowing it to vary across countries reveal a common rank with a single cointegrating vector,
which we interpret as the long-run production function. Estimation of its parameters is
performed using the pooled mean group (PMG) estimator, which allows for unrestricted
short-run parameter heterogeneity across countries while imposing the (testable) restriction
of long-run parameter homogeneity. The long-run elasticity of output with respect to
the synthetic infrastructure index ranges between 0.07 and 0.10. The estimates are
highly significant, both statistically and economically, and robust to alternative dynamic
specifications and infrastructure measures. There is little evidence of long-run parameter
heterogeneity across countries, whether heterogeneity is unconditional, or conditional on
their level of development, population size, or infrastructure endowments.
JEL Classification: H54, E23, O40.
Keywords: Infrastructure, panel cointegration, parameter heterogeneity.

Frequently asked questions

Q1. What are the contributions in "Is infrastructure capital productive? a dynamic heterogeneous approach" ?

This paper offers an evaluation of the output contribution of infrastructure. Drawing from a large data set of infrastructure stocks covering 88 countries and spanning the years 1960-2000, and using a panel time-series approach, the paper estimates a long-run aggregate production function relating GDP to human capital, physical capital, and a synthetic measure of infrastructure given by the first principal component of infrastructure endowments in transport, power and telecommunications. 

Q2. What is the effect of the econometric approach on the output elasticity of infrastructure?

The econometric approach deals explicitly with the non-stationarity of infrastructure and other productive inputs, reverse causality from output to infrastructure, and potential cross-country heterogeneity in the contribution of infrastructure (or any other input) to aggregate output. 

Q3. What is the test for the presence of a unit root in each panel series?

To test for the presence of a unit root in each panel series, the authors employ the unit root test of Im, Pesaran and Shin (2003) (IPS), which allows for heterogeneous short-run dynamics for different cross-sectional units. 

Q4. What is the PMG estimator's definition of a long-run coefficient?

As equation (3) makes explicit, the PMG estimator restricts the long-run coefficientsto be equal over the cross-section, but allows for the short-run coefficients, speed of adjustment and error variances to differ across cross-sectional units. 

Q5. What is the importance of quantitative assessments of the contribution of infrastructure?

1Quantitative assessments of the contribution of infrastructure are critical for manypolicy questions —such as the output effects of fiscal policy shocks instrumented through public investment changes [e.g., Leeper, Walker and Yang (2010); Ilzetzki, Mendoza and Végh (2010)], or the extent to which public infrastructure investment can be self-financing [Perotti (2004)]. 

Q6. What is the average t-value for a non-stationary series?

If the data are statistically independent across countries, under the null the authors can regard the average t-value as the average of independent random draws from a distribution with known expected value and variance (that is, those for a non-stationary series). 

Q7. How do the authors estimate the number of cointegration relations?

In short, the authors first use the LR-bar test to estimate the maximum number ofcointegration relations, and then the authors use the PC-bar test to assess if for any country the number of cointegrating relations is less than the maximum given by the LR-bar test. 

Q8. What is the correlation between paved road length and power generation capacity?

In turn, the correlation between paved (as opposed to total) road length and power generation capacity is 0.83, while that between paved road length and main telephone lines is 0.84. 

Q9. How can the authors check the significance of the cointegrating vector?

as shown by Johansen (1992) and Boswijk (1995), weak exogeneity for the long-run parameters can be checked by testing the significance of the cointegrating vector in a reduced-form regression of each input on its own past and those of output and the other inputs of the production function.