Geoscience Reference
In-Depth Information
potential, a large number of studies on public infrastructure have been conducted
following a neo-classical approach using various forms of aggregate production
functions (Gramlich
1994
,
2001
; Harmatuck
1996
; Nadiri and Mamuneas
1996
;
Fernald
1999
; Bhatta and Drennan
2003
; Boarnet
1997
; Boarnet and Haughwout
2000
; Mattoon
2002
; Duffy-Deno and Eberts
1991
). These studies have been
subjected to a variety of criticisms (Gramlich
1994
). One of the criticisms is that
these studies did not consider spatial interactions among units across geographic
locations. Instead these studies assumed spatial independence among their research
units.
10.2.2 Spatial Perspective
Spatial econometric theory indicates that estimation outcomes vary significantly if
spatial dependence is considered in regional analysis (LeSage and Pace
2009
). This
is because regional performance is influenced by a region's own as well as other
regions' performance. Munnell (
1992
) indicated that the estimated impact of public
capital becomes smaller as the geographic focus narrows. She believed that this is
because of the effects of leakages from an infrastructure investment could not be
captured at a small geographic scale. Although this hypothesis may not be entirely
accurate, as indicated by Boarnet (
1998
), it does suggest that the spatial dimension
has influence on estimation and should not be neglected.
LeSage (
1999
) emphasized that traditional econometrics has largely ignored the
spatial dimension of sample data. When data has geographic information, the issue
of spatial dependence between observations may violate the Gauss-Markov theo-
rem. Without considering this issue, estimation results may be statistically biased.
Thanks to the development of spatial econometric techniques by Paelinck and
Klaassen (
1979
), Cliff and Ord (
1981
), Anselin (
1988
), LeSage and Pace (
2009
),
Elhorst (
2012
) and many others, methodologies for empirical spatial analysis were
developed. One of the dominant functions is to allow for the measuring of spatial
spillover effects. These effects refer to the situation in which the input in one sector
or region influences changes in neighboring local economies through trade linkages
and market relationships (Bo et al.
2010
). Transportation infrastructure may have
spillover effects on regional economic growth because the impacts generated from
infrastructure are not confined to that specific region (Moreno and L´pez-Bazo
2007
). To test the hypothesis empirically, different spatial models were adopted
(Holtz-Eakin and Schwartz
1995
; Kelejian and Robinson
1997
; Cohen and
Morrison Paul
2003
,
2004
).
Reviews of the existing literature regarding the spatial impacts of transportation
infrastructure (Boarnet
1998
; Holtz-Eakin and Schwartz
1995
; Kelejian and
Robinson
1997
; Ozbay et al.
2007
; Moreno and L´pez-Bazo
2007
; Cohen and
Morrison Paul
2003
,
2004
; Cohen
2007
; Mohammad
2009
; Chen and Haynes
2013
)
show that the conclusions are not consistent given the fact that different data,
methods, regions and periods were used. Despite the development of spatial
econometric techniques enabling scholars to investigate spillover effects of
