Download The incidence of energy policy reform: fossil fuel

The incidence of energy policy reform: fossil fuel subsidies in Southeast Asia Ian Coxhead1 & Corbett Grainger1
30 April 2014
Preliminary Draft: Please do not Cite
Abstract:
Most studies of the distributional and welfare incidence of energy policies focus on
consumer expenditures, and the most prominent analytical models do not fit well with the small,
open economy model suitable for most developing countries. In this paper we begin construction of
the supply-side of an analytical model of a small open economy with heterogeneous industries and
sources of household income. We examine the impacts of fuel subsidies of taxes on factor prices,
product prices, and household income distribution. We then use our model’s predictions, combined
with Vietnamese data, to quantify the importance of factor market impacts in determining the
distributional incidence of energy taxes or subsidies. Neglecting the factor market impacts of an
energy policy change can result in misleading implications for income distribution and economic
welfare. We also highlight the large opportunity costs associated with using government revenues for
fossil fuel subsidies instead of other development goals, such as spending on cash transfers,
education, infrastructure, or health.
Key words: Energy subsidy, developing economy, factor market, nontradable, distribution
JEL codes: H2, Q43, O25, F18.
Dept of Agricultural and Applied Economics, University of Wisconsin–Madison. Ian Coxhead: [email protected].
Corbett Grainger: [email protected].
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1. Introduction
Governments in developing countries subsidize fossil fuel consumption for a variety of reasons,
including lowering and stabilizing gasoline or heating prices and to promote competitiveness of
energy-intensive industries. In some cases these subsidies serve as a mechanism to redistribute a
country’s natural resource wealth, while for net importers fossil fuel subsidies come as a direct cost
to the local government. Supporters argue that fossil fuel subsidies help the poor and promote
economic growth.2 As such, proposals to relax subsidies encounter considerable resistance due to
concerns that higher fuel prices will undermine efforts to achieve economic growth and poverty
reduction. There is also an active debate as to whether removal of subsidies would have regressive
effects on income distribution. In this paper, we ask: what are the welfare costs and gains associated
with relaxing a fossil fuel subsidy, and how are these welfare changes distributed in a small, open
economy? We use an analytical model to generate predictions, which we bring to Vietnamese data to
examine which sectors and households would experience the greatest impacts. We use a CGE model
to gain greater insights into the channels and mechanisms through which fossil fuel subsidy reform
would impact poverty and income distribution. We find that the impacts on incomes through factor
markets are likely more important than distributional impacts due to expenditure patterns.
Characterizing the net incidence of an environmental regulation is difficult because there are
many channels through which the policy impacts households. On the cost side, consumer prices are
affected, but so too are incomes.3 Many studies of the incidence of taxes or subsidies focus on
expenditure-side effects, such as how price changes affect consumers of different income groups
(e.g., Grainger and Kolstad 2010). Some estimate demand elasticities by income group to pin down
the demand-side effects of policy (e.g. West and Williams 2004). To date, most studies of energy
subsidies focus on product price effects, which is only part of the overall impact. Because incomes
2 See the IEA, OECD and World Bank joint report on fossil-fuel subsidies for an overview of the reasons subsidies were
originally adopted.
3 Other channels include the benefits of the regulation, capitalization of the costs and benefits into land or asset prices,
and transitional costs (see Fullerton, 2011). In this paper, we do not consider differential effects of the policy on
transfers to different household groups.
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would also be critically impacted by energy taxes or subsidies, it is also important to consider how
policy changes would affect returns to capital and labor, and other primary factors.
Environmental taxes and subsidies could have important general equilibrium effects, but to
date most studies of such instruments in low-income economies use partial equilibrium methods
(Ziramba et al. 2009; Datta 2010; Sterner 2011). A notable exception is Fullerton and Heutel (2007),
who consider the general equilibrium incidence of an environmental tax in a closed economy.
However, the predictions from this type of model do not apply in small, highly trade-dependent
economies that make up most of the developing world. To our knowledge, there is as yet no formal
analytical model that takes all these aspects into account.
In this paper we use a dual-approach to begin construction of an analytical general
equilibrium model of a small open economy with heterogeneous industries and households,
international trade, and fiscal accounts. Our specific focus is on supply-side phenomena, since these
are relatively neglected in the literature. We examine the impacts of fuel subsidies (and by extension,
taxes) on factor returns, prices, and household income distribution. We then use our model’s
predictions to highlight the importance of factor market impacts in determining the incidence of
energy taxes or subsidies. The results suggest that relaxing or removing subsidies would be mildly
progressive, though overall poverty might increase as a result. Finally, we use a CGE model to help
understand how these welfare changes are distributed across individuals and sectors in Vietnam, a
representative small open economy with substantial fuel subsidies. Our work underscores the critical
importance of fiscal policy and revenue recycling that would accompany any energy policy reform;
there would be substantial savings associated with the elimination of fossil fuel subsidies, and how
these funds are used would have a significant impact on the overall distributional impacts of the
policy reform.
2. Background
Concerns surrounding climate change are widespread in Southeast Asia, and much of the
attention in the policy world has shifted from mitigation to adaptation. There is limited support
from international sources to help facilitate adaptation, and regional governments are fiscally
constrained. At the same time, fossil fuel subsidies create incentives for increased carbon intensity of
consumption and production, which exacerbate externalities associated with fossil fuel use.
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Externalities in this case include global climate change (IPCC, 2014), but fossil fuel combustion also
causes increased ambient air pollution, a critical concern in many developing countries (e.g.
Jayachandran, 2006).4
Southeast Asian countries will bear some of the burden of a changing climate, but the region
also makes non-negligible contributions to global greenhouse gas (GHG) emissions. Best known, of
course, is the conversion of forest and peat swamp in Indonesia for forestry and commercial
agriculture. However, emissions from combustion of fossil fuels are also significant. The IEA
estimates that energy-related greenhouse gas emissions from the Southeast Asia region currently
make up 3.7% of global emissions, and projects an increase to 6.1% by 2035 (IEA 2013).
Globally, eliminating fossil fuel subsidies would have a measurable impact on GHG
emissions. A multi-agency analysis issued in 2010 calculated that global energy demand would be cut
by 5% in 2020 if fossil fuel subsidies were completely phased out (IEA, OPEC, OECD and World
Bank 2010). Increasing attention has also been paid to the role of subsidies in promoting carbonintensive growth; removing subsidies would cut greenhouse gas emissions and remove the
distortionary economic effects associated with subsidizing fossil fuels.
Fossil fuel subsidies are particularly widespread in Southeast Asia. Regional subsidies on
fossil fuel usage are also large (Table 1), encouraging a relatively carbon-intensive form of growth.
Indonesia, Malaysia and Thailand are all among the world’s top 20 countries for energy subsidy rates
(IEA 2011). Nearly all other countries in that group are net energy exporters in the Middle East and
elsewhere. Fuel subsidies applied by these countries are also large in relation to global fossil fuel
demand (Burniaux and Chateau 2010); in 2012 the International Energy Agency estimated their total
value at $51bn.5 They are also large in relation to government expenditures (Table 1), and as such
Low fossil fuel prices also exacerbate congestion externalities. Moreover, government price supports for fossil fuels
crowds out spending on infrastructure.
5 http://www.eco-business.com/news/southeast-asia-must-remove-51-billion-fossil-fuel-subsidies-distort-energymarkets-iea-chief/, accessed 10 January 2014. This is roughly ten percent of the total value of petroleum subsidies to
consumers worldwide, according to IEA (World Energy Outlook 2013:
http://www.worldenergyoutlook.org/resources/energysubsidies/, accessed 2/11/2014)
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they crowd out other development policy initiatives such as investments in infrastructure, education,
or even social safety nets.
What is the case for retaining subsidies? First, the fear of lower rates of economic growth.
Second, concerns about regressive incidence makes reform politically difficult. Energy subsidies are
often popular among local populations, as they lead to lower fuel prices for the poor and help
energy-intensive industries remain competitive in international markets. In recent years, plans to
relax subsidy rates have been met with intense opposition in Indonesia, Thailand, Malaysia and
Vietnam.
Who gains from these measures, and who would stand to lose from policy reform? Globally,
subsidies are found to be inefficient ways to provide income protection or job opportunities to the
poor (del Granado et al. 2010). This claim is backed by the few available findings for Southeast
Asian economies (Yusuf 2008; Coxhead et al. 2013). These studies focus on income and expenditure
effects by household. However, the effects of subsidies, and their incidence as implicit taxes, extend
more deeply into factor markets, choice of technique, and fiscal efficiency. As we show in this paper,
theory predicts that fossil fuel subsidies would have far-reaching effects in an economy, affecting
poverty and distribution.
2.1 Welfare and distributional impacts of fossil fuel subsidies
Relaxing fossil fuel subsidies would lead to higher costs in energy-intensive sectors, which would
lower profits (and hence GDP) in the short run. The role of the government’s fiscal response would
play a critical role in both the impacts on poverty as well as income distribution. Fossil fuel subsidies
are an important consideration because they comprise a large share of government expenditures and
crowd out government spending on other development imperatives, such as education,
infrastructure and health. Moreover, because fossil fuel subsidies must be financed through taxes
elsewhere in the system, there are likely other distortions caused in order to raise government
revenues.
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The economic incidence of a tax differs from its direct incidence because net tax burden is
passed on through product and factor markets.6 The extent to which tax burden is passed forward
(to consumers) or backward (to factor owners) depends on behavioral and technological responses
to the tax—for example the elasticity of consumer demand for a product, or the substitutability of a
less highly taxed input for a more highly taxed one. In general, tax burden is distributed according to
relative magnitudes of relevant elasticities of demand or supply.
In a small open economy, any price increase that raises costs in these intermediate services
will be passed forward until it reaches industries that compete directly with foreign producers at
(largely) fixed world prices, at which point it will be reflected back onto domestic factors of
production. If domestic non-traded industries can pass tax burden forward in higher prices while
those competing at the border cannot, then in a small open economy a tax applied to a widely used
input such as energy has effects analogous to those of a real exchange rate appreciation. That is, it
reduces the relative profitability of producing tradable goods and services, and so diminishes the
country’s competitiveness in world markets. This point is absent from standard carbon tax models
since they omit or minimize the role of international trade (e.g. Fullerton and Heutel 2007; Metcalf
2008).7 The loss of tradable sector competitiveness opens (or widens) a trade deficit, with a matching
excess of domestic aggregate expenditure over income. For given international capital flows, to
eliminate these deficits requires a combination of expenditure reduction and a fall in domestic
relative prices so as to restore the equilibrium real exchange rate. Among tradable industries, higher
costs and lower profits cause tax burden to be passed back in the form of lower factor prices, and
ultimately to household incomes. These are likely to be important components of the adjustment to
a new equilibrium. Accordingly, the shifting incidence of the tax affects not only the structure of
The focus here is on cost-side incidence. Other studies focus on the benefit-side distributional impacts of
environmental policy, such as Grainger (2012), Banzhaf and Walsh (2010), or Bento (2013). Also see Fullerton (2011) or
Parry et al (2005) for an overview of distributional impacts of environmental policies.
7 Several models of carbon policy highlight the importance of international trade, though they generally do not focus on
distributional impacts (e.g. Böhringer et al, forthcoming). To our knowledge, there are no analytical models that address
the questions on which we focus here.
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production and trade, but also factor prices and employment, and ultimately, through this channel,
the distribution of household income and welfare.8
The case of a subsidy on energy use is almost symmetric—but importantly, not wholly so.
Cheaper energy inputs mean higher profitability for energy-intensive industries, and most likely
higher relative returns to factors used intensively in those industries. Tradable industries become
more competitive in world markets, and if energy cost reductions are passed on, prices of
nontradable goods and services fall (equivalent to a real depreciation). Yet to the extent that a subsidy
must be financed from the public budget, it limits opportunities to compensate losers. The problem
is worse when domestic energy prices are fixed in nominal terms, as is common in Southeast Asia,
since this is equivalent to a variable subsidy at a rate increasing in world prices. During global energy
price booms, the cost of defending a fixed domestic price can absorb a large share of the public
sector’s discretionary spending (Clements et al. 2013). Thus an energy subsidy raises a different set
of distributional and welfare issues, drawing attention to the tradeoff between job creation (caused
by cheaper energy) and diminished capacity for public spending on education, infrastructure and
antipoverty programs.
As discussed earlier, the literature on distributional impacts of fossil fuel subsidies focuses
mostly on consumer expenditures. On the expenditure side, poorer households are thought to
benefit disproportionately from energy subsidies, as energy-intensive goods constitute a large share
of their income. Even if this is the case, however, we also need to take into account the impacts on
factor prices in order to determine impacts on real incomes.
The foregoing discussion draws our attention to the roles played by factor intensity, energy
intensity, and price endogeneity—especially that associated with the distinction between traded and
nontraded goods in a small open economy—in the supply-side determination of tax incidence.
These three features emerge clearly in a general equilibrium analysis, as we show in the next section.
8 Some of the adverse distributional or welfare impacts of an environmental tax can be offset through revenue recycling
and other policy packages financed by tax revenues, an issue extensively explored in the Double Dividend literature (e.g.
Bovenberg and Goulder, 1996).
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3. An analytical model
3.1 Setup
In this section we develop a model of the incidence of an energy subsidy (or a tax) in a small open
economy. The assumptions we make are intended to capture the major relevant features of such an
economy without imposing a burdensome level of complexity. Our focus, as already noted, is on the
relatively neglected effects of an energy tax on responses by industries with different technologies
and facing different market conditions, and transmitted therefrom to factor markets and household
incomes. The basic model assumes two primary factors, two final goods, and an intermediate good
(energy). We assume that energy is not produced domestically (or in practice, that the input
requirements for domestic production are sufficiently small in relation to factor markets that they
can be ignored). We also assume that energy is not consumed as a final good, though this
assumption is easily relaxed. We assume constant returns to scale and competitive markets, and
ignore trade in factor services. With this structure, the initial analysis of an energy tax is analogous to
that in models of effective protection (Corden 1966).
To formalize the model we take a dual approach (Woodland 1982, Dixit and Norman 1980).
The economy is endowed with two inelastically supplied factors vi, i = 1,2, with prices wi. These are
used to produce two goods with quantities gj and domestic prices pj, j = 1,2. The third good (energy)
is purely imported, with quantity and price y3 and p3. This good is subject to a tax at rate t3, so p3 =
p3*(1 + t3), where p3* is the world market price in local currency terms. If t3 < 0, energy use is
subsidized.
Following Woodland (1982), the supply side of the economy can be summarized by an
aggregate revenue function g(p1, p2, p3, v), where v is the vector of factor endowment. This function is
increasing in p1, p2 and v, and decreasing in p3. It is homogeneous of degree 1 in p and convex in
output prices. The final good supply functions gj(p1, p2, p3, v) = ∂g(p1, p2, p3, v)/∂pj, j=1,2 are obtained
by Shephard’s lemma. Similarly, the gradient of the revenue function with respect to any factor
endowment gives the shadow price (or under the assumption of complete and competitive markets,
the market-clearing price) of that factor, so we have wi(p1, p2, p3, v) = ∂g(p1, p2, p3, v)/∂vi, i=1,2.
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3.2 Household incomes
With the focus on incidence, we begin by considering the incomes of households in a population of
size H. Each household owns a vector of factors vh, where ! h=1 v h = v (all factors are domestically
H
owned). The income of each household is m h ( p1 , p2 , p3 ,v h ) , defined by the identity:
m h ( p1 , p2 , p3 ,v h ) ! v h w( p1 , p2 , p3 ,v )+ s h ,
(1)
where s h ( p3 ) is a household’s income from transfers. To keep the focus on the supply side story, we
will ignore endogenous changes in transfers. Assume initially that both intermediate and final goods
prices are subject to change and that factor supplies are fixed. Taking the total differential of (1):
2
3
dm h = " " v ih
i=1 j=1
!w i
dp + ds h
! pj j
(2)
Converting variables to proportional change form (denoted by “hats” such that x̂ = dx / x for any
variable x):
m̂ h = ! ! ! ih "ij p̂ j + ! sh ŝ h ,
i
(3)
j
where each ! ih = v ih w i / m h is the share of factor i in the income of household h, and likewise
! sh = s h m h is the share of transfers. The latter share is positive in the case of an energy tax, or
negative in the case of a subsidy financed by levies on household income. Each elasticity !ij = !!wp /w
is
/p
i
j
i
j
the proportional change in factor i’s price with respect to a change in the price of good j.
Expression (3) establishes in general terms that when households are heterogeneous in terms
of factor endowments, any shock that results in a change in relative factor prices will have
differential effects on earned incomes. In the extreme, each household owns just one factor (e.g.
labor or capital) and its earned income rises or falls equiproportionately with that factor’s price.
As we develop the model further, a case of particular interest will be that in which some final
goods are traded with exogenous prices, and others are nontraded with endogenous prices. Suppose
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that the price of good 2 is fixed in world markets so that p̂2 = 0 , but that good 1 is nontraded and
therefore its price is endogenous. For this case, (3) can be rewritten as:
! p̂
$
m̂ h
ŝ h
,
= ' ! ih ###"i1 1 + "i 3 &&& + ! sh
&%
#" p̂3
p̂3
p̂3
i
(4)
The change in each household’s income due to an exogenous change in the energy price depends on
the impact of that price change on factor prices, both directly and also indirectly through the market
for the non-traded final good, and on each household’s share of income from each factor, plus any
change in net transfers. Of course, if both final goods are traded at fixed world prices, then the first
term within parentheses in (4) drops out and only direct effects and transfer changes remain.
3.3 Supply side: energy price and factor prices
Under the assumption of constant returns, each sectoral supply function is associated with a unit
cost function:
c j (w, p3 ) = p j
j = 1, 2 .
(5)
Derivatives of the unit cost function yield sector-level factor demands cij(w, p3) = ∂cj(w, p3)/∂wi and
demand for the intermediate good: c3j(w, p3) = ∂cj(w, p3)/∂p3. Assume again that both final goods’
prices are fixed in world markets. Taking total differentials of the cost functions and converting to
proportional change form as before, we have a system of equations for factor price changes that can
be compactly expressed in matrix notation as follows:
! ! !
# 11 21
#
# !12 !22
"
$ ! ŵ $ ! p̂ '! p̂
& # 1 & # 1 31 3
&#
&=#
& # ŵ 2 & # p̂2 '!32 p̂3
%"
% "
$
&
&
&
%
(6)
in which !ij is the cost share of input i used in sector j. Elements of the vector on the right hand side
of the equality are changes in sectoral value-added and can be written p̂ j !!3 j p̂3 = "ˆ j , consistent
with notation in the literature on effective protection.
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We can assume without loss of generality that sector 1 is intensive in the use of factor 1.
Then the determinant of the coefficient matrix in (6) is ! = !11!22 "!12!21 > 0 . Suppose also that
!31 > !32 — that is, sector 1 is more energy-intensive than sector 2. Then holding output prices
constant, we obtain the following results for the effects of an energy price rise on factor returns:
"!31 !21
ŵ1
= !"1 #
= !"1 #(!21!32 "!22!31 ) < 0
p̂3
"!32 !22
(7)
! "!31
ŵ 2
= !"1 # 11
= !"1 #(!12!31 "!11!32 )
p̂3
!12 "!32
(8)
The sign of ŵ 2 p̂3 cannot be established without more information, but we can affirm from (7) and
(8) that ( ŵ1 ! ŵ 2 ) p̂3 < 0 . Since p1 and p2 are fixed, a rise in the price of energy unambiguously
reduces the real return to the factor used intensively in the energy-intensive sector. The return to the
other factor may rise or fall in real terms, but will not fall relative to returns to the first factor.
Recall that energy is assumed to be imported (or, if produced domestically, to employ a
negligible share of factors in the economy). If the source of the change in p3 is a change in the
energy tax or subsidy holding world price constant, then p̂3 = !dt 3 , where ! = 1 (1+ t 3 ) . (This
formulation allows for zero initial tax rates, and has the advantage for comparative static purposes
that dt 3 is a direct measure of tax changes, e.g. if the tax rate rises from 5% to 10% then dt3 = 0.05.)
Thus (7) and (8) give us the basis for an initial welfare result, the partial equilibrium impact of the tax
on the functional distribution of income. For example, if sector 1 is both capital-intensive and
energy-intensive relative to sector 2, then a rise in the rate of a tax on energy is equivalent to
reducing sector 1’s effective protection. The real return on capital falls; the real wage may fall or rise
(and will certainly rise if sector 2 uses no energy input), but will never fall by as much as the return
to capital. By crude extrapolation, if rich households own capital and poor households own labor,
the energy tax causes a reduction in household income disparity. However, if real wages do fall then
greater equality may be accompanied by greater poverty.
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Equations (7) and (8) also provide a means to answer questions about the effects of energy
price shocks on gross output by sector, and on employment and other factor demands. Sectoral
output changes are found by substituting factor price changes into the final good supply functions
gj(p1, p2, p3, v). Thereafter, the effects of the shock on employment and factor demands can be found
by differentiation as before from the full employment conditions:
!
c (w, p3 )g j = v i
j ij
i = 1, 2; j = 1, 2
.
For brevity, however, we do not derive these results here.
3.4 Nontraded goods and tax incidence
What if the price of sector 1’s output is endogenous? We address this question rigorously below, but
to build intuition we can find a rough approximation by supposing that firms in sector 1 are able to
raise prices so as to pass on the entire energy cost increase to customers. Then we have one more
endogenous variable ( p̂1 ) and one additional condition:
p̂1 = !31 p̂3
(9)
such that !ˆ 1 = 0 . Using (9) in (6) and solving as before, we find that the predicted effects of an
energy price (or tax) increase are now quite different to those in (7) and (8):
ŵ1
= !"1!21!32 > 0 and
p̂3
ŵ 2
= "!"1!11!32 < 0 .
p̂3
(10)
When sector 1 producers can pass the entire tax burden on to their customers, the return to
the factor used intensively in sector 1 unambiguously rises relative to the energy price, and that to the
factor used intensively in sector 2 just as certainly falls – a near-complete reversal of the earlier result!
Moreover, from (9) we know that p̂1 p̂3 = !31 > 0 . When good 1’s price rises to compensate for
higher energy costs, the return to its intensively used factor rises relative to the energy price and may
even rise in real terms, while that to the other factor falls in real terms. If sector 1 is capital-intensive
and can pass on the tax burden, and if (as before) capital is owned by rich households and labor by
poor households, then the tax causes both an increase in income inequality and an unambiguous decline in the
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welfare of the poor. Clearly, market structure matters greatly for any prediction of the incidence of the
energy tax.9
For the case of an energy subsidy, all relative price results above are merely reversed.
However this partial equilibrium result leaves two important welfare questions unresolved. The first
is its effects on consumers, taking account not only of incomes (as in the thought experiments above)
but also of expenditure patterns and responsiveness to changes in relative prices and incomes. The
second question concerns how a subsidy is to be financed. Whereas a tax generates revenues that
can be used to (partially) compensate losers via changes in sh, a subsidy creates demands for new
revenues. Therefore the conclusions of this section about changes in absolute welfare—that is,
poverty—remain indeterminate. Moreover the means by which the subsidy is financed may have
additional distributional consequences.
To grasp the full effects of a fuel subsidy or tax requires a general equilibrium approach. We
undertake this with data from Vietnam, in the next section.
4. Reducing the subsidy: the case of Vietnam
4.1 Energy and energy subsidies in the Vietnamese economy
Vietnam imports nearly all its refined fuels. The Dung Quat refinery, thus far the only domestic
facility, was built to supply up to 30% of the domestic refined fuels market, but in practice typically
operates far below capacity. Pump prices are set by a regulatory agency. Rising world fuel prices
since the mid-2000s have caused the official stabilization fund for fuel importers and wholesalers to
run a persistent deficit. The magnitude of this deficit varies from year to year and with policy
changes (such as the abolition of import duties on gasoline, jet fuel, kerosene and diesel in early
9
Of course, industry supply and factor demand results will also change when one or more output prices are endogenous.
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2012). However, the International Energy Agency estimated the deficit associated with this subsidy
to be $4.1bn in 2011, equivalent to 3.4% of GDP.10
Vietnam also subsidizes the use of coal (a product of which it has historically been a net
exporter) to domestic buyers, primarily the electricity generation industry (Table 2). The pretax
subsidy on electricity is computed to be large: 2.4% of GDP, or 8.6% of government revenues
(Clements et al. 2013, Tables A.2 and A.3). In recent years the estimated total value of subsidies has
ranged from $1.2bn (2009) to $3.6bn (2008).11
What distributional and welfare effects would reducing these subsidies have in the
Vietnamese economy? Cheap energy fuels economic growth, and fossil fuels make up 54% of
Vietnam’s total energy supply, a share that is growing rapidly as the economy expands and
modernizes (UNDP 2012). In Vietnam, the largest consumer of fossil fuels is the power generation
industry.12 Electricity is cheaper in Vietnam, at 7c/kWh, than in Thailand (12c/kWh), Singapore
(17c/kWh) or the ASEAN average (10c/kWh) (UNDP 2012). But an energy subsidy, like all
product-specific distortions, is unlikely to be a first-best means to further economic growth.
Vietnam’s most energy-intensive industries (the biggest beneficiaries from subsidies) are
mainly producers of import-competing goods (such as heavy machinery and transport equipment) or
of non-traded goods such as domestic road, rail and water transport. The country’s export industries
are mostly not capital-intensive, nor are they energy-intensive by comparison with other industry
sectors. The differences can be seen in summary data based on the Vietnam social accounting matrix
for 2007 (the most recent version available). Across industries, capital and energy inputs are
correlated whereas energy and labor inputs are not. A regression of energy share in total costs on
labor and capital shares bears this out. In log-linear form, with t-statistics in parentheses:
10 In 2013, the government allocated $141m in support of the stabilization fund; however, this allotment was almost
entirely exhausted in the first 6 months of the year. http://www.thanhniennews.com/2010/pages/20130714-vietnamministry-says-fund-to-fuel-price-balance-almost-used-up.aspx, accessed 10 January 2014.
11 http://vccinews.com/news_detail.asp?news_id=26058, accessed 14 January 2014.
12 Not surprisingly, the power generation industry is also the country’s largest source of GHG emissions (UNDP 2012).
14
ln(energyshare ) = 0.286+ 0.551* ln(capitalshare )+ 0.032 * ln(laborshare ), R 2 = 0.189, N = 60
( 0.511)
( 3.90***)
( 0.25 )
The capital-energy correlation has considerable economic significance, as Vietnam has comparative
advantage in labor-intensive products; nearly all capital-intensive activities are import-competing, or
are non-traded service sectors such as transport.
Figure 1 plots industries in the Vietnam SAM by their cost shares of energy and capital.
There is an overall positive correlation, as the above regression estimates reveal. More subtly, most
of the exportable industries have energy and capital intensity values below the median values of the
data, whereas nearly all non-traded industries are above median values – and in fact, most are within
the top quartile of both energy and capital intensity.13 Transport industries in particular are (not
surprisingly) among the most energy and capital intensive in the data. Many import-competing
industries occupy an intermediate zone of energy and capital-intensity. Though highly aggregated,
these data nonetheless suggest that ceteris paribus, the largest proportional gains from fuel subsidies
accrue to industries that are less labor-intensive than most, and are more likely than most to have
prices set not in global markets, but within the domestic economy.
Figure 1 about here
Attention to the differential income effects of fuel subsidies is important in low and middleincome economies. Poorer households derive the largest share of their income from labor. The
largest industries, by share of employment, are highly labor-intensive—and with globalization, these
are also the industries that are expanding most rapidly, in line with comparative advantage.
Therefore policies that impose implicit taxes on these industries—as fuel subsidies do, by conferring
cost advantages on other industries—also limit labor productivity in the aggregate, and reduce
earnings to the factor of production owned most intensively, and relied on most heavily, by the poor.
Once again, Vietnamese data bear out the broad claim. Among Vietnamese households, the
lower three quintiles by income derive roughly half their earnings from low and medium skill labor
13
Government and other public service sectors such as health and education have been excluded from this plot.
15
(Figure 2). That share is much lower (about 30%) for the upper two quintiles. Therefore any taxes,
subsidies or other policies that lower the relative return to labor of low or medium skills have
proportionately large effects on the welfare of poor households, and are likely also to widen income
inequality.
Figure 2 about here
Taken together, the foregoing cost share and income source data make it clear that from the
income side, the distributional burden of fuel subsidies in a country like Vietnam is likely to be
borne most heavily by less well-off households and individuals. This is in addition to the much
better-documented evidence of regressive distributional effects from the expenditure side (Yusuf
2008; Kojima 2013). The Vietnamese data also point to regressive expenditure effects; households in
the lowest quintile of the expenditure distribution devote 5% of total expenditures to energy, while
those in the highest quintiles spend 7-9% (Table 3).
Table 3 about here
These data suggest that reducing the fossil fuel subsidy in Vietnam and other similar countries will
not be regressive. However, it may reduce the incomes of the poor.
4.2. Numerical experiments with an applied general equilibrium model
The model and database
To evaluate the effects of changes in Vietnam’s fossil fuel subsidies we use an applied
general equilibrium (AGE) model of the Vietnamese economy. Such models combine baseline data
from national accounts and other sources about the activities of firms, households, enterprises and
government with theory-based specifications of markets, factor supplies, trade balances and other
16
constraints, and the assumed behavior of foreign partners in trade and investment. They provide an
internally consistent account of economic activity, at least in the realm of the real economy.14
We seek to observe the effects of an exogenous reduction in fuel subsidies on prices,
production and factor demand, and through these channels the impact on factor prices. Since
factors are ultimately owned by households, changes in wages and returns on non-labor factors alter
household income. Because households are heterogeneous in terms of asset ownership, income, and
expenditure we can also measure effects on income distribution and poverty. The model we use is
based on a template by Lofgren et al. (2002), modified to fit Vietnamese data. The following is a
very brief summary of its main features.15
The dimensions of the model are determined by its primary data source, the 2007 Vietnam
Social Accounting Matrix (SAM) (Arndt et al. 2010). There are 63 sectors, each producing a single
commodity. There are three primary factors, land, labor, and capital. Land is used only in agriculture
and some natural resource sectors. Capital has two components: part of the stock is mobile among
sectors, while another part is specific to each sector. Labor is divided into six categories by location
(urban/rural) and skill (low/medium/high). The SAM contains 20 household types. There are urban
and rural households; these are further subdivided by primary income source (farm/nonfarm), and
within each subcategory the SAM reports separate data by quintile of the expenditure distribution.
The model “theory” dictates responses to a shock imposed by the modeler. In each industry,
factor demands are derived in the usual way from the profit-maximizing choices of a representative
firm. The model has a nested constant elasticity of substitution (CES) factor demand structure. At
the top level is composite factor demand, an aggregate of the demands for labor, capital and land.
Labor, in turn, is aggregated by CES from demands for labor of each type by location and skill.
Similarly, intermediate inputs used in each industry are aggregated using CES into a single composite
14 For recent surveys of AGE Models applied to the Vietnamese economy, see Coxhead et al. 2010; and Abbott et al.
2009.
15 For more detail see Coxhead et al. 2010, and see Coxhead et al. 2013 for a related application and discussion.
17
input.16 Finally, the model allows for two-way trade in goods via the Armington assumption,
although the SAM also contains some pure non-traded goods such as domestic trade and
transportation, public administration, and personal services.
Households earn income from ownership of factors, and may receive transfers from
government or enterprises as well as remittances from the rest of the world. Households are
heterogeneous in terms of factor income shares (Figure 1). In the national living standards
measurement survey from which the SAM was constructed, 44% of workers had primary or lower
education; 33% had completed lower secondary school; 19% upper secondary school, and just 4.2%
had some form of tertiary education. Labor earnings are by far the most important single income
source, and already noted, poorer households earn relatively higher shares of income from lowskilled labor. Policy shocks that operate through the labor market will thus have differential effects
on household income.
Households consume goods and services, both those produced domestically and imported
from abroad. Consumption is assumed to take a Stone-Geary form, in which expenditure is
allocated first to satisfy minimum subsistence consumption levels, and then to income-elastic
discretionary expenditures. The SAM provides household-specific budget shares for each type of
good consumed. Since these shares form the weights of a consumer price index, each household has
a unique cost of living measure, used to deflate nominal into real income.
Vietnam remains a small player in global trade, and the model reflects this by assuming fixed
world prices of imports and highly elastic global demand for exports. These assumptions contrast
with those usually made in environmental tax models for the US and other large industrialized
economies, in which domestic markets typically dominate trade. In most of those models, prices of
goods and services are all endogenous and final demands are inelastic, hence virtually all tax burden
is shifted to domestic consumers.
16 This structure allows for interfuel substitution in response to relative energy price changes. The possibility of
substitution among fuel types is an important feature for any study of the effects of a tax in the long run. However, a
suitable model for that purpose must allow for capital investment and depreciation, whereas our model is focused on a
shorter-run incidence analysis.
18
Closure and solution method
In order to conduct policy experiments we must make assumptions about the way in which the
economy responds to a shock, by choosing which variables and policy settings are exogenously fixed
and which may endogenously adjust. We assume investment-driven savings and a fixed current
account balance with zero net financial flows to and from the rest of the world. The latter
assumption requires that the balance of trade must remain constant. This eliminates unaccounted
intertemporal borrowing, forcing all adjustment into the single period of the simulation. The
nominal exchange rate of VND for USD (assumed fixed) is the model’s numéraire price. Therefore,
when a shock applied to the model creates pressures for an imbalance on the trade account,
domestic spending and (where applicable) factor employment must adjust to restore external balance.
In each closure we assume that half the capital stock for each sector is fixed, while the other
half is mobile (it can be reallocated across sectors, either within agriculture or non-agricultural
sectors).17 We also assume that labor of a given skill level is mobile across sectors and locations—
that is, we assume costless rural-urban migration within the equilibrium timeframe of the model.
It is conventional in models of this kind to assume that labor is supplied inelastically with
respect to price. This assumption (Case A in the simulations below), however, is potentially
important to predictions of welfare and distributional outcomes, especially when there is reason to
believe that labor supply varies by characteristics or across households. The earnings of rural
households in developing countries are derived from a combination of labor and land. When wages
rise relative to land returns there is an inducement to migration from farming to laboring—and vice
versa, relative wage declines may cause a return to farming. To capture this we present a variant of
the model closure (Case B) in which labor, especially rural and low-skill labor, is supplied elastically
with respect to wages. The elasticity values used are shown in Table 4.18
Table 4 about here
17 The Vietnam SAM provides no guidance on fixed and mobile capital, and our 50-50 division is merely an ad hoc
assumption. However, robustness checks using 25-75 and 72-25 splits show that the results are not very sensitive to the
exact percentage allocations.
18 For a more detailed discussion of this labor supply structure, see Coxhead et al. 2013.
19
Finally, we show two alternative uses of the additional government revenues. In cases A and
B, they are saved. In Case C, with flexible labor supply, they are recycled to consumers in the form
of proportionally higher transfers to households. The pattern that these transfers take reflects that
in the SAM. It is not an anti-poverty measure as such, although lower-income rural households are
among the bigger gainers.
The model is implemented using GEMPACK software (Harrison and Pearson, 1996) and
relies heavily on code from the well-known ORANI-G model (Horridge 2005). Most variables are
solved in percentage change form. However, variables whose values can move through zero—for
example, savings or budget balances—are expressed in changes in levels (billions of Vietnamese
dong) rather than in percentage change form.
4.3 Fossil fuel subsidy simulation
Vietnamese law mandates fixed but adjustable purchaser prices of coal, gasoline and other fossil
fuels. The difference between these prices and their world market counterparts, evaluated at an
appropriate point in the marketing chain, provides a measure of the initial subsidy rate. In our policy
experiment we approximate this complex system by setting the tariff-adjusted import prices of fossil
fuels to be exogenous. These are the base import prices of the model, so their levels determine the
levels of fuel prices throughout the marketing chain, up to final consumers. Because world prices are
also exogenous, the margin between the world price and the base import price—that is, the tariff
applied to imports—must be made endogenous in order for the domestic price to be adjusted. The
subsidy reduction experiment then consists of imposing an exogenous 25% increase in base fuel
prices. The corresponding increase in tariff revenues per unit of fuel imported mimics the effect of a
lower subsidy rate on the government’s budget.
To save space, we report and discuss only the most relevant results. Table 5 shows
macroeconomic impacts; Table 6 shows changes in output, price and fixed capital returns by sector,
and Table 7 shows changes in nominal income, price indices and real expenditures for households.
Complete simulation results as well as model code and data are available in an online appendix.
Effects on fuel prices
20
As noted, an increase in the (exogenous) base import price, holding rates of sales and other taxes
and marketing margins constant, is passed forward along the marketing chain. The change in the
price faced by final consumers is an aggregate of the change in the base import price and the price
charged by domestic producers at the factory gate. However, since Vietnam produces so little of its
own fuel, the latter price has virtually no influence in this model. A 25% rise in the base price raises
the consumer price by almost exactly the same amount.
Table 5 shows the main macroeconomic effects of a rise in the price of fuel. In case A, with total
supply of each labor type fixed, real GDP declines slightly, by 1%, and real absorption by -2.2%.
The consumer price index rises by 0.8%. Government tax revenues rise substantially, by 7.8%, or
about $US***m at $US1=VND17,000). In case B, with total employment adjustable at the margin,
jobs are lost and so cuts in real GDP and real absorption are larger (-1.6% and -2.7%). Case C is
similar, except that government spending rises to maintain budget balance with fixed savings; this
reduces the fall in absorption and drives the CPI higher, at 1.3%. We discuss factor market effects
shown in this table later.
Table 5 about here
Among individual industries, the range of impacts is wide, and industry-level variations in
production and prices illustrate the means by which the incidence of the taxes is shifted (Table 6).
The most fuel-intensive industries experience the greatest cost increases, of course. Among these,
transport industries are the most severely affected since gasoline and other fuels account for
between 29-33% of their total costs.19 The prices they charge to users rise much faster than inflation,
by 3-5% (road and other transport), and about 3% (air transport). Higher transport costs mean more
costly production and distribution (domestic and export margins), and so raise costs throughout the
economy. Fisheries, with fuel making up 45% of total costs, raises its prices by 8-8.5%, depending
on the closure. Other fuel-intensive industries also experience large cost increases but because they
compete with imports, cannot raise prices. In fact, in Case C only 10 sector prices rise by more than
19
These and other baseline data reported in the text are calculated from the 2007 SAM; see Arndt et al. 2010.
21
1% despite the overall CPI rising by 1.3%, and the average price change among manufacturing
sectors, other than fuels, is close to zero.
Table 6 about here
Despite higher input costs, not all sectors contract. Of those that expand, all but two (rice
and flour milling) are in the top 1/3 of sectors by labor-intensity (Figure 3). The others are the big
light manufacturing sectors (wood products, furniture, garments, footwear, and leather products) as
well as large export-oriented farming sectors (coffee and rubber). The top one-third of industries by
labor intensity accounts for 74% of total employment of low and medium skill labor. The expanding
industries, being tradable, do not raise output prices—in fact there is no correspondence between
sectors that expand and those that raise prices. Rather, output growth is due primarily to lower labor
costs, which outweigh the negative effects of higher fuel costs.
Figure 3 about here
These results provide numerical confirmation of the insight developed earlier in this paper
that some sectors experience much greater adjustment pressure than others. In general, energyintensive activities are most heavily affected, as expected. But these include some sectors which,
because they supply domestic markets virtually free from international competition, have discretion
to raise prices, thereby passing part of their input cost increase forward to other industries and final
consumers. Transport services and fisheries exemplify this property.
Other sectors produce goods for which output prices are set in the world market. Among
these are several that are large employers of low or medium-skilled labor. They are not necessarily
energy-intensive in production, but are affected by energy prices in other ways—most especially
through their use of domestic transport services to source inputs and to move outputs to markets
and ports. For some (such as processed seafood, which buys its inputs from the fisheries sector),
fuel costs are passed on through higher input prices. For others, contractions in other sectors lower
net input costs, allowing them to expand.
We see the consequence of this adjustment in factor price changes (Table 5). With the largest
contractions taking place among highly fuel-intensive industries, and given that industries with high
fuel costs shares in general also have high capital and human capital intensity, wages for the most
22
highly skilled workers fall furthest, by -4.7% when labor supply is assumed fixed. Wages for medium
and low skilled workers fall by -3.2% and -3.5% respectively when total supply is fixed. When supply
is elastic the wage declines are much smaller (-0.5% and -1.7% in Case C), but earnings are reduced
by diminished employment. Adding the wage and employment changes gives declines of -2.3% for
low-skill labor and -3.1% for medium skill labor in Case B, and -2% and -2.8% respectively when
revenues are redistributed in Case C.
Different rates of change in earnings by skill are important because they indicate the
differential shifting of tax burden via factor markets. In terms of labor income, reducing the subsidy
is noticeably progressive across the skill distribution, even when government transfers remain fixed,
in Case B. Returns to land, another factor of particular importance to poor households, fall, but
never by as much as unskilled labor earnings. To complete the factor earnings picture, changes in
sector-specific capital returns (not shown) are positive for the labor-intensive industries that expand,
mildly negative (-0.4% in Case A, -2.5% in Case C) for the paddy rice sector, which is a primary
income source for most poor rural households, and moderately to strongly negative for most
manufacturing sectors. Once again, fisheries and fish processing stand out. Fixed capital returns in
these sectors fall much further than most—the former because of the direct impact of higher fuel
costs, the latter because those cost increases are passed forward in higher fisheries output prices.
These industries aside, the factor market impacts of lower fuel subsidies are generally progressive.
Finally, what of the household incidence of the fuel subsidy reform? Table 7 confirms two claims
made earlier in this paper: that poorer rural households gain in relative terms (i.e., lose by less) from
a lower subsidy, and that most of the change in their welfare is due not to higher consumer prices,
but to changed factor earnings (for brevity, we omit Case A results in this table). The CPI increases
of lower-quintile groups in rural areas are much smaller than the economy-wide average, a result that
replicates findings from other expenditure-based studies of the incidence of fossil fuel taxes,
discussed earlier. These differences are swamped, however, by changes in nominal (factor) incomes,
as shown in the first two columns. In the lowest two quintiles, rural households (who make up over
90% of this group) have negative income shocks that are smaller than any other household group.
Table 7 about here
23
Despite being progressive, the lower subsidy still reduces total income in the short run, so in
Case B the real expenditures of all households decline. Severe poverty in Vietnam corresponds
roughly to the lowest quintile, while near-poverty includes the second quintile. Case C presumes that
all additional government revenue is returned as higher transfers to households. The sixth column
of Table 7 reveals that after transfers are raised, rural households in Quintile 1 experience zero net
change in real expenditures. These households represent 93.5% of poor households in Vietnam.
Rural households in Quintile 2 (88% of the near-poor) experience losses of 0.8% in real expenditure.
So even without targeting, or other measures directed at poverty alleviation, the worst poverty
effects of lower overall income can be virtually eliminated simply by increasing the rate of
government-household transfers. Any more targeted measure is clearly capable, in principle, of being
both distributionally progressive and not increasing poverty.
4.4 Discussion and implications of the Vietnam simulation
Our results are best thought of as indicative but not conclusive predictions of real-world outcomes.
However, they highlight and quantify some important but indirect channels of tax incidence, and
because of this it is our view that they merit careful consideration at policy level. One conclusion is
clear: there is no real threat that the reduction of a fuel subsidy is regressive. However, real GDP
does fall: a wide range of industries are negatively affected, and many households are made worse
off in real terms. An initial reaction, then, might be to regard the reduced subsidy as a threat to
continued economic growth and development. In the longer run, however, an economy responds to
higher energy prices in a variety of ways not captured in our model. These include interfuel
substitution, technical progress, and improvements in efficiency, as well as ongoing changes in fiscal
and macroeconomic policy.20 There are other gains as well: these include reduced emissions and
20
A computable general equilibrium study reported in UNDP (2012) evaluates the costs and benefits of reducing
Vietnam’s current energy subsidies and imposing a carbon tax. Although the model predicts a short-run decline in GDP,
it also finds that in the longer run as firms and households make adjustments in response to relative price changes, GDP
growth accelerates—with 1% GDP growth due to subsidy removal, and 1.5% growth due to subsidy removal plus
carbon tax.
24
associated lower costs of pollution abatement or mitigation at local level. Studies in other developing
countries indicate that particulate matter and gaseous emissions from industries and vehicles have
large and costly impacts on human health, as well as reducing the productivity of labor. If reducing
the fuel subsidy rate lowers emissions growth, then it also deliver benefits in the form of a more
healthy and productive workforce and lower rates of depreciation of some forms of capital.
Second, we have assumed that the net government revenue gain from a reduced subsidy is
either saved or simply returned to existing transfer recipients. When the government budget
constraint binds, spending on fuel subsidies crowds out other potentially growth-enhancing
expenditures, such as on infrastructure, education or health. Depending on income multipliers
associated with each of these (or indeed, with other fiscal policy responses such as lowering income
taxes or raising transfers to households), the net change in aggregate income and absorption could
be quite different. This is a point made for environmental tax reform in the double dividend
literature (for example, Bovenberg and Goulder 1996).
Finally, lower subsidies move the economy onto a less carbon-intensive growth path. Even
though the impact on global emissions may be small, there is nevertheless a case to be made for
compensation from the international community. Some uses of such hypothetical compensation
would also increase overall income, reduce poverty, or further amend distributional inequality.
However, existing international institutions and agreements provide only very limited tools for such
compensation to be calculated, let alone paid (Coxhead et al. 2013).
5. Conclusions and agenda for further research
There is an emerging consensus that energy subsidies in developing countries do more harm than
good. The majority of the evidence in support of this claim comes either from CGE studies that
focus on aggregate measures such as GDP or growth, or from household level studies that focus
primarily on the pattern of energy expenditures. To date, however, there has been relatively little
analytical or empirical focus on factor markets as channels for transmission of energy policy effects.
25
In this paper we seek to fill an important gap by addressing the supply-side issue of the incidence of
energy policy measures on household incomes via factor markets.
A simple model (section 3) highlights the main mechanisms and parameters in play, and
brings into focus the importance, for analytical models, of specifying trade relationships. Most
current models of energy tax incidence downplay the role of trade, but the reality of developing
countries is that they comprise a mix of sectors ranging from fully tradable to fully non-tradable. We
make it clear that the distinction is vital to predictions of factor price changes in response to a policy
reform.
While there is much more to be done (and done much more rigorously), an experiment
using a CGE model with Vietnamese data lends support to the claim that the factor market effects
of energy policy interventions have welfare and distributional impacts of economically meaningful
magnitudes. The results also suggest that relaxing a fuel subsidy might be progressive rather than
regressive, and that with the right set of tools, might even be pro-poor in the sense of causing at
least a zero net increase in poverty.
We now live in an era of diminished multilateral action on climate change. Governments of
developing and emerging market economies are rightly concerned at the negative consequences of
unilateral environmental measures, especially since some of the benefits from their actions will spill
over to others through reduced greenhouse gas emission. This paper lays the groundwork for more
detailed research. with a specific initial agenda: before launching costly environmental programs, it
may be economically, environmentally, and even politically beneficial to remove existing distortions
in favor of fossil fuel overconsumption.
26
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29
Table 1: Regional subsidies on fossil fuel usage, 2011
Country
Subsidy rate
Value ($bn)
Share of GDP (%)
Indonesia
23.2%
21.3
2.5
Thailand
20.0%
10.3
3.0
Malaysia
18.4%
7.2
2.6
Vietnam
15.5%
4.1
3.4
Philippines
4.3%
1.5
0.7
Source: World energy subsidy database http://www.iea.org/subsidy/index.html, and
http://www.iisd.org/gsi/sites/default/files/ffs_gsibali_meetingreport.pdf, accessed 2 December 2013. Rates are
calculated for 2009-11, when world petroleum prices were about 50% of levels prior to the 2008 global economic crisis.
Table 2: Vietnam: subsidies on fossil fuel usage, 2011
Petroleum
Electricity
Natural Gas
Coal
Pre-tax
0.00
2.37
0.13
n.a.
Post-tax
0.00
8.59
0.47
n.a.
Pre-tax
0.83
2.64
0.78
1.60
Post-tax
3.00
9.54
2.81
5.78
As percent of GDP
As percent of gov’t revenues
Note: pre-tax measures the extent of a subsidy measured by the difference between purchasers’
prices and [estimated] supply costs. Post-tax includes calculation of the extent to which the tax
system is inefficient, for example when a subsidy is financed by higher rate of a consumption tax,
30
and when environmental externalities are taken into account. Petroleum subsidies were close to zero
in 2011, but have been positive in most other years, depending on the global import price. Source:
Clements et al. 2013, Tables A.2–A.5).
Table 3: Household spending on energy (share of total expenditures), 2007
Poorest 20%
Quintile 2
Quintile 3
Quintile
Richest 20%
Urban farm
0.059
0.079
0.084
0.085
0.058
Urban non-farm
0.075
0.089
0.108
0.116
0.085
Rural farm
0.049
0.057
0.070
0.073
0.059
Rural non-farm
0.058
0.077
0.096
0.110
0.082
Quintile average
(pop’n weights)
0.050
0.058
0.079
0.088
0.071
Source: Authors’ computations from Vietnam SAM 2007 (Arndt et al. 2010).
Table 4. Assumed values of labor supply elasticities
Labor type
Rural Urban
Unskilled (primary education)
1.0
0.5
Medium-skilled (secondary ed.) 0.5
0.1
High-skilled (tertiary ed.)
0.1
0.1
31
Table 5. Fuel subsidy reduction (25%): macroeconomic impacts
A: Fixed labor
supply
B: Elastic labor
supply
C. Elastic labor
supply, transfers
Real GDP, % change
-1.04
-1.61
-1.55
Real absorption, % change
-2.17
-2.67
-1.39
CPI, % change
0.77
0.82
1.31
Government tax revenues, % change
7.81
7.20
8.01
0.02
-0.61
10.19
Low-skill labor wage
-3.49
-0.86
-0.48
Medium-skill labor wage
-3.17
-2.03
-1.71
High-skill labor wage
-4.74
-4.91
-3.63
Agricultural land return
-0.57
-1.72
-2.06
Mobile capital return
0.77
0.82
1.31
Low-skill labor
0.00
-1.44
-1.53
Medium-skill labor
0.00
-1.04
-1.10
High-skill labor
0.00
-0.52
-0.44
Variables
Government tax revenues, change
(VND mn)
Gov’t expenditures, % change
Factor prices, % change:
Employment, % change
32
Note: * denotes exogenously zero. For complete simulation results see online appendix.
33
Table 6. Fuel subsidy reduction (25%): effects on output, prices and fixed factor returns (%
changes)
Sector
Paddy rice
Sugarcane
Other annual crops
Rubber
Coffee
Tea leaf
Other perennial crops
Cows and pigs
Poultry
Other livestock
Forestry
Fishery
Aquaculture
Coal mining
Crude oil
Natural gas
Other mining
Meat processing
Fish processing
Vegetable and fruit processing
Oils and fats processing
Dairy
Rice husking
Other flours
Other food processing
Non-alcoholic beverages
Alcoholic beverages
Tobacco processing
Yarn and other fibres
Textiles
Clothing
Leather products
Output Quantity
Case A Case B Case C
0.01 -0.63
-1.10
-2.39 -3.01
-2.42
-0.79 -1.47
-1.25
2.06
1.68
1.07
4.15
3.84
3.07
-2.60 -3.17
-3.29
-1.07 -1.64
-1.26
-0.97 -1.56
-0.65
-1.84 -2.42
-1.11
-2.20 -2.72
-1.07
-0.30 -1.59
-1.92
-9.58 -10.42 -10.51
-2.96 -3.66
-4.16
-7.46 -7.98
-8.82
-2.71 -2.75
-3.02
-2.61 -3.20
-2.81
-5.25 -5.90
-6.38
-0.73 -1.40
-1.02
-10.47 -11.49 -13.20
-0.40 -1.05
-1.99
-3.83 -4.23
-3.54
-2.41 -2.86
-2.42
4.14
3.46
1.05
1.87
1.21
-0.11
-2.51 -3.11
-2.45
-1.12 -1.81
-2.09
-1.14 -1.80
-1.91
-1.04 -1.52
-0.62
-0.37 -0.94
-2.04
-1.16 -1.58
-2.54
3.12
2.28
0.77
0.95
0.23
-0.88
Domestic Price
Case A Case A Case C
-0.45
-0.37
-0.25
-0.48
-0.41
-0.27
-0.33
-0.28
-0.18
-0.30
-0.29
-0.24
-0.29
-0.28
-0.20
-0.71
-0.68
-0.56
-0.62
-0.61
-0.48
-0.92
-0.83
-0.04
-0.86
-0.77
-0.04
-0.89
-0.81
-0.04
-0.87
-0.40
-0.09
7.90
8.27
8.57
-0.99
-0.95
-0.64
1.63
1.69
2.17
-1.25
-1.30
-1.20
0.00
0.00
0.00
1.36
1.48
1.72
-0.81
-0.68
0.09
0.74
0.82
1.04
-0.14
-0.08
0.23
0.15
0.16
0.26
-0.11
-0.10
0.34
-0.93
-0.85
-0.25
-0.76
-0.70
-0.28
-0.13
-0.06
0.27
-0.26
-0.17
0.32
-0.22
-0.14
0.33
-0.39
-0.35
-0.01
0.31
0.31
0.41
0.06
0.07
0.10
-0.06
-0.04
0.01
-0.05
-0.03
0.03
34
Table 6 (continued)
Footwear
Wood products
Paper products
Printing products
Petroleum products
Other chemicals
Non-metallic minerals
Cement
Basic metals
Metal products
Machinery and equipment
Eletrical machinery
Vehicles and transport equipment
Furniture
Other manufacturing
Electricity and gas distribution
Water distribution and utilities
Construction
Retail and wholesale trade
Hotels and catering
Road transport
Air transport
Other transport
Communications
Business services
Financial services
Real estate
Public administration
Education
Health
Other services
Output Quantity
Case A
Case B
Case A
2.21
1.37
0.04
1.65
-0.11
-1.33
-2.86
-3.44
-3.46
-2.64
-3.09
-2.03
-62.54
-62.69
-63.25
-3.62
-4.19
-4.58
-3.40
-3.90
-4.25
-2.00
-2.48
-2.46
-3.08
-3.47
-3.92
-1.54
-2.03
-2.58
-0.97
-1.39
-1.71
-2.02
-2.53
-1.88
-1.16
-1.47
-1.93
1.95
0.51
-0.45
-5.13
-5.93
-6.99
-2.86
-3.37
-2.74
-4.39
-4.94
-4.30
-1.13
-1.70
-1.63
-2.60
-3.23
-3.17
-0.95
-1.69
-1.11
-7.78
-8.33
-8.03
-22.53
-22.86
-22.58
-8.76
-9.28
-8.91
-1.43
-1.76
-1.33
-1.92
-2.38
-2.08
-0.84
-1.05
-0.70
-1.85
-2.30
-0.86
-1.16
-1.73
-1.66
0.03
-0.45
-0.57
-1.07
-1.56
-0.58
-1.94
-2.50
-1.30
Note: Complete tables of simulation results available from authors.
Domestic Price
Case B
Case A
Case B
-0.06
-0.04
0.03
-0.28
-0.07
0.12
0.14
0.16
0.36
-0.06
-0.06
0.43
24.98
24.98
24.98
0.25
0.27
0.40
0.77
0.82
1.12
0.58
0.64
1.03
0.15
0.15
0.19
0.00
0.02
0.10
-0.04
-0.04
0.03
-0.12
-0.09
0.24
-0.01
0.00
0.05
-0.61
-0.41
0.05
0.15
0.19
0.27
-1.11
-1.24
-0.40
-1.19
-1.25
-0.47
0.50
0.74
1.09
-1.34
-1.04
-0.46
-1.05
-0.89
-0.23
5.49
5.60
6.04
2.95
2.95
3.12
5.06
5.07
5.37
-1.41
-1.52
-0.65
-0.88
-0.91
-0.21
-0.70
-0.76
-0.30
-2.55
-2.65
-1.32
-2.12
-2.18
-1.29
-2.01
-2.12
-1.34
-1.55
-1.58
-0.91
-1.20
-1.10
-0.15
35
Table 7. Income, consumer prices and expenditures by quintile and household type (%
change) – Cases B and C only
Quintile
Rural
and HH type
(%)
Case B
Case C
Case B
Case C
Case B
Case C
Quintile 1
93.5
-2.42
0.72
0.36
0.82
-2.76
-0.10
Urban
-3.10
-0.81
0.50
0.96
-3.59
-1.75
Rural
-2.37
0.82
0.35
0.81
-2.71
0.01
-2.71
0.12
0.62
1.10
-3.31
-0.96
Urban
-3.55
-1.38
0.88
1.35
-4.40
-2.70
Rural
-2.59
0.33
0.59
1.06
-3.16
-0.73
-2.95
-0.06
0.96
1.43
-3.88
-1.47
Urban
-3.54
-0.95
1.14
1.61
-4.62
-2.51
Rural
-2.79
0.19
0.91
1.39
-3.66
-1.18
-3.13
0.03
1.10
1.58
-4.18
-1.53
Urban
-3.65
-0.76
1.35
1.84
-4.93
-2.55
Rural
-2.86
0.45
0.97
1.45
-3.79
-0.99
-3.26
-0.08
0.68
1.21
-3.91
-1.27
Urban
-3.64
-0.41
0.77
1.27
-4.37
-1.66
Rural
-2.88
0.25
0.60
1.14
-3.46
-0.88
-2.90
0.14
0.74
1.23
-3.61
-1.07
Quintile 2
Quintile 3
Quintile 4
Quintile 5
All Households
88.1
77.8
65.5
50.4
74.9
Nominal income
Source: VHLSS and computations using 2007 SAM.
Price index
Real expenditure
36
0
1
lenergyshare
2
3
4
Vietnam: energy and capital cost shares by sector
0
1
2
lcapitalshare
Exportables
Importables
3
4
Nontradables
Transport
Data in logs of percentage shares. Lines drawn at median values. Source: 2007 SAM
Figure 1. Vietnam: distribution of sectors by cost shares of energy and capital
37
Figure 2. Vietnam: sources of household income (percent), by type and quintile.
Source: authors’ computations from Vietnam SAM 2007 (Arndt et al. 2010).