Xem mẫu
- ECONOMIC RESEARCH
Just how quickly has the Vietnamese capital stock grown
over the past decade?
James A. Giesecke and
Tran Hoang Nhi
ABSTRACT
We use a detailed growth accounting method to estimate the annual growth rate of the aggregate
Vietnamese capital stock over the period 1996-2005. Our results show that the rate was likely to
have been in the vicinity of 7-8 % per annum. This is approximately 2 percentage points lower
than estimates appearing in some previous studies.
Key words: Vietnamese capital growth rate, growth accounting, TFP growth.
1. Introduction A number of such studies have been undertaken
for Vietnam (Tran Tho Dat 2004, Tang Van Khien
The Solow growth accounting equation
(equation 1) is often used to estimate 2005, Le Viet Anh 2006). A difficulty with applying
movements in total factor productivity (TFP). (1) to the Vietnamese case is that, to date, the
General Statistics Office (GSO) has not published
gdpRFC = S Ll + S K k + S N n + a (1)
estimates of k. Equation (1) thus presents the growth
In such exercises, official statistical data on: accounting researcher with one equation, but two
(a) percentage rates of change in real GDP at unknowns. To solve this problem, researchers studying
factor cost ( gdpRFC ), employment (l), capital stocks (k) the Vietnamese case must supply their own k
and land (n); and, estimates. These estimates tend to be high - in the
(b)shares of payments to labour (SL), vicinity of 10 per cent1. In this paper, we argue that
capital (SK) and land (SN) in GDP at factor cost are these estimates may be too high, perhaps by as much
used to calculate movements in TFP (a). as 2-3 percentage points per annum.
James A. Giesecke and Tran Hoang Nhi, Centre of Policy Studies, Monash University, Australia.
Volume 2 - Number 2 - 2008 Vietnam Economic management review 31
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- VEMR ECONOMIC RESEARCH Just how quickly has the Vietnamese capital stock grown over the past decade?
In this paper we provide annual estimates of Ti is the rate of indirect taxation on activity
the rate of growth of the aggregate Vietnamese i; and,
capital stock over the period 1996-2005, using a Pi is the price of activity i.
detailed growth accounting framework. Our
approach takes into account not only changes in An example of activity i might be sales of
aggregate inputs of labour and land, but also the imported five-seat-automobiles to households.
effects of movements of these factors between According to the tax code in 2005, such a transaction
sectors of the economy. Since GSO publishes data attracts tariff at the rate at 100%, special consumption
for real gross domestic production (GDP) at market tax (SCT) at the rate of 80% and value added tax
prices, but not real GDP at factor cost, we must also (VAT) at the rate of 10%. Dixon and Rimmer
account for movements in indirect taxes. We argue (2002, pp. 187-188 and 230-232) show that if the
that the growth rate of the aggregate capital stock levels variables in (3) are interpreted as Divisia
can only be in the vicinity of 10% if the rate of TFP indexes, then (3) and its components have the
growth is implausibly low (in the vicinity of 0.0 to percentage change forms:
0.5 % per annum). If, as we suspect, annual TFP
GDP MP ( pGDP
MP
+ gdpRMP ) = GDP FC ( pGDP
FC
+ gdpRFC ) + å i X i PT
i ( xi + pi + ti )
(4)
growth has been about 1.5 % per annum, then the
average capital growth rate over the past decade has
MP
pGDP = SGDPMP pGDP + SGDPMP
GDPFC FC ITAX
å i SITAX
i
( pi + ti ) (5)
been about 7.5% per annum. gdpRMP = SGDPMP
GDPFC
.gdpRFC + SGDP
ITAX
.åi SITAX
i
xi (6)
2. Methodology where pGDP MP
is the percentage change in the
MP
We begin with equation (2), the definition of GDP at market prices deflator; gdpR is the
nominal GDP at market prices: percentage change in real GDP at market
prices; pGDP is the percentage change in the GDP
FC
GDP MP = GDP FC + ITAX (2) FC
at factor cost deflator; gdpR is the percentage change
where: in real GDP at factor cost; xi is the percentage
change in the quantity of activity i that is subject to
GDP MP is nominal GDP at market prices;
indirect taxation; pi is the percentage change in the
GDP FC is nominal GDP at factor cost; and price of activity i; ti is the percentage change in the
ITAX is nominal collections of indirect tax rate of indirect taxation of activity i).
revenue.
For growth accounting, (6) is the key equation.
We re-write (2) in terms of real variables and We focus first on the indirect tax term, SGDP .å i SITAX xi.
ITAX i
price indices as follows: Movements in this term contribute to real GDP
MP
PGDP .GDPRMP = PGDP
FC
.GDPRFC + å i X i PT
i i
(3) movements via allocative efficiency effects arising
from the wedge that indirect taxes drive between
where: values in use and values in supply for the activities
GDPRMP is real GDP at market prices; i that are indirectly taxed. We do not have data on
MP
PGDP
the billions of transactions that constitute i.
is the GDP at market prices deflator;
Instead, we simplify by defining three broad sets of
FC
PGDP is the GDP at factor cost deflator; activities that are the major bases for Vietnamese
Xi is the quantity of activity i that is subject indirect taxation, and a residual. The three broad
to indirect taxation; activities are: (1) real private consumption, which
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is subject to Special Consumption Tax (SCT) and to use quantity weights. Movements in l have been
much of the incidence of Value Added Tax (VAT); defined as the percentage change in the number of
(2) imports, which are subject to tariffs; and (3) persons. This underestimates the growth in
natural resource extraction (mainly crude oil and effective Vietnamese employment, by failing to
gas), which is subject to natural resource tax. account for movement of labour from low wage to
high wage activities. Movements in k are either
While this list represents only four taxes in
assumed, or estimated via the perpetual inventory
over a dozen types of Vietnamese indirect taxation,
method. However the perpetual inventory method
they constitute a large share of total indirect
implicitly weights movements in sector-specific
taxation, starting at 63% of indirect tax revenue in
capital using asset value weights. This might
1996, rising to 96% by 2005 (see Table 3).
over-estimate growth in the (rental weighted)
We define the percentage changes in the indirect capital stock, if Vietnamese investment is used
tax bases as follows: (1) for VAT and SCT, cR, the inefficiently or directed towards sectors with
percentage change in real private consumption; (2) relatively low rates of return2.
for tariff revenue, mR, the percentage change The capital growth rate in any particular year
in import volumes; (3) for natural resource can be calculated based on (8) as:
tax, xRMining , the percentage change in mining output;
1 é gdpRMP - SGDPMP
GDPFC L
.SGDPFC l - SGDPMP .SGDPFC n - SGDPMP
GDPFC N GDPFC
.a ù
and (4) for all other indirect taxes, gdpRMP , the k =[ ]. ê ú (9)
SGDPMP .SGDPFC êë -SGDPMP éë S ITAX cR + SITAX mR + S ITAX xR + S ITAX gdpR ùû úû
GDPFC K ITAX VAT + SCT TARF NRT Mining Other MP
percentage change in real GDP.
On this basis, we assume that:
Our aim is o calculate k. To do this using (9),
we need values for the year-on-year movements in
åS i
i ITAX i
x = SVAT
ITAX
+ SCT
cR + SITAX
TARF
mR + S ITAX xR + S ITAX
NRT Mining Other
gdpRMP (7)
the percentage change variables and annual values
Substituting (1) and (7) into (6) provides: for the shares on the right-hand-side of the
equation. We explain in Section 3 our calculations
gdp = S
MP
R
GDPFC
GDPMP éë S L
GDPFC l +S K
GDPFC k+S N
GDPFC n + a ùû + of these variables and shares.
(8)
ITAX
SGDPMP éë S VAT
ITAX
+ SCT
cR + S ITAX
TARF
mR + S ITAX xR + S ITAX
NRT Mining Other
gdp RMP ùû
3. Data
In equation (8), the percentage change
3.1 Factor payment shares in GDP at
variables l, k and n, have precise meanings. In
factor cost ( S ,S ,S )
L K N
GDPFC GDPFC GDPFC
particular, l is wage-bill weighted percentage
changes in employment categories, k is rental Table 1 reports factor payment shares in GDP
at factor cost for the year 1996-2005. As we
weighted percentage changes in types of physical
explain in Part 1 of the Appendix, we calculate
capital, and n is rental weighted percentage
factor shares for 1996, 2000, 2003, and 2005 using
changes in parcels of land. Unfortunately, in
IO and SAM data (GSO 1999, 2003, Jensen and
implementing equations like (8) for Vietnamese Tarp 2007, Ministry of Finance (MOF) 2007), and
growth accounting exercises, researchers have not GTAP 6.0 database (Dimaranan 2006). Values for
always defined these variables using the appropriate intervening years are interpolated assuming linear
factor payment weights. Rather, they have tended growth.
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Table 1: Factor payment shares in GDP at factor cost, 1996-2005
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Average
1. Labour (S L
GDPFC ) 0.56 0.56 0.55 0.55 0.55 0.55 0.54 0.54 0.54 0.54 0.55
2. Capital (S K
GDPFC ) 0.32 0.32 0.33 0.33 0.34 0.34 0.34 0.34 0.35 0.35 0.34
3. Land ( S N
GDPFC ) 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.11 0.11 0.12
4. Total 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
Source: Authors' calculations from GSO (1999, 2003), Jensen and Tarp (2007), MOF (2007) and GTAP
6.0 (Dimaranan 2006).
3.2 Factor payment and indirect the ratio of IMF estimates of Vietnamese indirect
tax shares in GDP at market prices tax collections to our estimate of GDP at factor cost
(S and S
GDPFC
GDPMP ) ITAX
GDPMP
(IMF 2003, 2006, 2007). Then we calculate the shares
of GDP at factor cost and indirect tax collections in
GSO does not publish income side data for GDP GDP at market prices. Table 2 reports our share
GDPFC
at market prices. Hence we must estimate SGDPMP and estimates. More details on our approach are provided
SITAX
GDPMP using other sources. We do this by first calculating in Part 2, Appendix.
Table 2: Income-side GDP shares
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Average
1. Share of GDPFC in 0.85 0.87 0.87 0.88 0.89 0.88 0.88 0.87 0.87 0.87 0.87
GDPMP ( S ) GDPFC
GDPMP
2. Share of ITAX in 0.15 0.13 0.13 0.12 0.11 0.12 0.12 0.13 0.13 0.13 0.13
GDPMP ( S ITAX
GDPMP )
3. Total 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
Source: Authors' calculations from GSO (1999, 2003), Jensen and Tarp (2007), MOF (2007), GTAP 6.0
(Dimaranan 2006), and IMF (2003, 2006, 2007).
3.3. Indirect tax shares VAT and SCT ( SITAX ), tariffs ( S ITAX ), natural resource
VAT +SCT TARF
tax ( SITAX
NRT
) and other indirect taxes (S ITAX
Other
). We calculate
Table 3 reports our estimates of the shares of these shares from IMF government revenue data
aggregate indirect tax collections represented by (IMF 2003, 2006, 2007).
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Table 3: Shares of important taxes in total indirect tax revenues at current prices
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Average
1. VAT(a) 0.25 0.30 0.27 0.36 0.35 0.34 0.39 0.42 0.41 0.41 0.35
(S )
VAT
ITAX
2. Special consumption 0.08 0.12 0.13 0.09 0.11 0.11 0.11 0.12 0.13 0.14 0.11
tax (S ) SCT
ITAX
3. Natural Resource tax 0.08 0.09 0.07 0.10 0.15 0.15 0.13 0.14 0.18 0.20 0.13
(S )
NRT
ITAX
4. Tariff 0.23 0.25 0.25 0.24 0.22 0.25 0.24 0.24 0.21 0.19 0.23
(S )
TARF
ITAX
5. Other taxes 0.37 0.25 0.28 0.22 0.17 0.15 0.13 0.09 0.06 0.07 0.18
(S )
Other
ITAX
Total 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
Notes: (a): Turnover tax prior to 1999.
Source: Calculated from IMF (2003, 2006, 2007).
3.4. Real GDP at market prices, real output at constant prices (GSO 2007). We calculate
private consumption, import volumes, the annual percentage changes in these series,
mining output ( gdp , cR, mR, and x )
MP Mining MP Mining
R R allowing us to evaluate gdpR , cR, mR, and xR .
Values for these variables are reported in rows
The GSO publishes annual estimates of real
1 - 4 respectively of Table 4.
GDP at market prices, real private consumption,
aggregate imports at constant prices, and mining
Table 4: Real GDP, private consumption, import volume and output
of mining sector at market prices
(percentage change from previous year)
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Average
1. Real GDP 9.3 8.2 5.8 4.8 6.8 6.9 7.1 7.3 7.8 8.4 7.23
(gdp )
MP
R
2. Real private 9.1 5.9 4.5 2.6 3.1 4.5 7.6 8.0 7.1 7.3 5.94
consumption (cR)
3. Import volume 15.8 16.8 31.6 22.0 31.7 13.3 -3.8 -0.8 14.9 47.0 18.0
(mR)
4. Output of mining 14.7 14.7 15.3 16.4 11.2 6.4 4.2 8.0 14.4 2.4 10.7
sector (x ) Mining
R
5.Weighted average 11.1 9.9 12.4 9.0 11.2 7.3 4.3 5.9 10.1 13.9 9.6
indirect taxes
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3.5. Economy-wide growth in labour l = å j S Ljl j (10)
and land inputs (l and n)
GSO does not publish estimates of growth in
where SLj is the share of payments to labour in
wage-bill-weighted employment (l) and rental-
weighted land use (n). We calculate l and n using industry j in economy-wide payments to labour,
data from GSO (2007), Jensen and Tarp (2007) and and lj is the percentage change in employment in
GTAP 6.0 (Dimaranan 2006). Our estimates for l industry j. Hence, to calculate l, we require
and n are reported in row 11, Table 6 and row 9,
estimates of SLj and lj. Tables 5 and 6 report our
Table 8. We explain our method for calculating
estimates. To calculate SLj we use industry data on
these values below.
payments to labour obtained from GSO (1999,
3.5.1. Wage-bill-weighted employment growth (l)
Equation (10) defines l, the percentage change in 2003), Jensen and Tarp (2007), MOF (2007) and
wagebill-weighted employment growth: GTAP 6.0 (Dimaranan 2006).
Table 5: Wage-bills shares, by industry ( S ) L
j
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Average
1. Agriculture and 0.29 0.27 0.27 0.25 0.23 0.23 0.22 0.21 0.20 0.20 0.24
forestry
2. Fishing 0.03 0.03 0.03 0.03 0.03 0.04 0.04 0.04 0.04 0.04 0.03
3. Industry 0.19 0.20 0.21 0.22 0.25 0.27 0.29 0.31 0.31 0.31 0.26
4. Construction 0.06 0.06 0.06 0.05 0.05 0.06 0.06 0.06 0.06 0.07 0.06
5. Trade 0.10 0.09 0.09 0.08 0.11 0.10 0.09 0.08 0.08 0.08 0.09
6. Hotels, restaurants 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.04 0.03
7. Transport, 0.03 0.03 0.03 0.03 0.04 0.04 0.04 0.04 0.04 0.04 0.04
communications
8. Culture, health, 0.08 0.08 0.08 0.08 0.09 0.09 0.09 0.09 0.09 0.09 0.08
education
9. Other services 0.19 0.20 0.21 0.23 0.16 0.15 0.15 0.15 0.15 0.15 0.18
10. Total 1.00 0.99 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
Source: Authors' calculations from GSO (1999, 2003), Jensen and Tarp (2007), MOF (2007) and GTAP
6.0 (Dimaranan 2006).
We elaborate on our use of these data in Note that l is substantially higher than the simple
calculating SLj in Part 1(b) of the Appendix. Values growth rate in total number of persons employed
for lj are calculated from GSO employment data (row 10 Table 6). This reflects inter-sectoral
for nine broad sectors (GSO 2005, 2007). Row 11 movements of labour, particularly movements
of Table 6 reports our estimates for l using data from low-paid industries such as agriculture, to
from Table 5 and 6 to implement equation (10). high-paid industries such as manufacturing.
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Table 6: Number of employed persons (percentage change on previous year) (lj)
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Average
1. Agriculture and 1.3 1.2 1.1 1.0 0.8 0.2 -0.9 -0.2 -0.4 -0.7 0.3
forestry
2. Fishing 10.1 9.5 7.9 9.4 9.1 9.3 18.4 3.4 5.9 5.5 8.8
3. Industry 3.5 3.4 3.4 3.5 3.4 6.7 7.0 9.3 6.2 8.5 5.5
4. Construction 3.4 3.5 3.5 3.4 3.3 19.0 18.2 10.6 13.9 3.9 8.1
5. Trade 7.0 7.0 7.1 7.0 7.0 5.6 5.4 5.9 5.2 3.5 6.0
6. Hotels, restaurants 5.0 5.4 5.4 5.5 5.5 3.8 2.2 3.4 2.1 1.6 4.0
7. Transport, communications 4.1 4.1 4.1 4.1 3.9 5.4 0.3 1.0 0.7 -4.5 2.3
8. Culture, health, education 2.1 2.1 2.0 2.0 2.0 4.6 5.7 5.8 4.6 4.1 3.5
9. Other services 3.1 3.2 3.4 3.5 3.6 6.4 9.0 9.2 10.5 20.1 7.1
10. Total employment 2.2 2.2 2.1 2.1 2.0 2.6 2.5 2.7 2.5 2.3 2.3
11. Wagebill weighted 3.3 3.2 3.2 3.2 3.3 5.5 6.0 6.1 5.4 6.4 4.6
employment (l)
Source: Employment data in rows 1 - 10 are from GSO (2005, 2007). We calculate the weighted change
in employment at row 11 by computing shares from rows 1-9 and multiplying by corresponding percentage
changes in rows 1 - 9 of Table 5 (see text for details).
3.5.2 Rental-weighted growth of land use industry j in economy-wide payments to land, and
areas (n) nj is the percentage change in land use in industry
Equation (11) defines n, the percentage j. Clearly, to calculate n, we require estimates
change in rental-weighted land-use: of S Nj and nj. Tables 7 and 8 report our estimates.
To calculate S Nj we use industry data on payments
n = å j S Nj n j (11) to land calculated from GSO (1999, 2003), Jensen
and Tarp (2007), MOF (2007) and GTAP 6.0
where S Nj is the share of payments to land in (Dimaranan 2006).
Table 7: Shares in land rentals, by industry ( S ) j
N
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Average
1. Paddy 0.51 0.51 0.52 0.52 0.52 0.49 0.47 0.46 0.46 0.47 0.49
2. Raw rubber 0.01 0.01 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02
3. Coffee bean 0.02 0.02 0.02 0.03 0.03 0.03 0.03 0.02 0.02 0.02 0.02
4. Sugar cane 0.03 0.03 0.03 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02
5. Other crops 0.20 0.22 0.23 0.25 0.26 0.26 0.25 0.24 0.24 0.25 0.24
6. Forest 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02
7. Fish farming 0.21 0.18 0.16 0.15 0.13 0.15 0.19 0.22 0.21 0.20 0.18
8. Total 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
Source: Authors' calculations from GSO (1999, 2003), Jensen and Tarp (2007), MOF (2007) and GTAP
6.0 (Dimaranan 2006).
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We elaborate on our use of these data in and 8 to implement equation (11). On average, the
calculating S Nj in Parts 1(a) and 1(c) of the growth in n is slightly higher than the simple
Appendix. Values for nj are calculated from GSO average growth rate in total area used in agriculture
data on the area of land used in agriculture, forestry (row 8 Table 8). This reflects above-average
and fishing (GSO 2005, 2007). Row 9 of Table 8 growth in fish farming and below-average growth
reports our estimates for n using data from Table 7 in paddy.
Table 8: Land used in agriculture, forestry and fisheries (percentage change from previous year)(nj)
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Average
1. Paddy 3.5 1.4 3.7 4.0 0.2 -2.3 0.2 -0.7 -0.1 -1.6 0.8
2. Raw rubber -8.7 36.7 9.9 3.4 4.3 0.9 3.1 2.8 3.0 6.3 5.7
3. Coffee bean 36.4 33.9 8.9 28.9 17.6 0.6 -7.6 -2.3 -2.6 0.1 10.3
4. Sugar cane 5.4 8.4 10.1 21.6 -12.2 -3.8 10.1 -2.1 -8.7 -6.9 1.7
5. Other crops 4.5 2.9 2.1 3.2 7.3 1.1 8.4 5.2 5.5 4.6 4.5
6. Forest -3.2 9.3 -6.0 10.3 -14.6 -2.9 -0.4 -4.6 1.7 -3.9 -1.7
7. Fish farming 9.9 1.1 4.0 0.0 22.4 17.7 5.6 8.8 6.1 3.5 7.7
8. Total 4.2 3.5 3.6 4.8 3.1 -0.2 2.7 1.5 1.8 0.9 2.6
9. Rental-weighted land 5.6 3.2 3.6 4.4 4.9 1.8 3.3 2.8 2.4 1.0 3.3
areas (n)
Source: Land rental data in rows 1 - 7 are from GSO (2005, 2007). We calculate the rent-weighted
change in land area at row 9 by computing shares from rows 1-7 and multiplying by corresponding
percentage changes in rows 1 - 7 of Table 6 (see text for details).
3.6. Growth in total factor productivity at state enterprise reform, public administration
(a) reform, private sector development, further
removal of barriers to international trade, and
Recall that to calculate k, an independent
encouragement of foreign direct investment. These
estimate of a is required. We take our preferred
developments have improved the functioning of
estimate for a (1.5 per cent) by placing it at the
market mechanisms, increased domestic competition
low-end of the range of findings from previous and competition for international markets, and
studies (1.7 - 3.4 %). increased productive and allocative efficiency.
Many studies on Vietnam's economic High levels of FDI are also likely to have
progress over the last decade have attributed the contributed to productivity growth via diffusion of
economy's strong growth to high rates of technical foreign technology and management practices.
progress (see, for example, Van Arkadie and Previous studies have estimated Vietnam's
Mallon 2003, Tran Nam Binh and Pham Do Chi economy-wide TFP growth over the past decade to
2003, Tran Tho Dat 2004, Tran Hoang Nhi 2007, have been in the range of 1.7 to 3.4% per annum
Vu Quoc Ngu 2002). This is consistent with the (Tran Tho Dat 2004, Le Viet Anh 2006, Tran
strong focus of policy on microeconomic reform. Hoang Nhi 2007). Sectoral studies have also
Over the past decade, such policies have been directed estimated high rates of TFP growth. For example,
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Tang Van Khien (2005) estimated annual TFP right-hand-side terms of Equation (9). Row 6 of
growth in manufacturing to be 1.6% over 1996- Table 9 reports the resulting estimates for k. The
2003. Vu Quoc Ngu (2002) annual TFP growth in path of these estimates appears plausible: in 1996
state owned enterprises to be 5.37% over the and 1997 we see high capital growth rates, reflecting
period 1990-1998. For our calculations, we adopt a high levels of FDI; over 1998 and 1999 we see low
conservative value of 1.5 % as our preferred esti- levels of capital growth as this FDI dried up in the
mate for TFP growth. However we also provide
face of the Asian financial crisis; consistent with
Table 10 to show the sensitivity of our k estimate to
observations that Vietnam recovered quickly from
different values for a.
this crisis3, a relatively stable capital growth rate of
approximately 7% per annum is established from
4. Estimated results 2000 to 2005. The annual average capital growth
Table 9 brings together our estimates for the rate over the whole period is 7.5%.
Table 9: Right-hand-side components of equation (9)
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Average
1. Real GDP ( gdp ) MP
R 9.34 8.15 5.76 4.77 6.79 6.89 7.08 7.34 7.79 8.44 7.23
2. Wage-weighted 3.28 3.20 3.20 3.24 3.35 5.52 6.02 6.12 5.42 6.44 4.57
employment (l)
3. Rental-weighted land 5.56 3.19 3.60 4.39 4.91 1.78 3.29 2.75 2.45 1.05 3.29
use (n)
4. Weighted indirect taxes 11.1 9.94 12.4 8.98 11.2 7.31 4.33 5.85 10.1 13.9 9.49
( S .å S x )
ITAX
GDP i
i
ITAX i
5. Total factor 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50 1.50
productivity (a)
6. Share of GDPFC in 0.85 0.87 0.87 0.88 0.89 0.88 0.88 0.87 0.87 0.87 0.87
GDPMP ( S ) GDPFC
GDPMP
7. Labour share in 0.56 0.56 0.55 0.55 0.55 0.55 0.54 0.54 0.54 0.54 0.55
GDPFC ( S ) L
GDPFC
8. Capital share in 0.32 0.32 0.33 0.33 0.34 0.34 0.34 0.34 0.35 0.35 0.34
GDPFC (S ) K
GDPFC
9. Land share in GDPFC 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.11 0.11 0.12
(S )
N
GDPFC
10. Hence, growth rate 15.8 13.1 3.29 1.10 6.86 6.26 6.81 7.09 7.84 7.12 7.45
of capital stock (k)
Since there is uncertainty about the value of Table 10 shows that the high capital growth rates
TFP growth, we undertake sensitivity analysis that have appeared in some previous studies, that is
around the value of a. Table 10 reports the results of annual capital growth in the range of 9-11%, imply
applying equation (9) using alternative values for a. rates of TFP growth that are implausibly low.
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Table 10: Sensitivity analysis: Capital growth rates under alternative TFP growth assumptions
TFP growth rate (a) 0.0 0.5 1.0 1.5 1.7 2.0 2.5
Annual average (1996-2005) 11.9 10.4 8.9 7.5 6.9 6.0 4.5
capital growth rate (k)
Source: GSO (2005, 2007).
Our capital growth estimates are approximately Our paper suggests that these estimates may have
2-3 percentage points lower than those in some been too high, and that the true figure is
previous studies . Our estimates are lower for two probably in the vicinity of 7.5 % for the period
main reasons: 1996-2005.
1. Application of the growth accounting The absence of official capital stock data is a
framework requires inputs of wage-bill-weighted result of the more general limitation that the GSO
movements in employment, not total hours. The does not publish yearly supply-side estimates of
former has grown more quickly than the latter as the components of real GDP at market prices. As
labour has moved from agriculture to manufacturing. we discussed in Sections 3 and in the Appendix,
2. We take into account changes in indirect this also presented challenges for our calculations,
taxes. As evident from rows 1 and 4 of Table 9, real which we overcame by going to other data sources
indirect taxes have grown at a faster rate than real such as Jensen and Tarp (2007), IMF (2003, 2006,
GDP at market prices for most years of the study 2007) and GTAP (Dimaranan 2006). Future GSO
period. Hence, for most years, growth in real GDP estimates of the components of income-side GDP
at factor cost has been lower than growth in real will be very valuable. This would greatly assist
GDP at market prices. This presents an issue when researchers interested in studying supply-side structural
researchers use GSO estimates of growth in real features of Vietnam's economic development.
GDP at market prices to inform values for real
GDP at factor cost ( gdpRFC ) in growth accounting Appendixes
applications of equation (1).
1. Calculation of factor payments
5. Conclusion for the period 1996-2005
Growth accounting equations like (1) are There are four main sources of Vietnamese
typically used to calculate TFP growth from sectoral-level factor payment data for the study
published data on such variables as growth in real period. They include three sets of input-output (IO)
GDP, employment and capital stocks. A difficulty data for the years 1996, 2000, 2003 and 2005 (GSO
in applying such an equation to Vietnam is the 1999, 2003, MOF 2007), and a social accounting
absence of official data on growth in capital stocks. matrix (SAM) for 2003 (Jensen and Tarp 2007). Of
Hence researchers applying (1) to estimate TFP these, only the SAM has payment data for all three
have needed to produce independent estimates for k. factors of production: labour, capital and land.
These estimates have been in the range of 8.5 - 11 %. The input-output tables contain only data on
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- Just how quickly has the Vietnamese capital stock grown over the past decade? ECONOMIC RESEARCH VEMR
payments to labour and capital. We explain below industries in the available IO tables provides the
how we (a) calculate factor payment shares in the economy-wide factor payments data for the years
years for which we have data (1996, 2000, 2003 and 1996, 2000, 2003 and 2005, which we highlight in
2005) and (b) estimate factor shares for the Table A1. We explain in Parts 1(b) and 1(c) below
intervening years. how we calculate factor payments for the intervening
years.
1 (a). Calculating factor payments in
1996, 2000, 2003 and 2005 1(b). Sectoral shares in economy-wide
Our first task is to calculate payments to land.
payments to labour
Such payments are not explicitly recognised in the From the IO data for 1996, 2000, 2003 and
1996, 2000 and 2005 databases. 2005 we know sector-specific payments to labour.
The main users of "land" (which we shall We reproduce these in Table A2, highlighting the
define to include agricultural land, water surface years for which we have independent estimates. Our
and returns to sub-soil assets) are agriculture, aim is to calculate sector-specific wagebills for the
forestry, fishing, and mining. In the initial IO data, remaining years (1997-1999, 2001, 2002, and
returns to land are spread among payments to 2004). We do this in four steps. First, we estimate
labour and capital. Hence, factor payments in these sector-specific wage rates for 1996, 2000, 2003
sectors need to be reallocated to all three factors: and 2005 by dividing the known sectoral wage-bills
labour, capital and land. for these years by the known sectoral employment
numbers for these years (GSO 2005, 2007).
SAM 2003 has data for land rentals in
Second, we calculate year-on-year percentage
agricultural and forestry sectors. We use these 2003
changes in sector-specific wage rates for 1997-
factor payment shares to split total factor payment
1999, 2001, 2002 and 2004 by assuming that
in the IO data for 1996, 2000 and 2005. Overall,
sector-specific wage rates grow smoothly between
land accounts for about 28% of factor payment in
years for which we have wage-bill and employment
agricultural and forestry sectors.
data (1997-1999, 2001, 2002, and 2004). Third, we
However, SAM 2003 does not contain calculate year-on-year percentage changes in
estimates for the rental values of water rights used sectoral employment for all years between 1996
in fish farming, or returns to owners of natural and 2005 using employment data from GSO (2005)
resource concessions in mining industries. For and GSO (2007). Finally, we calculate sector-specific
these industries, we use factor payment shares wage-bills for 1997-1999, 2001, 2002 and 2004 by
from the GTAP 6.0 database for Vietnam . Overall, applying our estimates of year-on-year percentage
natural resources account for about 41 percent of changes in employment and wage rates to the know
total factor payments in the fishery and mining wagebill data for 1996, 2000, 2003 and 2005. Table
sectors. A1 reports the resulting sectoral wage-bills. The
Combining our newly created factor sectoral shares in economy-wide labour payments
payments data for agriculture, forestry, fishing, and reported in Table 5 in the main body of the paper
mining with the factor payments data for all other are calculated from Table A1.
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Table A1: Wage bills, by industry (VND billion, current prices)
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
1. Agriculture and 37,292 40,278 43,480 46,868 48,708 51,855 54,955 58,629 67,142 76,637
forestry
2. Fishing 3,987 4,254 4,471 4,766 6,966 8,148 10,305 11,388 12,646 13,995
3. Industry 25,325 29,634 34,664 40,584 52,661 63,275 74,267 89,043 102,199 119,736
4. Construction 8,131 8,593 9,080 9,588 11,212 13,341 15,109 16,016 21,360 25,997
5. Trade 12,926 13,536 14,185 14,852 22,326 21,779 21,476 21,274 26,419 32,278
6. Hotels, 3,340 3,984 4,753 5,673 6,840 7,164 7,508 7,963 10,718 14,359
restaurants
7. Transport, 4,365 4,738 5,144 5,581 7,645 8,434 9,289 10,299 13,151 15,933
communications
8. Culture, health, 9,951 11,370 12,986 14,832 18,104 19,969 22,249 24,803 28,946 33,625
education
9. Other services 25,301 29,789 35,115 41,463 32,851 36,004 39,566 43,582 48,568 58,824
10. Total 130,616 146,176 163,879 184,208 207,312 229,969 254,724 282,997 331,149 391,384
Note: Highlighted columns show the values for which there are data. The remaining columns are
extrapolated by the authors.
Source: Authors' calculations from GSO (1999, 2003,. 2005, 2007), Jensen and Tarp (2007), MOF
(2007) and GTAP 6.0 (Dimaranan 2006).
1(c). Primary factor payments for the outlined in Part 1(b) above. Payments to capital
years 1997-1999, 2001, 2002 and 2004 and land for the years for which we do not have
Table A2 presents our factor payment independent data sources (1997, 1998, 1999, 2001,
estimates. As discussed above, data for the years 2002 and 2004) are calculated by assuming smooth
1996, 2000, 2003 and 2005 come either directly or growth rates between the years for which we have
indirectly from independent IO sources (GSO 1999,
factor payment estimates. We use the values in
2003, MOF 2007, Jensen and Tarp 2007,
Dimaranan 2006). Wage-bill data for the Table A2 to calculate the factor shares appearing in
intervening years come from our calculations Table 1.
Table A2: Factor payment at current prices (VND billion)
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
1. Labour 130,616 146,176 163,879 184,208 207,312 229,969 254,724 282,997 331,149 391,384
2. Capital 73,526 84,352 96,773 111,022 127,370 142,737 159,959 179,259 212,278 251,379
3. Land 28,312 31,580 35,226 39,292 43,828 48,705 54,123 60,145 68,764 78,618
4. GDPFC 232,453 262,109 295,878 334,522 378,510 421,411 468,807 522,402 612,191 721,381
Notes: Highlighted columns show the values for which there are data. The remaining columns are
extrapolated by the authors.
Source: Authors' calculations from GSO (1999, 2003), Jensen and Tarp (2007), MOF (2007) and GTAP
6.0 (Dimaranan 2006).
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2. Indirect tax shares and GDP 3. See, for example, Fforde (2001), Van Arkadie and Mallon
(2003).
income-side shares
4. Indeed, if the high TFP rates used in the previous studies are
Data on the collections of major indirect taxes taken into account, the difference between our k estimates
for all years of the study period are available from and those of previous studies is even higher. For example, if
IMF government revenue data (IMF 2003, 2006, annual TFP growth is 1.9% for the period 1996-2002 (as
2007). We use the IMF classification of indirect estimated in Le Viet Anh 2006) then our estimate for k for
taxes in all cases except natural resource tax. the same period is 6.3 %, not the 10% assumed by Anh. If
Whereas IMF considers revenue from natural annual TFP growth is 3.4% for the period 1996-2000 (as in
resources a non-tax revenue, we treat it as an indirect Tran Tho Dat 2004) then our estimate for k for the same
tax, since it is levied on mining sector output. With period is 2.1 %, not the 8.5 % assumed by Dat.
this adjustment, we use the IMF data to calculate 5. Hertel and Tsigas (2002) consider natural resources in fish-
the indirect tax shares reported in Table 3. ery and mining as the fixed factors which constrain the price
Our final task is to calculate the shares of supply response of these sectors. With given econometric
GDP at factor cost and indirect taxes in income-side estimates of the supply elasticities for these sectors, they
GDP ( SGDPMP
GDPFC
and SGDPMP
ITAX
respectively). As discussed back-solve for the implicit natural resource payment shares.
above, we know annual values for indirect tax These form the basis of the factor shares for these industries
collections ( ITAX ) from IMF data. From our appearing in the GTAP 6.0 database.
calculations outlined in Part 1(c) of this Appendix
we know annual values for GDP at factor cost References:
( GDPFC ). We calculate annual values for SGDPMP
GDPFC
and n Central Institute for Economic Management
SGDPMP by applying the following formulae:
ITAX
(2003), Vietnam Economy in 2002, National
Political Publisher, Hanoi.
GDPFC Dapice, D. (2004), "Celebration and reflection:
GDPFC
S GDPMP = and
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GDPFC + ITAX Vietnam's economy enters a new era", John F.
Kennedy School of Government, Harvard University,
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GDPFC + ITAX accessed November 2007].
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in Le Viet Anh (2006) for the period 1996-2002, and 10-11 the 2001 downturn", Paper for the Vietnam
percent for the period 2000-2004 in Dapice (2004). Tran Updates 2001: Governance in Vietnam: The
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Khien (2005) estimates k at 14.4% per annum for the period Vietnamese Input - Output Tables for 1996,
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the case. See, for example, Dapice (2004) and CIEM Vietnamese Input-Output Tables for 2000,
(2003). Statistical Publishing House, Hanoi.
Volume 2 - Number 2 - 2008 Vietnam Economic management review 43
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- VEMR ECONOMIC RESEARCH Just how quickly has the Vietnamese capital stock grown over the past decade?
n General
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n International Monetary Fund (2003), "Vietnam: Finance, Hanoi.
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03/382, International Monetary Fund, Development of a dynamic CGE model for the
Washington, D.C. [http://www.imf.org/exter- Vietnamese economy and analysis of structural
nal/pubs/ft/scr/2003/cr03382.pdf, accessed April
changes during 1996-2003, Unpublished PhD
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thesis, Centre of Policy Studies, Monash
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Washington, D.C., retrieved August 2007, Growth: Survey Report - Vietnam", National
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07/386, International Monetary Fund, .pdf, accessed January 2006].
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January 2008].
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44 Vietnam Economic management review Volume 2 - Number 2 - 2008
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