Download prudent management of oil revenues: impacts of government capital

PRUDENT MANAGEMENT OF OIL REVENUES: IMPACTS OF
GOVERNMENT CAPITAL EXPENDITURES IN AZERBAIJAN
Sarvar Gurbanov1*, Jeffrey B. Nugent2 and Ceyhun Mikayilov1
1
Qafqaz University, Baku, Azerbaijan
University of Southern California, Los Angeles, USA
E-mails: [email protected] ; [email protected] ; [email protected]
2
Abstract
Azerbaijan is an oil rich country facing three severe problems at the same time: economic
volatility, the need to promote industrial diversification and the recent sharp fall in oil prices which many
expect to continue. It is thus a highly appropriate time to conduct a study for this resource-rich country
that would relate its insufficient and ineffective industrial diversification to the effectiveness of its efforts
to overcome these problems, including the encouragement of FDI, the creation of its State Oil Fund and
the establishment of a fiscal rule. To this end, in this study we pull together empirical evidence
concerning the allocation of oil windfall gains, the quality of the country’s budgetary institutions and its
State Oil Fund and their effects on Azerbaijan’s budgetary outcomes. But, more uniquely, we develop and
apply some models to capture the long terms effects of oil prices and fiscal management on industrial
diversification, where we find the efforts to date to have fallen far short of what is needed. Our analysis
leads us to suggestions for much needed improvements in policy.
Key words: oil windfall gains, government capital expenditures, non-oil diversification, industrial policy,
JEL Classification: Q01, Q32, Q43, H54, L52, O23, O25, O53
* Sarvar Gurbanov expresses his gratitude to The Fulbright Scholarship of US Department of State,
Bureau of Educational and Cultural Affairs and the Der Deutsche Akademische Austausch Dienst
(DAAD) for financial support.
I. Introduction
With time series data on its oil production dating from 1871, it is clear that Azerbaijan has been an
oil-rich country for some time. During the Soviet Union, its oil revenues accrued mainly to the central
government of the USSR. But during the 25 years since Azerbaijan’s independence, its oil revenues have
increased and their use has come under the management of the Azerbaijan state. To its credit, Azerbaijan
has taken four significant steps toward suitable management of its oil.
The first such step was the well-known "Contract of the Century", a bundle of numerous
Production Sharing Agreements (PSA) which Azerbaijan signed in 1994 with 11 major oil companies for
the Azeri-Chirag-Guneshli oilfields.1 This led to some $60 billion of FDI and sharp increases in
Azerbaijan’s oil production since 1997 (Ciaretta and Nasirov, 2012: 285) Even though oil prices remained
low throughout most of the 1990s, the second important step taken by Azerbaijan was that in 1999 to
create a special oil fund, the State Oil Fund of the Republic of Azerbaijan (SOFAZ), Its purpose was to
accumulate savings from its oil revenues for purposes of macroeconomic stabilization, saving for future
1
Ciaretta and Nasirov (2012) attribute the Azerbaijani comparative success in this relative to that of their neighboring oil
producers (Russia, Kazakhstan and Turkmenistan and Uzbekistan) to (1) its willingness to offer exemptions from various kinds
fees and taxes and restrictions on foreign bank accounts (which in turn have been facilitated by the absence of parliamentary
involvement in the negotiations, making it easier to reach the agreements, and (2) its efforts to improve its business environment.
1
generations and investment in important national development projects. Third, soon after that, it decided
to join the Extractive Industries Transparency Initiative (EITI), an international NGO designed to increase
transparency in the flow of funds between the extractors of the oil or minerals and the recipients
(governments or national oil companies) and thereby to reduce the likelihood of missing funds and
corruption through the adoption of best practice standards. As its experience with the volatility of world
oil prices and hence the unpredictability of its revenues continued, in 2004 Azerbaijan took a fourth
important step to manage its oil revenues by initiating a fiscal rule linking the oil price to the percentage
of oil revenues which would be automatically syphoned off to SOFAZ2.
While these steps have been impressive and have been demonstrated to compare favorably to most
other oil exporters, in view of the extreme volatility it has experienced from sudden shocks in oil prices,
they seem not to have been sufficient (Ahmadov et al 2009, Pomfret 2012, and Aslanli 2015). Indeed, as
demonstrated in Section II (to follow), Azerbaijan’s dependence on oil has rather steadily increased, at
least up to the dramatic fall in oil prices beginning in late 2014. To the extent that it has diversified at all,
this has been not to manufacturing but rather in the direction of non-tradables in which TFP is known to
be very low. Because of the volatility of oil prices, the importance of oil revenues in total government
revenues, and (as will be demonstrated in the following section) its less than optimal fiscal policy
regimes, these volatilities carry over to volatility in both government spending and the economy as a
whole. Because of the on-going fracking revolution, oil prices may well stay low for some time and the
fact that oil production (though not gas) is expected to decline by 2024 (World Bank 2012), economic
diversification away from its extremely high dependence on oil is much needed. Yet, especially in a
possibly enduring new era of lower oil prices, achieving this will be by no means easy. With this
objective in mind, the focus of this study is on the role of fiscal policy in diversification from oil and the
problems associated with this.
The remainder of the paper is organized as follows. In the next section, Section II, we provide a
more comprehensive description on Azerbaijan’s experience in managing its oil revenues, beginning with
the oil boom lasting through 2013 and then after that with the fall in oil prices, especially in relation to its
non-oil industrial production. Section III presents a brief review of relevant literature on both the fiscal
management problem in general and its application to Azerbaijan in particular. In Section IV we present
the data and methods utilized, as well as the empirical findings, including a discussion of the results and
related tests. Finally, in Section V we utilize these findings to draw some important policy
recommendations.
II. Further Background on Azeri Oil, Its Management, Accomplishments and Problems
As Hasanov (2013) and others have suggested, Azerbaijan’s transition after the collapse of Soviet
Union was very painful indeed. It displayed symptoms similar to those of Russia and other Former Soviet
Union countries. Its heavy reliance on central government subsidies for its manufacturing sectors
rendered these industries uncompetitive after the breakup of the USSR. Once they faced competition in
free world markets beginning in 1991, these sectors collapsed as shown in Figure 1. Since the industrial
output index in Figure 1 includes the hydrocarbon sector itself, the real decline in the non-oil
manufacturing sector was even greater than the index shows. Indeed, the share of manufacturing value
added in Azerbaijan’s GDP was only 4.19 percent in 2005 and by 2011 was even lower, 3.41 percent
(UNIDO, 212:192, 2013:196). Even its services sector was quite underdeveloped and considerable time
was required for this sector to expand and develop.
2
The Decree had been announced publicly in 2004 and covers the 2005 - 2025 periods and carries the following
title: The Long term strategy on management of oil and gas revenues. According to this rule when the oil price rises
to a level above that of any previous year, no more than 75% of these oil revenues can be spent, the remaining 25%
being saved in SOFAZ (Ciaretta and Nasirov, 2012: 284).
2
Yet, as a result of Azerbaijan’s success in inducing eleven oil companies to sign the
aforementioned Production Sharing Agreements (PSA) with the government in 1994, FDI was plowed
into the oil sector and the infrastructural investments needed to develop both its production and export
capabilities. As a result, after the year 2000 substantial increases in oil production were realized. Thanks
also to the rapidly increasing oil prices after 2000, the impacts of oil on the Azerbaijan economy became
extremely powerful, inducing a true oil boom by about 2003, leading to real GDP growth of 10 percent in
2004, another 26 percent in 2005, 34.5 percent in 2006 and 25 percent in 2007, clearly demonstrating a
close link between oil and the overall economy (Hasanov and Huseynov, 2013). Bildirici and Kayıkçı
(2013) showed oil production and revenues to be very tightly linked (not only in Azerbaijan but also in
the other oil-exporting Eurasian countries) to the extent that a 1 percent increase in oil production would
increase GDP by about 1 percent.
Even though the growth rates of oil production and GDP have slowed down since 2007, the levels
have stayed high. Oil and gas exports and revenues are likely to continue for some time, offering further
potential for growth of Azerbaijan’s economy if these revenues would be managed well. Indeed, the
World Bank (2009, p.28) estimated the net present value of Azerbaijan oil and gas revenues to be realized
only between 2008 and 2024 to be 198 billion USD (in 2007 prices). The BP Statistical Review of World
Energy 2014 depicted the total proven oil reserves of Azerbaijan to be 7 billion barrels (BP: 2015:6) and
its natural gas reserves to be 1.2 trillion cubic meters (BP: 2015:20). Other estimates of oil reserves by the
World Bank (2009) and of gas reserves by SOFAZ have been even higher.
Nevertheless, as shown in Table 1 below and in more detail by Aslanli (2015), despite both SOFAZ
and the fiscal rule, government expenditures, much of it financed by transfers to the State Budget from
SOFAZ, rose sharply. Those revenues and expenditures being over five times as large in 2013 as they
were in 2006 and almost ten times what they were in 2005. While Azerbaijan clearly benefited from oil
during the period of generally high and rising oil prices since 2000, oil prices began to fall in late 2014,
leading to ever greater volatility, and financial problems. To deal with these problems oil countries like
Azerbaijan need to pay much more attention to economic diversification so as to reduce the volatility of
the economy and avoid excessive concentration on the oil sector itself and energy-intensive industries.
Some examples of what can happen to countries which do not diversify sufficiently away from the
energy sector itself, were provided by Damette and Seghir (2013). They showed, that Egypt and
Indonesia, though mindful of the need to diversify away from their energy sector, did so by heavily
promoting energy-intensive industries, but in the process this drastically increased local demand for
energy, converting these countries from being substantial energy exporters to being net energy importers.
While that has not happened in Azerbaijan, its overall economic dependence on the oil sector has
increased, at least until the sharp fall in oil prices beginning in 2014. According to data taken from the
National Accounts of Azerbaijan, the share of Mining and Quarrying (including oil and gas) increased
sharply from 14.8% of GDP in 1997 to 53.7% of GDP by 2007 when oil prices were especially high,
before leveling off and falling slightly to 37% in 2014 and even further following the sharp reduction in
oil prices in 2015. According to data taken from the World Integrated Trade Solution (WITS) of the
World Bank, the share of oil and gas in total exports increased even more sharply from 0.32% in 1997 to
93.1% in 2013 before falling to 75.2% in 2014, again as a result of the fall in the price of oil in the last
part of that year.
Due to the combined effect of increasing oil production and increasing oil prices, especially
between 2005 and 2008, Azerbaijan`s oil revenues increased rapidly, thereby triggering sharp hikes in
public spending (Ciaretta and Nasirov, 2012: 283). These increases in spending have been mitigated
somewhat by the existence of SOFAZ and the fiscal rule identified above. Although Azerbaijan’s fiscal
rule falls far short of that of Norway3, it is one of the few fiscal rules adopted by any non-OECD oil
exporter. Between 2001:Q2 and 2014:Q1, 105 billion dollars had been accumulated in SOFAZ. By April
3
Norway puts almost all of its oil revenues into its oil fund and then transfers to the budget a specified percent of its
returns on those assets (not the assets themselves). In 2014 these transfers accounted for 10 percent of total
government expenditures (NMF, 2013 - 2014: 7).
3
1, 2014 these assets equaled to 36.6 billion dollars (SOFAZ, 2014). Yet, because of the effect of the
slump in oil prices on the government budget, the assets remaining in the fund in April 1, 2016 had fallen
to $34.3 billion.
Nevertheless, as clearly depicted in Tables 1 and 2, Azerbaijan’s budget remains extremely
dependent on oil revenues which, in turn, are very vulnerable to oil price shocks.
Table 1. Oil Revenues and Azerbaijan State Budget Relationship
Years
State Budget Revenues
(mil. manat)
Transfers from SOFAZ to
the State Budget
(mil. manat)
Share of SOFAZ transfers
in State Budget Revenues,
percent
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2055
3881
6007
10762
10326
11403
15701
17282
19495
18401
17153
16822
150
585
585
3800
4915
5915
9000
9905
11350
9337
8130
7010
7
15
10
35
48
52
57
57
58
51
47
42
SOFAZ Revenues
Share of its transfers to the
State Budget in SOFAZ
revenues, percent
SOFAZ oil revenues from
the oil PSAs (mil manat)
Share of state budget
transfers in the "Profit Oil",
percent
660
986
1886
11864
8274
13089
15628
13674
13601
12731
7721
na
23
59
31
32
59
45
58
72
83
73
105
na
569
929
1800
11633
7870
12656
15258
13117
13108
12320
7370
na
26
63
33
33
62
47
59
76
87
76
110
na
Source: State Oil Fund of the Republic of Azerbaijan (SOFAZ) Annual Reports (2005, 2006, 2007, 2008, 2009, 2010,
2011, 2012, and 2013), Central Bank of Azerbaijan (CBAR) Statistical Bulletin April 2014, and authors` calculations.
Details on the role of SOFAZ in the State Budget can be seen in Table 1. The SOFAZ revenues in
the table include not only oil revenues but also other revenues gained by managing the oil fund’s assets,
transit fees, and bonus payments and so on. “Profit Oil” in the table represents the revenues from the oil
and gas Production Sharing Agreements (PSAs). While in 2005, the share of the SOFAZ transfers in State
Budget Revenues was only 7 percent, in recent years the share has averaged well over 50 percent.
Moreover, corporate income taxes of the State Oil Company of the Azerbaijan Republic (SOCAR) and
multinational oil companies are paid directly to the state budget (Ciaretta and Nasirov, 2012: 284). Under
these conditions, dependency of the state budget on oil revenues is actually very high despite the intent in
creating SOFAZ.
When oil and gas resources run out, of course, the main source of finance as well as of
employment and economic growth will have to be the non-oil industrial sectors. This, too, calls attention
to the importance of examining the relation among oil prices, fiscal spending and the non-oil sector. For
long term sustainable economic development, therefore, economic and export diversification will be of
crucial importance. Diversifying the economy away from the oil industry quite naturally will require
reviving the non-oil industrial sectors, and especially manufacturing which, as noted above, even in 2013
accounted for only a little over 3 percent of GDP. Notably, in 2014 Azerbaijan announced a five year
state industrial development program.4 Yet, especially after the sharp fall in oil prices immediately after
that (which many expect to continue for some time), the feasibility of this program is in jeopardy, thereby
further justifying our investigation into the research question: "How well is Azerbaijan doing in allocating
its oil windfall gains so as to foster development of non-oil exports and non-oil GDP?”.
4
This plan, currently under implementation, arose from a decree of the President of the Azerbaijan Republic
ordering relevant ministries and institutions to prepare "Azerbaijan 2015 - 2020 State Program on the Industrial
Development".
4
From Table 2, one can see rather clearly that its expenditures on non-oil goods and services are
being financed by oil revenues and that, even in the most recent years, the contribution of non-oil
industrial sectors to the state budget is rather negligible. The promotion of non-oil exports and GDP will
be the means of developing a strong non-oil tax base. For long term sustainable development, all these
components will have to come into play.
Table 2.
Azerbaijan: Consolidated Central Government Operations (2008 - 2015), in percent of non-oil GDP
2008
Non-oil
primary
balance 1
-39.2
2009
-35.5
2010
-36.3
2011
-40.3
2012
-45.4
2013
-45.1
2014
Prel.
2015
2016
Proj.
Proj.
-41.1
-31.1
-31.2
1
defined as non-oil revenue minus expenditure (excluding interest payments) and statistical discrepancies
Source: IMF Country Report No. 13/164, 2013: 27. IMF Country Report No. 14/159, 2014: 29.
5
Figure 1. Real Gross Industrial Output in Azerbaijan (Indices, 1989 = 100)
120.0
100.0
100.0
93.7
85.4
80.0
59.4
60.0
40.0
47.7
Indices
35.9
28.2 26.3 26,4 27.0 28.0
29.9
31.4
20.0
0.0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
Source: UNECE, Economic Survey of Europe, 2002 No.1: 232
Note also that the currently extremely low share of manufacturing and non-oil production in GDP
and exports puts Azerbaijan in a very different position than countries like Netherlands, Norway and even
Indonesia when their oil booms started. As Dülger et al (2013) pointed out, this is likely to make it more
difficult for manufacturing and the rest of the non-oil sector to make up for oil revenues as an alternative
source of finance and needed macroeconomic and fiscal stability whenever, as will certainly occur in the
not too distant future, oil revenues start to decline.
Since the share of oil and gas sector in total employment is less than 1 percent, but the sector
accounts for about half of GDP, and employment opportunities are of increasing concern to the citizens of
Azerbaijan, it is clear that diversification to non-oil sectors is important not only for diversification of
exports and GDP but also for sustainable job growth. There are at least two other important reasons why
this study on diversification of GDP, exports and employment is rather urgently needed. First, during the
last two years government policy makers have very seriously diverged from adherence to Azerbaijan’s
fairly unique fiscal rule. Second, it is also true that the quality of its adherence to the international
standards associated with its membership in EITI for the way it receives and manages it oil revenues has
been downgraded from “compliant to its standard” to only “eligible for becoming compliant”. The EITI
website5 has attributed this downgrading (based on a 2013 evaluation) to insufficient involvement of civil
society in the process of oil revenue management and the especially low scores it received for corruption
and other elements of the “enabling environment”. The relevance of involvement of civil society is
apparently attributable to the belief that stronger engagement of civil society would help limit corruption
and the ability of the policy makers to violate the fiscal rules and the objectives of SOFAZ. These two
shortcomings help explain the behavioral problems that we shall be examining below.
Table 2, for example, demonstrates very clearly the continuing excessively high dependence of the
state budget on oil revenues and as a result the increasing non-oil budget deficit as a percentage of non-oil
GDP. Indeed, it shows also that the percentage of non-oil tax revenue in non-oil GDP has been declining,
whereas the non-oil budget deficit as a percentage of non-oil GDP has been increasing. These trends
5
https://eiti.org/extractive-industries-transp (May 5, 2016)
6
imply that oil price and/or oil revenue shocks, unless treated more efficiently, are likely to generate everstronger adverse effects on fiscal and macro-economic stability.
Meanwhile, Table 3 shows very clearly the unusually high share of government investment in total
investment of Azerbaijan since 2007, and hence also the potential importance of government investment
in determining the subsequent path of non-oil GDP and exports.
Table 3. Share of public and private sector in fixed capital investments (percent)
Years
Private Sector
Public Sector
2006
85,8
14,2
2007
57,4
42,6
2008
45,6
54,4
2009
57,2
42,8
2010
61,4
38,6
2011
57,4
42,6
Source: NBA, 2007: 19, CBAR, 2008:17, CBAR 2009: 21, CBAR, 2011: 13.
As Arif Aliyev, Head of the State Statistical Committee of the Republic of Azerbaijan announced
in late 2013, (1) the total investment taking place in social and infrastructure projects in Azerbaijan during
the period 2003 - 2013 equaled about 132 billion dollars and (2) some 51 percent of the financing for
these investments came from domestic sources (Trend, 2013). With such a large share of these coming
from government capital expenditures, it again raises the aforementioned question: How effective is the
allocation of government capital expenditures in terms of fostering non-oil diversification in both overall
GDP and in exports? Answering that question is the main objective of this paper.
Also as noted above, Azerbaijan did not have a viable manufacturing sector after the collapse of
Soviet Union. Its Soviet technology was outdated and non-competitive with modern international
standards. Up until to 2004, Azerbaijan did not have enough funds to finance even the slightest amount
of diversification into non-oil industrial sectors. The oil boom that commenced in 2004, however, gave it
an opportunity to use its oil revenues to finance long term investments including industrial and
especially manufacturing development. Manufacturing is important for three reasons; it is the source of
R&D and innovation, it helps countries to build up their middle class and it is widely recognized for
having multiplier effects on job creation. All three virtues of the manufacturing sector are also crucial for
the economy of Azerbaijan. Was Azerbaijan successful in this respect?
III. Literature Review
Before going on to our own search for an answer to this last question and to demonstrate the
contribution of the present study, we deem it important to review some relevant literature.
As is well-known, there is of course by now an enormous literature on the Dutch disease effects of
oil, emphasizing those high prices of a country’s oil exports can bring about decline in its tradable goods
sector through the appreciation of the country’s real exchange rate (Corden 1984). While this is likely to
be a more serious concern for developing countries with lesser ability to engage in efficient monetary and
fiscal policies and other means of preventing adverse effects on industrial structure, Dissou (2010) has
shown that it also is a common result in developed countries like Canada. Goodness et al. (2014) among
many others have shown that adverse effects on tradable goods can occur even if the country is an
7
exporter, not of oil but of minerals and other primary products which could have similar effects on the
real exchange rate.
When it comes to oil exporting developing and transition countries the examination of effects of
oil and oil prices has spread considerably beyond the Dutch disease effects to a wide variety of other
variables. Among the common findings are positive effects of oil revenues on government consumption
expenditures, the government wage bill, fuel and housing subsidies and military spending, and negative
effects on the non-oil economy. (e.g., Farzanegan and Markwardt (2009), Farzanegan (2010), Emami and
Adibpour (2012), on Iran, Dizaji (2014), on MENA countries, Bhattacharyya and Blake (2010), on
Nigeria, Iwayemi and Fowowo (2011) on Russia, Dülger et al. (2013), on Kazakhstan. Both Arezki and
Ismail (2013) and El Anshasy and Bradley (2012) do so for a large number of oil exporting countries.
Many of these studies identify the ability to deal with volatility in their government revenues as a major
weakness of oil rich developing countries. Still other studies on a variety of developing countries show
that oil revenues also tend to have harmful effects on growth and diversification away from oil.
In some of these cases, the blame for adverse effects of positive oil price shocks is traced back to
weak institutions, either weak political systems that allow incumbent political leaders to retain inefficient
and weak institutions, or directly to the weak institutions themselves (especially weak fiscal institutions or
the absence of rule of law and of property rights) (See, for example, Arezki, R. and F. Van der Ploeg
(2007), Mehlum, H. Karl Moene and R. Torvik (2006a, 2006b), Collier and Hoeffler (2009) Elbadawi and
Soto (2016) and Selim and Zaki (2016).
More specifically, on real exchange rate appreciation and the effects on manufacturing of oil
price booms, based on a sample of 10 energy-exporting countries, Dauvin (2014) finds that a 10 percent
increase in the energy price brings about a 2.5 percent appreciation of the currency. Dülger et al. (2013)
pointed to its role in the decline of its manufacturing sector and the rise of services (mostly non-tradable).
In a related study for Kazakhstan, Azhgaliyeva (2013) shows that the real value of oil production raises
real government expenditures but that the country’s national oil fund mitigates that unwanted effect to
some extent.
In contrast to the large number of such studies on other oil exporting countries, there are far fewer
existing studies of this sort on Azerbaijan. One exception is the aforementioned study of Arezki and
Ismail (2013) since it included Azerbaijan among the 32 oil-exporting countries in its panel data analysis.
This study showed that current government spending tends to rise when oil prices rise but not to decrease
when oil prices go down, the latter being a good sign in terms of limiting the extent of procyclicality
typical of most oil exporters. On the other hand, in the case of government capital expenditures, they
showed that there is considerable procyclicality in its effects but they did not relate this to the industrial
structure or industrial diversification of these countries. Also they detected an interesting asymmetry in
the effects of the two different types of expenditures on the real effective exchange rate, namely that
government current expenditures bring about appreciation of that rate but that government capital
expenditures bring about depreciation in that rate. They attribute this difference to differences in the input
content between the two types of spending, i.e., import-intensive in the case of capital spending and
domestically produced intensive goods-intensive in the case of current spending. Consistent with this
analysis, Cherif and Hasanov (2013) suggest that, if productivity in the tradable sector is low as it is
believed to be in Azerbaijan, it would be better for the oil-exporting country to put its oil revenues in its
oil fund rather than investing in its expansion. Hasanov and Huseynov (2013) find that, in Azerbaijan a 1
percent real exchange rate appreciation generates a 0.61 percent decline in the output of its non-oil
tradable sectors in the long run, and a 3.21 percent decline in the short run. Their data, however, was
limited to the 2000 – 2007 period, making their estimates vulnerable to a small sample bias and capturing
the effect of only about three years of the oil boom. Earlier, Hasanov (2010) used an ARDL Error
8
Correction Model and the Johansen Co-integration approach somewhat similar to that we use below, to
show that a 1 percent increase in the real oil price leads to a 0.7 percent increase in the real effective
exchange rate of its currency, the manat, but again with data only based on the 2000-2007 period. In
further investigating Dutch Disease effects for Azerbaijan, Hasanov (2013), but again with data only for
the 2000-2007 period, suggests that the price increase in non-tradable sectors in Azerbaijan brought about
by the increase in government current expenditures directly increases the overall domestic price level and
indirectly the real value of the manat. Moreover, he concludes that, rather than yielding positive spillover
effects for non-oil exports, the FDI inflows into Azerbaijan aggravated the Dutch Disease effects,
reducing manufacturing production not only in relative terms but also in absolute terms.
This relationship, however, can be explained in different ways. First, it can be explained indirectly
by the effect of oil prices on input prices. When the input costs rise in the non-oil industrial sectors, it
takes a toll on production of tradable goods like manufacturing which have to compete with imports.
Second, it can be attributed to a direct effect of oil prices on manufacturing since many manufacturing
industries use oil as an input, in many cases quite intensively. Third, when the oil price increases, both the
terms of trade and the real exchange rate rise. The aforementioned findings of Hasanov (2010) are
consistent with this inference. Domestic manufactured goods get less affordable in domestic markets and
less competitive in international markets. Since the 2004 oil boom, the Azerbaijani manat continued to
appreciate nominally and, despite the global financial crisis of 2008-9, Azerbaijan did not devalue its
national currency until February 21, 2015 when it did so by 34 percent relative to the euro and the US
dollar. The main purpose of this action was to stimulate economic diversification and promote export
competitiveness (APA, 2015).
But, there is still another potentially important link between oil prices and non-oil manufacturing
production, one that has not yet been investigated. This is one going from oil prices to government capital
expenditures and thereby to non-oil manufacturing. This could certainly be positive and thereby act as an
offset to the other negative effects. But, if the state capital expenditures flow mainly into infrastructure
most useful to non-tradable sectors such as construction and transportation, this effect could also be
negative. We believe that this latter negative effect would be the most likely outcome, especially
considering the limited absorptive capacity of the Azerbaijan domestic economy. When absorptive
capacity is low, government capital expenditures are not likely to be effective in increasing non-oil
industrial output. In such cases, government capital expenditures are likely to create a bias toward nontradable sectors. To be successful, public procurement policy should be designed in tandem with
improving efficiency of the capital expenditures and the ability to absorb them. As Ross (2012) put it,
"Investment is critical, but it cannot be done all at once. Economies have a limited ability to absorb new
investments, which are typically constrained by diminishing returns. For instance, if a government tries to
build too much infrastructure too quickly, it will lead to poor planning, lax oversight, and shoddy
construction at inflated prices"(Ross, 2012: 206).
An important objective of the empirical analysis in the following section is to test the validity of the
above hypothesis that the net effect of government capital expenditures on manufacturing should be very
weak. Since the data on real non-oil GDP includes a considerable amount of non-tradable, but by
definition non-oil exports do not, our primary focus will be on the links between oil prices and non-oil
exports. Note that this link is not part of the received literature on effects of oil price increases in oil
exporting countries.
IV. Data and Methods Used
A. Data and Its Sources
9
All data used in the models is available on a quarterly basis. Their sources are as follows:
Oil price (OP) the Brent oil price per barrel in terms of US dollars. Source: US Energy Information
Administration.
Government capital expenditures (Govcap) in million manats (Azerbaijan national currency) at constant
2005 prices. Source: State Development Indicators Bulletin, published by the The State Statistical
Committee of the Republic of Azerbaijan.
Non-oil export (noexp) in million USD atconstant 2005 prices, Source: Central Bank of Azerbaijan. Real
non-oil gross domestic product(rgdpno) in constant 2005 US dollars, Source: Central Bank of
Azerbaijan. The available time series covers the 2000Q1 - 2013Q4 period.
op
govcap
rgdpno
noex_r
5.0
8
8.4
6.4
4.5
7
8.0
6.0
4.0
6
7.6
5.6
3.5
5
7.2
5.2
3.0
4
6.8
4.8
2.5
3
6.4
2000
2002
2004
2006
2008
2010
2012
2000
2002
2004
2006
2008
2010
2012
4.4
2000
2002
2004
2006
2008
2010
2012
2000
2002
2004
2006
2008
2010
2012
2010
2012
Figure 1. Graphs of the logs of the variables
Differenced op
Differenced govcap
.4
.2
Differenced rgdpno
2
.4
1
.2
0
.0
Differenced noex_r
1.0
0.5
.0
0.0
-.2
-0.5
-1
-.2
-2
-.4
-3
-.6
-.4
-1.0
-.6
-.8
2000
2002
2004
2006
2008
2010
2012
2000
2002
2004
2006
2008
2010
2012
-1.5
-2.0
2000
2002
2004
2006
2008
2010
2012
2000
2002
2004
2006
2008
Figure 2. Growth rates of the variables
As can be seen from Figure 1, the oil price, government capital expenditures and real non-oil
GDP all increased during the period under study, but despite ups and downs non-oil exports did not
increase. Indeed, non-oil exports in real terms declined sharply in 2005 as a result of the sudden increase
in oil revenues and thereby government capital expenditures (arising from the “Contract of the Century”
and the completion of the Baku-Tbilisi-Ceyhan main export oil pipeline).
The descriptive statistics on these variables are given in Table 1. As reflected by the high values
of their coefficients of variation in the last column of the table, all these variables, but especially
government capital expenditures, were very volatile over the period under study.
10
Table 1: Descriptive statistics of the variables
variable
mean
max
min
Standard
Coefficient
deviation
variation, %
op
64.749
121.400
19.350
33.368
52
govcap
364.596
1576.700
29.300
343.963
94
noex_r
216.391
496.438
87.821
83.948
39
rgdpno
1951.575
4081.400
750.900
840.958
43
of
B.Methodology
1. Models to be Estimated
We investigate three different models. First, we estimate the model which relates oil prices (op)
to government capital expenditures (govcap). Next, we estimate the relationship between government
capital expenditures (govcap) and non-oil exports (noex). Finally, we estimate the relationship between
government capital expenditures (govcap) and real non-oil gdp (rgdpno) .
2. The Unit Root Test
In each case, before conducting a co-integration analysis by applying co-integration method, the
order of integration of the variables is examined by means of a Unit Root (UR hereafter) Test. We employ
the Augmented Dickey-Fuller test (ADF) of Dickey and Fuller (1981) for this purpose. The test maintains
the null hypothesis of non-stationarity of a given time series.
3. The Johansen Cointegration Method
The co-integration test employed is that of Johansen (1988) and Johansen and Juselius (1990)
based on the following full information maximum likelihood estimation of a Vector Error Correction
Model (ECM):
k 1
yt  yt 1 
  y
i
t i
   t
(1)
i 1
Where, y t is a (n x 1) vector of the n variables of interest, μ is a (n x 1) vector of constants,  represents a (n x
(k-1)) matrix of short-run coefficients,  t denotes a (n x 1) vector of white noise residuals, and  is a (n x n)
coefficient matrix. If the matrix  has reduced rank (0 < r < n), it can be split into a (n x r) matrix of
loading coefficients  , and a (n x r) matrix of cointegrating vectors  . The former, matrix  , shows the
importance of the co-integration relationships in the individual equations of the system and the speed of
adjustment to disequilibrium. On the other hand, the latter (matrix  ) represents the long-term
equilibrium relationship, so that     . Testing for cointegration, using Johansen’s reduced rank
regression approach, centers on estimating the matrix  in unrestricted form, and then testing whether
the restriction implied by the reduced rank of  can be rejected. Max and Trace tests statistics are used
to test for nonzero characteristic roots. If a given variable is statistically significant, it implies that the null
hypothesis of corresponding  = zero can be rejected, while stationarity or trend stationarity of a variable
assumes that a 1 0 0  restriction on long-run coefficients cannot be rejected.
/
11
4. Fully Modified Ordinary Least Squares Method (FMOLS)
The FMOLS method, developed by Phillips and Hansen (1990), has the advantage of eliminating
the sample bias and of correcting for endogeneity resulting from co-integrated relationships and serial
correlation effects (Narayan and Narayan, 2004). See Phillips and Hansen (1990) for a detailed
mathematical derivation of the model.
5. Dynamic Ordinary Least Squares Method (DOLS)
We also employ Dynamic OLS (DOLS) as advocated by Saikkonen (1992) and Stock and
Watson (1993). This approach enables one to construct an asymptotically efficient estimator that
eliminates the feedback in the co-integrating system. This method involves augmenting the co-integrating
regression with lags and leads of differenced variables so that the resulting co-integrating equation error
term is orthogonal to the entire history of the stochastic regressor innovations. Under the assumption that
adding lags and leads of the differenced regressors soaks up all of the long-run correlation between
residuals of the system, the least-squares estimates of the long-run equation coefficients have the same
asymptotic distribution as those obtained from FMOLS.
C. Empirical Results
1. Unit Root Test Results
As indicated in the methodology section, first we test variables for stationarity. The results of employed
ADF test are given in the Table 5:
Table 5: The Unit Root Test Results
The ADF test
Variable
Intercept
Intercept
and trend
First
Level
k
op
-0.841
2
-6.388***
1
govcap
-1.926
1
-8.758***
2
noex_r
-2.693*
1
-7.442***
2
rgdpno
-0.333
2
-31.676***
2
op
-3.445*
1
-6.322***
1
govcap
-5.514***
0
-8.707***
2
noex_r
-3.086
1
-7.365***
2
rgdpno
-16.784***
1
-31.986***
2
difference
k
Notes: ADF denote the Augmented Dickey-Fuller test. Maximum lag order is set to two and the optimal lag order (k) is selected
based on the Schwarz criterion in the ADF test; ***, ** and * indicate rejection of the null hypotheses at the 1%, 5% and 10%
12
significance levels, respectively; The critical values are taken from MacKinnon (1996) for the ADF test. Estimation period:
2000Q1 - 2013Q4.
As Table 5 demonstrates, all the variables examined are integrated of order one, in other words, they are
I(1) processes. This result enables us to employ the different co-integration methods for modeling the
relationship among the variables.
2. Results of Co-integration Methods
First, we model the relationship between oil prices (op) and government capital expenditures
(govcap). Since the variables follow an I(1) process, we can proceed to the Johansen co-integration
analysis. Using VAR and taking four as a maximum lag length and applying each of the three lag
selection criteria, we obtain the results shown in Table 6. From the Likelihood Ratio (LR), Final
Prediction Error (FPE) test statistics and Hannan-Quinn tests, a lag length of two is preferred, with no
serial correlation in residuals. In order to “catch” the effect of 2008 Financial Crisis on govcap variable
which arose in the last quarter of 2008 and in other years the tendency for these expenditures to rise
sharply in the last quarter of each year (as can be seen in Figure 1), we added to the model the dummy
variables d2008Q4 and Seas(4). Here d2008Q4 = 1 for the last quarter of 2008 and 0 otherwise, and
Seas(4) = 1 in the last season of each year.
Table 6: Test Results for Optimal Lag Length Selection.
Endogenous variables: govcap and op; Exogenous variables: C d2008Q4, Seas(4)
Lag
LogL
LR
FPE
AIC
SC
HQ
0
-602.8066
NA
50634417
23.4156
23.6408
23.5019
1
-534.0644
124.2648
4201667
20.9256
21.3008*
21.0694
2
-527.5554
11.2656*
3823160*
20.8291
21.3544
21.0305*
3
-523.5481
6.6274
3836458
20.8288*
21.5042
21.0877
4
-519.6328
6.1742
3871867
20.8320
21.6576
21.1485
Notes: * indicates lag order selected by the criterion; LR is sequential modified LR (Likelihood Ratio) test statistic
(each test at 5% level); FPE denotes Final prediction error, AIC, SC and HQ represent the Akaike, Schwarz and
Hannan-Quinn information criteria, respectively.
As a next step, the Johansen co-integration test is performed on this VAR, yielding the test results
presented in Table 7.
13
Table 7: Johansen’s Cointegration Test Results
Number of CE
None
At most 1
Trace Statistics
Max-Eigenvalue Statistics
30.4287***
28.9039***
1.5248
1.5248
Notes: The test type is Intercept and no trend in the co-integrating equation and the VAR; Critical values are taken from
MacKinnon et al. (1999); ***, ** and * denote rejection of the null hypothesis of no cointegration at least at the 1%, 5% and 10%
significance levels, respectively; CE means co-integrating equation(s); Estimation period: 2001Q1-2013Q4.
Both, the Trace and Max- Eigen Value statistics indicate there is a co-integrating relationship
between the variables at the 1 % significance level. Additionally, Phillips-Ouliaris co-integration test also
shows that the variables are co-integrated variables at the 1 % significance level. The results of the test are
given in Table 8:
Table 8: Results of the Cointegration Tests for Oil Price and Government Capital Expenditures
Phillips-Ouliaris Cointegration test
Phillips-Ouliaris Cointegration test
z-statistic
p-values
Tau-statistic
p-values
-34.431
0.000***
-5.260
0.000***
Dependent variable
govcap
Notes: The null hypothesis for both tests is: variables are not co-integrated; ***, ** and * denote rejection at 1, 5 and 10 %
significance levels, respectively; Optimal lag length is selected based on the Schwarz criterion taking 2 lags as a maximum;
p-values are MacKinnon(1996) p-values for the tau-statistic.
As a result of the co-integration tests, it can be concluded that there is a long-run relationship
between govcap, and op. The next step, therefore, is to find the long-run relationship between these two
variables. The results for all three co-integration methods are given in the Table 9:
Table 9: Results of Co-integration Equations for Government Capital Formation and Oil Price
Variable
VECM
FMOLS
DOLS
op
1.658*** (0.000)
1.677*** (0.000)
1.616*** (0.000)
Notes: The dependent variable is govcap. Estimation period is 2001q1-2013q4. p-values are in parentheses. ***, ** and *
indicate significance of the coefficients at the 1%, 5% and 10% significance levels ,respectively. The Speed of Adjustment
Coefficient in the VECM equation is found to be (-0.73) and statistically significant at the 1% significance level.
Note that the results obtained from all three methods are quite close to each other. The VECM
estimation result indicates the speed of adjustment to be negative (-0.73) and statistically significant,
indicating that short-run deviations adjust quite quickly to the long-run equilibrium path and, hence, that
there is a stable co-integrating relationship between the variables. Since the variables are in log form, the
coefficient of the op variable is statistically significant and indicates that a 1% increase in oil prices cause an
average 1.66% increase in government capital expenditures. This, of course, is indicative of rather extreme
14
procyclicality in fiscal policy, which is known to have negative effects on long-term growth.
Next, we proceed to use the same methods to estimate the relationship between government
capital expenditures (govcap) and non-oil exports(noex). Once again, in the VAR context, the maximum
lag length is selected to be 4. In this case, however, the optimal lag length without serial correlation
problem in residuals is found to be four lags. Although the Max eigenvalue and Trace tests indicate no
cointegration in this case, as shown in Table 10 the Engle-Granger and Phillips-Ouliaris cointegration
tests based on the aforementioned DOLS and FMOLS methods show that these variables are in fact
cointegrated.
Table 10: Results of the Cointegration Tests between Government Capital Expenditures and Non-Oil
Exports
Phillips-Ouliaris Cointegration test
Phillips-Ouliaris Cointegration test
z-statistic
p-values
Tau-statistic
p-values
-36.612
0.000***
-5.135
0.000***
Dependent variable
noex
Notes: The null hypothesis for both tests is: variables are not cointegrated; ***, ** and * denote rejection of the null
hypothesis at the 1, 5and 10 % significance levels, respectively; the optimal lag length is selected based on the Schwarz
criterion taking 2 lags as a maximum; p-values are MacKinnon(1996) p-values for the tau-statistic.
The estimates obtained for the long run relation between between government capital
expenditures (govcap) and non-oil exports (noex) from all three of these estimation methods are presented
in Table 11.
Table 11: Results of co-integration equations for Non-Oil Exports and Government Capital Formation
Variable
VECM
FMOLS
DOLS
govcap
-0.157** (0.016)
-0.106** (0.024)
-0.133** (0.026)
Notes: The dependent variable is non-oil export. The estimation period is 2001q1-2013q4. p-values are in parentheses. ***,
** and * indicate significance of the coefficients at the 1%, 5% and 10% significance levels, respectively. Speed of
Adjustment Coefficient in VECM equation is found to be (-0.41) and statistically significant at 1% significance level.
Note that the test results (available upon request) show that the residuals satisfy the GaussMarkov assumptions. As the figures in Table 11 show, the results obtained by all three estimation
methods are very close to each other, demonstrating their robustness. Since the variables are in level
form, via the VECM approach, a 1-unit increase in government capital expenditures is associated with a
0.157 units decrease in non-oil exports. In addition, the VECM estimation result indicates the speed of
adjustment to be negative (-0.41) and statistically significant, implying that 41 % of the short-run deviations
converge to the long-run equilibrium path within one quarter.
Next, we turn to the relationship between government capital expenditures (govcap) and real nonoil gdp (rgdpno). In the VAR context where the maximum lag length is 4, once again 4 is the optimal lag
length by all criteria. The results of the cointegration tests are given in Tables 12 and 13, in each case,
demonstrating that the Government Capital Expenditures and Non-Oil GDP are cointegrated.
15
Table 12: Johansen’s co-integration Test Results for Government Capital Expenditures and Non-Oil GDP
Number of CE
None
At most 1
Trace Statistics
Max-Eigenvalue Statistics
15.9308**
14.9327**
0.9981
0.9981
Notes: The test type is Intercept and no trend in co-integrating equation and the VAR; Critical values are taken from MacKinnon
et al. (1999); ***, ** and * denote rejection of the null hypothesis of no co-integration at the 1%, 5% and 10% significance
levels, respectively; CE means co-integrating equation(s); Estimation period: 2001Q1-2013Q4
Table 13: Results of Phillips-Ouliaris Co-integration tests for Government Capital Expenditures and Non-Oil
GDP
Phillips-Ouliaris Co-integration test
Phillips-Ouliaris Co-integration test
z-statistic
p-values
Tau-statistic
p-values
-31.406
0.000***
-4.753
0.000***
Dependent variable
Noex
Notes: The null hypothesis for both tests is: variables are not cointegrated; ***, ** and * denote rejection of the null
hypothesis at the 1, 5 and 10 % significance levels, respectively; the optimal lag length is selected based on the Schwarz
criterion taking 2 lags as a maximum; p-values are MacKinnon(1996) p-values for the tau-statistic.
The results of VECM, DOLS and FMOLS co-integration estimations are given below in Table 14:
Table 14: Results of the Long Run Relationship between Government Capital Expenditures and Non-Oil
GDP
Variable
VECM
FMOLS
DOLS
govcap
0.482*** (0.000)
0.381*** (0.000)
0.388*** (0.000)
Notes: Dependent variable is non-oil GDP. Estimation period is 2001q1-2013q4. p-values are in parentheses. ***, ** and *
indicate significance of the coefficients at 1%, 5% and 10% significance level respectively. Speed of Adjustment Coefficient
in VECM equation is found to be (0.031) and statistically insignificant.
In the case of VECM the speed of adjustment coefficient (SOA) is positive, indicating theoretic
insignificance of that coefficient which means the co-integration relationship is unstable. The positive
sign of SoA coefficient means that the short-run deviation from the long-run does not converges to the
long-run equilibrium path. Result of the employed Chi-square test also shows the statistical insignificance
of the SoA coefficient. As it well known, the Johansen approach might give inadequate results even for a
sample size as large as 50. Therefore, the insignificant SOA coefficient might be the result of using small
sample. Moreover, the other employed co-integration tests, as can be seen from the results given in Tables
12 and 13, indicate that the variables are co-integrated. Therefore, we conclude that the variables are cointegrated and, based on the estimates obtained from the other two methods, give satisfactory findings.
16
The test results for residuals are in line with the conventional approach. (The test results are not provided
here, but are available on request). Coefficients of the regression equations are statistically significant at
1% significance level. The estimated coefficients are almost same in the two models, indicating the
robustness of the estimates. Once again, since the variables are measured in log form, the DOLS estimate
indicates that a 1% increase in government capital expenditures is associated with 0.388% increase in real
non-oil gdp.
V. Conclusion
As emphasized in Section III, the existing analysis of oil exporting countries from developing
and transition economies has made a lot of progress on the Dutch disease effects and linkages there
from through the appreciation of the real exchange rate and excessive procyclicality via government
consumption. On the other hand, the problems of oil revenue-triggered government investment in the
presence of limited absorptive capacity have to our knowledge hardly been touched. The purpose of our
paper on Azerbaijan has been to show that in the absence of sufficient absorptive capacity (as indicated
by little experience in manufacturing) even massive government capital expenditures are unlikely to
generate much progress in producing tradable non-oil products. We demonstrate this with the use of
three interrelated econometric models.
The first such model employed in this study suggests that oil price increases stimulate very
sizable increases in government capital expenditures. Specifically, a 1% increase in oil prices cause on
average a 1.66% increase in government capital expenditures. This of course is a major contributor to
volatility and procyclicality in the economy.
From the third such model, linking government capital expenditures to non-oil GDP, we show
that a 1% increase in government capital expenditures causes a much more modest 0.388% increase in
real non-oil gdp, a measure which includes much in the way of non tradables. From the second model,
the one most specific to our primary hypothesis and one not investigated in the previous literature, we
find that the impact of government capital expenditures on non-oil exports is negative. Specifically, a 1
unit increase in government capital expenditures causes a 0.157 units decrease in non-oil exports. Put
differently, through its fiscal operations, Azerbaijan’s oil revenues are used to substantially increase
government capital expenditures. While, in principle, these investments could help develop
manufacturing and other tradable goods output, in practice that is not happening.
But, as suggested above, under the right circumstances this could happen. We suggest that it
could happen if (but only if) these investments are carried out in a way that allows a sufficient amount
of absorptive capacity to be built in tandem with these investments. The facts that the impact on real
non-oil GDP is positive but rather small, and that the impact on non-oil exports (which excludes non
tradable from the non-oil GDP) is negative, makes it clear that our hypothesis is supported. The sector
which benefits most from oil revenues is the non-tradable goods sector which of course includes even
government services. Yet, expanding the production of government and other non-traded goods and
services does little to reduce dependency on oil and to avoid the Dutch disease and other problems
arising from oil booms in oil exporting developing countries.
Based on these findings plus what else we know from our broader review of Azerbaijan’s
experience since managing its own oil revenues, we urge the country’s policymakers to adopt several
important reforms. First, it should reaffirm and further tighten the fiscal rule that it adopted and make
information relevant to it easily available to the legislature and citizenry to make sure that any such rule
could never be violated as it seems to have been in a number of recent years. This would not only
mitigate the extent of real exchange rate appreciation but would also reduce the rapidly expanding non17
tradable sectors including government; which undermines the non-oil diversification in sectors that are
internationally competitive including exports.
A second and complementary reform is to strengthen the savings for the future component in
SOFAZ so that it should perform at least as well as it was intended to. Third, it should moderate the pace
of growth of its government capital expenditures so that these do not exceed the capability of the country
to absorb them efficiently. Increasing the involvement of civil society organizations in the reporting of oil
revenues and expenditures, so as to regain its recently lost fully compliant status in EITI (as discussed in
Section I) could be an important vehicle for achieving this objective. Fourth, at the same time it should
see to it that these capital expenditures are allocated to an increasing degree toward tradable goods sectors
like manufacturing that can help diversify the economy away from oil. Fifth, in order to help direct its
government capital expenditures to tradable goods like manufacturing, it should make this the primary
focus of its recently initiated “2015 - 2020 State Program on Industrial Development". Sixth, to minimize
waste and inefficiency of such expenditures at this rather crucial time in Azerbaijan’s development, heavy
emphasis should be given to the use of appropriate program evaluation techniques and to the use of welldesigned training programs for the workers and managers to be employed in these industries and in others
to which these industries may be linked. These programs could go a long way toward improving the
absorptive capacity that has quite understandably limited Azerbaijan’s ability to diversify in the direction
of industrial development to date.
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