Download DETERMINANTS OF U.S. PRIVATE FOREIGN DIRECT

J. OF PUBLIC BUDGETING, ACCOUNTING & FINANCIAL MANAGEMENT, 9(2), 331-355
SUMMER 1997
DETERMINANTS OF U.S. PRIVATE FOREIGN DIRECT
INVESTMENTS IN OPEC NATIONS : FROM PUBLIC AND
NON-PUBLIC POLICY PERSPECTIVES
Kingsley O. Olibe and C. Larry Crumbley*
ABSTRACT. Previous research demonstrates that non-public policy variables (wage rate,
raw material, GDP, GDP/capita, inverse of tax rate, and population) have significant influence
in determining the flow of U.S. investment. Research has not, however, demonstrated that
government accounting variables significantly affect Foreign Direct Investments (FDI) flow
into either Organization of Petroleum Exporting Countries (OPEC) or non-OPEC countries.
In light of this omission, the focus of this inquiry is on the examination of the potential influence
of both government accounting and non-public variables in influencing the flow of the stock of
U.S. foreign direct investment in the OPEC nations. To accomplish the objective, government
accounting and non-public policy variables are employed to investigate whether they matter
in determining investment flows into these countries. The results of the study suggest a direct
linkage between the flow of FDI and accounting variables.
INTRODUCTION
This article proposes and tests propositions related to two issues: (1) Do
government financial characteristics influence U.S. foreign direct investment
in OPEC countries ? and (2) Do non-government financial variables (wage
rate, GDP, etc.) systematically influence U.S. foreign direct investment
(FDI) in OPEC countries?(1) This study has two primary objectives. The first
is to identify public policy factors that determine the flow of stocks of FDI
into OPEC countries. The second objective is to determine any nonpublic
policy variables that explain why FDI flows into these countries. Since the
early 1980s, more countries have reversed their FDI policies with
_______________
* Kingsley O. Olibe is a Ph.D. Candidate, Department of Accounting, Texas A&M
University. Larry Crumbley. Ph.D., is KPMG Peat Marwick Professor, Department of
Accounting, Louisiana State University. His teaching and research interests are in
taxation and accounting education.
Copyright © 1997 by PrAcademics Press
332
OLIBE & CRUMBLEY
a view towards encouraging and facilitating its flow. In retrospective,
determinants of the flow of foreign direct investments have been an elusive
variable for empirical research. Loree and Guisinger (1995) suggest that the
elusiveness of FDI determinants is predicated on the operational difficulties of
the policy variables, which are hard to capture.
In investigating FDI determinants, Root and Ahmed (1978) employed
statutory corporate tax rate as a proxy to capture the overall effects of fiscal
policies on new investors’ sentiments, ignoring the effects of tax holidays,
costs allocation of tangible assets (accelerated depreciation), and other policy
incentives that diminish or dilute the effects of corporate tax rate on reported
earnings. Agodo (1978), for example, used growth in domestic market,
income per capita, lower wage rate, etc. to proxy for U.S. (manufacturing
firms) foreign direct investment in Africa. More recently in a cross-sectional
study, Loree and Guisinger (1995) employed net investment incentives, net
performance requirements measure, cultural distance(1) wage rate, and the
inverse of host country tax rate to examine U.S. stock of FDI flow to forty
countries. Contrary to intuition, their study did not find wage rates to be an
insignificant determinant of FDI in 1977 and 1982.
These studies suffer from misspecifications, ignoring the effects of rate
of return on invested capital (ROI), government type, and the liquidity of the
host government (surplus/deficit budget). A budget deficit, ceteris paribus,
translates to higher tax rates for firms and individuals. The net effect is a
reduction in disposable income (Y-T=Yd), which dampens consumption
patterns. The problem of omitted variables limits the generalization of the
research outcome. Vernon (1977) suggests that FDI flows, for instance, are
usually influenced by the nationality of the entrepreneurs. The location of
most units of a multinational network, however, are predicated on their
functions such as market seeking, resources control, and tax havens. Some
affiliates (Goldsbrough, 1979) posit that FDI flows are located by “straightforward least-cost calculations aimed at minimizing the delivered cost of the
output.”
While these studies are vital and valid, there exists a void in both
empirical and theoretical research investigating public policy determinants of
U.S. FDI flows to OPEC countries. The OPEC countries possess an
abundance of a world-important natural resource--petroleum. Thus, the
principal objective of this study is to examine the role of public accounting
and nonpublic policy determinants of FDI in the host OPEC nations. (1) The
remainder of this article is organized into six sections: section 2 describes
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
333
background information, motivation, and a brief literature review; OPEC
history is explained in section 3; section 4 delineates the hypotheses and
model form; variable selection, and data descriptions are explained in section
5; and the final section contains a summary of the findings and conclusions.
BACKGROUND
Developing nations in particular are employing the stock of FDI as a
source of capital, technology, managerial know-how and other resources that
are essential for sustainable and stable economic development and growth.
This phenomenon was widespread during the early 1990s, as developing
countries and economies in transition create incentives for FDI flows. In
1993, the flow of FDI received impetus from a number of vital developments
at the international level. While differences exist in the scope and depth of
the free-flow of foreign direct investments and the operations of multinational enterprises (MNEs), regional bilateral and unilateral efforts have led
to a remarkably favorable government policy towards FDI flow among
countries (Fatouros, 1990).
Governments of various countries had adopted market distorting
measures such as concessionary tax rate and other incentives designed to
attract and encourage FDI. Accordingly, investment incentives are
government measures designed primarily to influence the location, size or
industry of an investment by affecting relative cost or potential for earnings or
by altering the risks of such business (OECD, 1976). Some of the major
investment incentives include tax incentives (e.g. tax holidays, accelerated
depreciation of tangible assets, tax credits, lower tax rates), and other financial
incentives, such as grants, preferential loan treatment, lower cost of capital,
tariff concessions and structural measures, including the provision of
infrastructure and quality of labor skills. Guisinger and Associates (1985)
suggest that, on the whole, incentives distort resource allocation. Relative
abundance of natural resources may make a country more attractive for FDI
flow.
In spite of these developments, there are still differences in the nature of
measures taken by nations, reflecting differing political, economic and social
priorities and attitudes towards FDI flows. Therefore, to gain an insight and
understanding of FDI flows and the spread of MNEs, an important question
is what public and nonpublic policy
factors determine overseas
investments?(1) The vital nature of this question may be viewed from two
334
OLIBE & CRUMBLEY
perspectives. First, the mode of entry into foreign markets is predicated on
the motive underlying the FDI flows into the host country. Second, FDI flow
depends upon the long-term objectives of the firm entering into the host
country. Thus, any theoretical or empirical study to provide information on
international investment decisions must reflect a firm’s motive to engage in
cross-border economic activity.
Further, government policy on equity investment must be designed with
a clear understanding of the factors that determine foreign direct investment.
In a global economic setting, MNEs capital allocation decisions are influenced
by their capacity to generate funds for investment. The allocation of funds for
foreign capital outlay depends on the expected rate of return, infrastructure,
concessionary tax rates, host country cost of capital, budget surplus/deficit of
the host country, host country reserves in exchangeable currency, political
risk, government type, wage rates, gross domestic product (GDP) per capita,
population, and balance of payment viability.(1) The economic underpinnings
of these variables are discussed in the variable selection section.
Motivation
There is substantial literature relating to the flow of foreign direct
investments (FDI). Research on FDI has largely focused on U.S. FDI flow
into Europe, NAFTA Signatory nations, Asia and Pacific Rim nations, and
economies in transition (Eastern Europe). In a cross-sectional study of
countries, Loree and Guisinger (1995) employed Net Investment Measures,
Net Performance Requirement Measures, Cultural Distance, and Tax Rate as
a proxy for public policy determinants of FDI flow.
This study provided evidence of the significance of tax rate and gross
domestic product per capita variables in 1972, but they were insignificant in
1982 in determining U.S. FDI flow. Cultural distance, however, was
significant in 1977 but insignificant in 1982, and infrastructure variables were
significant in both years. With respect to FDI flows based on risk avoidance
or minimization, Boatwrite and Renton (1975) suggest that oversea capital
stock is a function of international differences in interest rates of long-term
government bonds. Thus, FDI flows are sensitive to U.S. and foreign real
cost of capital and investment demand variables.
Caves (1996) employed capital asset pricing model (CAMP) to
demonstrate how low risk tolerance investors “behave as market competitors
set asset prices that convey claims to uncertain streams of future cash flows.”
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
335
According to Caves, the principal concept underlying risk aversion is the
diversification of the composition of the portfolio to maximize wealth and
minimize risk inherent in volatile assets. Thus, FDI offers firms
diversification opportunity absent in local markets. The financial-hierarchy
hypothesis posits that exchange rate movements will induce a wealth effect
due to the willingness of firms to acquire assets abroad. Goldsbrough (1979)
conjects that the proportion of MNEs oversea borrowing depends on
international interest-rate differentials, the distribution of its capital
investments between countries, and the covariation of cash flows from the
investment. Hymer’s (1960) FDI theory postulates that firms undertake
oversea investments due to the monopolistic advantages inherent in such
ventures “relative to host firms, in an imperfect market environment.” There
is empirical evidence in support of the monopolistic advantage of FDI theory,
indicating that MNEs possess monopolistic rents over host firms (Kim and
Lyn, 1986).
Agodo (1978), employing the ordinary least square (OLS) model in a
study of the determinants of U.S. equity manufacturing investments, found
no significant relationship between African low wage rate, but systematic
support for both GDP and GDP/capita which were proxies for domestic
market size and income level of the citizens. From a different perspective,
Lecrew (1991) argued that FDI flows are sensitive to shifts in the locational
attributes of a host country. According to Loree and Guisinger (1995),
Lecrew’s model is based on the assumption that the stock of FDI in each
country is at equilibrium state at the commencing period. Thus, changes in
the stock of FDI flows is a function of shift in the productive resource
variables (capital, labor and other input resources) of the host country. The
theoretical and empirical literature reviewed above suggest that MNEs
rationalize cross-border production to exploit international differences in
factor prices.
Thus, government incentives (quality of infrastructure, budget surplus,
trade policy, mineral resources, lower cost of capital, etc.) may increase the
attractiveness of FDI flow in a country. Among the empirical and theoretical
studies examining U.S. FDI flow, Moxon (1975), Kirkpatrick and Yamin
(1981), Lee (1986), and Clark, Sawyer and Sprinkle (1989) have analyzed
FDI nonpublic policy determinants across industries. These studies found
stock of FDI flow to be significantly related to a measure of labor intensity
and inversely related to a measure of capital intensity.
336
OLIBE & CRUMBLEY
Others such as Woodward and Rolfe (1993) employing conditional logit
models examined determinants of country selection in direct investments.
Their study found that the probability of country selection varied inversely
with wage rates, and favorably with quality of infrastructure and duration of
tax holidays, among other factors. Contractor (1991) and Nigh (1985),
directed their studies on the levels of host countries locational characteristics.
Although these two studies examined locational selection from differing
perspectives, Nigh specifically focused on the impact of political stability,
while Contractor emphasized the consequences of government policies in
inducing FDI flows. In general, the two studies conceptually share the same
theoretical framework that the stock of FDI flows are functions of host
country locational characteristics.
While these studies have offered some perspectives on the locational
determinants of FDI flows, none has really addressed the determinants of
U.S. FDI flows in OPEC countries, given their unique possession of natural
resources needed by the industrialized world. Therefore, this inquiry focuses
on the determinants of U.S. foreign direct investments in OPEC countries.
Specifically, the study examines the association between public policy and
nonpublic policy determinants of stock of FDI flows into the OPEC nations.
History of OPEC Member Nations
The union of thirteen sovereign nations into the group now known as the
Organization of the Petroleum Exporting Countries (OPEC) is a natural
phenomenon evolving from the geographic distribution of petroleum reserves.
The OPEC came into existence due to a conference held in Baghdad, Iraq,
September 9-14, 1960 (Danielsen,1982). The founding members (Saudi
Arabia, Iran, Kuwait, Iraq and Venezuela) have veto power over the
admission of new members, but otherwise all full members have equal rights
within the organization. For membership into the cartel, the country must be
a “substantial net exporter,” and the petroleum interest must be fundamentally
in consonance with those of member countries. (1)
The OPEC cartel derives its power from the fact that its members own
and control two-thirds of the world’s known petroleum reserves, and their
exploration and extraction costs are minuscule. Of the known oil reserves,
OPEC effectively controls in excess of 75 percent, and currently produces
over 40 percent of the crude oil consumed worldwide (Suranovic, 1994).
Current estimates of the ratio of reserves to production are 79.6 years for
OPEC nations while the worldwide ratio is estimated at 40 to 45 years. (1)
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
337
Petroleum from the cartel can effectively compete favorably with alternative
energy resources. OPEC members export approximately 86% of the
petroleum resources entering into international trade. The modus operandi of
the cartel is to substitute collective interest for individual action (Danielsen,
1992).
The world petroleum market is only a part of the total resource and
energy picture, but it is the largest, and by many criteria, the most important
part. Petroleum is the swing fuel in energy markets, and OPEC is the swing
producer. Furthermore, the prices of all other energy resources are
dependent on the current and prospective price of oil (Danielson, 1982).
The oil industry is by far the most important industry in the world as
measured by sales volume. Appendix A shows that 20 percent of the top 44
U.S. corporations relative to sales are oil companies. Danielsen (1982),
suggests that petroleum accounts for half the tonnage, two-thirds of the ton
miles, and one-fourth of the value of all commodities exchanged in
international markets. The U.S. is the leading energy consumer and leading
oil importing country. Empirical evidence regarding U.S. FDI flow into these
petroleum resource-rich countries represents a void in the accounting
literature. The purpose of this study is to fill that void.
This investigation contributes to the extant literature by providing
evidence that governmental accounting and financial practices influence U.S.
stock of FDI flow into the OPEC countries. Any empirical examination of
U.S. FDI determinants requires the inclusion of non-policy variables to
control for alternative explanations. Thus, this article first develops the
propositions that will test the effects of both government accounting variables
and well-established non-policy variables on FDI.
HYPOTHESES AND MODEL DEVELOPMENT
The variables thought to influence the stock of investment flow can be
broken into two broad categories, including a distinction between public and
non-public policy variables. In theoretical and empirical concepts, the
decomposition of these factors into these categories seems logical, given the
normative desire of bureaucrats to manipulate accounting numbers that
consequently influence the flow of investment. In retrospect, non-policy
factors also are subject to manipulation, though their rate of change is
assumed to be slower than that of public accounting and financial variables.
338
OLIBE & CRUMBLEY
It is vital to examine public accounting factors and nonpublic variables
influencing the flow of U.S. FDI to these countries, and their unique
characteristics relative to petroleum surpluses. Therefore, our explicit
objective is to investigate through empirical testing what public and nonpublic
proxies influence U.S. FDI flows into the OPEC nations. These variables
relative to FDI provide an indication of what government incentives and
financial characteristics induce U.S. FDI flow to offshore production activity.
Specifically, the focus of this study is to identify empirically the financial,
economic and political characteristics of the OPEC countries that are
expected to enhance their attractiveness for U.S. FDI. Therefore, we used
the model form that relates to absolute values of both government accounting
and non-government accounting variables that explain United States’ FDI
flows.
The basic analytical approach consists of two testable propositions each
of which postulates an independent proxy that simple economic logic or
empirical evidence demonstrates to be relevant in explaining FDI decision.
Agodo (1978), and Loree and Guisinger (1995) employed the ordinary least
square (OLS) regression model in their analyses of FDI flows. Both models
proved to be statistically significant. Thus, the specific statistical
methodology for this research is multiple regression for one dependent
variable definition, and the hypotheses to be tested are stated in the alternate
form. Thus, we propose the following hypotheses:
H1: Ceteris paribus, U.S. FDI flow to the OPEC countries is likely to be
systematically influenced by any one of the government policy
variables, such as budget surplus/deficit, foreign reserves, etc.
H2: Ceteris paribus, U.S. FDI flow to the OPEC countries is likely to be
systematically influenced by non-public policy variables, such as
GDP, change in wage rate, GDP/capita, population, etc.
Model Form, Variable Selection, and Explanations
The OLS model exployed to test the explanatory power of both
governmental accounting and nonpolicy variables are stated as follows:
ln(FDI) = á0 + â1 BUSD + â2 RESER + â3 ln(GOCA) +
â4 DESER + â5 POLSA + â6ÄCUDV +
â7 ln(AVBAR) +â8 GOTYPE + åi
ln(FDI) = á0 + â1 ÄWARA + â2GDPC +â3GDP +
(1)
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
339
â4POPU + åi
(2)
where:
FDI is the normalized logarithmic dollar value of U.S. foreign direct investment
flow to
each of the countries under investigation. Alternatively, FDI is the aggregate composite
of equity investment, reinvested earnings, and other long- and short-term capital flows
received by each of the OPEC countries.(1)
BUSD is the deflated value of budget surplus/deficit from each OPEC country
measured at fiscal year-end. The BUSD of the central government is deflated by
population.
RESER is a measure of international liquidity (i.e., Special Drawing Rights,
the country in foreign accounts measured at the end of the fiscal year.
gold, etc.) of
GOCA is the logarithmic value of government capital expenditure measured at
of the fiscal year.
the end
DESER refers to the debit service ratio (i.e., central government cost of capital)
external indebtedness of the country measured at the end of the fiscal year.
due to
POLSA is the political risk-index that measures the relative political stability of
anation.
ÄCUDV is a measure of the rate of devaluation of the host country monetary unit relative
to the U.S. dollar.
AVBAR is the average daily crude petroleum production measured at the end of
year.(1)
the
GOTY refers to the nature of the host country government (i.e., elected or unelected
government) and is employed as a dummy variable (1= elected, 0, otherwise).
á and âs are the OLS regression coefficients; and åi is an error term.
The research design has two specific tasks to test empirically the effects
of (1) governmental accounting and financial policies, and (2) non-public
sector factors in explaining U.S. foreign direct investment flow in the OPEC
countries. The economic rationale and our prior expectations about the
variables in the models are as follows. Prior studies examining U.S. equity
investments abroad employed the aggregate foreign direct investment, even
though some components of FDI respond differently to location
characteristics of the host country (Agodo, 1978). Loree and Guisinger
(1995) desegregate FDI by excluding reinvested earnings. However, we argue
that both reinvested earnings and inter-firm debt components of FDI should
be excluded because they carry elements of sunk-costs that are unaffected by
the host country factors that invariably affect initial investment flow from the
340
OLIBE & CRUMBLEY
U.S. More specifically, the primary focus of this study is on the factors that
influence the component of FDI that originates from the U.S. to the OPEC
countries. This component of FDI is the one more likely to face government
scrutiny and incentive packages.
The surrogate chosen to represent internal liquidity and financial efficacy
of the host government is budget surplus/deficit. A budget surplus in the
presence of zero taxation is interpreted as “good news” and budget deficit
implies “bad news” by the investment community. A budget surplus is
indicative of a government’s prudent financial husbandry, and a deficit is
viewed otherwise. Budget deficit may be interpreted as a government’s
excess expenditures that may induce potential austerity and concomitant
higher taxes. A negative coefficient is predicted for BUSD, reflecting the
relative preference for a budget surplus.
The level of international liquidity of each country is proxied by the
absolute value of that country’s foreign reserve. The higher the international
solvency of a country relative to exchangeable “hard” currencies, the greater
the likelihood of investment flow. Thus, a positive coefficient is predicted,
reflecting earning repatriation motive of firm owners. Government capital
expenditure is used as a proxy to capture particularly the level of
infrastructure (e.g., roads, airports, wharf, etc.). This choice is based on
previous research by Loree and Gusinger (1995), Schneider and Bruno
(1985), and Agodo (1978), who found infrastructure significant in explaining
FDI flow. The debt service ratio is chosen as a proxy for cost of capital by
the central government of the OPEC countries. This ratio focuses on the
proportion of the GDP that is used to service external debts. A high debt
service ratio raises the specter of increased risk default on international loans.
Therefore, the expectation is that higher (lower) debt service ratios should be
negatively (positively) associated with U.S. FDI flow.
Political risk-index is a surrogate for relative political and social stability
of the countries under investigation. The political and social stability of a
country minimizes the uncertainty of potential investors, and may induce U.S.
foreign direct investment flow, though prior analyses relative to the
relationship between political strife and FDI have resulted in differing
perspectives. Agodo (1978) and Contractor (1991) suggest that political and
social stability are essential in foreign investment decisions. Firms may give
different considerations to the political, social, and economic conditions of a
country prior to assets commitment. The political risk-index employed in this
study is a country composite score developed by The Economist cited by
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
341
Shapiro (1992). The formula for the composite risk-index is weighted more
heavily toward political risk, which fits the study.
The composite score ranges from a high of 57 for a high-risk
environment to 11 for a relatively risk-free environment. Since many
investors are risk-averse, the expectation is for a positive (negative)
coefficient relative to risk-free (volatile) environment.
International transactions are sometimes hampered by the lack of
currency homogeneity. To proxy for the devaluation of a host country’s
currency, we selected the rate of change in currency. Where a country
maintains an overvalue exchange rate, the ability to maintain debt service is
dim. Thus, a devalued currency relative to the dollar, ceteris paribus will
induce FDI flow as the dollar’s purchasing power rises with devaluation.
Currency devaluation will more likely improve FDI flow, hence, demand
elasticity for petroleum is relatively high. The raw material variable is proxied
by the logarithmic value of average daily barrels of crude petroleum
production. Given that the U.S. is a net importer of oil, the expectation is a
positive relationship between raw material (crude petroleum) and the flow of
U.S. foreign direct investment. The proxy for elected and unelected officials
is government type. No prediction is made with respect to the GOTY
coefficient because most OPEC country governments are absolute monarchs.
Non-public Policy Variables
Labor costs are an integral component of drilling and production activity
in the oil and gas industry. Therefore, high labor costs may be a structural
impediment to the investment location decision of a U.S. investor, particular
in a labor intensive industry. Agodo’s (1978) study of the investments of
thirty-three U.S. manufacturing firms in selected African countries found that
the relatively low labor African wage rate is insignificant in determining the
flow of FDI. Conversely, Woodwind and Rolf (1993) found a significant
negative association between wage rates and the probability of country
selection for export induced FDI in the Caribbean Basin. Loree and Gusinger
(1995) and Schneider and Frey (1985) both found labor wage rates to be a
significant determinant of U.S. foreign direct investment flow. Although the
empirical outcomes have been mixed, the economic rationale behind the
association between wage rates and FDI location decision is still supported.
Thus, we expect a negative (positive) relation between high (low) wage rates
within a country and the level of investment flow.
342
OLIBE & CRUMBLEY
Gross Domestic Product (GDP) Per Capita is chosen as a proxy for
income level for the residents of the countries under study (Agodo, 1978;
Loree and Gusinger, 1995). High income level stimulates high standard of
living and consumption patterns. Thus, with the stream of oil revenue, some
OPEC countries experienced an enhanced GDP per capita. The expectation
is for a positive and significant relationship between GDP per capita and
investment flow.
Gross domestic product is a surrogate for each of the countries’
domestic market size. We expect host-country market size to be influential
because of the obvious fact that investment in oil drilling and production will
usually require maximum plant capacity and output level to justify any
investment. The larger the market, the more the probability of the flow of
U.S. investment.
Cost of capital is a proxy for lending rate in the host country. The
capital-arbitrage hypothesis posits that multinational corporations borrow
where the world funds are cheapest and invest them where expected returns
are highest (Caves, 1996: 160). The expectation is that the high cost of
capital should negatively correlate with FDI flow. Though, most OPEC
nations do not have functioning capital markets, there is some suggestion that
MNEs have utilized local borrowing as off-balance-sheet financing, to
minimize the parent’s leverage ratio upon consolidation. Robbins and
Stobaugh (1973: 127) noted that affiliates of multinational firms demonstrate
higher aggregate proportion of current liabilities to current assets than their
parents’ domestic operation. This behavior is consistent with a risk-induced
reliance on local currency financing.
Since most firms are profit maximizers, we conjecture that lower cost of
capital should be associated with investment flows. Size variable is proxied
for population. Though the population parameter is employed to compute
GDP per capita, it is included for varying population size of the OPEC
countries. On the basis of gross domestic product per capita alone, some
OPEC countries may be considered poor and unattractive for investment
decision. Yet some of these countries may have large populations so that on
the average, aggregate purchasing power may be appealing. We expect a
positive relationship between each country’s population and U.S. investment
flow. The predicted sign for each dependent vvariable is summarized in
Table 1. The negative (positive) sign indicates a negative (positive)
relationship between the independent and the explanatory variable. No sign
prediction is made between government type (GOTY) and FDI flow.
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
343
SELECTION AND DATA DESCRIPTIONS
TABLE 1
Summary of Coefficient Sign Predictions for Equations 1 and 2
_____________________________________________________________________
Independent Variable
Predicted Sign for the Dependent Variable (FDI)
--------------------------------------------------------------------------------------------BUSD
-
CUDV
-
GOTY
?
FOSER
+
DESER
-
GOCA
+
AVBAR
+
POLSA
ÄWARA
+
+
GDPC
+
GDP
+
POPU
+
COTAX
-
COCA
-
FDI = the normalized logarithmic dollar value of U.S. foreign direct investment flow to the OPEC
countries.
BUSD = the deflated value of budget surplus/deficit from each OPEC country measured at year-end.
CUDV = a measure of the rate of change of the host country monetary unit relative to the dollar.
GOTY = refers to the nature of the host country government (i.e., elected or unelected government),
and is employed as a dummy variable (1= elected, 0, otherwise).
FOSER = a measure of international liquidity of the host country. It reflects the country’s special
drawing rights in tradable currencies.
DESER = the debit service ratio (i.e., central government cost of capital) due to external indebtedness
of the country.
GOCA = the logarithmic value of government capital expenditure on infrastructure, etc.
AVBAR = the average daily crude petroleum production measured at the end of the year.
POLSA = the surrogate for relative political and social stability of the OPEC nations.
ÄWARA = a measure of relative change in labor costs.
GDPC = measure of income level of the citizens of the OPEC nations.
GDP = measure of the relative size of the host country domestic market.
POPU = the total number of the citizens of the host countries.
COTAX = the effective corporate tax rate on earnings of multinational firms engaged in operation in the
OPEC countries.
COCA = the lending rate or cost of capital in the host country.
344
OLIBE & CRUMBLEY
The sample analyzed in this study consists of OPEC members for a six year
period from 1989 through 1994. The sample of the countries and the daily
production of crude petroleum was obtained from the OPEC’s 1993 Annual
Statistical Bulletin.(1) The key government accounting and financial data
(budget surplus/deficit, international liquidity, etc.), population size, and
lending rate were obtained from the 1994 International Financial
Statistics(1). Currency devaluation rates, debt service ratios, changes in wage
rates, GDP, and GDP per capita were obtained from U.S. Bureau of
Economic Analysis (1993). The initial sample consists of 13 OPEC
countries, with 78 observations. We exclude Libya, Iraq and Algeria because
TABLE 2
Descriptive Statistics for Regression Variables in Equations 1 and 2
______________________________________________________________
_
Variable
Mean
STD
MIN
MAX
-------------------------------------------------------------------------------------------F
B
1316.4
-18.27
1283.47
30.48
-401.00
-139.20
5015.00
14.70
C
G
-1.05
.17
3.45
5.98
-18.56
-21.10
.42
8.70
F
D
G
A
4967.9
19.00
11.46
2156.9
4215.41
16.55
13.44
2041.59
12.00
00
1.18
150.00
16748
68.00
51.04
8331.70
P
Ä
G
G
P
25.13
.17
6012.4
48.60
44.23
12.83
5.9
6672.43
42.4
65.91
11.00
-21.10
275.00
3.98
1.80
42.00
8.70
21175.0
144.58
203.54
C
.427
.14
.20
.68
C
.18
.18
.00
.75
______________________________________________________________________
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
345
of missing data. Based on these criteria, the final sample yielded 10 countries
with 60 observations.
The descriptive statistics of the variables used in the models is presented
in Table 2. Clearly the international liquidity variable (FOSER) dominates in
average size and dispersion. Appendix B displays Pearson Correlations for all
the variables. These correlations do not suggest any collinearity problems.
We also examined a more reliable indicator of collinearity, the eigenvalue and
the variance inflation factor (VIF) for each explanatory variable, and no
eigenvalue exceeded 5.00 in magnitude. A level of 30 for the eigenvalue and
10 for the VIF is generally an indication of a problem according to Neter,
Wasserman and Kutner (1989) and Kennedy (1992).
EMPIRICAL RESULTS
Cross-Sectional Results
Table 3 reports equations 1, 2 and 3 coefficient estimates and statistical
significance levels. The model has a high degree of explanatory power
employing host government accounting and financial measures with R2 above
.90. Generally, the estimated coefficients are statistically significant and,
where sign predictions are made, carry expected signs. Consistent with Table
2 predictions, the DESER, FOSER, GOTY, GOCA, GDPC, GDP, and
COTAX coefficients reported in Table 3 are positive and highly significant at
.0001, .005, .05 and .10 levels with respect to the flow of U.S. investment.
These results suggest that government accounting and non-policy variables
are value-relevant in attracting U.S. investment to these OPEC countries.
More specifically, government capital expenditure is highly significant with the
expected positive relationship. With respect to non-public policy variables,
GDP, COTAX, and AVBAR are significant and consistent with Agodo, 1978
and Loree and Guisinger (1995). The results of this study do not support the
population factor as an influencer of investment flow. This lack of support
appears to be inconsistent with Agodo’s 1978 outcome.
The economic underpinning represented by the level of infrastructure
which exists in a nation influences the flow of U.S. direct investment is
demonstrated in this study. When average daily barrels of crude oil is
included in the government accounting and financial model (i.e., the FDI
measure), currency devaluation lacks significance. This lack of significance
implies that petroleum resources is vital for U.S. FDI flow into these nations.
346
OLIBE & CRUMBLEY
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
347
A possible explanation for the lack of significance for currency devaluation
(CUDV), change in wage rate (ÄWARA), and population (POPU) may be
investors= indifference.(1) Consequently, if investors’ are indifferent to the
host country currency devaluation, wage rate and population, then the sign of
the coefficient is investment flow insensitive. A somewhat surprising result is
the negative coefficient of average daily barrels of crude petroleum production
which is a proxy for raw material in the government accounting model.
Intuitively, prior expectation is that U.S. FDI flow is specifically to access such
unique natural resources to hedge against future potential oil shock. This
conjecture is supported by the highly significant level (.005) of average daily
crude petroleum production in the non-public policy model, although the sign
of the coefficient is not as predicted. One explanation for the negative
coefficient is the incremental capital commitment associated with exploration
and drilling, noting that petroleum is a depletable resource. Thus, as the oil
wells are depleted, there is more likelihood for potential investment for
exploration. In a separate result not reported, average daily barrels of oil in
Model 1 is significant at .10 percent level in a two-tailed test.
CONCLUSIONS
This study presents empirical evidence pertaining to a number of
government accounting and financial variables of relative influence in
determining U.S. foreign direct investment in the OPEC countries. With
respect to accounting variables, the investor should be cognizant that
government policies change with time. These governments are not subject to
external evaluation and monitoring with respect to their budgets, making it
impractical to determine whether the budget surplus/deficit is overstated
(understated). One noticeable condition is a change in government corporate
tax policy and earnings repatriation. Changes in these OPEC policies can either
stimulate or stifle investment flow within a year or more.
As with any empirical study, there are limitations. This study is limited to
the determinants of U.S. equity investment in the OPEC countries. Foreign
direct investment from other countries may have differing responses to the
accounting and financial factors found significant here. With respect to U.S.
FDI flow, we have been unable to disaggregate export-oriented investment
flow and foreign direct investment specifically designed to serve host country
petroleum resource exploration.
348
OLIBE & CRUMBLEY
According to Loree and Gusinger (1995), the separation of investments
into export-oriented investments and foreign direct investment is vital due to
host country tariff, custom, and excise policies on exports and imports.
Further, host country wage rate, income level, and population size are not
significantly related to investment flow. The evidence in this study suggests
that the crucial factors that influence U.S. FDI flow to OPEC countries are
factors that permit earnings repatriation, promote stable economic growth and
development. Despite the robustness of the test results, most of the variables
are based on estimates; hence, in third-world countries, data for empirical
research are hard to operationalize. However, test results corroborate H1 and
H2 that accounting and non-public policy variables are key determinants of
investment flow. Another study is necessary to test and accentuate the
relevance of government accounting variables in influencing investment flow in
non-OPEC countries.
Finally, the normative desire of government bureaucrats to manipulate
accounting numbers and create fiscal illusion should be considered when
interpreting the implications of the findings.
NOTES
1.
Foreign direct investment (FDI) is an investment in which a resident of
one country obtains a lasting interest in, and possess a degree of influence
over the management of a business enterprise in another country. In the
U.S., the criterion used to distinguish U.S. direct investment abroad
(USDIA) from other types of investment is the 10 percent ownership of a
foreign firm.
2.
Cultural distance may be defined as the cultural differences among
nations which create potential investment uncertainty between the home
and host countries. In general, culture represents the “set of attitudes and
values that are common to a group of people” (Benito and Gripsrud
1991).
3.
It is evident that the unprecedented rise in oil prices in 1973 due to the oil
embargo induced U. S. foreign direct investment (FDI) flow in OPEC
countries to secure supplies of petroleum resources..
4.
The worldwide coordination of resources by a single centralized
management distinguishes MNEs from other firms engaged in
international business activities. From a financial theory standpoint,
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
349
MNEs have the ability to shift money and earnings among their affiliated
firms by internal transfer mechanisms.
5.
Political stability measures may include the rate of changes of
government, the level of violence associated with governance, the number
of armed insurrections, military conflicts with other states, and religious
and ethnic strife.
6.
Other OPEC member countries are Nigeria, Libya, Algeria, Qatar,
Ecuador, and Gabon.
7.
This ratio is computed by dividing proven recoverable petroleum reserves
for a given year by production for the same year. The interpretation of
the ratio is that reserves exist for “Y” number of years if the production
rate remains constant (i.e., continues at the current rate of drilling and
refining). For a detailed discussion of world-wide petroleum ratio, see
OPEC (1994)..
8.
The natural log of FDI was used to transform the dependent variable
since the Kolmogorov goodness-of-fit-test for normality rejected the
normality assumption at .05 level of significance. Besides, OLS regression
results exhibit nonrandom pattern in plots of residual against predicted
value when FDI (untransformed) is employed as the dependent variable.
Upon transformation, the Kolmogorov test fails to reject the normality
assumption at .05 level, and the residual plots show a linear pattern.
9.
To lessen departures of residual errors from normality in the estimated
regression model, the log of average daily barrels of crude petroleum
production is used. Other variables are not transformed because they are
not highly skewed, and also some of the data have negative values. They
were also not transformed in order to maintain consistency with prior
studies that employ some of the variables in model 2.
10. The Annual OPEC Statistical Bulletin is published annually by the
OPEC Secretariat, headquartered in Vienna Austria. The Bulletin
includes all information on OPEC oil production.
11. The International Financial Statistics is a publication of the IMF, which
includes information on most central government financial and nonfinancial data
12. We examined for lag structure effect on the DEVAL variable, and the
result is consistent with the result reported here
350
OLIBE & CRUMBLEY
REFERENCES
Agodo, O. (1978, March), “The Determinants of U.S. Private Manufacturing
Investment in Africa,” Journal of International Business Studies, 9: 95107.
Benito, G. R. G., and Gripsrud, G. (1991), “An Expansion of Foreign Direct
Investment: Discrete Rational Location Choices or a Cultural Learning
Process?” Journal of International Business Studies, 23, 3: 461-76.
Boatwright, B. D., and Renton, G. A. (1975, November), “Analysis of United
Kingdom Inflows and Outflows of Direct Foreign Investment,” Review of
Economics Statistics, 57: 478-86.
Caves, R. E. (1996), Multinational Enterprise and Economic Analysis,
Cambridge: Cambridge University Press.
Clark, D. P., Sawyer, W. C., and Sprinkle, R. L. (1989, May), “Determinants
of Industry Participation Under Offshore Assembly Provisions in the U.S.
Tariff Code,” Journal of World Trade, 23: 123-30.
Contractor, F. (1993), Do Government Policies Towards Foreign Direct
Investment Matter? An Empirical Investigation of the Link Between
National Policies and FDI Flows (UNCTC Current Series A, No. 21),
New York: United Nations.
Danielsen, A. L. (1982), The Evolution of OPEC, New York: Harcourt Brace
Jovanovich.
Fatouros, A. A. (1990), “The Code and the Uruguay Round Negotiation on
Trade in Services,” Centre Reporter, 29: 7-15.
Goldsbrough, D. J. (1979, December), “The Role of Foreign Direct
Investment in the External Adjustment Process,” IMF Staff Paper, 26:
725-54.
Guisinger, S. and Associates (1985), Investment Incentives and Performance
Requirements, New York: Praeger.
Hymer, S. A. (1960), The International Operations of National Firms: A
Study of Direct Foreign Investment (Ph.D. dissertation), Cambridge,
MA: MIT Press.
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
351
International Monetary Fund (1994), International Financial Statistics
Yearbook, XLVII, Washington, DC: Author.
Kennedy, P. (1992), A Guide to Econometrics, 3rd ed., Cambridge, MA:
The MIT Press.
Kim, W. S., and Lyn, E. (1986, January), “Excess Market Value, the
Multinational Corporation and Tobin’s Q-ratio,” Journal of
International Business Studies, 17: 119-125.
Kirkpatrck, C., and Yamin, M. (1981, April), “The Determinants of Export
Subsidiary Formation by U.S. Transnationals in Developing Countries:
An Inter-industry Analysis,” World Development, 9: 373-82.
Lecrew, D. J. (1991), “Factors Influencing Foreign Direct Investment by
Transnational Corporations in Host Developing Countries: A Preliminary
Report,” in P. J. Buckley and J. Clegg (Eds.), Multinational Enterprise
in Less Developed Countries, New York: St. Martin’s Press.
Lee, J. (1986, December), “Determinants of Offshore Production in
Developing Countries,” Journal of Development Economics, 20: 1-13.
Loree, D., and Guisinger, S. E. (1995, February), “Policy and Non-policy
Determinants of U.S. Equity Foreign Investment,” Journal of
International Business, 32: 281-299.
Moxon, R. W. (1975, January), “The Motivation for Investment in Offshore
Plants: The Case of the U.S. Electronics Industry,” Journal of
International Business Studies, 6: 51-65.
Neter, J., Wasserman, W., and Kutner, M. H. (1989), Applied Linear
Regression Models, 2nd ed., Homewood, IL: Irwin.
Nigh, D. (1985, January), “The Effect of Political Events on the United States
Direct Foreign Investment: A Pooled Time-Series Cross-Sectional
Analysis,” Journal of International Business Studies, 16: 1-17.
Organization of Petroleum Exporting Countries (1993), Annual Statistical
Bulletin, Vienna, Australia: Author.
Root, F. R., and Ahmed, A. A. (1978, March). “The Influence of Policy
Instruments on Manufacturing Direct Investment in Developing
Countries,” Journal of International Business Studies, 9: 81-93.
352
OLIBE & CRUMBLEY
Robbins, S. M., and Stobaugh, R. B. (1973), Money in the Multinational
Enterprise: A Study of Financial Policy, New York: Basic Books.
Schneider, F., and Bruno, F. S. (1985), “Economic and Political Determinants
of Foreign Direct Investment,” World Development, 13, 2: 161-175.
Shapiro, A. C. (1992), Multinational Financial Management, 4th ed.,
Boston, MA: Allyn and Bacon.
Suranovic S. M. (1994, July), “Import Policy Effect on the Optimal Price,”
Energy Journal, 15: 123-144.
U.S. Bureau of Economic Analysis, Department of Commerce (1993), U.S.
Direct Investment Abroad: Operation of U.S. Parent Companies and
their Affiliates, Washington, DC: Author.
Vernon, R. (1977), Storm Over the Multinationals: The Real Issue,
Cambridge, MA: Harvard University Press.
Woodward, D., and Rolfe, R. J. (1993, January), “The Location of ExportOrientated Foreign Direct Investment in the Caribbean Basin,” Journal
of International Business Studies, 24: 121-141.
U.S. PRIVATE INVESTMENTS IN OPEC NATIONS
353
APPENDIX A
Leading Petroleum Corporations in the United States, 1990
_______________________________________________________________
_
Firm Name (Head-Office)
Net Revenues
Rank among
(Billions of U.S. All U.S. Firms
Dollars)
---------------------------------------------------------------------------------------------1 Exxon (New York)
103.1
1
2 Mobil (New York)
59.5
2
3 Texaco (Harrison, New York)
51.2
4
4 Standard Oil of California (San Francisco) 40.5
5
5 Gulf Oil (Pittsburgh)
26.5
7
6 Standard Oil of Indiana (Chicago)
26.1
9
7 Atlantic Richfield (Los Angeles)
23.7
11
8 Shell Oil (Houston)
19.8
12
9 Conoco (Stanford, Connecticut)
18.3
14
10 Philips Petroleum (Oklahoma)
13.4
16
11 Tenneco (Houston)
13.2
17
12 Sun (Radner, Pennsylvania)
12.9
18
13 Occidental Petroleum (Los Angeles)
12.5
20
14 Standard Oil (Cleveland)
11.0
23
15 Getty Oil of California (Los Angeles)
10.2
26
16 Union Oil of California (Los Angeles)
10.0
28
17 Marathon Oil (Findley, Ohio)
8.2
39
18 Ashland Oil (Russell, Kentucky)
8.1
40
19 Amerada Hess (New York)
7.9
43
_______________________________________________________________
Source: “The 500 Largest Industrial Corporations,” Fortune, May 1991.
354
OLIBE & CRUMBLEY
APPENDIX B
Correlation Matrix of Independent Variables and FDI in Equation 1
(N=60)
_______________________________________________________________
_
Panel A. Equation 1
FDI BUSD CUDVAL DEBSER FORSER GOTY AVBAR
--------------------------------------------------------------------------------------------------------FDI
1
-
-0.152
0.172
BUSA
-0.152
1
0.172
CUDVAL 0.222 -0.107
0.081 0.253
DEBSER -0.034 0.491
0.417 0.001
FORSER
0.726 -0.292
0
0.032
GOTY
-0.009 0.392
0.477 0.006
AVBAR
0.312 -0.552
0.024
0
0.222
0.081
-0.107
0.253
1
-0.468
0.001
0.317
0.022
-0.064
0.346
0.230
0.074
-0.034
0.417
0.491
0.001
- -0.468
0.001
1
-0.38
0.007
0.267
0.046
0.545
0
0.726
0
-0.292
0.032
0.317
0.022
-0.380
0.007
1
-0.248
0.059
0.590
0
-0.009
0.477
0.392
0.006
-0.064
0.346
0.267
0.046
0.059
0.590
1
-0.614
0
0.312
0.024
-0.552
0
0.230
0.074
-0.545
0
0
0
0
-0.614
1
-
Panel B. Equation 2
FDI GDP
GDPC
POP
CORTA WARA COSCA
--------------------------------------------------------------------------------------------------------FDI
1
-
GDP
0.858
0
0.858
1
0
0.074
GDPC
-0.167
0.128
-0.159
-
-0.167
0.128
0.531
0.531
0
0.583
0.140
0.165
0.131
-0.014
0
0.398
0.003
0.522
0.463
-0.146
0.162
-0.212
0
-0.159
1
-0.504
-0.482
0.138
-0.632
0.140
0
0
0.175
0
POP
0.583
-0.504
1
-0.777
0.277
0.187
0
0
0
0.115
0.028
0.101
CORTA
0.165 -0.014
-0.482
-0.177
1
-0.150
0.238
0.131 0.463
0
0.115
0.155
0.052
WARA
0.398 0.522
0.138
0.277
-0.150
1
-0.502
0.003
0
0.175
0.028
0.155
0
COSCA
-0.146 -0.212
-0.632
0.187
0.238
-0.502
1
0.162 0.074
0
0.101
0.052
0
_______________________________________________________________________