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ENERGY INTENSITY, ECONOMIC GROWTH AND THE ENVIRONMENT: IDENTIFYING STRUCTURAL LINKAGES

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Graduate School of The Ohio State University

By

Ansari Zaid Ameen, B.S., M.A

* * * *

The Ohio State University

1995

Dissertation Committee: Approved by

J. Craig Jenkins

Edward M. Crenshaw Advisor epartmAnt of Sociology Kazimierz M. Slomczynski UMI Number: 9544512

UMI Microform 9544512 Copyright 1995, by UMI Company. All rights reserved.

This microform edition is protected against unauthorized copying under Title 17, United States Code.

UMI 300 North Zeeb Road Ann Arbor, MI 48103 To My Parents ACKNOWLEDGMENTS

Before beginning a new stage in my life, I would like to thank Professor Edward Crenshaw for his guidance, assistance, and friendship over the course of the last six years. Our relationship is one that will endure with time. I am also indebted to Professor Jenkins for his encouragement, patience, and help. I would also like to thank Professors Slomczynski, Kaufman, and Namboodiri for assisting me over the course of my graduate studies. To Nancy Stancic, who has provided me the emotional support needed to complete my graduate studies, I am eternally grateful. VITA

October 9, 1963 ...... Born - San Fernando, Trinidad

1989 ...... B.S., Psychology, University of Houston, Houston, Texas

1990-1992 ...... M.A., Sociology, University of Houston, Houston, Texas

1991-Presen t ...... Graduate Research Associate, The Ohio State University, Columbus Ohio

PUBLICATIONS

Crenshaw, Edward and Ansari Ameen. 1993. "Dimensions of Social Inequality in the Third World: A Cross-National Analysis of Infant Mortality and Fertility Decline." Population Research and Policy Review 12: 297-313.

Crenshaw, Edward and Ansari Ameen. 1994. "The Distribution of Income Across National Populations: Testing Multiple Paradigms." Social Science Research 23: 1-22

FIELDS OF STUDY

Major Field: Sociology Studies in : International Development, Population Studies and Social Change. Dr. Edward Crenshaw, Dr. Craig Jenkins, Dr. Kazimierz Slomczynski, and Dr. Krishnan Namboodiri. TABLE OF CONTENTS

DEDICATION...... ii

ACKNOWLEDGEMENTS ...... iii

VITA ...... iv

LIST OF TABLES ...... vii

LIST OF FIGURES...... xi

CHAPTER PAGE

I. THE IMPORTANCE OF ENERGY TO HUMAN SURVIVAL

Introduction...... 1 Energy Efficiency and Sociological Theory...... 1 Energy Efficiency and Global W arm ing ...... 4 Depletion of Non-renewable Sources of Energy and Population Growth ...... 6 Overview of Study ...... 8

II. PREVIOUS EMPIRICAL WORK ON ENERGY INTENSITY

Non-Sociological Research...... 12 The Manufacturing Sector ...... 13 The Transportation S ector...... 16 The Residential Sector ...... 19 The Service Sector ...... 21 Research on the Determinants of Energy Efficiency ...... 22 Energy Efficiency and the Quality of Life ...... 24 Energy Intensity and Economic Growth...... 25

v III. ADAPTATIONS OF THEORIES OF DEVELOPMENT

Modernization Theory ...... 31 Dependency\WorId Systems T h e o rie s ...... 38 Ecological-Evolutionary Theory ...... 44

IV. METHOD AND DATA

Overview of Analysis ...... 48 Sam ple...... 51 Method ...... 52 Dependent Variable and Operationalizations ...... 52 Phase One ...... 52 Phase T w o...... 53 Phase T hree ...... 53 Phase F o u r...... 55 Phase F iv e ...... 56 Independent Variables used in Energy Intensity Equations ...... 57 Independent Variables used in Economic Growth Equations ...... 64

V. RESULTS

Results Pertaining to the Determinants of Energy Intensity ...... 67 Phase One ...... 67 Summary of Findings for Phase One and Substantative Interpretations ...... 75 Phase T w o...... 77 Summary of Findings for Phase T w o...... 80 Phase T hree ...... 81 Summary of Findings for Phase T h ree ...... 84 Phase F o u r...... 85 Summary of Findings for Phase F our...... 91 Summary of Findings for Phases One Through Four: Putting the Pieces Together...... 92 Results Pertaining to the Determinants of Economic G row th...... 94

VI. IMPLICATIONS AND FUTURE RESEARCH AGENDA

The Immediate Relevance of the Findings ...... 134

vi Implications and Relevance of Economic Growth M o d e ls...... 144 Relevance of Findings for Sociological Theory ...... 147 The Implications for Sociological Theory...... 150 Concluding Comments...... 151

APPENDICES

A. Lists of Countries Included in the Equations ...... 152 B. List of Influential O u tliers...... 158 C. Means and Standard Deviations of Varriables Used in the Analysis ...... 162

LIST OF REFERENCES ...... 166

vii LIST OF TABLES TABLE PAGE

1. Zero-order correlations between change in energy intensity from 1956 to 1973 and independent variables ...... 99

2. Unstandardized regression coefficients for the change in total energy intensity from 1965 to 1973 ...... 100

3. Zero-order correlations between change in energy intensity from 1974 to 1985 and independent variables ...... 101

4. Unstandardized regression coefficients for the change in total energy intensity from 1974 to 1985 ...... 102

5. Zero-order correlations between total energy intensity for 1965 and independent variables ...... 103

6. Unstandardized regression coefficients for total energy intensity for 1965 ...... 104

7. Zero-order correlations between total energy intensity for 1975 and independent variables ...... 105

8. Unstandardized regression coefficients for total energy intensity for 1975 ...... 106

9. Zero-order correlations between total energy intensity for 1985 and independent variables ...... 107

10. Unstandardized regression coefficients for total energy intensity for 1985 ...... 108

11. Zero-order correlations between change in total energy intensity from 1979 to 1989 and independent variables ...... 109

12. Unstandardized regression coefficients for the change in total energy intensity from 1979 to 1989 ...... 110

viii 13. Zero-order correlations between total energy intensity for 1979 and independent variables ...... I l l

14. Unstandardized regression coefficients for total energy intensity for 1979 ...... 112

15. Zero-order correlations between change in industrial energy intensity from 1979 to 1989 and independent variables ...... 113

16. Unstandardized regression coefficients for change in industrial energy intensity from 1979 to 1989 ...... 114

17. Zero-order correlations between change in services energy intensity from 1979 to 1989 and independent variables ...... 115

18. Unstandardized regression coefficients for change in services energy intensity from 1979 to 1989 ...... 116

19. Zero-order correlations between change in agriculture energy intensity from 1979 to 1989 and independent variables ...... 117

20. Unstandardized regression coefficients for change in agriculture energy intensity from 1979 to 1989 ...... 118

21. Zero-order correlations between agriculture energy intensity for 1979 and independent variables ...... 119

22. Unstandardized regression coefficients for agriculture energy intensity for 1979 ...... 120

23. Zero-order correlations between industrial energy intensity for 1979 and independent variables ...... 121

24. Unstandardized regression coefficients for industrial energy intensity for 1979 ...... 122

25. Zero-order correlations between transportation energy intensity for 1979 and independent variables ...... 123 26. Unstandardized regression coefficients for transportation energy intensity for 1979 ...... 124

27. Zero-order correlations between residential energy intensity for 1979 and independent variables ...... 125

28. Unstandardized regression coefficients for residential energy intensity for 1979 ...... 126

29. Zero-order correlations between economic growth from 1965 to 1973 and independent variables ...... 127

30. Unstandardized regression coefficients for economic growth from 1965 to 1973 ...... 128

31. Zero-order correlations between economic growth from 1974 to 1985 and independent variables ...... 129

32. Unstandardized regression coefficients for economic growth from 1974 to 1985 ...... 130

x LIST OF FIGURES

FIGURE PAGE

Figure 1. Plot of per capita GNP for 1965 and growth in energy intensity from 1965 to 1974 ...... , 131

Figure 2. Plot of per capita GNP for 1974 and growth in energy intensity from 1974 to 1985 ...... 132

Figure 3, Plot of per capita GNP for 1979 and growth in energy intensity from 1979 to 1979 ...... 133

xi CHAPTER I

THE IMPORTANCE OF ENERGY TO HUMAN SURVIVAL

Introduction

Energy intensity, or the amount of energy used to generate a specific amount of product or service, has become an especially important topic in recent years. Although little empirical sociological analysis has been devoted to the subject of energy intensity, it is central to macrosocial theorizing, although this is not well recognized. The manner and efficiency/intensity with which individuals and societies use energy also has indirect implications for processes such as the emissions of greenhouse gases into the atmosphere and resultant global warming, the continued depletion of non-renewable sources of energy, the availability of energy supplies for future generations, the abilities of governments to supply basic goods and services to their populations, and, as exemplified by the Gulf War, often the global balance of political power itself. The analysis presented in the following chapters represents one of the first macro sociological studies with the goal of ascertaining the structural determinants of energy intensity.

Energy Efficiency and Sociological Theory

The centrality of energy consumption to sociology and its theoretical development essentially dates back to the discipline's origins. It is the ability to harness greater and greater amounts of inanimate energy that occurred with the industrial revolution that influenced the development of sociology. The traditional founding fathers of sociology, 2

Spencer, Durkhein, Marx and Weber, all responded to and made attempts at explaining the rapid social changes engendered by greater and greater conversions of energy.

Herbert Spencer, for example, is quoted in Rosa and Machlis (1983:152) as having written in 1862 "whatever takes place in a society results from either the undirected physical energies around, from energies as directed by men, or from the energies of men themselves". Since the discipline’s inception, attention has been directed at the outcomes of energy transformations and its organizational forms and inter-connectedness.

Unfortunately, until recently there has been a distinct neglect of the fact that energy is an input in the system and its stock and flow affect the processes many sociologists study. The oil crises of the 1970’s served as the brutal reminder. Sociologists appear to have taken for granted the basic fact that it is the surplus generated from inanimate energy transformations and increased productivity that are the reasons some members of society can pursue "higher order" academic activities such as the study of social organization.

Rosa and Machlis (1983) document the relative lack of theorizing on energy from its inception to the present, essentially pointing out a lack of progress made in the area.

The authors divide theorists into those who recognized the limited supply of energy and those who failed to see energy as a scarce commodity. They further point out that energy is typically treated as an independent variable with the outcomes of energy transformations as dependent variables. Development studies typify this point. Per capita energy consumption has been used as an indicator of modernization or societal development for decades with little or no discussion of its supply. By implication, the 3 supplies and efficiencies were treated as if they had no effect on the organizational

patterns under scrutiny. The centrality of energy to development is implied in the works

of sociologists such as Hawley (1950). Hawley points to the importance of the key

function in increasing productivity and economic specialization and differentiation, both

prerequisites to economic growth. One short step back in causal sequence will quickly

point to the role of increasing use and efficiency of energy as crucial to productivity and

concomitant differentiation. In the analysis to follow, energy will be brought back into

development studies and accorded the attention it deserves at both the empirical and

theoretical levels. As I have attempted to point out earlier, in this analysis energy is

viewed as indispensable to human survival. Energy is viewed as irreplaceable in the

material progress of humans. Rather than focus on health care provision, employment structures, spatial organization and living arrangements, (i.e, more typical topics of sociological analyses), this study will focus on energy itself in an attempt to demonstrate the potential deficiencies that result from excluding energy in the study of social change.

As Rosa and Machlis (1983:171) so aptly point out, rather than ask why the study of energy is relevant to the study of social change and sociology as a whole, "good reasons need to be offered when energy is not incorporated into theories purporting to explain fundamental social structure and change."

The analysis that follows in no way claims to solve all of the deficiencies on energy analysis to date. Instead, it should be viewed as a preliminary analysis that can provide some initial insight into the macro-structural determinants of energy intensity and serve as a foundation for additional empirical investigation and theorizing. Based on the 4 preceding discussion, the policy implications of reducing energy intensity should be clear.

A few incentives for pursuing this line of inquiry would be: 1) to illuminate structural

barriers that inevitably impinge on or constrain reductions of energy intensity at end uses,

2) to provide a picture of how end use strategies are reflected in aggregate consumption

patterns, 3) to prevent resource misallocation through a greater understanding of

structural constraints, 4) to reduce the pace of global warming and transboundary air

pollution, 5) to extend the use of existing resources, and 6) to reduce potential sources

of global political instability in the post Cold War period.

Energy Efficiency and Global Warming

The transboundary nature of air pollution and greenhouse gas emissions has led

to the general acknowledgement that activities in one part of the hemisphere ultimately

have global effects and that isolated attempts at reducing air pollution and global

warming will be largely ineffective. Consequently, international cooperation directed at mitigating further environmental damage has begun.

Although critics of environmental movements often argue that the threat of global warming has been overstated, reviews of the scientific evidence to date reveal the threats of global warming and massive environmental damage stemming from greenhouse gas emissions have not been exaggerated. In general terms, increased industrial activity, especially by developed countries, has greatly accelerated the release of carbon dioxide, nitrous oxide, water vapor, methane and CFCs into the earth’s atmosphere. These

"greenhouse gases" trap the heat usually radiated by the earth and over time raise the earth’s mean temperatures. The buildup of these gases led leading scientists to argue that 5 "the rapid climate change that would result threatens to de-stabilize the natural and societal systems upon which economic growth depends" (Mintzer, 1990:514).

Local air pollution problems and the buildup of greenhouse gases in the atmosphere are direct consequences of increased human activity since the industrial revolution. A decomposition of the relative contributions of various economic sectors in terms of the percentage of greenhouse gases added to the atmosphere identifies the energy sector as the leading culprit with respect to human-induced contributions. Gases emitted from direct energy use (49 percent) and as by-products of industrial sector activity (24 percent) together account for almost three quarters of the greenhouse gas emissions and resultant global warming from anthropogenic sources (Mintzer, 1990).

Given the critical role played by the energy and industrial sectors, research directed at identifying and illuminating the most efficient ways of utilizing energy is imperative.

Consequently, in terms of intervention, coordinated action or mitigation strategies directed at these sectors appear to be the most logical and cost effective starting point.

The National Research Council (1992:120) clearly acknowledges that "energy efficiency is the most widely accepted strategy for mitigating global warming." Identification of the structural as well as proximate causes of energy efficiency, (i.e. energy intensity), therefore becomes a necessary precursor to mitigation strategies for slowing the pace of global warming.

In addition to increasing the efficiency with which energy is currently being used, forethought and planning are required with regard to growth in future energy requirements, the majority of which is expected to occur in the developing world. 6 International organizations and multilateral lending agencies have recognized that the majority of developing countries are in the process of planning and making infrastructural developments, activities that require enormous inputs of energy. Experts at the World

Bank appear to concur with Mintzer’s (1990:532) view that "it will prove much cheaper in the long-term to incorporate a concern for global warming when making these investments, than having to retrofit these infrastructures once installed." The energy rationalization programs supported by the World Bank and other lending institutions, although not specifically designed to limit environmental pollution, has the dual effect of improving environmental quality while also increasing economic competitiveness.

Depletion of Non-renewable Sources of Energy and Population Growth

Additional policy relevant debates that can be enhanced through the identification of the determinants of energy efficiency are 1) those related to the depletion of non­ renewable forms of energy and the availability of commercial alternatives and 2) those concerning the carbon content of fuels currently being used. Approximately four- fifths of global energy use comes from the combustion of fossil fuels (Goldemberg et al, 1987), the reduction of which is the most effective way of limiting additional atmospheric carbon dioxide buildup. Although the world’s supplies of coal, oil, and natural gas are fixed and therefore subject to depletion, the problem is more acute for gas and oil since the world’s resources of coal are greater than those of oil and gas resources combined

(Goldemberg et al, 1987). Irrespective of the relative abundance of coal, it is unlikely to become the fuel of choice in the future because of its high carbon content and the very uneven global distribution. 7 From 1950 to 1985 the percentage of commercial energy supplied by petroleum rose from 29 to 40 percent, that of natural gas rose from 9 to 21 percent, while coal declined from 57 to 31 percent (Mintzer, 1990). While these broad trends illustrate a shift toward "relatively cleaner" modes of energy use, the absolute increase in energy use and carbon dioxide emissions by far nullifies any gains made by shifts within the fossil fuel categories. Furthermore, the quadrupling of world energy use in the past forty years alone (Mintzer, 1990) inevitably implies reductions in the Finite quantities of these life- sustaining materials. As mentioned earlier, the forthcoming infrastructural requirements of developing countries are likely to strain energy reserves. Unlike industrialized countries which are primarily engaged in maintenance and the retrofitting of existing infrastructure, many developing countries have yet to build roads, bridges, factories, warehouses, schools, hospitals, electricity powerplants, houses, and the like. The activities will necessitate larger and larger quantities of steel, cement, iron, paper and pulp, the production and use of which are very energy-intensive. Catering to this aspect of developing countries’ energy needs is merely part of the problem. The rapid population growth experienced by developing countries and their projected increase in energy use simply for the provision of basic human needs will place yet more strains on the world’s energy supplies. Currently the majority of the world’s energy consumption is done by the 25 percent of the world’s population living in the developed world.

Although 75 percent of the world’s population resides in developing countries, it currently consumes only about 30 percent of total worldwide energy consumption.

Consequently, supplying enough energy to provide adequate food, housing, sanitation, 8 medical care, educational facilities and employment for more than half the world’s

population living in villages and small towns will amplify the energy problem. Currently

the rural poor tend to rely on traditional and inefficient sources of energy such as dung

and crop residues. As the transition to commercial fuels becomes more common, the potential for energy growth in the developing world is staggering. The problems of

supplying energy to fulfill the basic needs of Third World populations and of financing the energy needs for economic development assume massive proportions. Unfortunately, development strategies in the Third World are at odds with increases in energy efficiency since fuel subsidies designed to aid the poor tend to keep prices artificially low, encouraging waste. If the populations of Third World countries are to be provided with the basic necessities such as food, shelter, clean water, and access to basic health services, massive inputs of energy will be required along with development strategies that explicitly incorporate energy conservation. Needless to say, the more efficient use of existing resources will slow the rate of depletion and buy some time until viable alternative energy sources are developed.

Overview of Study

In the analysis the three major sociological theories of development are used as a theoretical guide. Hypotheses derived from modified versions of modernization theory, dependency/world systems theories, and ecological-evolutionary theories will be tested.

Relevant control variables thought to affect energy regimes will be included in the analysis to aid in separating effects. In short, modified versions of modernization theory would result in the

expectation of a curvilinear pattern of energy intensity with level of development.

Countries at low levels of development are expected to exhibit low energy-intensities

because of excessive reliance on traditional non-commercial forms of fuel and a general

lack of industrial activity. Countries at intermediate levels of development are expected

to be the most energy-intensive given the shift from agrarian to industrial bases and the

building of basic infrastructure. The shift to service sector and information processing

activities typically occurring at very high levels of development are expected to result in

relatively low energy intensities. Expectations derived from the dependency/world systems traditions would include low energy-intensities in developing countries engaged

in vertical trade patterns. The concentration of economic activities in basic materials production without economic-base diversification should result in apparently lower energy-intensities through underdevelopment. Ecological-evolutionary theorists’ emphasis on population pressure, competition and scarcity engendered by historically high population densities. Labor in old agrarian societies was cheap while land was very dear. The outcome was the tendency to use labor intensive production systems that maximize land productivity (Nolan and Lenski, 1985). These observations lead to expectations of slowed growth in energy intensity as development proceeds based on long histories of resource scarcity. Energy resource endowment will be included as a control because countries with superior resource endowments are expected to exhibit higher than normal energy-intensities. 10 Generally, I will attempt to provide an overall picture of the determinants of energy-intensity from 1965 to 1989. The choices of time periods and sectors under investigation are the result of data limitations and theoretical considerations. Four sets of analyses of dependent variables will be analyzed in order to arrive at the composite picture of the determinants of energy-intensity. A fifth set of analyses is added to demonstrate the utility of considering energy intensity in conventional sociological analyses. The first set of analyses looks at changes in total energy intensity from 1965 to 1985 and is broken down into two periods reflecting the pre- and post-oil shock periods. The second set examines total energy intensity in the decade following the oil shocks. The third phase of the research decomposes the aggregate intensity measure for the post-oil shock decade into the agricultural, industrial and service sectors. The fourth set of analyses cross-sectionally analyzes energy intensity for agriculture, transportation, industry, and residential sectors for the year 1979. In the fifth phase of the research replicates models used to assess the determinants of economic growth for the pre- and post-oil shock periods and includes energy intensity as an additional independent variable.

This will be conducted as a test of the argument that the use and supply of energy are central to national development and should be included in the study of social change.

The results are expected to complement the lines of inquiry currently being pursued by physical scientists. The theoretical models will serve to provide tests of some of the speculations discussed in the literature. More importantly, however, is the gap in the energy intensity literature this research will fill. A fairly large body of literature exists on reducing energy intensities at end uses and this appears to be one of the more 11 endorsed methods for increasing efficiencies (World Resources, 1987; Gamba et al,

1986). Others advocate sectoral approaches to reducing intensities (Mintzer, 1990). The paucity of research at the macro level is perhaps responsible for inattention to its

importance. Changes at end uses and even at sectoral levels often tend to balance themselves out, an aggregate view can provide a total picture of the effectiveness of changes made at other levels. Furthermore, end use adjustments and sectoral changes are constrained by even broader factors such as historical population growth rates and resource endowments, factors that should be included in energy rationalization plans. As

Buttel (1978: 146) pointed out in the first attempt to identify structural constraints on energy regimes: " it will become apparent that many of the variables or factors that account for variation in energy efficiency among nations of the world are - at least for the present time - rather permanent parameters of most nations’ social structures and are unlikely to be changed in the near future without radical shifts in political-economic organization". This research will also provide some focus for a large body of atheoretical analyses. Contributions in terms of expanding the range of issues covered by theories of development as well as theoretical reformulations based on empirical findings are likely. CHAPTER II

PREVIOUS EMPIRICAL WORK ON ENERGY INTENSITY

The subject of energy intensity has largely escaped the attention of social

scientists. The majority of research on energy intensity has been conducted by industrial

engineers and other physical scientists. These researchers have produced a rich,

descriptive body of literature that covers almost the entire range of units of analysis.

However, data limitations and a general reluctance to utilize aggregate measures of

intensity have resulted in little research that includes both developed and developing

countries. Nonetheless, the research conducted to date does provide some insight and a

backdrop against which cross-national analyses can be performed. Previous literature can

be divided into sociological and non-sociological categories.

Non-Sociological Research

Global trends in energy use indicate an increase of over one-third between 1970 and 1990. In spite of periods of stagnation during the immediate post-oil shock years, the average annual global increase over the twenty year period was 2.3 percent (Schipper and

Meyers, 1992). The increase is largely attributable to the growing needs of the developing world. The less developed countries share of total world energy use for the decades since 1970 rose from 20 percent to 31 percent. The share for OECD countries fell from 60 to 48 percent while that of the former East Bloc rose from 20 to 21 percent.

The growth rates for the three categories, 1.3 percent for the OECD, 2.4 percent for the

12 Former East Bloc, and 4.5 percent for the developing world, illustrate the potential for growth in the future emanating from population and structural changes in less developed countries (LDCs) (Schipper and Meyers, 1992). Recent estimates indicate declines in the shares of oil and coal, 41 to 36 percent and 28 to 25 percent respectively, but absolute increases in quantities between the years 1970 to 1990. In fact, total oil consumption was over one-third higher in 1990 than 1970 (Schipper and Meyers, 1992).

The Manufacturing Sector

Disaggregation of world energy consumption point to the manufacturing sector as the most dominant with respect to energy consumption. Although data limitations do not allow for very detailed examinations of trends in the developing world, some insight into manufacturing energy-intensities is possible from trends in the OECD countries.

Evidence from the industrial sector, which includes mining, manufacturing and construction, highlights the importance of manufacturing growth for energy consumption in LDCs. The industrial sector has grown faster than economies as a whole as LDCs shift away from agricultural bases, with the majority of growth occurring in the most energy- intensive manufacturing industries (Sathaye et al, 1987). Research has identified the paper and pulp, chemical, stone, clay and glass, iron and steel, and nonferrous metals industries as the most energy-intensive within the manufacturing categories (Schipper and

Meyers, 1992). These industries tend to require more energy per unit of value-added than other manufacturing categories, claiming 70 percent of energy use in the manufacturing sectors, while contributing only 20 percent to manufacturing value-added (Schipper and

Meyers, 1992). These manufacturing categories are considered fundamental to the

13 14 production of consumer products, building construction and transportation infrastructure,

both of which are expected to experience rapid growth in LDCs as their economies mature. Data from 20 LDCs confirm this expectation, as industrial growth in Asia and

Latin America was found to be fueled by growth in chemicals, refineries, iron and steel, minerals, and paper (Sathaye et al, 1987). Consequently, identifying factors that constrain growth in industrial sector intensities, one of the dependent variables in this analysis, will prove advantageous in conserving supplies of energy.

Detailed analysis of the manufacturing sector for eight OECD countries-the United

States, Japan, France, the United Kingdom, West Germany, Norway, Sweden, and

Denmark- identified a decline in energy intensities as evidenced by a growth in manufacturing value-added at about 2.3 percent per year between 1972 and 1988, while energy use fell by 1.2 percent per year (Schipper and Meyers, 1992). The oil shocks were partially responsible for declines in intensities as well as a slight shift away from oil. The bulk of the "decoupling" of production from energy use, however, was shown to occur from structural shifts within the manufacturing sectors and actual improvements in efficiencies (Howarth and Schipper, 1991). With regard to the structural shifts, the share of the five most energy-intensive industries for the OECD-8 fell from 24 to 22 percent between 1973 to 1988 thereby reducing intensities somewhat. The authors attribute the structural changes to a long-term trend away from energy- intensive industries such as steel and cement toward plastics, modern ceramics, and composite materials that are less bulky and lighter (Schipper and Meyers, 1992). It is also argued that technical advances reduced material waste and material quantities in finished 15 products, in essence factors suggested by modernization theory. Other factors identified by the Schipper and Meyers as contributing to intensity reductions were improvements in operations, maintenance, retrofitting, added technologies, and introducing new technologies in new facilities. The absence of data on manufacturing for the former

Eastern Bloc preclude discerning any trends in manufacturing, but there appear to have been no reductions in intensities due to low energy costs and little competition.

Governmental programs to improve energy efficiency in China resulted in significant manufacturing intensity declines between 1980 and 1985 even though manufacturing technology remains outdated. The patterns for other developing countries appear to be a general movement toward increasing intensities, but detailed data are lacking. While there was a general tendency toward manufacturing sector growth and investment in heavy energy-intensive industry depending on energy resource endowment, some LDCs, notably Taiwan and South Korea, showed declining intensities because of investments in energy-efficient technology (Schipper and Meyers, 1992). These data lend support to contentions that forethought and planning can reduce future energy use.

The descriptive patterns lend themselves to interesting questions and tests to be addressed in the analysis. The apparent decoupling of value-added from energy consumption at high levels of development (Schipper and Meyers, 1992; Howarth and

Schipper, 1991) begs the question of whether a curvilinear pattern of energy-intensity is borne out by the data for a large number of countries. Should this modernization perspective be supported, it would lend additional support to the contention that maturation and physical structural changes are likely to have profound effects in the 16 future. Support for this hypothesis coupled with suggestions for incorporating energy- efficient technologies during the early stages of development (Mintzer, 1990; World

Bank, 1986) would constitute significant progress in both the policy and academic arenas.

Additionally, by implication, the importance of hastening the transition of low-income countries through the shift from agriculture to manufacturing to services would be demonstrated. In effect, contrary to current dependency/world systems thinking, intervention in developing countries’ economies and insertion in the world economy may prove ecologically-sound in the long run. This type of policy recommendation used in conjunction with the standard end use strategies suggested in the literature will prove to be of greater utility than either used in isolation.

The Transportation Sector

The transportation sector is also expected to experience significant growth in the decades to come. Energy use from the transportation sector is largely accounted for by processes related to urbanization and the development of more well articulated links between urban centers and rural hinterlands as development proceeds. The services rendered by the movement of people and goods within and between urban areas results in the higher energy consumption in urban compared to rural areas. Naturally, the tendency for over-urbanization becomes even more perturbing with this in mind. The overall trends point to further increases in worldwide energy use and intensities because of the increasingly dominant role LDCs will play. Growth in the transportation sector tends to push oil consumption up. The patterns indicate that the OECD countries account for most of the energy use connected to transportation (64%). As in the case of 17 manufacturing, the largest growth in recent years has come from the developing countries

(5.1%) compared to OECD (2.4%) or former East Bloc countries (2.0%) (Schipper and

Meyers, 1992). Compared to developing countries (5%) or former East Bloc countries,

passenger travel accounts for a much higher proportion of final energy use in

industrialized countries (22%), with automobiles being the dominant mode in the OECD

(Meyers and Schipper, 1992; Sathaye et al, 1987). Within industrialized countries some

minor shifts were observed, such as a relative decline in automobile’s share of

transportation in the U.S. compared to increases for Japan and European countries. The

majority of these minor fluctuations in the developed world can be accounted for by

demographic shifts, market saturation, and social factors.

The increases in transportation energy-intensity in the industrialized countries are

likely to be modest relative to those evident for developing countries. The trends for the

few developing countries for which some data are available point to movement in the

realization of their growth potential. Per capita travel in South Korea and Brazil

increased 7 % annually, while the increase was 11 % for China (Meyers and Schipper,

1992). Descriptive trends seem to point to a general shift from rail to buses and mopeds to automobiles as economies mature, the result of which is increasing energy use.

Automobile use, for example, has growth considerably in Latin America and the Middle

East (Schipper and Meyers, 1992; Sathaye et al, 1987). Automobile growth rates between

1960 and 1970 range from 7 to 15 percent in large Third World cities (Sathaye and

Meyers, 1987). Automobile use is inefficient compared to other modes of transportation available in urban settings and tends to elevate energy use. Data for Argentina, Brazil 18 and Colombia, for example, revealed that automobile use accounted for 65 to 75 percent

of energy use in transportation compared to the 25 to 35 percent of traffic moved by

automobiles (Sathaye and Meyers, 1987). The situation in LDCs is compounded by the

current uneven distribution of incomes. High levels of inequality in the developing world

imply any future income equalization, an outcome generally viewed as positive and

desirable, will bring with it large strains on the world’s energy reserved. The reasons for

this are simple. The wealthy tend to consume much more energy than the poor. For example, surveys of Hong Kong find a forty-fold increase in per capita energy use for transportation between the highest and lowest income groups (Sathaye and Meyers,

1987). Evidence from other LDCs confirm the observation that energy use increases with

income (Sathaye and Meyers, 1987; Schipper and Meyers, 1992; Meyers and Schipper,

1992). Consequently, any economic growth and concomitant trickle down effects or income redistributions are likely to boost energy intensity. Ironically, income equalization, while desirable from a human welfare perspective, may prove to be detrimental from an environmental point of view.

Similar increases in intensities are likely for freight transport. In relative terms, energy use for freight movement contributes more to energy use than passenger transportation in developing countries than in industrialized countries where it counts for only half as much as freight (Meyers and Schipper, 1992). Two primary factors affecting the energy intensity of freight transportation appear to be the type of goods produced and the mode of transportation used. Generally, there appeared to be decreases in rail intensities in industrialized countries with shifts toward increasing intensities for trucks 19 (Meyers and Schipper, 1992). Except for India and China, which have extensive rail

systems, developing countries’ reliance on trucks seems to expand along with growth in

manufacturing. Apparently, countries relying on extractive industries and basic materials

processing tend to utilize rail systems more, whereas growth in manufacturing is

associated with shifts to trucks which afford manufacturers greater flexibility and

convenience. The implications of the patterns described for transportation again point to

large increases in energy consumption and intensities emanating from economic

development in LDCs. In the case of the industrialized world, once again market

saturation and increases in technical efficiencies are likely to minimize additional growth

in energy intensities, as are low population growth rates. However, as developing countries expand their manufacturing bases and income levels rise, both freight intensities and passenger travel intensities can be expected to rise. Whether the positive effects of overurbanization and agglomeration will negate or contribute to the projected increases

is a matter that can only be settled through empirical analysis. Furthermore, to the extent

that economic growth benefits the burgeoning populations in LDCs, continued increases

in energy use of the residential sector can also be expected.

The Residential Sector

Approximately 35 percent of final energy use in developing countries is accounted for by residential use compared to only 20 percent in industrialized countries, the difference being attributable to inefficient use of traditional fuels in LDCs. Additionally, despite a 10 percent increase in population growth in the OECD between 1973 and 1988, residential energy use has remained constant compared to growth in developing countries 20 resulting from population growth and growth in appliance ownership (Meyers and

Schipper, 1992). Once again, urbanization is expected to mediate the effects of population growth on energy use and intensity. Specifically, cooking demands and electric appliance growth in LDCs are expected to change with increases in urbanization and have mixed effects on energy intensity but an overall increase in the total energy used in LDCs. The choices of cooking fuels change as families move to urban areas with kerosene, liquified petroleum gas (LPG), and electricity replacing biomass and firewood

(Sathaye and Meyers, 1987; Sathaye et al, 1987). Although this represents an improvement in ecological terms, given the greater efficiency of modern fuels and equipment, it also drives up demand. The apparent "gains" in efficiency are very likely to be offset, however, from growth in ownership of energy-intensive electrical appliance such as refrigerators, water heaters, and air conditioners (Sathaye and Meyers, 1987).

End use trends for industrialized countries showed a per capita decline of about

15% for the U.S., but 10% and 46% percent increases for Europe and Japan respectively

(Schipper and Meyers, 1992). The structural changes resulting in these patterns appeared to be larger home living space per capita, increasing sizes of heating equipment, and growth in appliance ownership, all of which were greater in Europe and Japan than in the U.S. (Meyers and Schipper, 1992). Concomitant factors working to decrease energy use in industrialized countries were increases in retrofit and thermal integrity of buildings and a shift toward electricity.

The paucity of data on residential sectors of LDCs preclude definitive statements regarding changes in energy intensity. Nevertheless, the indications all point to increasing 21 energy use. Residential electricity rose in almost all LDCs, as did the transition away from biomass for cooking to LPG and commercial kerosene (Meyers and Schipper, 1992;

Sathaye et al, 1987). Among the forces driving energy use and intensity up in LDCs are urbanization and electric appliance ownership whereas the switch to commercial fuels for cooking probably lowered intensities (Meyers and Schipper, 1992). Once again, evidence of forthcoming large scale increases in energy use in LDCs is apparent as is the decoupling of value-added from energy use at very high levels of development.

Individuals in industrialized countries can only consume so many additional refrigerators, televisions, radios, microwaves and the like. The low level of market saturation in

LDCs, however, suggest rapid increases ensuing development. Once again, evidence at the sectoral level supports the broad outlines of modernization theory.

The Service Sector

Consistent with conventional wisdom, the service sector in industrialized countries accounts for a far greater proportion of final energy use (11%) than in the developing world (5%) (Schipper and Meyers, 1992). Developed countries have achieved the bulk of their physical and infrastructural developments with large scale economic shifts to service industries occurring. Increased technology and the need for highly skilled labor forces typically result in heavy investments and growth in educational systems, one of the major service industries in developed countries. Similarly, increased longevity from advances in medical technology and advances in public health measures result in heavy emphasis being placed on the provision of medical services, the other major service industry in developed countries. The close association between energy and value-added 22 evident in manufacturing is less evident in the service sector. For the service sector, energy use per value-added declined in both the U.S. and Japan along with a decrease in fuel intensity and increase in electricity intensity (Meyers and Schipper, 1992). The causes of aggregate declines were most likely due to retrofit, increases in building thermal integrity, and improved energy management practices. Technological advancements developed in industrialized countries leads to well developed information processing sectors of their service economies, a major factor that in large measure contributes to the decoupling of energy from production. Trading of stocks, bonds, consultation services, the expansions of legal services and the like all require relatively small inputs of energy while making major contributions to service sector productivity.

Unfortunately, data for LDCs are virtually non-existent given the informal nature of many service sector activities in LDCs. The overall trends in service sectors, however, imply a curvilinear relationship between energy intensity and development as suggested by the broad outlines of modernization theory. This research will attempt to provide a test of this hypothesis.

Research on the Determinants of Energy Efficiency

The only research conducted to date which approximates that to be conducted in this analysis was performed by Frederick Buttel (1978). Buttel attempted to determine the relationship between social structure and energy efficiency. He employed the conventional GNP-energy ratio as his measure of energy efficiency and independent variables thought to be associated with level of societal development. Buttel (1978) argues that high GNP countries would exhibit less energy efficiency due to increases in 23 both scale of production and consumption, while percentage of the GDP from agriculture

should be positively related to efficiency since it represents a lack of economic-base

diversification. Concerning the decrease in efficiency at high levels of development,

Buttel apparently forgets his dependent variable is a proportion and that increases in the

scale and consumption of products generally increase productivity as well. Expectations

derived from modernization theory would predict the opposite pattern. Similarly,

percentage of the labor force in agriculture was expected to enhance "efficiency" by

virtue of its implication of a lack of mechanization. Urbanization, military expenditures,

and territory size were all argued to reduce efficiency. Urbanization’s effect was thought

to occur through the increasing inputs of energy required as the spatial concentration of

people occurred and they are divorced from animate forms of energy. The wastefulness of government enterprises was extended to include the military and thereby reduce aggregate efficiency, whereas the difficulties of administering large areas and problems of decentralizing were believed to foster waste (Buttel, 1978). As for population density, although Buttel (1978) recognized the potential for population density to increase efficiency through retarding the introduction of mechanization, he opted for postulating energy subsidies as an intervening variable in dense societies with a resultant negative effect on efficiency.

Results for the sample of 118 countries provided support for his expectations. Net of development, urbanization and per capita defense expenditures as a proportion of

GNP, territory size and population density are negatively related to energy efficiency, while agricultural GDP and percentage of the labor force in agriculture are positively 24 related to energy efficiency. With regard to the most consistent effects of his analysis,

i.e. agricultural GDP and percentage of the labor force in agriculture, Buttel suggests that

a revitalization of rural sectors and demechanization are possible avenues for increasing

the efficiency of nations. The possibility that Buttel actually found support for ecological-evolutionary theory is distinct, however. Since the positive correlation between agrarian structure and energy efficiency are probably the result of institutional

inheritance (or advanced social development based on centuries of labor-intensive production), Buttel’s policy recommendation is unrealistic, a fact lost to any study that is not driven by an appreciation of macrosocial theory. Moreover, given the cross- sectional nature of his study, Buttel’s research (1978, 1979) is of limited utility as either a test of dynamic theory or a guide to public policy in energy use. What is clearly needed is a new set of longitudinal studies that place these variables within the contexts of strong theoretical frameworks with competing tests in order to sort out effects. The research conducted in this analysis will attempt to provide answers to these issues as well as the relevance of energy-intensity for studies of other areas of sociological inquiry, in this case economic growth.

Energy Efficiency and the Quality of Life

Social scientists have largely ignored the role of energy efficiency as an independent variable in their analyses. The one exception to this statement was in regard to standards of living. "Trickle down" economics formed the basis for much economic policy during the 1960s and 1970s and was apparently supported by the high correlations between energy consumption, national output and standards of living. Spurred by the 25 energy crises and need to use resources more frugally, a few scientists attempted to

address the question of whether or not reductions in the quality of life would occur if

energy consumption declined.

Concern at that time focused not on the plight of individuals of Third World

populations and a desire to improve their standards of living, but rather on the potential

deterioration of the quality of life in the U.S. should energy conservation practices be

instituted. The general conclusion drawn from cross-national studies was that reductions

in energy consumption through increasing efficiency would not reduce standards of living

in the developed world (Mazur and Rosa, 1974; Schipper and Lichtenberg, 1976; Buttel,

1979). The cross-sectional nature of these studies and restricted range of countries used

in the analyses suggest that re-specification and reanalysis are needed. In this analysis,

however, I will focus on the effect of energy intensity on national economic growth rates,

a subject that has been of continued interest to sociologists since the early 1970s and one

that has conceptual links to issues such as urbanization and the quality of life.

Energy Intensity and Economic Growth

Research on the determinants of economic growth rates has flourished within sociology since the early 1970s. Attempts at ascertaining the determinants of economic growth rates were partially spurred by concerns for the apparently deteriorating living conditions of individuals in Third World countries. The research was based on assumptions flowing from conventional modernization perspectives, neoclassical economics, and the trickle down/spread effect models (e.g. Rostow, 1960). Stage theories developed on the observed experiences of the now-developed world predominated. It was 26 believed that the development trajectories of Third World countries would emulate the apparently immutable paths taken by the now industrialized world. Acceptable rates of rural-to-urban migration, regional articulation emanating from the needs of modem industrial sectors to link with their hinterlands, and stable political structures based on an increasingly educated populations were all expected to occur. Unfortunately, as a direct result of the questionable assumptions upon which this research was based, the expected outcomes were not forthcoming. Instead, rural-to-urban migration far exceeded anticipated levels resulting in "overurbanization" and "hypertrophy of the tertiary," income and regional inequalities failed to moderate; educational, social, and health provision facilities lagged behind the populations’ needs; and the fertility and mortality declines typically accompanying development emerged much less quickly than predicted.

The dependency/world systems theoretical approach in sociology partially rectified standard conceptions of economic growth by calling attention to the new economic milieu in which developing countries are forced to compete, unlike their now-developed predecessors.

Dependency/world systems theories' contributions to economic growth debates revolve around their shift of focus from intranational factors affecting development to international factors. Previous explanations of economic growth focused only on factors such as human capital development, internal market size and resource endowment (Jaffee,

1985). Briefly, an educated work force and investments in education are thought to enhance development by cultivating skilled labor, whereas large internal markets lend themselves to mass production and cost reductions that boost economic development. 27 Similarly, raw material endowments foster economic independence and reduce production costs. The newer body of economic growth literature incorporates both internal and external factors in competing tests of validity (Bornschier and Chase Dunn, 1985; Jaffee,

1985; Timberlake and Kentor, 1983; Firebaugh, 1992).

The dominant debate until Firebaugh’s (1992) work surrounded the effect of multinational corporate penetration on the internal dynamics of LDCs. Multinational involvement in LDC economies allegedly distorted development patterns, resulting in retarded fertility declines (London, 1988), slower mortality reductions (Wimberley,

1990), increased political instability (Boswell and Dixon, 1990), higher income inequalities (Crenshaw and Ameen, 1994), and more rapid over-urbanization (Bradshaw,

1987). Some movement toward the development of more comprehensive examinations of economic growth emerged from these debates. The general conclusions seemed to be that the various forms of external involvement in the domestic economies of LDCs, either measured as vertical trade patterns, commodity concentration, export dependence or foreign capital penetration, all exert deleterious or negative effects on economic growth rates. More recently, excessive urbanization was brought into the discussions and empirical analyses and is being touted as an intervening factor between foreign investment and lagging growth (Timberlake and Kentor, 1983; London and Smith, 1988).

Irrespective of the addition of external factors to explanatory schemes, measurement refinements, and specification improvements, and debates surrounding the interpretation of the PEN indicator (see Firebaugh (1992) for a discussion), a serious gap in the economic growth literature exists. A blatant disregard for the crucial role of played by 28 energy supply and use plagues this literature.

Undoubtedly, the supply and use of inanimate sources of energy constitute the

building blocks upon which all societal life and progressions rest. The ability of humans

to harness greater and greater amounts of energy and generate surpluses are responsible

for societal transitions from hunting and gathering through industrial societies (Lenski,

1966). For example, the shifts from hunting and gathering societies to simple

horticultural to advanced horticultural were all contingent upon developments in the

"technology" (e.g. the plow) that permitted the more efficient translation of human

energies into work. More specifically, the use of metals, hoes, axes etc, increased the

efficiency with which human energy was transformed into work. The use of animal

power, and the plow in particular, resulted in the shift from advanced horticultural to

agrarian societies. The use of machines and mechanical production that characterizes the

industrial and post-industrial phases of societal development fundamentally rests upon the

conversion of inanimate sources of energy into work. Given the central role played by

greater and greater energy conversions and increasing efficiencies in societal

transformations, (i.e., economic growth), the exclusion of these factors in current

explanations of economic growth is puzzling.

Apparently cognizant of the importance of energy to development, researchers

seemed content to use energy consumption merely as a proxy for modernity and social

complexity. Researchers continually fail to recognize energy’s role as a basic factor of

production, the differential supply and use of which has effects on national debt, the competitiveness of the exports that allegedly retard growth, and the effect of energy 29 exports on economic growth rates. Perhaps even more striking is the continued disregard

for the role of energy efficiency even after some researchers switch from energy

consumption per capita to measures such as real gross domestic product, following

recognition that countries use energy with varying degrees of efficiency which

consequently distorts comparisons of development levels. Energy production or fuel exports and energy efficiency would clearly constitute additional exogenous variables in the models currently employed. Another anomaly occasionally evident in the literature on economic growth is the disregard for the oil price shocks that occurred in 1973 and

1979. For instance, Timberlake and Kentor (1983) opted to analyze economic growth for periods which were characterized by these price "disturbances." Apparently, they perceive absolutely no effect of high fuel prices on production and growth. Even if one argues that the prices had effects that were evenly distributed across the board, should it not be the case that technical adjustments made during times of high prices be maintained following the return to lower prices (see Schipper and Meyers, 1992 for examples) and that the differential adjustments (efficiencies) would then have effects in later periods? In any event, it should be abundantly clear by this time that the omission of energy from conceptual and empirical analyses on economic growth has been a grave mistake. I will begin to rectify this situation by replicating the basic models of Bornschier and Chase-Dunn (1985) as closely as possible and including energy intensity as an additional independent variable. Furthermore, this will be conducted for the pre- and post-oil shock periods in an attempt to identify changes that may have occurred as a result. CHAPTER III

ADAPTATIONS OF THEORIES OF DEVELOPMENT

Three theories of development will guide the analyses to be conducted. These include modernization/convergence theory, dependency/world-systems theories, and ecological-evolutionary theory. While earlier development studies tended to treat these three theoretical schemes as opposing or competitive, I prefer to view them as providing potentially complementary explanations for a variety of phenomena associated with societal development. Modernization theory provides the primary explanations for the dynamics occurring as countries make their shifts from agrarian to industrial to post­ industrial forms. Dependency/world systems and ecological-evolutionary theories highlight deficiencies in the basic modernization explanations and suggest dynamics that alter or modify the orderly course of development predicted by modernization theory.

The result is a more comprehensive and nuanced explanation of development. More specifically, dependency/world system theorists argue that histories of colonization and dependent insertion into the global economy retard economic development and attendant internal processes. Ecological-evolutionary theory and its variants, on the other hand, provide reminders that technological, ecological and bio-physical histories of nations affect the pace and abilities of nations to modernize and adopt innovations. In essence, their contributions reside in highlighting factors that affect the societal transformations which have been overlooked by modernization theorists. In the discussion that follows,

30 31 the central tenets of each theory will be described along with a discussion of how each theory can be modified to accommodate energy intensity.

Modernization Theory

Modernization/convergence theory provides the principal explanations for the sectoral evolution of nations and concomitant forms of stratification and differentiation.

Although used to explain processes such as mortality and fertility transitions and patterns of economic growth, modernization theory has most frequently been used to explain the size distribution of income both within and across nations. The essentials of modernization theory highlight the centrality of the economic maturation of national economies as shifts are made from agricultural to industrial bases. Issues such as rates of urbanization, mortality declines, and income inequalities, are among be the consequences resulting from shifting economic bases.

Modernization/convergence theory is predicated on assumptions of less developed countries (LDCs) ultimately assuming the economic and social forms of the now developed world as their economies mature. The core of modernization theory centers around the sectoral evolution of countries (Rostow, 1960), The topics of standard cross­ national research direct attention to the consequences of shifting sectoral configurations and the concomitant dislocations. Generally, the disequilibrating effects such as high levels of income inequality and excessive population growth stemming from low mortality and high fertility are viewed as transitional, factors which eventually moderate with the onset of mature industrialism. Theoretically, curvilinear patterns are expected for a variety of phenomenon. In the case of income distributions, for example, excessive 32 inequalities at intermediate stages of development are thought to occur because the costs of financing development efforts necessitate wealth concentration. Relatively low levels of inequality exist at very low and high levels of development but for different reasons.

At low levels of development there is very little surplus and individuals tend to be equally impoverished. At high levels of development following industrial maturation the need for capital accumulation to finance development efforts becomes less imperative and institutional and social diffusion occurs. The outcome is moderating sectoral and personal inequalities. Another example of the "worsening then improving" theses emerging from modernization explanations is evident in the case of population growth. Low rates of population growth prior to the onset of modernity are a function of simultaneously high mortality and fertility regimes. Low mortality and fertility are responsible for the low population growth rates at high levels of development. High population growth during intermediate stages of development arise from low mortality but high fertility, in essence an imbalance occurring from the uneven pace of the diffusion of innovation and sectoral imbalances at this stage of development (Alonso, 1980; Kuznets, 1963). As the theoretical exposition unfolds, it will become apparent that the sectoral shifts and energy

"needs" of countries differ depending on the stage of development. The result will be predictions of yet another "worsening then improving" scenario, in this case for energy intensity.

Based on examinations of developed countries, five stages of growth were identified through which economies endure. Stage one, or traditional society, for all practical purposes can be considered the starting point. During this phase production is 33 limited because of pre-Newtonian science and technology and output per head is low

(Rostow, 1960). Naturally one can infer that the use of commercial fuels is very low or

virtually non-existent at this stage. The lack of technology means that the ability to

harness energy other than that of humans and animals is limited. The result is a natural

cap on production. Energy intensity, or the amount of commercial energy expended in

the production of goods or materials should also be very low. The congruence of this adoption of modernization theory with standard cross-national research will become even more apparent.

During stage two, the pre-conditions for take-off, the role of technology becomes more prominent with more productive agricultural and industrial techniques being developed. Old forms of social organization still predominate, however, and power and values remain regionally based with little national organization (Rostow, 1960). Limits on the rate of change exist, however, but the idea that economic growth is indeed possible takes hold, the "pre-conditions for take-off" become rooted. At this stage of development national energy regimes are also being transformed. Technological advancements accompanying the shift from stages one to two permit the use of more efficient commercial fuels and thereby result in increased productivity relative to the earlier stage. Both fuel consumption and productivity increase simultaneously, thereby resulting in little overall change in intensities. The additional surplus generated by the use of commercial fuels does have organizational consequences in that it fosters greater occupational specialization and generates the need for more centralized forms of organization. 34 The trends accelerate during stages three and four. Technological advancements rise in importance and new growth industries are developed. Tremendous strides in political organization must occur during these stages in order for development to proceed.

More specifically, the erosion of "traditional” mindsets begins and political power becomes concentrated in the hands of those with modem views. Advanced political organization is almost a prerequisite since it is the principal mechanism through which capital transfers between sectors, wealth concentration and enhancement of the expansive impulses of the modern sectors are achieved (Kerr et al., 1960). While the new manufacturing and industrial sectors of the economy are productive, the burden of financing the basic infrastructure and start-up costs falls on the traditional sectors of the economy. The development of one or more substantial manufacturing sectors with high growth rates depends on capital extracted from the primary sectors. The inequalities engendered by the sectoral imbalances during these intermediate stages of development have been the focus of cross-national research to date. The shifts described also exert profound influences on patterns of energy use and intensity.

Obviously as countries make transitions from agricultural to industrial bases the absolute amounts of commercial energy consumed rises. The intensity or amount of fuel used per unit of production, however, also increases because of the structural changes needed to support modern industries. Mass production and producing manufactured products for export are most efficiently done in concentrated spaces, usually cities. The spatial concentration of industrial activities serves several functions including 1) enhanced communication between individuals, firms and social organizations, 2) the creation of 35 larger markets thereby providing greater opportunities for niche formation, and 3) the

lowering of transportation, warehousing and infrastructure (Henderson, 1988). Therefore,

as the shift away from agricultural production occurs, city-building including the

construction of railways, roads, office buildings, factories, warehouses, schools,

hospitals, urban housing, electricity power plants, water purifications plants and the like occur. In essence, most of the heavy industrialization and construction tends to coincide with the intermediate stages of development. Given that production of the requisite materials for these activities such as concrete, steel, wood, paper, chemicals, etc. are the most energy intensive of all industrial activities (Schipper and Meyers, 1992), modernization theory would predict that countries at these intermediate stages of development will display the highest levels of energy intensity. The pace of rural-to- urban migration also quickens during the intermediate stages of development in response to the mechanization of agriculture and burgeoning urban economic opportunities and services available in cities. The result, in addition to severe income disparities, is growing use of modem appliances and automobiles by wealthier segments of national populations as well as a general shift to modern cooking fuels (Meyers and Schipper,

1992). These changes place additional strains of energy supplies and increases in energy intensity occur in addition to the aforementioned structural shifts.

During stage five, the age of mass consumption and transition to post-industrial society, the building of infrastructure is complete with maintenance activities predominating. Structural maturation occurs in this phase of development and the new growth industries become consumer goods and services such as finance, insurance, 36 management, marketing, medical care and education. Societal attention becomes directed

toward social welfare, education and security. In effect, in terms of the types of products

required and produced by nations at high levels of development, there is a shift to less energy and material intensive production. Consequently, less inputs of all types,

including energy, are required. Research and development produce new technologies that reduce the costs of all factors of production, including energy. There is increasing use of synthetic fibers, higher strength steel and alloys. Furthermore, market saturation for energy intensive products such as refrigerators, dishwashers, stoves and automobiles have already occurred. The result is that consumers purchase items that are less material­ intensive (less material per value-added, e.g. electronics) (Goldemberg et al, 1987). The shift away from "dirty" industry to information processing and service sector activities are expected to lead to increased productivity relative to energy use, or lowered energy intensity. The continuing technological advancements accompanying development is expected to further enhance the tendency toward lower energy intensities at high levels of development. The inherently energy intensive intermediate phase of development gives way to one in which production remains high, given the enormous investment and high inequities suffered during earlier stages, but the inputs remain relatively low.

Some theoretical elaboration of traditional modernization theory to include the effect of post-industrialism on patterns of energy use and intensity exist (Crenshaw et al,

1994; Jenkins and Crenshaw, 1994), Among the dynamics discussed are 1) the role of technological diffusion across economic sectors and countries, 2) the role of the state, and 3) the effect of opportunity structures on environmental activism. The increasing 37 complexity characteristic of post-industrial societies lends itself to reduced energy intensities, net of the structural shifts discusses before. Increasing competition at the local and international levels fosters the adoption of innovation and cost-minimization procedures. Consequently, unless energy supplies are so heavily subsidized so as not to affect production costs, the overall competitiveness of firms and individuals and the tendency toward institutional isomorphism (Hawley, 1950) is expected to further reduce energy intensities. This tendency toward the diffusion of technological advances and efficient standard operating procedures coupled with competitive marketing and research practices is expected to produce declines in energy intensity. Furthermore, the greater integration into the international economic order by highly developed countries places additional pressures on firms and organizations to improve competitiveness and reduce the costs of factors of production (Crenshaw et al, 1995). Innovation adoption spreads much more rapidly across well integrated firms given the need to remain competitive.

These factors give mature and post-industrial societies additional advantages, particularly in terms of energy conservation, over countries at earlier stages of development.

Developed market economies without heavy-handed state control are also most likely to be most responsive to fluctuations in fuel supplies. These economies can more readily withstand fuel shortages and price increases not only because of increased flexibility and lowered response time for specific industries, but also because of the greater economic base diversification. In short, unlike state-owned enterprises or socialist economies, developed market economies are less subject to the vicissitudes of fuel supplies. Furthermore, irrespective of natural resource endowment, developed market 38 economies are more likely to have instituted energy rationalization programs early in their development careers. The overall result is the more efficient use of fuel and lower

intensities.

Finally, elaborations of modernization theory to include post-industrial forms incorporate the role of political democracy and social activism (Crenshaw et al, 1994).

It is argued that environmental activism and calls for reductions in pollution levels are more likely to occur where governments are sensitive to public opinion and do not employ repressive means of population control, in essence democratic states. Citizens of post-industrial societies are also more likely to be literate and to have already acquired the basic "necessities" such as refrigerators, stoves, air-conditioners and the like.

Consequently, they are more likely to direct their attention to issues such as recycling and making upgrades to more energy efficient items. Familiar with the democratic apparatuses, individuals in highly developed democratic states are thought to be more effective in translating calls for cleaner environments into action. The overall effects democratic structures, market integration, advanced technology, literacy, urbanization, improved communications and shifts in basic economic structure should be lowered energy intensities at very high levels of development.

Dependency/World Systems Theories

Dependency and world systems theories are variants of the conflict model that has become pervasive within sociology. These particular theories were developed to address the changing macro-level dynamics that occurred as a consequence of the changing economic milieu fostered by radical advances in communication. It will become 39 increasing evident as the theoretical exposition continues that these theories can be brought to bear on issues of ecological degradation and energy intensity. Recognition of the utility of conflict perspectives to issues of environmental damage is not new. Buttel

(1976) abstracted general principles that cut across various conflict oriented perspectives, the basics of which will become evident as the specifics of the dependency/world systems theories are discussed, To summarize, he argues that 1) environmental problems are

"irrationalities of capitalist production" (Buttel, 1976:315), 2) the capitalist classes "buy off" labor by promises of economic growth and increases in wages thereby averting conflict, 3) capitalism is based on individual ownership of properties and production decisions of individuals are at odds with "societal" interests 4) environmental destruction is necessary for the persistence of capitalism, and 5) given that environmental activists are drawn from the elite stratum, "environmental demands will be modified to dovetail the exigencies of economic growth" (Buttel, 1976:317).

The dependency/world systems traditions complement our understanding of the dynamics of societal transformations as delineated by modernization theory. By calling attention to the differing contexts in which developing countries must operate and compete compared to the now developed countries, this tradition suggests ways in which the orderly maturation processes predicted by modernization theory are distorted. The most definitive features of these perspectives are the notions that dependent insertion into the global economy inevitably results in distorted development patterns and, within the capitalist global system, development by one country or group of countries necessarily entails under-development and exploitation of other regions. Dependency/wo rid system 40 theorists posit a variety of mechanisms through which the resources of LDCs are used

to further advance the development of core nations.

At the most general level, dependency/world system theorists argue that there is

an international division of labor with elites in the developed world (core countries) using

the essential logic of capitalism to exploit the resources of the developing world

(peripheral countries). While these elites possess superior military strength and are capable of simply taking surpluses from developing countries, they instead use combinations of co-optation of peripheral country elites, the legitimacy of the capitalist

system, and the dissemination of their national culture to legitimate disparities and foster conditions of unequal exchange. Elites in the developing world, in order to advance their own interests and positions within the international order, facilitate and assist in the exploitation of local resources. In this way the sphere of influence of elites in the core is extended. The outcome of these alliances is the exacerbation of the disequilibrating effects following the onset of modernity and the development of under-development

(Baran, 1957; Frank, 1967; Evans, 1979).

The result of foreign involvement in the domestic affairs of developing countries is a structural condition labelled "disarticulation". Disarticulation refers to the juxtaposition of economic sectors with radically different levels of productivity (Amin,

1976). Disarticulated countries are typically characterized by a very productive capital intensive modern sector that produces products for international markets located within contexts of subsistence and informal types of activities. These economies lack the economic, social and political connections and interdependencies that bind national 41 economies. Economic sectors are fragmented and backward and forward linkages absent.

The lack of economic ties translates into lagging economic growth, excessive

urbanization, and lagging reductions in population growth. The absence of "spread

effects" typical of distorted economies is argued to be a direct consequence of the types

of international economic linkages these countries hold.

In the case of foreign investment, for example, international corporations provide

packages of patents, designs, industrial processes, high salaried technicians, trademarks,

salesmanship, and recently obsolete equipment from developing countries (Frank, 1967).

Based on their reputations and credit-worthiness, they acquire local capital for their

investments and, in doing so, deprive indigenous businesses of loans. Furthermore,

weaker local firms are either swallowed up or driven out of business by the new business

ventures. Unfortunately, the consequences of multinational investment corporations for

LDCs are devastating.

In purely economic terms, multinationals utilize local capital and hence discourage domestic investment, create unemployment and destroy indigenous competition through the use of capital intensive techniques, and exacerbate income inequalities and regional inequalities. Furthermore, given the abilities of multinationals to choose from different

LDCs all vying for relatively advanced technologies and competitive edges, LDCs are often forced to make concessions to multinational firms which usually work to their detriment. These concessions include wage freezes and rigid controls over labor so as to guarantee a low wage pool of workers, tax credits for extended periods (Bornschier and

Chase-Dunn, 1985), and more recently environmental concessions (Leonard, 1988). 42 Specific examples of LDC concessions abound. During the 1970’s, for example,

Brazil’s dire need for capital led the government to institute wage freezes in attempts to give them a competitive advantage over other LDCs in attracting foreign investment

(Wood and de Carvahlo, 1988). The lowering of absolute levels of living conditions given inflation also raised infant mortality rates for families living close to the poverty line. Examples of countries willing to permit environmental pollution as incentives to multinational corporations in exchange for capital investments are provided by Leonard

(1988). Ireland’s Industrial Development Authority initially actively recruited pharmaceutical and chemical companies with explicit recognition that "for the sake of the economy and jobs, some of the dirtier industrial facilities from the advanced industrial nations might have to be sited on terms that offered less stringent pollution controls than in Europe or the United States" (Leonard, 1988:127).

The specific and deliberate involvement of multinationals and core nations in the development processes of LDCs is not the only mechanism through which under­ development is created and perpetuated. The general type of development strategy pursued by developing countries and the type of economic connections to the global economy can also result in under-development. More to the point, some versions of dependency/world systems theories emphasize characteristics such as vertical trade patterns, commodity concentration, export partner concentration and reliance on extractive industries as creating conditions of under-development (e.g. Galtung, 1971).

The crux of these arguments center around the failure of these types of development platforms to create economic and social multipliers. Unlike countries that pursue more 43 diversified development strategies, specialization in a select few commodities and/or reliance on only a few partners for trade accentuates the vulnerabilities emanating from unstable global markets. These economies are severely affected by conditions that include general economic downturns, product and/or material obsolescence, and the general health of their primary economic partners. The susceptibility of these economies to economic fluctuations is exacerbated by the disarticulation brought on by pursuing these types of development strategies.

With regard to ecological degradation as a whole and energy intensity in particular, some theorists have suggested that core countries and multinationals may be using LDCs as pollution havens (Leonard, 1988; Jenkins and Crenshaw, 1994; Crenshaw et al, 1994). The recent rise in environmental activism and stringent regulations concerning pollutants in the developed world have prompted firms in core nations to seek alternative plant sites in LDCs. As mentioned earlier, capital scarcity and the ability to choose from a multiplicity of sites gives multinational and core countries the upper hand.

Evidence from case studies point to instances of elites in LDCs adopting rigid environmental policies on paper in order to claim they support sustainable practices, but a blatant disregard for policy enforcement (Leonard, 1988). Modifications of dependency/world systems theories to accommodate ecological degradation point to increases in pollution stemming from foreign investment. From the standpoint of energy intensity, however, theoretical expectations point to overall reductions in energy intensity emanating from global integration. Lowered intensities are thought to be a function of the general under-development and disarticulation fostered by either multinational 44 penetration or extraverted economic orientations rather than increased efficiencies. The normal developmental paths of these economies are thwarted in that they fail to make the complete transition to the high-intensity intermediate stages of development predicted by modernization theory. Consequently, while beneficial from a global warming perspective, the fruits of development continue to elude the majority of individuals trapped in these economies.

Ecological-Evolutionary Theory

The third theory from which hypotheses will be derived and tested is ecological-evolutionary theory. The contribution of this theory to development studies rests in its complementary approach to modernization and dependency/world systems theories. Modernization theory emphasizes the internal dynamics of the development process, dependency/world systems theories remind us that countries compete in international markets and their relations with other nations cannot be ignored. Ecological- evolutionary theory calls attention to the fact that the initial conditions that predate the onset of development affect developmental trajectories and countries should therefore not be viewed as uniformly underdeveloped prior to the onset of development.

The original formulation of ecological-evolutionary theory points to the early adoption of plow agriculture as the principal historical event that differentiates countries

(Lenski and Nolan, 1984; Nolan and Lenski, 1985). The large increase in surplus created by use of plow agriculture had revolutionary social organizational consequences which were to exert lasting effects on the development histories and stratification systems of these nation (old agrarian societies). More specifically, the additional surpluses in these 45 societies increased social carrying capacities. The most significant barrier to supporting

larger populations was therefore removed and both densities and numbers increased. By

freeing significant proportions of the population from agricultural production, economic

specialization and the development of occupational niches resulted. For the first time pre­

industrial cities came into existence. Advanced social organization became possible and

was in fact a necessity given the larger populations and greater occupational diversity.

With the growth of "urban" areas, transportation routes linking rural agricultural areas

to new urban centers developed resulting in overall higher levels of regional articulation

than ever before (Crenshaw, 1992), The increased lines of communication and control

also enhanced political centralization. These developments, all basically attributable to

rises in agricultural productivity and concomitant population growth, are the major

factors that differentiate pre-industrial societies. Ecological-evolutionary theorists argue

that, following the onset of industrial development, these "institutional" inheritances

further differentiate societies by tempering the disequilibrating negative effects of the

intermediate stages of development. Furthermore, the advanced organizational

"inheritances" described above facilitate the process of diffusion so critical to the modernization process. Consequently, old agrarian societies may actually advance through the painful transitional stages of development at accelerated rates.

Previous research supports the basic contentions of ecological-evolutionary theorists. Analyses conducted on income inequality and infant mortality employing simultaneous tests of modernization, dependency/world systems theories, and ecological- evolutionary theory find that the advanced technological and ecological histories of old 46 agrarian societies did indeed exert independent influences on the social structural characteristics of nations (Crenshaw, 1992; Crenshaw and Ameen, 1993, 1994). Old agrarian societies, for example, were found to be less prone to be characterized by the sharp income inequalities during the intermediate stages of development.

Similarly, infant mortality reductions were found to proliferate more quickly in nations with advanced rural social organization. The lower levels of both income inequality and infant mortality are most likely to be functions of lower levels of rural- urban disparities brought on by modernization. Prior to the onset of modernity, the high population densities of old agrarian societies forced more equitable distributions of resources. Also, the inequalities typically brought on by industrialism are moderated by the advanced pre-existing social organization and the greater diffusion of innovation, technology, urban forms, and wealth. Explanations for accelerated declines in infant mortality are straightforward. Histories of high population densities inevitably resulted in lowered levels of regional disparities, greater communication between villages and towns and more advanced roads. The greater regional, institutional and spatial articulation of old agrarian societies expedites the diffusion of mortality reducing technologies thereby resulting in the observed patterns. Preliminary analyses indicate that the same structures should also facilitate the diffusion of fertility reducing technologies and result in lowered fertility rates (Crenshaw and Ameen, 1994, 1995). Further modifications of ecological-evolutionary theory to include national energy regimes has been begun, (Crenshaw et al, 1994) but, until now, rigorous empirical tests remain absent. 47 The core arguments for the effects of "institutional inheritances on energy use and intensity reside in EETs focus on competition for scarce resources and the accelerated rates of the diffusion of innovation. The advanced social organization of old agrarian societies predisposes these nations to the faster diffusion of modern innovations and thereby shortens the painful transitional stages of modernization. Nolan and Lenski argue that the "shift from horticulture to agriculture meant a substantial increase in productivity and in the potential size of the economic surplus, and these developments led, in turn, to increases occupational specialization, the growth of towns and cities, the growth of the state, and numerous other changes that are part of what we have come to associate with societal development" (Nolan and Lenski, 1985:343). Furthermore, labor abundance in these countries advantages them by affording them opportunities to fill labor intensive niches in the world system. The overall result for energy use is straightforward. Prior to the onset of industrialism, competition for scarce resources should lead these nations to exhibit lower levels of energy. Long histories of frugality and scarcity with regard to surpluses of all forms would be expected to be extended to the area of energy use.

Following the onset of industrialism, these nations should continue to experience lower growth in energy intensity compared to other nations as they mature at accelerated rates and move toward the stages of mass consumption. Energy conservation techniques and technologies are expected to be diffused more rapidly compared to less densely populated countries through the same mechanisms that mortality and fertility reducing technologies are disseminated. CHAPTER IV

METHOD AND DATA

Overview of Analysis

The ultimate goal of this project is to arrive at a comprehensive view of the

structural determinants of changes in energy intensity using the theories of development

described earlier. Ideally this would be accomplished by a longitudinal analyses of

aggregate energy intensity with decompositions by detailed economic sector.

Unfortunately, national data reporting systems vary considerably even for the simplest

of data required to conduct this analysis (e.g. gross domestic product). Therefore the

analyses are constrained by data availability. Irrespective of this limitation, sufficient data

are available so that a relatively complete analysis of changes in energy intensity can be conducted. The analysis will include five sets of dependent variables. The first four will be used to assess the utility of theories of development for identifying structural constraints on changes in energy intensity. The fifth set of analyses will be used to assist in ascertaining the effect of energy intensity on economic growth.

The first phase of the research is included for the purpose of determining changes in aggregate energy intensity between 1965 and 1985. This phase of the research is further sub-divided into two periods. The first pre-shock period covers the years 1965 to 1973 while the post shock period extends from 1974 to 1985. Admittedly, the second dependent variable in this set of analyses includes the oil-shock of 1979. Given that an

48 49 analysis of the period 1979 to 1985 would be too short of a period to analyze, I opted

to use the longer 1974 to 1985 period. Consequently, the first set of analyses essentially

becomes a comparison of a period free of oil price disturbances and one with price

disturbances. A completely oil price disturbance period is included in phase 2 of the

research. The other three dependent variables in the first phase of the research are cross-

sectional and "supplementary" in that they are included to ensure rigor. These variables

are aggregate energy intensity for 1965, 1975 and 1985. The assumption behind including

the cross-sections is simple. Should the findings of the longitudinal and cross-sectional

models prove to be congruent, confidence in the findings will be increased.

The second set of analyses focuses exclusively on the post-oil shock period. A

longitudinal analysis of change in aggregate energy intensity from 1979 to 1989 will be

conducted along with a cross-sectional analysis for the year 1979. The results of this set

of analyses will be compared to those of the previous phase of the research in order to

identify: 1) shifts in the determinants of energy intensity between the pre- and post-oil

shock periods; 2) consistency in the findings as a whole; 3) consistency in the determinants of the post-oil shock period from alternative constructions of the dependent variables. Some overlap in variables is deemed necessary given the absence of previous

findings in this area against which to compare the results.

The decomposition of the aggregate intensity measures begins in third phase of

the research. Data limitations on energy consumption by sector restrict the period of analysis to the decade spanning 1979 to 1989. The three broad economic sectors to be analyzed include agriculture, industry and services. As with the previous dependent 50 variables, the same theoretical models will be applied to these categories. Given the overwhelming importance of industrial energy consumption to total national energy use, a comparison of the findings of this phase of the research to those in the second set of analyses will shed light on the extent to which constraints on energy regimes are primarily sectorally determined. Results from this set of analyses will also contribute to assessing the validity of theories of development to national energy use and intensity.

The fourth phase of the research further disaggregates the total energy intensity measure. Unfortunately, data limitations become more restrictive as level of specificity increases. Consequently, the analysis in this set of analyses is purely cross-sectional for the year 1979. The potential advantages of including this set of analyses reside in the level of specificity possible. The energy intensity variables to be analyzed in this phase of the research include 1) agriculture, 2) transportation, 3) residential, 4) industry and

5) a residual variable labelled "services." Results will be specifically compared to the third phase of the research longitudinal sectoral analysis of the third phase of the research and to the theoretical findings as a whole.

In the fifth phase of the research the utility of energy intensity to theories purporting to explain development-related phenomena will be explored. Specifically, well established models of economic growth (Bomschier and Chase-Dunn, 1985) will be replicated and energy intensity will be added as an additional independent variable. Given the argument throughout this manuscript that the supply and cost of energy affect the manner in which it is used, two economic growth equations will be estimated. The first equation will examine economic growth rates from 1965 to 1973, a period free of price 51 disturbances. The second will focus on the 1974 to 1985 period. Therefore, in addition

to ascertaining whether or not the efficiency with which energy is used affects economic

growth, I will attempt to ascertain if changes are discernable across the pre- and post-oil

shock periods.

Sample

Appendix A contains a list of the countries used in each of the 16 models estimated in this research, Depending on the dependent variable in question, the sample sizes for the fully specified equations range from a minimum of 52 countries for the longitudinal analyses of sectoral energy intensity to a maximum of 95 for the analysis of total energy intensity for 1965. A brief inspection of appendix A will reveal that except for the absence of Soviet Bloc countries, there is adequate representation of countries from the developed as well as developing worlds. Fair numbers of African, Asian, Latin

American, and European countries all make their way into the analyses. The exclusion of countries from particular equations was based on data availability and, with the exception of Soviet Bloc countries, no systematic biases were apparent. The reader should bear in mind that the samples are not randomly selected and t-tests and significance levels should only be viewed as rough as rough guides in interpreting the findings. No noteworthy anomalies were evident from and inspection of the means and standard deviations of the variables used in the analysis. Variables that were skewed were logged to improve their distributions. A table containing the means and standard deviations of all variables used in the final analyses is included in Appendix C. 52 Method

Panel regression and Ordinary Least Squares (OLS) regression are the methods

of choice for this analysis. Regression diagnostics including partial plots, studentized

residuals, DFITS, hat matrix, and dfits are used to identify influential outliers. As a

general rule, countries needed to exceed cutoffs on at least two diagnostics to be

excluded from equations. Also, in order to ensure stability of findings, a second round of outlier analysis was conducted to determine if the results were truly robust. Following

identification of the significant independent variables, cases were re-introduced into the equations on a one by one basis to determine if they needed to be excluded from the results presented. This strategy allowed for minimizing the number of cases excluded while preserving the integrity of the analysis. Sample sizes ranges from 121 to 52 depending on the dependent variable and model specification. The theoretical schemes advanced dictated that both developed and developed countries be included in the analysis. As discussed above, while the bulk of the analysis is longitudinal, cross- sectional methods were also employed to add rigor and, in the case of the fourth set of analyses, because data limitations precluded the use of longitudinal analyses.

Dependent Variable and Operationalizations

Phase one

Phase one contains the 5 energy intensity dependent variables described above and are constructed in similar fashions from similar data sources. Analyses of these dependent variables require the construction of energy intensity for 1965, 1973, 1974,

1975, and 1985. Energy intensity for a particular year (the amount of energy used per 53 unit of production) is calculated as the total energy use for that year divided by total real gross domestic product for that year. Total energy use is calculated as the energy use per capita multiplied by the population in that year. Similarly, total real gross domestic product is calculated as real gross domestic product per capita multiplied by the population in that year. Data on energy use per capita were obtained from various years of World Energy Supplies (United Nations). Data on population sizes were obtained from

Summers and Heston (1992). The real gross domestic product per capita data are also from Summers and Heston (1992). It should be noted that real gross domestic product excludes factor income from abroad and has been adjusted to eliminate the effects of inflation. These data also adjust for purchasing power and are reported in 1985 constant international prices, all desirable characteristics for this type of analysis.

Phase Two

The calculation of the dependent variables for the second phase of the research is very similar to that for phase one. Aggregate energy intensity for 1989 and 1979 are calculated as total energy use for the particular year divided by total real gross domestic product. Data on total population and energy use were obtained from the World Bank

(1992). Total real gross domestic product figures were obtained from Summers and

Heston, 1995).

Phase Three

Phase three examines growth in energy intensity from 1979 to 1989 for agriculture, industry and service sectors of national economies. Analysis of these dependent variables requires the construction of sectoral energy intensity for both 1979 54 and 1989 for each economic sector. Each variable is constructed in a similar fashion. For each sector and year the proportion of energy used in a particular sector was multiplied by total energy used in that year to yield the total amount of energy used in a particular sector for that year. The total sectoral energy use was then divided by total real gross domestic product from that sector. Total real gross domestic product for each sector was calculated from multiplying the proportion of GDP from that sector by total RGDP. Data on gross domestic product from industry, agriculture and services were obtained from the World Tables (1992). Total energy use for 1979 and 1989 were adopted from various years of the World Energy Supplies (United Nations). The percentage of energy use by sector is reported by the World Resources Institute (1992). Unfortunately, at this point complications arising from apparently incompatible definitions arise. Given that the

World Bank’s disaggregations of gross domestic product by sector do not directly match up with the World Resources Institute’s breakdown of energy use by sector, some judgement was required in matching categories. The match-ups for industry and agriculture were fairly straightforward since both sources reported these categories.

While the World Bank reported gross domestic product for services, the World

Resources Institute (WRI) did not. As a result, energy use in services was calculated as a residual of energy not used in industry or agriculture. In effect, energy use in services amounted to summing the energy used in the transportation, commercial, residential and other sectors as reported by WRI. The problem of category match-ups became somewhat more acute for phase four. 55 Phase Four

Phase four contains 4 dependent variables each measured in 1979. They include

energy intensity for agriculture, transportation, industry, and the residential sector. The

basic construction of each dependent variable essentially mirrors that of the previous

intensity variables. Total energy consumption used in a particular sector was divided the

total real gross domestic product derived from that sector. Once again problems of matching World Bank and WRI categories required some judgement. The case for agriculture was straightforward. Agriculture energy intensity was calculated as the proportion of energy used in agriculture (World Resources, 1992) multiplied by the total energy used in 1979 (World Bank, 1992), thereby producing total energy used in agriculture. This number was then divided by the total real gross domestic product produced by the agricultural sector. The GDP data were obtained from the World Bank

(1983). The proportion of GDP from the respective sector was multiplied by total RGDP to aid in standardization. Calculating energy intensity for the transportation sector also proved to be relatively simple. The proportion of energy used in the transportation sector

(World Resources, 1992) multiplied by total energy used in 1979 (World Bank, 1992).

The result of this operation was then divided by total real gross domestic product from the transportation and communication sector (World Bank, 1983; Summers and Heston,

1995). Industry energy intensity was calculated as the proportion of energy used in the industrial sector (World Resources, 1992) multiplied by the total energy used in 1979

(World Bank, 1992). This figure was then divided by the sum of real gross domestic product from the manufacturing, mining, and construction sectors (World Bank, 1983; 56 Summers and Heston, 1995), Given that the World Bank’s reporting system for detailed

categories in 1979 did not specifically include an industrial sector, some aggregation was

necessary. Industry energy use was defined by the WRI to include energy use from iron

and steel; chemicals; nonferrous materials; nonmetallic mineral products such as glass,

ceramic and cement; paper, pulp and printing wood and wood products; food processing;

textiles and leather; transportation equipment; construction; machinery and non-energy

mining. Mining, manufacturing, and construction were the detailed World Bank

categories that were most closely associated with the definition of energy and therefore

used as the corresponding GDP category. Energy intensity for the residential sector was

calculated as the proportion of energy used in the residential sector (World Resources,

1992) multiplied by total energy used in 1979 (World Bank, 1992) divided by real gross

domestic product derived from electricity, gas and water (World Bank, 1983; Summers

and Heston, 1995). All energy intensity variables were logged to improve their distributions.

Phase five

The construction of the economic growth dependent variables follows conventional practice. Economic growth from 1965 to 1973 was calculated as per capita real gross domestic product (RGDP) for 1973 subtracted from RGDP for 1965, the result of which

is then divided by 8. This figure is then divided by RGDP for 1965 and multiplied by

100. This operationalization produces an average annual percentage growth rate following

Jackman (1982). Similarly, economic growth for the 1974 to 1985 period was calculated as RGDP for 1974 subtracted from RGDP for 1985 and then divided by 11. The result 57 of this operation was divided by RGDP for 1974 and then multiplied by 100. All RGDP data were obtained from Summers and Heston (1992).

Independent Variables used in Energy Intensity Equations

Two modernization indicators were used in the analysis. Gross national product per capita (GNPC)for the years 1965, 1974, 1975, 1979, and 1985 and each year’s respective quadratic. This particular indicator was used as the modernization indicator in phases one, two, three, and four. The data were obtained from the World Bank

(1992). As with other indicators such as per capita energy consumption or per capita real gross domestic product, GNPC was used to test for the effect of level of economic development. The reason for utilizing GNPC over energy consumption or RGDP is simple. As argued earlier, energy consumption is an inappropriate indicator for level of development given the differing technological endowments and efficiencies of nations.

Consequently, per capita energy use is not necessarily comparable across nations, especially across nations at differing levels of development. Although RGDP is as equally appropriate indicator of development as GNPC in most analyses, given the use of gross domestic product (GDP) in the calculation of the dependent variables, the use of a conventional indicator of development that was somewhat removed from GDP was the most appropriate choice. Data on GNPC were available and the indicator filled these requisites nicely. The test for curvilinear effects amounted to including a quadratic in most equations, The quadratic for each indicator was constructed by simply squaring each term. As a brief reminder, given a sufficiently large sample size, a curvilinear effect of development is anticipated on energy intensity. Countries at very low and high levels of 58 development are expected to display low levels of intensities with those at intermediate levels of development being the most energy intensive.

The variable used to test for dependency/world systems theory was commodity concentration. The use of this measure was preferable to that of the foreign direct investment indicator because the timing of the observations and coverage are superior and the use of the conventional PEN indicator is problematic in light of Firebaugh's criticisms (Firebaugh, 1992). Also, the preliminary nature of many of these analyses dictate that sample sizes be maximized. Depending on the dependent variable under investigation, the version of the variable used was measured either in 1965, 1970 or

1980. This variable was used given the emphasis on the disarticulating effects of both narrow export platforms and foreign investment. Commodity concentration is expected to be negatively related to both level and growth in energy intensity due to its effect on stunting economic base diversification and restricting spread effects. This indicator is defined as the proportion of all exports accounted for by the three largest export products

(World Bank, 1984).

Population density was the ecological-evolutionary theory indicator used in this analysis. In all cases population density measured at the beginning of the period under analysis. The World Bank (1992) was the source of the population density data for the years 1965, 1975, 1979, and 1985. This variable is formally defined population per square kilometer of land. Theoretically, population density is expected to be negatively correlated to level of energy intensity given ecological-evolutionary theory’s emphasis on the frugal use of resources stemming from intense competition. Density’s relationship 59 to growth should also be negative since it allegedly facilitates the diffusion of innovation and technology and expedites the use of energy efficient production techniques. It should be noted that although agricultural density would be a more appropriate measure of the effect of technoecological heritage, insufficient coverage in terms of arable land and population in principally agricultural areas forces the use of population density rather than agricultural density.

The percentage of the population living in urban areas was also included in the energy intensity equations. The variables percentage population urban for the years 1965,

1975, 1979, and 1985 were obtained from the World Bank (1992). This variable was included to test for the agglomeration effects discussed along with modernization theory.

Net of level of development, high levels of urbanization are thought to increase energy efficiency through conquering the negative externalities associated with space. Since the concentration of economic activity reduces the costs associated with transportation, communication, and warehousing, its effect on growth in energy intensity is expected to be negative.

A component of modernization theory’s predicted decline in energy intensity at very high levels of development stems from the shift to post-industrial society. Aside from the structural maturation characteristic of post-industrial societies, there is a general shift in the labor force composition away from heavy manufacturing toward service oriented activities. The result of this transition is a decline in energy use relative to production as measured in terms of contributions to GDP. Percentage of the labor force in service related activities is included in all energy intensity equations. According to 60 modernization theory and conventional wisdom, the effect of percentage of the labor

force in services on energy intensity should be negative. Given the absence of direct

measures of services related employment, percentage of the labor force in services for

the years 1965, 1975, 1979, and 1980 is calculated using a residual method. The

percentage of the labor force in industry for the year in question year is added to

percentage of the labor force in agriculture and then subtracted from 100. These data

were adopted from the World Bank (1992).

During the theoretical discussion it was suggested that the local availability and

resulting domestic policy may also influence energy regimes by way of either energy

subsidies or state owned enterprises. More specifically, it was argued that countries that

were well endowed with energy resources might exhibit a tendency to subsidize or have

policies that fail to encourage price rationalizations. In order to control for the possible

effect of resource endowment, the value of energy exports was included in all energy

intensity equations. Data for the years 1970, 1974, 1975, 1979, and 1985 were available

from various years of the World Energy Supplies series (United Nations). This variable

was standardized by dividing them by RGDP to control for size of the national economy.

To reiterate, a positive association between energy exports and energy intensity was anticipated.

The variables discussed above constitute the core variables used in the analyses.

In the case of the energy intensity models, however, particularly the detailed sectoral

variables used in phases three and four, additional variables that made intuitive sense

were tested in order to sort out effect. Any explanations derived from models used to 61 determine energy intensity for the agricultural sectors would probably be of little utility unless some measure of capital intensity were included. Unfortunately, data on imports of farm equipment or fertilizers are unavailable at the cross-national level. Regardless of the absence of these data, a measure of the capital intensity of the agricultural sector was constructed by dividing the gross domestic product from agriculture by labor force in agriculture. This measure gives a crude approximation of labor productivity per worker. The assumption behind this proxy is simple: The higher the productivity, the greater the likelihood that mechanization and fertilizers (i.e. modem technologies) are being used and the lower the level of energy per unit of production. Data on GDP from the agricultural sector were available from the World Tables (World Bank, 1992) while that for percentage of the labor force in agriculture were taken from the World Bank

(1992).

The literature on energy efficiency seems to suggest that wealth and income and education increase energy intensity, but following market saturation at high levels of development, there is a negative effect of these factors on energy use. In effect, at very high levels of development there becomes a point at which individuals and families can only use limited numbers of stoves, refrigerators, televisions, air conditioners and the like. In addition to market saturation, new purchases and replacement models are almost invariably more energy efficient than the older models they are replacing, factors that are conducive to lowered energy intensities. In an attempt to sort out the effects of structural economic maturation from those occurring as a function of increasing education, market saturation, and the rise of environmental activism, the effect of literacy was tested in 62 some equations. High levels of literacy are assumed to be associated with greater concern for environmental issues including energy efficiency. Data on adult literacy for 1975 were taken from (Unesco, 1980). A negative effect of literacy on energy intensity was anticipated given the tendency for literacy to be associated with factors such as political democracy and development, both of which are prerequisites for successful environmental activism.

The close connection between increasing productivity and increases in energy use and intensity through most of the stages of growth described suggests that economic growth may raise energy intensities. In order to test for this effect economic growth from

1960 to 1979 was used in the analysis. This variable was calculated as RGDP per capita in 1960 subtracted from RGDP per capita in 1979 divided by 19. The result was then divided by per capita RGDP in 1960 and multiplied by 100. Economic growth is believed to increase energy intensity given that increasing productivity almost invariably entails raising the level of inputs, including energy.

A variable related to the productivity of nations is the proportion of gross domestic product from the manufacturing sector. As discusses in previous chapters, the production of some materials such as paper, pulp, cement, and steel necessarily involve more energy use per unit of value-added compared to the production of other items.

Furthermore, since most of these energy intensive items are considered to fall in into manufacturing, nations with large manufacturing sectors should display higher energy intensities. The proportion of GDP from manufacturing in 1979 was calculated as GDP in manufacturing divided by total GDP in 1979. These data were obtained from the 63 World Tables (World Bank, 1983).

Two additional variables thought to be of significance in affecting energy regimes

used in the analysis but that also failed to make their way into the final models were

political democracy and the production of minerals. As a reminder, successful political

environmental activism is believed to be dependent on the existence of democratic

structures (Crenshaw et al, 1994). The democracy measure used in the analysis was

Bollen’s Political Democracy Index (BoIIen, 1980). A negative relationship between

political democracy and energy intensity was anticipated. Net minerals exports

standardized by size of the economy was used in an attempt to control for the differing

industrial bases of nations. This variable was calculated as mineral imports subtracted

from mineral exports divided by RGDP. The data on mineral exports and imports were

obtained from multiple years of the UNCTAD Commodity Yearbook (United Nations).

The variable was used in an attempt to control for the production of energy intensive raw

materials. The results presented in the following chapter do not include literacy,

agricultural gross domestic product, democracy and mineral exports in the models. These

variables failed to display any consistent effects and were not used in the analysis.

Democracy and adult literacy failed to display consistent effects, probably due to the

inclusion of several other modernization-related variables in the equations (GNP, the

quadratic of GNP, urbanization, and percentage of the labor force in services) and the

lack of unique independent effects of literacy and democracy . Minerals exports also

failed to exert any demonstrable effect on energy intensity and was dropped for the sake of parsimony. 64 Independent Variables used in Economic Growth Equations

The development indicators used in the analysis were real gross domestic product

per capita (GNPC) and its quadratic. The inclusion of the squared term follows conventional practice and is designed to account for the fact that the most rapidly growing countries tend to be those at intermediate stages of development (Bomschier and

Chase-Dunn, 1985). These data were obtained from the World Bank (1992). GNPC was

logged in accordance with previous empirical research. Following Firebaugh’s (1992) work illustrating the shortcomings of the conventional foreign direct investment indicator

(FDI and PEN), the flow measure is used in this analysis to avoid ambiguity in findings.

For the economic growth equation for the period 1965 to 1973 foreign investment rate from 1967 to 1973 is used. This variable is simply an average annual flow rate from

1967 to 1973. The rate is calculated by subtracting foreign investment rate for 1967 from foreign investment from 1973 and dividing by 6. The result is then divided by foreign flows in 1967 and multiplied by 100. In the equation for the period 1974 to 1985 foreign flows from 1967 to 1978 is used as the dependency/wo rid systems indicator. This variable is calculated in the same fashion as the flow measure for the earlier period.

These data were adopted from Ballmer-Cao and Scheidegger (1979). Dependency\world systems theorists expect that foreign investment would encourage economic growth in the short run while negative effects are expected in the long term due to the lack of re­ investment and economic multipliers.

Data on gross domestic investment were taken from the World Tables (World

Bank, 1984). For the earlier period gross domestic investment for the decade 1960 to 65 1970 was used. For the latter period gross domestic investment from 1970 to 1980 was employed. As noted by Rostow (I960), investment leads to the expansion of economic opportunities, job creation, and prompts infrastructural developments, all factors contributing to economic growth. These variables are constructed as average annual growth rates using the method described above for the foreign flow rates. In accordance with previous research, gross domestic investment is expected to increase national economic growth rates.

In order to replicate the Bornschier and Chase-Dunn economic growth equation, controls for export dominance and market size are included in the models. Export dominance is measured as the value of exports divided by real gross domestic product

Bornschier and Chase-Dunn (1985). Size of the domestic economy is measured by energy consumption for 1965 for the earlier period and 1974 for the latter economic growth period. Bornschier and Chase-Dunn (1985) include size of the local market since is a resource that can aid countries in gaining upward mobility in the world system. Local demand for products protects dependent nations from fluctuations and downturns in world demand, thereby ensuring continued economic health. The use of total energy consumption is deemed appropriate since total commercial energy consumption provides a rough indication of the size of the modem sector of national economies, a factor that is necessary to economic growth in the modem world system.

Two variables included in this analysis of economic growth that set it apart from previous research are energy intensity and population density. The rationale for both these variables has been discussed earlier. In the case of energy intensity it was argued 66 that the supply and flow of energy is crucial to development efforts and should not be

neglected. Life in the modem world rests upon the conversion of inanimate forms of

energy into material goods and services. Obviously, the efficiency with which nations use

energy affects the prices of the materials they produce for both domestic and international

markets and should therefore naturally affect national economic growth rates. All else

constant, the higher the energy intensity of a nation the higher the expected economic

growth rate. Energy intensity for 1965 and 1974 are constructed as total energy use in

each year divided by total gross domestic product for that year. Data on energy use were

obtained various years of the World Energy Supplies (United Nations) while the gross

domestic product data were taken from the World Tables (World Bank).

Population density is used as a proxy for the technological and institutional

inheritances of nations as suggested by ecological-evolutionary theory. Briefly, nations

that experienced historically high rates of population growth due to surpluses produced

by plow agriculture are thought to be institutionally advantaged following the onset of

industrialization (Crenshaw, 1992). The faster diffusion of innovations, technology,

spatial and social articulation and more "modern" mindsets, stemming from their superior

internal institutional linkages allegedly accelerates their economic development. As a

result, population density in 1965 is expected to exert a positive effect on economic growth rates for both periods under examination. The data for this variable were taken

from the World Bank (1992). CHAPTER V

RESULTS

Results Pertaining to the Determinants of Energy Intensity

Phase One

The first dependent variable in this set of analyses is growth in energy intensity

from 1965 to 1973. Bivariate correlations presented in Table 1 show that, as expected,

higher levels of energy intensity in 1965 are associated with lower growth rates in the

ensuing 8 year period. The modernization-related indicators are all associated with

decreases in energy intensity. Both gross national product per capita and its quadratic are

weakly correlated to growth in energy intensity (-.16 and -.18 respectively) while the correlation for urbanization is somewhat stronger (-.22). These bivariate correlation lend preliminary support to modernization arguments that at high levels of development growth in energy intensity is reduced. Undoubtedly, part of the negative relationship is also produced because high growth rates are difficult to achieve given relatively high levels at the onset. Ecological-evolutionary theory’s arguments regarding energy conservation appear not to be supported for this initial period as evidenced by the modest positive correlation. This findings may be related to the relatively abundant and cheap supply of energy in the pre-oil shock period. As expected, a positive correlation between energy resource endowment and growth in energy intensity is in evidence indicating that availability does influence patterns of use.

67 68 Results from the panel regression are presented 1 in Table 2 . Equation 1 contains the lagged dependent variable and the principal modernization indicators, GNP per capita and its quadratic. As expected, both GNP and its quadratic are significant and are in the anticipated directions. Also, as expected the majority of the variance is explained by these 3 variables (88 percent). Equation 1 therefore provides clear support for modernization theory and illustrates that development is in fact related to increases in energy intensity with decreases occurring at very high levels of development. These basic findings remain unaltered as urbanization and commodity concentration are introduced into the model (equations 2 and 3). The introduction of population density in equation

4 produces results that are contrary to the theoretical expectations of ecological- evolutionary theory. The consistent positive coefficient of population density in equations

4, 5 and 6 would seem to indicate that, at least for the pre-oil shock period, densely populated countries tended to experience increases in growth in energy intensity. Also, contrary to theoretical expectations commodity concentration increases energy intensity during this period. Apparently, at least for the earlier period, economic specialization in specific commodities bolsters energy intensity, perhaps through spread effects. The fully specified equation (#6) that controls for energy endowment and percentage of the labor force in services shows that modernization theory received support while the patterns predicted by dependency\wor!d systems and ecological-evolutionary theories failed to emerge. The significant negative effect of urbanization is viewed as support for the post­ industrial thesis in light of the failure of the quadratic of GNP to attain significance following urbanization’s introduction. Overall, the addition of proxies representing 69 ecological-evolutionary and dependency World systems theories do not contribute

significantly to the variance explained thereby lending credence to the argument for the

principal role of modernization in determining energy regimes.

Calculation of the inflection point from the coefficients for gross national product

per capita and its quadratic in equation 1 of Table 2 (.86 and -.06) indicates that, during

the pre-oil shock period, a minimum RGDP level of $1300 per capita is required before

declines in energy intensity begin to occur (refer to Figure 1). The mean per capita

RGDP for 1965 was $656 lending yet additional support for the modernization hypothesis

that a countries must begin to move past the intermediate stages of development before

structural conditions become conducive to reductions in energy intensity. With regard to

urbanization, the coefficient (-.008) indicates that a one unit increase in urbanization (see

equation 6 of Table 1) leads to a small (.8 percent), but significant, decrease in energy

intensity. The effect for commodity concentration is positive with a 1 unit increase in the

percentage of the three largest exports leading to a .3 percent increase in energy

intensity. In a similar vein, a one percent increase in population density results in a .1 percent increase in energy intensity for the countries in the sample for the period 1965

to 1973.

The second dependent variable in phase 1 is growth in energy intensity from 1974

to 1985. Inspection of the bivariate correlations (see table 3) largely mirror those of the previous dependent variable. The lagged dependent variable exhibits the largest negative

correlation with growth as expected while the modernization-related variables appear to

reduce energy intensity. The magnitude of the correlations between per capita gross 70 national product and its quadratic are substantially weaker for the latter compared to the

previous period. This would seem to indicate that the logic of modernization theory may

fail to obtain as a consequence of disturbances emanating from the oil shocks (a

speculation that is substantiated by the regression analysis). Urbanization and commodity

concentration are only weakly correlated to growth in energy intensity in this period

while the correlations for density and energy exports are much stronger. Ecological-

evolutionary theory receives support in this latter period as indicated by the negative

correlation (-.23), Apparently, densely populated countries are able to respond to rising

costs and increasing scarcity by reducing their growth. Not surprisingly, fuel abundance

is consistently associated with high levels of energy intensity.

The patterns emerging from the panel regression for the second period are not as

clear as that of the earlier pre-oil shock period (see Table 4)3 . Only after controlling for

population density in equation 4 do significant findings emerge. In accordance with the

predictions of ecological-evolutionary theory, population density in the latter period

apparently reduces growth in energy intensity. This finding is very consistent across equations. The consistent modernization findings of the earlier period are less apparent

in this panel. Only the quadratic of GNP attains significance while urbanization’s effect

is positive. Consistent with theoretical expectations, however, commodity concentration consistently reduces energy intensity across all specifications. The relevance of energy

resource endowment for patterns of energy intensity are more evident in this panel with the control variable being significant and positively related to energy intensity. Overall the modernization model did not fare particularly well in the latter period, perhaps a 71 function of having included the second oil-shock in the period. The dependency\world systems and ecological-evolutionary theories’ predictions were supported in analyses of the latter period.

Calculation of the inflection point for the 1974 to 1985 period points to a different picture compared to the earlier period (refer to Figure 2). The point at which energy intensity decreases in the earlier period was $1300 per capita while it is $460 per capita for the 1974 to 1985 period (see equation 6 of Table 4). This rather dramatic "shifting" of the inflection point to the left (a reduction of approximately $800) is most likely a direct consequence of the very dramatic increase in the costs of energy. The logic of modernization theory continues to obtain as evidenced by the curvilinear pattern, however, during the post-oil shock period countries appear to have made adjustments to increase their efficiencies to accommodate the increasing role of the cost of energy in production costs. With regard to urbanization, and in contrast to the earlier period, a one unit increase in the level of urbanization is associated with a ,55 percent increase in energy intensity during the post-oil shock period. Similar changes in the directions of relationships are evident for both commodity concentration and population density. A one unit increase in the commodity concentration index cause a .6 percent decrease in energy intensity during the post oil-shock period. It would appear that the increasing costs of energy and protectionist policies of developed countries did indeed cause lagging development in countries specializing in the production of a few selected products. A one unit increase in population density is associated with a .1 percent decrease in energy intensity for the period under discussion. This finding would indicate that, with the rising 72 costs of energy, dense nations are able to adapt to shortages more rapidly than those

lacking high levels of social organization.

Cross-sectional panels for 1965, 1975 and 1985 were produced to assist in

producing an overall picture of energy intensity over the period. Furthermore,

consistency of findings across both cross-sectional and longitudinal methods would lead

to increased confidence in the stability of results. Bivariate correlations for energy

intensity in 1965 are reported in Table 5. The observed patterns are consistent with previous correlations. Development indicators are strongly positively related to level of energy intensity as is percentage of labor force in services. Commodity concentration is exhibits a negative correlation with energy intensity (-.55) while population density is only weakly correlated to energy intensity in 1965 (.09).

Results from the OLS regression for energy intensity in 1965 are to be found in

Table 64. As was the case with the longitudinal panels, the modernization variables account for the bulk of the variance explained. The findings produced are very consistent with theoretical expectations. The log of GNP is significant and positive in all 5 equations with the quadratic attaining significance in the more fully specified model. The surprising finding from this model is the consistent positive effect of urbanization on energy intensity. In this instance it appears that conventional wisdom takes precedence over theoretical expectations. More specifically, previous empirical research (Schipper and Meyers, 1992) would predict the observed pattern given the large growth in energy intensive products (automobiles, refrigerators, etc) that typically accompany urbanization.

Sociological theory, on the other hand, would have us expect a negative effect of 73 urbanization on energy intensity, net of development, since urbanization assists in the concentration of economic activities and conquers the constraints of space. The dependency\world systems theories received consistent support as indicated by the negative coefficients for commodity concentration. Similarly, the expectations of ecological-evolutionary theory are borne out in for this dependent variable. The positive coefficient for percentage of the labor force in services is unanticipated. Apparently, at least for the year 1965, large service sectors contributed to inefficient use of energy relative to production. The absence of a control for resource endowment in this set of equations stems from the lack of data on energy exports before 1970.

The zero-order correlations for energy intensity for 1975 are contained in Table

7. The coefficients show a familiar pattern. Modernization indicators such as GNP per capita, urbanization and percentage of the labor force in services are all highly positively correlated with energy intensity. Commodity concentration’s negative correlation is once again evident as is the positive correlation between population density and energy intensity. Energy exports displays a small negative correlation to energy intensity for this year.

Results produced from regressing total energy intensity on the independent variables are found in Table 85 . In all six equations the essential logic of modernization theory is borne out. Both GNP per capita and its quadratic are significant across all six equations. Urbanization, while it fails to achieve significance in equations 2 through 5, achieves significance after controlling for energy resource endowment. Once again, the direction of the coefficient is positive as one would expect based on previous work rather 74 than negative as predicted by sociological theory. The findings regarding commodity concentration are also particularly strong and consistent across all equations in which it was included. It would appear that countries specializing in a few selected products failed to experience the spread effects and concomitant increase in energy intensity/development as expected by dependency\world systems theorists. The findings related to ecological- evolutionary theory are somewhat less consistent for this dependent variable, but it was nevertheless supported. Neither percentage of the labor force in services nor energy exports exerted any influence on energy intensity for 1975.

The final dependent variable in phase one is energy intensity for 1985. Patterns produced by the zero-order correlations closely mirror those from other years (see Table

9). All indicators related to modernization, GNP per capita, its quadratic, urbanization and percentage of the labor force in services are highly correlated to energy intensity in

1985. Commodity concentration exhibits its familiar negative correlation to energy intensity as does population density with its weak positive correlation. The correlation between energy exports is much higher for 1985 than the previous year (.25 compared to .05).

Table 10 contains the coefficients produced from regressing energy intensity for

1985 on the standardized model. The principal modernization indicators, GNP per capita and its quadratic, fare well in all equations except the final model. The introduction of energy exports in equation 6 results in GNP and its quadratic "falling out" while the control variable itself remains insignificant. This probably occurs because of the high levels of affluence emanating from specialization in oil exports. Urbanization is 75 consistently positive lending additional support to research which finds that urbanization increases energy demand and intensity. Also consistent and strong is the negative effect of population density on energy intensity. While not quite as consistent in all specifications, commodity concentration does exert a negative effect on energy intensity for 1985. As in some of the other cross-sectional and longitudinal models percentage of the labor force in services and energy exports fail to have any demonstrable effect on energy intensity. In terms of contributions to variance explained, the principal modernization variables consistently explain most of the variance.

Summary of Findings for Phase 1 and Substantative Interpretations

Overall, the results produced from the longitudinal and cross-sectional models are quite consistent and demonstrate the unique contributions sociological theories of development can have on studies of energy intensity. As suggested in chapter 3, the principal explanations for patterns of energy are likely to be found in the tenets of modernization theory. Arguments for a curvilinear pattern of energy intensity are found in all but one of the five dependent variables. In the pre-oil shock period and in all of the cross-sectional models energy intensity was found to increase as level of development increased and to decrease or at least moderate at very high levels of development. Arguments that post-industrial societies have experienced structural maturation and evolved to service and light industry dominated economies are supported.

While researchers have always suspected this pattern exists at the cross-national level, the results presented from this set of analyses provides compelling evidence. The minimum sample size in this set of analyses was 81 with maximums reaching 116. 76 Findings based on case and regional studies conducted produced principally by

the group at the Lawrence Berkeley Laboratory are supported by the positive effect of

urbanization on energy intensity. The increase in energy intensity associated with

increased urbanization has been shown to exist net of level of economic development.

Although conventional development theory would have us anticipate a negative effect of

urbanization on energy intensity, the positive points to avenues for theoretical

modification.

The dependency\world systems logic suggesting a stunting of economic base

diversification and a lack of spread effects emanating from economic specialization in a

few select commodities and vertical trade patterns received support but principally for

the post-oil shock period. Apparently, during the sixties and early seventies economic

specialization and the reliance on a few specific commodities for enhancing development

was an appropriate strategy. Following the expansion of the global economy, however, countries that continues this strategy appeared to experience slowed development and

reduced energy intensities. Additionally, the protectionist policies of OPEC countries in the seventies adversely affected the economies of countries that were heavily dependent on the exports, particularly those with narrow ranges of exports.

Very consistent support for ecological-evolutionary theory was also found in the analysis of phase one. With the exception of pre-oil shock period, population density exerted a consistently negative effect on energy intensity. Long histories of high rates of population growth and resultant advanced social organization resulted in what seems to be an appetite for energy in the period of plenty but the more efficient use of energy 77 following price disturbances. Based on these preliminary findings, it would appear that countries are not uniformly under-developed as conventional modernization theory would have us believe and initial starting conditions do indeed influence trajectories of development, including patterns of energy use.

Phase 2

The two dependent variables in phase 2 are growth in energy intensity from 1979 to 1989 and a cross-sectional analysis of energy intensity for 1979. This set of analyses is included so that the results can be compared to those of the previous phase to check for consistency in findings. Table 11 contains the bivariate correlations for energy intensity for 1989 and the independent variables. Consistent with the first two analyses conducted in phase one of the research the lagged dependent variable and modernization- related variables are all negatively correlated with growth in energy intensity. Gross national product, its quadratic, urbanization, and labor force in services are all weakly correlated with growth in energy intensity in the post-1979 decade. Population density is negatively correlated with growth in energy intensity in the ten year period as would be expected given the hypotheses derived from ecological-evolutionary theory. Contrary to the expectations of dependency\wor!d systems theories, commodity concentration is strongly associated with growth in energy intensity as evidenced by the positive correlation (.46), Energy exports continues to display its familiar strong positive correlation with growth in energy intensity.

Table 126 contains the results from the panel regression for energy intensity for

1989. As indicated by the high correlation between the lagged dependent variable and 78 energy intensity for 1989, prior level of energy intensity strongly determines current levels. In all six equations estimated modernization theory is supported. Gross national product per capita and its quadratic are significant in all specifications illustrating that level of economic development is consistently and curvilinearly related to patterns of energy intensity. The pattern of a positive relationship between level of urbanization and energy intensity found in the previous phase and suggested by earlier case and regional studies fails to be supported in this analysis of the post-oil disturbance period. Although not significant, both the sign of the coefficients and their magnitude would lead to the conclusion that, net of development, urbanization does not influence energy intensity in this decade. In equations 3, 4 and 5 commodity concentration was positively related to energy intensity but falls out following the introduction of the control for energy exports.

This finding implies oil is probably one of the principal commodities exported by countries that are high on the commodity concentration measure. An unanticipated finding is the positive coefficient for percentage of the labor force in services. As a reminder, the shift to service dominated economies was expected to reduce energy intensities. The direction of this coefficient may be a function of the relatively large sample size and the inclusion of many less developed countries with bloated but unproductive service sectors. The introduction of the control for energy exports also results in population density attaining statistical significance. It would appear that the suggestions of ecological-evolutionary theory are supported in the analysis of this post-oil shock decade. However, final judgement regarding this finding will be reserved until a complete picture of changes in energy intensity is evaluated. As in the previous category, 79 the lagged dependent variable and modernization indicators account for the majority of the variance explained and the sample sizes are well above acceptable limits for standard cross-national research. The reader should also bear in mind that the calculation of the total productivity for each sector was based on proportions of gross domestic product

(World Bank) which were then multiplied by total real gross domestic product.

Calculation of the inflection point for the decade spanning 1979 to 1989 shows somewhat of a return to older patterns in that the point at which declines in energy intensity occur is now $1420 per capita (mean = $3216) (refer to Figure 3). A comparison of this inflection points to those of the 1965 to 1973 and 1974 to 1985 period reveals that some of the gains in efficiencies instituted during the immediate post-oil shock period are maintained but there was a slight movement of the inflection point back to the right. Urbanization fails to attain significance in this period compared to earlier periods. Commodity concentration fails to obtain in this period while a one unit increase in population density leads to a very small decrease (.01 percent) in energy intensity. A very large effect is found for the resource endowment variable indicating that a one unit increase in energy exports is associated with a 1.7 percent point increase in energy intensity. Apparently local availability does indeed cause ''inefficiency.1'

The cross-sectional findings for energy intensity for 1979 are found in Tables 13 and 14. Inspection of the correlation matrix shows no significant departures from prior analyses, Indicators of modernity are highly correlated to energy intensity with commodity concentration exhibiting a strong negative correlation to energy intensity.

Population density continues to be weakly and negatively correlated with energy intensity 80 while energy exports exhibits a modest positive correlation.

Regression results show that, prior to controlling for energy exports, gross

national product and its quadratic consistently behave in accordance with expectations.

Urbanization’s effect is less consistent, but it achieves significance in the fully specified equation. Similar findings energy for both commodity concentration and population density. Not surprisingly, energy intensity for the year 1979 was in large measure affected by the supply of energy. This becomes evident with the introduction of the control for energy resource endowment. Following the introduction of the energy exports

variable development indicators fall out while commodity concentration, urbanization, and population density achieve significance. The importance of the energy exports variable becomes evident from inspection of the r-squares. A full 10 percent of the variance explained is added following that variable’s introduction. As in all other equations, removal of additional outliers only serve to strengthen the observed patterns.

Summary of Findings for Phase 2

Overall, results produced from the analysis of the post-oil shock period are consistent with those from the previous category. Modernization theory once again provides a cogent explanation of patterns of energy intensity. To reiterate, as development increases so does energy intensity. This pattern is probably largely a function of structural maturation and the building of infrastructure. Following the completion of this structural maturation, energy intensities decline as post-industrial forms become ascendant. Consistent with previous research on energy intensity, urbanization increases energy intensity rather than decreasing it as predicted by 81 development theory. The benefits of population density once again manifest themselves

in the form of reduced energy intensities lending additional support to the central tenets

of ecological-evolutionary theory. The dependency\world systems theories contention of

the stunting of development and economic base diversification emanating from reliance

on the exports a few select commodities is again supported. Perhaps least surprising of

all is the very pronounced effect of energy resource endowment in the post-oil shock

period. Energy exports was associated with increases in both level and growth of energy

intensity.

Phase 3

The three dependent variables contained in phase 3 include growth in energy

intensity for industry, services and agriculture from 1979 to 1989, a post-oil shock

period. As mentioned earlier, data limitations preclude the analysis of any other period

for these particular categories. In terms of contributing to the total picture the utility of theories of development to the topic of energy intensity, the results from this set of analyses can be compared to those of phase 2 as well as to those of the first category.

Table 15 contains the bivariate correlations of industrial energy intensity for 1989 with the independent variables. The familiar negative correlation between the lagged dependent variable and growth in energy intensity is evidenced for the industrial sector.

Unlike the correlations produced for the total energy intensity measures, the modernization related variables (except for labor force in services) are positively, though weakly, related to growth in energy intensity. This finding lends preliminary support for the need to decompose total measures in order to make more pointed policy 82 recommendations. The negative correlation between labor force in services and growth in industrial energy intensity is probably a reflection of the natural tendency for economies to shift from industrial to service bases. Commodity concentration is positively related to industrial energy intensity as is energy exports. The possibility that oil-exports being a component of the commodity concentration measure remains a distinct possibility as evidence by the modest correlation between energy exports and commodity concentration (.28).

Results produced from regressing industrial energy intensity for 1989 on different specifications are reported 2 in Table 16. Except for the lagged dependent variable, equations 1 through 5 fail to produce any significant findings. Not until the introduction of the resource endowment variable, energy exports, do the nature of the relationships emerge. The development effect is strong and both indicators are in the appropriate directions. Urbanization fails to exert a significant effect on industrial energy intensity as do population density and percentage of the labor force in services. The negative effect of commodity concentration is consistent with dependency\world systems theories’ logic. The effect of the energy exports variable is strong and positive as expected. The importance of this resource endowment variable is again evidenced by the gains in variance explained following its introduction (8%). Coverage problems stemming from energy consumption by sector result in a diminution of the sample size to 52 in the fully specified model, still acceptable by cross-national standards.

Bivariate correlations for energy intensity for services produces a somewhat different picture from earlier dependent variables. Table 17 shows that indicators of 83 modernity such as GNP per capita, its quadratic, urbanization are all only moderately

correlated to services energy intensity in 1989. The pattern of correlations for the

services category more closely mirrors that of the total analyses and is undoubtedly a

function of the larger percentage of total energy intensity used in this service category

compared to the industrial category. Commodity concentration is again positively related

to growth as it was for the first two dependent variables. Ecological-evolutionary theory

again receives preliminary support based on the negative correlation between population

density and growth in energy intensity. Not surprisingly, energy exports is much less

highly correlated with services energy intensity that for the intensity of the industrial

sector.

Results from the panel regression provide unequivocal support for the logic of

modernization theory. In all 6 equations estimated (see Table 18) gross national product

per capita and its quadratic are significant. In fact, the addition of other variables to the

models result in a loss of parsimony as indicated by the lowering of the variance explained (73% to 71%). Neither dependencyYworld systems nor ecological evolutionary theory contribute to explanations for growth in services energy intensity for the decade

1979 to 1989.

Correlations between agriculture energy intensity for 1989 and the independent variables are reported in Table 19. Gross national product per capita, its square, urbanization, and percentage of the labor force in services are all positive related to growth agriculture energy intensity. It was anticipated that development would reduce energy intensity given that the use of fertilizers and machines would be more pronounced 84 thereby increasing land productivity. Although firm conclusions cannot be drawn from simple correlations, the positive correlation seems to indicate otherwise. Both commodity concentration and population density are negatively correlated to agriculture energy intensity lending support to both ecological-evolutionary and dependency\world systems theories. Energy exports is weakly negatively correlated with agriculture energy intensity, probably an artifact.

Results from the panel regression show that only the lagged dependent variable and population density exert any influence on growth in agriculture energy intensity during the decade 1979 to 1989. The "poor fit" is most likely a consequence of the small amount of change over the decade in terms of the percentage of energy used in the agricultural sectors of national economies. In 1979 the average percentage of total energy consumption used in the agricultural sectors was 2.5 percent while that corresponding number for 1989 was 2.7 percent. In all six equations (see Table 20)7 neither GNP per capita, its quadratic, urbanization, nor percentage of the labor force in services significantly affect agriculture energy intensity indicating a lack of modernization findings. While commodity concentration is significant in equations 4 and 5, the finding is not as robust as that of population density and falls out following the inclusion of energy exports.

Summary of findings for Phase 3

Overall, modernization theory fare quite well at the broad sectoral level in terms of explaining energy intensity. Dependency\world systems and ecological-evolutionary theories failed to receive as much support as the level of specificity increases. In terms 85 of the three sectors, modernization findings obtain in both the industrial and service sectors and the findings are quite robust. Dependency\world systems are in evidence only

in the industrial sector as indicated by the negative coefficient of commodity concentration. Findings consistent with the central tenets of ecological-evolutionary theory only appear with regard to the agricultural sector. Preliminary conclusions at this point would seem to indicate that development theories are of utility principally at the aggregate level but loses some of its explanatory power as the level of specificity increases. Final judgement should be reserved, however, since in all 3 sectors under examination sample sized were reduced to the low fifties due to data constraints. The paucity of additional research of this type against which to compare findings means additional research should be conducted before dismissing sociological theories of development as useless at the sectoral level. The next set of dependent variables addresses this problem to some degree.

Phase 4

Phase four is entirely cross-sectional and contains four dependent variables.

Energy intensity for agriculture, industry, transportation, and residential sectors are analyzed. The findings generated from this set of analyses should in part address the issue of the utility of theories of development for sectoral analyses of energy intensity brought by the analysis in the previous category. Although cross-sectional, this set of dependent variables offers the advantages of an even greater level of specificity over the previous set of variables and a modest increase in sample sizes. 86 Table 21 contains no real surprises. Even with the expanded sample size (N=64), the modernization-related indicators (GNP, its quadratic, urbanization, and percentage of the labor force in services) continue to be moderately correlated to agriculture energy intensity for 1979. The now familiar negative correlation between commodity concentration is again evident while population density continues to be positive. Energy exports is also modestly positively correlated with energy intensity as expected.

Table 228 reports the standardized regression coefficients produced after regressing agriculture energy intensity on the independent variables. In all of the six equations estimated modernization compatible effects are in evidence. GNP and the quadratic are both significant in four of the six equations, and most importantly in the fully specified model. Neither dependencyVworld systems nor ecological-evolutionary theory effects are found. The positive effect of resource endowment on agriculture energy intensity is not surprising. One reason for the effect of labor force in services on agriculture energy intensity is the artifactual relationship between productivity of the agricultural sector and the movement of labor into the service sector. Growth in energy intensity in the agriculture implies more use of modem production methods and the displacement of labor. In turn, displaced labor from the agricultural sector has no alternative but to move to either the industrial or service sectors. Another possible reason for the positive effect of percentage of the labor force in services on agriculture energy intensity is the mixing of developed with developing countries in the sample. Again, one must entertain the possibility that this finding stems from the inclusion of LDCs with bloated unproductive service sectors in the sample. A comparison of the results for this 87 dependent variable with those for change in agriculture energy intensity from 1979 to

1989 reveals that while modernization theory obtains for the cross-section for 1979, population density was the most consistent finding for change in the 1979 to 1989 decade. The discrepancies can be attributed to 1) differing time periods, 2) different sample compositions, and 3) different operationalizations of the dependent variable.

Taken together, the findings from both sets of analyses indicate that theories of development need not be dismissed as irrelevant to energy intensity at the sectoral level.

Zero-order correlations between industrial energy intensity for 1979 and the independent variables appear in Table 23. Correlations between GNP per capita, the quadratic of GNP, urbanization, and percentage of the labor force in services with the dependent variable are all moderately strong and positive as expected. Commodity concentration is very strongly and negatively related to industrial energy intensity relative to its magnitude for other dependent variables. This provides tentative support for dependency\world systems arguments related to the failure of economies characterized by reliance on a few select commodities to develop in a balanced fashion. Population density is only weakly correlated with industrial energy intensity, a Finding not inconsistent those from previous dependent variables, Energy exports is surprisingly negatively correlated with industrial energy intensity for 1979. This is possibly due to its association with commodity concentration.

Table 24 contains the results of the OLS regression of industrial energy intensity for 1979 regressed on the independent variables. GNP per capita and the quadratic fail to obtain in any of the six different specifications indicating a lack of support for 88 modernization theory with regard to this specific dependent variable. The exclusion of the quadratic from the fully specified model failed to change the results. Neither percentage of the labor force in services nor urbanization, the other modernization related variables, appear to significantly influence industrial energy intensity for 1979. As foreshadowed by the results of the bivariate correlations, commodity concentration is consistently and negatively associated with industrial energy intensity lending support to dependency\world systems theories. The strength of this finding is illustrated by the gain in 20 percent of the variance following the inclusion of commodity concentration.

Ecological-evolutionary theory also receives support in this analysis as can be seen from the positive coefficients for population density in equations 4, 5 and 6. Despite the high correlation between energy exports and industrial energy intensity, resource endowment fails to affect industrial energy intensity after controlling for other relevant variables.

Overall these findings accord somewhat with the longitudinal analysis for growth in energy intensity for the decade spanning 1979 to 1989. The overlap between the results emanate from the consistent finding that commodity concentration reduced industrial energy intensity, in spite of differences in terms of operationalization, sample sizes, and time period differences. This provides a strong rationale against excluding theories of development in future analyses of energy intensity.

Transportation energy intensity for 1979 is the next dependent variable under consideration. Very similar patterns emerge from the bivariate correlations (see Table

25). Modernization variables are the most strongly associated with transportation energy intensity. Commodity concentration’s bivariate correlation is much weaker with 89 transportation energy intensity than with other dependent variables as in the energy

exports variable. The inclusion of a control for land area in analyzing transportation

energy intensity represents a slight departure from the uniform models applied throughout

this analysis. Inclusion of this control was deemed necessary in light of its obvious

relevance for transportation sectors of national economies. Larger countries by necessity

face greater difficulties in terms of product and raw material movement, a problem most

likely solved by large networks of roads and train lines and concomitant increases in energy use and intensity in the transportation sector. The bivariate correlation between

land area and transportation is moderate and positive as one would anticipate.

Table 26 contains the results of the analysis of transportation energy intensity.

Equations 1 and 2 and 7 provide clear support for modernization theory. As level of development increases transportation energy intensity increases, most of which is related to the building roads and railways. At high levels of development, following the completion of the major infrastructural developments energy intensity declines and more emphasis is placed on maintenance activities and efficiency upgrades. This finding lends clear support to modernization theory’s arguments of the building of infrastructure (in this case roads and railways) in pronounced at intermediate stages of development and contributes to increased energy intensity. Inspection of the r-squares shows that modernization is the principal determinant of transportation energy intensity. The amount of variance explained actually decreases by 10 percent following the inclusion of commodity concentration, population density, percentage of the labor force in services and energy exports, indicating a loss of parsimony. The control variable is significant and 90 positive as expected and makes a significant contribution to the explanatory power of the

model (see r-squares).

The final dependent variable in phase 4 is residential energy intensity for 1979.

No surprises are evident from an inspection of the correlations (see Table 27). The

strongest correlations are those between GNP, its quadratic and urbanization with the

dependent variable. Percentage of the labor force in services is also moderately positively

correlated with residential energy intensity while population density is only slightly

negatively correlated with the dependent variable. Modest correlations between energy

exports and commodity concentration and the dependent variable exist in the expected directions.

Findings from the regression analysis provide results that make intuitive sense and support previous research on energy intensity. The only modernization finding in evidence for the residential sector is that of a positive urban finding (refer to Table 28)9.

Previous research suggests that the increase in rural-to-urban migration LDCs are experiencing is likely to increase both energy demand and intensity stemming from the shift away from traditional sources of fuel and the growth in appliance usage. This suggestion appears to be borne out by the cross-national evidence in Table 28. The other significant finding produced from this analysis is the negative effect of density on residential energy intensity. In addition to being generally supportive of the ecological- evolutionary perspective, this finding represents a countervailing tendency associated with increased urbanization. The spatial concentration of people facilitates the delivery of services, including the provision of energy, electricity in particular. Therefore, while 91 urbanization provides both positive and negative effects on energy use and intensity, the effects of which are likely to be the subject of future research. The variable representing the dependency\world systems theories do not obtain with regard to residential energy intensity nor does the control for resource endowment.

Summary of Findings for Phase 4

The weight of the overall evidence from the detailed sectoral analysis of energy intensity for 1979 points to the potential contribution of sociological theories of development to the study of energy intensity. Modernization related Findings are clear in two of the four sectors (agriculture and transportation), providing support for a general

"worsening then improving" trend with respect to energy intensity. Alternatively, the general trend toward reductions in energy intensity may not stem solely from service- sector dominance but may arise from other sectors as well. Previous research neglects to entertain this possibility. The consistent urban Finding for the residential sector presents no surprises given previous research in the are, but does suggest that either 1 ) modiFications in development theory are necessary in light of this unexpected finding or

2 ) additional research is needed to that truly separates the effects of level of development from the potential beneFits of urbanization. Very convincing dependency Findings are in evidence for the industrial sector, the category in which they were most likely to be found given theoretical consideration. The logic of the dependency\world systems tradition clearly should not be dismissed in future work. Benefits accruing from high population densities were found for both the industrial and residential sectors. In the case of the residential sector, the tendency toward increases in total energy use resulting from 92 having to supply large numbers of people is in part offset by the gains in efficiency from

having these individuals in close proximity to one another. Reductions from the industrial

sector are also most likely a function of spatial proximity of businesses, warehouses and

the like. The occasional significance of controls such as energy exports and land area

point to the need for tailor made models of energy intensity at the sectoral level rather

than the mere application of very general theoretical models across levels of specificity.

Summary of Findings for Phases 1 through 4: Putting the Pieces Together.

The majority of the analysis was focused on the post-oil shock period given data

limitations on the pre-oil shock period. A comparison of the results generated from analyses of the pre-oil shock period poses a few problems when compared to results of the post-oil shock period. First, we can be fairly certain that the logic of modernization theory applies in both the pre- and post-oil shock period. Gross national product per capita and its quadratic consistently produce the theoretically anticipated effects. Increases in development are associated with increases in energy intensity with relative reductions in energy intensity occurring at very high levels of development. The one occasion in which this finding failed to emerge was in the 1974 to 1985 period. This can be clearly attributed to the inclusion of the second price disturbance in the dependent variable.

Analysis of the decade following the second oil-shock revealed that modernization findings re-emerged. Furthermore, findings from the cross-sections consistently buttress results generated from panel models.

The weight of the results regarding dependency\world systems theories is somewhat less clear, but nonetheless sufficient evidence suggests that economic 93 specialization in a few select commodities is detrimental to balance economic growth in the long run and results in reductions in energy intensity. During the pre-oil shock period commodity concentration served to bolster energy intensity, probably as a result of the cheap supply of energy and resultant negligible effect of its supply for development efforts. In the post-oil shock period, at both the aggregate and sectoral levels, the bulk of the evidence points to negative effect of commodity concentration on energy intensity.

Whether or not this occurs through increased efficiency stemming from the increased cost of energy or a decline in economic development and growth attributable to narrow specialization in a few commodities is a topic for additional research.

On the whole, predictions derived from ecological-evolutionary theory have been supported. At both the aggregate and sectoral levels, the overwhelming weight of the evidence points to reductions in energy intensity resulting from high population densities.

The pre-oil shock period from 1965 to 1973 represents the one exception. Apparently, either because of the relative cheap supply of energy or the initial increase in energy demand associated with increasing densities, the benefits accruing from population agglomeration failed to develop until the post-oil shock period. The negative effect of population density in the cross-sectional panels for total energy intensity for 1965, 1975, and 1985 tend to support the latter interpretation.

Longitudinal and cross-sectional analyses at the sectoral level are very consistent with findings at the aggregate level but point to the need for more tailor made models as the level of aggregation is decreased. Specific examples would include the urban and density effects for the residential sector while the development and land area effects 94 dominate in the transportation model. Obviously, more theoretical elaboration about the effects of development theories at the sectoral levels is needed before specific tests can be conducted.

Results Pertaining to the Determinants of Economic Growth

The first economic growth equation covers the pre-oil shock period spanning from

1965 to 1973. Zero-order correlations (see Table 29) show that level of development and the quadratic as measured by real gross domestic product per capita are only weakly correlated with the dependent variable for the pre-oil shock period, indicating that it is not likely to be a strong determinant of economic growth. Similarly, the flow of foreign investment exhibits a weak but positive correlation to economic growth for the period under investigation. In accordance with dependency arguments, gross domestic investment’s correlation to economic growth is stronger than that of foreign investment

(.34 compared to .10). Export dominance displays only a weak negative correlation to economic growth while size of the domestic market as measured by energy consumption shows only a very weak positive correlation. As expected, both energy intensity and population density are positively correlated to economic growth. Energy exports, the control variable, is only weakly related to economic growth for this initial period.

Results generated from the regression equation are contained in Table 30l°.

Equation 1 contains the modernization indicators as well as the foreign flow measure.

Although the signs of the coefficients are in the appropriate direction, none of the variables achieve significance, probably a result of underspecification. The introduction of gross domestic investment (unlogged) for the decade 1960 to 1970 produces a 95 significant positive effect indicating that local investment does indeed accelerate

economic development. Export dominance is added in equation 3 and, while negative,

fails to alter the substantative findings produced from the earlier specification.

Controlling for market size causes gross domestic investment to fall out while market

size itself fails to achieve statistical significance. The addition of the first new variable,

energy intensity for 1965, cause the effect of gross domestic investment to re-appear

while energy intensity itself is significant and positive. This finding lends support to the

thesis that the supply and manner in which energy is utilized does indeed affect the pace

of national economic growth rates. Apparently, the use of large amounts of energy

accelerates the pace of national development. Energy exports in 1970 is then added to the previous specification to ensure that the finding is an artifact or a function of resource endowment. The coefficients are presented in equation 6 . Controlling for energy exports cloud the nature of the relationships and does indeed cause the energy intensity variable to lose significance while the resource endowment variable itself is not significant. The completely specified model results following the introduction of population density in equation 7. Results produced reveal that density does accelerate the pace of economic growth as predicted by ecological-evolutionary theory. Furthermore, controlling for population density clarifies the nature of several relationships and causes the energy intensity, resource endowment and export dominance variables to become significant. The findings suggest that economic growth is facilitated by the abundance of large supplies of energy, an essential component to any development effort as well as massive uses of energy. Clearly the exclusion of both variables from prior research constitutes a major 96 oversight. The robust effect of population density indicates that initial starting conditions

(high densities and attendant complex social organization) need to be accounted for in analyses of development patterns. The final patterns are robust and become stronger following the removal of additional outliers.

The second economic growth equation spans the period from 1974 to 1985.

Bivariate correlations show that per capita RGDP and its quadratic are only weakly correlated to economic growth for the 1974 to 1985 period (see Table 31). Particularly strong positive correlations exist for both gross domestic investment from 1970 to 1980 and foreign flows from 1967 to 1987 (.35 and .59 respectively), indicating that both should promote economic growth during the period, Weak correlations are evident for both export dominance (-.07) and energy exports (.07) while population density is moderately correlated to economic growth. Market size and total energy intensity at the beginning of the period are both weakly correlated to the dependent variable.

The first equation in Table 32 shows no development effects as suggested by the bivariate correlation while gross domestic investment accelerates economic growth for the 1974-1985 period. The addition of the foreign flows variable results in a sizeable contribution to variance explained (an addition of 30 percent), but there is an unfortunate reduction in the sample size (from 95 to 64 countries). Given that foreign flows was the most highly correlated with economic growth this finding is not surprising. Export dominance fails to change the findings as shown in equation 3 as does the introduction of market size in equation 5. Contrary to expectations, energy exports exerts no influence on economic growth following its introduction in equation 5 while energy exports 97 displays and unanticipated significant negative effect on economic growth in equation 6 ,

In the fully specified equation that controls for population density (equation 7), the nature of several relationships becomes clearer. First, RGDP and its quadratic become significant and display the appropriate signs. This is indicative of an increase in economic growth as development increases with a tapering off at high levels of development. The most robust and consistent effects throughout the analysis were for those of gross domestic investment and foreign flows both of which increase national rates of economic growth. These findings are consistent across both periods under scrutiny. Contrary to the findings of previous research, market size fails to contribute to the explanation of economic growth in either period, possibly a function of greater specification. In both periods energy intensity contributes to economic growth as predicted indicating that energy and its supply are crucial to development efforts. The unexpected effect of the resource endowment control variable falls out following the inclusion of population density. Ecological-evolutionary theory receives strong support in both sets of equations indicating that histories of high rates of population density and concomitant social organization contribute to the rapid diffusion of modernity following its onset.

Overall, the replication of conventional models of economic growth has provided very strong support for claims that the supply of energy is crucial to economic development. The positive effect of energy intensity on economic growth in both periods under examination indicates that massive inputs of energy are necessary to spur development and concomitant spread effects. Thus, countries attempting to boost economic growth will find themselves in somewhat or a predicament. The use of the 98 same material that is a prerequisite for higher standards of living also simultaneously

lowers the quality of life by increasing local levels of air pollution and contributing to global warming. Once again the need for using existing resources as efficiently as possible and incorporating energy rationalization techniques appears to be the most logical course of action. The results also point to the fact that countries are not uniformly underdeveloped prior to modernization and that initial conditions need to be accounted for in models of economic growth. These preliminary findings suggest that tailor made strategies for national development that pay particular attention to rural development and ensuring adequate supplies of affordable energy are preferable to the adoption of very broad prescriptions for solving problems of slowed rates of economic growth. Table 1. Zero-order correlations between change in energy intensity from 1965 to 1973 and independent variables (N=81).

1 2 3 4 5 6 7 8

1. Change in intensity 1.0* from 1965 to 1973

2. Log of energy -0.39* 1.0* intensity, 1965

3. Log of GNP, 1965 -0.16 0.73* 1.0*

4. Sq. of GNP, 1965 -0.18* 0.72* 0.99* 1.0*

5. Urbanization, 1965 -0.22* 0.65* 0.82* 0.81* 1.0*

6. Commodity Cone., 1965 0.28* -0.51* -0.53* -0.55* -0.48* 1.0*

7. Pop. density, 1965 0.20* 0.07 0.09 0.08 0.38* -0.30* 1.0*

8. Labor Force in -0.06 0.53* 0.72* 0.71* 0.81* . -0.44* 0.50* 1.0* Services, 1965

9. Energy Exports/RGDP, 1970 0.21* 0.05 0.03 0.02 0.05 0.08 0.14 0.05 1.0*

v o VO TABLE 2 Unstandardized Regression Coefficients for the Change in Total Energy Intensity from 1965 to 1973.

1 2 3 4 5 6

Log total energy .19** .80** .82** .8 6 ** .85** .81** intensity, 1965

LogofGNP/c, 1965 .86** .91** .79** .59* .59** .50*

Square of GNP/c, 1965 *.06** -.06** -.05** -.03 -.03 - . 0 2

Percentage Urban, 1965 -.003 -.003 -.008** -.008** -.008**

Commodity Concentration, 1965 . 0 0 2 004** .004** .003**

Population Density, 1965 .0 0 1 ** .0 0 1 ** .0 0 1 **

Percentage of labor . 0 0 1 .0 0 1 force in services, 1965

Energy exports/RGDP, 1970 56.28

N 93 93 93 93 93 81 R2 .87 . 8 8 .8 8 .90 .90 .89 Adjusted R 2 .87 .87 .8 8 .89 .89 . 8 8 Saudi Arabia was identified as an outlier and excluded from all equations.

** p<..05, two-tailed test * p < , 1 0 , two-tailed test c c Table 3. Zero-order correlations between change in energy intensity from 1974 to 1985 and independent variables (N=83)

1 2 3 4 5 6 7

1. Change in intensity 1.0* from 1974 to 1985

2. Energy Intensity, 1974 -0.33* 1.0*

3. Log of GNP, 1974 -0.10 0.73* 1.0*

4. Sq. of GNP, 1974 -0.11 0.71* 0.99* 1.0*

5. Urbanization, 1975 -0.06 0.64* 0.85* 0.84* 1.0*

6. Commodity Cone., 1970 0.04 -0.49* -0.54* -0.56* -0.46* 1.0*

7. Pop. Density, 1965 -0.23* 0.17 0.15 0.14 0.35* -0.29* 1.0*

8. Labor force in -0.13 0.59* 0.79* 0.79* 0.86* -0.44* 0.44' Services, 1975

9. Energy Exports/RGDP, 1975 0.26* 0.13 0.15 0.14 0.10 0.22* 0.03 TABLE 4 Unstandardized Regression Coefficients for the Change in Total Energy Intensity from 1974 to 1985.

1 2 3 4 5 6

Log total energy .69** .69** .6 8 ** .6 6 ** .6 8 ** .6 8 ** intensity, 1974

Log of GNP/c, 1974 .40 .36 .47 .50 .50 .49*

Square of GNP/c, 1974 - . 0 2 - . 0 2 -.03 -.04* -.04* -.04*

Percentage Urban, 1975 .0 0 1 .0 0 1 .004 .004 .005*

Commodity Concentration, 1970 - . 0 0 1 -.003* -.003* -.006**

Population Density, 1965 -.0 0 1 ** -.0 0 1 ** -.0 0 1 **

Percentage of labor .0 0 1 . 0 0 1 force in services, 1975

Energy exports/RGDP, 1975 169.14**

N 98 98 98 98 98 82 Rz .81 .81 .81 .83 .83 . 8 6 Adjusted Rz .80 .80 .80 .81 .81 .85 Panama, Gambia, and Nigeria were identified as outliers and excluded from all equations.

** p<..05, two-tailed test * P<-10, two-tailed test Table 5. Zero-Order correlations between total energy intensity for 1965 and independent variables (N -95)

1 2 3 4

1. Log of total energy 1.0* Intensity, 1965

2. Log of GUP, 1965 0.75* 1. 0*

3. Sq. of GNP, 1965 0.74* 0.99* 1.0*

4. Urbanization, 1965 0.71* 0.84* 0.83* 1.0*

5. Coamodity Cone., 1965 -0.55* -0.55* -0.58* -0.54* 1.0*

6. Population Density, 1965 0.09 0.10 0.09 0.36* 0.30* 1.0*

7. Labor Force in Services 0.63* 0.74* 0.73* 0.82* 0.47* 0.48* 1.0* TABLE 6 Unstandardized Regression Coefficients for TotalEnergy Intensity for 1965.

1 2 3 4 5

Log of GNP/c, 1965 1.32** 1.07* 1.45** 1.60** 1.60**

Square of GNP/c, 1965 -.05 -.05 -.09* -.1 1 ** -.04*

Percentage Urban, 1965 .0 1 ** .008* .0 2 ** .0 0 1 **

Commodity Concentration, 1965 -.006** -.008** -.009**

Population Density, 1965 -.0 0 1 ** -. 0 0 1 **

Percentage of labor .0 1 * force in services, 1965

N 95 95 95 95 98 R2 .57 .59 .62 .64 .83 Adjusted R 2 .56 .58 .60 .62 .81 Zimbabwe was identified as an outlier and excluded from all quations.

** p<.-05, two-tailed test * P

1 2 3 4 5 6 7 8

1. Log of total energy 1.0* intensity, 1975

2. Log of GNP, 1975 0.75* 1.0*

3. Sq. of GNP, 1975 0.74* 0.99* 1.0*

4. Urbanization, 1975 0.71* 0.84* 0.83* 1.0*

5. Commodity Cone. 1970 -0.65* -0.57* -0.59* -0.49* 1.0*

6. population density, 1975 0.13 0.14 0.13 0.34* -0.28* 1.0*

7. Labor force 0.64* 0.78* 0.77* 0.86* -0.46* 0.43* 1 . 0* in Services, 1975

8. Energy exports/RGDP, 1975 -0.07 0.17 0.16 0.06 0.28* 0.02 -0.03 1.0*

O U l TABLE 8 Unstandardized Regression Coefficients for Total Energy Intensity for 1975.

1 2 3 4 5 6

Log of GNP/c, 1965 1.52** 1.41** 1.72** 1.75** 1.63** 1 . 1 1 **

Square of GNP/c, 1965 -.07** -.07** -.1 0 ** -.1 1 ** -.1 0 ** -.07**

Percentage Urban, 1965 .003 .003 .006 .0 0 2 ** .007*

Commodity Concentration, 1965 -.006** -.007** -.007** -.009**

Population Density, 1965 - . 0 0 1 -.0 0 1 ** -.0 0 1 *

Percentage of labor .009* . 0 0 2 force in services, 1965

Energy Exports/RGDP, 1975 -29.39

N 104 104 1 0 0 1 0 0 1 0 0 83 R2 .64 .64 .67 .67 .69 .6 8 Adjusted R 2 .63 .63 .65 . 6 6 .67 . 6 6 Jamaica, Liberia, China, Zimbabwe, and Nepal were identified as outliers and excluded from all equations.

** p<_.05, two-tailed test * p < J 0 , two-tailed test

a\o Table 9. Zero-order correlations between total energy intensity for 1985 and independent variables (N=94)

1

1. Log of total energy 1. 0* intensity, 1985

2. Log of GNP, 1985 0. 68* 1. 0*

3. Sq. of GNP, 1985 0.67* 0.99* 1. 0*

4. Urbanization, 1985 0.65* 0.81* 0.80* 1. 0*

5. Commodity Cone., 1980 -0.39* -0.51* - 0. 52* -0.46* 1. 0*

6. Population density, 1985 0.04 0.20 0.19 0.32* -0.26* 1. 0*

7. Labor force 0.52* 0.79* 0,78* 0.79* *0.46* 0.36* 1. 0* in services, 1985

8. Energy exports/RGDP, 1985 0.25* 0 . 22* 0. 21* 0.11 0.27* 0.13 - 0.01 1. 0*

o TABLE 10 Unstandardized Regression Coefficients for Total Energy Intensity for 1985.

1 2 3 4 5 6

Log of GNP/c, 1965 1.51** 1.34** 1.27** 1.23** 1.28** .71

Square of GNP/c, 1965 -.07** -.07** -.07** -.07** -.07** -.04

Percentage Urban, 1965 .006 .008* . 0 1 ** .0 1 ** .0 1 **

Commodity Concentration, 1965 - . 0 0 1 - . 0 0 2 - . 0 0 2 -.004**

Population Density, 1965 -.0 0 1 ** -.0 0 1 * -.0 0 1 **

Percentage of labor . 0 0 2 .0 0 1 force in services, 1965

Energy Exports/RGDP, 1975 276.28**

N 116 116 103 103 103 93 R2 .58 .59 .54 .56 .56 .56 Adjusted R 2 .57 .58 .52 .54 .53 .52 Zimbabwe was identified as an outlier and excluded from all equations.

** p<. .05, two-tailed test * p<.. 1 0 , two-tailed test

o 00 Table 11. Zero-order correlations between change in energy intensity from 1979 to 1989 and independent variables (N -83)

1 2 3 4 5 6 7 8 9

1. Change in intensity 1.0* from 1979 to 19B9

2. Log of Total -0.17 1.0* Intensity, 1979

3. Log of GNP, 1979 -0.10 0.67* 1.0*

4. Sq. of GNP, 1979 -0.12 0.66* 0.99* 1.0*

5. Urbanization, 1979 -0.13 0.62* 0.82* 0.81* 1.0*

6. Commodity Cone., 1970 0.46* -0.48* -0.54* -0.55* -0.48* 1.0*

7. Pop. Density, 1979 -0.19 0.08 0.16 0.15 0.33* -0.27* 1.0*

8. Labor Force in -0.14 0.57* 0.78* 0.78* 0.85* -0.51* 0.40* 1.0* Services, 1979

9. Energy Exports, 1979 0.47* 0.18 0.24* 0.24* 0.11 0.28* 0.06 0.01 1.0*

o VO TABLE 12 Unstandardized Regression Coefficients for the Change in Total Energy Intensity from 1979 to 1989.

1 2 3 4 5 6

Log total energy .90** .91** .95** .95** .94** .91** intensity, 1979

Log of GNP/c, 1979 .44* .47* .45** .45** .44* .58**

Square of GNP/c, 1979 -.03* -.03* -.03* -.03* -.03* -.04**

Percentage Urban, 1979 . 0 0 2 .0 0 1 - . 0 0 1 - . 0 0 1 - . 0 0 0 1

Commodity Concentration, 1980 .004** -.004** -.004** - . 0 0 1

Population Density, 1979 - . 0 0 0 1 - . 0 0 0 1 -.0 0 0 1 *

Percentage of labor . 0 0 1 .004* force in services, 1979

Energy exports/RGDP, 1979 170.24**

N 109 109 99 99 99 83 R2 .91 .91 .94 .94 .94 .92 Adjusted R 2 .91 .91 .93 .93 .93 .91 Jamaica was identified as an outlier and excluded from all equations.

** p<..05, two-tailed test * p < . 1 0 , two-tailed test

o Table 13. Zero-order correlations between total energy intensity for 1979 and independent variables (N=83)

1 2 3 4 5 6 7 8

1. Log of Total energy 1.0* Intensity, 1979

2. Log of GNP, 1979 0.69* 1.0*

3. Sq. of GNP, 1979 0.69* 0.99* 1. 0*

4. Urbanization, 1979 0.64* 0.82* 0.81* 1.0*

5. Cocmodity Cone., 1970 -0.49* -0.54* -0.55* -0.48* 1.0*

6. Population density, 1979 0.09 0.16 0.15 0.33* -0.27* 1.0*

7. Labor force in 0.57* 0.79* 0.7B* 0.86* -0.51* 0.41* 1. 0* services, 1979

8. Energy exports/RH)P, 1979 0.19 0.24* 0.24* 0.11 0.28* 0.06 0.01068 1.0* TABLE 14 Unstandardized Regression Coefficients for Total Energy Intensity for 1979.

1 2 3 4 5 6

Log of GNP/c, 1979 1.83** 1.70** 1.26* 1.27* 1.18* .39

Square of GNP/c, 1979 -.09** -.09** -.06 -.07 -.06 - . 0 2

Percentage Urban, 1979 .007 .008 -.009* -.007 -.008*

Commodity Concentration, 1980 - . 0 0 0 1 - . 0 0 0 1 -.0007 -.007**

Population Density, 1979 - . 0 0 0 1 - . 0 0 0 1 -.1 0 *

Percentage of labor .006 .0 0 1 force in services, 1979

Energy expoits/RGDP, 1979 163.28

N 1 1 2 1 1 2 99 99 99 83 R2 .49 .50 .44 .44 .45 .55 Adjusted R 2 .48 .48 .42 .42 .42 .50 Jamaica was identified as an outlier and excluded from all equations.

** p<.05. two-tailed test * p<_. 1 0 , two-tailed test Table 15. Zero-order correlations between change in industry energy intensity from 1979 to 1989 and independent variables (N=52)

1 2 3 4 5 6 7 8

1. Change in Industry 1.0* Intensity, 1979-1989

2. Log of Industry -0.31* 1.0* Energy Intensity, 1979

3. Log of GNP, 1979 0.10 0.30* 1.0*

4. Sq. of GNP, 1979 0.08 0.31* 0.99* 1.0*

5. Urbanization, 1979 0.05 0.2B* 0.80* 0.79* 1.0*

6. Comnodity, Cone., 1970 0.22 -0.43* -0.47* -0.48* -0.43* 1.0*

7. Pop. Density, 1979 -0.03 0.05 0.20 0.20 0.45* -0.32* 1.0*

8. Labor Force -0.10 0.29* 0.71* 0.71* 0.86* -0.46* 0.57* 1.0* in services, 1979

9. Energy Exports/RGDP, 1979 0.65* -0.13 0.3S* 0.34* 0.15 0.2B* 0.03 0.01 TABLE 16 Unstandardized Regression Coefficients for the Change in Industrial Energy Intensity from 1979 to 1989.

1 2 3 4 5 6

Log industrial energy .84** .84** .87** . 8 8 ** .89** . 8 6 ** intensity, 1979

Log of GNP/c, 1979 .62 .69 1.07 1.07 .92 1.14**

Square of GNP/c, 1979 -.04 -.04 -.06 -.06 -.05 -.09**

Percentage Urban, 1979 -.001 -.001 -.002 -.004 -.004

Commodity Concentration, 1970 . 0 0 2 . 0 0 2 - . 0 0 2 -.004**

Population Density, 1979 .0 0 0 1 .0001 -.0001

Percentage of labor -.0 1 * .0 0 1 force in services, 1979

Energy exports/RGDP, 1979 345.78**

N 54 54 52 53 53 52 R2 .78 .78 .79 .80 .81 . 8 8 Adjusted R 2 .77 .76 .77 .77 .78 .85 Panama was identified as an outlier and excluded from all equations.

** p<..05, two-tailed test * P <.■ 10. two-tailed test Table 17. Zero-order correlations between change in services energy intensity from 1979 to 1989 and independent variables (N=53).

1 2 3 4 5 6 7

1. Change in services 1.0* Intensity, 1979-1989

2. Log of Services -0.29* 1.0* Energy Intensity, 1979

3. Log of GNP, 1979 -0.09 0.46* 1.0*

4. Sq. of GNP, 1979 -0.12 0.45* 0.99* 1.0*

S. Urbanization, 1979 -0.11 0.35 0,80* 0.79* 1.0*

6. Comodity, Cone., 1970 0.35* -0.19 -0,46* -0.48* -0.42* 1.0*

7. Pop. Density, 1979 -0.22 0.01 0.20 0.20 0.45* -0.32* 1.0*

8. Labor force in -0.15 0.27* 0.71* 0.71* 0.85* -0.44* 0.57* Services, 1979

9. Energy Exports/RGDP, 1979 0.08 0.40* 0.35* 0.34* 0.15 0.28* 0.03 TABLE 18 Unstandardized Regression Coefficients for the Change in Services Energy Intensity from 1979 to 1989.

1 2 3 4 5 6

Log services energy .77** .77** .77** .76** .76** .71** services, 1979

Log of GNP/c, 1979 1.62** 1.77** 1.48** 1.48** j 4 9 ** 1.55**

Square of GNP/c, 1979 -.1 1 ** -.1 1 ** -.09** -.1 0 ** -.1 0 ** -. 1 0 **

Percentage Urban, 1979 -.003 -.003 - . 0 0 0 1 - . 0 0 0 1 - . 0 0 0 1

Commodity Concentration, 1970 .003* .003 . 0 0 2 .0 0 0 1

Population Density, 1979 -.0001 -.0001 - . 0 0 0 1

Percentage of labor .0 0 1 .003 force in services, 1979

Energy exports/RGDP, 1979 77.43

N 54 54 54 54 54 53 R1 .73 .73 . 6 8 .69 .69 .71 Adjusted R 2 .71 .71 .65 .65 .65 .65 The removal of outliers failed to substantatively alter the results.

** p_< .05, two-tailed test * p<_. 1 0 , two-tailed test ~ o Table 19. Zero-order correlations between growth in agriculture energy intensity from 1979 to 1989 (N=52)

1 2 3 4 5 6 7 8

1. Change in Agriculture 1.0* Intensity, 1979-1989

2. Log of Agriculture *0.31* 1.0* Energy Intensity, 1979

3. Log of GNP, 1979 0.22 0.27* 1.0*

4. Sq. of GNP, 1979 0.21 0.28* 0.99* 1.0*

5. Urbanization, 1979 0.19 0.12 0.80* 0.79* 1.0*

6. Cocrmodjty, Cone., 1970 -0.18 -0.19 -0.4B* -0.50* -0.43* 1.0*

7. Pop. Density, 1979 -0.05 -0.28* 0.21 0.20 0.45* -0.32* 1.0*

8. Labor force in 0.22 -0.05 0.71* 0.71* 0.85* -0.46* 0.57* 1.0* Services, 1979

9. Energy Exports/ROGP, 1979 -0.04 0.07 0.35* 0.34* 0.15 0.27* 0.03 0.01 TABLE 20 Unstandardized Regression Coefficients for the Change in Agriculture Energy Intensity from 1979 to 1989.

I 2 3 4 5 6

Log agriculture energy .75** .75** .75** .67** .68** .67** intensity, 1979

Log of GNP/c, 1979 -.15 0.02 1.23 1.27 1.35 1.32

Square of GNP/c, 1979 .03 .03 -.06 -.07 -.08 -.08

Percentage Urban, 1979 -.004 -.006 .01 .005 .006

Commodity Concentration, 1970 -.007 -.01 -.01* -.01

Population Density, 1979 -.0006 -.0006** -.0006**

Percentage of labor .01 .009 force in services, 1979

Energy exports/RGDP, 1979 5.67

N 53 54 53 53 53 52 R7 .70 .70 .71 .74 .75 .73 Adjusted Rz .68 .68 .68 .71 .71 .68 South Korea was identified as an outlier and excluded from all equations.

** p<..05, two-tailed test * P<.-10, two-tailed test

00 Table 21. Zero-Grder correlations between agriculture energy intensity for 1979 and independent variables (N=64)

1 2 3 4 5 & 8

1. Log of agriculture 1.0* energy intensity, 1979

2. Log of GNP, 1979 0.45* 1.0*

3. Sq. of GNP, 1979 0.43* 0.99* 1.0*

4. Urbanization, 1979 0.45* 0.83* 0.82* 1.0*

5. Coenodity Cone., 1979 -0.22 -0.50* -0.52* -0.40* 1.0*

6. Population Density, 1979 0.26* 0.14 0.14 0.34* -0.28* 1.0*

7. Labor force in 0.49* 0.76* 0.75* 0.86* -0.38* 0.41* services, 1979

8. Energy exports/RGDP, 1979 0.19 0.24 0.23 0.08 0.33* 0.04 1. 0* TABLE 22 Unstandardized Regression Coefficients for Agriculture Energy Intensity for 1979.

1 2 3 4 5 6

Log of GNP/c, 1979 3.50** 3.15** 3.16* 3.00** 3.07* 3.12*

Square of GNP/c, 1979 -.20** -.18* -.19* -.17 -.18 -.21*

Percentage Urban, 1979 .01 .01 .005 .007 .003

Commodity Concentration, 1970 -.003 -.003 -.001 -.01

Population Density, 1979 .0003 .0002 -.0001

Percentage of labor .02 .04 force in services, 1979

Energy exports/RGDP, 1979 441.96

N 67 67 64 64 64 64 R2 .31 .32 .25 .28 .30 .33 Adjusted R2 .29 .29 .20 .21 .22 .25 Sri lanka and Cameroon were identified as outliers and excluded from all equations.

** P

1 2 3 4 7 8

1. Log of industry 1 . 0* energy intensity, 1979

2. Log of GNP, 1979 0.37* 1.0*

3. Sq. of GNP, 1979 0.38* 0.99* 1. 0*

4. Urbanization, 1979 0.34* 0.83* 0.82* 1.0*

5. Cormodity, Cone., 1970 -0.62* -0.51* -0.52* -0.42* 1. 0*

6. Population density, 1979 0.04 0.14 0.13 0.34* -0.28* 1.0*

7. Labor force in 0.36* 0.75* 0.75* 0.86* -0.37* 0.41* 1. 0 * services, 1979

8. Energy exports/RGDP 1979 -0.34* 0.24* 0.23 0.09 0.33* 0.03 -0.03 1.0* TABLE 24 Unstandardized Regression Coefficients for Industrial Energy Intensity for 1979.

1 2 3 4 5 6

Log of GNP/c, 1979 -.90 -1.04 .17 .26 .39 .38

Square of GNP/c, 1979 .08 .08 -.01 -.03 -.04 -.03

Percentage Urban, 1979 .005 .004 .009 .001 .0005

Commodity Concentration, 1970 -.02** -.02** -.02** -.02**

Population Density, 1979 .0002* .0001** -.0002*

Percentage of labor .02* .01 force in services, 1979

Energy exports/RGDP, 1979 -81.36

N 67 67 65 64 65 65 R2 .20 .21 .40 .43 .47 .47 Adjusted R2 .18 .17 .36 .38 .41 .41 Zimbabwe was identified as an outlier and excluded from all equations.

** p<. .05, two-tailed test * p<_.10, two-tailed test Table 25. Zero order correlations between agriculture energy intensity and independent variables (N=65)

1 2 3 4 5 6 7 8

1. Transportation 1.0* Energy Intensity, 1979

2. Log of GNP, 1979 0.44* 1.0*

3. Sq. of GNP, 1979 0.42* 0.99* 1.0*

4. Urbanization, 1979 0.46* 0.85* 0.84* 1.0*

5. Cannodity, Cone., 1979 -0.19 -0.53* -0.55* -0.43* 1.0*

6. Population density, 1979 0.07 0.14 0.13 0.33* -0.28* 1.0*

7. Labor Force in 0.3B* 0.78* 0.77* 0.86* -0.37* 0,41* 1.0* services, 1979

8. Energy exports/RGDP, 1979 0.13 0.24 0.23 0.15 0.27* 0.06 0.06 1.0*

9. Land Area, 1980 0.29* 0.06 0.08 0.05 -0.09 -0.13 0.03 -0.02

to TABLE 26 Unstandardized Regression Coefficients for Transportation Energy Intensity for 1979.

1 2 3 4 5 6

Log of GNP/c, 1979 1.58** 1.44** .61 .62 .62 1.07*

Square of GNP/c, 1979 _ 09** -.08** -.04 -.04 -.04 -.07*

Percentage Urban, 1979 .004 .005 .007 .006 .0006

Commodity Concentration, 1970 .0006 .0002 -.0003 -.001

Population Density, 1979 -.0001 .0001 -.0001

Percentage of labor .0006 .0006 force in services, 1979

Energy exports/RGDP, 1979 28.10 41.03

Land Area, 1980 .00001*

N 66 66 63 63 63 62 R2 .29 .30 .20 .21 .21 .34 Adjusted R2 .27 .26 .15 .14 .11 .24 The removal of outliers failed to substantatively alter the results.

** p<..05, two-tailed test * p <.. 10, two-tailed test Table 27. Zero-order correlations between residential energy intensity for 1979 and independent variables (N=57).

1 2 3 4 5 6 7 8

1. Log of residential 1.0* energy intensity, 1979

2. Log of GNP, 1979 0.50* 1,0*

3. Sq. of GNP, 1979 0.50* 0.99* 1.0*

4. Urbanization, 1979 0.51* 0.83* 0.82* 1.0*

5. Canmdity Cone., 1979 -0.25 -0.57* -0.58* -0.42* 1.0*

6. Pop. Density, 1979 -0.03 0.14 0.13 0.35* -0.29* 1.0*

7. Labor force 0.38* 0.76* 0.76* 0.85* -0.40* 0.42* 1.0* in services, 1979

8. Energy exports/RGDP, 1979 0.22 0.25 0.24* 0.17 0.25 0.05 0.06 1.0*

to TABLE 28 Unstandardized Regression Coefficients for Residential Energy Intensity for 1979.

1 2 3 4 5 6

Log of GNP/c, 1979 -.28 -.62 .33 .41 .39 -.42

Square of GNP/c, 1979 .04 .05 -.01 -.02 -.02 -.03

Percentage Urban, 1979 .01 .01 .02** .02** .02**

Commodity Concentration, 1970 .0006 .001 -.001 -.005

Population Density, 1979 -.0002 -.0001 -.002*

Percentage of labor .006 -.0007 force in services, 1979

Energy exports/RGDP, 1979 196.24

N 60 60 57 57 57 56 R1 .23 .26 .28 .32 .32 .35 Adjusted R2 .20 .22 .23 .25 .24 .26 Indonesia was identified as an outlier and excluded from all equations.

** P<.-05, two-tailed test * p<_. 10, two-tailed test

C\t o Table 29, Zero-order correlations between economic growth from 1965 to 1973 and independent variables (N=71)

1 2 3 4 5 6 7 8 9 10

1. Economic Growth 1.0* from 1965-1974

2. Log of ROOP, 1965 0.11 1.0*

3. Sq. of RGOP, 1965 0.11 0.99* 1.0*

4. Foreign Flows 0.10 0.02 0.02 1.0* from 1967-1973

5. Gross domestic 0.34* -0.14 -0.15 -0.06 1.0* investment, 1960*1970

6. Export dominance -0.03 0.10 0.09 -0.03 -0.04 1.0*

7. Market size, 1965 0.01 0.33* 0.35* -0.01 •0.06 -0.21 1.0*

8. Energy intensity, 1965 0.21 0.69* 0.69* 0.13 -0.09 0.20 0.31* 1.0*

9. Energy exports/RGDP, 1970 0.07 0.16 0.16 -0.05 -0.23* 0.19 -0.06 0.07 1.0*

10. Population density, 1965 0.24* 0.12 0.11 -0.01 0.02 0.40* -0,01 0.03 -D.05 1.0*

-oto TABLE 30 Unstandardized Regression Coefficients for Economic Growth from 1965 to 1973.

1 2 3 4 5 6 7

Log of GNP/c, 1965 7.53 2.02 2.19 1.82 .88 1.68 .89

Square of GNP/c, 1965 -.44 -.09 -.10 -.07 -.06 -.11 -.07

Foreign Flows, 1967-1973 .00001 .000001 .000001 .000001 .00001 .000001 .000001

Gross Domestic .26** .26** .26** .23** .22** .22** Investment, 1960-1970

Export Dominance -.00001 -.0001 -.0002 -.0001 -.00005*

Market Size, 1965 -.000001 -.000001 -.000001 -.000001

Energy Intensity, 1965 1.18** .92 1.19**

Energy Exports/RGDP, 1970 35.11 202.56

Population Density, 1965 .0002**

N 91 SI 81 80 80 71 71 R2 .09 .23 .23 .23 .30 .20 .28 Adjusted R2 .06 .19 .18 .17 .23 .09 .17 India and Singapore were identified as outliers and excluded from all equations.

** p<..05, two-tailed test * p<_. 10, two-tailed test to Table 31. Zero-order correlations between economic growth from 1974 to 1985 and independent variables (N=53)

1 2 3 4 5 6 7 8 9

1. Economic growth 1.0* from 1974-1935

2. Log of (trap, 1974 0.05 1.0*

3. Sq. of RGOP, 1974 0.05 0.99 1.0*

4. Gross domestic 0.35* 0.38* 0.40* 1.0* investment, 1970-19B0

5. Foreign flows, 1967-1978 0.59* 0.05 0.05 0.17 1.0*

6. Export dominance -0.07 0.30* 0.31* 0.15 0.01 1.0*

7. Market size, 1974 0.20 0.27* 0.28* 0.14 0.14 -0.23* 1.0*

8. Energy intensity, 1974 0.12 0.46* 0.45* -0.16 0.20 0.43* 0.20 1.0*

9. Energy exports/RGDP, 1975 0.07 0.04 0.05 0.40* 0.30* 0.05 0.04 -0.12 1.0*

10. Population density, 1975 0.46* 0.29* 0.30* 0.07 0.29* 0.51* -0.01 0.25 -0.04 TABLE 32 Unstandardized Regression Coefficients forEconomic Growthfrom 1974 to 1985.

1 2 3 4 5 6 7

Log of GNP/c, 1974 -1.41 10.14 9.47 10.84* 8.33 8.67 11.76**

Square of GNP/c, 1974 .10 -.70* -.65 -.7* -.62 -.65 -.90**

Foreign Flows, 1970-1980 .11 .13** .13** .13** .15** .18** .23**

Gross Domestic .04** .04** .04** .04** .05** .02** Investment, 1967-1978

Export Dominance -.0001 -.0001 -.0002 -.0002 -.00009

Market Size, 1974 .00001 .000001 .000001 .000001

Energy Intensity, 1974 .86 .82 1.53**

Energy Exports/RGDP, 1975 -.04** -.02

Population Density, 1975 .002**

N 95 64 63 63 63 53 52 R2 .12 .42 .42 .45 .47 .54 .76 Adjusted R2 .09 .38 .37 .39 .41 .45 .71 The removal of outliers failedto substantatively alter the results.

** p<..05, two-tailed test * p<..10, two-tailed test U I

J .5 *

1 .0 ♦

1.5 ♦

PERIOD1

1.0 ♦

0.5 * AB

A A A AA AA A A A AA A A A 0.0 ♦ A A ABA A A A A AA A B A A A A A B A

-0.5 ♦ A A

'j! s ” i!o" 4.5 5.0 S .5 6.0 6.5 7.0 7.5 0.0 0.5

LGNP65

Figure 1. Plot of per capita GNP for 1965 and growth in energy intensity from 1965 to 1973. 04 I

PERIQD2 |

1.50 +

1.35 !

1.00 +

0.7 5 + A A A A A

A AA A A 0 .5 0 A A A A AAA AAA A A A A A A 0 .3 5 ♦ A A A A A A A A AAA A A AA A 0.00 * a a

- 0.35 ♦

A A . 0 .5 0 ♦

- 0 .7 5 ♦ A A

- 1.00 + I

4.0 4.5 5.0 5.5 6.0 6 .5 7.0 7,5 S.O 8.5 9.0

LCNP74

Figure 2. Plot of per capita GNP for 1974 and growth in energy intensity from 1974 to 1985. w IO I

PERIOD! | 1.2S t

1 .00 +

0 . 7 S *

0 , 5 0 +

A A A A A A A A A A A AA A AA

0,00 A A A A AA A A A A B A AA A A A A A A A A A AA A A A A A B A A A A A A A A AA A -0.25 «■ A A

•0.50 *

- 0 . 7 5 ♦ A A. 5 5.0 5.5 6.0 6.5 7.0 7.5 a.o S.5 9.0 9.5 10.0 10.5 LGNP79

Figure 3. Plot of per capita GNP for 1979 and growth in energy intensity from 1979 to 1989. CHAPTER VI

IMPLICATIONS AND FUTURE RESEARCH AGENDA

The principal aim of this research project was to assess the utility of sociological theories of development in aiding in the identification of the structural determinants of energy intensity at the aggregate and sectoral levels. The second, equally important aspect involved ascertaining the extent to which neglect of issues surrounding the supply and use of energy constitutes a deficiency in both the theoretical and empirical terms for research on economic growth and development studies as a whole. Overall, as indicated in the previous chapter, modernization, dependency\world systems, and ecological- evolutionary theories all make significant contributions in explaining the efficiency with which energy is used in both the pre- and post-oil shock periods and therefore suggest broad parameters within which energy rationalization programs can be implemented.

Implications of the findings can be extended beyond the immediate policy relevant variables to include issues such as global warming, basic needs provision, nuclear non­ proliferation, as well as sociological theory and research.

The Immediate Relevance of the Findings

Earlier, in chapter 2 ,1 argued that research on energy intensity\efficiency to date has been largely atheoretical and conducted principally at the industrial and regional levels leaving a void at the aggregate cross-national level. It was suggested that, while of enormous utility, policy-driven research at those levels can be augmented by a more

134 135 complete understanding of the broader structural parameters or contexts in which efficiency adjustments such as retrofitting and rationalization programs are to be made.

The research conducted in this analysis represents a start in filling that void.

Let us begin with the findings that are supportive of modernization theory and its implications for future energy conservation. The bulk of the evidence across the 14 dependent variables and differing time periods provides fairly clear evidence that energy intensity increases as development proceeds with reductions occurring at higher levels of development. Modernization theory and previous empirical research agree in this respect by attributing the growth in energy intensity during the intermediate stages to development to fundamental structural changes rather than to differing efficiencies per se across countries at similar levels of development. More specifically, modernization theory suggests that countries at intermediate stages of development require and use more energy intensive products compared to countries at higher levels of development.

Concrete, steel, iron, paper and clay are a but few materials essential to the construction of basic infrastructure, activities that characterize countries at intermediate levels of development.

The most obvious policy implications of this observation are, at least in some measure, already being implemented. The World Bank and other uni- and multilateral lending agencies should incorporate concerns for energy issues in their lending policies and foster energy rationalization. As discussed in previous chapters, since most developing countries are in the planning and initial stages of making infrastructural developments, the adoption of energy conservation programs and long range planning 136

that specifically incorporates concerns of energy efficiency will have benefits beyond

those of cost-efficiency in the long run. Among the global benefits are reductions in

greenhouse gas emissions and resultant slowing of the anticipated pace of global

warming, the slowed pace of depletion of non-renewable sources of energy and resultant

preservation of natural habitats, increased time for the development of safe non-carbon

based sources of energy, and reduced international tension emanating from the

accelerated use of nuclear reactors by developing countries. Since most of the money and

equipment for development projects come from developed countries, these countries are

in the best positions to ensure that energy rationalization policies are implemented from

the onset. The tendency for capital-deprived developing countries to discount the long

range benefits of energy efficiency and concerns for the environment while minimizing short term costs is great. Consequently, the burden for ensuring that concerns for energy issues are incorporated in development projects falls on donor countries. Japan therefore becomes the country in the best position to facilitate this endeavor, since in recent years

Japan has become the single largest supplier of aid to developing countries.

The second general observation derived from modernization theory is that yet another "worsening then improving" scenario can be expected as far as energy intensity is concerned, but also that this tendency is dependent on the price of energy. As with income distributions, population growth, and fertility and mortality transitions, it appears that the intermediate stages of development pose serious threats to the environment stemming from increased energy intensity. The "solution," once again, points to the deliberate incorporation of energy conservation policies as these countries embark on 137 their development paths. The coincidence of the worsening then improving scenarios along several dimensions can be viewed ironically as fortuitous rather than simply the compounding of problems since it affords these countries the opportunities to develop holistic approaches to sustainable development rather than using piecemeal short-term development strategies. Additionally, the results point to the advantages of accelerating the pace of development of LDCs in attempts to reduce strains on the world’s supplies of energy. Such a strategy would probably be more appropriate for all developing counties that already have advanced levels of social organization and "institutional inheritances". The other modernization findings of somewhat inconsistent findings of positive effects of urbanization and percentage of the labor force in services are not conducive to drawing specific conclusions given relative lack of previous empirical support and inconsistency of findings. Clearly, additional cross-national research that explicitly attempts to sort out the effects of urbanization and percentage of the labor force in services from the reductions in energy intensity at high levels of development is necessary, a subject beyond the scope of this exploratory project.

A comparison of the findings generated from the analyses of the structural determinants of energy intensity and the determinants of the economic growth panels suggest that the oil shock may in fact be responsible for the divergence in findings across the periods. Comparisons of the determinants of total energy intensity for the periods

1965 to 1973, 1974 to 1985, and 1979 to 1989 (refer to tables 2, 4 and 12) show that in the pre-oil shock period both commodity concentration and population density increased energy intensities while in the post-oil shock periods they reduced energy intensities. The 138

findings concerning the second period are supportive of the development theories these

variables are thought to represent while they appear to contradict the dependencyVworld systems and ecological-evolutionary theories for the earlier period. Also, inspections of the patterns for GNP and its quadratic from Tables 2, 4 and 12 show that the modernization findings are more robust and consistent for the 1965 to 1973 and 1979 to

1989 periods when compared to the 1974 to 1985 period. Comparisons of the pre and

"post" oil-shock periods for the determinants of economic growth rates also shows that modernization compatible effects obtain for the 1974 to 1985 period rather than the pre­ oil shock period.

Although we cannot be positive, these changes in coefficients and variations in patterns may be attributable to the oil crises of the 1970s. The combined effects of the more consistent results for modernization theory for the latter energy intensity periods and economic growth panels imply that in the pre-oil shock period (1965 to 1973) the cost of energy was negligible. In essence, only with the increase in prices did the differing "efficiencies" with which nations at different levels of development begin to manifest themselves in the form of the curvilinear pattern as predicted by modernization theory. This interpretation would appear to accord with the apparently inconsistent effects found for dependency\world systems theories and ecological-evolutionary theory as well.

In the case of commodity concentration, the positive effect on energy intensity in the earlier period in all probability reflects the fact that in the 1960s, prior to the energy crisis, most countries tended to experience fairly high rates of economic growth from a booming world economy. Following the oil shocks, however, with the developed world 139

instituting austerity and protectionist policies including protective tariffs, nations that

specialized in the production of a few selected commodities were unable to continue to experience the same patterns of growth as in the 1960s. The explanation for the positive effect of population density in the early period compared to the negative effect in the latter periods is also straightforward. Prior to rises in energy costs, dense nations and those with high population growth rates had high rates of energy consumption that was a direct function of their larger population bases and the availability of cheap supplies of energy. Following the oil crisis, however, these are the same nations that were able to adjust most rapidly to the rising costs of energy due to their greater abilities to diffuse innovative energy conserving techniques and practices. In effect, their technological and developmental histories had provided them with increased readiness and flexibility stemming from greater social and institutional organization. The oil crisis apparently served the general function of "reminding" nations that energy was a factor of production that was no longer negligible. This is evidenced by the shifting inflection points for the three periods. As a reminder, during the pre-oil shock period the point at which energy intensities began to decline was $1300 compared to $460 for the post-oil shock period and a shifting back to the right ($1420) in the post-oil crises decade. These findings seem to indicate that as energy accounted for larger and larger proportions of national budgets, countries increased their efficiencies and that these were maintained, in large measure, following the normalization of oil prices.

The argument for viewing modernization theory as the primary explanation for the dynamics occurring as countries make shifts from agrarian to industrial to post­ 140 industrial forms has been supported with respect to energy intensity. Dependency\world systems theories were argued to augment our understanding of the fundamental dynamics of societal transitions. In this regard, policy relevant implications emerging from the dependency\world systems tradition are in evidence as well as several very important, but yet untested, implications. First, the rather consistent negative effect of commodity concentration in the post-oil shock period supports the contention that vertical trade patterns and excessive reliance on raw materials production without economic base diversification stunts national development efforts in the more recent periods. The lesson to be learned from this Finding is mixed. From an environmental and purely conservationist perspective it would appear that commodity concentration is an advantageous development path. Unfortunately, considered as part of a development plan which has as part of its objective basic needs provision and economic expansion beyond the intermediate stages of development, such a development strategy could prove harmful in the long run. Consequently, while support for the dependency\world systems perspectives is in evidence, the pursuit of a development trajectory that specifically embraces one of commodity concentration in attempts to limit pollution and further depletion of non-renewable sources of energy may be ill-advised. Such a strategy is further ill-advised, particularly for developing countries, since broader bases of economic production provide insurance from economic fluctuations and the vicissitudes of world market prices.

The preliminary support for dependency\world systems theory does lead to several interesting hypotheses regarding First and Third World relations that can be addressed 141 in future analyses. The crux of arguments set forth by this tradition are rooted in exploitation of Third World resources for the economic benefit of the core. As the preceding analysis demonstrates, the predictions of dependency\world systems theories need not necessarily be ones of using less developed countries as pollution havens. First and foremost, dependency\wor!d systems theorists would argue that core nations and multinational corporations are primarily interested in maximizing profits. The result is that both pollution-haven and energy-exploitation hypotheses can coexist within the dependency tradition. Pollution haven related hypotheses co-exist with pollution- reduction hypotheses within the dependency\world systems traditions and creative critical experiments need to be designed to test these hypotheses. Assuming that the core uses

LDCs as merely additional factors of production, then, the possibility of LDC use as pollution havens mechanisms of escaping increasingly stringent environmental laws in

First World countries remains a distinct possibility. Support for this thesis based on findings from selected countries (Leonard, 1988) means that this becomes a promising avenue for future cross-national research on ecological-degradation. Another equally viable hypothesis derived from the dependency\world systems tradition is the possibility that core countries may be capitalizing on the energy endowments of LDCs and citing factories in LDCs based on energy resource endowment, given the increasing economic and political costs of fuel in the post-oil shock period. Finally, while this analysis used commodity concentration as the dependency\worId systems indicator of choice based on coverage and timing considerations, analyses using indicators of multinational corporate penetration, its sectoral counterparts, and the newer flow and stock measures suggested 142 by Firebaugh (1992) are in need. Such analyses will address the issue of whether or not ecological degradation is among the disequilibrating effects engendered by the newer form of core exploitation of LDCs. Also of considerable importance are the extent to which the consequences of dependent development affect national trajectories of development and resultant levels of ecological degradation. For example, dependency\world systems theorists argue that foreign investment retards national development in the long run through the processes of profit repatriation, stifling of domestic investment via capital monopolization, and the absence of spread effects. By extension, less developed countries are brought into the intermediate stages but their potential for balanced growth is stifled thereby resulting in stagnation and immobility in the world system. The implications of fixation at intermediate levels of development for ecological damage including energy intensity are potentially devastating. Research that specifically determines the effects of foreign investment on energy intensity (as well as other forms of ecological degradation) will prove to be invaluable in terms of stemming unrestrained ecological damage.

Expectations derived from the ecological-evolutionary theory were strongly supported in this analysis, suggesting that countries are not uniformly underdeveloped prior to the onset of modernity. The robust and consistent negative effect of population density on energy intensity indicates that technological, ecological and institutional histories do indeed affect trajectories of development and therefore energy intensity. This finding, as in the case of those for dependency\world systems theories, forces adjustments in the manner in which orthodox modernization theory conceptualizes the 143 development process. Insight gained from the ecological-evolutionary approach points

to an accelerated pace of diffusions of technology and culture. The implications of this

finding are relatively straightforward. As developing countries embark on the road to

modernity, the rapid adoption of modem ways and the advanced pace of modernity

experienced by historically advantaged nations should not cause immediate alarm

concerning the apparent increase in energy intensity. Given that the essential logic of

modernization has been borne out, rapidly forthcoming reductions in energy intensity can

be expected in the near future as countries at intermediate levels of development make

transitions to service-based economies. Recognition that this "worsening then improving"

phenomenon"is merely part of a modified trajectory of development should lead to

greater tolerance and more planning rather than denouncing these nations for apparent

energy inefficiency. Conversely, in the absence of growth in transportation sectors or

some obviously energy intensive sector, sparsely populated nations experiencing very

rapid growth in energy intensity should be considered cause for alarm according to

ecological-evolutionary theory. The rapid growth of energy intensity in sparsely

developed countries would be indicative of truly "wasteful" or inefficient patterns of

energy consumption. Such observations could also prove to be of utility in identifying

potential areas for intervention. A more immediate consequence of increased population

also stems from the agglomeration benefits gained from the spatial concentration of activities.

In chapter 3 it was suggested that urbanization would exert a negative influence on energy intensity by virtue of the benefits accruing from the concentration of industrial 144

and residential activities and the cost-effectiveness of service delivery with greater spatial

concentration. Although urbanization failed to obtain in the models presented, the

compatibility of the urban argument with that of the logic of ecological-evolutionary

theory (as well as the consistently high positive correlations between the two measures)

leads to the recommendation that research on the potential beneficial effects of

urbanization on energy intensity not be discounted. Analyses that use disaggregated

measures of development could be performed to separate the effects of residential from

urban energy use. Similar arguments can be made for the findings regarding percentage

of the labor force in services. As a reminder, with the exception of transportation energy

intensity, standardized models were applied to all dependent variables in this analysis.

While such an approach is of appropriate and of considerable utility in exploratory

analyses of the sort performed here, greater latitude in terms of model specification

would in all likelihood increase the explanatory power of specific models. Now that the

utility of development theories for the study of energy intensity has been established,

research is needed that looks at more limited numbers of dependent variables with more flexible tailor-made models. More tailor-made and sector-specific models may produce findings supportive of the urbanization and post-industrial/service sector expectations.

Implications and Relevance of Economic Growth Models

The intent of the replication of standard models of economic growth was to test the hypothesis that current models are underspecified. It was argued that energy constitutes an integral part of the development process and is so critical to development that neglect of its availability and supply represents a grave omission. Furthermore, with 145 respect to the supply of energy, it was suggested that failure to consider a decomposition

of the time frame into pre- and post-oil price disturbance periods should pose further

problems when considering the determinants of economic growth. Finally, neglect of

ecological-evolutionary’s potential contribution to models of economic growth was

another potential shortcoming of models of economic growth that the replication and

extension was designed to address. The first two criticisms of current economic growth

research differ fundamentally from the third, since recognition of the relevance of the oil

shocks and supply of energy to development should have been included from the

inception of studies on economic growth. The potential contribution of ecological- evolutionary theory, on the other hand, flows from the newest variants of ecological- evolutionary and, should the hypotheses be supported, researchers cannot be faulted for gross oversights as in the former case.

Results presented in the previous chapter provide clearly support the contention that currently used models of economic growth are deficient. The intensity with which energy is used, to a lesser degree the local resource endowment, and countries’ historical social organizational patterns were all found to contribute to explanations of economic growth. The consistently positive and significant effect of energy on economic growth in both periods under investigation leads to the conclusion that energy use is central to economic growth and, by extension, advances in human welfare. Among the implications of this Finding is the observation that development and economic growth, both prerequisites for general social welfare advances along several dimensions, necessitates an unencumbered flow of preferably cheap supplies of energy. Many 146

developing countries spend disproportionate amounts of their gross domestic product on

meeting their basic energy needs, a factor that often results in reductions in social

welfare spending. This further reinforces the need for increasing the efficiency with

which existing supplies of energy are used and expediting the process by which safe

alternatives to carbon-based fuels are developed.

Regardless of the period under examination, the veiy consistent and robust

positive effect of population density on economic growth attests to the influence of

institutional and demographic inheritances on current organizational forms and development paths. Clearly, countries that have had histories of high rates of population growth and density made organizational accommodations that are serving them well in the modern era. For example, South Korea, Indonesia, and Taiwan have all experienced rapid growth in recent decades and are expected to continue with their current momentum. The international community recognition of this is evidenced by Japan’s inclusion of these countries in their long range economic plans. In poising itself for the acquisition of and cornering of future markets, Japan sends a disproportionate percentage of its foreign assistance to densely populated Asian countries. Japan’s foreign ministers openly acknowledge that by providing aid and building infrastructure in these countries they expect to create markets which Japanese corporations will then supply. Development theorists would be well served to pay careful attention to ecological-evolutionary theory and its more recent variants in future research. 147

Relevance of Findings for Sociological Theory

The analyses conducted in this project were more exploratory in nature rather

than replication oriented because of the absence of previous theoretically grounded work

in the area of energy intensity. As a direct consequence, a great deal of additional

research remains to be done. First, now that the utility of applying sociological theories

of development to the issue of energy intensity has been demonstrated, more detailed

analyses are needed, especially at the sectoral level. Even within the limitations imposed

by the lack of completely standardized data, more sector specific models that include

variables designed to tap dynamics occurring within each of the sectors analyzed can be

developed. Modernization theory is uniquely suited to this task since it deals principally

with the sectoral evolution of societies. Using the results of this analysis as a start,

theoretically-derived hypotheses regarding factors affecting the various sectors of the economy can be developed and tested by theorists working within the modernization tradition. Examples might include the use of variables measuring the size of the manufacturing sector in modeling industrial energy intensity or the use of measures of mechanization and fertilizer use in analyzing the agricultural sector.

Similarly, dependency\world systems theories suggest dynamics that should exert influences at the sectoral level. Some of the more obvious examples of questions that can be addressed by researchers are: Since foreign investment is often capital intensive, does penetration in agriculture lead to reductions in levels of energy intensity? Given that mineral and extractive industries are inherently energy intensive, does foreign direct investment in the extractive sector boost national levels of energy intensity? Penetration 148 in the manufacturing sector also tends to be capital intensive. Consequently, does foreign

investment in manufacturing lead to declines in energy intensity? Also, since most dependency\worId systems theorists argue that foreign investment distorts the internal processes of penetrated countries, the possibility that energy intensity intervenes between foreign investment and outcomes such as overurbanization, economic growth and income

inequality is distinct. The effects of foreign investment are also likely to manifest themselves in other sectors as well. For example, is it the case that residential energy intensity is reduced because of skewed income distributions, excessive urbanization rates, lagging fertility declines etc., allegedly engendered by foreign investment?

The paucity of research in this area to date means that a tremendous number of opportunities exist for ascertaining the underlying causal structures leading to differing energy intensities. Variables representing the three theories of development can be used as exogenous variables analysis along with controls for fuel and mineral exports.

Potential intervening variables/constructs will include mortality and fertility regimes, percentage of national populations in specific age categories, income distribution, urbanization, government subsidies, economic growth, growth of the tertiary labor force, political democracy, and adult literacy. The dependent variables can include aggregate energy intensity for pre- and post-oil shock periods as well as sectoral energy intensity for the post-oil shock periods. The outcome should be a synthesis of literature and theory from apparently diverse areas of inquiry and will probably result in a more comprehensive and nuanced explanation of energy intensity than is currently available. 149

Aside from the most obvious as stated above, an entirely different avenue for

additional research has been opened up by this research project. The inclusion and

significance of energy intensity as an additional independent variable in the area of

economic growth leaves open the very distinct possibility that the manner and efficiency

with which energy is used (and its availability) has effects on a wide range of topics

usually analyzed by social scientists. Perhaps the most widely analyzed set of dependent

variables used by cross-national researchers pertains to those related to the physical

quality of life and social well-being of individual in Third World countries. As discussed

in chapter one, energy is central not only to societal but to basic needs provision for all

individuals. Researchers tend to focus on models designed to explain the causal factors

involved in determining the level of basic needs provisions across different societies.

Often differences are found between countries at similar levels of development and

indicators of basic needs provision. Attempts at explaining these differences should

probably include measures of both energy resource endowment and energy intensity net of development. The reason for this suggestion is straightforward. Since large percentages of national budgets are devoted to paying for energy, should it not be the case that both local availability and the efficiency with which countries use energy exert indirect effects on a variety of basic needs indicators via potential spending redistributions? Researchers attempting to discern the determinants of debt burdens would also do well to at least consider the role of the energy sector in their analyses. Finally, following the recent suggestions of Firebaugh (1994), researchers may want to consider using completely dynamic models to test many of the hypotheses suggested in this 150 discussion. Stability of findings across both dynamic and static or mixed models would lead to more confidence in the findings. On the whole, I am not suggesting that energy intensity should be included in all analyses pertaining to cross-national research, rather it should serve as a warning that failure to consider its potential effect may be a major oversight.

The Implications for Sociological Theory

The analysis and findings demonstrate the relevance of the interaction between theory and empirical research. The richly descriptive body of research on energy intensity lacked any over-arching theoretical frameworks from which they could be viewed. In large measure, sociologists tend to ignore the work conducted by scholars in other disciplines. As illustrated by this analysis, interdisciplinary cross-pollination can indeed result in advances that would take disciplines working separately much longer to achieve. The work of scholars in all fields would probably benefit enormously from the ideas and findings generated in other disciplines. The superimposition of sociological theories of development on findings derived disparate sources has resulted in the beginnings of a more complete picture of the determinants of national energy regimes.

The interplay between theory and empirical analysis is vital to theoretical development and sociologists would be well served by paying more careful attention to the works of researchers in other fields. The familiar comment that demography has too little theory while sociology has too much appears to be true, except this time it applies to sociology and the physical sciences. The overall message from this research echoes that which was made approximately 12 years ago when Rosa and Machlis warned that macrosociology’s 151 inattention to energy does so "only at the peril of ignoring a key factor in social structure

and change" (1983:171). Sociological theories of change and development would be

greatly enhanced from a greater appreciation of the central role played by energy in

societal development. More careful attention to the work of early sociologists regarding social change would probably enhance the state of current theory.

Concluding Comments

Academic and theoretical debates aside, the centrality of energy to human activity cannot be understated. The continued survival of humans societies depends on the reliable and continued supply of energy. Unfortunately, the same materials that sustain life also carry with them the potential to destroy life. The key seems to reside in the abilities of governments to arrive at agreements concerning the appropriate use and distribution of these life-sustaining materials. Over-use and a history of blatant disregard for the finite quantities of non-renewable sources of energy have resulted in international conflicts that threaten to destabilize life as we know it. Issues ranging from global warning, Middle

East peace, nuclear non-proliferation, the destruction of natural habitats and the provision of basic needs for the world’s population all have energy use and consumption at their core. International cooperation has the potential to solve many of these issues but progress in that direction is painfully slow. Until adequate equitable solutions can be found, the more efficient use of existing resources is our most promising route. APPENDIX A

List of Countries used in the Analysis of Change in Total Energy Intensity from 1965 to 1973. (See Tables 1 and 2, N=81)

United States, Canada, Jamaica, Trinidad and Tobago, Barbados, Mexico, Guatemala, Honduras, Nicaragua, Costa Rica, Panama, Colombia, Venezuela, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, Uruguay, United Kingdom, Ireland, Netherlands, France, Switzerland, Spain, Portugal, Federal Republic of Germany, Austria, Italy, Malta, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Senegal, Benin, Ivory Coats, Upper Volta, Liberia, Ghana, Togo, Nigeria, Gabon, Zaire, Kenya, Rwanda, Ethiopia, Zambia, Zimbabwe, Malawi, South Africa, Madagascar, Mauritius, Morocco, Algeria, Tunisia, Iran, Iraq, Turkey, Egypt, Syria, Israel, Hong Kong, Korea, Japan, India, Pakistan, Sri Lanka, Nepal, Thailand, Malaysia, Singapore, Philippines, Indonesia, Australia, Papua New Guinea, New Zealand, Fiji.

List of Countries used in the Analysis of Change in Total Energy Intensity from 1974 to 1985. (See Tables 3 and 4, N=83)

United States, Canada, Jamaica, Trinidad and Tobago, Barbados, Mexico, Guatemala, Honduras, Nicaragua, Costa Rica, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, Uruguay, United Kingdom, Ireland, Netherlands, France, Switzerland, Spain, Portugal, Federal Republic of Germany, Austria, Italy, Malta, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Senegal, Benin, Ivory Coast, Upper Volta, Liberia, Ghana, Gabon, Zaire, Uganda, Kenya, Tanzania, Rwanda, Ethiopia, Zambia, Zimbabwe, Malawi, South Africa, Madagascar, Mauritius, Morocco, Algeria, Tunisia, Sudan, Iran, Iraq, Turkey, Egypt, Syria, Saudi Arabia, China, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Nepal, Thailand, Malaysia, Singapore, Philippines, Indonesia, Australia, New Zealand, Fiji.

List of Countries used in the Analysis of Total Energy Intensity for 1965. (See Tables 5 and 6, N=95)

United States, Canada, Haiti, Dominican Republic, Jamaica, Trinidad and Tobago, Barbados, Mexico, Guatemala, Honduras, El Salvador, Nicaragua, Costa Rica, Panama, Colombia, Venezuela, Guyana, Suriname, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, Uruguay, United Kingdom, Ireland, Netherlands, France, Switzerland, Spain, Portugal, Federal Republic of Germany, Austria, Italy, Malta, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Iceland, Gambia, Senegal, Benin, Mauritania,

152 153 Niger, Ivory Coast, Upper Volta, Liberia, Ghana, Togo, Cameroon, Nigeria, Gabon, Central African Republic, Chad, Congo, Zaire, Kenya, Burundi, Rwanda, Ethiopia, Zambia, Malawi, South Africa, Madagascar, Mauritius, Morocco, Algeria, Tunisia, Iran, Iraq, Turkey, Egypt, Syria, Israel, Saudi Arabia, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Nepal, Thailand, Malaysia, Singapore, Philippines, Indonesia, Australia, Papua New Guinea, New Zealand, Fiji.

List of Countries used in the Analysis of Total Energy Intensity for 1975. (See Tables 7 and 8 , N=83)

United States, Canada, Trinidad and Tobago, Barbados, Mexico, Guatemala, Honduras, Nicaragua, Costa Rica, Panama, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, Uruguay, United Kingdom, Ireland, Netherlands, France, Switzerland, Spain, Portugal, Federal Republic of Germany, Austria, Italy, Malta, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Gambia, Senegal, Benin, Ivory Coast, Upper Volta, Sierra Leone, Ghana, Nigeria, Gabon, Congo, Zaire, Uganda, Kenya, Tanzania, Rwanda, Ethiopia, Zimbabwe, Malawi, South Africa, Madagascar, Mauritius, Morocco, Algeria, Tunisia, Sudan, Iran, Iraq, Turkey, Egypt, Syria, Israel, Saudi Arabia, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Thailand, Malaysia, Singapore, Philippines, Indonesia, Australia, New Zealand, Fiji.

List of Countries used in the Analysis of Total Energy Intensity for 1985. (See Tables 9 and 10, N=94)

United States, Canada, Jamaica, Trinidad and Tobago, Barbados, Mexico, Guatemala, Honduras, El Salvador, Nicaragua, Costa Rica, Panama, Colombia, Venezuela, Suriname, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, Uruguay, United Kingdom, Ireland, Netherlands, France, Switzerland, Spain, Portugal, Federal Republic of Germany, Poland, Austria, Hungary, Italy, Malta, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Gambia, Senegal, Benin, Ivory Coast, Liberia, Liberia, Sierra Leone, Ghana, Togo, Cameroon, Nigeria, Gabon, Zaire, Uganda, Kenya, Tanzania, Rwanda, Somalia, Angola, Mozambique, Zambia, Malawi, South Africa, Madagascar, Mauritius, Morocco, Algeria, Tunisia, Sudan, Iran, Iraq, Turkey, Egypt, Syria, Jordan, Israel, Saudi Arabia, China, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Thailand, Malaysia, Singapore, Philippines, Indonesia, Australia, Papua New Guinea, New Zealand, Fiji.

List of Countries used in the Analysis of Change in Total Energy Intensity for 1979 to 1989. (See Tables 11 and 12, N=83)

United States, Canada, Trinidad and Tobago, Barbados, Mexico, Guatemala, Honduras, Nicaragua, Panama, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, Uruguay, United Kingdom, Ireland, Netherlands, France, Switzerland, 154 Spain, Portugal, Federal Republic of Germany, Austria, Hungary, Italy, Malta, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Gambia, Senegal, Benin, Ivory Coast, Sierra Leone, Ghana, Togo, Cameroon, Nigeria, Gabon, Zaire, Uganda, Kenya, Rwanda, Somalia, Zambia, Zimbabwe, Malawi, South Africa, Madagascar, Mauritius, Morocco, Algeria, Tunisia, Sudan, Iran, Turkey, Egypt, Syria, Israel, Saudi Arabia, China, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Thailand, Malaysia, Singapore, Philippines, Indonesia, Australia, New Zealand, Fiji.

List of Countries used in the Analysis of Total Energy Intensity for 1979. (See Tables 13 and 14, N=83)

United States, Canada, Trinidad and Tobago, Barbados, Mexico, Guatemala, Honduras, Nicaragua, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, Uruguay, United Kingdom, Ireland, Netherlands, France, Switzerland, Spain, Portugal, Federal Republic of Germany, Austria, Hungary, Italy, Malta, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Gambia, Senegal, Benin, Ivory Coast, Sierra Leone, Ghana, Togo, Cameroon, Nigeria, Gabon, Zaire, Uganda, Kenya, Tanzania, Rwanda, Somalia, Zambia, Zimbabwe, Malawi, South Africa, Madagascar, Mauritius, Morocco, Algeria, Tunisia, Sudan, Iran, Turkey, Egypt, Syria, Israel, Saudi Arabia, China, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Thailand, Malaysia, Singapore, Philippines, Indonesia, Australia, New Zealand, Fiji.

List of Countries used in the Analysis of Change in Industry Energy Intensity from 1979 to 1989. (See Tables IS and 16, N -52)

Jamaica, Trinidad and Tobago, Mexico, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Argentina, Netherlands, France, Austria, Hungary, Italy, Yugoslavia, Greece, Finland, Norway, Denmark, Senegal, Benin, Ivory Coast, Ghana, Cameroon, Nigeria, Gabon, Kenya, Zambia, Zimbabwe, South Africa, Morocco, Algeria, Tunisia, Sudan, Iran, Turkey, Egypt, Syria, Saudi Arabia, China, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Thailand, Singapore, Philippines, Indonesia.

List of Countries used in the Analysis of Change in Services Energy Intensity from 1979 to 1989. (See Tables 17 and 18, N=53)

Jamaica, Trinidad and Tobago, Mexico, Panama, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Argentina, Netherlands, France, Austria, Hungary, Italy, Yugoslavia, Greece, Finland, Norway, Denmark, Senegal, Benin, Ivory Coast, Ghana, Cameroon, Nigeria, Gabon, Kenya, Zambia, Zimbabwe, South Africa, Morocco, Algeria, Tunisia, Sudan, Iran, Turkey, Egypt, Syria, Saudi Arabia, China, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Thailand, Singapore, Philippines, Indonesia. 155 List of Countries used in the Analysis of Change in Agriculture Energy Intensity from 1979 to 1989. (See Tables 19 and 20, N=52)

Jamaica, Trinidad and Tobago, Mexico, Panama, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Argentina, Netherlands, France, Austria, Hungary, Italy, Yugoslavia, Greece, Finland, Norway, Denmark, Senegal, Benin, Ivory Coast, Ghana, Cameroon, Nigeria, Gabon, Congo, Kenya, Zambia, Zimbabwe, South Africa, Morocco, Algeria, Tunisia, Sudan, Iran, Turkey, Egypt, Syria, Saudi Arabia, China, Hong Kong, Japan, India, Pakistan, Sri Lanka, Thailand, Singapore, Philippines, Indonesia.

List of Countries used in the Analysis of Agriculture Energy Intensity for 1979. (See Tables 21 and 22, N=64)

United States, Canada, Jamaica, Trinidad and Tobago, Mexico, Panama, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, United Kingdom, Netherlands, France, Spain, Portugal, Federal Republic of Germany, Austria, Hungary, Italy, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Senegal, Benin, Ivory Coast, Ghana, Nigeria, Gabon, Tanzania, Ethiopia, Zambia, Zimbabwe, Morocco, Algeria, Tunisia, Sudan, Turkey, Iraq, Egypt, Syria, Israel, Saudi Arabia, China, Hong Kong, South Korea, Japan, India, Pakistan, Thailand, Malaysia, Singapore, Philippines, Indonesia, Australia, New Zealand.

List of Countries used in the Analysis of Industry Energy Intensity for 1979. (See Tables 23 and 24, N=65)

United States, Canada, Jamaica, Trinidad and Tobago, Mexico, Panama, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, United Kingdom, Netherlands, France, Spain, Portugal, Federal Republic of Germany, Austria, Hungary, Italy, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Senegal, Benin, Ivory Coast, Ghana, Cameroon, Nigeria, Gabon, Kenya, Tanzania, Ethiopia, Zimbabwe, Morocco, Algeria, Tunisia, Sudan, Turkey, Iraq, Egypt, Syria, Israel, Saudi Arabia, China, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Thailand, Malaysia, Singapore, Philippines, Indonesia, Australia, New Zealand.

List of Countries used in the Analysis of Transportation Energy Intensity for 1979. (See Tables 25 and 26, N=62)

United States, Canada, Jamaica, Trinidad and Tobago, Mexico, Panama, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, United Kingdom, Netherlands, France, Spain, Federal Republic of Germany, Austria, Hungary, Italy, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Senegal, Benin, Ivory Coast, Cameroon, Nigeria, Kenya, Tanzania, Ethiopia, Zambia, Zimbabwe, Algeria, Tunisia, Sudan, Turkey, Iraq, Egypt, Syria, Israel, Saudi Arabia, China, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Thailand, Malaysia, Singapore, 156 Philippines, Indonesia, Australia, New Zealand.

List of Countries used in the Analysis of Residential Energy Intensity for 1979. (See Tables 27 and 28, N=57)

United States, Canada, Jamaica, Trinidad and Tobago, Mexico, Panama, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, United Kingdom, Netherlands, France, Portugal, Federal Republic of Germany, Austria, Italy, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Ivory Coast, Ghana, Cameroon, Nigeria, Kenya, Tanzania, Ethiopia, Zambia, Zimbabwe, Morocco, Algeria, Tunisia, Sudan, Turkey, Iraq, Egypt, Saudi Arabia, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Thailand, Malaysia, Singapore, Philippines, Australia, New Zealand.

List of Countries used in the Analysis of Services Energy Intensity for 1979. (Sec Tables 29 and 30, N=66)

United States, Canada, Jamaica, Trinidad and Tobago, Mexico, Panama, Colombia, Venezuela, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, United Kingdom, Netherlands, France, Spain, Portugal, Federal Republic of Germany, Austria, Hungary, Italy, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Senegal, Benin, Ivory Coast, Ghana, Cameroon, Nigeria, Gabon, Kenya, Tanzania, Ethiopia, Zambia, Zimbabwe, Morocco, Algeria, Tunisia, Sudan, Turkey, Iraq, Egypt, Syria, Israel, Saudi Arabia, China, Hong Kong, South Korea, Japan, India, Pakistan, Sri Lanka, Thailand, Malaysia, Singapore, Philippines, Indonesia, Australia, New Zealand.

List of Countries used in the Analysis of Economic Growth from 1965 to 1973. (See Tables 31 and 32, N=71)

United States, Canada, Jamaica, Trinidad and Tobago, Mexico, Guatemala, Honduras, Nicaragua, Costa Rica, Panama, Colombia, Venezuela, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, Uruguay, United Kingdom, Ireland, Netherlands, France, Switzerland, Spain, Portugal, Federal Republic of Germany, Austria, Italy, Yugoslavia, Greece, Finland, Sweden, Norway, Denmark, Senegal, Benin, Ivory Coast, Liberia, Ghana, Togo, Nigeria, Zaire, Kenya, Tanzania, Rwanda, Ethiopia, Angola, Mozambique, Zambia, Malawi, South Africa, Madagascar, Morocco, Algeria, Tunisia, Iran, Iraq, Turkey, Egypt, Hong Kong, South Korea, Japan, Pakistan, Burma, Sri Lanka, Thailand, Malaysia, Philippines, Indonesia, Papua New Guinea.

List of Countries used in the Analysis of Economic Growth from 1974 to 1985. (See Tables 33 and 34, N=53)

Jamaica, Mexico, Guatemala, Honduras, Nicaragua, Costa Rica, Panama, Colombia, Ecuador, Peru, Brazil, Bolivia, Paraguay, Chile, Argentina, Uruguay, Senegal, Benin, 157 Ivory Coast, Upper Volta, Liberia, Sierra Leone, Ghana, Nigeria, Zaire, Kenya, Tanzania, Rwanda, Ethiopia, Angola, Mozambique, Zambia, Malawi, Madagascar, Morocco, Algeria, Tunisia, Sudan, Iraq, Turkey, Egypt, Syria, Hong Kong, South Korea, India, Pakistan, Sri Lanka, Thailand, Malaysia, Singapore, Philippines, Indonesia. APPENDIX B

1. Saudi Arabia was excluded from the set of equations modeling change in energy intensity from 1965 to 1973 because of its unusually low level of energy intensity in 1965 compared to other countries in the sample. Saudi Arabia’s per capita energy consumption was approximately one-fourth of the average energy consumption for other countries in 1965 (365 kilograms of coal equivalent per capita compared to a mean of 1166), Combined with Saudi Arabia’s unusually high per capita real gross domestic product stemming from its oil production ($5981 compared to a mean of $2659), this resulted in an unusually low level of energy intensity compared to other countries in the sample. By 1975 Saudi Arabia had become the world’s largest exporter of oil and the world’s third largest producer (Kurian, 1987). Not surprisingly, the removal of Saudi Arabia from the sample affects only the energy exports variable (it loses significance).

2. Panama displayed very high energy intensity scores for 1974 and for industrial energy intensity for 1979. This resulted in its undue influence on the results for both sets of equations. Panama’s energy consumption in 1974 was approximately two and one half times the mean energy consumption of other countries for that year, perhaps a function of industrial activities around the Panama Canal. During the 1970s Panama became very dependent on oil and its annual production rates between 1973 and 1983 averaged 17 percent (Kurian, 1987), This ultimately led to the development and use of hydroelectric during the 1980s which now accounts for over 90 percent of Panama’s current energy consumption. This pattern of energy use is compared to a per capita real gross domestic product amount that was well below the average for 1974 ($2922 compared to $4232). The resultant energy intensity figure reveals that Panama was extremely inefficient relative to other nations. Panama’s industrial energy consumption was also above the level expected given the amount of real gross domestic product derived from that sector. The result was an unusually high level of energy intensity for the industrial sector for 1979.

3. Gambia and Nigeria were excluded from the equations reported in Table 2 for the analysis of change in energy intensity from 1974 to 1985 because of their very low levels of energy intensity. The mean real gross domestic product for 1974 was $3854 while that for Gambia was $8 6 6 . Gambia’s per capita energy consumption was also below the sample average with a per capita energy consumption in kilograms of coal equivalent of 37 compared to an average of 1321. Nigeria exhibited similar patterns. Nigeria’s per capita energy consumption was 58 (mean = 1321) while its RGDP was $1192 compared to the average of $3854. This pattern is undoubtedly a function of Nigeria’s exploitation of its large oil reserves which tends to elevate its RGDP. Unfortunately, Nigeria’s vast

158 159 development needs, mishandled development, ill-managed agriculture, excessive food import dependency and its chronic budget deficits contribute to its continued low level of development (Kurian, 1992). The resultant energy intensity scores for Gambia and Nigeria were .04 and .05, respectively while the mean energy intensity was .25. Both countries were found to bias the results and therefore excluded.

4. Zimbabwe was a consistent outlier in several analyses, primarily as a result of its apparent inefficient use of energy. Zimbabwe’s energy consumption was consistently below that of most other countries in the sample. The high energy intensity score, however, results from Zimbabwe’s very low levels of per capita real gross domestic product compared to other nations. Over 75 percent of Zimbabwe’s labor force is still employed in the agricultural sector which suffers from chronic droughts that affect food quality and quantity (Kurian, 1992). In 1965, for example, Zimbabwe’s energy consumption was approximately one-half of the mean energy consumption for that year (577 kilograms of coal equivalent per capita compared to an average of 1166). That country’s per capita real gross domestic product, however, was about one-third that of the mean for countries in the sample (Zimbabwe’s per capita RGDP in 1965 was $953 while the sample average was $2659). Basically the same pattern emerges for the years 1975 and 1985. The result of the very low levels of RGDP is very high energy intensity scores.

5. Liberia, China, and Nepal were all found to exert undue influence on the results from the cross-sectional analysis of energy intensity for 1975. One of the principal sources of its biases stem from Liberia’s sparse population density. Liberia had a population density of 14 per square kilometer whereas the sample mean was 174. Another unusual characteristic of Liberia is its excessive reliance on oil as a source of revenue. Liberia has one of the highest commodity concentration indices of all countries in the sample (91.1 compared to a mean of 45.7). Liberia’s score was twice the mean and less than 8 away from the maximum. Inspection of the diagnostics showed that these were indeed the sources of Liberia’s excessive influence on the results. China’s principal unique characteristic for the time period under consideration is related to its pattern of energy exports. Petroleum has been the key to China’s industrial development and by 1985 China had become the world’s sixth largest producer of oil (Kurian, 1992). Although coal now dominates China’s industrial development (Stern et al, 1992), by the mid 1970s China’s local production of petroleum had increased such that it was no longer dependent on oil imports and petroleum became China’s major source of foreign earnings (Kurian, 1992), The principal reason for excluding Nepal stems from its very low energy intensity score and its low level of development. General indicators of level of development clearly point to the exceptionally low level of economic development of Nepal. While the average per capita gross national product for countries in the sample was $1835, the per capita GNP for Nepal was $1 1 0 , Most of Nepal’s population remains tied to subsistence agriculture (90 percent of the population is still engaged in subsistence farming (Kurian, 1992)). Also, Nepal’s energy consumption is the lowest of any nation in the world. The average per capita energy consumption in 1975 was 1516 while it was 160 10 for Nepal. Real gross domestic product figures point to essentially the same pattern. The resultant energy intensity score for Nepal was .01 compared to an average of .27. Clearly Nepal has yet to enter the modem world.

6 . Jamaica was an outlier in the set of equations modeling the level of energy intensity in 1975, the growth in energy intensity from 1979 to 1989 and the level of energy intensity in 1979, The reason Jamaica is a consistent outlier is its high level of energy intensities or, more specifically, its apparent inefficiency in energy use. Jamaica’s per capita energy consumption is very similar to that of the average energy consumption of other countries in the sample (In 1979 Jamaica had a per capita energy use of 1359 kilograms of coal equivalent compared to a sample mean of 1582 kilograms of coal equivalent). With regard to productivity, however, Jamaica falls well below the average ( Jamaica’s 1979 per capita RGDP was $2508 while the sample mean was $4745). The resultant energy intensity score for Jamaica was twice that of the sample mean. The unusually high energy intensity of Jamaica is directly related to global economic changes in the 1970s and 1980s. The Jamaican economy declined in the late 1970s and 1980 with GNP falling at 2.1 percent annually (Kurian, 1987). The declining foreign earnings were related to the decline in bauxite earnings and the escalating costs of oil imports and inflation.

7. Inspection of the regression diagnostics point to level of development and commodity concentration as the problem areas for South Korea. Descriptives on these variables do indeed show that South Korea is unusual. With regard to commodity concentration, South Korea has a very low score and resembles a highly developed country (South Korea has a commodity concentration score of6 . 8 while the sample mean is 44). In the case of South Korea’s level of development as indicated by its gross national product, however, it appears more like a developing country (South Korea’s per capita GNP for 1979 was $1520 while the sample average was $2665). South Korea’s low score on the commodity concentration indicator is a function of the long term economic planning and investment made by that country since the 1950s. South Korea has a very balanced economy and has had some of the world’s most impressive growth rates since the 1950s. Between 1980 and 1989, for example, the country had the world’s highest annual growth rate of 10 percent. During the seventies the figures were equally impressive with a 15.1% in 1976, a 10.3%% in 1977 and an 11.6% rate in 1978.

8 . Sri Lanka and Cameroon were excluded from all equations modeling level of agricultural energy intensity for 1979. The two countries suffer from the same problem, very low levels of development. According to the data reported by the World Resources Institute, the percentages of total commercial energy used in their agricultural sectors was 0. This would indicate that human and animal power dominate in these countries’ agricultural sectors. It is therefore not surprising that these countries were diagnosed as outliers which biased the results for this particular sector. 161 9. In the equations modeling residential energy intensity Indonesia was found to exert undue influence on the results. Indonesia was unusual because of the high percentage of total commercial energy use in the residential sector compared to its level of urbanization. The percentage of total commercial energy used in the residential sector for 1979 was about twice that of other countries (the percent of residential energy use for Indonesia was 31 while the average for other countries was 15.8 percent). This high level of residential energy use is probably a function of the beginning of the third of Indonesia’s 5 year plans called the Repelita III. This plan was aimed at tackling problems of food production, employment and income distributions. An economic growth rate of 6 percent was targeted along with the expansion of the manufacturing sector. The high percentage of energy use from the residential sector probably reflects the attempt by planners to encourage economic expansion to absorb 9.3 million new workers (Kurian, 1987).

10. Singapore and India were excluded from the equations modeling economic growth for the 1965 to 1973 period. In the case of Singapore the reason is very straightforward, Singapore is completely urbanized (level of urbanization is 100 percent) and as a consequence is very dense. Partial plots clearly point to the influence of Singapore on population density. The mean population density for countries in the sample was 189 persons per square kilometer while it was 3,845 for Singapore. India’s low level of exports was the reason for its influence on the results. The mean score on the exports indicator was 2433 while it was 417 for India. India has consistently suffered from severe trade deficits and it continues to rise. The trade deficit combined with India’s lack of an export culture, its large subsistence sector, and poor technology management (Kurian, 1987) serve to depress export earnings. India’s attempts to achieve sustained economic growth from import substitution failed because of government protectionist policies that encouraged inefficiency. The result was that local producers remained uncompetitive and exports decreased. The effect of India on the results pertaining to the exports variable was confirmed by re-running the equation with India in the sample. Results revealed that it caused the exports variable to lose significance. APPENDIX C

VARIABLE MEAN STANDARD DEVIATION

1. Log of total energy intensity, 1965 (N = 110) -1.80 .96

2. Log of total energy intensity, 1973 (N = 115) -1.76 1.05

3. Log of Total Energy Intensity, 1974 (N = 101) -1.74 .89

4. Log of Total Energy Intensity, 1975 (N = 117) -1.62 .87

5. Log of Total Energy Intensity, 1979 (N=131) -1.72 1.13

6 . Log of Total Energy Intensity, 1989 (N = 133) -1.70 1.06

7. Log of Total Energy Intensity, 1985 (N=101) -1.57 .76

8 . Log of Industrial Energy Intensity, 1979 (N=73) -1.55 1.14

9. Log of Industrial Energy Intensity, 1979 (N=74 -8.25 . 8 8

10. Log of Industrial Energy Intensity, 1989 (N = 6 6 ) -1.39 .90

11. Log of Services Energy Intensity, 1979 (N=73) -1.19 .70

162 163 12. Log of Services Energy Intensity, 1989 (N = 6 6 ) -1.13 .76

13. Log of Agriculture Energy Intensity, 1979 (N=73) -4.09 2.17

14. Log of Agriculture Energy Intensity, 1979 (N=74) -8.79 1.59

15. Log of Agriculture Energy Intensity, 1989 (N = 6 6 ) -3.57 2.13

16. Log of Trans. Intensity, 1979 (N=71) -6.76 .60

17. Log of Residential Energy Intensity, 1979 (N= 6 6 ) -6.15 .84

18. Log of Economic Growth from 1965 to 1973 (N= 126) 4.00 3.55

19. Log of Economic Growth from 1974 to 1985 (N = 133) 1.50 3.05

20. Log of RGPD, 1965 (N = 126) 7.46 .93

21. Log of RGPD, 1974 (N = 133) 7.75 .99

22. Log of GNP, 1965 (N = 117) 5.83 1.16

23. Log of GNP, 1974 (N=101) 6.49 .26

24. Log of GNP, 1975 (N = 131) 6.73 1.32

25. Log of GNP, 1979 (N = 130) 7.14 1.41

26. Log of GNP, 1985 (N = 145) 7.23 1.41

27. Sq. of RGDP, 1965 (N=126) 56.45 14.11

28. Sq. of RGDP, 1974 (N=133) 60.99 15.39

29. Sq. of GNP, 1965 (N = 117) 35.38 13.90 164 30. Sq. of GNP, 1974

31. Sq. of GNP, 1975 (N = 131) 46.97 18.26

32. Sq. of GNP, 1979 (N=130) 52.98 20.74

33. Sq. of GNP, 1985 (N=145) 54.22 20,96

34. Urbanization, 1965 (N=166) 37.77 24.65

35. Urbanization, 1975 (N = 101) 43.48 24.53

36. Urbanization, 1979 (N = 166) 44.51 25.27

37. Urbanization, 1985 (N=166) 47.34 24.75

38, Commodity Cone,, 50.32 30.70 1965 (N=133)

39. Commodity Cone., 49.62 30.43 1970 (N = 101)

40. Commodity Cone., 43.46 31,27 1980 (N=124)

41. Population Density, 182.26 933.6 1965 (N=167)

42. Population Density, 213.76 1090.16 1975 (N = 167)

43. Population Density, 238.85 1281.26 1979 (N = 167)

44. Population Density, 278.38 1594.34 1985 (N = 168)

45, Percentage of Labor Force in Services, 1965 (N=147) 27.9 17.78

46. Percentage of Labor Force in Services, 1975 (N = 101) 33.7 19.18 165 47. Percentage of Labor Force in Services, 1979 (N = 147) 35.47 19.55

48. Percentage of Labor Force in Services, 1980 (N = 147) 35.97 19.70

49. Energy Exports/RGDP, 1970 (N=97) .00037 .00099

50. Energy Exports/RGDP, 1970 (N = 8 6 ) .00035 ,0009

51. Energy Exports/RGDP, 1970

52. Energy Exports/RGDP, 1970 (N = 102) .00038 .0008

53. Land Area, 1980 (N = 169) 75913.64 226764.7

54. Foreign Flows, 11565.64 116086.2 1967-1973, (N= 101)

55. Foreign Flows, 17656.31 31873.44 1967-1978,

56. Gross Domestic Investment, 1960-1970 (N=97) 6 . 8 8 5.13

57. Gross Domestic Investment, 1970-1980 (N=97) 5.86 8.56

58. Export Dominance (N = 102) 2422.82 1381.16

59. Market Size, 1965 (N=117) 30820295 169490000

60. Market Size, 1974 (N = 117) 36330255 162970000 REFERENCES

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