This week you will use the case study ?to examine the usefulness of interdisciplinary studies ‘in the real world. First, answer these questions: 1. What is the claim

An Interdisciplinary Analysis of the Causes

of Economic Growth

In: Case Studies in Interdisciplinary Research

By: Rick Szostak

Pub. Date: 2013

Access Date: January 31, 2021

Publishing Company: SAGE Publications, Inc.

City: Thousand Oaks

Print ISBN: 9781412982481

Online ISBN: 9781483349541

DOI: https://dx.doi.org/10.4135/9781483349541

Print pages: 159-190

© 2012 SAGE Publications, Inc. All Rights Reserved.

This PDF has been generated from SAGE Research Methods. Please note that the pagination of the

online version will vary from the pagination of the print book.

An Interdisciplinary Analysis of the Causes of Economic Growth

RickSzostak

Introduction

With billions of people still living in poverty in the world, there is perhaps no more important question in human

science than what are the causes of economic growth. Moreover, it is a very complex question, for economic

growth is influenced by interactions among a host of economic, political, social, cultural, and geographical

phenomena. This chapter discusses how a process for interdisciplinary research can usefully be applied to

the study of economic growth. It is thus simultaneously an exploration of how to do interdisciplinary social

science and how to develop a more comprehensive understanding of economic growth. It shows how a

variety of distinct research programs across all social science disciplines can be integrated to enhance our

understanding of the causes of economic growth.

This chapter is organized according to the steps in the interdisciplinary process.1 Although the chapter

will review each of the various steps ideally involved in interdisciplinary analysis, the presentation focuses

primarily on how “common ground” can be achieved among disciplinary insights that conflict, notably with

respect to the role of government, the role of international trade relationships, and the process by which

economic institutions are and should be developed. Lessons are drawn for each step regarding both our

understanding of economic growth and how best to perform interdisciplinary research.

AUTHOR'S NOTE: My chapter summarizes and comments upon my book The Causes of Economic Growth:

Interdisciplinary Perspectives (Szostak, Rick, 2009, Berlin: Springer).

The question addressed in this chapter is both very complicated and very broad. Both characteristics increase

the difficulty of performing any of the steps as completely as one might like (though perhaps especially

the literature survey). The question is complicated because a variety of phenomena combine to influence

economic growth. By asking the question at the general level rather than with respect to a particular time and

place, we broaden the scope of inquiry significantly: We could forget about questions of basic property rights

if we focused on only the rich world, for example. That is, the breadth of the question forces us to engage

its full complexity. We thus need a broader literature survey, and we need to identify, evaluate, and integrate

across a much broader set of disciplinary insights than would normally be the case. One possible exception

may be the first step: It may be just as easy to frame a broad question as a narrow one. Indeed, it may be

easier, for the narrow question requires detailed definition of the boundaries of the question.

Identify an Interdisciplinary Research Question

We have selected our question: What are the causes of economic growth? It is then necessary to ask whether

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this question is suitably interdisciplinary in nature. Can economic growth be understood by relying only on

the insights of one discipline? Or does our understanding increase markedly if insights from many disciplines

are integrated? Economic growth must, in the first instance, involve an increase in the resources devoted

to production—broadly, labor, capital, and natural resources (including land itself)—and/or the productivity

with which these resources are combined to produce output. These four variables—labor, capital, natural

resources, and productivity—are commonly termed the proximate causes of growth, and economists (and

economic historians, who are treated as a separate discipline here) dominate the study of the question

of which of these is most important in driving particular episodes of economic growth. As we shall see,

economists are far from achieving consensus on this basic question. Moreover, economists have long

appreciated that this question then invites a more complicated set of questions, such as the following:

• Why is labor more skilled in some countries than in others?

• Why is there more (saving and) investment in some countries than in others?

• Why do some countries use resources more productively than do others?

• Why is productivity higher in some countries than in others?

These questions tend naturally to invite interdisciplinary speculation. How does a society's culture or social

structure or politics influence its educational attainment, work effort, saving rate, or environmental policy? The

study of these deeper causal influences is pursued across the human sciences (see below).

Special mention should be made here of institutions and technology. The formal rules of a society—its

legal system, economic regulations, firm structure, and so on—have a profound influence on its economic

performance, and yet such institutions arguably (see below) emerge from a historical process involving

political, social, and cultural influences. Likewise, technological innovation is an important source of (at least

modern) economic growth, and again, it seems likely that the rate of innovation in a society may well be

influenced by a host of non-economic factors.

Even the statistical analyses of economists point toward interdisciplinary analysis. Political, institutional, and

social variables are often found to be important in cross-country analyses of postwar growth experience

(Snowdon, 2002, pp. 97–99)—and this despite the twin facts that such variables are often hard to measure

and likely exert their effects over a very long time. Surveying this evidence and the widely divergent growth

experiences of postwar economies more generally, Snowdon concludes:

To understand why some countries have performed so much better than others with respect to

growth it is therefore necessary to go beyond the proximate causes of growth and delve into the

wider fundamental determinants. This implies that we cannot hope to find the magic bullet by

economic analysis alone. (p. 100)

The observation that it is crucial to look beyond proximate causes provides an important insight regarding

interdisciplinary research more generally. Economists have, until recently, been able to view the causes of

economic growth as a strictly disciplinary question by looking only at the interaction of a handful of economic

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variables. Interdisciplinarians need to be sensitive to the precise wording of their focus question (and be

prepared to revise it as they perform later steps), in order to ensure that relevant disciplines are not arbitrarily

excluded from examination. Even though we are striving to explain movements in an economic variable, our

question becomes interdisciplinary once we embrace a wide range of potential causes.

Identifying Relevant Phenomena, Theories, Methods, and Disciplines

The next step or steps must involve the gathering of relevant disciplinary insights. How does the researcher

know where to look? There are two complementary strategies identified in Repko (2008). One is to reflect

on the character of different disciplines and identify those that are likely to have something to say about the

issue of concern. The second—and the one pursued in this chapter—is to ask what phenomena, theories, or

methods are implicated, and then ask which disciplines study each phenomenon identified and/or apply each

theory or method. This approach reduces the risk of favoring the larger and most familiar disciplines (Szostak,

2002). Szostak (2004) develops exhaustive classifications of phenomena, theory types, and methods to

facilitate the latter approach: In the absence of these, it is all too easy to assume that the subset of relevant

theory, method, or phenomena pursued by disciplines is somehow appropriate. Repko (2008) identifies the

defining elements of disciplines in terms of these and other classifications. One challenge the interdisciplinary

researcher will face is that library catalogues are organized by disciplines, and different terminology is used

in different disciplines to refer to the same phenomenon, theory, or method (Szostak [2007, 2008] addresses

how a classification suited to interdisciplinarity might be developed).

In the case of growth, it is embarrassingly easy to identify phenomena that, at least potentially, influence

growth but lie outside the (at least until recently) narrow gaze of economists. These include cultural attitudes,

political institutions, geographic constraints, and ethnic tensions, among others. It is thus straightforward to

implicate (parts of) all social science disciplines as well as the humanities in this study.

As for types of theories, economists rely almost exclusively on methodological individualism: Only individuals

are causal agents. Yet, surely the alternatives of relationship or group agency2 matter for at least some of the

proximate causes of growth. Historians have long since abandoned the idea of the heroic innovator working

in isolation in favor of an appreciation of the networks in which innovators operate; the same logic applies

to entrepreneurship and trade more generally, and surely institutional change cannot be fully appreciated

without recourse to relationships and groups.

Economists also stress rational decision making. Yet, the history of institutional change suggests that

rationality likely plays some role in institutional design—agents consciously design institutional

improvements—but also that tradition does—agents are cautious in moving away from existing institutions.

Historians of both science and technology have long appreciated that a mix of reason and intuition is

involved: The investigator consciously gathers relevant information, but insight comes subconsciously as

novel connections are drawn. Moreover, in a world awash in information, who can doubt that economic

agents often follow decision-making rules (“Buy when the market is rising”) rather than attempt rational

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calculations? Perhaps most important, both investment and innovation decisions must be made under

uncertainty—people simply cannot know the likelihood of particular outcomes—and people cannot fully rely

on rational decision making when faced with uncertainty (as economic theory admits), but necessarily follow

hunches or decision rules or mimic others. Various sorts of nonrational decision making have long been

studied outside economics, especially in sociology. Psychologists have long argued for different types of

decision making; brain imaging shows that different parts of the brain are activated at different times and

make decisions in different ways (Cohen, 2005).

Economists model growth solely in terms of steady-state (constant) growth rates. Yet, growth occurred in the

West much more rapidly in the 19th century than ever before and more rapidly in the first postwar decades

than before or since. In both the 19th and 20th centuries, one can discern multiple periods of a decade

or so in length in which growth was relatively slow (by the standards of those centuries) or negative. The

growth experience of other regions of the world is even more diverse. These diverse experiences suggest

that theories with either cyclical or stochastic elements—allowing growth rates to both rise and fall—should be

important. The fact that growth rates are, at least potentially, much higher than a mere two centuries ago (or

alternatively, common prognostications that growth will soon decline) suggests that theories positing dynamic

change in one direction may also have a role to play.

Various theories more commonly employed outside rather than within economics are thus important in

understanding economic growth (though each of these has its own limitations). Alternative theories worth

exploring include the following:

• Evolutionary theory can potentially embrace all types of agency, decision making, and time path.

• Systems theories (or structuralism/functionalism more generally) can also reflect a variety of types

of agency and decision making. In practice, systems theorists have tended to emphasize system

stability (equilibrium) and thus have had less to say than they might about dynamic processes of

change.

• Social constructionist theories stress the importance of attitudes and beliefs. This provides a useful

complement to the focus of most social science theory on actions, though social constructivists often

see their theories as substitute rather than complement.

• Modernization theories in the early postwar period posited that all countries would move toward

“Western” economic, political, and cultural realizations. These gave way to more pessimistic

dependency and world systems theories (inspired in part by Marxian analysis) that suggested that

poor countries would remain poor. These theories can each be valued for detailing possible links

among economic, political, cultural, and other phenomena without adopting their assumptions about

the inevitable outcome of these systems of interaction.

• Complexity theories can generate all types of time path. They are perhaps particularly valuable

in stressing stochastic outcomes. Complexity theories often emphasize system-level emergent

properties at the expense of careful specification of individual causal links.

• Various theories stress how culture shapes behavior. These theories are often characterized by

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vague terminology and fail to appreciate how cultures evolve.

• Psychological theories support the insight that decision making is not always rational, but these

theories have not often been carefully applied to economic decisions. (The emerging field of

behavioral economics aspires to change this.)

• Literary theory may also be useful. In studying technological diffusion, scholars have long

appreciated that people, not just blueprints, generally have to move from one locale to another.

There is a range of tacit knowledge that is imperfectly captured by the most careful instructions.

This observation is the same as that long made by theories of texts in general: There is always a

divergence between the textual signifier and that which it is presumed to signify.

A similar analysis could be performed with respect to research method. One of the key insights of Szostak

(2004) was that each method is better at investigating some theory types than others, and disciplines

thus choose mutually compatible sets of theory and method (and phenomena). Various case study

methods—observation, textual analysis, interviews—are better suited to the investigation of many of the

theories listed above than are the statistical analyses favored by economists. Moreover, different methods

shed different light on different theories: We should have the greatest confidence in a theory that is supported

by different methods. When examining a complex historical process such as economic growth, which involves

many causal interactions, recourse to multiple methods is particularly important.

There are four criteria for identifying a causal relationship: establishing correlation, establishing temporality

(the cause should generally appear before the effect), ruling out alternative explanations of the result, and

showing how the causal relationship unfolds in practice (including identifying intermediate variables; Singleton

& Strait, 1999). The methods of economists excel with respect to the first two. Their lack of attention to

alternative theories limits the third. With respect to the fourth, economists are often attracted to mathematical

models even when the evidence for particular causal relationships is quite limited. The latest type of economic

growth models—called unified growth models—attempts to model the course of economic performance over

the last millennium. These models posit that small changes (in the first models, changes in population density,

but later models treat other variables) eventually surpass some threshold where they begin to have dynamic

effects on growth. But of course, one can develop mathematical models such that any cause can have any

effect, if one assumes that small changes achieve big results. The creation of these models should not

enhance one's confidence in such a relationship in the absence of careful case study evidence.

Disciplinary perspectives will be treated briefly here. As both Szostak (2003) and Repko (2008) have

stressed, preferences with respect to theory and method and phenomena are critical components of

disciplinary perspective. Ideological, ethical, and epistemological predispositions need also to be appreciated

in evaluating disciplinary insights. In these latter respects, the following can be noted:

• On average, economists believe in markets more than other social scientists do. Although economic

theory suggests a variety of market imperfections that may arise, the average economist may,

nevertheless, tend to downplay the role of governments in the process of economic growth. In turn,

other disciplines may underestimate the role of markets in fostering growth.

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• Economists are generally consequentialist in ethical orientation, while other disciplines place greater

emphasis on tradition, virtue, or intuition. Economists in particular tend to think that economic growth

is good, while scholars in other disciplines are more likely to critique at least some elements of

growth. Although questions regarding the desirability of growth can be distinguished from questions

about causes, thoughts about one naturally influence thoughts about the other.

• Economists tend to be realists and assume that scholars can obtain reasonably accurate

understandings of a fixed external reality. Other disciplines, especially in the humanities, cast

a useful, if often exaggerated, skepticism on the possibility of human understanding. They thus

encourage scholars to be more careful in both their theorizing and policy advice. In particular, these

other disciplines are suspicious of broad generalizations and encourage careful context-dependent

research.

The preceding analysis has illustrated the following points regarding these steps in interdisciplinary analysis:

• Interdisciplinarians should be careful of curtailing the scope of their research unwittingly by following

major currents in the existing literature. In the case of economic growth, which other disciplines have

rarely stressed as a topic, it is particularly likely that scholars may produce valuable insights that are

relatively unheralded within their own discipline.

• Nevertheless, interdisciplinarians can usefully focus on particular disciplinary subfields. The danger

of missing relevant literature will be reduced if they also reflect on what theories and methods might

be relevant to the issue at hand.

• Interdisciplinarians must evaluate disciplinary insights in the context of disciplinary perspective and

with attention to the (complementary) strengths and weaknesses of different theory types and

methods.

Evaluating Disciplinary Insights

The interdisciplinary researcher must next evaluate the disciplinary insights generated by the relevant

theories and methods. This is an exercise in critical thinking. Interdisciplinarians must know how to distinguish

argument from assertion and assumption from evidence. In addition to standard strategies for the critical

analysis of any text, interdisciplinary analysis suggests several important strategies for critique:

• In what ways might a particular disciplinary insight be shaped by the particular “perspective” of that

discipline?

• More concretely, how might the insight be altered if the researcher(s) had examined a wider set of

phenomena?

• Likewise, what are the strengths and weaknesses of the theories and methods used by the discipline,

and how might the insight in question be shaped by these?

• Do the insights of one discipline point to possible weaknesses in the insights of another? Insights

from outside the academy can also be quite useful here.

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The analysis of the causes of economic growth provides examples of each of these evaluative strategies. As

we have seen, economists are likely to stress the role of individuals and rationality and may thus overlook the

actions of groups and/or various types of nonrational behavior. Economists have focused on a narrow set of

economic variables while downplaying the importance of, for example, culture. Economists stress equilibrium

or steady-state outcomes in their modeling exercises (in large part because this makes the math more

tractable, but also because of the emphasis of economists' general equilibrium theory on system stability);

in the real world, of course, growth has never been steady. Economic historians, sociologists, and political

scientists often stress that different countries have differing experiences of economic growth; this provides a

useful counterpoint to the economist tendency to identify central tendencies.

The interdisciplinarian can be heartened by the observation that other disciplines avoid at least some of these

biases in economic analysis. Yet, the interdisciplinarian should never forget that all disciplines have limiting

perspectives:

• The other social sciences have long stressed group or relationship agency (or viewed individuals as

constrained to act in a certain way by culture or institutions), without detailing how these constraints

emerge. In sociology, this approach has, in recent decades, been supplemented by individual-level

analysis, but syntheses of these approaches are rare. The interdisciplinarian must be prepared to

integrate insights that have rarely been juxtaposed in the past.

• Various sorts of nonrational behavior have been investigated in sociology and other social sciences.

As in economics, particular types of decision making are often assumed rather than established

empirically. The interdisciplinarian must thus be prepared to reflect on what sorts of decision making

motivate people in particular situations. This task is made more difficult by the fact that these are

often mixed in practice: An investor may only act if gut instinct, rational calculation, and the actions

of others all point in the same direction. The analyses of many social scientists present a further

challenge: They celebrate the “irrationality” of certain behaviors without carefully identifying what sort

of nonrational decision making is at work.

• The social sciences (including psychology) collectively employ each of the dozen methods utilized

in the scholarly enterprise. Yet, each of these is applied to only a subset of appropriate questions.

The interdisciplinarian, aware of the biases of one method, may look in vain for the application

of alternative methods to particular questions. For the present inquiry, this problem—of difficulty in

identifying work that applies different methods to the same question—is exacerbated by the fact that

scholars in other disciplines have rarely addressed economic growth itself.

• Other social sciences often assume processes involving sustained change in particular directions,

just as economists assume equilibrium outcomes. The important possibility of stochastic

(unpredictable) outcomes is much less commonly explored. The growth process likely entails

elements of each. Investment decisions at times seem to follow herd behavior and at times seem

inexplicable, and yet there is an amazing stability (lack of volatility) in average rates of return over

time. As with types of decision making, the interdisciplinarian generally has recourse to few previous

attempts to integrate insights reflecting these different perspectives.

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• Political scientists and sociologists often assume