Working Paper

The Era of Evidence

1
The Era of Empirical Evidence
Brandon D. Brice
*
, Hugo M. Montesinos-Yufa
Abstract
We document a dramatic methodological shift in the economics profession. By
text mining the titles of the 500 most-cited titles in economics’ top journals, by
decade since the 1950s, we provide evidence for a shift away from advancing
and testing theory, and towards a profession that is directed by the provision of
empirical evidence. We provide a simple model to explain this methodological
shift through changes in relative costs of producing theoretical and empirical
research, in which innovative advancements in computing technology and data
accessibility since the 1990s play a significant role.
Key words: History of Economic Thought, Economic Methodology, Word Clouds
JEL codes: B20, B41, Y10
*
Brice: Department of Economics and Finance, Cameron School of Business, University of North Carolina
Wilmington, Wilmington NC 28412, USA. briceb@uncw.edu.
Montesinos-Yufa: Department of Mathematics and Computer Science, Ursinus College, Collegeville PA 19426,
USA. hmontesinosyufa@ursinus.edu .
We would like to thank Randall G. Holcombe for his helpful comments.
2
I. Introduction
In 1947, Paul Samuelson wrote Foundations of Economic Analysis. This influential work
formalized a theoretical structure for economics by providing a mathematical framework for
constrained optimization and its implications for human action (Dixit, 2012). This approach to the
discipline influenced teaching and research in the discipline for the decades to come. Much of the
reason for this framework’s success was Samuelson’s Economics text, which was first published
the following year. This revolutionized economic instruction, which because of his influence
began increasingly to focus on formalized theoretical structures to investigate economic questions.
The education of generations of economists to follow were rooted in these lessons
3
.
This formalization coincided with the postwar expansion of economics and journal
publications in the American Economic Review (AER), as documented by Margo (2011) in his
Economic History of the American Economic Review. Early in the Samuelson era, researchers in
economics’ top journals focused on rigorously creating, and creatively testing, economic theory.
With the passage of time, the profession drifted away from theoretical models to give more
emphasis to applied work, resulting in a profession dominated by the provision of empirical
evidence. Biddle and Hamermesh (2017) document this as a movement away from consensus,
where the discipline focused on optimization and equilibrium, and towards a focus on applied work
in an experimentalist paradigm. This implies a subtle, yet major, shift in how economists see their
contributions. We contribute to this literature by providing a simple model for this shift based on
the relative costs of conducting each type of research. We then provide evidence consistent with
this shift utilizing bibliometric techniques on the most-cited articles in three of economics top
3
Both directly through students such as Diamond, Krugman, and Stiglitz; and indirectly through the thousands of
students that utilized his text.
3
journals; AER, Quarterly Journal of Economics (QJE), and Journal of Political Economy (JPE);
by decade since the 1950s. We create word clouds from the most utilized words in the titles of the
500 most-cited papers of these journals for each decade. To complement this analysis, we also
provide the number of pages, equations, figures, regressions, tables, appendices, and citations for
the five most cited articles in the AER, by decade, and the most cited article in the JPE and QJE.
See the Appendix for this analysis, which supports the methodological trends documented in the
body of this paper.
We are not the first to note or to acknowledge this shift. For example, Card, DellaVigna,
and Malmendier (2011) document that over 68 percent of field experiments in five top economic
journals from 1975 to 2010 are descriptive studies lacking any explicit model. Margo (2011) states
that much of the change in the economic profession reflects the growing use of mathematics and
statistics in economic analysis. Card and DellaVigna (2013), Hamermesh (2013), and Margo
(2011) also provide insightful evidence on how the profession has changed in multiple dimensions
including the number and type of submissions, acceptance rates, length of the articles, number of
authors, utilization of data, and citations. These papers, however, do not provide an analysis of the
fundamental methodological change in the profession or a framework to understand it. This paper
provides evidence for a major systematic methodological shift in the profession by applying
bibliometric techniques to economics most-cited publications, and provides a formal model to
assist in our understanding for why this shift has occurred. We also provide insight into the major
focus of economic research, for each decade since the 1950s.
Additionally, our paper informs a growing body of literature on the history of economic
thought, and the history of economic methodology. This existing literature outlines how the field
has developed (Backhouse 2008), how it has become more applied (Hamermesh 2013, Backhouse
4
and Cherrier 2014, Biddle and Hamermesh 2017). Our paper also informs a growing literature on
bibliometric methods. For example, Ambrosino et al. (2017) use the Latent Dirichlet Allocation
method to assess the prevalence of topics in economic publications, but does not address the
methodology used in economic publications, or its prevalence over time.
By understanding how the topics, and methodology, evolved in the most-cited articles from
economics’ top journals since 1950; we provide strong evidence for how the focus of the discipline
has progressed. Additionally, we provide insight for the future direction of the discipline.
Organization for the rest of the paper is as follows: Section II provides a simple model for
economic research tradeoffs. Section III provides a bibliometric analysis of the most-cited articles
in the AER, QJE, and JPE by decade; providing evidence for how empirical research trends have
evolved in the profession. Section IV provides further discussion and acknowledges potential
limitations of the analysis. Section V provides a brief survey of emerging data sources and its
applications as the focus of the discipline becomes more empirical. Section VI concludes the
paper.
5
II. A Simple Model for Economic Research Tradeoffs
To assist in our understanding of why the economics profession has shifted away from
the creation of pure theory and towards empirical analysis, we consider a researcher solving the
following maximization problem:
      (1)
where is a measure of the knowledge created, or the importance of the research in terms
of advancing a new theory or testing an existing theory. is a measure of the evidence provided
consistent with the previous theory. and represent the time spent on each activity, and
represents the total impact of the research conducted. The first order conditions imply:
 
(2)
This implies that there is a tradeoff between creating new theory and providing evidence
for existing theory, and the optimal allocation depends on the relative costs of doing each
activity
 .
4
With advancements in computing technology and data accessibility in recent
decades, the relative cost of performing empirical techniques, conducive to evidence provision,
has declined. Consequently, the optimal time allocation shifts towards providing evidence for
existing theories rather than advancing new knowledge. Researchers, thus, optimize by utilizing
more of their scarce time for empirical research and experimentation as advancements occur in
data collection, availability, software, and empirical techniques.
4
This tradeoff exists regardless of the functional form of utility function , as long as minimal conditions are satisfied.
A necessary condition is that the first derivatives and exist. A sufficient condition is that is twice differentiable
and strictly quasi-concave.
6
III. Research Trends
Utilizing the bibliometric technique of text mining, we search the titles of the 500 most-
cited journal articles in the AER, JPE, and QJE from each decade since 1950; to see which words
are most commonly used. This informs our analysis by providing insight into the focus and
methodology in top-ranked journals in economics during these decades. We create word clouds
for each decade to help visualize the most important topics and emerging trends.
1950s
The most common words in the titles of the most-cited articles from the 1950s were
economic’, ‘theory, growth, income, and development. See Figure 1: Panel A. The use of
these words suggests a profession dominated by theoretical contributions and their implications.
Testing economic theory was the major focus in the discipline’s most influential articles from this
decade. Even the most-cited article in the AER is titled, “Theories of Decision-Making in
Economics, and Behavioral-Science” by Herbert A. Simon (1959). Theories specifically
pertaining to growth, income, and development were widely tested. These articles most notably
include “A Contribution to the Theory of Economic-Growth” by Robert M. Solow (1956), which
tested the knife-edge assumption in the Harrod-Domar Growth Model, and provided a new
theoretical framework incorporating the substitution of capital and labor.
1960s
The most utilized word in the 1960s was theory; followed by economic, investment,
growth, and capital. See Figure 1: Panel B. Again, the focus of this decade was economic
theory. Economic growth theory remains an important topic, with a focus on investment and
capital accumulation. “Toward a Theory of Property Rights” by Harold Demsetz (1967) described
7
the theoretical importance of institutions for growth by internalizing externalities. “National Debt
in a Neoclassical Growth Model” by Peter A Diamond (1965) identified the mechanisms through
which debt reduces capital stocks. “International Investment and International Trade in the
Product Cycle” by Raymond Vernon (1966) tested the Heckscher-Ohlin international trade model
and introduced a new model for dynamic comparative advantage. All of these highly cited articles
relate to this continued focus.
1970s
Again, theory is the most utilized word in the 1970s. See Figure 1: Panel C. This
demonstrates consistency in the most cited-papers from the 1950s through the 1970s, in economics
top journals. While the primary topics shifted, a focus on testing theory is consistently present.
The other most utilized words are model, market, income, economic, and analysisas
economic modeling climbs in importance. There is also a rejuvenation in the analysis of income,
and an emerging interest in market analysis in the profession. “Market for Lemons Quality
Uncertainty and Market Mechanism” by George A. Akerlof (1970) is an example of a highly cited
article in this area.
1980s
For the first time in this analysis, theory falls to the third most utilized word in these titles.
See Figure 1: Panel D. The word ‘market is now number one, after climbing to number three in
the previous decade. This suggests a subtle shift in the profession with a growing interest in market
analysis. Again, model is the second most used word, representing the continued importance of
modeling in the profession. The words ‘economic and price are the fifth and sixth most utilized.
“Agency Costs of Free Cash Flow, Corporate-Finance, and Takeovers” by Michael C. Jensen
8
(1986) is the most-cited article in the AER from this decade, and illuminates the frictions between
managers and shareholders, particularly in companies with free cash flows, in the market.
1990s
Growth analysis has a resurgence in the 1990s with many of the most-cited articles
investigating this topic. For instance, A Sensitivity Analysis of Cross-Country Growth
Regressions” by Ross Levine and David Renelt (1992) is the most-cited article from the AER from
this decade, and “Economic Growth in a Cross-Section of Countries” by Robert J. Barro (1991) is
the most-cited work in the QJE. Given the focus on economic growth during this decade, it is no
surprise that growth is the most utilized word in these titles. See Figure 2: Panel A. The word
‘theory falls to fifth and modeling falls to sixth, while evidence’ appears for the first time as it
moves into third on the list. The other top words in the 1990s are economic and market,
consistent with the continued focus on market analysis since the 1970s.
2000s
In the 2000s, evidence becomes the most utilized word in the titles of economics’ top
journal articles. See Figure 2: Panel B. This corresponds with a dramatic shift in methodology, as
theory and model fall to fifth and sixth on this list. The most cited articles in economics’ top
journals were beginning to focus heavily on the provision of empirical evidence in the 2000s. This
is consistent with the findings of Biddle and Hamermesh (2017) which document a partial
abandonment of economic theory in applied work beginning in the late 1990s.
Daron Acemoglu et al. actually have highly-cited articles in all three journals (AER, JPE,
and QJE) during this decade; making use of advanced empirical methods while helping to establish
9
a new focus on institutional analysis. “The Colonial Origins of Comparative Development: An
Empirical Investigation” (2001) is the most-cited article in the AER. “Unbundling Institutions”
(2005) was one of the most-cited articles in the JPE, and “Reversal of Fortune: Geography and
Institutions in the Making of the Modern World Income Distribution” (2002) was one of the most
cited in the QJE. All of these articles make use of empirical methodology, cross-country
regression, and two stage least-squared approaches in an attempt to identify causal parameters in
structural equations.
While these papers by Acemoglu et.al. highlight the continued push towards empirical
analysis in the discipline, the most-cited paper in the QJE during this decade calls for caution when
employing a particular type of empirical analysis. “How Much Should We Trust Differences-in-
Differences Estimates?” by Marianne Bertrand, Esther Duflo, and Sendhil Mullainathan (2004)
reflects the concern in the profession for the increasing reliance on empirics, and the pursuit of
providing non-theoretical evidence in economics.
2010s
During the 2010s, almost one in five of the 500 most-cited papers in the profession contains
the word evidencein its title. ‘Evidence’ appears significantly more frequently than any other
word, in each prior decade, in our analysis. See Figure 2: Panel C. The words ‘trade, risk,
experiment, effects, and economic round out the list. Words that commonly appeared in other
decades such as market, growth, and theory no longer make the list. This provides evidence
that by this decade economists largely see themselves as providing evidence, rather than creating
or testing theory, and that they value the research of others who provide evidence over articles that
create pure theory.
10
1950 2015
Even though the word ‘evidence’ first appeared in our analysis in the 1990s, ‘economic’
and ‘evidence’ are by far the most utilized words when pooling and investigating the titles from
all decades. This is because the profession had a tremendous and noticeable shift away from
creating theory and towards providing evidence beginning in the 1990s. See Figure 2: Panel D.
11
IV. Discussion and Limitations
The analysis in Section III provides evidence consistent with our model, indicating that the
trade-off between advancing knowledge (creating new ways of thinking, new theories, new
models, or falsifying existing theories) and providing evidence for already existing theories is
leaning significantly toward the latter in recent years. The explanation suggested by our model lies
in the reduction in relative costs of performing applied work, relative to theoretical research, over
time. This fits with the existing literature that identifies a contemporary trend in economic
research, which is becoming more applied.
While our analysis is intensive, we recognize that is limited in several dimensions. Field
journals publish applied and theoretically specialized work. A more comprehensive analysis could
include a detailed examination of the methodological shift in field journals. We chose not to
include this analysis for brevity, and because a focus on top general-interest journals better informs
our understanding of the general direction of the discipline. A focus on the AER, QJE, and JPE
achieves these goals. Therefore, we limit our scope to these three top economic journals.
A second limitation is that a focus on the 500 most-cited papers in these journals inevitably
omits crucial papers in the profession published in other journals. For example, we exclude highly
cited works such as "The Problem of Social Cost" by Ronald Coase, published in the Journal of
Law and Economics in 1960, when we limit our focus to other journals. Although we regret not
including such articles, providing such articles in an ad-hoc manner could be misleading and bias
our analysis, as our own prior knowledge of the literature could influence the results of our
bibliometric analysis. We therefore adhere to the original focus on highly cited articles in
12
economics top journals, and address our research question scientifically acknowledging that some
important papers may inevitably fall outside scope of our study.
Third, we text mine the titles, not the full-texts, of the 500 most-cited papers by decade.
This approach has benefits and drawbacks. On one hand, the titles are short, efficient, and
representative of their papers. They also tend not to have duplicate words. On the other, titles may
capture systematic trends among economists not reflected in the body of the paper. To minimize
this concern, we perform two separate analyses. In one, we carefully read the full text of the five
most-cited papers by decade in the AER, and the most-cited articles in the JPE and QJE by decade.
We tabulated the number of equations, regressions, tables, figures, theorems, proofs, and
mathematical appendices. These results are available in the appendix of this paper. In the second,
we text mined the abstracts of the 500 most cited papers in these journals by decade. These results
are available upon request. In both analyses, the results corroborated our primary findings that
research in top journals became more empirical, and less theoretical, over time.
13
V. A Brief Survey of Emerging Data Sources and Applications
Corresponding with economics’ methodological shift towards the provision of evidence
and empirical analysis, which began in the 1990s, are increases in the collection and utilization of
data. In particular, we witness the emergence and analysis of “big data”. These massive datasets
are a consequence of the same phenomena that has led to increases in sophisticated empirical
analysis, and advancements in computing power and memory. Below we outline a few of the
currently available big data sources, highlight how economists have begun utilizing this data,
identify analytical problems that these sources can help overcome, and provide a road-map for the
future of the economics profession which we anticipate will increase its analysis and utilization of
these types of data sources.
Nothing may highlight the amazing possibilities of the big data revolution in economics
more than the recent use of satellite imagery in empirical research. This type of data collection
and analysis certainly was not available in Samuelson’s era, and showcases the potential of modern
technology to display and collect massive amounts of data from very sophisticated sources.
Maxim L. Pinkovskiy and Xavier Sala-i-Martin (2016) use data associated with satellite imagery
of artificial lighting, whose error is likely independent of measurement error, to evaluate existing
economic activity measures. Remarkably, this analysis concluded that unadjusted GDP growth
predicts true income better than series based on purchasing power parity (PPP) adjustments. This
is a conclusion that would have been difficult, if not impossible, to evaluate without the emergence
of this contemporary big data source. In a more recent publication, the same authors, along with
Hunter Clark, overcome historically unreliable data sources to analyze China’s true GDP growth
rate using satellite imagery (Clark et. al, 2017). The possibilities to utilize satellite data seem
14
endless when you consider that this data contains information not just on lights; but also on
variables such as heat, wave activity, and weather.
In Section III, we demonstrate that prices were a major focus in economics’ top journals
beginning in the 1970s. Prices even cracked the top five most utilized words in our journal analysis
in the 1980s. It is unlikely that the authors of these highly cited articles ever could have imagined
having access to data on over fifteen million products, from over 900 retailers, in over sixty
countries updated daily. Remarkably, today this data is publically available thanks to the Billion
Prices Project. This big data project utilizes advances in automated software to scrape millions of
online prices in real time. This overcomes the problems associated with historically expensive,
complex, and slow price collection procedures to provide more reliable, larger, and faster price
data for research investigating topics such as inflation (Cavallo and Rigobon, 2016).
Other venues, which we are all familiar with, also generate big data. For instance
Facebook, which has over one billion users logging in daily, provides huge amounts of data about
its users in their Graph API. Many large facial recognition databases exist, and along with it the
endless possibilities for its analytical uses. Google searches, student performance, songs, health,
genetics, and government data are just several of the many big datasets that are appearing for use
in the era of empirical evidence.
In 2015, Bernard Marr wrote that in the previous two years alone more data was generated
than in all of the previous years in human history.
5
With this data explosion expected to continue,
we anticipate that the economic profession will become even more focused on the provision of
evidence and empirical analysis of new, larger, and better data sources. While this revolution and
5
See Bernard Marr’s Forbes article (September, 2015). His books include Big Data in Practice, Big Data, Key Business
Analytics, and Key Performance Indicators.
15
its future economic contributions are certain to provide important insights into human behavior, it
is important for economists to ensure that the data they decide to analyze (out of the immense
number of emerging data sources) are reputable and reliable. It is more important than ever to
ensure that the analytical strategies we use to investigate these data are the correct ones; and that
the conclusions we draw as economists for businesses, the public, and governments are sound and
reserved.
16
VI. Conclusion
Bibliometric analysis of the titles of the 500 most-cited articles in three of economics’ top
journals uncovers a rapid methodological shift in the profession that began in the 1990s. Before
this, economists focused on creatively testing and advancing economic theory. By the 1990s, a
revolution was taking place where economists began to see their role as providers of evidence.
This corresponds with a massive shift in computing power, and technological innovation, that
concurrently occurred in the 1990s; which likely explains the widespread use of empirical
techniques. This shift was not due to the predictions or calls of any particular economist, but rather
from a spontaneous process in how economists saw their role in the profession, and aided by
technological advances that were not previously available. Since the 1990s, there now appears to
be a growing expectation for rigorous empirical analysis in order to publish in these top journals.
To better visualize this shift in economic publications, we form word clouds from the most
commonly used words in the 500 most-cited articles from the AER, JPE, and QJE for each decade
since the 1950s. From the 1950s through the 1970s, testing economic theory was the major focus
of highly cited research in these journals. Theoretical analysis of many topics such as growth,
income, capital, investment, and markets appear in our results. This theoretical analysis began to
focus on markets more broadly in the 1980s.
In the 1990s, economic growth research dominated the profession, while there were
emerging signs of evidence provision starting to play an important role. By the 2000s, evidence
was the most used word in the titles of the most-cited articles and the methodological approaches
in the profession were shifting. By the 2010s, the word ‘evidence is in almost one in every five
17
titles. A search for evidence is what the economics profession has become, and we expect
continued focus on empirical analysis long into the future.
Corresponding with the shift towards empirical analysis and a search for evidence was the
emergence of big data sources. Along with advances in data availability come new methods to
analyze the data, new protocols to collect it, and new ways to understand the world. Empirical
evidence allows us to measure and test hypotheses that otherwise had not been possible, expanding
the knowledge frontier. The changes and implications that this exponential trend has had, and will
continue to have, on the economic profession are dramatic. We are currently witnessing many of
those changes. Records of satellite imagery, the Billion Price Project, biological and genome data,
political surveys, social media data, and web searches are just a few examples of big data sources
that economic researchers utilize today.
In order to document the methodological evolution in the profession since the 1950s, we
amusingly use a computer intensive technique and a large data source that was not available
decades ago. This research fits with the growing methodological trend that we identify. We are
in an era of change, the era of evidence. Understanding and adapting to this change is paramount
for understanding the future of our discipline, and ensuring the “evidence” we provide is justifiable
and sound will be of ever-increasing importance.
18
Figure 1: Most Utilized Words in the Titles of the 500 Most-Cited Articles in the
AER, JPE, and QJE by Decade
Panel A: 1950s (1950-1959) Panel B: 1960s (1960-1969)
Panel C: 1970s (1970-1979) Panel D: 1980s (1980-1989)
Based on the titles of the 500 most cited articles in the AER, JPE and QJE.
Source: Thomson Reuters Web of Science.
19
Figure 2: Most Utilized Words in the Titles of the 500 Most-Cited Articles in the
AER, JPE, and QJE by Decade
Panel A: 1990s (1990-1999) Panel B: 2000s (2000-2009)
Panel C: 2010s (2010-2015) Panel D: All Decades (1950-2015)
Based on the titles of the 500 most cited articles in the AER, JPE and QJE.
Source: Thomson Reuters Web of Science.
20
Appendix: The five most cited papers in the AER, by decade. From 1950 to 2015.
Panel A: 1950s
Title
Authors
Year
Volume
Issue
#Pages
#Equations
#Figures
#Regressions
#Tables
#Appendices
Cites
Cites/year
The Cost Of Capital,
Corporation Finance
And The Theory Of
Investment
Modigliani
, F; Miller,
M
1958
48
3
36
34
6
4
4
0
2524
43.52
Theories Of Decision-
Making In Economics
And Behavioral-
Science
Simon, Ha
1959
49
3
30
0
0
0
0
0
728
12.77
Distribution Of
Incomes Of
Corporations Among
Dividends, Retained
Earnings, And Taxes
Lintner, J
1956
46
2
21
2
0
1
1
0
543
9.05
International-Trade
And Factor Mobility
Mundell,
Ra
1957
47
3
14
0
4
0
0
0
401
6.8
The Size Distribution
Of Business Firms
Simon,
Ha;
Bonini, Cp
1958
48
4
10
3
0
0
2
0
329
5.67
A Pure Theory Of
Local Expenditures
Tiebout,
Cm
1956
64
5
8
0
0
0
0
0
3549
59.17
A Contribution To
The Theory Of
Economic-Growth
Solow,
Rm
1956
70
1
29
20
9
0
0
0
3279
54.65
21
Panel B: 1960s
Title
Authors
Journal
Year
Volume
Issue
#Pages
#Equations
#Figures
#Regressions
#Tables
#Appendices
Cites
Cites/year
Uncertainty And The
Welfare Economics
Of Medical-Care
Arrow, Kj
AER
1963
53
5
32
2
0
0
0
1
1618
30.53
Toward A Theory Of
Property Rights
Demsetz,
Harold
AER
1967
57
2
12
0
0
0
0
0
1494
30.57
Role Of Monetary
Policy
Friedman,
Milton
AER
1968
58
1
16
0
0
0
0
0
1382
28.79
National Debt In A
Neoclassical Growth-
Model
Diamond,
Pa
AER
1965
55
5
24
38
8
0
0
2
993
19.47
Allocative Efficiency
Vs X-Efficiency
Leibenstei
n, H
AER
1966
56
3
23
0
4
0
2
0
968
19.36
Crime And
Punishment -
Economic Approach
Becker,
Gs
JPE
1968
76
2
48
55
4
0
2
1
2989
62.33
International
Investment And
International Trade In
Product Cycle
Vernon,
Raymond
QJE
1966
80
2
17
0
1
0
0
0
1930
38.60
22
Table 1 (Continued): The five most cited papers in the AER, by decade. From 1950 to 2015.
Panel C: 1970s
Title
Authors
Journal
Year
Volume
Issue
#Pages
#Equations
#Figures
#Regressions
#Tables
#Appendices
Cites
Cites/year
Production,
Information
Costs, And
Economic
Organization
Alchian,
Aa;
Demsetz,
H
AER
1972
62
5
18
0
0
0
0
0
3051
69.34
Monopolistic
Competition And
Optimum Product
Diversity
Dixit, Ak;
Stiglitz,
Je
AER
1977
67
3
11
58
4
0
0
0
2135
54.74
Migration,
Unemployment
And
Development - 2-
Sector Analysis
Harris, Jr;
Todaro,
Mp
AER
1970
60
1
16
12
3
0
0
3
1456
31.65
Political
Economy Of The
Rent-Seeking
Society
Krueger,
Ao
AER
1974
64
3
12
19
3
0
1
0
1326
31.57
Money, Income,
And Causality
Sims, Ca
AER
1972
62
4
12
2
2
5
5
1
1128
25.64
Pricing Of
Options And
Corporate
Liabilities
Black, F;
Scholes,
M
JPE
1973
81
3
17
27
1
0
0
0
6737
156.70
Market For
Lemons - Quality
Uncertainty And
Market
Mechanism
Akerlof,
Ga
QJE
1970
84
3
12
10
0
0
2
0
4181
90.89
23
Panel D: 1980s
Title
Authors
Journal
Year
Volume
Issue
#Pages
#Equations
#Figures
#Regressions
#Tables
#Appendices
Cites
Cites/year
Agency Costs Of
Free Cash Flow,
Corporate-
Finance, And
Takeovers
Jensen,
Mc
AER
1986
76
2
6
0
0
0
0
0
3580
119.3
Credit Rationing
In Markets With
Imperfect
Information
Stiglitz,
Je;
Weiss, A
AER
1981
71
3
17
25
10
0
0
0
2352
67.2
Clio And The
Economics Of
Qwerty
David, Pa
AER
1985
75
2
5
0
0
0
0
0
1663
53.65
Network
Externalities,
Competition, And
Compatibility
Katz, Ml;
Shapiro,
C
AER
1985
75
3
16
16
0
0
0
1
1619
52.23
Equilibrium
Unemployment
As A Worker
Discipline Device
Shapiro,
C;
Stiglitz,
Je
AER
1984
74
3
11
12
4
0
0
0
1433
44.78
Increasing
Returns And
Long-Run
Growth
Romer,
Pm
JPE
1986
94
5
35
9
5
0
3
0
3746
124.87
A Theory Of
Competition
Among Pressure
Groups For
Political Influence
Becker,
Gs
QJE
1983
98
3
29
30
2
0
0
1
1446
43.82
24
Table 1 (Continued): The five most cited papers in the AER, by decade. From 1950 to 2015.
Panel E: 1990s
Title
Authors
Journal
Year
Volume
Issue
#Pages
#Equations
#Figures
#Regressions
#Tables
#Appendices
Cites
Cites/year
A Sensitivity
Analysis Of
Cross-Country
Growth
Regressions
Levine, R;
Renelt, D
AER
1992
82
4
21
2
0
10
10
0
1511
62.96
Incorporating
Fairness Into
Game-Theory
And Economics
Rabin, M
AER
1993
83
5
21
0
6
0
0
2
1316
57.22
R&D Spillovers
And The
Geography Of
Innovation And
Production
Audretsch,
D; Feldman,
M
AER
1996
86
3
10
0
1
3
6
0
1281
64.05
Financial
Dependence
And Growth
Rajan, Rg;
Zingales, L
AER
1998
88
3
27
1
1
3
10
0
1157
64.28
Protection For
Sale
Grossman, G;
Helpman, E.
AER
1994
84
4
17
19
3
0
0
0
1043
47.41
Law And
Finance
La Porta, R;
Et. Al.
JPE
1998
106
6
42
0
0
3
8
0
3198
177.67
Economic-
Growth In A
Cross-Section
Of Countries
Barro, Rj
QJE
1991
106
2
36
0
11
6
6
3
2278
91.16
25
Panel F: 2000s
Title
Authors
Journal
Year
Volume
Issue
#Pages
#Equations
#Figures
#Regressions
#Tables
#Appendices
Cites
Cites/year
The Colonial Origins
Of Comparative
Development: An
Empirical
Investigation
Acemoglu, D;
Johnson, S;
Robinson, Ja.
AER
2001
91
5
32
5
0
8
8
3
1823
121.67
Erc: A Theory Of
Equity, Reciprocity,
And Competition
Bolton, Ge;
Ockenfels, A
AER
2000
90
1
27
13
6
0
0
1
1235
77.19
Gravity With
Gravitas: A Solution
To The Border
Puzzle
Anderson, J;
Van Wincoop
AER
2003
93
1
22
26
0
1
6
2
973
74.85
Cooperation And
Punishment In
Public Goods
Experiments
Fehr, E;
Gachter, S
AER
2000
90
4
14
2
3
1
5
0
947
59.19
Risk Aversion And
Incentive Effects
Holt, Ca;
Laury, Sk
AER
2002
92
5
11
3
6
0
4
0
861
61.50
Nominal Rigidities
And The Dynamic
Effects Of A Shock
To Monetary Policy
Christiano, Lj;
Eichenbaum,
M, M; Evans,
Cl
JPE
2005
113
1
44
43
6
1
2
0
1003
91.18
How Much Should
We Trust
Differences-In-
Differences
Estimates?
Bertrand, M;
Duflo, E;
Mullainathan, S
QJE
2004
119
1
26
3
0
7
8
0
1339
111.58
26
Table 1 (Continued): The five most cited papers in the AER, by decade. From 1950 to 2015.
Panel G: 2010s
Title
Authors
Journal
Year
Volume
Issue
#Pages
#Equations
#Figures
#Regressions
#Tables
#Appendices
Cites
Cites/year
Beyond Markets And
States: Polycentric
Governance Of
Complex Economic
Systems
Ostrom, Elinor
AER
2010
100
3
31
2
6
0
0
0
186
31.00
SOCIAL
PREFERENCES,
BELIEFS, AND THE
DYNAMICS OF
FREE RIDING IN
PUBLIC GOODS
EXPERIMENTS
Fischbacher, Urs;
Gachter, Simon
AER
2010
100
1
15
1
2
0
2
0
158
26.33
Learning About A
New Technology:
Pineapple In Ghana
Conley, Timothy;
Udry, Christopher
AER
2010
100
1
34
8
5
7
7
2
151
25.17
Growth In A Time Of
Debt
Reinhart,
Carmen; Rogoff,
Kenneth
AER
2010
100
2
5
0
4
0
1
0
147
24.50
The Macroeconomic
Effects Of Tax
Changes: Estimates
Based On A New
Measure Of Fiscal
Shocks
Romer, Christina;
Romer, David
AER
2010
100
3
38
8
14
0
1
0
133
22.17
When Is The
Government Spending
Multiplier Large?
Christiano,
Lawrence;
Eichenbaum,
Martin; Rebelo,
Sergio
JPE
2011
119
1
43
63
7
0
0
0
104
20.80
Did Securitization
Lead To Lax
Screening? Evidence
From Subprime Loans
Keys, Benjamin
J.; Mukherjee,
Tanmoy; Seru,
Amit; Vig,
Vikrant
QJE
2010
125
1
55
2
13
6
6
4
150
25
*Comprises the period from 2010 to June 1, 2015. Source: Thomson Reuters Web of Science.
27
REFERENCES
Acemoglu, Daron, and Simon Johnson. 2005. "Unbundling Institutions." Journal of Political
Economy 113.5: 949-95.
Acemoglu, Daron, Simon Johnson, and James A. Robinson. 2001. "The Colonial Origins of
Comparative Development: An Empirical Investigation." The American Economic Review
91.5: 1369-401.
––––––. 2002. "Reversal of Fortune: Geography and Institutions in the Making of the Modern
World Income Distribution." The Quarterly Journal of Economics 117.4: 1231-294.
Akerlof, George A. 1970. "The Market for "Lemons": Quality Uncertainty and the Market
Mechanism." The Quarterly Journal of Economics 84.3: 488-500.
Alchian, Armen A., and Harold Demsetz. 1972. "Production, Information Costs, and Economic
Organization." The American Economic Review 62.5: 777-95.
Anderson, James E., and Eric Van Wincoop. 2003. "Gravity with Gravitas: A Solution to the
Border Puzzle." The American Economic Review 93.1: 170-92.
Arrow, Kenneth J. 1963. "Uncertainty and the Welfare Economics of Medical Care." The
American Economic Review 53.5: 941-73.
Audretsch, David B., and Maryann P. Feldman. 1996. "R&D Spillovers and the Geography of
Innovation and Production." The American Economic Review 86.3: 630-40.
Backhouse, Roger E. 2008. Methodology of Economics. In: Palgrave Macmillan (eds) The New
Palgrave Dictionary of Economics. Palgrave Macmillan, London
––––––. 2014. "Revisiting Samuelson's Foundations of Economic Analysis." Journal of Economic
Literature. 53(2): 326-50.
28
Backhouse, Roger E. and Beatrice Cherrier. 2014. "Becoming Applied: The Transformation of
Economics after 1970." The Center for the History of Political Economy Working Paper
Series No. 2014-15.
Barro, Robert J. 1991. "Economic Growth in a Cross Section of Countries." The Quarterly Journal
of Economics 106.2: 407-43.
Becker, Gary S. 1968. "Crime and Punishment: An Economic Approach." Journal of Political
Economy 76.2: 169-217.
––––––. 1983. "A Theory of Competition Among Pressure Groups for Political Influence." The
Quarterly Journal of Economics 98.3: 371-400.
Bertrand, Marianne, Esther Duflo, and Sendhil Mullainathan. 2004. "How Much Should We Trust
Differences-in-Differences Estimates?" The Quarterly Journal of Economics 119.1: 249-
75.
Biddle, Jeff E. and Daniel S. Hamermesh. 2017. "Theory and Measurement: Emergence,
Consolidation and Erosion of Consensus." History of Political Economy 49(Supplement):
34-57.
Black, Fischer, and Myron Scholes. 1973. "The Pricing of Options and Corporate Liabilities."
Journal of Political Economy 81.3: 637-54.
Bolton, Gary E., and Axel Ockenfels. 2000. "ERC: A Theory of Equity, Reciprocity, and
Competition." The American Economic Review 90.1: 166-93.
Card, David, Stefano DellaVigna, and Ulrike Malmendier. 2011. "The role of theory in field
experiments." Journal of Economic Perspectives 25.3: 39-62.
Card, David, and Stefano DellaVigna. "Nine facts about top journals in economics." Journal of
Economic Literature 51, no. 1 (2013): 144-61.
29
Cavallo, Alberto, and Roberto Rigobon. 2016. "The Billion Prices Project: Using Online Prices
for Measurement and Research." Journal of Economic Perspectives Spring Vol 30(2): 151-
78.
Christiano, Lawrence J., Martin Eichenbaum, and Charles L. Evans. 2005. "Nominal Rigidities
and the Dynamic Effects of a Shock to Monetary Policy." Journal of Political Economy
113.1: 1-45.
Christiano, Lawrence, Martin Eichenbaum, and Sergio Rebelo. 2011. "When Is the Government
Spending Multiplier Large?" Journal of Political Economy 119.1: 78-121.
Clark, Hunter, Maxim Pinkovskiy, and Xavier Sala-I-Martin. 2017. "China's GDP Growth May
Be Understated." NBER Working Paper 23323.
Coase, Ronald H. 1960. "The Problem of Social Cost." Journal of Law and Economics October
Vol 3: 1-44.
Conley, Timothy G., and Christopher R. Udry. 2010. "Learning about a New Technology:
Pineapple in Ghana." The American Economic Review 100.1: 35-69.
David, Paul A. 1985. "Clio and the Economics of QWERTY." The American Economic Review
75.2, Papers and Proceedings of the Ninety-Seventh Annual Meeting of the American
Economic Association: 332-37.
Demsetz, Harold. 1967. "Toward a Theory of Property Rights." The American Economic Review
57.2, Papers and Proceedings of the Seventy-ninth Annual Meeting of the American
Economic Association: 347-59.
Diamond, Peter A. 1965. "National Debt in a Neoclassical Growth Model." The American
Economic Review 55.5, Part 1: 1126-150.
30
Dixit, Avinash K., and Joseph E. Stiglitz. 1977. "Monopolistic Competition and Optimum Product
Diversity." The American Economic Review 67.3: 297-308.
Dixit, Avinash K.. 2012. “Paul Samuelson’s Legacy”. Annual Reviews of Economics Vol 4: 1 - 45
Fehr, Ernst, and Simon Gachter. 2000. "Cooperation and Punishment in Public Goods
Experiments." The American Economic Review 90.4: 980-94.
Fischbacher, Urs, and Simon Gachter. 2010. "Social Preferences, Beliefs, and the Dynamics of
Free Riding in Public Goods Experiments." The American Economic Review 100.1: 541-
56.
Friedman, Milton. 1968. "The Role of Monetary Policy." The American Economic Review 58.1:
1-17.
Grossman, Gene M., and Elhanan Helpman. 1994. "Protection for Sale." The American Economic
Review 84.4: 833-50.
Hamermesh, Daniel S. 2013. "Six Decades of Top Economics Publishing: Who and How?"
Journal of Economic Literature 51(1): 162-72.
Harris, John R., and Michael P. Todaro. 1970. "Migration, Unemployment and Development: A
Two-Sector Analysis." The American Economic Review 60.1: 126-42.
Holt, Charles A., and Susan K. Laury. 2002. "Risk Aversion and Incentive Effects." The American
Economic Review 92.5: 1644-655.
Jensen, Michael C. 1986. "Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers."
The American Economic Review 76.2, Papers and Proceedings of the Ninety-Eighth
Annual Meeting of the American Economic Association: 323-29.
Katz, Michael L., and Carl Shapiro. 1985. "Network Externalities, Competition, and
Compatibility." The American Economic Review 75.3: 424-40.
31
Keys, Benjamin J., Tanmoy Mukherjee, Amit Seru, and Vikrant Vig. 2010. "Did Securitization
Lead to Lax Screening? Evidence from Subprime Loans *." Quarterly Journal of
Economics 125.1: 307-62.
Krueger, Anne O. 1974. "The Political Economy of the Rent-Seeking Society." The American
Economic Review 64.3: 291-303.
La Porta, Rafael, Florencio Lopez-de-Silanes, Andrei Shleifer, and Robert W. Vishny. 1998. "Law
and Finance." Journal of Political Economy 106.6: 1113-155.
Leibenstein, Harvey. 1966. "Allocative Efficiency vs. "X-Efficiency"" The American Economic
Review 56.3: 392-415.
Levine, Ross, and David Renelt. 1992. "A Sensitivity Analysis of Cross-Country Growth
Regressions." The American Economic Review 82.4: 942-63.
Lintner, John. 1956. "Distribution of Incomes of Corporations Among Dividends, Retained
Earnings, and Taxes." The American Economic Review 46.2, Papers and Proceedings of
the Sixty-eighth Annual Meeting of the American Economic Association: 97-113.
Margo, Robert A. 2011. "The Economic History of The American Economic Review: A Century's
Explosion of Economics Research." American Economic Review. 101.1: 9-35.
Marr, Bernard. 2015. “Big Data: 20 Mind-Boggling Facts Everyone Must Read” Forbes / Tech.
https://www.forbes.com/sites/bernardmarr/2015/09/30/big-data-20-mind-boggling-facts-
everyone-must-read/
McCombie, John, and Maureen Pike. "No End to the Consensus in Macroeconomic Theory? A
Methodological Inquiry." American Journal of Economics and Sociology 72, no. 2 (2013):
497-528.
32
Modigliani, Franco, and Merton H. Miller. 1958. "The Cost of Capital, Corporation Finance and
the Theory of Investment." The American Economic Review 48.3: 261-97.
Mundell, Robert A. 1957. "International Trade and Factor Mobility." The American Economic
Review 47.3: 321-35.
Ostrom, Elinor. 2010. "Beyond Markets and States: Polycentric Governance of Complex
Economic Systems." The American Economic Review 100.3: 641-72.
Pinkovskiy, Maxim, and Xavier Sala-I-Martin. 2016. "Newer Need Not Be Better: Evaluating the
Penn World Tables and the World Development Indicators Using Nighttime Lights."
NBER Working Paper 22216.
Rabin, Matthew. 1993. "Incorporating Fairness into Game Theory and Economics." The American
Economic Review 83.5: 1281-302.
Rajan, Raghuram G., and Luigi Zingales. 1998. "Financial Dependence and Growth." The
American Economic Review 88.3: 559-86.
Reinhart, Carmen M., and Kenneth S. Rogoff. 2010. "Growth in a Time of Debt." American
Economic Review 100.2: 573-78.
Romer, Christina D., and David H. Romer. 2010. "The Macroeconomic Effects of Tax Changes:
Estimates Based on a New Measure of Fiscal Shocks." American Economic Review 100.3:
763-801.
Romer, Paul M. 1986. "Increasing Returns and Long-Run Growth." Journal of Political Economy
94.5: 1002-037.
Samuelson, Paul A. 1947. Foundations of Economic Analysis. Cambridge: Harvard UP. Print.
Shapiro, Carl, and Joseph E. Stiglitz. 1984. "Equilibrium Unemployment as a Worker Discipline
Device." The American Economic Review 74.3: 433-44.
33
Simon, Herbert A., and Charles P. Bonini. 1958. "The Size Distribution of Business Firms." The
American Economic Review 48.4: 607-17.
Simon, Herbert A. 1959. "Theories of Decision-Making in Economics and Behavioral Science."
The American Economic Review 49.3: 253-83.
Sims, Christopher A. "Money, Income, and Causality. 1972. " The American Economic Review
62.4: 540-52.
Solow, Robert M. 1956. "A Contribution to the Theory of Economic Growth." The Quarterly
Journal of Economics 70.1: 65-94.
Stiglitz, Joseph E., and Andrew Weiss. 1981. "Credit Rationing in Markets with Imperfect
Information." The American Economic Review 71.3: 393-410.
Tiebout, Charles M. 1956. "A Pure Theory of Local Expenditures." Journal of Political Economy
64.5: 416-24.
Vernon, Raymond. 1966. "International Investment and International Trade in the Product Cycle."
The Quarterly Journal of Economics 80.2: 190-207.

Supplementary resource (1)

ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
"Nowhere does history indulge in repetitions so often or so uniformly as in Wall Street," observed legendary speculator Jesse Livermore. History tells us that periods of major technological innovation are typically accompanied by speculative bubbles as economic agents overreact to genuine advancements in productivity. Excessive run-ups in asset prices can have important consequences for the economy as firms and investors respond to the price signals, resulting in capital misallocation. On the one hand, speculation can magnify the volatility of economic and financial variables, thus harming the welfare of those who are averse to uncertainty and fluctuations. But on the other hand, speculation can increase investment in risky ventures, thus yielding benefits to a society that suffers from an underinvestment problem.
Article
New data-gathering techniques, often referred to as “Big Data” have the potential to improve statistics and empirical research in economics. In this paper we describe our work with online data at the Billion Prices Project at MIT and discuss key lessons for both inflation measurement and some fundamental research questions in macro and international economics. In particular, we show how online prices can be used to construct daily price indexes in multiple countries and to avoid measurement biases that distort evidence of price stickiness and international relative prices. We emphasize how Big Data technologies are providing macro and international economists with opportunities to stop treating the data as “given” and to get directly involved with data collection.