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Scientific epistemology is a serious business in economics—as it is in any science. Not surprisingly, therefore, discussions about value-ladeness tend to focus on theoretical and methodological issues within the discipline, while the question of the social consequences of science is approached with more reservation. And for many good reasons, one may say, because it is not entirely up to scientists how will the scientific product be disseminated and interpreted in society, or how will it be used by policy makers. Or, that’s not the job of the scientist, one could reason, to determine and be ready for all possible applicative scenarios.

Since the last few decades, research practices have undergone a far-reaching transformation at the interface between science, policy and society. It involves an increased engagement of science in problem solving and policy advice, and the enhancing role of participatory research methods in problem-based approaches. The social consequences of science become therefore more readily visible, opening up new perspectives on debates about facts and values dichotomy, or the relationship between knowledge, truth, and values (cf. Kitcher, 2001). One way of looking at the transformation of scientific practices focuses on the criteria of scientific rationality with regard to scientific knowledge and the very process of knowledge production, echoing a Weberian contrast between instrumental and axiological rationality of social action (Weber 1968). Specifically, the scientific rationality criteria have been extended in the process from purely (i) internal rationality, that can be defined as a conventional scientific rationality approach focused on disciplinary epistemology and methodology, to (ii) external rationality that pertains to axiological, ethical, and societal elements of knowledge and its production (Kiepas, 2006). 

There are many reasons for including external rationality in scientific practices. For one thing, all applied sciences can be considered as value-laden in virtue of their goal-oriented values (Pullin, 2002). Furthermore, many contemporary problems, as subjects of research, are radically complex. They are laden with systemic uncertainties, meaning that “the problem is concerned not only with the discovery of a particular fact (as in traditional research), but with the comprehension or management of a reality that has irreducible complexities or uncertainties” (see more in Funtowicz & Ravetz, 1994, p. 1882). They also pose future incalculable risks in an unprecedented scope. For example, in the context of complex, adaptive problems such as climate change, uncertainty in science follows (Brown, 2013). Scientific uncertainty regarding the severity and scope of the problem fuels general disagreement about the appropriate actions to undertake. Attempts to accurately assess all the possible climate change impacts and to exhaustingly assign an economic value to alternative courses of action are bound to fail (Jamieson, 2010). That being the case, the policy-relevance of standard economic analysis as the sole knowledge-base for environmental decision making is limited.

In case of economics, the shift in approaches to rationality can be seen in debates about reflexivity in economics, bounded rationality, or performativity of economic models, to name a few topics. But for the most part, ethical- and value-neutrality continue to feature much of economic research, such as in standard normative theories of decision making under uncertainty and risk. The burgeoning of economics as a separate discipline, accompanied by distancing from philosophy, build up strong methodological foundations to prevent any extra-scientific elements to interfere in its analysis (cf. Hausman, 1992).

The classic conceptualisation of uncertainty and risk in economics is very specific and differs from the above-mentioned, sociologically incrusted understanding. Following the paradigmatic distinction formulated by Knight (1921), uncertainty refers to situations of radical uncertainty that cannot be expressed as sets of probabilities, whereas risk is related to situations in which actions do not lead with certitude to specific outcomes, but the alternative outcomes and their probabilities can be discerned. 

The categories of uncertainty and risk, as considered here, lend themselves to complexity of many policy issues, and are associated with the transformation of postmodern societies due to technology, consequences of globalisation, and environmental crises that follow (Beck, 1992; Giddens, 1990). These circumstances, “external” to standard methodological practices, motivate the extension of scientific rationality criteria and rethinking the role of science by researchers themselves. An example of this transformative process is the so-called advocacy science for environmental justice. It represents a socially engaged, multidisciplinary research approach that emerged in response to environmental toxicity movements, and developed an alternative epidemiological paradigm based on participatory research methods (see, e.g., Ottinger & Cohen, 2011).

With regard to the interface between science, policy, and society and the extra-scientific aspects of uncertainty and risk, one can note that the assessment and acceptance of risk are not purely a matter of data analysis or applying the “right” indicators. The perception and interpretation of uncertainty and risk are influenced by a mixture of social, political, and scientific processes that interact with each other. Consider the relationship between environmental pollution and risk. While pollution appears to be solely as a matter of scientific measures, the question of what is an acceptable level of pollution and its risk for a given society, and whether there are cases of unacceptable risks, involves our pre-conceptions and assumptions about what constitutes a good quality of life, wellbeing, and sustainable development (cf. Evernden, 1999).

Why would an individual economist care about the science-policy interface, or about considering extra-scientific elements of her research practice? There are several reasons to seriously reflect on this question. For one thing, transparency about the value content of specific research programs may translate into more careful and accountable approach to complex problems of public policy and the remedying capacity of science and technological progress. Furthermore, Söderbaum (2000) argues that economics should be more properly approached as political economics to make clear the fact that each scientist, as the discipline itself, has an ideological orientation (in the sense of means-ends philosophy) that plays out in the problem-framing, and reflects on the performative features of economic expertise. To the latter point, the analyst’s conclusion that reduces the extra-monetary aspects of a given problem to monetary ones is not without policy consequences; it suggests certain framings and solution-imageries to economic agents and decision makers. Besides, academia itself is not free of subjective interests and rent seeking. But—I haste to add—this does not undermine the value of scientific expertise per se. Neither does it suggest that citizens and policy makers are passive or unreflective recipients of scientific knowledge. It rather suggests a double-edge approach to science that recognises the subjective, cultural, and societal components in scientific practices on the one hand, and the aspiration of scientific community to reach objectivity (understood broadly as a normative objective) on the other hand. Although scientific practices are saturated with theoretical pre-conceptions and cultural perspectives, it does not immediately follow that science has nothing to do with truth and objectivity (a subject that deserves a separate discussion). 

The double-edge approach to science calls for more explicit discussions about the social consequences of science and scientific literacy in society:

  • Concerns about the role of science and scientific expertise in society may facilitate disciplinary reflexivity. It may also feed into methodological approaches. In case of economics, instead of focusing only on expanding the standard framework of economic analysis onto new subjects, concerns about the social consequences of science create a platform for a more direct consideration of methodological alternatives. Especially for contexts in which standard economic tools of analysis display some limits (e.g., cost-benefit analysis in sustainable development planning), alternative approaches that directly accommodate non-monetary impacts and justice concerns are needed (Brown et al., 2017). 
  • According to a political scientist Frank Fischer, in face of technical and social complexity that characterises most of policy issues, citizens and politicians need to display a good level of competence (2009, 1). In this context, an urgent question arises: how to democratise science on the one hand, and how to prevent populism and the spread of fake facts to take the provenience of science (as a source of information about the world) on the other hand? While the aspiration of science to be the absolute truth holder has been widely challenged, it does not immediately follow that there is nothing to scientific knowledge that would make it somehow different from other forms of knowledge. No differentiation at all can give way to anti-science of dangerous kind, in which “facts” are matters of preferences or interests. A caveat here is in order: such differentiation does not imply that scientific knowledge is inherently better than any other form of knowledge.

Certainly there are many challenges to balancing the double-edge approach to science both within and outside of the scientific community, as there are multiple philosophical framings of the role and status of scientific expertise in society. To be continued!

References

Beck, U. (1992). Risk Society: Towards a New Modernity. London: Sage.

Brown, J. Söderbaum, P. & Dereniowska, M. (2017). Positional Analysis for Sustainable Development: Reconsidering Policy, Economics and Accounting. London: Routledge. 

Evernden, N. (1992). The Social Creation of Nature. Baltimore and London: The John Hopkins University Press.

Hasuman, D. M. (1992). The Inexact and Separate Science of Economics. New York: Cambridge University Press.

Fischer, Frank (2009). Democracy & Expertise. Reorienting Policy Inquiry. Oxford: Oxford University Press.

Funtowicz, S. O. & Ravetz, J. R. (1994). Uncertainty, Complexity and Post-normal Science. Environmental Toxicology and Chemistry 13(2), 1881-1885. 

Jamieson, D. (2010). Ethics, Public Policy, and Global Warming. In S. M. Gardiner, S. Caney, D. Jamieson & Henry Shoue (Eds), Climate Ethics. Essential Readings (pp. 77-86). Oxford: Oxford University Press.

Kiepas, A. (2006). Ethics as the Eco-development Factor in Science and Technology. Problems of Eco-development 1(2), 77–86.

Kitcher, P. (2001). Science, Truth, and Democracy. Oxford University Press, Oxford, New York. 

Knight, F. H. (1921). Risk, Uncertainty and Profit. Chicago: University of Chicago Press.

Ottinger, G. & Cohen, B. R. (Eds). (2011). Technoscience and Environmental Justice. Expert Cultures in Grassroots Movement. Cambridge: the MIT Press.

Pullin, A. S. (2002). Conservation Biology. Cambridge & New York; Cambridge University Press. 

Söderbaum, P. (2000). Ecological Economics. A Political Economics Approach to Environment and Development. London: Earthscan/Routledge.

Weber, M. (1968). Economy and Society. New York: Bedminster Press.

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That economics is a value-laden science is not a new idea. Most of the prominent economic thinkers were also philosophers, wary of moral and philosophical content of scientific assumptions, models, and theories. That economics needs philosophy, and the separation between these two cannot be maintained any longer, is gaining recognition, and has become a subject of debates in the field of philosophy of economics that brings together (to various extends) philosophers, mainstream, and heterodox economists. For example, Daniel Hausman (1992) discusses that at an analytic level economists do successfully separate the philosophical and ethical content from economic analysis, albeit this separation is possible only at the analytic level. Karl Polanyi (1957), in his discussion on the entanglement of economic activities in the social totality, gives insights from a different perspective how considering the subject of economic study in social vacuum can in fact lead to thinking that scientific practice indeed has disentangled from society.

Today economists of both mainstream (e.g., Jean Tirole) and heterodox approaches more readily admit: economics is a moral and philosophical science. Yet the meaning and scope of the normative components of economics, the epistemic consequences of the social embeddedness of science, and the social consequences of economics are raising so far inconclusive debates. These issues constitute two-tiered dimensions of scientific rationality: external and internal ones. While the criteria of internal rationality (which constitute the standard approach to scientific rationality) refer to disciplinary epistemology and methodology, the criteria of external rationality involve the axiological, ethical, and societal elements of the process of knowledge production and the social consequences of science.

Interestingly, as Gustav Márquez (2016) points out, even in the field of philosophy of economics, the discussions are often focused on the elements of what I call here internal rationality. Márquez argues that the predominant focus on these issues characterize the mainstream philosophy of economics, while the more normatively-laden issues, such as a broader theoretical reorientation towards more responsive and socially engaged approaches (which I considered as aspects related to the external scientific rationality), are not so much a part of the dominant concerns and discourse.

Why would an external rationality matter? What is the meaning of the social consequences of economics as a science? And how the acknowledgment of the value-laden component of scientific practices plays out in research practices of the scientific community, and of an individual researcher? These questions are not easy to answer, as they involve several complex issues, such as what is the meaning of scientific truth, scientific objectivity, how to account for the normative components of science, or what are the grounds for our confidence in scientific methods and analysis—to name a few. While each of these questions opens a Pandora box by itself, my goal is to simply open up some of the ways these profound issues can be approached for a discussion. My guiding thought is that one of the elements that drastically shapes our take on these questions pertains to the context in which science and the process of knowledge production is considered.

My specific focus will be on the role of science in society and for policy making. In my next entries of the WEA Pedagogy Blog, I am going to consider several issues, problems, and controversies raised at the intersection of economics, society, and policy, with an eye towards their educational and pedagogical challenges. My objective is to problematize, hopefully for a broader discussion with the readers, the fact that the specific philosophical commitments (e.g. ontological and epistemological assumptions about the role of science, function of knowledge, scientific truth, etc.) bear impact on how the epistemic consequences of the value-ladedness of economics are framed, and on the acknowledgment and role assigned to the extra-scientific components of research practices.

References:

Hasuman, Daniel M. 1992. The Inexact and Separate Science of Economics. New York: Cambridge University Press.

Márquez, Gustavo. 2016. A Philosophical Framework for Rethinking Theoretical Economics and Philosophy of Economics. London: College Publications.

Polanyi, Karl, [1944] 1957. The Great Transformation. Boston: Beacon Press.

After the 1920s, the theoretical and methodological approach to economics deeply changed. Based on a criticism of Marshall’s work and legacy, a new generation of American and European economists developed Walras’ and Pareto’s mathematical economics. As a result of this trend, the Econometric Society was founded in 1930.

The constitutional assembly was held in  Cleveland, Ohio, during the annual joint meeting of the American Economic Association and the American Statistical Association. The Norwegian economist Ragnar Frisch played an important role in the Econometric Society that was founded to enhance studies based on the theoretical-quantitative and the empirical-quantitative approach to economic problems. In this way, the  founding fathers believed that  economic thinking could be as rigorous as the one that dominates the natural sciences.

At the 5th European Meeting of the Econometric Society, in 1935, Jan Tinbergen presented a paper on ‘A mathematical theory of business cycle policy’ that followed the Econometric Society’s guidelines. His causal explanation of the business cycle began with a priori economic-theoretical considerations about explanatory variables and then he proceeded to test a model.

In the late 1930s, John Maynard Keynes and other economists objected to this recent “mathematizing” approach. Keynes, as editor of the Economic Journal, wrote  a negative review of Tinbergen’s 1939 book A Method and its Application to Investment Activity. This book  presented an statistical testing of business cycle theories based on the application of the method of  multiple regression and  mathematical framing in the form of a specified model. At the core of Keynes’ concern lied the question of methodology. Recalling his own words:

Am I right in thinking that the method of multiple correlation analysis essentially depends on the economist having furnished, not merely a list of the significant causes, which is correct so far as it goes, but a complete list? For example, suppose three factors are taken into account, it is not enough that these should be in fact veræ causæ; there must be no other significant factor. If there is a further factor, not taken account of, then the method is not able to discover the relative quantitative importance of the first three. If so, this means that the method is only applicable where the economist is able to provide beforehand a correct and indubitably complete analysis of the significant factors. The method is one neither of discovery nor of criticism. It is a means of giving quantitative precision to what, in qualitative terms, we know already as the result of a complete theoretical analysis. (Keynes 1939: 560)

In this paragraph, it is clear that Keynes doubted the use of inductive methods of generalization and statistiicial inference to build economic theories because of the peculiarity of the economic systems characterized by:

  • a low degree of homogeneity,
  • a high degree of complexity
  • the lack of stability through time.

Indeed, on behalf of the peculiarities of the economic systems, Keynes highlighted that econometrics turns out to be a method not of testing or of discovery, but of measurement of selected variables.

 

refeences

Keynes, J. M.,  Professor Tinbergen’s Method, The Economic Journal, Vol. 49, No. 195 (Sep., 1939), pp. 558-577. Published by: Blackwell Publishing for the Royal Economic Society. Stable URL: http://www.jstor.org/stable/2224838

Tinbergen, J. A Method and its Application to Investment Activity. Geneva: League of Nations, 1939.

The concept of nudge became popular after the publication of the 2008 book Nudge: Improving decisions about health, wealth, and happiness, written by Cass Sunstein and the most recent Nobel Laureate, Richard Thaler.  According to the authors, nudge refers to “any aspect of the choice architecture that alters people’s behavior in a predictable way without forbidding any options or significantly changing their economic incentives. To count as a mere nudge, the intervention must be easy and cheap to avoid. Nudges are not mandates. Putting fruit at eye level counts as a nudge. Banning junk food does not” (Thaler and Sunstein, 2008).

In a previous paper, Thaler and Sunstien (2003) highlighted the paternalistic intention and the libertarian tone that overwhelm the concept. As a result, while policymakers shape contexts of individual choice towards optimal policy goals, individuals are free to choose.

Currently, nudges are used to foster social policy goals, such as the so called consumer protection. The aim of the nudge approach is both to test non-coercive alternatives to traditional regulation and to enhance cooperation between the public and the private sector.  Indeed, after 2008, a Behavioural Insights Team (BIT) was created in the UK and in many others countries – like Australia, Canada, the Netherlands, Germany, U.S. and Qatar. Since 2010, the Behavioural Insights Team (BIT) in the UK has been exploring and testing policy options by means of randomised controlled trials (RCTs). Taking into account the American experience, the Obama’s administration stimulated the introduction of nudges in new regulations to generate welfare with cost effectiveness.

Considering this background, the relevant question is: which are the reasons that explain the increasing acceptance of the nudge approach to public policy?

First, the use of nudges in public policy seems to be associated to the broader processes of deregulation and privatization in the context of financialization.

Second, the focus on individual behaviour is consistent with a neoliberal agenda where the new approach to public policy enhances the illusion of free individual choice. In this respect, Ramsey (2012) highlights the real burden on individuals that actually result from labor market flexibility and increasing indebtedness. In his own words: “Deregulation and privatisation often imposed greater choices on individuals (e.g. pensions). Forced to make choices, individuals were invited to regulate themselves according to particular norms of behaviour. Thus in consumer finance markets individuals must learn the appropriate norms of credit and savings behaviour and become financially literate. More recently insights from behavioural economics have been harnessed to ‘nudge’ individuals to change their behaviour

Third, behind the partnerships between the public and the private sectors that aim at developing new forms of non-coercive regulations, there is, in truth, a set of economic and political interrelations that shape the financialization of corporate strategies in sectors that used to be related to public services. For example, in relation to the health sector, Maryon-Davis (2016) addresses: “Today’s most liberal governments tend to resist calls for regulatory approaches to health behaviour. They are averse to regulating industries such as the tobacco, alcohol and food industries for fear of interfering with companies’ rights to sell their legal products and their legal obligation to shareholders to maximise profits. They tend to be even more reluctant to pass laws directly curtailing the personal freedoms and behaviour of individuals.”

Following the nudge approach, the responsibility for public welfare is shifted to individuals. In spite of encouraging active civic engagement, this approach to public policies seems to neglect the social constraints that restrain individual autonomy. Finally, it is worth noting that, while putting emphasis on individual behaviors and choices, the nudge approach dismisses the global increasing economic, social and political challenges at national, state and local levels.

 

References

Goodwin, T. (2012) Why we should reject ‘nudge’. Politics, 32(2), pp. 85-92.

Maryon-Davis, A. (2016) Government legislation and the restriction of personal freedom. In F. Spotswood (Ed.) Beyond behaviour change: Key issues, interdisciplinary approaches and future directions. UK: University of Bristol Policy Press.

OECD (2015) OECD Regulatory Policy Outlook 2015. Geneve.

Ramsay, I. (2012) Consumer law and policy: Text and materials on regulating consumer markets. Bloomsbury Publishing.

Thaler, R. H., and Sunstein, C. R. (2008) Nudge: Improving decisions about health, wealth, and happiness. U.S.:Yale University Press.

Thaler, R. H., & Sunstein, C. R. (2003a). Libertarian paternalism. The American Economic Review, 93(2), pp.175-179.

 

Bank transactions by internet and mobile banking have sharply increased since the 2008 global financial crisis. In this digital environment, new technologies – such as advanced analytics and big data, in addition to the use of robotics, artificial intelligence, besides new forms of encryption and biometrics – have been enabling changes in the provision of financial products and services. The current wave of financial innovations is being increasingly oriented to more friendly digital channels through apps in the context of mobile banking strategies that privilege the development of open bank softwares and the interaction with social media.

Indeed, the increasing digitalization of financial transactions is also related to changes in the banks’ competitive environment, where the intense growth of the startups called fintechs, especially since 2010, has revealed a new articulation between finance and technology. Such fintechs are companies organized as digital platforms with business models focused on costumer relationship in the areas of payment systems, insurance, financial consultancy and management, besides virtual coins. The advantages of their business models are low operating expenses, greater operational agility and the ability to generate data for the design of customized financial products and services. As a result of the advance of these new non-bank competitors, big banks have begun to establish collaborative partnerships with selected fintechs in order to produce new technological solutions and to promote the development of a culture of technological entrepreneurship among bank workers.

Taking into account the global changes in the provision of financial products and services, Central Banks have closely followed the recent expansion of fintechs. Indeed, the transformations provoked by these startups in the financial markets have raised a relevant discussion about the impacts of recent technological innovations on the financial regulation agenda- mainly focused on the Basel Accords. The intense advance of fintechs is settling new questions for regulators: How to deal with loan activities that are being performed by means of electronic platforms? How to regulate the fintechs’ activities of consultancy and financial management that are characterized by the collection, treatment and custody of information from users? Which is the scope of the Central Bank and of other financial regulators when considering the surveillance over the fintechs? Moreover, there are legal concerns related to information security practices, legal validity of electronic documents, digital signatures and data storage in the cloud.

As a result of the new competitive digitalized and deregulated environment, the current wave of technological innovations will decisively affect the future of bank workers. Currently, one of the main cost-reducing bank strategies is centered on administrative expenses mainly labour costs that remain tightly controlled by banks in order to improve operational efficiency. In this scenario, technological strategies aimed to increase profitability will foster further organizational innovations and changes in labor relations. Thus, the future impacts on jobs in the financial sector will deepen the power of financial holdings, that is to say, of centralized blocks of financial capital that base their global expansion on the digitalization of products, services and delivey channels .

 

The roots of gender and poverty studies began with Pearce (1978) who coined the expression ‘feminization of poverty’. Pearce considered female-headed families, excluding poor women who live in male- headed families, based on the argument that the proportion of families headed by women among the poor has been  increasing since the 1950s. In her opinion, women have become poorer because of their gender.

The recent dynamics of the global labour market has reinforced the precariousness of women’s employment and working conditions. Among other issues, the recent global highlights about the participation of women in the labour markets are listed below:

Unemployment: Women are more likely to be unemployed than men, with global unemployment rates of 5.5 per cent for men and 6.2 per cent for women

Informal Work:      In 2015, a total of 586 million women were own-account or contributing family workers. Many working women remain in occupations that are more likely to consist of informal work arrangements

Wage and salaried jobs: Moreover, 52.1 per cent of women and 51.2 per cent of men in the labour market are wage and salaried workers.

Jobs and occupations by economic sectors:  Globally, the services sector has overtaken agriculture as the sector that employs the highest number of women and men. In the period between 1995 and 2015, women are employed in the services sector: since 1995, women’s employment in services has increased from 41.1 per cent to 61.5 per cent.

High-skilled occupations: High-skilled occupations expanded faster for women than for men in emerging economies where there is a gender gap in high-skilled employment in women’s favour.

Part-time jobs: Globally, women represent less than 40 per cent of total  employment, but make up 57 per cent of those working on a part-time basis.

Hours of work: Across the global labour scenario, one fourth of women in employment (25.7 per cent) work more than 48 hours a week, mainly in Eastern , Western and Central Asia, where almost half of  women employed work more than 48 hours a week.

Gender wage gap: Globally, women earn 77 per cent of what men earn.

 

Indeed, although women have been increasing their participation rate in the labor market in the last decades, they worked in more precarious occupations. This situation characterized by precarious jobs, mainly based on short-term contracts, enhances the vulnerability of workers, mainly women, as the financialization of management strategies turns out to be subordinated to economic efficiency targets, that shape employment relations, overwhelmed by longer working hours, job destruction, turnover and outsourcing. Workforce displacement and loss of rights could also be part of the spectrum of management alternatives aimed at cost reduction. In addition to the wage gap, women’s participation is stronger in the services sector where working hours are longer and wages lower.

Besides, unpaid work could also be considered an extra onus on women. In addition to women´s challenges in the labour market, the increasing weight of unpaid work is more likely when women become unemployed and return to their homes and take more responsibility for housework than men, or because the loss of family income makes it impossible to support the remuneration of domestic workers. Gender-differentiated time use patterns are affected by many factors, including:  household composition (age and gender composition of household members); seasonal considerations; regional and geographic factors; availability of infrastructure and social services. But social and cultural norms also play an important role both in defining, and sustaining rigidity in, the gender division of labour.

Building on the United Nations goals, gender equality is required for the erradication of the many dimensions of poverty and to promote sustainable human development. Taking into account a macroeconomic approach to the labour markets, the “vicious circle” of impoverishment could be surmounted if policy makers rethink employment an income policies under a gender approach to the labour markets.

References

Ilo (2016) http://www.ilo.org/wcmsp5/groups/public/—dgreports/—dcomm/—publ/documents/publication/wcms_457086.pdf

Pearce, Diana (1978). “The feminization of poverty: women, work, and welfare”. Urban and Social Change Review, Special Issue: Women and Work, Vol. 11, No. 1-2, pp. 28–36.

aaeaaqaaaaaaaahhaaaajdq5nmzhzwvllwmxn2utndg0yy05mtg2lwe5ymqxzjhhmji0nqThe first post on Reading Keynes provided an outline of the reasons why this is a good idea. It is clear that economics is broken. We need a new macroeconomics for the 21st century, one which can solve the massive problems which humanity as a whole is facing on political, social, economic, and environmental dimensions. Keynes faced similar problems, and found solutions which guided economic policy in the mid twentieth century. It is always useful to absorb the insights of our predecessors, before trying to build upon them. Such a methodology is essential for the advancement, progress and accumulation of knowledge. Our current stock of human knowledge is based on the collected insights and labors of hundreds of thousands of scholars, accumulated over the centuries. We would return to the stone ages if we were to reject it as being full of contradictions and errors (which it is). Instead, progress occurs by absorbing the past accumulated wisdom, and trying to remove the errors, or add missing insights, building on our heritage, rather than discarding it and starting over from scratch.

Several of the central Keynesian insights into the causes of the Great Depression never made it into the economics textbooks. However, our goal in studying Keynes goes far beyond just the re-discovery of these lost Keynesian insights.   A central goal is to apply and illustrate a radically different methodology for studying economics in particular, and social science in general. This is derived from a study of The Methodology of Polanyi’s Great Transformation. This is an extremely important point, which we proceed to amplify and explain further.

1.       Problems with contemporary economic theory arise from a fundamentally flawed methodology, which is incapable of learning from real world experiences. As Romer said, macroeconomics has gone backwards for the last several decades. This is because the methodology currently in use does not lead to progress and accumulation of knowledge. Very briefly, this is because current methodology is the Axiomatic-Deductive Methodology of Greek Geometry, which was never successful in dealing with natural phenomenon. Instead, what is needed is scientific methodology as practiced and demonstrated by Ibn-ul-Haytham. Unfortunately, logical positivism created massive confusions and misunderstandings regarding scientific methodology, which persist to this day, despite the fact that logical positivism has been rejected.

2.       Why have modern economists adopted and practiced a deeply flawed methodology? This is a complex and tangled tale, but its origins lie in the Battle of the Methodologies (Methodenstreit) in the 1890’s. In this battle, the German Historical School of Schmoller, which advocated a contextual and historical approach lost to the Austrian School of Menger, which advocated a more scientific, mathematical and a-historical methodology. The details and consequences have been explained at length in “How Economics Forgot History” by Geoffrey Hodgson. As a consequence of the economists’ search for scientific laws which are universal invariants, economic theorists have invented an artificial world of maximizing robots without history, culture, institutions, and social norms.The process of economic modelling — learning to think like an economist — involves translating economic problems to this artificial world and then calculating the results. This can be done because all the robotic agents behave in predictable ways, and the environment is sterilized of all particular historical, social, environmental elements. However, most often, economic outcomes in this artificial world bear no resemblance to outcomes in the real world. Mistaking a highly distorted map for the territory, economists are confused when real world phenomena do not match the results of their models.

Some of the key methodological issues which we will try to develop in this re-reading of Keynes are highlighted below:

3.       Theories cannot be separated from their historical context. Thus Keynesian theory can only be understood within its historical context. We cannot understand Keynesian theory as a collection of principles and/or mathematical laws, taken out of context and understood to apply to all economies across time and space. When placed within it historical context, Keynes becomes much easier to understand.

4.       Even more important, theories interact with history. Human being formulate theories in order to try to understand and explain changing social circumstances. When circumstances change rapidly, theories are devised to understand the change. These theories, whether right or wrong, are used to  respond to changes, and thus end up shaping history. From this perspective, it is important to study Keynes, regardless of whether his theories were right or wrong, because economic policies from mid-twentieth century onwards were guided by his views. Thus Keynesian theories have shaped economic history. There is a complex interaction of theories and history, and we cannot understand history without theories, just as we cannot understand theories without their historical context.

5.       Because of the central importance of point 4 above, we provide a simple illustration to clarify it. As described in greater detail by Polanyi, the process of enclosures of common land deprived the masses of access to livelihood and created poverty on a large scale in England. Large numbers of authors described the problems and searched for causes of this phenomena. However, the analysis of Malthus, which blamed the problem on the excessive fertility of the poor, came to dominate. His theories deeply influenced the Poor Laws, and the British response to poverty, and thus millions of lives. Even though Malthusian theories about the arithmetic increase of food and the geometric increase of population were empirically incorrect, we must understand Malthus to understand the economic policies and circumstances of England at that time.

Accordingly to widely accepted methodological principles underlying the development of modern economics, theories are formulated without historical context. In addition, economics is studied in isolation from politics and society. We propose to study Keynesian theories within their historical context. This will substantially enrich our understanding of Keynes. In addition, the historical context includes the political, social, and economic environment, which will allow us to see that economic events cannot be studied in isolation, since all these dimensions of human lives interact with each other. Again our approach goes against a core methodological commitment of modern economics, which insists that economics can be separated from political and social circumstances and studied in isolation.

HOMEPAGE for Re-Reading Keynes. Links to more material on Methodology