Where economics is dominated by a monolithic methodology of axiomatic theorizing and econometric analysis of secondary datasets, multiple and mixed methods research offers a much and richer toolkit to examine economic problems from a variety of perspectives with custom methods suited for the particular task. Rather than limiting analysis to the application of approved methods to an approved dataset, with little consideration of its content, a multiple or mixed method approach inherently interrogates choices and limitations of data and methods from the outset. This chapter aims to equip readers with a grounding in the principles of multiple and mixed methods research and to consider benefits and limitations of triangulation of methods, issues in research design, choices of methods and their integration, and issues of validity and ethics.
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Gyun Cheol Gu
Based on the grounded theory methodology covered in Chapter 2, this chapter proposes a comprehensive and coherent theoretical system to provide an analytical framework for price stability. In order to establish an empirically grounded pricing procedure, it analyzes a body of empirical studies which investigate the advances in accounting and managerial techniques, thereby examining the causal mechanisms for price setting. By doing so, it sheds light on the mechanisms through which price stability is secured. In particular, it refines and extends a heterodox theory of price stability by differentiating between intrinsic and extrinsic stability, identifying their roles and implications for stable prices, and incorporating labor hoarding and labor discipline effects to the theorization of the extrinsic price stability.
Amit Basole and Smita Ramnarain
This chapter examines the relevance of qualitative and ethnographic methods for the discipline of economics, especially in heterodox economic inquiry. Using examples such as Adam Smith and Ronald Coase, we argue that qualitative and ethnographic techniques have always informed the development of economic theory, but remain invisible in its presentation. In view of common objections to such work within economics, we discuss how these methods contribute to a greater understanding of real-world economic and social phenomena, power relations, and social hierarchy. We then discuss specific ethnographic techniques _ interviews, key informant interviews, focus group discussions, participant observation, non-participant observation, and document analysis – and their uses in economics, drawing on studies in both the mainstream and heterodox traditions. The chapter presents a typology of these studies, sorting them into five broad categories of research queries that are amenable to a qualitative approach. We conclude with a discussion of the ways in which ethnographic work may be encouraged within heterodoxy.
Explanation in critical realism (CR) is based on the conduction of open critical analyses in three domains: empirical, actual and real, or deep. The scientific aim of CR is finding deep internal patterns of behavior for the explanation of phenomena. Critical realism, which later on will be used for grounding data in theory, must be based on an appropriate selection of data for their continuing comparison and approval in terms of topics, perspectives, assumptions, methods, and data. This permanent task is relevant for macro-finance, which is out of paradigm according to the post-Keynesian view since no orthodox explanations are offered about the generation mechanisms, irregularities or interconnections of the inherently and abruptly volatile financial sector. Financial events are volatile since the consequences of men activities are neither eternal nor ubiquitous. Therefore the standard explanation related to efficiency-rationality does not explain the main aspects of reality. In this sense the only regularity in finance is uncertainty, which possesses its own rationality and is hence real and susceptible to be researched in qualitative terms. In addition since money is an emerging property, financial interrelationships are complex. Hence analyses of the financial sector must take account of organicism and the existence of permanent and apparently unexplainable fluxes. Therefore a qualitative interpretation of real and dynamic-compared data, along with data triangulation must be conducted. In particular, the qualitative methods of interviews and documental analysis are to be used in this case study in finance related to the obtaining of qualitative information for explaining both volatility and irrationality in financial instruments and indices. On the other hand, the research by-product of historical investigation captures the gist of the development of finance. The aim is to do justice heterodox economics and finance by appropriately explaining the causes, interrelations and consequences of such issues as money, uncertainty, financial stability and the role of financial institutions in a case study of the Mexican Stock Market (BMV), an emerging market, which is highly susceptible to permanent volatility.
This chapter presents a heterodox critique of regression analysis in economics in the sense that it reviews whether critical realist concerns should lead to the abandonment of regression analysis. A review of the different ways in which econometrics has tried to cope with the generally agreed difficulties of identification is presented. The critical realist position is then examined, and its argument that the general econometric approach is indicative of an ontologically illegitimate application of a closed system to a structured open system. The chapter closes by arguing that set within the context that causes of events might relatively endure, but are subject to change, regression analysis can be linked to other forms of evidence in an empirical strategy.
Industry sector analysis is generally static and framed narrowly in terms of composition, employment, and investment, thus ignoring the process and many outcomes of structural change as well as the distributional consequences. This chapter discusses an analysis of the Australian electricity sector, often hailed as the exemplar of global electricity sector liberalization, using a mixed methods approach. The research design was guided by the study’s theoretical framework – Régulation theory – which takes into account a wide range of factors driving change over time, and incorporates more than economic concepts. The chapter’s discussion covers the research design for the Australian study which transformed its theoretical framework to an empirical representation, the multiple data collection methods and data sources used, the steps taken to develop the study’s critical content analysis of documents, the key findings of the analysis, and some observations about the study’s analytical framework, triangulation, and mixed methods research design.
Lynda Pickbourn and Smita Ramnarain
Qualitative and quantitative research methods are typically treated as distinct tools in economics research. This chapter explores the presumed analytical separation of these methods, questioning whether they are distinct from one another, or whether, in fact, they are interdependent and mutually informative avenues for social exploration. After reviewing the different arguments for and against the integration of these methods, we argue the latter: that is, that quantitative and qualitative research methods must each be, and are, necessarily related to the other in the construction of empirically grounded theory. In addition, if economic research is to adequately explain the complexities of social reality, both qualitative and quantitative methods can and should also be used in conjunction with one another (for instance, through data triangulation and case-study methods).
Social network analysis comprises a powerful set of techniques for quantifying, differentiating, and interpreting social interactions or relational data in general. This provides a means of interrogating assumptions of independent yet homogeneous actions and pay-offs in economic processes, a particular interest of heterodox approaches to economics. Contemporary applications include modelling opinion leadership among consumers, search and matching in labour markets, collaboration in research and development, patterns of innovation diffusion among firms, and global commodity chains. This chapter introduces the central concepts and methods of social network analysis, including data collection and interpretation considerations and a brief discussion of specialized software in the field. Each is illustrated with an economic application, either a heterodox example or with a discussion of its heterodox implications.
Studying low-income households poses a number of methodological issues. Nevertheless, there are a number of measures which a researcher can take to access ‘hard to reach’ low-income households using reliable and valid data collection instruments. Drawing on a study which investigated the impacts of rising energy prices on low-income Australian households, this chapter discusses the suitability of a mixed methods approach to study low-income households along with the strengths and weaknesses of the chosen data collection methods of an online survey, focus groups and interviews. Observations are made about the use of intermediaries to recruit low-income households, the potential barriers to participation, the impact on the conduct of research by ethics committee requirements, the use of participation rewards, and the need for a research design which takes all these issues and more into account.
Thomas E. Lambert and Michael Bewley
There are times when due to a lack of data or the impossibility of random assignment of cases, a researcher is limited in the use of the usual statistical and experimental methods to assess a particular intervention or ‘treatment’ given to subjects or to a target group or region. An assessment technique often used is quasi-experimental design, whereby although random assignment does not occur, threats to validity are reduced by comparing cases which are as similar as possible. One group becomes a quasi-experimental group which has received some form of ‘treatment’ whereas another is a comparison group which has not received the treatment. Such a research design is necessary when certain economic events occur or when economic development projects or new policies are undertaken in urban and regional economies, and there exist no two subregions which are exactly the same for the purposes of evaluating the effect of the events, projects or policies. Quasi-experimental design offers a solution for assessing the impacts of different urban and regional phenomena.