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Hamilton Emma (Arcola Research)
Rejoinder to Evidence and the Micro-Foundations of Economic Growth by Michael Joffe
Economics and Business Review, 2017, vol. 3 (17), nr 3, s. 143-147, bibliogr. 10 poz.
Słowa kluczowe
Wzrost gospodarczy, Teoria wzrostu gospodarczego, Model wzrostu gospodarczego, Fundacje, Ustrój kapitalistyczny, Gospodarka kapitalistyczna, Sprzężenia zwrotne, Wyścig zbrojeń, Metodologia ekonomii, Eseje
Economic growth, Economic growth theory, Economic growth model, Foundation, Capitalist system, Capitalist economy, Feedback, Arms race, Economic methodology, Essays
Organizacja Współpracy Gospodarczej i Rozwoju
Organization for Economic Cooperation and Development (OECD)
This is a response to Joffe (this issue) and aims to demonstrate that economics needs theory that is developed in collaboration with real-world data and that approaches utilised in other disciplines may be transferred to enable this goal. Building better theory will enable improved explanation of economic phenomena to aid the understanding of causation in interacting systems. In turn, this will allow more effective application to policy problems as such theory can inform intervention within these systems. With poor theory, data collection, analysis and interpretation can all be misdirected and misleading. This paper has suggested carrying out multimethod research, combining within-case analysis and cross-case analysis. The within-case in-depth study can provide evidence of causal mechanisms while the cross-case analysis can demonstrate the distribution of causal patterns. Additionally, set-theoretic within-case and cross-case methods are proposed, as they enable the analysis of mechanisms and 'conjunctural causation', both characteristics of causal systems. (fragment of text)
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Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka Szkoły Głównej Handlowej
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
Pełny tekst
  1. Beach, D., & Rohlfing, I. (2015). Integrating cross-case analyses and process tracing in set-theoretic research: Strategies and parameters of debate. Sociological Methods & Research, 49124115613780.
  2. Befani, B. (2012). Models of causality and causal inference. In E. Stern, N. Stame, J. Mayne, K. Forss, R. Davies, & B. Befani (Eds.), Broadening the range of methods for impact evaluations. Retrieved from Default.aspx.
  3. Befani, B. (2013). Between complexity and generalization: Addressing evaluation challenges with QCA. Evaluation, 19(3), 269-283.
  4. Byrne, D., & Callaghan, G. (2013). Complexity theory and the social sciences (1 edition). New York: Routledge.
  5. Joffe, M. (2017a). Causal theories, models and evidence in economics - some reflections from the natural sciences. Cogent Economics & Finance, 5(1), 1280983. https://
  6. Joffe, M. (2017b). Evidence and the micro-foundations of economic growth. Economics and Business Review.
  7. Lewin, K. (1951). In D. Cartwright, Field theory in social science: Selected theoretical papers. New York: Harper Row.
  8. OECD. (2015). Final naec synthesis: New approaches to economic challenges.
  9. OECD. (2017). New approaches to economic challenges: Towards a new narrative. Retrieved from
  10. Ramos, G. (2017, June 23). We need an empowering narrative. Retrieved 17 August 2017, from
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