And what should we do about it?

Transcription

1 as And what should we do about it? TINT, Centre of Excellence for the Philosophy of the Social Sciences University of Helsinki PhD Summer School in, Management, Governments Politics, Political Science, Law Public Manor, Estonia 27 June / 19

2 Overview as 1 2 as / 19

3 What is Interdisciplinary Research ()? as NAS (2005) says it is... a mode of research by teams or individuals that integrates information, data, techniques, tools, perspectives, concepts, /or theories from two or more disciplines or bodies of specialized knowledge to advance fundamental understing or to solve problems whose solutions are beyond the scope of a single discipline or field of research practice. -National Academy of Sciences, National Academy of Engineering, Institute of Medicine Facilitating Interdisciplinary Research. Washington, DC: The National Academies Press. p. 26 cf. Porter et al. (Research Evaluation 2006); Huutoniemi et al. (Research Policy 2010) many more 3 / 19

4 What is Interdisciplinary Research ()? as NAS (2005) says it is... a mode of research by teams or individuals that integrates information, data, techniques, tools, perspectives, concepts, /or theories from two or more disciplines or bodies of specialized knowledge to advance fundamental understing or to solve problems whose solutions are beyond the scope of a single discipline or field of research practice. -National Academy of Sciences, National Academy of Engineering, Institute of Medicine Facilitating Interdisciplinary Research. Washington, DC: The National Academies Press. p. 26 cf. Porter et al. (Research Evaluation 2006); Huutoniemi et al. (Research Policy 2010) many more 3 / 19

5 What is? as A bit of conceptual analysis... Process: S do(es) A to O Subject: individuals, teams, disciplines Action: integration, transfer, exchange, etc. Object: evidence, methods, tools, models, concepts, theories, etc. Outcome: new... subjects ( fields: e.g. cognitive science) /or objects (ID theories: e.g. evolutionary game theory) See e.g. Holbrook (Synthese 2013); Mäki (EJPS 2016) 4 / 19

6 What is? as A bit of conceptual analysis... Process: S do(es) A to O Subject: individuals, teams, disciplines Action: integration, transfer, exchange, etc. Object: evidence, methods, tools, models, concepts, theories, etc. Outcome: new... subjects ( fields: e.g. cognitive science) /or objects (ID theories: e.g. evolutionary game theory) See e.g. Holbrook (Synthese 2013); Mäki (EJPS 2016) 4 / 19

7 Why? as Dem-side reasons: the need to address complex contemporary problems (environmental, urban, public health, etc.) that cannot be effectively addressed by traditional disciplines separately knowledge is disciplined; problems are not. Supply-side reasons: different kinds of benefits Epistemic (better understing, explanation, prediction) Practical (novel solutions, inventions) Economic (some are only in it for the money...) But [e]vidence on whether is more or less successful is scarce, messy inconclusive. (Yegros-Yegros et al. PLoS ONE 2015:2) 5 / 19

8 Why? as Dem-side reasons: the need to address complex contemporary problems (environmental, urban, public health, etc.) that cannot be effectively addressed by traditional disciplines separately knowledge is disciplined; problems are not. Supply-side reasons: different kinds of benefits Epistemic (better understing, explanation, prediction) Practical (novel solutions, inventions) Economic (some are only in it for the money...) But [e]vidence on whether is more or less successful is scarce, messy inconclusive. (Yegros-Yegros et al. PLoS ONE 2015:2) 5 / 19

9 Why? as Dem-side reasons: the need to address complex contemporary problems (environmental, urban, public health, etc.) that cannot be effectively addressed by traditional disciplines separately knowledge is disciplined; problems are not. Supply-side reasons: different kinds of benefits Epistemic (better understing, explanation, prediction) Practical (novel solutions, inventions) Economic (some are only in it for the money...) But [e]vidence on whether is more or less successful is scarce, messy inconclusive. (Yegros-Yegros et al. PLoS ONE 2015:2) 5 / 19

10 1. Institutional approach as Identify institutional obstacles, remove them discipline-oriented reward system (publication, hiring, promotion, tenure, funding, prestige) low individual incentives for discipline-oriented organizational structure (department-based education research, physical locations) high coordination costs for Assumption: Once institutional costs of are lowered, its (potential) epistemic benefits will naturally lead scientists to conduct (Yegros-Yegros et al. 2015) Problem Institutional approach underestimates cognitive costs of 6 / 19

11 1. Institutional approach as Identify institutional obstacles, remove them discipline-oriented reward system (publication, hiring, promotion, tenure, funding, prestige) low individual incentives for discipline-oriented organizational structure (department-based education research, physical locations) high coordination costs for Assumption: Once institutional costs of are lowered, its (potential) epistemic benefits will naturally lead scientists to conduct (Yegros-Yegros et al. 2015) Problem Institutional approach underestimates cognitive costs of 6 / 19

12 1. Institutional approach as Identify institutional obstacles, remove them discipline-oriented reward system (publication, hiring, promotion, tenure, funding, prestige) low individual incentives for discipline-oriented organizational structure (department-based education research, physical locations) high coordination costs for Assumption: Once institutional costs of are lowered, its (potential) epistemic benefits will naturally lead scientists to conduct (Yegros-Yegros et al. 2015) Problem Institutional approach underestimates cognitive costs of 6 / 19

13 1. Institutional approach as Identify institutional obstacles, remove them discipline-oriented reward system (publication, hiring, promotion, tenure, funding, prestige) low individual incentives for discipline-oriented organizational structure (department-based education research, physical locations) high coordination costs for Assumption: Once institutional costs of are lowered, its (potential) epistemic benefits will naturally lead scientists to conduct (Yegros-Yegros et al. 2015) Problem Institutional approach underestimates cognitive costs of 6 / 19

14 Why do we have disciplines in the first place? as Insights from evolutionary biology cognitive science 1 Niche construction: agents actively modify their environment, which in turn changes selective dynamics, creating a feedback loop between nich construction natural selection affordances of epistemic niche (Sterelney PCS 2010): environment that agents can trust individualize/entrench themselves in use for coordinating with others 2 Cognition (in general) is scaffolded by external material, conceptual social environments, therefore situated in specific domain domain specificity of disciplinary cognition (MacLeod Synthese 2016). 7 / 19

15 Why do we have disciplines in the first place? as Insights from evolutionary biology cognitive science 1 Niche construction: agents actively modify their environment, which in turn changes selective dynamics, creating a feedback loop between nich construction natural selection affordances of epistemic niche (Sterelney PCS 2010): environment that agents can trust individualize/entrench themselves in use for coordinating with others 2 Cognition (in general) is scaffolded by external material, conceptual social environments, therefore situated in specific domain domain specificity of disciplinary cognition (MacLeod Synthese 2016). 7 / 19

16 Why do we have disciplines in the first place? as Insights from evolutionary biology cognitive science 1 Niche construction: agents actively modify their environment, which in turn changes selective dynamics, creating a feedback loop between nich construction natural selection affordances of epistemic niche (Sterelney PCS 2010): environment that agents can trust individualize/entrench themselves in use for coordinating with others 2 Cognition (in general) is scaffolded by external material, conceptual social environments, therefore situated in specific domain domain specificity of disciplinary cognition (MacLeod Synthese 2016). 7 / 19

17 2. Cognitive-methodological approach as Identify cognitive obstacles arising from domain specificity of scientific practices, find methodological frameworks to mitigate them cognitive obstacles: opacity of practices; conceptual divides; conflicting epistemic values; unstructured problem-solving environments (MacLeod 2016) methodological frameworks: use of model templates as platforms of ID collaboration coordination (MacLeod& PoS 2016; WP 2017) Hypothesis Epistemic benefits of are more likely to be realized by (i) addressing epistemic costs of while (ii) emulating methodologies of effective disciplinary research 8 / 19

18 2. Cognitive-methodological approach as Identify cognitive obstacles arising from domain specificity of scientific practices, find methodological frameworks to mitigate them cognitive obstacles: opacity of practices; conceptual divides; conflicting epistemic values; unstructured problem-solving environments (MacLeod 2016) methodological frameworks: use of model templates as platforms of ID collaboration coordination (MacLeod& PoS 2016; WP 2017) Hypothesis Epistemic benefits of are more likely to be realized by (i) addressing epistemic costs of while (ii) emulating methodologies of effective disciplinary research 8 / 19

19 2. Cognitive-methodological approach as Identify cognitive obstacles arising from domain specificity of scientific practices, find methodological frameworks to mitigate them cognitive obstacles: opacity of practices; conceptual divides; conflicting epistemic values; unstructured problem-solving environments (MacLeod 2016) methodological frameworks: use of model templates as platforms of ID collaboration coordination (MacLeod& PoS 2016; WP 2017) Hypothesis Epistemic benefits of are more likely to be realized by (i) addressing epistemic costs of while (ii) emulating methodologies of effective disciplinary research 8 / 19

20 2. Cognitive-methodological approach as Identify cognitive obstacles arising from domain specificity of scientific practices, find methodological frameworks to mitigate them cognitive obstacles: opacity of practices; conceptual divides; conflicting epistemic values; unstructured problem-solving environments (MacLeod 2016) methodological frameworks: use of model templates as platforms of ID collaboration coordination (MacLeod& PoS 2016; WP 2017) Hypothesis Epistemic benefits of are more likely to be realized by (i) addressing epistemic costs of while (ii) emulating methodologies of effective disciplinary research 8 / 19

21 2. Cognitive-methodological approach as Identify cognitive obstacles arising from domain specificity of scientific practices, find methodological frameworks to mitigate them cognitive obstacles: opacity of practices; conceptual divides; conflicting epistemic values; unstructured problem-solving environments (MacLeod 2016) methodological frameworks: use of model templates as platforms of ID collaboration coordination (MacLeod& PoS 2016; WP 2017) Hypothesis Epistemic benefits of are more likely to be realized by (i) addressing epistemic costs of while (ii) emulating methodologies of effective disciplinary research 8 / 19

22 Is interdisciplinary? as We should first ask: Is a discipline? YES (cf. Kuhn Structure 1962): conceptual ecology (&Põder mimeo 2017) well-established distinction between orthodox ( neoclassical) heterodox (evolutionary, complexity, institutional, feminist, ecological, etc.) Is interdisciplinary? depends (remember conceptual analysis) subjects: collaboration not so common (economists often come across as inflexible even arrogant) action: transfer exchange more common than integration (cf. imperialism) objects: tools (maths, experiments, simulation, neuroimaging) more than methods concepts 9 / 19

23 Is interdisciplinary? as We should first ask: Is a discipline? YES (cf. Kuhn Structure 1962): conceptual ecology (&Põder mimeo 2017) well-established distinction between orthodox ( neoclassical) heterodox (evolutionary, complexity, institutional, feminist, ecological, etc.) Is interdisciplinary? depends (remember conceptual analysis) subjects: collaboration not so common (economists often come across as inflexible even arrogant) action: transfer exchange more common than integration (cf. imperialism) objects: tools (maths, experiments, simulation, neuroimaging) more than methods concepts 9 / 19

24 Is interdisciplinary? as We should first ask: Is a discipline? YES (cf. Kuhn Structure 1962): conceptual ecology (&Põder mimeo 2017) well-established distinction between orthodox ( neoclassical) heterodox (evolutionary, complexity, institutional, feminist, ecological, etc.) Is interdisciplinary? depends (remember conceptual analysis) subjects: collaboration not so common (economists often come across as inflexible even arrogant) action: transfer exchange more common than integration (cf. imperialism) objects: tools (maths, experiments, simulation, neuroimaging) more than methods concepts 9 / 19

25 The rise of behavioural as Historical background: ordinal revolution as s escape from psychology (see Hs CJE 2010) Three lines of recent comeback of psychology to in BE (see Ma lecka& forthcoming) 1 Behavioural Decision Research (Tversky, Kahneman, Lichtenstein, Slovic et al.) risk preference (Prospect Theory; Rank-Dependent Utility Theory; Regret Theory) 2 Operant psychology (Herrnstein, Ainslie et al.) time preference (hyperbolic, quasi-hyperbolic, subadditive discounting) 3 Social psychology social preference (reciprocal fairness, distributive fairness, team preference) social norms; cf. JEL classification altruism [D64] (1993) 10 / 19

26 The rise of behavioural as Historical background: ordinal revolution as s escape from psychology (see Hs CJE 2010) Three lines of recent comeback of psychology to in BE (see Ma lecka& forthcoming) 1 Behavioural Decision Research (Tversky, Kahneman, Lichtenstein, Slovic et al.) risk preference (Prospect Theory; Rank-Dependent Utility Theory; Regret Theory) 2 Operant psychology (Herrnstein, Ainslie et al.) time preference (hyperbolic, quasi-hyperbolic, subadditive discounting) 3 Social psychology social preference (reciprocal fairness, distributive fairness, team preference) social norms; cf. JEL classification altruism [D64] (1993) 10 / 19

27 The rise of behavioural as Historical background: ordinal revolution as s escape from psychology (see Hs CJE 2010) Three lines of recent comeback of psychology to in BE (see Ma lecka& forthcoming) 1 Behavioural Decision Research (Tversky, Kahneman, Lichtenstein, Slovic et al.) risk preference (Prospect Theory; Rank-Dependent Utility Theory; Regret Theory) 2 Operant psychology (Herrnstein, Ainslie et al.) time preference (hyperbolic, quasi-hyperbolic, subadditive discounting) 3 Social psychology social preference (reciprocal fairness, distributive fairness, team preference) social norms; cf. JEL classification altruism [D64] (1993) 10 / 19

28 The rise of behavioural as Historical background: ordinal revolution as s escape from psychology (see Hs CJE 2010) Three lines of recent comeback of psychology to in BE (see Ma lecka& forthcoming) 1 Behavioural Decision Research (Tversky, Kahneman, Lichtenstein, Slovic et al.) risk preference (Prospect Theory; Rank-Dependent Utility Theory; Regret Theory) 2 Operant psychology (Herrnstein, Ainslie et al.) time preference (hyperbolic, quasi-hyperbolic, subadditive discounting) 3 Social psychology social preference (reciprocal fairness, distributive fairness, team preference) social norms; cf. JEL classification altruism [D64] (1993) 10 / 19

29 The rise of behavioural as Historical background: ordinal revolution as s escape from psychology (see Hs CJE 2010) Three lines of recent comeback of psychology to in BE (see Ma lecka& forthcoming) 1 Behavioural Decision Research (Tversky, Kahneman, Lichtenstein, Slovic et al.) risk preference (Prospect Theory; Rank-Dependent Utility Theory; Regret Theory) 2 Operant psychology (Herrnstein, Ainslie et al.) time preference (hyperbolic, quasi-hyperbolic, subadditive discounting) 3 Social psychology social preference (reciprocal fairness, distributive fairness, team preference) social norms; cf. JEL classification altruism [D64] (1993) 10 / 19

30 Illustration from models of social preference as Fehr Schmidt (QJE 1999): outcome-based fairness U i (π i, π j ) = π i α i max {π j π i, 0} β i max {π i π j, 0} i j, β i α i, 0 β i < 1 Rabin (AER 1993): intention-based fairness U i (a i, b j, c i ) = π i (a i, b j ) + f j (b j, c i ) [1 + f i (a i, b j )] f j = player i s belief about how kind j is being to i f i = player i s kindness to j 1 f j, f i 1/2 11 / 19

31 Illustration from models of social preference as Fehr Schmidt (QJE 1999): outcome-based fairness U i (π i, π j ) = π i α i max {π j π i, 0} β i max {π i π j, 0} i j, β i α i, 0 β i < 1 Rabin (AER 1993): intention-based fairness U i (a i, b j, c i ) = π i (a i, b j ) + f j (b j, c i ) [1 + f i (a i, b j )] f j = player i s belief about how kind j is being to i f i = player i s kindness to j 1 f j, f i 1/2 11 / 19

32 A recipe of behavioral as Camerer Loewenstein (Advances in BE 2004, p. 7) First, identify normative assumptions or models that are ubiquitously used by economists, such as Bayesian updating, expected utility, discounted utility. Second, identify anomalies i.e., demonstrate clear violations of the assumption or model, painstakingly rule out alternative explanations (such as subjects confusion or transactions costs). Third, use the anomalies as inspiration to create alternative theories that generalize existing models. A fourth step is to construct economic models of behavior using the behavioral assumptions from the third step, derive fresh implications, test them. 12 / 19

33 The rise of behavioural as Observation: In most cases, behavioural insights were integrated by stretching economic models within entrenched methodological conceptual frameworks, e.g. constrained maximization, equilibrium analysis, belief-preference-choice schema, consequentialist utilitarianism. Criticism by e.g. Berg&Gigerenzer (HEI 2010) Much of BE is neoclassical in disguise, these as if approaches should be given up for psychological realism. Main point drawing on Section 1 Epistemic benefits of BE are incremental, resulting from integration of psychological ideas findings into existing economic models. 13 / 19

34 The rise of behavioural as Observation: In most cases, behavioural insights were integrated by stretching economic models within entrenched methodological conceptual frameworks, e.g. constrained maximization, equilibrium analysis, belief-preference-choice schema, consequentialist utilitarianism. Criticism by e.g. Berg&Gigerenzer (HEI 2010) Much of BE is neoclassical in disguise, these as if approaches should be given up for psychological realism. Main point drawing on Section 1 Epistemic benefits of BE are incremental, resulting from integration of psychological ideas findings into existing economic models. 13 / 19

35 The rise of behavioural as Observation: In most cases, behavioural insights were integrated by stretching economic models within entrenched methodological conceptual frameworks, e.g. constrained maximization, equilibrium analysis, belief-preference-choice schema, consequentialist utilitarianism. Criticism by e.g. Berg&Gigerenzer (HEI 2010) Much of BE is neoclassical in disguise, these as if approaches should be given up for psychological realism. Main point drawing on Section 1 Epistemic benefits of BE are incremental, resulting from integration of psychological ideas findings into existing economic models. 13 / 19

36 as Historical background: Humans as ontologically distinct from Nature according to Aristotle Mill (Des Roches et al. forthcoming) Contemporary background: Human-Environment Interface, Coupled Human Natural Systems (CHANS), the Anthropocene wicked socio-environmental problems need for involving both natural social sciences. Two kinds of interaction between ecology 1 Ecological : e.g. valuation of global ecosystem services (Costanza et al. Nature 1997; GEC 2014) 2 Environmental : e.g. cost-benefit analysis, management of renewable natural resources (forestry fishery) 14 / 19

37 as Historical background: Humans as ontologically distinct from Nature according to Aristotle Mill (Des Roches et al. forthcoming) Contemporary background: Human-Environment Interface, Coupled Human Natural Systems (CHANS), the Anthropocene wicked socio-environmental problems need for involving both natural social sciences. Two kinds of interaction between ecology 1 Ecological : e.g. valuation of global ecosystem services (Costanza et al. Nature 1997; GEC 2014) 2 Environmental : e.g. cost-benefit analysis, management of renewable natural resources (forestry fishery) 14 / 19

38 as Historical background: Humans as ontologically distinct from Nature according to Aristotle Mill (Des Roches et al. forthcoming) Contemporary background: Human-Environment Interface, Coupled Human Natural Systems (CHANS), the Anthropocene wicked socio-environmental problems need for involving both natural social sciences. Two kinds of interaction between ecology 1 Ecological : e.g. valuation of global ecosystem services (Costanza et al. Nature 1997; GEC 2014) 2 Environmental : e.g. cost-benefit analysis, management of renewable natural resources (forestry fishery) 14 / 19

39 as Historical background: Humans as ontologically distinct from Nature according to Aristotle Mill (Des Roches et al. forthcoming) Contemporary background: Human-Environment Interface, Coupled Human Natural Systems (CHANS), the Anthropocene wicked socio-environmental problems need for involving both natural social sciences. Two kinds of interaction between ecology 1 Ecological : e.g. valuation of global ecosystem services (Costanza et al. Nature 1997; GEC 2014) 2 Environmental : e.g. cost-benefit analysis, management of renewable natural resources (forestry fishery) 14 / 19

40 as Observation: Mainstream economists are sceptical about the rigour of ecological, but accept environmental as a well-established sub-field in. Issues on value Controversies around ecological indicate problems with positive-normative distinction in ( fact-value distinction in science in general); I sidestep them here. Main point drawing on Section 1 Given cognitive obstacles of, at least in the short run, we expect incremental epistemic benefits from environmental. 15 / 19

41 as Observation: Mainstream economists are sceptical about the rigour of ecological, but accept environmental as a well-established sub-field in. Issues on value Controversies around ecological indicate problems with positive-normative distinction in ( fact-value distinction in science in general); I sidestep them here. Main point drawing on Section 1 Given cognitive obstacles of, at least in the short run, we expect incremental epistemic benefits from environmental. 15 / 19

42 as Observation: Mainstream economists are sceptical about the rigour of ecological, but accept environmental as a well-established sub-field in. Issues on value Controversies around ecological indicate problems with positive-normative distinction in ( fact-value distinction in science in general); I sidestep them here. Main point drawing on Section 1 Given cognitive obstacles of, at least in the short run, we expect incremental epistemic benefits from environmental. 15 / 19

43 Case study: renewable resources at Tahvonen bio-economic optimization Lab (HY) as Uses a collaborative modelling framework that we call substitutive model-coupling, which takes established frameworks from two disciplines that both address a given set of problems (harvesting renewable natural resources) in a similar way on similar scales; replaces less accurate elements from one field which are typically outside its expertise with those of the other field. Affordances: deep integration of models while preserving existing model building practices stards feedback between model components can improve each component (MacLeod& 2016) One of four ID modelling strategies we have identified in environmental science (MacLeod& WP 2017) 16 / 19

44 Case study: renewable resources at Tahvonen bio-economic optimization Lab (HY) as Uses a collaborative modelling framework that we call substitutive model-coupling, which takes established frameworks from two disciplines that both address a given set of problems (harvesting renewable natural resources) in a similar way on similar scales; replaces less accurate elements from one field which are typically outside its expertise with those of the other field. Affordances: deep integration of models while preserving existing model building practices stards feedback between model components can improve each component (MacLeod& 2016) One of four ID modelling strategies we have identified in environmental science (MacLeod& WP 2017) 16 / 19

45 Case study: renewable resources at Tahvonen bio-economic optimization Lab (HY) as Uses a collaborative modelling framework that we call substitutive model-coupling, which takes established frameworks from two disciplines that both address a given set of problems (harvesting renewable natural resources) in a similar way on similar scales; replaces less accurate elements from one field which are typically outside its expertise with those of the other field. Affordances: deep integration of models while preserving existing model building practices stards feedback between model components can improve each component (MacLeod& 2016) One of four ID modelling strategies we have identified in environmental science (MacLeod& WP 2017) 16 / 19

46 Methodological framework of bio-economic substitutive model-coupling as Figur: from Tahvonen (2013); modified 17 / 19

47 : Lessons for economists non-economists as Whether is interdisciplinary or not depends on how you unpack the concept. Totally new ID models or theories are unlikely; case studies (model-stretching in BE model-coupling in EE) suggest rather conservative methodological practice. Such conservative practice can nevertheless generate models with substantial ID benefits while hling cognitive obstacles. Lesson for economists Work with disciplinary heads but interdisciplinary hearts! Lesson for non-economists Challenge economists, but offer something they can use! 18 / 19

48 : Lessons for economists non-economists as Whether is interdisciplinary or not depends on how you unpack the concept. Totally new ID models or theories are unlikely; case studies (model-stretching in BE model-coupling in EE) suggest rather conservative methodological practice. Such conservative practice can nevertheless generate models with substantial ID benefits while hling cognitive obstacles. Lesson for economists Work with disciplinary heads but interdisciplinary hearts! Lesson for non-economists Challenge economists, but offer something they can use! 18 / 19

49 : Lessons for economists non-economists as Whether is interdisciplinary or not depends on how you unpack the concept. Totally new ID models or theories are unlikely; case studies (model-stretching in BE model-coupling in EE) suggest rather conservative methodological practice. Such conservative practice can nevertheless generate models with substantial ID benefits while hling cognitive obstacles. Lesson for economists Work with disciplinary heads but interdisciplinary hearts! Lesson for non-economists Challenge economists, but offer something they can use! 18 / 19

50 : Lessons for economists non-economists as Whether is interdisciplinary or not depends on how you unpack the concept. Totally new ID models or theories are unlikely; case studies (model-stretching in BE model-coupling in EE) suggest rather conservative methodological practice. Such conservative practice can nevertheless generate models with substantial ID benefits while hling cognitive obstacles. Lesson for economists Work with disciplinary heads but interdisciplinary hearts! Lesson for non-economists Challenge economists, but offer something they can use! 18 / 19

51 : Lessons for economists non-economists as Whether is interdisciplinary or not depends on how you unpack the concept. Totally new ID models or theories are unlikely; case studies (model-stretching in BE model-coupling in EE) suggest rather conservative methodological practice. Such conservative practice can nevertheless generate models with substantial ID benefits while hling cognitive obstacles. Lesson for economists Work with disciplinary heads but interdisciplinary hearts! Lesson for non-economists Challenge economists, but offer something they can use! 18 / 19

52 Acknowledgements This research is part of the project Model-building Across Disciplinary Boundaries:, Ecology,, funded by Academy of Finl (No : ). as I thank my collaborators: Miles MacLeod (Twente) Magdalena Ma lecka (Helsinki) Kaire Põder (EBS) 19 / 19