{"id":3010,"date":"2011-04-27T12:11:35","date_gmt":"2011-04-27T12:11:35","guid":{"rendered":"http:\/\/meeseeks:5080\/blog\/?p=3010"},"modified":"2011-04-27T12:11:35","modified_gmt":"2011-04-27T12:11:35","slug":"what-use-are-models","status":"publish","type":"post","link":"https:\/\/vukutu.com\/blog\/2011\/04\/what-use-are-models\/","title":{"rendered":"What use are models?"},"content":{"rendered":"<p>What are models for?\u00a0\u00a0 Most developers and users of models, in my experience, seem to assume the answer to this question is obvious and thus never raise it.\u00a0\u00a0 In fact, modeling has many potential purposes, and some of these conflict with one another.\u00a0\u00a0 Some of the criticisms made of particular models arise from mis-understandings or mis-perceptions of the purposes of those models, and the modeling activities which led to them.<br \/>\nLiking cladistics as I do, I thought it useful to list all the potential purposes of models and modeling.\u00a0\u00a0 The only discussion that considers this topic that I know is a brief discussion by game theorist Ariel Rubinstein in an appendix to a book on modeling rational behaviour (Rubinstein 1998).\u00a0 Rubinstein considers several alternative purposes for economic modeling, but ignores many others.\u00a0\u00a0 My list is as follows (to be expanded and annotated in due course):<\/p>\n<ul>\n<li>1. To better understand some real phenomena or existing system.\u00a0\u00a0 This is perhaps the most commonly perceived purpose of modeling, in the sciences and the social sciences.<\/li>\n<li>2. To predict (some properties of) some real phenomena or existing system.\u00a0 A model aiming to predict some domain may be successful without aiding our understanding\u00a0 of the domain at all.\u00a0 Isaac Newton&#8217;s model of the motion of planets, for example, was <a href=\"http:\/\/meeseeks:5080\/blog\/2009\/09\/nicolas-fatio-de-duillier\/\" target=\"_blank\">predictive but not explanatory<\/a>.\u00a0\u00a0 I understand that physicist David Deutsch argues that predictive ability is not an end of scientific modeling but a means, since it is how we assess and compare alternative models of the same phenomena. \u00a0\u00a0 This is wrong on both counts:\u00a0 prediction IS an end of much modeling activity (especially in business strategy and public policy domains), and it not the only means we use to assess models.\u00a0 Indeed, for many modeling activities, calibration and prediction are problematic, and so predictive capability may not even be\u00a0 possible as a form of model assessment.<\/li>\n<li>3. To manage or control (some properties of) some real phenomena or\u00a0existing system.<\/li>\n<li>4. To better understand a model of some real phenomena or existing system.\u00a0 Arguably, most of economic theorizing and modeling falls into this category, and Rubinstein&#8217;s preferred purpose is this type.\u00a0\u00a0 Macro-economic models, if they are calibrated at all, are calibrated against artificial, human-defined, variables such as employment, GDP and inflation, variables which may themselves bear a tenuous and dynamic relationship to any underlying economic reality.\u00a0\u00a0 Micro-economic models, if they are calibrated at all, are often calibrated with stylized facts, abstractions and simplifications of reality which economists have come to regard as representative of the domain in question.\u00a0\u00a0\u00a0 In other words, economic models are not not usually calibrated against reality directly, but against other models of reality.\u00a0 Similarly, large parts of contemporary mathematical physics (such as string theory and brane theory) have no access to any physical phenomena other than via the mathematical model itself:\u00a0 our only means of apprehension of vibrating strings in inaccessible dimensions beyond the four we live in, for instance, is through the mathematics of string theory.\u00a0\u00a0\u00a0 In this light, it seems nonsense to talk about the effectiveness, reasonable or otherwise, of mathematics in modeling reality, since how we could tell?<\/li>\n<li>5. To predict (some properties of) a model of some real phenomena or existing system.<\/li>\n<li>6. To better understand, predict or manage some intended (not-yet-existing) artificial system, so to guide its design and development.\u00a0\u00a0 Understanding a system that does\u00a0 not yet exist is qualitatively different to understanding an existing domain or system, because the possibility of calibration is often absent and because the model may act to define the limits and possibilities of subsequent design actions on the artificial system.\u00a0 The use of speech act theory (a model of natural human language) for the design of artificial machine-to-machine languages, or the use of economic game theory (a mathematical model of a stylized conceptual model of particular micro-economic realities) for the design of online auction sites are examples here.\u00a0\u00a0 The modeling activity can even be performative, helping to create the reality it may purport to describe, as in the case of the Black-Scholes model of options pricing.<\/li>\n<li>7. To provide a locus for discussion between relevant stakeholders in some business or public policy domain.\u00a0 Most large-scale business planning models have this purpose within companies, particularly when multiple partners are involved.\u00a0 Likewise, models of major public policy issues, such as epidemics, have this function.\u00a0 In many complex domains, such as those in public health, models provide a means to tame and domesticate the complexity of the domain.\u00a0 This helps stakeholders to jointly consider concepts, data, dynamics, policy options, and assessment of potential consequences of policy options, \u00a0all of which may need to be socially constructed.\u00a0<\/li>\n<li>8. To provide a means for identification, articulation and potentially resolution of trade-offs and their consequences in some business or public policy domain.\u00a0\u00a0 This is the case, for example, with models of public health risk assessment of chemicals or new products by environmental protection agencies, and models of epidemics deployed by government health authorities.<\/li>\n<li>9. To enable rigorous and justified thinking about the assumptions and their relationships to one another in modeling some domain.\u00a0\u00a0 Business planning models usually serve this purpose.\u00a0\u00a0 They may be used to inform actions, both to eliminate or mitigate negative consequences and to enhance positive consequences, as in <a href=\"http:\/\/meeseeks:5080\/blog\/2009\/01\/retroflexive-decision-making\/\" target=\"_blank\">retroflexive decision making<\/a>.<\/li>\n<li>10. To enable a means of assessment of managerial competencies of the people undertaking the modeling activity. Investors in start-ups know that the business plans of the company founders are likely to be out of date very quickly.\u00a0 The function of such business plans is not to model reality accurately, but to force rigorous thinking about the domain, and to provide a means by which potential investors can challenge the assumptions and thinking of management as way of probing the managerial competence of those managers.\u00a0\u00a0\u00a0 Business planning can thus be seen to be a form of epideictic argument, where arguments are assessed on their form rather than their content, as I have argued <a href=\"http:\/\/meeseeks:5080\/blog\/2008\/11\/epideictic-arguments\/\" target=\"_blank\">here<\/a>.<\/li>\n<li>11. As a means of play, to enable the exercise of human intelligence, ingenuity and creativity, in developing and exploring the properties of models themselves.\u00a0 This purpose is true of that human activity known as doing pure mathematics, and perhaps of most of that academic activity known as doing mathematical economics.\u00a0\u00a0 As I have argued <a href=\"http:\/\/meeseeks:5080\/blog\/2010\/07\/the-glass-bead-game-of-mathematical-economics\/\" target=\"_blank\">before<\/a>, mathematical economics is closer to theology than to the modeling undertaken in the natural sciences. I see nothing wrong with this being a purpose of modeling, although it would be nice if academic economists were honest enough to admit that their use of public funds was primarily in pursuit of private pleasures, and any wider social benefits from their modeling activities were incidental. <em><br \/>\n<\/em><\/li>\n<\/ul>\n<p><strong><em>POSTSCRIPT<\/em> (Added 2011-06-17):\u00a0 <\/strong>I have just seen Joshua Epstein&#8217;s 2008 discussion of the purposes of modeling in science and social science.\u00a0\u00a0 Epstein lists 17 reasons to build explicit models (in his words, although I have added the label &#8220;0&#8221; to his first reason):<\/p>\n<blockquote><p>0. Prediction<br \/>\n1. Explain (very different from predict)<br \/>\n2. Guide data collection<br \/>\n3. Illuminate core dynamics<br \/>\n4. Suggest dynamical analogies<br \/>\n5. Discover new questions<br \/>\n6. Promote a scientific habit of mind<br \/>\n7. Bound (bracket) outcomes to plausible ranges<br \/>\n8. Illuminate core uncertainties<br \/>\n9. Offer crisis options in near-real time. [Presumably, Epstein means &#8220;crisis-response options&#8221; here.]<br \/>\n10. Demonstrate tradeoffe\/ suggest efficiencies<br \/>\n11. Challenge the robustness of prevailing theory through peturbations<br \/>\n12. Expose prevailing wisdom as imcompatible with available data<br \/>\n13. Train practitioners<br \/>\n14. Discipline the policy dialog<br \/>\n15. Educate the general public<br \/>\n16. Reveal the apparently simple (complex) to be complex (simple).<\/p><\/blockquote>\n<p>These are at a lower level than my list, and I believe some of his items are the consequences of purposes rather than purposes themselves, at least for honest\u00a0modelers\u00a0(eg, #11, #12, #16).<br \/>\n<em>References:<\/em><br \/>\n<a href=\"http:\/\/www.hopkinsmedicine.org\/emergencymedicine\/Faculty\/JHH\/EPSTEIN_joshua.html\">Joshua M Epstein<\/a> [2008]: Why model? <em>Keynote address to the Second World Congress on Social Simulation<\/em>, George Mason University, USA.\u00a0 Available <a href=\"http:\/\/www.mit.edu\/~scienceprogram\/Materials\/Monday%20Materials\/WhyModel.pdf\" target=\"_blank\">here (PDF)<\/a>.<br \/>\nRobert E Marks [2007]:\u00a0 Validating simulation models: a general framework and four applied examples. <em>Computational Economics<\/em>, 30 (3): 265-290.<br \/>\nDavid F Midgley, Robert E Marks and D Kunchamwar [2007]:\u00a0 The building and assurance of agent-based models: an example and challenge to the field. <em>Journal of Business Research<\/em>, 60 (8): 884-893.<br \/>\nRobert Rosen [1985]: <em>Anticipatory Systems. <\/em>Pergamon Press.<br \/>\nAriel Rubinstein [1998]: <em>Modeling Bounded Rationality<\/em>. Cambridge, MA, USA: MIT Press.\u00a0 Zeuthen Lecture Book Series.<br \/>\nAriel Rubinstein [2006]: Dilemmas of an economic theorist. <em>Econometrica<\/em>, 74 (4): 865-883.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>What are models for?\u00a0\u00a0 Most developers and users of models, in my experience, seem to assume the answer to this question is obvious and thus never raise it.\u00a0\u00a0 In fact, modeling has many potential purposes, and some of these conflict with one another.\u00a0\u00a0 Some of the criticisms made of particular models arise from mis-understandings or [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,13,15,23,25,28,40,49,50,54,62,67,77,82],"tags":[],"class_list":["post-3010","post","type-post","status-publish","format-standard","hentry","category-argumentation","category-computer-science","category-computing-as-interaction","category-decision-theory","category-economics","category-forecasting","category-joint-action-society","category-marketing-strategy","category-mathematics","category-military-strategy","category-planning","category-prophecy","category-team-working","category-uncertainty","p1","y2011","m04","d27","h12"],"_links":{"self":[{"href":"https:\/\/vukutu.com\/blog\/wp-json\/wp\/v2\/posts\/3010","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vukutu.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/vukutu.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/vukutu.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/vukutu.com\/blog\/wp-json\/wp\/v2\/comments?post=3010"}],"version-history":[{"count":0,"href":"https:\/\/vukutu.com\/blog\/wp-json\/wp\/v2\/posts\/3010\/revisions"}],"wp:attachment":[{"href":"https:\/\/vukutu.com\/blog\/wp-json\/wp\/v2\/media?parent=3010"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vukutu.com\/blog\/wp-json\/wp\/v2\/categories?post=3010"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vukutu.com\/blog\/wp-json\/wp\/v2\/tags?post=3010"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}