Policy Design in the Presence of Technological Change An Agent-based Approach

Transcription

1 Policy Design in he Presence of Technological Change An Agen-based Approach Disseraion zur Erlangung des Grades eines Dokors der Wirschafswissenschafen der Universiä Bielefeld vorgeleg von Philipp Haring Bielefeld, Mai 24

2 Firs advisor: Prof. Dr. Herber Dawid Second advisor: Jun.-Prof. Dr. Sander van der Hoog Dean: Prof. Dr. Thomas Braun

3 Diese Arbei wurde auf alerungsbesändigem Papier gemäß ISO 976 gedruck.

4 Acknowledgmens Wriing his disseraion would no have been possible wihou he assisance of many people. I am deeply graeful o my supervisor Prof. Dr. Herber Dawid for his guidance and encouragemen as well as for giving me he opporuniy o work in a mos inspiring, friendly, and srongly research-oriened environmen. He araced my aenion o he promising and ineresing field of agen-based compuaional economics, which is he mehodological foundaion of his hesis. My hanks go also o Jun.-Prof. Dr. Sander van der Hoog for being my second advisor and o Jun.-Prof. Dr. Anna Zaharieva for her willingness o be he hird advisor in my dispuaion. I am also indebed o my co-auhors Prof. Dr. Michael Neugar, Dr. Simon Gemkow and Dr. Klaus Wersching for he excellen eamwork ha led o a several quie ineresing research papers. Furhermore, I have o hank Dr. Beina Fincke and Gregor Böhl for helpful suggesions during he final sage of my disseraion. And I wish o hank Dr. Dennis Heimann, Serha Gezer, Michael Grohe, Michel Yevenunye Keoula, Ph.D, Diana Grieswald, Karin Borcher, and many oher colleagues from he Deparmen of Economics and Business Adminisraion for fruiful discussions and grea help in all circumsances. Moreover, financial suppor of he Universiy of Bielefeld, he Deparmen of Economics and Business Adminisraion and he FP-6 projec EURACE, financed by he European Commission is graefully acknowledged. Las bu no leas I am ruly hankful o my family for seing up all precondiions for his disseraion and especially o Julia for supporing and encouraging me during he course of his disseraion and for her paience when I had o spend pars of our weekends a he desk. Bielefeld, May 24 i

5 Conens Conens General Inroducion Capuring Firm Behavior 7. Inroducion Approaches o modeling firm decisions in ACE: a brief survey A Managemen Science Approach o Model Firm s Decision Making.4 Conclusions A Appendix A. Overall Srucure A.2 Consumpion goods producer A.3 Invesmen goods producer A.4 Households consumpion A.5 Labor marke Economic convergence Inroducion Relaed Lieraure The Model Overall Srucure Agens, Markes, and Decisions Paramerizaion and Validaion Policy Analysis General Seup, Mehod of Policy Evaluaion, Policies Considered Baseline Simulaion Wih No Policies Effec of Human Capial Policy Effec of Technology Policy Ineracion Effecs Robusness of Qualiaive Findings Discussion and Conclusion A Appendix A. Robusness Checks Sabilizaion Policies and Long Term Growh Inroducion The Model The Overall Srucure Decision-Making and Expecaion Formaion Skill Dynamics The Consumpion Goods Firm Technological Change ii

6 Conens iii Labor Marke Ineracion Consumpion Marke Ineracion Paramerizaion and Iniializaion Business Cycle Properies and Sylized Facs The Policy Analysis Policy Design The Baseline Scenario Wih No Policies Policy Effecs on he Business Cycle Volailiy The Consumpion Simulaing Policy The Invesmen Subsidy Policy The Technology Subsidy Policy Robusness Checks Sensiiviy of he Model Robusness of Policy Findings Discussion and Conclusion

7 Lis of Figures Lis of Figures. Dynamics of per capia oupu averaged over runs for differen values of he sock-ou probabiliy: χ =. (solid line), χ =. (dashed line), χ =.2 (doed line), χ =.8 (dashed-doed line) Dynamics of per capia oupu averaged over runs for differen values of he mark-up: 5% (solid line), % (dashed line), 5% (doed line), 2% (dashed-doed line) Dynamics of he mark-up charged by firms in a single simulaion run. The bold line gives he populaion mean he dashed line he mean plus/minus one sandard deviaion Dynamics of per capia oupu averaged over runs for synchronized (dashed line) and asynchronized (solid line) firm decisions The evoluion of oupu (a) inegraed labor markes, (b) separaed labor markes (black line: R; red line R2) The evoluion of echnologies (a) inegraed labor markes, (b) separaed labor markes (green line: echnological fronier; black line: average echnology used in R; red line: average echnology used in R2) The evoluion of mean prices (a) inegraed labor markes, (b) separaed labor markes (black line: R; red line R2) Commuers for inegraed labor markes (a) low general skill, (b) high general skill (black line: workers from R working in R; red line: workers from R2 working in R2; blue line: workers from R commuing o R2; green line: workers from R2 commuing o R) The effec of he human capial policy on oupu for (a) inegraed labor markes, (b) separaed labor markes (black line: R, red line: R2) The relaive effec of he human capial policy on (a) vinage choice and (b) general skill mix, compued as he effec on he raio of variable values from Region 2 o ha from Region (black line: inegraed labor marke, red line: separaed labor markes) The relaive effec of he human capial policy on (a) base wage offers, (b) uni coss, (c) prices and (d) mark ups, compued as he effec on he raio of variable values from Region 2 o ha from Region (black line: inegraed labor marke, red line: separaed labor marke) The effec of he human capial policy on he produciviy weighed capial socks for (a) inegraed labor markes, (b) separaed labor markes (black line: R, red line: R2) iv

8 Lis of Figures v 2.9 Effec of he Tech-policy on oupu in region (black line) and region 2 (red line) for (a) inegraed labor markes and (b) separaed labor markes The relaive effec of he echnology policy on (a) vinage choice and (b) average qualiy of he capial sock and (c) general skills of workers employed in a region and (d) average price posed by firms, compued as he he effec on he raio of variable values from Region 2 o ha from Region (black line: inegraed labor marke, red line: separaed labor marke) Comparison of he effec of he argeed (black line) and non-argeed (red line) Tech-policy on oupu in (a) region and (b) region 2, for inegraed labor markes Comparison of ineracion effecs for (a) inegraed and (b) separaed labor markes. (black line region, red line region 2) Effecs of a variaion of commuing coss on he evoluion of oupu ((a) and (b)), he effeciveness of he human capial policy ((c) and (d)), and he effeciveness of he echnology policy ((e) and (f)) in Region (lef column) and Region 2 (righ column) Effecs of a variaion of households price sensiiviy on he evoluion of oupu wihou policy ((a) and (b)), he effeciveness of he human capial policy ((c) and (d)), and he effeciveness of he echnology policy ((e) and (f)) in he lagging Region 2 for inegraed (lef column) and separaed (righ column) labor markes Effecs of a variaion of he speed of echnological change on he evoluion of oupu wihou policy ((a) and (b)), he effeciveness of he human capial policy ((c) and (d)), and he effeciveness of he echnology policy ((e) and (f)) in he lagging Region 2 for inegraed (lef column) and separaed (righ column) labor markes Effecs of a variaion of he depreciaion rae on he evoluion of oupu wihou policy ((a) and (b)), he effeciveness of he human capial policy ((c) and (d)), and he effeciveness of he echnology policy ((e) and (f)) in he lagging Region 2 for inegraed (lef column) and separaed (righ column) labor markes Effecs of a variaion of he discoun rae on he evoluion of oupu wihou policy ((a) and (b)), he effeciveness of he human capial policy ((c) and (d)), and he effeciveness of he echnology policy ((e) and (f)) in he lagging Region 2 for inegraed (lef column) and separaed (righ column) labor markes Effecs of a variaion of he unemploymen insurance replacemen rae on he evoluion of oupu wihou policy ((a) and (b)), he effeciveness of he human capial policy ((c) and (d)), and he effeciveness of he echnology policy ((e) and (f)) in he lagging Region 2 for inegraed (lef column) and separaed (righ column) labor markes Time series of (log) oupu (a), annual growh rae (b), annual inflaion rae (c), and unemploymen rae (d) Capial growh rae disribuions; unweighed and weighed by invesmen The Beveridge curve approximaed by means of a log-linear regression. 98

9 Lis of Figures vi 3.4 Firm size disribuion; Log Rank vs. Log Size plo of firm oupu (a) and evoluion of oupu disribuion (b). The color code indicaes he densiy of he populaion disribuion in he considered range of he variable oupu Evoluion of he produciviy disribuion (a) and evoluion of average produciviy of firms ha are low-producive (red) and highproducive (black) a = (b) Spline smoohed evoluion of he rajecory of aggregaed oupu (a) and quarerly growh raes (b) Spline smoohed evoluion of he rajecory of unemploymen raes (a), quarerly inflaion raes (b), capial sock (c); panel d: spline smoohed evoluion of capial produciviy (black), specific skills (red) and he unsmoohed evoluion of echnological fronier (green) Spline smoohed sandard deviaions (in percen of he mean) used as an indicaor for he heerogeneiy of firms wih respec o firm size (a) and echnological produciviy (b) Upper row: Spline smoohed evoluion of he capial produciviy of high- and low-ech firms (a) and corresponding produciviy raio beween high-ech and low-ech firms and oupu (b); lower row: Spline smoohed evoluion of he oupu of high- and low-ech firms (c) and corresponding oupu raio beween high-ech and low-ech firms and oupu (d) Spline smoohed evoluion of invesmens (a), capial socks (b), vinage choices (c) wih he corresponding raio high vs. low-ech firms (d), average general skills (d), and growh raes of produciviy for low-ech (red line) and high-ech (black line) firms (f) Spline smoohed raios high-ech vs. low-ech firms for base wage offers (a), wage offer for high-skilled (red line) and low-skilled (black line) workers (b) and uni labor coss (red line) and uni producion coss (black line) (c) Spline smoohed raios high vs. low-ech firms for prices (a), markups (b), earnings (c); spline smoohed evoluion of deb equiy raios (f) for high-ech (black line) and low-ech (red line) firms Effecs of he consumpion subsidy policy (a), invesmen subsidy policy (b), and echnology subsidy policy (c) on he volailiy of he business cycle Esimaed relaion beween business cycle volailiy and policy expendiures per GDP (averaged over all periods) for he consumpion subsidy policy (a), invesmen subsidy policy (b), and echnology subsidy policy (c) Effec of he consumpion subsidy policy on he deb GDP raio of he governmen measured a he end of he simulaion Policy effec on he average annual growh rae (lef) and he evoluion of he aggregaed oupu (righ) Policy effec on he nominal consumpion budge (a) and he deflaed consumpion budge (b) Policy effec on he average annual inflaion rae (lef) and he evoluion of he change of quarerly inflaion raes (righ)

10 Lis of Figures vii 3.9 Policy effec on planned oupu of firms (a), number of posed vacancies (b), unemploymen rae (c), share of posed vacancies remaining unfilled (d), quarerly growh rae of labor uni coss (e) and quarerly growh rae of deflaed labor uni coss (f) Policy effec on he average produciviy of he used capial sock (a) and he average vinage choice (b) Policy effec on he percenage sandard deviaion of firms oupu (a) and produciviy (b) Upper row: policy effec on he oupu level of high-ech (a) and low-ech firms (b); lower row: policy effec on he invesmen level of high-ech (c) and low-ech firms (d); Policy induced change of he raio of posed vacancies (a), base wage offers (b), wage offers for low-skilled workers (c) and wage offers for high-skilled workers (d) beween high- and low-ech firms Upper row: policy induced change of he raio of uni labor coss (a) and he growh rae of mark-ups on uni labor coss (b) beween highand low-ech firms; lower row: policy effec on he general skill level of high-ech (c) and low-ech firms (d) Policy induced change of he raio of unfilled vacancies (a) and producion rae (b) beween high- and low-ech firms Upper row: policy effec on he vinage choice of high (a) and low-ech firms (b); lower row: policy effec on he average capial produciviy of high (c) and low-ech firms (d) Policy effec of he invesmen subsidizing policy on he public deb measured as deb o GDP raio a monhs Spline-smoohed policy effecs of he invesmen subsidizing policy on quarerly growh raes of oupu (a) and he evoluion of aggregaed oupu Policy effec on invesmens (a) and capaciy uilizaion (b) Policy effec on he aggregaed level of planned oupu (a), producion rae (b), nominal (c) and deflaed consumpion budge (d) Policy effec on he average annual inflaion rae (lef) and he evoluion of he change in he quarerly inflaion raes (righ) Policy induced change of he growh rae of uni labor coss (a); policy effec on he number of posed vacancies (b), he share of posed vacancies ha remains unfilled (c); policy induced change of he unemploymen rae (d) Policy effec on he average produciviy of he capial sock (a) and he average vinage choice of invesing firms (b) Policy effec on he percen sandard deviaion of firms oupu (a) and capial produciviy (b) Policy effec on he oupu level of high-ech (a) and low-ech firms (b) Policy induced change of he raio of base wage offers (a), wage offers for low-skilled workers (b) and high-skilled workers (c) and number of workers (d) beween high- and low-ech firms Policy induced change of he raio of uni labor coss (a), prices (b), and mark-ups (c) beween high- and low-ech firms Upper row: policy effec on he general skill level of high (a) and lowech firms (b); lower row: policy effec on he average specific skill level of high (c) and low-ech firms (d)

11 Lis of Figures viii 3.39 Upper row: policy effec on he vinage choice of high (a) and lowech firms (b); lower row: policy effec on he capial produciviy of high (c) and low-ech firms (d) Policy effec on he producion rae of high (a) and low-ech firms (b) Upper row: policy effec on he average raio beween purchased capial and exising capial of invesing high (a) and low-ech firms (b); lower row: policy induced change of he deviaion of he individual from he economy-wide produciviy growh for high (c) and low-ech firms (d) Spline-smoohed policy effecs of he echnology subsidizing on he governmen deb GDP raio (a) and he average annual growh rae (b) Spline-smoohed policy effecs of he echnology subsidizing on he evoluion of aggregaed oupu (a) and he evoluion of quarerly growh raes (b) Spline-smoohed policy effecs of he echnology subsidizing policy on he evoluion of he vinage choice (a) and he capial produciviy (b) Spline-smoohed policy effecs of he echnology subsidizing policy on he evoluion of posed vacancies (a), base wage offers (b), growh raes of uni labor coss (c), and oal consumpion budge (d) Policy effec on average annual inflaion rae (lef) and he evoluion of he change of quarerly inflaion raes (righ) Spline-smoohed policy effecs of he echnology subsidizing policy on he evoluion of invesmens (a) and he unemploymen rae (b) Policy effec on he percen sandard deviaion of firms oupu (a) and capial produciviy (b) Policy effec on he aggregaed oupu rajecory of high-ech (a) and low-ech firms (b) Policy effec on invesmens of high-ech (a) and low-ech firms (b) Upper row: policy effec on he vinage choice of high (a) and lowech firms (b); lower row: policy effec on he capial produciviy of high (c) and low-ech firms (d) Policy effec on he raio of capial produciviy (a), he workforce size (b) and he vacancy filling rae (c) beween high- and low-ech firms Policy effec on he base wage offers (a), wage offers for low-skilled workers (b), and wage offers for high-skilled workers (c) beween highand low-ech firms Policy effec on he general skill level of high-ech (a) and low-ech firms (b) Policy effec on he raio of uni labor coss (a) and prices (b) beween high- and low-ech firms Esimaed smooh funcions of he saisical mea-model explaining long-erm growh for he parameers of he simulaion model depreciaion rae δ (a), inensiy of choice γ C (b), invesmen planning horizon T LT (c), echnological progress q inv (d), deb repaymen period T Loan (e), Cenral bank base rae r C (f), hreshold full dividend payou d (g), consumpion adjusmen κ (h), expeced demand variance σd 2 (i), service level demand χs (j), wage updae ϕ (k), and unemploymen benefi percenage u (l)

12 Lis of Figures ix 3.57 Esimaed smooh funcions of he saisical mea-model explaining shor-erm volailiy for he parameers of he simulaion model growh (a), consumpion adjusmen κ (b), invesmen planning horizon T LT (c), maximum deferral period T Ex (d), deb repaymen period T Loan (e), Cenral bank base rae r C (f), deb rescaling facor ω (g), wage updae ϕ (h), service level demand χ S (i), expeced demand variance σd 2 (j), firm birh hazard rae hf B (k), and unemploymen benefi percenage u (l) Smooh erms for he inensiy of he consumpion subsidy esimaed for he GAM wih volailiy (a) and average growh rae (b) as dependen variables Join smooh erms for he policy inensiy of he consumpion subsidy and he parameer invesmen planning horizon T LT (a), expeced demand volailiy σd 2 (b), and service level of demand χs (c), esimaed for he GAM explaining he business cycle volailiy Join smooh erms for he policy inensiy of he consumpion subsidy and he parameer depreciaion rae δ (a), invesmen planning horizon T LT (b), speed of he fronier growh q inv (c), and he inensiy of consumers choice γ C, esimaed for he GAM explaining he average growh rae Smooh erms for he inensiy of he invesmen subsidy esimaed for he GAM wih volailiy (a) and average growh rae (b) as dependen variables Join smooh erms for he policy inensiy of he invesmen subsidy and he parameer invesmen planning horizon T LT (a), expeced demand volailiy σd 2 (b), and service level of demand χs (c), esimaed for he GAM explaining he business cycle volailiy Join smooh erms for he policy inensiy of he invesmen subsidy and he parameer depreciaion rae δ (a), invesmen planning horizon T LT (b), speed of he fronier growh q inv (c), and he inensiy of consumers choice γ C, esimaed for he GAM explaining he average growh rae Smooh erms for he inensiy of he echnology subsidy esimaed for he GAM wih volailiy (a) and average growh rae (b) as dependen variables Join smooh erms for he policy inensiy of he echnology subsidy and he parameer invesmen planning horizon T LT (a), expeced demand volailiy σd 2 (b), and service level of demand χs (c), esimaed for he GAM explaining he business cycle volailiy Join smooh erms for he policy inensiy of he echnology subsidy and he parameer depreciaion rae δ (a), invesmen planning horizon T LT (b), speed of he fronier growh q inv (c), and he inensiy of consumers choice γ C, esimaed for he GAM explaining he average growh rae Policy effecs of he consumpion (upper row), invesmen (middle row), and echnology subsidizing policy (lower row) on volailiy (lef column) and average growh raes (righ column) for differen iniial condiions of he economy

13 Lis of Tables Lis of Tables. Parameer seings Iniializaion of capial sock and skills Se-up and paramerizaion of he model Percen sandard deviaions of he cyclical componen of he ime series (second column) and cross-correlaions of he cyclical componens of each ime series wih he cyclical componen of oupu, led k periods (oher columns) Spline esimaed regression models for growh and volailiy x

14 General Inroducion General Inroducion Economies can be characerized as complex adapive sysems of heerogeneous agens in which he ineracion of agens a he micro level forms he macro properies of he economic sysem, hereby deermining he emergence of macro regulariies such as economic growh, unemploymen, and income disribuions. These global regulariies in urn feed back ino he deerminaion of he ineracions a he micro level. The resul is a dynamic sysem of ineracing agens and inerdependen feedback loops connecing he micro and macro level of he economy (Tesfasion, 26). This imporan aspec of he funcioning of economic sysems has widely been negleced in conemporary mainsream frameworks based on he paradigm of equilibrium models of represenaive agens wih full raionaliy. Unlike is mainsream counerpars, he mehodological approach agen-based compuaional economics is able o capure he complexiy of dynamical processes ha arise hrough he local ineracion of heerogeneous agens. Following Tesfasion (26), agen-based compuaional economics can be defined as he compuaional sudy of economic processes modeled as a dynamic sysem of ineracing agens; agens refers broadly o an encapsulaed collecion of daa and mehods represening an eniy residing in a compuaionally consruced world. Examples of possible agens include individuals (e.g. workers, consumers), social groups (households, firms), and insiuions (governmen, cenral bank, markes). Thus, agens can range from acive informaion gahering and decision making eniies ha communicae and inerac wih oher agens o passive insiuional agens wihou any acive social funcioning. A key aspec of he agen-based approach is is assumpion of boundedly raional agens. Bounded raionaliy means ha in decision making agens are limied o informaion hey have and agens do no fully observe all he consequences of heir own acions and ha of oher agens. Aggregae behavior in agen-based models is generaed from he boom up by explicily modeling he micro-level ineracion of he auonomous agens. Agens behave according o explici rules describing how differen agens ake differen decisions. This boom-up approach provides empirically based micro behavior and esablishes he emergence of srongly micro-founded macro phenomena hrough an aggregaion of he individual decision making. The complex sysem in which agens inerac evolve over ime so ha aggregae properies emerge ou of repeaed ineracions of he agens (Fagiolo and Rovenini, 22). The agen-based approach allows for a highly empirically grounded axonomic classificaion of agens by providing a sysemaic way o incorporae whaever axonomic classificaion seems o be useful for he explanaory sudy of a paricular economic phenomenon (LeBaron and Tesfasion, 28). Once a axonomy is specified, he se of agen-specific behavioral rules can be implemened, where he concree collecion of empirically founded rules is subjec o heir relevance for he paricular macroeconomic phenomena under sudy. Hence, as sressed by LeBaron and Tes-

15 General Inroducion 2 fasion (28), agen-based modeling provides a remendous flexibiliy o ailor he breadh and deph of he agens o paricular applicaions a hand. In his conex, issues relaed o keeping he model analyically racable ha consrain he scope of a model play a less prominen role for agen-based modeling. I is his high degree of flexibiliy ha makes agen-based compuaional economics o an appropriae ool for he evaluaion of economic policy measures. Generally, a policy analysis requires a horough undersanding of he underlying mechanisms driving he effecs of he policy under consideraion. The choice of candidae explanaory mechanisms and heir represenaion in a model are herefore crucial for he resuls of he policy analysis, where a consideraion of only one or a subse of possible explanaory mechanisms can resul in misleading policy recommendaions (see Dawid and Neugar, 2). Such a horough exploraion of differen alernaive mechanisms is, however, hardly possible in a model framework ha has o ake accoun of analyical racabiliy. Unlike mos sandard models, agen-based models can incorporae differen possible channels in one framework in a flexible manner. The comprehensiveness of agen-based macroeconomic models allows hereby no only o consider differen possible mechanisms bu also o examine he emergence of simulaneous policy effecs on differen economic figures. Furhermore, since one of he enes of agen-based modeling are ou-of-equilibrium dynamics of a complex evolving sysem, his approach enables a policy analysis on differen ime scales, where policy effecs can hen be ypically disinguished in shor-, medium-, and long-erm effecs. The requiremen of a new complemenary mehodological approach in macroeconomic heory has become eviden during he financial and economic crisis ha sared in 28. Sandard general equilibrium models were no able o predic he crisis and even afer he bubble had broken hey were no able o anicipae he severiy of he following downurn. Moreover, hese models provided lile guidance for policymakers on how o ge ou of he downward spiral (see, e.g., Sigliz, 2). I is herefore no surprising ha several policymakers have voiced concerns ha i is hard for hem o base heir decisions on exising mainsream models, which migh no be able o capure he mechanisms ha seem o be mainly responsible for he problems. To quoe former ECB Presiden Jean-Claude Triche: When he crisis came, he serious limiaions of exising economic and financial models immediaely became apparen.[...] Macro models failed o predic he crisis and seemed incapable of explaining wha was happening o he economy in a convincing manner. As a policy-maker during he crisis, I found he available models of limied help. In fac, I would go furher: in he face of he crisis, we fel abandoned by convenional ools. Jean-Claude Triche also skeched properies of economic models ha would make hem in his opinion more suiable o capure crucial properies of economic sysems and make hem more appealing o policy makers: We need o deal beer wih heerogeneiy across agens and he ineracion among hose heerogeneous agens. We need o enerain alernaive Quoed from he speech Reflecions on he naure of moneary policy non-sandard measures and finance heory by Jean-Claude Triche, Presiden of he ECB given as opening address a he ECB Cenral Banking Conference Frankfur, 8 November 2. The ex of he full speech is available a hp:// (las accessed on April, 3rd 24).

16 General Inroducion 3 moivaions for economic choices. [...] Agen-based modeling dispenses wih he opimizaion assumpion and allows for more complex ineracions beween agens. Such approaches are worhy of our aenion. Agen-based analyses have been carried ou for numerous policy areas, where sudies relaed o financial marke dynamics, banking regulaions, credi linkages and moneary policies have araced considerable aenion. There has also been research aiming a he developmen of comprehensive macroeconomic models using an agen-based approach. In his respec, a prominen example has been he EURACE projec ( An Agen-based Sofware Plaform for European Policy Design wih Heerogeneous Ineracing Agens: New Insighs from a Boom-Up Approach o Economic Modeling and Simulaion ) which was carried ou from 26 o 29 wihin he 6h European Framework Programme by a consorium of economiss and compuer scieniss (see, e.g., Deissenberg e al., 28). The agenda of his projec was o develop a simulaion plaform conaining a sofware environmen, graphical user inerfaces and an agen-based macroeconomic model wih srong empirical grounding, all ogeher providing a common framework o address issues of differen areas of economic policy. Examples of policy analyses ha have been carried ou wih he agen-based model developed during he projec (he EURACE model) can be found in, e.g., Dawid e al. (29, 22a, 28). The EURACE model is he basis for he work presened in his disseraion. 2 The hesis consiss of hree independen research papers all covering research quesions regarding agen-based macro modeling. Differen agen-based models are considered in he papers, where all models share he same roos ha reside in he EURACE model. The general aim of he disseraion is o apply he agen-based approach for analyzing concree srucural and fiscal policy measures and o obain new insighs from his analysis ha can be uilized in he process of economic policy design. The focus of he policy analysis is hereby on he inerplay of hese policy measures wih he process of echnological change. The reason why he role of echnological change is emphasized is ha echnological change is one of he main sources of dynamism in capialized economies and is herefore a main driver of economic growh (see, e.g., Freeman, 998). If, however, a policy measure ineracs wih he process of echnological change, hen i migh have a susained impac on he economic developmen in he medium and long erm. Therefore, one of he key policy quesions is wheher hese specific economic policies lead o unexpeced and non-rivial mediumand long-erm implicaions in he presence of echnological change. I is paricularly emphasized in how far hese implicaions emerge hrough ineracions and feedback loops of desired policy effecs wih he diffusion of echnologies, he dynamics of produciviy and skills, and he labor mobiliy across firms and beween regions. In his conex, a furher imporan policy quesion addressed in he policy analysis is how hese policy implicaions inerac wih differen insiuional seings of he economy under sudy. As discussed in Dawid (26), here are some properies of agen-based modeling ha make his approach appealing for he analysis of innovaion and echnological change. One of hem is he decenralized decision making of heerogeneous ineracing agens, which is also an inheren characerisic of he process of echnological change. Dawid (26) argues, innovaion and echnological progress can be characerized as a decenralized dynamic search process, in which heerogeneous firms search for new echnologies under srong uncerainy, hereby being inerlinked wih 2 The auhor of his hesis conribued o he EURACE projec as a member of he research group a he Bielefeld Universiy led by Herber Dawid.

17 General Inroducion 4 oher firms hrough marke and non-marke ineracions. Thus, micro-founded economic models such as agen-based models have he poenial o capure he essenial effecs influencing he phenomenon of echnological change. A policy analysis sressing he role of echnological change is clearly focused on he real sphere of he economy and here especially on he producion secor. Firms conribue o he process of echnological change by eiher developing new producs or processes, or by acquiring improved echnologies embodied in new machines. Accordingly, firms as he mos relevan acor in he producion secor mus be modeled wih a sronger emphasis han oher agens conained in a model of echnological change. Wha is, however, missing in he lieraure of agen-based modeling is a clear concepual basis for he choice of firms decision rules. This mehodological shorcoming of he agen-based approach is addressed in he firs of he hree papers of his hesis (see Chaper ). This paper reviews differen approaches o model firm behavior in agen-based simulaion models and proposes he Managemen Science Approach, where well documened heurisics pu forward in he managerial lieraure are used o capure he decision processes of firms. This approach is illusraed wihin he framework of an exend version of he EURACE model. Then, i is explored how robus he dynamics of his model is wih respec o changes of he firms decision rules wihin he se of rules proposed by he Managemen Science Approach. This paper is join work wih Herber Dawid 3 and has been published in he book Evoluion, Organizaion and Economic Behavior edied by Guido Bünsorf. In conras o he firs paper, which considers concepual issues of agen-based modeling, he wo oher papers conained in his disseraion provide concree policy analyses. The second paper, which can be found in Chaper 2, sudies he effeciveness of cohesion policies wih respec o convergence of regions. The policy analysis relies on simulaions carried ou wih he Eurace@Unibi model, which is a compleely revised and in many direcions exended and subsanially alered follow-up release of he EURACE model (see Dawid e al., 22b). A wo-region seup of he model is used o analyze shor-, medium-, and long-erm effecs of policies improving human capial and fosering he adopion of echnologies in lagging regions. In wo differen scenarios i is examined wheher and how he cohesion policies inerac wih he level of spaial inegraion of he wo local labor markes. Wih fully inegraed labor markes he human capial policy posiively affecs he economically sronger region bu reduces producion in he argeed weaker region. Subsidies for high echnology invesmen in he weaker region have a posiive local oupu effec and a negaive effec on he neighboring region, hereby fosering convergence. When labor markes are no inegraed boh policies suppor convergence. This paper is join work wih Herber Dawid and Michael Neugar 4 and has been acceped for publicaion in he Journal of Economic Dynamics and Conrol. In he hird paper in Chaper 3, he auhor proposes subsanial changes o he Eurace@Unibi model, where especially some of he refinemens o he producion secor inroduced afer he compleion of he EURACE projec have been revised. The resul of his major revision is basically a compleely new producion secor in which especially he invesmen decision of firms has been modeled in a consisen manner following he Managemen Science Approach. The added value of he revised model is demonsraed by showing ha he model generaes endogenous business cycles wih realisic properies and ha he model replicaes several sylized facs 3 Deparmen of Business Adminisraion and Economics and Insiue of Mahemaical Economics, Bielefeld Universiy, Germany 4 Deparmen of Law and Economics, Technical Universiy of Darmsad, Germany

18 General Inroducion 5 wih respec o business cycles, firm size and produciviy disribuions, and labor marke regulariies. This model is hen used o carry ou a policy analysis regarding he effeciveness of fiscal sabilizaion policies. The research quesions are hereby focused on long-erm implicaions of discreionary sabilizaion policies. In paricular, do fiscal sabilizaion policies affec he long-erm growh of he economy? If so, are he long-erm effecs growh-enhancing or growh-reducing? These quesions have again become relevan o he poliical and academic debae since governmens have been forced o spend considerable funds for economic simulus packages as a response o he recen economic crisis. The answers ha he economic lieraure provides are inconclusive. However, he heoreical lieraure has emphasized he imporance of srucural issues of he models such as he modeling approach of endogenous echnological change or sources of disurbances driving economic flucuaion in he models. In his conex, less aenion has been paid o he design of he considered fiscal sabilizaion policies. The imporance of he policy design for long-erm effecs of sabilizaion policies is demonsraed in he policy analysis of he hird paper by comparing a demandoriened consumpion policy and wo differen invesmen subvenion policies. The comparison shows ha all policies are equally successful in smoohing he business cycle bu differ in heir implicaions for he medium and long-erm growh of he economy. Therefore, no only modeling assumpions and srucural issues as sressed by he lieraure bu also he concree implemenaion of he policy seem o be imporan for he long-erm effecs of sabilizaion policies and should herefore be aken ino accoun when deciding abou sabilizaion policies. Besides deailed policy analyses sressing he imporance of he inerplay beween policies and several aspecs associaed wih he process of echnological change, he papers in Chaper 2 and 3 also conribue o he lieraure of agen-based modeling by proposing he use of generalized addiive models (GAM) wih penalized spline smoohers as saisical ools for he analysis of he simulaion oucome (see, e.g., Wood, 2, for a discussion of GAMs). In paricular, i is proposed o use GAMs o idenify policy effecs (Chaper 2 and 3) and o carry ou a sysemaic sensiiviy analysis of he model as well as robusness checks of policy findings, boh wih respec o a variaion of parameers conained in he model (Chaper 3). All agen-based models used in he simulaions for he hree papers of he hesis have been implemened in FLAME (Flexible Large-scale Agen-based Modeling Environmen) 5. FLAME is a simulaion environmen ha has been developed by compuer scieniss wihin he EURACE projec. The daa analysis for each of he papers has been based on he saisical sofware R by using a collecion of exising packages and self-wrien R-scrips. 5 See hp:// for more informaion (las accessed April, 4h, 24)

19 References 6 References Dawid, H. (26): Agen-based Models of Innovaion and Technological Change, in Handbook of Compuaional Economics, Volume II, ed. by L. Tesfasion and K. Judd, Norh-Holland, Dawid, H., S. Gemkow, P. Haring, and M. Neugar (29): On he effecs of skill upgrading in he presence of spaial labor marke fricions: an agenbased analysis of spaial policy design, Journal of Arifical Socieies and Social Simulaion JASSS, 2, 4. (22a): Labor marke inegraion policies and he convergence of regions: he role of skills and echnology diffusion, Journal of Evoluionary Economics, 22, Dawid, H., S. Gemkow, P. Haring, M. Neugar, K. Kabus, and K. Wersching (28): Skills, innovaion and growh: an agen-based policy analysis, Jahrbücher für Naionalökonomie und Saisik/Journal of Economics and Saisics, 228, Dawid, H., S. Gemkow, P. Haring, S. van der Hoog, and M. Neugar (22b): The Eurace@Unibi Model: An Agen-Based Macroeconomic Model for Economic Policy Design, Bielefeld Working Papers in Economics and Managemen No Available a SSRN: hp://ssrn.com/absrac= Dawid, H. and M. Neugar (2): Agen-based Models for Economic Policy Design, 37, Deissenberg, C., S. van der Hoog, and H. Dawid (28): Eurace: A massively parallel agen-based model of he european economy, Applied Mahemaics and Compuaion, 24, Fagiolo, G. and A. Rovenini (22): Macroeconomic policy in agen-based and DSGE models, Revue l OFCE, 24, Freeman, C. (998): The economics of echnical change, Trade, Growh and Technical Change, Cambridge, LeBaron, B. and L. Tesfasion (28): Modeling macroeconomies as openended sysems of ineracing agens, American Economic Review: Papers and Proceedings, 98, Sigliz, J. E. (2): Rehinking macroeconomics: wha failed, and how o repair i, Journal of he European Economic Associaion, 9, Tesfasion, L. (26): Agen-Based Compuaional Economics, in Handbook of Compuaional Economics, Volume II, ed. by L. Tesfasion and K. Judd, Norh- Holland, Wood, S. (2): Fas sable resriced maximum likelihood and marginal likelihood esimaion of semiparameric generalized linear models, Journal of he Royal Saisical Sociey, 73, 3 36.

20 Capuring Firm Behavior Chaper Capuring Firm Behavior in Agen-Based Models of Indusry Evoluion and Macroeconomic Dynamics. Inroducion The descripion of he dynamics emerging from he ineracion of differen ypes of economic acors, who independenly make decisions and ake acions, is a challenging ask underlying any analysis of marke dynamics, indusry evoluion or macroeconomic dynamics. This ask has been ackled using a number of differen approaches. In he area of Evoluionary Economics, he use of agen-based simulaion models has radiionally been an imporan ool and one ha coninues o arac an increasing amoun of research. Saring wih he pioneering work of Nelson and Winer (982) various aspecs of indusry dynamics have been explored using simulaion mehods boh in raher generic indusry frameworks and in specific applicaion areas aking ino accoun characerisic feaures of he considered indusry (see, e.g., surveys in Dawid, 26; Safarzynska and van den Bergh, 2). Recenly subsanial effor has also been invesed in he developmen of agen-based closed macroeconomic models ha capure he inerplay of differen markes and secors in he economy while a he same ime providing an explici represenaion of behavior of differen ypes of poenially heerogeneous acors and he insiuions governing heir (local) ineracion paerns (e.g. Dawid e al., 29; Delli Gai e al., 25; Dosi e al., 2; Silverberg and Verspagen, 993). In he radiion of Evoluionary Economics, his kind of work is based on he asserion ha economic sysems generically are no in equilibrium and aims o explore of properies ha emerge from cerain assumpions abou micro-behavior and micro-srucure. In conras o dynamic equilibrium models, where i is assumed ha he behavior of all acors is deermined by maximizaion of he own (iner-emporal) objecive funcion using correc expecaions abou he behavior of he oher acors, agenbased simulaion models need o provide explici consrucive rules ha describe how differen agens ake differen decisions. The need o provide such rules is no This chaper has been published as H. Dawid and P. Haring (22): Capuring Firm Behavior in Agen-Based Models of Indusry Evoluion and Macroeconomic Dynamics, in Evoluion, Organizaion and Economic Behavior, edied by G. Bünsorf, Edgar-Elgar. 7

21 Capuring Firm Behavior 8 only based on he basic convicion underlying hese models, ha in mos economic seings acual behavior of decision makers is far away from iner-emporally opimal behavior under raional expecaions, bu also on he fac ha in mos models incorporaing heerogeneiy among agens and explici ineracion proocols (e.g. marke rules) he characerizaion of dynamic equilibria is ouside he scope of analyical and numerical analysis. Given ha need o specify explici rules for all decisions aken by all acors in an agen-based model he deerminaion and moivaion of he implemened rules becomes a major modeling issue. The Wilderness of bounded raionaliy (Sims, 98) is a serious concern since a large number of differen approaches o model boundedly raional behavior and is adapaion have been pu forward in he lieraure and a his poin here is lile indicaion for he emergence of a widely acceped consensus ha provides empirically or heoreically well founded conceps for ackling his issue (see, e.g., Hommes, 29). Providing such conceps however seems imporan for several reasons. Firs and foremos, i would add o he credibiliy of agen-based models and he normaive implicaions derived from such models in he areas of firm sraegy, marke design or economic policy. Second, he comparison beween resuls derived in differen models capuring differen economic seings is faciliaed if hese models share a common approach o modeling cerain (sandard) decision processes, such as he consumpion choice of households or pricing and invesmen of firms. Third, if he srucure of he considered rules for a given ype of decision can be resriced, for example o a paramerized family of rules, he es for robusness of simulaion resuls becomes much easier, since i involves only he consideraion of parameer variaions raher han of srucural changes in he decision rule. The mos suiable approach o provide empirical or heoreical foundaions for cerain ypes of rules depends srongly on he ype of agen ha is o be modeled. Describing he decision rule of an individual choosing a consumpion good is very differen from capuring he rule deermining he ineres rae decisions of a cenral bank. In fac, he ineres rae decision of a cenral bank is one of he few ypes of decisions where here indeed seems o be some consensus abou he srucure of he corresponding decision rule wihin he agen-based models ha include a cenral bank. Since cenral banks have an ineres in making heir decision processes ransparen and predicable, here is somehing similar o publicly documened decision rules (like he Taylor rule) which can be easily implemened in an agen-based model. If we consider decisions aken by individuals raher han an insiuion like a cenral bank such documenaion of he rules or processes leading o a decision is missing. An obvious candidae o obain empirically founded insighs ino he decision processes of individuals in differen economic frameworks is he consideraion of experimenal evidence. The fas growing lieraure in experimenal and behavioral economics provides a rich basis o develop empirically grounded represenaions of individual decisions in agen based models. There is quie a bi of work linking experimenal wih agen-based work (see, e.g., he survey in Duffy, 26) and recenly aemps have been made o design individual decision and learning rules as well as expecaion rules in agen-based models in a way such ha hey closely resemble experimenal evidence (e.g. Arifovic and Ledyard, 28; Hommes, 29)). The focus of his aricle is on he represenaion of firm decisions in agen-based models. Mos decisions of firms ha are ypically considered in agen-based models are aken according o well srucured processes and are only o a small exen a he discreion of individual decision makers. Hence, evidence from laboraory experi-

22 Capuring Firm Behavior 9 mens migh be of limied use when developing models of firms decision rules. The fac ha firms in many domains indeed follow well esablished rouines or heurisics has been highlighed in he lieraure on evoluionary heory (Nelson, 25; Nelson and Winer, 982) bu is also eviden from considering he Managemen lieraure. For many decision problems relevan for a firm sandard decision heurisics have been developed in he corresponding lieraure in Managemen Science and Operaions Research. They are presened in he main exbooks for Business Sudies and have been a leas parly implemened in decision suppor sofware available o companies. Hence, for many decision problems of firms here exis well documened algorihms ha deermine or a leas srongly influence he way he corresponding decisions are aken in a large percenage of firms. Paying aenion o such decision algorihms and rying o implemen hem in an agen-based framework should provide addiional empirical grounding for he models and also lead o a sronger sandardizaion of he represenaion of firms decisions. The purpose of his aricle is o highligh how such an approach, which we call he Managemen Science Approach can be used in differen economic seings o derive descripive and in paricular normaive insighs ino firm behavior and policy design. Prior o he reamen of he Managemen Science Approach in he framework of a macroeconomic model (Secion 3) we will give a brief discussion and caegorizaion of he approaches o he modeling of firm decision ha are presen in he lieraure (Secion 2). A concluding discussion is given in Secion 4..2 Approaches o modeling firm decisions in ACE: a brief survey To pu he differen approaches for modeling firm decision processes ha have been pu forward in he agen-based lieraure ino perspecive i migh be useful o realize ha he role of firms and heir decision processes depends crucially on he research agenda underlying he sudy under consideraion. A leas hree differen branches of he lieraure ha have araced considerable aenion can be disinguished in his respec. Firs, papers ha deal wih he effecs of policy inervenions or changes in marke characerisics on marke oucomes, indusry dynamics or growh (e.g. Dawid e al., 29, 28; Dosi e al., 2; Li e al., 2; Malerba e al., 2; Nelson and Winer, 982; Winer, 984). Here he focus is no on he firms behavior, bu on he effecs of cerain changes in he economic environmen given he decision rules (and maybe heir adjusmen dynamics) of he firms. Obviously, differen ypes of decision rules for firms migh, in principle, generae quie differen effecs of hese change in he economic environmen. Therefore, alhough he exac form of he decision rules used migh no be of major imporance, he validiy of he derived marke design or policy conclusions is srongly affeced by he empirical foundaion of he considered rules and he robusness of he qualiaive conclusions wih respec o changes of he rules wihin an (empirically) reasonable range. The larges par of he ACE lieraure where firm behavior plays some role falls ino his caegory. Second, here is some lieraure exploring he characerisics of firm sraegies ha evolve in paricular marke frameworks (e.g. Dawid and Reimann, I should be noed ha we do no deal here wih issues of he organizaion of he firm including he organizaion of cerain decision processes. Experimenal, evoluionary and agen-based research has been very acive in his area (see, e.g., Chang and Harringon, 26), bu a his poin in Agenbased Compuaional Economics (ACE) models of indusry-dynamics and macro-dynamics he inner srucure of firms has no been explicily represened.