Menu Expand
  1. Journals
  2. Economics, Finance, Business & Management
  3. Applied Economics Quarterly
  4. Vol. 64, Issue 4
  5. pp. 325–350

JOURNAL ARTICLE

Cite JOURNAL ARTICLE

Style
Kaiser, T. Can Social Interaction Based Expectations Create the Characteristics of the Business Cycle?. Applied Economics Quarterly, 64(4), 325-350. https://doi.org/10.3790/aeq.64.4.325
Kaiser, Timo Pascal "Can Social Interaction Based Expectations Create the Characteristics of the Business Cycle?" Applied Economics Quarterly 64.4, , 325-350. https://doi.org/10.3790/aeq.64.4.325
Kaiser, Timo Pascal: Can Social Interaction Based Expectations Create the Characteristics of the Business Cycle?, in: Applied Economics Quarterly, vol. 64, iss. 4, 325-350, [online] https://doi.org/10.3790/aeq.64.4.325
Format
Download

Can Social Interaction Based Expectations Create the Characteristics of the Business Cycle?

Kaiser, Timo Pascal

Applied Economics Quarterly, Vol. 64 (2018), Iss. 4 : pp. 325–350

Preview Login to order (PDF)

Additional Information

Article Details

Publisher Name
Duncker & Humblot
DOI
https://doi.org/10.3790/aeq.64.4.325
Language
English
Pages
26

Pricing

Individual
€ 24.00 (incl. local VAT if applicable)

Author Details

Timo Pascal Kaiser, Pforzheim University, Tiefenbronner Str. 65, 75175 Pforzheim, Germany.

References

  1. Albert, R. / Barabási, A.-L. (2002): “Statistical mechanics of complex networks”, Reviews of modern physics 74 (1), 47–97.  Google Scholar
  2. Alvarez, L. / Dhyne, E. / Hoeberichts, M./ Kwapil, C. / Bihan, H./ Lünnemann, P. / Martins, F. / Sabbatini, R. / Stahl, H. /Vermeulen, P. (2006): “Sticky prices in the euro area: a summary of new micro-evidence”, Journal of the European Economic association 4 (2 –3), 575–584.  Google Scholar
  3. Arrow, K. (1962): The rate and direction of inventive activity: Economic and social factors, in: ed. by Arrow, K., 609 –626, Princeton University Press, Princeton.  Google Scholar
  4. Asch, S. (1951): “Effects of group pressure upon the modification and distortion of judgments”, in: Groups, leadership, and men, ed. by Henle, M., 222 –236, Carnegie Press, Lancester.  Google Scholar
  5. Asch, S. (1956): “Studies of independence and conformity: I. A minority of one against a unanimous majority.”, Psychological monographs: General and applied 70 (9), 1 –70.  Google Scholar
  6. Barabási, A.-L. / Albert, R. (1999): “Emergence of scaling in random networks”, Science 286 (5439), 509–512.  Google Scholar
  7. Baron, R. /Vandello, J. / Brunsman, B. (1996): “The forgotten variable in conformity research: Impact of task importance on social influence.”, Journal of Personality and Social Psychology 71 (5), 915–927.  Google Scholar
  8. Barro, R. /Gordon, D. (1983): “Rules, discretion and reputation in a model of monetary policy”, Journal of monetary economics 12 (1), 101 –121.  Google Scholar
  9. Blinder, A. /Ehrmann, M./ Fratzscher, M./De Haan, J. / Jansen, D.-J. (2008): “Central bank communication and monetary policy: A survey of theory and evidence”, Journal of Economic Literature 46 (4), 910 –945.  Google Scholar
  10. Chari, V. / Kehoe, P. / McGrattan, E. (2000): “Sticky price models of the business cycle: can the contract multiplier solve the persistence problem?”, Econometrica 68 (5), 1151 –1179.  Google Scholar
  11. Chari, V. /Kehoe, P. / McGrattan, E. (2009): “New Keynesian models: not yet useful for policy analysis”, American Economic Journal: Macroeconomics 1 (1), 242 –266.  Google Scholar
  12. Chen, S.-H. /Chang, C.-L. /Tseng, Y.-H. (2014): “Social networks, social interaction and macroeconomic dynamics: How much could Ernst Ising help DSGE?”, Research in International Business and Finance 30, 312 –335.  Google Scholar
  13. Clarida, R. / Gali, J. / Gertler, M. (2000): “Monetary Policy Rules And Macroeconomic Stability: Evidence And Some Theory”, The Quarterly Journal of Economics 115 (1), 147 –180.  Google Scholar
  14. De Grauwe, P. (2011): “Animal spirits and monetary policy”, Economic theory 47 (2 –3), 423–457.  Google Scholar
  15. De Grauwe, P. (2012): “Lectures on behavioral macroeconomics”, Princeton University Press, Princeton.  Google Scholar
  16. Deutsch, M./ Gerard, H. B. (1955): “A study of normative and informational social influences upon individual judgment.”, The journal of abnormal and social psychology 51 (3), 629 – 636.  Google Scholar
  17. Dynan, K. E. (2000): “Habit formation in consumer preferences: Evidence from panel data”, American Economic Review, 391 –406.  Google Scholar
  18. Eggertsson, G. B. (2008): “Great Expectations and the End of the Depression”, The American Economic Review 98 (4), 1476 –1516.  Google Scholar
  19. Erdös, P. / Rényi, A. (1959): “On random graphs, I”, Publicationes Mathematicae (Debrecen) 6, 290–297.  Google Scholar
  20. Estrella, A./ Fuhrer, J. (2002): “Dynamic inconsistencies: Counterfactual implications of a class of rational-expectations models”, The American Economic Review 92 (4), 1013 – 1028.  Google Scholar
  21. Evans, G.W. / Honkapohja, S. (2001): “Learning and expectations in macroeconomics”, Princeton University Press, Princeton.  Google Scholar
  22. Franke, R. (2008): “A microfounded herding model and its estimation on German survey expectations”, Intervention: European Journal of Economics and Economic Policies 5, 305 – 332.  Google Scholar
  23. Fuhrer, J. (2008): “Expectations as a Source of Macroeconomic Persistence: Evidence from Survey Expectations in Dynamic Macro Models”, Working Papers, Federal Reserve Bank of Boston.  Google Scholar
  24. Galí, J. (2008): “Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework and Its Applications”, Princeton University Press, Princeton.  Google Scholar
  25. Galí, J. / Gertler, M. (1999): “Inflation dynamics: A structural econometric analysis”, Journal of monetary Economics 44 (2), 195 –222.  Google Scholar
  26. Hohnisch, M./Westerhoff, F. (2008): “Business cycle synchronization in a simple Keynesian macro-model with socially transmitted economic sentiment and international sentiment spill-over ”, Structural Change and Economic Dynamics 19 (3), 249 –259.  Google Scholar
  27. Kahneman, D. (2002): “Maps of bounded rationality: A perspective on intuitive judgment and choice”, Nobel prize lecture 8, 351 –401.  Google Scholar
  28. Keynes, J. (1936): “The General Theory of Employment, Interest, and Money”, New York: Harcourt, Brace & World.  Google Scholar
  29. Korniotis, G. M. (2010): “Estimating panel models with internal and external habit formation”, Journal of Business & Economic Statistics 28 (1), 145 –158.  Google Scholar
  30. Milani, F. (2007): “Expectations, learning and macroeconomic persistence”, Journal of monetary Economics 54 (7), 2065 –2082.  Google Scholar
  31. Milani, F. (2009): “Adaptive Learning and Macroeconomic Inertia in the Euro Area*”, Journal of Common Market Studies 47 (3), 579 –599.  Google Scholar
  32. Muth, J. F. (1961): “Rational expectations and the theory of price movements”, Econometrica: Journal of the Econometric Society 29 (3), 315 –335.  Google Scholar
  33. Newman, M. (2002): “Assortative mixing in networks”, Physical review letters 89 (20), 208701.  Google Scholar
  34. Newman, M. (2003): “Properties of highly clustered networks”, Physical Review E 68 (2), 026121.  Google Scholar
  35. Newman, M./ Park, J. (2003): “Why social networks are different from other types of networks”, Physical Review E 68 (3), 036122.  Google Scholar
  36. Newman, M./Watts, D. / Strogatz, S. (2002): “Random graph models of social networks”, Proceedings of the National Academy of Sciences, 99 (suppl 1), 2566 –2572.  Google Scholar
  37. Noldus, R. /Van Mieghem, P. (2015): “Assortativity in complex networks”, Journal of Complex Networks 3 (4), 507 –542.  Google Scholar
  38. Simon, H. A. (1959): “Theories of decision-making in economics and behavioral science”, The American economic review 49 (3), 253 –283.  Google Scholar
  39. Sims, C. A. (2003): “Implications of rational inattention”, Journal of monetary Economics 50 (3), 665 –690.  Google Scholar
  40. Stevenson, B. /Wolfers, J. (2011): “Trust in public institutions over the business cycle”, The American Economic Review 101 (3), 281 –287.  Google Scholar
  41. Watts, D./ Strogatz, S. (1998): “Collective dynamics of’small-world’networks.”, Nature 393 (6684), 440.  Google Scholar
  42. Westerhoff, F. (2010): “An agent-based macroeconomic model with interacting firms, socioeconomic opinion formation and optimistic / pessimistic sales expectations”, New Journal of Physics 12 (7), 075035.  Google Scholar
  43. Westerhoff, F. / Hohnisch, M. (2007): “A note on interactions-driven business cycles”, Journal of Economic Interaction and Coordination 2 (1), 85 –91.  Google Scholar
  44. Wilder, D. A. (1977): “Perception of groups, size of opposition, and social influence”, Journal of Experimental Social Psychology 13 (3), 253 –268.  Google Scholar
  45. Woodford, M. (2003): “Interest and prices: Foundations of a theory of monetary policy”, Princeton University Press, Princeton.  Google Scholar

Abstract

Abstract

This paper introduces social-interaction based expectations in a New Keynesian frame and compares the characteristics with that of the standard rational expectation model. Agents in this model are connected with each other and build their rational expectation on their neighborhood’s opinions and recent economic developments. Instead of precise forecast they use rule of thumbs which reflect whether they assume a positive or a negative future. As result an endogenous business cycle arises. The autocorrelation of the output gap is much larger than in a model with rational expectation and two-way causality from output gap to expectation about output gap arises while kurtosis decreases and correlation between inflation and output gap is quite negative. The use of different networks changes the characteristics of the model. Situations where people trust much more their social network than economic developments can lead to continual recession, boom, inflation or deflation.

JEL classifications: E10, E32, E71

Keywords: Rational expectations, non linear dynamics, animal spirit

Table of Contents

Section Title Page Action Price
Timo Pascal Kaiser: Can Social Interaction Based Expectations Create the Characteristics of the Business Cycle? 1
Abstract 1
1. Introduction 1
2. The New Keynesian Model 3
3. Expectations Formed by Social Interaction 4
3.1 Criticism on the Statements of Muth 4
3.2 Formal Description 5
3.2.1 Public Information 7
3.2.2 Network Information 7
4. Networks 8
4.1 Regular Networks 9
4.2 The Erdös-Renyi Random Network 9
4.3 The Small World Model of Watts and Strogatz 9
4.4 The Scale-free Model of Barabasi and Albert 9
4.5 The Assortative Mixing Model of Newman 1
5. Simulation 1
5.1 Business Cycles 1
5.2 The Persistence 1
5.3 Causality Between Expectation and Output Gap 1
5.4 Higher Moments 1
5.5 Correlation Between Output Gap and Inflation 1
6. Sensitivity 1
6.1 The Influence of X̂ and Π 1
6.2 The Influence of a and b 1
6.3 The Influence of the Shocks 1
7. Summary and Conclusion 1
References 1
A. Sensitivity 2
Table 2: Sensitivity: Autocorrelation 2
Table 3: Sensitivity: Correlation Between Inflation and Output Gap 2
Table 4: Sensitivity: P-value of Granger Causality from Expectation to the Output Gap 2
Table 5: Sensitivity: P-value of Granger Causality from Output Gap to Expectation 2
Table 6: Sensitivity: Kurtosis 2

Contact

Duncker & Humblot GmbH Carl-Heinrich-Becker-Weg 9 12165 Berlin, Deutschland T: +49 30 790006-0

Quick Navigation

2024 Duncker & Humblot GmbH

Powered by CloudPublish

We use cookies to ensure that you get the best experience on our website. Learn more about how we use cookies.