Recent years have seen a surge of applied work using bunching approaches, a development that is closely linked to the increased availability of administrative data. These approaches exploit the incentives for bunching created by discontinuities in the slope of choice sets (kinks) or in the level of choice sets (notches) to study the behavior of individuals and firms. Although the bunching approach was originally developed in the context of taxation, it is beginning to find applications in many other areas, such as social security, social insurance, welfare programs, education, regulation, private sector prices, and reference-dependent preferences. This review provides a guide to bunching estimation, discusses its strengths and weaknesses, surveys a range of applications across fields, and considers reasons for the ubiquity of kinks and notches.


Article metrics loading...

Loading full text...

Full text loading...


Literature Cited

  1. Allen E, Dechow P, Pope D, Wu G. 2016. Reference-dependent preferences: evidence from marathon runners. Manag. Sci. In press [Google Scholar]
  2. Almunia M, Lopez-Rodriguez D. 2015. Under the radar: the effects of monitoring firms on tax compliance Work. Pap., Univ. Warwick [Google Scholar]
  3. Bachas P, Soto M. 2016. Not(ch) your average tax system: corporate taxation under weak enforcement Work. Pap., Univ. Calif., Berkeley [Google Scholar]
  4. Bastani S, Selin H. 2014. Bunching and non-bunching at kink points of the Swedish tax schedule. J. Public Econ. 109:36–49 [Google Scholar]
  5. Bertrand M, Kamenica E, Pan J. 2015. Gender identity and relative income within households. Q. J. Econ. 130:571–614 [Google Scholar]
  6. Best M, Brockmeyer A, Kleven H, Spinnewijn J, Waseem M. 2015a. Production vs revenue efficiency with limited tax capacity: theory and evidence from Pakistan. J. Polit. Econ. 123:1311–55 [Google Scholar]
  7. Best M, Cloyne J, Ilzetzki E, Kleven H. 2015b. Interest rates, debt and intertemporal allocation: evidence from notched mortgage contracts in the UK Work. Pap., London School Econ. [Google Scholar]
  8. Best M, Kleven H. 2013a. Housing market responses to transaction taxes: evidence from notches and stimulus in the UK Work. Pap., London School Econ. [Google Scholar]
  9. Best M, Kleven H. 2013b. Optimal income taxation with career effects of work effort Work. Pap., London School Econ. [Google Scholar]
  10. Best M, Kleven H. 2016. Housing market responses to transaction taxes: evidence from notches and stimulus in the UK Work. Pap., London School Econ. [Google Scholar]
  11. Blinder AS, Rosen HS. 1985. Notches. Am. Econ. Rev. 75:736–47 [Google Scholar]
  12. Blundell R, MaCurdy T. 1999. Labor supply: a review of alternative approaches. Handbook of Labor Economics 3 O Ashenfelter, D Card 1559–695 Amsterdam: North-Holland [Google Scholar]
  13. Brehm M, Imberman S, Lovenheim M. 2015. Achievement effects of individual performance incentives in a teacher merit pay tournament NBER Work. Pap. 21598 [Google Scholar]
  14. Brodeur A, Le M, Sangnier M, Zylberberg Y. 2016. Star Wars: The empirics strike back. Am. Econ. J. Appl. Econ. 8:11–32 [Google Scholar]
  15. Brown KM. 2013. The link between pensions and retirement timing: lessons from California teachers. J. Public Econ. 98:1–14 [Google Scholar]
  16. Burtless G, Hausman JA. 1978. The effect of taxation on labor supply: evaluating the Gary negative income tax experiment. J. Polit. Econ. 86:1103–30 [Google Scholar]
  17. Burtless G, Moffitt R. 1984. The effect of social security benefits on the labor supply of the aged. Retirement and Economic Behavior HJ Aaron, G Burtless 135–74 Washington, DC: Brookings Inst. [Google Scholar]
  18. Busse M, Lacetera N, Pope D, Silva-Risso J, Sydnor J. 2013. Estimating the effect of salience in wholesale and retail car markets. Am. Econ. Rev. 103:575–79 [Google Scholar]
  19. Camacho A, Conover E. 2011. Manipulation of social program eligibility. Am. Econ. J. Econ. Policy 3:241–65 [Google Scholar]
  20. Card D, Lee DS, Pei Z, Weber A. 2015. Inference on causal effects in a generalized regression kink design. Econometrica 83:2453–83 [Google Scholar]
  21. Chetty R. 2012. Bounds on elasticities with optimization frictions: a synthesis of micro and macro evidence on labor supply. Econometrica 80:969–1018 [Google Scholar]
  22. Chetty R, Friedman JN, Olsen T, Pistaferri L. 2010. Adjustment costs, firm responses, and labor supply elasticities: evidence from Danish tax records NBER Work. Pap. 15617 [Google Scholar]
  23. Chetty R, Friedman JN, Olsen T, Pistaferri L. 2011. Adjustment costs, firm responses, and micro vs. macro labor supply elasticities: evidence from Danish tax records. Q. J. Econ. 126:749–804 [Google Scholar]
  24. Chetty R, Friedman JN, Saez E. 2013. Using differences in knowledge across neighborhoods to uncover the impacts of the EITC on earnings. Am. Econ. Rev. 103:2683–721 [Google Scholar]
  25. Dawkins R. 2011. The tyranny of the discontinuous mind. New Statesman Dec. 19. http://www.newstatesman.com/blogs/the-staggers/2011/12/issue-essay-line-dawkins [Google Scholar]
  26. Dee T, Jacob B, Rockoff J, McCrary J. 2011. Rules and discretion in the evaluation of students and schools: the case of the New York Regents Examinations Work. Pap., Columbia Univ., New York [Google Scholar]
  27. DeFusco A, Paciorek A. 2016. The interest rate elasticity of mortgage demand: evidence from bunching at the conforming loan limit. Am. Econ. J. Econ. Policy. In press [Google Scholar]
  28. Devereux MP, Liu L, Loretz S. 2014. The elasticity of corporate taxable income: new evidence from UK tax records. Am. Econ. J. Econ. Policy 6:219–53 [Google Scholar]
  29. Diamond R, Persson P. 2016. The long-term consequences of teacher discretion in grading of high-stakes tests Work. Pap., Stanford Univ., Stanford, CA [Google Scholar]
  30. Dwenger N, Kleven H, Rasul I, Rincke J. 2016. Extrinsic and intrinsic motivations for tax compliance: evidence from a field experiment in Germany. Am. Econ. J. Econ. Policy. 8203–32 [Google Scholar]
  31. Einav L, Finkelstein A, Schrimpf P. 2015a. Bunching at the kink: implications for spending responses to health insurance contracts Work. Pap., Mass. Inst. Technol., Cambridge, MA [Google Scholar]
  32. Einav L, Finkelstein A, Schrimpf P. 2015b. The response of drug expenditure to non-linear contract design: evidence from Medicare Part D. Q. J. Econ. 130:841–99 [Google Scholar]
  33. Fack G, Landais C. 2016. The effect of tax enforcement on tax elasticities: evidence from charitable contributions in France. J. Public Econ. 133:23–40 [Google Scholar]
  34. Friedberg L. 1998. The Social Security earnings test and labor supply of older men. Tax Policy Econ. 12:121–50 [Google Scholar]
  35. Friedberg L. 2000. The labor supply effects of the Social Security earnings test. Rev. Econ. Stat. 82:48–63 [Google Scholar]
  36. Garicano L, Lelarge C, Van Reenen J. 2013. Firm size distortions and the productivity distribution: evidence from France Discuss. Pap. 7241, IZA, Bonn, Ger. [Google Scholar]
  37. Gelber A, Jones D, Sacks DW. 2014. Earnings adjustment frictions: evidence from the Social Security earnings test Work. Pap., Univ. Calif., Berkeley [Google Scholar]
  38. Gerber A, Malhotra N. 2008. Publication bias in empirical sociological research. Sociol. Methods Res. 37:3–30 [Google Scholar]
  39. Gillitzer C, Kleven H, Slemrod J. 2016. A characteristics approach to optimal taxation: line drawing and tax-driven product innovation. Scand. J. Econ. In press [Google Scholar]
  40. Gourio F, Roys N. 2014. Size-dependent regulations, firm size distribution, and reallocation. Quant. Econ. 5:377–416 [Google Scholar]
  41. Grubb M, Osborne M. 2015. Cellular service demand: biased beliefs, learning, and bill shock. Am. Econ. Rev. 105:234–71 [Google Scholar]
  42. Harasztosi P, Lindner A. 2015. Who pays for the minimum wage? Work. Pap., Univ. Coll. London [Google Scholar]
  43. Hausman JA. 1981. Labor supply. How Taxes Affect Economic Behavior HJ Aaron, JA Pechman 27–72 Washington, DC: Brookings Inst. [Google Scholar]
  44. Hausman JA. 1983. Stochastic problems in the simulation of labor supply. Behavioral Simulations in Tax Policy Analysis M Feldstein 47–69 Chicago, IL: Univ. Chicago Press [Google Scholar]
  45. Heckman J. 1983. Comment.. Behavioral Simulations in Tax Policy Analysis M Feldstein 70–82 Chicago, IL: Univ. Chicago Press [Google Scholar]
  46. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econ. 142:615–35 [Google Scholar]
  47. Ito K. 2014. Do consumers respond to marginal or average price? Evidence from nonlinear electricity pricing. Am. Econ. Rev. 104:537–63 [Google Scholar]
  48. Ito K, Sallee J. 2015. The economics of attribute-based regulation: theory and evidence from fuel-economy standards NBER Work. Pap. 20500 [Google Scholar]
  49. Kahneman D, Tversky A. 1979. Prospect theory: an analysis of decision under risk. Econometrica 47:263–92 [Google Scholar]
  50. Kleven H, Knudsen M, Kreiner C, Pedersen S, Saez E. 2011. Unwilling or unable to cheat? Evidence from a tax audit experiment in Denmark. Econometrica 79:651–92 [Google Scholar]
  51. Kleven H, Landais C, Saez E, Schultz E. 2014. Migration and wage effects of taxing top earners: evidence from the foreigners' tax scheme in Denmark. Q. J. Econ. 129:333–78 [Google Scholar]
  52. Kleven H, Landais C, Søgaard J. 2016. The breadwinner notch: a bunching approach to estimating reference-dependent preferences Unpublished manuscript, London School Econ. [Google Scholar]
  53. Kleven H, Schultz E. 2014. Estimating taxable income responses using Danish tax reforms. Am. Econ. J. Econ. Policy 6:4271–301 [Google Scholar]
  54. Kleven H, Waseem M. 2012. Behavioral responses to notches: evidence from Pakistani tax records Work. Pap., London School Econ. [Google Scholar]
  55. Kleven H, Waseem M. 2013. Using notches to uncover optimization frictions and structural elasticities: theory and evidence from Pakistan. Q. J. Econ. 128:669–723 [Google Scholar]
  56. Kopczuk W, Munroe D. 2015. Mansion tax: the effect of transfer taxes on the residential real estate market. Am. Econ. J. Econ. Policy 7:214–57 [Google Scholar]
  57. Koszegi B, Rabin M. 2006. A model of reference-dependent preferences. Q. J. Econ. 121:1133–65 [Google Scholar]
  58. Lacetera N, Pope D, Sydnor J. 2012. Heuristic thinking and limited attention in the car market. Am. Econ. Rev. 102:2206–36 [Google Scholar]
  59. Le Barbanchon T. 2016. Optimal partial unemployment insurance: evidence from bunching in the U.S.Work. Pap., Bocconi Univ., Milan [Google Scholar]
  60. Le Maire D, Schjerning B. 2013. Tax bunching, income shifting and self-employment. J. Public Econ. 107:1–18 [Google Scholar]
  61. Liu L, Lockwood B. 2015. VAT notches Work. Pap., Univ. Warwick [Google Scholar]
  62. MaCurdy T. 1981. An empirical model of labor supply in a life-cycle setting. J. Polit. Econ. 89:1059–85 [Google Scholar]
  63. MaCurdy T, Green D, Paarsch H. 1990. Assessing empirical approaches for analyzing taxes and labor supply. J. Hum. Resour. 25:415–90 [Google Scholar]
  64. Manoli D, Weber A. 2015. Nonparametric evidence on the effects of financial incentives on retirement decisions. Work. Pap., Univ. Mannheim [Google Scholar]
  65. Mirrlees JA. 1971. An exploration in the theory of optimal income taxation. Rev. Econ. Stud. 38:175–208 [Google Scholar]
  66. Moffitt R. 1990. The econometrics of kinked budget constraints. J. Econ. Perspect. 4:2119–39 [Google Scholar]
  67. Mosberger P. 2015. Tax optimization responses to the minimum tax scheme: bunching evidence Work. Pap., Central Eur. Univ., Budapest [Google Scholar]
  68. Persson P. 2014. Social insurance and the marriage market Work. Pap., Stanford Univ., Stanford, CA [Google Scholar]
  69. Pope D, Pope J, Sydnor J. 2015. Focal points and bargaining in housing markets. Games Econ. Behav. 93:89–107 [Google Scholar]
  70. Pope D, Simonsohn U. 2011. Round numbers as goals: evidence from baseball, SAT takers, and the lab. Psychol. Sci. 22:71–79 [Google Scholar]
  71. Rees-Jones A. 2014. Loss aversion motivates tax sheltering: evidence from U.S. tax returns. Work. Pap., Wharton School Univ. Penn., Philadelphia [Google Scholar]
  72. Saez E. 1999. Do taxpayers bunch at kink points? NBER Work. Pap. 7366 [Google Scholar]
  73. Saez E. 2002. Do taxpayers bunch at kink points? Work. Pap., Univ. Calif., Berkeley [Google Scholar]
  74. Saez E. 2010. Do taxpayers bunch at kink points?. Am. Econ. J. Econ. Policy 2:180–212 [Google Scholar]
  75. Sallee JM, Slemrod J. 2012. Car notches: strategic automaker responses to fuel economy policy. J. Public Econ. 96:981–99 [Google Scholar]
  76. Seim D. 2015. Behavioral responses to wealth taxes: evidence from Sweden Work. Pap., Stockholm Univ. [Google Scholar]
  77. Simonsohn U, Nelson L, Simmons J. 2014. P-curve: a key to the file-drawer. J. Exp. Psychol. Gen. 143:534–47 [Google Scholar]
  78. Slemrod J. 1985. An empirical test for tax evasion. Rev. Econ. Stat. 67:232–38 [Google Scholar]
  79. Slemrod J. 2010. Buenas notches: lines and notches in tax system design Work. Pap., Univ. Michigan, Ann Arbor [Google Scholar]
  80. Yelowitz AS. 1995. The Medicaid notch, labor supply, and welfare participation: evidence from eligibility expansions. Q. J. Econ. 110:909–39 [Google Scholar]

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error