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The Effect of Discretion on Procurement Performance. (2015). Spagnolo, Giancarlo ; Coviello, Decio ; Guglielmo, Andrea.
In: CEIS Research Paper.
RePEc:rtv:ceisrp:361.

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  1. Public Procurement and the Tension Between the Economically Most Advantageous Tender and Lowest Price. (2017). Holzl, Werner ; Pichler, Eva ; Klien, Michael ; Boheim, Michael.
    In: WIFO Studies.
    RePEc:wfo:wstudy:59256.

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  2. Can Audits Backfire? Evidence from Public Procurement in Chile. (2017). Pomeranz, Dina ; Litschig, Stephan ; Gerardino, Maria Paula.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:23978.

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  3. Can Audits Backfire? Evidence from Public Procurement in Chile. (2017). Pomeranz, Dina ; Litschig, Stephan ; Gerardino, Maria Paula.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:12529.

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  4. To bid or not to bid: That is the question: Public procurement, project complexity and corruption. (2016). Conti, Maurizio ; Bottasso, Anna ; Piccardo, Chiara ; Baldi, Simona .
    In: European Journal of Political Economy.
    RePEc:eee:poleco:v:43:y:2016:i:c:p:89-106.

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References

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  18. Column 1 reports the result for the Full Sample. Columns 2 through 5 report the results from 2000 and 2005. Significance at the 10% (*), at the 5% (**), and at the 1% (***).
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  19. Columns 2 and 4 report the results of a model that add as additional control the contracting authority experience, defined as the number of works awarded in the past year. Observations reports the number of observations. Standard Errors are clustered at region level. Significance at the 10% (*), at the 5% (**), and at the 1% (***). Source: Statistics for all the public construction works tendered between 2000 and 2005, with project value y ∈ [2, 5], in 100,000 euro.
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  21. COPYRIGHT Copyright 2015 by authors. All rights reserved. No part of this publication may be reproduced in any manner whatsoever without written permission except in the case of brief passages quoted in critical articles and reviews. MEDIA INQUIRIES AND INFORMATION For media inquiries, please contact Barbara Piazzi at +39 06 72595652/01 or by email at ufficiostampa@ceis.uniroma2.it. Our web site, www.ceistorvergata.it, contains more information about Center’s events, publications, and staff. DEVELOPMENT AND SUPPORT For information about contributing to CEIS Tor Vergata, please contact Carmen Tata at +39 06 72595615/01 or by e-mail at segr.ceis@economia.uniroma2.it
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  29. Figure 2: Rebates, Number of Bidders and Discretion 5 10 15 20 25 30 35 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Number of bidders Minimum Winning Maximum % rebate from the starting value Notes: Distribution of the rebates conditional on the number of bidders participating to the auction at different levels of discretion: high (in red) or low (in blue). Circles denote the minimum rebate; triangles the winning rebate; diamonds the maximum rebate. Vertical lines denote the 95% confidence intervals. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euros (2005 equivalents). Figure 3: Overall Distribution of the Auctions Reserve Price 0 .2 .4 .6 .8 Density −1 0 1 2 Dist. from the discontinuity, in 100000 euro Notes: The running variable is the difference between reservation price and the 300,000 euro threshold (red vertical line).
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  30. Figure 4: Discontinuity Test of Auctions Reserve Price Around the Threshold 0 .2 .4 .6 .8 −2 −1 0 1 2 Dist. from the discontinuity, in 100000 euro Notes: The running variable is the difference between the reserve price and the 300,000 euro threshold (vertical line). Circles are average observed values, the bold solid line is a kernel estimate (see McCrary, 2008), and the two thin lines are 95% confidence intervals.
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  51. Rows 1 and 2 report the Coefficient and Standard Errors of the of the Discontinuity Test according to McCrary (2008).
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  53. Source: Statistics for all the construction procurements works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents). The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  54. Source: Statistics for all the public construction works tendered between 2000 and 2005, with auction value y ∈ [2, 5], in 100,000 euros (2005 equivalents).
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  55. Source: Statistics for all the public construction works tendered between 2000 and 2005, with auction value y ∈ [2, 5], in 100,000 euros (2005 equivalents).
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  56. Source: Statistics for all the public construction works tendered between 2000 and 2005, with auction value y ∈ [2, 5], in 100,000 euros (2005 equivalents). Figure A.2: Estimated Effects at Different Bandwidths, Region-Year Fixed Effects 0 .2 .4 .6 .8 1 Effect 0 .2 .4 .6 .8 1 1.2 1.4 1.6 1.8 2 Bandwidth Trattativa Privata −25 −20 −15 −10 −5 0
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  57. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  58. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  59. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  60. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  61. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  62. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  64. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  65. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  66. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  67. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents). The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012) and works with missing value in the dependent variables are not dropped.
    Paper not yet in RePEc: Add citation now
  68. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents). The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  69. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents). The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  70. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents). The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
    Paper not yet in RePEc: Add citation now
  71. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents). The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  72. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euros (2005 equivalents).
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  73. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euros (2005 equivalents).
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  74. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euros (2005 equivalents).
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  75. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euros (2005 equivalents).
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  76. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euros (2005 equivalents). Figure 7: Estimated Effects at Different Bandwidths 0 .2 .4 .6 .8 Effect 0 .2 .4 .6 .8 1 1.2 1.4 1.6 1.8 2 Bandwidth Trattativa Privata −30 −20 −10 0 Effect 0 .2 .4 .6 .8 1 1.2 1.4 1.6 1.8 2 Bandwidth Number of Bidders −5 0 5
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  77. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euros (2005 equivalents). Figure A.3: Estimated Effects at Different Bandwidths, Local Linear Regression .1 .2 .3 .4 .5 Effect 0 .2 .4 .6 .8 1 1.2 1.4 1.6 1.8 2 Bandwidth Trattativa Privata −20 −15 −10 −5 0 5 Effect 0 .2 .4 .6 .8 1 1.2 1.4 1.6 1.8 2 Bandwidth Number of Bidders −4 −2 0 2 4
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  78. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euros (2005 equivalents). Figure A.4: Estimated Effects at Different Bandwidths, Local Linear Regression with Region-Year Fixed Effects 0 .2 .4 .6 .8 Effect 0 .2 .4 .6 .8 1 1.2 1.4 1.6 1.8 2 Bandwidth Trattativa Privata −25 −20 −15 −10 −5 0 Effect 0 .2 .4 .6 .8 1 1.2 1.4 1.6 1.8 2 Bandwidth Number of Bidders −5 0 5
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  79. Source: Statistics for all the public construction works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euros (2005 equivalents). The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  80. Source: Statistics for all the public construction works tendered between 2001 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  82. Source: Statistics for all the public constructon works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents). The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  83. Source: Statistics for all the public procurements works tendered between 2003 and 2005 and by the county and municipality of Turin, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  84. Source: Statistics for all the public road works tendered between 2000 and 2005, with auction value y ∈ [2, 5], in 100,000 euros (2005 equivalents).
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  85. Source: Statistics for all the public road works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents). The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  86. Spagnolo, G. 2012. Reputation, Competition and Entry in Procurement. International Journal of Industrial Organization, 30(3), 291-296.

  87. Spulber, D.F. 1990. Auctions and Contract Enforcement. Journal of Law, Economics and Organization, 6(2), 325-44.

  88. Standard Errors are adjusted for heteroskedasticity. Significance at the 10% (*), at the 5% (**), and at the 1% (***). Source: Statistics for all the public procurements works tendered between 2000 and 2005, with reserve price y ∈ [2, 5], in 100,000 euro (2005 equivalents).
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  89. Table 3: McCrary Discontinuity Test All Years 2000 2001 2002 2003 2004 2005 Discontinuity-0.154-0.194 0.146-0.185-0.253-0.282-0.549* (SE) (0.131) (0.300) (0.252) (0.237) (0.237) (0.262) (0.322) Notes: The running variable is the difference between the reserve price and the 300,000 euro threshold (in 100,000 euros).
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  90. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012) and works assigned with Trattativa Privata, one bidder and less than five invited bidder or the number of invited bidders is missing are dropped.
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  91. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012) and works assigned with Trattativa Privata, one bidder and only less than 5 invited bidder are dropped.
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  92. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012) and works assigned with Trattativa Privata, one bidder and only one invited bidder are dropped.
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  93. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012) and works executed in 2000 are dropped.
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  94. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012) and works executed in 2000 are dropped.
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  95. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012) and works from the North and Center of Italy.
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  96. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012) and works with missing values in the dependent variable are not dropped.
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  97. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  98. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  99. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  100. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  101. The number of observations is smaller compared the full sample described in Table 1, because we restrict the analysis the optimal bandwidth sample, as in Imbens and Kalyanaraman (2012).
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  102. Van der Klauw, W. 2002. Estimating the Effect of Financial Aid Offers on College Enrollment: a Regression-Discontinuity Approach. International Economic Review, 43(4), 12491287.
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  103. Yukins, C. R. 2008, Are IDIQs Inefficient? Sharing Lessons with the European Framework Contracting. Public Contracts Law Journal, 37, 545-568.
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  7. What do people ‘learn by looking’ at direct feedback on their energy consumption? Results of a field study in Southern France. (2017). Lazaric, Nathalie ; Marechal, Kevin ; Kendel, Adnane.
    In: Post-Print.
    RePEc:hal:journl:halshs-01630972.

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  8. What Do People Learn By Looking at Direct Feedback on their Energy Consumption? Results of a Field Study in Southern France. (2017). Maréchal, Kevin ; Lazaric, Nathalie ; Marechal, Kevin ; Kendel, Adnane.
    In: GREDEG Working Papers.
    RePEc:gre:wpaper:2017-19.

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  9. Scaling for economists: lessons from the non-adherence problem in the medical literature. (2017). List, John ; Suskind, Dana ; Lore, Danielle ; Al-Ubaydli, Omar.
    In: Artefactual Field Experiments.
    RePEc:feb:artefa:00616.

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  10. What do people ‘learn by looking’ at direct feedback on their energy consumption? Results of a field study in Southern France. (2017). Lazaric, Nathalie ; Marechal, Kevin ; Kendel, Adnane.
    In: Energy Policy.
    RePEc:eee:enepol:v:108:y:2017:i:c:p:593-605.

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  11. Scaling for Economists: Lessons from the Non-Adherence Problem in the Medical Literature. (2017). list, john ; Suskind, Dana ; Lore, Danielle ; Al-Ubaydli, Omar.
    In: Journal of Economic Perspectives.
    RePEc:aea:jecper:v:31:y:2017:i:4:p:125-44.

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  12. Can Myopic Loss Aversion Explain the Equity Premium Puzzle? Evidence from a Natural Field Experiment with Professional Traders. (2016). Metcalfe, Robert ; list, john ; Larson, Francis .
    In: NBER Working Papers.
    RePEc:nbr:nberwo:22605.

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  13. Can Myopic Loss Aversion Explain the Equity Premium Puzzle? Evidence from a Natural Field Experiment with Professional Traders. (2016). Metcalfe, Robert ; list, john ; Larson, Francis .
    In: Natural Field Experiments.
    RePEc:feb:natura:00534.

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  14. The Effect of Discretion on Procurement Performance. (2016). Spagnolo, Giancarlo ; Coviello, Decio ; Guglielmo, Andrea.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:11286.

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  15. The Effect of Discretion on Procurement Performance. (2016). Spagnolo, Giancarlo ; Coviello, Decio ; Guglielmo, Andrea.
    In: CEP Discussion Papers.
    RePEc:cep:cepdps:dp1427.

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  16. The Effect of Discretion on Procurement Performance. (2015). Spagnolo, Giancarlo ; Coviello, Decio ; Guglielmo, Andrea.
    In: CEIS Research Paper.
    RePEc:rtv:ceisrp:361.

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  17. Do Natural Field Experiments Afford Researchers More or Less Control than Laboratory Experiments? A Simple Model. (2015). list, john ; Al-Ubaydli, Omar.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:20877.

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  18. Do Natural Field Experiments Afford Researchers More or Less Control than Laboratory Experiments? A Simple Model. (2015). list, john ; Al-Ubaydli, Omar.
    In: Artefactual Field Experiments.
    RePEc:feb:artefa:00458.

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  19. The Effect of Discretion on Procurement Performance. (2015). Spagnolo, Giancarlo ; Coviello, Decio ; Guglielmo, Andrea.
    In: EIEF Working Papers Series.
    RePEc:eie:wpaper:1510.

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  20. What do we learn from public good games about voluntary climate action? Evidence from an artefactual field experiment. (2015). Lohse, Johannes ; Goeschl, Timo ; Kettner, Sara Elisa ; Schwieren, Christiane.
    In: Working Papers.
    RePEc:awi:wpaper:0595.

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  21. Car Mechanics in the Lab - Investigating the Behavior of Real Experts on Experimental Markets for Credence Goods. (2014). Sutter, Matthias ; Kerschbamer, Rudolf ; Beck, Adrian ; Qiu, Jianying .
    In: Working Papers.
    RePEc:inn:wpaper:2014-02.

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  22. Car mechanics in the lab: investigating the behavior of real experts on experimental markets for credence goods. (2014). Sutter, Matthias ; Kerschbamer, Rudolf ; Beck, Adrian ; Qiu, Jianying .
    In: Economics Working Papers.
    RePEc:eui:euiwps:eco2014/02.

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  23. On the Generalizability of Experimental Results in Economics: With A Response To Camerer. (2013). list, john ; Al-Ubaydli, Omar.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:19666.

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  24. Can Indifference Make the World Greener?. (2013). Ekström, Mathias ; Egebark, Johan ; Ekstrom, Mathias.
    In: Research Papers in Economics.
    RePEc:hhs:sunrpe:2013_0012.

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  25. Can Indifference Make the World Greener?. (2013). Ekström, Mathias ; Egebark, Johan ; Ekstrom, Mathias.
    In: Working Paper Series.
    RePEc:hhs:iuiwop:0975.

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  26. On the Generalizability of Experimental Results in Economics: With A Response To Camerer. (2013). list, john ; Al-Ubaydli, Omar.
    In: Artefactual Field Experiments.
    RePEc:feb:artefa:j0001.

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  27. Using field experiments to change the template of how we teach economics.. (2013). list, john.
    In: Artefactual Field Experiments.
    RePEc:feb:artefa:00389.

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  28. Opting-in: Participation bias in economic experiments. (2013). Wang, Carmen ; Slonim, Robert ; Garbarino, Ellen ; Merrett, Danielle .
    In: Journal of Economic Behavior & Organization.
    RePEc:eee:jeborg:v:90:y:2013:i:c:p:43-70.

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  29. On the Generalizability of Experimental Results in Economics: With a Response to Commentors. (2013). list, john ; Al-Ubaydli, Omar.
    In: CESifo Working Paper Series.
    RePEc:ces:ceswps:_4543.

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  30. When will there be Gift Exchange? Addressing the Lab-Field Debate with Laboratory Gift Exchange Experiments. (2013). Kessler, Judd .
    In: CESifo Working Paper Series.
    RePEc:ces:ceswps:_4161.

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  31. Identifying Confirmatory Bias in the Field: Evidence from a Poll of Experts. (2012). Logan, Trevon ; Sinkey, Michael J. ; Andrews, Rodney J..
    In: NBER Working Papers.
    RePEc:nbr:nberwo:18064.

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  32. Opting-In: Participation Biases in the Lab. (2012). Wang, Carmen ; Slonim, Robert ; Merrett, Danielle ; Garbarino, Ellen.
    In: IZA Discussion Papers.
    RePEc:iza:izadps:dp6865.

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  33. Do Option-like Incentives Induce Overvaluation? Evidence from Experimental Asset Markets. (2012). Kirchler, Michael ; Holmen, Martin ; Kleinlercher, Daniel.
    In: Working Papers in Economics.
    RePEc:hhs:gunwpe:0540.

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