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Incentive effects of funding contracts: an experiment

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Abstract

We examine the incentive effects of funding contracts on entrepreneurial effort and on allocative efficiency. We experiment with funding contracts that differ in the structure of investor repayment and, thus, in their incentives for the provision of entrepreneurial effort. Theoretically the replacement of a standard debt contract by a repayment-equivalent non-monotonic contract reduces effort distortions and increases efficiency. Likewise, distortions can be mitigated by replacing outside equity by a repayment-equivalent standard-debt contract. We test both hypotheses in the laboratory. Our results reveal that the incentive effects of funding contracts must be experienced before they are reflected in observed behavior. With sufficient experience, observed behavior is either consistent with or close to theoretical predictions and supports both hypotheses. If we allow for entrepreneur-sided manipulations of project outcomes, we find that non-monotonic contracts lose much of their appeal.

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Notes

  1. See, e.g., Romer (1990) and Aghion and Howitt (1992). For textbook treatments of growth economics, see, e.g., Aghion and Howitt (1998) and Barro and Sala-i-Martin (2003).

  2. For example, Malmendier and Tate (2005) have shown that CEO overconfidence can lead to corporate investment distortions among Forbes 500 CEO’s. More generally, Baker and Wurgler (2012) and Baker et al. (2007) survey literature in behavioral corporate finance that distinguishes between investor-sided and manager-sided behavioral effects. Although these empirical studies investigate settings that are fundamentally different from our entrepreneur-based external finance setting, they show that theoretical predictions, given the assumptions of self-interest and full rationality, require careful empirical and/or experimental evaluation, also in corporate finance settings.

  3. For simplicity we refer to cases where the entrepreneur retains the full return on a project as no-repayment contracts, even if no explicit repayment contract is written. Examples would include cases where the entrepreneurial project is fully subsidized or where entrepreneurs do not rely on external finance but self-finance instead.

  4. For example, DeJong et al. (1985) demonstrate the relevance of moral hazard with flat wage employment contracts. Fehr et al. (1993) and Irlenbusch and Sliwka (2005) show that agents’ effort levels increase in the generosity of flat wages. Fehr et al. (2007), on the other hand, report that bonus contracts outperform flat wage contracts, while Brandt and Charness (2004) investigate the impact of competitive imbalances and minimum wages. Contract design has also been shown in the field to affect behavior. For example, Lazear (2000) finds that replacing flat rate hourly pay by piece rates, for windshield installers, increases productivity, while Shearer (2004) reports a similar effect for workers in tree-planting.

  5. If the start-up cost is not larger than the lowest project return z 1, the financing problem is trivial.

  6. Due to the generality of feasible contracts and revenue distributions, it is possible to find contracts that imply a strictly negative marginal entrepreneurial income net of repayment, even with zero effort (e.g., a contract that always requires full repayment, except in the lowest return state, where no repayment is required). It is then impossible to satisfy the first-order condition (1), and a boundary solution emerges in which \(\widetilde{x}(\vec{t}\;)=0\).

  7. Recall that \(\sum p'_{i}(x)=0\); otherwise, the probabilities would sum to more or less than unity with variations in effort.

  8. Reiß and Wolff (2013) endogenize the selection of repayment contracts, studying the structures of subject-selected repayment contracts and their effects on entrepreneurial effort.

  9. The exact numbers are 54.96 % and 110.99 %, respectively.

  10. Exceptions were the NoRepay treatment and the one-shot treatment SDC-OS with different conversion rates, where the endowments were set to 100,000 ECU and 3,000 ECU, respectively.

  11. In treatment NoRepay, the threshold was 20,000 ECU and in the one-shot treatment SDC-OS, bankruptcy procedures were irrelevant and not mentioned in the instructions.

  12. Average earnings in Maastricht were higher than in Erfurt and Konstanz due to treatment differences that allowed for higher earnings, e.g., with false state reporting in treatment NMC-R.

  13. See, e.g., Fischbacher and Heusi (2013) and Mazar et al. (2008).

  14. Similarly, the sign test reveals significant differences between observed median effort and first-best effort in rounds 3 to 15 (two-tailed, p<0.023); for the remaining two rounds at the beginning of the experiment, observed differences are insignificant in round 2 (p=0.540) and significant in round 1 (p=0.007).

  15. For a more detailed exploration of learning effects, see Sect. 4.3 in the working paper version Reiß and Wolff (2012).

  16. The sign test indicates significant differences in rounds 1–3, 9, and 14 (two-tailed, p<0.053) in the EQUI treatment and in the first seven rounds (p<0.024) in the SDC treatment.

  17. The sign test finds significant differences in rounds 1–2 and 15 (p<0.064) in the NMC condition and significant differences in four rounds (1, 5, 7, and 12, p≤0.064) in the NoRepay condition.

  18. We estimate this and the next model using OLS, such that the computation of standard errors takes into account that observations of the same individual might be correlated across time (Rogers 1993).

  19. An F-test of the joint hypothesis (I) \(\widehat {\beta}_{0}=57\), (II) \(\widehat{\beta}_{1}=-\widehat{\beta_{3}}\), (III) \(\widehat{\beta}_{1}=6\), (IV) \(\widehat{\beta}_{2}=0\) with F 4,93=5.94 yields p=0.0003.

  20. Two-tailed sign test, p=0.000.

  21. Two-tailed MWU-test, p=0.984.

  22. If earlier rounds are included, non-monotonic contracts perform even better. For example, NMC income tops SDC income by 315 % on average, if data for rounds 3–15 are used.

  23. Similarly, the two-tailed Mann-Whitney U test indicates highly significant income differences in all 15 rounds (p<0.008).

  24. In the first two rounds, SDC welfare is even slightly higher than NMC welfare. This is due to the fact that quite large effort levels are initially chosen in the SDC treatment, similar to those observed in the NMC treatment but somewhat closer to first-best effort, indicated by the horizontal line in the figure.

  25. Mann-Whitney U test, two-tailed, for rounds 11–15, p<0.044; and for rounds 9 and 10, p>0.117.

  26. Please see Electronic Supplementary Material for a regression analysis confirming the dominance of non-monotonic-contracts in terms of effort, entrepreneurial income, and total surplus.

  27. Average effort in treatment NMC-R does not significantly differ from the theoretical prediction in any of the fifteen rounds; two-tailed t-tests, p>0.257; two-tailed sign-test, p>0.307.

  28. Alternatively, our finding of little misrepresentation may follow from an experimenter demand effect, introduced by our instruction wording “The capital provider can distinguish between a low revenue and other revenues, but not between an intermediate revenue and a high revenue. Therefore if the project revenue is low, this is reported to the capital provider automatically. But if the project revenue is not low, then you have to report to the capital provider if the project attained an intermediate revenue or a high revenue.”, as suggested by a reviewer. If this is the case, then we would underestimate the disadvantages, which reinforces our conclusions from treatment NMC-R, as summarized in Result 6.

  29. This is facilitated by average repayments falling short of the borrowed amount, so that investors partially subsidize project execution.

  30. Two-tailed MWU, p=0.482.

  31. Two-tailed sign tests, p<0.007.

  32. Two-tailed MWU-test, p=0.274.

  33. Two-tailed MWU-test, p>0.148.

  34. Two-tailed MWU-test, p<0.039, for each round except round 14, where p=0.124.

  35. Of course, in real life, inexperienced entrepreneurs can also access other sources of information, which can mitigate the losses due to minimal experience with contract incentives. Cases in point are start-up consultancies and financial advisories.

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Correspondence to J. Philipp Reiß.

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Financial support from Maastricht University through METEOR is gratefully acknowledged. We thank Paul Smeets and audiences in Alicante (IMEBE2008), Caltech (ESA2008), Gothenburg (ESEM2013), Heidelberg, Luxembourg (GfEW2010), and Lyon (ESA2008) for helpful comments. The paper greatly benefited from helpful suggestions and comments of Jordi Brandts and two anonymous reviewers.

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Reiß, J.P., Wolff, I. Incentive effects of funding contracts: an experiment. Exp Econ 17, 586–614 (2014). https://doi.org/10.1007/s10683-013-9385-5

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