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Work environment and moral hazard

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Abstract

We consider a firm’s provision of safety and health measures (working conditions) in a hidden action agency problem in which effort and working conditions interact in multiplicatively separable (neutral) manner in the cash flow process. Under this common formulation, the firm under supplies working conditions and effort at its second best, regardless of the share of accident damages borne by the firm. At this optimum, increases in the damage share paid by the firm decrease the compensation to the agent so as to render working conditions and effort unchanged. Shifting the damage share then does not impact the firm’s or the agent’s welfare. We show that direct regulation of working conditions can improve total surplus, but that the regulation of the damage share is ineffectual. Under first order approximations, we also examine the effects of changes in the hazard level of the job and the efficiency of working conditions. Finally, we show that our results can be changed if the neutral interaction between effort and working conditions is violated.

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Notes

  1. Because a two instrument hidden action agency problem introduces difficult second order complexities, we assume risk neutrality in order to make the analysis tractable.

  2. We thereby consider the class of technologies wherein the elasticity of cash flow with respect to effort is unaffected by working conditions. This class includes the case where working conditions do not impact the productivity of effort.

  3. By strategic complements (substitutes) in total surplus, we mean that the marginal effect of effort on total surplus is increasing (decreasing) in working conditions. Strategic substitutes (complements) in cash flow means that the marginal effect of effort on the firm’s revenue is decreasing (increasing) in working conditions.

  4. In this case, the marginal product of effort is unaffected by working conditions, but the average product of effort is increasing in working conditions. Whence, the elasticity of effort is affected.

  5. This analysis would be an interesting extension of the present study, but it is beyond our scope. If the agent could supply accident reducing effort (precautionary effort), then this would seem to increase the firm’s provision of working conditions if cash flow effort and precautionary effort were complements and decrease the firm’s provision of working conditions if they were substitutes.

  6. These conditions are implied by \(h^{\prime }(y)(\gamma +\sigma y)+\sigma h<0\) and \(h^{\prime \prime }(y)(\gamma +\sigma y)+\sigma h^{\prime }(y)>0.\)

  7. In this version, each unit of effort carries the same possible dollar damages. This makes sense, because effort is exerted to produce cash flow alone. Effort to reduce accident loss is not modeled, so that more or less cash flow effort does not change the possible damages per unit of effort. Each unit of effort (first or last unit) has the same damage attachment. That is, it is not possible for one to work one more hour and somehow be more or less negligent and contribute more or less to the possible damages for that hour. This type of analysis would be included in a model where the worker has precautionary care.

  8. Given the two outcome technology, this formulation is fully general.

  9. This is true, because the function \(c\) is a strictly convex and increasing composition of a strictly convex and increasing function.

  10. This assumption is employed in Marino and Zabojnik (2008a).

  11. This class includes the case where \(f\) is a constant function of \(y\) so that effort productivity is not affected but damages are reduced by more \(y.\)

  12. Note that the agent’s objective function has a negative second derivative in \(e\), so that the second order condition is met.

  13. The second order conditions are stated in the Appendix in the proof of Proposition 3. They are more likely to be met when \(g^{\prime \prime },\phi ^{\prime \prime }>0\) are large, when \(e^{\prime \prime }\le 0~(\)the marginal cost of effort is convex and large in absolute value), and the direct effects \(\pi _{\beta \beta }\pi _{yy}\) dominate the cross effects \( (\pi _{y\beta })^{2}.\)

  14. This requires that the direct effects dominate the cross effects again.

  15. Let \(\alpha _{c},\alpha _{p}\in (0,1)\) denote the exogenous weights applied to consumer and producer surplus, respectively, with \(\alpha _{c}+\alpha _{p}=1.\) The regulator’s objective function is \(TS\,^{{\scriptscriptstyle \tilde{}}}=\alpha _{c}[\beta xe(\gamma +\sigma y)-(1-s)L(x)\phi e-c(e)]+\alpha _{p}[(1-\beta )xe(\gamma +\sigma y)-sL(x)\phi e-g(y)].\) This objective function is equivalent to the original neutral case when \(\alpha _{c}=\alpha _{p}=1/2.\) We have \(TS_{s}^{\,{\scriptscriptstyle \tilde{}}}=\alpha _{c}(r_{a}-c^{\prime })\frac{\partial e }{\partial s}+\alpha _{p}r_{f}\frac{\partial e}{\partial s}+e(\alpha _{c}-\alpha _{p})(\frac{\partial \beta }{\partial s}x(\gamma +\sigma y)+L(x)\phi ).\) Again, \(\frac{\partial e}{\partial s}=e^{\prime }(r_{a})[ \frac{\partial \beta }{\partial s}x(\gamma +\sigma y)+L(x)\phi ]=\frac{ \partial \beta }{\partial s}x(\gamma +\sigma y)+L(x)\phi =0,\) so that \( TS_{s}^{\,{\scriptscriptstyle \tilde{}}}=0\) and the optimal level of \(s\) is indeterminate.

  16. See the Appendix for these solutions.

  17. In the fully general case where \(p(e,y)\) is a concave function, we can show that there is pseudo under supply of effort at the firm’s second best but that \(y\) might be pseudo over or under supplied. At this equilibrium, \( TS_{e}=\frac{xp}{\partial e/\partial \beta }>0\) whereas \(TS_{y}=(\beta xp_{y}-(1-s)L\phi ^{\prime }e)+\frac{p}{p_{e}}(1-s)L\phi ^{\prime }-\frac{p}{ p_{e}}\beta xp_{ey}.\) The first term of \(TS_{y}\) is positive, the second term is negative and the third has the sign of \(p_{ey}\).Thus, \(TS_{y}\) is not generally signable. Further, the signs of \(\partial y/\partial s\) and \( \partial \beta /\partial s\) are indeterminate.

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Acknowledgments

I thank the Marshall School of Business for generous research support. Ricardo Alonso, Odilon Camara, Yanhui Wu and an anonymous referee provided valuable advice and comments.

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Correspondence to Anthony M. Marino.

Appendix

Appendix

Proof of Lemma 1

Divide (P) by \(e>0\)

$$\begin{aligned} \beta x(\gamma +\sigma y)-(1-s)L(x)\phi (y)-c(e)/e+\alpha /e\ge 0. \end{aligned}$$

This condition is met if

$$\begin{aligned} \beta x(\gamma +\sigma y)-(1-s)L(x)\phi (y)-c(e)/e\ge 0. \end{aligned}$$

From (1), substitute \(c^{\prime }=\beta x(\gamma +\sigma y)-(1-s)L(x)\phi (y),\) so that (P) is met if

$$\begin{aligned} c^{\prime }(e)-c(e)/e\ge 0. \end{aligned}$$

This expression is strictly positive because \(c^{\prime },c^{\prime \prime }>0\) and \(c(0)=0.\)

The principal’s Lagrangian can now be written as

$$\begin{aligned} L=-\alpha +\big [(1-\beta )x(\gamma +\sigma y)-sL(x)\phi (y)\big ]e(r_{a})-g(y)+\lambda _{\alpha }\alpha +\lambda _{\beta }\beta +\lambda _{y}y, \end{aligned}$$

where \(\lambda _{i}\ge 0\), \(i=\alpha ,\beta ,y,\) are the multipliers for the non-negativity constraints on \(\alpha ,\beta \) and \(y,\) respectively. The first order condition for \(\alpha \) is \(-1+\lambda _{\alpha }=0.\) Thus, it follows that \(\lambda _{\alpha }>0\) and \(\alpha =0.\) \(\square \)

Proof of Proposition 1

Let \(H_{TS}\) denote the Hessian of TS in \((e,y).\) We have that \(\partial e^{*}/\partial b=\) \((1/|H_{TS}|)(L(x)g^{ \prime \prime }y+L(x)e(x\sigma +bL(x)))>0\) and \(\partial y^{*}/\partial b=\) \((1/|H_{TS}|)(L(x)ec^{\prime \prime }+L(x)y(x\sigma +bL(x)))>0.\) Further, \(\partial e^{*}/\partial a=-(1/|H_{TS}|)\) \((L(x)g^{\prime \prime })<0\) and \(\partial y^{*}/\partial a=-(1/|H_{TS}|)L(x)(\sigma x+L(x)b)<0. \) Finally, \(\partial e^{*}/\partial \gamma \) \( =(1/|H_{TS}|)g^{\prime \prime }x>0, \partial y^{*}/\partial \gamma =(1/|H_{TS}|)x(\sigma x+bL(x))>0,\) \(\partial e^{*}/\partial \sigma =(1/|H_{TS}|)[g^{\prime \prime }\cdot xy+ex(x\sigma +bL(x))],\) and \(\partial y^{*}/\partial \sigma =(1/|H_{TS}|)[exc^{\prime \prime }+yx(\sigma x+bL(x))].\) \(\square \)

Proof of Proposition 2

Because \(TS\) is strictly concave and differentiable,

$$\begin{aligned} \sum \limits _{i=e}^{y}\frac{\partial TS^{o}}{\partial i}(i^{*}-i^{o})>TS(e^{*},y^{*})-TS(e^{o},y^{o})>0. \end{aligned}$$

Thus, \(TS_{e}^{o}(e^{*}-e^{o})+TS_{y}^{o}(y^{*}-y^{o})>0.\) However, \( TS_{e}^{o}>0\) while \(TS_{y}^{o}=0,\) so that \(e^{*}>e^{o}.\) Next note that \(TS_{ey}=\sigma x-L(x)\phi ^{\prime }>0,\) by A.1. By \(e^{*}>e^{o}\) and \(TS_{ey}>0,\) it follows that

$$\begin{aligned} TS_{y}(e^{*},y^{*})-TS_{y}(e^{o},y^{*})>0. \end{aligned}$$

Because it is true that \(TS_{y}(e^{*},y^{*})-TS_{y}(e^{o},y^{o})=0,\) it is, therefore, necessary that \(y^{o}<y^{*},\) by \(TS_{yy}<0.\) \(\square \)

Proof of Proposition 3

The second order conditions to the principal’s problem include

$$\begin{aligned} \pi _{yy}= & {} -sL(x)e\phi ^{\prime \prime }\!-\!g^{\prime \prime }\!+\!2e^{\prime }\big (\beta \sigma x\!-\!(1\!-\!s)L(x)\phi ^{\prime }\big )\big ((1\!-\!\beta )\sigma x\!-\!sL(x)\phi ^{\prime }\big ) \\&+(r_{f})\big (e^{\prime \prime }(\beta \sigma x-(1-s)L\phi ^{\prime }\big )^{2}-e^{\prime }\big ((1-s)L(x)\phi ^{\prime \prime }\big )<0 \end{aligned}$$

and

$$\begin{aligned} \pi _{\beta \beta }=-2e^{\prime }x^{2}(\gamma +\sigma y)^{2}+e^{\prime \prime }x^{2}(\gamma +\sigma y)^{2}r_{f}<0. \end{aligned}$$

The second order cross partial \(\pi _{y\beta }\) is given by

$$\begin{aligned} \pi _{y\beta }= & {} \!-x\sigma e\!-\!x(\gamma \!+\!\sigma y)e^{\prime }\big [\sigma \beta x\!-\!(1\!-\!s)L(x)\phi ^{\prime }\big ]\!+\!\big [(1\!-\!\beta )x\sigma \!-\!sL(x)\phi ^{\prime }\big ]e^{\prime }\\&x(\gamma +\sigma y) +r_{f}e^{\prime }x\sigma +r_{f}e^{\prime \prime }x(\gamma +\sigma y)(\beta \sigma x-(1-s)L(x)\phi ^{\prime })]. \end{aligned}$$

Using \(\pi _{\beta }=0,\) we have that \(e=r_{f}e^{\prime },\) so that \(\pi _{y\beta }\) can be rewritten as

$$\begin{aligned} \pi _{y\beta }\!=\!e^{\prime }x(\gamma \!+\!\sigma y)\big [(1\!-\!2\beta )x\sigma \,+\,(1\!-\!2s)L(x)\phi ^{\prime }\big ]+\,e^{\prime \prime }x(\gamma +\sigma y)r_{f}\big [\beta x\sigma -(1-s)\phi ^{\prime }L(x)\big ]. \end{aligned}$$

We will make use of

$$\begin{aligned} \frac{\partial }{\partial s}\pi _{y}\equiv & {} \pi _{ys}=-L(x)e\phi ^{\prime }-L(x)\phi e^{\prime }\big [\beta x\sigma -(1-s)\phi ^{\prime }L(x)\big ]\\&+\,\big [(1-\beta )x\sigma -sL(x)\phi ^{\prime }\big ]e^{\prime }L(x)\phi \\&+\,r_{f}e^{\prime }\phi ^{\prime }L(x)+r_{f}e^{\prime \prime }L(x)\phi \big [ \beta x\sigma -(1-s)\phi ^{\prime }L(x)\big ]. \end{aligned}$$

Employing \(e=r_{f}e^{\prime },\) this can be rewritten as

$$\begin{aligned} \pi _{ys}=e^{\prime }L(x)\phi \big [(1-2\beta )x\sigma +(1-2s)L(x)\phi ^{\prime }\big ]+e^{\prime \prime }L(x)\phi r_{f}\big [\beta x\sigma -(1-s)L(x)\phi ^{\prime }\big ]. \end{aligned}$$

Moreover, we have

$$\begin{aligned} \frac{\partial }{\partial s}\pi _{\beta }\equiv \pi _{\beta s}=-2e^{\prime }L(x)\phi x(\gamma +\sigma y)+e^{\prime \prime }L\phi x(\gamma +\sigma y)r_{f}. \end{aligned}$$

The effect of \(s\) on \(y\) is given by

$$\begin{aligned} \partial y^{o}/\partial s=(1/H)(-\pi _{ys}\pi _{\beta \beta }+\pi _{\beta s}\pi _{y\beta })=0. \end{aligned}$$

We will show that \([\pi _{ys}(-\pi _{\beta \beta })+\pi _{\beta s}\pi _{y\beta }]=0.\) Let us use \(Z\equiv [(1-2\beta )x\sigma +(1-2s)L(x)\phi ^{\prime }]\) and \(\partial r_{a}/\partial y=[\beta x\sigma -(1-s)L(x)\phi ^{\prime }]\) to rewrite this expression:

$$\begin{aligned}&\big [e^{\prime }L\phi Z+e^{\prime \prime }L\phi r_{f}(\partial r_{a}/\partial y)\big ]\big [2e^{\prime }x^{2}(\gamma +\sigma y)^{2}-e^{\prime \prime }x^{2}(\gamma +\sigma y)^{2}r_{f}\big ] \\&\quad +\,\big [-2e^{\prime }L\phi x(\gamma +\sigma y)+e^{\prime \prime }L\phi x(\gamma +\sigma y)r_{f}\big ] \\&\quad \times \,\big [e^{\prime }x(\gamma +\sigma y)Z +\,e^{\prime \prime }x(\gamma +\sigma y)r_{f}(\partial r_{a}/\partial y)\big ]. \end{aligned}$$

Multiplying terms

$$\begin{aligned}&\!\!2(e^{\prime })^{2}L\phi x^{2}(\gamma \!+\!\sigma y)^{2}Z\!-\!L\phi Zr_{f}x^{2}(\gamma \!+\!\sigma y)^{2}e^{\prime }e^{\prime \prime }\!+\!2L\phi r_{f}(\partial r_{a}/\partial y)x^{2}(\gamma \!+\!\sigma y)^{2}e^{\prime }e^{\prime \prime } \\&\quad -\,L\phi (r_{f})^{2}(\partial r_{a}/\partial y)x^{2}(\gamma +\sigma y)^{2}(e^{\prime \prime })^{2}-2(e^{\prime })^{2}L\phi x^{2}(\gamma +\sigma y)^{2}Z\\&\quad +\,L\phi Zr_{f}x^{2}(\gamma +\sigma y)^{2}e^{\prime }e^{\prime \prime } \\&\quad -\,2L\phi r_{f}(\partial r_{a}/\partial y)x^{2}(\gamma +\sigma y)^{2}e^{\prime }e^{\prime \prime }+L\phi (r_{f})^{2}x^{2}(\gamma +\sigma y)^{2}(\partial r_{a}/\partial y)(e^{\prime \prime })^{2} \\&\quad =0. \end{aligned}$$

Thus, \(\partial y^{o}/\partial s=0.\)

Next consider

$$\begin{aligned} \partial \beta ^{o}/\partial s=\frac{(-\pi _{yy}\pi _{\beta s} +\pi _{ys}\pi _{y\beta })}{\pi _{yy}\pi _{\beta \beta }-(\pi _{y\beta })^{2}}. \end{aligned}$$

From above we know that \(\pi _{ys}=(\pi _{\beta s}\pi _{y\beta })/\pi _{\beta \beta }\), so that

$$\begin{aligned} \partial \beta ^{o}/\partial s= & {} \frac{\Big (-\pi _{yy}\pi _{\beta s} +\frac{\big (\pi _{\beta s}\pi _{y\beta }\big )}{\pi _{\beta \beta }}\pi _{y\beta }\Big )}{\pi _{yy}\pi _{\beta \beta }-(\pi _{y\beta })^{2}}=\frac{\frac{-\pi _{\beta s}}{\pi _{\beta \beta }}\big (\pi _{yy}\pi _{\beta \beta }-(\pi _{y\beta })^{2}\big )}{\pi _{yy}\pi _{\beta \beta }-(\pi _{y\beta })^{2}} \\= & {} \frac{-\pi _{\beta s}}{\pi _{\beta \beta }}=\frac{2e^{\prime }L(x)\phi x(\gamma +\sigma y)-e^{\prime \prime }L(x)\phi x(\gamma +\sigma y)r_{f}}{ -2e^{\prime }x^{2}(\gamma +\sigma y)^{2}+e^{\prime \prime }x^{2}(\gamma +\sigma y)^{2}r_{f}} \\= & {} \frac{-L(x)\phi }{x(\gamma +\sigma y)}. \end{aligned}$$

This completes the proof. \(\square \)

Proof of Proposition 4

Note that, given a general \(\phi ,\) \( e(r_{a})=r_{a},e(r_{a})=e^{\prime }(r_{a})r_{f}\), \(e^{\prime }=1,\) so that \( r_{a}=r_{f}.\) It immediately follows that \(s\gtreqqless \frac{1}{2}\) implies \(\beta \lesseqqgtr \frac{1}{2}.\) Now let \(\phi =a-by.\) For this case, at a point where the first order conditions are met,

$$\begin{aligned} \pi _{yy}= & {} 2\big [(1-\beta )\sigma x+sLb)(\beta \sigma x+(1-s)Lb\big ]-g^{\prime \prime }, \\ \pi _{\beta \beta }= & {} -2x^{2}(\gamma +\sigma y)^{2}, \\ \pi _{y\beta }= & {} x(\gamma +\sigma y)\big [(1-2\beta )\sigma x-(1-2s)Lb\big ]. \end{aligned}$$

Whence, \(\pi _{y\beta }\gtreqqless 0\) as \(s\gtreqqless \frac{1}{2}.\) Using the notation of the proof of Proposition 3,

$$\begin{aligned} \pi _{ya}= & {} -(1-s)L\big [(1-\beta )\sigma x+sLb)-sL (\beta \sigma x+(1-s)Lb\big ]<0, \\ \pi _{\beta a}= & {} x(\gamma +\sigma y)(1-2s)L. \end{aligned}$$

We have

$$\begin{aligned} \partial y^{o}/\partial a=(1/H)(-\pi _{ya}\pi _{\beta \beta } +\pi _{\beta a}\pi _{y\beta }). \end{aligned}$$

With \(|H|\) \(>0,\) the \(sign\) \(\partial y^{o}/\partial a=\) \(sign\) \((-\pi _{ya}\pi _{\beta \beta }+\pi _{\beta a}\pi _{y\beta }).\) Clearly, \(-\pi _{ya}\pi _{\beta \beta }<0,\) \(\pi _{\beta a}\gtreqqless 0\) as \(s\lesseqqgtr \frac{1}{2},\) and \(\pi _{y\beta }\gtreqqless 0\) as \(s\gtreqqless \frac{1}{2} . \) Thus, \(\pi _{\beta a}\pi _{y\beta }<0\) and \(\partial y^{o}/\partial a<0.\)

Next note that

$$\begin{aligned} \partial \beta ^{o}/\partial a=(1/H)(-\pi _{\beta a} \pi _{yy}+\pi _{ya}\pi _{y\beta }). \end{aligned}$$

If \(s\ge 1/2,\) then \(\pi _{\beta a}<0\) and \(-\pi _{\beta a}\pi _{yy}\le 0.\) Further, \(s\ge 1/2\) implies \(\pi _{y\beta }\ge 0,\) with \(\pi _{ya}\pi _{y\beta }\le 0.\) Whence, \(s\ge 1/2\) implies \(\partial \beta ^{o}/\partial a\le 0.\) The converse argument for \(s<1/2\) implies \(\partial \beta ^{o}/\partial a>0.\)

Next consider a change in \(b.\) We have

$$\begin{aligned} \partial y^{o}/\partial b=(1/H)(-\pi _{yb}\pi _{\beta \beta } +\pi _{\beta b}\pi _{y\beta }). \end{aligned}$$

Moreover,

$$\begin{aligned} \pi _{yb}= & {} sLr_{a}\!+\![(1\!-\!\beta )\sigma x\!+\!sLb](1\!-\!s)Ly\!+\![\beta \sigma x\!+\!(1\!-\!s)bL]sLy\!+\!r_{f}(1\!-\!s)L, \\ \pi _{\beta b}= & {} x(\gamma +\sigma y)yL(2s-1). \end{aligned}$$

Using the same arguments as above, \(-\pi _{yb}\pi _{\beta \beta }>0\) and \( s\gtreqqless \frac{1}{2}\) implies \(\pi _{\beta b}\pi _{y\beta }\ge 0.\) Thus, \(\partial y^{o}/\partial b>0.\) Likewise,

$$\begin{aligned} \partial \beta ^{o}/\partial b=(1/H)(-\pi _{\beta b} \pi _{yy}+\pi _{yb}\pi _{y\beta }). \end{aligned}$$

We have \(-\pi _{\beta b}\pi _{yy}\) \(\ge 0\) as \(s\ge \frac{1}{2}.\) Moreover, \(s\ge \frac{1}{2}\) implies that \(\pi _{yb}\pi _{y\beta }\ge 0.\) Thus, \(\partial \beta ^{o}/\partial b\ge 0.\) For \(s<\frac{1}{2},\) the converse argument holds.

A change in \(\gamma \) will be considered next. We have

$$\begin{aligned} \pi _{y\gamma }= & {} [(1-\beta )\sigma x+sLb]\beta x+[\beta \sigma x+(1-s)Lb](1-\beta )x>0, \\ \pi _{\beta \gamma }= & {} x^{2}(\gamma +\sigma y)(1-2\beta ), \end{aligned}$$

The sign of \(\partial y^{o}/\partial \gamma \) is that of \(-\pi _{y\gamma }\pi _{\beta \beta }+\pi _{y\beta }\pi _{\beta \gamma }.\) From above, \(-\pi _{y\gamma }\pi _{\beta \beta }>0.\) Further, \(\pi _{y\beta },\pi _{\beta \gamma }\gtreqqless 0\) as \(s\gtreqqless \frac{1}{2},\) so that \(\pi _{y\gamma }\pi _{\beta \gamma }>0\). Whence, \(\partial y^{o}/\partial \gamma >0.\) The sign of \(\partial \beta ^{o}/\partial \gamma \) is that of \(-\pi _{yy}\pi _{\beta \gamma }+\pi _{y\gamma }\pi _{\beta y}.\) We have that \(\pi _{\beta \gamma },\pi _{\beta y}\gtreqqless 0\) as \(s\gtreqqless \frac{1}{2}\) and \( -\pi _{yy}\pi _{\beta \gamma }\gtreqqless 0\) as \(s\gtreqqless \frac{1}{2}.\) Thus, \(\partial \beta ^{o}/\partial \gamma \gtreqqless 0\) as \(s\gtreqqless \frac{1}{2}.\)

Finally, we examine a change in \(\sigma .\) For this case we have that

$$\begin{aligned} \pi _{y\sigma }= & {} r_{a}x+xy\{\beta [(1-\beta )\sigma x+sLb]+(1-\beta )[\beta \sigma x+(1-s)Lb]\}>0, \\ \pi _{\beta \sigma }= & {} x^{2}(\gamma +\sigma y)(1-2\beta ). \end{aligned}$$

The sign of \(\partial y^{o}/\partial \sigma \) is that of \(-\pi _{y\sigma }\pi _{\beta \beta }+\pi _{y\beta }\pi _{\beta \sigma }.\) We have that \(-\pi _{y\sigma }\pi _{\beta \beta }>0\) and \(\pi _{y\beta },\pi _{\beta \sigma }\gtreqqless 0\) as \(s\gtreqqless \frac{1}{2}.\) It follows that \(\partial y^{o}/\partial \sigma >0.\) The sign of \(\partial \beta ^{o}/\partial \sigma \) is that of \(-\pi _{\beta \sigma }\pi _{yy}+\pi _{y\beta }\pi _{y\sigma }.\) We have \(-\pi _{\beta \sigma }\pi _{yy}\gtreqqless 0\) as \(s\gtreqqless \frac{ 1}{2}\) and \(\pi _{y\beta }\pi _{y\sigma }\gtreqqless 0\) as \(s\gtreqqless \frac{1}{2},\) so that \(\partial \beta ^{o}/\partial \sigma \gtreqqless 0\) as \(s\gtreqqless \frac{1}{2}.\) \(\square \)

Proof of Lemma 2

From (12), we have that

$$\begin{aligned} \beta ^{\prime }(y)=\frac{x(\gamma +\sigma y)e^{\prime }(r_{a})((1-2\beta )\sigma x+(1-2s)L\phi ^{\prime })+x(\gamma +\sigma y)e^{\prime \prime }(r_{a})(\beta \sigma x-(1-s)L\phi ^{\prime })r_{f}}{2x^{2}(\gamma +\sigma y)^{2}e^{\prime }(r_{a})-x^{2}(\gamma +\sigma y)^{2}r_{f}e^{\prime \prime }(r_{a})}. \end{aligned}$$

From (13), \(\partial e/\partial y=e^{\prime }(r_{a})[\beta ^{\prime }(y)(\gamma +\sigma y)x+\beta \sigma x-(1-s)L(x)\phi ^{\prime }].\) Substituting for \(\beta ^{\prime }(y),\)

$$\begin{aligned} \partial e/\partial y= & {} \frac{x(\gamma \!+\!\sigma y)e^{\prime }(r_{a})\{x(\gamma \!+\!\sigma y)e^{\prime }(r_{a})[(1\!-\!2\beta )x\!+\!(1\!-\!2s)L\phi ^{\prime }]\!+\!x(\gamma \!+\!\sigma y)e^{\prime \prime }(r_{a})[\beta \sigma x\!-\!(1\!-|!s)L\phi ^{\prime }]r_{f}\}}{2x^{2}(\gamma \!+\!\sigma y)^{2}e^{\prime }(r_{a})\!-\!x^{2}(\gamma \!+\!\sigma y)^{2}r_{f}e^{\prime \prime }(r_{a})} \\&+\,e^{\prime }(r_{a})[\beta \sigma x-(1-s)L\phi ^{\prime }]. \end{aligned}$$

Placing this expression over a common denominator and simplifying we obtain

$$\begin{aligned} \partial e/\partial y=\frac{e^{\prime }(r_{a})^{2}(\sigma x-L\phi ^{\prime }) }{2e^{\prime }(r_{a})-r_{f}e^{\prime \prime }(r_{a})}. \end{aligned}$$

The assumption that the second order condition \(\pi _{\beta \beta }<0\) holds implies that \(2e^{\prime }(r_{a})-r_{f}e^{\prime \prime }(r_{a})>0,\) and A.1 implies that \((\sigma x-L\phi ^{\prime })>0.\) Thus, \(\frac{\partial e}{ \partial y}>0.\) \(\square \)

Proof of Proposition 5

By strict concavity, \(\sum \nolimits _{i=e}^{y} \frac{\partial TS^{o}}{\partial i}(\hat{\imath }-i^{o})>TS(\hat{e},\hat{y} )-TS(e^{o},\) \(y^{o})>0.\) Thus, \(TS_{e}^{o}(\hat{e}-e^{o})-TS_{y}^{o}(\hat{y} -y^{o})>0.\) We know that \(TS_{y}^{o}=0\) while \(TS_{e}^{o}>0.\) It follows that \(\hat{e}>e^{o}.\) Next note that \(TS_{y}(e^{o},y^{o})=0,\) while \(TS_{y}( \hat{e},y^{o})>0,\) by \(TS_{ye}>0.\) Given that \(TS_{y}(\hat{e},\hat{y})<0,\) it must be that \(\hat{y}>y^{o},\) because \(TS_{yy}<0.\) \(\square \)

Non-neutral interactions between effort and working conditions The second and first best solutions are given by

$$\begin{aligned} \beta ^{o}= & {} \frac{aLs[2bL(1-s)z^{2}-w]+x[w+bL(1-s)z^{2}]}{ x[w+bL(1-2s)z^{2}]}, \quad y^{o}=\frac{z^{2}(aL-x)(w+bLz^{2})}{ [w+z^{2}bL(1-2s)]^{2}}, \\ e^{o}= & {} \frac{z(aL-x)[-w^{2}(1-z)+2z^{4}b^{2}L^{2}(1-s)s-z^{2}bwL(1-2s-z)]}{ [w+z^{2}bL(1-2s)]^{2}},\\ y^{*}= & {} \frac{(aL-x)(w+bLz^{2})}{ (z^{2}L^{2}b^{2}+2bwL-1)},{\text { and }} \; e^{*} =\frac{z(aL-x)(bwL-1)}{(z^{2}L^{2}b^{2}+2bwL-1)}. \end{aligned}$$

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Marino, A.M. Work environment and moral hazard. J Regul Econ 48, 53–73 (2015). https://doi.org/10.1007/s11149-015-9278-y

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