This paper can be downloaded without charge at:

The Fondazione Eni Enrico Mattei Note di Lavoro Series Index: http://www.feem.it/Feem/Pub/Publications/WPapers/default.htm

Social Science Research Network Electronic Paper Collection:

http://ssrn.com/abstract=744604

The opinions expressed in this paper do not necessarily reflect the position of Fondazione Eni Enrico Mattei

Corso Magenta, 63, 20123 Milano (I), web site: www.feem.it, e-mail: working.papers@feem.it

Quality and Investment Decisions in Hospital Care when Physicians

are Devoted Workers Rosella Levaggi,

Michele Moretto and Vincenzo Rebba

NOTA DI LAVORO 85.2005

JUNE 2005 ETA – Economic Theory and Applications

Rosella Levaggi and Michele Moretto, Dipartimento di Scienze Economiche, University of Brescia Vincenzo Rebba, Dipartimento di Scienze Economiche, Università di Padova

Quality and Investment Decisions in Hospital Care when Physicians are Devoted Workers

Summary This paper analyses the decision to invest in quality by a hospital in an environment where doctors are devoted workers, i.e. they care for specific aspects of the output they produce. We assume that quality is the result of both an investment in new technology and the effort of the medical staff. Hospital services are paid on the basis of their marginal cost of production while the number of patients treated depends on a purchasing rule which discriminates for the level and timing of the investment. We show that the presence of devoted doctors affects the trade-off between investment and the purchasing rule so that for the hospital it is not always optimal to anticipate the investment decision.

Keywords: Hospital technology, Devoted worker, Quality, Irreversible investment, Real options

JEL Classification: I11, D81

Address for correspondence: Michele Moretto Department of Economics University of Brescia Via S. Faustino, 74b 25122 Brescia Italy E-mail: moretto@eco.unibs.it

1 Introduction

All advanced health care systems have to cope with the need to controlgrowth expenditure without over-reducing investments in new technology,in order to guarantee patients adequate quality (Bokhari, 2001; Baker, 2001;Propper, 2004; HTC 2003). In this context, it is important to overcome thetraditional (and somehow misleading) trade-o¤ between cost and quality,where the latter is simply seen as a running cost1.

In this paper, we argue that the quality of hospital care is determinedby two main factors: the capital invested (i.e. adoption of new technologies)which is usually irreversible, and the e¤ort of the personnel employed whichhas a more complex objective function than standard workers. Therefore,hospital care needs a more comprehensive modelling approach which consid-ers the particular features of the production process as regards investmentdecisions on medical equipment and human capital. Following Chalkley andMalcomson (2000), we de�ne quality as a multivariable vector that includesall the aspects of medical care such as the appropriateness of the treatment,the investment in technology that bene�ts the recipients, and other aspectsthat are not strictly medical but that can improve hospital output, suchas patient accessibility (proper information by hospital sta¤, short waitingtimes before treatment etc.) and hotel quality.

In this respect, the paper analyses a Nash game between a hospitaland its medical sta¤ to determine the quality level of health care withinan intertemporal model where the investment implemented by the hospitalis irreversible, because of physical or economic reasons. In this game, thequality of hospital care and doctors�e¤orts are non-contractable variables(i.e. they cannot be enforced before a court). In modelling the behaviourof the medical sta¤ and the related choice of doctors�e¤orts, we follow theliterature on the �devoted workers�which has pointed out the di¤erences inthe choice of the e¤ort by a worker (in our case, a doctor) who is interestedin both the outcome and the technology content of the productive processadopted (Francois, 2000, 2003; Glazer, 2004)2.

Furthermore, we analyse how a purchaser (e.g. an insurance company,an HMO or a public health authority) who pursues its patients� welfaremay in�uence the hospital�s quality choice through strategic setting of theparameters of a purchasing rule that relates the volume of hospital care tobe reimbursed to the timing of the hospital�s investment decision.

1See Harris (1979), Ellis and Mc Guire (1986), Newhouse (1996), Ma (1994), Chalkleyand Malcomson (1998, 2000 and 2002), Bigliaser and Ma (2003).

2 Interesting examples are �remen, university professors and medical sta¤.

2

In order to analyse hospital investment in health care technology, we usea real option approach3. Essentially this approach posits that the opportu-nity to invest in a project is analogous to an American call option on theinvestment opportunity. Since the future value of the project is uncertain,there is an opportunity cost to investing today. Another example of optiongame between a purchaser and a hospital over the investment in qualitycan be traced in Levaggi and Moretto (2004). In that model, however, themedical sta¤ did not play any role in the investment in quality4.

We show that the strategic behaviour between the doctors and the hos-pital a¤ects the hospital�s decision both on the level and the timing of in-vestment. Since the investment decision is the result of the Nash gamebetween the medical sta¤ and the hospital, the latter can use the devotedcharacteristic of the physician to substitute investment with e¤ort in orderto maximise its intertemporal surplus. In particular, our model provides asurprising result as regards the timing of the investment: if the purchaseraims at maximising the current level of quality (i.e. the earlier adoption ofa new technology by the hospital), the adoption of a purchasing rule linkingthe volume of current hospital admissions to be reimbursed to the invest-ment made in the past periods may not be optimal. That is, in contrastwith the real option theory, we show that it is not necessary to drive to zerothe �rm�s option to wait for more information to convince it to invest soon5.

The paper is organized as follows. Section two presents the basic model.In section three, the Nash equilibrium of the game between the hospital andthe medical sta¤ is presented. In section four, the relationship between theNash equilibrium and the purchasing rule is analysed. Lastly, section �veconcludes.

3See Abel et al. (1996), Dixit and Pindyck (1994).4Also Bös and Fraja (2002) study a game between a health care authority and a hospital

over the investment in quality. However, they do not consider the intertemporal aspectof the investment in health care and the speci�c e¤ort of the medical sta¤ in determiningthe level of quality. Furthermore, they allow the purchaser to rely on outside providers toinduce the hospital to increase its investment.

5This contrasts also with the result obtained by Levaggi and Moretto (2004) whoshowed that the problem of non-veri�ability of quality could usually be avoided by apurchasing rule linking the volume of current care to be reimbursed to the investmentmade in the past periods, which induces the hospital to anticipate the investment.

3

2 The model

The model deals with the investment choices of a representative hospitaland the e¤ort decision made by its medical sta¤ in a two-period framework.To simplify the analysis, we assume that patients admitted to the hospitalcan be a¤ected only by one disease that requires a standard treatment. Thetotal quality of hospital care is determined by its clinical e¤ectiveness andby perceived quality, as explained in the next section. A new technology forproducing hospital care is available at time 1 and the hospital may decidethe level of investment (i.e. the number of technology units) in each period.The e¤ort of medical sta¤ is set at time 1 and is kept constant over time.Both capital and doctors�e¤orts contribute to determining the total qualityqt, t = 1; 2. We also assume that, once the investment in the new technologyis undertaken, it cannot be diverted and depreciation is absent6.

2.1 Quality and its aspects

The outcome of hospital care depends on several variables, some of whichcannot be controlled by any of the parts involved in the hospital productionprocess. The main determinants of hospital care outcome are: the quality ofthe treatment, patient�s compliance with therapy and his ability to recover.These elements interact: a high level of quality makes the patient con�dentof recovering his health and motivates him to comply and, sometimes, mightenhance the placebo e¤ect of the treatment. In this process the perceivedquality is equally (sometimes more) important than the clinical quality ofhealth care. However, the patient cannot fully perceive clinical outcomebecause of his ignorance of health care. In his assessment of quality hemight sometimes be biased towards elements that he can readily observeand measure, even if they are not the most important ones.

In our analysis we de�ne total quality as:

q = F (qp; qc) (1)

where qp � 0 represents the quality perceived by patients, qc � 0 is theclinical quality, with F (0; qc) � 0 and F (qp; 0) � 0: Perceived and clinicalquality can be interpreted as two intermediate outcomes in the process lead-ing to total quality. The term qp captures important aspects relating to the

6Together with irreversibi lity of investment, this assumption avoids the need to consideroperating options for the hospital such as reducing output or even shutting down, andthereby considering reducing variable costs. For further details on this issue see e.g. Dixitand Pindyck (1994).

4

quality as perceived by patients: access to hospital services, level of com-fort in hospital care (hotel quality measured by number of beds per room,visiting times, private telephones, nurses per ward, etc.) and relationshipwith the medical sta¤ (appropriate information on the therapy and its likelye¤ectiveness, shared motivation with doctors and other personnel as regardsthe therapy, establishing a satisfactory human relationship with sta¤, etc.)7.Perceived quality can be assumed to be a function of the ancillary services s(which the literature often de�nes "hotel-related quality services") and thee¤ort of the medical sta¤ devoted to patient-centered care e (Stewart, 1995,2000). That is:

qp = h(s; e; ") (2)

where " is a random variable which is related to unknown patients�charac-teristics and their prior beliefs concerning health outcomes. This speci�ca-tion corresponds to the way most of the traditional literature models healthcare quality: a running cost that depends on some inputs and the e¤ortof the medical sta¤8. This de�nition, however, and especially its speci�ca-tion, are not su¢ cient to de�ne the overall quality of hospital care. Anotherimportant element is clinical quality which, we believe, has to be treated sep-arately from the previous term since it also depends on investment decisionsconcerning medical technology.

The clinical quality of hospital care can be written as an increasingfunction of three inputs:

qc = g(k; e; a; �)

where: k represents the level of capital invested in medical technology, e isthe e¤ort of the medical sta¤, a is the appropriateness of the care o¤eredto the patient and � is a random parameter that captures the unknowncharacteristics of each patient (which can in�uence the health outcome) aswell as all the other uncertain determinants in�uencing clinical quality (e.g.shocks on input productivity etc.). Appropriateness a measures the use ofhospital resources in order to respond (according to clinical standards andexisting medical evidence) to a speci�c health care demand. We assume

7qp represents the quality as perceived by patients when they actually use hospitalcare services and experience a relationship with hospital sta¤. Under this perspective,the concept of perceived quality we adopt here is very close to relational quality andshould be considered distinct from the concept of reputation which can drive competitionbetween hospitals and which depends not only on patients�experience of hospital care (i.e.perceived quality) but also on people�s beliefs concerning hospital technology and sta¤before their actual experience of hospital services.

8See Chalckley and Malcomson (2000).

5

that the appropriateness of the care delivered is an increasing function ofmedical e¤ort, i.e.:

a = a(e; �) (3)

The underlying assumption is that the e¤ort of the medical sta¤ permitsprecise diagnosis and appropriate treatment for the patient9. The e¤ort ofthe medical sta¤ provides the patient with personalised treatment which,due to the presence of �, cannot be standardised (e.g. through protocols orguidelines). The e¤ort of the medical sta¤ enhances the productivity of thecapital invested in health care. Medical technology is per se important toimprove medical care, but it is the e¤ort of the medical sta¤ that determinesthe appropriateness of the treatment. Using (3), clinical quality can bewritten as:

qc = g(k; e;�) (4)

where � = (�; �): Substituting (4) and (2) into (1), and assuming, withoutany loss of generality, that s is �xed10 (so that qp depends only on e), weobtain the following functional form for total quality:

q = F (h(e; "); g(k; e;�)) (5)

For the perceived and clinical quality the usual marginal properties hold:he > 0; hee < 0 and ge > 0; gk > 0; gee < 0; gkk < 0 respectively. Wecomplete these properties by assuming that capital and e¤ort are substitutes,i.e. gke < 0 and gk� > 011.

9Therefore, we assume that appropriateness does not depend on k However, the reale¤ect of k on the appropriateness of hospital care is controversial. Sometimes appropri-ateness is determined by the ability of doctors to keep themselves abreast of technicaldevelopments which are often more �capital intensive�and are considered really e¤ectiveaccording to Evidence Based Medicine (e.g. the adoption of laparoscopy instead of tradi-tional surgery in cholecystectomy); in this case, appropriateness could be positively relatedto k. In other cases, however, the relationship between a and k could assume a negativesign. For instance, to accomplish a �rst diagnosis of bronchopneumonia or to ascertain theexistence of particular orthopaedic diseases, the use of traditional X-ray diagnostics couldbe sometimes equally (or even more) e¤ective than using CAT (Computed Axial Tomog-raphy) scan. Therefore, the relationship between a and k is rather ambiguous, dependingon the particular health care problem considered.10For the sake of simplicity, we assume that hotel-related quality is set at a standard

level. In this way, we focus on the perceived quality determined by the e¤ort of medicalsta¤ devoted to the relationship with patients. Moreover, we do not consider a hospital�sinvestment in hotel services but only in new clinical technology. Anyway, our main resultshold even with a variable s.11Although not strictly necessary for the results we may add that g(0; e;�) = g(k; 0;�) =

0.

6

Finally, we assume that (5) is additive and separable in qp and qc; i.e.:12

q = (1� �)qp + �qc � (1� �)h(e; ") + �g(k; e;�) (6)

where 0 � � � 1 parameterizes the marginal rate of substitutionbetween k and e:

2.2 The actors

In this paper we model the behaviour of three main actors: an agencypurchasing hospital care (the purchaser), a hospital (the provider) and itsmedical sta¤.

2.2.1 The purchaser

We do not assume a speci�c objective function for the purchaser. However,even if this actor limits itself to setting the parameters of a purchasing rulein order to maximise total quality on behalf of its patients13, its role is notmarginal as will be shown in this paper14. The maximisation of total qualitycan be pursued by supporting hospital investment in new technologies andstimulating a high level of e¤ort by the medical sta¤. The purchaser pursuesits objective by rewarding the hospital a �xed price p for each treatmentand setting a quality-contingent long-term contract with the hospital15. Inparticular, we assume that the number of patients needing treatment isindependent of quality, but the purchaser reimburses the hospital for thetreatment of a number of patients which is �xed in the �rst period, x1 �x � 0; and may increase in the second period if the hospital increases itstotal quality. In other words, we assume that the purchaser is committedto linking the number of patients to be treated in the second period to thequality provided by the hospital using the following linear rule:

x2(q1; q2) � x+ q1 + �(q2 � q1) with ; � � 0 and � � (7)

where x is �xed, q1 and q2 are the level of total quality in the �rst periodand in the second period respectively, and and � represent the relative

12This is like assuming a Cobb-Douglas representation of total quality with qp and qc

as inputs.13 In this respect, it can be considered a perfect agent of the patients.14A vast empirical literature has studied the e¤ect of di¤erent reimbursement setting

on the adoption of new technology. See HTC (2003) for a review.15Price p can be either a DRG tari¤ or any other form of prospective price for a speci�c

treatment.

7

weights attached by the purchaser to the quality in the two periods. Sinceinvestment is irreversible, if = 0; the hospital is allowed to increase its(reimbursed) activity level only if it increases the total quality in the secondperiod; if � = 0; x2 depends only on the quality level at time t = 1 while, if = �, x2 depends on the quality level at time t = 2:

The purchasing rule (7) can be interpreted in this way: each hospital,by increasing total quality (in both periods) can increase the number ofadmitted (and rewarded) patients. Therefore, rule (7) represents either asituation in which higher quality hospitals attract more patients who are freeto choose their preferred provider (and the purchaser pays for the increasedadmissions to higher quality hospitals), or a situation in which the purchaserbuys more treatments from higher quality hospitals on behalf of the patientsit represents. For example, in the US an HMO could set the number ofpatients to be treated in each hospital according to some quality indices; inthe Italian NHS, an ASL (Azienda Sanitaria Locale: the purchaser) couldremove (reduce) part of the yearly ceiling set on the number of treatmentsif the hospital increases the quality of treatments16.

2.2.2 The medical sta¤

Doctors are "devoted workers", i.e. they receive utility from increasing theirpatients�health and therefore they prefer an earlier adoption of new tech-nologies by the hospital that enables a rapid achievement of health outcomeson behalf of their patients. The �devoted worker�assumption can be justi-�ed on several grounds: the doctor could be considered a benevolent agentthat truly believes that better health outcomes for patients can be achievedthrough progress in medical technology; he might even be biased in hisevaluation of the e¤ectiveness of the new technology since he wants earlyadoption for the bene�t of his principal (the patient). On the other hand,the doctor might also be motivated by sel�sh interests and might wish touse the new technology to quicken his career and enhance his reputation. Inany case, the technology of production enters the doctor�s utility functionwith a positive sign and he is interested in earlier adoption of new med-ical equipment. He provides the e¤ort that determines the level of totalquality as de�ned by (6). In particular, the doctor�s e¤ort input consistsof two components. The �rst is a minimum level of e¤ort el; which can bede�ned as �monitored e¤ort of the doctor�, and is delivered independently

16 It must be pointed out that, following rule (7), higher quality hospitals are rewardedwith more bought admissions at a given price p; however, the results hold even if thenumber of admissions were set constant, while the price varies according to quality levels.

8

of the adoption of the new technology by the hospital (we assume withoutlosing in generality that el = 0). The second component is a level of e¤orte; which cannot be observed or veri�ed by the other actors. Following theliterature on the devoted worker (Francois, 2000, 2003; Glazer, 2004), weassume that the doctor is not paid for the unveri�able e¤ort, though thisassumption can be relaxed without substantially changing the results. Thehospital hires doctors at the constant exogenous wage w; the private costfor the unveri�able e¤ort e is de�ned by m(e); with m0 > 0 and m00 > 0: Fi-nally, since doctors are interested in earlier adoption of the new technology,we can assume, without losing in generality, that e1 = e2 = e.

2.2.3 The hospital

The hospital is a surplus maximiser and in this respect it is interested in costminimisation. In our model the hospital becomes interested in the qualityof the care provided through the purchasing rule (7).

It stipulates a contract with the purchaser that foresees the payment ofa prospective price p for each treatment. In each period, the hospital caninvest in a new technology at unit cost r17. Then capital accumulation isgiven by k2 = k1 + i2; where i2 denotes investment in period 2. Both theinvestment and the e¤ort made by the medical sta¤ determine the level oftotal quality according to (6).

In addition to investment costs, the hospital faces some operating costsin running the new technology. Operating costs di¤er from period to perioddue to our assumption concerning the nature of the investment decision. Ingeneral, these costs are higher in the �rst period due to set-up costs, suchas learning cost and human capital formation, and lower in the subsequentperiods18. Again, to simplify we set c1 = c < p and c2 = 0:

By the above arguments, the hospital net surplus in the �rst period is:

R1(k1; e) � (p� c)x ; (8)

17 In this article, we assume that the investment cost does not change over time. How-ever, the results would not change if we assume that the investment cost at time 2 is lowerthan at time 1, i.e. r2 < r1 (Levaggi and Moretto, 2004) or decreases with the dimensionof the project, i.e. r(k) with r0(k) < 0 (Dixit, 1993).18As an example, we might think about introducing laser therapy to treat patients with

speci�c diseases. In the �rst period, we will have to bear the cost of the equipment andthe cost related to teaching the sta¤ how to use the new technology. In the second period,the purchase of another laser to treat the same ailment simply increases the cost due tothe higher number of treated patients.

9

and in the second period is:

R2(k1; k2; e; ";�) � px2(q1; q2) (9)

� p[x+ q1(k1; e; "1;�1) + �(q2(k2; e; "2;�2)� q1(k1; e; "1; �1))]

2.2.4 Information structure and timing

Since the quality of hospital care and the doctors�e¤orts are non-contractablevariables (i.e. even though the parties of a contract can observe or measurethem, they cannot be enforced before a court), our model may present sev-eral forms of asymmetry of infomation among the three actors consideredhere. In particular, we assume that in each period:

� No one of the three actors is able to verify the current level of totalquality qt;

� The purchaser and the hospital cannot directly verify the doctors�e¤orts et.

Yet, since quality is a function of both the investment by the hospitaland the e¤ort of the medical sta¤, which is not observable by a third party,we also get:

� The contribution of the capital to the current quality level is not fullyveri�able by both the purchaser and the doctors19.

However, since in our two-period model the purchaser may observe ex-post the hospital capital k1 and the doctors�e¤orts e, we introduce a time-gap in observing and verifying the main elements of the contract, that is:

� The purchaser may always verify ex post q1 before a court (or a healthcare authority).

3 E¤ort and investment decision

Given the purchasing rule (7) and the information set, at time 1 the hospitaland the doctors choose their state variables k1 and e simultaneously andnon-cooperatively.

19 Intuitively, given that quality is not veri�able, even if the medical sta¤ can observethe level of investment in new technology, it cannot claim a high result in quality by theprovision of its e¤ort.

10

Since doctors keep the level of e¤ort constant over time, qp di¤ers fromperiod 1 to period 2 only for the realisation of the patients�characteristics ":Without any loss in generality, we simplify the model by setting " constantover time20.

Therefore, uncertainty in the production process derives only from shocksa¤ecting the clinical quality �. As for �, we assume that, in the �rst period,�1 is known and normalised to 1 while, in the second period, �2 � � isstochastic and its realisation is characterised by the cumulative distribution�(�) with density �0(�) > 0 on � 2 [0;1), which is known by all theactors21.

By the above assumptions, the timing of the model can be summarisedas follows. At the beginning of period 1, the purchaser announces the pur-chasing rule (7) and the price p. The hospital and the medical sta¤, knowing�1; and the purchasing rule, decide non-cooperatively k1 and e respectively.At the beginning of period 2, q1 becomes veri�able, nature reveals �2 and,conditional on k1 and e (i.e. q1), the hospital chooses k2:

Before proceeding with the medical sta¤ and hospital decisions, we needto consider the ex-ante objective function of both these actors.

3.1 The medical sta¤�s ex-ante objective function

The medical sta¤ are paid an exogenous wage w and their e¤ort is constantover time; their objective function can be written as:

B(k1; e) � w+vq1(k1; e)�m(e) = w+v[(1��)h(e)+�g(k1; e)]�m(e) (10)

where v is the doctor�s evaluation of each unit of quality.

3.2 The hospital�s ex-ante objective function

The hospital decision to invest in health care technology is intertemporal.In particular, if in period 1 the hospital makes an investment that it cannotresell in period 2 and future capital returns are uncertain, this investmentdecision involves the exercise of an option. Because of this uncertainty, theopportunity of waiting to learn more about the future productivity level hasa timing premium (i.e. a holding value).

We start by describing the hospital action in the second period, giventhe stock of investment k1 inherited from period 1. We then step back and

20" can be the mean value of the shocks a¤ecting the perceived quality.21As in Bös and De Fraja (2002), we assume that there is symmetry of information

about the technology.

11

show how the marginal pro�t in the �rst period depends on the hospital�sexpected action in the second period.

Second period

By (9), (7) and (6) the hospital�s surplus at time 2 can be written as:

R2(k1; k2; e;�) � p[x+ q1(k1; e) + �(q2(k2; e;�)� q1(k1; e))] (11)

� p[x+ (1� �)h(e) + ( � �)�g(k1; e) + ��g(k2; e;�)]

The assumptions on qc guarantee that R2k2(k1; k2; e;�)) � 0 is continuousand strictly decreasing in k2 and continuous and strictly increasing in � (seeAppendix A). Then, for a given stock of k1 inherited from period 1 ande¤ort e, we can de�ne a critical value of � such that:22

R2k2(k1; e;~�) � p��gk2(k1; e; ~�) = r (12)

At the beginning of period 2, nature reveals � and the hospital adjustsits stock of capital to the new optimal level that we identify as k2(�): Thestock of capital must satisfy the constraint:

k2(�) � k1 (13)

Thus, depending on the inherited stock k1 and e; from (12) it emerges thatwhen � > ~�(k1; e); it is optimal for the hospital to invest in extra units oftechnology up to the point where the marginal return equals the marginalinvestment cost r: On the other hand, when � < ~�(k1; e) the pro�t is so lowthat the hospital �nds it convenient not to invest, so k2(�) = k1:

First period

By using the option decomposition proposed by Abel et al.(1996), wecan show that:22By assumptions on (4) we get:

@~�

@r=

1

p��gk�> 0

@~�

@k= � gkk

gk�> 0

and

@~�

@e= � gke

gk�> 0

12

Lemma 1 The value of the hospital�s investment can be written as:

V (k1; e) � G(k1; e)� �O(k1; e) (14)

where:

G(k1; e) � (p�c)x+�p[x+ (1��)h(e)+( ��)�g(k1; e)+1Z0

��g(k1; e;�)d�(�)]

O(k1; e) �+1Z~�

f�[p��g(k2(�); e;�)� rk2(�)] + [p��g(k1; e;�)� rk1]g d�(�)

and � is the discount factor.

Proof. See Appendix AThe term G(k1; e) is the hospital�s expected present value of returns,

keeping the stock of capital �xed at k1: This can be interpreted as thehospital�s value when it does not expand its investment in the second period.The term O(k1; e) indicates the value of the (call) option to expand thecapital in the second period if � rises above ~�: Equation (14) then hasan interesting and immediate interpretation: when the hospital invests inperiod 1 it gets the value G(k1; e) but gives up the opportunity or option toinvest in the future, valued at O(k1; e):

The non-contractability of k1 and e in the �rst period implies that theinvestment decisions by both actors are taken non-cooperatively. In thisrespect, equations (10) and (14) constitute a two-person normal form game.Therefore, we need to derive the best reply functions of the two actors.

3.3 The best reply function of the doctor

The doctor�s reaction curve is derived from his �rst-order condition on (10),that is:

Be(k1; e) � v[(1� �)h0(e) + �ge(k1; e)]�m0(e) = 0 (15)

Moreover, since:

Bee(k1; e) � v[(1� �)h00(e) + �gee(k1; e)]�m00(e) < 0

for any given value of k1 a unique value of e� exists satisfying equation (15).The total di¤erential of (15) yields:

13

de

dk1 je=e�= �Bek1(k1; e)

Bee(k1; e)(16)

� � v�gek(k1; e)

v[(1� �)h00(e) + �gee(k1; e)]�m00(e)

Since the two inputs are substitutes, i.e. gek(k1; e) < 0; the doctor�sreaction curve slopes downwards. This assumption appears plausible: anincrease in the doctor�s e¤ort somehow reduces hospital investment in capi-tal, and vice versa. This is represented by the curve DD in Figure 1.

Figure 1 about here

3.4 The best reply function of the hospital

Similarly, the hospital reaction function is obtained by the �rst-order con-dition on (14). The optimal amount of capital in period 1 depends on acomparison between marginal bene�ts and marginal costs:

Vk1(k1; e) � Gk1(k1; e)� �Ok1(k1; e) = r (17)

where:

Gk1(k1; e) � �p[( � �)�gk1(k1; e) ++1Z0

��gk1(k1; e;�)]d�(�)]

= �p �gk1(k1; e) +

+1Z0

�p��[gk1(k1; e;�)� gk1(k1; e)]d�(�)]

Ok1(k1; e) �+1Z~�

[p��gk1(k1; e;�)� r]d�(�) � 0

Equation (17) emphasises the role played by the option pricing approachin determining the stock of capital in period 1. The hospital optimal behav-iour does not simply require the equalisation of the expected present valueof marginal returns in the �rst period, i.e. Gk1(k1; e) and the marginal costof the investment r: In fact, costs are represented by the price of the invest-ment, r; plus the value of the marginal call option, Ok1(k1; e); as investing

14

in period 1 means giving up the opportunity of delaying the investment.Moreover, since:

Vk1k1(k1; e) � Gk1k1(k1; e)� �Ok1k1(k1; e)

� �p( � �)�gk1k1(k1; e) + �+1Z0

p��gk1k1(k1; e;�))d�(�)

��+1Z~�

p��gk1k1(k1; e;�)d�(�)

� �p( � �)�gk1k1(k1; e) + �

~�Z0

p��gk1k1(k1; e;�))d�(�) < 0

for any given value of r and e, a unique value of k�1 exists satisfying equation(17).

The total di¤erential of (17) can be written as:

dk1de jk1=k�1

= � Vk1e(k1; e)Vk1k1(k1; e)

(18)

where:

Vk1e(k1; e) = �p( � �)�gk1e(k1; e) + �

~�Z0

p��gk1e(k1; e;�))d�(�) < 0

Since the two inputs are substitutes we get Vk1e(k1; e) < 0 and then (18)is downward-sloping. This is represented by the curve HH in Figure 1.

3.5 The equilibrium

The intersection of the two best reply functions is the Nash equilibrium, de-noted by N in Figure 1. We also assume that the doctor�s reaction functionis steeper than the hospital reaction function23. This guarantees that theNash equilibrium is unique and stable (Vives 1999, p. 49-52). Therefore,the following proposition holds (see Figure 1):

23This assumption seems reasonable since in most cases the rate of substitution betweencapital and e¤ort is higher for doctors than for the hospital.

15

Proposition 1 1) The presence of devoted doctors implies underinvestmentat time t = 1.

2) The Nash equilibrium is not optimal since it usually implies a lowerlevel of e¤ort and investment than the First Best.

Proof. See Appendix BThe �rst part of proposition 1 is a straightforward application of the

geometric solution of the Nash equilibrium. In Figure 1, the point (k̂1; 0)represents the benchmark solution for the case of a doctor that is not adevoted worker. In this case, the level of capital is higher than in our Nashsolution N = (k�1; e

�).To compare the Nash solution with the First Best, we need to depict

the hospital iso-pro�t and the doctor�s iso-utility curves. In Figure 1, PPrepresents the hospital iso-pro�t curve and UU the doctor iso-utility curvegoing through point N . The First Best is the set of points where the iso-pro�t and iso-utility curves are tangent. From Figure 1, it can be seen thatthese points are characterized by a higher level of e¤ort and investment.

4 Purchasing rule and Nash equilibrium

Let�s now investigate how the purchaser can in�uence the investment/e¤ortmix by changing the parameters of the purchasing rule (7). In particularwe compare the Nash equilibria for the following alternative values of theparameters of the purchasing rule:

� � = 0;so that the number of patients whose treatment is reimbursedin the second period depends only on the quality level at time t = 1;

� = �;so that the number of patients whose treatment is reimbursedin the second period depends only on the quality level at time t = 2 ;

� = 0; and the hospital can increase the number of patients treated inthe second period (and its rewards) only if the quality increases in thesecond period.

This comparison has important policy implications as in the �rst casethe option to delay the investment held by the hospital is neutralized. Thatis, even if the level of quality can be observed only ex post, asymmetry ofinformation is ruled out of the system. When the contract is signed, thepurchaser cannot observe both the level of investment in health technologyand the doctor�s e¤ort, but he will be able to do so before implementing the

16

relevant part of the contract. In our model this is a su¢ cient deterrent toprevent the hospital and doctor cheating on their decision variables in the�rst period. In the second period the issue becomes irrelevant since the newinvestment is not considered in the decision of how many patients to sendto the hospital.

Since the purchasing rule a¤ects only the hospital objective function,in order to analyse how the Nash solutions change varying the parametersof (7), we need to compare the di¤erent hospital best reaction functions.De�ning k��=01 ; k� =�1 and k� =01 the level of capital that the hospital wouldobtain under the three cases examined, we can prove the following proposi-tion.

Proposition 2 1) For � su¢ ciently low, the level of capital and e¤ort inperiod 1 can be ranked as follows:

k�1 > k� =�1 >

k� =01 > 0k��=01 > 0

and 0 < e� < e� =� <e� =0

e��=0

2) For � su¢ ciently high the level of capital and e¤ort in period 1 canbe ranked as follows:

k��=01 > k�1 > k� =�1 and e��=0 < e� < e� =�

while a Nash equilibrium for = 0 does not exist.

Proof. See Appendix CA �rst important result follows from Proposition 2: the purchaser can

induce the substitution of capital with e¤ort by reducing the weight ofthe �rst period quality q1 in the rule (7). That is, an increase in the ratio�= shifts down the hospital�s best reply function (17) with respect to (18),and we obtain k�1 > k

� =�1 > k� =01 ; and e� < e� =� < e� =0 as depicted in

Figure 2.As the real option theory predicts, an increase in the ratio �= (i.e in

the weight of the option to wait � compared to the weight of investing today ) delays the investment decision. This is a consequence of the "bad newsprinciple of irreversible investment": a variance in health quality makes theinvestment return volatile with positive e¤ect on the value of the investment.However, the net marginal bene�t of waiting, arising from the avoidance ofan investment in the bad state, increases. This induces delay (Bernanke,1983).

A second important result that follows from Proposition 2 is the im-possibility of a global ranking in terms of substitution between capital and

17

e¤ort. In fact, the optimal level of investment is not maximised for � = 0;which contradicts the real option theory. That is, despite the disappearanceof the option e¤ect, we do not obtain a clear increase in the investment inthe �rst period compared with k�1 (and/or k

� =�1 ).

The parameter � in�uences both the expected marginal returns of theinvestment Gk1(k1; e) and the marginal call option, Ok1(k1; e): This meansthat its e¤ect is countervailing since it incentivates delaying the investment,but it increases its expected marginal return in the �rst period. The overalle¤ect may lead to Vk1(k1; e) > V

�=0k1

(k1; e) and then k�1 > k��=01 . This leads

indeed to the second important result of proposition 2. For any given ; athreshold ~� may exist such that:

Vk1(k1; e) � V �=0k1 (k1; e) for � � ~�

Vk1(k1; e) < V �=0k1 (k1; e) for � > ~�

If the option e¤ect (i.e. �) is su¢ ciently high; the disequality may be re-verted and we get k�1 < k

��=01 (Appendix C).

Figure 2 about here

5 Purchasing rule and total quality

As argued, the purchaser wants to maximise total quality in order to makethe best treatment available for its patients. Although it cannot controlhospital care quality, it can pursue its goal by in�uencing both the hospitalinvestment in new technologies and the level of e¤ort by the medical sta¤in the �rst period. This can be done by setting the parameters of thepurchasing rule. In particular the following proposition holds :

Proposition 3 Within the long-term contract between the hospital and thepurchaser, the latter is able to rank the total quality at t = 1 as follows:

1) For � su¢ ciently low, we get:

q�1 > q� =�1 >

q� =01 > 0q��=01 > 0

2) For � su¢ ciently high, the rank becomes:

q��=01 > q�1 > q� =�1 > q� =01 = 0

18

Proof. See Appendix DThe intuition for this result relies on the properties of the doctor�s best

reply function DD. For example, we can compare the total quality at Nwith the one at N =�(see Figure 3). Let�s consider the �isoqual�QQ thatgoes throughN and depicts all the values of k1 and e compatible with a givenquality level. As k1 decreases, the doctor increases e along the curve DD;but if the marginal cost of the e¤ort increases with e; this is not su¢ cientto keep the quality constant. Therefore, to the right of the point N , theisoqual QQ lies above the doctor�s reply function DD; while to the left ofN , it lies below DD. This implies that point N =�, which represents theNash solution for = �; lies on an isoqual lower than the one through N;with a reduction in the total quality. Similar results apply for the cases of = 0 and � = 0.

These results have important implications both in theoretical and policyterms. In our model - as stated by the �rst part of Proposition 3 - for �below a speci�c threshold

��, total quality is higher than when the purchasing

rule is based only on past investment (� = 0). This implies that, for �su¢ ciently low but positive, the purchaser can increase total quality in the�rst period without eliminating the hospital option value of investing in thesecond period. This is possible because of the existence of a substitutione¤ect between capital and devoted physicians�e¤orts. If � = 0, there shouldbe no substitution between capital and e¤ort24.

Figure 3 about here

From proposition 3, we can also determine whether total quality is higherat the Nash solution, where the doctor values the quality, than at the solutionwhere the doctor does not.

Corollary 1 The total quality is higher when the doctor values it, i.e.

q�1 > q1(k̂1; 0)

Proof. See Appendix EIf the doctor is not devoted, he sets e = 0 (i.e. his e¤ort is only el) and

the hospital sets the investment at (k̂1; 0), where the reply function intersectsthe vertical axis. To compare the total quality at N with the one at (k̂1; 0)

24Di¤erently in Moretto and Levaggi (2004) the investment was higher when the optionvalue to invest in the second period was set to zero (i.e. � was made equal to zero); in fact,the purchasing rule is backward looking (since the hospital receives more patients only ifit has invested in past periods) and the current level of investment i2 is never considered.

19

we consider the isoqual that goes through (k̂1; 0), i.e. the curve Q̂Q̂ in Figure3. Since the marginal rate of transformation between k1 and e is decreasing,the isoqual through point (k̂1; 0) lies below the curve of the hospital�s replyfunction HH. That is, the hospital may respond optimally to an increasein the e¤ort made by the doctor by reducing the investment less than thereduction required by the isoqual through point (k̂1; 0). Therefore, point Nlies on an isoqual higher than the one through (k̂1; 0).

If the medical sta¤ are not devoted, the purchaser is not able to in�uencethe trade-o¤ between e¤ort and capital, hence it is indi¤erent between apurchasing rule de�ned on quality or on the level of capital. Its purchasingrule can be written as:

x2(k1; k2) � x+ k1 + �(k2 � k1) with ; � � 0 and � �

In this case, it is possible to show that the only possible rank is: k��=01 >k�1 > k

� =�1 > k� =01 as in Levaggi and Moretto (2004).

In a context where the medical sta¤ are not devoted, the purchaserfaces an intertemporal trade-o¤ in deciding the level of investment, i.e. itmight decide to delay hospital investment in new technology either for policyreasons or due to the existence of a budget constraint, but by doing so itfaces the cost of verifying hospital care quality (i.e. it can verify quality onlyex-post). In this case the problem in itself o¤ers a simple solution: setting� = 0 in the purchasing rule permits maximisation of the level of investmentat t = 1 and rules out any veri�ability problem.

On the contrary, with the presence of devoted doctors, a true trade-o¤exists between the level and veri�ability of quality. The devoted workeradds an important dimension to the set of choices of the purchaser. Besidesthe intertemporal substitution between present and future investment, itbecomes possible to substitute capital with doctor�s e¤ort to increase totalquality. In this way, it is possible to get a higher quality even with a lowerinvestment in new technology, but now � = 0 is no longer su¢ cient to ruleout the veri�ability problem.

6 Conclusions

The model presented in this paper adds important new dimensions to thedebate on quality and investment in new technology in hospital care.

Considering the interaction between three actors (a purchaser, a hos-pital and a hospital�s medical sta¤), we explicitly model two fundamental

20

determinants of hospital care quality: the e¤ort of the medical sta¤ andthe investment in hospital technology which has the characteristic of beingirreversible. The latter had been introduced by Levaggi and Moretto (2004);in this paper the �devoted worker�characteristics of the e¤ort produced bythe medical sta¤ - an aspect so far neglected in the traditional literature - ismodelled explicitly. The utility of the hospital medical sta¤ depends bothon the salary received and on the outcome of care. In this respect, doctorscan be considered devoted workers. This assumption has important conse-quences both on the level of investment decided by the hospital and then on�nal quality of in-patient care. We show that in the game developed betweenthe hospital and the medical sta¤ the presence of devoted doctors allows thehospital to reduce its investment while increasing the level of quality.

We then show that, when investment in new technology is irreversible,a purchasing rule that cancels out the option to delay (i.e. � = 0; wherethe purchaser reimburses the hospital only on the current level of quality) isnever optimal. From a policy perspective, this result has an important im-plication: in the de�nition of the long-term contract between the purchaserand the hospital there is a trade-o¤ between the level and the veri�abilityof quality. The purchaser could use the substitutability between capital anddoctors�e¤orts to increase quality, but this reduces its ability to verify it.

The model presented in this paper is a �rst step in modelling qualityin a devoted workers setting and our approach can be extended in severaldirections.

First of all, we could consider, as in Levaggi and Moretto (2004), that thetechnology is innovative only at the beginning (�rst period) of its adoptionwhen learning costs (related to the size of the investment) are higher andfuture operating costs of running the technology are not known. However,it should be considered that in the second period (in general, in subsequentperiods) the technology is consolidated and the hospital investing in the �rstperiod produces a positive externality to the whole system.

The assumption of the devoted worker also adds new dimensions to thequality setting of hospital care. In this paper we have in fact assumed thatall the actors care about the same type of quality, but this assumption mightbe relaxed. In particular, it could be considered that the type of hospitalcare quality depends on the type of treatment. For surgical treatment, forexample, clinical quality is probably very important, but for rehabilitationor for palliative care, perceived (relational) quality might be considered morerelevant. In the latter cases, the relatively higher importance of perceivedquality might mitigate the e¤ect of the devoted physician on the investmentdecision, hence on the optimal purchasing rule. Another important extension

21

could be the explicit consideration within the model of hospital competitionon quality ruled by patients� choices. This would add another importantactor (the patient) to the model and in this case the hospital�s reputationwould become an essential ingredient of perceived quality.

22

A Proof of Lemma 1

At t = 2; the hospital�s surplus is given by (11), i.e:

R2(k1; k2; e;�) � p[x+ ( � �)q1(k1; e) + �q2(k2; e;�)]� p[x+ (1� �)h(e) + ( � �)�g(k1; e) + ��g(k2; e;�)]

with the properties:

R2k2 � p�@q2@k2

� p��gk2(k2; e;�) > 0; (19)

R2k2k2 � p�@2q2@k22

� p��gk2k2(k2; e;�) < 0; (20)

If the hospital does not invest in the second period, i.e. k2 = k1; its surplus(11) reduces to:

R2(k1; e;�) � p[x+ ( � �)q1(k1; e) + �q2(k1; e;�)]� p[x+ (1� �)h(e) + ( � �)�g(k1; e) + ��g(k1; e;�)]

which still depends on both q1 and q225. Finally:

R2k2� � p�@2q2@k2@�

� p��gk2�(k2; e;�) > 0 (21)

Since the value of the hospital at t = 1 is:

V (k1; e) � R1(k1; e) + �

8><>:~�Z0

R2(k1; e;�)d�(�) (22)

+

+1Z~�

fR2(k1; k2(�); e;�)� r[k2(�)� k1] gd�(�)

9>=>; ;25Only if � = 1 we get q2 = q1 and

R2(k1; e;�) � p[x+ q1(k1; e)]

23

easy computation shows that (22) can be written as:

V (k1; e) � R1(k1; e) + �+1Z0

R2(k1; e;�)d�(�) (23)

+�

+1Z~�

f�[R2(k1; k2(�); e;�)� rk2(�)] + [R2(k1; e;�)� rk1]gd�(�):

where � is the discount factor. Then, de�ning:

G(k1; e) � R1(k1; e) + �+1Z0

R2(k1; e;�)d�(�);

O(k1; e) �+1Z~�

f�[R2(k1; k2(�); e;�)� rk2(�)] + [R2(k1; e;�)� rk1]gd�(�);

by direct substitution of (8) and (11), we obtain:

V (k1; e) = G(k1; e)� �O(k1; e)

where:

G(k1; e) � (p� c)x + �

1Z0

p[x+ ( � �)q1(k1; e) + �q2(k1; e;�)]d�(�)

� (p� c)x+ �1Z0

p[x+ (1� �)h(e) + ( � �)�g(k1; e) + ��g(k1; e;�)]d�(�)

� (p� c)x+ �p[x+ (1� �)h(e) + ( � �)�g(k1; e) +1Z0

��g(k1; e;�)d�(�)]

O(k1; e) �+1Z~�

f�[p(x+ ( � �)q1(k1; e) + �q2(k2(�); e;�))� rk2(�)]

+ [p(x+ ( � �)q1(k1; e) + �q2(k1; e;�))� rk1]g d�(�)

24

�+1Z~�

f�[p�q2(k2(�); e;�))� rk2(�)] + [p�q2(k1; e;�))� rk1]g d�(�)

�+1Z~�

f�[p(�((1� �)h(e) + �g(k2(�); e;�)))� rk2(�)]

+ [p(�((1� �)h(e) + �g(k1; e;�)))� rk1]g d�(�)

�+1Z~�

f�[p��g(k2(�); e;�)� rk2(�)] + [p��g(k1; e;�)� rk1]g d�(�)

This concludes the proof.

B Proof of Proposition 1

The �rst part of the proposition is a straightforward application of the geo-metric solution of the Nash equilibrium. For the second part, we need todraw the hospital�s iso-pro�t curve and the doctor�s iso-utility curve in the(k1; e) plane.

Let�s start with the doctor�s iso-utility curve. Totally di¤erentiating (10)we get:

Bk1(k1; e)dk1 +Be(k1; e)de = dB

and, setting dB = 0; we can evaluate the sign of:

dk1de

= � Be(k1; e)Bk1(k1; e)

(24)

The numerator is simply given by (15) while the denominator is:

Bk1(k1; e) � v�gk1(k1; e) > 0

Then the slope of the iso-utility curve is simply determined by (15). Fora �xed value of k1;(24) is decreasing up to e� and increasing for a higher

25

value of e: The same procedure determines the hospital�s iso-pro�t curve.By totally di¤erentiating (14) we get

Vk1(k1; e)dk1 + Ve(k1; e)de = dV

and, then:dk1de

= � Ve(k1; e)Vk1(k1; e)

(25)

The numerator of (25) is simply (17) and the denumerator is given by:

Ve(k1; e) � Ge(k1; e)� �Oe(k1; e)

� �p[ (1� �)h0(e) + ( � �)�ge(k1; e) +1Z0

��ge(k1; e;�)d�(�)]

��+1Z~�

f�[p��ge(k2(�); e;�)] + [p��ge(k1; e;�)]g d�(�)

� �p[ (1� �)h0(e) + ( � �)�ge(k1; e) +

~�Z0

��ge(k1; e;�)d�(�)]

+�

+1Z~�

fp��ge(k2(�); e;�)g d�(�)

Since the above expression is always positive the slope of the iso-pro�t curveis, for a �xed value of e;decreasing up to k�1 and increasing for a higher valueof k1: This concludes the proof.

C Proof of Proposition 2

Since the purchasing rule a¤ects only the hospital�s objective function, tocompare the Nash solutions varying the parameters of (7) we need to com-pare the di¤erent hospital best reaction functions.

Firstly, if = � the purchasing rule becomes x2 = x+�q2. The necessarycondition for a maximum (17) becomes:

V =�k1(k1; e) � G =�k1

(k1; e)� �Ok1(k1; e) = r (26)

26

where:

G =�k1(k1; e) � �

+1Z0

p��gk1(k1; e;�))d�(�)

Ok1(k1; e) �+1Z~�

[p��gk1(k1; e;�)� r]d�(�) � 0

and ~� is given by (12). Since G =�k1(k1; e) < Gk1(k1; e) the hospital�s reaction

function shifts down and to the left as depicted in Figure 2.Secondly, if = 0 the purchasing rule becomes x2 = x + �(q2 � q1);

which makes the surplus R2(k2; k1; e;�) independent from q at q2 = q1: Thenecessary condition for a maximum (17) becomes:

V =0k1(k1; e) � G =0k1

(k1; e)� �Ok1(k1; e) = r (27)

where:

G =0k1(k1; e) � �

+1Z0

p��[gk1(k1; e;�)� gk1(k1; e; 1)]d�(�)]

Ok1(k1; e) �+1Z~�

[p��gk1(k1; e;�)� r]d�(�) � 0

and ~� is still given by (12). Since G =0k1(k1; e) < G

=�k1

(k1; e) we have anothershift to the left of the hospital�s reply curve as in Figure 2.

Finally, if � = 0 the purchasing rule reduces to x2 = x + q1: For anygiven stock of q1 inherited from period 1, the surplus at t = 2 is alwaysconstant, which makes q2(�) = q1 for all �: Then, condition (17) reduces to:

V �=0k1 (k1; e) � G�=0k1 (k1; e) = r (28)

where:G�=0k1 (k1; e) � �p �gk1(k1; e)

O�=0k1 (k1; e) � 0

To compare (28) with (17), we can �rst rewrite Gk1(k1; e) in the followingform:

27

Gk1(k1; e) � �p[( � �)�gk1(k1; e) ++1Z0

��gk1(k1; e;�))d�(�)]

= �p �gk1(k1; e) + �

+1Z0

p��[gk1(k1; e;�)� gk1(k1; e)]d�(�)

= G�=0k1 (k1; e) +G =0k1(k1; e)

and:

Vk1(k1; e) � V �=0k1 (k1; e) +G =0k1(k1; e)� �O =0k1

(k1; e) (29)

� V �=0k1 (k1; e) + V =0k1

(k1; e)

Therefore, if V =0k1(k1; e) > 0 , k�=01 cannot be greater than k1:Furthermore,

if we specify (29) for the case in which � = it is easy to show that:

V =�k1(k1; e) � V �=0k1 (k1; e) + V

=0k1

(k1; e) (30)

hence, if V =0k1(k1; e) > 0 we get V

=�k1

(k1; e)� V �=0k1(k1; e) > 0 and the �rst

part of the proposition follows.Let�s now consider the second part of the proposition. By (29) (and (30)),

a necessary condition for having k�=01 > k�1 is V =0k1

(k1; e) � G =0k1(k1; e) �

�Ok1(k1; e) < 0; which in turn implies k =01 = 0: After some simple alge-

28

braical manipulations we obtain:

G =0k1(k1; e)� �Ok1(k1; e)�y (31)

= �[

+1Z0

p��[gk1(k1; e;�)� gk1(k1; e)]d�(�)�+1Z~�

[p��gk1(k1; e;�)� r]d�(�)]

= �[

~�Z0

p��[gk1(k1; e;�)� gk1(k1; e)]d�(�) ++1Z~�

p��[gk1(k1; e;�)� gk1(k1; e)]d�(�)

�+1Z~�

[p��gk1(k1; e;�)� r]d�(�)]

= �[

~�Z0

p��[gk1(k1; e;�)� gk1(k1; e)]d�(�) ++1Z~�

[r � p��gk1(k1; e)]d�(�)]

= �[

~�Z0

p��[gk1(k1; e;�)� gk1(k1; e)]d�(�) + [r � p��gk1(k1; e)](1� �(~�)]

= �[

~�Z0

p��[gk1(k1; e;�)� gk1(k1; e)]d�(�) + p��[gk1(k1; e; ~�)� gk1(k1; e)](1� �(~�)]

If ~� < 1, the �rst and second terms of (31) are both negative which yieldsG =0k1

(k1; e) � �Ok1(k1; e) < 0: On the contrary if ~� > 1 the second term ispositive while the sign of the �rst term is ambiguous, and becomes positiveif ~� � 1: Therefore, since:

@~�

@�= �gk(k1; e;

~�)

�gk�< 0

a trigger value ~� may exist such that:

Vk1(k1; e) < V �=0k1 (k1; e) for � > ~�

Vk1(k1; e) � V �=0k1 (k1; e) for � � ~�

This concludes the proof.

29

D Proof of Proposition 3

To prove the proposition it is su¢ cient to show that the isoquals that passthrough the Nash equilibrium can be ranked.

Lemma 2 The isoqual that passes through a Nash equilibrium, say N; liesabove the hospital�s reply function HH and below DD to the left of N andbelow HH and above DD to the right.

Proof. To do this we compare the slope of the isoqual with the slope ofthe hospital�s reply function and the slope of the doctor�s reply functionrespectively. Let�s �rst recall the MRT between k and e and the slope of thehospital�s reaction function, i.e.:

MRTk;e �dk1de q=�q

= �(1� �)h0(e) + �ge�gk

< 0; (32)

dk1de jk1=k�1

= � Vk1eVk1k1

< 0 (33)

By (32) and (33), the slope of the isoqual is greater than the slope of thehospital�s reaction function if:

(1� �)h0(e) + �ge�gk

>Vk1eVk1k1

(34)

Secondly, the condition that guarantees that the MRT is decreasing in e is:

@MRTk;e@e

= � [(1� �)h00(e) + �gee]�gk � [(1� �)h0(e) + �ge]�gke

(�gk)2> 0

or:(1� �)h00(e) + �gee

�gke>(1� �)h0(e) + �ge

�gk(35)

Putting together (34) and (35), with an MRT decreasing in e; the condition(34) becomes:

(1� �)h00(e) + �gee�gke

>Vk1eVk1k1

(36)

Thirdly, the condition that guarantees the stability of the Nash equilibrium(Vives 1999, p. 49-52) requires:

Vk1k1Bee > Vk1eBek1

30

or:BeeBek1

� v[(1� �)h00(e) + �gee]�m00(e)

v�gek>Vk1eVk1k1

(37)

which is equivalent to (36) if m00 = 0: Therefore, if (37) holds for m00 < 0also (36) holds. Finally,

de

dk1 je=e�= �Bek1

Bee� � v�gek

v[(1� �)h00(e) + �gee]�m00(e)

is also the inverse of the doctor�s best reply function.Let�s consider the isoqual that passes through N . As HH shifts down

(i.e. k1 decreases) the doctor increases e along the curve DD and a newequilibrium N 0 is reached. By Lemma 2, however, N 0 lies on an isoquallower than the one through N; with a reduction in the total quality. On thecontrary if HH shifts up (i.e. k1 increases) the doctor decreases e along thecurve DD and by Lemma 2, the new Nash solution N 00 lies on an isoqualhigher than the one through N; with an increase in the total quality. Thisconcludes the proof.

31

References

[1] Abel, A.B., A.K. Dixit, J.C. Eberly and Pindyck R.S. (1996), �Options,the value of capital, and investment�, Quarterly Journal of Economics,111(446), 753-777

[2] Baker, L.C and Phibss, C.S.(2002), "Managed care, technology adop-tion, and health care: The adoption of neonatal intensive care", RANDJournal of Economics, 33(3), 524-48

[3] Baker, L.C and Phibss, C.S.(2002), "Managed care and technologyadoption in health care:evidence from Magnetic Resonance Imaging ,Journal of Health Economics, 20(3), 395-421

[4] Bernanke, B.S. (1983), �Irreversibility, uncertainty and cyclical invest-ment�, Quarterly Journal of Economics, 98, 85-103.

[5] Biglaiser, G. and C.A. Ma (2001) �Price and Quality Competition underAdverse Selection: Market Organization and E¢ ciency, mimeo

[6] Bokhari, FAS (2001) Managed care and the adoption of hospital techn-nology: the case of cardiac catherization, mimeo

[7] Bös, D. and De Fraja, G. (2002), �Quality and outside capacity inthe provision of health services�, Journal of Public Economics, 84, 2,199-218.

[8] Chalkley, M. and Malcomson, J.H. (1998), Contracting for health ser-vices with unmonitored quality, Economic Journal, 108, 1093-1110

[9] Chalkley, M. and Malcomson, J.H. (2000), Government Purchasing ofHealth Services, in Culyer, A.J. and Newhouse, J.P. (eds.), Handbookof Health Economics, North-Holland, 461-536.

[10] Chalkley, M. and Malcomson, J.H. (2002), Cost sharing in health ser-vice provision: an empirical assessment of cost saving, Journal of HealthEconomics, 84, pp.219-249

[11] Dixit, A. and Pindyck R.S (1994), Investment under uncertainty,Princeton: Princeton University Press.

[12] Ellis, R. and T. Mc Guire (1986) Provider behaviour under prospectivereimbursement, Journal of Health Economics, 5(2), 129-51

32

[13] Francois, P. (2000) Public service motivation as an argument for gov-ernment provision, Journal of Public Economics, 78, 275-299.

[14] Francois, P. (2003) Not-for-pro�t provision of public services, EconomicJournal , 113, C53-C61.

[15] Glazer, A. (2004) Motivating devoted workers, International Journal ofIndustrial Economics, 22, 427-440.

[16] Gravelle H., (1999), Capitation Contracts: Access and Quality, Journalof Health Economics, 18(3), 315-340.

[17] Harris, JE (1979), Pricing rules for hospitals, Bell Journal of Eco-nomics, 10(1), 224-243

[18] HTC - Health Tecnology Centre (2003) Technology and quality: con-sideration for adoption and di¤usion. A literature review. mimeo

[19] Levaggi R., Moretto M. (2004) Investment in Hospital Care TechnologyUnder Di¤erent Purchasing Rules: A Real Option Approach, FEEMWorking Paper No. 75.04 http://ssrn.com/abstract=536002

[20] Ma, C. A. (1994) Health care payment systems: costs and quality in-centives, Journal of Economics and Management Strategy, vol.3 (1)pp.93-112

[21] Newhouse, J. (1996) Reimbursing health plans and health providers:e¢ ciency in production vs. selection, Journal of Economic Literature,34, 1236-1263

[22] Propper, C. Burgess, S.Green, K. (2004) Does Competition betweenHospitals Improve the Quality of Care? Hospital Death Rates and theNHS Internal Market; Journal of Public Economics, 88(7-8), 1247-72

[23] Stewart MA (1995), E¤ective physician-patient communication andhealth outcomes: a review, Canadian Medical Association Journal,152(9),1423-33

[24] Stewart, MA et al. (2000), The impact of patient-centered care on out-comes, Journal of Family Practice, 49(9), 796-804

[25] Varian, H. (1994) Sequential contributions to public goods, Journal ofPublic Economics, 53, 165-186.

[26] Vives, X. (1999), Oligopoly Pricing, Cambridge (MA), The MIT Press

33

D

D e

k1

N

H

Hospital’s iso-profit function P-P

Doctor’s iso-utility function U-U

First Best Solution

N0

*1k

H

e*

H

P

P

U

U

Figure 1

34

D

D e

k1

N

Nα=γ

Nγ=0

H

H

Figure 2

35

D

D e

k1

N

QH

HQ

H

1kH

*1k

H

e*

H

Nα=γQ

Q

Figure 3

36

NOTE DI LAVORO DELLA FONDAZIONE ENI ENRICO MATTEI

Fondazione Eni Enrico Mattei Working Paper Series Our Note di Lavoro are available on the Internet at the following addresses:

http://www.feem.it/Feem/Pub/Publications/WPapers/default.html http://www.ssrn.com/link/feem.html

http://www.repec.org

NOTE DI LAVORO PUBLISHED IN 2004

IEM 1.2004 Anil MARKANDYA, Suzette PEDROSO and Alexander GOLUB: Empirical Analysis of National Income and So2 Emissions in Selected European Countries

ETA 2.2004 Masahisa FUJITA and Shlomo WEBER: Strategic Immigration Policies and Welfare in Heterogeneous Countries

PRA 3.2004 Adolfo DI CARLUCCIO, Giovanni FERRI, Cecilia FRALE and Ottavio RICCHI: Do Privatizations Boost Household Shareholding? Evidence from Italy

ETA 4.2004 Victor GINSBURGH and Shlomo WEBER: Languages Disenfranchisement in the European Union ETA 5.2004 Romano PIRAS: Growth, Congestion of Public Goods, and Second-Best Optimal Policy CCMP 6.2004 Herman R.J. VOLLEBERGH: Lessons from the Polder: Is Dutch CO2-Taxation Optimal PRA 7.2004 Sandro BRUSCO, Giuseppe LOPOMO and S. VISWANATHAN (lxv): Merger Mechanisms

PRA 8.2004 Wolfgang AUSSENEGG, Pegaret PICHLER and Alex STOMPER (lxv): IPO Pricing with Bookbuilding, and a When-Issued Market

PRA 9.2004 Pegaret PICHLER and Alex STOMPER (lxv): Primary Market Design: Direct Mechanisms and Markets

PRA 10.2004 Florian ENGLMAIER, Pablo GUILLEN, Loreto LLORENTE, Sander ONDERSTAL and Rupert SAUSGRUBER (lxv): The Chopstick Auction: A Study of the Exposure Problem in Multi-Unit Auctions

PRA 11.2004 Bjarne BRENDSTRUP and Harry J. PAARSCH (lxv): Nonparametric Identification and Estimation of Multi-Unit, Sequential, Oral, Ascending-Price Auctions With Asymmetric Bidders

PRA 12.2004 Ohad KADAN (lxv): Equilibrium in the Two Player, k-Double Auction with Affiliated Private Values PRA 13.2004 Maarten C.W. JANSSEN (lxv): Auctions as Coordination Devices PRA 14.2004 Gadi FIBICH, Arieh GAVIOUS and Aner SELA (lxv): All-Pay Auctions with Weakly Risk-Averse Buyers

PRA 15.2004 Orly SADE, Charles SCHNITZLEIN and Jaime F. ZENDER (lxv): Competition and Cooperation in Divisible Good Auctions: An Experimental Examination

PRA 16.2004 Marta STRYSZOWSKA (lxv): Late and Multiple Bidding in Competing Second Price Internet Auctions CCMP 17.2004 Slim Ben YOUSSEF: R&D in Cleaner Technology and International Trade

NRM 18.2004 Angelo ANTOCI, Simone BORGHESI and Paolo RUSSU (lxvi): Biodiversity and Economic Growth: Stabilization Versus Preservation of the Ecological Dynamics

SIEV 19.2004 Anna ALBERINI, Paolo ROSATO, Alberto LONGO and Valentina ZANATTA: Information and Willingness to Pay in a Contingent Valuation Study: The Value of S. Erasmo in the Lagoon of Venice

NRM 20.2004 Guido CANDELA and Roberto CELLINI (lxvii): Investment in Tourism Market: A Dynamic Model of Differentiated Oligopoly

NRM 21.2004 Jacqueline M. HAMILTON (lxvii): Climate and the Destination Choice of German Tourists

NRM 22.2004 Javier Rey-MAQUIEIRA PALMER, Javier LOZANO IBÁÑEZ and Carlos Mario GÓMEZ GÓMEZ (lxvii): Land, Environmental Externalities and Tourism Development

NRM 23.2004 Pius ODUNGA and Henk FOLMER (lxvii): Profiling Tourists for Balanced Utilization of Tourism-Based Resources in Kenya

NRM 24.2004 Jean-Jacques NOWAK, Mondher SAHLI and Pasquale M. SGRO (lxvii):Tourism, Trade and Domestic Welfare NRM 25.2004 Riaz SHAREEF (lxvii): Country Risk Ratings of Small Island Tourism Economies

NRM 26.2004 Juan Luis EUGENIO-MARTÍN, Noelia MARTÍN MORALES and Riccardo SCARPA (lxvii): Tourism and Economic Growth in Latin American Countries: A Panel Data Approach

NRM 27.2004 Raúl Hernández MARTÍN (lxvii): Impact of Tourism Consumption on GDP. The Role of Imports CSRM 28.2004 Nicoletta FERRO: Cross-Country Ethical Dilemmas in Business: A Descriptive Framework

NRM 29.2004 Marian WEBER (lxvi): Assessing the Effectiveness of Tradable Landuse Rights for Biodiversity Conservation: an Application to Canada's Boreal Mixedwood Forest

NRM 30.2004 Trond BJORNDAL, Phoebe KOUNDOURI and Sean PASCOE (lxvi): Output Substitution in Multi-Species Trawl Fisheries: Implications for Quota Setting

CCMP 31.2004 Marzio GALEOTTI, Alessandra GORIA, Paolo MOMBRINI and Evi SPANTIDAKI: Weather Impacts on Natural, Social and Economic Systems (WISE) Part I: Sectoral Analysis of Climate Impacts in Italy

CCMP 32.2004 Marzio GALEOTTI, Alessandra GORIA ,Paolo MOMBRINI and Evi SPANTIDAKI: Weather Impacts on Natural, Social and Economic Systems (WISE) Part II: Individual Perception of Climate Extremes in Italy

CTN 33.2004 Wilson PEREZ: Divide and Conquer: Noisy Communication in Networks, Power, and Wealth Distribution

KTHC 34.2004 Gianmarco I.P. OTTAVIANO and Giovanni PERI (lxviii): The Economic Value of Cultural Diversity: Evidence from US Cities

KTHC 35.2004 Linda CHAIB (lxviii): Immigration and Local Urban Participatory Democracy: A Boston-Paris Comparison

KTHC 36.2004 Franca ECKERT COEN and Claudio ROSSI (lxviii): Foreigners, Immigrants, Host Cities: The Policies of Multi-Ethnicity in Rome. Reading Governance in a Local Context

KTHC 37.2004 Kristine CRANE (lxviii): Governing Migration: Immigrant Groups’ Strategies in Three Italian Cities – Rome, Naples and Bari

KTHC 38.2004 Kiflemariam HAMDE (lxviii): Mind in Africa, Body in Europe: The Struggle for Maintaining and Transforming Cultural Identity - A Note from the Experience of Eritrean Immigrants in Stockholm

ETA 39.2004 Alberto CAVALIERE: Price Competition with Information Disparities in a Vertically Differentiated Duopoly

PRA 40.2004 Andrea BIGANO and Stef PROOST: The Opening of the European Electricity Market and Environmental Policy: Does the Degree of Competition Matter?

CCMP 41.2004 Micheal FINUS (lxix): International Cooperation to Resolve International Pollution Problems KTHC 42.2004 Francesco CRESPI: Notes on the Determinants of Innovation: A Multi-Perspective Analysis CTN 43.2004 Sergio CURRARINI and Marco MARINI: Coalition Formation in Games without Synergies CTN 44.2004 Marc ESCRIHUELA-VILLAR: Cartel Sustainability and Cartel Stability

NRM 45.2004 Sebastian BERVOETS and Nicolas GRAVEL (lxvi): Appraising Diversity with an Ordinal Notion of Similarity: An Axiomatic Approach

NRM 46.2004 Signe ANTHON and Bo JELLESMARK THORSEN (lxvi): Optimal Afforestation Contracts with Asymmetric Information on Private Environmental Benefits

NRM 47.2004 John MBURU (lxvi): Wildlife Conservation and Management in Kenya: Towards a Co-management Approach

NRM 48.2004 Ekin BIROL, Ágnes GYOVAI and Melinda SMALE (lxvi): Using a Choice Experiment to Value Agricultural Biodiversity on Hungarian Small Farms: Agri-Environmental Policies in a Transition al Economy

CCMP 49.2004 Gernot KLEPPER and Sonja PETERSON: The EU Emissions Trading Scheme. Allowance Prices, Trade Flows, Competitiveness Effects

GG 50.2004 Scott BARRETT and Michael HOEL: Optimal Disease Eradication

CTN 51.2004 Dinko DIMITROV, Peter BORM, Ruud HENDRICKX and Shao CHIN SUNG: Simple Priorities and Core Stability in Hedonic Games

SIEV 52.2004 Francesco RICCI: Channels of Transmission of Environmental Policy to Economic Growth: A Survey of the Theory

SIEV 53.2004 Anna ALBERINI, Maureen CROPPER, Alan KRUPNICK and Nathalie B. SIMON: Willingness to Pay for Mortality Risk Reductions: Does Latency Matter?

NRM 54.2004 Ingo BRÄUER and Rainer MARGGRAF (lxvi): Valuation of Ecosystem Services Provided by Biodiversity Conservation: An Integrated Hydrological and Economic Model to Value the Enhanced Nitrogen Retention in Renaturated Streams

NRM 55.2004 Timo GOESCHL and Tun LIN (lxvi): Biodiversity Conservation on Private Lands: Information Problems and Regulatory Choices

NRM 56.2004 Tom DEDEURWAERDERE (lxvi): Bioprospection: From the Economics of Contracts to Reflexive Governance CCMP 57.2004 Katrin REHDANZ and David MADDISON: The Amenity Value of Climate to German Households

CCMP 58.2004 Koen SMEKENS and Bob VAN DER ZWAAN: Environmental Externalities of Geological Carbon Sequestration Effects on Energy Scenarios

NRM 59.2004 Valentina BOSETTI, Mariaester CASSINELLI and Alessandro LANZA (lxvii): Using Data Envelopment Analysis to Evaluate Environmentally Conscious Tourism Management

NRM 60.2004 Timo GOESCHL and Danilo CAMARGO IGLIORI (lxvi):Property Rights Conservation and Development: An Analysis of Extractive Reserves in the Brazilian Amazon

CCMP 61.2004 Barbara BUCHNER and Carlo CARRARO: Economic and Environmental Effectiveness of a Technology-based Climate Protocol

NRM 62.2004 Elissaios PAPYRAKIS and Reyer GERLAGH: Resource-Abundance and Economic Growth in the U.S.

NRM 63.2004 Györgyi BELA, György PATAKI, Melinda SMALE and Mariann HAJDÚ (lxvi): Conserving Crop Genetic Resources on Smallholder Farms in Hungary: Institutional Analysis

NRM 64.2004 E.C.M. RUIJGROK and E.E.M. NILLESEN (lxvi): The Socio-Economic Value of Natural Riverbanks in the Netherlands

NRM 65.2004 E.C.M. RUIJGROK (lxvi): Reducing Acidification: The Benefits of Increased Nature Quality. Investigating the Possibilities of the Contingent Valuation Method

ETA 66.2004 Giannis VARDAS and Anastasios XEPAPADEAS: Uncertainty Aversion, Robust Control and Asset Holdings

GG 67.2004 Anastasios XEPAPADEAS and Constadina PASSA: Participation in and Compliance with Public Voluntary Environmental Programs: An Evolutionary Approach

GG 68.2004 Michael FINUS: Modesty Pays: Sometimes!

NRM 69.2004 Trond BJØRNDAL and Ana BRASÃO: The Northern Atlantic Bluefin Tuna Fisheries: Management and Policy Implications

CTN 70.2004 Alejandro CAPARRÓS, Abdelhakim HAMMOUDI and Tarik TAZDAÏT: On Coalition Formation with Heterogeneous Agents

IEM 71.2004 Massimo GIOVANNINI, Margherita GRASSO, Alessandro LANZA and Matteo MANERA: Conditional Correlations in the Returns on Oil Companies Stock Prices and Their Determinants

IEM 72.2004 Alessandro LANZA, Matteo MANERA and Michael MCALEER: Modelling Dynamic Conditional Correlations in WTI Oil Forward and Futures Returns

SIEV 73.2004 Margarita GENIUS and Elisabetta STRAZZERA: The Copula Approach to Sample Selection Modelling: An Application to the Recreational Value of Forests

CCMP 74.2004 Rob DELLINK and Ekko van IERLAND: Pollution Abatement in the Netherlands: A Dynamic Applied General Equilibrium Assessment

ETA 75.2004 Rosella LEVAGGI and Michele MORETTO: Investment in Hospital Care Technology under Different Purchasing Rules: A Real Option Approach

CTN 76.2004 Salvador BARBERÀ and Matthew O. JACKSON (lxx): On the Weights of Nations: Assigning Voting Weights ina Heterogeneous Union

CTN 77.2004 Àlex ARENAS, Antonio CABRALES, Albert DÍAZ-GUILERA, Roger GUIMERÀ and Fernando VEGA-REDONDO (lxx): Optimal Information Transmission in Organizations: Search and Congestion

CTN 78.2004 Francis BLOCH and Armando GOMES (lxx): Contracting with Externalities and Outside Options

CTN 79.2004 Rabah AMIR, Effrosyni DIAMANTOUDI and Licun XUE (lxx): Merger Performance under Uncertain Efficiency Gains

CTN 80.2004 Francis BLOCH and Matthew O. JACKSON (lxx): The Formation of Networks with Transfers among Players CTN 81.2004 Daniel DIERMEIER, Hülya ERASLAN and Antonio MERLO (lxx): Bicameralism and Government Formation

CTN 82.2004 Rod GARRATT, James E. PARCO, Cheng-ZHONG QIN and Amnon RAPOPORT (lxx): Potential Maximization and Coalition Government Formation

CTN 83.2004 Kfir ELIAZ, Debraj RAY and Ronny RAZIN (lxx): Group Decision-Making in the Shadow of Disagreement

CTN 84.2004 Sanjeev GOYAL, Marco van der LEIJ and José Luis MORAGA-GONZÁLEZ (lxx): Economics: An Emerging Small World?

CTN 85.2004 Edward CARTWRIGHT (lxx): Learning to Play Approximate Nash Equilibria in Games with Many Players

IEM 86.2004 Finn R. FØRSUND and Michael HOEL: Properties of a Non-Competitive Electricity Market Dominated by Hydroelectric Power

KTHC 87.2004 Elissaios PAPYRAKIS and Reyer GERLAGH: Natural Resources, Investment and Long-Term Income CCMP 88.2004 Marzio GALEOTTI and Claudia KEMFERT: Interactions between Climate and Trade Policies: A Survey

IEM 89.2004 A. MARKANDYA, S. PEDROSO and D. STREIMIKIENE: Energy Efficiency in Transition Economies: Is There Convergence Towards the EU Average?

GG 90.2004 Rolf GOLOMBEK and Michael HOEL : Climate Agreements and Technology Policy PRA 91.2004 Sergei IZMALKOV (lxv): Multi-Unit Open Ascending Price Efficient Auction KTHC 92.2004 Gianmarco I.P. OTTAVIANO and Giovanni PERI: Cities and Cultures

KTHC 93.2004 Massimo DEL GATTO: Agglomeration, Integration, and Territorial Authority Scale in a System of Trading Cities. Centralisation versus devolution

CCMP 94.2004 Pierre-André JOUVET, Philippe MICHEL and Gilles ROTILLON: Equilibrium with a Market of Permits

CCMP 95.2004 Bob van der ZWAAN and Reyer GERLAGH: Climate Uncertainty and the Necessity to Transform Global Energy Supply

CCMP 96.2004 Francesco BOSELLO, Marco LAZZARIN, Roberto ROSON and Richard S.J. TOL: Economy-Wide Estimates of the Implications of Climate Change: Sea Level Rise

CTN 97.2004 Gustavo BERGANTIÑOS and Juan J. VIDAL-PUGA: Defining Rules in Cost Spanning Tree Problems Through the Canonical Form

CTN 98.2004 Siddhartha BANDYOPADHYAY and Mandar OAK: Party Formation and Coalitional Bargaining in a Model of Proportional Representation

GG 99.2004 Hans-Peter WEIKARD, Michael FINUS and Juan-Carlos ALTAMIRANO-CABRERA: The Impact of Surplus Sharing on the Stability of International Climate Agreements

SIEV 100.2004 Chiara M. TRAVISI and Peter NIJKAMP: Willingness to Pay for Agricultural Environmental Safety: Evidence from a Survey of Milan, Italy, Residents

SIEV 101.2004 Chiara M. TRAVISI, Raymond J. G. M. FLORAX and Peter NIJKAMP: A Meta-Analysis of the Willingness to Pay for Reductions in Pesticide Risk Exposure

NRM 102.2004 Valentina BOSETTI and David TOMBERLIN: Real Options Analysis of Fishing Fleet Dynamics: A Test

CCMP 103.2004 Alessandra GORIA e Gretel GAMBARELLI: Economic Evaluation of Climate Change Impacts and Adaptability in Italy

PRA 104.2004 Massimo FLORIO and Mara GRASSENI: The Missing Shock: The Macroeconomic Impact of British Privatisation

PRA 105.2004 John BENNETT, Saul ESTRIN, James MAW and Giovanni URGA: Privatisation Methods and Economic Growth in Transition Economies

PRA 106.2004 Kira BÖRNER: The Political Economy of Privatization: Why Do Governments Want Reforms? PRA 107.2004 Pehr-Johan NORBÄCK and Lars PERSSON: Privatization and Restructuring in Concentrated Markets

SIEV 108.2004 Angela GRANZOTTO, Fabio PRANOVI, Simone LIBRALATO, Patrizia TORRICELLI and Danilo MAINARDI: Comparison between Artisanal Fishery and Manila Clam Harvesting in the Venice Lagoon by Using Ecosystem Indicators: An Ecological Economics Perspective

CTN 109.2004 Somdeb LAHIRI: The Cooperative Theory of Two Sided Matching Problems: A Re-examination of Some Results

NRM 110.2004 Giuseppe DI VITA: Natural Resources Dynamics: Another Look

SIEV 111.2004 Anna ALBERINI, Alistair HUNT and Anil MARKANDYA: Willingness to Pay to Reduce Mortality Risks: Evidence from a Three-Country Contingent Valuation Study

KTHC 112.2004 Valeria PAPPONETTI and Dino PINELLI: Scientific Advice to Public Policy-Making

SIEV 113.2004 Paulo A.L.D. NUNES and Laura ONOFRI: The Economics of Warm Glow: A Note on Consumer’s Behavior and Public Policy Implications

IEM 114.2004 Patrick CAYRADE: Investments in Gas Pipelines and Liquefied Natural Gas Infrastructure What is the Impact on the Security of Supply?

IEM 115.2004 Valeria COSTANTINI and Francesco GRACCEVA: Oil Security. Short- and Long-Term Policies

IEM 116.2004 Valeria COSTANTINI and Francesco GRACCEVA: Social Costs of Energy Disruptions

IEM 117.2004 Christian EGENHOFER, Kyriakos GIALOGLOU, Giacomo LUCIANI, Maroeska BOOTS, Martin SCHEEPERS, Valeria COSTANTINI, Francesco GRACCEVA, Anil MARKANDYA and Giorgio VICINI: Market-Based Options for Security of Energy Supply

IEM 118.2004 David FISK: Transport Energy Security. The Unseen Risk? IEM 119.2004 Giacomo LUCIANI: Security of Supply for Natural Gas Markets. What is it and What is it not? IEM 120.2004 L.J. de VRIES and R.A. HAKVOORT: The Question of Generation Adequacy in Liberalised Electricity Markets

KTHC 121.2004 Alberto PETRUCCI: Asset Accumulation, Fertility Choice and Nondegenerate Dynamics in a Small Open Economy

NRM 122.2004 Carlo GIUPPONI, Jaroslaw MYSIAK and Anita FASSIO: An Integrated Assessment Framework for Water Resources Management: A DSS Tool and a Pilot Study Application

NRM 123.2004 Margaretha BREIL, Anita FASSIO, Carlo GIUPPONI and Paolo ROSATO: Evaluation of Urban Improvement on the Islands of the Venice Lagoon: A Spatially-Distributed Hedonic-Hierarchical Approach

ETA 124.2004 Paul MENSINK: Instant Efficient Pollution Abatement Under Non-Linear Taxation and Asymmetric Information: The Differential Tax Revisited

NRM 125.2004 Mauro FABIANO, Gabriella CAMARSA, Rosanna DURSI, Roberta IVALDI, Valentina MARIN and Francesca PALMISANI: Integrated Environmental Study for Beach Management:A Methodological Approach

PRA 126.2004 Irena GROSFELD and Iraj HASHI: The Emergence of Large Shareholders in Mass Privatized Firms: Evidence from Poland and the Czech Republic

CCMP 127.2004 Maria BERRITTELLA, Andrea BIGANO, Roberto ROSON and Richard S.J. TOL: A General Equilibrium Analysis of Climate Change Impacts on Tourism

CCMP 128.2004 Reyer GERLAGH: A Climate-Change Policy Induced Shift from Innovations in Energy Production to Energy Savings

NRM 129.2004 Elissaios PAPYRAKIS and Reyer GERLAGH: Natural Resources, Innovation, and Growth PRA 130.2004 Bernardo BORTOLOTTI and Mara FACCIO: Reluctant Privatization

SIEV 131.2004 Riccardo SCARPA and Mara THIENE: Destination Choice Models for Rock Climbing in the Northeast Alps: A Latent-Class Approach Based on Intensity of Participation

SIEV 132.2004 Riccardo SCARPA Kenneth G. WILLIS and Melinda ACUTT: Comparing Individual-Specific Benefit Estimates for Public Goods: Finite Versus Continuous Mixing in Logit Models

IEM 133.2004 Santiago J. RUBIO: On Capturing Oil Rents with a National Excise Tax Revisited ETA 134.2004 Ascensión ANDINA DÍAZ: Political Competition when Media Create Candidates’ Charisma SIEV 135.2004 Anna ALBERINI: Robustness of VSL Values from Contingent Valuation Surveys

CCMP 136.2004 Gernot KLEPPER and Sonja PETERSON: Marginal Abatement Cost Curves in General Equilibrium: The Influence of World Energy Prices

ETA 137.2004 Herbert DAWID, Christophe DEISSENBERG and Pavel ŠEVČIK: Cheap Talk, Gullibility, and Welfare in an Environmental Taxation Game

CCMP 138.2004 ZhongXiang ZHANG: The World Bank’s Prototype Carbon Fund and China CCMP 139.2004 Reyer GERLAGH and Marjan W. HOFKES: Time Profile of Climate Change Stabilization Policy

NRM 140.2004 Chiara D’ALPAOS and Michele MORETTO: The Value of Flexibility in the Italian Water Service Sector: A Real Option Analysis

PRA 141.2004 Patrick BAJARI, Stephanie HOUGHTON and Steven TADELIS (lxxi): Bidding for Incompete Contracts

PRA 142.2004 Susan ATHEY, Jonathan LEVIN and Enrique SEIRA (lxxi): Comparing Open and Sealed Bid Auctions: Theory and Evidence from Timber Auctions

PRA 143.2004 David GOLDREICH (lxxi): Behavioral Biases of Dealers in U.S. Treasury Auctions

PRA 144.2004 Roberto BURGUET (lxxi): Optimal Procurement Auction for a Buyer with Downward Sloping Demand: More Simple Economics

PRA 145.2004 Ali HORTACSU and Samita SAREEN (lxxi): Order Flow and the Formation of Dealer Bids: An Analysis of Information and Strategic Behavior in the Government of Canada Securities Auctions

PRA 146.2004 Victor GINSBURGH, Patrick LEGROS and Nicolas SAHUGUET (lxxi): How to Win Twice at an Auction. On the Incidence of Commissions in Auction Markets

PRA 147.2004 Claudio MEZZETTI, Aleksandar PEKEČ and Ilia TSETLIN (lxxi): Sequential vs. Single-Round Uniform-Price Auctions

PRA 148.2004 John ASKER and Estelle CANTILLON (lxxi): Equilibrium of Scoring Auctions

PRA 149.2004 Philip A. HAILE, Han HONG and Matthew SHUM (lxxi): Nonparametric Tests for Common Values in First- Price Sealed-Bid Auctions

PRA 150.2004 François DEGEORGE, François DERRIEN and Kent L. WOMACK (lxxi): Quid Pro Quo in IPOs: Why Bookbuilding is Dominating Auctions

CCMP 151.2004 Barbara BUCHNER and Silvia DALL’OLIO: Russia: The Long Road to Ratification. Internal Institution and Pressure Groups in the Kyoto Protocol’s Adoption Process

CCMP 152.2004 Carlo CARRARO and Marzio GALEOTTI: Does Endogenous Technical Change Make a Difference in Climate Policy Analysis? A Robustness Exercise with the FEEM-RICE Model

PRA 153.2004 Alejandro M. MANELLI and Daniel R. VINCENT (lxxi): Multidimensional Mechanism Design: Revenue Maximization and the Multiple-Good Monopoly

ETA 154.2004 Nicola ACOCELLA, Giovanni Di BARTOLOMEO and Wilfried PAUWELS: Is there any Scope for Corporatism in Stabilization Policies?

CTN 155.2004 Johan EYCKMANS and Michael FINUS: An Almost Ideal Sharing Scheme for Coalition Games with Externalities

CCMP 156.2004 Cesare DOSI and Michele MORETTO: Environmental Innovation, War of Attrition and Investment Grants

CCMP 157.2004 Valentina BOSETTI, Marzio GALEOTTI and Alessandro LANZA: How Consistent are Alternative Short-Term Climate Policies with Long-Term Goals?

ETA 158.2004 Y. Hossein FARZIN and Ken-Ichi AKAO: Non-pecuniary Value of Employment and Individual Labor Supply

ETA 159.2004 William BROCK and Anastasios XEPAPADEAS: Spatial Analysis: Development of Descriptive and Normative Methods with Applications to Economic-Ecological Modelling

KTHC 160.2004 Alberto PETRUCCI: On the Incidence of a Tax on PureRent with Infinite Horizons

IEM 161.2004 Xavier LABANDEIRA, José M. LABEAGA and Miguel RODRÍGUEZ: Microsimulating the Effects of Household Energy Price Changes in Spain

NOTE DI LAVORO PUBLISHED IN 2005 CCMP 1.2005 Stéphane HALLEGATTE: Accounting for Extreme Events in the Economic Assessment of Climate Change

CCMP 2.2005 Qiang WU and Paulo Augusto NUNES: Application of Technological Control Measures on Vehicle Pollution: A Cost-Benefit Analysis in China

CCMP 3.2005 Andrea BIGANO, Jacqueline M. HAMILTON, Maren LAU, Richard S.J. TOL and Yuan ZHOU: A Global Database of Domestic and International Tourist Numbers at National and Subnational Level

CCMP 4.2005 Andrea BIGANO, Jacqueline M. HAMILTON and Richard S.J. TOL: The Impact of Climate on Holiday Destination Choice

ETA 5.2005 Hubert KEMPF: Is Inequality Harmful for the Environment in a Growing Economy?

CCMP 6.2005 Valentina BOSETTI, Carlo CARRARO and Marzio GALEOTTI: The Dynamics of Carbon and Energy Intensity in a Model of Endogenous Technical Change

IEM 7.2005 David CALEF and Robert GOBLE: The Allure of Technology: How France and California Promoted Electric Vehicles to Reduce Urban Air Pollution

ETA 8.2005 Lorenzo PELLEGRINI and Reyer GERLAGH: An Empirical Contribution to the Debate on Corruption Democracy and Environmental Policy

CCMP 9.2005 Angelo ANTOCI: Environmental Resources Depletion and Interplay Between Negative and Positive Externalities in a Growth Model

CTN 10.2005 Frédéric DEROIAN: Cost-Reducing Alliances and Local Spillovers

NRM 11.2005 Francesco SINDICO: The GMO Dispute before the WTO: Legal Implications for the Trade and Environment Debate

KTHC 12.2005 Carla MASSIDDA: Estimating the New Keynesian Phillips Curve for Italian Manufacturing Sectors KTHC 13.2005 Michele MORETTO and Gianpaolo ROSSINI: Start-up Entry Strategies: Employer vs. Nonemployer firms

PRCG 14.2005 Clara GRAZIANO and Annalisa LUPORINI: Ownership Concentration, Monitoring and Optimal Board Structure

CSRM 15.2005 Parashar KULKARNI: Use of Ecolabels in Promoting Exports from Developing Countries to Developed Countries: Lessons from the Indian LeatherFootwear Industry

KTHC 16.2005 Adriana DI LIBERTO, Roberto MURA and Francesco PIGLIARU: How to Measure the Unobservable: A Panel Technique for the Analysis of TFP Convergence

KTHC 17.2005 Alireza NAGHAVI: Asymmetric Labor Markets, Southern Wages, and the Location of Firms KTHC 18.2005 Alireza NAGHAVI: Strategic Intellectual Property Rights Policy and North-South Technology Transfer KTHC 19.2005 Mombert HOPPE: Technology Transfer Through Trade PRCG 20.2005 Roberto ROSON: Platform Competition with Endogenous Multihoming

CCMP 21.2005 Barbara BUCHNER and Carlo CARRARO: Regional and Sub-Global Climate Blocs. A Game Theoretic Perspective on Bottom-up Climate Regimes

IEM 22.2005 Fausto CAVALLARO: An Integrated Multi-Criteria System to Assess Sustainable Energy Options: An Application of the Promethee Method

CTN 23.2005 Michael FINUS, Pierre v. MOUCHE and Bianca RUNDSHAGEN: Uniqueness of Coalitional Equilibria IEM 24.2005 Wietze LISE: Decomposition of CO2 Emissions over 1980–2003 in Turkey CTN 25.2005 Somdeb LAHIRI: The Core of Directed Network Problems with Quotas

SIEV 26.2005 Susanne MENZEL and Riccardo SCARPA: Protection Motivation Theory and Contingent Valuation: Perceived Realism, Threat and WTP Estimates for Biodiversity Protection

NRM 27.2005 Massimiliano MAZZANTI and Anna MONTINI: The Determinants of Residential Water Demand Empirical Evidence for a Panel of Italian Municipalities

CCMP 28.2005 Laurent GILOTTE and Michel de LARA: Precautionary Effect and Variations of the Value of Information NRM 29.2005 Paul SARFO-MENSAH: Exportation of Timber in Ghana: The Menace of Illegal Logging Operations

CCMP 30.2005 Andrea BIGANO, Alessandra GORIA, Jacqueline HAMILTON and Richard S.J. TOL: The Effect of Climate Change and Extreme Weather Events on Tourism

NRM 31.2005 Maria Angeles GARCIA-VALIÑAS: Decentralization and Environment: An Application to Water Policies

NRM 32.2005 Chiara D’ALPAOS, Cesare DOSI and Michele MORETTO: Concession Length and Investment Timing Flexibility

CCMP 33.2005 Joseph HUBER: Key Environmental Innovations

CTN 34.2005 Antoni CALVÓ-ARMENGOL and Rahmi İLKILIÇ (lxxii): Pairwise-Stability and Nash Equilibria in Network Formation

CTN 35.2005 Francesco FERI (lxxii): Network Formation with Endogenous Decay

CTN 36.2005 Frank H. PAGE, Jr. and Myrna H. WOODERS (lxxii): Strategic Basins of Attraction, the Farsighted Core, and Network Formation Games

CTN 37.2005 Alessandra CASELLA and Nobuyuki HANAKI (lxxii): Information Channels in Labor Markets. On the Resilience of Referral Hiring

CTN 38.2005 Matthew O. JACKSON and Alison WATTS (lxxii): Social Games: Matching and the Play of Finitely Repeated Games

CTN 39.2005 Anna BOGOMOLNAIA, Michel LE BRETON, Alexei SAVVATEEV and Shlomo WEBER (lxxii): The Egalitarian Sharing Rule in Provision of Public Projects

CTN 40.2005 Francesco FERI: Stochastic Stability in Network with Decay CTN 41.2005 Aart de ZEEUW (lxxii): Dynamic Effects on the Stability of International Environmental Agreements

NRM 42.2005 C. Martijn van der HEIDE, Jeroen C.J.M. van den BERGH, Ekko C. van IERLAND and Paulo A.L.D. NUNES: Measuring the Economic Value of Two Habitat Defragmentation Policy Scenarios for the Veluwe, The Netherlands

PRCG 43.2005 Carla VIEIRA and Ana Paula SERRA: Abnormal Returns in Privatization Public Offerings: The Case of Portuguese Firms

SIEV 44.2005 Anna ALBERINI, Valentina ZANATTA and Paolo ROSATO: Combining Actual and Contingent Behavior to Estimate the Value of Sports Fishing in the Lagoon of Venice

CTN 45.2005 Michael FINUS and Bianca RUNDSHAGEN: Participation in International Environmental Agreements: The Role of Timing and Regulation

CCMP 46.2005 Lorenzo PELLEGRINI and Reyer GERLAGH: Are EU Environmental Policies Too Demanding for New Members States?

IEM 47.2005 Matteo MANERA: Modeling Factor Demands with SEM and VAR: An Empirical Comparison

CTN 48.2005 Olivier TERCIEUX and Vincent VANNETELBOSCH (lxx): A Characterization of Stochastically Stable Networks

CTN 49.2005 Ana MAULEON, José SEMPERE-MONERRIS and Vincent J. VANNETELBOSCH (lxxii): R&D Networks Among Unionized Firms

CTN 50.2005 Carlo CARRARO, Johan EYCKMANS and Michael FINUS: Optimal Transfers and Participation Decisions in International Environmental Agreements

KTHC 51.2005 Valeria GATTAI: From the Theory of the Firm to FDI and Internalisation:A Survey

CCMP 52.2005 Alireza NAGHAVI: Multilateral Environmental Agreements and Trade Obligations: A Theoretical Analysis of the Doha Proposal

SIEV 53.2005 Margaretha BREIL, Gretel GAMBARELLI and Paulo A.L.D. NUNES: Economic Valuation of On Site Material Damages of High Water on Economic Activities based in the City of Venice: Results from a Dose-Response-Expert-Based Valuation Approach

ETA 54.2005 Alessandra del BOCA, Marzio GALEOTTI, Charles P. HIMMELBERG and Paola ROTA: Investment and Time to Plan: A Comparison of Structures vs. Equipment in a Panel of Italian Firms

CCMP 55.2005 Gernot KLEPPER and Sonja PETERSON: Emissions Trading, CDM, JI, and More – The Climate Strategy of the EU

ETA 56.2005 Maia DAVID and Bernard SINCLAIR-DESGAGNÉ: Environmental Regulation and the Eco-Industry

ETA 57.2005 Alain-Désiré NIMUBONA and Bernard SINCLAIR-DESGAGNÉ: The Pigouvian Tax Rule in the Presence of an Eco-Industry

NRM 58.2005 Helmut KARL, Antje MÖLLER, Ximena MATUS, Edgar GRANDE and Robert KAISER: Environmental Innovations: Institutional Impacts on Co-operations for Sustainable Development

SIEV 59.2005 Dimitra VOUVAKI and Anastasios XEPAPADEAS (lxxiii): Criteria for Assessing Sustainable Development: Theoretical Issues and Empirical Evidence for the Case of Greece

CCMP 60.2005 Andreas LÖSCHEL and Dirk T.G. RÜBBELKE: Impure Public Goods and Technological Interdependencies

PRCG 61.2005 Christoph A. SCHALTEGGER and Benno TORGLER: Trust and Fiscal Performance: A Panel Analysis with Swiss Data

ETA 62.2005 Irene VALSECCHI: A Role for Instructions

NRM 63.2005 Valentina BOSETTI and Gianni LOCATELLI: A Data Envelopment Analysis Approach to the Assessment of Natural Parks’ Economic Efficiency and Sustainability. The Case of Italian National Parks

SIEV 64.2005 Arianne T. de BLAEIJ, Paulo A.L.D. NUNES and Jeroen C.J.M. van den BERGH: Modeling ‘No-choice’ Responses in Attribute Based Valuation Surveys

CTN 65.2005 Carlo CARRARO, Carmen MARCHIORI and Alessandra SGOBBI: Applications of Negotiation Theory to Water Issues

CTN 66.2005 Carlo CARRARO, Carmen MARCHIORI and Alessandra SGOBBI: Advances in Negotiation Theory: Bargaining, Coalitions and Fairness

KTHC 67.2005 Sandra WALLMAN (lxxiv): Network Capital and Social Trust: Pre-Conditions for ‘Good’ Diversity?

KTHC 68.2005 Asimina CHRISTOFOROU (lxxiv): On the Determinants of Social Capital in Greece Compared to Countries of the European Union

KTHC 69.2005 Eric M. USLANER (lxxiv): Varieties of Trust KTHC 70.2005 Thomas P. LYON (lxxiv): Making Capitalism Work: Social Capital and Economic Growth in Italy, 1970-1995

KTHC 71.2005 Graziella BERTOCCHI and Chiara STROZZI (lxxv): Citizenship Laws and International Migration in Historical Perspective

KTHC 72.2005 Elsbeth van HYLCKAMA VLIEG (lxxv): Accommodating Differences KTHC 73.2005 Renato SANSA and Ercole SORI (lxxv): Governance of Diversity Between Social Dynamics and Conflicts in

Multicultural Cities. A Selected Survey on Historical Bibliography

IEM 74.2005 Alberto LONGO and Anil MARKANDYA: Identification of Options and Policy Instruments for the Internalisation of External Costs of Electricity Generation. Dissemination of External Costs of Electricity Supply Making Electricity External Costs Known to Policy-Makers MAXIMA

IEM 75.2005 Margherita GRASSO and Matteo MANERA: Asymmetric Error Correction Models for the Oil-Gasoline Price Relationship

ETA 76.2005 Umberto CHERUBINI and Matteo MANERA: Hunting the Living Dead A “Peso Problem” in Corporate Liabilities Data

CTN 77.2005 Hans-Peter WEIKARD: Cartel Stability under an Optimal Sharing Rule

ETA 78.2005 Joëlle NOAILLY, Jeroen C.J.M. van den BERGH and Cees A. WITHAGEN (lxxvi): Local and Global Interactions in an Evolutionary Resource Game

ETA 79.2005 Joëlle NOAILLY, Cees A. WITHAGEN and Jeroen C.J.M. van den BERGH (lxxvi): Spatial Evolution of Social Norms in a Common-Pool Resource Game

CCMP 80.2005 Massimiliano MAZZANTI and Roberto ZOBOLI: Economic Instruments and Induced Innovation: The Case of End-of-Life Vehicles European Policies

NRM 81.2005 Anna LASUT: Creative Thinking and Modelling for the Decision Support in Water Management

CCMP 82.2005 Valentina BOSETTI and Barbara BUCHNER: Using Data Envelopment Analysis to Assess the Relative Efficiency of Different Climate Policy Portfolios

ETA 83.2005 Ignazio MUSU: Intellectual Property Rights and Biotechnology: How to Improve the Present Patent System

KTHC 84.2005 Giulio CAINELLI, Susanna MANCINELLI and Massimiliano MAZZANTI: Social Capital, R&D and Industrial Districts

ETA 85.2005 Rosella LEVAGGI, Michele MORETTO and Vincenzo REBBA: Quality and Investment Decisions in Hospital Care when Physicians are Devoted Workers

(lxv) This paper was presented at the EuroConference on “Auctions and Market Design: Theory, Evidence and Applications” organised by Fondazione Eni Enrico Mattei and sponsored by the EU, Milan, September 25-27, 2003 (lxvi) This paper has been presented at the 4th BioEcon Workshop on “Economic Analysis of Policies for Biodiversity Conservation” organised on behalf of the BIOECON Network by Fondazione Eni Enrico Mattei, Venice International University (VIU) and University College London (UCL) , Venice, August 28-29, 2003 (lxvii) This paper has been presented at the international conference on “Tourism and Sustainable Economic Development – Macro and Micro Economic Issues” jointly organised by CRENoS (Università di Cagliari e Sassari, Italy) and Fondazione Eni Enrico Mattei, and supported by the World Bank, Sardinia, September 19-20, 2003 (lxviii) This paper was presented at the ENGIME Workshop on “Governance and Policies in Multicultural Cities”, Rome, June 5-6, 2003 (lxix) This paper was presented at the Fourth EEP Plenary Workshop and EEP Conference “The Future of Climate Policy”, Cagliari, Italy, 27-28 March 2003 (lxx) This paper was presented at the 9th Coalition Theory Workshop on "Collective Decisions and Institutional Design" organised by the Universitat Autònoma de Barcelona and held in Barcelona, Spain, January 30-31, 2004 (lxxi) This paper was presented at the EuroConference on “Auctions and Market Design: Theory, Evidence and Applications”, organised by Fondazione Eni Enrico Mattei and Consip and sponsored by the EU, Rome, September 23-25, 2004 (lxxii) This paper was presented at the 10th Coalition Theory Network Workshop held in Paris, France on 28-29 January 2005 and organised by EUREQua. (lxxiii) This paper was presented at the 2nd Workshop on "Inclusive Wealth and Accounting Prices" held in Trieste, Italy on 13-15 April 2005 and organised by the Ecological and Environmental Economics - EEE Programme, a joint three-year programme of ICTP - The Abdus Salam International Centre for Theoretical Physics, FEEM - Fondazione Eni Enrico Mattei, and The Beijer International Institute of Ecological Economics (lxxiv) This paper was presented at the ENGIME Workshop on “Trust and social capital in multicultural cities” Athens, January 19-20, 2004 (lxxv) This paper was presented at the ENGIME Workshop on “Diversity as a source of growth” RomeNovember 18-19, 2004 (lxxvi) This paper was presented at the 3rd Workshop on Spatial-Dynamic Models of Economics and Ecosystems held in Trieste on 11-13 April 2005 and organised by the Ecological and Environmental Economics - EEE Programme, a joint three-year programme of ICTP - The Abdus Salam International Centre for Theoretical Physics, FEEM - Fondazione Eni Enrico Mattei, and The Beijer International Institute of Ecological Economics

2004 SERIES

CCMP Climate Change Modelling and Policy (Editor: Marzio Galeotti )

GG Global Governance (Editor: Carlo Carraro)

SIEV Sustainability Indicators and Environmental Valuation (Editor: Anna Alberini)

NRM Natural Resources Management (Editor: Carlo Giupponi)

KTHC Knowledge, Technology, Human Capital (Editor: Gianmarco Ottaviano)

IEM International Energy Markets (Editor: Anil Markandya)

CSRM Corporate Social Responsibility and Sustainable Management (Editor: Sabina Ratti)

PRA Privatisation, Regulation, Antitrust (Editor: Bernardo Bortolotti)

ETA Economic Theory and Applications (Editor: Carlo Carraro)

CTN Coalition Theory Network

2005 SERIES

CCMP Climate Change Modelling and Policy (Editor: Marzio Galeotti )

SIEV Sustainability Indicators and Environmental Valuation (Editor: Anna Alberini)

NRM Natural Resources Management (Editor: Carlo Giupponi)

KTHC Knowledge, Technology, Human Capital (Editor: Gianmarco Ottaviano)

IEM International Energy Markets (Editor: Anil Markandya)

CSRM Corporate Social Responsibility and Sustainable Management (Editor: Sabina Ratti)

PRCG Privatisation Regulation Corporate Governance (Editor: Bernardo Bortolotti)

ETA Economic Theory and Applications (Editor: Carlo Carraro)

CTN Coalition Theory Network