Committee for Proprietary Medicinal Products (CPMP)
A number of recent applications have led to CPMP discussions concerning the interpretation of superiority, noninferiority and equivalence trials. These issues are covered in ICH E9 (Statistical Principles for Clinical Trials). There is further relevant material in the Step 2 draft of ICH E10 (Choice of Control Group) and in the CPMP Note for Guidance on the Investigation of Bioavailability and Bioequivalence. However, the guidelines do not address some specific difficulties that have arisen in practice. In broad terms, these difficulties relate to switching from one design objective to another at the time of analysis. The types of trials in question are those designed to compare a new product with an active comparator. The objective may be to demonstrate: the superiority of the new product the noninferiority of the new product or the equivalence of the two products. When the results of the trial become available, they may suggest an alternative interpretation. Thus the results of a superiority trial may only appear to be sufficient to support noninferiority, while the results of a noninferiority trial may appear to support superiority. Alternatively, the results of an equivalence trial may appear to support a tighter range of equivalence. A satisfactory approach to this subject requires an understanding of confidence intervals and the manner in which they capture the results of the trial and indicate the conclusions that can be drawn from them. Such an understanding also leads to an appreciation of why power calculations are of relatively little interest when a trial is complete. For simplicity, this paper addresses the issues of superiority, noninferiority and equivalence from the perspective of an efficacy trial with a single primary variable. Some comments on other situations are made in Section VI. It is assumed throughout this document that switching the objective of a trial does not lead to any change in the selection or definition of the primary variable. A superiority trial is designed to detect a difference between treatments. The first step of the analysis is usually a test of statistical significance to evaluate whether the results of the trial are consistent with the assumption of there being no difference in the clinical effect of the two treatments. In a trial of good quality, the degree of statistical significance (P value) indicates the probability that the observed difference, or a larger one, could have arisen by chance assuming that no difference really existed. The smaller this probability is, the more implausible is the assumption that there really is no difference between the treatments. Once it is accepted that the assumption of âno differenceâ is untenable, it then becomes important to estimate the size of the difference in order to assess whether the effect is clinically relevant. This has two aspects. First there is the best estimate of the size of the difference between treatments (point estimate). For normally distributed data this is usually taken as the observed difference between the mean values on each. Next, there is the range of values of the true difference that are plausible in the light of the results of the trial (confidence interval). It is clear that this range should not include zero since the possibility of a zero difference has already been rejected as unreasonable. The method of constructing confidence intervals generally ensures that this is so, provided it corresponds to the choice of significance test. Thus the following two statements are usually equivalent: The two-sided 95% confidence interval for the difference between the means excludes zero. The two means are statistically significantly different at the 5% level (P < 0.05) two-sided. The above text addresses the situation where the difference between two mean values is the statistic of interest and a zero difference represents no effect. In practice a number of other summary statistics are used for the evaluation of differences between treatments, for example the odds ratio for proportions or the ratio of geometric means in bio-equivalence studies. (The latter arises from the logarithmic transformation used for bioavailability data.) In such cases the same principles apply but âno differenceâ may be represented by a value other than zero â a value of 1 in both the examples quoted here. In these cases it is the position of the confidence interval for the test statistic relative to this âno differenceâ value that is of interest. When significance tests are carried out in practice, precise numerical values of probabilities are usually quoted, for example P = 0.032, because this is more informative than P < 0.05. This allows judgement to be based more precisely on the extent of the disagreement between the null hypothesis and the observed data rather than on the approximations implied by using cut-off points of 0.05, 0.01 and 0.001. However, confidence intervals have to be associated with a specific probability value (coverage probability) and this is nearly always taken as 95% (0.95). When a difference is statistically significant at a more extreme level, e.g. P = 0.002, the two-sided 95% confidence interval will exclude zero by a wider margin. Figure 1 illustrates these points. Relationship between significance tests and confidence intervals. Whether the observed difference is indeed clinically relevant is a matter of judgement. In contrast to an equivalence or noninferiority trial where clinical relevance is addressed through the prestudy choice of Î (see II.2 and II.3), in a superiority trial clinical relevance requires separate consideration: a statistically significant difference may not be clinically relevant. The difference taken as the basis of the power calculation in a superiority trial cannot be assumed to provide a suitable value. Note that in Figure 1, and throughout the rest of the document, it is assumed that values to the right of zero correspond to a better response on the new treatment so that values to the left are worse, i.e. better on the control treatment. An equivalence trial is designed to confirm the absence of a meaningful difference between treatments. In this case it is more informative to conduct the analysis by means of the calculation and examination of the confidence interval although there are closely related methods using significance test procedures. (See also II.3.) A margin of clinical equivalence (Î) is chosen by defining the largest difference that is clinically acceptable, so that a difference bigger than this would matter in practice. There are well-recognized difficulties associated with this task which will not be discussed in any detail here. If the two treatments are to be declared equivalent, then the two-sided 95% confidence interval â which defines the range of plausible differences between the two treatments â should lie entirely within the interval âÎ to + Î, see Figure 2. There are situations in which the equivalence margins may be chosen asymmetrically with respect to zero. Confidence interval approach to analysis of equivalence trial. In the case of bioequivalence studies a coverage probability of 90% for the confidence interval has become the accepted standard when evaluating whether the average values of the pharmacokinetic parameters of two formulations are sufficiently close. Clinical equivalence trials, with two-sided 95% confidence intervals, may be carried out when conventional bio-equivalence trials are impossible, for example in the case of a generic inhaled or topically applied product. In Phase III drug development, noninferiority trials are more common than equivalence trials. In these we wish to show that a new treatment is no less effective than an existing treatment â it may be more effective or it may have a similar effect. Again a confidence interval approach is the most straightforward way of performing the analysis but now we are only interested in a possible difference in one direction. Hence the two-sided 95% confidence interval should lie entirely to the right of the value âÎ, see Figure 3. Non-inferiority trials are sometimes mistakenly referred to, and designed as, equivalence trials. This distinction is important and can be a source of confusion. Confidence interval approach to analysis of non-inferiority trial. Note also that by using the closely related significance testing procedures referred to in II.2, it is possible to calculate a P value associated with the null hypothesis of inferiority. This is a valuable further aid to assessing the strength of the evidence in favour of noninferiority. It will be assumed throughout this document that two-sided 95% confidence intervals are to be used for all clinical trials whatever their objective. Among other benefits, this preserves consistency between significance testing and subsequent estimation. It is also consistent with the guidance provided in the ICH E9 Note for Guidance. If one-sided intervals are used, then they should be used with a coverage probability of 97.5%. In the special case of bioequivalence studies, two-sided 90% confidence intervals have been established as the norm as recommended, for example, in the CPMP Note for Guidance on the Investigation of Bioavailability and Bioequivalence. A conclusion of equivalence or noninferiority clearly depends upon the value of Î chosen as the maximum acceptable difference. It is always possible to choose a value of Î which leads to a conclusion of equivalence or noninferiority if it is chosen after the data have been inspected. Since the choice of Î is generally a difficult one, there is ample room for bias here, however, well intentioned the researcher may be. Plausible arguments may often be advanced for a retrospective choice. In the design of equivalence and noninferiority trials, this reason (amongst others) makes it necessary for the choice of Î, and the reasoning behind the choice, to be set down in advance by the researcher in the study protocol. The corresponding coverage probability for the confidence interval (usually 95%) should also be chosen at this time. (See Section IV.2 for how these requirements apply when objectives are changed.) The question of how to choose an appropriate Î will be addressed in a subsequent CPMP Points to Consider. Pre-definition of a trial as a superiority trial, an equivalence trial or a noninferiority trial is necessary for numerous reasons including the following: to ensure that comparator treatments, doses, patient populations and endpoints are appropriate (see ICH E10) to allow sample size estimates to be based on the correct power calculations to ensure that equivalence and noninferiority criteria are predefined to permit appropriate analysis plans to be described in the protocol to ensure that the trial has sufficient sensitivity to achieve its objectives (see ICH E10) If the objective of a trial is switched from superiority to noninferiority, or vice versa, these aspects may lead to greater difficulty than the interpretation of significance tests and confidence intervals. The only switching which is likely to have any practical relevance is switching between superiority and noninferiority. The place of equivalence trials is so specific that they stand alone. If the 95% confidence interval for the treatment effect not only lies entirely above âÎ but also above zero then there is evidence of superiority in terms of statistical significance at the 5% level (P < 0.05). See Figure 4. In this case it is acceptable to calculate the P value associated with a test of superiority and to evaluate whether this is sufficiently small to reject convincingly the hypothesis of no difference. There is no multiplicity argument that affects this interpretation because, in statistical terms, it corresponds to a simple closed test procedure. Usually this demonstration of a benefit is sufficient on its own, provided the safety profiles of the new agent and the comparator are similar. When there is an increase in adverse events, however, it is important to estimate the size of the effect to evaluate whether it is sufficient in clinical terms to outweigh the adverse effects. Non-inferiority to superiority. There are a number of other factors that might be affected by this changed objective. If the comparator was suitable for a demonstration of noninferiority, then there should be well-controlled data to show that it is an effective treatment. Hence, for proof of efficacy, a clear demonstration of superiority to the comparator in terms of statistical significance should be acceptable. Non-inferiority trials are generally large because of their need to exclude the possibility of a small degree of inferiority of a new agent relative to an active control. However if the new agent is actually superior to control by a small amount, then the power to show its noninferiority is increased. Demonstrating the small amount of superiority to control might in principle require the planning of an even larger trial. When the trial is completed, however, the results provided by the confidence interval supply a concrete assessment of the precision actually achieved, superseding any calculations of power carried out before the trial was undertaken. Since the comparator in a noninferiority trial must be an effective agent, any superiority to that agent should carry the implication of acceptable superiority to no treatment (placebo). For this reason the size of the additional clinical benefit demonstrated is not likely to be relevant to a claim of efficacy except in relation to any increase in adverse effects and hence relative risk/benefit. However, when the proposed licence includes a claim of superiority to the comparator, the size of the additional benefit should be discussed in clinical terms. In a superiority trial the full analysis set, based on the ITT (intention-to-treat) principle, is the analysis set of choice, with appropriate support provided by the PP (per protocol) analysis set. In a noninferiority trial, the full analysis set and the PP analysis set have equal importance and their use should lead to similar conclusions for a robust interpretation. A switch of objective would require this difference of emphasis to be recognized. More details of the relative importance of these two analysis sets in superiority and noninferiority trials can be found in the ICH E9 Note for guidance. A trial to show equivalence or noninferiority must show a high degree of consistency with protocolled plans if it is to be reliable. Deviations from the inclusion criteria, from the intended treatment regimen, from the schedule, manner and precision of taking measurements, and so on, all tend to reduce the sensitivity of a trial and to make a conclusion of âno differenceâ more likely, even when the deviations are of an unsystematic or random nature. The size of the bias associated with these and other departures from the protocol is generally unknown and may render such a trial uninterpretable. Failure to show a difference between two treatments can also arise when both treatments are inefficacious, perhaps as a result of being inappropriately administered. This problem does not affect superiority trials to the same extent because the demonstration of a difference is itself validation of the sensitivity of the trial. The estimate of the size of the effect may however, be similarly affected. For these reasons, switching from noninferiority to superiority is likely to carry with it a greater degree of confidence in the conclusion. Switching the objective of a trial from noninferiority to superiority is feasible provided: The trial has been properly designed and carried out in accordance with the strict requirements of a noninferiority trial. Actual P values for superiority are presented to allow independent assessment of the strength of the evidence. Analysis according to the intention-to-treat principle is given greatest emphasis. If a superiority trial fails to detect a significant difference between treatments, there may be interest in the lesser objective of establishing noninferiority. If the results of the superiority trial are summarized by means of a 95% confidence interval for the treatment difference, the lower end of that confidence interval provides a quantitative estimate of the minimum estimated effect of the new treatment relative to the comparator. When the study protocol an acceptable, margin âÎ for noninferiority, the objective less a noninferiority margin would appear only to make in trials with noninferiority as an However, in any superiority trial where noninferiority may be an acceptable for it is to a noninferiority margin in the protocol in order to the difficulties that can arise from such it is also to design to the possible need to that the study sufficient sensitivity to detect the drug effects of interest (see It is important to that there are of where noninferiority to an active control is to be acceptable as the or evidence of efficacy, and trials are to In trials where there is no noninferiority such a has to be after the and in situations this will not be It is likely that the will have to be after the results have been and there may be little basis for an objective choice of margin. there does not appear to be a statistical multiplicity related to this switch of that does not the difficulties associated with the definition of A number of other issues require A comparator chosen for a demonstration of superiority may not be acceptable for a conclusion of noninferiority. In order for it to be acceptable, it will be necessary to that there are data from good superiority trials consistent evidence that the comparator is an effective treatment with and establishing the size of its effect relative to no treatment. There should also be a basis for that the same degree of efficacy would be in the trial. For example, the patient and the endpoints should be similar. These issues are covered in ICH in the results provided by the confidence interval supply a concrete assessment of the precision actually by a clinical trial, superseding any calculations of power carried out before the trial was undertaken. The position of the lower end of the confidence interval relative to the of noninferiority provides the for noninferiority. In a superiority trial the full analysis set, based on the ITT (intention-to-treat) principle, is the analysis set of choice, with appropriate support provided by the PP (per protocol) analysis set. In a noninferiority trial the full analysis set and the PP analysis set have equal importance and their use should lead to similar conclusions for a robust interpretation. A switch of objective would require this difference of emphasis to be recognized. More details of the relative importance of these two analysis sets in superiority and noninferiority trials can be found in the ICH E9 Note for Guidance. A trial to show equivalence or noninferiority must show a high degree of consistency with protocolled plans if it is to be reliable. Deviations from the inclusion criteria, from the intended treatment regimen, from the schedule, manner and precision of taking measurements, and so on, all tend to reduce the sensitivity of a trial and to make a conclusion of âno differenceâ more likely, even when the deviations are of an unsystematic or random nature. The size of the bias associated with these and other departures from the protocol is generally unknown and may render such a trial uninterpretable. Failure to show a difference between two treatments can also arise when both treatments are inefficacious, perhaps as a result of being inappropriately administered. This problem does not affect superiority trials to the same extent because the demonstration of a difference is itself validation of the sensitivity of the trial. For these reasons, switching from superiority to noninferiority is likely to carry with it a lesser degree of confidence in the It will be necessary to to the sensitivity of the trial by or that the control treatment is its efficacy the trial with trials which demonstrated the efficacy of the control agent in of and of of and data that are at to those in the trials similar results from the full analysis set and PP analysis set. Switching the objective of a trial from superiority to noninferiority may be feasible provided: The noninferiority margin with respect to the control treatment was predefined or can be (The latter is likely to difficult and to be to cases where there is a accepted value for Analysis according to the intention-to-treat principle and PP confidence intervals and P values for the null hypothesis of similar The trial was properly designed and carried out in accordance with the strict requirements of a noninferiority trial (see ICH E9 and The sensitivity of the trial is high to ensure that it is of relevant differences if they There is or evidence that the control treatment is its level of A further related that has arisen in with equivalence and noninferiority trials to the equivalence margins when the trial is complete. that a bioequivalence trial a 90% confidence interval for the relative bioavailability of a new that from to we only that the relative bioavailability lies between the conventional of and because these the predefined equivalence can we that it lies between and The interval based on the data is the appropriate one to Hence, if the changed to this study would have satisfactory There is no question of a selection However, if the trial in a confidence interval from to then a change of equivalence margins to would not be acceptable because of the conclusion that the equivalence margin was chosen to the These apply to the 95% confidence intervals used for clinical equivalence and for noninferiority. The confidence interval based on the results of the trial is always the best summary of the It is the choice of equivalence margin that is subject to This should be chosen on the basis of and not chosen to the This Points to has been from the perspective of an efficacy trial active with a single primary variable. In practice some studies have more than one primary and most studies have respect to switching of these requires separate in the of the specific drug development, separate conclusions superiority or noninferiority for in judgement whether the trial as a has established the superiority or noninferiority of the new treatment will upon the requirements for that clinical and the of results all relevant The covered in these Points to can also be applied to specific safety when these have been as endpoints of a trial to compare active In practice the of switching objectives is not relevant to trials, even where noninferiority to is a valuable i.e. for safety The problem of switching objectives can be by a trial in the that both noninferiority and superiority are of value. In this case all the issues in this document should be addressed In the statistical analysis should be using an appropriate from noninferiority to superiority. The interpretation of superiority trials as noninferiority trials and vice is best by the results as a confidence interval for the difference between the test treatment and control. There is no problem associated with the use of this confidence interval as a basis for of interpretation. For a and trial, there are difficulties with the change from noninferiority to superiority that cannot be addressed by appropriate analysis. However, there are more difficulties associated with the switch from superiority to noninferiority because of the possible need to a basis and on, a margin of equivalence after the and because of the difficulties of noninferiority trials. There are for the design of a superiority trial in which noninferiority might be an acceptable When the results with respect to alternative of the equivalence margins the problem from to switch to wider acceptable that equivalence margins may be in this
Open access
Statistical Methods in Clinical Trials
Health Systems, Economic Evaluations, Quality of Life
The Act No. 221999 on regional government and No. 251999 on the balance of finance between central government and regional government, have vast impact on all aspects of the nation life. The impacts are not only on politic and economic aspects, but they also have logic consequence on the changes of Indonesian education form and system. Based on the rules above, the education process in schools should be independent gradually and will not depend on central government moreover on regional government especially in finance. Consequenly, the quality of school must be improved either in planning or process or outcome aspect. To reach the aimed quality of the schools need a management system that can improve the quality of schools. In this frame, this writing offers the total quality management system as a medium to autonomous education having a certain quality in decentralization era.
In this chapter we discuss pseudorandom generators. Loosely speaking, these are efficient deterministic programs that expand short, randomly selected seeds into much longer âpseudorandomâ bit sequences (see illustration in Figure 3.1). Pseudorandom sequences are defined as computationally indistinguishable from truly random sequences by efficient algorithms. Hence the notion of computational indistinguishability (i.e., indistinguishability by efficient procedures) plays a pivotal role in our discussion. Furthermore, the notion of computational indistinguishability plays a key role also in subsequent chapters, in particular in the discussions of secure encryption, zero-knowledge proofs, and cryptographic protocols. The theory of pseudorandomness is also applied to functions, resulting in the notion of pseudorandom functions, which is a useful tool for many cryptographic applications. In addition to definitions of pseudorandom distributions, pseudorandom generators, and pseudorandom functions, this chapter contains constructions of pseudorandom generators (and pseudorandom functions) based on various types of one-way functions. In particular, very simple and efficient pseudorandom generators are constructed based on the existence of one-way permutations. We highlight the hybrid technique , which plays a central role in many of the proofs. (For the first use and further discussion of this technique, see Section 3.2.3.) Organization . Basic discussions, definitions, and constructions of pseudorandom generators appear in Sections 3.1â3.4: We start with a motivating discussion (Section 3.1), proceed with a general definition of computational indistinguishability (Section 3.2) next present and discuss definitions of pseudorandom generators (Section 3.3), and finally present some simple constructions (Section 3.4). More general constructions are discussed in Section 3.5.
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This Selected Issues paper presents the current status of fiscal decentralization in Nigeria; discusses issues in reference to revenue assignment, distribution rules, and expenditure devolution; and analyzes the key challenges posed by the Nigerian model of fiscal decentralization. The paper also provides a statistical report for Nigeria on gross domestic product by sector of origin at current prices, constant 1990 prices, expenditure category at current prices, and constant 1990 prices; consolidated government revenue, finance, and expenditure; federal accounts operations; monetary survey during 1995â2000; summary of the tax system as of March 2001, and so on.
Olivier Baudron, Pierre-Alain Fouque, David Pointcheval, Jacques Stern · 5 authors
The aim of electronic voting schemes is to provide a set of protocols that allow voters to cast ballots while a group of authorities collect the votes and output the final tally. In this paper we describe a practical multi-candidate election scheme that guarantees privacy of voters, public verifiability, and robustness against a coalition of malicious authorities. Furthermore, we address the problem of receipt-freeness and incoercibility of voters. Our new scheme is based on the Paillier cryptosystem and on some related zero-knowledge proof techniques. The voting schemes are very practical and can be efficiently implemented in a real system.
Financial services industries have been an important source of central-city employment, including new jobs. Although decentralization occurred in the 1970s and 1980s, widespread national growth in the sector generally resulted in central-city employment gains. In the 1990s, despite continuing national growth in the sector overall, financial services became a key source of job losses in many cities. From 1991 to 1996, financial services employment declined by 5% in a sample of 40 large cities but increased by 9% in corresponding suburbs. Twenty-five of these cities lost finance jobs, with losses exceeding 10% in 11 cities. Moreover, financial services were often a disproportionate contributor to total employment losses. This article describes these trends and explores the relationship between industrial structure, city size, and region on the suburbanization of financial services employment.
A proof is concurrent zero-knowledge if it remains zero-knowledge when many copies of the proof are run in an asynchronous environment, such as the Internet. Richardson and Kilian have shown that there exists a concurrent zero-knowledge proof for any language in NP, but with round complexity polynomial in the maximum number of concurrent proofs. In this paper, we present a concurrent zero-knowledge proof for all languages in NP with a poly-logarithmic round complexity: specifically, Ï(log^2 k) rounds given at most k concurrent proofs. Finally, we show that a simple modification of our proof is a resettable zero-knowledge proof for NP, with Ï(log^2 k) rounds; previously known protocols required a polynomial number of rounds.
We consider zero knowledge interactive proofs in a richer, more realistic communication environment. In this setting, one may simultaneously engage in many interactive proofs, and these proofs may take place in an asynchronous fashion. It is known that zero-knowledge is not necessarily preserved in such an environment; we show that for a large class of protocols, it cannot be preserved. Any 4 round (computational) zero-knowledge interactive proof (or argument) for a non-trivial language L is not black-box simulatable in the asynchronous setting.
This paper studies the issue of designing an optimal organizational form: design for sub-units' task allocation, decision-making structure, and incentive schemes for organizational members. Depending on the way tasks are allocated between the sub-units, and whether decision-making is centralized or not, organizations face a trade-off between coordination and information. Task allocation by production processes calls for coordination more strongly than the allocation by final products. Centralized decision-making serves for better coordination, whereas decentralization serves for better information. The coordinational benefit under centralization gets bigger as the organization's common uncertainty increases, and this benefit is magnified when the sub-units are functionally divided by production processes. The informational benefit under decentralization gets bigger as the organization's local uncertainty increases, and this benefit is magnified when the sub-units are designed autonomous. Thus, complementarily designed organizations tend to have centralized decision-making structures and fixed salary scheme, whereas less complementarily designed organizations tend to have decentralized decision-making and 'pay for performance' incentive contract.
Teresa GarcĂa-MilĂĄ, Timothy J. Goodspeed, Therese J. McGuire
As part of a process of democratization, many countries spanning Europe, Latin Amertica, Africa, and Asia are reorganizing their governments bydevolving fiscal responsibility and authority to newly empowered regionaland local governments. Although decentralization in each country proceedsdifferently, a common element tends to be an initially heavy relianceon central government grants to fund regional spending. We develop atheoretical model of regional borrowing decisions in which the incentivesfor regional borrowing depend crucially on how the regions expect thefederal system of finance to evolve. We examine the implications of themodel using data on Spanish regions for the period 1984-1995 and findevidence that regions may be borrowing inefficiently in response toincentives imbedded in the Spanish system of fiscal decentralization.
This article presents the results from an evaluative longitudinal study with before-after design. The main objective was to determine the effects of health care decentralization on changes in health financing. Taking into account feasibility, political and technical criteria, three Latin American countries were selected as study populations: Mexico, Nicaragua and Peru. The methodology had two main phases. In the first phase, the study referred to secondary sources of data and documents to obtain information about the following variables: type of decentralization implemented, source of finance, funds of financing, providers, final use of resources and mechanisms for resource allocation. In the second phase, the study referred to primary data collected in a survey of key personnel from the health sectors of each country. Taking into account the changes implemented in the three countries, as well as the strengths and weaknesses of each country in financing and decentralization, a rule for decision-making is proposed that attempts to identify the main financial changes implemented in each country and the basic indicators that can be used in future years to direct the planning, assessment, adjustment and correction of health financing and decentralization.
THE SURFACE TRANSPORTAtion Board (STB) issued its long-awaited rules for railroad mergers and received negative reactions from all sides. The rules were prepared during a 15-month moratorium on rail mergers imposed because earlier mergers had caused severe service disruptions and substantially increased shippers' costs. The STB rules affect mergers and consolidations of class 1 railroadsâthose with annual revenues over $250 millionâand are supposed to require more proof from railroads that a merger will be in the public's best interest. STB seeks more emphasis on enhancing competition while ensuring stable, reliable service for all involved. The railroads think the rules are too tough. The Association of American Railroads, the umbrella trade organization, says the new rules make railroads subject to stricter rules for competition than other industries. Major rail carrier CSX Corp. says in a statement that STB "has raised the bar for rail consolidation," making future transactions, "all the more difficult to achieve." As a major user of railroads, the chemical industry has a big stake in the rules. And it is not pleased. "The STB decision definitely misses the mark," says Frederick L. Webber, president and ...
Over the last decade, many unions affiliated to the Federation des travailleurs du papier et de la foret (FTPF-CSN), which represents about 25% of unionized workers in this industry in Quebec, have become involved in the management of work organization and the modernization of their plants. In 1993, the FTPF put forward an action program that encouraged active union and worker participation in work reorganization so long as the autonomy of union action was guaranteed through the use of formal agreements establishing joint committees to implement organizational change. Work reorganization leads unions to focus their activity on the workplace level, which in turn modifies the relationship between local unions and the federation. This shift in the strategic level of union activity alters the traditional sources of union power by reducing the ability of unions to neutralize wage competition between establishments within the same industrial sector. Several researchers (Betcherman 1991; Heckscher 1988; Katz 1993; Lapointe and Belanger 1996) argue that new forms of work organization that rely on the active involvement of workers in the management of their work, on improved technical skills, and on team work, represent a new source of power for unions, allowing them to participate in the implementation of organizational change in the interests of their members. Lapointe and Belanger (1996) identify two factors that can help strengthen union power through participation in the management of work organization: the democratic character of the union; and the union's ability to define and defend an autonomous and independent point of view.The involvement of local unions in the management of work leads to a demand for new services and a redefinition of the responsibilities of appointed union representatives from the industry federation and of elected local union officers. For the FTPF, the coordination of local collective bargaining is a strategically important activity in terms of setting the overall bargaining objectives and priorities for all of the unions in the paper industry. This coordination also makes it possible to reconcile local demands with common priorities, thereby providing a framework for local negotiations. However, over the last decade, the FTPF's ability to coordinate local negotiations has declined as a result of increasingly decentralized bargaining in response to union participation in work reorganization and job insecurity in a number of establishments.The involvement of local unions in work reorganization has had a significant impact on the nature of the tasks and responsibilities assumed by the FTPF's union representatives, for this involvement has often gone hand in hand with new negotiating practices at the local level, practices that combine integrative and continuous bargaining (Deschenes et al. 1998). Under these new negotiating approaches, elected representatives from the local union play a larger role and federation representatives need to have a wider array of technical skills than in the past. In many ways, the work of a union representative now more closely resembles that of an organizational consultant providing advice to local unions. Local union officials seek the advice of the representative on a range of questions related to the organization of work and the management of the firm.The increased involvement of the FTPF's affiliates in work organization and plant modernization over the last decade has sparked a renewal of union action at the local level. Officials and stewards have had to get involved in new areas linked to the management of organizational change, like process reengineering, the organization of production, quality assurance, and problem-solving techniques. In many of the paper mills organized by the FTPF, bargaining over work reorganization has given birth to partnerships that have substantially changed the approach to negotiating and the conduct of union-management relations. Collective bargaining has become more integrative and continuous so as to allow the gradual implementation of organizational changes. Local unions' internal structures and activities, as well as the role and responsibilities of their leaders, stewards and members have been redefined in order to support union and worker involvement in the organization of work.An analysis of the experience with work reorganization and technological modernization involving two local unions affiliated to the FTPF - in the Clermont and Donnacona mills - highlights the interaction between the economic context and union action. First, it should be emphasized that the two unions involved successfully fought, each in its own way, to have their mill modernized. To support their actions, they turned to the CSN's Research Department for studies of technological and organizational change, and, with the support of the FTPF, they led campaigns to raise public awareness of the need to secure investments in their mills. Each of the two unions has a core of active stewards who meet regularly to discuss problems and decide what action to take. Since 1995, they have held regular discussion meetings with union stewards and other union members with the purpose of assessing the role of the union in the mill and the members' perceptions of local union activities. However, the two unions have adopted different approaches to the issue of the modernization of their mills. Since the early 1980s, the Clermont union has adopted a proactive approach, whereas the involvement of the Donnacona local in the management of the mill is the result of a management plan to reduce production costs, which led to a union-management partnership agreement in 1991 aimed at reviving the mill.A number of scholars (Katz 1993; Voos 1994; Walton, Cutcher-Gershenfeld, McKersie 1994) link the decentralization of bargaining to a decline in union power. Fiorito, Gramm and Hendricks (1991) argue that it can also reflect a union preference for greater internal democracy, or for an âefficiency strategyâ based upon the union's contribution to the improvement of organizational performance. The FTPF's experience corroborates these ideas in many respects because, parallel to the decline in the federation's influence over industry-wide coordination of local bargaining, it is possible to observe an intensification of its efforts to help local unions improve the organizational efficiency and competitiveness of their mills. As a result of these efforts, the officials and members of the local unions get more involved in the management of the firm, as demonstrated by the two case studies.The changing relationship between the FTPF and its affiliated unions reflects a shift in power towards the local level rather than an overall weakening of bargaining power of the FTPF. As Fiorito, Gramm and Hendricks (1991) stress, union structures and strategies are dependent on the objectives that unions seek to attain. In this respect, they distinguish between two fundamental objectives. In the workplace, unions have to work to improve working conditions and job security, whereas at the societal level union action focuses on the quality of life of all workers. In periods of economic insecurity and industrial restructuring, these two objectives are difficult to achieve, and it is often through the search for practical solutions to them that other aspects of union action surface, like the democratization of the workplace. For local unions, bolstering the competitiveness of their plant can therefore be seen as a necessary condition to protecting working conditions and jobs, as the two case studies clearly show.
This article studies the effects of political institutions on inflation. In our view, hyperinflation is the manifestation of a tragedy of commons in a divided society with a weak central monetary authority. Economies with fiat money are inherently inflation-prone: the collection of seigniorage through the inflation tax is less conspicuous than other taxes, and the printing of money is essentially costless. In many countries, the control of the money supply is de facto or de jure decentralized. Sets of agents (in various regions or interest groups) can effectively pressure the central government to finance their expenditures. As these interest groups pursue their self-interest, they neglect the welfare effects of the inflation tax on individuals in other groups. These elements combine to imply that countries which rely on the inflation tax to meet the resource demands of competing interest groups will typically experience inefficiently (due to negative spillovers) high inflation.
South Africa is at a crossroads in its decentralization policy. On the one hand, it has declared its intention to strengthen the fiscal powers of local governments. On the other hand, the institutional arrangement necessary to guarantee fiscal decentralization, the power to raise local revenues, has not yet been fully defined. Nor has a target been set for the vertical division of resources between the central and lower levels of government. The revenue dimension of fiscal decentralization in South Africa is the subject of this paper. In this paper, we describe the system of local government and local government finance in South Africa. We turn then to a discussion of the normative criteria for proper revenue assignment in an intergovernmental system, and to an evaluation of each of the major revenue sources. In that context, we consider the potential role of the property tax as a source of financing local government in South Africa.
We model the links between skills and changes in work organization. As the proportion of skilled workers increases, the economy travels through a sequence of organizational equilibria. We show that as the relative supply of skills increases the organization of work becomes more decentralized. Both skilled and unskilled workers become more autonomous and perform a wider range of tasks: decentralization spreads across firms at the expense of the old centralized organization based on a strict division of labor. Moreover, as firms switch to decentralization, their employment structure becomes more homogeneous and wage inequality stops decreasing. These predictions are compared with empirical evidence based on French establishmentâlevel data and we find support for both of them. This suggests that the longâterm increase in the skill level of the workforce may have been one important factor driving the recent introduction of new work practices by a large number of firms.
The so-called charitable choice policy of the Clinton and Bush administrations is another milestone in the transformation of a social services sector that was once decentralized, independent, often informal, and voluntary into a deliberate instrument of public policy. Issues associated with government purchase of care from private, voluntary agencies date back at least a century, although there were wide variations in such practices among states and localities. It was during the Kennedy and Johnson presidencies that intentional federal appropriation of private social service capacity and skill began in earnest. The result is that private social services are now predominantly financed by government and by fees and charges, and contracts with large, for-profit firms are growing in importance. These developments have had important benefits. Public policy is more likely than private charity to address wealth-based inequities in service provision and to ensure better financed, more efficiently administered, and more uniformly available social services to a wide spectrum of beneficiaries. But there is a cost, too, in terms of diminished social capital represented by spontaneous private response to need. Voluntary social service agencies may find that sustaining the distinctive normative climates that ensure their uniqueness and selectivity is increasingly difficult as their involvement with government and with commercialized environments continues to increase.
Bill Hamilton was always at his best in small groups, and I would like to open and close my reflections with some thoughts generated by two small scientific meetings that Bill Hamilton attended. I was not present at the first meeting, in Tvarminne, Finland, but a photograph from the meeting made an impression on me. In the foreground stood Pekka Pamilo, the organizer of the meeting, with a rather worried expression on his face. In the background was Bill Hamilton, skating across the ice. Bill had brought his ice skates, intent on taking every advantage of this visit to the north. It turned out, however, that the ice was quite thin, so the organizers attempted to dissuade Bill. They made a general request that speakers at the meeting should please not attempt any ice skating, at least until after they had delivered their talks. Bill followed the letter of this request, but did not follow its spirit. After giving his talk, he donned his skates and set off. This picture brought to mind all sorts of associations. How can one not remember J. B. S. Haldane's musings about being willing to rescue two drowning brothers, or eight cousins. I hope Pekka will forgive me if I try to imagine his thoughts about the possibility of Bill falling though the ice. â Well, I do not think I am related to him... On the other hand, everyone in Finland is more or less related! But then, he is not from Finland, is he? Still, we may not share many genes, but we do share a great many memes.â The other thought that comes to my mind is one that has been noted frequently since Bill's recent death from malaria. Bill Hamilton was a risk taker, not just in his life, but also in his science. In his work, too, he sometimes skated on thin ice, traveling where others would not. E. O. Wilson once used exactly this metaphor to describe a certain kind of scientist who is always drawn to the dangerous or to the forbidden: âThey are the taboo breakers who enjoy the whiff of grapeshot and the crackle of thin iceâ (Wilson, 1978: 283). When Bill skated on thin ice in Finland, the results were satisfactory: the ice may have crackled but it did not give way. When he skated on thin scientific ice, the results were usually not just satisfactory, but glorious. Bill Hamilton's most glorious ideas were kin selection and inclusive fitness. Talking about Hamilton's contributions to inclusive fitness is a bit like talking about Isaac Newton's contributions to dynamics or Charles Darwin's contributions to natural selection. He invented the idea, and he developed most of its important implications. There were some forerunners, as there always are in science. I think of Hamilton's contribution as a fusing of two traditions. First, there was population genetics. Hamilton didn't completely invent the idea of kin selection. The idea was foreshadowed by Haldane (1955), Fisher (1958), and Williams (Williams and Williams, 1957). However, none of them developed it in any detail, perhaps because they did not appreciate its general importance in nature. For that we can thank animal behaviorists, particularly those like Wynne-Edwards (1962) and Emerson (1960), who believed that cooperation was very common in nature. Bill neatly hybridized the two traditions. If cooperation and altruism were important in nature, then we needed an explanation that was consistent with population genetics, and so inclusive fitness was born. Hamilton was well suited to make this match. Those acquainted with Hamilton only through his best-known papers may think of him as a theoretician and might conclude that he had the theoretician's superficial knowledge of the natural world. But in fact it was his mathematical skills that were hard won, while as a natural historian he was, well, a natural. You can see evidence of this in many of his papers, but it comes out particularly in his lesser known papers on insects under bark (Hamilton, 1978) and on fig wasps (Hamilton, 1979). So was Hamilton's contribution a simple merging of the insights of an ethologist and a population geneticist? No, it wasn't that simple, for several reasons. First, there was a lot of thin ice between these areas, and skating from one to the other was not encouraged in the early 1960s. Geneticists were leery of anything that smacked of eugenics. That included any application of population genetics to behavior. It included most of all applications to understanding social behavior, something we have always been a little touchy about. If nature was nasty, rude, or bawdy, better not to know about it, let alone let the public know. Let me illustrate the idea in an unconventional way, with a bit of verse that I call âFamily Valuesâ: Would I jump in a lake To save my drowning cousin? It's not a risk I'd take For him plus half a dozen. But if you raise the stake And make the prize my brother? Now that's a deal I'll make... If you'll just toss in another. If this poem, and the Haldane quip it is based upon, elicit chuckles, it is in large part because they treat a topic that is uncomfortable for us. Most humor is built on discomfort of one form or another. In this case, we recognize that we make unconscious judgments akin to these, with awkward balances of self-interest and family interest, but we don't like to see ourselves as calculating self-servers. Now throw in a good dash of genetics, and the mixture becomes truly taboo. Perhaps that's why Haldane and others did not pursue the topic. Bill's recollections of his graduate career (Hamilton, 1996) describe the price that he paid for his desire to be where the ice is thin. He had difficulty finding advisors. He had no desk. He had no invitations to talk about his work. It was not even clear that his thesis work, which would produce some of the most heavily cited papers in evolutionary biology (Hamilton, 1964a,b), would be acceptable for a Ph.D. For someone who was not socially outgoing in the first place, the effect of this isolation was severe. He feared that he might be a crank; why else would all these manifestly smart people fail to see the interest in what he was doing? He took to working in train stations and public parks simply to have some minimal level of human interaction. Mary Jane West Eberhard made a telling point in her talk about Bill at a recent meeting (West-Eberhard, 2000). She noted that Bill's life serves as a counter-example to those critics who said that sociobiological knowledge was dangerous. He was proof that one can see all that is grim in the depths of our nature and still live a life of decency and kindness. Bill would have been uncomfortable with hagiography. His writings allude to a knowledge of the dark side of human nature, obvious to him through introspection, so clearly his thoughts were not always saintly. But whatever dark thoughts swirled in his mind, on the surfaceâand this is where it countsâhe was basically a gentle man. Despite his highly critical mind, I never heard him criticize anyone in anything but the kindest, most self-effacing manner. He did not judge people by credentials and had time for people that others might consider to be amateurs or even crackpots, George Price being a notable example. And while he no doubt appreciated the recognition he eventually received, particularly given his lonely days as a graduate student, he did not seem to crave recognition excessively. Dawkins reported one example where Bill gave credit to someone else for an idea that was really his own and had to be confronted with the evidence from his own paper (Dawkins, 2000). Then, as Dawkins described it with an adverbial tour de force, Bill â eeyorishlyâ admitted that, yes, he'd had the idea, but the other fellow had put it much better. I can give another small illustration from my own experience. In 1985 I published a paper using Price's rule to obtain a new expression for inclusive fitness (Queller, 1985). Alan Grafen then chided me (Grafen, 1985), quite rightly, for having neglected to cite Hamilton's paper using Price's rule (Hamilton, 1970). My only excuse is that Bill had read my paper in manuscript without ever pointing out the omission, which he must have noticed. For that matter, I had learned about Price's rule directly from Bill in seminars at the University of Michigan. If I remembered Price's rule well and forgot Bill's uses of it, it is partly because of the selfless way that Bill taught the subject. There is a another reason that Hamilton's contribution cannot be viewed as a simple merging of naturalist and theoretical traditions. He did not just come up with any old theoretical model. For example, one could model the evolution of altruism for some particular limited set of conditions (George and Doris Williams had already done this; Williams and Williams, 1957), but then one has to wonder how general the conclusions are. And it is also possible, as other modelers later showed, to add so many mathematical bells and whistles that we lose track of the general theme. In contrast, what Hamilton came up with was a theory that was not only basically true, but also beautiful and elegant. I'm not speaking of the mathematical derivation in his 1964 paper, which was actually rather gruesome. I'm speaking of the result, what has come to be known as Hamilton's rule. It is so simple that even a non-mathematical mind can easily understand it and wield it, and so general that it can often be applied to new social evolution problems without any fresh mathematical modeling. How was this simple elegance achieved? I think there are two main reasons. First, Hamilton was willing to make assumptions that allowed the result to be simple without seriously compromising the biology. For example, he assumed that selection would be weak. Stronger selection has the effect of distorting the relatednesses away from their familiar values, and it makes them dependent on genetic details such as dominance. Hamilton's assumption was justified because weak selection is presumably common. For that matter, it's probably not so bad an approximation for stronger selection. A little distortion of correlation coefficients doesn't matter too much to someone interested in the real world, where estimates of parameters are typically only good to about one significant digit anyway. The second reason inclusive fitness is so useful is its inversion of fitness calculation methods. Instead of grouping together all effects of others on x's fitness, it calculated all the inclusive effects of x on others' fitnesses. This actor-centered approach is what makes the method so easy to apply. In Hamilton's own words: âThe social behaviour of a species evolves in such a way that in each distinct behaviour-evoking situation the individual will seem to value his neighbors' fitness against his own according to the coefficients of relationship appropriate to the situationâ (Hamilton, 1964b: 19). It has become clear in recent years that the same behaviors can also often be understood as a form of group selectionânot the old group selection of Wynne-Edwards, but nevertheless a method that involves partitioning of selection into within-group and between-group components (see Sober and Wilson, 1998). But the fact remains that almost no one uses these methods much to think about and solve interesting problems. Each of the two methods can dissect social evolution into component parts, but where inclusive fitness divides nature neatly at the joints, other methods seem to hack clumsily through the long bones. Inclusive fitness and kin selection were important on several levels. First, of course, they provided an explanation for the evolution of altruism. We still don't know whether Hamilton's famous haplodiploid hypothesis, based on three-quarters relatedness (Hamilton, 1964b, 1972), explains the origin of eusociality. But it seems certain that the answer does lie within his more general framework of relatedness, costs, and benefits. For the study of social insects, another result of inclusive thinking was perhaps even more interesting. The theory did not simply explain the altruism that we already knew about. It also predicted something we did not know much about: conflicts within colonies. Because inclusive fitness interests often differ even among close relatives (Hamilton, 1972), there can be conflicts over who should be queen, conflicts over who should lay the male-destined eggs, and conflicts over sex ratios (reviewed in Queller and Strassmann, 1998). Studies in these areas have amply satisfied the requirement that a good theory should not just explain what is known, but also make novel and successful predictions. I think a parallel phenomenon occurs in the world beyond social insects. Perhaps even more important than the explanation of altruism itself was the general validation given to selfish gene models. If selfish genes are to be of any value in explaining the evolution of social behavior, they simply must be able to explain the cases where the behavior is not phenotypically selfish. Otherwise the method must be counted as a failure. So kin-selected explanations of altruistic behavior gave life to selfish gene explanation in areas where kinship was not paramount. Hamilton's own work clearly shows this. He didn't stop with altruism. He made pioneering contributions in many other areas. The accompanying pieces in this issue describe his contributions to the study of sexual selection and parasites, but his work also included important contributions to senescence theory (Hamilton, 1966), sex ratios (Hamilton, 1967), selfish herds (Hamilton, 1971), dispersal (Hamilton and May, 1977), tit-for-tat cooperation (Axelrod and Hamilton, 1981), and within-individual conflict (Hamilton, 1967). This truly formidable list of accomplishments, and the whole selfish gene tradition of which it is a part, emerged from a confidence based on Hamilton's success in solving the potentially fatal problem of altruism. Finally, in recent years it has become increasingly clear that a theory of altruism and cooperation is important for a much grander reason than solving the annoying puzzle of the social insects. It is also needed to explain a much more pervasive kind of cooperation; the evolution of the organism itself (Maynard Smith and SzathmĂĄry, 1995) why do cells cooperate in a body? Why do formerly independent bacteria evolve into organelles? How did replicators get together in the first place? Organisms, though they compete selfishly with each other, are themselves cooperative entities. Cooperation is therefore fundamental to all of life. I began with a small scientific meeting in Finland. Let me close with another one, in Castiglioncello, Italy. The highest scientific compliment I have ever received was one that Bill delivered there, actually to my wife and collaborator Joan Strassmann. Bill had, many years previously, done field work in Brazil on the troubling question of how sociality could be maintained in wasps with many queens. We had recently helped show, with molecular tools that had not been available to Bill, how relatedness was kept at levels consistent with kin selection (Queller et al., 1988, 1993; West Eberhard, 1978). What he said to Joan was âNow I will have to think up a different question to ask St. Peter when I meet him.â Of course, this was ridiculously inflated praise, a reflection of Bill's generosity rather than his acumen. He was no doubt signaling this exaggeration by his use of the religious reference, since Bill did not seem to be a conventionally religious man. Instead, he is some one who saw his afterlife more in terms of burying beetles (Hamilton, 2000) than in terms of meeting St. Peter. Still, I'd like to run with idea for just a moment. In the sad days after Bill died, the thought of him interrogating St. Peter gave me a certain amount of solace, and perhaps even pleasure. It's not that I can imagine what Bill's question was. Nor was it the thought of him receiving a satisfactory answer. Instead, what appeals to me is the impact on old St. Peter. I imagine him at first flummoxed because he couldn't answer the question, then annoyed because he had never thought of it himself, and finally intrigued by the implications. I imagine him spending his free moments over the next few centuries thinking about it, making new observations on the teeming life below, scribbling some population genetic equations in the margins of his heavenly register, and perhaps running some simulations on God's fastest supercomputer. Perhaps I overestimate St. Peter's curiosity, but Bill's questions have always had that kind of effect. That they will long continue to do so is his legacy to us.