Risk attitudes, randomization to treatment, and self-selection into experiments

Randomization to treatment is fundamental to statistical control in the design of experiments. However randomization implies some uncertainty about treatment condition, and individuals differ in their preferences towards taking on risk. Since human subjects often volunteer for experiments or are allowed to drop out of the experiment at any time if they want to, it is possible that the sample observed in an experiment might be biased because of the risk of randomization. On the other hand, the widespread use of a guaranteed show-up fee that is non-stochastic may generate sample selection biases of the opposite direction, encouraging more risk averse samples into experiments. We directly test these hypotheses that risk attitudes play a role in sample selection. Our results suggest that randomization bias does affect the overall level of risk aversion in the sample we observe, but that it does not affect the demographic mix of risk attitudes in the sample. We show that the common use of non-stochastic show-up fees can generate samples that are more risk averse than would otherwise have been observed.     

Randomization and simplification in dynamic decision-making

Randomization adds beneficial flexibility to the construction of optimal simple plans in dynamic environments. A decision-maker, restricted to the use of simple plans, may find a stochastic plan that strictly outperforms all deterministic ones. This is true even in noninteractive deterministic environments where the decision-maker's choices have no influence on his signals nor on the future evolution of the system. We describe a natural decomposition of simple plans into two components: an action selection rule and a behavior modification rule. In noninteractive environments optimal simple plans do not require randomization in the action selection rule. Only randomization in the behavior modification rule may be necessary.     

Some sensitivity aspects of optimal control calculations for economic systems

In this paper we consider the problem of minimizing a quadratic welfare cost function constrained by a linear macro-econometric model. First we formulate the optimal control problem in a suitable form and specify the solution. Then we consider the sensitivity of the optimal control to changes in the targets and the weights of the welfare cost function. It is shown that the targets should not be selected without reference to the selection of the weights. Next, some simulation experiments, comparing open-loop versus closed-loop controls, are briefly reported on. The effects of changes in the lag structure are also mentioned.     

Negative recency, randomization device choice, and reduction of compound lotteries

We report an experiment in which subjects are not indifferent between real-money lotteries implemented with randomization devices that are equivalent under the Reduction Axiom. Instead, choice behavior is consistent with subjective distortion of conditional probability, and this persists in treatment conditions that control for (i) computational limitations and (ii) possible confounding by ratio bias.     

Procurement favouritism and technology adoption

It is well known that the design of cost minimizing procurement rules for the selection of a contractor among distinct technological groups requires the favouritism of inefficient firms. In this paper, I show that, if technology adoption is non-contractible, these policies will also provide optimal incentives for the inefficient firms to adopt more efficient technologies.     

A dual characterization of incentive efficiency

We show that incentive efficient allocations in economies with adverse selection and moral hazard problems can be determined as optimal solutions to a linear programming problem and we use duality theory to obtain a complete characterization of the optima. Our dual analysis identifies welfare effects associated with the incentives of the agents to truthfully reveal their private information. Because these welfare effects may generate non-convexities, incentive efficient allocations may involve randomization. Other properties of incentive efficient allocations are also derived.     

Selection bias in innovation studies: A simple test

The study of the innovative output of organizations often relies on a count of patents filed at one single office of reference such as the European Patent Office (EPO). Yet, not all organizations file their patents at the EPO, raising the specter of a selection bias. Using novel datasets of the whole population of patents by Belgian firms and German universities, we show that the single-office count results in a selection bias that affects econometric estimates of invention production functions. We propose an easy-to-implement methodology to evaluate whether estimates that rely on the single-office count are affected by a selection bias.     

The Impact of Computer Use On Earnings in the UK

The effect of new technology on relative demands for workers has been the subject of much research in economics. Krueger (1993) and others have studied the impact of computers on earnings in the US and elsewhere. Such studies have been criticised for ignoring the possibility of bias due to unobserved heterogeneity between computer users and non‐users, resulting in computer users not being a random sub‐sample of all workers. As well as looking at the effects of computers on earnings in the UK, this paper extends previous analyses by using a sample selection framework to deal with the bias problem. Results indicate not only that returns to computer use are positive but that it is important to correct for the sample selection bias.     

Randomization of commodity taxes: An expenditure minimization approach

Using an expenditure minimization approach, necessary and sufficient conditions for local random taxation are obtained in terms of the curvature of the compensated demand function, so that intuition from excess burden analysis can be applied. Major findings include: (1) random taxation is locally optimal if the compensated demand function is sufficiently convex; (2) horizontally equitable taxation is locally optimal if the compensated demand function is concave, and (3) local randomization is not optimal if the tax revenue requirement is sufficiently close to zero or to any local maximum. We also derive an inverse elasticity characterization of the optimal random tax structure.     

Monetary Policy Delegation, Contract Costs and Contract Targets

We reconsider the optimal central banker contract derived in Walsh (1995). We show that if the government's objective function places weight (value) on the cost of the contract, then the optimal inflation contract does not completely neutralize the inflation bias. Furthermore, the more concerned the government is about the cost of the contract or the less selfish is the central banker, the smaller is the share of the inflation bias eliminated by the contract. Finally, a central banker contract written in terms of output can completely eradicate the inflationary bias, regardless of concerns about contract costs.     

Learning with bounded memory in games

We study learning with bounded memory in zero-sum repeated games with one-sided incomplete information. The uninformed player has only a fixed number of memory states available. His strategy is to choose a transition rule from state to state, and an action rule, which is a map from each memory state to the set of actions. We show that the equilibrium transition rule involves randomization only in the intermediate memory states. Such randomization, or less frequent updating, is interpreted as a way of testing the opponent, which generates inertia in the player's behavior and is the main short-run bias in information processing exhibited by the bounded memory player.     

Utilitarian mechanism design for an excludable public good

This paper studies the design of optimal utilitarian mechanisms for an excludable public good. Excludability provides a basis for making people pay for admissions; the payments can be used for redistribution and/or funding. Whereas previous work assumed that admissions are governed by the payment or nonpayment of a price, this paper allows for arbitrary admission rules. With sufficient inequality aversion, nondegenerate randomization in admissions is shown to be desirable for certain model specifications, with and without participation constraints. The paper also gives a sufficient condition on the distribution of preferences under which randomization is undesirable.     

Application of Sample Selection Model to Double-Bounded Dichotomous Choice Contingent Valuation Studies

Modeling households' behavior with the data from a contingentvaluation (CV) survey is often complicated by samplenon-response, which can cause non-response bias and sampleselection bias, leading to inconsistent parameter estimates and adistorted mean willingness-to-pay estimate. This paper reportsthe results of empirical tests for both biases using householdsurvey data in which the double-bounded dichotomous choice CVquestion involved the benefit of a tap water quality improvementpolicy in Korea. No non-response bias, but sample selection bias,is detected in the sample. To correct for sample selection bias,a sample selection model is employed. The authors also discusshow failure to correct for bias may distort aggregate benefitestimates.     

IMPACT OF PRICING STRUCTURE SELECTIVITY ON URBAN WATER DEMAND

Interest in demand management policies has intensified as residential water demand has grown in the United States. Using data from the 1984 American Water Works Association (AWWA) survey, the study here provides an empirical analysis of the differences in price elasticities of demand across water pricing block structures and examines these structures' "conservation-orientedness." However, a potential sample selection bias exists. That is, in cities where people are more interested in conservation, utility managers may be more likely to select a rate structure that they believe is conservation-oriented–an increasing block structure, for example. Managers' selectivity bias may cause research results either to understate or to overstate a particular block structure's impact on water conservation. The analysis here corrects for this selectivity bias in estimating water demand and tests whether consumers respond to average prices or to marginal prices. Correcting for selectivity bias involves an explicit analysis of the factors that influence utility managers' selection of rate structures. Estimating water demand under increasing and decreasing block structures suggests that sample selection bias remains a problem worthy of further investigation.     

Effort maximization in asymmetric contest games with heterogeneous contestants

Contest rules are set up by administrators who frequently have discretionary power in specifying the details of these rules, i.e., they can bias the contest rules toward specific contestants in order to further their prime objective. We derive the optimal bias of the contest rule for a contest administrator, who is interested in maximizing the total efforts expended in the contest. The solution is obtained in closed form for a widely used class of n-person contest games. Setting the optimal bias has important implications: (i) there is never exclusion of strong players, instead there is (endogenously induced) inclusion of weak contestants; (ii) the contest administrator will optimally level the playing field by encouraging weak contestants, but he will not equalize the contestants’ chances unless they are identical; and (iii) at least three contestants will be active in equilibrium of the optimal contest, irrespective of heterogeneity.     

EVIDENCE ON GENDER WAGE DISCRIMINATION IN PORTUGAL: PARAMETRIC AND SEMI‐PARAMETRIC APPROACHES

In this paper we consider several alternative approaches to analyze gender wage discrimination. Besides the traditional OLS estimator, we use two other approaches to control for sample selection bias problems: the parametric procedure suggested by Vella and Wooldridge, and the Li and Wooldridge semi‐parametric estimator. We study the case of Portugal, employing data from the European Community Household Panel. The results reveal that the discrimination estimates are sensitive to the different econometric approaches. In fact, when sample selection bias is taken into account, the discrimination values are reduced and are typically not significant.     

THE OPTIMAL MINIMUM WAGE FOR POVERTY MINIMIZATION

This paper characterizes the poverty minimizing minimum wage, and shows how it varies as productivity, inequality and market competitiveness change. We show that the optimal minimum wage is equal to the competitive wage only in special cases. In general, the former is higher than the latter. Thus, poverty minimization does not coincide with employment maximization. We also show that the optimal minimum wage always rises with productivity and, under certain conditions, falls with competitiveness and inequality. Furthermore, the higher the competitiveness and inequality, the more the optimal wage rises with productivity.     

Non-asymptotic tests of model performance

This paper describes a non-asymptotic approach to the problem of selection bias in economic forecasting. By using non-asymptotic measure concentration results, it is possible to deal with settings in which the class of potential models is large with respect to the number of data points. The bounds on p values obtained by these methods are necessarily conservative, but they provide a useful benchmark for model selection in settings where asymptotics may not apply.     

SHARED PATENT RIGHTS AND TECHNOLOGICAL PROGRESS

We study how to reward innovators who build on one another. Rewards come in the form of patents. Because patent rights are scarce, the optimal allocation involves sharing: More than one innovator's patent is in force at a given time. We interpret such allocations as patents that infringe one another as licensing through an ever growing patent pool and as randomization through litigation. We contrast the rate of technological progress under the optimal allocation with the outcome if sharing is prohibitively costly. Avoiding sharing initially slows progress and leads to a more variable rate of technological progress.     

Priorities and sequencing in privatization: Evidence from Czech firm panel data

While privatization of state-owned enterprises has been one of the most important aspects of the economic transition from a centrally planned to a market system, no transition economy has privatized all its firms simultaneously. This raises the question of whether governments privatize firms strategically. In this paper we examine the determinants of the sequencing of privatization. To obtain testable predictions about the factors that may affect sequencing, we investigate the following competing government objectives: (i) Maximizing efficiency through resource allocation; (ii) maximizing public goodwill from the free transfers of shares to the public; (iii) minimizing political costs; (iv) maximizing efficiency through information gains; and (v) maximizing privatization revenues. Next, we use firm-level data from the Czech Republic to test the competing predictions about the sequencing of privatization. Consistent with the hypotheses of a government priority on revenues and public goodwill, we find strong evidence that more profitable firms were privatized first. The sequencing of privatization is also consistent with maximizing efficiency through information gains. Our results indicate that many empirical studies of the effects of privatization on firm performance suffer from a selection bias.