policy implications of potential conflicts between short term and long term efficiency in co2 emissions abatement abstract this paper shows that under certain conditions including path dependence and lock in policies and measures leading to a cost effective ghg emissions mitigation in the short term may not allow reaching long term emissions targets at the lowest possible cost that is they might not be cost effective in the long term the reason is that in a situation where currently expensive technologies have a large potential for cost reductions through learning effects and r d investments the implementation of incentive based mitigation policies such as taxes or tradable permits will encourage the adoption and diffusion of currently low cost abatement technologies but might not be enough to make attractive the diffusion of expensive ones which is a necessary condition for these technologies to realise their cost reduction potential through the aforementioned effects a simple model and a numerical simulation are provided to show this possible conflict between static and dynamic efficiency which points out to the need to combine different instruments some aiming at short term cost efficiency such as incentive based environmental policy and others at encouraging dynamic cost reductions such as technology innovation policy

a dynamic model of brand choice when price and advertising signal product quality in this paper we develop a structural model of household behavior in an environment where there is uncertainty about brand attributes and both prices and advertising signal brand quality four quality signaling mechanisms are at work 1 price signals quality 2 advertising frequency signals quality 3 advertising content provides direct but noisy information about quality and 4 use experience provides direct but noisy information about quality we estimate our proposed model using scanner panel data on ketchup if price is important as a signal of brand quality then frequent price promotion may have the unintended consequence of reducing brand equity we use our estimated model to measure the importance of such effects our results imply that price is an important quality signaling mechanism and that frequent price cuts can have significant adverse effects on brand equity the role of advertising frequency in signaling quality is also significant but it is less quantitatively important than price in the printed version of marketing science vol 27 no 6 erdem et al 2008 was mistakenly identified as a research note it is a regular article and has been corrected here and in the online table of contents

advertising learning and consumer choice in experience good markets an empirical examination this article empirically analyzes different effects of advertising in a nondurable experience good market a dynamic learning model of consumer behavior is presented in which i allow both informative effects of advertising and prestige or image effects of advertising this learning model is estimated using consumer level panel data tracking grocery purchases and advertising exposures over time empirical results suggest that in this market advertising s primary effect was that of informing consumers the estimates are used to quantify the value of this information to consumers and evaluate the welfare implications of an alternative advertising regulatory regime

when starting with the most expensive option makes sense optimal timing cost and sectoral allocation of abatement investment this paper finds that it is optimal to start a long term emission reduction strategy with significant short term abatement investment even if the optimal carbon price starts low and grows progressively over time moreover optimal marginal abatement investment costs differ across sectors of the economy it may be preferable to spend 25 dollars to avoid the marginal ton of carbon in a sector where abatement capital is expensive such as public transportation or in a sector with large abatement potential such as the power sector than 15 dollars for the marginal ton in a sector with lower cost or lower abatement potential the reason distinct from learning spillovers is that reducing greenhouse gas emissions requires investment in long lived abatement capital such as clean power plants or public transport infrastructure the value of abatement investment comes from avoided emissions but also from the value of abatement capital in the future the optimal levelized cost of conserved carbon can thus be higher than the optimal carbon price it is higher in sectors with higher investment needs those where abatement capital is more expensive or sectors with larger abatement potential we compare our approach to the traditional abatement cost curve model and discuss implications for policy design

economy wide estimates of the implications of climate change sea level rise the economy wide implications of sea level rise in 2050 are estimated using a static computable general equilibrium model this allows for a better estimate of the welfare effects of sea level rise than the common direct cost estimates and for an estimate of the impact of sea level rise on greenhouse gas emissions overall general equilibrium effects increase the welfare costs of sea level rise but not necessarily in every sector or region in the absence of coastal protection economies that rely most on agriculture are hit hardest although energy is substituted for land overall energy consumption falls with the shrinking economy hurting energy exporters with full coastal protection gdp increases particularly in regions with substantial dike building but utility falls least in regions that protect their coasts and export energy energy prices rise and energy consumption falls the costs of full protection exceed the costs of losing land the results also show direct costs the usual method for estimating welfare changes due to sea level rise are a bad approximation of the general equilibrium welfare effects previous estimates of the economic impact of sea level rise are therefore biased

uncertain infant mortality learning and life cycle fertility this article examines the links between infant mortality and fertility in an environment with unobserved heterogeneity in infant mortality risk across mothers in such an environment replacement behavior i e the fertility response to an experienced child death might be influenced by mothers learning about a family specific component of infant mortality risk i explicitly introduce learning by mothers in a dynamic stochastic model of life cycle marital fertility and i estimate the model s structural parameters using malaysian panel data the framework is used to estimate replacement rates and to correct for birth selectivity in the estimation of the relationship between infant mortality risk and health inputs

second order sustainability conditions for the development of sustainable innovations in a dynamic environment abstract in particular radical innovations can be important means to achieving improved sustainability due to the existence of path dependency and lock in however the transition from one technological trajectory to another more sustainable one is often impeded by significant barriers fortunately these barriers are by their nature subject to substantial changes in time so it makes sense to carefully distinguish between periods of stability showing high barriers in which the given trajectory can hardly be left and periods of instability characterized by low barriers where a new trajectory can be reached more easily the latter distinction matters since sustainable innovations often rely on governmental regulation and the economic burden arising from this regulation will be much lower in periods of instability moreover due to the complexity and dynamics of change in their respective environments innovations are generally associated with fundamental uncertainty such that it becomes impossible to predict the degree of sustainability yielded by specific innovations in the longer run under these circumstances it is essential to facilitate the change between trajectories and to allow for the possibility to select between a variety of alternative trajectories within a process of trial and error sustainability as viewed from this evolutionary perspective is therefore better understood as the general capability to adapt that is to readily change from less to more sustainable technological trajectories since the latter kind of sustainability determines the conditions under which the former kind i e sustainability related to a specific technology can be achieved the two kinds are respectively called second order and first order sustainability finally a series of determinants and corresponding indicators from the techno economic political and socio cultural sphere is identified which after proper measurement and weighting allow for making an assessment whether and when the incumbent industry is sufficiently destabilized and the political system rendered sufficiently favorable to the new more sustainable technology such that a transition to the preferred trajectory is possible without too much effort

modeling multiattribute utility risk and belief dynamics for new consumer durable brand choice this paper proposes a brand choice model to aid in the prelaunch management of a new consumer durable entry in an existing category the model contributes to theory by integrating the critical phenomena of multiattribute preference risk and dynamics in an individual level expected utility framework the integration is based on established theoretical constructs in utility bayesian decision analysis and discrete choice theory measurement and estimation procedures are presented an application is described and the managerial relevance of this work as a planning and forecasting tool is examined

information and the skewness of music sales this paper studies the role of product discovery in the demand for recorded music we show that releasing a new album causes a substantial and permanent increase in sales of the artist s old albums especially if the new release is a hit patterns in these backward spillovers suggest that they result from consumers discovering the artist upon hearing the new release to explore the implications of consumers incomplete information we estimate a simple learning based model of market demand our results imply that the distribution of sales is substantially more skewed than it would be if consumers were more fully informed

do deployment policies pick technologies by not picking applications a simulation of investment decisions in technologies with multiple applications abstract the role of deployment policies that aim to foster technological change has grown considerably especially in the fields of energy and climate however recent research has shown that the adoption of deployment policies carries the potential of locking in the technology that is most cost effective at the point of policy introduction but may be inefficient in the long term the present paper contributes to the emerging literature on the role of deployment policies in creating path dependency and eventually technology lock in while previous studies focused on the relationship between lock in and the technology specificity of deployment policies this paper introduces a new factor the existence of multiple applications for a technology we argue that this factor is highly relevant for technological lock in and should be considered by policy makers to support our argument we simulate the competition among four stationary battery technologies across energy system applications in an investment simulation model this simulation shows that the degree of competition among technologies differs strongly across applications which corresponds with a highly varying lock in probability hence selecting applications in deployment policies very likely corresponds to selecting technologies we discuss the implications of these results for both policy makers and for the academic debate on deployment policies and technological lock in as well as on technology assessment and governance more generally based on the notion that policies can have different technology specificity levels we develop the idea of the application specificity of policies and provide examples of currently enacted deployment policies that vary in terms of their technology and application specificity

momentum and social learning in presidential primaries this paper investigates social learning in sequential voting systems in the econometric model candidates experience momentum effects when their performance in early states exceeds expectations the empirical application uses daily polling data from the 2004 presidential primary we find that kerry benefited from surprising wins in early states and took votes away from dean owing to these momentum effects early voters had up to five times the influence of late voters in the selection of candidates and this helps to explain the distribution of advertising expenditures finally we use the estimated model to conduct two counterfactual experiments

a dynamic oligopoly structural model for the prescription drug market after patent expiration this article incorporates consumer learning and heterogeneity into a dynamic oligopoly model for the prescription drug market in the model both firms and patients need to learn the generic qualities via patients experiences generic firms entry decisions are endogenous but their entry timings depend on a random approval process i apply the model to examine the impact of shortening the expected generic approval time although this policy experiment brings generics to the market sooner it increases a potential entrant s likelihood of entering a crowded market and hence could reduce the total number of generic entrants and consumer welfare

consumer learning in a turbulent market environment modeling consumer choice dynamics after a product harm crisis abstract the authors empirically study consumer choice behavior in the wake of a product harm crisis which creates consumer uncertainty about product quality they develop a model that explicitly incorporates the impact of such uncertainty on consumer behavior assuming that consumers are uncertain about the mean product quality level and learn about product quality through the signals contained in use experience and the product harm crisis and also that consumers are uncertain about the precision of the signals in conveying product quality and update their perception of this precision over time they estimate this model using a scanner panel data set that includes consumer purchase history before during and after a product harm crisis that affected kraft foods australia s peanut butter division in june 1996 the proposed model fits the data better than the standard consumer learning model which assumes consumers are uncertain about product quality level but the precision of information in conveying p

is 75 of the sales promotion bump due to brand switching no only 33 is abstract several researchers have decomposed sales promotion elasticities based on household scanner panel data a key result is that the majority of the sales promotion elasticity approximately 74 on average is attributed to secondary demand effects brand switching and the remainder is attributed to primary demand effects timing acceleration and quantity increases the authors demonstrate that this result does not imply that if a brand gains 100 units in sales during a promotion the other brands in the category lose 74 units the authors offer a complementary decomposition measure based on unit sales the measure shows the ratio of the current cross brand unit sales loss to the current own brand unit sales gain during promotion the authors report empirical results for this measure they also derive analytical expressions that transform the elasticity decomposition into a decomposition of unit sales effects these expressions show the nature of the difference between the two decompositions to ga

decision making under uncertainty capturing dynamic brand choice processes in turbulent consumer goods markets we construct two models of the behavior of consumers in an environment where there is uncertainty about brand attributes in our models both usage experience and advertising exposure give consumers noisy signals about brand attributes consumers use these signals to update their expectations of brand attributes in a bayesian manner the two models are 1 a dynamic model with immediate utility maximization and 2 a dynamic forward looking model in which consumers maximize the expected present value of utility over a planning horizon given this theoretical framework we derive from the bayesian learning framework how brand choice probabilities depend on past usage experience and advertising exposures we then form likelihood functions for the models and estimate them on nielsen scanner data for detergent we find that the functional forms for experience and advertising effects that we derive from the bayesian learning framework fit the data very well relative to flexible ad hoc functional forms such as exponential smoothing and also perform better at out of sample prediction another finding is that in the context of consumer learning of product attributes although the forward looking model fits the data statistically better at conventional significance levels both models produce similar parameter estimates and policy implications our estimates indicate that consumers are risk averse with respect to variation in brand attributes which discourages them from buying unfamiliar brands using the estimated behavioral models we perform various scenario evaluations to find how changes in marketing strategy affect brand choice both in the short and long run a key finding obtained from the policy experiments is that advertising intensity has only weak short run effects but a strong cumulative effect in the long run the substantive content of the paper is potentially of interest to academics in marketing economics and decision sciences as well as product managers marketing research managers and analysts interested in studying the effectiveness of marketing mix strategies our paper will be of particular interest to those interested in the long run effects of advertising note that our estimation strategy requires us to specify explicit behavioral models of consumer choice behavior derive the implied relationships among choice probabilities past purchases and marketing mix variables and then estimate the behavioral parameters of each model such an estimation strategy is referred to as structural estimation and econometric models that are based explicitly on the consumer s maximization problem and whose parameters are parameters of the consumers utility functions or of their constraints are referred to as structural models a key benefit of the structural approach is its potential usefulness for policy evaluation the parameters of structural models are invariant to policy that is they do not change due to a change in the policy in contrast the parameters of reduced form brand choice models are in general functions of marketing strategy variables e g consumer response to price may depend on pricing policy as a result the predictions of reduced form models for the outcomes of policy experiments may be unreliable because in making the prediction one must assume that the model parameters are unaffected by the policy change since the agents in our models choose among many alternative brands their choice probabilities take the form of higher order integrals we employ monte carlo methods to approximate these integrals and estimate our models using simulated maximum likelihood estimation of the dynamic forward looking model also requires that a dynamic programming problem be solved in order to form the likelihood function for this we use a new approximation method based on simulation and interpolation techniques these estimation techniques may be of interest to researchers and policy makers in many fields where dynamic choice among discrete alternatives is important such as marketing decision sciences labor and health economics and industrial organization

measuring the temporal dynamics of policy mixes an empirical analysis of renewable energy policy mixes balance and design features in nine countries abstract complex societal or environmental problems require fast and substantial socio technical transitions for instance in the case of climate change these transitions need to take place in the energy transport and several industry sectors to induce and accelerate such transitions numerous policy interventions are required which interact with each other in policy mixes while several conceptual studies on policy mixes have been published recently there is very little empirical research apart from single case or small n studies it has been prominently argued that the debate about policy mixes has reached an impasse partly due to this lack of empirical work this paper addresses this gap by providing a first analysis of the temporal dynamics of complex policy mixes to do so we develop a conceptualization and measurement of policy mix balance across instrument types as well as policy mix design features in the form of intensity as a general and technology specificity as a technology focused design feature this allows us to answer the question how temporal dynamics of policy mixes differ between countries regarding their balance and design features our measurement approach is developed bottom up i e policies are assessed individually and then aggregated systematically at the policy mix level this enables overcoming the dependent variable problem in the study of policy change i e the problem of measuring policy output more specifically we develop a comparative dataset of 522 renewable energy policies in nine oecd countries our analysis shows that countries policy mix dynamics vary strongly regarding some variables e g technology specificity but less regarding others e g balance as a validity check we also test the effects of these mix dynamics on policy outcome in the form of renewable energy technology diffusion we reflect our findings in light of the theoretical debates around policy mixes and policy design and discuss how our results provoke an agenda for the new generation of research on policy mixes we specifically discuss avenues for future research with a particular focus on the politics of policy mixes

learning about new products an empirical study of physicians behavior i introduction an important aspect of economic innovation is the development of new products thus firms often devote large amounts of resources to research and development the pharmaceutical industry in particular is characterized by a high degree of product innovation and significant investments in research and development 1 critical to the adoption of a new pharmaceutical however is the willingness of physicians to prescribe it although clinical trials and advertising convey information about the quality of a new pharmaceutical considerable uncertainty remains not only about its general quality but also about its effect on individual patients 2 because physicians ultimately resolve this uncertainty by prescribing the new drug 3 to their patients namely by experimentation the adoption of a new pharmaceutical is closely related to the experimentation process by which physicians gain information in this paper we focus on the entry of a new antiulcer drug omeprazole in the italian pharmaceutical market in june of 1990 4 our data consist of monthly prescriptions of antiulcer medications by physicians in the rome metropolitan area between june 1990 and december 1992 we develop and estimate a dynamic discrete choice model of physician bayesian learning about the quality of a new drug in our model physicians have initial beliefs about the new drug s efficacy and update them every time that they prescribe the new drug and observe the treatment outcome when choosing which drug to prescribe to a particular patient a forward looking physician considers not only the expected outcome for that patient but also the opportunity to learn about the new drug s quality and use the information on future patients our parameter estimates allow us to disentangle how uncertainty about the new drug s quality intertemporal preferences and prices affect the adoption of the new drug and the corresponding health outcomes a recent literature has explored the role of learning about pharmaceuticals 5 as noted by manchanda et al 2005 in their review of this literature some important aspects of the learning mechanism are the channels through which agents learn prescription detailing marketing meetings and events their preferences toward risk risk averse or risk neutral and whether they are short sighted myopic or forward looking myopic agents maximize their current expected utility while forward looking agents evaluate their current utility as well as the expected future value of the information they might gain through the current prescription 6 the studies also differ in whether they use physician level or aggregate data a central contribution of our paper is the prediction of market demand for the new drug through a parsimonious yet behaviorally rich model using the same physician level data used here coscelli and shum 2004 model the behavior of doctors who learn in a bayesian fashion yet are myopic we in contrast model the forward looking behavior of physicians and reject the null hypothesis that physicians are myopic according to our estimates myopic behavior significantly delays the adoption of the new drug and generates large losses to patients health crawford and shum 2005 use related patient level data and model how forward looking patients learn about their curative and symptomatic matches with respect to alternative medications in their model a patient s learning about a medication is not driven by the fact that the medication is new rather it is driven by her need to learn which medication suits her best hence she learns about her match to each medication not just the new one in our model however learning is driven by the market level uncertainty associated with omeprazole as a new product 7 while it would be of interest to study both doctors and patients learning our doctor level data motivate our focus on physician learning

understanding carbon lock in abstract this paper narrative argues that industrial economies have been locked into fossil fuel based energy systems through a process of technological and institutional co evolution driven by path dependent increasing returns to scale it is asserted that this condition termed carbon lock in creates persistent market and policy failures that can inhibit the diffusion of carbon saving technologies despite their apparent environmental and economic advantages the notion of a techno institutional complex is introduced to capture the idea that lock in occurs through combined interactions among technological systems and governing institutions while carbon lock in provides a conceptual basis for understanding macro level barriers to the diffusion of carbon saving technologies it also generates questions for standard economic modeling approaches that abstract away technological and institutional evolution in their elaboration the question of escaping carbon lock in is left for a future paper

does ecological economics have a future contradiction and reinvention in the age of climate change abstract this paper addresses the role of neoclassical methodologies in ecological economics and the contradictions these methodologies pose to the field s critical founding principles we first consider robert costanza s treatment of nicholas stern s global deal and then survey climate change related articles published in this journal over the past five years this survey reveals how mainstream neoclassical methodologies dominate discourse and do so by marginalizing more critical political economy analyses this situation imperils the field s founding vision of a no growth steady state it also fails to address the related growth dynamics of capitalism without such a critical treatment the field s formal embrace of methodological pluralism actually entails an ideological empiricism that renders ecological economics theoretically incoherent this situation undermines the field s historical promise as an alternative economic paradigm ecological economics now faces a problematic future its survival in a form faithful to its founding vision will require an explicit choice to address its internal contradictions and reinvent itself in ways relevant to our contemporary context without such a choice ecological economics will likely succumb to an implicit acceptance of the hegemony of mainstream economic methodologies and their pro growth imperatives

estimates of the economic effects of sea level rise regional estimates of direct cost dc are commonly used to measure the economic damages of sea level rise such estimates suffer from three limitations i values of threatened endowments are not well known ii loss of endowments does not affect consumer prices and iii international trade is disregarded results in this paper indicate that these limitations can significantly affect economic assessments of sea level rise current uncertainty regarding endowment values as reflected in two alternative data sets for example leads to a 17 percent difference in coastal protec tion a 36 percent difference in the amount of land protected and a 36 percent difference in dc globally also global losses in equivalent variation ev a welfare measure that accounts for price changes are 13 percent higher than dc estimates regional ev losses may be up to 10 percent lower than regional dc however because international trade tends to redistribute losses from regions with relatively high damages to regions with relatively low damages

optimal transition from coal to gas and renewable power under capacity constraints and adjustment costs this paper studies the optimal transition from existing coal power plants to gas and renewable power under a carbon budget it solves a model of polluting exhaustible resources with capacity constraints and adjustment costs to build coal gas and renewable power plants it finds that optimal investment in renewable energy may start before coal power has been phased out and even before investment in gas has started because doing so allows for smoothing investment over time and reduces adjustment costs gas plants may be used to reduce short term investment in renewable power and associated costs but must eventually be phased out to allow room for carbon free power one risk for myopic agents comparing gas and renewable investment is thus to overestimate the lifetime of gas plants e g when computing the levelized cost of electricity and be biased against renewable power these analytical results are quantified with numerical simulations of the european commission s 2050 energy roadmap

comment on the global impacts of extreme sea level rise a comprehensive economic assessment pycroft et al environ resour econ 1 29 2015 used incorrect and outdated data to study the economic impact of sea level rise they misinterpret some of their input data and fail to exploit the strengths of their computable general equilibrium model and previously developed methods to study impacts and adaptation

a theory of dynamic oligopoly iii cournot competition abstract we study the markov perfect equilibrium mpe of an alternating move infinite horizon duopoly model where the strategic variable is quantity we exhibit a pair of difference differential equations that when they exist differentiable mpe strategies satisfy for quadratic payoff functions we solve these equations in closed form and demonstrate that the mpe corresponding to the solution is the limit of the finite horizon equilibrium as the horizon tends to infinity we conclude with a discussion of adjustment costs and endogenization of the timing

invited paper learning models an assessment of progress challenges and new developments learning models extend the traditional discrete choice framework by postulating that consumers have incomplete information about product attributes and that they learn about these attributes over time in this survey we describe the literature on learning models that has developed over the past 20 years using the model of erdem and keane as a unifying framework erdem t keane m 1996 decision making under uncertainty capturing dynamic brand choice processes in turbulent consumer goods markets marketing sci 15 1 1 20 we describe how subsequent work has extended their modeling framework and applied learning models to a wide range of different products and markets we argue that learning models have contributed greatly to our understanding of consumer behavior in particular in enhancing our understanding of brand loyalty and long run advertising effects we also discuss the limitations of existing learning models and potential extensions one key challenge is to disentangle learning as a source of

understanding responses to contradictory information about products although prior literature has examined reactions to drastic negative news we examine the situation in which decision makers receive contradictory information about products and they have to decide whether to persist with or abandon product usage we investigate physician reactions to conflicting information concerning the cardiovascular risk of avandia a diabetes drug we examine how beliefs about both drug effectiveness and drug safety are updated and speculate that experience expertise and self efficacy impact how such information is integrated with current quality beliefs unlike previous bayesian learning models we consider that some signals such as positive and negative news releases and the firm s marketing effort may be biased in that they provide an opinionated point of view the results show interesting differences in how physician types specialists hospital based primary care physicians heavy and light prescribers update their beliefs and the information sources they use to do so we find evidence that safety issues about avandia resulted in spillover concern to close competitor actos the results have implication for determining who should be targeted and what vehicles should be used if a firm is faced with a situation where consumers are in a quandary because of receiving conflicting messages

escaping carbon lock in this article explores the climate policy implications of the arguments made in understanding carbon lock in unruh 2000 which posited that industrial countries have become locked into fossil fuel based energy systems through path dependent processes driven by increasing returns to scale carbon lock in arises through technological organizational social and institutional co evolution culminating in what was termed as techno institutional complex tic in order to resolve the climate problem an escape from the lock in condition is required however due to the self referential nature of tic escape conditions are unlikely to be generated internally and it is argued here that exogenous forces are probably required

social learning and peer effects in consumption evidence from movie sales using box office data for all movies released between 1982 and 2000 i quantify how much the consumption decisions of individuals depend on information they receive from their peers when quality is ex ante uncertain in the presence of social learning we should see different box office sales dynamics depending on whether opening weekend demand is higher or lower than expected i use a unique feature of the movie industry to identify ex ante demand expectations the number of screens dedicated to a movie in its opening weekend reflects the sales expectations held by profit maximizing theatre owners several pieces of evidence are consistent with social learning first sales of movies with positive surprise and negative surprise in opening weekend demand diverge over time if a movie has better than expected appeal and therefore experiences larger than expected sales in week 1 consumers in week 2 update upward their expectations of quality further increasing week 2 sales second this divergence is small for movies for which consumers have strong priors and large for movies for which consumers have weak priors third the effect of a surprise is stronger for audiences with large social networks finally consumers do not respond to surprises in first week sales that are orthogonal to movie quality like weather shocks overall social learning appears to be an important determinant of sales in the movie industry accounting for 32 of sales for the typical movie with positive surprise this implies the existence of a large social multiplier such that the elasticity of aggregate demand to movie quality is larger than the elasticity of individual demand

an empirical model of optimal dynamic product launch and exit under demand uncertainty this paper considers the decision problem of a firm that is uncertain about the demand and hence profitability of a new product we develop a model of a decision maker who sequentially learns about the true product profitability from observed product sales based on the current information the decision maker decides whether to scrap the product central to this decision problem are sequential information gathering and the option value of scrapping the product at any point in time the model predicts the optimal demand for information e g in the form of test marketing and it predicts how the launch or exit policy depends on the firm s demand uncertainty furthermore it predicts what fraction of newly developed products should be launched on average and what fraction of these products will fail i e exit the model is solved using numerical dynamic programming techniques we present an application of the model to the case of the u s ready to eat breakfast cereal industry simulations show that the value of reducing uncertainty can be large and that under higher uncertainty firms should strongly increase the fraction of all new product opportunities launched even if their point estimate of profits is negative alternative simpler decision rules are shown to lead to large profit losses compared to our method finally we find that the high observed exit rate in the u s ready to eat cereal industry is optimal and to be expected based on our model

search and active learning with correlated information empirical evidence from mid atlantic clam fishermen this paper examines search with active learning and correlated information we first develop a simple model to show how correlation affects the decision to acquire information a unique data set on fishing site choice by mid atlantic clam fishermen is used to test the model predictions results find that clam fishermen search new sites when the catch at familiar sites declines i e when the opportunity cost of gathering information is low and also when catch at familiar sites is on the rise search following a catch decline occurs at spatially distant sites whereas search following a catch increase occurs at nearby sites correlated learning is crucial for explaining the site choice patterns in our data these results provide new insights that may extend to a variety of economic search problems where correlated learning is important

the sound of silence observational learning in the u s kidney market mere observation of others choices can be informative about product quality this paper develops an individual level dynamic model of observational learning and applies it to a novel data set from the u s kidney market where transplant candidates on a waiting list sequentially decide whether to accept a kidney offer we find strong evidence of observational learning patients draw negative quality inferences from earlier refusals in the queue thus becoming more inclined towards refusal themselves this self reinforcing chain of inferences leads to poor kidney utilization despite the continual shortage in kidney supply counterfactual policy simulations show that patients would have made more efficient use of kidneys had the concerns behind earlier refusals been shared this study yields a set of marketing implications in particular we show that observational learning and information sharing shape consumer choices in markedly different ways optimal marketing strategies should take into account how consumers learn from others

the global impacts of extreme sea level rise a comprehensive economic assessment this paper investigates the world wide economic cost of rapid sea level rise of the kind that could be caused by accelerated ice flow from the west antarctic and or the greenland ice sheets such an event would have direct impacts on economic activities located near the coastline and indirect impacts further inland using data from the diva model on sea floods river floods land loss salinisation and forced migration we analyse the effects of these damages in a computable general equilibrium model for 25 world regions we consider three sea level rise scenarios that correspond to 0 47 1 12 and 1 75 m by the 2080s by incorporating a wider range of damage categories implemented in an economy wide framework and including very rapid sea level rise the study offers a new contribution to climate change impact studies we find that the loss of gdp worldwide is 0 5 in the highest sea level rise scenario with a loss of welfare equivalent variation of almost 2 world wide within these aggregates there are large regional disparities with the central europe north region and parts of south east asia and south asia being especially prone to high costs welfare losses in the range of 4 12 the analysis assumes that there is not public adaptation which would substantially lower the costs in this way the analysis demonstrates what is at risk and could be used to justify adaptation expenses

the usefulness of marginal co2 e abatement cost curves in austria energy efficiency measures are manifold in all economic sectors these measures can be pictured by a marginal abatement cost curve macc which is a common way to show co2 e abatement potential and its related costs in various fields in this paper we calculated the marginal co2 e abatement cost curve for austria for the first time to fulfill the need for country specific cost curves one of the strengths of such curves lies in their ability to highlight that energy efficiency measures can even have negative abatement costs the weaknesses consist of neglecting a change in energy prices the rate of diffusion and compatibility with existing technologies by using a static bottom up approach we constructed the macc for four economic sectors household service transport energy and found a national mitigation potential of 45 4 million tons co2 e the results further show that even with the measures with negative abatement costs it is possible to make the necessary co2 e mitigation to fulfill the kyoto protocol the conclusions emphasize that the curve makes a contribution to overcome one of the barriers of implementation by providing enhanced information on energy efficiency measures and its costs

impacts of alternative allowance allocation methods under a cap and trade program in power sector emission trading is considered to be a cost effective environmental economic instrument for pollution control however the policy design of an emission trading program has a decisive impact on its performance allowance allocation is one of the most important policy design issues in emission trading not only for equity but also for policy performance in this research an artificial market for sulfur dioxide so2 emission trading was constructed by applying an agent based model the performance of the jiangsu so2 emission trading market was examined under different allowance allocation methods and transaction costs the results showed that the market efficiency of emission trading would be affected by the allocation methods when the transaction costs are positive the auction allowance allocation method was more efficient and had the lowest total emission control costs than the other three allocation methods examined however the use of this method will require that power plants pay for all of their allowance and doing so will increase the production costs of power plants on the other hand output based allowance allocation is the second best method

innovation and diffusion of environmental technology industrial nox abatement in sweden under refunded emission payments we study the actual process of technical change in the case of nox abatement from large stationary sources that have been regulated by very forceful policies in sweden considerable progress has been made in lowering aggregate emissions and this paper seeks to disaggregate average industry improvements to study how much of it is due to innovations by first movers and how much is achieved by adoption and diffusion of technology we find both factors very important innovation has been rapid the best firms have cut emissions on the order of 70 in spite of this reductions have actually been even more rapid for the majority of firms so that the median firms have caught up with best practice we analyze various characteristics of the technological change observed

informing transforming and persuading disentangling the multiple effects of advertising on brand choice decisions prior behavioral research has suggested that advertising can influence a consumer s quality evaluation through informative and transformative effects the informative effect acts directly to inform a consumer of product attributes and hence shapes her evaluations of brand quality the transformative effect affects the consumer s evaluation of brand quality by enhancing her assessment of her subsequent consumption experience in addition advertising may influence a consumer s utility directly even without providing any explicit information this is the persuasive effect in this paper we propose a framework that formally models the processes through which all three effects of advertisements impact consumers brand evaluations and their subsequent brand choice decisions in particular we model source credibility confirmatory bias and bounded rationality on the part of consumers by appropriately modifying the standard bayesian learning approach our model conforms closely to prior behavioral literature and the experimental findings therein in our empirical analysis we get significant estimates of both informative and transformative effects across brands we find interesting temporal patterns across the effects for instance the importance of transformative effects seem to grow over time while that of informative effects diminishes finally we conduct policy experiments to examine the impact of increased ad intensity on advertising effects as well as the role played by consumption ambiguity

redefining innovation eco innovation research and the contribution from ecological economics while innovation processes toward sustainable development eco innovations have received increasing attention during the past years theoretical and methodological approaches to analyze these processes are poorly developed against this background the term eco innovation is introduced in this paper addressing explicitly three kinds of changes towards sustainable development technological social and institutional innovation secondly the potential contribution of neoclassical and co evolutionary approaches from environmental and innovation economics to eco innovation research is discussed three peculiarities of eco innovation are identified the double externality problem the regulatory push pull effect and the increasing importance of social and institutional innovation while the first two are widely ignored in innovation economics the third is at the least not elaborated appropriately the consideration of these peculiarities may help to overcome market failure by establishing a specific eco innovation policy and to avoid a technology bias through a broader understanding of innovation finally perspectives for a specific contribution of ecological economics to eco innovation research are drawn it is argued that methodological pluralism as established in ecological economics would be very beneficial for eco innovation research a theoretical framework integrating elements from both neoclassical and evolutionary approaches should be pursued in order to consider the complexity of factors influencing innovation decisions as well as the specific role of regulatory instruments and the experience gathered in ecological economics integrating ecological social and economic aspects of sustainable development is highly useful for opening up innovation research to social and institutional changes 2000 elsevier science b v all rights reserved

the long term effects of price promotions on category incidence brand choice and purchase quantity abstract to what extent do price promotions have a long term effect on the components of brand sales namely category incidence brand choice and purchase quantity the authors answer this question by using persistence modeling on weekly sales data of a perishable and a storable product derived from a scanner panel their analysis reveals first that permanent promotion effects are virtually absent for each sales component next the authors develop and apply an impulse response approach to estimate the promotional adjustment period and the total dynamic effects of a price promotion specifically they calculate the long term equivalent of gupta s 1988 14 84 2 breakdown of promotional effects because of positive adjustment effects for incidence but negative adjustment effects for choice the authors find a reversal of the importance of category incidence and brand choice 66 11 23 for the storable product and 58 39 3 for the perishable product the authors discuss the implications of the findings an

choosing the wrong calling plan ignorance and learning when a firm offers several tariff options to its customers the possibility arises that they will make an ex post mistake in tariff choice this occurs since consumers cannot commit to a certain purchase level at the time they subscribe to the service option and thus they might find out later that a different choice of tariff could have resulted in a lower payment for their actual level of consumption this is a common feature of increasingly important subscriptions markets in which buyers and sellers maintain long term nonanonymous relations and where learning induces interesting dynamics on the one hand buyers may learn their taste over time thus making the right choice as times goes by on the other hand the seller may design options to identify the type of each buyer and if possible to extract a higher proportion of their consumer surplus by offering tariff options that are better tailored to the profile of the consumer this paper focuses on the first type of learning in turn i document buyer behavior in a subscriptions market using data from a tariff experiment run by south central bell scb in kentucky during the second half of 1986 the most frequently studied case of subscriptions markets is the choice among optional calling plans ocps in the telephone industry this paper shows that contrary to the conven

decomposing the sales promotion bump with store data sales promotions generate substantial short term sales increases to determine whether the sales promotion bump is truly beneficial from a managerial perspective we propose a system of store level regression models that decomposes the sales promotion bump into three parts cross brand effects secondary demand cross period effects primary demand borrowed from other time periods and category expansion effects remaining primary demand across four store level scanner datasets we find that each of these three parts contribute about one third on average one extension we propose is the separation of the category expansion effect into cross store and market expansion effects another one is to split the cross item effect total across all other items into cannibalization and between brand effects we also allow for a flexible decomposition by allowing all effects to depend on the feature display support condition and on the magnitude of the price discount the latter dependence is achieved by local polynomial regression we find that feature supported price discounts are strongly associated with cross period effects while display only supported price discounts have especially strong category expansion effects while the role of the category expansion effect tends to increase with higher price discounts the roles of cross brand and cross period effects both tend to decrease

services as experience goods an empirical examination of consumer learning in automobile insurance accurate is information at initial purchase how rapidly do consumers learn from product experiences and how much impact does learning have on purchase decisions i answer these questions for the case of automobile insurance using a panel of 18 595 consumers from one firm my principal findings are patterns of consumer departures following claims point to learning consumers enter the firm overly optimistic about its quality and are generally disappointed by experience and the impact of learning is mitigated by the slow arrival of claims and the development of lock in jel d12 d83 g22 l15

dynamic incentives by environmental policy instruments a survey abstract in this paper i survey and discuss recent developments on the incentives provided by environmental policy instruments for both adoption and development of advanced abatement technology a main conclusion to be drawn from the literature is that under competitive conditions market based instruments usually perform better than command and control moreover taxes may provide stronger long term incentives than tradable permits if the regulator is myopic if the government can anticipate new technology or is able to react on it optimally regulatory policies by virtue of administered prices taxes and policies by setting quantities issuing tradable permits are almost equivalent the literature also shows that under competitive conditions there is no difference between auctioning permits and grandfathering moreover timing and commitment of environmental policy is not crucial for adoption under competitive conditions commitment has positive incentive effects however if an r d sector has market power in the presence of market imperfections the ranking of the different policy instruments is ambiguous

determining consumers discount rates with field studies abstract because utility profits state transitions and discount rates are confounded in dynamic models discount rates are typically fixed for the purpose of identification the authors propose a strategy of identifying discount rates the identification rests on imputing the utility profits using decisions made in a context in which the future is inconsequential the objective function is concave and the decision space is continuous they then use these utilities profits to identify discount rates in contexts in which dynamics become material the authors exemplify this strategy using a field study in which cell phone users transitioned from a linear to a three part tariff pricing plan they find that the estimated discount rate corresponds to a weekly discount factor 90 lower than the value typically assumed in empirical research 995 when using a standard 995 discount factor they find that the price coefficient is underestimated by 16 moreover the predicted intertemporal substitution pat

a tale of two market failures technology and environmental policy abstract market failures associated with environmental pollution interact with market failures associated with the innovation and diffusion of new technologies these combined market failures provide a strong rationale for a portfolio of public policies that foster emissions reduction as well as the development and adoption of environmentally beneficial technology both theory and empirical evidence suggest that the rate and direction of technological advance is influenced by market and regulatory incentives and can be cost effectively harnessed through the use of economic incentive based policy in the presence of weak or nonexistent environmental policies investments in the development and diffusion of new environmentally beneficial technologies are very likely to be less than would be socially desirable positive knowledge and adoption spillovers and information problems can further weaken innovation incentives while environmental technology policy is fraught with difficulties a long term view suggests a strategy of experimenting with policy approaches and systematically evaluating their success

the price consideration model of brand choice the workhorse brand choice models in marketing are the multinomial logit mnl and nested multinomial logit nmnl these models place strong restrictions on how brand share and purchase incidence price elasticities are related in this paper we propose a new model of brand choice the price consideration pc model that allows more flexibility in this relationship in the pc model consumers do not observe prices in each period every week a consumer decides whether to consider a category only then does he she look at prices and decide whether and what to buy using scanner data we show the pc model fits much better than mnl or nmnl simulations reveal the reason the pc model provides a vastly superior fit to inter purchase spells

persuasion or information the economics of prescription drug advertising the economic and welfare effects of advertising have been extensively studied over the last half century however these efforts have not led to a consensus either as to the effects or the value of advertising economists continue to reach polar conclusions that appear to be derived mainly from preconceptions of the social desirability of advertising on the one hand is research that emphasizes promotion s ability to create artificial product differentiation and thereby produce informational confusion 1 this line of research stresses the empirical association of extensive advertising with high concentration and high accounting profits evidence judged to support increased market power and entry barrier effects 2 a contrary body of research emphasizes the value of advertising in providing information and hence in promoting competition 3 the empirical findings most consistent with this view are that prices paid by consumers in selected markets are lower with advertising than without it 4

job matching and occupational choice this paper presents a model of job matching the generalizes the existing literature by allowing for different jobs types or occupations such differences affect the value of job specific experience inducing a career profile where certain types are sampled before others more specifically the analysis shows that it is optimal for the young and inexperienced to gravitate toward jobs exhibiting a certain kind of risk then after deriving the equilibrium job turnover rate for an economy in which people do not switch occupations panel data are used to estimate its underlying parameters the hypothesis that people do not switch occupations is rejected against the alternative that they do thus providing empirical support for the theoretical extension undertaken here

tariff choice with consumer learning and switching costs abstract consumers choosing flat rate contracts tend to have insufficient usage to warrant the cost particularly for new products we propose and estimate a bayesian learning model of tariff and usage choice that explains this flat rate bias without relying on behavioral misjudgments or tariff specific preferences for new products consumers are uncertain about both their utility relative to the population mean and the mean itself we show that this latter uncertainty inflates prior variances which leads consumers to weight their private signals more heavily when updating beliefs posteriors are unbiased across products for a given product however the unknown mean yields a winner s curse consumers with high posteriors tend to overestimate their utility these consumers choose fixed rate tariffs and lower their usage as they correct their beliefs the flat rate bias arises when switching costs deter them from changing tariffs using the estimated model the authors find that tariff menus are ineff