Browsing by Subject "Decision theory"
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Item Essays in direct marketing : understanding response behavior and implementation of targeting strategies(2011-05) Sinha, Shameek; Mahajan, Vijay; Ter Hofstede, Frenkel; Duan, Jason; Khan, Romana; Carvalho, CarlosIn direct marketing, understanding the response behavior of consumers to marketing initiatives is a pre-requisite for marketers before implementing targeting strategies to reach potential as well as existing consumers in the future. Consumer response can either be in terms of the incidence or timing of purchases, category/ brand choice of purchases made as well as the volume or purchase amounts in each category. Direct marketers seek to explore how past consumer response behavior as well as their targeting actions affects current response patterns. However, considerable heterogeneity is also prevalent in consumer responses and the possible sources of this heterogeneity need to be investigated. With the knowledge of consumer response and the corresponding heterogeneity, direct marketers can devise targeting strategies to attract potential new consumers as well as retain existing consumers. In the first essay of my dissertation (Chapter 2), I model the response behavior of donors in non-profit charity fund-raising in terms of their timing and volume of donations. I show that past donations (both the incidence and volume) and solicitation for alternative causes by non-profits matter in donor responses and the heterogeneity in donation behavior can be explained in terms of individual and community level donor characteristics. I also provide a heuristic approach to target new donors by using a classification scheme for donors in terms of the frequency and amount of donations and then characterize each donor portfolio with corresponding donor characteristics. In the second essay (Chapter 3), I propose a more structural approach in the targeting of customers by direct marketers in the context of customized retail couponing. First I model customer purchase in a retail setting where brand choice decisions in a product category depend on pricing, in-store promotions, coupon targeting as well as the face values of those coupons. Then using a utility function specification for the retailer which implements a trade-off between net revenue (revenue – coupon face value) and information gain, I propose a Bayesian decision theoretic approach to determine optimal customized coupon face values. The optimization algorithm is sequential where past as well as future customer responses affect targeted coupon face values and the direct marketer tries to determine the trade-off through natural experimentation.Item Essays in economic design : information, markets and dynamics(2011-05) Khan, Urmee, 1977-; Hayashi, Takashi, Ph D.; Stinchcombe, Maxwell; Peski, Marcin; Lieli, Robert P.; Zitkovic, GordanThis dissertation consists of three essays that apply both economic theory and econometric methods to understand design and dynamics of institutions. In particular, it studies how institutions aggregate information and deal with uncertainty and attempts to derive implications for optimal institution design. Here is a brief summary of the essays. In many economic, political and social situations where the environment changes in a random fashion necessitating costly action we face a choice of both the timing of the action as well as choosing the optimal action. In particular, if the stochastic environment possesses the property that the next environmental change becomes either more or less likely as more time passes since the last change (in other words the hazard rate of environmental change is not constant over time), then the timing of the action takes on special importance. In the first essay, joint with Maxwell B Stinchcombe, we model and solve a dynamic decision problem in a semi-Markov environment. We find that if the arrival times for state changes do not follow a memoryless process, time since the last observed change of state, in addition to the current state, becomes a crucial variable in the decision. We characterize the optimal policy and the optimal timing of executing that policy in the differentiable case by a set of first order conditions of a relatively simple form. They show that both in the case of increasing and decreasing hazard rates, the optimal response may be to wait before executing a policy change. The intuitive explanation of the result has to do with the fact that waiting reveals information about the likelihood of the next change occurring, hence waiting is valuable when actions are costly. This result helps shed new light on the structure of optimal decisions in many interesting problems of institution design, including the fact that constitutions often have built-in delay mechanisms to slow the pace of legislative change. Our model results could be used to characterize optimal timing rules for constitutional amendments. The paper also contributes to generalize the methodology of semi-Markov decision theory by formulating a dynamic programming set-up that looks to solve the timing-of-action problem whereas the existing literature looks to optimize over a much more limited set of policies where the action can only be taken at the instant when the state changes. In the second essay, we extend our research to situations, where the current choice of action influences the future path of the stochastic process, and apply it to the legal framework surrounding environmental issues, particularly to the ‘Precautionary Principle' as applied to climate change legislation. We represent scientific uncertainty about environmental degradation using the concept of 'ambiguity' and show that ambiguity aversion generates a 'precautionary effect'. As a result, justification is provided for the Precautionary Principle that is different from the ones provided by expected utility theory. This essay serves both as an application of the general theoretical results derived in the first essay and also stands alone as an analysis of a substantive question about environmental law. Prediction markets have attracted public attention in recent years for making accurate predictions about election outcomes, product sales, film box office and myriad other variables of interest and many believe that they will soon become a very important decision support system in a wide variety of areas including governance, law and industry. For successful design of these markets, a thorough understanding of the theoretical and empirical foundations of such markets is necessary. But the information aggregation process in these markets is not fully understood yet. There remains a number of open questions. The third essay, joint with Robert Lieli, attempts to analyze the direction and timing of information flow between prices, polls, and media coverage of events traded on prediction markets. Specifically, we examine the race between Barack Obama and Hillary Clinton in the 2008 Democratic primaries for presidential nomination. Substantively, we ask the following question: (i) Do prediction market prices have information that is not reflected in viii contemporaneous polls and media stories? (ii) Conversely, do prices react to information that appears to be news for pollsters or is prominently featured by the media? Quantitatively, we construct time series variables that reflect the "pollster's surprise" in each primary election, measured as the difference between actual vote share and vote share predicted by the latest poll before the primary, as well as indices that describe the extent of media coverage received by the candidates. We carry out Granger Causality tests between the day-to-day percentage change in the price of the "Obama wins nomination" security and these information variables. Some key results from our exercise can be summarized as follows. There seems to be mutual (two-way) Granger causality between prediction market prices and the surprise element in the primaries. There is also evidence of one-way Granger causality in the short run from price changes towards media news indices. These results suggest that prediction market prices anticipate at least some of the discrepancy between the actual outcome and the latest round of polls before the election. Nevertheless, prices also seem to be driven partly by election results, suggesting that there is an element of the pollster’s surprise that is genuine news for the market as well.Item The von Neumann/Morgenstern approach to ambiguity(2011-08) Dumav, Martin; Ẑitković, Gordan; Sirbu, MihaiAn outcome is ambiguous if it is an incomplete description of the probability distribution over consequences. An `incomplete description' is identified with the set of probabilities that satisfy the incomplete description. A choice problem is uncertain if the decision maker is choosing between distributions, and is ambiguous if the decision maker is choosing between sets of probabilities. The von Neumann/Morgenstern approach to uncertain choice problems uses a continuous linear function on probabilities. This paper develops the theory of ambiguous choice problems as a continuous, linear functions on closed convex sets of probabilities. This delivers: a framework encompassing most of the extant ambiguity averse preferences; a complete separation of attitudes towards risk and attitudes toward ambiguity; and generalizations of rst and second order stochastic dominance rankings to ambiguous decision problem. Quasi-concave preferences on sets that satisfy a restricted betweenness property capture variational preferences.