"Marketing strategies that firms adopt are based on consumers' response in the marketplace when they face and interact with these strategies. This dissertation examines the tendency of consumers to repeat their last purchase choices and the implications of this type of behavior on pricing related strategies of consumer packaged goods brand manufacturers. The first essay is a theory based empirical investigation about the commonly observed practice of brands offering temporary price promotions. There have been many theories that attempt to explain the popularity of price promotions as a marketing tool but with very few exceptions they are disconnected from choice dynamics. We examine the empirical support of a recent theory that connects price promotions with demand state dependence. In our investigation we measure how much each brand benefits from the consumers' tendency to repeat purchase and we examine the connection between this measure (AMEL) and the brands' price promotional frequencies. Our extensive sample includes all major brands from twenty product categories of frequently purchased goods and twenty stores in two separate geographical markets. Our empirical model accounts explicitly for the dependence of price promotions on demand response and vice versa. In summary, we find significant and robust evidence that brands which gainmore from consumers' repeat purchase behavior are offered on promotion formore weeks on average. We also demonstrate the value of our proposed estimation algorithm over simpler, two-step, approaches. In the second essay we examine consumers' state dependence not only to specific choice alternatives but also to parent brands that cover multiple sub-brands. Using a structural, forward looking, pricing model for multiproduct firms, we explore the implications of parent brand state dependence on equilibrium prices and firm profitability through counterfactual experiments. Empirically, we examine household level choice data from the category of yogurt and estimate state dependence to both the parent brand and the sub-brand level. We find evidence of parent brand state dependence for the category of yogurt. Its impact on the market equilibrium is to push prices downwards, because firms invest in future demand, and increase profitability of multiproduct firms, because per period demand increases"--Leaves iv-v.
This dissertation, "Essays on State Dependent Pricing Models" by Wai-yip, Alex, Ho, 何偉業, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled Essays on State Dependent Pricing Models submitted by Wai-Yip Alex HO for the degree of Master of Philosophy in Economics at The University of Hong Kong in August 2004 Abstract A dynamic general equilibrium model is developed to study the properties of state dependent pricing. In the rst section, we analyze the long-run properties of the model and nd that the eect of strategic complementarity in pricing decision between rms plays an important role in the model. When trend ination rate exceeds some critical level, such strategic complementarity results in existence of multiple equilibria in the model (2 equilibria). As trend ination increases, the dierence between the two equilibria gets wider. We then investigate the number of possible equilibrium by looking at the best response function of rms over certain values of trend ination rate. We nd that there exist one more unstable equilibrium. We nally access the long run dierence between the state dependent pricing model and the Calvo-pricing model and nd that the eect of trend ination on the model with state dependent pricing is much smaller than with Calvo-pricing. Under the same model specication and over the range of 1% to 6% trend ination rate, we nd that the eect of an increase in trend ination with state dependent pricing is smaller than with Calvo-pricing. In the next section, we explore the properties of the impulse responses of the state-dependent pricing model and compare it with a time-dependent pricing model. State-dependent pricing models show asymmetries in responding to dierent signs of a temporary money supply growth rate shock. However, real eects of such monetary shocks are not increasing proportionally to the size of the shock. Interestingly, we nd that if the size of the shock exceeds some critical level, the impulse response of the model to a positive shock converges to the impulse response to a negative shock. DOI: 10.5353/th_b3105994 Subjects: Pricing - Mathematical models
The three essays of this dissertation cover issues of understanding and managing price uncertainty across the meat value chain and related futures market. The first essay discussed the implications of recent change in retailing industry's pricing strategy; the second essay described a State Space Model approach estimation of the joint distribution of cash-futures prices and a simulation-based Conditional-VaR approach determination of optimal futures exposure determination in contrast with minimum variance hedge ratio when preference free optimal hedge ratio does not exist; the third essay described the empirical changes in the hog price volatility summarized by a series of long memory GARCH model of the absolute return series in view of the recent industry structural change. The first essay investigated the impact of two coexisting retail price strategies for selling perishable products on the volatility of both the farm-level price and the retailer's margin. The two strategies included the traditional High-Low strategy and the Every-Day-Low-Price (EDLP) pricing strategy. In contrast to non-perishable consumer products, perishable products, which are often of very inelastic demand, obtain their price fluctuations mainly through supply side shocks. A two-retailer model was developed to examine the volatilities of grocery retailers' margin and producer price due to supply shocks for a perishable product. Results indicated a volatility difference exists between EDLP and High-Low retailers' marginal revenue when the two pricing strategies coexist, and as the market share of EDLP format increases this margin volatility difference deepens and farm-level price volatility also increases. The second essay proposed a state space model based estimation of the cash-futures price dependence relationship and a coherent C-VaR-approach optimal futures exposure determination based on simulated data in response to situations where the preference-free optimal hedge ratio no longer exists and the minimum variance hedge ratio is not appropriate. The State Space Model serves as an alternative method to other joint distribution estimation methods. The determined optimal futures exposure showed that the minimum variance hedge ratio discourages hedging. Parallel analyses using existing constant minimum conditional variance (MCV) hedge ratio models and a time-varying MCV ratio based on Multivariate GARCH models was also conducted for comparison. The C-VaR approach optimal futures position exposure reported different optimal futures positions for the "short hedge" and the "long hedge" situations. The third essay analyzed the historical change of the realized price volatility defined as the weekly hog price absolute return from 1973 to 2008 using long memory effect in the mean and variance process. The ARFIMA-FIGARCH/IGARCH Model results confirmed a significant long memory effect in the absolute return for a period around the end of the 1990s with documented structural change. I found no significant long memory effect for any other period. The model result also showed a significant ARCH-M effect that is explained as a fierce industry structural adjustment leading to a more dramatic price volatility change.
This dissertation explores the impact of government interventions on economic outcomes. In the first chapter, my colleague Juan Carlos Suárez Serrato and I propose a new identification strategy to measure the causal impact of government spending on the economy. Our methodology isolates exogenous cross-sectional variation in government spending using a novel instrument. We use the fact that a large number of federal spending programs depend on local population levels. Every ten years, the Census provides a count of local populations. A different method is used to estimate non-Census year populations and this discontinuous change in methodology leads to variation in the allocation of billions of dollars in federal spending. We use this variation to analyze the effect of exogenous changes in federal spending across counties on local economic outcomes. Our IV estimates imply that government spending has a local income multiplier of 1.88 and an estimated cost per job of $30,000 per year. These estimates are robust to the inclusion of potential confounders, such as local demand shocks. We also show that the local effects of government spending are not larger than aggregate effects at the MSA and state levels. Finally, we characterize the cross-sectional heterogeneity of the impacts of government spending. These results confirm that government spending has a higher impact in low growth areas and leads to reduction of inequality in economic outcomes. The second chapter uses timing of childbirth to measure the income effect of taxes on parents' labor supply. The IRS Residency Test states that families can claim a dependent for the entire fiscal year if the child was born at any time during the year. This rule provides an exogenous source of variation in tax liabilities for births that occur late in the year versus those that occur early the following year. By measuring the difference in earnings in the subsequent year for parents of December and January births, I can identify the impact of a one-time non-labor income shock on parents' labor supply since both groups face on average the same future stream of tax schedules after birth. Using data from two large scale household surveys in the United States, I find that a temporary increase in after-tax income leads to a significant decrease in mothers' earnings with an estimated income effect of -0.9. This result demonstrates that the income effect of taxes on labor supply can potentially be very large. It also highlights the crucial role of liquidity constraints in parents' labor supply decisions around the time of birth. The third chapter also uses timing of childbirth to measure the income effect of taxes on mothers' labor supply. The analysis is done using Canadian data. Until 1992, various provisions in the Canadian tax code gave important tax reductions to low and middle-income parents of eligible children. Families could claim a child as a dependent for the entire fiscal year if the child was born at any time during the year. In 1992, the last year the Canadian tax code featured these fiscal benefits, a two parent family claiming a dependent could save nearly a thousand dollars in taxes due to the Child Tax Credit, the dependent amount and the GST credit. Using this variation in tax liabilities, it is possible to identify the impact of a one-time non-labor income shock on mothers' labor supply. This important parameter has not been systematically measured in the literature on the effect of taxes on labor supply. Using natural experiments provided by tax reforms in various countries, the literature has mostly focused on changes in earnings due to the price effect of marginal tax rate changes. However, if the income effect of a tax change is large, observed elasticities of income with respect to net-of-tax rates understate the distortions associated with these changes.
The thesis includes three papers: 1. Limited Arbitrage Analysis of CDS Basis Trading By modeling time-varying funding costs and demand pressure as the limits to arbitrage, the paper shows that assets with identical cash-flows have not only different expected returns, but also different expected returns in excess of funding costs. I solve the model in closed-form to show that the arbitrage on the CDS and corporate bond market is a risky arbitrage. The sign of the expected excess return of the arbitrage is decided by the sign and size of market frictions rather than the observed price discrepancy. The size and risk of the arbitrage excess return are increasing in market friction levels and assets' maturities. High levels of market frictions also destruct the positive predictability of credit spread term structure on credit spread changes. Results from the empirical section support the above-mentioned model predictions. 2. General Equilibrium Analysis of Stochastic Benchmarking This paper applies a closed-form continuous-time consumption-based general equilibrium model to analyze the equilibrium implications when some agents in the economy promise to beat a stochastic benchmark at an intermediate date. For very risky benchmark, these agents increase volatility and risk premium in the equilibrium. On the other hand, when they promise to beat less risky benchmark, they decrease volatility and risk premium in the equilibrium. In both cases, the degree of effect is state-dependent and stock price rises. 3. Institutional Asset Pricing with Heterogenous Belief (Co-authored) We propose an equilibrium asset pricing model in which investors with heterogeneous beliefs care about relative performance. We find that the relative performance concern leads agents to trade more similarly, which has two effects. First, similar trading directly decreases volatility. Second, similar trading decreases the impact of the dominant agents. When the economy is extremely good or bad, the second effect is dominant so that the relative performance concern enlarges the excess volatility caused by heterogeneous beliefs. When the first effect is dominant, which corresponds to a normal economy, the volatility is lower than without the relative performance concern. Moreover, this paper shows that the relative performance concern also influences investors' holdings, stock prices and risk premia.
This thesis is in two parts. The first part of the thesis, "Essays in Behavioral Macroeconomics," is motivated by the simple observation that the macroeconomy is complicated; many households and firms interact across myriad markets in ways that change over time. This part of the thesis studies, empirically and theoretically, the microeconomic foundations and macroeconomic implications of hypotheses inspired by these complications: that people adopt simplified and misspecified narratives to understand the world; and that people will only pay attention to the macroeconomy when it is important to them. In the first chapter, "The Macroeconomics of Narratives" (coauthored with Karthik A. Sastry), we study the macroeconomic implications of narratives, or beliefs about the economy that affect decisions and spread contagiously. Empirically, we use natural-language-processing methods to measure textual proxies for narratives in US public firms' end-of-year reports (Forms 10-K). We find that: (i) firms' hiring decisions respond strongly to narratives, (ii) narratives spread contagiously among firms, and (iii) this spread is responsive to macroeconomic conditions. To understand the macroeconomic implications of these forces, we embed a contagious optimistic narrative in a business-cycle model. We characterize, in terms of the decision-relevance and contagiousness of narratives, when the unique equilibrium features: (i) non-fundamental business cycles, (ii) non-linear belief dynamics (narratives "going viral") that generate multiple stable steady states (hysteresis), and (iii) the coexistence of hump-shaped responses to small shocks with regime-shifting behavior in response to large shocks. Our empirical estimates discipline both the static, general equilibrium effect of narratives on output and their dynamics. In the calibrated model, we find that contagious optimism explains 32% and 18% of the output reductions over the early 2000s recession and Great Recession, respectively, as well as 19% of the unconditional variance in output. We find that overall optimism is not sufficiently contagious to generate hysteresis, but other, more granular narratives are. In the second chapter, "Attention Cycles" (coauthored with Karthik A. Sastry), we document that, in aggregate downturns, US public firms' attention to macroeconomic conditions rises and the size of their input-choice mistakes falls. We explain these phenomena with a business-cycle model in which firms face a cognitive cost of making precise decisions. Because firms are owned by risk-averse households, there are greater incentives to deliver profits by making smaller input-choice mistakes when aggregate consumption is low. In the data, consistent with our model, financial markets punish mistakes more in downturns and macroeconomically attentive firms make smaller mistakes. Quantitatively, attention cycles generate asymmetric, state-dependent shock propagation and stochastic volatility of output growth. In the third chapter, "Strategic Mistakes" (coauthored with Karthik A. Sastry), to study the equilibrium implications of decision frictions, we introduce a new class of control costs in continuum-player, continuum-action games in which agents interact via an aggregate of the actions of others. The costs that we study accommodate a rich class of decision frictions, including ex post misoptimization, imperfect ex ante planning, cognitive constraints that depend endogenously on the behavior of others, and consideration sets. We provide primitive conditions such that equilibria exist, are unique, are efficient, and feature monotone comparative statics for action distributions, aggregates, and the size of agents' mistakes. We apply the model to make robust equilibrium predictions in a monetary business-cycle model of price-setting with planning frictions and a model of consumption and savings during a liquidity trap when endogenous stress worsens decisions. The second part of this thesis, "Essays in Mechanism Design," studies two contentious issues in the allocation of resources in the modern economy: How should we account for diversity when we allocate resources in two-sided matching markets? How should digital goods and information be priced and regulated? In the fourth chapter, "Priority Design in Centralized Matching Markets" (coauthored with Oğuzhan C̦elebi), we observe that in many centralized matching markets, agents' property rights over objects are derived from a coarse transformation of an underlying score. Prominent examples include the distance-based system employed by Boston Public Schools, where students who lived within a certain radius of each school were prioritized over all others, and the income-based system used in New York public housing allocation, where eligibility is determined by a sharp income cutoff. Motivated by this, we study how to optimally coarsen an underlying score. Our main result is that, for any continuous objective function and under stable matching mechanisms, the optimal design can be attained by splitting agents into at most three indifference classes for each object. We provide insights into this design problem in three applications: distance-based scores in Boston Public Schools, test-based scores for Chicago exam schools, and income-based scores in New York public housing allocation. In the fifth chapter, "Adaptive Priority Mechanisms" (coauthored with Oğuzhan Çelebi), we ask how authorities that care about match quality and diversity should allocate resources when they are uncertain of the market they face? Such a question appears in many contexts, including the allocation of school seats to students from various socioeconomic groups with differing exam scores. We propose a new class of adaptive priority mechanisms (APM) that prioritize agents as a function of both scores that reflect match quality and the number of assigned agents with the same socioeconomic characteristics. When there is a single authority and preferences over scores and diversity are separable, we derive an APM that is optimal, generates a unique outcome, and can be specified solely in terms of the preferences of the authority. By contrast, the ubiquitous priority and quota mechanisms are optimal if and only if the authority is risk-neutral or extremely risk-averse over diversity, respectively. When there are many authorities, it is dominant for each of them to use the optimal APM, and each so doing implements the unique stable matching. However, this is generally inefficient for the authorities. A centralized allocation mechanism that first uses an aggregate APM and then implements authority-specific quotas restores efficiency. Using data from Chicago Public Schools, we estimate that the gains from adopting APM are considerable. In the sixth and final chapter, "Nonlinear Pricing with Under-Utilization: A Theory of Multi-Part Tariffs" (coauthored with Roberto Corrao and Karthik A. Sastry), we study the nonlinear pricing of goods whose usage generates revenue for the seller and of which buyers can freely dispose. The optimal price schedule is a multi-part tariff, featuring tiers within which buyers pay a marginal price of zero. We apply our model to digital goods, for which advertising, data generation, and network effects make usage valuable, but monitoring legitimate usage is infeasible. Our results rationalize common pricing schemes including free products, free trials, and unlimited subscriptions. The possibility of free disposal harms producer and consumer welfare and makes both less sensitive to changes in usage-based revenue and demand.
When we think about Operations Management and Business Analytics, we think about optimization, efficiency, algorithms, optimality, profits and costs, exact quantitative analyses, etc. However, the field was created by humans and for humans. So what is the role of humans in the process of operational decision-making? In this dissertation, we study two aspects of the interface between humans and operational decision making, in the context of the apparel industry. The first part (Chapter 1) is related to social responsibility, i.e., how operational decision making affects workers, communities, and society. The second part (Chapters 2 and 3) shows how human biases affect operational decision-making. In the first chapter, we study unauthorized subcontracting, i.e., when suppliers outsource part of their production to a third party without the retailer's consent. This practice has been common practice in the apparel industry and it is often tied to non-compliant working conditions. Since retailers are unaware of the third party, the production process becomes obscure and cannot be tracked adequately. We present an empirical study of the factors that can lead suppliers to engage in unauthorized subcontracting. We use data provided by a global supply chain manager with over 30,000 orders, of which 36% were subcontracted without authorization. Our results show that there are different factory types, ranging from factories that used unauthorized third parties for all of their orders to factories that used none. Moreover, the degree of unauthorized subcontracting in the past is highly related to the probability of engaging in unauthorized subcontracting in the future, which suggests that factories behave as if they choose a strategic level of unauthorized subcontracting. At the order level, we find that state dependence (i.e., the status of an order carrying over to the next one) followed by price pressure are the key drivers of unauthorized subcontracting. Buyer reputation and factory specialization can also play a role, whereas the size of an order shows no effect. We find that the main effect (state dependence) is tied to factory utilization. Finally, we show that unauthorized subcontracting can be predicted correctly for more than 80% of the orders in out-of-sample tests. This indicates that retailers can use business analytics to predict unauthorized subcontracting and help prevent it from happening. In the second chapter, we study the adherence to the recommendations of a decision support system (DSS) for markdowns during clearance sales. The DSS was implemented at Zara, the Spanish fast fashion retailer. Managers' initial adherence was low, which motivated two interventions: 1. showing a revenue metric; and 2. showing a reference point for that metric. We use data collected by Zara during seven clearance sales campaigns to analyze the effect of the two interventions and the behavioral drivers of managers' adherence decisions. Intervention 1 did not significantly alter managers' adherence, but Intervention 2 increased it, and also decreased their likelihood to mark a product down when DSS recommended keeping its price unchanged. Managers were more likely to adhere to the DSS's recommendations when the suggested price was aligned with the heuristic they followed before the DSS was implemented. Managers' decisions were consistent with inventory minimization, as opposed to revenue maximization. Higher salvage values were related to higher adherence, but also to larger deviations when managers did not adhere. Managers were minimizing the number of different prices to set and basing their pricing decisions on metrics that were aggregated at the group level, instead of at the individual product level. These findings can be explained by preference for the status quo, salience of the inventory (compared to a revenue forecast), loss aversion, and inattention. Some of these biases were mitigated after the interventions. Our findings provide insights on how to increase voluntary adherence that can be used in any context in which a company wants an analytical tool to be adopted by its users. In Chapter 3, we continue to study pricing decision making by country managers at Zara. We aim to disentangle managers' degree of loss aversion from other behavioral biases by building a structural model to replicate managers' price decision making process and fitting it using data collected by Zara prior to the DSS's implementation. In our model, managers choose prices to maximize their utility over the whole season, subject to a number of constraints given by the firm's pricing rules. The utility function consists of a revenue component and a loss aversion component that depends on a loss aversion parameter. Both components include demand uncertainty and contain all products of the same type (shirts, pants, etc.). This model is, therefore, a dynamic program over a finite horizon with a large state space and uncertainty set. We use a certainty equivalent for the demand function, and discretize the problem, given that the set of available prices is discrete. Our model thus becomes a mixed integer linear program. We find, for each value of the loss aversion parameter, its corresponding set of utility-maximizing prices, and then pick the value of the parameter that best fits the prices that managers implemented. We then compare their degree of loss aversion across product groups (e.g. fashion or basic products) and across country managers. Preliminary results using a very small dataset suggest that country managers at Zara are, indeed, loss averse, but some managers are more so than others. There seem to be no clear pattern on what product types trigger loss aversion in managers. Our model explains managers' observed prices 11\% better than if we assume they are pure revenue maximizers, and several times better than if we model them as inventory minimizers.
Professor Dreze is a highly respected mathematical economist and econometrician. This book brings together some of his major contributions to the economic theory of decision making under uncertainty, and also several essays. These include an important essay on 'Decision theory under moral hazard and state dependent preferences' that significantly extends modern theory, and which provides rigorous foundations for subsequent chapters. Topics covered within the theory include decision theory, market allocation and prices, consumer decisions, theory of the firm, labour contracts, and public decisions.
