How do prices affect inequality and living standards worldwide? To address existing biases in the measurement of prices and expenditure patterns across countries, this paper introduces a new global scanner database. This dataset provides harmonized barcode-level data on expenditures and prices for fast-moving consumer goods during the last decade in thirty four countries, which include both developing (e.g., Brazil, China, India, and South Africa) and developed countries (e.g., the United States, Russia, and most European countries) and represent 70% of world GDP and 60% of world population. We quantify the importance of several common biases stemming from substitution, product variety, and taste shocks, and how they vary with the level of economic development. We then build purchasing power parity indices using identical barcodes across countries. We show that adjustments for product variety, non-homotheticities, and taste heterogeneity are quantitatively important. Overall, these findings indicate that using micro data on prices and expenditures is crucial to accurately describe patterns of inclusive growth worldwide.
{"title":"Prices and Global Inequality: New Evidence from Worldwide Scanner Data","authors":"Gunter W. Beck, Xavier Jaravel","doi":"10.2139/ssrn.3671980","DOIUrl":"https://doi.org/10.2139/ssrn.3671980","url":null,"abstract":"How do prices affect inequality and living standards worldwide? To address existing biases in the measurement of prices and expenditure patterns across countries, this paper introduces a new global scanner database. This dataset provides harmonized barcode-level data on expenditures and prices for fast-moving consumer goods during the last decade in thirty four countries, which include both developing (e.g., Brazil, China, India, and South Africa) and developed countries (e.g., the United States, Russia, and most European countries) and represent 70% of world GDP and 60% of world population. We quantify the importance of several common biases stemming from substitution, product variety, and taste shocks, and how they vary with the level of economic development. We then build purchasing power parity indices using identical barcodes across countries. We show that adjustments for product variety, non-homotheticities, and taste heterogeneity are quantitatively important. Overall, these findings indicate that using micro data on prices and expenditures is crucial to accurately describe patterns of inclusive growth worldwide.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124540025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Product sales and rentals often occur in parallel, allowing customers to choose their preferred option. In settings where consumers face significant valuation uncertainty, rentals also provide a mechanism for consumers to discover whether they like a product. For some products, such as movies and books, the rental option may yield a significant proportion of the utility associated with ownership. The convenience of renting products in digital forms (e.g., e-books) makes the managerial challenge of jointly pricing rentals and sales increasingly relevant. Rental and sales prices are interdependent not only because consumers can choose between the two options, but also because a customer may rent before purchasing. Given these considerations and allowing for consumer uncertainty, we analyze the optimal joint pricing of product rentals and sales. We show that when consumers have a relatively high probability of liking a product and will experience a significant drop in their post-rental residual utility, then the practice of allowing a portion of the rental price to apply to a future purchase is optimal.
{"title":"Pricing Joint Sales and Rentals: When are Purchase-Conversion Discounts Optimal?","authors":"M. Jalili, Michael S. Pangburn","doi":"10.2139/ssrn.3251599","DOIUrl":"https://doi.org/10.2139/ssrn.3251599","url":null,"abstract":"Product sales and rentals often occur in parallel, allowing customers to choose their preferred option. In settings where consumers face significant valuation uncertainty, rentals also provide a mechanism for consumers to discover whether they like a product. For some products, such as movies and books, the rental option may yield a significant proportion of the utility associated with ownership. The convenience of renting products in digital forms (e.g., e-books) makes the managerial challenge of jointly pricing rentals and sales increasingly relevant. Rental and sales prices are interdependent not only because consumers can choose between the two options, but also because a customer may rent before purchasing. Given these considerations and allowing for consumer uncertainty, we analyze the optimal joint pricing of product rentals and sales. We show that when consumers have a relatively high probability of liking a product and will experience a significant drop in their post-rental residual utility, then the practice of allowing a portion of the rental price to apply to a future purchase is optimal.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122165230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Manufacturers routinely rely on retailers to reach potential customers. Concurrently, they often offer low-price guarantees (LPGs) to customers who purchase through their direct channel. That is, should consumers find a lower price from distribution partners, manufacturers promise to match or even beat the lower price. Many manufacturers, such as Apple, Dell, Hewlett-Packard, Lenovo, and Goodyear, use price-matching guarantees (PMGs) against retailers. In the online travel industry, price-beating guarantees (PBGs) are prevalent among travel suppliers. In this paper, we develop a game-theoretic model to investigate the manufacturer's optimal choice of LPG policies and its implications for the manufacturer, retailer, and channel. Our analysis demonstrates that no LPG, PMG, and PBG can each emerge in equilibrium depending on consumer characteristics. While LPGs can improve channel profit, they may benefit the manufacturer at the expense of the retailer. As such, LPGs can intensify vertical channel conflict. However, both horizontal channel conflict and vertical channel conflict are present in dual channels. LPGs are not merely price discrimination device, they mitigate horizontal channel conflict. The benefit of LPGs in reducing horizontal channel conflict outweighs the loss from intensified vertical channel conflict under a wide range of conditions. Therefore, LPGs serve as channel coordination devices.
{"title":"Low-Price Guarantees in a Dual-Channel of Distribution","authors":"Juncai Jiang, Chuan He","doi":"10.2139/ssrn.3651349","DOIUrl":"https://doi.org/10.2139/ssrn.3651349","url":null,"abstract":"Manufacturers routinely rely on retailers to reach potential customers. Concurrently, they often offer low-price guarantees (LPGs) to customers who purchase through their direct channel. That is, should consumers find a lower price from distribution partners, manufacturers promise to match or even beat the lower price. Many manufacturers, such as Apple, Dell, Hewlett-Packard, Lenovo, and Goodyear, use price-matching guarantees (PMGs) against retailers. In the online travel industry, price-beating guarantees (PBGs) are prevalent among travel suppliers. In this paper, we develop a game-theoretic model to investigate the manufacturer's optimal choice of LPG policies and its implications for the manufacturer, retailer, and channel. Our analysis demonstrates that no LPG, PMG, and PBG can each emerge in equilibrium depending on consumer characteristics. While LPGs can improve channel profit, they may benefit the manufacturer at the expense of the retailer. As such, LPGs can intensify vertical channel conflict. However, both horizontal channel conflict and vertical channel conflict are present in dual channels. LPGs are not merely price discrimination device, they mitigate horizontal channel conflict. The benefit of LPGs in reducing horizontal channel conflict outweighs the loss from intensified vertical channel conflict under a wide range of conditions. Therefore, LPGs serve as channel coordination devices.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117048279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
How has the COVID-19 pandemic affected the consumption of audio music streaming?
新冠肺炎疫情对音频音乐流媒体的消费有何影响?
{"title":"Virus Shook the Streaming Star: Estimating the COVID-19 Impact on Music Consumption","authors":"J. Sim, D. Cho, Youngdeok Hwang, Rahul Telang","doi":"10.2139/ssrn.3649085","DOIUrl":"https://doi.org/10.2139/ssrn.3649085","url":null,"abstract":"How has the COVID-19 pandemic affected the consumption of audio music streaming?","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123002663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
During my last conversation with Masanao Aoki, he told me that the concept of non-self averaging in statistical physics, frequently appearing in economic and financial systems, has important consequences to policy implication. Zipf's law in firms-size distribution is one of such examples. Recent Malevergne, Saichev and Sornette (MSS) model, simple but realistic, gives a framework of stochastic process including firms entry, exit and growth based on Gibrat's law of proportionate effect, and shows that the Zipf's law is a robust consequence. By using the MSS model, I would like to discuss about the breakdown of Gibrat's law and the deviation from Zipf's law, often observed for the regime of small and medium firms. For the purpose of discussion, I recapitulate the derivation of exact solution for the MSS model with some correction and additional information on the distribution for the age of existing firms. I argue that the breakdown of Gibrat's law is related to the underlying network of firms, most notably production network, in which firms are mutually correlated among each other leading to the larger volatility in the growth for smaller firms that depend as suppliers on larger customers.
{"title":"Firms Growth, Distribution, and Non-Self Averaging Revisited","authors":"Y. Fujiwara","doi":"10.2139/ssrn.3644742","DOIUrl":"https://doi.org/10.2139/ssrn.3644742","url":null,"abstract":"During my last conversation with Masanao Aoki, he told me that the concept of non-self averaging in statistical physics, frequently appearing in economic and financial systems, has important consequences to policy implication. Zipf's law in firms-size distribution is one of such examples. Recent Malevergne, Saichev and Sornette (MSS) model, simple but realistic, gives a framework of stochastic process including firms entry, exit and growth based on Gibrat's law of proportionate effect, and shows that the Zipf's law is a robust consequence. By using the MSS model, I would like to discuss about the breakdown of Gibrat's law and the deviation from Zipf's law, often observed for the regime of small and medium firms. For the purpose of discussion, I recapitulate the derivation of exact solution for the MSS model with some correction and additional information on the distribution for the age of existing firms. I argue that the breakdown of Gibrat's law is related to the underlying network of firms, most notably production network, in which firms are mutually correlated among each other leading to the larger volatility in the growth for smaller firms that depend as suppliers on larger customers.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116448326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A marketplace such as Amazon hosts a variety of products by third party sellers and acts as a first party or private label retailer. Assuming an advantage of Amazon in logistics and of sellers in marketing, we investigate whether entry by Amazon is excessive from the point of view of consumers (as through self-preferencing to win the Featured Offer position or promote its own products). With competitive sellers, entry may be either over-provided or under-provided, but the incentives of Amazon and consumers are correctly aligned for a family of power surplus functions (generating for instance linear, isoelastic and log-linear demands). Platform competition for customers reduces commissions and prices preserving the efficiency result. Market power by sellers increases (reduces) the incentives to retail private label (first party) products, and generates a bias toward under-provision of entry. We also study issues related to delivery fulfillment by Amazon, advertising and dynamic incentives to launch products on the platform.
{"title":"Product Selection in Online Marketplaces","authors":"Federico Etro","doi":"10.2139/ssrn.3641307","DOIUrl":"https://doi.org/10.2139/ssrn.3641307","url":null,"abstract":"A marketplace such as Amazon hosts a variety of products by third party sellers and acts as a first party or private label retailer. Assuming an advantage of Amazon in logistics and of sellers in marketing, we investigate whether entry by Amazon is excessive from the point of view of consumers (as through self-preferencing to win the Featured Offer position or promote its own products). With competitive sellers, entry may be either over-provided or under-provided, but the incentives of Amazon and consumers are correctly aligned for a family of power surplus functions (generating for instance linear, isoelastic and log-linear demands). Platform competition for customers reduces commissions and prices preserving the efficiency result. Market power by sellers increases (reduces) the incentives to retail private label (first party) products, and generates a bias toward under-provision of entry. We also study issues related to delivery fulfillment by Amazon, advertising and dynamic incentives to launch products on the platform.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132931798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a structural econometric model in which listings in an Airbnb market differ not only in their attributes, but also in their seller’s characteristics as trust indicators. Applying the model to Stockholm’s Airbnb market reveals that hosts’ attributes significantly affect market performance. Simulations of market scenarios show that the very high review scores and the Superhost certification help Airbnb compete with hotels and increase its market welfare. We also show that the “Airbnb plus” luxury program, which makes the apartments a closer substitute for hotels, leads to an increase in Airbnb’s market welfare. Our analysis provides a framework for understanding the full impact of the different attributes of the products, their providers and their management in the sharing-economy accommodation market.
{"title":"Exploring the Role of Trust Indicators in the P2P Economy: Analysis and Simulations of an Airbnb Market","authors":"A. Fleischer, E. Ert, Z. Bar-Nahum","doi":"10.2139/ssrn.3683366","DOIUrl":"https://doi.org/10.2139/ssrn.3683366","url":null,"abstract":"We propose a structural econometric model in which listings in an Airbnb market differ not only in their attributes, but also in their seller’s characteristics as trust indicators. Applying the model to Stockholm’s Airbnb market reveals that hosts’ attributes significantly affect market performance. Simulations of market scenarios show that the very high review scores and the Superhost certification help Airbnb compete with hotels and increase its market welfare. We also show that the “Airbnb plus” luxury program, which makes the apartments a closer substitute for hotels, leads to an increase in Airbnb’s market welfare. Our analysis provides a framework for understanding the full impact of the different attributes of the products, their providers and their management in the sharing-economy accommodation market.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127299576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Boxiao Chen, D. Simchi-Levi, Yining Wang, Yuanshuo Zhou
We consider the periodic review dynamic pricing and inventory control problem with fixed ordering cost. Demand is random and price dependent, and unsatisfied demand is backlogged. With complete demand information, the celebrated [Formula: see text] policy is proved to be optimal, where s and S are the reorder point and order-up-to level for ordering strategy, and [Formula: see text], a function of on-hand inventory level, characterizes the pricing strategy. In this paper, we consider incomplete demand information and develop online learning algorithms whose average profit approaches that of the optimal [Formula: see text] with a tight [Formula: see text] regret rate. A number of salient features differentiate our work from the existing online learning researches in the operations management (OM) literature. First, computing the optimal [Formula: see text] policy requires solving a dynamic programming (DP) over multiple periods involving unknown quantities, which is different from the majority of learning problems in OM that only require solving single-period optimization questions. It is hence challenging to establish stability results through DP recursions, which we accomplish by proving uniform convergence of the profit-to-go function. The necessity of analyzing action-dependent state transition over multiple periods resembles the reinforcement learning question, considerably more difficult than existing bandit learning algorithms. Second, the pricing function [Formula: see text] is of infinite dimension, and approaching it is much more challenging than approaching a finite number of parameters as seen in existing researches. The demand-price relationship is estimated based on upper confidence bound, but the confidence interval cannot be explicitly calculated due to the complexity of the DP recursion. Finally, because of the multiperiod nature of [Formula: see text] policies the actual distribution of the randomness in demand plays an important role in determining the optimal pricing strategy [Formula: see text], which is unknown to the learner a priori. In this paper, the demand randomness is approximated by an empirical distribution constructed using dependent samples, and a novel Wasserstein metric-based argument is employed to prove convergence of the empirical distribution. This paper was accepted by J. George Shanthikumar, big data analytics.
研究了具有固定订货成本的定期评审、动态定价和库存控制问题。需求是随机的，依赖于价格，未满足的需求积压。在需求信息完全的情况下，证明了著名的[公式:见文]策略是最优的，其中s和s分别是订货策略的再订货点和订货水平，[公式:见文]是现货库存水平的函数，表征了定价策略。在本文中，我们考虑了不完全的需求信息，并开发了在线学习算法，该算法的平均利润接近于具有紧[公式:见文]遗憾率的最优[公式:见文]。我们的工作与运营管理(OM)文献中现有的在线学习研究有许多显著的特点。首先，计算最优策略需要解决涉及未知数量的多个周期的动态规划(DP)问题，这与OM中大多数只需要解决单周期优化问题的学习问题不同。因此，通过DP递归建立稳定性结果是具有挑战性的，我们通过证明利润-走函数的一致收敛来完成。分析多个时期的动作依赖状态转移的必要性类似于强化学习问题，比现有的强盗学习算法困难得多。其次，定价函数[公式:见文]是无限维的，接近它比接近现有研究中有限数量的参数要困难得多。需求-价格关系基于上置信区间估计，但由于DP递推的复杂性，无法明确计算置信区间。最后，由于[公式:见文]政策的多周期性质，需求随机性的实际分布在确定最优定价策略[公式:见文]方面起着重要作用，这对于学习者先验来说是未知的。本文用依赖样本构造的经验分布来近似需求随机性，并采用一种新颖的基于度量的Wasserstein论证来证明经验分布的收敛性。本文被大数据分析J. George Shanthikumar接受。
{"title":"Dynamic Pricing and Inventory Control with Fixed Ordering Cost and Incomplete Demand Information","authors":"Boxiao Chen, D. Simchi-Levi, Yining Wang, Yuanshuo Zhou","doi":"10.2139/ssrn.3632475","DOIUrl":"https://doi.org/10.2139/ssrn.3632475","url":null,"abstract":"We consider the periodic review dynamic pricing and inventory control problem with fixed ordering cost. Demand is random and price dependent, and unsatisfied demand is backlogged. With complete demand information, the celebrated [Formula: see text] policy is proved to be optimal, where s and S are the reorder point and order-up-to level for ordering strategy, and [Formula: see text], a function of on-hand inventory level, characterizes the pricing strategy. In this paper, we consider incomplete demand information and develop online learning algorithms whose average profit approaches that of the optimal [Formula: see text] with a tight [Formula: see text] regret rate. A number of salient features differentiate our work from the existing online learning researches in the operations management (OM) literature. First, computing the optimal [Formula: see text] policy requires solving a dynamic programming (DP) over multiple periods involving unknown quantities, which is different from the majority of learning problems in OM that only require solving single-period optimization questions. It is hence challenging to establish stability results through DP recursions, which we accomplish by proving uniform convergence of the profit-to-go function. The necessity of analyzing action-dependent state transition over multiple periods resembles the reinforcement learning question, considerably more difficult than existing bandit learning algorithms. Second, the pricing function [Formula: see text] is of infinite dimension, and approaching it is much more challenging than approaching a finite number of parameters as seen in existing researches. The demand-price relationship is estimated based on upper confidence bound, but the confidence interval cannot be explicitly calculated due to the complexity of the DP recursion. Finally, because of the multiperiod nature of [Formula: see text] policies the actual distribution of the randomness in demand plays an important role in determining the optimal pricing strategy [Formula: see text], which is unknown to the learner a priori. In this paper, the demand randomness is approximated by an empirical distribution constructed using dependent samples, and a novel Wasserstein metric-based argument is employed to prove convergence of the empirical distribution. This paper was accepted by J. George Shanthikumar, big data analytics.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"322 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116770252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates search and matching in online marketplaces, emphasizing how user behavior responds to the presence of others on the platform, which I call ``market thickness". Unlike standard settings in which firms typically benefit from increasing their customer base, in two-sided markets, changes in market thickness can induce complex effects in matching due to the endogenous adjustment of search and selectivity. This paper explores how changes in one side of the marketplace can affect the platform as a whole by causally measuring the independent effects of market size and competition size on behavior. I implement a field experiment that varies information sent to platform participants about the number of potential matches (market size) and number of competitors. I use this experimentally-induced variation to estimate the parameters of a microfounded model to measure general equilibrium matching outcomes. Consistent with intuition and observational patterns, individuals generally become more selective when they are told they have more potential matches, and less selective when they are told they have more competition. I find that an increase in market size does not necessarily increase match quality due to heterogeneous effects of market thickness on selectivity. I then show how changing selectivity by adjusting the cost of sending match proposals may mitigate negative effects of changes in market and competition size.
{"title":"Search, Selectivity, and Market Thickness in Two-Sided Markets: Evidence from Online Dating","authors":"Jessica Fong","doi":"10.2139/ssrn.3458373","DOIUrl":"https://doi.org/10.2139/ssrn.3458373","url":null,"abstract":"This paper investigates search and matching in online marketplaces, emphasizing how user behavior responds to the presence of others on the platform, which I call ``market thickness\". Unlike standard settings in which firms typically benefit from increasing their customer base, in two-sided markets, changes in market thickness can induce complex effects in matching due to the endogenous adjustment of search and selectivity. This paper explores how changes in one side of the marketplace can affect the platform as a whole by causally measuring the independent effects of market size and competition size on behavior. I implement a field experiment that varies information sent to platform participants about the number of potential matches (market size) and number of competitors. I use this experimentally-induced variation to estimate the parameters of a microfounded model to measure general equilibrium matching outcomes. Consistent with intuition and observational patterns, individuals generally become more selective when they are told they have more potential matches, and less selective when they are told they have more competition. I find that an increase in market size does not necessarily increase match quality due to heterogeneous effects of market thickness on selectivity. I then show how changing selectivity by adjusting the cost of sending match proposals may mitigate negative effects of changes in market and competition size.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126400972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Does uncertainty about future wholesale prices facilitate coordination? We address this question in the context of the Chilean retail-gasoline industry, where a policy intervention (Mepco) limited the week-to-week variation of wholesale prices. First, we show that Mepco caused a decrease in retail-gasoline margins in Chile. Second, using price leadership intensity as a proxy for the strength of coordination in a market, we show that margins decreased more in markets with higher leadership intensity. We rationalize these findings in a repeated-game framework, showing that a reduction in uncertainty about future wholesale prices hinders price coordination incentives, and has a greater impact in more coordinated markets.
{"title":"Price Leadership and Uncertainty about Future Costs","authors":"Jorge Lemus, Fernando Luco","doi":"10.2139/ssrn.3186144","DOIUrl":"https://doi.org/10.2139/ssrn.3186144","url":null,"abstract":"Does uncertainty about future wholesale prices facilitate coordination? We address this question in the context of the Chilean retail-gasoline industry, where a policy intervention (Mepco) limited the week-to-week variation of wholesale prices. First, we show that Mepco caused a decrease in retail-gasoline margins in Chile. Second, using price leadership intensity as a proxy for the strength of coordination in a market, we show that margins decreased more in markets with higher leadership intensity. We rationalize these findings in a repeated-game framework, showing that a reduction in uncertainty about future wholesale prices hinders price coordination incentives, and has a greater impact in more coordinated markets.","PeriodicalId":150569,"journal":{"name":"IO: Theory eJournal","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121489101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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