A Dynamic Model of Demand for Houses and Neighborhoods

This paper develops a dynamic model of neighborhood choice along with a computationally light multi‐step estimator. The proposed empirical framework captures observed and unobserved preference heterogeneity across households and locations in a flexible way. We estimate the model using a newly assembled data set that matches demographic information from mortgage applications to the universe of housing transactions in the San Francisco Bay Area from 1994 to 2004. The results provide the first estimates of the marginal willingness to pay for several non‐marketed amenities—neighborhood air pollution, violent crime, and racial composition—in a dynamic framework. Comparing these estimates with those from a static version of the model highlights several important biases that arise when dynamic considerations are ignored.     

Consumption Commitments and Habit Formation

We analyze the implications of household‐level adjustment costs for the dynamics of aggregate consumption. We show that an economy in which agents have “consumption commitments” is approximately equivalent to a habit formation model in which the habit stock is a weighted average of past consumption if idiosyncratic risk is large relative to aggregate risk. Consumption commitments can thus explain the empirical regularity that consumption is excessively sensitive and excessively smooth, findings that are typically attributed to habit formation. Unlike habit formation and other theories, but consistent with empirical evidence, the consumption commitments model also predicts that excess sensitivity and smoothness vanish for large shocks. These results suggest that behavior previously attributed to habit formation may be better explained by adjustment costs. We develop additional testable predictions to further distinguish the commitment and habit models and show that the two models have different welfare implications.     

Benefits of Hybrid Lateral Transshipments in Multi‐Item Inventory Systems under Periodic Replenishment

Lateral transshipments are a method of responding to shortages of stock in a network of inventory‐holding locations. Conventional reactive approaches only seek to meet immediate shortages. The study proposes hybrid transshipments which exploit economies of scale by moving additional stock between locations to prevent future shortages in addition to meeting immediate ones. The setting considered is motivated by retailers who operate networks of outlets supplying car parts via a system of periodic replenishment. It is novel in allowing non‐stationary stochastic demand and general patterns of dependence between multiple item types. The generality of our work makes it widely applicable. We develop an easy‐to‐compute quasi‐myopic heuristic for determining how hybrid transshipments should be made. We obtain simple characterizations of the heuristic and demonstrate its strong cost performance in both small and large networks in an extensive numerical study.     

Information Sharing in a Manufacturer–Supplier Relationship: Suppliers' Incentive and Production Efficiency

While there have been vast discussions on the materialistic benefits of continuous improvement from the Toyota and Honda experiences, the academic literature pays little attention to information sharing. In this study, we construct a dynamic adverse selection model in which the supplier privately observes her production efficiency, and in the contractual duration the manufacturer obtains an informative but imprecise signal regarding this private efficiency. We show that despite the disclosure of proprietary information, information sharing may benefit the supplier; the supplier's voluntary participation is more likely to occur when the shared information is rather imprecise. On the other hand, our analysis also reveals that this information sharing unambiguously gives rise to an upward push of the production quantity, and may sometimes lead to an upward distortion that ultimately hurts the supply chain. We also document the non‐trivial impact of the timing of information sharing on the supplier's incentive to participate.     

Dynamic Marriage Matching: An Empirical Framework

This paper develops a new model for empirically analyzing dynamic matching in the marriage market and then applies that model to recent changes in the U.S. marriage distribution. Its primary objective is to estimate gains by age from being married today (till death of at least one spouse) relative to remaining single for that same time period. An empirical methodology that relies on the model's equilibrium outcomes identifies the marriage gains using a single cross‐section of observed aggregate matches. This behavioral dynamic model rationalizes a new marriage matching function. The model also solves the inverse problem of computing the vector of aggregate marriages, given a new distribution of available single individuals and estimated preferences. Finally, this paper develops a simple test of the model's empirical validity. Using aggregate data of new marriages and available single men and women in the United States over two decades from 1970 to 1990, I investigate the changes in marriage gains over this period.     

Inventory‐Based Dynamic Pricing with Costly Price Adjustment

We study an average‐cost stochastic inventory control problem in which the firm can replenish inventory and adjust the price at anytime. We establish the optimality to change the price from low to high in each replenishment cycle as inventory is depleted. With costly price adjustment, scale economies of inventory replenishment are reflected in the cycle time instead of lot size—An increased fixed ordering cost leads to an extended replenishment cycle but does not necessarily increase the order quantity. A reduced marginal cost of ordering calls for an increased order quantity, as well as speeding up product selling within a cycle. We derive useful properties of the profit function that allows for reducing computational complexity of the problem. For systems requiring short replenishment cycles, the optimal solution can be easily computed by applying these properties. For systems requiring long replenishment cycles, we further consider a relaxed problem that is computational tractable. Under this relaxation, the sum of fixed ordering cost and price adjustment cost is equal to (greater than, less than) the total inventory holding cost within a replenishment cycle when the inventory holding cost is linear (convex, concave) in the stock level. Moreover, under the optimal solution, the time‐average profit is the same across all price segments when the inventory holding cost is accounted properly. Through a numerical study, we demonstrate that inventory‐based dynamic pricing can lead to significant profit improvement compared with static pricing and limited price adjustment can yield a benefit that is close to unlimited price adjustment. To be able to enjoy the benefit of dynamic pricing, however, it is important to appropriately choose inventory levels at which the price is revised.     

中国粮食增产的主要因素贡献分解与实证估算

已有测算中国粮食增产要素贡献率的方法存在虚增或低估某要素贡献率的缺陷,文章通过改进粮食增产贡献率测算方法实证估计了2003—2016年期间单产、播种面积和结构调整对中国粮食增产的贡献。结果表明,中国粮食实现“十二连增”的巨大成就主要是单产增长贡献,年均贡献率50%以上,播种面积和作物内部结构调整也是不可忽视的重要力量,年均贡献率分别为30%与10%以上。然而,未来中国粮食增产依靠播种面积扩大和结构调整的空间变窄,需要探索新的增产路径。     

如何解释资本结构的调整方式和速度--基于福耀玻璃的案例分析与讨论

以现有资本结构理论为基础,试图寻找能解释各种典型公司资本结构调整方式和速度的理论框架。首先以案例分析为基础分析了主流资本结构理论对案例公司资本结构调整方式的解释程度和解释异同。然后结合公司的财务政策,定性分析了主流理论对于资本结构调整方式存在解释异同的背后原因以及将主流理论融合的理论框架。认为从资金供需的角度理解权衡理论和优序融资理论以及市场择时理论,可以将这些主流理论统一起来解释各种典型的资本结构调整方式。同时,发现以计量模型估算的资本结构调整速度推断资本结构调整到目标水平所需的时间,会误导人们对于资本结构调整方式的理解。     

贸易开放对中国水环境污染影响的实证研究

文章基于2004-2013年中国31个省市的面板数据,采用动态面板模型和差分GMM估计方法,分别选取化学需氧量排放和氨氮排放作为水环境污染的有机污染物和无机污染物的排放指标,对贸易开放的结构效应引致的中国水环境污染排放进行了实证研究.研究结果表明,经济增长的规模和技术效应是影响水环境污染排放的主要因素,直接结构效应对中国水污染排放的影响不显著,贸易开放的结构效应也在一定程度上加剧了中国水环境污染的排放.通过引入贸易开放的相关交叉项进一步对决定贸易结构效应的比较优势来源进行识别,结果发现,对于中国水环境污染排放并不存在所谓的“污染天堂效应”和“要素禀赋效应”.贸易的结构效应会导致西部经济欠发达地区的水污染排放降低,而对中东部经济相对发达地区,贸易的结构效应会引致其水污染排放量的增大和排放强度的加剧.