Matching Returning Donors to Projects on Philanthropic Crowdfunding Platforms

We propose an approach to match returning donors to fundraising campaigns on philanthropic crowdfunding platforms. It is based on a structural econometric model of utility-maximizing donors who can derive both altruistic (from the welfare of others) and egoistic (from personal motivations) utilities from donating—a unique feature of philanthropic giving. We estimate our model using a comprehensive data set from DonorsChoose.org—the largest crowdfunding platform for K–12 education. We find that the proposed model more accurately identifies the projects that donors would like to donate to on their return in a future period, and how much they would donate, than popular personalized recommendation approaches in the literature. From the estimated model, we find that primarily egoistic factors motivate over two-thirds of the donations, but, over the course of the fundraising campaign, both motivations play a symbiotic role: egoistic motivations drive the funding in the early stages of a campaign when the viability of the project is still unclear, whereas altruistic motivations help reach the funding goal in the later stages. Finally, we design a recommendation policy using the proposed model to maximize the total funding each week considering the needs of all projects and the heterogeneous budgets and preferences of donors. We estimate that over the last 14 weeks of the data period, such a policy would have raised 2.5% more donation, provided 9% more funding to the projects by allocating them to more viable projects, funded 17% more projects, and provided 15% more utility to the donors from the donations than the current system. Counterintuitively, we find that the policy that maximizes total funding each week leads to higher utility for the donors over time than a policy that maximizes donors’ total utility each week. The reason is that the funding-maximizing policy focuses donations on more viable projects, leading to more funded projects, and, ultimately, higher realized donors’ utility. This paper was accepted by Kartik Hosanagar, information systems.

Is there a market power in the Philippine Rice Industry?

Rice, as a staple food for the Filipinos, is widely studied from production to consumption. However, observations of the National Food Authority domestic procurement and price stabilization policy, as well as results of the marketing and market-related studies, still reveal some gaps which call forth for an in-depth investigation and analysis. One ofthese is the possible presence ofmarket power, a market inefficiency in rice. Hence, this study aimed to ascertain the presence of market power in the Philippine rice industry. Secondary data published by the Philippine Statistics Authority from 1990 to 2015 were utilized. A structural econometric model using a time series approach was used in estimating the presence of market power. Results revealed the presence of market power in non-major rice-producing regions for well-milled and regular-milled rice in major rice-producing areas. The more the demand curve becomes inelastic the more the market power becomes apparent. The price elasticity of demand in the non-major rice-producing regions is -0.63 for both well-milled and regular-milled rice and -0.83 and -0.59, respectively, in the major rice producing areas. To minimize, if not solve market power, a substitute staple for rice may be introduced, programs/policies that will encourage more palay traders may be implemented, and farmers may be trained to operate like industry clusters.

The Use of Structural Models in Econometrics

This paper discusses the role of structural economic models in empirical analysis and policy design. The central payoff of a structural econometric model is that it allows an empirical researcher to go beyond the conclusions of a more conventional empirical study that provides reduced-form causal relationships. Structural models identify mechanisms that determine outcomes and are designed to analyze counterfactual policies, quantifying impacts on specific outcomes as well as effects in the short and longer run. We start by defining structural models, distinguishing between those that are fully specified and those that are partially specified. We contrast the treatment effects approach with structural models, and present an example of how a structural model is specified and the particular choices that were made. We cover combining structural estimation with randomized experiments. We then turn to numerical techniques for solving dynamic stochastic models that are often used in structural estimation, again with an example. The penultimate section focuses on issues of estimation using the method of moments.

On the Extent to which the Presence of Intermediate-stop(s) Air Travel Products Influences the Pricing of Nonstop Air Travel Products

Analysts of air travel markets, which include antitrust authorities, are interested in understanding the extent to which the presence of intermediate stop(s) products influences the pricing of nonstop products. This paper uses a structural econometric model to investigate the potential pricing interdependence between these two product types in domestic air travel markets. Counterfactual experiments using the estimated model suggest that in many (but far from a majority) markets the current prices of nonstop products are at least 5% lower than they would otherwise be owing to the presence of intermediate-stop(s) products.

On the Efficiency of Codeshare Contracts between Airlines: Is Double Marginalization Eliminated?

Previous research has suggested that codeshare agreements eliminate double marginalization that exists when unaffiliated airlines independently determine the price for different segments of an interline trip. Using a structural econometric model, this paper investigates whether codeshare contracts do eliminate double marginalization. The results suggest that both upstream and downstream margins persist when the operating carrier of a codeshare product also offers competing single-carrier product(s) in the concerned market. Furthermore, counterfactual simulations from the model suggest that efficient pricing of these codeshare products would lower their price, and yield nontrivial increases in consumer welfare. (JEL D86, L13, L14, L93)

Who Thinks about the Competition? Managerial Ability and Strategic Entry in US Local Telephone Markets

We examine US local telephone markets shortly after the Telecommunications Act of 1996. The data suggest that more experienced, better-educated managers tend to enter markets with fewer competitors. This motivates a structural econometric model based on behavioral game theory that allows heterogeneity in managers' ability to conjecture competitor behavior. We find that manager characteristics are key determinants in managerial ability. This estimate of ability predicts out-of-sample success. Also, the measured level of ability rises following a shakeout, suggesting that our behavioral assumptions may be most relevant early in the industry's life cycle. (JEL L96, L98, M10)

El Paso Housing Sector Econometric Forecast Accuracy

There is comparatively little empirical evidence regarding the accuracy of regional housing sector forecasts. Much of the recent analysis conducted for this topic is developed for housing starts and indicates a relatively poor track record. This study examines residential real estate forecasts previously published for El Paso, TX using a structural econometric model. Model coverage is much broader than just starts. Similar to earlier studies, the previously published econometric predictions frequently do not fare very well against the selected random walk benchmarks utilized for the various series under consideration.