Massachusetts is known to be a leader in health policy innovation, especially its near-universal insurance coverage and national benchmark on health care cost growth. However, despite such an advanced policy infrastructure, the Commonwealth is still experiencing increased health care expenditure, limited access to primary care, and long-standing disparities in health outcomes. Current policy studies rightly identify the causes of cost increase, such as administrative complexity, price dispersion, unnecessary utilization, and endemic under-investment in primary care, but fail to go further to identify a structural failure underlying that: the lack of care delivery designs that can transform cost standards into operational change at the point of care. This paper will contend that Massachusetts has exhausted reforms that are focused on measurement, accountability, and refinement of policies in small steps. The second step of reform needs to be a transition to cost benchmarks as retrospective control systems into the intentional design of primary care as an architectural form of care- one that coordinates legal authority, administrative form, workforce placement and payment models around access, equity, and cost containment all at the same time. Based on health policy analysis, health law, health economics, and administrative realities guided by national medical group benchmarks, the paper illustrates why cost containment strategies have not increased access and reduced inequity despite a wide agreement on underlying causes. It determines the structural contradictions inherent in existing delivery models and demonstrates how administrative complexity, misaligned payment, and fragmented governance serve as hidden taxes on access. The conclusion of the analysis is that a sustainable reform within cost growth limits demands rethinking primary care not as a collection of services or care locations, but as a care architecture. In the absence of this change, cost benchmarks will persist as diagnostic, but not system transformation tools, and the policy leadership of Massachusetts will not be connected to lived patient and provider experience.

Abstract Empirical studies find that the pass-through of input cost changes to prices is incomplete: a 10 percent increase in costs causes downstream prices to rise less than 10 percent, even at long horizons. Using microdata from gas stations, food products, and manufacturing industries, we find that incomplete pass-through in percentages often disguises complete pass-through in levels: a $1/unit increase in input costs leads to $1/unit higher downstream prices. Pass-through appears incomplete in percentages due to a gap between prices and costs. Complete pass-through in levels contrasts with workhorse macroeconomic models that feature homothetic demand systems. We identify an alternative class of demand systems that yields pass-through in levels and highlight four implications. First, measuring pass-through in percentages can lead to spurious evidence of asymmetry and size-dependence. Second, pass-through in levels leads to systematic fluctuations in relative price and markup dispersion that are not associated with changes in allocative efficiency. Third, pass-through in levels can explain dynamics of industry gross margins, operating profits, and entry in the data that are at odds with workhorse models. Finally, incorporating pass-through in levels into an input-output model of the U.S. economy better matches the volatility of consumer price inflation and the response of inflation to identified shocks.

This study applies Prospect Theory to examine how star rating classification affects the relationship between price dispersion, price fairness, and customers' decisions when choosing a hotel and booking channel. Data were collected from 207 hotel customers using Trivago’s metasearch engine in a scenario-based experimental design to test the hypotheses. The findings show that star ratings significantly influence hotel booking choices, with customers favouring cheaper options in wide price dispersion scenarios and more expensive options in narrow price dispersion scenarios. This study contributes to the literature by extending Prospect Theory to metasearch platforms and revealing how star ratings moderate the effects of price dispersion and fairness on the booking channel. The results provide valuable insights for hotel managers and online travel agency practitioners in developing effective marketing and pricing strategies.

ABSTRACT We study the pricing of homogeneous products sold to customers who consider different sets of suppliers. We identify prices that are stable in the sense that no firm wishes to undercut a rival or to raise its price when rivals are able to respond by offering special deals. We derive stable and dispersed prices across several price‐consideration specifications. We contrast the implications against those of conventional approaches.

ABSTRACT This article investigates the short-term impact of the Alitalia–ITA Airways transition on pricing strategies and market competition in the Italian domestic air transport sector. Using a novel dataset simulating over 21,000 ticket purchases before and after ITA’s market entry, we apply a difference-in-difference approach combined with propensity score matching to estimate the causal effect of this ownership transition. Our results show a significant fare reduction of approximately 25% on affected routes, driven by ITA’s more competitive pricing and reduced intertemporal price dispersion. The study also documents heterogeneous reactions among competing airlines, particularly Ryanair. These findings provide new empirical evidence on how structural changes in flag carrier ownership affect market dynamics, raising important considerations for competition policy and future regulatory design.

Transparency, Repricing, and Price Convergence in Cancer Care.

This study analyzes the determinants of prices for small and medium-sized buildings in Gangnam-gu, Seoul, using actual transaction data and examines how these determinants differ across price levels by jointly applying OLS and quantile regression. The dataset comprises 332 transactions concluded between January 2021 and May 2022, and the hedonic price model includes building, location, and land characteristics, as well as buyer attributes (corporate and non-Seoul buyers), the retail area ratio, and franchise presence. The OLS results show that land and location factors—such as land area, road width, zoning, and subway accessibility—have statistically significant effects on prices, and that buyer characteristics and the retail area ratio also play important roles in explaining small and medium-sized building prices. The quantile regression results indicate that number of floors, land area, road width, subway accessibility, and the retail area ratio consistently emerge as key variables across all quantiles, whereas basement presence, proximity to transfer stations, specific administrative districts, zoning, and buyer characteristics exhibit heterogeneous signs and significance depending on the price level. In particular, corporate buyers have a positive effect on prices on average but a negative effect in the lower-price segment, suggesting that they leverage superior information and bargaining power to acquire properties at relatively lower prices, while non-Seoul buyers show a negative effect on average but a positive effect across all quantiles, indicating a tendency to pay higher prices for small and medium-sized buildings due to the anchoring effect and search costs. By combining OLS and quantile regression, this study provides a multifaceted view of the price structure in the small and medium-sized building market and empirically identifies price- segment-specific features that cannot be captured by mean-based approaches alone. It also demonstrates that, for assets with substantial price dispersion, it is necessary to complement OLS analysis with quantile regression to investigate price-quantile-specific determinants.

Seasonal price volatility of agricultural commoditiesposes significant challenges to farmers and market stakeholdersin Nepal due to climate variability, supply disruptions, andlimited access to predictive market information. This studyanalyzes long-term seasonal price behavior using daily wholesaleprice data from Kalimati Tarkari Bazaar spanning 2013–2023.Machine learning and time-series techniques including FacebookProphet, logistic regression, STL decomposition, and K-meansclustering are employed to examine seasonal patterns, pricevolatility, and future price trends across six Nepali seasons.The results reveal strong and consistent seasonal dependencies,with most vegetables exhibiting peak prices during winter (Hemanta) and lower prices during the monsoon (Barsha). Prophetbased forecasting demonstrates moderate predictive performancewith an average MAE of 32.95 and an average R² of 0.42,effectively capturing trend and seasonal components for mostcommodities. Volatility analysis identifies high-risk commoditieswith substantial price dispersion, while clustering reveals distinctmarket segments based on price levels and variability. Thefindings highlight the importance of seasonal awareness and datadriven forecasting in improving production planning, marketparticipation, and policy formulation in Nepal’s agriculturalsector.

Global energy markets have experienced persistent dispersion in real energy prices, creating structural competitiveness pressures that standard indicators often fail to capture in real time. These pressures have intensified as energy-intensive sectors face asymmetric exposure across advanced and emerging economies. This study addresses two critical gaps in international energy cost competitiveness. The first is a frequency gap: conventional indicators such as the Real Unit Energy Cost (RUEC) are typically published with delays of 2–5 years, limiting their usefulness for timely policy evaluation. Here, both RUEC and the Real Price Level Index for energy (Real PLI)—the ratio of the Purchasing Power Parity (PPP) for energy to that for GDP—are measured with only a 2–3-month lag for nine countries—four in Asia, four in Europe, and the U.S. The second is a competitiveness gap that calls for policy responses. Real PLIs indicate that the energy price disadvantages of Japan, Korea, France, Germany, Italy, and the UK have widened from 1.76–2.91 times the U.S. level before the pandemic to 2.14–3.28 times by Q3 2025, with the gaps relative to China and India also widening. Once country-specific thresholds are exceeded, output in energy-intensive and trade-exposed (EITE) industries tends to contract disproportionately. These findings highlight that sustainable transitions require not only internationally differentiated burden-sharing but also structural reforms to avoid persistent widening of energy price gaps. The Real PLI framework provides a timely indicator of competitiveness and an early-warning tool, signaling when growing asymmetries may undermine policy feasibility. Policy implications include the need to monitor real energy price dispersion as a core source of competitiveness risk, to strengthen structural measures that stabilize marginal energy costs, and to design transition pathways that account for heterogeneous adjustment pressures across countries.

ABSTRACT This article examines effects of internet search technologies on match‐quality markets. A model in which sellers of unusual objects wait for high‐value buyers illustrates how more efficient search may simultaneously increase price levels, price dispersion, and social welfare. A reduced‐form analysis of the used‐book market finds support for several nuanced model predictions. Estimates from a novel structural framework indicate the shift to online sales more than doubled social welfare, with gains roughly evenly split between booksellers and consumers. Amazon's acquisition and incorporation of a used‐book marketplace spurred price competition, but appears to have had minimal welfare effects.

A rise of e-commerce has a huge impaction on individuals’ consumption behaviors. Many factors may explain its influence, but the relative economic theory is significant to be aware of for a better development in terms of national well-being. We used equilibrium price, Network Effect and the Price Dispersion model to indicate how online stores may benefit consumers through their specific characters such as organized information and comparatively low prices. By comparing models given different variables (variables in each model differed based on its corresponded market) and sketching their relative distribution functions, we observed that when the number of informed consumers increases, more shops would choose to set relatively low prices for their selling goods given there are both online and offline stores in the market. In addition, by applying the price dispersion model, we notice consumers would be better off in general when there is an increased quantity of online stores in the market. We also found online retail market decreases individuals’ valuation of offline store products. Thus, online stores benefit consumers by providing various choices and cheap products, which the offline stores would also follow. In this condition, consumers in general would be benefits from the online store in both online and offline purchase channel, respectively.

Intertemporal price dispersion: The role of competition

The rise of digital platforms has profoundly transformed modern markets, particularly through the deployment of algorithmic pricing strategies powered by big data. As firms increasingly rely on sophisticated algorithms to set prices dynamically, questions arise about the implications for market efficiency and consumer welfare. This paper explores how algorithmic pricing, when implemented on data-rich digital platforms, affects competitive behavior, price transparency, and consumer outcomes. While algorithmic systems can theoretically enhance efficiency by matching prices more closely to real-time demand and supply conditions, they may also facilitate tacit collusion, reduce price dispersion, and undermine traditional competitive dynamics. The power of big data enables platforms to segment consumers, personalize prices, and predict purchasing behavior with unprecedented accuracy, raising concerns about fairness, privacy, and market manipulation. Additionally, the opacity of algorithmic processes poses regulatory challenges in ensuring that pricing strategies align with pro-competitive principles and consumer protection goals. This study contributes to the growing discourse on the economic consequences of digitalization by examining how algorithmic pricing impacts allocative efficiency, price stability, and surplus distribution. Ultimately, the paper underscores the dual potential of these technologies to foster innovation and efficiency while also risking distortions that may harm consumer welfare and weaken competition in increasingly data-driven markets.

How does COVID-19 affect intertemporal price discrimination and price dispersion? Evidence from the airline industry

Housing price dispersion highlights the individual differences in capital gains by capturing the varying prices among comparable properties. We examine the impact of investors’ activities on housing price dispersion within the Hong Kong private housing market, based on micro-level transactions. Our results indicate that investors’ activities can significantly lower price dispersion in housing markets, even after accounting for trading volumes. The reduction effect of investment activities on price dispersion varies across boom-bust cycles, being more pronounced in cooler markets. We address the roles of housing investors in facilitating the price discovery process and reducing price dispersion by providing liquidity and mitigating information asymmetry. This suggests that well-informed investors can play a welfare-enhancing role by improving information efficiency. We also demonstrate that nearby investment activities can indirectly influence local price dispersion through information spillover effects. Our findings have profound implications for facilitating information efficiency and the potential for reducing price dispersion.

The proliferation of broadband internet has sparked concerns about the future of brick-and-mortar retail. This article explores consumer behavior in the U.S. consumer packaged goods sector during broadband's proliferation from 2004 to 2019. Using household panel and retail scanner data covering more than 40,000 brands in 900 categories, the author analyzes nine household and retailer outcomes: brands purchased, trips taken, retailers visited, offline spending, any online spending, online spending share, prices, price dispersion, and demand elasticities. The author combines U.S. Census and Federal Communications Commission data to track the rollout of broadband. In contrast to established notions that broadband adoption would rapidly transform shopping behaviors in this period, the findings reveal a more nuanced and gradual pattern of change. Exploiting geographic variation in broadband growth, the author finds economically modest average effects with significant heterogeneity by age and household income. The analysis reveals generational differences: sharp declines in brick-and-mortar shopping among younger consumers counterbalanced by relative stability in larger older cohorts. In short, this article finds that broadband access drove a gradual evolution in consumer behavior, rather than a dramatic upheaval.

This paper studies the impact of imperfect competition on life-cycle consumption profiles and consumption-risk sharing, along with its policy implications. We develop a framework by incorporating the Shapley-Shubik market game into a stochastic overlapping generations model. We characterize the inverse income-marginal price relationship under market power, where wealthy agents face lower prices for identical goods compared to a perfectly competitive economy. We present several novel findings due to the additional price effect channel arising from price dispersion. First, we show that income-dependent prices in an imperfectly competitive economy lead to a failure of consumption smoothing and generate hump-shaped consumption profiles without other frictions. We also demonstrate that the market power of agents increases consumption volatility and worsens consumption-risk sharing due to the double luck effect resulting from price dispersion caused by income shocks. The additional volatility from imperfect competition creates a complementary welfare loss. Lastly, we illustrate a severed link between fiscal and monetary policy in improving welfare in an imperfectly competitive economy, as monetary policies reinforce the inverse income-price relationship and adversely affect the poor, while fiscal policies do not.

Price dispersion and price stickiness in a competitive search model of housing markets

Abstract Brown rice has many advantages over white rice, and it is thus sold in e-commerce at a higher price than white rice. Consumers who buy the product know that brown rice is offered at various price levels. Consumers can quickly choose products through their preferences by reading descriptions that can be rapidly seen on the mobile screen. Price variations on a particular product type can indicate production and handling costs. Research on brown rice price behavior aimed to investigate and analyze the dispersions of prices in Java and outside Java as online sales attributes. The methods used were a two-sample unpaired t-test and Moderated Regression Analysis (MRA) using numbers of products as moderated variables. The analysis revealed that sales were influenced by store performance, which could be examined from ratings, number of stars, availability of photos and videos, and seller location. The number of products on display did not affect brown rice purchases because consumers who bought brown rice were willing to pay more for a healthier life. The selling price of brown rice was distinct and varied due to differences in location, Java, and outside Java, although markets tend to be perfect. There was price dispersion for the same brand and quantity for e-commerce. The profit expectation of the seller also determined the price variation. Competition with other sellers would constrain price increases if the product did not have special specifications that were very different from similar products in the market.

An Analysis of Radiology Procedure Price Variation in Children's Hospitals Between 2023 and 2024: Hospital Price Transparency in Action.