City Pairs Research Articles

Pollution-induced trips: Evidence from flight and train bookings in China

Utilizing a novel database including nearly 2.2 billion booking records in China, we examine whether people escape from pollution by traveling to “cleaner” places. Combining an instrumental variable approach with high-dimensional fixed effects, we find a 50-unit increase in the AQI gap between a city pair leads to a 1.30% (1.33%) increase in train and airline ticket bookings from the origin to the destination city departing within one day (2–7 days). In addition, the destination of such pollution-induced trips is more likely to be an intra-province city with more tourist attractions. We also measure willingness to pay for clean air.

Transport accessibility changes in metropolitan regions: high-speed rail connection frequency estimation

This article focuses on a very narrowly specific segment of this issue, considering the impacts of HSR in the long term, not as transport arteries connecting the most important metropolitan areas but, on the contrary, as an internal factor of development within a metropolitan region. The paper aims to transfer the present operational European HSR commuting connection frequency experience to a generally applicable frequency estimation formula. Through a quantitative approach, the research analyses the total sample of 1,446 train connections from 10 European metropolitan regions. It answers the secondary research question of what the range of accessibility change between the metropolitan core and the intermediate city is after introducing HSR connection inside metropolitan regions in the time of 1 hour of journey. The estimation model formula calculates the optimal number of HSR connections between the metropolitan core and intermediate city in the HSR developing countries. It is derived and verified from the analysed dataset values. The potential operational change scenarios are presented and described based on the example of 34 metropolitan city pairs.

Linked spatial and temporal success of urban growth boundaries to preserve ecosystem services

Urban expansion and sprawl lead to loss of green space. This has the potential to degrade natural capital and associated ecosystem services. Urban growth boundaries (UGBs) are a planning tool to delineate where growth may or may not occur as a strategy to protect green and open space.However, how these policies impact ecosystem services is unknown, particularly across multiple years. Here we compare pairs of cities: one of which has a UGB and one that does not.Specifically, we analyzed the following city pairs: (1) Lexington, KY: Huntsville, AL and (2) Portland, OR: Denver, CO. We modeled the ecosystem services provided to each city, quantifying carbon storage, pollinator abundance, urban flood risk, and urban cooling. Our results show that UGBs succeed in preserving the ecosystem services, over time, at a higher and more predictable rate than cities that do not have a UGB. Change over time highlights the effectiveness of UGBs in preserving ecosystem services overall and concentrating loss of ecosystem service delivery within highly urbanized areas. We discuss how the data necessitates analyzing spatial and temporal trends together to incorporate starting values of ecosystem service function for comparison between case studies. Natural capital and its associated ecosystem services should be key criteria for assessing policies for urban planning and used to further implement laws and policies to enhance environmental and human health within urban areas.

The effects of commuting subsidies in a competitive two-city system

This paper develops a spatial equilibrium model for a competitive two-city system consisting of a high-income and a low-income city. Using this model, we investigate the effects of intracity and intercity commuting subsidies on such urban performances as spatial structures, residents’ utility, and social welfare of cities and the system. The three unilateral subsidy scenarios and two subsidy competition scenarios are investigated individually. Results show that intercity commuting subsidy gives residents incentives to reside in the low-income city and intercity commuting to the high-income city, while intracity commuting subsidies lead to the inflow of population. Subsidy competitions increase residents’ utility and mitigate the impacts of unilateral subsidies on the social welfare of the system. A numerical example and case study based on city pairs of Jing-Jin-Ji Urban Agglomeration in China are conducted to examine the proposed model.

Night-time light loss during the 2022 Kyiv offensive revealed through VIIRS DNB

ABSTRACT The satellite low-light imagers can detect changes in nighttime lights caused by ground military conflict. The Kyiv Offensive in Kyiv, Ukraine, which lasted less than 40 days during the Russia – Ukraine conflict, began on 24 February 2022. In addition to the monthly light product, we included a daily light product to analyse the number and average intensity of light pixels in the area around Kyiv over time. The changing trends of two parameters are similar. From February to March, the number of light pixels dropped by 65.2%, and average intensity by 24.5%. To account for daily fluctuations, the relative light ratio was introduced, comparing Kyiv to Moscow, Gomel, and Warsaw. This parameter showed a significant decrease in both the number and intensity of light pixels between days 411 and 423 since January 1, 2021, aligning with the conflict’s start. The relative light ratio revealed a 70.6%, 63.5%, and 57.3% drop in light pixel numbers, and a 9.5%, 24.2%, and 48.4% drop in their average intensity for the respective city pairs. However, unusual fluctuations in the reference cities, such as in Gomel during Christmas and in Moscow at the conflict’s onset, present some problems in using the relative light ratio.

Investigating the Effects of Control Strategies of Urban Bus Systems during the early outbreak of COVID-19 epidemic in China: a Survey of 211 cities

Whether large-scale COVID-19 tightening policies related to public transit contribute to slower rises in COVID-19 infection rates remains debatable. Therefore, this article extracted text data on urban bus control strategies in 211 Chinese cities and recorded active confirmed cases per million persons per day in each city. The Kruskal-Wallis one-way ANOVA test (K samples) and accompanying pairwise comparisons were conducted using SPSS. Analysis shows that there are noticeable regional differences in the northern and southern parts of China during the pandemic in the control of public transit. Furthermore, based on the economic scale of the same population level, a comparison was made between all cities with high control intensity and some with low control intensity. We find no significant differences in the number of people diagnosed with COVID-19 between the two pairs of some of the compared cities, indicating that the public transport control strategies of some cities are overly strict and questionable. The heat maps of pairwise comparisons show that city pairs with no significant differences in the number of confirmed COVID-19 cases account for many city clusters in the same interval. Additionally, in the comparative analysis of cities with the same population base, the proportion of no significant difference in the statistical analysis results of the number of confirmed COVID-19 cases increased with the decrease of the economic level of the cities. This pattern reflects the overly strict bus control strategies of some less economically developed cities during the COVID-19 pandemic. Therefore, in the face of large-scale epidemics in the future, policies should formulate control strategies based on reality.

An Analysis of Meteorological Data in Sumatra and Nearby using Agglomerative Clustering

Sumatra is one of the biggest and the second most crowded islands in Indonesia. Sumatra is also a place of abundance of tropical flora and fauna. This paper aims to cluster the cities in Sumatra and nearby based on the meteorology data. It implements Agglomerative hierarchical clustering and uses a daily time series dataset from 17 cities from 1 January 2010 to 31 December 2023. The dataset contains variables minimum temperature, maximum temperature, average temperature, humidity, sunshine duration, and average wind speed. The preprocessing data was dedicated to managing the missing values and data aggregation to create single-form data. The single-form data contains cities and meteorological variables used as an input for the clustering algorithm, i.e. K-Means, Fuzzy C-Means, K-Medoid, intelligent K-KMeans, and Agglomerative clustering. The Agglomerative clustering outperforms other methods (i.e. K-Means, Fuzzy C-Means, K-Medoid, and intelligent K-KMeans) and produces Silhouette scores of 0.11. The clusters are then analyzed to find their unique pattern. The cut-off when the number cluster is two, Agglomerative hierarchical clustering gathers Aceh, Sabang, Pekanbaru, Padang, and Padang Lawas in Cluster 1. Other cities, i.e., Nagan Raya, Batam, Jambi, Bandar Lampung, Medan, Pangkalpinang, Palembang, Bengkulu, Belitung, Tapanuli, Deli Serdang, and Nias are in Cluster 2. The results can be briefly explained that the characteristic of Cluster 1 has a higher average temperature, lower humidity, and lower sunshine duration than cities in Cluster 2. However, Cluster 1 has a lower average minimum temperature than Cluster 2. The pairs of cities which have the most similarities are (Aceh, Sabang), (Pekanbaru, Padang Lawas), (Nagan Raya, Nias), (Jambi, Palembang), (Bengkulu, Tapanuli), and (Medan, Deli Serdang). The annual trend in several cities shows that there exists an increasing trend in minimum temperature, rising sunshine duration, and decreasing wind speed. These are signs of climate change that need a proper handling.

Synergistic regional emission reductions in China: Network evolution, spatial and temporal characteristics, and driving factor

Synergistic regional emission reduction (SRER) is an important part of the strategy to achieve carbon neutrality. In this paper, a system efficiency value-added model is proposed to measure the strength of SRER network relationships for 40,186 sets of city pairs and the SRER levels of 284 cities in China from 2011 to 2021. Subsequently, the evolution characteristics of the SRER network, the spatial and temporal characteristics of urban SRER levels, and the driving factors of the SRER network evolution are further analyzed. The results are as follows: SRER network is shifting from a fan-shaped network pattern of “three-region clustering and sporadic coverage” to a shuttle-shaped nested network pattern of “east-west linkage and multi-region support”. Time series analysis found that urban SRER level in China showed fluctuating growth characteristics during the study period. Spatial analysis reveals that the spatial autocorrelation of urban SRER level is decreasing, and the spatial distribution range is expanding towards the southwest. Emission reduction comparative advantages (CAER), green innovation division of labor (GIDL) and urban economic linkages (LCEL) are driver factors of SRER network evolution. This study proposes an evaluation method for the urban SRER level from network relationships perspective. Subsequently, network evolution characterization, spatial and temporal characterization, and driving factor analysis were conducted. The results of the study provide important theoretical guidance and inspiration for grasping the current status and enhancement paths of China's urban SRER level.

Minimum wage and the survival of hotel industry: Evidence from China

The economic impacts of the minimum wage have been the focus of ongoing conflicting debates among policymakers and researchers. Taking a sample of 69694 firms established from 2011 and 2019 in the Chinese hotel sector, we analyzed the impact of minimum wage on firm survival and the moderating effect of the digital economy. Empirical evidences show that minimum wage has a positive impact on the survival risk of hotels, and the digital economy can negatively moderate the relationship between minimum wage and the survival risk of hotels. These findings are robust when tested with the hotel data of cross-provincial city pairs, other estimation models or longer observation periods. In addition, this study finds that the impact of the minimum wage and the moderating effect of the digital economy vary with hotel types. The rise of the minimum wage has brought greater operating pressure to formal hotel enterprises, and the digital economy has a greater inhibitory effect on the relationship between the rise of the minimum wage and the survival risk of hotel enterprises in informal hotel enterprises. The results indicate that informal hotels are less adversely affected by the increasing minimum wage and benefit more from the development of the digital economy.

Game in another town: Geography of stock watchlists and firm valuation

Beyond a bias toward local stocks, investors prefer companies in certain cities over others. This study uses the geographic network of investor-followed stocks from stock watchlists to identify intercity investment preferences in China. We measure the city-pair connectivity by its likelihood of sharing an investor in common whose stock watchlist is highly concentrated in the firms of that city pair. We find that a higher connectivity-weighted aggregate stock demand-to-supply ratio across connected cities is associated with higher stock valuations, higher turnover, better liquidity, and lower cost of equity for firms in the focal city. The effects are robust to controls for geographic proximity and the broad investor base, are stronger among small firms, extend to stock return predictability, and imply excess intercity return comovement. Our results suggest that city connectivity revealed on the stock watchlist helps identify network factors in asset pricing.

Proximity and Knowledge Spillovers: Evidence from the Introduction of New Airline Routes

This paper examines the causal relationship between proximity and knowledge diffusion by estimating the elasticity of core-based statistical area (CBSA) pair-level citations to variations in travel time induced by the introduction of new flight routes. The findings reveal that decreasing travel time between U.S. cities by 20% increases knowledge flow by 0.5%, which corresponds to an increase of over 15,000 citations at the aggregate level. Rather than boosting within-firm knowledge transfer, travel time reduction leads to a rise in knowledge spillovers primarily across firm boundaries, particularly among those that form joint ventures, have block holdings in each other, or form supply chain relationships. These effects are stronger among city pairs located farther away from each other, with higher absorptive capacity, in complex technology classes, and for newly developed technologies. Additional mechanism tests suggest that the most likely channel through which travel time reduction impacts knowledge spillover is by influencing the transfer of tacit knowledge via facilitating cross-CBSA inventor flow and information acquisition. This paper was accepted by Tomasz Piskorski, finance. Funding: S. Zhou receives support from the National Natural Science Foundation of China [Grant 71804155] and China Fundamental Research Funds for the Central Universities [Grant 20720181047]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.01717 .

북한 쌀 시장의 지역 간 통합과 거래 구조

Since the 2000s, North Korea has been shifting away from a socialist planned economy towards a mixed plan-market system, marking a significant transformation in its economic approach. This research concentrates on scrutinizing the North Korean consumer goods market, with a specific focus on rice. The study encompasses nine cities (five/four in Western/Eastern region), covering the period from January 2012 to December 2021. The paper adopts a theoretical framework rooted in the efficient market hypothesis, using statistical analysis to examine absolute and relative prices. Notably, it identifies nearly perfect price parity in two pairs of cities (F-H, West and D-G, East). The relative price analysis shows that all pairs are in relative equilibrium, indicating that market integration has been established across regions. These findings offer statistical evidence of the coexistence of planned and market-based elements in the North Korean rice distribution system. In addition to price analysis, this paper delves into the North Korean rice trading network and associated transaction costs in selected regions. Consequently, this study holds substantial academic distinction, offering valuable insights into North Korea's essential goods distribution system.

Capital flows under integration: Evidence from China's metropolitan area development planning

This paper uses the introduction of metropolitan area development planning (MADP) in China to examine the effects of regional integration on capital flow in the context of intranational investment. Using the data of inter-regional capital flows that aggregated by data of listed companies in China from 1999 to 2019, we find that MADP can improve inter-regional investment substantially at the city-pair level. The mechanism analysis indicates that MADP fosters capital flow by diminishing institutional distance, erasing market segmentation, and enhancing transportation infrastructure connectivity. Furthermore, the influence of MADP on capital flows is more significant in cities endowed with robust big data application foundations, lower levels of total factor productivity (TFP), and in city pairs with no administrative borders.

Analysis of the Effectiveness of Public Health Measures on COVID-19 Transmission.

In this study, we investigate the COVID-19 epidemics in Brazilian cities, using early-time approximations of the SIR model in networks and combining the VAR (vector autoregressive) model with machine learning techniques. Different from other works, the underlying network was constructed by inputting real-world data on local COVID-19 cases reported by Brazilian cities into a regularized VAR model. This model estimates directional COVID-19 transmission channels (connections or links between nodes) of each pair of cities (vertices or nodes) using spectral network analysis. Despite the simple epidemiological model, our predictions align well with the real COVID-19 dynamics across Brazilian municipalities, using data only up until May 2020. Given the rising number of infectious people in Brazil-a possible indicator of a second wave-these early-time approximations could be valuable in gauging the magnitude of the next contagion peak. We further examine the effect of public health policies, including social isolation and mask usage, by creating counterfactual scenarios to quantify the human impact of these public health measures in reducing peak COVID-19 cases. We discover that the effectiveness of social isolation and mask usage varies significantly across cities. We hope our study will support the development of future public health measures.

An Approach for Quick Method of Estimating Passenger And Aircraft Demand for Feeder Air Services in India

The recent and the proposed entry of new airlines both in the ‘no-frills’ and in the "full service" categories has completely changed the aviation scenario in India. Obviously this explosive increase in capacity will have a profound effect on the economy of the airlines both in the short term as well as in the long-term period. A growth of over 25% per annum in passenger traffic may not be sustainable for long; thus galloping increase in capacity may result in mergers and strategic alliances of airlines on one side and closing down of some of the airlines on the other side. A point, which is to be noted is that, most of the new entrants also operate in the major trunk routes and serve the metros and the major cities. What appears to have not been tapped is the equally large potential in the regional and short haul sectors, which serve major, and small city pairs and also act as feeders to the major hubs.Realizing the importance of this, the government in its new civil aviation policy has given thrust to regional/ short-haul air travel. In this paper, an attempt is made to review the hierarchy of airline networks in India with respect to trunk, major and feeder routes. The air passenger traffic carried in terms of revenue passenger kilometers (RPK) is compared with upper class rail traffic. The present status of feeder airline services in India is outlined. It is pertinent to study the passenger traffic demand in these feeder routes as compared to upper class rail traffic as some percentage of upper class rail passengers are willing to shift to air travel due to marginal difference between airfare and upper class rail fare and time factor. The future RPKs are forecasted based on the actual RPKs data and the estimated RPKs of earlier market survey. A suitable aircraft size for airline operations in these feeder routes is arrived at based on existing air traffic data by a simplified approach from the basic principles of airline business. A macroscopic measure is used to determine the aircraft demand by assuming average block speed and utilization for each aircraft type. A sensitivity analysis was carried out for various levels of traffic growth keeping in view the sharp increase of air travel in recent years and further growth in air traffic fuelled by feeder sector as the hinterland opens up industry, services and tourism.

Leave for where? The impact of air quality on migration: Evidence at the city-pair level in China

We comprehensively explore the question of “Leave for where?” by utilizing city-pair level data of China spanning from 2011 to 2017. Our investigation focuses on the impact of disparities in air quality between city pairs on migration. we find that a 1% increase in the difference air quality between inflow and outflow locations raises the number of people migrating from the outflow to the inflow location by approximately 0.07%. This finding is robust after overcoming possible endogeneity problems with average wind speed as an instrumental variable. In addition, we conducted a heterogeneity analysis in terms of intention to migrate and individual characteristics, finding that individuals who migrated for work and family are more sensitive to differences in air quality between city pairs, whereas those who moved for business are not sensitive to differences in air quality. Regarding individual characteristics, differences in air quality between city pairs have a greater impact on the migration decisions of low-educated, female, and younger migrants. Further, a mechanistic analysis by constructing cohort dummy variables reveals that poor air quality is more motivational than the desire for good air quality and the crowding-out effect of air pollution on migration is more pronounced.

Mumps epidemic dynamics in the United States before vaccination (1923–1932)

Mumps is a vaccine-preventable, reemerging, and highly transmissible infectious disease. Widespread vaccination dramatically reduced cases; however, case counts have been increasing over the past 20 years. To provide a quantitative overview of historical mumps dynamics that can act as baseline information to help identify causes of mumps reemergence, we analyzed timeseries of cases reported from 1923 to 1932 in the United States. During that time, 239,230 mumps cases were reported in 70 cities. Larger cities reported annual epidemics and smaller cities reported intermittent, sporadic outbreaks. The critical community size above which transmission continuously occurred was likely between 365,583 and 781,188 individuals but could range as high as 3,376,438 individuals. Mumps cases increased as city size increased, suggesting density-dependent transmission. Using a density-dependent SEIR model, we calculated a mean effective reproductive number (Re) of 1.2. Re varied by city and over time, with periodic high values that could characterize short periods of very high transmission known as superspreading events. Case counts most often peaked in March, with higher-than-average transmission from December through April and showed a correlation with weekly births. While certain city pairs in Midwestern states had synchronous outbreaks, most outbreaks were less synchronous and not driven by distance between cities. This work demonstrates the importance of long-term infectious disease surveillance data and will inform future studies on mumps reemergence and control.

Flight Reservation System

Flight Reservation System

Housing prices in Spain: convergence or decoupling?

In this article, we measure changes in the synchronization of housing price cycles across Spanish cities over time. We rely on a regime-switching framework that identifies the housing price cycles of pairs of cities and simultaneously infers the evolving relation between those cycles. These bilateral relationships are then summarized into an aggregate index of city-level housing cycle synchronization. The estimates suggest that Spanish housing prices have followed a convergence pattern that reached a peak in 2009 and decreased slightly afterward. We also identify the cities that have been the main contributors to this convergence process. Moreover, we show that differences in population growth and economic structure are key factors in explaining the evolution of housing price synchronization among Spanish cities.

Temporal visitation patterns of points of interest in cities on a planetary scale: a network science and machine learning approach

We aim to study the temporal patterns of activity in points of interest of cities around the world. In order to do so, we use the data provided by the online location-based social network Foursquare, where users make check-ins that indicate points of interest in the city. The data set comprises more than 90 million check-ins in 632 cities of 87 countries in 5 continents. We analyzed more than 11 million points of interest including all sorts of places: airports, restaurants, parks, hospitals, and many others. With this information, we obtained spatial and temporal patterns of activities for each city. We quantify similarities and differences of these patterns for all the cities involved and construct a network connecting pairs of cities. The links of this network indicate the similarity of temporal visitation patterns of points of interest between cities and is quantified with the Kullback-Leibler divergence between two distributions. Then, we obtained the community structure of this network and the geographic distribution of these communities worldwide. For comparison, we also use a Machine Learning algorithm—unsupervised agglomerative clustering—to obtain clusters or communities of cities with similar patterns. The main result is that both approaches give the same classification of five communities belonging to five different continents worldwide. This suggests that temporal patterns of activity can be universal, with some geographical, historical, and cultural variations, on a planetary scale.