Dissertation abstract: “Essays in applied economics on the intervention of a third player in agency relationships”

Agency theory has established that appropriate incentives can reconcile the diverging interests of the principal and the agent. Focusing on three applications, this dissertation evaluates the empirical relevance of these results when a third party interacts with the primary contract. The analyses provided rely on either laboratory or natural experiments. First, corruption is analyzed as a two-contract situation: a delegation contract between a Principal and an Agent and a corruption pact concluded between this Agent and a third player, called Briber. A survey of the recent microeconomic literature on corruption first highlights how corruption behavior results from the properties of those two agreements. We thereafter show that the Agent faces a conflict in reciprocities due to those two conflicting agreements. The resulting delegation effect, supported by observed behavior in our three-player experimental game, could account for the deterrence effect of wages on corruption. Second, health care is governed by contradictory objectives: patients are mainly concerned with the health provided, whereas containing health care costs is the primary goal of health care administrators. We provide further insights into the ability of incentives to balance these two competing objectives. In this matter, our theoretical and econometric analysis evaluates how a new mixed compensation scheme, introduced in Quebec in 1999 as an alternative to fee-for-services, has affected physicians’ practice patterns. Free switching is shown to be an essential feature of the reform, since it implements screening between physicians. Finally, the demand for underground work departs from the traditional Beckerian approach to illegal behavior, due to the dependence of benefits from illegality on competitors’ behavior. We set up a theoretical model in which the demand for underground work from all producers competing on the same output market is analyzed simultaneously. We first show that competition drastically undermines the individual benefits of tax evasion. At equilibrium, each firm nonetheless chooses evasion with a positive probability, strictly lower than one. This Bertrand curse could then account for the “tax evasion puzzle” i.e. the overprediction of evasion in models that ignore market interactions. We thereafter show that allowing firms to denounce competitors’ evasion is not likely to solve this curse—by providing a credible threat against price cuts, it fosters illegal work. Empirical evidence from a laboratory experiment confirms these predictions. Without denunciation, experimental firms often choose evasion whereas evasion benefits are canceled out by competition. When introduced, denunciation is rarely used by firms, but the threat makes evasion profitable. JEL Classification K42, I18, D21, C25, C91     

“一带一路”倡议下中国口岸出入境货运量的时空格局演变探究

口岸作为国家指定的对外开放门户,承担着国与国之间货物运输和人员往来的重要功能。"一带一路"倡议的实施促进了我国口岸的发展,带动了口岸经济与区域经济的发展,反过来进一步加强了与"一带一路"沿线国家的合作。本文利用口岸运行指标中的出入境货运量数据,借助探索性空间数据分析方法,对我国2011—2017年31个省(区、市)的口岸出入境货运量的时空格局进行分析。结果表明:"一带一路"倡议提出后,尤其是2015年后,我国口岸出入境货运总量呈现快速增长态势且存在显著的空间正相关性;三类口岸(水运、陆运和空运口岸)中,水运口岸存在更显著的、更强的空间相关性;各类口岸出入境货运量中,东部沿海地区水运呈现正向空间集聚现象,西部沿边地区陆运呈现极化现象。此外,本文对全国31个省(区、市)的地区货运总量也进行了空间动态分析,发现也存在空间相关性,且集聚效应在"一带一路"倡议提出后不断增强。在此基础上,为了更好地服务于"一带一路"建设,本文提出了提升各类口岸运输能力的相关对策建议。     

Spatial Competition and Shopping Externalities: Evidence from the Housing Market

In search markets, greater spatial concentration of sellers increases price competition. At the same time, though, a greater concentration of sellers can create a shopping externality by attracting more buyers to the site. Using housing sales data, we test for spatial competition and shopping externality effects on prices and marketing time. We find that they reflect both competitive and shopping externality effects from surrounding houses, although the relative strength varies with how fresh the house is in the market, the freshness of surrounding houses, and the phase of the market cycle. New listings have the strongest shopping externality effect on neighboring houses that have been on the market for some time. Vacant houses have their strongest competition effects in the declining market and externality effects in the rising market. Fresh houses on the market reap little benefit from shopping externalities in all phases of the market cycle.     

Spatial patterns of poverty in Vietnam and their implications for policy

This study examines the geographic distribution of poverty in Vietnam by applying small area estimation methods to household budget data and population census data. The resulting district-level poverty estimates suggest that the incidence of poverty is highest in the remote northern and central highlands and lowest in the south-east and in large urban centres. However, mapping the density of poverty reveals that most poor people do not live in the poorest districts but in the two lowland deltas, where poverty incidence is intermediate. The policy implications of these findings present an important trade-off between targeting poor areas and poor people that can only be resolved with better information on the relative costs of delivering different programmes and their expected impact. Existing government estimates of poverty at the district level are not closely correlated with our poverty estimates, perhaps because of regional variation in their methods of collecting poverty data.     

Anthropogenic and topographic correlates of natural vegetation cover within agricultural landscape mosaics in Turkey

Natural vegetation enhances the value of agricultural landscapes for people and wildlife. However, the role of anthropogenic versus topographic factors in driving the extent of natural vegetation cover within agricultural lands at large spatial scales remains unexplored. I assessed the influence of anthropogenic and topographic variables on the extent of agricultural mosaics with high natural vegetation cover in the country of Turkey where a large extent of natural and semi-natural vegetation is maintained by traditional agriculture. GIS layers depicting human land use, elevation, slope, roads and population data were obtained and summarized at two spatial scales, within provinces and for 100 km² grid cells covering the country’s entire agricultural land area. Average farm size was also obtained at province level. Hierarchical Partitioning was conducted to determine the independent effect of anthropogenic and topographic variables on the variation in agriculture with high natural vegetation. Slope had the largest independent effect on the variation in the proportion of agricultural mosaic with high natural vegetation cover. The extent of agricultural and settlement area also explained much of the variation in natural vegetation across both grid cells and provinces. The proportion of natural vegetation increased as human population and road density decreased across grid cells and as average farm size decreased across provinces. These results suggest that while topography is the primary driver of natural vegetation cover within agricultural mosaics in Turkey, the pressures associated with urban development and agricultural industrialization may also influence the cultural and wildlife value of agricultural landscapes.     

Does high frequency algorithmic trading matter for non-AT investors?

The extant literature has typically measured the impact of high frequency algorithmic trading (HFT) on short term outcomes, in seconds or minutes. We focus on outcomes of concern for longer term non-algorithm investors. We find in some cases HFT increases volatility arising from news relating to fundamentals. Furthermore HFT is associated with the transmission of that volatility across industries, and that transmission is based on short term correlations. Finally, we find that the period since the introduction of algorithmic trading (AT) has seen increases in both the variances and covariances of return volatility in most industries. However increases in the variances has not been uniform in that it has fallen sharply in a few industries. The magnitudes are such that, overall, AT has coincided with reduced return volatility variance.     

长江经济带生态保护效率与科技服务业发展效率时空关联分析

建立超效率DEA模型并运用视窗分析测算2010-2017年长江经济带11个省市生态保护效率与科技服务业发展效率，通过空间计量模型分析后者对前者的影响。结果表明：科研技术服务业效率对当地及周边地区的生态保护效率具有正向影响；科技资本服务业效率对当地生态保护效率具有正向影响，但对其周边地区有抑制效应；科技宣传服务业未对生态保护效率产生显著影响。据此，提出长江经济带通过提高科技服务业效率改进生态保护效率的对策。     

基于GIS的铁路密度空间分异研究——以新疆铁路交通网络为例

城市对外交通中,铁路是发展较早的交通运输方式。本文以新疆的铁路交通网络为依据,以道路密度为指标,利用Arc GIS的叠加分析和空间分析功能,研究新疆铁路交通网络的空间分异,并分析新疆各区域人口、生产总值差异与铁路密度差异之间的相互关系。结果表明:(1)新疆铁路密度差异显著,大体呈现"南北低中部高"的趋势;(2)新疆各地区铁路密度与人口分布、生产总值高度正相关。     

Identifying the internal structure evolution of urban built-up land sprawl (UBLS) from a composite structure perspective: A case study of the Beijing metropolitan area,China

Differences in the internal composite structure during urban built-up land sprawl (UBLS) will generate different effects, and thus, a city’s spatial structure has important bearings on urban sustainability. This study investigates the spatial and temporal characteristics of the internal structure and allocation relationship of UBLS using multivariate spatial correlation and the Weaver-Tomas composite coefficient based on site data of granted built-up land parcels. Moreover, the composite structure evolution process of UBLS and its driving mechanism are examined in this study. The results reveal that the amount structure of the three types of UBLS (i.e. industrial land sprawl, residential land sprawl and commercial land sprawl) tended to be balanced during the study period. Following the transformation and upgrade of the urban industry structure, the overall composite structure of UBLS ranged from single residential land-use structure (Res.) to industrial-residential land-use structure (Ind.-Res.) In the early period of land marketization, the marketization land granting mechanism caused low spatial correlation between the various types of UBLS and a single composite structure, i.e. Res., single commercial land-use structure (Com.), and residential-commercial land-use structure (Res.-Com.). Subsequently, a dual-driving force including the market economy and government interventions caused a relatively high degree of spatial correlation and a multiple composite structure, i.e. Ind.-Res. and industrial-residential-commercial land-use structure (Ind.-Res.-Com.). However, the evolution characteristics of the composite structure in various regions illustrate some problems, such as the spatial isomorphism phenomenon of the composite structure and the dislocation of urban built-up land allocation. The urban internal built-up land spatial layout pattern is the embodiment of two dominant driving forces, the market and the government, interacting with each other according to natural and socioeconomic conditions. Therefore, we suggest that it is necessary to reform the future urban built-up land granting mechanism based on market guidance, and the composite structure of UBLS should be adjusted according to the regional function. The government should reinforce the macro-control of land-use planning for the dispersed granted land parcels so as to optimize the urban land-use structure.     

The eruption of Airbnb in tourist cities: Comparing spatial patterns of hotels and peer-to-peer accommodation in Barcelona

In recent years, what has become known as collaborative consumption has undergone rapid expansion through peer-to-peer (P2P) platforms. In the field of tourism, a particularly notable example is that of Airbnb. This article analyses the spatial patterns of Airbnb in Barcelona and compares them with hotels and sightseeing spots. New sources of data, such as Airbnb listings and geolocated photographs are used. Analysis of bivariate spatial autocorrelation reveals a close spatial relationship between Airbnb and hotels, with a marked centre-periphery pattern, although Airbnb predominates around the city's main hotel axis and hotels predominate in some peripheral areas of the city. Another interesting finding is that Airbnb capitalises more on the advantages of proximity to the city's main tourist attractions than does the hotel sector. Multiple regression analysis shows that the factors explaining location are also different for hotels and Airbnb. Finally, it was possible to detect those parts of the city that have seen the greatest increase in pressure from tourism related to Airbnb's recent expansion.