Location choices of firms and workers in an urban model with heterogeneities in skills and preferences

This paper investigates the location choices of firms and workers, and the implied commuting behavior, in a city comprising several jurisdictions. Jurisdictions are geographically represented by segments that are connected to each other at the center. Each jurisdiction has its own amenities. Workers are classified into types on the basis of their skills and amenity preferences. Firms employ all types of worker. A business area may be formed in the center or in the suburban segments. A monocentric configuration arises when the commuting cost is small and heterogeneity of workers is large.     

Every ending is a new beginning: Poignancy increases consumer preferences for self-made products

Retailers and brands such as IKEA, Home Depot, and Build-a-Bear encourage consumers to ‘make’ their products rather than be passive recipients. While a growing literature explores ‘why’ consumers purchase self-made products, it is less understood ‘how’ marketers can develop effective advertising and marketing communications to promote such products. Building on the functionalist framework of emotion, the present research explores the potential of a mixed emotional appeal – poignancy – that may be useful in enhancing consumer preferences for self-made products. Notably, this effect is mediated by a fresh start mindset and openness to learning. The effect is also attenuated among consumers with a low personal control. In addition to having substantive practical implications to marketers in developing effective communication strategies, this research offers a novel perspective on the effect of poignancy on consumer decision making.     

耕地重金属污染治理生态补偿政策选择与组合研究

研究目的:考察不同规模农户对生态补偿多元政策的偏好及政策间的相互作用,以期为增强耕地重金属污染生态补偿政策的实施效果和构建污染治理长效补偿机制提供参考。研究方法:Mixed Logit模型。研究结果:(1)农户对各类生态补偿政策的偏好程度受经营规模影响显著,规模户偏好技术指导、产量保险和分级收购政策,目前试点的现金补贴政策对其激励不足;(2)技术补偿与资金补偿政策呈显著互补性,当技术补偿缺失时,市场化的分级收购补偿政策激励效果将被弱化。研究结论:耕地重金属污染治理生态补偿需要探索针对性治理技术指导、产量保险、分级收购等新政策,同时对补偿政策进行合理组合。     

混业经营趋势下的金融协调监管

在混业经营的趋势下,金融协调监管显得尤为重要。本文从金融协调监管的必要性出发,分析了我国金融协调监管中存在的问题,并在此基础上提出如何来构建我国的金融监管协调机制。     

混合双寡头模型下的R&D竞争:不确定性和模仿视角

通过引入模仿参数δ来衡量R&D容易被模仿的程度,对Joanna Poya-go-Theotoky(1998)的研究进行了拓展,验证了其基本结论的稳健性。此外,通过引入二次R&D成本函数,研究发现,混合双寡头与私人双寡头情况下的社会福利的比较是不确定的,除了依赖创新规模P以外,还取决于模仿参数d,即——(1)对于任意的d,创新规模越大,私人双寡头越倾向于占优混合双寡头,混合双寡头仅在创新规模较小的时候可能优于私人双寡头;(2)对于创新规模比较小的R&D,只有同时具备较容易的模仿程度,混合双寡头才会优于私人双寡头;(3)在不完全模仿(d≠1)的情况下,在R&D越来越容易被模仿的过程中,利率越高(低),私人双寡头优于混合双寡头的最低P值先上升(下降)后下降(上升)。     

非国有大股东对国企超额雇员的影响:成本效应还是激励效应

基于竞争理论的国企改革思路强调减少政策性负担摊派,基于产权理论的改革思路侧重于引入非国有资本,以解决产权不清晰与所有者缺位问题.本文尝试融合两种理论,以国企超额雇员问题为研究对象,从非国有大股东视角探究混合所有制改革成效.研究发现:非国有大股东能够显著降低国企超额雇员,减弱超额雇员对公司价值的损害作用,且该治理作用会随非国有大股东相对力量的提高而增强;从作用机制来看,该治理作用不仅表现为劳动力成本尤其是员工薪酬的节约,还表现为内部薪酬差距和管理层薪酬业绩敏感性的提高,兼具成本效应与激励效应;该作用在地区就业压力较小、劳动密集度较低以及劳动保护水平更低的环境下更为显著.     

Robust multivariate analysis for mixed-type data: Novel algorithm and its practical application in socio-economic research

We propose a novel method and algorithm for the analysis and clustering of mixed-type data using a hierarchical approach based on Forward Search. In our procedure, the identification of groups is based on the identification of similar trajectories and then linked to very intuitive two-dimensional maps. The proposed algorithm can use different measures for the calculation of distance in the case of mixed-type data, such as Gower’s metric and Related metric scaling. A key feature of our algorithm is its ability to discard redundant information from a given set of variables. The practical usefulness of the algorithm is illustrated through two applications of high relevance for empirical economic research. The first one focuses on comparing different indicators of environmental policy stringency in different countries. The second one applies our procedure to identify clusters of countries based on information regarding their institutional characteristics.     

What prevents consumers that are aware of Airbnb from using the platform? A mixed methods approach

The hospitality sector is now characterised by the co-existence of traditional providers and sharing economy enterprises. It is important to better understand what prevents the use of peer-to-peer accommodation rentals in the tourism marketplace. Adopting a mixed-methods approach, this study first examines travellers’ Airbnb use constraints, and then profiles 252 Airbnb non-users based on their constraints and characteristics. The findings suggest that travellers do not use Airbnb because of distrust in the providers, in the platform and in other users, as well as perceived risk and unfamiliarity. Loss of service quality, lack of local experience, legal and regulatory issues, and disinterest also prevented consumers to book Airbnb accommodations. A cluster analysis divided non-users into three segments: Traditional travellers, Sharing economy misbelievers and Airbnb prospective users. Significant differences based on age confirmed that young travellers are more confident in using peer-to-peer accommodation platforms and more interested in the philosophy.     

Corporate financial distress: The case of publicly listed firms in an emerging market economy

Occurrences of financial distress (FD) are not readily obvious yet can span several periods. This paper examines episodes of FD using industry‐relative (IR) firm‐/ accounting‐, market‐ and macro‐level information. Mixed logit regressions reveal that firm‐ and market‐based measures, as well as macro‐level variables explain the likelihood of FD in 263 publicly listed non‐banking firms in the Philippines during the period 1995 to 2018. Rates of identification of firms in financial distressed states of close to 69 percent are obtained at a cutoff probability of 0.30 in the model with time‐varying intercept and slope. This study shows the importance of recognizing heterogeneous firm behavior. The ability to more accurately predict the probability of FD and to determine the financial health of firms can help financial institutions in allocating funds and policy makers in predicting crises episodes.     

A MIP model for locating slow-charging stations for electric vehicles in urban areas accounting for driver tours

In this paper we propose an improved mathematical model for locating EV charging stations. We consider the successive activities of the travelers, i.e., a person with two main stops during the day should charge the vehicle in just one of the parking spots, hence avoiding double counting the demand. The model is tested for the city of Coimbra (Portugal), where there is a network of nine stations. We conclude that our solution is better than the one that was implemented in reality, moreover we are able to conclude that demand transference has a rather significant impact on the solutions.