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- Member of: ASU Electronic Theses and Dissertations
Description
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Before 1990s, the relationship between money supply and inflation was positively correlated, however, from 1990 onwards, the US and other major developed countries entered into a new financial era with a typical belief that hyper money supply coexisted with lower inflation. This phenomenon is called “the paradox of inflation”. Traditional theories cannot provide reasonable explanations of this new phenomenon.
In my study, I have taken the linear filtering techniques which Lucas developed in 1980, and the recursive estimation method, as well as the chow test and F-test, and choose the data of the US, Britain, Japan, Germany, Euro area, BRICKs and some members of ASEAN, from 1960 to 2012, to study the relationship between annual rate of M2 growth and CPI inflation. The results show that in most sample developed and developing countries the positive correlation relationship between money supply and inflation began to weaken since the 1990s, and “the paradox of inflation” is now a common phenomenon.
In my paper, I attempt to provide a new explanation of “the paradox of inflation”. I conjecture that, in the past two decades, some advanced countries were becoming a “relatively wealthy society”, which means that commodity supply as well as money supply is abundant. I state that the US is a “relatively wealthy society” and try to determine what features could mark a “relatively wealthy society”.
I choose the credit growth rate of nonfinancial sectors and the ratio of dividends to investment to represent the production inclination of the business sector, and choose the income per capita and the GINI index to represent the consumption inclination of the resident sector. Then, through a semi parametric varying-coefficient regression model, I found that, in the US, when the credit growth of the business sector is under 5%, the ratio of dividends to investment is over 0.20, the per capita income is more than $30,000, and the GINI index is over 0.45, the country becomes a “relatively wealthy society”.
Base on this new explanation, I can conclude “in the relatively wealthy society, inflation is no longer a monetary phenomenon; it is a wealth allocation phenomenon”.
In my study, I have taken the linear filtering techniques which Lucas developed in 1980, and the recursive estimation method, as well as the chow test and F-test, and choose the data of the US, Britain, Japan, Germany, Euro area, BRICKs and some members of ASEAN, from 1960 to 2012, to study the relationship between annual rate of M2 growth and CPI inflation. The results show that in most sample developed and developing countries the positive correlation relationship between money supply and inflation began to weaken since the 1990s, and “the paradox of inflation” is now a common phenomenon.
In my paper, I attempt to provide a new explanation of “the paradox of inflation”. I conjecture that, in the past two decades, some advanced countries were becoming a “relatively wealthy society”, which means that commodity supply as well as money supply is abundant. I state that the US is a “relatively wealthy society” and try to determine what features could mark a “relatively wealthy society”.
I choose the credit growth rate of nonfinancial sectors and the ratio of dividends to investment to represent the production inclination of the business sector, and choose the income per capita and the GINI index to represent the consumption inclination of the resident sector. Then, through a semi parametric varying-coefficient regression model, I found that, in the US, when the credit growth of the business sector is under 5%, the ratio of dividends to investment is over 0.20, the per capita income is more than $30,000, and the GINI index is over 0.45, the country becomes a “relatively wealthy society”.
Base on this new explanation, I can conclude “in the relatively wealthy society, inflation is no longer a monetary phenomenon; it is a wealth allocation phenomenon”.
ContributorsCao, Tong (Author) / Prescott, Edward C. (Thesis advisor) / Liu, Jun (Thesis advisor) / Chun, Chang (Committee member) / Arizona State University (Publisher)
Created2015
Description
More people live in cities or metropolitan areas than ever before, which encompass many types of urbanization. These areas are culturally diverse and densely populated heterogeneous landscapes that are shaped by socio-ecological patterns. Cities support human and wildlife populations that are influenced indirectly and directly by human decisions. This process can result in unequal access to environmental services and accessible green spaces. Additionally, biodiversity distribution is influenced by human decisions. Although neighborhood income can drive biodiversity in metropolitan areas (i.e., the ‘luxury effect’), other socio-cultural factors may also influence the presence and abundance of wildlife beyond simple measures of wealth. To understand how additional social factors shape distributions of wildlife, I ask, are patterns of wildlife distribution associated with neighborhood ethnicity, in addition to income and ecological landscape characteristics within metropolitan areas? Utilizing data from 38 wildlife cameras deployed in neighborhood public parks and non-built spaces in metro Phoenix, AZ (USA), I estimated occupancy and activity patterns of coyotes (Canis latrans), desert cottontail rabbits (Sylvilagus audubonii), and domestic cats (Felis catus) across gradients of median household income and neighborhood ethnicity, estimated by the proportion of Latinx residents. Neighborhood ethnicity appeared in the top models for all species, and neighborhood % of Latinx residents was inversely associated with presence of native Sonoran Desert animals (coyotes and cottontail rabbits). Furthermore, daily activity patterns of coyotes differed in neighborhoods with higher vs. lower proportion of Latinx residents. My results suggest that socio-cultural variables beyond income are associated with wildlife distributions, and that factors associated with neighborhood ethnicity may be an informative correlate of city-wide ecological patterns. In this research, I unraveled predictive social variables and differentiated wildlife distribution across neighborhood gradients of income and ethnic composition, bringing attention to the potentially unequal distribution of mammals in cities.
ContributorsCocroft, Alexandreana (Author) / Hall, Sharon J (Thesis advisor) / Lerman, Susannah B (Committee member) / Lewis, Jesse (Committee member) / Arizona State University (Publisher)
Created2022
Description目前我国社会主要矛盾是“人民日益增长的美好生活需要和不平衡不充分的发展之间的矛盾”。消费对经济增长的贡献率达76.2%，而消费场所-购物中心为代表的的商业地产发展却落后于住宅地产的发展，不被房地产商所青睐。本文希望通过对影响购物中心租金收入因素的研究，运用统计回归模型分析，发现购物中心运营效益的重要决定因素。样本数据主要来自于8家上市公司的146个项目，对各项目2015年-2019年连续的租金收入进行分析。
现有研究购物中心文献，对于中国购物中心多区域多品牌动态运营绩效的研究文献很少，同时研究数据的取得难度大，还没有发现通过大样本数理统计得出的结论。
本文通过实证分析研究框架，运用二手数据，采用归纳研究，以“城市商圈的影响力”对购物中心每平米每日租金的影响进行回归分析。通过回归模型的量化分析，对日租金收入的影响因素城市商圈、城市人均GDP、开业期限、建筑面积、资金成本、出租率等进行分析，对购物中心品牌进行调节变量分析，得出城市商圈对日租金收入的影响是显著的，大城市的核心商圈或新城区核心商圈的购物中心日租金收入将强于同行，同时购物中心品牌的影响也是明显的。
中国住宅房地产投资已经到高点，房地产商未来的发展之路将面临新的选择。不同于住宅，购物中心的持有型特性将会给房地产商带来稳定的收入。通过对城市商圈等影响因子的分析，将对房地产商未来投资运营购物中心有重要的指导意义。
ContributorsLu, Xiaohui (Author) / Chen, Pei-Yu (Thesis advisor) / Chen, Xin (Thesis advisor) / Zhang, Anming (Committee member) / Arizona State University (Publisher)
Created2021