计量经济分析 = Econometric analysis

In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

It comes as something ofa surprise to reflect that the New York Review ofBooks is now over twenty years old. Even people of my generation (that is, old enough to remember the revolutionary 196os but not young enough to have taken a very exciting part in them) think of the paper as eternally youthful. In fact, it has gone through years of relatively quiet life, yet, as always in a competitive journalistic market, it is the controversies that attract the interest of the reader and to which the history (especially an admittedly impressionistic survey that tries to include something of the intellectual context in which a journal has operated) must give some attention. Not all the attacks which the New York Review has attracted, both early in its career and more recently, are worth more than a brief summary. What do we now make, for example, of Richard Kostelanetz's forthright accusation that 'The New York Review was from its origins destined to publicize Random House's (and especially [Jason] Epstein's) books and writers'?1 Well, simply that, even if the statistics bear out the charge (and Kostelanetz provides some suggestive evidence to support it, at least with respect to some early issues), there is nothing surprising in a market economy about a publisher trying to push his books through the pages of a journal edited by his friends. True, the New York Review has not had room to review more than around fifteen books in each issue and there could be a bias in the selection of

http://www.jstor.org/stable/pdfplus/3507774.pdf

The New York Review of Books

Social Justice and the City

Innovation Diffusion as a Spatial Process

Street networks may be planned according to clear organizing principles or they may evolve organically through accretion, but their configurations and orientations help define a city’s spatial logic and order. Measures of entropy reveal a city’s streets’ order and disorder. Past studies have explored individual cases of orientation and entropy, but little is known about broader patterns and trends worldwide. This study examines street network orientation, configuration, and entropy in 100 cities around the world using OpenStreetMap data and OSMnx. It measures the entropy of street bearings in weighted and unweighted network models, along with each city’s typical street segment length, average circuity, average node degree, and the network’s proportions of four-way intersections and dead-ends. It also develops a new indicator of orientation-order that quantifies how a city’s street network follows the geometric ordering logic of a single grid. A cluster analysis is performed to explore similarities and differences among these study sites in multiple dimensions. Significant statistical relationships exist between city orientation-order and other indicators of spatial order, including street circuity and measures of connectedness. On average, US/Canadian study sites are far more grid-like than those elsewhere, exhibiting less entropy and circuity. These indicators, taken in concert, help reveal the extent and nuance of the grid. These methods demonstrate automatic, scalable, reproducible tools to empirically measure and visualize city spatial order, illustrating complex urban transportation system patterns and configurations around the world.

/pdf/urban-spatial-order-street-network-orientation-configuration-eokb5d4vow.pdf

Urban Spatial Order: Street Network Orientation, Configuration, and Entropy

OpenStreetMap offers a valuable source of worldwide geospatial data useful to urban researchers. This study uses the OSMnx software to automatically download and analyze 27,000 US street networks f...

/pdf/a-multi-scale-analysis-of-27-000-urban-street-networks-every-2e6oeizwcj.pdf

A Multi-Scale Analysis of 27,000 Urban Street Networks: Every US City, Town, Urbanized Area, and Zillow Neighborhood

Current sources of data on rental housing—such as the census or commercial databases that focus on large apartment complexes—do not reflect recent market activity or the full scope of the US rental market. To address this gap, we collected, cleaned, analyzed, mapped, and visualized eleven million Craigslist rental housing listings. The data reveal fine-grained spatial and temporal patterns within and across metropolitan housing markets in the United States. We find that some metropolitan areas have only single-digit percentages of listings below fair market rent. Nontraditional sources of volunteered geographic information offer planners real-time, local-scale estimates of rent and housing characteristics currently lacking in alternative sources, such as census data.

/pdf/new-insights-into-rental-housing-markets-across-the-united-2qhiovnolh.pdf

New Insights into Rental Housing Markets across the United States: Web Scraping and Analyzing Craigslist Rental Listings:

Current sources of data on rental housing - such as the census or commercial databases that focus on large apartment complexes - do not reflect recent market activity or the full scope of the U.S. rental market. To address this gap, we collected, cleaned, analyzed, mapped, and visualized 11 million Craigslist rental housing listings. The data reveal fine-grained spatial and temporal patterns within and across metropolitan housing markets in the U.S. We find some metropolitan areas have only single-digit percentages of listings below fair market rent. Nontraditional sources of volunteered geographic information offer planners real-time, local-scale estimates of rent and housing characteristics currently lacking in alternative sources, such as census data.

New Insights into Rental Housing Markets across the United States: Web Scraping and Analyzing Craigslist Rental Listings

https://escholarship.org/content/qt6mn025sb/qt6mn025sb.pdf?t=pz5pgv

Geoff Boeing

Papers

Urban Spatial Order: Street Network Orientation, Configuration, and Entropy

A Multi-Scale Analysis of 27,000 Urban Street Networks: Every US City, Town, Urbanized Area, and Zillow Neighborhood

New Insights into Rental Housing Markets across the United States: Web Scraping and Analyzing Craigslist Rental Listings:

New Insights into Rental Housing Markets across the United States: Web Scraping and Analyzing Craigslist Rental Listings

Spatial Information and the Legibility of Urban Form: Big Data in Urban Morphology