Gabriel Ahlfeldt lecturer at the London School of Economics, presents on the digital conversion of data derived from Olcott’s Blue Books, the unique dataset of historical land values, land uses, building heights, and other information in Chicago and its suburbs, published annually between 1900 and 1990. The digitization project, which opens up new possibilities for statistical analysis of long-run adjustments in land values, involves using geographic information system (GIS) software to create a rectangular grid following Chicago’s street pattern and produce a unique spatiotemporal dataset, providing insights into changes in the spatial structure of the city.
For the 12 days before and including Labor Day, Minnesotans reconvene at the State Fair. It is traditional and embedded in the culture. It matters here, unlike the fairs in other states I have lived (Maryland, Georgia, California). It is reportedly the best in the United States. The evidence for its centrality is that the University of Minnesota cannot open for classes until after the Fair concludes. The reasoning explains there is some shared parking, and that would involve traffic chaos, but we know it’s the Pronto-Pups.
Permanent marketplaces were supplemented with temporary and traveling fairs. The first fairs have been dated to 500 BCE, and may have occurred earlier. Fairs were events where foreign traders could show their wares, and were often coupled with religious festivals, taking place at and around temples. The fair changed over many centuries, evolving into several different types of activities, ranging from world to state and county fairs to conventions and trade shows. They are now less a place for purchasing, and more for information exchange. In fact, the International Association of Fairs and Expositions (IAFE), which specializes in agricultural events (like State Fairs), itself has an annual convention and trade show in Las Vegas.
Fairs enable mobile customers to meet mobile vendors. We often now think of the fair as a place for entertainment, what the British call a Fun Fair, like Carter’s Steam Fair, or the Midway (or Kidway) at the Minnesota Steam Fair. That fun too is commerce, we exchange bills for thrills.
There is the food. The fair brings foods one does not ordinarily encounter, deep-fried candy-bars on a stick, Scotch eggs, cooked sushi and poutine. Where else can you get ice cream made by a John Deere. Everyone has their go-to places, and the advantage of traveling in a large group is the increased ability to sample a variety.
At the Minnesota State Fair, in addition to every organization getting publicity, there is commerce. Machinery Hill was once the go-to place for farm equipment. There is still farm-equipment, but machinery now includes cars, motorcycles, and ATVs.
My favorite part is looking at gutter-clog prevention technology. Living under the great Minnesota tree canopy (about which more in a future post), my house’s gutters clog semi-annually and need clearing. There are several solutions. The most obvious is to eliminate gutters, but that risks more problems. There is the leaf guard, gutter helmet, leaf relief, etc. all of which have cool demonstrations of water running down shingles into the gutter, while the leaves themselves miss. In reality it is different, if stuff is not accumulating in the gutter, it accumulates on the narrowed entrance to the gutter. Since water droplets are not infinitesimally smaller than other things you are trying to eliminate, the problem is not solvable with just hardware. Let’s just say, I am skeptical, and I am lucky I don’t have a tree growing in my gutters given the rate of accumulation.The fair is an event city. A temporary city, in miniature, that has all the feature of a permanent full-sized place. There are residents, production, consumption, entertainment, inputs, outputs, economies of agglomeration, specialization, and so on. It comprises public streets over which the pedestrian has precedence. Would the real city were like the fair, and cars dominated streets only on the fairgrounds, only during the classic car show.
The dominant method for measuring values of travel time savings (VOT), and values of travel time reliability (VOR) is discrete choice modeling. Generally, the data sources for these models are: stated choice experiments, and revealed preference observations. There are few studies using revealed preference data. These studies have only used travel times measured by devices such as loop detectors, and thus the perception error of travelers has been largely ignored. In this study, the influence of commuters’ perception error is investigated on data collected of commuters recruited from previous research. The subjects’ self-reported travel times from surveys, and the subjects’ travel times measured by GPS devices were collected. The results indicate that the subjects reliability ratio is greater than 1 in the models with self-reported travel times. In contrast, subjects reliability ratio is smaller than 1 in the models with travel times as measured by GPS devices.
This paper undertakes an empirical analysis with the aim of improving the current understanding of the relationship between labor productivity and urban agglomeration economies across a sample of urbanized areas in the US. Agglomeration economies are represented with driving time measures of employment accessibility to establish a direct account for the link between transport and agglomeration economies. The paper investigates the presence of nonlinearities in the relationship between labor productivity and agglomeration economies, and examines the spatial decay pattern of the effects arising from this relationship. The findings indicate that there is considerable nonlinearity in the relation between productivity and transport induced agglomeration effects, implying that the estimation of country-level aggregate elasticities is likely to misrepresent the actual magnitude of any productivity gains from urban agglomeration. The results also suggest that the magnitude of the productivity-agglomeration effects decays very rapidly with time and is very strong within 20 minutes driving time. This suggests that knowledge spillover externalities are likely to be a very important Marshallian source of agglomeration economies.
JEL Classification: J31, R12, R40
Key words: agglomeration economies, network accessibility, labor productivity
This paper aims to look at the variation of network structure within a metropolitan area and relate it to observed travel, measured here as the average travel time to work. The Minor Civil Divisions (MCD) within the Twin Cities (Minneapolis, St. Paul) metropolitan area are chosen for this analysis. Quantitative measures, compiled from various sources, are used to capture the various aspects of network structure within each MCD. The variation of these measures within the metropolitan area is analyzed using spatial analyses. The measures of network structure are then related to observed travel using statistical regression models. The results confirm a relation between network structure and travel and point to the importance of understanding the underlying street network structure.
Because people seek to minimize their time and travel distance (or cost) when commuting, the circuity–the ratio of network distance traveled to the Euclidean distance between two points–plays an intricate role in the metropolitan economy. This paper seeks to measure the circuity of the United States’ 51 most populated Metropolitan Statistical Areas and identify trends in those circuities over the time period from 1990- 2010. With many factors playing a role such as suburban development and varying economic trends in metropolitan areas over this timeframe, much is to consider when calculating results. In general, circuity is increasing over time.
The set of models available to predict land use change in urban regions has become increasingly complex in recent years. Despite their complexity, the predictive power of these models remains relatively weak. This paper presents an example of an alternative modeling framework based on the concept of a Markov chain. The model assumes that land use at any given time, which is viewed as a discrete state, can be considered a function of only its previous state. The probability of transition between each pair of states is recorded as an element of a transition probability matrix. Assuming that this matrix is stationary over time, it can be used to predict future land use distributions from current data. To illustrate this process, a Markov chain model is estimated for the Minneapolis-St. Paul, MN, USA (Twin Cities) metropolitan region. Using a unique set of historical land use data covering several years between 1958 and 2005, the model is tested using historical data to predict recent conditions, and is then used to forecast the future distribution of land use decades into the future. We also use the cell-level data set to estimate the fraction of regional land use devoted to transportation facilities, including major highways, airports, and railways. The paper concludes with some comments on the strengths and weaknesses of Markov chains as a land use modeling framework, and suggests some possible extensions of the model.
Carrion and Levinson (2012) studied the bridge choice behavior of commuters before and after a new bridge opened to the public. This bridge replaced the previously collapsed I-35W bridge in the metro area of Minneapolis-St. Paul. The original I-35W bridge collapsed on August 1st, 2007, and the replacement bridge opened to the public on September 18th, 2008. This study extends Carrion and Levinson (2012) by considering explicitly the day-to-day behavior of travelers, and by also considering the previously excluded subjects that are transitioning between bridge alternatives not including the I-35W bridge. The primary results indicate that the subjects react to day-to-day travel times on a specific route according to thresholds. These thresholds help discriminate whether a travel time is within an acceptable margin or not, and travelers may decide to abandon the chosen route depending on the frequency of travel times within acceptable margins. The secondary results indicate that subjects previous experience, and perception of the alternatives also influence their decision to abandon the chosen route.
Accessibility is traditionally considered to be a property of a point or region in space, and to be invariant over time (or at least over some computationally convenient time interval). How- ever, a locations accessibility can vary over time on a wide range of scales. This temporal variation is especially significant for schedule-based transportation systems. Current measures of accessibility generally reflect the accessibility only at points in time corresponding to the departures of one or more trips; accessibility between these time points remains unconsidered and undefined. Consequently, these measures are insensitive to changes in route frequency and the distribution of trip departure times. Furthermore, these approaches ignore the disutility experienced by a system user who is limited to departing or arriving at scheduled times rather than at preferred times. As a result, they systematically overestimate the accessibility experienced by users of scheduled transportation systems. We establish new methods for representing the accessibility provided by a schedule-based transportation system from a specific location as a continuously-defined accessibility function (CDAF) of desired departure time, defined for all time points. Using schedule and route information from metropolitan transit providers, we demonstrate the application of these methods to gain new insight into the accessibility provided by real-world transportation systems. Four examples are developed to represent common service types in metropolitan transit networks. The results confirm that accessibility is significantly overestimated by measuring single points and show that trip frequency is more valuable for sustained accessibility than high accessibility on individual trips.
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