City Data and Urban Efficiency Economic Impacts

Categories: Big DataCityEconomics

City Data and Urban Efficiency: Economic Impacts

Urban big data is still in its early stages, but what will be clear from the investigation in this report is that there is already a consolidated global movement around this phenomenon. Oftentimes, observers use the term smart city to encompass the places and initiatives that embrace the use of computerized information and analytics to improve municipal and building operations. Of course, it will take a while for urban data systems to be widely adopted in all their potential applications.

Nonetheless, we are certain to eventually see urban analytics play an important role in many metropolises around the world.

The extent and shape of the implementation of smart-city initiatives will have impacts on land use patterns, real estate markets, and the quality of life. It is therefore imperative for practitioners in the real estate industry to anticipate their effects, in order to take advantage of new opportunities, or simply to take corrective action to avoid disruption of established business practices.

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There are many angles to such horizon scanning. One of them focuses on the relative advantages of cities that adopt smart city technologies compared to other areas that do not.

Economists have long formulated research on cities in terms of spatial equilibrium. A city is in spatial equilibrium at the point where there is no payoff for people to move in or out. The vast majority are doing fine where they are. Those who are not and who might want to move on would not be better off by leaving either, due to a lack of better opportunities elsewhere.

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Of course, a highly mobile society always has people hopping across locales. In equilibrium, most of these moves cancel out so that net migration flows are smaller than gross movements. Where mobility does take place in thriving societies, it tends to follow opportunity in ways that are predictable. A wealth of evidence demonstrates that population growth tends to follow wage growth andincreasinglythe availability of amenities. But if the more successful cities tend to attract people, why dont we see most of the population clustering in a just a few metropolitan areas? The answer partially resides in the role of the housing market. As cities grow larger, they also tend to become more expensive. When a city is somewhere close to its equilibrium, housing price inflation will exactly compensate for the gains in productivity, which gives rise to higher wages, so that there is no general advantage for even more people to move into more attractive places such as London, New York, Barcelona, or Boston.

In practical terms, this means that if wages and the quality of life in urban areas are much higher than wages in non-urban areas, we expect higher urban rents for real estate as offsetting this urban wage premium. Glaeser, Kolko and Saiz6 formulate a simple equation to capture this concept of a spatial equilibrium: Productivity Premium + Amenity Premium = Rent Premium This equation simply states that the effect of local wages and availability of good jobs (productivity premium) plus the local effect of quality of life (amenity premium) must be offset by local real estate values or rents (rent premium). This equation is not simply a theoretical identity, as it has been validated in many cities over many periods. It provides a good framework for forecasting the evolution of local real estate markets and for exploring the impact of current trends, such as the application of big data techniques to the management of cities. As an example, consider a case in which city wages are growing but housing costs are booming even faster. We can infer that the quality of life in the city has risen faster than the rise in p 8 The productivity premium, which drives wages, comes mainly from two sources.7 One of them is the existence of agglomeration economies. These are efficiency gains in production that arise from having firms locate close to each other. More saliently, the clustering of firms by sector allows for flexible supply chains and reduces the transportation costs of inputs in industrial production. In the services sector, physical proximity facilitates face-to-face communication of high-level information and allows parties involved in complex transactions to develop trust.

Parallel to physical input-output relationships between industrial plants, proximity between service firms allows for the presence of specialist sub-contractors and for fast reaction times from service providers. Agglomeration economies also arise with respect to attracting talent: if the best firms in a sector co-locate in a city, that city becomes a beacon for highly skilled workers, which in turn makes it yet more productive for more firms to locate there. Similar arguments can be made about the access to support networks for new firms, such as computer coding workshops or meet-and-greet cocktail parties. In parallel, firms can also be more productive in places where they have better access to ideas, technology, and skilled workers. These ideas range from changes in industrial techniques or product types to the most up-to-the-minute news about prices. This information is often transmitted by workers as they change firms and in social settings, like after-work happy hours. The amenity premium can arise from the provision of four types of amenities. 8 First, an important amenity is the presence of a rich variety of services and consumer goods. A second amenity is aesthetics: physical attributes of a community that make life more pleasant appear to be increasingly valued by consumers. A third amenity is good public services, which include good schools, better public utilities and less crime, and cultural opportunities. The fourth amenity is the speed or ease with which individuals can move around in a city. As people become wealthier, they value their time more, in the sense that they are willing to pay higher amounts for more expeditious services, or they are willing to pay higher rents to live in locations closer to their jobs.

The framework outlined above suggests that wherever big data efforts enable greater productivity gains and/or help cities provide better amenities, those gains and amenities will be associated with local real estate value appreciation. Urban data analytics certainly have the potential to improve the provision of urban amenities. Alternatively, they could maintain current municipal service levels at relatively low cost. If new IT systems and methods are successful in this latter regard, they could stem the secular cost disease of public services: their productivity has historically grown more slowly than in other sectors, rendering them relatively more expensive. Urban information systems could also help cities organize urban functions so that negative externalities are reduced. Negative externalities are instances where the behavior of some individuals has detrimental impact on the welfare of others.

Negative externalities destroy amenities locally and at the city level. For instance, by using sensors to monitor noise levels in the street and software to contact municipal police whenever some pre-established thresholds are crossed, such nuisances could be swiftly remediated. Similarly, positive externalities 9 where individual behavior has positive spillovers onto otherscan be encouraged. For instance, crowdsourcing platforms can allow citizens to report problemsas in the Boston-based app allowing citizens to report the geolocation of potholesthereby providing free monitoring services to all neighbors. Finally, the application of big data may increase the productivity of private firms in the city and generate new business opportunities for them. For instance, when app developers and corporate IT departments gain access to large quantities of data, they can develop new software and build better customer predictive analytics platforms. This discussion suggests that, either by providing productive value or by improving the local quality of life, the use of big data has the potential to increase urban residential and office demand, and therefore support local real estate valuations in the cities in which it is deployed.

Yet, some substantive questions remain: 1. How much value? While urban IT systems can improve our quality of life and reduce economic costs, the real issue is by h

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City Data and Urban Efficiency Economic Impacts. (2019, Nov 29). Retrieved from https://studymoose.com/city-data-and-urban-efficiency-economic-impactsurban-big-data-is-example-essay

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