Quiz #4

Select one of the following three questions for a brief statement:

Select one:

The law of diminishing returns is at the core of any explanation which relates the intensity of land use at a location to the accessibility of that location (e.g. to the distance of that location to a center or market). Explain this statement.
- See: Stutz, p.262
- The law of diminishing returns (LDR) suggests that as long as one factors of production remains constant, an increase in all other factors will eventually lead to diminishing increases in output levels. The corollary of this law then proposes that marginal costs would eventually increase. We would expect profit maximizing farmers or skyscraper developers to operate at an intensity level which is associated with increasing marginal costs (above the intersection with the average cost curve, i.e. as long as average costs are covered by revenues). The optimal intensity of land use would then be the point where marginal costs equal marginal revenues or where the price for the last additional unit of output just covers the additional costs.
  The LDR has to do with the combinations of factors of production. Geography is not an explicit part of the discussion and transport costs should initially probably be left out in order not to muddle the argument. However, now we introduce transport costs as a factor which reduces revenues. Thus, accessibility of a location would influence the marginal revenues which a unit of land would be able to achieve. HIGH TRANSPORT COSTS WOULD DIMINISH THE ABILITY OF THE LAND TO OVERCOME THE EFFECTS OF THE LDR. In other words, less accessible land (i.e. land at locations with high transport costs) would be expected to be cultivated at (relatively low) intensity levels where the returns have NOT YET BEEN DIMINISHED as much as they would be at more accessible and preferred locations. OR: The increasing transport costs associated with more peripheral locations are "crowding out" (reducing the feasibility of) other cost increases which would be associated with more intensive land use. OR: The higher the value of land (due to high accessibility or agglomeration economies) or the opportunity costs of a particular land use, the greater is the incentive to work with relatively high marginal costs. The high price for floor space will justify possibly strongly diminishing returns (as long as the total product/floor space is not declining).
- One member has suggested that increased intensity of land use may be associated with detrimental environmental effects: soil erosion, pollution, disappearing views blocked by skyscrapers etc. In other words: private costs are too low. Privately diminishing returns are slower to set in than "diminishing social returns". Similar to the way in which transport costs reduce land use intensity, an environmental tax would increase private costs and represent an intensity reducing incentive.
- Two members suggested that diminishing returns may set in over time, i.e. if a given intensity level continues over several years, returns may diminish due to soil (or other resource-) depletion. One could extend this phenomenon to the urban scene by suggesting that overly intensive land uses without continuous maintenance may lead to diminishing returns as a result of aging and deterioration.
Write an account of the reading on geographic networks in Stutz in which you stress what you felt were the most important points for an economic geographer. (Reading for week #7, pp.173-81)
- There was more in this section of Stutz than you could possibly have used in your 10-minutes statement. Thus, alternative foci could have included:
  1. the accessibility of specific nodes or hubs within networks
  2. the connectivity of different kinds of networks (and the possibilities of measuring such connectivity)
  3. the question as to what are "optimal" networks under different (e.g. cost) conditions
  4. the use of different kinds of networks (e.g. routing within network)
Why could it be important for the understanding of the urban economy to distinguish between "basic" and "non-basic" activities and to measure the "pcl" of households?
- The emphasis of this question is squarely on the "Why?". Thus while it is essential to be able to make a conceptual distinction between "basic" and "non-basic" activities, it is NOT sufficient. The "why" which we stressed in class (on May 16) relates to the calculation of "multipliers", more specifically the "local income multiplier" which is based on the (structural) relationship between basic and non-basic activities in a local economy or region. Once we know the numerical characteristics of this (inter)dependence relationship (the non-basic activities being dependent on the basic activities) then we may have sufficient confidence in the stability of this relationship (at least for the short- to medium time horizon) that we can use this "frozen structure" in the form of a multiplier to estimate impacts of changes in the basic ("exogenous") components of the economy on the total income (or employment if we use the equivalent "local employment multiplier").
- At least one member of the class (who was absent on May 16) tried to answer the question locationally, i.e. identify different location factors for basic and non-basic activities in the city. That could become a very interesting extension of our urban economic base discussion, or a conceptual and analytical links between locational micro perspectives and economic base (macro) perspectives. Multiplier induced impacts are not just affecting whole regions, but particular sub-regions and locations. In other words, once we know the location of basic activities, we could then try to locationally allocate first the basic households, then the non-basic activities (e.g. shopping centers) dependent on these basic households, then the residences of the first-round non-basic households, then the locations of second-round non-basic activities etc.. We would have to do that on the basis of what we know about commuting behaviors, residential location behaviors, shopping behaviors etc. Such a "spatial economic base model" would help us e.g. to identify where WITHIN our region an expansion or reduction of Boeing employment might result in impacts on the housing market, traffic load, retail demand etc..