Tag Archives: CDA

Exit, voice, and loyalty in cities

Economist Albert Hirschman’s 1970 book Exit, Voice, and Loyalty: Responses to Decline in Firms, Organizations, and States presents a theory of how consumers express their dissatisfaction to firms and other organizations after a decline in product or service quality. In terms of interjurisdictional competition exit is demonstrated by migration: dissatisfied residents migrate to a community that better matches their preferences for local government services, externality mitigation, and fiscal policy. Voice, on the other hand, requires staying in place and is usually manifested through voting. Other methods such as protests, letters, and public comments directed at officials may also be effective ways to create change.

Loyalty plays a role in whether voice or exit is employed. Someone who is loyal to a city will be less likely to exit due to a given deterioration in quality. Hirschman argues that loyalty serves an important function by limiting the use of exit and activating voice. If exit is too easy, the quality-conscious people most capable of using voice to elicit change at the local level will tend to leave early, sparking a “brain drain” and generating cumulative deterioration. If some of the most quality-conscious residents are loyal they will remain in place, at least initially, and try to fix a city’s problems from within i.e. they will use some method of voice.

The presence of loyalty within a city’s population has implications for city population decline and growth. The diagram below, based on one from Hirschman’s book on p. 90, shows the relationship between city quality and population.

Exit and loyalty diagram

Quality deteriorates as one moves up the y-axis and population increases along the x-axis, which enables a depiction of the relationship between quality and population similar to that of a traditional demand curve.

The example begins at point A. If quality declines from Q1 to Q2, the population will decline from Pa to Pb. The relatively small population decline relative to the decline in quality is due to the presence of loyalty. Loyalty can be conscious, meaning that the loyal residents are aware of the quality decline and are staying to try to improve the situation, or it can be unconscious, meaning that some residents are unaware that quality is deteriorating. These unaware residents appear loyal to outsiders, but in reality they have just not perceived the decline in quality. Perhaps the decline has not impacted their particular neighborhood or is so gradual that many people don’t realize it is happening. Hirschman notes that unconscious loyalty will not spark voice since by definition the resident is unaware that decline is occurring.

As quality continues to decline from Q2 to Q3 it becomes more observable and even the most loyal residents accept the fact that voice will not save their city. Additionally, the unconscious “loyal” residents will finally notice the decline. Both groups of people will then exit the city in order to reside somewhere else. This leads to a larger drop in population and is shown in the diagram as a movement from Pb to Pc.

This pattern is repeated as a city recovers. An initial quality improvement from Q3 to Q2 induces a relatively small amount of migration back to the city (Pc to Pd), since most people will need confirmation that the city has actually started down a path of sustainable improvement before they will return. Further improvement from Q2 to Q1 will generate a larger increase in population, represented by a movement from point D to point A (Pd to Pa).

What is interesting about this theoretical analysis is that it generates two different populations for the same level of quality. At quality Q2 the city’s population will be relatively large (Pb) if the city is declining in quality and it will be relatively small (point Pd) if the city’s quality is improving. This means that a declining city such as Detroit, Baltimore, Cleveland, Buffalo, etc. will have to make substantial quality improvements before they will see a large influx of people. So even if a city such as Cleveland returns to its 1970 level of relative quality we shouldn’t expect a drastic increase in population, as this model predicts that its population will be less than its actual 1970 population since it will be on the returning curve (CDA) rather than the exiting curve (ABC).

A city that is consistently losing population over a long period of time faces a variety of problems such as increased crime, declining housing values, a decline in the quality of public services, and higher costs in the provision of public services. Fixing these problems is often expensive and this model implies that the costs required for increasing quality from Q1 to Q2 will not result in substantial population gain, which means per capita costs to taxpayers are unlikely to decline by much and may even increase as the city begins to improve. This model predicts that revitalizing America’s struggling cities is a more difficult task than many politicians and policy makers are acknowledging.