Section 1 starts by giving a brief discussion of two important concepts in information economics: asymmetric information and signaling. Section 2 then illustrates how asymmetric information can be used to explain the low pay which we observe in the translators' market. This section
Section 1 starts by giving a brief discussion of two important concepts in information economics: asymmetric information and signaling. Section 2 then illustrates how asymmetric information can be used to explain the low pay which we observe in the translators' market. This section also analyzes why this problem of asymmetric information may lead to an outflow of "good" translators. In Section 3, I suggest how effective signals, such as a valid and reliable certification system, can be used to solve the problem of asymmetric information in the translators' market and hence improve the pay of capable professional translators.
- Asymmetric information and signaling theory
In economics jargon, a market with asymmetric information refers to one in which one side of the market has more information than the other side and this results in a market price lower than the "fair" price (Kingma 2001). The fundamentals of asymmetric information theory were first put forward by Akerlof (1970) in his seminal paper "The market for lemons: Quality uncertainty and the market mechanism". The theory he laid down has a wide application ranging from the insurance and credit market to the labor market. He was awarded the Nobel Prize in Economics in 2001 for his contribution to the field of information economics.
In his original paper, Akerlof (1970) uses the example of second-hand cars to illustrate the problem of asymmetric information. For simplicity's sake and for the purpose of illustration, he assumes that in the market of used cars, there are only two types of cars: good cars and bad cars (bad cars are called "lemons" in the US). Before buying a used car, the potential buyer forms a probability distribution: a probability q that a car is a good second-hand car and a probability of 1-q that it is a lemon. After owning a specific used car for some time, the owner can form a better idea of its quality. It is highly likely that a new probability distribution is to be formed. This estimate is more accurate than the original one. This is clearly a case of an asymmetry in available information: the sellers have more knowledge about the quality of a car than the buyers. Since it is impossible for a potential buyer to tell the difference between a good used car and a bad one, sellers may sell both of them at the same price.
This might lead to a problem which some people may call a version of Gresham's Law: Most traded cars will be "lemons" and good cars may not be traded at all. The original version is "Bad money drives out good money". Bad cars drive out good cars because both of them are sold at the same price, and the owners of good cars therefore do not find it worthwhile to sell their cars.
One possible way to tackle this problem is to use an effective signal. In this case, a signal is effective if we can use it to differentiate between good used cars and lemons. This concept of signaling was first used by Spence (1973) in his studies of the job market. He maintains that an education or degree can act as a signal to employers about the ability of a potential employee. In the example of the second-hand car market, a reputable large car dealer may be a more effective signal than someone who advertises in the newspaper because the former has spent a great deal of money on their showroom and is more likely to be dependable.
Asymmetric information in the translators' market
Most would agree that professional translators (or certainly the majority of translators) do not receive good pay. However, most seem to be unable to provide an empirical and testable hypothesis to explain this phenomenon. Many attribute this plight to the low perceived status of translators and their work. For example, Schreiber writes that "Most people still look upon us [professional translators] as, at best, semi-professionals, at worst non-professionals" (quoted in Liu 2001: 51). Therefore, most suggested solutions to this problem involve raising the status of translators. Robinson (2003) points out that "[translators should] work to educate clients and the general public about the importance of translation, so that money managers will be more willing to pay premium fees for translation" (28). The following discussion attempts to provide an alternative explanation using the theory of asymmetric information.
In a translation service market, it is difficult for service buyers or clients to assess the skills of a translator before they receive the translation. Therefore, the problem of asymmetric information exists in this market. In practice, clients can ask potential translators to first translate a small sample of the entire project, however, there is no guarantee that this sample will be a valid and reliable representative of the whole.
Since translation service buyers cannot distinguish between a good translator and a bad translator because of the asymmetric information problem, they tend to pay a going price that is below the "fair" level. For example, let us first assume good translators are worth $10 for a certain number of words and bad translators $5. As clients do not have complete information about the quality of translators, they are only willing to pay according to a certain probability distribution. Assuming a probability of 50% for both types of translators, i.e. half are good and half are bad, clients are only willing to pay $10(1/2)+$5(1/2)=$7.5. (This distribution is actually a bit conservative. We often hear complain