Social sciences proceed by developing models of social phenomena. By a model we mean a ‘simplified’ representation of reality. A model that attempts to describe every aspect of reality is quite useless. A model’s power stems from the elimination of irrelevant details, which allows the researcher to focus on the essential features of the reality that is being sought to be understood. In general, we want to adopt the simplest model that is capable of describing the economic situation we are examining. We can then add complications one at a time, allowing the model to become more complex and, consequently more realistic.
Let us consider a particular example of the market for apartments in a college town in the US. In this town there are two sorts of apartments. There are some that are adjacent to the university, and others that are farther away. The adjacent apartments are more desirable by students and faculty because of easier access to the university, and everyone would have been living in these adjacent apartments if they were able to afford it. Now suppose, as Economics researchers we are interested in estimating the supply curve of apartments adjacent to the university. How are we supposed to model this situation?
We will think of the apartments as being located in two large rings surrounding the uiversity. The adjacent apartments (henceforth denoted by A) are in the inner ring, while the rest (henceforth denoted by B) are located in the outer ring. We will focus exclusively on the market for A while treating the market for B as exogenous information. In other words, the price of B will be assumed to be an exogenous variable, while the price of the inner-ring is an endogenous variable. This means that the price of B is taken as determined by factors not discussed in the model, while the price of A is determined by forces described in the model. The first simplifying assumption will be that all A type apartments are identical in terms of their qualitative characteristics. In other words, our model is going to abstract from differences like number of bedrooms in each apartment, or the type of flooring in the apartment, etc. This will make speaking about “the price” of A meaningful, without worrying about quality differentials. But what determines the price of A? Typically the equilibrium price of anything depends on its demand and supply. We will simplify our model further by assuming that the parameters of the supply curve of A are not changing over time, that is, there is no shift of the supply curve. Given all these simplifying assumptions, any change in the observed quantity and price of A can be attributed to shifts of the demand curve. In fact, shifts of the demand curve causes changes in the equilibrium points which trace out the supply curve. In other words, demand shifts identify the supply. Now, the demand curve for A can shift for various reasons like the change in the number of students being admitted to the university, a change in the price of B, a change in the preference of renters for A over B, etc. Thus, given a dataset on the prices and quantities of type A apartments over time, we can identify the supply curve of A, provided we are willing to make all the above modelling assumptions.
From the above example, it should be clear that answering even a simple question requires a theoretical framework with substantial amount of simplifying assumptions. Stating the theoretical model clearly not only helps to interpret the empirical results later on in the light of the predictions or hypotheses of the model, but also to argue why the empirical results might be different from the model predictions.
