CHAPTER 2 Tools of economic analysis ©McGraw-Hill Education, 2014

Economic models Help us to organize our thinking we need a simplified picture of reality Help us to focus on key elements are developed so that understanding of how the economy functions can be improved. Allow us to generate hypotheses that can be tested against the facts. ©McGraw-Hill Education, 2014

Economic models: an example Tube revenue = tube fare  number of passengers Number of passengers = f (tube fare, taxi fare, petrol price, bus fare, passenger incomes …) Tube revenue = tube fare  f (tube fare, taxi fare, petrol price, bus fare, passenger incomes …) ©McGraw-Hill Education, 2014

We do indeed see a positive relationship between fares and revenue Scatter diagrams show the relationship between two variables plotted in the diagram. By fitting a ‘line of best fit’ through these points we summarize the average relationship between the two variables. ©McGraw-Hill Education, 2014

The other things being equal or ceteris paribus assumption Other things equal, higher fares reduce the number of tube journeys, but if the number of journeys made falls only a little, overall revenue may actually rise when fares are increased. ©McGraw-Hill Education, 2014

The other things being equal or ceteris paribus assumption Other things equal, higher fares reduce the number of tube journeys, but if the number of journeys made falls only a little, overall revenue may actually rise when fares are increased. But other things were not equal over the period. In this period Britain’s national income, adjusted for inflation, grew substantially ©McGraw-Hill Education, 2014

The other things being equal, or ceteris paribus, assumption Even if tube fares had been constant, rising incomes should have led to (and did lead to) rising tube use and rising tube revenues. ©McGraw-Hill Education, 2014

Econometrics (1) Analytical diagrams are often useful in building a model. They show relationships between two variables holding other things equal. Econometrics uses computers to fit average relationships between many variables simultaneously. In principle this allows us to get round the ‘other things equal’ problem, which always applies in two dimensions ©McGraw-Hill Education, 2014

Econometrics (2) Once relationships have been established, they are useful as  a test of our hypotheses  they can be use to make predictions about the likely impact of a change in one variable (e.g. price) on another (e.g. demand). ©McGraw-Hill Education, 2014

Concluding comments (1) A model is a simplified framework to organize how we think about a problem. Data are important as they suggest relationships which we should aim to explain and they allow us to test our hypotheses and to quantify the effects that they imply. Time-series data are values of a given variable at different points in time. Cross-section data refer to the same point in time but to different values of the same variable across different people. ©McGraw-Hill Education, 2014

Concluding comments (2) Panel data are a mix between time-series and cross-section data. Index numbers express data relative to some given base value. The consumer price index summarizes changes in the prices of all goods bought by households. The annual percentage change in the retail price index is the usual measure of inflation. Real or constant price variables adjust nominal variables for changes in the general level of prices. ©McGraw-Hill Education, 2014