Suppose an economy possesses presently 60 million automobiles; and that each automobile must be replaced every 5 years. Suppose also that the present population of 240 million people grows \(2 \%\) per year. Calculate on the basis of these data, all other things remaining equal, the expected demand for automobiles for this year.

Understanding demand forecasting is critical for economic planning and resource allocation. It involves predicting future consumer demand based on various factors such as current demand trends, future events, and market dynamics. In the exercise provided, forecasting is simplified to highlight only replacement rates and population growth. This approach, although rudimentary, gives a starting point for estimating future demand.

The replacement aspect of demand is the focus here, showcasing a portion of what businesses and economists might include in a more comprehensive demand forecast. To improve the accuracy of such an estimate, one could also consider factors like technological advancements, changes in consumer preferences, and economic climate, which could all significantly impact demand for products like automobiles.

Population growth impacts economic demand in a straightforward yet profound way: as the population increases, so does the potential market for goods and services. The exercise illustrates this by calculating the additional demand for automobiles as the population grows by 2% annually. It assumes that the car ownership ratio remains constant, which means that as more people are born or move into the economy, more vehicles are needed.

However, this simplified scenario doesn’t account for demographic shifts or changes in consumer behavior over time, which could also significantly influence demand. Economies might experience variations in age distribution, urbanization trends, and income levels—all of which can affect the car ownership ratio.

Replacement demand is a concept within demand forecasting that specifically looks at the need to replace old or worn-out goods. In our automotive example, the need to replace cars every five years provides a baseline for estimating how many new vehicles will be demanded solely due to obsolescence or end-of-life.

The exercise correctly divides the total number of automobiles by the replacement rate but could be further enhanced by considering factors like changes in vehicle durability, legislative changes affecting vehicle life (such as emissions standards or safety regulations), and even economic cycles that influence consumer ability to replace vehicles as frequently as assumed. Forecasting replacement demand becomes complex when we consider a real-world scenario where not all automobiles will necessarily be replaced at the same rate.