New private sector works registered by year (boxes), by province (map), the numbers shown refer to the number of new square meters. Information provided by the center of the National Statistics Office of the Dominican Republic (Official Data).
Monetary amount in real estate investments in the private sector by year and province.Information provided by the center of the National Statistics Office of the Dominican Republic (Official Data).
Investment by building type and destination, studied by year.
Projection of the future investment market in the country
After analyzing the investment market per month from the period 01/01/2014 to the period 12/31/2021 and implementing a predictive mathematical model (Arima), we can observe a possible behavior of the investments until the period 2024, exposing it in the graph “Forecast_data for Investment”, obtaining a monthly average in the period 2023 of 224 MILLION and an average for the period 2024 of 221 MILLION U$D.
Below are the resulting graphs, the first shows the behavior of the investment market in the accumulated periods and the second shows the possible prediction of the behavior of the future market.
Introduction
Companies move in their daily life within a highly uncertain context, since there are many variables that affect their results; These variables can be uncontrollable, and within them we can talk about different types such as: political, economic, sociocultural, technological, ecological and legal, which have a significant impact on production costs, inventories, and especially on the estimation of sales. It is there, in this last aspect, where the margin of uncertainty of the future can be reduced.
Many managers think that sales forecasts are the most important piece of information in their marketing plan, and they are not wrong because:
Who would not like to know the future?
Who wouldn’t like to know what would happen if making some changes could affect sales positively or negatively?
As a definition: The sales forecast is an estimate of future events, always based on past events, and within a certain period of time, with the specific purpose of reducing the uncertainty of events and being able to support sound decision making. to prepare for such events.
R’s auto.arima function is a quick option for forecasting
The auto.arima function is included in the forecast library and provides a quick option to build models and forecasts with time series, since it evaluates the best among all possible models, considering various criteria: stationarity, seasonality, differences, among others.