Introduction to Econometric Data

It is hard to imagine an economy without econometrics. Economic studies and decisions all depend on data for the best outcome. After all, human beings, and indeed, the whole world is rational. Without data and information, there is no way they can make decisions. In this case, both firms and individuals are faced with decision making challenges on a daily basis. And these decisions bring out the relationship between the two. For instance, if producing a particular product goes high, a manufacturer may be forced to increase the price or reduce the quantity to cater to the extra expenses. The consumer may be forced to abandon the product or adjust its budget to fit the new prices.

In other words, everything in the world is tied together. We all depend on each, in a proper economic ecosystem. Therefore, it is important to understand that every decision we make affects other people either directly or indirectly. The economic relationship must exist for and economy to grow and develop.

Econometrics a branch of economics that deals with economic relationships. It is the bridge between mathematical economics and statistics, aiming to offer numerical values to the parameters that define economic relationships. And to achieve this, it becomes critical to look at the existence of economic theories and models with the aim of gaining values of the parameters, or the coefficients of a mathematical approach to economic relationships. In other words, econometrics deals a lot with numbers and things that can be proven numerically from an economic perspective. Econometric relations are important because they show the random behavior of economic relationships that are seen as mathematical formulas.

Econometrics is all about finding using numbers to create a foundation for economic decisions. For this reason, there is a need to have data that can be verified. Note that econometric methods can be used in other areas like engineering sciences, biological science, geosciences, agricultural science, and many other areas. As long as there is a need for data, econometric methods will be applied. Whenever one needs to find the scholastic link using mathematical formats, they will always be bound to econometric methods and tools.

But nothing will happen in this field if there is not data. You may have noticed that many people use the terms statistics and probability when defining econometrics. Even though these terms are different in definition, statistics is a very vital aspect of econometrics. Therefore, we say that econometrics helps us top understand why consumers will behave in a certain way if the producer makes certain decisions. It is this relationship that truly defines an economy. If people refuse to consume a particular product, they will be forcing companies that make that product out of the market, which contributes to market failures. An economy cannot survive without markets, which is why there are fiscal and monetary policies that control these ideas.

Data and econometrics

Economic data is also economic statistics, which refers to the quantitative measures that describe an actual economy in the past or present. Hence, the data is usually found in time-series format, meaning it covers more than one period of time. Data can also be cross-sectional in a specific period, for instance, the consumption and income levels of specific households within and economic period. Also, data can be collected from surveys, of chosen individuals and firms, or aggregated to sectors within a single, or international economy. Proper data collection methods are necessary for determining the correct outcomes.

Economic statistics has become one of the most important crucial aspects of modern economies. When there is a problem causing a burble of a recession in the economy, the policymakers have to go back and analyze the reasons behind such changes. Once they establish why, they will need to come up with a more probable cause of action, which depends on their ability to use available data. In other words, economies will be crippled if there are no verifiable data sets to set the records straight. It becomes essential to go back to the field to collect information that can be applied effectively in the development of a solution. For instance, a country may decide to analyze the rate of unemployment in the past, say five years, which could have had a huge impact on economic development. They will have to look at existing data, reasons that cause it, and make sure they do not go beyond the estimated limits. Government decisions, such as knowing where to invest, depend on their ability to understand consumption patterns over time.

Methodological and statistical elements for economic data include measuring, collecting, analyzing, and publishing the data. Hence, economic statistics can also be referred to as a subtopic of official statistics given by an official body. In other words, statistical institutes, an intergovernmental organization like the UN, and EU, Central banks, ministries, and many other similar bodies collect and store data that can offer an empirical foundation for economic research. Note that the research can be carried out in a descriptive or otherwise and econometric manner, but it must still remain relevant to the research process. Data archives have been years for many years in assessing replicability in empirical findings. They have been very fundamental in decision making as well as designing economic policy. In other words, data is the backbone of economic development, and it offers the best way to understanding why certain groups of individuals of firms will behave in a specific manner.

At any given economic level, you will find a huge array of organized economic data compiled according to national accounting. For instance, you will find Gross National Product and its components, Gross National Expenditure, Gross National Income, among others within the National Incomes and Product Accounts. It can be referred back to when looking at certain behaviors that influenced specific direction to a chosen economy, helping to come up with proper decisions to mitigate further damages. Other data such as capital stock and national wealth is all part of ensuring there is somewhere to turn to when things are not working as expected within an economic system.

Econometrics and statistics

It is important to note the difference between mathematical statistics and economic statistics. This is one subject that has confused many people who think there is a direct link between the two. Even though statistics sound the same all around – it is all about numbers and data – specific approaches bring out important differences when applied in different fields. For example, economic statistics call for collecting, recording, and tabulating empirical data, which is then used to describe how they develop. The statistics of economics describes economics. It does not explain why or how the development of different variable occurs, or the measurements of determinants in the relation.

The statistical methodology offers the description of measurement, builds on the foundation of a controlled experiment. These methods may be false in an economic phenomenon because they don't fit in the framework of controlled findings. Consider real-world experiments; for instance, the variables are never constant. They keep changing continuously and simultaneously, which means using controlled experiments may not keep the most accurate results.

It is safe to say that econometrics does not have a specific approach with statistical methods. It will only use the methods after changing them to adapt to the current issue in an economic environment. And one of the statistical methods have been adopted, they become econometric methods, which are adjusted constantly according to the measurement of stochastic relationships necessary. Once adjusted, the methods will attempt to specify the stochastic aspect that works in real-world data and inserts it into the determinant of discovered information. In this case, data becomes a random sample critical to the use of statistical parameters.

There is also the aspect of theoretical econometrics, which includes the construction and development of the right methods for measuring economic relations, not meant for investigation under controlled environments, like laboratories. Econometric methods generally emerge from non-experimental data.

In applied econometrics, there is the use of econometric approaches to particular branches of economic theory. Experts can also use it in resolving problems like demand, supply, production, investment, and consumption, among others. Applied econometrics, like the name suggests, comes with the application of parameters of the econometric model when analyzing economic model and trying to predict economic behaviors. Thus, they are crucial to economic growth and development both in the short-run and in the long-run.

Types of data in econometrics

As seen above, data is the backbone of any economy that seeks to grow and develop. Without it, there is no way of understanding what is happening at the moment or what may happen next – which leads to poor decision making. It is critical for data to be made available to anyone who needs it, especially since we live in an economic era. And in this case, here are various types of data used in estimating the econometric model.

Time-series data

Sometimes there is a need to look at different variables in a specific economy over a given period. This is where time-series data comes into play. It is described as the data that provides information about the numerical values of variables from period to period. This data is collected over time because it compares economic parameters over a long period. For instance, one may seek to find out monthly income for specified works in a certain sector between 1989 and 2012. Within the period, there would have been several downs and ups in the economy that caused specific changes that may have occurred within the parameter.

Cross-sectional data

Whereas time series data is general, cross-sectional data comes down to individual elements. It is data that provides information on variables about individual agents, like consumers and products, at a specific point in time. A good example is a cross-section of consumers where a sample of family budget indication expenditure of various commodities is shown. For instance, it could show how family expenditure and household consumption changed during the 2008/2009 great recession. Such data could also include information on family income, family composition, and other demographic, social, and financial behaviors. Since individuals' decisions affect the outcome of an economy, it becomes crucial for such data to be verifiable.

Panel data

We have seen the difference between cross-sectional and time-series data in the example above. Some people get confused when looking for panel data because there is both time and individual parameters involved. However, it is crucial to note that panel data is that data that comes from a repeated survey of a single sample in different time periods. For instance, one could be surveying the income ratio (cross-section data), or workers in the automobile industry. If they take a sample between 1907 and 1915 and compare to say data between 2010 and 2015, it becomes panel data.

Dummy variable data

Sometimes qualitative data is used in research. In this case, the variables cannot be quantified, yet the data is necessary; hence it is recorded as an indicator function. The values of the variables do not show the magnitude of the data. Such research is only intended to show the presents or absence of a particular trait. For instance, parameters like religions, tastes, and similar things are considered variables because they cannot be counted. If you are working on 'sex' are your subject, for instance, you can only get male or female. And if you go with 'taste' is either values-like or dislike. These values are denoted by the dummy variable where '1' may represent male or value-like, and '0,' female of dislike of taste.  

Conclusion

Data is all around. It is the force that drives human decisions and ensures economic growth and sustainability. This is why studying economic statistics is crucial in modern economies. However, this is one of the most challenging subjects because it includes statistical analysis of economic data. Here, students will be exposed to the combination of probability and statistical theory with computer-based analysis. But it is also very interesting because students test economic models using real-life information. You also get the skills to develop your own hypotheses and use them to prove certain aspects of human-like concerning their economic issues.

Author: James Hamilton