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Numbers tell stories, reveal facts and underlying patterns. If put together and analyzed correctly, they offer insights and provide a strong base for making important decisions.

Data (numbers) tell you the effect of something and thus, serve as a mere indicator, critical though. From an analysis perspective, however, it may not suffice. They represent the ‘what’ and most likely, you want to know the ‘why’ also.

This is where econometrics comes in.

It offers the answers to ‘why’, so that you can take actions to:

  • prevent a negative outcome from recurring, or
  • cause a positive event to repeat, or
  • improvise the existing situation

Let’s try and understand further:

Say, for example, the employee productivity in a particular department is decreasing. Now what would you want to know? Probably, things like:

  • Why is employee productivity decreasing ?
  • Why aren’t they able to meet their targets ?
  • Why don’t they feel motivated enough ?
  • How is it affecting your company’s bottom line ?

Since any outcome directly or indirectly hits your ROI, you wouldn’t want to adjust your HR policies without any concrete foundation. Rather you would test their practicality.

Econometrics finds its applicability here. It tests the economic viability of a decision and derives the more exact cause and effect relationship.

Econometrics, therefore, can be defined as:

  • deriving economic relations
  • by applying mathematical and statistical methods
  • to data collected or available.

It helps in, both, analyzing the impact of an existing phenomenon and testing a given hypothesis.

We have already seen how it can be of help in the case of an observed phenomenon. Let’s now see examples where econometrics can test hypothetical situations:

Estimating the probable impact of a training and development initiative

Say, for example, you want to study the hypothesis that a learning and development initiative will result in improved employee productivity.

Most companies nowadays have a separate learning and development department, introducing new ways of skill enhancement and constant learning. Needless to mention, it involves a huge expenditure. What needs to be considered here is that:

  • not all initiatives are equally effective
  • the cost involved in implementing some initiatives may exceed the benefits reaped

Therefore, L & D managers can resort to econometrics models to determine which initiatives are more feasible and lead to higher returns.

Econometrics here can be defined as:

  • Performing quantitative analysis
  • Of a given economic phenomenon
  • To derive an optimal state

Determining the apparent impact of an merit-based promotion

Here is another situation where econometrics can be applied.

Promoting employees is a way to show that you respect their contribution and want to reward them for it. A merit-based promotion will motivate your workers to put forth the extra efforts on continuous basis. This may also prompt innovation and creativity. Because of its obvious benefits, you want to introduce merit-based promotion in your organization.

It’s a great practice but may spread unrest among experienced employees. They may not perform the way they have been. In worst cases, they may leave the organization, if they see inexperienced ones being promoted. Apart from losing the trusted employees, you end up spending huge costs to seek their replacement.

This means the actual impact of a practice cannot be measured without taking the pros and cons into account. This is where econometrics plays a role. You can identify the more optimal state using econometrics analysis.

Elements of an Econometrics Analysis

The most distinguished feature of econometrics is that it also takes into account the random error, cons or the possible side effects of a decision or an initiative, along with the variables. And since it’s about performing quantitative analysis, it’s obvious that the variables are given numerical values. The procedure is carried out to either verify a given hypothesis or analyze the impact of an observed phenomenon.

An econometrics analysis can be conducted in several ways:

  • Time-series: when variables are examined over time. This takes into account the ‘period of time’.

  • Cross-section: when variables are examined at a particular time. This takes into account the ‘point of time’.

  • Panel: when variables are examined simultaneously for a time period as well as for a particular point of time. It’s a combination of time-series and cross section.

Econometrics Techniques

An econometrics analysis makes use of numerous techniques, linear regression being the most basic tool. More advanced techniques include:

  • Multiple Regression Analysis
  • Simultaneous Equations Model
  • Probit and Logit
  • Quantile Regression
  • Panel Data Model
  • Cointegration
  • Hazard
  • Statistical Inferences
  • ARIMA
  • Vector Autoregression

Econometrics Applications

Econometrics find its applicability across all industries, including but not limited to finance, agricultural, legal, education, information, health, IT, insurance, natural resources, manufacturing, geography, welfare, telecom, digital, eCommerce, international business and so on.

It can be used to analyze all kinds of situations, business processes, policies, decisions and actions taken by any organization. You can use it for a large number of issues to investigate their effect, without actually modifying a process or a system.

Econometrics is not an easy subject. But we simplify the complexities for you. Studying econometrics with us is sure going to be a pleasant experience. Dig in to learn more about it.

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