Econometrics is the study of economic data through mathematical and statistical techniques. It is often described as the branch of economics that lends empirical support to theoretical models applied to the whole economy, an industry, or individual businesses. It thus has the potential of covering several fields, such as finance, health economics, development economics, industrial economics, labour economics, environmental economics and public policy, which can apply econometric tools to shed light on whether empirical data is consistent with specific theoretic questions. Econometrics is a blend of statistics, mathematics and economics thus making econometrics an economic decision-support set of techniques.

Through advancements in statistics and computer power, researchers can carry out quantitative analyses of economic phenomena based on hypotheses, theories and observation using large amounts of actual or simulated data. When carrying out econometric estimations, a set of assumptions might need to be made to allow the model to be specific and to be able to realistically and correctly draw inferences, results and conclusions from real world economic data. These results are used to justify government and business decisions, validate and support public policy debates, and to forecast future events.

Economic data can be cross-sectional data, where a sample of individuals, households, firms or countries are studied at a single point in time, time-series data, where a variable is studied over time, like the Unemployment Rate, Gross Domestic Product, Government Expenditure, Inflation, and Personal Disposable Income or Panel-data. The latter combines cross-sectional and time-series data to observe relevant data entities over time.

Econometrics techniques are applied to economic data to determine whether an economic model or a hypothesis based on economic theory is statistically consistent with empirical data. The econometric model will specify the relationship of the variables and phenomena being studied. The simplest econometric model is a linear regression. Regression analyses help understand how the typical value of a dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. An example of a linear regression is the study of the effects of income on consumer spending. Consumer spending is the dependent (or endogenous) variable, that is, the variable being studied, while income is the independent (or exogenous) variable, that is, the variable used to try and explain changes in the dependent variable. Through the estimations of the parameters of the model, one can determine the effects of income on consumption. An error term will show the extent to which the model fails to explain consumer spending. Other econometric models do not distinguish between variables that are being studied and variables that are used as explanatory variables as one may affect the other.

There are several econometric techniques that are applicable to different economic problems ensuring that a clear-cut tailor-made solution is available. Some of the most commonly used econometric models include: the Linear Regression; Generalised Linear Models; ARIMA models; Vector Autoregression models; Input-Output Models; Fixed-Effects and Random-Effects models; Vector Error Correction models; Cointegration; Impulse Response functions; and Probit/Logit/Tobit models. Structural models are also commonly used in real-life situations as they convey causal and counterfactual information about the decision at hand.

Econometrics can be used to forecast how economic units or an entire economy will perform in the future, subject to what is already currently known. Forecasting techniques can be applied to large macroeconomic variables such as GDP, inflation, interest rates and unemployment or at a disaggregated level for sector-specific, commodity-specific or firm-specific data. There are several forecasting applications for businesses and governments. For example, the future demand for a specific good or service can be extrapolated such as the demand for oil, electricity, and public or private projects. This can give an indicator of the revenue generated and whether or not the project is worth undertaking from a financial or economic point of view. Forecasting models are also used by businesses to forecast trends in the financial markets in the hope of generating a strategic advantage and to translate that into profit. Some firms prefer to keep their forecasting models in-house while others use their models to give investment advice or to give their opinion about economic developments in the media.

Several forecasting methods exist. The most basic approach to forecasting is that of extrapolating past trends and forecasting them into the future. More sophisticated models make attempts to understand past changes in the data and build these justifications into the model to arrive at a higher level of accuracy. There are several forecasting techniques such as forecasting with linear and non-linear regression models, forecasting time-series data including seasonal adjustments, ARIMA models, TRAMO-SEATS and exponential models. Forecasting is not an exact science, but through the understanding of its shortcomings a decision-making basis can be formulated subject to the limitations that apply.

The econometrics team at Equinox Advisory can use their experience in econometric modelling and estimation to:

  • Provide tailor-made solutions through the applications of the required data and econometric techniques;
  • Provide advice about which data sets are required to solve the specific problem at hand. If not publicly available, our data collection team can collect raw data for you professionally using state-of-the-art sampling techniques, and CATI data collection methods, while avoiding biases;
  • Apply econometric modelling and data analyses to a range of business and policy issues such as corporate financing and regulatory issues;
  • Aid professionals, small and large business owners, individuals, politicians and governments to make good decisions based on scientific rationale; and
  • Provide training on statistical and econometric techniques through our specialised training and educational arm Equinox Academy.
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