## How to Forecast Volatility of the Conditional Variance in the GARCH Model

To forecast the volatility of the conditional variance using a GARCH model in EViews, follow these steps: Step-by-Step Guide: Load Your Data: Open EViews and load your time series data. Specify the GARCH Model: Go to Quick -> Estimate Equation. In the equation specification box, enter the mean equation (e.g., Y = C(1) + C(2)*X […]

## How to Detect Heteroscedasticity using Eviews

Detecting heteroskedasticity in EViews involves running specific tests and analyzing residual plots. Here are the steps: Step-by-Step Guide: Run Initial OLS Regression: Load your dataset in EViews. Go to Quick -> Estimate Equation. Enter your regression equation (e.g., Y = C(1) + C(2)*X1 + C(3)*X2). Click OK to estimate using Ordinary Least Squares (OLS). Plot […]

## How to correct Heteroscedasticity with Functional Forms of the Model in Eviews

Correcting heteroskedasticity by transforming the functional form of the model in EViews involves the following steps: Step-by-Step Guide: Run Initial OLS Regression: Load your dataset in EViews. Go to Quick -> Estimate Equation. Enter your regression equation (e.g., Y = C(1) + C(2)*X1 + C(3)*X2). Click OK to estimate using Ordinary Least Squares (OLS). Diagnose […]

## How to correct Heteroscedasticity with Weighted (Generalised) Least Squares in Eviews

To correct heteroskedasticity with Weighted (Generalized) Least Squares (WLS/GLS) in EViews, follow these steps: Step-by-Step Guide: Run Initial OLS Regression: Load your dataset in EViews. Go to Quick -> Estimate Equation. Enter your regression equation (e.g., Y = C(1) + C(2)*X1 + C(3)*X2). Click OK to estimate using Ordinary Least Squares (OLS). Diagnose Heteroskedasticity: Check […]

## How to correct Heteroscedasticity with Robust Standard Errors using Eviews

To correct heteroskedasticity using robust standard errors in EViews, follow these expanded steps: Step-by-Step Guide: Run the Initial OLS Regression: Open EViews and load your dataset. Navigate to Quick -> Estimate Equation. Enter the regression equation in the form of Dependent Variable = C(1) + C(2)*Independent Variable + …. Click OK to estimate the equation […]

## Moderation Modelling in Time Series Analysis using EVIEWS

Here are the steps of moderation modelling in time series analysis using EViews, based on a hypothetical scenario: Define Research Objectives and Hypothesis: Clearly state your research question and the moderating effect you’re investigating. For example, you might be studying how marketing affects sales (independent variable) and how economic conditions (moderating variable) influence that relationship. […]

## Linear vs. Logistic Probability Models: Which is Better, and When?

Interpretability Let’s start by comparing the two models explicitly. If the outcome Y is a dichotomy with values 1 and 0, define p = E(Y|X), which is just the probability that Y is 1, given some value of the regressors X. Then the linear and logistic probability models are: p = a0 + a1X1 + a2X2 + … + akXk (linear) ln[p/(1-p)] = b0 + b1X1 + b2X2 + … + bkXk (logistic) […]

## The Difference Between the Bernoulli and Binomial Distributions

You might already be familiar with the binomial distribution. It describes the scenario where the result of an observation is binary—it can be one of two outcomes. You might label the outcomes as “success” and “failure” (or not!). Or, if you want to get mathematical about it, you might label them “1” and “0.” You […]

## Logistic Regression Analysis: Understanding Odds and Probability

Probability and odds measure the same thing: the likelihood or propensity or possibility of a specific outcome. People use the terms odds and probability interchangeably in casual usage, but that is unfortunate. It just creates confusion because they are not equivalent. How Odds and Probability Differ They measure the same thing on different scales. Imagine how confusing it would be […]

## How to Conduct Probit and Logit Models (Binary Outcome Models)

Probit and Logit Models (Binary Outcome Models) Do you want to understand the factors that influence binary outcomes? Then you’ve come to the right place. In this article, we’ll delve into the world of Probit and Logit models, which are commonly used in statistical analysis to predict binary outcomes. Whether you’re a researcher, […]