Economic Impact Assessment using Input-Output (IO) framework

22nd June 2020



Group Members (Group I):

  • Najlaa Ramli (17219402)
  • Nurul Aswani (17218967)
  • Aghilan Narayanan (17218898)
  • Nurarlisa Sulong (17220304)

Project Introduction

Problem Statement

Due to recent circumstances, there are a lot of uncertainties in regard to the economic outlook. Although information on potential demand changes are available, there are no exploratory or visualization tools to showcase such impact in an easier and comprehensible manner.

Question / Objective

To gauge and illustrate the wider economic impacts (i.e. direct, indirect, and induced impacts) with any demand changes in the Malaysian economy using an established Input-Output framework

Beneficiaries

The Shiny app serves as an exploratory and visualization tool for any user to explore the wider economic impacts with any demand changes in the Malaysian economy.

Dataset Used

There are 4 type of datasets acquired from DOSM Malaysia being used in the project which are further explained in our Shiny dashboard under “Documentation”. The Documentation also provides the calculation done on the data. Refer to the last slide for the link.

Data Science Process

As the project progressed, there are SIX (6) processes done in order to set up this project,

  1. Asking Question – As explained in previous slide.
  2. Requirement Gathering – Requires several features which is list of economy sectors, employment count, GDP, output multiplier and value added multiplier.
  3. Data Acquisition – Several datasets are acquired from DOSM Malaysia.
  4. Data Cleansing and Transformation – Data are cleansed, filtered, mutated and combined for data analysis purpose.
  5. Data Analysis – Calculations are performed accordingly as per documented formula in the Documentation part in our R Shiny Dashboard. Link are provided at the end of the slides.
  6. Presenting Data – Data are visualized in such a way that the user can immediately see what direct, indirect, induced as well as total impact based on the selected demand changes.

Shiny Dash Overview

1. Several menus available in our dashboard

2. Several input to set before calculating impacts

3. Several outputs in term of numbers, sunburst and treemap will appear

4. The breakdown of the calculated values and charts on the left

5. Documentation of datasets, formulas used and others are in Documentation tab.

6. List of group members involved.

Summary

Experiences Gained

  1. Data Science Processes done throughout the project taught us how to ask question, acquire appropriate datasets, cleansed, analyzed and visualize it.
  2. Using R programming language to do the calculations present a steep learning curve, but practices made it more understandable.
  3. Shiny App allows us to learn more on setting up Dashboard and link between the files, getting other interaction using observeEvent and observe.

References