Government & Military

Forecasting India's GDP over 2015-2019 to assess the performance of Modi Government

Application Area: 

Project Details

Term: 

2019

Students: 

Shashank Suryae, Amol Kamath, Soumya Joshi, Mithilesh Parvataneni, Gary Rohan Singh, Rashi Choudhari

University: 

ISB

Presentation: 

Report: 

Problem Description
The project aims to forecast India’s GDP through 3 methods – employment, GDP trend and
the sum of 4 expenditure components (household, government expenditure, investment and
net exports) and to use the same to assess if the Modi Government has been able to change
India’s GDP growth trajectory over its 5 years in power (2015-2019). The client is the
Department of Expenditure, Ministry of Finance. Using the project, they can do a high-level

Forecasting Job Market in UK

Application Area: 

Project Details

Term: 

2019

Students: 

Abhimanyu, Aseem Garg, Jagannath Panigrahi, Nagesh Singh, Sai Nikhit Grandhi, Srishti Saxena

University: 

ISB

Presentation: 

Report: 

Problem Statement
To determine and forecast job growth and workforce in various industries in the United
Kingdom. This will help the United Kingdom Government and the Education industry in the
following ways:

Forecasting Economic Indicators of Andhra Pradesh & Telangana for Central Budget Planning

Application Area: 

Project Details

Term: 

2019

Students: 

Ankana Dhar, Sri Harsha Bandi, Sireesha Tekuru, W Snigdha Rao, Ujjwal Vasisht, Susruta Meka

University: 

ISB

Presentation: 

Report: 

Business Problem

The ministry of Finance possesses a lot of data with respect to multiple financial indicators of all the states. A forecast of these indicators for the next 5 years, will guide the ministry in planning the fiscal budget for various states.

The dataset in usage has the data of all 28 states, however, we have chosen to construct forecasting models for the state of Andhra Pradesh. However, it should be noted that, due to the separation of Telangana from Andhra Pradesh in 2014, the forecasts will be an aggregation of both the states.

Preparing for e-invoice donation drops in Taiwan cities

Application Area: 

Project Details

Term: 

Fall 2016

Students: 

Neil Huang, Ian Lin, Leo Lee, Martin Hsia

University: 

NTHU

Presentation: 

Report: 

1. Business Problem
In 2017, a new regulation about invoice donation was issued. All the invoices issued will be
transformed into e-invoice instead of paper invoice. However, this regulation will cause great
donation drops, and this is a problem for central and local government in Taiwan.
This project provide forecast of the next 2 month e-invoice donation amount to central
government. With this forecast, central government could know which city or county would
confront a donation amount drop in the future and ask local government to take actions.

Forecasting numbers of patients as reference for medical profession enrollment

Application Area: 

Project Details

Term: 

Fall 2016

Students: 

Yu-Chu Shih, Tzu-Han Hung, Yi-Chun Chuang, Tonny Meng-Lun Kuo

University: 

NTHU

Presentation: 

Report: 

Every year, Ministry of Health and Welfare in Taiwan (MHW) decides the capacity of medical students to ensure each division includes enough doctors in the future. However, a recent report indicates the huge shortage of doctors in five demanding divisions which leads to serious problems in hospital management. Deciding the capacity of medical students in specific divisions is challenging for MHW.

Forecasting Unemployment rates in the UK and EU

Application Area: 

Project Details

Term: 

2017

Students: 

Rajesh Manivannan, Kartick B Muthiah, Debayan Das, Devesh Kumar, Chirag Bhardwa, Sreeharsha Konga

University: 

ISB

Presentation: 

Report: 

Problem Description:
Unemployment benefits are a huge cost to governments and are highly dependent on
projected unemployment rate for the country. Unemployment benefits are social welfare
payments to unemployed individuals. The definition of unemployed individual varies from
among different governments. Each year Governments allocate a certain percentage of
their financial outlay to meet these requirements.

Predicting Rural Migration in India using Socio-Demographic Information

Application Area: 

Project Details

Term: 

2011

Students: 

Akshad Viswanathan, Anjali Kumari, Imran Ali Richa Gupta, Varun Sayal

University: 

ISB

Presentation: 

Report: 

India as a nation has seen a high migration rate in recent years. Over 98 million people migrated from one place to another in 1990s, the highest for any decade since independence according to the 2001 census details. However in 1970s migration was slowing down. The number of migrants during 1991-2001 increased by about 22% over the previous decade an increase since 1951. Apart from women migrating due to marriage, employment is the biggest reason for migration. The number of job seekers among all migrants has increased by 45% over the previous decade.

Bribe Payments For Land Registrations

Application Area: 

Project Details

Term: 

2011

Students: 

Hussain Boltwala, Karthik Vemparala, Naveen Kumar HS, Salman Siddiqui, Smita Chakravorty

University: 

ISB

Presentation: 

Report: 

The project is based on the data collected over a period of time from the customers who have used Governance services in India for the land registration process. The goal is to predict whether a person availing the e-Governance Service will pay a bribe of over INR 100.

Predicting Car Prices in Federal Auctions

Application Area: 

Project Details

Term: 

2010

Students: 

Tetsuya Morito, Karen Pereira, Jung-Fu Su, Mahsa Saedirad

University: 

UMD

Presentation: 

Report: 

The goal of this project is to provide buyers who attend Federal government car auctions, a simple indicator of whether or not to bid for specific vehicles, thus helping to improve their decision-making process and their chances of winning a fair bid.

We thank Karl Olson for sharing the data and the problem.

Comparing US employee profiles in the private and public sectors

Application Area: 

Project Details

Term: 

2008

Students: 

Abrar Al-Hasan, Jorge Christian, Hideki Kakuma, Li Wei Chen, Yavor Nikolov

University: 

UMD

Presentation: 

Report: 

This project used a dataset from the 1994 U.S. Census to build a model that characterizes the demographic factors distinguishing between the public or private sectors.

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