Pushkar Singh

Pushkar Singh Pushkar Singh is an influencer

Patna, Bihar, India
99K followers 500+ connections

About

I help founders in storytelling and fundraising. Email me at [email protected] if you…

Articles by Pushkar

Activity

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Experience

  • Tremis Capital Graphic
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    Bergen Area, Norway

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    Mumbai Area, India

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    Mumbai Area, India

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    Mumbai Area, India

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    Mumbai Area, India

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    Hyderabad Area, India

Education

  • Norwegian School of Economics (NHH) Graphic

    Norwegian School of Economics (NHH)

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    Activities and Societies: Bartending, beer guzzling, tango, fishing, and hiking

    Master Thesis: Income Distribution and Income Inequality in Norway in 1930

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    Activities and Societies: Beer, Biking, Chess, Dramatics, and Quizzing

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    Activities and Societies: Astronomy, Basketball, Chess, Quizzing, and Travel

Licenses & Certifications

  • Bloomberg Aptitude Test: 650 (99 percentile) Graphic

    Bloomberg Aptitude Test: 650 (99 percentile)

    Bloomberg LP

    Issued

Volunteer Experience

  • Bartender

    Tango Abrazo

    - 2 years 3 months

    Arts and Culture

  • Bartender

    Stjernesalen, Det Akademiske Kvarter

    - 9 months

    Arts and Culture

  • Editor

    The Astronomy Club, Manipal

    - 11 months

    Science and Technology

Publications

  • The India Manufacturing Report 2011: Top states, best performing industries & future prospects

    Knight Frank India

    Principal Component Analysis (PCA) was used across indicators such as India’s GDP, secondary sector GDP, state GDP, rail-road & highway density, banking penetration & loans towards manufacturing sector to find out the top five industrial states.

    Factors like Gross value added (GVA) & share in manufacturing output were used to identify top sectors in all these five states.

    All sectors were ranked across various parameters such as ROCE, capital/labour ratio, labour productivity &…

    Principal Component Analysis (PCA) was used across indicators such as India’s GDP, secondary sector GDP, state GDP, rail-road & highway density, banking penetration & loans towards manufacturing sector to find out the top five industrial states.

    Factors like Gross value added (GVA) & share in manufacturing output were used to identify top sectors in all these five states.

    All sectors were ranked across various parameters such as ROCE, capital/labour ratio, labour productivity & real growth rate.

    Future output was estimated through regression across certain variables like GDP growth rate & industrial production growth rate.

    Using percentage growth in share as an indicator, all the top sectors for each state were categorized in a newly developed matrix called “Knight Frank Output Specialization” having four quadrants (‘Outperformer’, ‘Rising Star’, ‘Retreat’ and ‘Lost Opportunity’).

    Other authors

Courses

  • Applied Microeconomic Theory

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  • Business Analysis and Valuations

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  • Corporate Finance

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  • Econometric Techniques

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  • Empirical Methods & Applications in Macro and Finance

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  • Engineering Design

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  • Engineering Economics

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  • Engineering Mathematics

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  • History of Rock I (Coursera)

    University of Rochester

  • History of Rock II (Coursera)

    University of Rochester

  • International Business

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  • Labour Economics

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  • Legal Aspects of Business

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  • Mechanical Engineering Sciences

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  • Mergers, Acquisitions and Corporate Restructuring

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  • Optimization and Microeconomic Theory

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  • Production and Operations Management

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  • Security Analysis and Portfolio Management

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  • Time Series Analysis and Prediction

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Projects

  • Income Distribution and Income Inequality in Norway in 1930

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    Master Thesis, Supervisor: Dr Kjell Salvanes (Department of Economics, NHH)

    Research Question: How did income distribution and inequality look like in Norway in 1930?

    Data used: Municipality level pre-tax income data from Municipality Tax registries from Norway Census 1930 published by Archives, Stats Norway Kongsberg

    Methodology: Non-parametric models such as histogram and kernel density estimation for analysing income distribution, Gini coefficient and top income shares…

    Master Thesis, Supervisor: Dr Kjell Salvanes (Department of Economics, NHH)

    Research Question: How did income distribution and inequality look like in Norway in 1930?

    Data used: Municipality level pre-tax income data from Municipality Tax registries from Norway Census 1930 published by Archives, Stats Norway Kongsberg

    Methodology: Non-parametric models such as histogram and kernel density estimation for analysing income distribution, Gini coefficient and top income shares for calculating income inequality

    Conclusion: Urban areas in Norway were richer and more equal than rural areas in 1930, and although men were on an average richer than women, both men and women had similar levels of inequality. The Gini coefficient of Norway in 1930 was 0.522, much more than Norway’s Gini coefficient in 2013 that stood at 0.252.

  • Income inequality in Norway and United States

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    Course: Labour Economics

    Research Question: How did income inequality change in the United States and Norway over the 20th century and what were the reasons behind it?

    Data used: Top income shares of United States and Norway from World Wealth and Income Database (wid.world)

    Methodology: Comparison of income shares of top 1%, top 5%, top 10%, P 90-95 and P 95-99 in the period between 1918 and 2013 for the United States and between 1875 and 2011 for…

    Course: Labour Economics

    Research Question: How did income inequality change in the United States and Norway over the 20th century and what were the reasons behind it?

    Data used: Top income shares of United States and Norway from World Wealth and Income Database (wid.world)

    Methodology: Comparison of income shares of top 1%, top 5%, top 10%, P 90-95 and P 95-99 in the period between 1918 and 2013 for the United States and between 1875 and 2011 for Norway

    Conclusion: Both United States and Norway had the same level of inequality in 1945. Inequality decreased in both the countries from 1945 till the early 1970s. This decline continued in Norway till the early 1990s while inequality started increasing in the United States from 1970s. Inequality started increasing in the United States because of increase in top wage shares while it started increasing in Norway because of major financial markets and tax reforms.

  • Intergenerational correlations in intelligence between parents and children and intragenerational correlations in intelligence between siblings

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    Course: Empirical Methods and Applications in Macroeconomics and Finance

    Research Question: To discuss intelligence correlations in detail and to provide guidelines on how to formulate educational policies

    Data used: Danish Longitudinal Survey of Youth (DLSY) and the Danish Longitudinal Survey of Youth - Children (DLSY-C), two surveys that contain the scores of an intelligence test for both the parents and the children.

    Methodology: OLS and random effects…

    Course: Empirical Methods and Applications in Macroeconomics and Finance

    Research Question: To discuss intelligence correlations in detail and to provide guidelines on how to formulate educational policies

    Data used: Danish Longitudinal Survey of Youth (DLSY) and the Danish Longitudinal Survey of Youth - Children (DLSY-C), two surveys that contain the scores of an intelligence test for both the parents and the children.

    Methodology: OLS and random effects models

    Conclusion: Substantial intergenerational and sibling correlations exist, and shared environmental factors explain 13.7 % of the variance of children's IQ scores

  • The effect of change in energy prices on return of automobile and transport industries

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    Course: Empirical Analysis of Energy Markets

    Research Question: How does change in oil prices affect the profitability of automobile and transport sectors in Europe, the USA and Japan?

    Data used: Automobile and transport indices for Europe, USA, and Japan and Brent crude oil prices between 2004 and 2014

    Methodology: Cointegration test, Granger-causality test and sensitivity analysis using OLS

    Conclusion: Change in oil prices explain a high percentage of return in…

    Course: Empirical Analysis of Energy Markets

    Research Question: How does change in oil prices affect the profitability of automobile and transport sectors in Europe, the USA and Japan?

    Data used: Automobile and transport indices for Europe, USA, and Japan and Brent crude oil prices between 2004 and 2014

    Methodology: Cointegration test, Granger-causality test and sensitivity analysis using OLS

    Conclusion: Change in oil prices explain a high percentage of return in the automobile sector (90 % for Europe, 65 % for the USA and 77 % for Japan) and relatively lower proportion of return in the transport sector (36 % for Europe, 71 % for the USA and 33 % for Japan).

    Other creators
  • Challenges in profitable and safe extraction of gas from Norwegian Barents Sea

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    Course: Petroleum Economics

    Research question: To discuss the impact of extraction of gas from the Barents Sea on Norwegian State and public at large, oil companies and environment.

    Methodology: Financial feasibility of exploring and extracting the gas considering current and future gas prices, current policy and tax regime and physical constraints such as accessibility, infrastructure, and huge investments

    Conclusion: Progressive tax system encourages companies to invest…

    Course: Petroleum Economics

    Research question: To discuss the impact of extraction of gas from the Barents Sea on Norwegian State and public at large, oil companies and environment.

    Methodology: Financial feasibility of exploring and extracting the gas considering current and future gas prices, current policy and tax regime and physical constraints such as accessibility, infrastructure, and huge investments

    Conclusion: Progressive tax system encourages companies to invest since the risk is shared by the Norwegian state but can lead to misallocation of capital in cases when high investment costs are involved

Test Scores

  • Common Admission Test (CAT)

    Score: 99.41 percentile

Languages

  • Norsk

    Professional working proficiency

  • Spansk

    Limited working proficiency

  • Dansk

    Limited working proficiency

  • French

    Elementary proficiency

Organizations

  • Global Economic Perspectives at NHH

    Member

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  • idAnIm – The Film and Theatre Fraternity at IIM Indore

    Member

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  • Literary and Debating club at MIT, Manipal

    Member

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  • The Astronomy Club, Manipal

    Editor

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