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### A Pluto.jl notebook ###
# v0.15.0

using Markdown
using InteractiveUtils

# This Pluto notebook uses @bind for interactivity. When running this notebook outside of Pluto, the following 'mock version' of @bind gives bound variables a default value (instead of an error).
macro bind(def, element)
    quote
        local el = $(esc(element))

nilshg

using CSV, DataFrames, Econometrics, GLM, Statistics, TableView

# Read in the data - unbalanced panel
# Data from https://rdrr.io/cran/panelvar/man/abdata.html
df = CSV.read("abdata.csv", copycols = true)

# We start by estimating standard OLS on our data, running the model
#
# yᵢₜ = α₁Lyᵢₜ + α₂L²yᵢₜ + β₁wᵢₜ + β₂Lwᵢₜ + β₃kᵢₜ + β₄Lkᵢₜ + β₅L²kᵢₜ + β₆ysᵢₜ + β₇Lysᵢₜ + β₈L²ysᵢₜ
#        + ∑yearₜ

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{"nbformat_minor": 0, "cells": [{"source": "<h2>Deloitte Interview</h2>\n<a id=\"top\"></a>\n\n1. [Why Deloitte?](#deloitte) (What do they do?)\n2. [Why this job?](#job) (Senior Associate profile)\n3. [Why you?](#personal) (Personal questions)\n4. Statistical techniques for competition consulting (Compass Lexecon)\n5. Issues in NHS consulting (Deloitte briefings + my work)", "cell_type": "markdown", "metadata": {}}, {"source": "<a id=\"deloitte\"></a>\n<h3>Why Deloitte?</h3>\n\nMy reasons for choosing Deloitte:\n\n1. Personal references - friends who have conveyed positive experiences both from Germany and the London office\n2. Size - allows for larger variety in client projects, potentially better long-term fit as one can carve out niche within the business\n3. Fit - econ consulting team seems very engaged in NHS projects and public sector work, which is interesting to me personally\n4. Related: compared to other jobs (Economist at Compass Lexecon, Associate at CRA, Economist at Monitor, Research Officer at 

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