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%----------------------------------------------------------------------------------------
\documentclass[aspectratio=169,xcolor=dvipsnames]{beamer} \usetheme{SimpleDarkBlue} \usepackage{hyperref}
\usepackage{graphicx} % Allows including images
\usepackage{adjustbox}
\usepackage{framed}
\usepackage{tikz}
\usepackage{inputenc}
\usetikzlibrary{shapes, shapes.geometric, arrows, positioning}
\usepackage{adjustbox}
\usepackage{bm}
\usepackage{amssymb}
\usepackage{booktabs} % Allows the use of \toprule, \midrule and \bottomrule in tables
\usepackage{textpos}
%{\includegraphics[width=\paperwidth,height=\paperheight,keepaspectratio]{./img/Mines_background1.pdf}}
%----------------------------------------------------------------------------------------
% TITLE PAGE
%----------------------------------------------------------------------------------------
%\title[Bitcoin Mining, a Coproduct of Oil Production]{Bitcoin Mining, a Coproduct of Oil Production} % The short title appears at the bottom of every slide, the full title is only on the title page
\title[Will Bitcoin Mining Create the Next Shale Boom?]{Will Bitcoin Mining Create the Next Shale Boom?} % The short title appears at the bottom of every slide, the full title is only on the title page
\title[Bitcoin Mining, a Coproduct of Oil Production]{Bitcoin Mining, a Coproduct of Oil Production} % The short title appears at the bottom of every slide, the full title is only on the title page
\subtitle{An Estimation of Long Run Regional Welfare Effects}
\author[Alex Gebben] {Alexander Gebben}
@ -42,34 +37,22 @@
%------------------------------------------------
\section{Introduction \& Overview}
\input{./Sections/Intro.tex}
\input{./Sections/About_me.tex}
\input{./Sections/Other_Research.tex}
\section{Background}
\input{./Sections/Background.tex}
\input{./Sections/Maps.tex}
\input{./Sections/Subsidy_Chart.tex}
\input{./Sections/Key_Questions.tex}
\input{./Sections/Diagram.tex}
\input{./Sections/Mechanism.tex}
\section{Bitcoin Mining}
\input{./Sections/Bitcoin_Intro.tex}
\input{./Sections/Bitcoin_Incentives.tex}
\input{./Sections/Mining_Structure.tex}
\input{./Sections/Mining_Model.tex}
\input{./Sections/Mining_elast.tex}
%\input{./Sections/Reg_elas.tex}
\section{Oil Market}
\input{./Sections/Oil_Intro.tex}
\input{./Sections/Reg_elas.tex}
\input{./Sections/Oil_Structure.tex}
\input{./Sections/Oil_Assumptions.tex}
\input{./Sections/Oil_Econometrics.tex}
\input{./Sections/Data.tex}
\section{Results}
\input{./Sections/Maps.tex}
\input{./Sections/Subsidy_Chart.tex}
\input{./Sections/Results.tex}
\section{Conclusion}
\input{./Sections/Conclusion.tex}
\input{./Sections/Questions.tex}
\section{Bibliography}
\input{./Sections/bib.tex}
\section{Theory}
\section{Econometric Strategy}
\section{Data}
\end{document}

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State,Flaring
Alaska,55219
California,1506
Colorado,22787
Louisiana,37907
Montana,29822
New_Mexico,200339
North_Dakota,924350
Texas,1242937
Utah,2078
Wyoming,148226
1 State Flaring
2 Alaska 55219
3 California 1506
4 Colorado 22787
5 Louisiana 37907
6 Montana 29822
7 New_Mexico 200339
8 North_Dakota 924350
9 Texas 1242937
10 Utah 2078
11 Wyoming 148226

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library(tidyverse)
library(readxl)
library(lubridate)
df <- read_excel("NG_PROD_SUM_A_EPG0_VGV_MMCF_A.xls",sheet=2,col_names=T,skip=2)
colnames(df) <-c("Date","National","Alaska","Alaska_onshore","Alaska_State","Arkansas","California","Calif_onshore","California_State","Federal_Offshore_Calif","Colorado","Offshore_Gulf_of_Mexico","Kansas","Louisiana","Louisiana_onshore","Louisiana_State","Montana","New_Mexico","North_Dakota","Ohio","Oklahoma","Pennsylvania","Texas","Texas_onshore","Texas_State_Offshore","Utah","West_Virginia","Wyoming")
df$Year <- year(df$Date)
df <- df %>% filter(Year>2013) %>% summarize(Alaska=sum(Alaska,na.rm=TRUE),Arkansas=sum(Arkansas,na.rm=TRUE),California=sum(California,na.rm=TRUE),Colorado=sum(Colorado,na.rm=TRUE),Kansas=sum(Kansas,na.rm=TRUE),Louisiana=sum(Louisiana,na.rm=TRUE),Montana=sum(Montana,na.rm=TRUE),New_Mexico=sum(New_Mexico,na.rm=TRUE),North_Dakota=sum(North_Dakota,na.rm=TRUE),Ohio=sum(Ohio,na.rm=TRUE),Oklahoma=sum(Oklahoma,na.rm=TRUE),Pennsylvania=sum(Pennsylvania,na.rm=TRUE),Texas=sum(Texas,na.rm=TRUE),Utah=sum(Utah,na.rm=TRUE),West_Virginia=sum(West_Virginia,na.rm=TRUE),Wyoming=sum(Wyoming,na.rm=TRUE))
temp1 <- colnames(df)
temp2 <- df %>% as.data.frame %>% t %>% c
graph_dat <- cbind(temp1,temp2)
colnames(graph_dat) <- c("State","Flaring")
graph_dat <- graph_dat %>% as_tibble %>% mutate(Flaring=as.numeric(Flaring)) %>% filter(Flaring>0)
#ggplot(data=graph_dat,aes(x="",y=Flaring,fill=State)) + geom_bar(stat="identity",width=1)+coord_polar("y",start=0)
ggplot(data=graph_dat,aes(x="",y=Flaring,fill=State))+geom_col(color="black") +coord_polar(theta="y")

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library(tidyverse)
library(readxl)
library(ggthemes)
library(lubridate)
#devtools::install_github("Mikata-Project/ggthemr")
#library(ggthemr)
df <- read_excel("NG_PROD_SUM_A_EPG0_VGV_MMCF_A.xls",sheet=2,col_names=T,skip=2)
colnames(df) <-c("Date","National","Alaska","Alaska_onshore","Alaska_State","Arkansas","California","Calif_onshore","California_State","Federal_Offshore_Calif","Colorado","Offshore_Gulf_of_Mexico","Kansas","Louisiana","Louisiana_onshore","Louisiana_State","Montana","New_Mexico","North_Dakota","Ohio","Oklahoma","Pennsylvania","Texas","Texas_onshore","Texas_State_Offshore","Utah","West_Virginia","Wyoming")
df$Year <- year(df$Date)
Alaska <- df %>% mutate(State="Alaska",volume=Alaska/National) %>% select(Year,State,volume)
Arkansas <- df %>% mutate(State="Arkansas",volume=Arkansas/National) %>% select(Year,State,volume)
California <- df %>% mutate(State="California",volume=California/National) %>% select(Year,State,volume)
Colorado <- df %>% mutate(State="Colorado",volume=Colorado/National) %>% select(Year,State,volume)
Kansas <- df %>% mutate(State="Kansas",volume=Kansas/National) %>% select(Year,State,volume)
Louisiana <- df %>% mutate(State="Louisiana",volume=Louisiana/National) %>% select(Year,State,volume)
Montana <- df %>% mutate(State="Montana",volume=Montana/National) %>% select(Year,State,volume)
New_Mexico <- df %>% mutate(State="New Mexico",volume=New_Mexico/National) %>% select(Year,State,volume)
North_Dakota <- df %>% mutate(State="North Dakota",volume=North_Dakota/National) %>% select(Year,State,volume)
Ohio <- df %>% mutate(State="Ohio",volume=Ohio/National) %>% select(Year,State,volume)
Oklahoma <- df %>% mutate(State="Oklahoma",volume=Oklahoma/National) %>% select(Year,State,volume)
Pennsylvania <- df %>% mutate(State="Pennsylvania",volume=Pennsylvania/National) %>% select(Year,State,volume)
Texas <- df %>% mutate(State="Texas",volume=Texas/National) %>% select(Year,State,volume)
Utah <- df %>% mutate(State="Utah",volume=Utah/National) %>% select(Year,State,volume)
West_Virginia <- df %>% mutate(State="West Virginia",volume=West_Virginia/National) %>% select(Year,State,volume)
Wyoming <- df %>% mutate(State="Wyoming",volume=Wyoming/National) %>% select(Year,State,volume)
######
df <- rbind(Alaska,Arkansas,California,Colorado,Kansas,Louisiana,Montana,New_Mexico,North_Dakota,Ohio,Oklahoma,Pennsylvania,Texas,Utah,West_Virginia,Wyoming) %>% filter(!is.na(volume))
Other <- df %>% group_by(Year) %>% summarize(State="Other",volume=1-sum(volume,na.rm=TRUE))
graph_dat <- full_join(Other,df)
graph_dat$volume <- 100*graph_dat$volume
stacked <- ggplot(data=graph_dat,aes(x=Year,y=volume,fill=State)) + geom_area(postion='stacked') + scale_x_continuous(n.breaks = 10)+ylab(NULL)
ggsave(stacked,file="flared.jpeg")

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\begin{frame}{About Me}
\begin{columns}[c] % The "c" option specifies centered vertical alignment while the "t" option is used for top vertical alignment
\column{.45\textwidth} % Left column and width
\textbf{Experience}
\begin{itemize}
\item PhD candidate in Mineral and\newline Energy Economics % at Colorado School of Mines
\item Mineral and Energy Economics, M.S.
\item Petroleum Engineering, B.S.
\item Worked as a data analyst for oil companies
\end{itemize}
\textbf{Personal}
\begin{itemize}
\item{Coding and Linux}
\item{Fly fishing}
\item{Camping}
\end{itemize}
\column{.5\textwidth} % Right column and width
\includegraphics[width=\columnwidth,height=\textheight,keepaspectratio]{./img/fish.jpg}
\tiny Greenback trout caught at Rocky Mountain National Park
\end{columns}
\end{frame}

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@ -41,7 +41,7 @@
\begin{columns}[c] % The "c" option specifies centered vertical alignment while the "t" option is used for top vertical alignment
\column{.45\textwidth} % Left column and width
\textbf{Factors of the Wyoming Market}
\textbf{Factors of the Wyoming market}
\begin{itemize}
\item Increasing flaring rates
\item Regulatory concerns about emissions
@ -52,8 +52,11 @@
\end{itemize}
\column{.5\textwidth} % Right column and width
Percentage of U.S. Flaring by State
\includegraphics[width=\columnwidth,height=0.85\textheight,keepaspectratio]{./img/flared.jpeg}
%\includegraphics[width=\columnwidth,height=0.43\textheight,keepaspectratio]{./img/flaring.jpg}
Filler: Include heat map of US flaring
\end{columns}
\end{frame}

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%------------------------------------------------
\begin{frame}{Bitcoin Mining Rewards}
Two sources of income for Bitcoin Miners, a Block Reward and a User Fee.
Two sources of income for Bitcoin Miners, a Block Reward and a User fee
\newline
\begin{center}
\textbf{Constant Miner Reward}
Constant Miner Reward
\begin{formal}
``The steady addition of a constant amount of new coins is analogous to gold miners expending resources to add gold to circulation. In our case, it is CPU time and electricity that is expended.''
\begin{list}{$-$}
@ -14,10 +14,10 @@
\end{center}
%Current reward is 6.5 Bitcoin
\begin{center}
\textbf{Variable User Fees}
Variable User Fees
\begin{formal}
%The incentive can also be funded with transaction fees. If the output value of a transaction is less than its input value, the difference is a transaction fee that is added to the incentive value of the block containing the transaction. Once a predetermined number of coins have entered circulation, the incentive can transition entirely to transaction fees and be completely inflation free.
``The incentive can also be funded with transaction fees\ldots Once a predetermined number of coins have entered circulation, the incentive can transition entirely to transaction fees.''
``The incentive can also be funded with transaction fees\ldots Once a predetermined number of coins have entered circulation, the incentive can transition entirely to transaction fees''
\begin{list}{$-$}
\item{Satoshi Nakamoto}
\end{list}

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\begin{frame}[plain]{Understanding the Bitcoin Mining Market}
\begin{center}
\includegraphics[width=\textwidth,height=0.85\textheight,keepaspectratio]{./img/Bitcoin_miners.jpg}
\end{center}
\end{frame}

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%------------------------------------------------
\begin{frame}{Conclusion}
% The market for Bitcoin can create a new coproduct in oil production, acting like a subsidy. The revenue increase is sensitive to the price of bitcoin but is likely to persist even if the price of bitcoin drops.
% There is spatial variation in the size of the subsidy to oil production. The effect is predicted to shift the location of wells generally north, to lower population and higher GOR states.
% Bitcoin mining is starting to be used to increase the profits of oil wells in remote areas. States like Wyoming could see an increase in oil production of \(\approx 1.4\%\) Thethe U.S. has a lower average effect.
Bitcoin miners are starting to use flared natural gas as an afforable source of electricity. This will have long run impact on the oil market.
\begin{itemize}
% \item{Bitcoin mining can become a coproduct to oil production}
\item{The price of Bitcoin affects the price paid for the natural gas}
\item{A subisdy effect will persist even when Bitcoin prices are low}
\item{The profitability depends on geology}
\item{Bitcoin mining will disproportionately effect states like Wyoming, and North Dakota}
\end{itemize}
Stand in
\end{frame}

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%------------------------------------------------
\begin{frame}{Data}
\begin{enumerate}
\item{Enverus}
\begin{itemize}
\item{U.S. well data}
\item{Gas hookup company}
\item{SPUD date}
\end{itemize}
\item{Energy Information Administrations}
\begin{itemize}
\item{Population weighted cooling degree days (CDD)}
\item{Population weighted heating degree days (HDD)}
\item{Storage Levels}
\item{Price data}
\end{itemize}
\item{National Oceanic and Atmospheric Administration}
\begin{itemize}
\item{Disaster events}
\end{itemize}
\end{enumerate}
Stand in
\end{frame}

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\begin{frame}{Market Linkage}
\tikzstyle{market} = [rectangle, rounded corners, text centered,draw=black,fill=orange!30,minimum width=3cm,minimum height=1cm]
\tikzstyle{inputmarket} = [rectangle, rounded corners, text centered,draw=black,fill=green!30,minimum width=3cm,minimum height=1cm]
\tikzstyle{output} = [rectangle, rounded corners, text centered,draw=black,fill=blue!30,minimum width=3cm,minimum height=1cm]
\tikzstyle{both} = [rectangle, text centered,draw=black,fill=red!30,minimum width=3cm,minimum height=1cm]
\tikzstyle{input} = [rectangle, text centered,draw=black,fill=blue!30]
\tikzstyle{arrow} = [thick,dash dot, ->,>=stealth]
\tikzstyle{arrowsolid} = [thick, ->,>=stealth]
\begin{tikzpicture}[node distance=2cm]
\node (Bitcoin)[market] {Bitcoin Mining};
\node (Oil)[market,left of=Bitcoin,xshift=10cm] {Drilling Wells};
\node (BTCP)[inputmarket,above of=Bitcoin] {Bitcoin Price};
\node (OILP)[inputmarket,above of=Oil,xshift=4cm] {Oil Price};
\node (GASP)[inputmarket,above of=Oil,xshift=.5cm] {Gas Price};
\node (BGASP)[inputmarket, left of=GASP,xshift=-2cm] {Bitcoin Price for Gas};
\node (Gas)[output,below of=Oil,xshift=-3.5cm] {Gas};
\node (Oil_out)[output,below of=Oil] {Oil};
\node (BTCOUT)[output,below of=Bitcoin] {Mining Hash};
\node (Elect)[both,below of=Gas] {Electricity Price};
\draw [arrow] (BGASP) -- (Oil);
\draw [arrow] (BTCP) -- (Bitcoin);
\draw [arrow] (OILP) -- (Oil);
\draw [arrow] (GASP) -- (Oil);
\draw [arrow] (Gas) -- (Elect);
\draw [arrow] (Elect) -- (Bitcoin);
\draw [arrow] (Bitcoin) -- (BGASP);
\draw [arrowsolid] (Bitcoin) -- (BTCOUT);
\draw [arrowsolid] (Oil) -- (Oil_out);
\draw [arrowsolid] (Oil) -- (Gas);
\end{tikzpicture}
\end{frame}

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@ -1,42 +1,31 @@
%------------------------------------------------
\begin{frame}{Key Questions}
\textbf{What are the long term regional welfare changes that can be expected as Bitcoin mining becomes a coproduct of oil?}
\begin{enumerate}
\item{How much extra revenue will oil producers receive?}
\item{How will levels of drilling change?}
\item{How will the location of of drilling change?}
\end{enumerate}
\end{frame}
\begin{frame}{Strategy}
\textbf{What are the long run regional welfare changes that can be expected as Bitcoin mining becomes a coproduct of oil?}
\pause
\begin{itemize}
\item{Identify the incentives}
\item What type of incentives are created?
\begin{itemize}
\item{Microeconomics model of Bitcoin mining}
\item{Upstream oil production model}
\item{Microeconomics model of Bitcoin mining \& oil production choices}
\end{itemize}
\pause
\item{Find regional variation of the incentives}
\item What is the regional distribution of these incentives?
\begin{itemize}
\item{Collect well attribute data}
\item{Estimate of gas produced in oil wells}
\item{Identify wells that do not have a gas pipeline}
\item{Collection of well attribute data}
\end{itemize}
\pause
\item{Identify responses of oil producers in each region}
\item How might producers respond in each region?
\begin{itemize}
\item{Estimate response to oil and gas price changes}
\item{Econometric estimates at the state-basin level of elasticity of supply}
\item{Forecast new wells \& oil production}
\item{Econometric estimates state-basin level elasticity of supply}
\end{itemize}
\pause
\item{\emph{Future Work:} Estimate other welfare changes }
\item How will consumer and producer welfare change?
\begin{itemize}
\item{Model revenue changes}
\item{Engineering based pollution estimates}
\item{Local externality counterfactual}
\end{itemize}
\end{itemize}
%\textbf{Results in counterfactual oil production by geologic basin and state, in key metrics.}
\pause
\textbf{Results in counterfactual oil production by geologic basin and state, in key metrics.}
\end{frame}

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\begin{frame}{Mechanisms}
When Bitcoin miners pay for flared gas, the change in income is equivalent to a subsidy on oil production.
\newline
\newline
\textbf{Direct Effects}
\begin{enumerate}
\item{More drilling}
\item{Different location of wells}
\item{Bitcoin miners clean the gas}
\end{enumerate}
\end{frame}
\begin{frame}{Outcomes}
\begin{columns}[c] % The "c" option specifies centered vertical alignment while the "t" option is used for top vertical alignment
\column{.5\textwidth} % Left column and width
\textbf{Certain Outcomes}
\begin{itemize}
\item{Increase in number of wells}
\item{Increase in profits}
\item{Decrease in price of oil}
\item{Non-decreasing price of gas}
\end{itemize}
\column{.5\textwidth} % Left column and width
\textbf{Uncertain Outcomes}
\begin{itemize}
\item{More pollution: More wells drilled}
\item{Less pollution: Gas is cleaned}
\item{Localized benefits: New location of wells}
\item{Localized costs: New location of wells}
\end{itemize}
\end{columns}
\end{frame}

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\begin{frame}{Bitcoin Mining Market Structure}
\begin{center}
% \includegraphics[width=\textwidth,height=0.8\textheight,keepaspectratio]{./img/SDMining.png}
\begin{adjustbox}{width=\textwidth,height=0.85\textheight,keepaspectratio}
\begin{tikzpicture}[domain=0:4]
\def\qone{4}
\draw[very thin,color=gray] (-0.1,-0.1) grid (11.9,6.7);
\draw[- >,thick] (-0.2,0) -- (12,0) node[right] {$Hash$};
\draw[- >,blue,thick] (5.2,0.6) parabola (9,5.5) node[left] {Supply} ;
\draw[blue,thick] (0,0.3) -- (5.2,0.6) ;
\fill[black] (5.2,0.6) circle (2pt);
\draw (5.2,1) node[above] {Functional shift};
\draw[red] (6,3.5) node[left] {Total Revenue (\$)};
\draw[red] (5.5,3) node[left] {\(y=m\cdot x \)};
\draw[cyan] (8,1) node[above] {MR=m};
\draw[cyan] (10.5,2) node[above] {\(MR=m\cdot\)(1+x-k)};
\draw[- >,dashed,thick] (9.4,0) -- (9.4,5.8) node[above] {Capital Constraint (k)};
\draw[- >,thick] (0,-0.2) -- (0,6.9) node[above] {$\frac{\$}{BTC}$};
\draw[- >,thick, color=red] (0,0)--(11.5,5.5) ;
\draw[thick, color=cyan] (0,1)--(9.4,1) ;
\draw[- >,thick, color=cyan] (9.4,1)--(11,2.0909) ;
\end{tikzpicture}
\end{adjustbox}
\includegraphics[width=\textwidth,height=0.8\textheight,keepaspectratio]{./img/SDMining.png}
\end{center}
\end{frame}

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@ -2,7 +2,7 @@
\begin{frame}{Bitcoin Mining}
\begin{columns}[t] % The "c" option specifies centered vertical alignment while the "t" option is used for top vertical alignment
\column{.45\textwidth} % Left column and width
\textbf{Rewards and Fees}
\textbf{Rewards and fees}
\begin{enumerate}
\item{Awarded by ``lottery''}
\item{Lottery completes \(\approx \) every 10 minutes}
@ -19,11 +19,11 @@
\mbox{}
\newline
\newline
\textbf{Model of Single Period Returns}
\textbf{Model of single period returns}
\newline
\(Revenue=\text{Total Reward}\cdot \frac{\text{Tickets Owned}}{\text{All Tickets}}\)
\newline
\(Costs=\text{Electricity Used}\cdot\text{Price of Electricity}\)
\(Costs=\text{Electricity used}\cdot\text{Price of Electricity}\)
\newline
\(\text{Tickets Owned}=f(\text{Computer Output},\text{Electricity Used})\)
\newline

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@ -7,11 +7,11 @@
Where \(R_{i,t}\) is the revenue of miner \(i\in I\), at time t. \(q_{i}\) is the hash power of a miner i, and \(Q^{-i}_{t}\) is the hash of all other miners. The miner reward is \(\eta\)
\begin{block}{Revenue change from t to t+1}
\begin{align}
\begin{align*}
% R_{i,t+1}-R_{i,t}=\eta \cdot\frac{q_{i}}{Q^{-i}_{t+1}-Q^{-i}_{t}}
% \\
\%\Delta R=\%\Delta P_{btc}(1-\epsilon)
\end{align}
\end{align*}
\end{block}
If the Bitcoin price elasticity of hash \(\epsilon\) is greater than one (elastic), than a decrease in price will \alert{increase profits} for the low marginal cost producers, like the miners using flared gas.
If the Bitcoin price elasticity of hash \(\epsilon\) is elastic, than a decrease in price will \textbf{\emph{increase}} revenue, for low marginal cost producers.
\end{frame}

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\begin{frame}{Oil and Gas Production: Assumptions }
\textbf{Assumptions}
\begin{enumerate}
\item{Engineer probabilistically knows the production path of each well }
\item{Marginal production choice is to drill a new well in a particular location}
\item{Future production is modeled by a best fit Arps model}
\item{Constant discount rate of 4.5\%}
\end{enumerate}
\end{frame}

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@ -1,3 +1,12 @@
\begin{frame}{Oil and Gas Production: Assumptions }
\textbf{Assumptions}
\begin{enumerate}
\item{Engineer probabilistically knows the production path of each well }
\item{Marginal production choice is to drill a new well in a particular location}
\item{Future production is modeled by a best fit Arps model}
\item{Constant discount rate of 4.5\%}
\end{enumerate}
\end{frame}
\begin{frame}{Oil and Gas Production: Econometric Model }
\begin{block}{Estimated model}
@ -5,15 +14,14 @@
Q_{O,b,t}=\beta_{1} Q_{O,b,t-1}+\beta_{2} P_{WTI,t-1}+\beta_{3} P_{HH,t-1}+\beta_{4}\theta_{t}+\gamma_{t,b}+\epsilon_{b,t}
\end{equation}
\end{block}
Where \(Q_{O,b,t}\) is the net present oil produced in a basin state pair b, at time t, \(P_{WTI}\) is the West Texas Intermediate futures price, \(P_{HH}\) is the futures price of the Henry Hub spot market, \(\theta_{t}\) is a month dummy, and \(\gamma_{b,t}\) is a variable that represents the amount of monetary damage from natural disasters.\footnote{(Gilbert and Gavin, 2020)}\newline
Where \(Q_{O,b,t}\) is the net present oil produced in a basin state pair b, at time t, \(P_{WTI}\) is the West Texas Intermediate futures price, \(P_{HH}\) is the futures price of the Henry Hub spot market, \(\theta_{t}\) is a month dummy, and \(\gamma_{b,t}\) is a variable that represents the amount of monetary damage from natural disasters.\newline
\textbf{Three-stage least squares is used with instruments of:}
\textbf{2SLS is used, with instruments of:}
\begin{enumerate}
\item{Oil refinery shocks}
\item{Natural gas storage shocks}
\item{VAR model residuals of oil refinery volumes, and gas storage}
\item{Regional population weighted cooling and heating degree days}
\item{Sum of the standard deviation of each instrument over the preceding 12 months}
\item{Sum of the standard of each instrument over the last 12 months}
\end{enumerate}
\end{frame}

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\begin{frame}[plain]{Understanding Oil Production Decisions}
\begin{center}
\includegraphics[width=\textwidth,height=0.85\textheight,keepaspectratio]{./img/Well.jpg}
\end{center}
\end{frame}

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\begin{frame}{Other Research}
\begin{columns}[c] % The "c" option specifies centered vertical alignment while the "t" option is used for top vertical alignment
\column{.45\textwidth} % Left column and width
\textbf{Previous Topics of Research}
\begin{itemize}
\item Ground water with USDA grant \newline (loos et al.,2022) % \footnote{(loos et al.,2022)} %
\item Critical materials
\item Wind energy
\item CGE and electricity grids
\item Institutional economics in resource management
\end{itemize}
\column{.5\textwidth} % Right column and width
% \scalebox{.5}{\includegraphics{./img/SLV_Map.png} % scales both width and height by 0.5
\includegraphics[width=\columnwidth,height=\textheight,keepaspectratio]{./img/SLV_Map.png}
% \scalebox{.1}{\includegraphics{./img/SLV_Map.png}} % scales both width and height by 0.5
\end{columns}
\end{frame}

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\begin{frame}[plain]{Questions}
\huge
\begin{center}
Thank you for your time
\end{center}
\end{frame}

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%------------------------------------------------
\begin{frame}{Results}
\begin{columns}[c] % The "c" option specifies centered vertical alignment while the "t" option is used for top vertical alignment
\column{.5\textwidth}
\tiny
\input{tables/reg.tex}\footnote{Year/Month fixed effects omitted}\footnote{All reported values are logged}
\column{.5\textwidth} % Left column and width
\normalsize
\tiny
\begin{block}{Long Run Effect on Oil Production}
\begin{equation}
\Delta Q_{O}= \Delta P_{WTI}\cdot\beta_{2}\left[\sum_{t=1}^{\infty}\left( \beta_{1}^{t}\right)+ 1\right]
\end{equation}
\end{block}
\normalsize
\center
%\(\beta_{1}=0.198\),\(\beta_{2}=0.143\)
\begin{equation*}
\Delta Q_{O}= 0.18\cdot \Delta P_{WTI}
\end{equation*}
\end{columns}
Stand in
\end{frame}
\begin{frame}{Initial Estimates}
\textbf{United States}
\begin{itemize}
\item{Subsidy of 0.98\% to WTI }
\item{\(\Delta Q_{US}\approx 0.18\%\)}
\end{itemize}
\textbf{Wyoming}
\begin{itemize}
\item{Subsidy of 2.13\% to WTI }
\item{\(\Delta Q_{Wy}\approx 1.43\% \)\footnote{Elasticity of 0.67 (Mason et all,2017)}}
\end{itemize}
\end{frame}

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% Beamer does not support BibTeX so references must be inserted manually as below
\footnotesize{
\begin{thebibliography}{99}
\bibitem[mason]{p1} Mason, Roberts (2018)
\newblock Price Elasticity of Supply and Productivity: An Analysis of Natural Gas Wells in Wyoming
\newblock \emph{The Energy Journal} 39(S1), 79 -- 101.
%-------
\bibitem[gilbert]{p2} Gilbert, Gavin (2020)
\newblock Drill-Bit Parity: Supply-Side Links in Oil and Gas Markets
\newblock \emph{Journal of the Association of Environmental and Resource Economists} 7(S4), 619 -- 658.
%-------
\bibitem[loos]{p3} Loos, Gebben et al. (2022)
\newblock Individual to collective adaptation through incremental change in Colorado groundwater governance
\newblock \emph{Frontiers in Environmental Science} (Sec. Environmental Economics and Management ) V10
\bibitem[Smith, 2012]{p1} John Smith (2012)
\newblock Title of the publication
\newblock \emph{Journal Name} 12(3), 45 -- 678.
\end{thebibliography}
}
\end{frame}

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% Table created by stargazer v.5.2.3 by Marek Hlavac, Social Policy Institute. E-mail: marek.hlavac at gmail.com
% Date and time: Mon, Oct 31, 2022 - 04:40:50 PM
\begin{table}[!htbp] \centering
\caption{U.S. Elasticity of Oil Supply}
\label{}
\begin{tabular}{@{\extracolsep{1pt}}lc}
\\[-1.8ex]\hline
\hline \\[-1.8ex]
& \multicolumn{1}{c}{\textit{Dependent variable:}} \\
\cline{2-2}
\\[-1.8ex] & Net Present Oil at 5\% (log) \\
\hline \\[-1.8ex]
Lag of Net Present Oil& 0.198$^{***}$ \\
& (0.060) \\
WTI Price & 0.143$^{**}$ \\
& (0.071) \\
Henry Hub Price & 0.151$^{***}$ \\
& (0.054) \\
Constant & 14.862$^{***}$ \\
& (1.145) \\
& \\
\hline \\[-1.8ex]
Observations & 295 \\
R$^{2}$ & 0.804 \\
Adjusted R$^{2}$ & 0.774 \\
Residual Std. Error & 0.173 (df = 255) \\
F Statistic & 26.828$^{***}$ (df = 39; 255) \\
\hline
\hline \\[-1.8ex]
\textit{Note: Preliminary results} & \multicolumn{1}{r}{$^{*}$p$<$0.1; $^{**}$p$<$0.05; $^{***}$p$<$0.01} \\
\end{tabular}
\end{table}

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# Job_Talk
hi Alexc ttt
Beamer code for job talk presentation, and supplemental useful material.