Labor Market Dynamics and The Unconventional Natural Gas Boom: Evidence from the Marcellus Region...
-
Upload
anthony-dawson -
Category
Documents
-
view
213 -
download
0
Transcript of Labor Market Dynamics and The Unconventional Natural Gas Boom: Evidence from the Marcellus Region...
Labor Market Dynamics and The Unconventional Natural Gas Boom:
Evidence from the Marcellus Region
Tim Komarek, Old Dominion University
Prepared for the USAEE
Resource Boom and Labor Dynamics USAEE 2015
Source: Energy Information Administration
6,636 increase
Natural Gas Production in United States
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Shale Production in United States
Source: Energy Information Administration
9,299 increase
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
• Local Labor Market Effects- Growing literature examining the jobs and
income resulting from the fracking boom
- Short-run benefits through the multiplier process
- Long-run implications of the “resource curse”- Bidding up factor prices - Crowding-out in the traded sector (Dutch
Disease)
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
• Objectives
- Econometrically estimate the impact of resource
extraction activity on the labor market
- Utilize the timing of fracking activity to trace out the dynamics of the labor market response
- Exploit a natural experiment from differing policies related to fracking between NY and PA, OH and WV in the Marcellus region
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
• Exploit a natural experiment in the Marcellus region- New York ban on unconventional gas drilling- Pennsylvania, Ohio, and West Virginia that
permitted fracking
- Led to dramatically different natural gas production in each state
- Comparing counties in the Marcellus region before and after the fracking boom
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Shale Formations in the Northeastern United States
Source: Energy Information Administration
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Total County Level Unconventional Wells Spudded 2001-2013
Source: Author’s calculations from Drillinginfo.com
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Timing of the Fracking Boom (50 + wells): PA, OH, WV
Source: Author’s calculations from Drillinginfo.com
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
• Exploit a natural experiment in the Marcellus region- New York ban on unconventional gas drilling- Pennsylvania, Ohio, and West Virginia that
permitted fracking
- Led to dramatically different natural gas production in each state
- Comparing counties in the Marcellus region before and after the fracking boom
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Natural Gas Production For New York and Pennsylvania
Source: Author’s calculation from ERS County-level Oil and Gas Production
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
• County level data for NY, PA, OH and WV 2001 – 2013- 3,026 county-years
• Labor market data from BEA Regional Economic Accounts- Total employment, population, wages and wages
per job- Employment and wages by sector
- Manufacturing, construction, transportation retail trade, accommodations
• Horizontal wells from Drillinginfo.comResource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
• Unconventional wells from Drillinginfo.com- # of bore holes drilled per year in
unconventional formations
- Production data is highly variable from year to year due to measurement and reporting challenges
- Wells drilled more closely tied to economic activity related to fracking
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Distribution of Unconventional Natural Gas Wells
Source: Author’s calculations from Drillinginfo.com
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
50
Ycst = Σi=0 β-i HighFrackingcst + αc + Wst + tZc + εct
• Ycst = log of labor market variable
• HighFrackingcst = 1 if wells >50
• LowFrackingcst = 1 if 0 < wells < 50
• Unweighted OLS with standard errors clustered by county
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
• Economic theory suggests potentially different effects over time
• Estimates show a positive employment and wage effect that increases over the course of the boom period
• See wages being bid up in manufacturing, construction and transportation sectors
• No evidence of crowding-out in the traded sector (manufacturing)
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Resource Boom and Labor Dynamics USAEE 2015
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
• The current shale gas boom differs from the energy boom-bust cycle of the 1970s and 1980s- Based on technological innovations (hydraulic
fracturing and horizontal drilling)- Extracts gas from shale formations- EIA estimates the U.S. reserves hold 70 years of
natural gas supply
• Local impacts on communities “boomtowns” where extraction takes place
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
Resource Boom and Labor Dynamics USAEE 2015
Motivation Identification Strategy Data Empirical Model Results
VARIABLES Total Employment
Total Employment
Earnings per Worker
Earnings per Worker
High Fracking 0.0284*** 0.0368*** 0.0331** 0.0439**
(0.00968) (0.0107) (0.0165) (0.0177)
Low Fracking 0.000757 0.00288 -0.0015 0.00142
(0.00337) (0.00347) (0.00317) (0.00333)
Observations 1,911 3,016 1,911 3,016
Control Group NY All Counties NY All Counties
County FE Yes Yes Yes Yes
State-Time FE Yes Yes Yes Yes
County*Year Trend Yes Yes Yes Yes