The Local Economic Impacts of Natural Resource Extraction LSU Law Center March 4, 2016

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The Local Economic Impacts of Natural Resource Extraction LSU Law Center March 4, 2016 Mallory C. Vachon, Ph.D. Center for Energy Studies Louisiana State University

Shale Boom The past decade has been a dynamic one for the energy industry During the early and mid-2000s, the combination of rising prices and technological advancements, led to the extraction of previously unrecoverable shale reserves The shale boom saw the expansion of extraction activity in new geographic areas within the United States, including North Dakota and Pennsylvania Since late 2014, oil prices have fallen due to a combination of global demand and supply factors 2

Shale Boom What are the local economic implications of natural resource extraction? Resource booms lead to large increases in earnings and employment These labor market impacts have important secondary effects: Education Migration Social insurance participation What are the underlying economic mechanisms? What are the magnitudes of these effects? 3

Oil Production (Thousands of Barrels) Natural Gas production (Million Cubic Feet) History of the Shale Boom 350,000 300,000 250,000 200,000 150,000 100,000 50,000 - Oil and Natural Gas Production, 1991-2016 3,000,000 2,500,000 2,000,000 1,500,000 1,000,000 500,000 - Oil Production (Thousands of Barrels) Source: Energy Information Administration Natural Gas Production (Million Cubic Feet) However, these time series mask some important local variation in production 4

History of the Shale Boom - Oil Oil Production (Millions of Barrels) State 2000 2015 Change United States 2,130 3,442 62% Texas 443 1,262 185% North Dakota 32 429 1241% Source: Energy Information Administration 5

History of the Shale Boom Natural Gas Natural Gas Production (Bcf) State 2000 2015 Change United States 2,000 2,800 40% Texas 477 720 51% Pennsylvania 13 429 3200% Source: Energy Information Administration 6

Earnings and Employment Growth 7

Labor Economics 101 Y Labor Supply and Demand S E Resource price/technology shock shifts the labor demand curve outward from D to D Earnings increase from Y to Y Y E N N D D Employment increases from N to N In practice, the sizes of these effects depend on the slopes of the labor supply and demand curves 8

Employment (Thousands of Individuals) Oil Price ($/bbl) Empirical Evidence 600 500 400 300 200 100 0 Oil Prices and Employment, 1990-2015 140 120 100 80 60 40 20 0 Oil and Gas Employment WTI ($/bbl) Sources: Bureau of Labor Statistics and Energy Information Administration Clearly a positive relationship between prices and employment, but magnified during the shale boom 9

Shale Boom and Earnings Overall, there were large increases in earnings in resourcerich areas: Marchand (2012) finds a 22% increase in earnings per energy worker in Canada from 1996 through 2006 Weber (2012) finds a 26% increase in earnings in the Western U.S. from 1999 through 2008 Vachon (2015a and 2015b) find an approximately 30% increase in earnings in Montana, North Dakota, and South Dakota from 2005 through 2010 Other studies from the most recent boom as well as other booms are in line with these results 10

Shale Boom and Employment Overall, there were large increases in employment in resource-rich areas: Feyrer, Mansur, and Sacerdote (2015) find that every million dollars is associated with an additional 0.78 jobs within the county Marchand (2012) finds a 47% increase in earnings per energy worker in Canada from 1996 through 2006 11

Earnings and Employment While these earnings and employment effects are significant and garner much media attention, there are many secondary effects that may have more far-reaching impacts Education: potentially suboptimal investment in education Migration: large population changes that impact local governments Social insurance participation: implications for federal and state governments 12

Secondary Effects: Education, Migration, and Social Insurance 13

Economic Mechanism Economists and others have long been concerned with understanding how individuals respond to random changes in income The shale boom provides a natural experiment through which we can examine the impact of a change in earnings on various outcomes 14

Education As earnings increase, the value to employment increases relative to the value of high school completion Given that many oil and gas jobs are generally filled by lowerskilled, male workers, workers often substitute away from education and into the labor market during a boom In 2000, the male high school dropout rate was 10% in states with shale reserves (Cascio and Narayan, 2015) The shale boom increased the dropout rate by 3 to 3.5 percentage points These results suggest potentially suboptimal investments in education in response to an increase in earnings 15

Migration Economic theory suggests that individuals will choose to live in an area that provides the highest wages for a given level of local amenities Earnings growth in oil counties significantly increases net migration Net migration rate in North Dakota oil counties increased by 2.6 percentage points (Vachon, 2015b) Economically sizeable effects Pre-boom net migration rate was -1.5 percent (out-migration) Impact of boom is +2.6 percentage points Post-boom net migration rate is 1.1 percent (in-migration) The boom transformed these counties from population-losers to populationgainers, making them among the fastest-growing counties in the country 16

Social Security Disability Insurance The Social Security Disability Insurance (DI) program is the largest income replacement program in the United States for non-elderly adults Growth in the DI program since the 1970s coincided with a well-documented decline in wages and labor force participation of low-skilled workers 17

Social Security Disability Insurance Since DI is more attractive as outside options decline, a key question in labor economics is the extent to which changes in the labor economic conditions led to changes in DI program participation Coal boom of the 1970s reduced DI payments by 1.25% decrease for coal counties relative to non-coal counties in Appalachia (Black, Daniel, and Sanders, 2002) Shale boom reduced DI payments by 2.5% for oil counties relative to nooil counties in Montana, North Dakota, and South Dakota (Vachon, 2015a) Shale boom reduced DI participation by 1.6% for oil counties relative to no-oil counties in Montana, North Dakota, and South Dakota (Vachon, 2015a) 18

Center for Energy Studies Decline in Oil Prices Nearly 70% decline in oil prices June 2014: $105.48 September 2015: $34.66 Due to a combination of supply and demand factors: Supply US shale boom OPEC continues production Demand Lower than expected growth in Europe and China 19

Center for Energy Studies Decline in Oil Prices Eight states with highest levels of energy industry employment Alaska, Louisiana, New Mexico, North Dakota, Oklahoma, Texas, West Virginia, Wyoming Employment in these states will likely decrease with falling oil prices Oil State Employment Response to Decrease in Oil Prices New Mexico -0.7% West Virginia -0.7% Texas -1.2% Louisiana -1.6% Alaska -1.8% North Dakota -2.0% Oklahoma -2.3% Wyoming -4.3% Source: Brown and Yucel (2013) 20

Center for Energy Studies Decline in Oil Prices A decrease in oil and gas prices represents a negative shock to resource-rich areas that will reduce earnings and employment With regard to the secondary effects, falling incomes and employment opportunities should: Reverse the observed trends in dropout rates Reduce migration Increase DI payments and participation 21

mcvachon@lsu.edu www.enrg.lsu.edu 22