Economics of modern energy boomtowns: Do oil and gas shocks differ from shocks in the rest of the economy?

Abstract

The U.S. shale boom has intensified interest in how the expanding oil and gas sector affects local economic performance. Research has produced mixed results and has not compared how energy shocks differ from equal--sized shocks elsewhere in the economy. What emerges is that the estimated impacts of energy development vary by region, empirical methodology, as well as the time horizon that is considered. This paper captures these dimensions to present a more complete picture of energy boomtowns. Utilizing U.S. county data, we estimate the effects of changes in oil and gas extraction employment on total employment growth as well as growth by sector. We compare this to the effects of equal--sized shocks in the rest of the economy to assess whether energy booms are inherently different. The analysis is performed separately for nonmetropolitan and metropolitan counties using instrumental variables. We difference over 1--, 3--, 6--, and 10--year time periods to account for county fixed effects and to assess responses across different time horizons. The results show that in nonmetro counties, energy sector multiplier effects on total county employment first increase up to 6--year horizons and then decline for 10--year horizons. In metro counties, 1--year differences analysis suggests crowding out though the multipliers are insignificant in longer horizons. We also observe positive spillovers to the nontraded goods sector, while spillovers are small or negative for traded goods. Yet, equal--sized shocks in the rest of the economy produce more jobs on average than oil and gas shocks, suggesting that policymakers should seek more diversified development.

Heterogeneity in the local employment multipliers in the United States

“…The 2SLS estimated coefficient of 1.072 is relatively larger than the reduced form of estimate of 0.829. The averaged reduced form of multiplier ranges between 1.600 and 1.829, which is within the range of typically estimated local employment multipliers (see, e.g., Bartik & Sotherland, 2019;Jones & Yang, 2018;Partridge et al, 2017;Tsvetkova & Partridge, 2016;van Dijk, 2017van Dijk, , 2018. The 2SLS estimates may appear to be an improvement over the OLS estimates but as noted by Bartik and Sotherland (2019), the 2SLS approach omits some of the agglomeration and congestion effects following a demand shock.…”

“…In constructing their shift-share instruments, Partridge et al (2017) and Tsvetkova and Partridge (2016) used all industries, both tradables and nontradables. In constructing their shift-share instruments, Partridge et al (2017) and Tsvetkova and Partridge (2016) used all industries, both tradables and nontradables.…”

“…Starting from the seminal contribution of Moretti (2010), a growing body of empirical studies has estimated local employment multipliers (Adams, 2016;Bartik & Sotherland, 2019;van Dijk, 2017van Dijk, , 2018Fuller & Chapman, 2018;Gerolimetto & Magrini, 2016;Jones & Yang, 2018;Partridge, Rickman, Rose Olfert, & Tan, 2017;Tsvetkova & Partridge, 2016). Moretti (2010) used the shift-share instrumental variable's strategy to estimate the local multiplier effect in the US between 1980 and 2000.…”

The shale revolution and entrepreneurship: An assessment of the relationship between energy sector expansion and small business entrepreneurship in US counties

“…The empirical investigations of the relationship between energy sector growth in the US counties and total employment effects find positive, but rather modest and varying across space, impacts (Brown, 2014;Munasib & Rickman, 2015;Tsvetkova & Partridge, 2016;Weber, 2012Weber, , 2014Weinstein, 2014). These studies stop short of shedding light on the distribution of the effects across proprietors and WS segments of local economies.…”

“…Existing research documents job-creating effects of the recent expansion in oil and gas industry in the US (Lee, 2015;Tsvetkova & Partridge, 2016;Weber, 2012;Weinstein, 2014). To assess the distribution of these gains between self-employed and paid segments of the local economies, we separately estimate the effects of energy sector on self-employed (SE) and wage and salary (WS) job creation in nonmetro and metro counties after accounting for legacy effects.…”