What goes up must come down? The recent economic cycles of the four most oil and gas dominated states in the US

Rickman, Dan S.; Wang, Hongbo

doi:10.1016/j.eneco.2020.104665

Cited by 13 publications

(15 citation statements)

References 41 publications

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“…We apply the weight matrix to each corresponding outcome indicator and calculate their synthetic outcomes to obtain the SCM estimates of the shale effect. Before delving into the detailed estimation results, we follow Rickman and Wang (2020) to compare the synthetic control matching quality against the 27‐ANC average in the donor pool, which is akin to the unweighted DiD. We calculate: (i) the difference between the synthetic and actual values of the treated ANC; and (ii) the difference between the 27‐ANC average value and the actual value of the treated ANC.…”

Section: Resultsmentioning

confidence: 99%

“…Previous studies suggest that the SCM results are not sensitive to small changes in the treatment year (Munasib & Rickman, 2015; Rickman et al, 2017). For the donor pool, we start with the 30 non‐energy states used in Rickman and Wang (2020) minus Ohio. We then remove New Jersey and Rhode Island from the donor pool because of the absence of non‐metropolitan counties in these states.…”

Section: Datamentioning

confidence: 99%

“…In the late 1990s, the oil and gas industry in the United States began to combine horizontal drilling and hydraulic fracturing techniques for commercial drilling in the Barnett shale play across the south‐central states (Jacquet et al, 2018). Employment in the oil and gas sector started to rise in the early 2000s (Rickman & Wang, 2020), with the production from shale plays in Colorado, Texas, and Wyoming underwent significant increases in subsequent years (Weber, 2012). Not long after the initial success in the south‐central US, the first natural gas well was drilled in the Marcellus play, which underlies parts of New York, Pennsylvania, Ohio, West Virginia, Maryland, and Virginia (IER, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…We consider several metrics, including employment growth, income growth, poverty rate, and population growth in OH, PA, and WV. Furthermore, we evaluate if the three states suffered from the 2014–2016 energy price decline and industry bust found in Rickman and Wang (2020) for Louisiana, North Dakota, Oklahoma and Wyoming.…”

Section: Introductionmentioning

confidence: 99%

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Impact of Marcellus and Utica shale exploitation on Ohio, Pennsylvania, and West Virginia Regional Economies: A synthetic control analysis

Huang

Etienne

2021

Papers in Regional Science

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We use the synthetic control method to determine the economic impact of shale exploitation on Ohio, Pennsylvania, and West Virginia. Estimation results are mixed. The shale development decreased the poverty rate and increased the employment growth rate in Pennsylvania and West Virginia in the short run. Top oil and gas producing counties in West Virginia also experienced short-term personal income growth due to fracking. However, most of the positive impacts disappeared a few years after the initial boom periods. The shale development did not bring significant economic benefits to Ohio. Further, shale drilling activities exert a potential long-term negative effect on population growth in all three states.

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Section: Resultsmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact of Marcellus and Utica shale exploitation on Ohio, Pennsylvania, and West Virginia Regional Economies: A synthetic control analysis

Huang

Etienne

2021

Papers in Regional Science

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“…Furthermore, it allows the effect of the fuel price intervention to vary over time. Since its conception, the SCM has been applied in numerous studies across a variety of disciplines evaluating, for example, the effects of health policy (Bauhoff, 2014;Kreif et al, 2016), immigration policy (Bohn et al, 2014), crime (Pinotti, 2015), and, more recently, energy policy (Rickman et al, 2017;Rickman and Wang, 2020;Jardón et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Price Effects of the Austrian Fuel Price Fixing Act: A Synthetic Control Study

2021

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Fuel prices are commonly perceived to be excessively high, which regularly triggers political discussions about fuel price regulations. Consumers demand stricter fuel price regulations to provide transparency about the current price level and to protect them from sudden price fluctuations. Such regulations are already in place in several countries, but whether they indeed help lower the overall fuel price level is unclear. In this paper, we study the effect of Austria's Fuel Price Fixing Act on gasoline and diesel price levels. Using the synthetic control method, we construct a counterfactual and estimate Austria's price trends in absence of the intervention. Our empirical results suggest, that immediately after the Fuel Price Fixing Act came into effect, gasoline prices are 23.4% lower than the synthetic control predicts. The effect on diesel prices appears to be less pronounced and amounts to 6.6% lower prices. Austria's fuel price regulation seems to have been effective in terms of gasoline prices but may need further refinements to effectively tackle diesel prices as well.

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Shedding light on truck driver supply and demand: Heterogeneous state‐level recovery of trucking employment following the COVID‐19 employment shock

Phares,

Miller,

Burks

2024

Transp. j.

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Is there a long‐term systemic shortage of truck drivers? We throw light on the underlying context—the demand for and supply of truck drivers—by investigating why states within the contiguous United States showed vastly different rates of recovery of state‐level truck transportation payrolls for May 2020–December 2021 following the negative employment shock brought about by COVID‐19 lockdowns in April 2020. We focus on heterogeneity in the industries that create demand for trucking services: state‐level natural resource extraction, warehousing, and container port activity. We create a state‐level archival data set of truck transportation establishment payrolls from the Quarterly Census of Employment and Wages, which we combine with other archival sources. We test our hypotheses via discontinuous growth curve models estimated using the mixed effects modeling framework. We find states that saw greater declines in natural resource extraction activity had much slower growth in trucking payrolls for May 2020–December 2021, whereas states that saw more warehousing activity growth or were home to large container ports saw faster growth in trucking payrolls. Our work extends theories regarding labor market dynamics in truck transportation and factor market rivalry, in addition to having important implications for managers and policy makers.

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What goes up must come down? The recent economic cycles of the four most oil and gas dominated states in the US

Cited by 13 publications

References 41 publications

Impact of Marcellus and Utica shale exploitation on Ohio, Pennsylvania, and West Virginia Regional Economies: A synthetic control analysis

Impact of Marcellus and Utica shale exploitation on Ohio, Pennsylvania, and West Virginia Regional Economies: A synthetic control analysis

Price Effects of the Austrian Fuel Price Fixing Act: A Synthetic Control Study

Shedding light on truck driver supply and demand: Heterogeneous state‐level recovery of trucking employment following the COVID‐19 employment shock

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