The Economic Impact of the Coal Boom and Bust

By D. Black, Terra McKinnish, Seth G. Sanders. 2005

468 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Public Administration

View Paper: https://www.semanticscholar.org/paper/9578575e6693efd891093d5231649ec7cbe15a54

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. K. Løken
2. D. Fleming
3. T. Measham
4. S. Poelhekke
5. J. Rud
6. F. Aragón
7. Andreas Kotsadam
8. Michael Greenstone

In Finance

1. K. Løken
2. J. Weber
3. T. Measham
4. D. Fleming
5. Melissa S. Kearney
6. F. Aragón
7. Riley Wilson
8. J. Rud

In Public Administration

1. K. Løken
2. J. Weber
3. T. Measham
4. D. Fleming
5. F. Aragón
6. Riley Wilson
7. Melissa S. Kearney
8. J. Rud

Citations in the corpus

• Local economic impacts of an unconventional energy boom: the coal seam gas industry in Australia† (2015, methodology): “Also following Moretti (2010), we employ a two-stage least square (2SLS) specification to estimate these elasticities, but based on an instrumental variable (IV) identifying the treatment areas as in Black et al. (2005) and Marchand (2012). This IV procedure is done to empirically isolate the change”
• A Decade of Natural Gas Development: The Makings of a Resource Curse? (2014, background): “Studies of extractive booms have repeatedly speculated that their labor market effects likely extend beyond the localities where extraction occurs (Black et al., 2005; Michaels, 2010; Weber, 2012).”
• Dutch Disease or Agglomeration? The Local Economic Effects of Natural Resource Booms in Modern America (2018, unknown): “Analogous to Prediction 3, this follows from taking the total derivative of the tradable sector productivity cutoff in Equation (9), and it also requires that the county is “small.”
• Identifying Agglomeration Spillovers: Evidence from Winners and Losers of Large Plant Openings (2010, background): “42 Similarly, input (labor) spillovers may be less pronounced for incumbent plants that produce nationally traded goods (Black et al. 2005). 43 The information on distance is from Weiss (1972). The information on industry concentration is from the Bureau of Census ("Concentration Ratios" 2002).”
• African Mining, Gender, and Local Employment (2014, background): “A study of coal mining counties in the US during the coal boom of the 70’s finds modest local employment spillovers but increasing wage rates (Black et al., 2005).”
• Coal Mining, Economic Development, and the Natural Resource Curse (2015, background): “The coal boom of the 1970s and the bust of the 1980s identified by Black et al. (2005a) are apparent.”
• The Local Economic Impacts of Natural Resource Extraction (2015, background): “Aggregate government statistics at the subnational level are used in countries including for the US coal industry (Black et al., 2005).”
• Income and Health Spending: Evidence from Oil Price Shocks (2013, unknown): “Black et al. (2005) use a similar strategy focusing the coal boom and bust.”
• Tight Labor Markets and the Demand for Education: Evidence from the Coal Boom and Bust (2005, methodology): “11Additionally, Black, McKinnish, and Sanders (2005) use the 1970, 1980, and 1990 PUMS to compare population growth for men and women between coal-mining county groups and county groups without coal mining following a procedure similar to the wage analysis performed in this paper.”
• The effects of a natural gas boom on employment and income in Colorado, Texas, and Wyoming ☆ (2012, background): “Black et al. (2005) estimate how the coal boom and bust in the 1970s and 1980s affected counties in Kentucky, Ohio, Pennsylvania, and West Virginia.”
• Geographic Dispersion of Economic Shocks: Evidence from the Fracking Revolution (2020, unknown): “In 2013, the Energy Information Administration (EIA) projected that (6)Black et al. (2005) find that each coal mining job added to a county during the coal boom created an additional 0.”
• Family income and children's education: Using the Norwegian oil boom as a natural experiment (2010, methodology): “Since we do not have the data to account for the endogeniety of parental education we have to trust the results in Black et al. (2005), who present evidence against a causal relationship between parent and 12See Carneiro and Heckman (2002) for a discussion on IV estimations and credit constraints.”