RegData: A numerical database on industry‐specific regulations for all United States industries and federal regulations, 1997–2012

Al‐Ubaydli, Omar; McLaughlin, Patrick A.

doi:10.1111/rego.12107

Cited by 174 publications

(93 citation statements)

References 25 publications

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“…"Finance intensive" is set of business (excluding finance) industries with the highest finance shares constituting roughly half the value-added weight. Al-Ubaydli and McLaughlin (2015) produced the regulation data, available at regdata.org. The website summarizes the data as "RegData is a database that quantifies the number of individual restrictions in the Code of Federal Regulations and…determines which industries are targeted by those regulatory restrictions."…”

Section: Data Appendixmentioning

confidence: 99%

The Disappointing Recovery of Output after 2009

Fernald¹,

Hall²,

Stock³

et al. 2017

105

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U.S. output has expanded only slowly since the recession trough in 2009, even though the unemployment rate has essentially returned to a pre-crisis, normal level. We use a growthaccounting decomposition to explore explanations for the output shortfall, giving full treatment to cyclical effects that, given the depth of the recession, should have implied unusually fast growth. We find that the growth shortfall has almost entirely reflected two factors: the slow growth of total factor productivity, and the decline in labor force participation. Both factors reflect powerful adverse forces that are largely unrelated to the financial crisis and recession-and that were in play before the recession.A data appendix is available at http://www.nber.org/data-appendix/w23543Under standard growth theory, slower TFP growth and falling participation should raise the capital-output ratio, since less investment is needed simply to keep pace with technology and the labor force. This higher capital-output ratio reduces the marginal product of capital and lowers the equilibrium real interest rate. By 2016, the cyclically-adjusted capital-output ratio had returned to its trend growth path, but not above that path as growth theory would suggest.Possibly, additional capital deepening lies ahead. Or, other factors might have depressed the steady-state capital-output ratio. Gutierrez and Philippon (2016) argue that investment has been held back by rising market power, which lowers the marginal revenue product of capital and thus discourages capital formation. Alexander and Eberly (2016) attribute part of the decline in investment to the relocation of capital-intensive manufacturing industries outside the U.S. Importantly, neither of these hypotheses is obviously related to the recession.Although our account leaves little room for demand-side explanations of persistently slow growth, we do investigate demand-side forces. Two quantitatively important factors are the unusually slow growth of federal government purchases during 2012 through 2014, which we associate in part with the sequester; and the delay in the usual rebound of state and local government purchases, which we associate with the housing market collapse and the financial crisis. Absent such delays, output growth would have been higher early in the recovery. The black line in Figure 1 would have intersected the red line sooner, implying less cumulative loss in output (and employment). But, looking over the entire recovery, the seeds of the disappointing growth in output were sown prior to the recession in the form of a declining participation rate and slow TFP growth. Indeed, the scaling back of consumption and investment plans in response to slowing TFP growth could induce its own recessionary pressures beyond those from the financial crisis alone. Blanchard, Lorenzoni, and L'Huillier (2017) show that this effect could be large, especially with interest rates at the zero lower bound.Turning now to the details of our analysis, we use counterfactual "cyclically adjusted" paths t...

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Section: Data Appendixmentioning

confidence: 99%

The Disappointing Recovery of Output after 2009

Fernald¹,

Hall²,

Stock³

et al. 2017

105

View full text Add to dashboard Cite

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“…Figure 3formalizes this insight by showing a positive and highly significant correlation between the mean P Risk it across firms in a given 2-digit sector and an index of regulatory constraints(Al-Ubaydli and McLaughlin, 2017), as well as the share of the sector's revenue accounted for by federal government contracts.…”

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confidence: 90%

Firm-Level Political Risk: Measurement and Effects*

Hassan

Hollander

Lent

et al. 2019

The Quarterly Journal of Economics

802

420

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We adapt simple tools from computational linguistics to construct a new measure of political risk faced by individual U.S. firms: the share of their quarterly earnings conference calls that they devote to political risks. We validate our measure by showing that it correctly identifies calls containing extensive conversations on risks that are political in nature, that it varies intuitively over time and across sectors, and that it correlates with the firm’s actions and stock market volatility in a manner that is highly indicative of political risk. Firms exposed to political risk retrench hiring and investment and actively lobby and donate to politicians. These results continue to hold after controlling for news about the mean (as opposed to the variance) of political shocks. Interestingly, the vast majority of the variation in our measure is at the firm level rather than at the aggregate or sector level, in the sense that it is captured neither by the interaction of sector and time fixed effects nor by heterogeneous exposure of individual firms to aggregate political risk. The dispersion of this firm-level political risk increases significantly at times with high aggregate political risk. Decomposing our measure of political risk by topic, we find that firms that devote more time to discussing risks associated with a given political topic tend to increase lobbying on that topic, but not on other topics, in the following quarter.

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“…1 Regulation index for FRA and ICC/STB 3 RegData is a database that quantifies regulation by industry over time using text analysis software. It was created by Omar Al-Ubaydli and Patrick A. McLaughlin, and is broadly described in their recent journal article (Al-Ubaydli and McLaughlin 2015). It is also described and freely distributed on the website www.regdata.org.…”

Section: Measuring Railroad Regulationmentioning

confidence: 98%

“…The database, RegData, counts the number of restrictions (words such as ''must, '' ''shall,'' etc. ) in each chapter of the Code of Federal Regulations (CFR) and produces an index that measures the amount of regulation that applies to each 3-digit industry in the North American Industrial Classification System (NAICS) (Al-Ubaydli and McLaughlin 2015). Thus, RegData allows us to assess whether a discrete change in the amount of safety or economic regulation applied to railroads is correlated with the level of railroad safety.…”

Section: Introductionmentioning

confidence: 99%

The Regulatory Determinants of Railroad Safety

Ellig

McLaughlin

2016

Rev Ind Organ

Self Cite

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The dramatic improvement in railroad safety since the 1970s has been accompanied by a substantial increase in safety regulation and a substantial reduction in economic regulation after 1980. We assess the effects of both regulatory changes on railroad safety with the use of RegData: a new data set that was developed by one of the authors that measures the amount of regulation that is imposed by specific regulatory agencies on specific industries. We find that partial economic deregulation is associated with improved safety. Safety regulation was most closely associated with improved railroad safety during the period when economic regulation curtailed railroads' incentives to operate safely.

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RegData: A numerical database on industry‐specific regulations for all United States industries and federal regulations, 1997–2012

Cited by 174 publications

References 25 publications

The Disappointing Recovery of Output after 2009

The Disappointing Recovery of Output after 2009

Firm-Level Political Risk: Measurement and Effects*

The Regulatory Determinants of Railroad Safety

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