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180827 ||| eng |
| 020 |
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|a 9781484363973
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| 100 |
1 |
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|a Gurara, Daniel
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| 245 |
0 |
0 |
|a Losing to Blackouts: Evidence from Firm Level Data
|c Daniel Gurara, Dawit Tessema
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| 260 |
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|a Washington, D.C.
|b International Monetary Fund
|c 2018
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| 300 |
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|a 45 pages
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| 651 |
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4 |
|a Ethiopia, The Federal Democratic Republic of
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| 653 |
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|a Productivity
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| 653 |
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|a Investments: Energy
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| 653 |
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|a Capital and Total Factor Productivity
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| 653 |
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|a Cost
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| 653 |
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|a Industrial productivity
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| 653 |
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|a Electricity
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| 653 |
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|a Production
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| 653 |
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|a Aggregate Labor Productivity
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| 653 |
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|a Unemployment
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| 653 |
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|a Skills
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| 653 |
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|a Total factor productivity
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| 653 |
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|a Aggregate Human Capital
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| 653 |
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|a Labor Productivity
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| 653 |
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|a Macroeconomics: Production
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| 653 |
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|a Industrial capacity
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| 653 |
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|a Commodities
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| 653 |
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|a Capacity utilization
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| 653 |
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|a Legal Monopolies and Regulation or Deregulation
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| 653 |
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|a Macroeconomics
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| 653 |
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|a Electric Utilities
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| 653 |
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|a Occupational Choice
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| 653 |
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|a Wages
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| 653 |
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|a Capacity
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| 653 |
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|a Labor productivity
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| 653 |
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|a Investment & securities
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| 653 |
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|a Intergenerational Income Distribution
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| 653 |
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|a Human Capital
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| 653 |
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|a Employment
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| 653 |
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|a Production and Operations Management
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| 653 |
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|a Electric utilities
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| 700 |
1 |
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|a Tessema, Dawit
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b IMF
|a International Monetary Fund
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| 490 |
0 |
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|a IMF Working Papers
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| 028 |
5 |
0 |
|a 10.5089/9781484363973.001
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| 856 |
4 |
0 |
|u https://elibrary.imf.org/view/journals/001/2018/159/001.2018.issue-159-en.xml?cid=46032-com-dsp-marc
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 330
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| 520 |
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|a Many developing economies are often hit by electricity crises either because of supply constraints or lacking in broader energy market reforms. This study uses manufacturing firm census data from Ethiopia to identify productivity losses attributable to power disruptions. Our estimates show that these disruptions, on average, result in productivity losses of about 4–10 percent. We found nonlinear productivity losses at different quantiles along the productivity distribution. Firms at higher quantiles faced higher losses compared to firms around the median. We observed patterns of systematic shutdowns as firms attempt to minimize losses
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