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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 Commodities
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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 Labor Productivity
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| 653 |
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|a Unemployment
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| 653 |
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|a Electric Utilities
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| 653 |
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|a Investments: Energy
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| 653 |
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|a Capacity utilization
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| 653 |
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|a Electricity
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| 653 |
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|a Aggregate Labor Productivity
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| 653 |
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|a Industrial capacity
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| 653 |
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|a Human Capital
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| 653 |
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|a Production
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| 653 |
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|a Wages
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| 653 |
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|a Skills
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| 653 |
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|a Aggregate Human Capital
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| 653 |
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|a Employment
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| 653 |
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|a Electric utilities
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| 653 |
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|a Intergenerational Income Distribution
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| 653 |
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|a Capacity
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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 Production and Operations Management
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| 653 |
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|a Total factor productivity
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| 653 |
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|a Occupational Choice
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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 Macroeconomics
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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 Investment & securities
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| 653 |
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|a Productivity
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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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