| Description |
1 online resource (46 pages) |
| Contents |
880-01 Cover; Contents; 1 Background; 2 A Brief History of Outages; 3 Conceptual Framework and Data; 3.1 Conceptual Framework; 3.2 Data; 4 Empirical Strategy; 4.1 Estimating the Productivity Cost of Power Disruptions; 4.2 Firm Response to Outages; 5 Results and Discussion; 5.1 How Costly are Power Disruptions?; 5.2 Do Firms Shutdown to Avoid Bigger Losses?; 6 Concluding Remarks; Appendices; A Unbalanced panel results; B Balanced panel results; List of Figures; 1 A Decision Tree of Firms' Responses to Power Disruption; 2 Alternative Power Disruption Measures |
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880-01/(S 4 Fixed Effects and IV Estimation5 Panel Quantile Regression (aggregate); 6 Panel Quantile Regression (within-industry); 7 Negative Binomial Regression; A.1 Unreliability of Utility Services to Manufacturing Firms; A.2 Electricity Cost as a Share of Total Industrial Cost; A.3 Correlation Between S[(sup)σ] and Possible Reasons for Lower Power Consumption; A.4 Estimated Productivity Losses from Table 4; A.5 Fixed Effects and IV Estimation (with[(sup)σ]); A.6 Estimated Productivity Losses from Table A.5; A.7 Aggregate Production Functions; A.8 Industry Level Production Functions (LP) |
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3 The Productivity Loss from Electricity Disruptions4 Productivity Loss from Power Disruptions; 5 Productivity Loss Due to Power Disruptions (aggregate TFP); 6 Shutdown Incidents Vary by Age; A.1 Productivity Loss from Electricity Disruptions (Table 4, IV model: Col 8); A.2 Within-industry Productivity Loss Due to Power Disruptions; A.3 Within-industry Productivity Loss Due to Power Disruptions; A.4 Productivity Loss from Electricity Disruptions; A.5 Productivity Loss from Electricity Disruptions; List of Tables; 1 Total Number of Firms by ISIC-2; 2 Summary Statistics; 3 Benchmark Pooled OLS |
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A.9 Industry Level Production Functions (ACF)A.10 Industry Level Production Functions (LP); A.11 Industry Level Production Functions (ACF); A.12 Poisson Models; A.13 Alternative to Count Models-Pooled OLS; A.14 Panel Quantile Regressions (using ACF); A.15 Fixed Effects and IV Estimation (balanced panel); A.16 Estimated Productivity Losses from Table A.15; A.17 Fixed Effects and IV Estimation (balanced panel); A.18 Estimated Productivity Losses from Table A.17 |
| Summary |
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 |
| Notes |
Print version record |
| Subject |
Electric power failures -- Developing countries
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Emergency management -- Developing countries
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Electric power failures
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Emergency management
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Developing countries
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| Form |
Electronic book
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| Author |
Tessema, Dawit
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| ISBN |
1484368339 |
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9781484368336 |
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