1. Introduction and Overview Fig. 1....

1. Introduction and Overview
Fig. 1.	COVID-19 Deaths, by Region, 2020–2024.	2
Fig. 2.	Macroeconomic Indicators, End of 2019–End of 2023.	4
Fig. 3.	US Airline Carrier Indicators, December 2019–June 2023.	4
2. The Heterodox Economics of Passenger Airlines, Plagues, Pandemics, and Other Unhealthy Occurrences
Fig. 1.	The Layers of Economic Institutions.	22
Fig. 2.	A Synthesized Path of Epidemics/Pandemics.	25
Fig. 3.	Global Scheduled Commercial Airline Flights.	31
3. Nonmarket Strategies of Airlines in a COVID-19 World and Beyond
Fig. 1.	Net Profit and Loss of Airlines Worldwide From 2004 to 2022.	51
Fig. 2.	Economic Profit/Loss by Subsector in Aviation 2020.	53
Fig. 3.	Evolution of Revenue Passenger Kilometers (2017–2022).	53
Fig. 4.	Nonmarket Strategic Approaches of Airlines in Response to Governmental COVID-19 Measures.	61
4. COVID-19 Uncertainty and the Cross-Sectional Stock Returns of Airlines
Fig. 1.	US Stock Market Return in 2020.	72
Fig. 2.	PUI Over January 2020–February 2022.	76
Fig. 3A.	PUI and FSCs Over January 2020–February 2022.	77
Fig. 3B.	PUI and LCCs Over January 2020–February 2022.	78
Fig. 4A.	Scatter Plot of Average Daily Return Against Pandemic Beta, March 2020–May 2020.	80
Fig. 4B.	Scatter Plot of Average Daily Return Against Pandemic Beta, March 2020–Feb 2022.	81
Fig. 5.	The Coefficient $β_{i}^{m p}$ Across Airlines.	82
Fig. 6A.	R-Square of Eq. (3) Over the Sample Period.	83
Fig. 6B.	The Coefficient λ_pt of Eq. (3) Over the Sample Period.	84
5. COVID-19 and Airlines: A Final Analysis Through the Lens of Complex Networks
Fig. 1.	Overview on Historical Aviation Crises.	93
Fig. 2.	The Example for Metrics.	98
Fig. 3.	Comparison of the Number of Flights in Major Aviation Markets.	102
Fig. 4.	Biannual Snapshots of Airline Networks in This Study.	105
Fig. 5.	Year-to-Year Changes in the Number of Nodes and Edges.	107
Fig. 6.	Three Centrality Metrics and Clustering Coefficient.	108
Fig. 7.	Accumulative Percentages of Center and Periphery.	110
Fig. 8.	Average Shortest Path Length (ASPL) and Global Efficiency (GE).	111
6. Rebuilding Airline Networks in the Post-COVID-19 Era: New Network Configurations in Europe?
Fig. 1.	Variation in Supply (09/2019 vs. 09/2022).	125
Fig. 2.	Variation in Frequencies and Aircraft Size (09/2019–09/2022).	126
Fig. 3.	Air France Domestic Network 2019 and 2022.	132
Fig. 4.	Iberia's OD Not From or to Main Hub in Madrid 2019; 2022.	134
Fig. 5.	Wizz Air Nonmonopoly Routes, September 2019 and 2022.	137
7. Competition Between Full-Service Carrier and Low-Cost Carrier and the Impact of COVID-19 Pandemic: Evidence From China
Fig. 1.	LCC Penetration in Different Markets Around the World as of March 2022.	154
Fig. 2.	Financial Performance for the Big Three Airlines and Spring Airlines (2019–2022, in 100 Million RMB).	158
Fig. 3.	Normalized Ratio of Routes Compared to 2019 (Jan 2020 to Dec 2022).	160
Fig. 4.	Normalized Ratio of Routes Served by LCCs and FSCs Compared to 2019 (January 2020 to December 2022).	161
Fig. 5.	The Ratio of Density1 Routes Served by LCCs and FSCs (January 2020 to December 2022).	165
8. Measuring the Risk of COVID-19 Spread via the US Air Transportation Network
Fig. 1.	Confirmed Cases of COVID-19 in the United States – Cases per 100,000 Population on January 8, 2021.	185
Fig. 2.	Inbound Passenger Volume per Capita by County in the United States (2020).	186
Fig. 3.	Distribution of Destination Counties by Inbound Passengers per Capita Intervals for 2020 and 2021.	186
Fig. 4.	COVID-19 Relative Risk to Destination Counties (2020).	187
Fig. 5.	Distribution of Destination Counties by COVID-19 Relative Risk Intervals for 2020 and 2021.	187
Fig. 6.	Scatter Plot of County-Level Analysis for Relationship Between Population Density and Risk of COVID-19 Importation to Destination (2020–2021).	191
10. COVID-19’s Effect on the Technical Efficiency and Productivity of US Airlines: An Industry Sectoral Analysis
Fig. 1.	Graphical Representation of Technical Efficiency and Technical Change.	254
Fig. 2.	Graphical Representation of Technical Efficiency and Technical Change With Increasing Demand for Cargo-Only Service.	256
Fig. 3.	Graphical Representation of Technical Efficiency and Technical Change With Decreasing Demand for Passenger Service.	257
Fig. 4.	Output-Oriented DEA Based on Similar Representation From Coelli et al. (2005).	269
11. Analysis of the Impacts of COVID-19 on US Airline Schedule Planning and Service Delivery, 2018 to 2022
Fig. 1.	Comparison of Monthly Available Departure Seats for Domestic and International Seats, the United States, European Common Aviation Area (ECAA), and China, January 2018–December 2023. The Monthly Available Seats for the Last Month Before and First Month of the Pandemic Are Indicated (in Millions).	285
Fig. 2.	Cirium and T-100 Comparison of US Domestic and International Scheduled and Performed Seats and Passengers, January 2018–December 2022.	293
Fig. 3.	Monthly Available Departure Seats (Domestic and International) as a Proportion of the Equivalent Month in 2019, for the United States, European Common Aviation Area (ECAA), and China, January 2018–December 2023.	294
Fig. 4.	(a) Average Monthly Difference Between US Scheduled and Actual Departures by Hub Type, 2004–2022. (b) Average Monthly Difference Between US Scheduled and Actual Departures by Hub Type, 1/2017–12/2022. (c) Detail for Large Hubs of Total Scheduled and Performed Departures, January 2017–December 2022.	299
Fig. 5.	Total Annual Difference Between Scheduled and Performed Departures by Carrier and Hub Type, 2014–2022.	301
Fig. 6.	Monthly Difference Between Scheduled and Performed Departures and Load Factors (Bottom Figure) for the Four Largest (Mainline) Airlines, American Airlines (AA), Delta Air Lines (DL), United Airlines (UA), and Southwest Airlines (WN), January 2018 to December 2022.	303
Fig. 7.	Monthly Percentage Difference Between Scheduled and Performed Departures for the Three Largest FSCs and Their Regional Affiliates, 2018–2022.	306
Fig. 8.	Monthly Load Factors for the Three Largest FSCs and Their Regional Affiliates, 2018–2022.	307
Fig. 9.	Average Monthly Percentage Difference Between Actual Schedule and Published Scheduled Seats up to 5 Months Forward, 2021–2023.	309
Fig. 10.	Standard Deviation of Monthly Percentage Difference Between Actual and Published Scheduled Seats up to 5 Months Forward, 2021–2023.	309
12. Starting From the Backhaul: Evaluating the Effects of COVID-19 on Airline Traffic Flows
Fig. 1.	Mean Fronthaul Load Factors by Carrier Country of Origin.	332
Fig. 2.	Mean Backhaul (BH) Load Factors (LF) by Carrier Country of Origin.	333
Fig. 3.	Mean Fronthaul (FH) Load Factors (LF) and Stringency Scores by Carrier Country of Origin.	334
Fig. 4.	Mean Backhaul (BH) Load Factors (LF) and Stringency Scores by Carrier Country of Origin.	335
13. Global Airline Employment and the COVID-19 Pandemic: Impacts, Comparisons, and Implications for the Future
Fig. 1.	Total Passengers Boarded and Metric Tons of Cargo Moved, 2005–2022.	343
Fig. 2.	Difference in Airline Year-End Employment 2019–2020 and 2019–2021.	346
Fig. 3.	Employees per Departure in 2019, 2020, and 2021 at the Airlines With the Greatest Number of Employees per Departure.	347
Fig. 4.	Composition of Global Airline Employment (a) 2019 and (b) 2020.	349
Fig. 5.	Results From the Pandemics Impact on Airline Employment Year-over-year Percentage Growth Rate Across Airline Business Models and Regions.	350
Fig. 6.	Percent of (a) Total Pandemic Workforce Reductions by Region and (b) Total Government Relief.	352
Fig. 7.	Difference (%) in Airline Year-End Employment From 2019 to 2022.	353
Fig. 8.	Total Employment, Revenue Passenger Miles (RPM), and Available Seat Miles (ASM) in the US Airline Industry, 1990–2023.	354
Fig. 9.	Total Government Support per Employee and per Full-Time Employee (FTE) to Airlines.	357
Fig. 10.	Total, Full-Time (FT), and Part-Time (PT) Employment in the US Airline Industry, 1990–2021.	358
Fig. 11.	Total Employment in the US Airline Industry for Women and Men, 1990–2021.	359

1. Introduction and Overview
Fig. 1.	COVID-19 Deaths, by Region, 2020–2024.	2
Fig. 2.	Macroeconomic Indicators, End of 2019–End of 2023.	4
Fig. 3.	US Airline Carrier Indicators, December 2019–June 2023.	4
2. The Heterodox Economics of Passenger Airlines, Plagues, Pandemics, and Other Unhealthy Occurrences
Fig. 1.	The Layers of Economic Institutions.	22
Fig. 2.	A Synthesized Path of Epidemics/Pandemics.	25
Fig. 3.	Global Scheduled Commercial Airline Flights.	31
3. Nonmarket Strategies of Airlines in a COVID-19 World and Beyond
Fig. 1.	Net Profit and Loss of Airlines Worldwide From 2004 to 2022.	51
Fig. 2.	Economic Profit/Loss by Subsector in Aviation 2020.	53
Fig. 3.	Evolution of Revenue Passenger Kilometers (2017–2022).	53
Fig. 4.	Nonmarket Strategic Approaches of Airlines in Response to Governmental COVID-19 Measures.	61
4. COVID-19 Uncertainty and the Cross-Sectional Stock Returns of Airlines
Fig. 1.	US Stock Market Return in 2020.	72
Fig. 2.	PUI Over January 2020–February 2022.	76
Fig. 3A.	PUI and FSCs Over January 2020–February 2022.	77
Fig. 3B.	PUI and LCCs Over January 2020–February 2022.	78
Fig. 4A.	Scatter Plot of Average Daily Return Against Pandemic Beta, March 2020–May 2020.	80
Fig. 4B.	Scatter Plot of Average Daily Return Against Pandemic Beta, March 2020–Feb 2022.	81
Fig. 5.	The Coefficient $β_{i}^{m p}$ Across Airlines.	82
Fig. 6A.	R-Square of Eq. (3) Over the Sample Period.	83
Fig. 6B.	The Coefficient λ_pt of Eq. (3) Over the Sample Period.	84
5. COVID-19 and Airlines: A Final Analysis Through the Lens of Complex Networks
Fig. 1.	Overview on Historical Aviation Crises.	93
Fig. 2.	The Example for Metrics.	98
Fig. 3.	Comparison of the Number of Flights in Major Aviation Markets.	102
Fig. 4.	Biannual Snapshots of Airline Networks in This Study.	105
Fig. 5.	Year-to-Year Changes in the Number of Nodes and Edges.	107
Fig. 6.	Three Centrality Metrics and Clustering Coefficient.	108
Fig. 7.	Accumulative Percentages of Center and Periphery.	110
Fig. 8.	Average Shortest Path Length (ASPL) and Global Efficiency (GE).	111
6. Rebuilding Airline Networks in the Post-COVID-19 Era: New Network Configurations in Europe?
Fig. 1.	Variation in Supply (09/2019 vs. 09/2022).	125
Fig. 2.	Variation in Frequencies and Aircraft Size (09/2019–09/2022).	126
Fig. 3.	Air France Domestic Network 2019 and 2022.	132
Fig. 4.	Iberia's OD Not From or to Main Hub in Madrid 2019; 2022.	134
Fig. 5.	Wizz Air Nonmonopoly Routes, September 2019 and 2022.	137
7. Competition Between Full-Service Carrier and Low-Cost Carrier and the Impact of COVID-19 Pandemic: Evidence From China
Fig. 1.	LCC Penetration in Different Markets Around the World as of March 2022.	154
Fig. 2.	Financial Performance for the Big Three Airlines and Spring Airlines (2019–2022, in 100 Million RMB).	158
Fig. 3.	Normalized Ratio of Routes Compared to 2019 (Jan 2020 to Dec 2022).	160
Fig. 4.	Normalized Ratio of Routes Served by LCCs and FSCs Compared to 2019 (January 2020 to December 2022).	161
Fig. 5.	The Ratio of Density1 Routes Served by LCCs and FSCs (January 2020 to December 2022).	165
8. Measuring the Risk of COVID-19 Spread via the US Air Transportation Network
Fig. 1.	Confirmed Cases of COVID-19 in the United States – Cases per 100,000 Population on January 8, 2021.	185
Fig. 2.	Inbound Passenger Volume per Capita by County in the United States (2020).	186
Fig. 3.	Distribution of Destination Counties by Inbound Passengers per Capita Intervals for 2020 and 2021.	186
Fig. 4.	COVID-19 Relative Risk to Destination Counties (2020).	187
Fig. 5.	Distribution of Destination Counties by COVID-19 Relative Risk Intervals for 2020 and 2021.	187
Fig. 6.	Scatter Plot of County-Level Analysis for Relationship Between Population Density and Risk of COVID-19 Importation to Destination (2020–2021).	191
10. COVID-19’s Effect on the Technical Efficiency and Productivity of US Airlines: An Industry Sectoral Analysis
Fig. 1.	Graphical Representation of Technical Efficiency and Technical Change.	254
Fig. 2.	Graphical Representation of Technical Efficiency and Technical Change With Increasing Demand for Cargo-Only Service.	256
Fig. 3.	Graphical Representation of Technical Efficiency and Technical Change With Decreasing Demand for Passenger Service.	257
Fig. 4.	Output-Oriented DEA Based on Similar Representation From Coelli et al. (2005).	269
11. Analysis of the Impacts of COVID-19 on US Airline Schedule Planning and Service Delivery, 2018 to 2022
Fig. 1.	Comparison of Monthly Available Departure Seats for Domestic and International Seats, the United States, European Common Aviation Area (ECAA), and China, January 2018–December 2023. The Monthly Available Seats for the Last Month Before and First Month of the Pandemic Are Indicated (in Millions).	285
Fig. 2.	Cirium and T-100 Comparison of US Domestic and International Scheduled and Performed Seats and Passengers, January 2018–December 2022.	293
Fig. 3.	Monthly Available Departure Seats (Domestic and International) as a Proportion of the Equivalent Month in 2019, for the United States, European Common Aviation Area (ECAA), and China, January 2018–December 2023.	294
Fig. 4.	(a) Average Monthly Difference Between US Scheduled and Actual Departures by Hub Type, 2004–2022. (b) Average Monthly Difference Between US Scheduled and Actual Departures by Hub Type, 1/2017–12/2022. (c) Detail for Large Hubs of Total Scheduled and Performed Departures, January 2017–December 2022.	299
Fig. 5.	Total Annual Difference Between Scheduled and Performed Departures by Carrier and Hub Type, 2014–2022.	301
Fig. 6.	Monthly Difference Between Scheduled and Performed Departures and Load Factors (Bottom Figure) for the Four Largest (Mainline) Airlines, American Airlines (AA), Delta Air Lines (DL), United Airlines (UA), and Southwest Airlines (WN), January 2018 to December 2022.	303
Fig. 7.	Monthly Percentage Difference Between Scheduled and Performed Departures for the Three Largest FSCs and Their Regional Affiliates, 2018–2022.	306
Fig. 8.	Monthly Load Factors for the Three Largest FSCs and Their Regional Affiliates, 2018–2022.	307
Fig. 9.	Average Monthly Percentage Difference Between Actual Schedule and Published Scheduled Seats up to 5 Months Forward, 2021–2023.	309
Fig. 10.	Standard Deviation of Monthly Percentage Difference Between Actual and Published Scheduled Seats up to 5 Months Forward, 2021–2023.	309
12. Starting From the Backhaul: Evaluating the Effects of COVID-19 on Airline Traffic Flows
Fig. 1.	Mean Fronthaul Load Factors by Carrier Country of Origin.	332
Fig. 2.	Mean Backhaul (BH) Load Factors (LF) by Carrier Country of Origin.	333
Fig. 3.	Mean Fronthaul (FH) Load Factors (LF) and Stringency Scores by Carrier Country of Origin.	334
Fig. 4.	Mean Backhaul (BH) Load Factors (LF) and Stringency Scores by Carrier Country of Origin.	335
13. Global Airline Employment and the COVID-19 Pandemic: Impacts, Comparisons, and Implications for the Future
Fig. 1.	Total Passengers Boarded and Metric Tons of Cargo Moved, 2005–2022.	343
Fig. 2.	Difference in Airline Year-End Employment 2019–2020 and 2019–2021.	346
Fig. 3.	Employees per Departure in 2019, 2020, and 2021 at the Airlines With the Greatest Number of Employees per Departure.	347
Fig. 4.	Composition of Global Airline Employment (a) 2019 and (b) 2020.	349
Fig. 5.	Results From the Pandemics Impact on Airline Employment Year-over-year Percentage Growth Rate Across Airline Business Models and Regions.	350
Fig. 6.	Percent of (a) Total Pandemic Workforce Reductions by Region and (b) Total Government Relief.	352
Fig. 7.	Difference (%) in Airline Year-End Employment From 2019 to 2022.	353
Fig. 8.	Total Employment, Revenue Passenger Miles (RPM), and Available Seat Miles (ASM) in the US Airline Industry, 1990–2023.	354
Fig. 9.	Total Government Support per Employee and per Full-Time Employee (FTE) to Airlines.	357
Fig. 10.	Total, Full-Time (FT), and Part-Time (PT) Employment in the US Airline Industry, 1990–2021.	358
Fig. 11.	Total Employment in the US Airline Industry for Women and Men, 1990–2021.	359

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