Wielowymiarowa analiza wrażliwości gospodarczej krajów Unii Europejskiej

ISBN: 978-83-7972-973-9    ISBN (online): 978-83-7972-974-6    ISSN: 0860-2751    OAI    DOI: 10.18276/978-83-7972-974-6
CC BY-SA   Open Access 

Lista wydań / T. (MCDLXI) 1387

Rok wydania:2025
Dziedzina:Dziedzina nauk społecznych
Dyscyplina:ekonomia i finanse
Autorzy: Joanna Brzyska
Uniwersytet Szczeciński

Izabela Szamrej-Baran
0000-0002-9824-362X

Informacje

Wersja elektroniczna publikacji dostępna na licencji CC BY-SA 4.0 po 12 miesiącach od daty wprowadzenia do obrotu: listopad 2025

Wersję drukowaną publikacji można nabyć w sklepie Wydawnictwa Naukowego Uniwersytetu Szczecińskiego: wn.usz.edu.pl/sklep/

Abstrakt

Niniejsza monografia przedstawia kompleksową ocenę i klasyfikację krajów Unii Europejskiej pod względem ich wrażliwości gospodarczej na szoki, ze szczególnym uwzględnieniem pandemii Covid-19. W badaniu zastosowano autorski Syntetyczny Miernik Wrażliwości (SMW) do przeprowadzenia wielowymiarowej analizy wrażliwości ekonomicznej państw członkowskich UE w latach 2018–2023. Badanie dowodzi, że wrażliwość ekonomiczna jest zjawiskiem wielowymiarowym, kształtowanym przez czynniki gospodarcze, strukturalne, instytucjonalne, społeczne i zdrowotne. Przy zastosowaniu analizy skupień zidentyfikowano cztery grupy krajów UE o różnych profilach wrażliwości: klaster nordycki charakteryzujący się wyjątkowo niską wrażliwością, klaster kontynentalny o umiarkowanej wrażliwości, klaster południowoeuropejski o dużej niejednorodności oraz klaster środkowoeuropejski o bardzo wysokim zróżnicowaniu. Badanie ukazało wyraźny geograficzny wzorzec wrażliwości w UE, z niższą wrażliwością w krajach północnych i zachodnich oraz wyższą w regionach południowych i wschodnich. Zaobserwowano zjawisko „odroczonej wrażliwości”, pokazujące wzrost wrażliwości ekonomicznej w większości krajów UE po 2020 roku. Wyniki sugerują potrzebę zróżnicowanego podejścia do polityki gospodarczej, które uwzględnia specyficzne profile wrażliwości różnych grup krajów zamiast wdrażania uniwersalnych rozwiązań.

Bibliografia

1.Acemoglu, D., Chernozhukov, V., Werning, I., Whinston, M. D. (2021). Optimal Targeted Lockdowns in a Multigroup SIR Model. American Economic Review: Insights, 3(4), 487–502. https://doi.org/10.1257/aeri.20200590
2.Acemoglu, D., Robinson, J. A. (2012). Why nations fail: The origins of power, prosperity and poverty. Profile Books.
3.Acemoglu, D., Robinson, J. A. (with Penguin Random House). (2019). The narrow corridor: States, societies, and the fate of liberty. Penguin Press.
4.Aghion, P., Antonin, C., Bunel, S., Jaravel, X. (2020). What Are the Labor and Product Market Effects of Automation? New Evidence from France. Research Briefs in Economic Policy, 225. https://hal.science/hal-03384668
5.Alberola, E., Arslan, Y., Cheng, G., Moessner, R. (2021). Fiscal response to the COVID‐19 crisis in advanced and emerging market economies. Pacific Economic Review, 26(4), 459–468. https://doi.org/10.1111/1468-0106.12370
6.Amiti, M., Redding, S. J., Weinstein, D. E. (2019). The Impact of the 2018 Tariffs on Prices and Welfare. Journal of Economic Perspectives, 33(4), 187–210. https://doi. org/10.1257/jep.33.4.187
7.Atkins, P. J., Mazzi, S., Easter, C. D. (2001). Small States: A Composite Vulnerability Index. W: D. Peretz, R. Faruqi, E. J. Kisanga (red.), Small States in the Global Economy. Commonwealth. https://doi.org/10.14217/9781848599024-en
8.Azmeh, S., Foster, C. (2016). The TPP and the Digital Trade Agenda: Digital Industrial Policy and Silicon Valley’s Influence on New Trade Agreements. LSE International Development Working Paper Series, 16–175.
9.Baldwin, R. E. (2019). The great convergence: Information technology and the new globalization. The Belknap Press of Harvard University Press.
10.Baldwin, R., Freeman, R. (2022). Risks and Global Supply Chains: What We Know and What We Need to Know. Annual Review of Economics, 14(1), 153–180. https:// doi.org/10.1146/annurev-economics-051420-113737
11.Baldwin, R., Lopez‐Gonzalez, J. (2015). Supply‐chain Trade: A Portrait of Global Patterns and Several Testable Hypotheses. The World Economy, 38(11), 1682–1721. https:// doi.org/10.1111/twec.12189
12.Bangalore, M., Hallegatte, S., Bonzanigo, L., Kane, T., Fay, M., Narloch, U., Treguer, D., Rozenberg, J., Vogt-Schilb, A. (2016). Shock Waves: Managing the Impacts of Climate Change on Poverty. Climate Change and Development; World Bank. http://hdl. handle.net/10986/22787
13.Barbero, J., De Lucio, J. J., Rodríguez-Crespo, E. (2021a). Effects of COVID-19 on trade flows: Measuring their impact through government policy responses. PLOS ONE, 16(10), e0258356. https://doi.org/10.1371/journal.pone.0258356
14.Bardazzi, R., Gastaldi, F., Iafrate, F., Pansini, R. V., Pazienza, M. G., Pollastri, C. (2024). Inflation and distributional impacts: Have mitigation policies been successful for vulnerable and energy poor households? Energy Policy, 188, 114082. https://doi. org/10.1016/j.enpol.2024.114082
15.Barrero, J. M., Bloom, N., Davis, S. J., Meyer, B. H. (2021). COVID-19 Is a Persistent Reallocation Shock. AEA Papers and Proceedings, 111, 287–291. https://doi.org/ 10.1257/pandp.20211110
16.Barro, R., Ursúa, J., Weng, J. (2020). The Coronavirus and the Great Influenza Pandemic: Lessons from the “Spanish Flu” for the Coronavirus’s Potential Effects on Mortality and Economic Activity (w26866). National Bureau of Economic Research. https:// doi.org/10.3386/w26866
17.Bąk, A. (2016). Porządkowanie liniowe obiektów metodą Hellwiga i TOPSIS – analiza porównawcza. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, 426. https://doi.org/10.15611/pn.2016.426.02
18.Bąk, A. (2017). Statistical Methods of Variables Selection in Linear Ordering. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, 468, 29–37. https://doi. org/10.15611/pn.2017.468.03
19.Bąk, A. (2018). Comparative analysis of selected linear ordering methods based on empirical and simulation data. Prace naukowe Uniwersytetu Ekonomicznego we Wrocławiu, 508, 19–28. https://doi.org/10.15611/pn.2018.508.02 Bini, E., Garavini, G., Romero, F. (2016). Oil shock: The 1973 crisis and its economic legacy. I.B. Tauris.
20.Birkmann, J., Wisner, B. (2006). Measuring the Un-Measurable. The Challenge of Vulnerability. Studies Of The University: Research Counsel, Education, 6. https://www. researchgate.net/publication/285850126_Measuring_the_un-measurable_the_ challenge_of_vulnerability
21.Blaikie, P., Cannon, T., Davis, I., Wisner, B. (1994). At risk: Natural hazards, people’s vulnerability and disasters. Routledge.
22.Bloom, N., Bunn, P., Mizen, P., Smietanka, P., Thwaites, G. (2025). The Impact of Covid-19 on Productivity. Review of Economics and Statistics, 107(1), 28–41. https://doi.org/ 10.1162/rest_a_01298
23.Błażejczyk-Majka, L. (2018). Zastosowanie analizy skupień w przypadku zmiennych wyrażonych na skali porządkowej. StatSoft Polska. StatSoft Polska. https://www. statsoft.pl/wp-content/uploads/2018/11/analiza_skupien_i_zmienne_na_skali_ porzadkowej.pdf
24.Bogard, W. C. (1989). Bringing social theory to hazards research: Conditions and consequences of the mitigation of environmental hazards. Sociological Perspectives, 31, 147–168.
25.Briguglio, L. (1995). Small island developing states and their economic vulnerabilities. World Development, 23(9), 1615–1632. https://doi.org/10.1016/0305-750X(95)00065-K
26.Briguglio, L., Cordina, G., Farrugia, N., Vella, S. (2009). Economic Vulnerability and Resilience: Concepts and Measurements. Oxford Development Studies, 37(3), 229–247. https://doi.org/10.1080/13600810903089893
27.Brzyska, J., Szamrej-Baran, I. (2021). Covid-19 Economic Vulnerability Index: EU Evidence. Procedia Computer Science, 192, 3551–3559. https://doi.org/10.1016/j.procs.2021.09.128
28.Brzyska, J., Szamrej-Baran, I. (2022). Economic vulnerability assessment of EU countries to the impact of COVID-19 pandemic with the revised CEV index. Procedia Computer Science, 207, 3244–3253. https://doi.org/10.1016/j.procs.2022.09.382
29.Bunge, W. (1962). Theoretical Geography. The Royal University of Lund.
30.Burton, C. G., Toquica, M., Asad, K. M. B., Musori, M. (2022). Validation and development of composite indices for measuring vulnerability to earthquakes using a socio-economic perspective. Natural Hazards, 111(2), 1301–1334. https://doi. org/10.1007/s11069-021-05095-9
31.Burton, I., Kates, R. W., White, G. F. (1978). The Environment As Hazard (First). Oxford University Press.
32.Caldera-Sánchez, A., Gori, F., Röhn, O., De Serres, A. (2016). Strengthening economic resilience: Insights from the post-1970 record of severe recessions and financial crises. OECD Economic Policy Papers, 20.
33.Calderon, C., Norman, L., Schmidt-Hebbel, K. (2005). Does openness imply greater exposure? Policy Research Working Paper. http://documents.worldbank.org/ curated/en/363971468136813314
34.Chambers, R. (1989). Editorial Introduction: Vulnerability, Coping and Policy. IDS Bulletin, 20(2), 1–7. https://doi.org/10.1111/j.1759-5436.1989.mp20002001.x
35.Chang, R., Kaltani, L., Loayza, N. V. (2009). Openness can be good for growth: The role of policy complementarities. Journal of Development Economics, 90, 33–49.
36.Chiu, T., Fang, D., Chen, J., Wang, Y., Jeris, C. (2001). A robust and scalable clustering algorithm for mixed type attributes in large database environment. Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 263–268. https://doi.org/10.1145/502512.502549
37.Claessens, S., Kose, M. A. (2013). Financial crises: Explanations, types, and implications. International Monetary Fund.
38.Clemens, M. A., Lewis, E. G., Postel, H. M. (2018). Immigration restrictions as active labor market policy: Evidence from the Mexican bracero exclusion. American Economic Review, 108(6), 1468–87. https://doi.org/10.1257/aer.20170765
39.Cordina, G. (2004). Economic Vulnerability and Economic Growth: Some Results from a Neo-Classical Growth Modelling Approach. Journal of Economic Development, 29(2), 21–39.
40.Cutter, S. (1993). Living with risk. The geography of technological hazards. Edward Arnold.
41.Cutter, S. (red.) (2001). American Hazardscapes: The Regionalization of Hazards and Disasters (s. 10132). Joseph Henry Press. https://doi.org/10.17226/10132
42.Cutter, S., Hewitt, K. (1984). Interpretations of Calamity from the Viewpoint of Human Ecology. Geographical Review, 74(2), 226. https://doi.org/10.2307/214106
43.di Giovanni, J., Levchenko, A. A. (2008). Trade Openness and Volatility. IMF Working Paper, WP/08/146.
44.Domańska, A., Serwa, D. (2013). Czynniki wrażliwości gospodarek krajów Europy na szoki zewnętrzne na przykładzie skutków kryzysu 2008–2009 – analiza empiryczna. Zeszyty Naukowe SGGW, Polityki Europejskie, Finanse i Marketing, 9(58), 110–124. https://doi.org/10.22630/PEFIM.2013.9.58.9
45.Dow, K., Downing, T. E. (1995). Vulnerability research: Where things stand. National Emergency Training Centre.
46.Economic resilience and trade. (2021). World Trade Organization.
47.Birkmann, B. (red.) (2013). Measuring vulnerability to natural hazards: Towards disaster resilient societies (2nd wyd.). United Nations National Press.
48.Edison, H. J., Levine, R., Ricci, L., Slok, T. (2002). International Financial Integration and Economic Growth. Journal of International Money and Finance, 21.
49.Eichenbaum, M. S., Rebelo, S., Trabandt, M. (2021). The Macroeconomics of Epidemics. The Review of Financial Studies, 34(11), 5149–5187. https://doi.org/10.1093/ rfs/hhab040
50.Elektroniczny Podręcznik Statystyki. (2006). http://www.statsoft.pl/textbook/ stathome.html
51.European Commission. Directorate General for Research and Innovation. (2024).
52.European Innovation Scoreboard 2024. Publications Office. https://data.europa. eu/doi/10.2777/779689
53.European Innovation Scoreboard 2024 Methodology Report. (2024). European Commission, Directorate-General for Research and Innovation. https://research-and- -innovation.ec.europa.eu/document/download/074d5495-433a-440f-bcf9-dc620fce7af1_ en?filename=ec_rtd_eis-2024-methodology-report.pdf
54.Farrugia, N. (2007). The importance of institution building in small island states. Bank of Valletta Review, 36, 57–75.
55.Feindouno, S., Guillaumont, P. (2019). Measuring physical vulnerability to climate change: The PVCCI, an index to be used for international development policies. Ferdi Policy Brief B190, March.
56.Foster, C., Graham, M. (2017). Reconsidering the Role of the Digital in Global Production Networks. Global Networks, 17(1), 68–88.
57.Friedman, M., & Schwartz, A. J. (2008). A monetary history of the United States 1867– 1960. Princeton University Press.
58.Furceri, D., Loungani, P., Ostry, J. D., Pizzuto, P. (2021). Will COVID-19 have long-lasting effects on inequality? Evidence from past pandemics. International Monetary Fund. https://doi.org/10.5089/9781513582375.001
59.Gans, J. (2020). Economics in the Age of COVID-19. PubPub. https://doi.org/10.21428/ a11c83b7.c48fa91b
60.Gatnar, E., Walesiak, M. (2009). Statystyczna analiza danych z wykorzystaniem programu R. Wydawnictwo Naukowe PWN.
61.Gnangnon, S. K. (2022). Effect of Structural Economic Vulnerability on the Participation in International Trade. Journal of Risk and Financial Management, 15(9), 417. https://doi.org/10.3390/jrfm15090417
62.Grzegorczyk, M., Mariniello, M., Nurski, L., Schraepen, T. (2021). Blending the physical and virtual: A hybrid model for the future of work. Policy Contribution.
63.Guerrieri, V., Lorenzoni, G., Straub, L., Werning, I. (2022). Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages? American Economic Review, 112(5), 1437–1474. https://doi.org/10.1257/aer.20201063
64.Guillaumont, P. (2006). Macro Vulnerability in Low-Income Countries and Aid Responses. Revue d’économie du développement, 14(4), 21–77.
65.Guillaumont, P. (2008). An economic vulnerability index: Its design and use for international development policy. UNU-WIDER.
66.Guillaumont, P. (2013). Measuring structural vulnerability to allocate development assistance and adaptation resources. FERDI Working Paper P68.
67.Guillaumont, P., Wagner, L. (2021). Multidimentional vulnerability index. Potential develipment and uses. Analysis and recommendations. United Nations. https://sdgs. un.org/sites/default/files/2021-11/multidimensional_vulnerability_indices_0.pdf
68.Hafele, J., Bertram, L., Demitry, N., Le Lannou, L.-A., Korinek, L., Barth, J. D. (2023). The Economic Resilience Index. Assessing the ability of EU economies to thrive in times of change. ZOE Institute for Future-fit Economies.
69.Hallegatte. (2014). Economic Resilience: Definition and Measurement. World Bank Policy Research Working Paper, 6852.
70.Hamilton, J. (1985). Historical Causes of Postwar Oil Shocks and Recessions. The Energy Journal, 6(1), 97–116.
71.Hellwig, Z. (1968). Zastosowanie metody taksonomicznej do typologicznego podziału krajów ze względu na poziom ich rozwoju i strukturę wykwalifikowanych kadr. Przegląd Statystyczny, 15(4), 307–327.
72.Hinkel, J. (2011). Indicators of vulnerability and adaptive capacity: Towards a clarification of the science–policy interface. Global Environmental Change, 21(1), 198–208. https://doi.org/10.1016/j.gloenvcha.2010.08.002
73.International Monetary Fund. (2021). World Economic Outlook, April 2021: Managing Divergent Recoveries. International Monetary Fund. https://doi.org/10.5089/ 9781513575025.081
74.James, H. (2023). Seven crashes: The economic crises that shaped globalization. Yale University Press.
75.Jordà, Ò., Singh, S. R., Taylor, A. M. (2020). Longer-Run Economic Consequences of Pandemics. Federal Reserve Bank of San Francisco, Working Paper Series, 01–16. https://doi.org/10.24148/wp2020-09
76.Kasperson, J. X., Kasperson, R. E., Turner, B. L., Hsieh, W., Schiller, A. (2003). The Human Dimensions of Global Environmental Change. MIT Press. https://doi.org/10.4324/ 9781849772556
77.Kates, R. W. (1985). The interaction of climate and society. Climate impact assessment, SCOPE 27, 3–36.
78.Keynes, J. M. (2018). The General Theory of Employment, Interest, and Money. Palgrave Macmillan US.
79.Kose, M. A. (2002). Explaining Business Cycles in Small Open Economies: How Much do World Prices Matter. Journal of International Economics, 56(No 2 (March)).
80.Krzyśko, M. (red.) (2008). Systemy uczące się: rozpoznawanie wzorców, analiza skupień i redukcja wymiarowości (Wydanie I). Wydawnictwa Naukowo-Techniczne.
81.Kukula, K., Bogocz, D. (2014). Zero Unitarization Method and its Application in Ranking Research in Agriculture. https://doi.org/10.22004/AG.ECON.265035
82.Kydland, F. E., Prescott, E. C. (1982). Time to Build and Aggregate Fluctuations. Econometrica, 50(6), 1345. https://doi.org/10.2307/1913386
83.Leopardi, F. S., Trentin, M. (2022). The international ‘debt crisis’ of the 1980s in the Middle East and North Africa: A review, an outline. Middle Eastern Studies, 58(5), 699–711. https://doi.org/10.1080/00263206.2022.2081560
84.Mangiameli, P., Chen, S. K., & West, D. (1996). A comparison of SOM neural network and hierarchical clustering methods. European Journal of Operational Research, 93(2), 402–417.
85.Martin, R., Sunley, P. (2015). On the notion of regional economic resilience: Conceptualization and explanation. Journal of Economic Geography, 15(1), 1–42. https:// doi.org/10.1093/jeg/lbu015
86.Mazzucato, M. (2021). Mission economy: A moonshot guide to changing capitalism. Harper Business.
87.McKibbin, W., Fernando, R. (2023). The global economic impacts of the COVID-19 pandemic. Economic Modelling, 129, 106551. https://doi.org/10.1016/j.econmod.2023.106551
88.Migdał-Najman, K., Najman, K. (2013). Analiza porównawcza wybranych metod analizy skupień w grupowaniu jednostek o złożonej strukturze grupowej. Zarządzanie i Finanse, 3(2), 179–194.
89.Migut, G. (2009). Zastosowanie technik analizy skupień i drzew decyzyjnych do segmentacji rynku. https://media.statsoft.pl/_old_dnn/downloads/zastosowanie_technik.pdf
90.Mileti, D. (1999). Disasters by Design: A Reassessment of Natural Hazards in the United States. Joseph Henry Press.
91.Mishkin, F. S. (1999). Lessons from the Asian crisis. Journal of International Money and Finance, 18(4), 709–723. https://doi.org/10.1016/S0261-5606(99)00020-0
92.Mitchell, J. K. (1989). Hazards research. W: G. L. Gaile, C. J. Willmott (red.), Geography in America.
93.Modica, M., Reggiani, A. (2015). Spatial Economic Resilience: Overview and Perspectives. Networks and Spatial Economics, 15(2), 211–233. https://doi.org/10.1007/ s11067-014-9261-7
94.Naudé, W. A., Santos Paulino, A. U., McGillivray, M. (red.) (2009). Vulnerability in developing countries. United Nations University Press.
95.Nordhaus, W. (2013). The Climate Casino: Risk, Uncertainty, and Economics for a Warming World. Yale University Press. https://doi.org/10.2307/j.ctt5vkrpp
96.Nordhaus, W. (2019). Climate Change: The Ultimate Challenge for Economics. American Economic Review, 109(6), 1991–2014. https://doi.org/10.1257/aer.109.6.1991
97.Obstfeld, M., Taylor, A. M. (2017). International Monetary Relations: Taking Finance Seriously. Journal of Economic Perspectives, 31(3), 3–28. https://doi.org/10.1257/ jep.31.3.3
98.OECD. (2018). OECD Economic Surveys, Australia. OECD Publishing.
99.OECD, European Observatory on Health Systems and Policies. (2023a). Italy: Country Health Profile 2023. OECD. https://doi.org/10.1787/633496ec-en
100.OECD, European Observatory on Health Systems and Policies. (2023b). Malta: Country Health Profile 2023. OECD. https://doi.org/10.1787/2a821e8a-en
101.O’Keefe, P., Westgate, K., Wisner, B. (1976). Taking the naturalness out of natural disasters. Nature, 260(5552), 566–567. https://doi.org/10.1038/260566a0
102.O’Rourke, K. H. (2017). Two Great Trade Collapses: The Interwar Period & Great Recession Compared (w23825). National Bureau of Economic Research. https:// doi.org/10.3386/w23825
103.Pamuk, S. (2007). The Black Death and the origins of the „Great Divergence” across Europe, 1300–1600. European Review of Economic History, 11(3), 289–317. https:// doi.org/10.1017/S1361491607002031
104.Pitigala, N. (2020). COVID-19 Crisis: The Impact of Trade and Economic Contagion on Developing Countries. SSRN Electronic Journal. https://doi.org/10.2139/ ssrn.3709524
105.Posthumus, N. W. (2000). The Tulip Mania in Holland in the Years 1636 and 1637. W Great bubbles (T. 1). Routledge.
106.Prebisch, R. (1950). The Economic Development of Latin America and Its Principal Problems. United Nations Department of Economic Affairs. http://archivo.cepal. org/pdfs/cdPrebisch/002.pdf
107.Razin, A., Rubinstein, Y. (2004). Growth Effects of Exchange Rate Regimes and Capital Account Liberalization in the Presence of Crises: A Nuanced View. NBER Working Paper, 10555.
108.Reinhart, C. M., Rogoff, K. S. (2009). This time is different. Eight Centuries of Financial Folly (Online-Ausg). Princeton University Press.
109.Ricardo, D. (1817). On the Principles of Political Economy and Taxation. John Murray.
110.Rodrik, D. (1997). Has Globalization Gone Too Far? Institute for International Economics.
111.Rodrik, D. (1998). Why do More Open Economies Have Bigger Governments? Journal of Political Economy, 106(5), 997–1032. https://doi.org/10.1086/250038
112.Röhn, O., Sánchez, A. C., Hermansen, M., Rasmussen, M. (2015). Economic resilience: A new set of vulnerability indicators for OECD countries (OECD Economics Department Working Papers 1249; OECD Economics Department Working Papers, T. 1249). https://doi.org/10.1787/5jrxhgjw54r8-en
113.Runkel, C. (2022). Eurozone: Pandemic Emergency Purchase Program. Journal of Financial Crises, 4(2), 1569–1600.
114.Saarinen, T. F., Hewitt, K., Burton, I. (1973). The Hazardousness of a Place: A Regional Ecology of Damaging Events. Geographical Review, 63(1), 134. https://doi. org/10.2307/213252
115.Sen, A. (1983). Poverty and Famines: An Essay on Entitlement and Deprivation. Oxford University PressOxford. https://doi.org/10.1093/0198284632.001.0001
116.Shen, H., Fu, M., Pan, H., Yu, Z., Chen, Y. (2020). The Impact of the COVID-19 Pandemic on Firm Performance. Emerging Markets Finance and Trade, 56(10), 2213–2230. https://doi.org/10.1080/1540496X.2020.1785863
117.Singer, H. (1950). The Distribution of Gains between Investing and Borrowing Countries. The American Economic Review, 40(2).
118.Stern, N. (2007). The Economics of Climate Change: The Stern Review (1. wyd.). Cambridge University Press. https://doi.org/10.1017/CBO9780511817434
119.Stiglitz, J. E. (2013). The price of inequality: How today’s divided society endangers our future. Norton & Company.
120.Stiglitz, J. E. (2019). People, Power, and Profits. W. W. Norton & Company, Incorporated.
121.Strahl, D. (red.) (2006). Metody oceny rozwoju regionalnego. Wydawnictwo Akademii Ekonomicznej im. Oskara Langego.
122.Sun, M., Yan, S., Cao, T., Zhang, J. (2024). The impact of COVID-19 pandemic on the world’s major economies: Based on a multi-country and multi-sector CGE model. Frontiers in Public Health, 12, 1338677. https://doi.org/10.3389/fpubh.2024.1338677
123.Susman, P., O’Keefe, P., Wisner, B. (1983). Global disasters, a radical interpretation. W: K. Hewitt (red.), Interpretations of Calamity (263–283). Routledge. https://doi. org/10.4324/9780429329579-14
124.Tarczyńska-Łuniewska, M., Tarczyński, W. (2006). Metody wielowymiarowej analizy porównawczej na rynku kapitałowym. PWN.
125.Thakrar, H., Bhurat, C. (2025). Crisis Dynamics: Russia-Ukraine War, Oil Prices, and Currency Valuations. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5155645
126.Timmerman, P. (1981). Vulnerability, resilience and the collapse of society. Environmental Monograph 1. Institute for Environmental Studies. https://www.ilankelman.org/ miscellany/Timmerman1981.pdf
127.Topolewski, Ł., Moszyński, M., Guo, Y. (2023). Economic Vulnerability and Resilience to Shocks – An Attempt to Measure. Studies in Logic, Grammar and Rhetoric, 68(1), 463–477. https://doi.org/10.2478/slgr-2023-0025
128.Turner, B. L., Kasperson, R. E., Matson, P. A., McCarthy, J. J., Corell, R. W., Christensen, L., Eckley, N., Kasperson, J. X., Luers, A., Martello, M. L., Polsky, C., Pulsipher, A., Schiller, A. (2003). A framework for vulnerability analysis in sustainability science. Proceedings of the National Academy of Sciences, 100(14), 8074–8079. https:// doi.org/10.1073/pnas.1231335100
129.Van Hassel, E., Vanelslander, T., Neyens, K., Vandeborre, H., Kindt, D., & Kellens, S. (2022). Reconsidering nearshoring to avoid global crisis impacts: Application and calculation of the total cost of ownership for specific scenarios. Research in Transportation Economics, 93, 101089. https://doi.org/10.1016/j.retrec.2021.101089
130.Vezzoni, R. (2023). Green growth for whom, how and why? The REPowerEU Plan and the inconsistencies of European Union energy policy. Energy Research & Social Science, 101, 103134. https://doi.org/10.1016/j.erss.2023.103134
131.Walesiak, M. (2014). Przegląd formuł normalizacji wartości zmiennych oraz ich własności w statystycznej analizie wielowymiarowej. Przegląd Statystyczny, 61(2), 363–372.
132.Walesiak, M. (2017). Wizualizacja wyników porządkowania liniowego dla danych porządkowych z wykorzystaniem skalowania wielowymiarowego. Przegląd Statystyczny, 64.
133.Walesiak, M., Dudek, A. (2009). Ocena wybranych procedur analizy skupień dla danych porządkowych. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu. Taksonomia 16: Klasyfikacja i analiza danych – teoria i zastosowania, 47, 41–49.
134.Watts, M. J., Bohle, H. G. (1993). The space of vulnerability: The causal structure of hunger and famine. Progress in Human Geography, 17(1), 43–67. https://doi. org/10.1177/030913259301700103
135.Weber, E., Yilmaz, Y. (2023). Designing short-time work for mass use. European Journal of Social Security, 25(1), 60–76. https://doi.org/10.1177/13882627231161511
136.White, G. F., Haas, J. E. (1975). Assessment of research on natural hazards. MIT-Pr.