Share:


The macroprudential measures for mitigating the effects of the pandemic crisis in tourism economies

Abstract

Purpose – The paper evaluates the applied macroprudential measures in selected countries by testing their efficiency in tourism and reducing the revenue gap in tourism sector during the pandemic crisis.


Research methodology – The effects of macroprudential policy were tested using the Granger causality test and PVAR model. The research used data from the period 2019 to 2022 by quarters. The impulse response function evaluated the long run impact of macroprudential policy on performance of tourism entities.


Findings – The results confirm the positive effect of systemically important institutions buffer (SIB) on reducing the losses in tourism. The impulse response showed the significant impact of SIB on revenue gap (RG) reduction.


Research limitations – The research has limitations regarding to the short period of observation. The additional variables can be entered into the model.


Practical implications – The results serve the policy makers for shaping the measures for recovery policies and maintaining long-term economic stability. The findings are useful as they can serve as a guide in designing measures to help the tourism recovery.


Originality/Value – The contribution of this study is reflected in providing scientific evidence of macroprudential measures effectiveness for several countries and routing policies for tourism recovery.

Keyword : macroprudential policy, pandemic, tourism economy

How to Cite
Popek Biškupec, P., Herman, S., & Ružić, I. (2022). The macroprudential measures for mitigating the effects of the pandemic crisis in tourism economies. Business, Management and Economics Engineering, 20(1), 79–95. https://doi.org/10.3846/bmee.2022.15738
Published in Issue
Apr 19, 2022
Abstract Views
401
PDF Downloads
416
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Abrigo, M. R., & Love, I. (2016). Estimation of panel vector autoregression in Stata. The Stata Journal, 16(3), 778–804. https://doi.org/10.1177/1536867X1601600314

Aldao, C., Blasco, D., Poch Espallargas, M., & Palou Rubio, S. (2021). Modelling the crisis management and impacts of 21st century disruptive events in tourism: The case of the COVID-19 pandemic. Tourism Review, 76(4), 929–941. https://doi.org/10.1108/TR-07-2020-0297

Andrews, D. W., & Lu, B. (2001). Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models. Journal of Econometrics, 101(1), 123–164. https://doi.org/10.1016/S0304-4076(00)00077-4

Andries, A. M., Melnic, F., & Sprincean, N. (2021). The effects of macroprudential policies on credit growth. European Journal of Finance. https://doi.org/10.1080/1351847X.2021.1939087

Atems, B., & Jones, J. (2015). Income inequality and economic growth: A panel VAR approach. Empirical Economics, 48(4), 1541–1561. https://doi.org/10.1007/s00181-014-0841-7

Bahovec, V., & Erjavec, N. (2009). Uvod u ekonometrijsku analizu (1 izdanje). Element. Ekonomski fakultet Zagreb.

Bayraktar-Sağlam, B., & Sayek Böke, S. (2017). Labor costs and foreign direct investment: A panel VAR approach. Economies, 5(4), 36. https://doi.org/10.3390/economies5040036

Benoit, K. (2011). Linear regression models with logarithmic transformations. https://links.sharezomics.com/assets/uploads/files/1600247928973-from_slack_logmodels2.pdf

Blanchard, O. J., & Quah, D. (1988). The dynamic effects of aggregate demand and supply disturbances. National Bureau of Economic Research. https://doi.org/10.3386/w2737

Bhuiyan, M. A., Crovella, T., Paiano, A., & Alves, H. A. (2021). Review of research on tourism industry, economic crisis and mitigation process of the loss: Analysis on pre, during and post pandemic situation. Sustainability, 13, 10314. https://doi.org/10.3390/su131810314

Cao, J., Dinger, V., Grodecka-Messi, A., Juelsrud, R., Zhang, X. (2021). The interaction between macroprudential and monetary policies: The cases of Norway and Sweden. Review of International Economics, 29(1), 87–116. https://doi.org/10.1111/roie.12507

Choi, I. (2001). Unit root tests for panel data. Journal of international money and Finance, 20(2), 249–272. https://doi.org/10.1016/S0261-5606(00)00048-6

De Schryder, S., & Opitz, F. (2021). Macroprudential policy and its impact on the credit cycle. Journal of Financial stability, 58, 100818. https://doi.org/10.1016/j.jfs.2020.100818

Đorđević, S., Ganjto, T., & Vrenko, V. (2017). Rizičnost velikog udjela deviznog Prihoda od turizma u BDP-u Republike Hrvatske. In ERAZ 2017 (pp. 460–465), Beograd, Srbija. https://sekarl.euba.sk/arl-eu/sk/csg/?repo=eurepo&key=46898358974

Eller, M., Martin, R., & Vashold, L. (2021). CESEE’s Macroprudential Policy Response to Covid-19. (SUERF Policy Briefs No 71). https://www.suerf.org/docx/f_e467959ffcd45714c153f28692416c39_22861_suerf.pdf

European Banking Authority. (2021). Other Systemically Important Institutions (O-SIIs). https://www.eba.europa.eu/risk-analysis-and-data/other-systemically-important-institutions-o-siis-

European Central Bank. (2021a). Economic and monetary developments. https://www.ecb.europa.eu/pub/economic-bulletin/html/eb202102.en.html

European Central Bank. (2021b). Our response to the coronavirus pandemic. https://www.bankingsupervision.europa.eu/home/search/coronavirus/html/index.en.html

European Central Bank. (2021c). Macroprudential measures taken by national authorities since the outbreak of the coronavirus pandemic. https://www.ecb.europa.eu/pub/financial-stability/macroprudential-measures/html/index.en.html

European Central Bank. (2021d). Macroprudential database. https://sdw.ecb.europa.eu/browse.do?node=9689335

Eurostat Database. (2021). Economy and finance. https://ec.europa.eu/eurostat/web/main/search/-/search/estatsearchportlet_WAR_estatsearchportlet_INSTANCE_bHVzuvn1SZ8J?_estatsearchportlet_WAR_estatsearchportlet_INSTANCE_bHVzuvn1SZ8J_pageSize=11&_estatsearchportlet_WAR_estatsearchportlet_INSTANCE_bHVzuvn1SZ8J_text=gdp&_estatsearchportlet_WAR_estatsearchportlet_INSTANCE_bHVzuvn1SZ8J_sort=_score&p_auth=iB2UTbXG&_estatsearchportlet_WAR_estatsearchportlet_INSTANCE_bHVzuvn1SZ8J_theme=PER_ECOFIN

Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438. https://doi.org/10.2307/1912791

Hadri, K. (2000). Testing for stationarity in heterogeneous panel data. The Econometrics Journal, 3(2), 148–161. https://doi.org/10.1111/1368-423X.00043

Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica, 50(4), 1029–1054. https://www.jstor.org/stable/1912775

Harris, R. D., & Tzavalis, E. (1999). Inference for unit roots in dynamic panels where the time dimension is fixed. Journal of Econometrics, 91(2), 201–226. https://doi.org/10.1016/S0304-4076(98)00076-1

Holtz-Eakin, D., Newey, W., & Rosen, H. S. (1988). Estimating vector autoregressions with panel data. Econometrica, 56(6), 1371–1395. https://doi.org/10.2307/1913103

Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74. https://doi.org/10.1016/S0304-4076(03)00092-7

Kim, S., & Mehrotra, A. (2019). Examining macroprudential policy and its macroeconomic effects – some new evidence (BIS Working Papers No 825). https://www.bis.org/publ/work825.pdf

Kukanja, M., Planinc, T., & Sikošek, M. (2020) Crisis management practices in tourism SMEs during the Covid-19 pandemic. Organizacija, 53(4), 346–361. https://doi.org/10.2478/orga-2020-0023

Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1–24. https://doi.org/10.1016/S0304-4076(01)00098-7

Martínez-Hernández, C., Mínguez, C., & Yubero, C. (2021) Archaeological sites as peripheral destinations. Exploring Big Data on fieldtrips for an upcoming response to the tourism crisis after the pandemic. Heritage 2021, 4, 3098–3112. https://doi.org/10.3390/heritage4040173

Mikac, R., & Kravaršćan, K. (2021) Croatian tourism sector and crisis management – A case study related to the Covid-19 pandemic. Tourism, 69(4), 611–629. https://doi.org/10.37741/t.69.4.9

Motevalli-Taher, F., & Paydar, M. M. (2021). Supply chain design to tackle coronavirus pandemic crisis by tourism management. Applied Soft Computing, 104, 107217. https://doi.org/10.1016/j.asoc.2021.107217

National Tourism Policy. (2015). https://tourism.gov.mt/en/Documents/FINALBOOKLETexport9.pdf

Niestadt, M. (2020). EU tourism sector during the coronavirus crisis. (European Parliamentary Research Service PE 652.008). European Parliament. https://www.europarl.europa.eu/RegData/etudes/BRIE/2020/652008/EPRS_BRI(2020)652008_EN.pdf

OECD. (2011). Attractiveness and promotion of Italy as a tourism destination. https://read.oecd-ilibrary.org/industry-and-services/oecd-studies-on-tourism-italy/attractiveness-and-promotion-of-italy-as-a-tourism-destination_9789264114258-9-en#page1

OECD. (2020a). OECD Tourism Trends and Policies 2020. Portugal. https://www.oecd-ilibrary.org/sites/46decc94-en/index.html?itemId=/content/component/46decc94-en

OECD. (2020b). OECD Tourism Trends and Policies 2020. Spain. https://www.oecd-ilibrary.org/sites/8ed5145b-en/index.html?itemId=/content/component/8ed5145b-en

Papatheodorou, A., & Arvanitis, P. (2014). Tourism and the economic crisis in Greece: Regional perspectives. Région et développement, 39, 183–203. https://pure.solent.ac.uk/en/publications/tourism-and-the-economic-crisis-in-greece-regional-perspectives

Popek Biškupec, P., & Bilal Zorić, A. (2017). Optimizacija korištenja instrumenata monetarne i makroprudencijalne politike u svrhu očuvanja stabilnosti financijskog sustava, Zbornik Ekonomskog fakulteta u Zagrebu, 15(1), 31–49. https://doi.org/10.22598/zefzg.2017.1.31

Popek Biškupec, P. (2015). Utjecaj makroprudencijalnih instrumenata na kreditnu aktivnost banaka u zemljama Srednje i Istočne Europe. Zbornik Ekonomskog fakulteta u Zagrebu, 13(2), 85–101. https://hrcak.srce.hr/149149

Popek Biškupec, P., & Herman, S. (2021). The effectiveness and constraints of monetary policy in pandemic times. SHS Web of Conferences, 92, 07050. https://doi.org/10.1051/shsconf/20219207050

Robina-Ramírez, R., Sánchez, M.S.-O., Jiménez-Naranjo, H. V., & Castro-Serrano, J. (2021). Tourism governance during the COVID-19 pandemic crisis: A proposal for a sustainable model to restore the tourism industry. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-021-01707-3

Simionescu, M. (2015). The impact of economic crisis on inflation convergence in the European Union. A panel data approach. CEA Journal of Economics, 10(1). https://journal.cea.org.mk/files/journals/1/articles/27/public/27-106-1-PB.pdf

Takats, E., & Temesvary, J. (2021). How does the interaction of macroprudential and monetary policies affect cross-border bank lending? Journal of International Economics, 132, 103521. https://doi.org/10.1016/j.jinteco.2021.103521

The Commonwealth. (2021). Tourism and COVID-19: Mapping a way forward for small states. https://thecommonwealth.org/sites/default/files/inline/Mapping_a_Way_Forward_for_Small_States_UPDF.pdf

Traoré, M. (2018). Government spending and inclusive growth in Sub-Saharan Africa: A panel VAR analysis. https://ideas.repec.org/p/hal/wpaper/hal-01940506.html

World Travel and Tourism Council. (2021). Economic impact reports. https://wttc.org/Research/Economic-Impact

The World Bank. (2022). International tourism number of arrivals. https://data.worldbank.org/indicator/ST.INT.ARVL?end=2020&locations=HR-CY-MT-GR-IT-PT-ES&start=2005