Correlation macroeconomic, government efficiency, infrastructure, and climate change vulnerability: a cross-country analysis

The government is required to take proactive steps to participate in interventions that strengthen resilience in response to climate change as SDG 13: Climate Action. Therefore, this study aimed to examine the correlation of government performance, in the form of macroeconomic performance, efficiency, and infrastructure availability with vulnerability to climate change. Data were analyzed from 2021 to 2022 for 57 countries and the variables used were macroeconomic performance, government efficiency, infrastructure, and vulnerability. Furthermore, vulnerability variable has three dimensions, namely susceptibility, lack of coping capacities, and lack of adaptive capacities. The data used in this study were sourced from reputable references, such as World Competitiveness Yearbook and World Risk Report. For data analysis, correlation and comparison tests were judiciously applied. The results showed that macroeconomic performance, government efficiency, and infrastructure were negatively correlated with vulnerability. Macroeconomic performance and government efficiency variables had the strongest moderate correlation with climate change vulnerability, while infrastructure had a moderate to strong correlation. The results recommended a policy of providing infrastructure in vulnerable areas since economic performance could not guarantee resilience to climate change.


Introduction
The adverse effects of climate change are acutely experienced in regions characterized by heightened susceptibility.To address this multifaceted challenge, it is important to climate action as Sustainable Development Goal (SDG) 13 by foster resilience in the face of climate change, including both the ability to cope and adapt.This resilience depends on different factors crucial in mitigating the impact of climate change.Among these factors, the adaptive capacities of farming households are influenced by access to natural, physical, and financial capital [1].Agro ecology, education level, age, active labor, number of livestock (TLU), income outside farming, frequency of extension contacts, access to credit, and market access collectively influence the adaptation mechanisms to survive extreme climates [2].The adaptive capacities index of farmers varied across livestock corridor sub-regions, with innovation, asset base, knowledge, and information acting as significant indicators [3].Furthermore, the building of adaptive capacities requires expanding access to credit and savings 1302 (2024) 012074 IOP Publishing doi:10.1088/1755-1315/1302/1/012074 2 services as well as market information [4].Access to agricultural extension services and climate information are key factors that enable farmers to adopt different adaptation strategies [5].
Improving community adaptive capacities necessitates external institutional interventions by NGOs, using a range of direct and indirect initiatives.These include disseminating pertinent information to farmers concerning climate change, enhancing competencies and expertise to effectively address variability, establishing the groundwork for individuals to accrue diverse forms of capital, furnishing direct support for coping with adaptive livelihood, extending financial aid to improve capital, and actively participating in impact-balancing strategies [6].Studies including government institutions related to coping strategies were also conducted in Indonesia.Fishermen's households were implemented with internal and external coping strategies generated through the synergy of formal institutions in the community and government institutions as policymakers [7].
Previous studies showed the importance of awareness, access to information, and access to financial and institutional resources in promoting adaptive capacities to climate change.However, social, and economic factors affect vulnerability to climate change.There is a positive correlation between adaptive capacities and social assets, followed by economic and physical assets [8].Other results indicate the need for governmental efforts to increase resilience to climate change.Partnerships with the communities lead to new perspectives on climate risk-mitigation measures, cost-effective implementation of innovative adaptation solutions, as well as social inclusion and empowerment in terms of livelihood opportunities [9].In the absence of support, assets play an important role in determining the welfare capacity of vulnerable households to be resilient to economic shocks [10].Furthermore, one of governments' supports in dealing with climate change is the availability of infrastructure.The mitigation of climate variability and extreme risks can be achieved with the enhancement of extension services and facilities, by ensuring the availability of essential infrastructure [11].This is in line with the results that infrastructure is needed to increase household capacity to solve the problem of climate shocks [12].Adaptive capacities-building interventions in the form of awareness creation are also necessary to strengthen basic infrastructure and land management [13].Concerning the divergent findings, economic resources, awareness, training, and technological proficiency appear to hold greater significance in shaping the adaptive capacities of smallholder farmers.Meanwhile, infrastructure, social capital, and institutional factors are ranked as comparatively less important [14].The impact of infrastructure on vulnerability to climate change was examined.This study also analyzed the macro aspect, where government efficiency was correlated with vulnerability.Macroeconomic performance variable and country income groups are also estimated to capture the correlation between climate change vulnerability and economic assets from the micro level.The results are expected to contribute to policies that increase resilience to climate change at a macro level.

Materials and methods
This study analyzed 57 countries for the 2021 and 2022 period, and the variables used were macroeconomic performance, government efficiency, infrastructure, and vulnerability.Vulnerability variable had three dimensions, namely susceptibility, lack of coping capacities, and lack of adaptive capacities.Data on macroeconomic performance, government efficiency, and infrastructure were obtained from the World Competitiveness Yearbook by IMD publication, while climate change vulnerability data were sourced from the World Risk Report published by Bündnis Entwicklung Hilft Ruhr University Bochum Institute for International Law of Peace and Armed Conflict (IFHV).The year of data analysis was adjusted for the publication and in the context of this study, 2021 was marked by COVID-19 pandemic and its subsequent recovery phase.Meanwhile, 2022 was characterized as the year following the conclusion of COVID-19 recovery period.This study used a correlation and comparison test to show the difference in vulnerability and the recovery period.A normality test was performed before conducting comparison and correlation tests.The difference and correlation tests used parametric statistics when the data were normally distributed.However, nonparametric statistics were used when not normally distributed.The normality test used the Jarque-Bera value of the variable, with a probability of > 0.05.The interpretation of the results was that 0.9 ≤ rho ≤ 1 was very strong, 0.7≤ rho < 0.9 was strong, 0.5≤ rho < 0.7 was moderate, 0.3≤ rho < 0.5 was weak, and rho < 0.3 was very weak.

Results and discussion
Figures 1 and 2 show vulnerability index for the 57 countries studied in2021 and 2022, respectively.The most vulnerable group for the five highest positions did not change between 2021 and 2022, namely India, the Philippines, Indonesia, and Colombia.Peru, which was in the sixth vulnerability position in 2021, increased to the fifth position in 2022, and South Africa showed a better position in 2022 with a decrease in vulnerability ranking.In 2021, Switzerland had the lowest score, followed by Germany, Australia, Denmark, and Belgium.In 2022, Singapore entered the top five countries with the lowest vulnerability, and the index decreased by 2022, implying better resilience compared to 2021.   4 show the differences in the economic and vulnerability indicators for the group of countries with GDP of more than $20,000 and less than $20,000.Macroeconomic performance, government efficiency, and infrastructure are lower for countries earning less than $20,000 in both 2021 and 2022.This resulted in higher vulnerability for a GDP of less than $20,000 and in 2022, the index of both groups decreased.The countries with less than $20,000 had a vulnerability index of 41.7 to 26.2 from 2021 to 2022, while GDP greater than $20,000 had an index of 9.4 to 28.5 from 2021 to 2022.Table 1 shows the descriptive statistics of the variables for the analysis periods 2021 and 2022.The average values for macroeconomic performance, government efficiency, and infrastructure appear to be better in 2021 even with decreased vulnerability indicators.From the aspect of standard deviation, in 2021, macroeconomic conditions and infrastructure are more unequal between countries.For 2022, vulnerability variable between countries was unequal, which was indicated by the higher standard deviation value for the indicators.However, the normality test of the variables showed that the susceptibility and lack of coping capacities variables were not normally distributed for the 2021 data.Concerning 2022 data, three variables are not normally distributed, namely macroeconomic performance, susceptibility, and lack of coping capacities.In the next analysis method, nonparametric statistical tests were performed for variables that were not normally distributed.
Table 2 shows that the economic indicators are correlated with vulnerability indicators.According to 2021 data estimates, macroeconomic performance, government efficiency, and infrastructure are negatively correlated with susceptibility, lack of coping capacities, and lack of adaptive capacities.Macroeconomic values were in the moderate category with susceptibility and lack of coping capacities as well as the weak category concerning adaptive capacities.This is also in line with the correlation between government variable and vulnerability dimension variable.Meanwhile, infrastructure had a strong correlation with coping and adaptive capacities and a moderate correlation with susceptibility.Data estimation for 2022 shows that macroeconomic correlation with vulnerability dimension is in the weak category, and insignificant for coping capacities.Even though macroeconomic conditions are improving, the concepts do not have a direct impact on reducing vulnerability.This is because the increased resilience to climate change is closely related to the inclusiveness of economic progress.Inclusiveness factors that can increase resilience to climate change include access to local government services [9], information [3,5,6,11,15], finance [4,16] and social [9].The correlation between government efficiency is moderate for susceptibility and coping capacities and weak for adaptive capacities.The lack of appropriate intervention and support mechanisms affects the adaptation to climate variability [13].Increasing coping capacities is needed to synergize the role of formal and government institutions as policymakers [7].Therefore, a more efficient governance role is required to increase the coping capacities of communities affected by climate change.Table 2 shows that the correlation between infrastructure and all vulnerability dimensions was moderate to strong correlation.The results also support the recommendations that promote the provision of basic infrastructure facilities and services to strengthen adaptive capacities to climate change [11] as part of climate change action steps in line with SDG 13.This is different from previous findings where infrastructure is less important in supporting adaptive capacities to climate change [14].

Figure 1 .
Figure 1.Climate change vulnerability index of countries in 2021.

Figure 2 .
Figure 2. Climate change vulnerability index of countries in 2022.

Figure 3 .
Figure 3. Vulnerability, infrastructure, government efficiency, and macroeconomic performance index based on gross domestic product group in 2021.

Figure 4 .
Figure 4. Vulnerability, infrastructure, government efficiency, and macroeconomic performance index based on gross domestic product group in 2022.

Table 1 .
Descriptive statistics of research variables.

Table 2 .
Correlation between macroeconomic performance, government efficiency, infrastructure and climate change vulnerability.Thathsarani US and Gunaratne LHP 2018 Constructing and Index to Measure the Adaptive Capacity to Constructing and Index to Measure the Adaptive Capacity to Climate Procedia Eng 212 pp 278-85 [9] Khan MA, Hasan K and Kabir KH 2022 Determinants of households' livelihood vulnerability due to climate induced disaster in southwest coastal region of Bangladesh Prog Disaster Sci 15 100243 [10] Ansah IGK, Gardebroek C, and Ihle R 2022 Using assets as resilience capacities for stabilizing food demand of vulnerable households Int J Disaster Risk Reduct 82 103352 [11] Getahun AB, Ayal DY, Ture K, Zeleke TT 2021 Determinants of climate variability adaptation strategies: A case of Itang Special District, Gambella Region, Ethiopia Clim Serv 23 100245 [12] Abid M, Ali A, Rahut DB, Raza M, and Mehdi M 2020 Ex-ante and ex-post coping strategies for climatic shocks and adaptation determinants in rural Malawi Clim Risk Manag 27 100200 [13] Tamene H, Ayal DY, Zeleke TT, and Ture K 2023 Determinants of the choice of adaptation strategies to climate variability and extremes among pastoralist and agro-pastoralist households in Yabello and Arero Districts, Southeast Ethiopia Clim Serv 30 100381 [14] Abdul-Razak M, and Kruse S 2017 The adaptive capacity of smallholder farmers to climate change in the Region of Ghana Clim Risk Manag 17 pp 104-22 [15] Yeleliere E, Antwi-Agyei P, and Guodaar L 2023 Farmers response to climate variability and change in rainfed farming systems: Insight from lived experiences of farmers Heliyon 9(9) pp 1-20 [16] Beyene F, Senapathy M, Bojago E, and Tadiwos T 2023 Rural household resilience to food insecurity and its determinants: Damot Pulasa district, Southern Ethiopia J Agric Food Res 11 100500