A natural disaster is an unexpected condition that reduces economic development and destroys a region's physical capital, infrastructure, and economic growth. Economic growth will decline for some time, and then it will adjust according to the conditions of a country. S ome research shows the effect of natural disasters on economic growth in developed and dev eloping countries (see (Albuquerque & Rajhi, 2019);(Onuma et al., 2020);(Panwar & Sen, 2019);(Sseruyange & Klomp, 2021);(Strobl, 2012)). Some analysts argue natural disasters favour the economy ((Albala-Bertrand, 1993);(Skidmore & Toya, 2002)). Others argue that natural disast er harms the economy ((Cavallo et al., 2013);(Loayza et al., 2009);(Noy, 2009);(Raddatz, 2007)), yet they do not provide a definitive conclusion on the association between natural disasters a nd economic growth (see (Cavallo et al., 2013);(Fisker, 2012)).

Indonesia must deal with its natural conditions as a country prone to natural disaster s. According to (Earthquake early warning systems, 2007), Indonesia is located at the confluen ce of four tectonic plates, namely the Asian Continent plate, the Australian Continent plate, the Indian Ocean plate, and the Pacific Ocean plate, Indonesia is very potential and prone t o natural disasters, such as volcanic eruptions, earthquakes, tsunamis, floods, and landslide s. Also, the ring of the fire area stretches from the islands of Sumatra, Java, and Nusa Teng gara to Sulawesi, with a topography of old volcanic mountains and lowlands dominated by s wamps, doubling the risk of disaster. These natural hazards often strike densely populated and economically active regions, particularly rural areas where livelihoods depend heavily o n agriculture and natural resources.

In this context, natural disasters pose a significant challenge to economic developmen t. They cause direct damage to infrastructure and assets, disrupt economic activity, displace populations, and increase the fiscal burden on governments. While Indonesia has made pro gress in disaster risk reduction and mitigation efforts, the economic impact of these disaster s-especially at the subnational and rural levels-remains understudied. Most existing stud ies on the economic consequences of natural disasters tend to focus on national-level aggreg ates, specific catastrophic events, or use limited cross-sectional data. As a result, the spatial and temporal dynamics of disaster impacts on local economic growth are often overlooked.

Several researchers have studied the impact of natural disasters on the economy. Bas ed on the study from (Ahlerup, 2013), natural disasters have a favorable relationship with fu ture economic success on average. The experience of democratic emerging nations is driving this overall complementary connection. The general positive connection between natural dis asters and economic performance appears to be caused by good acts in democratic developin g countries that have received humanitarian help. (Fischer, 2021) also found a statistically si gnificant positive association between the geographical lag of natural disasters and the chan ge in the initial difference of the natural logarithm of GDP per capita. Post-disaster transfer payments are proven to increase the negative impact of disasters on China's economic growt h. As a result, (Xu & Mo, 2013) proposed getting relief toward creating work incentives to pre vent a lowering effect on economic development. According to (Dzator et al., 2021), the impac t of natural disasters on the economy depends on the type of natural disaster and the period of occurrence.

According to typical neoclassical development models, natural disasters are unlikely to impact the rate of technological progress. However, they may enhance short-run economic growth, partly because they pull countries away from their steady-state levels of macroeconomic objectives. Unlike neoclassical growth models, endogenous growth models advocate a radical perspective that natural disasters can stimulate economic growth by acting as catalysts for reinvestment and improving capital stock productivity (see (Caballero & Hammour, 1994); (Schumpeter, 1942)). According to (Barro & Lee, 1993), most macroeconomic parameters are favourably associated with growth and adversely associated with catastrophe risks: disasters reduce investment and increase government spending. They also raise the black-market premium on foreign exchange and the frequency of revolutions.

(Skidmore & Toya, 2002) discovered that climatic disasters benefit economic growth, whereas geological occurrences do not affect them. (Skidmore & Toya, 2002) found a partially direct association between the frequency of climatic disasters and total factor productivity growth in 89 developed and developing countries. The findings for geological disasters show no substantial impact on total factor productivity growth. (Skidmore & Toya, 2002) made the most significant contribution to the literature on the economics of natural disasters by directly assessing the relationship between foreign technology absorption and catastrophic events. According to their research, natural disasters update capital stock and drive new technologies, leading to higher TFP and GDP growth. After controlling for essential drivers, the frequency of climatic disasters has a positive relationship with TFP growth, human capital accumulation, and GDP per capita growth. One of the explanations for this correlation could be the adoption of new technology when natural disasters damage a country's capital stock, and the economic incentives replace it with more advanced technology. In other words, natural calamities may present opportunities to improve capital stock, leading to better rates of TFP and GDP per capita growth. Such explanations are an excellent illustration of Schumpeterian creative destruction (see (Schumpeter, 1942)). To our knowledge, (Skidmore & Toya, 2002) provided the most extensive empirical research on evaluating the direct long-run impacts of natural catastrophes on economies.

Others argue that disaster harms the economy ((Cavallo et al., 2013);(Loayza et al., 2009);(Noy, 2009);(Raddatz, 2007)). Meanwhile, according to (An & Park, 2019), developing countri es face significant challenges in paying post-disaster recovery expenses compared to industr ialized countries. Foreign aid from the international community enhances accessibility and may accelerate post-disaster rehabilitation in recipient nations. According to (McDermott et al., 2014), natural disasters have long-term detrimental consequences on economic growth i n nations with low levels of financial sector development. The government may encourage p olicymakers to investigate the efficacy of feasible ex-ante catastrophe risk funding methods, particularly in developing countries. (Cavallo et al., 2013), (Noy, 2009)), (Panwar & Sen, 2019), and (Raddatz, 2007) also make arguments for the negative consequences of natural disasters on economic growth.

However, (Noy, 2009) discovered adverse effects only for low-income or developing countries and lasted for only a short time. (Cavallo et al., 2010) and (Raddatz, 2007) found that only climatic and humanitarian disasters harm economic growth. Furthermore, the empirical growth studies do not provide a definitive conclusion on the association between natural disasters and economic growth (see (Cavallo et al., 2013); (Fisker, 2012)). (Guo et al., 2015) discovered that natural disasters do not significantly influence economic development. Thus, in managing recoveries, human capital reinvestment should be the goal, which is used to restore the local economy based on long-term sustainable growth.

This paper investigates the economic consequences of natural disasters at the subnational level in Indonesia by addressing two core questions: (1) to what extent do natural disasters influence economic growth, and (2) which provinces are most frequently affected by natural disasters, including the proportion of disaster-affected villages within each province. These questions are explored using the Village Potential Statistics (Potensi Desa/PODES) from 33 Indonesian provinces, which provide a uniquely granular dataset. Unlike most national-level disaster data, PODES offers information at the village level, allowing for provincial aggregation while preserving local-level variation. This feature has rarely been utilized in economic analyses of disaster impacts. PODES 2014 covered natural disasters from 2011 to 2013, and PODES 2018 covered natural disasters from 2015 to 2017. The data are presented at a provincial level and aggregated from the data at the village level, which is the uniqueness of PODES data. Despite the richness of this dataset, previous literature has not leveraged PODES to examine the relationship between natural disasters and economic outcomes, particularly in the rural context. This highlights a notable gap in disaster economics and regional development literature, where the impacts of disasters are often studied using national macroeconomic indicators or case studies rather than structured panel data with local disaggregation.

This study assumes that natural disasters tend to positively influence economic growt h through the destruction of infrastructure, reduction in labor productivity, and disruptions in capital formation in the long run. To empirically test this hypothesis, we employ static an d dynamic panel data models, including the Generalized Method of Moments (GMM) estima tor, to account for potential endogeneity and omitted variable bias. In addition, we perform a series of robustness checks to validate the consistency and reliability of our findings. In do ing so, this study contributes methodologically and fills an empirical gap in understanding how natural shocks shape regional growth trajectories in a disaster-prone country like Indo nesia.

These research findings indicate that the fixed effect model best fits the data. Based o n robust estimation techniques, the analysis reveals that the disaster variable also demonst rates a positive association with economic growth. Additionally, government expenditures on capital, labor, and technology, which are proxied by household cellular phone ownership, significantly impact economic growth. Our study makes two contributions. The first contrib ution in terms of policy implications, namely, the importance of increasing the policy of gove rnment spending on capital expenditure, for the first point, and the second point is that hu man resource investment is essential in driving economic improvement. Third is increasing the mitigation policy on disasters to reduce the impact of a disaster in terms of the number and area coverage. The province whose villages are affected by the disaster yearly is East N usa Tenggara. This information is essential to increase the mitigation policy on disasters an d reduce the impact of disasters in terms of the number and area coverage.

The second contribution of our study is to the Indonesia-specific literature on disaster s and economics. This paper contributes to the literature by investigating the disaster's effec t on economic growth in Indonesia using the PODES database. The original data are repres ented at the village level to meet another variable: the aggregated provincial data. To our k nowledge, no previous study in Indonesia has utilized the PODES database to construct the disaster data. It brings new findings to the context of Indonesia.

For further research, it should cover (i) the data that represent the district level and e mploy comprehensive series data, and (ii) the data that employ spatial econometrics to captu re the spillover effect of disasters both at the district level and at the province level. This pa per will continue with Section II discussing data and econometric models, Section III discus sing results, and Section IV discussing the conclusion and implications.

This paper used a labor augmenting technological progress model (Barro & Sala-I-Ma rtin, 1995) to explain economic growth, and (Okuyama, 2003) as a theory-based approach for economic growth, and with a disaster, as follows:

(1)

Where L.A(t) denotes the amount of effective labor (defined to be L), a measure that reflects the productivity of each worker. The capital per effective worker, k, can be written as:

(2)

Moreover, the output per effective worker can be written as:

(3)

Which can be further to:

(4)

Dividing both sides of (4) by k, the growth rate of capital per effective worker is:

(5)

Since there is no change in capital per effective worker at the steady state, the followi ng condition should apply:

From Equation 6, as (Okuyama, 2003) notes, when a disaster occurs, the capital stock per effective worker decreases from the steady state level to . (Okuyama, 2003) explains that “a higher rate of technological progress leads to a faster growth of the effective labor” to justify this effect further. Compared to the period of the regular technological growth rate, x, More resources are spent on making each worker more productive during the higher technological growth rate, xr. During the reconstruction process, the technology-replacing economy directs more resources towards human capital rather than physical capital than the economy with no technology replacement. This model suggests that climatic disasters can induce human capital investment for an economy that experiences creative destruction during recovery.

From a theoretical perspective, natural disasters create significant and intense dama ge to capital stocks and, sometimes, labor. The recovery activities change replace the older f acilities with newer ones, which may be built upon and use newer technologies. We assume that the level of technology in an economy is the aggregated technological level consisting of a mixture of old and new capital stocks. The recovery activities increase the rate of technolo gical progress to some extent by updating the technological level of the damaged older capit al. We added natural disaster as an independent variable and modified the model's natural disaster relation with growth from Dell et al. ( 2012), Felbermayr and Gröschl (2014), Loayza et al. (2012), and Lee et al. (2018).

From the explanation above, to capture the impact of natural disasters on economic g rowth, the data analysis technique carries out the econometrics model through panel data st atistics as follows:

(7)

This study hypothesizes that natural disasters positively impact economic growth, cap ital, labor, and technology, which positively affect economic growth, reflecting their role in e nhancing productivity and recovery. In contrast, capital depreciation is expected to have a n egative effect, as it diminishes the productive asset base. Therefore, β 2 , β 3 , β 4 and β 5 are ex pected to be positive, while β 6 is expected to be negative. Lastly, the subscript (t =1,2,…, t) denotes the period.

In order to find the best regression panel model, this study applied a simple Chow test with Restricted Residual Sums of Squares (RRSS), which was a simple test of OLS on the p ooled model, and the unrestricted residual sums of squares (URSS), which was a simple test of the fixed effect/Least Square Dummy Variable/LSDV regression (Baltagi, 2005). The Bre usch and Pagan Lagrange multiplier test was also applied in this study to decide on the bes t model between pooled and random models (Hill et al., 2011).

This study uses disaster occurrences in Potensi Desa (PODES) data issued by Statisti cs Indonesia (Badan Pusat Statistik/BPS). Lee at Al. (2018) used the same method and mea surement on disaster occurrence to construct the disaster variable. In the research, Lee et a l. ( 2018) used Pacific Islands' disaster data to construct severe natural disasters by specifyin g a threshold on the distribution of the economic and human costs of disasters. The intensit y measure is based on the distribution of economic damage or population affected, and ident ifying severe natural disasters based on this intensity is the key innovation.

Furthermore, this research divides the disaster variable into two forms: the number of disaster occurrences in the log natural form and the percentage of villages that have disasters. The original data were stated at the village level and then aggregated at the province level. The aggregation of disaster data at the province level to meet the other variables is only available at the province level. Detailed information related to variables is presented in Table 1 below:

This paper develops a framework for analyzing the economic impact of a disaster. Our findings imply that disasters have pulled the economic growth. The remaining variable repr esenting the growth economy theory shows the expected result in various coefficients and th eir significance level. The research has contributed to the policy implications and literature study in Indonesia.

From the policy perspective, firstly, it is important to increase the policy of governmen t spending on capital expenditure. Secondly, human resource investment is essential in driv ing economic improvement. Thirdly, there is a need to increase the mitigation policy on disa sters to reduce the impact of disasters in terms of the number and area coverage. The provi nce whose villages are affected by the disaster yearly is East Nusa Tenggara. This informati on is vital to increase the mitigation policy on disasters and reduce the impact of disasters i n terms of the number and area coverage.

This paper uses the PODES database to investigate the effect of the disaster on econo mic growth in Indonesia. The original data are represented at the village level. The data an alyses employ the aggregated data at the provincial level to control for other variables. To o ur knowledge, no previous study in Indonesia has utilized the PODES database to construct the disaster data. It brings new findings to the context of Indonesia. The study limits the ra nge of time series data to 2011-2017. Further research would (i) cover the data that represe nts the district level and employ the long time-series data, and (ii) employ spatial econometr ics to capture the spillover effect of disaster both at the district level and the province level.