Prof. Hiroyuki Shibusawa (p), Saki Ito, Mingji Cui

This study evaluates the economic impacts of external shocks through a simulation approach based on an inter-regional input–output (IRIO) modeling framework, with a particular focus on Asia. In recent years, Asian economies have become increasingly vulnerable to large external shocks such as natural disasters, global supply chain disruptions, pandemics, and geopolitical risks. Shocks originating in a single country can propagate widely across the region through tightly connected production networks and trade linkages. Despite this growing exposure, there remains a shortage of practical analytical frameworks that combine interregional economic modeling with systematic simulation approaches to quantify cross-border shock transmission.

To address this gap, the study develops an IRIO-based simulation framework for international and interregional shock assessment, focusing on shocks originating in Japan and their propagation across Asian economies. The empirical database is constructed using the ADB MRIO dataset and reorganized into an inter-regional structure with a limited number of regions and sectors to support scenario-based simulations while preserving key supply-chain linkages. Within this framework, simulation modules are designed to represent supply constraints, demand reductions, and staged recovery processes. Interregional multipliers, spillover effects, and feedback effects are estimated and compared across regions and industries.

To demonstrate the applicability of the simulation approach, the study conducts shock scenario experiments centered on Japan, including production disruptions and export supply constraints associated with large-scale disasters. The simulations quantify both direct and indirect economic impacts across Asian partner economies and sectors, illustrating how shocks propagate through interregional trade and intermediate input networks. Recovery paths are also evaluated by modeling gradual restoration of production capacity and trade flows, enabling comparative assessment of regional vulnerability and resilience within Asia.

This study contributes in three main ways. First, it provides empirical evidence on interregional economic interdependence in Asia using a harmonized multi-regional dataset. Second, it advances methodological practice by integrating IRIO modeling with a structured simulation approach for shock analysis. Third, it offers practical insights for disaster risk management, supply-chain resilience planning, and regional economic cooperation in Asia.

Konstantia Tolika, Jelena Svetozarevic, Dana Maria Constantin, Daiana Giorgiana Lüftner, Dr. Hristo Popov (p)

Description of climate variability has received increased interest over recent years. Köppen climate classification is based on quantitative which makes it easy to use. In the same time classification is based on needed of heat and humid for growing vegetation which is useful for agriculture forecasts and some other applications. Köppen climate classification defines climates zones using average monthly temperatures and annual precipitation regime. In recent paper we use data from meteorological stations possessed in Bulgaria, Romania, Greece, Serbia and North Macedonia.
Data are provided by Nationals Meteorological Institutes of these countries. The period of observation is at least 30 years for most of the used stations which make data statistically significant.
Annual Climate Type (ACT) is method which shows details stayed hide when we use monthly average for long periods.
Also, we have described better the areas with droughts and possible water deficits. According to future climate scenarios these areas are at serious risk of every type of droughts, water deficits and possible wildfires. The new point of view present risk of floods in study areas.

Dr Olga Ivanova, Ms Merel Roelands (p), Prof. Dr. Tatiana Filatova

The costs of climate inaction pose increasing risk to public finances. Yet there is limited evidence on the indirect economic and financial effects of climate change in The Netherlands. Moreover, fiscal sustainability analyses of public finances are usually conducted on a national level, while climate impacts materialize primarily at a local scale. As a result, regional differences in financial vulnerability remain underexplored.
This study examines the financial vulnerability of Dutch municipalities to climate change in the year 2050. We combine existing estimates of direct economic damages with projections of municipal budgets based on current fiscal data and population forecasts. Adaptation costs are estimated using neighborhood level cost data differentiated by urban typology. We then compare the projected distribution of climate damages and adaptation expenditures relative to municipal budgets.
The findings reveal large differences between municipalities. In several cases, projected climate damages and adaptation costs are likely to place increasing pressure on local fiscal positions. Climate change affects municipal budgets through two main channels. Firstly, the municipal income depends heavily on property taxes, damage to building foundations and declining property values may therefore erode the local tax base. Secondly, municipalities face rising expenditures related to damage repair and climate adaptation. Together, these dynamics create a systematic risk: municipalities that lack resources to invest in adaptation may see their tax base erode more rapidly, further constraining their fiscal capacity. The estimates presented in this study should be interpreted as a lower bound. Indirect economic effects are not included, and adaptation costs are limited to the built environment, omitting nature and agricultural areas.
Despite these conservative assumptions, this study provides novel insights into the distributional consequences of climate change for local public finances in The Netherlands. In order to reduce the pressure on local governments and level the playing field, we recommend a recalibration of national finance transfers, based on local risk profiles. In addition, we vouch for the introduction of a climate damage ladder to clarify the allocation of public and private responsibilities for climate relates costs across levels of government.

Dr. Antje Jantsch (p), Dr. Kathleen Hermans, Dr. Sarvarbek Eltazarov, Dr. Lena Kuhn

This paper examines how climate dynamics and place attachment jointly shape migration intentions in Southeast Europe’s temperate rural regions. We combine ~2,400 individual survey interviews collected in 2024 across Albania, Kosovo, Moldova, and Romania with high-resolution ERA5-Land indicators (1994–2023) of precipitation and temperature (long-run trends variability). Using two-level probit models with village random intercepts and country fixed effects, we estimate the probability of intending to migrate abroad. In baseline specifications, place attachment (PA) is a strong negative predictor of migration intentions, while the predictive power of our climate indicators is modest on average. Allowing climate effects to vary by PA reveals clear heterogeneity: (i) positive precipitation trends are associated with higher migration intentions at low PA, but this effect is strongly attenuated at high PA; and (ii) precipitation variability exhibits a sign flip—negative at low PA, positive at high PA—consistent with differential appraisal and coping. Temperature trend effects are weak, and temperature variability shows only a small association. Overall, climate dynamics do not uniformly raise migration intentions; rather, social rootedness conditions whether and how climate stress translates into an intention to leave.