Olga Ivanova (p), Corjan Brink , Kristian Bakker, Theodoros Chatzivasileiadis

Łukasz Gręda

Dutch regional economic and transport WLO (Welvaart en Leefomgeving) scenarios are developed every seven years and provide policymakers with scenario-based insights to guide decisions on mobility and urbanization. Given the inherent uncertainty of the future, WLO study employs multiple scenarios to analyze the impact of various developments and assess the effectiveness of policy measures. The WLO study combines different scenario elements including regional demography, regional economy and transportation.
For the development of Regional Economic and Sectoral scenarios we employ a methodological approach that combines qualitative scenario narratives, econometric data analysis, and dynamic regional general equilibrium model (EU-EMS model ). This approach aims to quantify sectoral and regional development trajectories within the four scenarios of the future along the dimensions of economic growth (High and Low) and the speed of international climate policy (Rapid and Delayed). Inputs for these analyses include demographic data at the provincial level, labor force participation, productivity, and GDP projections for the Netherlands. The international dimension is modeled using CEPII’s MaGE model , which simulates labor productivity, GDP, and employment trends across EU and non-EU countries.
An essential aspect of the analysis is the integration of marginal abatement cost (MAC) curves derived from the IMAGE global Integrated Assessment Model and CO₂ price trajectories corresponding to emission reduction targets. These MAC curves outline the costs associated with emission reductions by sector and country group, ensuring consistency across the future scenarios.
Scenario analysis within the EU-EMS model proceeds in three phases. Initially, the "WLO High, Delayed" scenario is validated using national and international sectoral and consumption data. Subsequently, the "WLO Low, Delayed" scenario is developed, reflecting slower demographic and macroeconomic growth, lower investments in education and R&D, and increased domestic production reliance. Finally, ambitious climate policy is explored within "WLO High, Rapid" and "WLO Low, Rapid" scenarios, targeting a maximum global warming threshold of 1.8 degrees Celsius, with CO₂ price pathways adjusted accordingly.

Łukasz Gręda (p)

Santiago Pinto

Distance is one of the fundamental geographical concepts and a key element in various economic analyses, including those related to trade, such as the gravity model of trade. Its popularity stems from highly successful empirical analyses, despite its simplicity. Unfortunately, there is a lack of uniformity in distance measurements. It is assumed that the distance between countries can be defined as the distance between their capitals or largest cities, and less often between their centroids. However, these are not the only possible approaches. Distance can be calculated in many other ways, for instance based on average distances between multiple cities, centers of gravity, or equidistance.
An additional approach to measuring distance is provided by remote sensing methods, which allow for the acquisition of global data without concerns about data quality. Of particular potential is the data on light emissions at night, as they correlate closely with actual economic activity. Therefore, it is important to standardize distance measurements and assess the differences between various measures and their impact on analyses.
To this aim, this work develops a gravity model of trade using a variety of distance measures based on a literature review and cartographic or remote sensing methods. Using the AIC and BIC information criteria, the study determines which measures provide the best estimates. The results show that measurements based on more complex methods yield statistically better results. However, no major differences were observed between the most commonly used measures, based on capitals and the largest cities.

Santiago Pinto (p), Kishore Gawande, Pablo Pinto

Olga Ivanova

Congressional districts, heterogeneous in their trade policy preferences, are key players determining trade protectionism. Yet, they are missing from even the best-established political economy models of trade protection. We characterize the (unobserved) district-level demand for protection, and model national tariffs as an aggregation of district-level preferences. The model centrally features exporter interests as a countervailing force against domestic protectionism. We estimate welfare weights on specific-factor owners implied by tariff and non-tariff protection from 2002, a critical juncture coinciding with China’s WTO accession. The findings offer a new reason for the current backlash against free trade--the diminished role of manufacturing exporters.