Sotirios Thanos (p), Jean Dubé

Minjeong Kwak

Difference-in-difference (DiD) exploits exogenous shocks to capture causal effects in hedonic pricing (HP) models but rely heavily on fixed effects (FE) to, both, define the quasi-experimental settings and satisfy the assumptions of no spatial and temporal omitted variable bias (OVB). This reliance makes HP-DiD sensitive to the “bias-variance trade-off”, in which smaller FEs reduce bias by better controlling for omitted amenities and temporal patterns but increase variance. To help address the bias-variance trade-off, we develop a causal identification strategy that integrates DiD and the “Differenced-Price-Peers” (DPP) approach. The DPP approach is based on comparable sales occurring in close spatial proximity and tight time-window before a house sale. By differencing out common spatial observables and unobservables between comparables, DPP delivers a spatiotemporal OVB treatment without relying on FEs, which is especially useful in cases of sparse and challenging data. We first validate DPP-DiD by replicating the influential Linden and Rockoff (2008) results with improved statistical significance. We, then, employ the rare exogenous shock of airport closure in 2001 in Athens, Greece, to construct a quasi-experimental setting for aviation noise valuation, which is not possible through HP-DiD due to its limitations. We find that the airport closure resulted on average to a 5.41% price increase or a 0.74% price increase per decibel of noise reduction. When we consider the total number of previously exposed houses, our results suggest over 1 billion €s of potential benefits capitalised in the local housing stock because of the aviation noise termination. We also found that noise reductions are not valued linearly above 65 decibels, as for instance we find a 4.6% price increase per decibel for noise reductions above 70 decibels, which translates to a substantial €219,649 price increase.

Minjeong Kwak (p), Kwansoo Kim

Alexandre Florindo Alves

South Korea has achieved rapid economic growth through urbanization and industrialization, leading to a continuous decline in the proportion of rural population and agricultural income relative to urban area. To counteract this trend, the Korean government has implemented various agricultural support policies, including the Farmland Gift Tax Exemption Policy for Successor Farmers. This policy allows parents to transfer farmland to their children tax-free, reducing successor farmers’ land acquisition costs and supporting the sustainability of farming.
This study empirically examines whether this policy effectively fosters successor farmers. Specifically, it evaluates (1) the policy’s impact on maintaining the farming population and increasing farm income and (2) its effectiveness over multiple time periods.
Previous studies applied Generalized Propensity Score (GPS) to overcome the binary classification limitation of Propensity Score Matching (PSM) and used Difference-in-Differences (DID) to compare changes in the farming population and income before and after policy implementation. However, these approaches failed to isolate the specific effect of this policy, due to the simultaneous implementation of multiple farm income support programs. To address this issue, this study adopts Coarsened Exact Matching (CEM) to control for multiple policy benefits as a covariate, followed by GPS to analyze the policy effects as a continuous treatment variable. Additionally, Difference-in-Differences with multiple periods method will be used to examine changes in farm household age and income across two time periods, distinguishing between exclusive recipients, multiple-policy beneficiaries, or non-recipients.
Covering 2016 to 2024, the study divides this period into three four-year intervals to track policy effects. Specifically, it assesses whether the scale of farmland gift tax exemptions influences regional farm household age and income. Data from the National Tax Service (NTS) and Statistics Korea (KOSTAT) will be used to analyze tax benefit scales and farm household characteristics.
This research provides empirical evidence on the policy’s impact on successor farmer retention and farm income growth. Additionally, it evaluates whether the policy should be sustained and suggests future improvements. The findings will contribute to reevaluating successor farmer policies in Korea and globally, serving as a foundation for more effective agricultural policies to combat rural population decline.

Alexandre Florindo Alves (p), Aline Andreotti Pancera

Flavio Vieira

The objective of the research is to study the distribution and concentration of employment in Knowledge Intensive Activities (KIA) and the Manufacturing Activities in Paraná State, focusing on the five most employment-intensive activities in each category. The discussion is anchored in the broader debate on the industrial decentralization process in Brazil and the extent to which Knowledge-Intensive Activities (KIA) can serve as an alternative for economic diversification. Methodologically, the research relies on data from the Annual Social Information Report (RAIS/MTE - 2023), with employment figures analyzed for all 399 municipalities. The selection of the top five KIA was based on Eurostat’s (2025) definition, considering the highest employment volumes, and these were compared with the five most representative industrial activities, using the same criteria. The analysis incorporated data normalization per 100 inhabitants and evaluated concentration levels using the Hirschman-Herfindahl (HH) Index and the CR10 Index. To avoid biases related to universal public-sector employment, "Public administration, defense, and social security" and "Education" Activities were excluded from the KIA dataset. The exclusion of education is particularly relevant, as state universities register employment data in their headquarters’ municipalities, which could distort the real geographical distribution of higher-education employment. Findings reveal that while the Manufacturing Activities accounts for 11.26% of total formal employment, KIA contribute 4.24%. However, KIA exhibit greater spatial dispersion, with only two municipalities without employment in these activities, as opposed to 19 municipalities without industrial employment. A key structural asymmetry is the high concentration of KIAs in Curitiba, which alone accounts for 38.68% of employment in the top five KIA activities, positioning the state capital as an outlier in the dataset. By excluding Curitiba, the HH and CR10 measures became significantly adjusted. In addition, employment in the manufacturing sector remains highly concentrated, with only 1 in 5 municipalities having a significant presence. The standard deviation of industrial employment per 100 inhabitants (5.6939) far exceeds that of KIA (0.4398), highlighting the polarized distribution of manufacturing jobs, where certain locations concentrate employment while others are excluded from the manufacturing activities in question. The main contribution of this study lies in the analysis of dispersion and concentration patterns of Knowledge-Intensive Activities (KIA) and the Manufacturing Activities in the state of Paraná. This is a preliminary study, and near-future research will focus on developing more robust spatial indicators that will allow a more accurate assessment of KIA dispersion and its potential role in statewide economic diversification.

Flavio Vieira (p), Laura Silveira Paiva

Sotirios Thanos

The goal of this study is to investigate the role of economic complexity for exchange rate volatility and misalignment for the BRICS. We estimate three autoregressive distributed lag (ARDL) models of exchange rate volatility, exchange rate misalignment and misalignment based on Hodrick-Prescott filter for each country using data from 1995 to 2021. The results indicates that economic complexity has a long run role for the exchange rate misalignment models for Brazil, China, Russia and South Africa. Other variables such as the interest rate is significant for Brazil, China and India. Inflation is significant for all five countries. For the volatility models, economic complexity, inflation and interest rate are significant for China, and inflation for Russia. Regarding the error correction mechanism, for the volatility models the average is -0.564, for the misalignment models is -0.665 and for the misalignment HP models is -0.788, suggesting that in average the correction towards the equilibrium is slightly faster for the exchange rate volatility models compared to the exchange rate misalignment models.