Tamás Krisztin

International Institute for Applied Systems Analysis | IIASA · Integrated Biosphere Futures (IBF)

Worldwide increasing demand for agricultural products poses the critical question of where this additional production will take place. In this context, the phenomenon of large scale Foreign Land Acquisition (FLA) is one strategy that has been controversially discussed in scientific and public debates. A better understanding of what factors drive FL...

International trade enables us to exploit regional differences in climate change impacts and is increasingly regarded as a potential adaptation mechanism. Here, we focus on hunger reduction through international trade under alternative trade scenarios for a wide range of climate futures. Under the current level of trade integration, climate change...

In this paper we use spatial econometric specifications to model daily infection rates of COVID-19 across countries. Using recent advances in Bayesian spatial econometric techniques, we particularly focus on the time-dependent importance of alternative spatial linkage structures such as the number of flight connections, relationships in internation...

Increased efforts are required to prevent further losses to terrestrial biodiversity and the ecosystem services that it provides1,2. Ambitious targets have been proposed, such as reversing the declining trends in biodiversity³; however, just feeding the growing human population will make this a challenge⁴. Here we use an ensemble of land-use and bi...

We develop a Bayesian approach to estimate weight matrices in spatial autoregressive (or spatial lag) models. Our approach focuses on spatial weights which are binary prior to row-standardization. However, unlike recent literature our approach requires no strong a priori assumptions on (socio-)economic distances between the spatial units. The estim...

The management of Soil Organic Carbon (SOC) is a critical component of both nature-based solutions for climate change mitigation and global food security. Agriculture has contributed substantially to a reduction in global SOC through cultivation, thus there has been renewed focus on management practices which minimize SOC losses and increase SOC ga...

Intensive agriculture with high reliance on pesticides and fertilizers constitutes a major strategy for ‘feeding the world’. However, such conventional intensification is linked to diminishing returns and can result in ‘intensification traps’ – production declines triggered by the negative feedback of biodiversity loss at high input levels. We deve...

Working paper analysing the economic implications of the proposed 30% target for areal protection in the draft post-2020 Global Biodiversity Framework

This paper studies the joint dynamics of foreign direct investments (FDI) and output growth in European regions by using spatially augmented systems of equations modeling framework that incorporates third‐region and spillover effects. The joint framework is used to study the dynamic impacts of regional human capital endowments, which demonstrates t...

We examine spillovers from agricultural estates to Malawian smallholders within an econometric counterfactual framework. We consider economic spillovers such as income, as well as agrarian spillovers such as yields, harvests, and crop diversity. We identify long-run effects of large agricultural investments on small-scale farmers. For the location...

We develop a Bayesian approach to estimate weight matrices in spatial autoregressive (or spatial lag) models. Datasets in regional economic literature are typically characterized by a limited number of time periods (Formula presented.) relative to spatial units (Formula presented.). When the spatial weight matrix is subject to estimation severe pro...

As they gain new users, climate change mitigation scenarios are playing an increasing role in transitions to net zero. One promising practice is the analysis of scenario ensembles. Here we argue that this practice has the potential to bring new and more robust insights compared with the use of single scenarios. However, several important aspects ha...

This paper presents an empirical study of spatial origin and destination effects of European regional FDI dyads. Recent regional studies primarily focus on locational determinants, but ignore bilateral origin- and intervening factors, as well as associated spatial dependence. This paper fills this gap by using observations on interregional FDI flow...

Deforestation of the Amazon rainforest is a threat to global climate, biodiversity, and many other ecosystem services. In order to address this threat, an understanding of the drivers of deforestation processes is required. Spillover effects and factors that differ across locations and over time play important roles in these processes. They are lar...

Trade liberalization in the early 21st century increased the adaptation capacity of global food systems to climate change; further liberalization and trade facilitation could help to avoid dozens of millions being undernourished at mid-century. The global trade agenda should explicitly include climate change adaptation to achieve SDG 2 Zero Hunger....

In this paper, we propose a Bayesian estimation approach for a spatial autoregressive logit specification. Our approach relies on recent advances in Bayesian computing, making use of Pólya–Gamma sampling for Bayesian Markov-chain Monte Carlo algorithms. The proposed specification assumes that the involved log-odds of the model follow a spatial auto...

Deforestation of the Amazon rainforest is a threat to global climate, biodiversity, and many other ecosystem services. In order to address this threat, an understanding of the drivers of deforestation processes is required. Indirect impacts and determinants that eventually differ across locations and over time are important factors in these process...

The paper proposes a Bayesian multinomial logit model to analyse spatial patterns of urban expansion. The specification assumes that the log-odds of each class follow a spatial autoregressive process. Using recent advances in Bayesian computing, our model allows for a computationally efficient treatment of the spatial multinomial logit model. This...

Even though enormous expectations for greenhouse gas mitigation in the land use sector exist at the same time worries about potential implications for sustainable development have been raised as many Sustainable Development Goals (SDGs) are closely tied to developments in the sector. Here we assess the implications of achieving selected key SDG ind...

Urban heat islands are an increasing concern even in small- to medium-sized cities, although these areas are still understudied especially in terms of the economic feasibility of adaptation options. This paper uses adaptation scenarios produced by an urban climate model as inputs to a social cost–benefit analysis in three small- to medium-sized cit...

Human land use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth’s surface, with consequences for climate and other ecosystem services. In the future, land use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the World Clima...

This paper presents an empirical study of spatial origin and destination effects of European regional FDI dyads. Recent regional studies primarily focus on locational determinants, but ignore bilateral origin- and intervening factors, as well as associated spatial dependence. This paper fills this gap by using observations on interregional FDI flow...

Background: The quantity, quality, and type (e.g., animal and vegetable) of human food have been correlated with human health, although with some contradictory or neutral results. We aimed to shed light on this association by using the integrated data at country level. Methods: We correlated elemental (nitrogen (N) and phosphorus (P)) compositio...

The paper proposes a Bayesian multinomial logit model to analyse spatial patterns of urban expansion. The specification assumes that the log-odds of each class follow a spatial autoregressive process. Using recent advances in Bayesian computing, our model allows for a computationally efficient treatment of the spatial multinomial logit model. This...

In this paper we use a spatial econometric specification to model daily infection rates of Covid-19 across countries. Using recent advances in Bayesian spatial econometric techniques, we particularly focus on the time-dependent importance of alternative spatial linkage structures such as the number of flight connections, relationships in internatio...

Abstract. Human land-use activities have resulted in large changes to the biogeochemical and biophysical properties of the Earth surface, with consequences for climate and other ecosystem services. In the future, land-use activities are likely to expand and/or intensify further to meet growing demands for food, fiber, and energy. As part of the Wor...

Countries are responding to unsustainable resource extraction, rising emissions, and increasing waste streams by implementing national bioeconomy strategies. Assuming that the purpose of a bioeconomy is to replace fossil use by biogenic resource use, we estimate biomass and fossil raw material consumption (RMC) by applying multiregional input-outpu...

Land-use change is a direct driver of biodiversity and carbon storage loss. Projections of future land use often include notable expansion of cropland areas in response to changes in climate and food demand, although there are large uncertainties in results between models and scenarios. This study examines these uncertainties by comparing three dif...

In this paper we propose a Bayesian estimation approach for a spatial autoregressive logit specification. Our approach relies on recent advances in Bayesian computing, making use of Pólya-Gamma sampling for Bayesian Markov-chain Monte Carlo algorithms. The proposed specification assumes that the involved log-odds of the model follow a spatial autor...

This work investigates whether mining activities relate to the economic performance of mining regions and their surrounding areas. We exploit a panel of 32 Mexican, 24 Peruvian and 16 Chilean regions over the period 2008 - 2015 and, in doing so, relate mine-specific data on extraction intensity to regional economic impacts. The study employs a Spat...

p>Rapidly increasing populations coupled with increased food demand requires either an expansion of agricultural land or sufficient production gains from current resources. However, in a changing world, reduced water availability might undermine improvements in crop and grass productivity and may disproportionately affect different parts of the wor...

The Indus River Basin faces severe water quality degradation because of nutrient enrichment from human activities. Excessive nutrients in tributaries are transported to the river mouth, causing coastal eutrophication. This situation may worsen in the future because of population growth, economic development, and climate change. This study aims at a...

International trade presents a challenge for measuring the greenhouse gas (GHG) emission footprint of human diets, because imported food is produced with different production efficiencies and sourcing regions differ in land use histories. We analyze how trade and countries of origin impact GHG footprint calculation for EU food consumption. We find...

Smallholder farms are often the focus of strategies to reduce poverty, inequality and hunger. They are also a very diverse group, leading to calls for more context-specific strategies to support smallholder farms. Until recently, a lack of both household and macro-level data prevented policymaking tailored to the context of smallholder farms, i.e....

The Fremont were members of an expansive maize-based Ancestral Puebloan (AP) cultural complex who disappeared from Utah between the 12th and 13th centuries CE. This period brackets that of a climatic transition in the Southwest from the warm, dry Medieval Climate Anomaly (MCA, ca. 850–1350 CE) to the cool, hydro-climatically variable Little Ice Age...

This paper proposes for the purposes of freight generation a spatial autoregressive model framework , combined with non-linear semi-parametric techniques. We demonstrate the capabilities of the model in a series of Monte Carlo studies. Moreover, evidence is provided for non-linearities in freight generation, through an applied analysis of European...

Unless actions are taken to reduce multiple anthropogenic pressures, biodiversity is expected to continue declining at an alarming rate. Models and scenarios can be used to help design the pathways that sustain a thriving nature and its ability to contribute to people. This approach has so far been hampered by the complexity associated with combini...

This article investigates projected changes in temperature and water cycle extremes at 1.5°C of global warming, and highlights the role of land processes and land-use changes (LUCs) for these projections. We provide new comparisons of changes in climate at 1.5°C versus 2°C based on empirical sampling analyses of transient simulations versus simulat...

We analyzed mean height of men born in the 1960s, 1970s and 1980s in 80 countries. Both height and the change in height during the last decades were correlated with N and P intake, as well as the N:P intake ratio. Rich countries had higher per capita N and P intake than poor countries (on average 19.5 ± 0.3 versus 9.66 ± 0.18 kg N y-1 and 2.17 ± 0....

In the context of modeling regional freight the four-stage model is a popular choice. The first stage of the model, freight generation and attraction, however, suffers from three shortcomings: first of all, it does not take spatial dependencies among regions into account, thus potentially yielding biased estimates. Second, there is no clear consens...

This paper proposes a large Bayesian Vector Autoregressive (BVAR) model with common stochastic volatility to forecast global equity indices. Using a monthly dataset on global stock indices, the BVAR model controls for co-movement commonly observed in global stock markets. Moreover, the time-varying specification of the covariance structure accounts...

Figure S1. Aggregated world regions as applied in the regional analysis. Figure S2. Schematic overview of the analysis conducted in this study. Figure S3. Variation of land use changes for 43 scenarios of 11 models. Figure S4. Projections of land cover areas [Mha] for cropland, pasture and forest. Figure S5. Full results of the variance decompo...

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies, and quantifying the impacts of land cover change on the climate system. Here we identify and quantify uncertainties in global and European land cover projections over a...

Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, w...

Using econometric models to estimate land-use change has a long tradition in literature. Recent contributions show the importance of including spatial information and of using a multi-nomial framework to take into account the inter-dependencies between the land-use classes. Few studies, however, agree on the relevant determinants of land-use change...

The Poisson gravity model along with pseudo maximum likelihood (ML) methods has become a popular way to model international trade flows. This approach has several econometric advantages that we outline in the paper. We argue that estimating the parameters by ML would only be justified statistically if the trade flows were independent. Such an assum...

Classical spatial autoregressive models share the same weakness as the classical linear regression models, namely it is not possible to estimate non-linear relationships between the dependent and independent variables. In the case of classical linear regression a semi-parametric approach can be used to address this issue. Therefore an advanced semi...

Classical spatial autoregressive models share the same weakness as the classical linear regression models, namely it is not possible to estimate non-linear relationships between the dependent and independent variables. In the case of classical linear regression a semi-parametric approach can be used to address this issue. Therefore we propose an ad...

In this paper an attempt is made to assess the hypothesis of re- gional club-convergence, using a spatial panel analysis combined with B-Splines. In this context, a ‘convergence-club’ is conceived as a group of regions that in the long-run move towards steady-state equilib- rium, approximated in terms of the average per-capita income. Using dat...

This paper presents a comparative assessment of two distinct urban growth modeling approaches. The first urban model uses a traditional Cellular Automata methodology, based on Markov transition chains to prospect probabilities of future urban change. Drawing forth from non-linear cell dynamics, a multi-criteria evaluation of known variables prospec...

Asynchronous multi-agent systems have been widely used to optimize complex combinatorial problems. Their main strength lies in their ability to combine different heuristic algorithms and thus arrive at comparatively better solutions then their constituting algorithms on their own. A further strength is their flexibility in interlinked problems. Thi...