An integrated approach for the estimation of agricultural drought costs

Abstract This study proposes a novel method to assess the overall economic effects of agricultural droughts using a coupled agronomic-economic approach that accounts for the direct and indirect impacts of this hazard in the economy. The proposed methodology is applied to Italy, where years showing different drought severity levels were analysed. Agricultural drought stress was measured using the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). Using a comprehensive, field-level dataset on agricultural yields, fAPAR-based statistical models were applied to major Italian crops and direct crop productivity impacts were estimated. Local-level, crop-dependent productivity shocks were fed into a regionalised Computable General Equilibrium model specifically calibrated for the Italian economy. Direct and indirect aggregate impacts after allowing for inter-regional trade and input reallocation were obtained. Total estimated damages ranged from 0.55 to 1.75 billion euro, depending on the overall drought severity experienced, while regional losses showed large spatial variability. Although most of the losses were concentrated on agriculture, other related sectors, such as food industry manufacturing and wholesale services, were also substantially affected. Moreover, our simulations suggested the presence of a land-use substitution effect from less to more drought-resistant crops following a drought. This study sheds light on the characterisation of the total damages caused by droughts while provides a tool with applicability in the implementation of drought risk management plans and the evaluation of drought management policies

A global CGE model at the NUTS 1 level for trade policy evaluation

This paper aims at building a global CGE trade model at NUTS 1 level (subnational level) for the EU15 regions. The focus is on the production side. The model is used to assess production reallocation across sectors in each NUTS 1 regions after an agricultural tariff liberalization. Nevertheless, it can also be used to simulate other trade policy reform according to the special objective of the researcher. The model is parsimonious in terms of data at the NUTS 1 level. The unskilled and skilled labour are the source of the heterogeneity across the NUT 1 regions. A stylised model is built in order to interpret the results. A sensitivity analysis on trade policy results according to two different degrees of skilled/unskilled labour mobility (perfect immobility and high mobility within the EU15) is conducted. Moreover, an integrated unskilled/skilled labour market within EU27 is tested.computable general equilibrium models, international trade

A global CGE model at the NUTS 1 level for trade policy evaluation

This paper aims at building a global CGE trade model at the NUTS 1 level (sub-national level) for the EU15 regions. The focus is on the production side. The model is used to assess production reallocation across sectors in each NUTS 1 regions after an agricultural tariff liberalization. Nevertheless, it can also be used to simulate other trade policy reform according to the special objective of the researcher. The model is parsimonious in terms of data at the NUTS 1 level. The unskilled and skilled labour are the source of the heterogeneity across the NUT 1 regions. A stylised model is built in order to interpret the results. A sensitivity analysis on trade policy results according to two different degrees of skilled/unskilled labour mobility (perfect immobility and high mobility within the EU15) is conducted. Moreover, an integrated unskilled/skilled labour market within the EU27 is tested

A global CGE model at the NUTS 1 level for trade policy evaluation

Negli ultimi anni lo sviluppo dell'Organizzazione mondiale del commercio (OMC) ha generato una grande richiesta di studi che analizzino le conseguenze potenziali delle politiche commerciali. L'Uruguay Round ed il Doha Round sono tipici esempi. Il policy maker potrebbe essere infatti interessato ad avere informazioni sugli effetti della liberalizzazione degli scambi su reddito, produzione e altre variabili macroeconomiche rilevanti. I modelli di equilibrio economico generale caclcolabile (EGC) rappresentano uno strumento importante per soddisfare questa esigenza perch\ue9 consentono di elaborare una grande quantit\ue0 di informazioni in una struttura economica coerente in cui le famiglie massimizzano la loro utilit\ue0 e le imprese i profitti. Oggi molti governi e istituzioni internazionali, per esempio l'OMC, la Commissione Europea (CE) e la banca mondiale (BM), dispongono di questo tipo di modelli per valutare l'impatto delle riforme commerciali. Nella mia tesi l'attenzione \ue8 orientata verso i modelli EGC per il commercio internazionale su scala mondiale, come GTAP, MEGABARE e MIRAGE, usati dalle organizzazioni internazionali (per esempio BM, OMC, CE) nelle loro analisi di liberalizzazione degli scambi. Questo tipo di modelli mantiene un forte spirito Walrasiano. I fattori sono pienamente impiegati, la moneta \ue8 neutrale e la soluzione \ue8 resa possibile attraverso i prezzi relativi. Tuttavia, alcuni importanti assunzioni non-Walrasiane, come la concorrenza imperfetta, possono essere introdotte. Il fatto che questi modelli EGC siano su scala mondiale presenta il vantaggio incontestabile di poter considerare all'interno della stessa struttura teorica le relazioni commerciali di tutti i paesi o i gruppi di paesi nel mondo, quali l'UE (Unione Europea), gli Stati Uniti, la Cina, l'India e l'Africa. Con riferimento a questo aspetto, \ue8 molto importante poter disporre di un database in cui le informazioni provenienti dalle diversi parti del mondo siano coerenti tra di loro. Il progetto GTAP nasce proprio per soddisfare questo bisogno; esso \ue8 una rete mondiale di ricercatori che conducono analisi quantitative riguardo questioni di economica internazionale, in particolare di politica commerciale. GTAP rappresenta la base di dati pi\uf9 comunemente utilizzata nei modelli EGC per il commercio internazionale. Essa \ue8 molto ricca e pratica, ma permette di svolgere l'analisi solo a livello nazionale o sovra-nazionale. Modelli EGC per il commercio internazionale esistono a livello sub-nazionale ma essi considerano soltanto una singola regione o una manciata di regioni. I modelli CAPRI-GTAP (Jansson, Kuiper e Aden\ue4uer, 2009), MONASH-MRF (Peter ed altri, 1996) e MIRAGE-DREAM (Jean e Laborde, 2004) sono esempi di modelli EGC che comprendono molte regioni. MONASH-MRF si riferisce alle regioni australiane, CAPRI-GTAP \ue8 specifico al settore agricolo dell'UE e MIRAGE-DREAM considera le regioni NUTS (Nomenclature d\u2019Unit\ue9s Statistiques) dell\u2019UE25. Ci sono cos\uec pochi modelli a livello sub-nazionale a causa della mancanza di dati adeguati riguardo il commercio tra le regioni all\u2019interno di un singolo Stato e gli altri Stati o regioni. Per esempio, nell'UE non esistono informazioni complete sui flussi commerciali per le regioni NUTS. Per quanto riguarda il commercio estero, alcune informazioni sono disponibili per alcuni paesi a livello regionale, ma questo non \ue8 sistematicamente il caso. Quindi, si ricorre ad ipotesi semplificatrici per rendere i modelli trattabili. Inoltre, questo genere di modello \ue8 molto pesante in termini di dati e di risorse computazionali. Gruppi di ricerca, finanziate da istituzioni pubbliche, lavorano su questi modelli altamente disaggregati a livello geografico. L'obiettivo di questa tesi \ue8 di sviluppare un modello EGC per il commercio internazionale a livello NUTS 1 per le 68 regioni che compongono l\u2019UE15. Lo scopo non \ue8 di replicare esattamente i modelli menzionati precedentemente ma piuttosto sviluppare un modello parsimonioso e semplice. I dati su lavoro qualificato, non qualificato e valore aggiunto sono disponibili a livello NUTS 1 (database EUROSTAT) mentre per le variabili restanti si ricorre ad ipotesi semplificatrici. Il modello riprende la struttura di MIRAGE ma specifica la produzione a livello NUTS 1. Questo tipo di modello dovrebbe permettere di analizzare le conseguenze di politica commerciale nell\u2019Europa a 15 ad un livello geografico disaggregato mantenendo l\u2019approccio su scala mondiale tipico di modelli come MIRAGE e GTAP. L'economia dell\u2019UE \ue8 molto diversificata e gli accordi in seno all\u2019OMC non considerano le disparit\ue0 che esistono a livello regionale. Questa eterogeneit\ue0 geografica nell'UE dovrebbe essere considerata nei negoziati dell\u2019OMC. Inoltre, \ue8 di interesse valutare come i lavoratori europei rispondono ad uno shock commerciale. Migreranno in un'altra regione europea? Il modello \ue8 stato applicato alle 68 regioni NUTS 1 nell\u2019UE15 principalmente per valutare la redistribuzione della produzione tra tre settori (agricoltura, industria e servizi) in ogni regione NUTS 1 dopo una liberalizzazione tariffaria nel settore agricolo a livello mondiale. Tuttavia, esso pu\uf2 anche essere usato per simulare altre riforme di politica commerciale secondo l'interesse specifico del ricercatore. Un\u2019attenzione speciale \ue8 rivolta all'interpretazione economica degli effetti di politica commerciale. Infatti, un punto debole dell\u2019approccio EGC \ue8 l\u2019insufficiente interpretazione economica dei risultati a causa del numero elevato di equazioni ed incognite. I risultati a livello NUTS 1 sono i seguenti. La liberalizzazione tariffaria nel settore agricolo colpisce tutte le regioni NUTS 1 che diminuiscono la produzione in questo settore. I decrementi pi\uf9 marcati si hanno nelle regioni austriache (est, ovest e sud), in Irlanda e Portogallo. Nei settori dei servizi e dell\u2019industria \ue8 possibile notare dinamiche inverse della produzione a livello NUTS 1. Infatti, mentre Nisia Aigaiou-Kriti, Attica e Portogallo mostrano le pi\uf9 grandi diminuzioni nel settore industriale l'Irlanda, l'Austria orientale ed il Lussemburgo hanno il pi\uf9 grande aumento in questo settore. Al contrario, Nisia Aigaiou-Kriti, Attica e Portogallo esibiscono i pi\uf9 grandi aumenti nel settore dei servizi mentre l'Irlanda, l'Austria orientale ed il Lussemburgo mostrano la pi\uf9 grande diminuzione in questo settore. Il modello stilizzato consente di determinare il parametro chiave per interpretare i risultati. Tale parametro \ue8 la differenza settoriale fra i rapporti dell'intensit\ue0 di utilizzo del lavoro qualificato sull\u2019intensit\ue0 di utilizzo del lavoro qualificato. Infatti il lavoro qualificato e non qualificato pu\uf2 essere considerato come la fonte primaria dell'eterogeneit\ue0 tra le regioni NUTS 1. Per riassumere, lo shock di politica commerciale colpisce il settore agricolo e causa una diminuzione della produzione in questo settore per tutte le regioni NUTS 1. Le regioni NUTS 1, che utilizzano pi\uf9 intensivamente il lavoro non qualificato nel settore agricolo e il lavoro qualificato nel settore manifatturiero e dei servizi rispetto alle altre regioni NUTS 1, sono le regioni pi\uf9 colpite nel settore agricolo. La diminuzione nella produzione di questo settore, a sua volta, determina una redistribuzione della produzione complessiva e riduce la domanda per il lavoro non qualificato. Di conseguenza, in generale il fattore lavoro non qualificato perde (il salario diminuisce) e quello qualificato vince (il salario aumenta). Tuttavia, nelle regioni NUTS 1 che utilizzano pi\uf9 intensivamente il lavoro non qualificato nel settore manifatturiero e quello qualificato nel settore dei servizi, la produzione manifatturiera diminuisce e la produzione dei servizi aumenta. Al contrario, nelle regioni NUTS 1, che utilizzano i due fattori nei settori manifatturiero e dei servizi con una intensit\ue0 simile, la produzione manifatturiera aumenta e quella dei servizi diminuisce.In recent years the development of the World Trade Organization (WTO) has generated a great demand for estimates of potential consequences of trade policy. The Uruguay round and Doha round negotiations are typical examples. The policy maker could be interested in having information about the effects of trade liberalization on income, production and other relevant macroeconomic variables. Computable General Equilibrium (CGE) models are an important tool for meeting this need because they allow a lot of trade information to be elaborated in a coherent economic structure where agents maximise their utility and firms maximise their profits. Today many governments and international institutions, e.g. the WTO, the European Commission (EC) and the World Bank (WB), use CGE models to assess the impact of global trade reform. In my thesis the attention is directed toward large-scale global CGE trade models, such as GTAP, MEGABARE and MIRAGE, used by international organizations (e.g. the WB, the WTO, the EC) for their analysis of trade liberalization. This type of models maintains a strong Walrasian spirit. Factors are fully employed, money does not explicitly figure into the model and a solution is made possible through relative prices. Nevertheless, some important non-Walrasian assumptions, such as imperfect competition and others, are introduced or can be introduced. A global approach has the unquestionable advantage of taking into account within the same theoretical structure the trade relationships of all countries or groups of countries in the world, such as the EU, the USA, China, India and Africa. With respect to this, it is very important to have a consistent economic global database that covers all parts of the world. GTAP, based in the Agricultural Economics Department at Purdue University (West Lafayette, Indiana), has been created to satisfy this need; It is a global network of researchers who conduct quantitative analysis of international economic policy issues, especially trade policy. GTAP is the most widely used dataset for global CGE trade models. It is very rich and practical, however it only allows analysis at the national level. CGE trade models exist at a sub-national level but they only consider a single region or a handful of regions. The CAPRI-GTAP (Jansson, Kuiper and Aden\ue4uer, 2009), MONASH-MRF (Peter et al., 1996) and MIRAGE-DREAM (Jean and Laborde, 2004) models are examples of large-scale global CGE trade models which also include many regions. MONASH-MRF refers to the Australian regions, CAPRI-GTAP is specific to the agriculture sector of the EU and MIRAGE-DREAM considers the NUTS (Nomenclature d\u2019Unit\ue9s Statistiques) regions of the 25 members of the EU (Romania and Bulgaria did not belong to the EU in 2004). There are so few models because there is a lack of well-suited regional data concerning foreign trade. For instance, in the EU there is no complete dataset on foreign trade that is available for the NUTS regions. Concerning foreign trade, some information is available for some countries at the regional level, but this is not systematically the case. Thus, simplifying assumptions must be made to make the models manageable. In addition, this kind of model is very demanding both in terms of data and computational resources. Research teams, supported by public institutions, work on these models which are highly disaggregated at the geographical level. The objective of this thesis is to build a global CGE trade model at the NUTS 1 level for the 68 regions within the first 15 member states of the European Union. The aim is not to exactly reproduce the models mentioned above but the aim is to build a simple parsimonious CGE model. Data on value added, skilled labour and unskilled labour are available at the NUTS 1 level (EUROSTAT database) while simplifying assumptions arise for the remaining variables. Therefore a CGE trade model is built in which only the production is specified at the NUTS 1 level. The model is built starting from the MIRAGE model. This type of model should allow the consequences of trade policy in Europe to be investigated at a disaggregated geographical level while maintaining a global approach. The EU economy is very diversified and world trade agreements do not take into account the disparities existing at regional level. This geographical heterogeneity in the EU should be considered in WTO negotiations. In addition, it is of interest to assess how European workers respond to trade shock. Will they migrate to another European region? The model is applied to the 68 NUTS 1 regions in the EU15 mainly to assess the production reallocation across three sectors (agriculture, manufactures, services) in each NUTS 1 region after a world tariff liberalization in agriculture. Nevertheless, it can also be used to simulate other trade policy reforms according to the special interest of the researcher. Special attention is given to the economic interpretation of the trade policy effects. Indeed, a weak link of the CGE approach is the poor economic interpretation of the results. The results at the NUTS 1 level are the following. The tariff liberalization in agriculture determines a decrease for all the NUTS 1 regions in this sector. The most affected regions are East, West and South Austria, Ireland and Portugal. In the manufactures and services sectors it is possible to note inverse patterns of production at the NUTS 1 level. Indeed, Nisia Aigaiou-Kriti, Attica and Portugal show the greatest decreases in the manufactures while Ireland, East Austria and Luxembourg experience the greatest increase in the same sector. In contrast, Nisia Aigaiou-Kriti, Attica and Portugal exhibit the greatest increases in services and Ireland, East Austria and Luxembourg show the greatest decrease in this sector. The stylised model allows the key parameter to be determined for interpreting the results. This parameter is the sectoral difference between the ratios of unskilled labour intensity to skilled labour intensity. Indeed, skilled labour and unskilled labour can be considered as the source of the heterogeneity across the NUTS 1 regions. To summarize, trade policy strikes the agricultural sector and causes a production decrease in this sector for all the NUTS 1 regions. The NUTS 1 regions, which use unskilled labour in agriculture and skilled labour in manufactures and services sectors more intensively with respect to the other NUTS 1 regions, are the most affected regions in the agricultural sector. The decrease in the agricultural production, in turn, determines a production reallocation and reduces the labour demand for unskilled labour. As a result, in general the unskilled factor loses (the wage goes down) and the skilled factor wins (the wage goes up). However, in the NUTS 1 regions which use the unskilled labour in the manufactures and the skilled labour in services more intensively, the manufacturing production decreases and services production increases. In contrast, in the NUTS 1 regions, which use the unskilled and skilled factors in the manufactures and services sectors by similar intensities, the manufacturing production goes up and the services production goes down. The introduction of the labour mobility causes amplification effects for the NUTS 1 regions which experienced strong increases or decreases in the IND and SERV sectors under the assumption of perfect immobility at the NUTS 1 level. In general, this hypothesis has a strong impact on the outcomes and determines unrealistic variations of the production in the services and manufactures sectors after agricultural liberalization. These results are not intended to be realistic but are a guide regarding the relevance of the assumption about labour mobility. The change in the unskilled/skilled labour supply is consistent with the production reallocation results

Policy-relevant Assessment Method of Socio-Economic Impacts of Floods: an Italian Case Study

This paper estimates the direct and indirect socio-economic impacts of the 2000 flood that took place in the Po river basin (Italy) using a combination of Computable General Equilibrium (CGE) model and Spatial and Multi-Criteria Analysis. A risk map for the whole basin is generated as a function of hazard, exposure and vulnerability. The indirect economic losses are assessed using the CGE model, whereas the direct social and economic impacts are estimated with spatial analysis tools combined with Multi-Criteria Analysis. The social impact is expressed as a function of physical characteristics of the extreme event, social vulnerability and adaptive capacity. The results indicate that the highest risk areas are located in the mountainous and in the most populated portions of the basin, which are consistent with the high values of hazard and vulnerability. Considerably economic damages occurred to the critical infrastructure of all the sectors with the industry/commercial sector having the biggest impact. A negative variation in the country and industry Gross Domestic Product (GDP) was also reported. Our study is of great interest to those who are interested in estimating the economic impact of flood events. It can also assist decision makers in pinpointing factors that threaten the sustainability and stability of a risk-prone area and more specifically, to help them understand how to reduce social vulnerability to flood events

Current and projected regional economic impacts of heatwaves in Europe

Extreme heat undermines the working capacity of individuals, resulting in lower productivity, and thus economic output. Here we analyse the present and future economic damages due to reduced labour productivity caused by extreme heat in Europe. For the analysis of current impacts, we focused on heatwaves occurring in four recent anomalously hot years (2003, 2010, 2015, and 2018) and compared our findings to the historical period 1981-2010. In the selected years, the total estimated damages attributed to heatwaves amounted to 0.3-0.5% of European gross domestic product (GDP). However, the identified losses were largely heterogeneous across space, consistently showing GDP impacts beyond 1% in more vulnerable regions. Future projections indicate that by 2060 impacts might increase in Europe by a factor of almost five compared to the historical period 1981-2010 if no further mitigation or adaptation actions are taken, suggesting the presence of more pronounced effects in the regions where these damages are already acute.D.G.L. acknowledges financial support from the European Commission (H2020-MSCA-IF-2015) under REA grant agreement no. 705408. A.B., A.C., A.F., and L.N. received funding from the European Union’s Horizon 2020 research and innovation program under the grant agreement no. 66878

Endogenous technical change linked to international mobility of primary factors in climate change scenarios: global welfare implications using the GTAP model

Recent econometric literature suggests that the level of the economic activity and economic productivity are linked to changes in temperature. The relationship is non-linear, inverted U-shaped and generalizable to both developing and developed countries. An optimum level of temperature seems to be associated with an optimum level of productivity. Starting from this our research question is to evaluate ex-ante the welfare (GDP) implications for the global economy induced by an increase in the international mobility of primary factors (labor and capital) associated with climate impacts on economic productivity. To achieve this goal we use a neo-classical Computable General Equilibrium model, GTAP. Compared to the standard GTAP we only modify the supply of labor and capital to allow for the international mobility of primary factors. Results show that in case of an asymmetric climate impact between regions international mobility of primary factors (capital and labor) can transform a climate cost in a climate opportunity. Importantly, a stronger negative climate impact can increase the climate opportunity provided by the international mobility of primary factors. The explanation behind these results is the movement of labor and capital prices which drive the relocation of primary factors toward the most productive regions

Welfare implications of increasing spatial resolution in national CGE models for climate change impact assessment

Computable General Equilibrium (CGE) models are a widespread tool to assess the economic impacts of climate change because they allow to capture the inter-sectoral and inter-regional interactions of the environmental and climatic shocks. The geographical resolution adopted in CGE models is usually the country level, however, climate impacts can be heterogenous even within countries as regions located at different latitudes or altitudes respond differently to changes in temperature and precipitations. Our aim in this work is to evaluate the welfare implications of increasing the spatial resolution of a CGE model when combined with sub-national level impacts of climatic change on sectoral Gross Value Added (GVA) derived through spatial econometrics. We compare a standard version of a national CGE model calibrated for Italy with its sub-national version (twenty Italian NUTS-2 regions). The objective is not only to show that the aggregated results obtained can differ in terms of national GDP loss but also to provide an economic explanation for these differences. Specifically, we will explain the importance of intra-national trade (flows of imports and exports between sub-national units) and capital/labour re-location across regions. These economic channels are absent in the national version of the CGE

Welfare implications of increasing spatial resolution in national CGE models for climate change impact assessment

Computable General Equilibrium (CGE) models are a widespread tool to assess the economic impacts of climate change because they allow to capture the inter-sectoral and inter-regional interactions of the environmental and climatic shocks. The geographical resolution adopted in CGE models is usually the country level, however, climate impacts can be heterogenous even within countries as regions located at different latitudes or altitudes respond differently to changes in temperature and precipitations. Our aim in this work is to evaluate the welfare implications of increasing the spatial resolution of a CGE model when combined with sub-national level impacts of climatic change on sectoral Gross Value Added (GVA) derived through spatial econometrics. We compare a standard version of a national CGE model calibrated for Italy with its sub-national version (twenty Italian NUTS-2 regions). The objective is not only to show that the aggregated results obtained can differ in terms of national GDP loss but also to provide an economic explanation for these differences. Specifically, we will explain the importance of intra-national trade (flows of imports and exports between sub-national units) and capital/labour re-location across regions. These economic channels are absent in the national version of the CGE