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A global CGE model at the NUTS 1 level for trade policy evaluation
Full text linkNegli 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 perché consentono di elaborare una grande quantità di informazioni in una struttura economica coerente in cui le famiglie massimizzano la loro utilità 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 è 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 è neutrale e la soluzione è 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, è 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 è 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 più comunemente utilizzata nei modelli EGC per il commercio internazionale. Essa è 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 Adenäuer, 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 è specifico al settore agricolo dell'UE e MIRAGE-DREAM considera le regioni NUTS (Nomenclature d’Unités Statistiques) dell’UE25. Ci sono così pochi modelli a livello sub-nazionale a causa della mancanza di dati adeguati riguardo il commercio tra le regioni all’interno 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 è sistematicamente il caso. Quindi, si ricorre ad ipotesi semplificatrici per rendere i modelli trattabili. Inoltre, questo genere di modello è 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 è di sviluppare un modello EGC per il commercio internazionale a livello NUTS 1 per le 68 regioni che compongono l’UE15. Lo scopo non è 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’Europa a 15 ad un livello geografico disaggregato mantenendo l’approccio su scala mondiale tipico di modelli come MIRAGE e GTAP. L'economia dell’UE è molto diversificata e gli accordi in seno all’OMC non considerano le disparità che esistono a livello regionale. Questa eterogeneità geografica nell'UE dovrebbe essere considerata nei negoziati dell’OMC. Inoltre, è di interesse valutare come i lavoratori europei rispondono ad uno shock commerciale. Migreranno in un'altra regione europea? Il modello è stato applicato alle 68 regioni NUTS 1 nell’UE15 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 può anche essere usato per simulare altre riforme di politica commerciale secondo l'interesse specifico del ricercatore. Un’attenzione speciale è rivolta all'interpretazione economica degli effetti di politica commerciale. Infatti, un punto debole dell’approccio EGC è l’insufficiente 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 più marcati si hanno nelle regioni austriache (est, ovest e sud), in Irlanda e Portogallo. Nei settori dei servizi e dell’industria è possibile notare dinamiche inverse della produzione a livello NUTS 1. Infatti, mentre Nisia Aigaiou-Kriti, Attica e Portogallo mostrano le più grandi diminuzioni nel settore industriale l'Irlanda, l'Austria orientale ed il Lussemburgo hanno il più grande aumento in questo settore. Al contrario, Nisia Aigaiou-Kriti, Attica e Portogallo esibiscono i più grandi aumenti nel settore dei servizi mentre l'Irlanda, l'Austria orientale ed il Lussemburgo mostrano la più grande diminuzione in questo settore. Il modello stilizzato consente di determinare il parametro chiave per interpretare i risultati. Tale parametro è la differenza settoriale fra i rapporti dell'intensità di utilizzo del lavoro qualificato sull’intensità di utilizzo del lavoro qualificato. Infatti il lavoro qualificato e non qualificato può essere considerato come la fonte primaria dell'eterogeneità 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 più 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 più 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 più 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 intensità 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 Adenäuer, 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’Unités 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
Sensitivity of Modeling Results to Technological and Regional Details: The Case of Italy’s Carbon Mitigation Policy
Full text linkModel differences in technological and geographical scales are common, but their contributions to uncertainties have not been systematically quantified in the climate policy literature. This paper carries out a systematic assessment on the sensitivity of Computable General Equilibrium models to technological and geographical scales in evaluating the economic impacts of carbon mitigation policies. Taking Italy as an example, we find that the estimation for carbon price and the economic cost of a de-carbonization pathway by means of a model with technological and regional details can be lower than a model without such details by up to 40%. Additionally, the effect of representing regional details appears to be far more important than the effect of representing the details of electricity technology in both the estimated carbon prices and the estimated economic impacts. Our results for Italy highlight the importance of modeling uncertainties of these two key assumptions, which should be appropriately acknowledged when applying CGE models for policy impact assessment. Our conclusions can be generalized to different countries and policy scenarios not in terms of absolute numbers but in terms of economic explanations. In particular, intra-national trade and the sub-national sectoral/technological specialization are important variables for understanding the economic dynamics behind these outcomes
An integrated assessment of the impact of agrobiodiversity on the economy of the Euro-Mediterranean region
Full text linkIn the past decades, agricultural landscapes have simplified with crop specialization and the reduction of
seminatural covers leading to a decline of biodiversity and (biodiversity-driven) ecosystem services. This study
measures the impact of landscape agrobiodiversity on the economy of southern Europe. The analysis relies on
regression analyses to measure the effect of agrobiodiversity on the value added of farms. A regionalized
Computable General Equilibrium model is then used to examine how these results affect the economy at large.
The results show that increasing local richness and regional evenness tends to have positive impacts on the
agricultural sector and GDP whereas increasing local evenness and regional richness tends to be harmful to the
agricultural sector and GDP. The results also suggest that some regions of southern Europe are better off with
more agrobiodiversity whereas other regions are better off with less. A targeted program may be better than a
uniform policy across all of southern Europ
Toward the full implementation of the water-energy-food nexus in computable general equilibrium modelling: methods and macroeconomic implications
Full text linkThis paper contributes to the advancement of Computable General Equilibrium (CGE) modelling in addressing the Water-Energy-Food (WEF) Nexus. As such, it introduces water resources as a production factor for both the energy sector and irrigated agriculture, as well as their competition for the
endowment, aiming to explicitly represent
additional components of the WEF with respect to a standard
CGE in the literature. Thus, it develops different modelling structures by computing impacts on regional GDP, sectorial prices, and production outputs in response to hypothetical water scarcity scenarios.
This analysis allows for the determination of the role of data and
modelling assumptions, such as production function, water substitutability with other endowments, water mobility across sectors, and sectorial water intensity, in influencing the results. Finally, the paper develops a dynamic scenario analysis, showing that an enhanced representation of the Nexus can significantly affect the macroeconomic dynamics of the simulations and their regional implications
An integrated approach for the estimation of agricultural drought costs
Full text linkThis 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 interregional 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
Cost of agricultural productivity loss due to soil erosion in the European Union: From direct cost evaluation approaches to the use of macroeconomic models
No full textMuch research has been carried out on modelling soil erosion rates under different climatic and land use conditions. Although some studies have addressed the issue of reduced crop productivity due to soil erosion, few have focused on the economic loss in terms of agricultural production and gross domestic product (GDP). In this study, soil erosion modellers and economists come together to carry out an economic evaluation of soil erosion in the European Union (EU). The study combines biophysical and macroeconomic models to estimate the cost of agricultural productivity loss due to soil erosion by water in the EU. The soil erosion rates, derived from the RUSLE2015 model, are used to estimate the loss in crop productivity (physical change in the production of plants) and to model their impact on the agricultural sector per country. A computable general equilibrium model is then used to estimate the impact of crop productivity change on agricultural production and GDP. The 12 million hectares of agricultural areas in the EU that suffer from severe erosion are estimated to lose around 0.43% of their crop productivity annually. The annual cost of this loss in agricultural productivity is estimated at around €1.25 billion. The computable general equilibrium model estimates the cost in the agricultural sector to be close to €300 million and the loss in GDP to be about €155 million. Italy emerges as the country that suffers the highest economic impact, whereas the agricultural sector in most Northern and Central European countries is only marginally affected by soil erosion losses
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Assessing Direct and Indirect Economic Impacts of a Flood Event Through the Integration of Spatial and Computable General Equilibrium Modelling
Full text linkIn this paper we developed and tested an integrated methodology for assessing direct and indirect economic impacts of flooding. The methodology combines a spatial analysis of damage to physical stocks with a general economic equilibrium approach using a regionally-calibrated (to Italy) version of a Computable General Equilibrium (CGE) global model. We applied the model to the 2000 Po river flood. To account for the uncertainty in the induced effects on regional economies, we explored three disruption and two recovery scenarios. The results prove that: i) indirect losses are a significant share of direct losses, and ii) the model is able to capture both positive and negative economic effects of a disaster in different areas of the same country. The assessment of indirect impacts is essential for a full understanding of the economic outcomes of natural disasters
Exploring market-driven adaptation to climate change in a general equilibrium global trade model
No full textClimate change will have a big impact on human societies and economies. However, huge uncertainty remains concerning the role of adaptation in absorbing the negative effects. Our aim is to investigate how autonomous adaptation, and specifically the interaction between the different dimensions of market-driven adaptation, may influence economic performance in the context of the global warming. These different dimensions refer to the degree of mobility of capital, labour and goods in the global markets, and the substitutability between production factors. To achieve our goal we use a neo-classical Computable General Equilibrium (CGE) trade model. Climate impacts are derived from existing empirical literature on heat stress, agricultural productivity and sea level rise, and are translated in the economic model as exogenous shocks on the stock and productivity of production factors. Results show that Tropical and sub-Tropical regions are more negatively affected by climate change compared to the regions in the North, and the international mobility of labour and capital amplifies the economic inequalities between North and South in terms of GDP and production factor distribution. However, the international mobility of labour and capital is important to relocate production factors in the most productive regions of the planet but a necessary condition for such relocation is a free global market for goods. We also note a positive interaction between production factor substitutability and free markets. One possible policy implication of this study may be considering free global markets for both goods and factors such as a useful option for climate change adaptation and implementing at the same time appropriate development policies in the most vulnerable regions to reduce the economic disparities between North and South
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