Generally, the movement of cattle within any country including Italy is very essential to the economics of livestock industry. However, this transmission can also carry and spread the risk of contracting the disease (infectious diseases) by other cattle in various geographical areas. For example, this pattern of animal movements brought about an outbreak of foot-and-mouth infectious disease throughout the UK in 2001. Also as Taylor et. al (2001) mentioned that these diseases can give rise to the productivity decline and even can lead to some threats to human health. Therefore, to reduce the risk and economic loss of this kind of contagious diseases, authorities should be able to manage and control them (Andesron, 2002). This control measures can consist of monitoring the animal trades, inspecting entry to and exit from premises, adopting some eradication programs (say, sending sick cattle to slaughterhouses), quarantining cattle, and etc. To properly assess this kind of control measures, we need a comprehensive and detailed information and regulation about the cattle movement pattern. To address these issues, European Economic Community (EEC) devised some regulations and imposed them on its member states to adhere to these measures (EU traceability framework). Actually, these measures originate from the public health and food health concerns, which are related to animal health and the economic impacts of the outbreak of infectious diseases. The EEC issued Council Directive 92/102/EEC in 1992 (with latest modifications in 2013), which obliged member states to record the origin and destination point of each cattle. Also, each cattle should be tagged by an ear tag to be traceable . Specifically, European Parliament and European council in 2000 tried to simplify and implement this process through a digital framework that allows countries to identify and register their bovines . In Italy, this procedure was done by Italian National Animal Identification and Registration Database which proposes us a rich and valuable dataset, including the all required parameters, to perform and analyze some important determinants of Bovines movements and the effects of this kind of disease outbreaks on the pattern of bovines trade among different holdings. In recognition of the importance of national and international bovines’ trade, this thesis attempts to assess and investigate some relevant determinants of bovines movements among Italian holdings and Italian provinces. This study consists of three chapters. In the first chapter, we introduced a structural gravity model of trade and then we linked it to the Italian bovine trade system. Then, we assessed two important determinants of any animal movements, i.e. feed prices and financial literacy rate of farmers. In addition, we tried to analyze the interaction of these determinants on the movements of bovines among Italian provinces. We found that feed (corn, in our case) price shocks and financial literacy rate of farmers could significantly affect on the pattern of bovines movement. Furthermore, our findings suggest that this two factors have a close relationship together and can offset each other's effects, in the sense that the enhancing financial literacy rate of farmers can somehow immune them to the unexpected price shocks and actually undermine the effects of unfavorable price shocks on their business. In the second chapter, we used again the structural gravity model and employed it to investigate the risk of the outbreak of bovine diseases among Italian provinces. We found that the disease incidence rate has a significant positive effect of the movement of bovines from origin nodes to destination points. Also, we tried to merge our findings with the feed (corn) price effects and saw that these two factors act in a different direction. That is the more is the incidence rate, the effect of feed prices become less relevant to the movement of bovines among different provinces. In chapter 3, we tried to have a more detailed view on the effects of disease outbreaks on the movements of bovines among farms and slaughterhouses. In general, we found that the disease status has a negative effect on bovines movement from farms to farms, and a positive influence on the movements of bovines from farms to slaughterhouses. In addition, we found that the ownership has a significant role in determining the pattern of trade among holdings, in the sense that the results are reliable only if two trading partners have different owner/keeper. Although, if the effects were driven by movements between farms with the same owner, it would be a rational decision by the owners in order to separate and protect healthy bovines from sick bovines. However, we found that in the case of positive disease tests, distance has a positive effect on the movement of bovines between various farms. This somehow shows us that some farms may act in such an opportunistic behaviors that can even lead to the spread of diseases among different regions. Finally, we analyzed some network characteristics of the bovines movements to see the effect of network structure and its interaction with disease status on the pattern of movements. More specifically, we used the most commonly used feature of any network i.e. indegree, outdegree, and degree and found that in the case of diseases the farms tend to send more bovines to the slaughterhouses. Actually, the results on the interaction of indegree and disease tests show us that the farms that have received more (probably sick) bovines from more suppliers in the previous period, tend to send more bovines to other farms in the current time period. Also, we should note that the indegree analysis can help us tracing back the diseases to the nodes that are more exposed to receiving bovines and consequently more subject to contracting diseases. On the other hand, we found the outdegree is also important only in case of the trade from farms to other farms. This tells us that in the case of diseases, the farms tend to not change significantly the pattern of their trading partners (other farms), and probably they tend to send their (probably sick) bovines to the other farms and this situation can even decrease the number of heads which transfer from farms to slaughterhouses. This confirms the importance of such nodes in the network in the sense that those with higher outdegree can be considered as most dangerous nodes and can act as a source of spreading diseases among different premises.
Gholami, M. (2017). Essays in Applied Economics: Disease Outbreaks and Gravity Model Approach to Bovines movement network in Italy.
Essays in Applied Economics: Disease Outbreaks and Gravity Model Approach to Bovines movement network in Italy
GHOLAMI, MAHDI
2017-01-01
Abstract
Generally, the movement of cattle within any country including Italy is very essential to the economics of livestock industry. However, this transmission can also carry and spread the risk of contracting the disease (infectious diseases) by other cattle in various geographical areas. For example, this pattern of animal movements brought about an outbreak of foot-and-mouth infectious disease throughout the UK in 2001. Also as Taylor et. al (2001) mentioned that these diseases can give rise to the productivity decline and even can lead to some threats to human health. Therefore, to reduce the risk and economic loss of this kind of contagious diseases, authorities should be able to manage and control them (Andesron, 2002). This control measures can consist of monitoring the animal trades, inspecting entry to and exit from premises, adopting some eradication programs (say, sending sick cattle to slaughterhouses), quarantining cattle, and etc. To properly assess this kind of control measures, we need a comprehensive and detailed information and regulation about the cattle movement pattern. To address these issues, European Economic Community (EEC) devised some regulations and imposed them on its member states to adhere to these measures (EU traceability framework). Actually, these measures originate from the public health and food health concerns, which are related to animal health and the economic impacts of the outbreak of infectious diseases. The EEC issued Council Directive 92/102/EEC in 1992 (with latest modifications in 2013), which obliged member states to record the origin and destination point of each cattle. Also, each cattle should be tagged by an ear tag to be traceable . Specifically, European Parliament and European council in 2000 tried to simplify and implement this process through a digital framework that allows countries to identify and register their bovines . In Italy, this procedure was done by Italian National Animal Identification and Registration Database which proposes us a rich and valuable dataset, including the all required parameters, to perform and analyze some important determinants of Bovines movements and the effects of this kind of disease outbreaks on the pattern of bovines trade among different holdings. In recognition of the importance of national and international bovines’ trade, this thesis attempts to assess and investigate some relevant determinants of bovines movements among Italian holdings and Italian provinces. This study consists of three chapters. In the first chapter, we introduced a structural gravity model of trade and then we linked it to the Italian bovine trade system. Then, we assessed two important determinants of any animal movements, i.e. feed prices and financial literacy rate of farmers. In addition, we tried to analyze the interaction of these determinants on the movements of bovines among Italian provinces. We found that feed (corn, in our case) price shocks and financial literacy rate of farmers could significantly affect on the pattern of bovines movement. Furthermore, our findings suggest that this two factors have a close relationship together and can offset each other's effects, in the sense that the enhancing financial literacy rate of farmers can somehow immune them to the unexpected price shocks and actually undermine the effects of unfavorable price shocks on their business. In the second chapter, we used again the structural gravity model and employed it to investigate the risk of the outbreak of bovine diseases among Italian provinces. We found that the disease incidence rate has a significant positive effect of the movement of bovines from origin nodes to destination points. Also, we tried to merge our findings with the feed (corn) price effects and saw that these two factors act in a different direction. That is the more is the incidence rate, the effect of feed prices become less relevant to the movement of bovines among different provinces. In chapter 3, we tried to have a more detailed view on the effects of disease outbreaks on the movements of bovines among farms and slaughterhouses. In general, we found that the disease status has a negative effect on bovines movement from farms to farms, and a positive influence on the movements of bovines from farms to slaughterhouses. In addition, we found that the ownership has a significant role in determining the pattern of trade among holdings, in the sense that the results are reliable only if two trading partners have different owner/keeper. Although, if the effects were driven by movements between farms with the same owner, it would be a rational decision by the owners in order to separate and protect healthy bovines from sick bovines. However, we found that in the case of positive disease tests, distance has a positive effect on the movement of bovines between various farms. This somehow shows us that some farms may act in such an opportunistic behaviors that can even lead to the spread of diseases among different regions. Finally, we analyzed some network characteristics of the bovines movements to see the effect of network structure and its interaction with disease status on the pattern of movements. More specifically, we used the most commonly used feature of any network i.e. indegree, outdegree, and degree and found that in the case of diseases the farms tend to send more bovines to the slaughterhouses. Actually, the results on the interaction of indegree and disease tests show us that the farms that have received more (probably sick) bovines from more suppliers in the previous period, tend to send more bovines to other farms in the current time period. Also, we should note that the indegree analysis can help us tracing back the diseases to the nodes that are more exposed to receiving bovines and consequently more subject to contracting diseases. On the other hand, we found the outdegree is also important only in case of the trade from farms to other farms. This tells us that in the case of diseases, the farms tend to not change significantly the pattern of their trading partners (other farms), and probably they tend to send their (probably sick) bovines to the other farms and this situation can even decrease the number of heads which transfer from farms to slaughterhouses. This confirms the importance of such nodes in the network in the sense that those with higher outdegree can be considered as most dangerous nodes and can act as a source of spreading diseases among different premises.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11365/1005912
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