1,720,965 research outputs found
Should I farm or should I not?
No full textIn this paper we use stochastic dynamic programming for modelling the investment decision
of a landowner contemplating the conversion of idle land to farmland. The landowner may, by
investing, develop land for active farming counting, whenever farming is not protable, on the
support secured by the CAP for land kept in good agricultural and environmental condition,
i.e. land "passively" farmed. We determine, under the current CAP frame, the optimal capital
intensity and the optimal investment timing and show that, if compared to a scenario where
no support is provided, land development occurs earlier in expected terms and the associated
capital intensity is lower. Our results contradict arguments against the support paid to farmers
that passively manage their land and show that the current policy frame allows maintaining
land in good state at limited cost in terms of excess capacity
Essays on Investment Efficiency and Timing
Full text linkA standard framework for the analysis of investment opportunities in the literature of corporate finance is the real options approach. The real options approach examines the value and timing of investment projects building on the idea that the opportunity to invest in a project is analogous to a financial option on a real asset. This means that, when evaluating an investment opportunity characterized by uncertainty and irreversibility, the potential investor needs to factor in that, at the time of the investment, s/he forgoes the option to postpone the investment decision for some future time point when the uncertainty will be, naturally, partly resolved.
With the real options approach as a starting point, this thesis is comprised by three papers examining primarily investments undertaken in a supply-chain setting (paper 1 and paper 2) and, secondarily, projects aiming at land development (paper 3)
Investments under vertical relations and agency conflicts
Full text linkWe examine the case of an investment project that, i) is characterized by uncertainty and
irreversibility, ii) is undertaken in a decentralized setting and iii) its completion is conditional
on the provision of an input by an outside supplier with market power.
Our findings suggest that, if compared to a case where the input is insourced, the vertical
relation increases the investment cost. Nevertheless, the effect on the timing and the value of
the investment is ambiguous since it depends on the information endowment of the involved
parties. We discuss three levels of information sharing among the links of the supply chain and
we identify the cost, the timing and the value of the option to invest for each one of them
How vertical relationships and external funding affect investment efficiency and timing?
No full textIn this paper we consider a potential investor who contemplates entering an uncertain new
market under two conditions: i) a prerequisite for the project to take place is the purchase
of a discrete input from an upstream firm with market power and ii) the completion of the
investment is conditional on the participation of an investment partner who is willing to bear
some of the investment cost receiving compensation in return.
Using the real option approach, we find that the involvement of any of the two alien agents
causes the postponement of the completion of the investment and we discuss how these timing
discrepancies are reflected on the value of the option to invest in the project. We next analyze
the synchronous effect of outsourcing and external funding both in a non-cooperative and in a
cooperative (Nash bargaining solution) game-theoretic setting and we show how the endogeneity
of the sunk investment cost a¤ects the timing and the value of the option to invest in projects
characterized by uncertainty and irreversibility
Investing in electricity production under a reliability options scheme
Full text linkReliability Options (ROs) are used to enhance the security of supply in electricity systems. When a power producer writes a RO, s/he agrees to set a cap on the price of electricity that s/he cashes. In return, the system operator, i.e. the party that is buying the option, pays to the option issuer a fixed premium. In this paper we analyze how ROs affect the timing and value of investments in the energy sector and we show under what conditions they can be used as investment stimuli. We prove that, contrarily to what is expected, ROs can potentially harm the security of supply by delaying the adoption of new capacity and by reducing the value of investing in it. To avoid such a result, a careful setting of the relevant parameters is needed
Investment in farming under uncertainty and decoupled support: a real options approach
No full textUnder the current version of the Common Agricultural Policy (CAP), payments to EU farmers are decoupled from the production of agricultural commodities. In fact, farmers qualify for CAP support as soon as their land is maintained in good agricultural and environmental condition.
In this paper, we study how decoupled payments influence the decision to invest in farming. We show that decoupling is implicitly providing a costless hedge against volatile farming profits. Consequently, a higher decoupled payment leads the potential farmer to hasten its investment but also results in a farm with lower productive capacity
Investment in farming under uncertainty and decoupled support: a real options approach
Full text linkWe develop a real options model to assess the impact of decoupled payments on agricultural investments. The context that we are addressing is the one set by the Common Agricultural Policy where farmers are eligible for decoupled payments as long as their land is properly maintained. We show that decoupled payments are non-neutral with respect to choices concerning timing and capacity. We find that they (i) induce earlier investment with lower productive capacity; (ii) increase the value of the investment option associated with land and (iii) reduce the volatility of farm income. A numerical exercise complements our theoretical analysis
ANONYMOUS PUBLICATION SUBMISSION AND REVIEW PLATFORM USING ML
No full textWe created an anonymous publication submission and review platform that uses an effective
machine learning model to protect the authors' privacy and the integrity of the review process.
The platform is designed with Django and the Django REST Framework (DRF) for backend
operations, React for the frontend interface, and PyTorch for training machine learning model.
Our technology automates the process of connecting papers with the most appropriate reviewers
based on their expertise, reducing human interference and any bias. Furthermore, it makes it
easier to provide feedback to assigned publications using an intuitive interface. We believe that
our website would significantly contribute to the academic publication review process
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