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At odds with a vast body of economic evidence reporting exceptionally high rates of return to investments in agricultural research and development (R&D), growth in public R&D spending for food and agriculture has slowed in numerous, especially rich, countries worldwide. The observed R&D spending behavior is consistent with a determination that the reported rates of return are perceived as implausible by policy makers. We examine this notion by scrutinizing 2,242 investment evaluations reported in 372 separate studies from 1958 to 2011. We find that the internal rate of return (IRR) is the predominant summary measure of investment performance used in the literature despite methodological criticisms dating back more than a half century. The reported IRRs imply rates of return that are implausibly high. We investigate the reasons for these implausibly high estimates by analytically comparing the IRR to the modified internal rate of return (MIRR). The MIRR addresses several methodological concerns with using the IRR, has the intuitive interpretation as the annual compounding interest rate paid by an investment, and is directly related to the benefit–cost ratio. To obtain more credible rate of return estimates, we then develop a novel method for recalibrating previously reported IRR estimates using the MIRR when there is limited information on an investment's stream of benefits and costs. Our recalibrated estimates of the rate of return are more modest (median of 9.8% versus 39% per year); however, they are still substantial enough to question the current scaling back of public agricultural R&D spending in many countries.

In Taiwan, large advertising billboards on commercial buildings consume significant energy, exacerbating environmental challenges and straining sustainability efforts. This study explores the potential of rooftop solar photovoltaic systems (SPVS) to power these billboards, offering a dual solution for energy reduction and financial viability. Using a fuzzy nonlinear multi-objective programming approach, the research demonstrates that SPVS investments become profitable by the ninth year (0.7232% return), rising to 5.4463% by the twentieth year, while a 26-day reduction in construction time cuts carbon emissions by 223.11 kg. The innovative Revenue–Time–Cost–Quality–Carbon Emissions (RTCQCE) framework balances economic gains with environmental benefits, leveraging advertising revenue to fund SPVS. This model bridges a research gap by integrating financial and ecological factors, providing a practical tool for sustainable urban development in Taiwan.

The aim of this study was to evaluate Pearson's linear correlations between productive and economic indicators as well as to estimate economic equations as tools in dairy farming. We used the database of the Research Group, registered with CNPq under the title ‘Animal and Forage Production in Piaui’, which consisted of two experiments with feedlot lactating cows. Economic and productive indicators were employed. Correlations were determined by Pearson’s linear correlation analysis, using the ‘t’ test. Equations were estimated via regression, using Saeg software (Statistical and Genetic Analysis System), considering α = 0.05. Based on concepts related to Pearson's linear correlation and dairy farming management, we were able to find correlations that allowed us to estimate simple, yet very informative equations, which facilitated the interpretation of the management of a dairy farm. Among the studied variables, net present value, internal rate of return, the cost per liter of milk produced and net margin were those which most contributed to the estimation of equations.

We present a new methodology to statistically determine the net present value (NPV) and internal rate of return (IRR) as financial estimators of shale gas investments. Our method allows us to forecast, in a fully probabilistic setting, financial performance risk and to understand the importance of the different factors that impact investment. The methodology developed in this study combines, through Monte Carlo simulation, the computational modeling of gas production from shale gas wells with a stochastic simulation of gas price as a geometric Brownian motion (GMB). To illustrate the methodology's validity, we apply it to an analysis of investments in shale gas wells. Our results show that gas price volatility is a key variable in the performance of an investment of this type, in such a way that at high volatilities, the potential return on an investment in shale gas increases significantly, but so do the risks of economic loss. This finding is consistent with the history of shale gas operations in which huge investment successes coexist with unexpected investment failures. [Display omitted]

Grid capacity constraints present a prominent challenge in the construction of ultra-fast charging (UFC) stations. Active load management (ALM) and battery energy storage systems (BESSs) are currently two primary countermeasures to address this issue. ALM allows UFC stations to install larger-capacity transformers by utilizing valley capacity margins to meet the peak charging demand during grid valley periods, while BESSs rely more on energy storage batteries to solve the gap between the transformer capacity and charging demand This paper proposes a four-quadrant classification method and defines four types of schemes for UFC stations to address grid capacity constraints: (1) ALM with a minimal BESS (ALM-Smin), (2) ALM with a maximal BESS (ALM-Smax), (3) passive load management (PLM) with a minimal BESS (PLM-Smin), and (4) PLM with a maximal BESS (PLM-Smax). A generalized comparison framework is established as follows: First, daily charging load profiles are simulated based on preset vehicle demand and predefined charger specifications. Next, transformer capacity, BESS capacity, and daily operational profiles are calculated for each scheme. Finally, a comprehensive economic evaluation is performed using the levelized cost of electricity (LCOE) and internal rate of return (IRR). A case study of a typical public UFC station in Tianjin, China, validates the effectiveness of the proposed schemes and comparison framework. A sensitivity analysis explored how grid interconnection costs and BESS costs influence decision boundaries between schemes. The study concludes by highlighting its contributions, limitations, and future research directions.

This paper addresses the internal rate of return (IRR) assessment of subsidised production. The difference between the result of IRR calculation and the reality can be largely attributed to uncertainty about the future market price and demand. Thus, in the IRR model the intervals of possible input values instead of uncertain point values should be taken into account. Within the intervals of the input values there is no relevant reason to prefer one value over another. The fuzzy approach is applied to decide whether or not the system of subsidies is adequate in terms of IRR. It leans on the “fuzzy numbers”, which are generalisations of real numbers within the meaning of not referring to a single value but rather to intervals of possible values. The results are then compared with the conventional statistical approach of IRR single-value evaluation. The analogy between the conventional statistical and fuzzy approach is shown on the theoretical level. The practical contribution of this paper lies in the IRR assessment of a subsidised electric car production project. Two scenarios of possible project development are considered. In the study, we derive the algorithm to calculate the average probability of the appearance of the subjectively expected IRR, which is compared with the minimum required profitability. We show that the IRR evaluation of the subsidised production should not be underestimated. The need to verify the adequacy of a subsidised project by a proper tool is given by the fact that many investors mistakenly believe that subsidies will ensure the required profitability. The use of statistical methods in a state of uncertainty can lead to misleading results. The fuzzy analysis offers the investors involving the subjective risk in their decision making more benefits and brings more information compared to statistical approach.

The real estate market is affected by great uncertainty due to the nexus of various factors: a) the specificity of the assets traded, which are illiquid, unique and very hetherogeneous from each other; b) the ‘structural disequilibrium’ of the market caused by the differences emerging in elasticity of supply with respect to demand; c) the non-competitiveness of the market, which often turns into a bilateral monopoly; d) the great variability of market prices. Since the subprime mortgage crisis that broke out at the end of 2006 in the United States, it has clearly emerged that, in a sector that represents about a third of world wealth, it is necessary, on the one hand, to implement proper and increasingly sophisticated valuation tools, to support the design of effective risk management strategies and, on the other hand, to improve the reliability of real estate data, in order to allow for a more robust verification of the hypotheses on the trend of the cash flows generated by the investment and a more accurate valuation of the investment risk and, consequently, of the project expected rate of return. The main objective of this work is to investigate the accuracy and robustness of the estimates of real estate investors of the expected returns on an urban development project in a medium-sized city representative of the North East of Italy. Using a simulation-based approach, the gap between the observed internal rate of return, estimated ex post on the basis of the actual trend of the parameters that influence investment returns, and the expected internal rate of return, calculated ex ante on the basis of the information available at the time of the investment decision. Firstly, we constructed the time series from 1995 to 2015 of the expected and observed internal rates of return of investments in the residential sector. We obtained the time series of the cash flows generated by the investment under investigation by implementing a simulation-based approach. Starting from the comparison between observed internal rate of return and expected internal rates of return, we identified ex post the risk implicitly assumed by the investor at the time of the decision to undertake the investment. Secondly, the effectiveness of the Capital Asset Pricing Model as a method for estimating the return on a property investment was verified, by comparing the project’s observed (ex post) internal rate of return with its ex ante rate of return, estimated through the Capital Asset Pricing Model. To carry out the above analyses, we constructed the time series of observed and expected internal rate of returns from 1995 to 2015 of investments in the residential sector. The time series of the internal rate of returns of real estate investments were obtained by implementing a simulation-based approach to determine the cash flows of real estate investments representative of the context under investigation and by adopting as model inputs the parameters usually adopted in ex-ante and ex-post real estate valuations. Starting from the comparison between observed and expected internal rate of returns, we identified ex-post the risk implicitly assumed by the developer at the time of the decision to undertake the investment. Finally, by investigating the determinants of the divergence between the investment’s observed and expected internal rate of return and cyclical variables, we identified the factors (i.e., the macroeconomic fundaments) which, in the period under investigation, affected investment risk and, consequently, investment return. Finally, by investigating the relationships that account for the difference between the observed and expected internal rate of return and the economic factors that can determine the current stage in economic cycles, we identified the determinants of invetment risk and returns. Il mercato immobiliare è affetto da grande incertezza dovuta a una concatenazione di diversi fattori: a) la specificità dei beni scambiati che sono illiquidi, unici e molto eterogenei tra loro; b) il “disequilibrio strutturale” del mercato causato dalla diversa elasticità del- l’offerta rispetto alla domanda; c) la non concorrenzialità del mercato che, assume spesso le caratteristiche del monopolio bilaterale; d) la grande variabilità dei prezzi di mercato. A partire dalla crisi dei mutui sub- prime scoppiata alla fine del 2006 negli Stati Uniti, è emerso chiaramente come, in un settore che rappresenta circa un terzo della ricchezza mondiale, sia necessario, da un lato, operare con strumenti valutativi adeguati e sempre più sofisticati, in grado di suppor- tare l’individuazione di strategie efficaci di gestione dei rischi e, dall’altro, migliorare l’affidabilità dei dati immobiliari, in modo da consentire una verifica più ro- busta delle ipotesi sull’andamento dei flussi di cassa generati e una stima più accurata del rischio e, conseguentemente, del tasso di rendimento atteso. Obiettivo principale del presente lavoro è di investigare l’accuratezza delle previsioni effettuate da un ipotetico operatore immobiliare sul rendimento di un investi- mento a sviluppo in una città di medie dimensioni rap- presentativa della provincia dell’Italia settentrionale. Attraverso un approccio basato sulla simulazione, è stato calcolato lo scarto fra il tasso interno di rendimento effettivo, stimato ex post in base all’andamento effettivo dei parametri influenti sul rendimento stesso, e il tasso interno di rendimento atteso, calcolato ex ante sulla base delle informazioni disponibili al mo- mento della decisione d’investimento. In primo luogo, è stata costruita la serie storica dal 1995 al 2015 dei tassi interni di rendimento attesi ed effettivi dell’investi- mento immobiliare residenziale a sviluppo. Le serie storiche sono state ottenute mediante la simulazione dei flussi di cassa di investimenti immobiliari rappresentativi della realtà indagata. A partire dal confronto fra tassi interni di rendimento effettivi e tassi interni di rendimento attesi è stato individuato, ex post, il rischio assunto implicitamente dall’investitore al momento della decisione di intraprendere l’investimento stesso. In secondo luogo, è stata verificata la bontà del Capital Asset Pricing Model come metodo di stima del rendi- mento di un investimento immobiliare a sviluppo, confrontando il tasso interno di rendimento effettivo e il tasso di rendimento ex ante stimato attraverso il Capi- tal Asset Pricing Model stesso. Infine, indagando sulle relazioni che intercorrono fra lo scarto fra tasso di rendimento interno effettivo e atteso e le variabili congiunturali, sono stati individuati i fattori che, nel periodo considerato, hanno maggiormente influito sul rischio al quale si è esposto l’investitore al momento di investire.

Public R&D stimulates domestic private and foreign private and public R&D, together enhancing technical change and thereby GDP. In this paper, we evaluate vector-error-correction model ( VECM) estimations and simulations of a companion paper in regard to internal rates of return (and related aspects) to additional public R&D of OECD countries and compare them to the macroeconomic literature. We show (i) internal rates of return to public R&D shocks, and (ii) the related payback periods, gain/GDP ratios, and sums of discounted (at 4%) gains. Fourteen of 17 countries show high internal rates of return, short payback periods, and high gains/GDP ratios from positive public R&D shocks if projects are stopped when gains get negative. Three countries show crowding-out effects and require (initial) reductions of public R&D before showing positive results.

Building energy consumption in Malaysia has increased by 31% over the past 10 years, primarily driven by the high demand for air conditioning in response to the country’s hot and humid climate. An effective way to address this problem is to increase building energy efficiency with the aid of thermal insulation. This paper presents a techno-economic analysis of roof assembly retrofits for commercial and residential buildings in Malaysia. Various roof configurations incorporating insulation materials such as radiant barriers, reflective insulation, mineral glass wool, and stone wool are investigated. The first section of this paper details the use of Sefaira building energy simulation software to evaluate the annual reduction in cooling energy consumption achieved by various roof configurations for commercial and residential buildings. Subsequently, an economic analysis is conducted by calculating the internal rate of return (IRR) and payback period for investment in each type of roof configuration. The findings show that roof assembly retrofits can reduce annual cooling energy consumption in commercial buildings by 8.65% to 16.25% and in residential buildings by 11.1% to 13.8%. Additionally, the total annual energy consumption decreases by 4.70% to 8.83% for commercial buildings, such as hypermarkets, and by 4.10% to 6.10% for residential buildings, depending on the insulation system applied. The economic analysis shows that the roof assembly insulated with a radiant barrier and thick enclosed air gap is the most economically beneficial option, offering the highest IRR of 20.60% and 6.79% for commercial and residential buildings, respectively, and the shortest payback periods of 4.6 years and 11.2 years, respectively. These results provide valuable insights to guide building owners and designers in choosing the most cost-effective type of roof insulation for new or existing projects.

Purpose Does it make economic sense to invest in winery startups with high land prices? This paper aims to apply a capital budgeting analysis for a startup project to investigate the role of land prices in the decision-making of a wine entrepreneur. Design/methodology/approach This paper uses a capital budgeting analysis to evaluate the value of a winery project using the six investment criteria: net present value (NPV), internal rate of return (IRR), modified IRR, profitability index, payback period (PB) and discounted PB. Findings This study finds that high land prices are economically justifiable (NPV is greater or equal to zero) when the weighted average capital cost is sufficiently low for investors who are able to diversify risks and with access to a cheap source of funds. Additionally, this study demonstrates that wine entrepreneurs need a long-term investment horizon because the recovery of the initial investment in winery startup projects takes many years. Research limitations/implications The startup winery projects are heavily influenced by wine pricing, production and cost assumptions. As a result, different assumptions made at other wine regions may result in slightly different outcomes for the acceptability of the wine startup projects. Practical implications High land prices are economically justified for investors and entrepreneurs with the ability to diversify risk and access to cheap financial resources. As such, land prices can be a critical obstacle for individual entrepreneurs who experience a lack of capital. Social implications In the famous wine regions of the world, high land prices may result in more wineries being owned by the capital rich wine conglomerates. Originality/value This paper provides estimations of land prices based on financial methods to discuss the justification of observed prices and the implications regarding the ability of investors and entrepreneurs to access capital.