Valuation Data Research Articles

A Hedonic Approach to Coastal Resilience in Post-Hurricane Maria’s Puerto Rico

Hurricane Maria devastated Puerto Rico in 2017, resulting in reduced beach width and dune flattening in certain coastal areas. Economic development activity observed in coastal regions of Puerto Rico after Hurricane Maria has partly focused on commercial and housing construction projects. The following study seeks to estimate the implicit value attributed by coastal homeowners to natural infrastructure attributes that may serve not only for recreation, but also as protection from future extreme weather events. We estimated a hedonic valuation model to assess the implicit value attributed by coastal homeowners to key natural attributes, emphasizing beach width and property elevation. Property owners sufficiently close to the coastline (1,000 m or less) implicitly assigned a positive value to beach width at their closest coastal location. An unexpected result was that elevation, when interacted with beach and human-made coastal types, was negatively associated with property prices, an indication of the importance of closeness to sea level. Given the impact of extreme weather events in coastal regions, hedonic valuation data on natural coastal attributes such as beach width can provide valuable information not currently considered in coastline development permitting.

A Study on Comprehensive Analysis of Fintech Unicorn Companies In India

This analysis of Indian fintech unicorn companies explores their significant impact on India’s financial landscape and global fintech. Motivated by their rapid growth and role in promoting financial inclusion, the study also examines the regulatory environment and the substantial investor interest these companies attract. Key focus areas include the competitive landscape, global implications, and gaps in existing knowledge. The research methodology incorporates literature reviews and industry report analysis, assessing historical valuation data, financial statements, and key metrics of selected companies. Findings reveal a vibrant fintech ecosystem in India, with startups specializing in digital payments, lending, and insurance. Valuation trends among these unicorns vary, highlighting the industry’s dynamism. A moderate positive correlation between investment and revenue underscores the role of funding in driving growth. The study provides valuable insights for policymakers, investors, and industry leaders, aiding strategic decisions and enhancing understanding of Indian fintech’s global influence.

How Spatial Differences in Climate Affect Agricultural Land Values in New Zealand

Abstract This paper implements the “spatial first differences” (SFD) method to a Ricardian approach to analyze spatial differences in climate and evaluate their impact on farmland values in New Zealand. We use property valuation data from 1993 to 2018 across different agricultural land uses. Ricardian analyses harness cross-sectional variation in climate and farmland values to estimate the effect of climate on agriculture. However, Ricardian studies are vulnerable to omitted variables varying slowly or not varying over time. The idea of the SFD approach is to apply spatial analogous of the “first-differences” estimator for longitudinal analyses to control for omitted variables that vary differently than climate variables among neighboring units. The results suggest that a warmer or drier climate is associated with higher farmland values in New Zealand. These findings may be mediated by productivity differences, costly physical improvements, and climate amenity values. Besides contributing novel insights by applying the Ricardian approach to New Zealand data and overcoming challenges of unobserved heterogeneity with the SFD method, we conclude that, for a better understanding of the welfare implications of climate change, it is crucial to differentiate between the effects of costly improvements and amenity values, apart from the pure climate productivity effect.

The impact of demographic change on value set validity and obsolescence.

To investigate the contribution of demographic trends in countries' age and gender composition to value set validity and obsolescence. Time-trade off (TTO) valuation data from 3 EQ-5D-3L value sets of 20 years or older from the United Kingdom, Japan, and the United States were re-analyzed using Bayesian heteroskedastic Tobit models with sex and age group-specific scale parameters. Original value sets were obtained by weighting the original preference structures with the countries' original demographic composition at the time of the data collection. Updated value sets were created using the original preference structure weighted using the countries' most recent demographic composition. The differences between the original and updated value sets were monitored and compared based on 95% credible intervals. The gender and age composition of the investigated countries changed in all 3 countries over time. The modelled health state preferences also depended on the respondents' gender and age. However, the overall impact of this demographic change on the investigated value sets was negligeable in all 3 countries and this finding was robust to accounting for the impact of ethnicity trends in the United States. Value sets may become redundant and obsolete for various reasons, but demographic change was not identified as a contributing factor.

Venture debt financing and firm development: evidence from Indian entrepreneurial landscape

ABSTRACT This paper explores the impact of Venture Debt (VD) funding on Indian firms’ development outcomes. We define success of funding round (FR) of a firm as (a) the prevalence of a subsequent FR and (b) based on percentage increase in self-reported valuation of consecutive FRs. Analysis of 13,809 FRs in Indian firms from January 1998 to September 2022 uncovered a positive and significant association between success and VD-backing of the firm. When success is defined as prevalence of a subsequent FR, we find VD investors to have marginally higher selection effects vis-à-vis their equity counterparts. On the other hand, when success is based on self-reported valuation data, selection effects are elusive. Further, counterfactual analysis for both definitions of success indicates that the likelihood of VD-funding rounds becoming successful are not any different had they received VC funding instead of VD funding. This goes to show the absence of treatment effects of VD investors. Taken together, our findings indicate that while Indian VD investors may select better portfolio companies, they fail to have any treatment effects on firms’ development outcomes. Lastly, parametric hazard model outcomes uncover reduction in investors’ time to exit in the event of the firm being VD-backed.

식품기업의 ESG 경영이 재무성과와 기업가치에 미치는 영향

ESG (Environment, Social and Governance) activities of food manufacturing companies are likely to affect consumers’ consumption behaviors and companies’ management performance; however, research on the effects of ESG activities on management performance for food manufacturing industry is still in its early stage due to data access problems in Korea. In this study, we constructed panel data for the top 30 food manufacturing companies based on revenue over a period of seven years (2016∼2022) to examine the effects of ESG evaluation ratings on their management performance such as financial performance and corporate value. For the analysis, we employed fixed-effects specification, and used ESG rating data evaluated and released by the Korea Corporate Governance Service, as well as financial information and corporate valuation data published by the Financial Supervisory Service and the Korea Exchange. We find that the ESG rating of food manufacturing companies did not have a statistically significant effect on return on sales (ROS) and return on equity (ROE). However, results indicate that the rating had a statistically significant positive effect on price-to-book ratio (PBR) and Tobin’s Q. This suggests that the ESG activities of food manufacturing companies can potentially be an effective management strategy in enhancing the value of the companies in both the shrot and long-term dimensions.

What impact has the Centre of Research Excellence in Digestive Health made in the field of gastrointestinal health in Australia and internationally? Study protocol for impact evaluation using the FAIT framework

IntroductionThe need for public research funding to be more accountable and demonstrate impact beyond typical academic outputs is increasing. This is particularly challenging and the science behind this form of...

Using Life Satisfaction and Happiness Data for Environmental Valuation: An Experienced Preference Approach

Using Life Satisfaction and Happiness Data for Environmental Valuation: An Experienced Preference Approach

ECONOMIC COST OF MITIGATING HOUSEHOLD AIR POLLUTION — A STUDY OF HOUSEHOLDS IN RURAL WEST BENGAL, INDIA

By exploiting unique contingent valuation data from rural Indian households, we estimate the individuals’ willingness to pay to reduce risk from household air pollution, using the double-bounded dichotomous choice model. The estimated mean annual willingness to pay for such risk reduction is obtained as INR 886.59 accounting for approximately 1% of the annual household income. Although conducted in a different time and sample, the ratio of our estimated WTP to average household expenditure lies in a comparable range with extant literature. Furthermore, the estimated WTP lies in a moderately comparable range to the market price of devices that reduces HAP exposure. The sensitivity analysis of the estimated willingness to pay with respect to relevant behavioral and health factors further provides scope for policy prescriptions.

Influence of Self-Reported Health Impairments on German EQ-5D-5L Values

ObjectivesThe German EQ-5D-5L value set is based on the average preferences of the general population. Nevertheless, in Germany, there is an ongoing debate about the appropriateness of using general population preferences and whether patient preferences should be used instead. Thus, this research aimed to determine the robustness of the German EQ-5D-5L valuation data for the general population compared with those with health impairments. MethodsSubgroups were built on the self-reported quality of life, measured with the EQ-5D-5L. To identify which groups significantly influenced the value set, different regression models, including dummy variables for the subgroups, were tested while controlling for preference heterogeneity. Backward selection based on the Akaike information criterion led to significant subgroup dummies, which were analyzed in more detail. For each significant subgroup, the value set model was estimated separately. The models were then compared. Sociodemographics of the subgroups were considered. ResultsThree significant dummies were identified: state 11111, severity levels 5 to 7, and self-reported problems with pain/discomfort. The value sets for the 6 subgroups were compared with the national German value set, showing only marginal deviations. The mean absolute deviation ranged from 0.004 to 0.013. No different densities were identified for the decrements of the different value sets. ConclusionsPeople with self-reported health impairments do not have different EQ-5D-5L health state preferences compared with the German general population. Further research is needed to determine whether the presence of a chronic health condition has a larger influence on health state valuation than the general population.

Ownership Structure and Shareholders: Perspectives on Conflict between State Participation in the Value of Companies on the Brazilian Stock Exchange - B3

Purpose: The main objectives are the influence on the various interested shareholders, the role of institutionalized the State in the shareholding structure of companies, and their influence on share prices after the events of media about disclose of these in this study. Design/methodology/approach: In the first moment, the investigation had a quantitative approach of a relational nature based on the events investigated between 2010 and 2020 and were published in the newspapers. In addition to the share prices, the variables investigated corresponded to the various forms of state participation. Based on stock valuation data, statistical methods were applied to a secondary database containing measurable information provided by organizations operating in the Brazilian stock market and documentary evidence provided by companies. Findings: The presence of the State as a shareholder has significant relevance in the Brazilian capital market and the application of public resources. It is the responsibility of society and academia to monitor such applications and ascertain whether it generates value for the business and the country. Within the study's boundaries on the management of public resources and investments, Corporate Governance has been arising the debate and questioning about the government's performance as a shareholder in the firm. Originality/value: When investigating the perspective of the State as a shareholder has significant relevance in the Brazilian capital market and the application of public resources. Society and academia's responsibility is to monitor such applications and ascertain whether it generates value for the business and the country.

PENGARUH PROFITABILITAS DAN UKURAN PERUSAHAAN TERHADAP AUDIT DELAY PADA PERUSAHAAN SEKTOR PROPERTY DAN REAL ESTATE YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2019-2021

This study aims to analyze the effect of profitability and company size on audit delay in property and real estate sector companies during the 2019-2021 period. Property and real estate companies listed on the IDX for the 2019-2021 period are the samples in this study. The method used in sampling using purposive sampling for samples that have been determined according to certain qualifications. Data for valuation and measurement variables are obtained from annual reports, such as published independent auditor reports, total assets, and net income which are included in the IDX data base. The analysis technique used is multiple linear regression analysis. The results of this study indicate that profitability and company size have a positive and significant influence on audit delay in property and real estate sector companies listed on the Indonesia Stock Exchange for the 2019-2021 period.

The cost of domestic water provision in Morogoro Municipality, Tanzania

Accessible water is a basic human right but due to its fugitiveness and paucity, water is an economic good, rather than a public one. A reduced supply of water causes high financial and social costs. This study examined using the cost-based approach, the value of Mindu Dam by providing public water to Morogoro Municipality in Tanzania. It focused on the cost of water treatment and of constructing boreholes to ensure an efficient water supply. Data were collected from Morogoro Water Supply and Sanitation Authority (MORUWASA), the Wami/Ruvu Basin Water Board (WRBWB) Office, and three wards of the municipality. Household data were analyzed by descriptive techniques that involved computation of proportions, and valuation data by cost-based approaches. Due to pollution and degradation of the Mindu Dam, the municipality loses about 1,168,756,011 TZS (24,145.22 USD) per year for water treatment while the dam capacity decreases progressively. By using the boreholes alternative, the value of Mindu Dam by providing water is 64,074,304,515.07 TZS (27,626,570 USD) in the investment year and 39,828,547,584 TZS (17,172,659 USD) per year then after. This value was unrevealed and not considered in decision-making, leading to prolonged degradation. It is advised from this study for regulatory authorities to conduct valuation studies and use them to refine appropriate decisions to promote conservation and avoid unnecessary financial losses. The final value should also take into consideration the intrinsic value that water has, not only the direct one that is easily traceable.

Scenic routing navigation using property valuation

Extensive prior work has provided methods for the optimization of routing based on weights assigned to travel duration, and/or travel cost, and/or the distance traveled. Routing can be in various modalities, such as by car, on foot, by bicycle, via public transit, or by boat. A typical method of routing involves building a graph comprised of street segments, assigning a normalized weighted value to each segment, and then applying the weighted-shorted path algorithm to the graph in order to find the best route. Some users desire that the routing suggestion include consideration pertaining to the scenic-architectural quality of the path. For example, a user may seek a leisure walk via what they might deem as visually attractive architecture. Here, we are proposing a method to quantify such user preferences and scenic quality and to augment the standard routing methods by giving weight to the scenic quality. That is, instead of suggesting merely the time and cost-optimal route, we will find the best route that is tailored towards the user’s scenic quality preferences as an additional criterion to the time and cost. The proposed method uniquely weighs the scenic interest or residential street segments based on the property valuation data.

Fair Value Measurement in Inactive Crypto Asset Markets

This article proposes a new dynamic method, the Principal Path Method (PPM), for pricing crypto asset against a primary or functional (fiat) currency in situations where these assets do not trade directly against the functional currency or trade at volumes that prevent resulting pricing information to qualify as Level 1 (ASC 820) for financial reporting. We base our method on the guidance provided in ASC 820, IFRS 13, and IAS 21. Our method is designed to extract prices from “compliant” markets that result in reliable inputs to the valuation process. We believe that our methodology improves the current techniques used to value thinly traded crypto assets such as using the last observable transaction price, creating a weighted-average price across multiple markets, or using data on comparable tokens, if available. Furthermore, we present empirical evidence that suggests pricing information generated by our method for non-exchangeable, thinly traded, or illiquid crypto assets better reflects the fundamental qualitative characteristics of useful information, relevance and faithful representation, and results in more reliable inputs used in the valuation process. Unlike methods currently used in practice, our method ensures the integrity of the valuation data employed by selecting prices from compliant markets.

Efficient Designs for Valuation Studies That Use Time Tradeoff (TTO) Tasks to Map Latent Utilities from Discrete Choice Experiments to the Interval Scale: Selection of Health States for TTO Tasks.

In eliciting utilities to value multiattribute utility instruments, discrete choice experiments (DCEs) administered online are less costly than interviewer-facilitated time tradeoff (TTO) tasks. DCEs capture utilities on a latent scale and are often coupled with a small number of TTO tasks to anchor utilities to the interval scale. Given the costly nature of TTO data, design strategies that maximize value set precision per TTO response are critical. Under simplifying assumptions, we expressed the mean square prediction error (MSE) of the final value set as a function of the number of TTO-valued health states and the variance of the states' latent utilities. We hypothesized that even when these assumptions do not hold, the MSE 1) decreases as increases while holding fixed and 2) decreases as increases while holding fixed. We used simulation to examine whether there was empirical support for our hypotheses a) assuming an underlying linear relationship between TTO and DCE utilities and b) using published results from the Dutch, US, and Indonesian EQ-5D-5L valuation studies. Simulation set (a) supported the hypotheses, as did simulations parameterized using valuation data from Indonesia, which showed a linear relationship between TTO and DCE utilities. The US and Dutch valuation data showed nonlinear relationships between TTO and DCE utilities and did not support the hypotheses. Specifically, for fixed , smaller values of reduced rather than increased the MSE. Given that, in practice, the underlying relationship between TTO and DCE utilities may be nonlinear, health states for TTO valuation should be placed evenly across the latent utility scale to avoid systematic bias in some regions of the scale. Valuation studies may feature a large number of respondents completing discrete choice tasks online, with a smaller number of respondents completing time tradeoff (TTO) tasks to anchor the discrete choice utilities to an interval scale.We show that having each TTO respondent complete multiple tasks rather than a single task improves value set precision.Keeping the total number of TTO respondents and the number of tasks per respondent fixed, having 20 health states directly valued through TTO leads to better predictive precision than valuing 10 health states directly.If DCE latent utilities and TTO utilities follow a perfect linear relationship, choosing the TTO states to be valued by weighting on the 2 ends of the latent utility scale leads to better predictive precision than choosing states evenly across the latent utility scale.Conversely, if DCE latent utilities and TTO utilities do not follow a linear relationship, choosing the states to be valued using TTO evenly across the latent utility scale leads to better predictive precision than weighted selection does.In the context of valuation of the EQ-5D-Y-3L, we recommend valuing 20 or more health states using TTO and placing them evenly across the latent utility scale.

Use of accounting concepts to study research: return on investment in XSEDE, a US cyberinfrastructure service

This paper uses accounting concepts—particularly the concept of Return on Investment (ROI)—to reveal the quantitative value of scientific research pertaining to a major US cyberinfrastructure project (XSEDE—the eXtreme Science and Engineering Discovery Environment). XSEDE provides operational and support services for advanced information technology systems, cloud systems, and supercomputers supporting non-classified US research, with an average budget for XSEDE of US$20M+ per year over the period studied (2014–2021). To assess the financial effectiveness of these services, we calculated a proxy for ROI, and converted quantitative measures of XSEDE service delivery into financial values using costs for service from the US marketplace. We calculated two estimates of ROI: a Conservative Estimate, functioning as a lower bound and using publicly available data for a lower valuation of XSEDE services; and a Best Available Estimate, functioning as a more accurate estimate, but using some unpublished valuation data. Using the largest dataset assembled for analysis of ROI for a cyberinfrastructure project, we found a Conservative Estimate of ROI of 1.87, and a Best Available Estimate of ROI of 3.24. Through accounting methods, we show that XSEDE services offer excellent value to the US government, that the services offered uniquely by XSEDE (that is, not otherwise available for purchase) were the most valuable to the facilitation of US research activities, and that accounting-based concepts hold great value for understanding the mechanisms of scientific research generally.

Neglected Peers in Merger Valuations

Abstract Using novel merger valuation data, we show that firms selected by investment banks as “comparable peers” are more than twice as likely to later become takeover targets themselves compared to matched control firms. Peer firms not subsequently acquired attract more institutional ownership and analyst coverage, deliver strong operating performance, reduce investments, and increase payouts. Investors are inattentive, though, to peer identification at the time of merger filings’ public disclosure. A portfolio that longs peers and shorts controls earns up to 15.6$\%$ alpha annually, which mainly comes from the long leg and is difficult to explain by short-sale constraints. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Censoring Time Trade-off Values at 0 Versus at −1: How Does the Assumption for Worse-Than-Dead Time Trade-off Values Affect the Modeling of EQ-5D-5L Valuation Data?

ObjectivesA recent study found that negative utility values elicited using composite time trade-off (TTO) were barely associated with the severity of EQ-5D-5L health states, suggesting poor discriminative ability. Assuming negative values provide limited information, this study aimed to explore the usefulness of censoring negative TTO values at 0 in modeling EQ-5D-5L valuation data. MethodsWe analyzed EQ-5D-5L valuation data from China, The Netherlands, Canada, Singapore, and Thailand. For each data set, we estimated value sets using 2 Tobit models, one left-censored at −1 (current practice) and one left-censored at 0 (our proposed method), and compared the model performances. We hypothesized that censoring at 0 and censoring at −1 would produce similar values, though on slightly different scales. ResultsWhen censoring at 0, logical inconsistencies and statistical significance were improved but the value range was compressed. In the cross-attribute level effects model, the 3-level parameters were similar between the models censored at 0 and −1, but the rank order of some dimension parameters was altered. Health state values predicted by the 2 censoring models approximated a perfect agreement after rescaling. ConclusionsCensoring TTO values at 0 improved model estimation and fit but produced higher utility values than models censoring at −1. Investigators of future EQ-5D value set studies using the composite TTO method are advised to examine the validity of negative TTO values before choosing modeling strategies.

Interaction Effects in Health State Valuation Studies: An Optimal Scaling Approach

ObjectivesThis study aimed to introduce a parsimonious modeling approach that enables the estimation of interaction effects in health state valuation studies. MethodsInstead of supplementing a main-effects model with interactions between each and every level, a more parsimonious optimal scaling approach is proposed. This approach is based on the mapping of health state levels onto domain-specific continuous scales. The attractiveness of health states is then determined by the importance-weighted optimal scales (ie, main effects) and the interactions between these domain-specific scales (ie, interaction effects). The number of interaction terms only depends on the number of health domains. Therefore, interactions between dimensions can be included with only a few additional parameters. The proposed models with and without interactions are fitted on 3 valuation data sets from 2 different countries, that is, a Dutch latent-scale discrete choice experiment (DCE) data set with 3699 respondents, an Australian time trade-off data set with 400 respondents, and a Dutch DCE with duration data set with 788 respondents. ResultsImportant interactions between health domains were found in all 3 applications. The results confirm that the accumulation of health problems within health states has a decreasing marginal effect on health state values. A similar effect is obtained when so-called N3 or N5 terms are included in the model specification, but the inclusion of 2-way interactions provides superior model fits. ConclusionsThe proposed interaction model is parsimonious, produces estimates that are straightforward to interpret, and accommodates the estimation of interaction effects in health state valuation studies with realistic sample size requirements. Not accounting for interactions is shown to result in biased value sets, particularly in stand-alone DCE with duration studies.