Capital Estimates Research Articles

Children’s Sleep and Human Capital Production

Abstract This paper uses exogenous variation in sleep induced by sunset time to present the first human capital estimates of (i) the effects of child sleep from the developing world and (ii) the long-run effects of child sleep in any context. Later sunset reduces children’s sleep: when the sun sets later, children go to bed later but fail to compensate by waking up later. Sleep-deprived children study less and increase nap time and indoor leisure activities. Short-run sleep loss decreases children’s test scores. Chronic sleep deficits translate into fewer years of education and lower primary and middle school completion rates among school-age children.

ESTIMATES OF CONSTRUCTION INFRASTRUCTURE STOCK FOR CAPE VERDE: 1980–2019

Building and other construction assets constitute a significant part of a country’s physical and economic infrastructure. According to several writers, the knowledge of reliable data of building and other construction assets of a specific country or region is a crucial element for the long-term management of these assets. Built capital stock statistics at the national or international levels have been available for most countries of the world, both developed and less developed ones, for some time, but construction infrastructure stock statistics at the disaggregated level are very scarce, even for most developed countries. Furthermore, the methodologies to produce the estimates of built capital stock, at the international level, do not consider countries’ specificities. This paper discusses the methodologic issues for producing construction infrastructure stock statistics for Cape Verde, and makes estimates for the period 1980–2019. The paper outlines the Perpetual Inventory Method (PIM) used to produce capital estimation, data employed, and the assumptions made to estimate missing data. The paper analyses the level of the construction infrastructure stock estimates for Cape Verde, as well as their impact on the development pattern of the country’s construction industry, and suggests how further studies can enhance our comprehension of the relationship between construction investment and economic growth and development.

Measuring Intangible Capital with Market Prices

Accounting standards prohibit internally created knowledge and organizational capital from being disclosed on firm balance sheets. As a result, balance sheets exhibit downward biases that have become exacerbated by increasing levels of intangible investments. To offset these biases, researchers must estimate the value of these off-balance sheet intangibles by capitalizing prior flows of research and development (R&D) and selling, general, and administrative (SG&A). In doing so, a set of capitalization parameters must be assumed (i.e., the R&D depreciation rate and the fraction of SG&A that represents a long-lived asset). We estimate these parameters using market prices from firm exits and use them to capitalize intangibles for a comprehensive panel of firms from 1978 to 2017. We then use a series of validation tests to examine the performance of our intangible capital stocks versus those developed from commonly used parameters. On average, our estimates of intangible capital are 15% smaller than estimates from status quo parameters while exhibiting larger variation across industry. Intangible capital stocks derived from exit price parameters outperform existing measures when explaining market enterprise values and identifying human capital risk. Adjusting book values with exit-based intangible capital stocks markedly attenuates well-documented biases in market-to-book and return on equity ratios while increasing the precision of the high-minus-low asset pricing factor. We conclude that our capitalization parameters create intangible stocks that perform equal to or better than status quo measures in various applications. This paper was accepted by Victoria Ivashina, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.02058 .

Towards an Estimate of Aboriginal and Torres Strait Islander Human Capital and How It Is Changing Over Time

Towards an Estimate of Aboriginal and Torres Strait Islander Human Capital and How It Is Changing Over Time

Error propagation and attribution in simulation-based capital models

AbstractCalculation of loss scenarios is a fundamental requirement of simulation-based capital models and these are commonly approximated. Within a life insurance setting, a loss scenario may involve an asset-liability optimization. When cashflows and asset values are dependent on only a small number of risk factor components, low-dimensional approximations may be used as inputs into the optimization and resulting in loss approximation. By considering these loss approximations as perturbations of linear optimization problems, approximation errors in loss scenarios can be bounded to first order and attributed to specific proxies. This attribution creates a mechanism for approximation improvements and for the eventual elimination of approximation errors in capital estimates through targeted exact computation. The results are demonstrated through a stylized worked example and corresponding numerical study. Advances in error analysis of proxy models enhance confidence in capital estimates. Beyond error analysis, the presented methods can be applied to general sensitivity analysis and the calculation of risk.

Supply Chain Simulation of Manufacturing Shirts Using System Dynamics for Sustainability

In supply chain management (SCM), goods and services flow from the raw materials stage to the end user with complexities and uncertainty at each stage. Computer modeling and simulation is a particularly useful method to examine supply chain operational issues because it can solve operational complexities that are challenging and time consuming to analyze. Manufacturing companies fear losing valuable time and assets during the manufacturing process; the inaccurate estimation of raw materials, human capital, or physical infrastructure not only leads to monetary loss for the manufacturing unit, but also has a detrimental effect on the environment. The purpose of this paper is to demonstrate that system dynamics modeling (SDM) in sustainable supply chain management (SSCM) can be applied to apparel manufacturing to optimize materials, labor, and equipment usage. Utilizing system dynamics (SD), the manufacturing unit can improve sustainability by reducing materials, labor, and equipment usage, which in turn reduces energy use. In our literature review, we did not identify any study addressing supply chain simulation of the manufacturing of shirts using SDM. We chose shirt manufacturing to demonstrate the model because of its relatively simple manufacturing process. In our study, we conclude that SDM simulation is an efficient way to optimize materials, labor, and equipment in apparel manufacturing. This leads to a more sustainable manufacturing process, as the model simulates different manufacturing supply chain scenarios in a risk-free environment, thereby minimizing waste and resources. Further, the outputs from the STELLA® model can be used as inputs into a subsequent life cycle assessment (LCA) model to determine the quantitative environmental impacts.

The capitalization of CAP subsidies into land prices in the EU

The objective of this paper is to estimate the capitalization of CAP subsidies into both rental prices and land values in the EU. We use FADN data at regional level for the period 1989–2016 and apply a dynamic panel approach (GMM estimator) to estimate the capitalization effect of coupled direct payments (CDPs), decoupled direct payments (DDPs) and rural development measures at EU level. The estimated results suggest that the short-run (long-run) capitalization rate of DDPs into land rents vary between 9.1% and 46.2% (11% and 55%) and DDPs implementation details matter. Compared to the flat-rate models, the heterogeneous DDPs models appear to have capitalization rates lower by between 34% and 37% in the short-run and between 41% and 45% in the long-run. CDPs are associated with capitalization rates of around 6% in the short-run and 7% in the long-run. No clear capitalization effect could be found for rural development measures. In contrast to rental prices, estimates for land values suggest that only DDPs may cause a capitalization rate between 28.8% and 32.1% in the short-run and between 154% and 164% in the long-run. However, estimates for land values are not robust and consistent across estimated models. Using more robust capitalization estimates for rental prices, the results indicate that only 10–12% of the overall EU CAP payments were leaked to non-farming landowners in 2016. However, there is a sizable variation in the non-farming landowners' gains across Member States, ranging from 2% to 37%.

HUMAN CAPITAL ASSESSMENT METHODOLOGY

The main purpose of the paper is to analyse the existing methods and procedures of estimation of human capital as a dominant factor in improving profitability and competitiveness of the enterprise. The main tasks of the paper are to study and analyse the concept of human capital and its characteristics, to systematise approaches and methods of estimation of human capital within the framework of the company and the national economy. Methodology. This study analyses the theoretical basis of the estimation of human capital at different levels. The method used is literature review. Findings. The article raises the problem of using human capital as one of the indicators of efficient development of the economy. The analysis of the methodology of estimation of human capital is carried out. The article considers current methods of estimation of human capital at different levels: micro-, meso-, macro-, as well as their comparative analysis. The characteristics of the basic approaches to the estimation of human capital are considered, the analysis of the problems of indirect methods of estimation of human capital, objectivity and sufficiency of data for the construction of estimates is carried out. External factors such as socio-psychological resources, environmental influences, human lifestyles, such as dietary intake, need to be taken into account in order to estimate human capital accurately. Each approach has its own strengths and weaknesses. The weaknesses are more related to the difficulties in quantifying some of the components of human capital and the difficulties in collecting, processing and statistically analysing information at all levels of the study. Each approach has its own strengths and weaknesses. The weaknesses are more related to the difficulties of quantifying some components of human capital, and the difficulties of collecting, processing and statistically analysing information at all levels of the study. The authors also found that the investment approach is the most popular and provides the most adequate estimates. Practical implications. The results of this study provide a methodological basis for improving the methodology of estimating the value of human capital. The analysed approaches can be used at different levels of the national economy (macro-, meso- and micro-) by different organisational structures for further management decisions.

A re-examination of the foundations of the cost of capital for regulatory purposes

In regulatory proceedings, few issues are more hotly debated than the cost of capital. This article seeks to formalise the theoretical foundation of cost of capital estimation for regulatory purposes. We find that several common regulatory practices lack a solid foundation in the theory. For example, the common practice of estimating a single cost of capital for the regulated firm suffers from a circularity problem, in that the estimate of the cost of capital depends on the regulated revenue allowance which, in turn, depends on the cost of capital. This problem is especially severe in the context of a multi-year regulatory period. We also show that, in the context of a multi-year regulatory period the cost of capital cannot be expressed as a weighted average of the cost of equity and the cost of debt. In addition, the relevant cost of debt cannot normally be estimated using the yield-to-maturity on a corporate bond. We suggest possible directions for reform of cost of capital practices in regulatory proceedings.

Validating implied cost of capital with realized returns by using alternative measures of cash-flow news

We outline analytically that, when testing different implied cost of capital (ICC) estimates for validation by employing the Vuolteenaho (2002) framework, the cash-flow news in the validation framework should be defined in a way that considers the ICC model specific assumed sequence of future cash flows. This is based on market expectations, as proxied by analysts' forecasts. We then propose adjusting the cash-flow news proxies accordingly and implement these adjustments empirically. Consistent with the theoretical predications, the results from these tests show that ICC estimates are significantly positively related to realized returns. Informed by these findings, we employ the adjusted cash-flow news proxies in the validation framework and compare the correlation between adjusted and unadjusted for analysts' bias ICC estimates with realized returns. These tests show no difference in these correlations. This suggests that it is not the analysts' bias that weakens the validity of ICC estimates, as argued by prior literature. It is the proxies used in the validation framework that lead to the suggestion in removing analysts’ optimism from ICC estimates. Overall, our proposed alternative framework not only unlocks the gate for extensive use of the existing ICC estimates but also enables future researchers to develop more reliable and meaningful ICC estimates.

Digitalization impact estimation on the economic growth of the European countries

The article deals with an attempt to assess an impact of digitalization on the economic development of the European countries. For these purposes, it is proposed to supplement the classical Cobb-Douglas production function with a digital capital parameter. However, the study showed the problem of absence of a representative statistical base for the cost estimation of the digital capital of the European countries. Under these conditions, method for the impact assessment of digitalization on the indicators of the countries’ economic growth was developed, based on the application of the rating correlation analysis to the classical production function calculations results and the business digitalization index. In general, the results of the performed calculations confirmed the positive impact of business digitalization on the economic growth of the European countries and made it possible to estimate the nature of the digital processes’ impact on the main production factors – labor and fixed asset. The prospects for further development of this subject should be associated with the scientific grounds of the general approaches to estimating digital capital and the formation of the corresponding statistical arrays.

Country risk and its impact on renewable energy investment in highly polluted economies.

The country's risk may significantly impact every sector of the economy, and the energy sector is no exception. However, no past study has empirically tested the relationship between country risk and renewable energy investment. Therefore, this study is an effort to investigate the relationship between country risk and renewable energy investment in highly polluted economies. We have employed different econometric techniques to analyze the relationship between renewable energy investment and country risk, including the OLS, 2SLS, GMM, and panel quantile regressions. The estimate of country risk influence renewable energy investment negatively in OLS, 2SLS, and GMM models. Similarly, the country's risk negatively impacts the renewable energy investment from the 10th to 60th quantiles in the panel quantile regression model. Moreover, the GDP, CO2 emissions, and technological development help promote renewable energy investment in OLS, 2SLS, and GMM models, while the human capital and financial development do not significantly impact the renewable energy investment. Furthermore, in the panel quantile regression model, the GDP and CO2 emission estimates are positively significant almost at all quantiles, and the estimate of technological development and human capital are positively significant at higher quantiles only. Therefore, the authorities in highly polluted economies should consider the respective countries' risk considerations while formulating rules about renewable energy.

Dividend change announcements, ROE, and the cost of equity capital

We hypothesize and present strong evidence that dividend increases (decreases) result in a general decrease (increase) in the opportunity cost of equity capital (Ke), measured by the discount rate implicit in analysts' forecasts. Estimates of Ke obtained from analyst forecast data likely capture priced information risk that is not reflected in cost of equity capital estimates customarily obtained from empirical excess returns data. In the presence of a full menu of control variables, our measured changes in the cost of equity capital are shown to provide high explanatory power for the market reaction to dividend change announcements. We also hypothesize and demonstrate that the impact of dividend changes on the cost of equity is conditional on how preannouncement Ke relates to preannouncement return on equity (ROE). Specifically, dividend increases result in a reduction in the cost of equity capital only when currently experienced ROE < Ke. This is consistent with shareholders preferring earnings to be reinvested by managers to earn a higher rate than their opportunity rate. When ROE > Ke, on the other hand, the cost of equity capital actually increases. For dividend decreases, the cost of equity capital increases only when ROE > Ke, consistent with firms currently experiencing positive economic income using dividend cuts to signal anticipated permanent earnings declines. Together with extensive robustness tests, our results indicate that dividend changes significantly affect shareholder value, contrary to the longstanding dividend irrelevance argument.

Human capital: valuation and management

The article considers approaches to the assessment of human capital taking into account the concept of value-oriented corporate management, which has become the methodological basis of the study. The tools of synthetic and analytical accounting in accordance with RAS and the tax legislation of the Russian Federation were used to disclose the content and comprehension of the studied financial notions. The methods of relative values of economic analysis, quantitative methods of evaluation, cost-based (property), revenue and market (comparative) approaches are used in relation to determining the value of human capital. A more specific definition of the human capital utilization coefficient and quantitative estimates of individual human capital, goodwill of human capital are proposed. A universal methodology has been developed for assessing human capital in proportion to the business qualities and labor contribution of employees to the capitalization of the enterprise and the increase in its value. The proposed methodology integrates revenue, cost-based (property) and market approaches. The quantitative relationship between the goodwill of individual human capital and the goodwill of the entire enterprise is revealed. For practitioners in the field of business valuation, researchers in the development of value-oriented corporate management, teachers and students of economics in the study of financial methods of corporate valuation.

The value of knowledge: Discovering hidden capital

The purpose of this research is to overcome the weaknesses of intellectual capital (IC) estimation models, constructing and empirically verifying a new model that has the same strengths as the value-added intellectual coefficient (VAIC) but not its weaknesses. To better outline our analysis with respect to the many meanings that can be evoked by the term IC in the literature, we also define a new term: “hidden capital” (HDC) in the balance sheet. First, we analyze the epistemological and methodological aspects of the models existing in the literature, highlighting their weak points. Subsequently, using a logical-deductive methodology, we build a theoretical model, named “HDC”, to discover the “hidden capital”. Finally, we proceed to the empirical verification of the HDC model on a sample of over 1,800 listed European companies observed in the pre-pandemic period 2011–2019 (over 10,000 firm-year observations). The empirical verification through a regression panel model on eight European countries shows that all the variables of the HDC model are, unlike VAIC, significant and directly correlated to Tobin’s Q.

Fixed Capital Estimation: Utilization of Macro Data to Account for Capital Heterogeneity at Firm Level

Fixed Capital Estimation: Utilization of Macro Data to Account for Capital Heterogeneity at Firm Level

Application of GA-SVM algorithm in improvement design of engineering cost model

Aiming at the problems of large data deviation and poor resistance of calculation results in the current construction project cost modeling, structural optimization and calculation improvement are carried out on the construction project cost modeling. The SVM algorithm reduces the influence of external conditions on the calculation results, and further optimizes the construction project cost modeling calculation. By using the SVM algorithm calculation formula for capital estimation, design estimation, and correction calculation, the data processing capability and precision construction are further improved. The purpose of this paper is to study the application of GA-SVM algorithm in the improvement and design of Engineering Cost Model (ECM). This paper analyzes the principle of the SVM, the advantages of the SVM algorithm and the kernel function of the SVM algorithm, and finally obtains the experimental results, The empirical analysis results show that the cost model designed in this paper can effectively estimate the cost of the project cost, with small error value, high budget value accuracy, strong anti-interference ability, short running time, wide application range and strong practicability. We conducted a questionnaire and found that more than 84% of people felt that the design ECM was applied to the SVM algorithm, and found that the design efficiency became high.

Techno-economic analysis of reactor types and biogas utilization schemes in thermophilic anaerobic digestion of sugarcane vinasse

This study conducted a techno-economic analysis to compare two types of thermophilic anaerobic reactors and three biogas utilization schemes in biogas production from vinasse. The reactors studied were the Fixed Bed Reactor (FBR) and Continuous Stirred Tank Reactor (CSTR). The biogas utilization schemes investigated were biogas conversion to electricity compared to direct biogas use for co-firing in the existing boiler and combined uses for co-firing and domestic fuel sale to the nearby households around the plant. The techno-economic calculations were based on experimental data using the prototypes of FBR and CSTR. The fixed and working capital estimations were based on Indonesia's construction industry database. At the same Organic Loading Rate (OLR) of 9.66 g sCOD per litre, 7-day Hydraulic Retention Time (HRT), and 200 m3/day vinasse capacity, FBR produced twice more biogas than CSTR. The economic analysis result indicated that the scheme of co-firing in existing boilers by fuel-oil replacement and partial substitution of coal was economically more attractive than the electricity production at the current electricity pricing in Indonesia. In this recommended scheme, we obtained 17.26% internal rate of return, 4.34 years payback period, and Rp20.94 billion net present value.

Oil price shocks and cost of capital: Does market liquidity play a role?

This paper provides novel perspective to the oil-stock market nexus by examining the role of stock market liquidity in the propagation of oil price shocks to the cost of capital (CoC) estimates from a set of 34 global economies. Utilizing implied cost of capital estimates that are extracted from a dividend discount model and disaggregated oil price shock series including oil supply, consumption demand, inventory demand and economic activity shocks, we show that oil price shocks have quite heterogeneous effects on equity financing costs across the world economies, depending on the nature of the shock and the time horizon. Our findings show that oil supply shocks have a consistent positive effect on CoC, particularly for emerging economies and net oil importers, suggesting that supply driven oil price uncertainty significantly raises firm level financing costs regardless of the level of market liquidity. Interestingly however, market liquidity takes on a significant role when interacted with oil consumption demand shocks, suggesting that the effect of oil demand shocks on firms' financing costs is transmitted via the liquidity channel. Considering that liquidity dry-ups can severely impact firm financing costs, our findings provide important insights to policy makers as demand driven oil market shocks present a double challenge via its effects on market liquidity dynamics, which in turn, can enhance the negative impact of these shocks on firm financing costs and corporate investment activity. Overall, the findings highlight the role of market liquidity in the propagation of oil price shocks to firm financing costs with significant implications for corporate managers and policy makers.

Eliminating proxy errors from capital estimates by targeted exact computation

AbstractDetermining accurate capital requirements is a central activity across the life insurance industry. This is computationally challenging and often involves the acceptance of proxy errors that directly impact capital requirements. Within simulation-based capital models, where proxies are being used, capital estimates are approximations that contain both statistical and proxy errors. Here, we show how basic error analysis combined with targeted exact computation can entirely eliminate proxy errors from the capital estimate. Consideration of the possible ordering of losses, combined with knowledge of their error bounds, identifies an important subset of scenarios. When these scenarios are calculated exactly, the resulting capital estimate can be made devoid of proxy errors. Advances in the handling of proxy errors improve the accuracy of capital requirements.