Real Rate Research Articles

Multicomponent prediction of Sudan dye adulteration in crude palm oil using SERS – Based bimetallic nanoflower combined with genetic algorithm

Crude palm oil (CPO) is an important edible vegetable oil used globally, recently subjected to Sudan dye adulteration. This study explored the feasibility of a novel SERS-based Au@Ag substrate to detect four Sudan dyes (I - IV) in CPO. When mixed with spiked CPO, the SERS substrate produced strong signals that increased with increasing concentrations from 0.001 to 4.0 ppm. The genetic algorithm partial least square (GA-PLS) model outperformed the partial least square (PLS) and the ant colony optimization – PLS (ACO-PLS) models with Rc values of 0.9844, 0.9865, 0.9884, and 0.9888 0.9846. The calculated LOD were 0.00088 ppm, 0.00092 ppm, 0.00095 ppm, and 0.00097 and real sample recovery rates of 88.0–113.0%, 92.0–103.0%, 91.2–98.5% and 97.0–109.5% for Sudan I, II, III, and IV, respectively. The findings affirmed the SERS sensor’s considerable potential for rapid and selective detection of Sudan dyes in CPO when combined with chemometrics.

The Effect of Market Asset Returns, Economic Conditions, and Firm Fundamentals on Net Lease Capitalization Rates

This study fills a void in the literature by examining real estate capitalization rates for single-tenant net lease (STNL) properties. First, we examine cap rate variation in relation to market and firm-level fundamentals using individual transaction data in a multistage regression approach. Second, our single-tenant dataset, which allows us to control for characteristics such as industry and tenant credit ratings, gives us unique insight into not only the pricing of cap rates, but also their underlying drivers and their relationship to market fundamentals and returns on alternative assets. Using this unique dataset of more than 8,000 single-tenant net lease retail property transactions, we develop a quarterly cap rate index controlling for Metropolitan Statistical Area (MSA) and industry fixed effects, property and lease characteristics, and localized influences such as population density and household income. Third, we examine the effect of excess corporate bond spreads, excess stock returns, stock market indicators, firm financials, and economic and demographic indicators. Finally, we examine the effect on cap rates of MSA characteristics such as size, wealth, poverty, crime, gross domestic product, and growth. The findings show that, besides the systematic risk from stock and bond returns, national and metropolitan economic forces and firm fundamental factors explain variation in cap rates.

Human Capital Development and Economic Growth: Evidence from Nigeria

This study examined the impact of human capital development on economic growth in Nigeria from 1981 to 2021using the autoregressive distributed lag (ARDL) method. Annual time series data on the dependent variable, real gross domestic product growth rate (RGDPG), alongside the independent variables, including government expenditure on education, government expenditure on health as well as gross fixed capital formation were sourced and collected from Central Bank of Nigeria [1] Statistical Bulletin, while the annual time series data on primary, secondary and tertiary school enrolments were collected from UNESCO [2] Institute for Statistics. The series were tested for stationarity using the Augmented Dickey Fuller (ADF) unit root test. The result showed a mix of variables integrated of order one, I(1) and of order zero, I(0). The Bounds test for cointegration showed the existence of long run relationship amongst the variables as the F-statistic value of approximately 3.43 was found to be higher than the 5% upper bounds value of 3.28. The results of the ARDL method of analysis revealed that in the long run, government expenditure on education and tertiary school enrolment had insignificant negative impact on economic growth while government expenditure on health, gross fixed capital formation, primary and secondary school enrolments had insignificant positive impacts on economic growth. On the other hand, in the short run, while government expenditure on education exhibited significant negative impact on economic growth, government expenditure on health had significant positive impact on economic growth. Gross fixed capital formation impacted positively on economic growth, primary school enrolment had negative impact while secondary and tertiary enrolments had positive impact on economic growth. Consequently, the study recommended among others that the government should set incremental annual targets expenditure on health aimed at achieving the Abuja agreement of 15% of total public expenditure in the health sector. This will create multiplier effect in the long run and serve as a boost to economic growth in the country.

Reaction of Indian Stock Market to Outbreak of COVID-19: An Empirical Analysis of Extreme Inter-day Movements

The contagious COVID-19 pandemic has been considered a massive global crisis since World War II and has disturbed business and economic activities across the globe. The current study examined the reaction of the stock market’s to the outbreak of COVID-19, considering the extreme inter-day movements in the Indian stock market. The extreme inter-day movements in S&P CNX Nifty-50 have been identified during the study period from January 2020 to December 2021 and further classified into decline and gain events based on positive and negative announcements related to COVID-19. The study utilized an event study approach and panel regression for empirical investigation. The results of the event study analysis illustrate that the significant abnormal loss ranges from 12.86% to 2.47% for the major decline events and significant abnormal return from 8.43% to 3.23% for the gain events. The regression analysis results showed that real return and Central Bank Policy rate have a considerable impact on the abnormal returns during COVID-19. The study’s findings are helpful to policy implications that identified the need to focus on financial education and strengthen the health and finance-related policies to deal with such pandemics in the future.

Predictive analytics study to determine undergraduate students at risk of dropout

In this this work, a study is presented with quantitative variables using machine learning tools to detect undergraduate students at risk of dropping out and the factors associated with this behavior. Clustering algorithms and classification methods were tested to determine the predictive power of several variables regarding the dropout phenomenon on an unbalanced database of 14,495 undergraduate students with a real dropout rate of 8.5% and a retention rate of 91.5%. The usual classification criterion that assigns individuals to a class if their probability of belonging to it is greater than 50% provided accuracies of 13.2% in the dropout prediction and 99.4% in the retention prediction. Among eight classifiers, Random Forest was selected and applied along with Threshold Probability, which allowed us to gradually increase the dropout precision to more than 50%, while maintaining retention and global precisions above 70%. Through this study, it was found that the main variables associated with student dropouts were their academic performance during the early weeks of the first semester, their average grade in the previous academic levels, the previous mathematics score, and the entrance exam score. Other important variables were the number of class hours being taken, student age, funding status of scholarships, English level, and the number of dropped subjects in the early weeks. Given the trade-off between dropout and retention precisions, our results can guide educational institutions to focus on the most appropriate academic support strategies to help students at real risk of dropping out.

법인세의 분배효과에 관한 연구

This study analyzes the effect of corporate income tax on income distribution in Korea. Studies on the economic effects of corporate income tax have mainly focused on investment and employment effects. This research trend is due to the prevailing idea that the investment effect of corporate income tax is decisive, employment and wages are determined incidentally, and that companies are merely conduits for distributing profits to shareholders. However, corporate income tax also affects the labor income share and household income distribution through changes in employment and wages, dividends, and internal reserve fund of a company. If corporate income tax cuts increase investment, but employment growth is weak and real wage growth rates falls short of labor productivity growth rates, the labor income share will decrease and household income inequality will widen. According to the results of the empirical research, the effects of corporate income tax rate on investment and employment are weak. The expanded investment is also capital-intensive, so the employment effect is not significant, and more the real wage increase does not keep up with labor productivity. As a result, a reduction in the effective corporate income tax rate lowers the labor income share and increases income inequality. Therefore, to increase the distribution effect of corporate income tax, corporate income tax should be reformed in a way that supports employment growth and real wage increases while including investment.

Forecasting the South African Real Spot-rate Curve During Covid-19 Stress

Purpose: The aim of this study is to investigate the performance of forecasting the South African real spot rate curve using different mathematical term-structure models during the Covid-19 period. This study follows previous studies by Reid (2009) and Mashoene et al., 2021) where dynamic term-structure models performed well compared to static term-structure models over normal market conditions. For high volatility, normality often breaks, which might result in a need for recalibration in the currently used methodology or a total change in the methodology.
 Methodology: This study explores the dynamism of both dynamic term-structure models, which follow the Nelson-Siegel framework, and static term-structure models with the option of recalibration of model parameters to account for a change in macro-economic dynamics brought by the effect of the Covid-19 pandemic. The forecasting exercise was applied to term-structure models following the Nelson-Siegel framework using AR(1) process.
 Findings: The incorporation of macroeconomic factors performed poorly in estimating future model parameters. This could be attributable to the effect of global stress, which resulted in poor linear relationships between macroeconomic and financial factors. Recalibration process on static Nelson-Siegel term-structure models improved the models' performance, especially during the high volatility/period of total economic shutdown due to the Covid-19 pandemic.
 Implications: The application of static Nelson-Siegel term-structure models with recalibrated parameters might improve bond pricing processes and risk management strategies in emerging markets, especially during market stress.

Investigation of Real Estate Tax Leakage Loss Rates with ANNs

In Türkiye, many changes have been made in the law within the past fifty years to determine the real estate tax value close to the real market value. However, the changes did not establish a fair valuation system for determining real estate tax. Despite the regulations and records of immovable properties with a geographic information system (GIS)-based inventory in recent years, the problem of leakage loss in real estate tax was still not resolved. Within the scope of this study, a mass appraisal model was created with a dataset of 499 independent sections including trading values from the last year in the district of Kayseri to determine the real estate tax leakage loss rates. Multiple regression analysis (MRA) and artificial neural network (ANN) methods, widely used in mass appraisal, were used in the analysis. Considering the analysis of the test data and the model performances, the ANN model was found to give better results than the MRA model. To conclude this study, the housing values obtained with the mass appraisal methods and the real estate tax values obtained with the existing system were compared, and a 3.7-fold difference was found between them.

Biolarvicide Activity of Male Breadfruit Flower Causes Mortality of Anopheles sp. Mosquito Larvae Malaria Vector

This study aims to determine the biolarvicidal activity of male breadfruit pollen causing mortality of Anopheles sp. malaria vector. This study used a completely randomized design (CRD), in which 600 Anopheles sp. divided into 8 groups with 3 replications, Anopheles sp. placed in 24 plastic cups, where each plastic contains 25 Anopheles sp. larvae. The results obtained were analyzed by Analysis of Variance (ANOVA) and continued with the Duncan test at real rate a = 0.05 using SAS software and continued with the smallest significant difference test to determine the difference in the treatment given. Then a LC50 probit analysis was performed to determine the concentration of breadfruit pollen biolarvicide which is good at 50% mortality of Anopheles sp. mosquito larvae. The results showed that male breadfruit powder concentrations of 0.5, 1, 1.5, 2, 4, and 6% had a biolarvicidal effect causing mortality of Anopheles sp. mosquito larvae with an effective concentration of 6% (97.2% mortality), of which 50% mortality ( LC50) of Anopheles sp. occurred at a concentration of male breadfruit pollen at a concentration of 3.95%.

A new strategy to guarantee retirement income using TIPS and longevity insurance: A second look

Shankar (2009) proposes a new investment strategy for retirees that bundles Treasury Inflation Protected Securities with a deferred annuity to guarantee real annual withdrawal rates of 5% or more with no risk of financial ruin. This strategy addresses three problems that retirees face: longevity risk, inflation risk, and liquidity risk inherent in the purchase of an immediate annuity. In our article, we evaluate the performance of this proposed strategy under realistic assumptions about costs, security design, and markets. In addition, we evaluate how the bequest motive might affect the choice between Shankar’s strategy and an immediate annuity.

The Rising Cost of Climate Change: Evidence from the Bond Market

Abstract Social discount rates (SDRs) are crucial for evaluating the costs of climate change. We show that the fundamental anchor for market-based SDRs is the equilibrium or steady-state real interest rate. Empirical interest rate models that allow for shifts in this equilibrium real rate find that it has declined notably since the 1990s, and this decline implies that the entire term structure of SDRs has shifted lower as well. Accounting for this new normal of persistently lower interest rates substantially boosts estimates of the social cost of carbon and supports a climate policy with stronger carbon mitigation strategies.

LOCAL GOVERNMENT FINANCE AND COMMUNITY DEVELOPMENT IN NIGERIA

Using the Ordinary Least Square (OLS) method, the research investigates the effect of local government budget on community development in Nigeria. The findings show that the overall loan taken out by local governments has a negative and significant effect on human development. Additionally, it was discovered that municipal governments' overall spending had a somewhat favourable effect on human development. Additional research revealed that local governments' present revenues significantly and favourably affected human development. The rate of population expansion had a detrimental and severe impact on human development. The total amount borrowed by municipal governments also had a detrimental but little effect on life expectancy. The results also demonstrated that local governments' overall spending, current revenue, and real GDP growth rate all had a favourable and significant impact on life expectancy. Local government autonomy is recommended. With local government autonomy, federal allocation (revenue) as well as other revenues will come direct to the local governments and not through the state governments. This will ensure higher revenue for the local governments to carry out development-oriented projects and programmes. Also, local government authorities should utilize available revenues in bringing about desired community development in the areas of human development in Nigeria. Local government autonomy is recommended so that revenue from the federation accounts and other revenues could go directly to local government, not through state governments. This could improve on local government revenue base and bring about desired human development in Nigeria.

Effect of Macroeconomic Dynamics on Bank Asset Quality under Different Market Conditions: Evidence from Ghana

This study assesses the dynamic relationship between macroeconomic factors and bank asset quality based on changes in the condition of stock market returns. A dynamic panel two-step system, the Generalized Method of Moments (system GMM) model, is employed using panel data from 18 universal banks spanning the period of 2007 to 2021. The analysis revealed that the real GDP growth rate, the average lending rate, and the real exchange rate represent a set of macroeconomic factors with a marked influence on banks’ asset quality, where a unit increase in these variables drive 0.02 percent, 0.98 percent, and 0.27 percent improvement in asset quality, respectively. In addition, a high-inflation rate was found to exert an adverse effect of −0.32 percent on asset quality, as it affects borrowers’ financial ability to meet loan repayment obligations. Furthermore, the study verified the existence of a positive relationship between market condition and asset quality, where a rise in the market return drives a 0.07 percent improvement in bank asset quality. This implies that bank performance adapts to changes in market conditions as posited under the Adaptive Market Hypothesis (AMH). Bank managers should consolidate banks’ asset bases during conditions of market stability to withstand periodic market fluctuations to boost trading momentum. Policy recommendations are suggested to foster a conducive business environment for bank stability.

Unusual Changes in the U.S. Treasury Security Market During the Fourth Round of Quantitative Easing

Abstract The Covid-19 Pandemic and policy response rattled the US Treasury markets. Conventional US Treasuries, inflation adjusted US Treasuries, and the relationship between the two developed in ways such that ignoring changes in real interest rates yielded distorted inflation expectations estimates. Since the beginning of the pandemic, monetary policy kept nominal rates low and close to zero, but positive. Real rates, on the other hand, became increasingly negative. The relationship between the two market rates became negatively correlated, and distorted because of the fourth round of quantitative easing, along with the Fed preventing nominal yields from turning negative. Federal Reserve actions during the Covid-19 pandemic drove a larger wedge between nominal interest rates and real interest rates in the inflation adjusted market.

Estimating the number of planets that PLATO can detect

Context. The PLATO mission is scheduled for launch in 2026. It will monitor more than 245 000 FGK stars of magnitude 13 or brighter for planet transit events. Among the key scientific goals are the detection of Earth-Sun analogs; the detailed characterization of stars and planets in terms of mass, radius, and ages; the detection of planetary systems with longer orbital periods than are detected in current surveys; and to advance our understanding of planet formation and evolution processes. Aims. This study aims to estimate the number of exoplanets that PLATO can detect as a function of planetary size and period, stellar brightness, and observing strategy options. Deviations from these estimates will be informative of the true occurrence rates of planets, which helps constraining planet formation models. Methods. For this purpose, we developed the Planet Yield for PLATO estimator (PYPE), which adopts a statistical approach. We apply given occurrence rates from planet formation models and from different search and vetting pipelines for the Kepler data. We estimate the stellar sample to be observed by PLATO using a fraction of the all-sky PLATO stellar input catalog (PIC). PLATO detection efficiencies are calculated under different assumptions that are presented in detail in the text. Results. The results presented here primarily consider the current baseline observing duration of 4 yr. We find that the expected PLATO planet yield increases rapidly over the first year and begins to saturate after 2 yr. A nominal (2+2) 2-yr mission could yield about several thousand to several tens of thousands of planets, depending on the assumed planet occurrence rates. We estimate a minimum of 500 Earth-size (0.8−1.25 RE) planets, about a dozen of which would reside in a 250–500 days period bin around G stars. We find that one-third of the detected planets are around stars bright enough (V ≤11) for RV-follow-up observations. We find that a 3-yr-long observation followed by 6 two-month short observations (3+1 yr) yield roughly twice as many planets as two long observations of 2 yr (2+2 yr). The former strategy is dominated by short-period planets, while the latter is more beneficial for detecting earths in the habitable zone. Conclusions. Of the many sources of uncertainties for the PLATO planet yield, the real occurrence rates matters most. Knowing the latter is crucial for using PLATO observations to constrain planet formation models by comparing their statistical yields.

Mortality Effects of Mosquito Anopheles Sp. Malaria Vectors Caused by Exposure to Burning Mosquito Drugs and Male Breadfruit Mat

This study aims to determine the effect of mortality on Anopheles sp . vector of malaria due to exposure to mosquito coils and male breadfruit mats. This study used a completely randomized design (CRD), in which 180 Anopheles sp. divided into 3 groups with 3 replications, Anopheles sp. placed in 9 plastic cups, where each plastic contains 20 Anopheles sp larvae, then reared until they become mosquitoes in a mosquito net box. The results obtained were analyzed by Analysis of Variance (ANOVA) and continued with the Duncan test at real rate a= 0.05 using SAS software and continued with the smallest significant difference test to determine the difference in the treatment given. The results showed that the use of mosquito coils and electric mats for male breadfruit flowers had the same mortality effect, where the percentage of mortality was 100%.

An evaluation of the relationship between company performance and executive pay of telecommunications companies listed on the Johannesburg stock exchange in South Africa

South Africa has experienced difficult trade conditions over recent years. South Africa’s real Gross Domestic Product growth rate from 2016 to 2021 has grown at less than 1.5%. This current economic condition makes it difficult for company executives to increase revenue, thereby increasing share price. This study aimed to evaluate the relationship between company performance and executive pay of telecommunications companies listed on the Johannesburg Stock Exchange in South Africa. The study adopted a quantitative research approach to gather and analyse published information from selected Johannesburg Stock Exchange-listed telecommunications companies in South Africa.

Realized genetic gains via recurrent selection in a tropical maize haploid inducer population and optimizing simultaneous selection for the next cycles

AbstractPlant breeders widely use recurrent selection schemes to increase the frequency of favorable alleles for quantitative traits in a population. Although simultaneous selection is complex because it involves several traits combined with selection cycles, the use of selection indexes (SI) is applied to increase the chance of success of the breeding program. Despite many indices are available in the literature, simulations can help breeders to determine which selection index can be better adjusted considering the selection goals, the intensity, and the genetic correlation among traits over breeding cycles. In this context, we estimated the realized genetic gains in a tropical maize haploid inducer population after two cycles of recurrent selection, using external testers and optimizing the simultaneous selection for this breeding population in the long term via stochastic simulations. Furthermore, we proposed a new approach to optimize the initial weights by applying Smith‐Hazel method to maximize the genetic gains for all traits in a balanced way. Overall, the estimated gains in real induction rate were about 63% per cycle, improving the population performance from 0.8% to 2.8%. Moreover, our results confirm that the traditional Smith‐Hazel approach outperformed other methods for long‐term response to selection. Finally, recurrent selection with external testers may be a suitable method to improve the haploid induction rate in tropical maize populations.

Undesired monetary policy effects in a bubbly world

AbstractStock market bubbles arise as a joint monetary and financial phenomenon. We assess the potential of monetary policy in mitigating the onset of bubbles by means of a Markov-switching Bayesian Vector Autoregression model estimated on US 1960–2019 data. Bubbles are detected and dated from the regime-specific interplay among asset prices, fundamental values, and monetary policy shocks. We rationalize the empirical evidence with an Overlapping Generations model, able to generate a bubbly scenario with shifts in monetary policy, and where agents form beliefs over transition dynamics. By matching the VAR impulse responses, we find that procyclicality and financial instability align with high equity premia and the presence of asset price bubbles. Monetary policy tightening, by increasing real rates, is ineffective in deflating bubble episodes.

Pengaruh Game Online terhadap Motivasi Belajar Peserta Didik SMAN 1 Adonara Tengah, Desa Kenotan, Kecamatan Adonara Tengah, Kabupaten Flores Timur Tahun Pelajaran 2022/2023


 
 
 
 The purpose of this study was to describe the effect of online games on the learning motivation of student of class X IPS of IPA SMAN 1 Adonara Tengah, Kenotan Village, Adonara Tengah, District, East Flores Regency for the 2022/2023 Academic Year. The problem in this study is how online games influence the learning motivation of student in class X IPA and class X IPS of SMAN 1 Adonara Tengah, Kenotan Village, Adonara Tengah District, East Flores Regency. The population in this study were class X IPA and X IPS of SMAN 1 Adoanara Tengah Kenotan Village, Adonara Tengah Discrict, East Flores Regency for the 2022/2023 academic year, which consisted of 40 student, so the sample was taken from the entire population, namely 40 students. The instruments used in this study were observation and quistionnaires, where the questionnaire contained 20 question items. The data analysis technique used in this study is the product moment correlation formula with the result of the correlation coefficient between online games on student learning motivation ( Rxy ) of 0.3 which shows that there is an influence between online games on student learning motivation carrelated significantly at a significant level of 9%. Then it was tested for significance using the “t” test form;;ula. For a real rate of 0.03, based on the calculation above, tcount = 1,93 while t table = 1. 684 tcount > t table, namely 1.93 > 1. 684, Ha is accepted, Ho is rejected. This shows that between variable X and variable Y it can be concluded that there is and influence of online games on student learning motivation at SMAN 1 Adonara Tengah Kenotan Village, Adonara Tengah District, Esat Flores Regency, in the 2022/2023 Academic Year. So from the calculations obtained above, the effect of online games on student learning motivation SMAN 1 Adonara Tengah, Kenotan Village, Adonara Tengah Discrict, East Flores Regency for the 2022/2023 academic year 9%.