Regression Estimates Research Articles

Selective Laser Trabeculoplasty after a Previous Glaucoma Treatment.

Recent prospective studies have shown that selective laser tra-beculoplasty (SLT) is a safe and cost-effective alternative to pressure-reducing eye drop therapy as a first-line treatment for ocular hypertension or open-angle glaucoma. In addition to its comparable efficacy to eye drop therapy, SLT has been particularly effective in delaying the time until a surgical intervention is needed. The aim of our evaluation is to analyze patients who have received SLT following a pressure-reducing procedure. The primary endpoint is the duration until a subsequent interventional or surgical procedure is required. A retrospective analysis of 98 patients who underwent selective laser trabeculoplasty following a previous pressure-reducing procedure between 2017 and 2023. The statistical analyses included Cox regression and Kaplan-Meier survival estimations. In total, 122 eyes of 98 patients received selective laser trabeculoplasty following a previous pressure-reducing procedure at the Department of Ophthalmology in Freiburg. The median follow-up period was 381.5 days (range 43.25-862.75 days). Approximately 68% of the eyes did not require another pressure-reducing procedure 365 days after the intervention, while about 58% of the eyes remained without another procedure after 730 days, according to Kaplan-Meier analysis. No significant difference was found between the different types of glaucoma regarding the duration until a subsequent pressure-reducing procedure was needed. The study indicated a tendency for patients with pseudoexfoliation glaucoma to undergo a secondary intervention earlier compared to those with primary open-angle glaucoma (p = 0.16). The intraocular pressure before SLT had a significant impact on the duration until the subsequent operation (p = 0.005). SLT is an effective method even after a previous pressure-reducing procedure for patients in whom further pressure-reducing interventions need to be delayed.

Do modifiable patient factors increase the risk of postoperative complications after total joint arthroplasty?

Numerous studies demonstrate that modifiable lifestyle risk factors can influence patient outcomes including survivability, quality of life, and postoperative complications following orthopaedic surgery. The purpose of this study was to determine the impact of modifiable lifestyle risk factors on postoperative medical and surgical complications following a total joint arthroplasty (TJA) in a large national healthcare system. A retrospective chart review of a large national health system database was performed to identify patients who underwent TJA between 2017 and 2021. TJA included total knee arthroplasty, total hip arthroplasty, and total shoulder arthroplasty. Modifiable lifestyle risk factors were defined as tobacco use, narcotic drug abuse, hypertension, and diabetes mellitus. Postoperative medical complications and postoperative surgical complications were collected. Logistic regression and odds ratio point estimate analysis were conducted to assess for associations between postoperative complications and modifiable lifestyle risk factors. Of the 16,940 patients identified, the mean age was 71 years, mean BMI was 29.7kg/m2, and 62% were women. We found that 3.5% had used narcotics, 8.7% were past or current smokers, 24% had diabetes, and 61% had hypertension; in addition, 5.4% experienced postoperative medical complications and 6.4% experienced postoperative surgical complications. Patients who used narcotics were 90% more likely to have postoperative complications (p < 0.0001) and 105% more likely to experience prosthetic complications (p < 0.0001). Similarly, patients with tobacco use were 65% more likely to have postoperative complications (p < 0.0001) and 27% more likely to experience prosthetic complications. Our results demonstrate critical rates of increased postoperative medical and surgical complications after TJA for patients with narcotic abuse, tobacco use, or diabetes mellitus. Furthermore, adopting preoperative interventions and optimization programs informed by our findings on specific modifiable risk factors could aid orthopaedic surgeons in optimizing patient health. III; Retrospective study.

Tensile Properties of Cattail Fibres at Various Phenological Development Stages.

Cattails (Typha latifolia L.) are naturally occurring aquatic macrophytes with significant industrial potential because of their abundance, high-quality fibers, and high fiber yields. This study is the first attempt to investigate how phenological development and plant maturity impact the quality of cattail fibers as they relate to composite applications. It was observed that fibers from all five growth stages exhibited a Weibull shape parameter greater than 1.0, with a goodness-of-fit exceeding 0.8. These calculations were performed using both the Least Square Regression (LSR) and Maximum Likelihood Estimation (MLE) methods. Among the estimators, the MLE method provided the most conservative estimation of Weibull parameters. Based on the Weibull parameters obtained with all estimators, cattail fibers from all five growth stages appear suitable for composite applications. The consistency of shape parameters across all five growth stages can be attributed to the morphological and molecular developments of cattail fiber during the vegetative period. These developments were confirmed through the presence of calcium oxalate (CaOx) plates, elemental composition, and specific infrared peaks at 2360 cm-1 contributing to the strength, cellulose peaks at 1635 cm-1, 2920 cm-1, and 3430 cm-1. In conclusion, it was found that the mechanical properties of cattail fiber remain similar when harvested multiple times in a single growing season.

COP27 Perspective of Food, Land Resources and Digitalization for Sustainable Economy: Novel Evidence From Lower‐Middle‐Income Countries

ABSTRACTEconomies in the environmentally conscious era follow the 27th Conference of the Parties' commitments to attaining environmental sustainability. However, using alternative energy sources reduces arable land and diminishes land resources, severely affecting food production, exports, and overall income. This issue raises concerns about attaining a sustainable economy, which has attracted little scholarly attention in the preceding literature. The present research examines the influence of food exports, digitalization, access to clean fuel and technologies for cooking, mineral resources, and oil resources on the economic sustainability of lower‐middle‐income economies. Covering the latest period from 1990 to 2022, this study uses several time series estimators to analyze the aggregate data of selected economies. The empirical results suggest that the mentioned variables are cointegrated in the long run. The regression estimates showed that food exports and mineral resources are adversely associated with economic sustainability. However, access to clean fuel and technologies for cooking and digitalization significantly contributes to the region's economic sustainability. Nonetheless, the role of oil resources is insignificant but negative, which validates the resource curse phenomenon in the region. The results are robust since these estimations are validated by regression accounting for structural breaks. This study recommends investment in clean energy resources, efficient mineral resource management, and the transition to clean energy to accomplish the 27th Conference of the Parties target and attain sustainable development.

Economic impact of large earthquakes: lessons from residential property values

Abstract Understanding how economic agents respond to seismic shocks in a developing country setting is crucial to evaluating the economic costs of natural disasters. This article makes use of the quasi-random spatial and temporal nature of ground tremors to estimate the economic impact of the April 2015 earthquake on residential property values in Nepal. Regression estimates from the difference-in-differences research design show that residential property values declined by about 40.52 percentage points in areas with high seismic intensity. The event study model illustrates that these negative economic effects are more pronounced between 12 and 24 months after the incidence of the earthquake. Findings further underscore the underlying mechanism of physical damage and indicate that residential properties with weaker outer walls, foundations and roof materials became more susceptible to the earthquake.

Agro-Pastoral Youth Participation in Livelihood Activities, Development Programs and Interventions in East and West Hararghe Zones of Oromia Regional State, Ethiopia

This study was conducted to identify the status and determinants of male and female youth participation in selected livelihood activities, development programs and interventions in agro-pastoral areas of Oromia regional state, Ethiopia. A cross-sectional research design and mixed methods research approach were employed. A multi-stage random sampling strategy was followed to select four agro-pastoral Woredas (A ‘Woreda’ is an administrative unit equivalent to a District), 12 Kebeles (A ‘Kebele’ is the smallest administrative unit in Ethiopia. A Woreda/District consists of several Kebeles) and 398 youth aged 15–29 years for a face-to-face interview. Data were analysed through descriptive and inferential statistics and an econometric model (Logistic regression) estimation. We found that whereas male youth had better access to land, participation in extension/advisory services and Farmers’ Training Centers (FTCs), agricultural training, and NGOs, female youth had better participation in non-/off-farm livelihood activities and Productive Safety Net Program (PSNP). Our findings indicated that lack of access to financial resources, limited access to land, poor extension and rural advisory services, limited skills development programs and mentorship were key factors affecting youth participation. Other factors include: targeting criteria, discrimination (e.g. on the basis of gender, social structure), cumbersome organizational procedures and requirements, limited availability and capacity of supporting organizations, poor infrastructural developments, mismatch between needs and services provided, conflict, and climate-induced shocks and uncertainties. To overcome these challenges, local and regional governments and their development partners operating in the area should implement a multi-stakeholder, participatory, co-design and development of programs, projects and interventions to enhance collaboration, youth engagement and benefit. Investments in capacity-building and alternative income-generating activities, entrepreneurship education and business skills training are also important.

30 Years of Macroeconomic Effects in Zambia-VECM, ARDL &amp; IRF Approaches

Purpose: This study examines the impact of selected time series macroeconomic variables on Zambia’s economic progress for thirty (30) years (1992 to 2022) Methodology: The study employs the autoregressive distributed lag (ARDL), vector error correction models (VECMs) and the impulse response functions (IRFs) approaches. Findings: The VECM regression estimates indicate that in the long-run, ceteris paribus, a 1% increase in inflation and population growth rates cause a significant positive impact on economic progress of 0.36% and 0.68 % respectively whereas the total public debt stock causes decrease in economic growth of 0.45%. The ARDL long-run regression estimates indicate that ceteris paribus, a 1% increase in inflation and public debt significantly reduces real GDP by 0.2% and 0.03%, respectively, but a 1% increase in population growth rate increases real GDP by 23.11%. The IRF estimates show that a negative shock to the real GDP causes a mildly negative effect on the inflation rate, causes a significant positive increase in the population growth rate, which dissipates after 9.5 years and causes a significant positive increase in public debt, which dissipates after 10 years. Unique Contribution to Theory, Policy and Practice: Therefore, the study recommends that the Zambian government should prioritize repayment of the outstanding public debt by bringing down the debt-to-GDP ratio to sustainable levels, adhering to prudent public financial management and continuing to grow the domestic revenue base. The policies to promote population growth should be pursued cautiously because rapid population growth rates could erode the future economic growth prospects of Zambia.

An analysis of the Impact of Political Regimes on the Economy: Understanding the Corruption-Growth Relationship

Corruption and economic growth are co- related. No theoretical evidence in the literature provides clear evidence of their relationship. Some researchers believe corruption increases economic growth while others say it negatively affects the economy. This paper aims to analyse the joint effect of corruption and the type of political government (i.e., democratic or autocratic) on economic growth to provide some clarity. Panel data (2000-2020) analysis of Pakistan and Saudi Arabia is used in this research paper to examine the relationship between corruption and the type of political government. GDP per capita is used as a dependent variable and economic factors are used as independent variables. A standard regression estimation approach is used. The relationship is estimated using econometric and statistical panel estimation techniques: FE, Two-stage least square and Dynamic-Panel-System GMM method. The data collected is from ICRG and WDI. The results show that corruption has a positive effect in autocratic systems than in democratic. Thus, it proves that the type of political government, corruption and economic growth are related.

Willingness to pay for sheep traits and their heterogeneous effects on prices: Evidence from primary livestock markets in Ethiopia

We test the hypothesis whether levels of key traits of sheep heterogeneously affect market prices of sheep in a rural setting. Feasible generalized least squares and (un)conditional quantile regression estimations were made on a dataset of 1153 sheep transactions in two primary small ruminant markets in the Amhara region of Ethiopia. The empirical results show that animal traits affect the observed prices of sheep differently, but only partly explain the sheep price differences. Our results also reveal that in addition to animal traits, the type of buyers and seasonality of sheep marketing cause heterogeneity in the observed prices. These findings imply that targeting the animal traits demanded by the market and access to price information that enables farmers to respond to the seasonal changes in livestock markets are essential to increase the income of sheep keepers.

Pre and Post Treasury Single Account (TSA) Implementation and the Nigeria’s Macroeconomic Performance

The paper examined the impact of pre- and post-TSA implementation on Nigeria’s macroeconomic performance. Robust regression estimates were used to analyze the sensitivity of both pre-TSA and post-TSA periods to three macroeconomic performance measures in Nigeria between 2007 and 2014 and 2015 and 2022, respectively. Meanwhile, a paired sample t-test was employed to determine whether the mean values of government total revenue, exchange rate, interest rate, and per capita income differed significantly. The results confirmed that federal government aggregate revenue plays a significant role in influencing Nigeria's macroeconomic performance. Additionally, the mean GTR increased from $8565.95 billion in the pre-TSA period to $9151.93 billion in the post-TSA period. However, this increase was not statistically significant, likely due to delays in TSA implementation. The exchange rate rose significantly, suggesting a notable devaluation of the Nigerian currency. Hence, it is imperative for the government to further strengthen the mechanisms of the TSA.

A dynamic pythagorean exponent: Applications to baseball and structural modeling in risk management

AbstractThe famous Pythagorean theorem relating a team's winning percentage over a season to it's total runs scored and surrendered has been the subject of much attention, in both popular culture and academia. In academia, a main focus has been to find the optimal value for the exponent in the formula, originally taken to be 2 in Bill James' work. The optimal value has been obtained in many published works via regression or other statistical estimation techniques, and calibrated to various sports to reflect the type of play in each sport. In this short article, we borrow from ideas in quantitative finance and risk management to estimate the distribution of these Pythagorean exponents, viewing them as random variables that can evolve over time. We carry out our analysis in a manner similar to that of implied volatility from the Black‐Scholes formula. We present the result of our analysis of 150 years of team data via the Lahman package in R, and also provide dynamic models for an evolving measure of the Pythagorean exponent. This includes suggestions for modeling credit default as well as contract valuation in sports via macro variables in connection with historically implied parameters.

Investigating Asymmetric Relationship between Financial Development and Global Competitiveness in Developed and Developing Countries

Globalization led to economic integration, which increased the competitiveness of economies through interconnection and interdependence. Financial Development (FD) is considered as an engine of Economic Growth (EG) that significantly contributes in economic productivity and raising prosperity in an economy. This study aims to analyze the relationship between FD and global competitiveness from a global perspective. For this purpose, panel data of 87 developed and 60 developing countries have been used for the period 2000- 2020. The Panel Quantile Regression (PQR) estimation technique has been used for the analysis. The results demonstrate that sustainable FD significantly increases the competitiveness of all countries. However, this impact is non-linear across different quantile groups which suggests evidence of an inverted U-shaped relationship. The linearized marginal effect indicates that all developed economies lie before the maturity of the inverted U-shaped curve. In contrast, except Bolivia, Cabo Verde, Egypt, India, Indonesia, Korea Rep of, Lebanon, Mongolia, Morocco, Nigeria, Pakistan, Philippines, Siri Lanka, Tunisia, and Vietnam, all remaining developing nations also lie before the maturity of an inverted U-shaped curve. This indicates that FD accelerates global competitiveness up to a certain optimal point, and excessive financialization may lead to the misallocation of resources and raising financial risk. The study suggests that developing countries need to implement policies to attain optimal level of sustainable FD, which boosts their competitiveness. The major contribution of the present study is to help the policy makers to formulate proper policies to increase global competitiveness.

Evaluating Model-assisted Estimators: A Comparative Study in High-dimensional Survey Data

Model-assisted estimators have gained significant attention due to their ability to efficiently utilize auxiliary information during the estimation process. These estimators rely on a working model that links the survey variable to the auxiliary variables, which is then fitted to the sample data to generate predictions. These predictions are subsequently integrated into the estimation procedures. In this study, were explores various model-assisted estimators including Generalized Regression (GREG), Ridge regression, Lasso regression, CART (Classification and Regression Tree), Random Forest, Cubist and Principal Components Regression (PCR) estimator. The analysis involved 2,000 samples of size 50 (n/N ≈ 10%) and employed a stepwise variable selection method to determine the most significant auxiliary variables, incrementally adding them to the model. The performance of these estimators was assessed using relative bias (RB), relative root mean square error (RRMSE) and relative efficiency (RE). Our findings reveal that tree-based models like CART and Random Forest and penalized regression estimators such as Ridge and Lasso display robustness with increased number of auxiliary variables. Among all the estimators, Random Forest consistently yielded the lowest RRMSE, particularly with five auxiliary variables, demonstrating superior efficiency. Conversely, the GREG estimator exhibited poor performance as the number of auxiliary variables increased. This study underscores the importance of selecting suitable model-assisted estimation procedures tailored to the data characteristics and the relationship between survey and auxiliary variables within this high-dimensional dataset.

New Techniques for Estimating Finite Population Variance Using Ranks of Auxiliary Variable in Two-Stage Sampling

This article presents a new set of estimators designed to estimate the finite population variance of a study variable in two-phase sampling. These estimators utilize the information about extreme values and ranks of an auxiliary variable. Through a first-order approximation, we investigate the properties of these estimators, including biases and mean squared errors (MSEs). Furthermore, a comprehensive simulation study is conducted to assess their performance and validate our theoretical insights. Results demonstrate that our proposed class of estimators performs better in terms of percent relative efficiency (PRE) across various simulation scenarios compared to existing estimators. In addition, in the application section, we utilize three data sets to further validate the performance of our proposed estimators against conventional unbiased variance estimators, ratio and regression estimators, as well as other existing methods.

Toilet construction under the Swachh Bharat Mission and infant mortality in India

Improvement of water and sanitation conditions may reduce infant mortality, particularly in countries like India where open defecation is highly prevalent. We conducted a quasi-experimental study to investigate the association between the Swachh Bharat Mission (SBM)—a national sanitation program initiated in 2014—and infant (IMR) and under five mortality rates (U5MR) in India. We analyzed data from thirty-five Indian states and 640 districts spanning 10 years (2011–2020), with IMR and U5MR per thousand live births as the outcomes. Our main exposure was the district-level annual percentage of households that received a constructed toilet under SBM. We mapped changes in IMR and U5MR and toilet access at the district level over time. We fit two-way fixed effects regression models controlling for sociodemographic, wealth, and healthcare-related confounders at the district-level to estimate the association between toilets constructed and child mortality. Toilet access and child mortality have a historically robust inverse association in India. Toilets constructed increased dramatically across India following the implementation of SBM in 2014. Results from panel data regression models show that districts with > 30% toilets constructed under SBM corresponds with 5.3 lower IMR (p < 0.05), and 6.8 lower U5MR (p < 0.05). Placebo, falsification tests and robustness checks support our main findings. The post-SBM period in India exhibited accelerated reductions in infant and child mortality compared to the pre-SBM years. Based on our regression estimates, the provision of toilets at-scale may have contributed to averting approximately 60,000–70,000 infant deaths annually. Our findings show that the implementation of transformative sanitation programs can deliver population health benefits in low- and middle-income countries.

Inequality in Public Provision of Healthcare: Do Fiscal Transfers Matter?

ABSTRACTIn this paper, we investigate the inequality in the public provision of healthcare in India and assess whether states are converging over time. We locate the equalization of public provision within the framework of fiscal federalism. Departing from previous work, we gauge disparity in public provision by scrutinizing the provision in terms of primary and community health centers. The and convergence analysis indicate no substantial reduction in inter‐state disparities, raising concerns regarding the attainment of universal healthcare access. In addition, the club convergence analysis identifies states converging into multiple clubs in the public provision of health centers, indicating the persistence of inter‐state disparity. The panel regression estimates indicate the prominence of own revenue over fiscal transfers in determining the public provision of healthcare. The findings underscore the necessity of reforms in fiscal devolution, with a particular emphasis on tax devolution and revamping sector‐specific grants to achieve national targets. The present paper contributes to a long‐standing debate on unconditional versus conditional transfers for public provision.

Financial Technology (Fintech) as a Driver for Poverty Reduction in Nigeria

ABSTRACT: The human race has been confronting the issue of poverty which is threatening its continued existence for a long time. Poor access to finance can lead to poverty this breeds health issues, lack of access to social and recreational facilities, social delinquencies, reduced living standard, malnutrition and economic difficulties. The goal of defeating poverty in its various ramification remains a cardinal concern for policy formulators in the Nigerian state and international bodies such as the World Bank and United Nations. Following the thriving emergence of financial technology (fintech) in Nigeria, there exist a dearth in academic researches to examine how fintech can be a driver in the reduction of poverty. This study examined the impact of financial technology on poverty reduction in Nigeria. Data on poverty rate, financial technology, mortality rate, literacy rate and gross domestic products were obtained from the National Bureau of Statistics (NBS) in Nigeria and the Central Bank of Nigeria (CBN) statistical bulletin for the period of 1991 – 2021. This study employed the multiple linear regression estimation technique to analyse collected data as it examines a cross-section of major key independent variables across a time series data, on the premise of a common effect model. Data analysed indicates a negative and significant nexus between poverty rate and financial technology innovation. The result also suggest that literacy rate and poverty rate have a negative and insignificant relationship. The poverty rate was also found to be positively and insignificantly related to mortality rate and gross domestic products respectively. The study findings have several significant policy implications. Firstly, infrastructures that support internet and mobile telephony should be expanded by providing incentives for investment since technology is the backbone of the operations of fintech. Secondly, education on fintech, information communication technology and finance should be increased to fill the gap among citizens who are not technological inclined especially in the rural areas to increase the use of fintech. Lastly, there should be further regulatory interventions through reforms to remove the barriers to credit.

Mortality (Dis)Similarities in the Context of Demographic Aging: The Countries of Ex-Yugoslavia

Generally, mortality declines at all ages, with varying intensities, as a result of heterogeneous factors affecting human lifespan. This paper considers switching regression estimation for six ex-Yugoslavian countries with the specification of a time-varying transition probability model of crude death rate. A two-state Markov switching means VAR estimates are used in which the mean growth rate of crude death rate is subject to regime switching, where the errors follow a constant transition probability. The UN data were employed consisting of the crude mortality rate series containing the log difference of yearly crude mortality rate in the six countries of ex-Yugoslavia for 1990–2021. The results show that the estimates of coefficients on the intercept in the mean equation both differ from zero in Bosnia &amp; Herzegovina, Serbia, Montenegro, and Slovenia and are with opposite and statistically significant signs only for Montenegro and Slovenia. The transition probability summaries show a higher probability of remaining in the first high regime state for Macedonia, Serbia, and Bosnia &amp; Herzegovina (0.96, 0.94, and 0.87, respectively). The higher probability of remaining in the second low-medium regime state was found in Slovenia, Croatia, and Montenegro (0.96, 0.87, and 0.56, respectively). The appropriate expected durations in the first regime are approximately 26.41, 16.19, and 7.78 years for Macedonia, Serbia, and Bosnia &amp; Herzegovina, and 28.30, 7.80, and 2.28 years were the corresponding expected durations in the second regime for Slovenia, Croatia, and Montenegro.

The Role of Financial Constraints in Shaping Non-Financial Firm Performance in Nigeria: Evidence from the KZ Index

This study examines the impact of financial constraints on the performance of non-financial firms in Nigeria, utilizing the KZ index as a measure of financial constraint. Employing a static panel regression estimation on a sample of 87 non-financial companies listed on the Nigerian Stock Exchange from 2016 to 2021, the study investigates the relationship between financial constraints and firm performance. The findings reveal that financial constraints significantly hinder firm performance, highlighting the importance of effective governance and access to external financing. The study contributes to the literature by providing insights into the financial challenges faced by non-financial firms in Nigeria and offers recommendations for policymakers and practitioners to improve corporate performance.

Green investments and inclusive growth: The case of the BRICS economies

Investments in green energy projects are highly critical to promoting climate transition and sustainable development. This objective motivates the investigation of the effect of green investments on inclusive growth. We develop an endogenous inclusive growth model that illustrates the channel through which private and public investments in green investments contribute to inclusive growth. By employing a dataset of the BRICS economies from 1990 to 2019, we fit both linear fixed-effects and fixed-effects threshold regression, the latter of which exhibits better prediction of green investment effects. Accordingly, the threshold regression estimates reveal that higher thresholds of green investments substantially accelerate inclusive growth in the BRICS economies. Furthermore, by controlling for the threshold role of financial sector development, we document the heterogeneous effects of green investments on inclusive growth. Unlike financial institutions’ development thresholds, a higher level of overall financial development and financial market development strengthens the positive role of green investments. Our findings offer impeccable policy actions to the governments and policymakers of the BRICS economies on pathways to promote green energy investments for sustainable development.