Second Stage Of Analysis Research Articles

Comparing the Effects of Information Globalization on Agricultural Producer Prices in Developing and Developed Countries

Existing studies claim that the Internet of Things (IoTs) raises agricultural producer prices while others claim the contrary. Meanwhile, no studies have been conducted to investigate the impact of IoTs at the macro level, as represented by information globalization. The main objective of this study is to determine the impact of information globalization on agricultural producer prices in developing and developed countries. This study used time series data from 1991 to 2020 and cross-section data from 66 developing and 26 developed countries. The data was analyzed using two-stage least squares. The first stage of analysis shows that pesticides and farm machinery increase agricultural production in developing and developed countries, while employment in agriculture, forestry, and fishing has the opposite effect. Meanwhile, nutrient nitrogen, manure, and irrigation have differing effects on agricultural production in the two areas. The second stage of analysis shows that agricultural producer prices in developing and developed countries will rise when agricultural production, agricultural import, and human capital increase. Agricultural value-added, food consumer price inflation and population growth have varying impacts on agricultural producer prices. Meanwhile, the main variable investigated in this study, information globalization, has been proven to increase agricultural producer prices in both developing and developed countries.

문화예술부문에 대한 재정지출이 온실가스배출에 미치는 영향분석

As the culture and arts sector develops alongside economic growth, the increase in greenhouse gas emissions highlights the importance of environmental considerations in the context of climate change. This study employs a two-step estimation method using a dynamic panel model to analyze the impact of fiscal expenditure for the culture and arts sector on greenhouse gas emissions, distinguishing between direct and indirect effects. The first-stage analysis reveals that increased fiscal expenditure in the culture and arts sector positively impacts regional economic growth. The second-stage analysis indicates the presence of an inverted U-shaped curve between per-capita GRDP and greenhouse gas emissions, supporting the Environmental Kuznets Curve hypothesis. While fiscal expenditure for the culture and arts sector directly increases greenhouse gas emissions, it indirectly reduces them through regional economic growth. However, the direct effect is greater and more significant than the indirect effect, resulting in a net increase in greenhouse gas emissions. These findings suggest that for effective greenhouse gas reduction policies at the local government level, it is necessary to improve energy efficiency in cultural and artistic activities and promote the use of eco-friendly energy sources. Additionally, there is a need for support that can raise environmental awareness among cultural and artistic professionals and induce changes in their energy consumption patterns.

Impact of Islamicity on the productivity of conventional and Islamic banks in selected southeast Asian countries

This study provides a new understanding of how bank-specific characteristics, the macroeconomic environment, and Islamicity affect the productivity of conventional banks (CBs) and Islamic banks (IBs) in selected Southeast Asian countries. The data of 153 banks, collected between 2015 and 2020, were used, and the influence of the selected factors was investigated by using panel data approaches, as well as the data envelopment analysis-based Malmquist productivity index (DEA-MPI). In the first-stage analysis, bank productivity was measured by using total factor productivity changes (TFPC), and in the second-stage analysis, panel regression analysis was performed, specifically, multiple panel regression analysis, which employed pooled ordinary least squares, a fixed-effects model, and a random-effects model. Parametric and nonparametric (Mann–Whitney and Kruskall–Wallis) tests found that the IBs were more progressive than the CBs. The findings indicated that unlike the IBs, change in the productivity of the CBs was adversely affected by economic Islamicity, as well as legal and governance Islamicity, which indicated that macroeconomic and legal structures that leaned toward Islamic values adversely affected the CBs. Meanwhile, the IBs were likely to be structured in line with such values and thus can mitigate the adverse impact of various factors. Both groups were negatively affected by human and political rights Islamicity, which indicated the use of a setup that could not benefit from Islamic values. This finding lends credence to the arguments in the literature that IBs mirror CBs in practice to remain competitive in their pricing based on market principles. The IBs were found to benefit from international relations Islamicity, which bodes well for the competitiveness of new players against the ancient setup of CBs in the globalized world.

Two-stage super-efficiency model for measuring efficiency of education in South-East Asia

AbstractThis paper aims to measure the efficiency of schools in six South-East Asian countries, taking into account the impacts of information and communication technologies (ICT). The educational institutions of South-East Asia are very dynamic; and to increase their competitiveness at international level, they need to manage their resources in an efficient way. We propose a two-stage super-efficiency model for measuring their efficiency, using 2018 PISA data. In the first stage, the non-parametric data envelopment analysis super-efficiency model is used to rank the schools in this region. Then, a second-stage analysis based on a bootstrapped quantile regression is performed to identify the factors that potentially influence efficiency. We analyze four different scenarios depending on the output considered. In the first stage of the analysis, Singapore has the best performance among the other countries in all scenarios. In the second stage, our results show that ICT is statistically significant as a determinant of efficiency in terms of the ratio of computers connected to the internet. However, the integration of ICT in education is mainly influenced by the socio-economic and educational factors of the analyzed countries. Moreover, concerning the other factors, the lower efficiency schools benefit more from the number of female students than higher efficiency schools. The reverse happens for the proportion of certified teachers.

Analysing the impact of digital technology diffusion on the efficiency and convergence process of the commercial banking industry of Pakistan

In a dynamic financial ecosystem, digitalisation is supporting banks in revamping their business processes to be more efficient, reducing costs, coping with customers’ evolving demands, and keeping them abreast of market competition. This two-stage research aims to investigate three issues in Pakistan’s banking industry from 2006 to 2020: (i) banking efficiency; (ii) the impact of digitalisation on banking efficiency; and (iii) banking efficiency’s absolute and conditional convergence. In our first-stage analysis, bootstrap data envelopment analysis has been applied, which exhibits bias-corrected overall, pure, and scale efficiencies of 74, 77, and 96%, respectively. In the second-stage analysis, we executed Tobit and two-step dynamic panel data system generalised method of moments (DPDSYS-GMM) models, and the results uncover that digitalisation has a positive influence on banking efficiency. Findings confirm that return on assets, bank size, interest rate, and gross domestic product growth rate have a positive association with banking efficiency. Our research reveals that state-controlled banks outperform their private sector and special-purpose counterparts. Our DPDSYS-GMM findings validate β and σ-convergence, implying that initially, low-efficient banks caught up (converged) to the more efficient opponents, reducing cross-sectional efficiency dispersion and attaining common equilibrium. The findings of banking efficiency conditional β-convergence assert that the adoption of digital technology has played a critical role in the convergence process and that digitalisation has acted as a catalyst for less efficient banks to catch up significantly faster to their more efficient rivals. This study displays digitalisation’s disruptive influence on the overall transformation of Pakistan’s banking system in the modern era, resulting in significant efficiency gains.

Efficiency variations of integrated urban transit stations before and during the COVID-19 pandemic: Insights from a Mega-City without pandemic lockdown measures

The COVID-19 pandemic ushered in unforeseen consequences for urban public transportation systems, raising concerns about their efficiency in cities during pandemics. Using a two-stage bootstrapped Data Envelopment Analysis with a regression approach, this study investigates the changes in integrated transit station efficiency/performance before and during the COVID-19 pandemic in Seoul, South Korea, presenting a unique case study due to its mega city status and absence of a complete lockdown during the pandemic. Besides, it explores the shifting impacts of external environmental factors on station efficiency from 2019 to 2021. Findings from the first-stage analysis underscore a gradual decline in station efficiency, with a pronounced impact evident in 2021. Examining land-uses around the stations revealed that the presence of eateries and hotels in station catchment areas corresponded to enhanced performance. Interestingly, high performing stations with high ridership during the pandemic had low station areas and operating costs. The second-stage analysis pinpointed influential environmental factors, notably young pedestrian volume, which exerted varying influence on station efficiency across different periods. Vehicular accidents and rainfall in the vicinity of transit station catchment areas were consistently positively associated with station efficiency, irrespective of the study year. These findings carry substantial implications and insights for urban planners worldwide.

Get the balance right: lessons from UK higher education in managing environmental and economic performance

ABSTRACT Since 2008, there have been a growing number of social policies placed on UK higher education institutions (HEIs) to engage in reducing carbon emissions and meet self-imposed carbon reduction targets while producing graduates, publishing research papers and attracting research income. HEI managers thus face the challenging task of having to determine the optimal level between environmental performance and economic performance – from activities that generate income, to which we refer as overall efficiency. To that end, the current study measures the overall efficiency levels of UK HEIs from 2012/13 to 2018/19 using a slacks-based measure model that incorporates bad outputs. The study aims to determine the extent to which the optimal balance between environmental performance and economic performance has been achieved as evidenced by the efficiency of HEIs over the course of the sample period. The study also identifies factors associated with efficiency and provides policy recommendations. Over the study period, overall efficiency (incorporating the bad output of carbon emissions) initially fell and then rose in the last 2 years suggesting some optimism that carbon emissions management has improved since then. The second-stage analysis, which identifies factors associated with efficiency, suggests that the ratio of students to staff and HEIs in the Russell group is positively associated with the efficiency of inefficient HEIs. When both efficient and inefficient universities are considered, having an environmental management system is positively associated with efficiency, while the opposite is the case for having science, engineering and medicine disciplines and having carbon reduction targets.

Organizational Citizenship Behavior Scale for Knowledge Workers: Empirical Evidence and New Validations

In order to analyze the empirical instabilities and adopt new validation procedures for the Organizational Citizenship Behavior—Knowledge Workers (OCB-KW) Scale this study was organized in two stages. In the first stage, studies were read for a general characterization of the production of works that used the OCB-KW and from these data, it was possible to characterize applications of the scale and assess their possible instabilities. In the second stage of analysis, a secondary database was used and subjected to the parallel analysis, and then to the exploratory factor analysis for the initial estimation and validation of the constructs, and in a third moment, the confirmatory estimation of the constructs and the comparison of different models. From the comparison indices between models, it can be concluded that the best structure for the Organizational Citizenship Behavior—Knowledge Workers Scale is built from five dimensions correlated with each other.

Gender asymmetries of the category “appearance” in the English language (based on the analysis of attributive-nominal word combinations with the core lexemes “man” and “woman”)

The relevance of this article is determined by the increasing interest in the asymmetries of gender-sensitive categories like “appearance” or “beauty”. The history of the issue and detailed results of contemporary studies in this field have been outlined in the article. The category of appearance has long been considered gender-biased and asymmetric, being related more to women than to men. Present-day studies offer support for the idea that notions of appearance and beauty are unevenly linked to women, resulting in a multitude of societal and individual difficulties. Certain modern linguists even argue that the concept of beauty is employed as a narrative to perpetuate women’s feelings of discontent and self-criticism. Our work presents an attempt to measure the relevance of this supposition against practical data of the semantic analysis of collocations with the core lexemes “man” and “woman”. A total of 2,814 noun phrases relevant to the category of appearance have been extracted from the texts of the British National Corpus of the English language. Three subcategories have been distinguished in the process of continuous sampling: parametric characteristics of appearance, general characteristics, and assessments. The method of comparative analysis allowed us to make conclusions regarding the degree of validity of assumptions about the asymmetry of the category of appearance in the English language. The analysis was carried out in two stages: the first stage required a general comparison of the amount and semantic nature of attribute-nominal word combinations with the core lexemes “man” and “woman”. The second stage of analysis was based on connotational analysis of nominal constructions semantics in the context of positive and negative characteristics of females’ and males’ appearance. The summary data of the study allowed us to present reliable evidence-based conclusions about the objective characteristics of the category of appearance. The study questions the widespread belief that the category of appearance is gender-biased and suggests considering it as a significant androgenic characteristic relevant to both men and women.

Effects of socioeconomic status and greenspace on respiratory emergency department visits under short-term temperature variations: An age-stratified case time-series study

IntroductionNeighborhood socioeconomic status (SES) and greenspace can affect respiratory health. However, it is unclear whether effects of neighborhood SES and greenspace on respiratory health still exist regardless of temperature variations. MethodsThis paper conducted a two-stage, age-stratified case time-series study. The first goal is to examine the associations between two temperature metrics (daily mean temperature [DMT] and diurnal temperature range [DTR]) and respiratory emergency department (ED) visits among four age groups in New York City. The second goal is to evaluate whether neighborhood SES and greenspace would be determinants of respiratory ED visits independent from temperature varying factors. A distributed lag nonlinear model was applied on ED data from 135 zip codes (October 2016 - February 2020). ResultsOur first-stage analysis indicated that older adults aged 65+ had higher risk of ED visits (RR=2.78, 95% eCI: 2.41, 3.22; with 7 days of lag) on days with low DMT (-10°C), followed by adults aged 18-64 (RR=2.48, 95% eCI: 2.32, 2.65), children and youth aged 5-17 (RR=1.38, 95% eCI: 1.24, 1.53), and young children aged 0-4 (RR=1.04, 95% eCI: 0.96, 1.13). However, no excess respiratory ED visits were observed on days with high DMT (30°C). Higher DTR was associated with higher risk, with children and youth more susceptible when DTR was high (DTR 20°C; RR=5.70, 95% eCI: 3.42, 9.49; with 7 days of lag). The second-stage analysis indicated neighborhood SES and greenspace had significant associations with respiratory ED visits regardless of temperature variations. Specifically, Higher income and greenspace exposure were negatively associated with ED visits among all age groups. ConclusionsNeighborhood SES and greenspace could affect respiratory morbidity regardless of weather conditions. Daily temperature variations accelerated the short-term risk among population subgroups under different weather conditions (e.g., higher risk of days with low DMT among older adults, higher risk of days with high DTR among children and youth aged 5-17), which could create co-effects with neighborhood SES and greenspace on respiratory health.

New Public Management and hospital efficiency: the case of Norwegian public hospital trusts

New Public Management-inspired reforms in the Norwegian hospital sector have introduced several features from the private sector into a predominantly public healthcare system. Since the late 1990s, several reforms have been carried out with the intention of improving the utilization of resources. There is, however, limited knowledge about the long-term, and sector-wide effects of these reforms. In this study, using a panel data set of all public hospital trusts spanning nine years, we provide an analysis of the efficiency of hospital trusts using data envelopment analysis (DEA), as well as a Malmquist productivity index. Thereafter we use the efficiency scores as the dependent variable in a second-stage panel data regression analysis. We show that during the period between 2011 and 2019, on average, efficiency has increased over time. Further, in the second-stage analysis, we show that New Public Management features related to incentivization are associated with the level of hospital efficiency. We find no association between degree of competition and efficiency.

기혼 보육교사의 직무스트레스가 이직의도에 미치는 영향

Objectives The purpose of this study was to investigate effects of job stress on job turnover intention and mediating effects of work-family role conflicts among married childcare teachers.
 Methods To this end, 272 married childcare teachers were tested to measure variables related to turnover intention. The collected data verified the mediating effect through the SPSS 22.0 program.
 Results First, job stress and work-family role conflict of married childcare teachers showed a positive correlation. Second, it was found that job stress of married childcare teachers had a significant effect on turnover intention. Third, when analyzing the mediating effect of work-family role conflict on job stress and turnover intention, the parameters increased when the independent variables increased in the first-stage analysis, and the dependent variables increased in the second-stage analysis. In the three-step analysis, it was found that the input of independent variables and parameters at the same time affects the dependent variable, but the standardization coefficient decreases and has a partial mediating effect.
 Conclusions The purposes of this study were to specify variables related to convergence competency, and to analyze the structural relationships among them. The purposes of this study were to specify variables related to convergence competency, and to analyze the structural relationships among them.

The ‘Healthcare Access and Quality Index’ revisited: A fuzzy data envelopment analysis approach

Nowadays, health systems comprise a series of resources structured to provide healthcare services to meet our health needs. However, premature deaths still occur. To quantify and understand personal healthcare conditions affecting such amenable mortality, the Healthcare Access and Quality Index (HAQI) was put forward, evaluating 195 countries and territories since 1990. Nevertheless, the literature acknowledges a series of limitations of this framework, such as the drawbacks of using principal component analysis to aggregate individual indicators, the absence of control for financing and environmental conditions, and the presence of a substantial degree of data uncertainty. Accordingly, we propose a methodological alternative to the computation of the HAQI using a novel fuzzy Data Envelopment Analysis model to handle the aforementioned shortcomings. We also propose its extension towards the quantification of efficiency (E-HAQI) – in the sense of value for money – by incorporating financial aspects as modelling inputs. This way, we contribute with innovative modelling approaches that can also deal with the high degree of data uncertainty. Furthermore, in a second-stage analysis, the impact of key exogenous factors on healthcare access and quality is assessed via non-parametric hypothesis testing. Our results show positive and significant correlations of both the revisited HAQI and E-HAQI with the original HAQI 2016 dataset. They also reveal a better use of resources by European and Oceanian countries and territories than by Sub-Saharan African ones. Concerning contextual determinants, socio-demographic development, human development, and the type of health system were found to be statistically significant drivers of healthcare access and quality efficiency.

Institutional support and self-efficacy as catalysts for new venture performance: a study of iGen entrepreneurs

PurposeThe success of a young entrepreneur depends on how institutional support can facilitate venture performance. Drawing on the institutional theory, this study posited the role of self-efficacy in supporting the effect of institutional support. Self-efficacy is a driving factor for entrepreneurs in managing and implementing business action confidently and successfully. With macro- and micro-oriented research, this study aims to examine how the micro-level factor that is self-efficacy could mediate the influence of macro-level factors (i.e. institutional governance, cultural and social norms and cognitive structure) toward iGen's new venture performance.Design/methodology/approachA total of 462 respondents representing the population of Malaysian iGen entrepreneurs participated in this study. The samples were selected using a multistage sampling technique (i.e. probability cluster sampling technique and non-probability purposive sampling). Survey items were adapted from the previous studies. Structural equation modelling was used, and the first stage involved testing confirmatory factor analysis (CFA) to test the measurement items' unidimensionality, validity and reliability. The second stage of analysis is to test the mediation model.FindingsThe mediation analysis results confirm that the relationship between institutional governance, cultural and social norms, cognitive structure and new venture performance is mediated by self-efficacy. The results confirm that the relationship between institutional governance and cultural and social norms toward new venture performance is fully mediated by self-efficacy. On the other hand, the relationship between cognitive structure and new venture performance is partially mediated by self-efficacy.Research limitations/implicationsFor future research, it is necessary to consider a wide-ranging sample size in improving research generalisation. Moreover, the cross-sectional study only observes the phenomenon at a certain point and cannot explain the process in the correlational relationship. Future researchers are encouraged to adopt a longitudinal study, which allows the researchers to study a sample throughout a period to draw firm conclusions. Survey data also raise the concern of common method variance (CMV), and future studies may use different data types to solve the problem. In addition, future studies are encouraged to examine other factors that could influence new venture performance.Originality/valueThis study extends the current literature on public policy and entrepreneurship. It comprehensively explains the relationship between institutional governance, cultural and social norms, cognitive structure and self-efficacy toward new venture performance. This study was also conducted in a developing country and iGen context, which can offer new insights into the current literature. Many empirical studies have applied institutional theory in examining entrepreneurship action and behaviour, yet the scholarly consecration on micro-level factors is limited. With macro- and micro-oriented research, this study has examined the influence of self-efficacy as a potential mediating variable.

Incorporating causal modeling into data envelopment analysis for performance evaluation

AbstractThe risk factors in banking have been considered an undesirable carryover variable by the literature. Methodologically, we consider the risk factor using loan loss reserves as a desirable carryover input with dynamic characteristics, which provides a new framework in the dynamic network Data Envelopment Analysis (DEA) modelling. We substantiate our formulation and results using novel techniques for causal modelling to ensure that our dynamic network model admits a causal interpretation. Finally, we empirically examine the impact of risk from various economic sectors on efficiency. Our results show that the inefficiencies were volatile in Chinese banking over the period 2013–2020, and we further find that the state-owned banks experienced the highest levels of inefficiency and volatility. The findings report that credit risk derived from the agricultural sector and the Water Conservancy, Environment and Public Facilities management sector decreases bank efficiency, while credit risk derived from the wholesale and retail sector improves bank efficiency. The results of our innovative causal modelling show that our pioneering modelling on the role of loan loss reserves is valid. In addition, from an empirical perspective, our second-stage analysis regarding the impact of risk derived from different economic sectors on bank efficiency can be applied to other banking systems worldwide because of our successful validation from causal modelling. Our attempt to incorporate causal inference into DEA can be generalized to future studies of using DEA for performance evaluation.

The Development of Efficiency Analysis in Transportation Systems: A Bibliometric and Systematic Review

This paper presents a literature review of efficiency analysis in transportation systems (TS). It builds a bibliometric review of published data-envelopment analysis and, for the first time, stochastic frontier analysis publications in TS. The retrieved publications were separated into five groups: highway/road transportation, air transportation, maritime/port transportation, railway transportation, and urban/bus transportation. The 135 data-envelopment-analysis rail-related publications were surveyed to assess the model used, the second-stage analysis (if any), the input–output variables, the model orientation, return-to-scale assumptions, and their methodological classification. The results show that frontier methods in transportation systems have gained relevance since 2017. Also, gaps in the literature and future directions have been identified in empirical rail research, such as eco-efficiency and safety-related issues, as well as the need for a better investigation of variable choice and scale return assumptions. Finally, this paper proposes a step-by-step methodology for data envelopment analysis in rail systems.

The Saga of Ruchi Soya Industries Limited : Could Credit Risk Models Predict Bankruptcy?

Purpose : The primary objective of this study was to examine the efficacy of credit risk models in predicting bankruptcy and evaluating the firm's post-acquisition performance. Design/Methodology : Ruchi Soya Industries Limited, an Indian listed firm that went into bankruptcy in 2018, was identified for back-testing and evaluating the predictive ability of four models: three accounting-based (Altman Z-score, Altman’s emerging market score, and Zmijewski) and the market-based KMV model. In the second stage of analysis, the operating and financial performance of the company was evaluated for pre-bankruptcy and post-acquisition by Patanjali Foods using t-tests on financial parameters of solvency, profitability, and efficiency. Findings : The findings of this study revealed that while all the models were accurate in predicting default accurately for up to 1 year before bankruptcy, they failed to do so accurately beyond that. The predictive ability of the models was highest for the KMV model, followed by Zmijewski and Altman's Z-score. The performance of the firm improved significantly post-acquisition on profitability and solvency parameters. Practical Implications : According to the findings of this research, credit risk models are accurate at predicting financial trouble and bankruptcy up to 1 year in advance. These findings can be used for credit appraisal by lenders to assess any financial trouble and enable effective risk management. These models can also be used to avoid business failure to develop proactive and preventive financial and managerial decisions. The impact on performance parameters post-acquisition can help consultants and advisors evaluate the restructuring process to see whether there has been value creation post-restructuring.

Automatic Interpretation of Oil and Gas Well Cement Evaluation Logs Using Fuzzy Convolutional Neural Networks

Summary Cementing, as a common operation in well drilling and completions, requires accurate calculations and feasible studies. High-quality well cementing is necessary to achieve objectives and to prevent accidents and damage. The correct levels of cementation and cementation of good quality must be achieved, and thus both of these must be accurately evaluated. Cement bond quality can be assessed in various methods, for instance, the use of acoustic equipment. Acoustic readings can be processed to generate graphics of the cement status. These images are inspected by experts who assess the cement bonding visually, providing qualitative estimates of their quality. Regarding the explanations, industry needs automatic, fast, and intelligent methods. In this study, the performance of neural networks for automatic interpretation was evaluated and combined with fuzzy systems. We present a convolutional neural network (CNN) to address these challenges. The data were extracted from the oilwell logs of District 1 of Ahvaz, sampled by the National Iranian South Oil Company (NISOC), and were divided into three classes of cementing bond quality—namely, good, midrate, and bad. Each class contained 1 m data entries. The input to the CNN comprised images of sampled variable density logs (VDLs). In the second stage of analysis, the weights of the learned networks were optimized and replaced with a Bees algorithm (BA) and a fuzzy system (fuzzy-CNN). The estimated efficiency of the CNN to classify the well cement quality and fuzzy-CNN was 80.15 and 83.62%, respectively. The study provides insight into the efficiency and outputs of each of the networks studied. Problems encountered in training the networks to operate optimally as an automatic interpretation system were investigated and are discussed.

Efficiency of the Islamic Banking Sector: Evidence from Two-Stage DEA Double Frontiers Analysis

This paper examines the multi-dimensional efficiency of the Islamic banking sector and its determinants, including the impacts of the COVID-19 pandemic. To do that, we use a novel approach of two-stage data envelopment analysis (DEA) double frontiers to evaluate the overall efficiency of 79 Islamic banks across 16 countries (2005–2020). In the first-stage analysis, we found that the Islamic banking sector experienced an increasing trend in its efficiency and performance, even during the recent pandemic, although it varied across banks and countries. Our empirical results of the second-stage analysis further showed that economic development can help countries both withstand the recent pandemic and improve the efficiency and performance of their (Islamic) banking system. This, in turn, could help speed up the recovery process of the global economy. Since there is evidence that the Islamic banking sector is resilient to the COVID-19 pandemic, it is expected that this sector will be a driving force of such recovery.

Estimating the Demand for Groundwater: A Second-stage Hedonic Land Price Analysis for the Lower Mississippi River Alluvial Plain, Arkansas

AbstractWe estimate the benefits of the saturated thickness (water-bearing porous material) of the alluvial aquifer in Arkansas through an application of the hedonic price model to the sale of agricultural land. There is evidence from the first-stage analysis of diminishing returns from increasing saturated thickness. Using a survey of farmer operators’ preferences and socioeconomic characteristics, we recover the underlying demand function for saturated thickness in a second-stage analysis. Shifts in the demand function reveal that produced/social capital can be a substitute or a complement to saturated thickness, and human capital is a substitute for saturated thickness.