Bootstrap Data Envelopment Analysis Research Articles

Technical efficiency analysis of advanced medical centers in Burkina Faso

IntroductionBurkina Faso faces many challenges in the health domain, with no real opportunity for an increase in public health expenditures. In Burkina Faso, as in all low-income countries, health spending efficiency is crucial. The objective of this paper is to assess the efficiency of Advanced Medical Centers (AMCs)—which correspond to district hospitals—in Burkina Faso over the 2017–2020 period and identify the factors that promote—or, on the contrary, limit—the efficiency of these health structures.MethodWe first assessed the efficiency level of the 45 AMCs running in the country between 2017 and 2020 using a bootstrap Data Envelopment Analysis (DEA) methodology. Inputs include the number of doctors, nurses, other medical staff, non-medical staff, and beds, while output variables correspond to the number of inpatients, surgeries, outpatients, and inpatient days. In a second step, determinants of AMC’s efficiency levels were explored using a double-bootstrap procedure. The roles of AMCs’ internal and environmental factors were both considered.ResultsWe found a mean efficiency score of 0.51 over the study period, indicating that AMCs could have almost doubled their healthcare production without needing additional resources. The size, education level, and health status of the covered population and the density of the healthcare supply in the district appeared to be the driving factors of AMCs’ efficiency.ConclusionOur results indicate that improving the efficiency of AMCs should be a high-level priority for the Burkinabe health policy. Resources could be reallocated across AMCs to increase the overall efficiency of the health system.

Evaluation of golfers’ performances in the ladies professional golf association tour based on bootstrapped data envelopment analysis and latent growth curve model

A latent growth curve model and bootstrapped data envelopment analysis were used to examine the performance and changes in professional golfers on the Ladies Professional Golf Association tour. The panel data for both analyses were obtained for the last three seasons (from 2020 to 2022). The dependent variable was the official money list of players, whereas the independent variables consisted of efficiency factors, technical factors (number of birdies, eagles, and hole-in-ones), mental factors (driving and putting accuracies), and career length. Each factor, other than the efficiency factor, was determined by the weighted combination of parenthesized variables using principal component analysis and was measured as two latent variables of the intercept and the slope of the growth pattern for the three seasons. The efficiency factor was measured using data envelopment analysis and its z with the output factors of scoring average and the percentage of rounds in the 60s, and the input factors of driving distance, greens in regulation, number of putts per green hit in regulation, and sand savings. The results confirm the homogeneity in players’ efficiency and prove Penick’s claim that golf performance is dependent on various factors and that golf is psychological.

Assessing Public Water Management Efficiency in North-western Mexico with a Two-stage Bootstrap Data Envelopment Analysis Model

Purpose: Mexico faces severe water availability problems, resulting in higher stress on its distribution in many states. To resolve the increasing water demand, it is essential to evaluate public water management to ensure the success of any decision-making policies to decrease the water pressure in the country. Methodology/Approach: For water management systems, benchmarking their performance relative to others can be an appropriate way to identify possible improvements. Using data from the National Census for drinking water and sanitation in 109 municipalities in the northwest region of Mexico, this analysis aims to evaluate the water management efficiency based on a two-stage Bootstrap Data Envelopment Analysis model with intermediate variables. Findings: The study found average efficiency in water system management but very low efficiency in system improvements. Additionally, no relationship was identified between the two stages or population size and density. Research Limitation/Implication: The study highlights the need for transparent water policies to address the country's shortage. Adjusting municipal public water system management operations and designing future strategic planning is essential. Originality/Value of paper: The presented analysis investigates a relationship between water management and water system improvements.

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.

A double bootstrap data envelopment analysis model with stochastic reducible outputs and expandable inputs: An application to power plants

Clean production of electricity is not only cost-effective but also effective in reducing pollutants. Toward this end, the use of clean fuels is strongly recommended by environmentalists. Benchmarking techniques, especially data envelopment analysis, are an appropriate tool for measuring the relative efficiency of firms with environmental pollutants. In classic data envelopment analysis models, decision-makers are faced with production processes in which reducible inputs are used to produce expandable outputs. In this contribution, we consider production processes when the input and output data are given in stochastic form and some throughputs are reducible and some others are expandable. A stochastic directional distance function model is proposed to calculate the relative technical efficiency of firms. In order to evaluate firm-specific technical efficiency, we apply bootstrap DEA. We first calculate the technical efficiency scores of firms by classic DEA model. Then, the double bootstrap DEA model is applied to determine the impact of explanatory variables on firm efficiency. To demonstrate the applicability of the procedure, we present an empirical application wherein we employ power plants.

Sustainable Governance for Promotional Market Competitiveness in Chinese Airports after COVID-19

Like many countries, China’s airports faced severe operational challenges after the COVID-19 outbreak. However, this predicament has been better mitigated by the Chinese government’s strong support for the aviation industry. However, whether this supportive policy can ensure the sustainable development of the industry needs to be further evaluated. In order to better understand the role of government promotional policies, this paper attempts to explore the driving mechanisms behind the sustainable development performance of Chinese airports. Using the bootstrap Data Envelopment Analysis (DEA) methodology, this study evaluates the operational efficiency of 43 major airports over the period from 2015 to 2022. The efficiency scores are compared with the regional distributions of supply and demand factors, as well as the different sizes based on their annual passenger throughput. The overall operational efficiency showed a fluctuating trend of an initial increase followed by a decline due to COVID-19, with significant regional disparities in airport efficiency. Regional differences are evident, with the eastern region having the highest efficiency value of 0.719, while the central region has the lowest efficiency of 0.594. The findings show that airports in the eastern region perform the best due to the proactive market support with rapidly increasing logistics demand, while airports in the west and northeast regions supported by the strong promotional policies follow closely in terms of operational efficiency. In contrast, airports in the central region are much less efficient due to the lack of market or policy support. To analyze more precisely this conflict on the governance, further analyses show that airport size also has a significant impact on the operational efficiency. Larger airports are typically more efficient, while smaller airports are less efficient, implying the market demand is slightly better to promote the airport operational efficiency than the promotional policies. These findings help us to gain a deeper understanding of the mechanism in the sustainable governance behind the operational efficiency of airports and suggest that more market-oriented appropriate policy direction is required to enhance the competitiveness of the aviation industry. These findings offer valuable insights for policymakers and stakeholders of the developing countries as well, underlining the necessity not for supply-driven policies, but for the demand–pull efforts to optimize resource allocation and adapt to evolving market dynamics.

The impact of public health efficiency on well-being in Italian provinces

PurposeThis work aims to analyse the relationship between public health efficiency and well-being considering a panel of 102 Italian provinces from 2000 to 2016 and evaluates if there are omitted variable biases and endogeneity biases and also evaluates if there are heterogeneous effects among provinces with different income levels.Design/methodology/approachWe use a multi-input and output bootstrap data envelopment analysis to assess public health efficiency. Then, we measure well-being indices using the min-max linear scaling transformation technique. A two-stage least squares model is used to identify the causal effect of improving public health efficiency on well-being to account for time-invariant heterogeneity, omitted variable bias and endogeneity bias.FindingsAfter controlling for important economic factors, the results show a significant effect of an accountable and efficient public health system on well-being. Those effects are concentrated in the North, the most economically, geographically and environmentally advantageous areas.Research limitations/implicationsThe use of the sample mean, probably the oldest and most used method for aggregating the indicators, could be affected by variable compensation, with consequent misleading results in the process of constructing the well-being index. Another limitation is the use of lagged values of the main predictor as an instrument in the instrumental variables setting because it could lead to information loss. Finally, the availability of data over a long period of time.Practical implicationsThe findings could help policymakers adopt measures to strengthen the public health system, encourage private providers and inspire countries worldwide.Social implicationsThese results draw the attention of local authorities, who play an important role in designing and implementing policies to stimulate local public health efficiency, which puts individuals in the conditions of achieving overall well-being in their communities.Originality/valueFor the first time in Italy, a panel of well-being indices was constructed by developing new methodologies based on microeconomic theory. Furthermore, for the first time, the assessment of the relationship between public health efficiency and well-being is carried out using a panel of 102 Italian provinces.

A firm-specific Malmquist productivity index model for stochastic data envelopment analysis: an application to commercial banks

In the data envelopment analysis (DEA) literature, productivity change captured by the Malmquist productivity index, especially in terms of a deterministic environment and stochastic variability in inputs and outputs, has been somewhat ignored. Therefore, this study developed a firm-specific, DEA-based Malmquist index model to examine the efficiency and productivity change of banks in a stochastic environment. First, in order to estimate bank-specific efficiency, we employed a two-stage double bootstrap DEA procedure. Specifically, in the first stage, the technical efficiency scores of banks were calculated by the classic DEA model, while in the second stage, the double bootstrap DEA model was applied to determine the effect of the contextual variables on bank efficiency. Second, we applied a two-stage procedure for measuring productivity change in which the first stage included the estimation of stochastic technical efficiency and the second stage included the regression of the estimated efficiency scores on a set of explanatory variables that influence relative performance. Finally, an empirical investigation of the Iranian banking sector, consisting of 120 bank-year observations of 15 banks from 2014 to 2021, was performed to measure their efficiency and productivity change. Based on the findings, the explanatory variables (i.e., the nonperforming loan ratio and the number of branches) indicated an inverse relationship with stochastic technical efficiency and productivity change. The implication of the findings is that, in order to improve the efficiency and productivity of banks, it is important to optimize these factors.

Triad influence on the detection of crime in Hong Kong.

We use bootstrap data envelopment analysis, adjusting for endogeneity, to examine police efficiency in detecting crime in Hong Kong. We address the following: (i) is there a correlation between the detection of crime and triad influence? (ii) does the level of triad influence affect the efficiency in translating inputs (police strength) into outputs (crime detection)? and (iii) how can the allocation of policing resources be adjusted to improve crime detection? We find that nighty-eight percent of Hong Kong police districts in our sample were found to be inefficient in the detection of crime. Variation was found across districts regarding the detection of violent, property and other crimes. Most inefficiencies and potential improvements in the detection of crime were found in the categories violent and other crimes. We demonstrate how less efficient police districts can modify police resourcing decisions to better detect certain crime types while maintaining current levels of resourcing. Finally, we highlight how the method we outline improves efficiency estimation by adjusting for endogeneity and measuring the conditional efficiency of each district (i.e. the efficiency of crime detection taking the instrumental variables (e.g. influence of triads) into consideration). The use of frontier models to assist in evaluating policing performance can lead to improved efficiency, transparency, and accountability in law enforcement, ultimately resulting in better public safety outcomes and publicly funded resource allocation.

Has the efficiency and productivity of the health system in India improved during post-policy period? Application of the bootstrap data envelopment analysis and Malmquist productivity index

ABSTRACT The efficiency and productivity of the health system are assessed using bootstrap data envelopment analysis and the bootstrap Malmquist productivity index across 21 states of India against the backdrop of the National Health Policy (NHP-2017). We took two child outcomes and three maternal outcomes as outputs and four inputs. A technical efficiency score of 0.760 suggests that the outputs could be increased by 24% without any additional inputs in the health system. A productivity of 0.993 indicates a decline at an average rate of 0.7% per year attributable to technological regress. Deducing from the statistical tests conducted, a significant change in the efficiency of the health system over the years was observed, particularly between the pre- and post-policy periods. In contrast, no significant change in productivity was observed. Despite having relatively better outcomes, Tamil Nadu lies farther away from the frontier, which indicates the inefficient utilization of public health resources. In contrast, Bihar, which has poor health outcomes, has better efficiency and witnessed significant productivity growth, indicating the efficient utilization of limited resources.

Spatiotemporal evolution and mechanisms of tourism efficiency and its decomposition: Evidence from 63 counties in Zhejiang, China.

Although efficiency analysis could reflect the state and quality of tourism's economic development, no research has been conducted investigating the spatiotemporal evolution and mechanisms of county-level tourism efficiency. We quantified tourism efficiency and its decomposition in 63 counties of Zhejiang, employing the bootstrap data envelopment analysis (DEA), hot spot analysis, and quantile regression to explore the spatiotemporal evolution and influencing factors of tourism efficiency, and examine its driving and constraining mechanisms. The results uncovered obvious upward trends in the tourism efficiency of Zhejiang's counties, with the mean value increasing from 0.285 to 0.688. Compared with scale efficiency, the influence of technological efficiency on the growth of comprehensive efficiency increased remarkably. Significant differences were evident in the spatial distributions of the identified hot and cold spots of comprehensive efficiency, which were respectively distributed in northern and southern Zhejiang. The distributions of decomposition efficiency were found to be spatially dependent. The driving mechanism of tourism efficiency involve two driving influences and two constraining influences, including economy and resource driving, market and traffic driving, industry and traffic constraining, and market and industry constraining. The findings of this study contribute to understanding of tourism efficiency growth in regional destinations and provide insights for strategic policymaking in various counties of Zhejiang.

Can the allocation of primary health care system resources affect efficiency? A spatial Dubin model study in China

BackgroundThe primary health care (PHC) system plays an important role in China’s health care system, but there are challenges such as irrational allocation of health resources and inefficient operation, which need to be improved. The purpose of this study was to explore the impact of resource allocation on the efficiency of the PHC system in China.MethodsThe data in 31 provinces were collected from the China Statistical Yearbook 2017–2021 and the China Health Statistical Yearbook 2017–2021. The comprehensive health resource density index (CHRDI) was constructed based on the entropy method and the health resource density index (HRDI), which was used to analyze the allocation of primary health resources in each province. The adjusted efficiency of the PHC system in each province was calculated by the bootstrap data envelopment analysis (DEA). Finally, the spatial Dubin model was used to explore the effect of the CHRDI on efficiency.ResultsFrom 2016 to 2020, the allocation of primary health resources in 31 provinces showed an increasing trend, and the average efficiency after correction showed a decreasing state year by year. The spatial direct effect and spatial spillover effect coefficients of CHRDI were 0.820 and 1.471, which positively affect the efficiency. Per capita Gross Domestic Product (GDP), urbanization rate, and the proportion of the elderly were the factors affecting the efficiency of the PHC system.ConclusionsThe allocation of primary health resources in all provinces in China has improved each year, but there are still great differences, and efficiency must be further improved. Pay attention to the spatial spillover effect of the level of resource allocation and formulate differentiated measures for different regions. Attention should also be paid to the impact of population aging and economic development on the utilization of primary health resources by increasing health needs and choices.

School productive performance and technology gaps: New evidence from PISA 2018

Improving educational outcomes is a global political imperative due to its favourable influence on a country's economic prosperity. Although researchers have endeavoured to gauge school performance through diverse data resources and techniques, there remains a lack of clarity regarding the factors that enhance school effectiveness. Using the latest version of the Programme for International Student Assessment (Pisa, 2018), this paper employs a bootstrapped data envelopment analysis (DEA) to investigate the factors underlying the performance of 8825 schools across 34 OECD countries in terms of their national and international technological capabilities. The central idea is that technological heterogeneity and the technology gap significantly influence the benchmarking process. The findings confirm the presence of substantial technology gaps, indicating that the examined schools are unable to fully harness their potential due to limitations in metatechnology. These gaps are influenced by student characteristics, school features and educational practices.

Efficiency effects of public hospital closures in the context of public hospital reform: a multistep efficiency analysis.

In the wake of hospital reforms introduced in 2011 in Turkey, public hospitals were grouped into associations with joint management and some shared operational and administrative functions, similar in some ways to hospital trusts in the English National Health Service. Reorganization of public hospitals effect hospital and market area characteristics and existence of hospitals. The objective of this study is to examine the effect of closure on competitive hospital performances. Using administrative data from Turkish Public Hospital Statistical Yearbooks for the years 2005 to 2007 and 2014 to 2017, we conducted a three-step efficiency analysis by incorporating data envelopment analysis (DEA) and propensity score matching techniques, followed by a difference-in-differences (DiD) regression. First, we used bootstrapped DEA to calculate the efficiency scores of hospitals that were located near hospitals that had been closed. Second, we used nearest neighbour propensity score matching to form control groups and ensure that any differences between these and the intervention groups could be attributed to being near a hospital that had closed rather than differences in hospital and market area characteristics. Lastly, we employed DiD regression analysis to explore whether being near a closed hospital had an impact on the efficiency of the surviving hospitals while considering the effect of the 2011 hospital reform policies. To shed light on a potential time lag between hospital closure and changes in efficiency, we used various periods for comparison. Our results suggest that the efficiency of public hospitals in Turkey increased in hospitals that were located near hospitals that closed in Turkey from 2011. Hospital closure improves the efficiency of competitive hospitals under hospital market reforms. Future studies may wish to examine the efficiency effects of government and private sector collaboration on competition in the hospital market.

Tourism Efficiency: Bootstrap-Data Envelopment and Tobit Panel Data Analysis

Tourism is an important sector for countries, not only for cultural but also for economic activities. The tourism sector, which operates effectively, contributes to the development of the country's economy. Therefore, the study aims at calculating tourism efficiency and identifying factors that influence it. The study discussed 18 European countries that are among the world's major destination centers. Firstly, tourism efficiency scores were calculated with the data covering the period 2002-2019. Inputs are the number of tourists and tourism expenditures, and output is tourism revenues. Tourism sector efficiency was calculated with the standard Data Envelopment Analysis (DEA) model. Because of the possible statistical limitations of the DEA method, analysis was repeated with the Bootstrap-DEA method. The resulting efficiency scores were used as dependent variables in the Tobit model. The variables including per capita income, digitalization, energy consumption, financial development, political stability, and life expectancy at birth were handled as new trends of tourism efficiency in the Tobit panel data analysis. Boostrap DEA results, which yield more accurate results, gave efficiency results for a smaller number of countries than the efficiency analysis performed with standard DEA. Tobit panel data analysis results showed that income per capita, digitalization, political stability, and life expectancy at birth enhanced tourism efficiency. In the study, unlike the literature, tourism efficiency was not considered at the level of companies, but at the level of countries. In addition to the standard DEA analysis, the Bootstrap DEA method was used, which yielded superior results. Additionally, not only the efficiency values were calculated in the study, but also the factors affecting the tourism efficiency were determined.

Microfinance Institutions’ Efficiency and its Determinants: Evidence from India

This study evaluates the financial and social efficiency of Indian Microfinance Institutions (MFIs) from 2005 to 2018 and also tries to find out the determinants of financial and social efficiency. In the first step, bias-corrected bootstrap Data Envelopment Analysis (DEA) efficiency scores for financial and social efficiency were calculated using two input and two output variables. In the second step of analysis above efficiency scores have been used as dependent variables and Seemingly Unrelated Regression (SUR) model is employed to ascertain the determinants of financial and social efficiency of Indian MFIs. The study finds that the aggregate financial efficiency of Indian MFIs is higher than the social efficiency. Over the study period, efficiency of Indian MFIs shows an increasing trend. Results of SUR suggest that as compared to Non-Banking Finance Company (NBFC) MFIs, Non-NBFC MFIs’ financial and social efficiency is better. Influence of age, scale of loan portfolio, asset quality and financial leverage on efficiency of MFIs are insignificant. This study also finds that asset size of the firm is positively associated with efficiency. Evidence from this study suggests that reform measures taken post microfinance crises has negatively affected the financial efficiency. However, social efficiency has improved during post reform period. JEL Codes: G21, C33

방송통신 관련 기업의 혁신 효율성 제고를 위한 방송통신 정책 및 규제의 영향 분석

In this study we investigate the impact of policy and regulatory system on the efficiency of broadcasting and telecommunication firms using bootstrapping data envelopment analysis and tobit regression. The result of this study shows that the innovation policy of Korean government has negative effect on innovation efficiency of broadcasting and telecommunication firms. And it is necessary to relax the regulation on autonomy of management for broadcasting and telecommunication firms. Furthermore, financial support is most important policy to improve the efficiency of broadcasting and telecommunication firms.

Efficiency of subnational government expenditure towards elementary education and nutrition: Bootstrap data envelopment analysis for India

The need of translating increasing outlays into better outcomes on various public programmes has attracted the attention of researchers worldwide to focus more on the quality of public spending, often assessed in terms of its efficiency. The present article is a contribution to the existing literature on the subject in that it assesses the efficiency of government expenditure of Indian states for two most basic social services—elementary education and nutrition during 2014–2015 and 2018–2019 using data envelopment analysis and Malmquist productivity index techniques, in both input‐oriented as well as output‐oriented settings under variable returns to scale assumption; it constructs the average performance index for children at elementary education and malnutrition index for women and children to utilise them as output indicators; and it adopts a robust bootstrap truncated regression procedure to avoid various econometric issues while estimating the impact of selected environmental factors on bias‐corrected inefficiency scores. The major findings of this article seem to suggest that, while states should be provided greater flexibility in their fiscal operations, they have to complement their fiscal autonomy with good governance to improve the efficiency of their spending on basic social services. Towards this end, states like Bihar, Jharkhand and those belonging to North‐Eastern and Himalayan regions need special attention with a different set of development policies.

The trade-off frontier for ESG and Sharpe ratio: a bootstrapped double-frontier data envelopment analysis

AbstractThe trade-off between the returns and the risks associated with the stocks (i.e., the Sharpe ratio, SR) is an important measure of portfolio optimization. In recent years, the environmental, social, and governance (ESG) has increasingly proven its influence on stocks’ returns, resulting in the evolvement from a two-dimensional (i.e., risks versus returns) into a multi-dimensional setting (e.g., risks versus returns versus ESG). This study is the first to examine this setting in the global energy sector using a (slacks-based measures, SBM) ESG-SR double-frontier double-bootstrap (ESG-SR DFDB) by studying the determinants of the overall ESG-SR efficiency for 334 energy firms from 45 countries in 2019. We show that only around 11% of our sampled firms perform well in the multi-dimensional ESG-SR efficient frontier. The 2019 average (in)efficiency of the global energy sector was 2.273, given an efficient level of 1.000. Besides the differences in the firm’s input/output utilization (regarding their E, S, G, and SR values), we found that the firm- (e.g., market capitalization and board characteristics) and country-level characteristics (e.g., the rule of law) have positive impacts on their ESG-SR performance. Such findings, therefore, are essential not only to the (responsible) investors but also to managers and policymakers in those firms/countries.