Are larger countries really more corrupt?

Several authors claim to provide evidence that government corruption is less severe in small than in large countries. The authors demonstrate that this relationship is an artifact of sample selection. Most corruption indicators provide ratings only for the countries in which multi-national investors have the greatest interest. These tend to include almost all large nations but, among small nations, only those that are well governed. The authors find that the relationship between corruption and country size disappears when one uses either a new corruption indicator with substantially increased country coverage or an alternative corruption indicator that covers all World Bank borrowers without regard to country size. They also show that the relationship between corruption and trade intensity--a variable strongly related to population--disappears when samples less subject to selection bias are used.National Governance,Governance Indicators,Corruption&Anitcorruption Law,Public Sector Corruption&Anticorruption Measures,Poverty Monitoring&Analysis

Which incentives work? An experimental analysis of incentives for trainers

One conjecture in the theory of incentives is that incentives based on broader outcomes may be better at motivating agents than incentives based on narrow measures. We designed an experiment to test these hypotheses using a ""prospective randomized evaluation procedure"" (PREP). We then apply PREP to training programs as typically funded by donors of economic development assistance. We randomly assigned 274 participating entrepreneurs in the Philippines to one of 26, simultaneous, one-day, training classes in marketing. Trainers were given cash incentives based on the average score of their ""students"" on a standardized test containing an alternative number of questions, which were randomly assigned to each class. We then examined outcomes based on student satisfaction ratings of the trainer. Our results suggest that incentives based on broad outcomes are more effective than incentives based on narrow outcomes. We conclude with ways to improve our approach as well as with a discussion of the implications for using prospective randomized evaluation for improving the evaluation of donor projects.randomized trials, project evaluation, teacher incentives, aid effectiveness

Gender and Corruption

Using several independent data sets, we investigate the relationship between gender and corruption. We show using micro data that women are less involved in bribery, and are less likely to condone bribe taking. Cross-country data show that corruption is less severe where women hold a larger share of parliamentary seats and senior positions in the government bureaucracy, and comprise a larger share of the labor force.Corruption; Gender; Public policy

The New Institutional Economics Approach to Economic Development: A Discussion of Social, Political, Legal, and Economic Institutions

The last 50 years of development economics have seen hopes for global development raised high and dashed time and again. While there has been positive, sometimes even impressive, growth in many countries, in most of the world experience has not matched expectations. The accumulation of physical capital and human capital, liberalisation and privatisation have all been proposed as the elixirs of growth. While all these arguments have some merit, by themselves they are incomplete solutions to the problem of development. The disappointing performance of the post-Communist transition, the slow growth of the 1970s and 80s in Africa and Latin America, and the Asian financial crisis of the 1990s were all rooted in poor governance. Good governance involves aligning the incentives of agents with the interests of principals in both economic and political spheres. This paper describes some insights from New Institutional Economics on how best to design these incentives

DECENTRALIZATION IN UGANDA

The theory of fiscal federalism provides several reasons to expect better public service delivery if government is decentralized. Demand for public services is expected to vary across jurisdictions, and local government officials are expected to match supply of public services with demand more effectively than if public services were centrally provided. Households are expected to have higher participation rates in elections and to vote for better reasons (the candidates' experience, agenda or political affiliation, rather than bribery or the candidates' race, religion etc.) at the local level, and to have better access to information about local affairs than about national politics. Finally, mobility across jurisdictions is expected to induce local governments to be more efficient. We review the decentralization process in Uganda and provide evidence on all these mechanisms. There turns out to be little support for the relevance of these hypotheses to Uganda

Knowledge, attitude and practice about leptospirosis prevention among town service workers in northeastern Malaysia: a cross sectional study

Introduction. Many efforts have been done to reduce leptospirosis infections in Malaysia especially among high risk groups including town service workers. Town service workers are more likely to be exposed to the leptospiral infection resulting from their occupational activities.Methods. A cross sectional study was conducted in northeastern Malaysia involving 321 town service workers who were subjected to answer an interviewer-guided validated questionnaire which consists of sociodemographic, knowledge, attitude and practice information. Data were entered and analyzed using SPSS Version 20.Results. All of the respondents were Malay with mean (SD) age of 40.6 (10.28) years old. The mean (SD) duration of employment was 12.1 (9.62) years. Fifty four respondents (16.8%) had never heard of leptospirosis. Among the respondents, 215 (67.0%) of them had poor knowledge on leptospirosis. Meanwhile, 167 (52.0%) and only 128 (39.9%) of them had satisfactory attitude and practice respectively. It was found that knowledge on risk factors for leptospirosis was lacking. There were high risk attitudes such as drinking habit and protective equipment used during working with the favourable answers ranged from 67.3% to 89.1%. The weakest area identified in their practice was also on the use of protective equipment.Conclusions. The workers’ level of knowledge and practice were relatively poor despite an overall good practice on leptospirosis. This finding might expose them to an increased risk of contracting leptospirosis. Identified weak areas in their knowledge, attitude and practice will assist the policy makers to develop a focused and well-directed intervention program on leptospirosis infection. 

Evaluating AI performance in infectious disease education: a comparative analysis of ChatGPT, Google Bard, Perplexity AI, Microsoft Copilot, and Meta AI

BackgroundThis study systematically evaluates and compares the performance of ChatGPT 3. 5, Google Bard (Gemini), Perplexity AI, Microsoft Copilot, and Meta AI in responding to infectious disease-related multiple-choice questions (MCQs).MethodsA systematic comparative study was conducted using 20 infectious disease case studies sourced from Infectious Diseases: A Case Study Approach by Jonathan C. Cho. Each case study included 7–10 MCQs, resulting in a total of 160 questions. AI platforms were provided with standardized prompts containing the case study text and MCQs without additional context. Their responses were evaluated against a reference answer key from the textbook. Accuracy was measured by the percentage of correct responses, and consistency was assessed by submitting identical prompts 24 h apart.ResultsChatGPT 3.5 achieved the highest numerical accuracy (65.6%), followed by Perplexity AI (63.2%), Microsoft Copilot (60.9%), Meta AI (60.8%), and Google Bard (58.8%). AI models performed best in symptom identification (76.5%) and worst in therapy-related questions (57.1%). ChatGPT 3.5 demonstrated strong diagnostic accuracy (79.1%) but had a significant drop in antimicrobial treatment recommendations (56.6%). Google Bard performed inconsistently in microorganism identification (61.9%) and preventive therapy (62.5%). Microsoft Copilot exhibited the most stable responses across repeated testing, while ChatGPT 3.5 showed a 7.5% accuracy decline. Perplexity AI and Meta AI struggled with individualized treatment recommendations, showing variability in drug selection and dosing adjustments. AI-generated responses were found to change over time, with some models giving different antimicrobial recommendations for the same case scenario upon repeated testing.ConclusionAI platforms offer potential in infectious disease education but demonstrate limitations in pharmacotherapy decision-making, particularly in antimicrobial selection and dosing accuracy. ChatGPT 3.5 performed best but lacked response stability, while Microsoft Copilot showed greater consistency but lacked nuanced therapeutic reasoning. Further research is needed to improve AI-driven decision support systems for medical education and clinical applications through clinical trials, evaluation of real-world patient data, and assessment of long-term stability