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Global drug policy has undergone significant change over the past decade, especially with the advent of the 2016 UN General Assembly Special Session (UNGASS) on drugs. This was a catalyst moment both in highlighting the need for a gender perspective in drug policy, and in initiating a review of the indicators used to evaluate progress in drug policy.

To date, the UN has not adequately tracked gender-specific data in drug policy. This is symptomatic of the lack of focus granted to the specific vulnerabilities and needs of women in the illicit drug trade. This has resulted in a knowledge and understanding gap in relation to the issues faced by women worldwide.

The importance of quantitative and qualitative data and analysis of how and why women are involved in the illicit drug trade, and how this relates to their age, ethnicity, socio-economic status, family situation and history of trauma, violence and mental illness cannot be understated. Without adequate indicators on the underlying factors of their engagement in the trade, the differentiated impacts that both drugs and drug policies have on their lives, and the vulnerabilities they may face, policy makers will be unable to design and implement drug policies that are truly effective.

This chapter provides a historic overview of how data on women has so far been tracked by the UN. The chapter will then look to the future, focussing on opportunities to identify more meaningful indicators within a revised Annual Reports Questionnaire, and also by leveraging the Sustainable Development Goals, UN human rights mechanisms and civil society research.

This study aims to elucidate the dynamics of monetary and fiscal policy interactions in Brazil, focusing on the impacts of positive shocks in government consumption and interest rates. By comparing rational and behavioral agent responses, it clarifies how these frameworks influence gross domestic product (GDP), inflation, private and government consumption and nominal interest rates.

The study employs a new Keynesian dynamic stochastic general equilibrium (DSGE) model with Bayesian estimation from 2000Q1 to 2022Q4, capturing rational and behavioral behaviors with adjustments for Brazilian economic idiosyncrasies. Impulse response functions (IRF) assess the dynamic effects of policy shocks, providing a comparative analysis of the two frameworks.

Behavioral agents show greater initial sensitivity to policy shocks, causing more pronounced fluctuations in GDP, inflation and private consumption compared to rational agents. Over time, the behavioral approach leads to a more robust recovery, while the rational approach results in a quicker return to equilibrium but less pronounced long-term recovery. The study also finds fiscal policy can partially offset the negative impacts of monetary tightening, with a more delayed effect in the behavioral model.

This paper provides insights into the interplay between monetary and fiscal policies under different agent expectations, emphasizing the importance of incorporating behavioral elements into macroeconomic models to better capture policy dynamics in emerging markets.

With the help of a quasi-natural experiment on Chinese policies, this study aims to understand the actual contribution of Smart City (SC) policies to the development of information and communications technology (ICT) in different cities. It also discusses the social and digital differences that such policies may generate, with a particular focus on the potential for exacerbating urban inequalities.

To achieve this, the study employs a principal component analysis (PCA) to develop an ICT development indicator system. It then employs a difference-in-differences (DID) model to analyze panel data from 209 Chinese cities over the period from 2007 to 2019, examining the impact of SC policies on ICT development across various urban settings.

Our findings show that SC policies have significantly contributed to the enhancement of ICT development, especially in ICT usage. However, SC policies may inadvertently reinforce developmental disparities among cities. Compared to less developed areas, the benefits of SC policies are more pronounced in economically booming cities. This is likely due to the agglomeration of the ICT industry and the strong allure of developed urban centers for high-caliber talent.

This study contributes to the related literature by explaining the role of SC policies in driving ICT development and by focusing on the often-overlooked impact of SC policies on urban inequality. These findings can provide guidance to policymakers on the need to recognize and address existing urban inequalities.

The purpose of this study is to investigate the interplay between fiscal dominance and monetary policy in South Africa from 1960 to 2023.

The study employs a structural vector autoregression (SVAR) medel to analyze the relationship between fiscal dominance and monetary policy. Short-term and long-term shocks of government borrowing and deficits are examined to understand their impact on inflation dynamics.

Fiscal dominance has a significant effect both in the short and long run. There is evidence that government debt and deficits increase inflation, overriding the effects of monetary policy aimed at maintaining price stability. On the other hand, the study reveals that money supply shocks have a greater effect in reducing fiscal dominance compared to interest rate shocks. The variance movement on inflation is significantly explained by government debt and deficits. This emphasizes the persistence of inflationary pressures associated with fiscal dominance, highlighting the importance of effective policy interventions to mitigate inflationary risks.

This study contributes to the existing literature by providing insights into the dynamics of fiscal dominance in South Africa. Moreover, this study extends the theoretical framework of the fiscal theory of the price level (FTPL) and the government budget constraint. This study contributes valuable insights into the dynamics of fiscal dominance in South Africa and offers guidance for policymakers in formulating strategies to safeguard economic stability.

Limiting the use of antibiotics in food animals is a cornerstone of contemporary EU policy. Despite that marketing of antibiotics for growth promotion and nutrition has been banned since 2006, the use is still high and varied. This paper aims to investigate the forces behind the different usage patterns in Italy, with one of the EU’s most extensive use of antibiotics in animals, versus Sweden, with the union’s most restricted use, including how these usage patterns are related to EU and national policies.

The industrial network approach/the 4R resources interaction model is adopted to investigate the major forces behind the different antibiotic usage patterns. Furthermore, the study relies on the notion of three main characteristics related to the use of a resource activated in several user settings (Håkansson and Waluszewski, 2008, pp. 20–22). The paper investigates the Swedish and the Italian using settings, with a minimised, respectively, extensive usage of antibiotics. The study is exploratory in nature and based on qualitative data collected through a combination of primary and secondary sources.

The paper underlines the importance of integrating forces for policy to succeed in attempts to reduce the use of a particular resource. It reveals that Sweden’s radically reduced use was based on great awareness, close interactions between animal-based food producers and policy – and that integrating forces were supported by an era of state-protected food production, with promising ability to distribute the cost of change. The Italian characteristics hindering the integration of forces mounting for reduced use were restricted awareness, top-down business and policy interactions – and a great awareness about the difficulties of distributing the cost of change.

The study deals with the analysis of forces affecting the different usage of antibiotics within two EU settings. The investigation, based on the industrial network approach’s notion of connectivity of economic resources, that is, of exchange having a content and substance beyond discrete transactions, reveals how indirect related contextual forces, neglected by policy, have an important influence on the ability to achieve change, in this case of antibiotics usage patterns.

This study aimed to utilize Epistemic Network Analysis (ENA) for a thorough evaluation of policy documents concerning the digital transformation in Vietnam's higher education sector.

Adopting a quantitative ethnography approach, this research employed ENA to analyse a curated collection of 21 documents that specifically addressed higher education (HE) and digital transformation within Vietnam. The study also incorporated qualitative content analysis, utilizing the constant comparison method as outlined by Onwuegbuzie et al. (2009), for data coding. ENA facilitated the examination of connections among various policy aspects.

The study revealed a consistent overarching theme in Vietnam's digital transformation policies during and post-pandemic, focusing on key areas such as ADMINISTRATION, VISION, QUALITY, and INFRASTRUCTURE. However, a temporal shift in emphasis was observed: during the pandemic, policies were more focused on ADMINISTRATION and INFRASTRUCTURE, while post-pandemic, there was an increased emphasis on COLLAB, VISION, and TEACH_LEARN.

This research represents one of the initial efforts to showcase the utility and significance of ENA in analysing policy documents. It underscores ENA's potential in elucidating the complex interplay of policy elements in the context of digital transformation in higher education, particularly within a developing country setting.

As a response to challenges that globalization poses, governments often utilize an expansionary fiscal policy, a mix of increased compensation spending and capital tax cuts. To account for these policy measures that are consistent with neither the compensation nor the efficiency hypothesis, this study examines government fractionalization as the key conditional factor.

We test our hypothesis with a country-year data covering 24 OECD countries from 1980 to 2011. To examine how a single country juggles compensation spending and capital taxation policies jointly, we employ a research strategy that classifies governments into four categories based on their implementation of the two policies and examine the link between imports and fiscal policy choices conditioned on government fractionalization.

This study shows that highly fractionalized governments are more likely to implement an expansionary fiscal policy than marginally fractionalized governments as a policy response to economic globalization and import shock.

Our findings imply that fractionalized governments are likely to face budget deficits and debt crises, as the expansionary fiscal policy persists over time.

By examining government fractionalization as one of the critical factors that constrain the fiscal policy choice, this study enhances our understanding of the relationship between economic globalization and compensation or efficiency policies. The arguments and findings in this study explain why governments utilize the seeming incompatible policy preferences over increased compensation spending and reduced capital tax burdens as a response to globalization, potentially subsuming both hypotheses.

The study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.

The study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.

The F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.

Although the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.

The findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.

The study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.

The study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.

This study intended to bridge this gap by investigating the perspectives of international students regarding Taiwan’s bilingual education policy and its impact on their willingness to enroll in graduate programs in Taiwan. Additionally, the comparisons among international students from diverse backgrounds were examined.

Employing a qualitative research design, the study included nine participants from three countries, with each country contributing three students. Three sessions of semi-structured interviews were conducted, supplemented by the analysis of 15 documents from 8 organizations and universities.

Results indicated predominantly negative views toward Taiwan’s bilingual education policy, with little impact reported by two participants and none by others. Furthermore, themes derived from document analysis deviated from participants' viewpoints.

A focus on students from southern Asia, which was the major source of international students in Taiwan, becomes critical. In the same vein, little literature has been found concerning graduate students' perceptions toward bilingual education policy, which should be thoroughly explored as well.

This study aims to investigate the satisfaction of farmers with the compensation policy for wildlife-caused damages and its influencing factors, analyze the current situation of satisfaction with the compensation policy among farmers, identify factors significantly affecting satisfaction, and explore ways to optimize the compensation policy and improve the satisfaction of farmers based on the effects of various influencing factors.

The Xishuangbanna National Nature Reserve in Yunnan Province, China, is selected as the research area for the study. Through field interviews, 370 valid questionnaires were collected to obtain relevant data on farmers' satisfaction with the compensation policy for wildlife-caused damages. The Oprobit model is utilized to explore the factors influencing farmer satisfaction and to analyze their underlying reasons.

The study reveals that farmers in the communities surrounding the Xishuangbanna National Nature Reserve generally experience low satisfaction with the compensation policy, particularly concerning satisfaction with compensation amounts, which tends to be dissatisfied on average. Satisfaction with the compensation policy is significantly influenced by individual characteristics and household labor structure, while the degree of human-wildlife conflict, wildlife conservation attitudes and household income structure have insignificant impact. Among individual characteristics, gender, education level, health status, and ethnicity are highly significant. In household labor structure, the number of agricultural laborers, non-agricultural laborers, and household agricultural labor time are highly significant.

Building on the overall satisfaction of farmers with the compensation policy, this study further decomposes policy satisfaction into satisfaction with compensation amounts, coverage, and procedures. It provides more targeted recommendations for enhancing satisfaction with the compensation policy, which can help effectively mitigate human-wildlife conflicts and achieve harmonious coexistence between humans and nature.